What is the level of work-family conflict of non-academic staff of Nigerian polytechnics?

CHAPTER ONE

INTRODUCTION

1.1. Background to the Study

Job satisfaction and well-being among employees have been a source of concern to organisations, management strategists and human relations departments in Nigeria, and perhaps globally. Robbin and Judge (2013) described job satisfaction as positive feelings about a job, resulting from an evaluation of its characteristics. He further stated that a person with high level of job satisfaction holds positive feeling about his or her job, while person with low level holds negative feelings. Workers tend to have several challenges when performing their duties but when satisfied with their job, they are committed to their organisations. Akuegwu (2014) stated that there can be no sustainabe development without quality tertiary education. This is so because, it is in tertiary institution that human mind is trained to function effectively. It is not out of place to say that workers in such institutions must be socially, physically, emotionally and psychologically stable because of the task ahead of them.Non-academics staffs are faced with numerous constreaints when performing their duties. If the constraints are not properly managed it could affect their level of job satisfaction and well-being.

However, the motivation for this research work stemmed from the fact that it has become noticeable by the researcher that many non–academic staff of polytechnics in Nigeria slumed while on duty which may lead to disability or death before reaching the retirement age. Probing further into the cause of their slumming or death, the researcher investigated whether job demands, work-family conflict and social support have impact on job satisfaction and well-being of non-academic staff of polytechnics. The study of job satisfaction and well-being and its antecedents has increased among organisational researchers in and outside Nigeria in the past few years. This is particularly among employees in helping and services occupations such as hospitals, hotels, police force, call centres and schools (Bakker & Schaufeli, 2007; Burke & Mikkelsen, 2006; Ogungbamila, 2013). Job satisfaction is an attitudinal variable that reflects how people feel overall about their jobs, as well as various aspects of the jobs (Spector, 2012).

The concept of job satisfaction was first introduced by Landberger (1958) cited in Khoung and Tien (2013). Job satisfaction is the emotional reaction of an individual about their job. Mafini and Dlodio (2014) assert that job satisfaction is simply a perception of an individual regarding the different aspects of job at the work place. Job satisfaction has been well-defined as the level of gladness that a person feels about his or her work. In other words, job satisfaction is a collection of positive approaches, attitudes, and opinions that employees display towards their job at the workplace. Job satisfaction is dependent on a lot of factors within an individual’s control and it is known to influence not only employees but also organisations (Hollad, 2018). Job satisfaction is crucial as it is related to job performance and turnover in the 21st century and this has become a serious problem in the management of educational institutions (Anil, Kumar, & Agnihotri, 2013). This is because research has proved that employees with high job satisfaction exhibit high energy, pleasurable engagement and enthusiasm and employees with dissatisfaction show distress, unpleasant engagement and nervousness (Heller, Judge, & Watson, 2002).

(Naderi, 2013) reports that job satisfaction is the contentment employees feel concerning their work and the level they are at their job, while (Baral & Bhargava, 2010) contend that one of the most effective factors of job satisfaction is worker’s job content. They report that job satisfaction is often brought about by many factors such as achievement of set target within the workplace and recognition by the management. Baral, & Bhargava, (2010) also report that most employers of labour are now working on the aforementioned to improve work output from their employees to the extent that in recent time most employers make job satisfaction one of their top priorities which in turn and translates to better quality of work and later on to bigger profit to the organization. They further state that if employees are not satisfied with their job, then this may have negative impact on the workers’ well- being and productivity.

These days, for an organization to be successful and achieve its organizational objectives, it is imperative that its employees are satisfied with their work, since their work occupies an important place in their lives. Such conditions are likely to affect not only their physical but also a high level of social, psychological and spiritual well-being. Therefore, well-being is the state of acceptable level of good physical health, emotional and mental wellness (WHO, 2004). Well-being is all encompassing, referring to aspects of psychological, physical, health, financial, social well-being and the likes (WHO, 2004).Well-being refers to perceived and experienced satisfaction with life generally with domains of life such as work, finances, physical health and community (Dienner, 2006). Sears, Shi, and Coberley (2013) posit that well-being is a multidimensional composite of six domains: life evaluation, emotional health, physical health, healthy behaviours, work environment and basic access. However, Schulte, Pandalai, Wulsin, and Chun (2012) assert that workers well-being and safety are connected in other ways that may not be obvious. For instance, age and excess body fat put workers at risk for certain musculoskeletal disorders.

Yang, Fu, Zhao, and Zou, (2015) posit that well-being is an overall assessment of individuals quality of life as well as an important indicator of personal, physical, mental status and quality of life. Gandy, Cowberry, & Pope 2014; Sears, Shi, & Coberley (2013) report that well-being has been linked to a number of productivity outcomes for organisations, including job performance, absenteeism, presenteeism, short-term disability leave, intention to stay and voluntary turnover. Also, Sharpe, (2011) reports that income; labour market, housing and food security are important indicators of well-being not only at individual level but also at community level and population level. According to Harter, Schmidt, and Keyes, (2002) well- being of an employee does not necessarily relate solely to tangible factors such as salaries, increments or promotion. Rather, more broadly, the worker well-being is accompanied by the positive feelings and perceptions about work place that result in a happy and productive workforce. Mann (2004) as well as Shapiro and Hammer (2004) opine that due to the vital role well-being plays in the lives of workers, organisations, and institutions, employers of labour have seen the need to adopt policies that encourage staff to express their emotion and as this is a fundamental part of the job.

Well-being at job plays a vital role, not only for workers, but also for organisations, the economy and the social order confined (Berry, Mirabito, & Baun, 2010: Black, 2008; Danna & Griffin, 1999; Jeffrey, Mahony, Michaelson, & Abdallah, 2014). Although, there is no consensus around a single definition of well–being, there is general agreement that a minimum of well-being includes the presence of positive emotions and mood (for example contentment and happiness), the absence of negative emotions (e.g depression and anxiety), satisfaction with life, fulfillment and positive functioning. In other words, well-being generally includes global judgments of life satisfaction and feelings, ranging from depression to joy (Diener, Scollon, & Lucas, 2009; Frey & Stutzer 2002). Diener and Seligman (2004) observe that good living conditions such as housing and employment are fundamental to well-being. Gasper, (2007) conceptualizes well-being as externally assessed, approved, and thereby normatively endorsed, on feeling features of a person’s life. He also opines that the feelings and or judgments of the person whose well-being is being assessed place him on the well-being continuum.

Sumner, (2007) reports that well–being can be determined by economic indicators such as per capital income, poverty, and income inequality. Well-being integrates mental health (mind) and physical health (body) promotion. Well-being is associated with numerous health, job, family, and economics resulting in more holistic approaches to disease prevention and health -related benefits (Makomisile, 2010). For example, higher levels of well-being are associated with decreased risk of disease, illness, and injury; better immune functioning; speedier recovery; and increased longevity (Rauf & Ijaduola, 2012). Individuals with high levels of well-being are more productive at work and are more likely to contribute to their communities (Awosiyan, 2014).

Kaur (2013) asserts that well-being has progressed rapidly since the emergence of the field over five decades ago. Ogungbamila (2013) found out that work demand predicted the emotional, physical and psychological exhaustion of workers. Demerouti and Bakker (2011) posit that job demands are those physical, psychological, social or organizational aspects of job that require sustained physical and or psychological (cognitive and emotional) efforts and skills and are therefore associated with certain physiological and psychological cost. Pediwal (2011) affirms that the effect of job demand leads to job stress, employees’ absence from organization and loss of working hours. Amelia & Dorobantu (2012) posit that job demand is a growing concern in the current state of the economy in which workers on daily basis face conditions of overwork, job insecurity and low level of job commitment. Ajibola (2013) posit that work accounts for a significant portion of Nigerians’ daily lives and is increasingly recognized as a determinant of health status.

Corroborating this view, Adeyemo and Ogunyemi (2005) posit that workers, who are involved in high level of personal interaction such as nurses, are more vulnerable to occupational stress and burnout than those in product–oriented organisation. Previous research has demonstrated that job demands such as long work hours, work role ambiguity, work role conflict, shift work, physical and psychological effort, contribute to job strain which results in role overload and feeling overwhelmed and consequently contributes to work –family conflict. High demands at work increase the risk of experiencing work family conflicts. (Chung, 2011; Fagan, & Walthery, (2011). Work-family conflict is becoming an issue in the contemporary organisation. This is the reason why both work and family life of employees has continued to overlaped due to individual commitment to work, (Burke, Allen & Spector, 2002). Meetrz and Carr (2008) opine that there exists a relationship between lengthy working periods, obligation, and heavy labour on work-family conflict. Thus, there is the need to ensure balance between the two domains to facilitate efficiency and job satisfaction.

In Nigeria, female labour participation in paid jobs has risen drastically in the past few years, largely as a result of educational improvement (Ajiboye, 2008) suggesting that family structure is moving from traditional single-income family to a double-income family. The new family structure calls for multiple roles to be played within the family-work context resulting in role-conflicts caused by limited time among husband and wife. Ajala (2016) observes that dual-family employees experience work-family conflict and low life-work balance leading to lower job satisfaction, poor job performance and low quality of life. It is noted that the time committed to work contributes to conflict between employees’ work and family roles. Employees in professional positions experience greater intensity of work-to-family conflict while those working in non–professional positions experience greatest intensity of family-to-work conflict (Aminah, 2008). Cultural dictate in Nigeria, especially in the southern part of the country, demands that women should pay greater premium to their family roles more than anything else, including the workplace roles. Some husbands have forced their wives to resign from paid employments in order for the wives to take care of the homes.

The implication is that any slight family-work conflict may be resolved in favour of the family rather than the workplace and indication for possible poor performance of married women. Sao, (2012) posits that work-family conflict occurs when family demands and job demands are incompatible, and where one or both family and job suffer. Work-to-family conflict occurs when experience at work interferes with family life, like extensive irregular or inflexible work hours, work overload and other forms of job stress, interpersonal conflict at work, extensive travel, career transitions and unsupportive supervisors or organisation, for example, an unexpected meeting late in the day may prevent a parent from picking up his/her child from school. Work-family conflict increases as employees move upward in the managerial hierarchy. This may be due to the fact that senior workers do jobs that place greater responsibilities on their shoulders. As a result, they often take their work home and may feel that their family obligations hinder the fulfillment of their tasks (Patel, Govender, Paruk, & Ramgroon 2006).

Ajibola and Farombi (2012) assert that workers in order to accommodate their family responsibilities and increase the time they spend with their families, have changed or gone into occupations that offer greater flexibility, passed on promotions, limited work hours , schedules and work closer to home. Folorunsho (2015) posits that social support is necessary in countering work–family conflict. He observes that in the absence of social supports from families, friends and partners, employees may be at greater risk of strain- related outcomes that arise from work family conflict. Siedlelecki, Cesnauskas and Lazauskaite (2014) posit that lack of social support is positively related to depressive and anxious symptoms both in the general population and among unemployed population.

Social support refers to an individual’s belief that help is available from other people in different situations (Cobb, 1976; Mayo, Sanchez, Pastor, Rodriguez, 2012). Utilizing this perspective, social support has been found to be a job resource that buffers the effect of stress (Cohen and Wills, 1985; Bakker, and Geurts, 2004; Mayo et al., 2012) and thus descreasing the onset of burnout. (DeFreese &Smith, 2013) found out that social support has also been shown to be inversely related to burnout in a sporting context. Defreese & Smith (2014) reported that social support is encouraged by sport psychologists in the maintenance of an athlete’s well-being. Ogunronbi and Akinlabi (2015) contend that social support promotes positive relationship between work and family affairs. For example, the interference of job demand and job related factors will not increase employees’ work-family conflict when supervisors care to provide adequate materials and moral support to workers in the work place. Malik (2011) reveals that overall gender differences can be seen as women do not have high expectations on pay, fringe benefits and nature of job.

Gender refers to the socially constructed expectation for male and female behaviour which prescribes a division of labour and responsibilities between the male and the female and granting of different rights and obligations to them (Pollard & Morgan 2001). Azikiwe (2001) describes gender as social and historical constructs for masculine and feminine roles, behaviour, attributes and ideologies, which connote some notion of biological sex. Woolfork (2010) asserts that gender usually refers to traits and behaviour that a particular culture judges to be appropriate for men and women. Gender relates to the difference in sex (that is, either male or female) and how this quality affects their dispositions and perceptions toward life coping skills (Adenuga & Ayodele, 2010). According to Sotonade (2012) gender is a concept used in social sciences to look at roles and activities which are shaped by the tradition, religion and belief of a particular culture. Previous studies on gender do not have consistent direct impact on outcome variables such as behavioural change. (Abosede, 2007; Adeyemo, 1999; Salami, 1999). The factors that influence a change in behaviour may vary across gender.

The difference in gender as it affects individual coping skills is inconclusive (Adenuga & Ayodele, 2010). This has necessitated the need to find out if there is any significant influence of gender on the combined and relative determinants of job demand, work-family conflict and social support to the prediction of job satisfaction and well-being of non- academic staff of polytechnics in South West Nigeria. According to Kovac, (2009) cadre was found to affect every area of human performance. Staff cadre is also considered as a moderating variable that may likely mediate the effect of job demand, work-family conflict and inadequate social supports on job satisfaction and well-being among non-academic staff in this study. Cognitive development and competence (which are associated with cadre) are necessary for a worthwhile higher job positions. Job cadre of the individual, as it increases or changes, usually affects the various roles performed and mental health. Therefore, it has become necessary to include gender and cadre in this study as moderating variables.

1.2 Objectives of the Study

The major objective of this study is to determine the extent to which job demand, work–family conflict and social support predict job satisfaction and well- being of non- academic staff of polytechnics in South-West Nigeria.

The specific objectives are as follows:

i. To find the extent of the combined contribution of job demand, work-family conflict, and social-support will jointly and individually predict job satisfaction and well-being of Nigerian polytechnics non- academic staff.

ii. To explore the moderating influence of gender and staff cadre on the joint and individual contributions of job demand, work-family-conflict and social support in the prediction of job satisfaction and well-being of Nigerian polytechnics non-academic staff.

iii. To establish the interrelationship among job demand, work-family conflict, social-support, job satisfaction and well-being of Nigerian polytechnics non- academic staff.

1.3 Statement of the Problem

One has probably observed that the lack of job satisfaction of some non-academic staff of Nigerian Polytechnics could result in some of them having another source of income, not punctual in their office, spending less time at work, attending poorly to the students needs. Moreover, some non-academic staff absented themselves from office without due permission from their superior. To an outside observer, these things which appear as common problems in Nigerian Polytechics are indicator of low job satisfaction and well-being among non academic staff of Polytechnics.It is clear that many non-academic staff lack job satisfaction and adequate well-being. As observable in the way they attend to student’s needs, care of students and other job responsibilities.This scenario may not be unconnected with job demand, work-family conflict and social support of these non-academic staff in the day to day running of the polytechics. One has equally observed that, job satisfaction and well-being tend to have direct influences on individuals. For instance, where a worker experiences higher job demand coupled with the work-family conflict and is deprived of social support in the running of the affairs of his or her institution, the individual may not be able satisfied with his or her job let alone experience good well-being.

Furthermore, since the non-acdemia includes male and female personnel operating at the various cadres, the possibility of gender and staff cadre variations in workers’ job satisfaction and well-being cannot be completely ruled out.Hence, the two factors are carried along in this study as moderating variables.

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1.4 Research Questions.

i. What is the level of work-family conflict of non-academic staff of Nigerian polytechnics?

ii. What is the level of job demands of non-academic staff of Nigerian polytechnics?

iii. What is the level of social support of non-academic staff of Nigerian polytechnics?

iv. What is the level of job satisfaction of non-academic staff of Nigerian polytechnics?

v. What is the level of well-being of non-academic staff of Nigerian polytechnics?

vi. What is the relationship among job demand, work-family conflict, social-supports, job satisfaction and well-being of Nigerian Polytechnic non- academic staff?

vii. Would there be any significant differences in the job demand of Nigerian Polytechnics non-academic staff?

viii. Would there be any significant differences in the work-family conflict of Nigerian Polytechnic non-academic staff?

ix. Would there be any significant differences in the social support of Nigerian Polytechnics non-academic staff?

x. Would there be any significant differences in the job satisfaction of Nigerian Polytechnics non-academic staff?

xi. Would there be any significant differences in the well-being Nigerian Polytechnics non- academic staff?

1.5. Statement of Hypotheses

Ho1: Job demand, work-family conflict and social-support will not significantly correlate w ith job satisfaction among Nigerian polytechnics non -academic staff.

Ho2: There is no significant composite contribution of job demand, work-family conflict and social support to the prediction of job satisfaction among non- academic staff of Nigerian polytechnics.

Ho3: There is no significant relative contribution of job demand, work-family conflict and social support to the prediction of job satisfaction of Nigerian polytechnics’ non-academic staff.

Ho4: There is no significant gender difference in the composite contribution of job demand, work-family conflict and social support to the prediction of job satisfaction of Nigerian polytechnics’ non- academic staff.

Ho5: There is no significant gender difference in the relative contribution of work-family conflict and well-being to the prediction of job satisfaction of Nigerian polytechnics’ non- academic staff.

Ho6: There is no significant cadre difference in the composite contribution of job demand, work-family conflict, and social support to the prediction of job satisfaction of Nigerian polytechnics’ non- academic staff.

Ho7: There is no significant cadre difference in the relative contributions of job demand work-family conflict and social support to the prediction of job satisfaction of Nigerian polytechnics’ non – academic staff.

Ho8: There is no significant composite contribution of job demand, work-family conflict and social support to the prediction of well- being of Nigerian polytechnics’ non- academic staff.

Ho9: There is no significant relative contribution of job demand, work-family conflict, and social support to the prediction of well-being of Nigerian polytechnics’ non- academic staff.

Ho10: There is no significant gender difference in the composite contribution of job demand, work-family conflict and social-support to the prediction of well-being of Nigerian polytechnics’ non- academic staff.

Ho 11: There is no significant gender difference in the relative contribution of job demand, work-family conflict and social- support to the prediction of well-being of Nigerian polytechnics’ non- academic staff.

Ho12: There is no significant cadre difference in the composite contribution of job demand, work-family conflict and social support to the prediction of well-being of Nigerian polytechnics’ non- academic staff.

Ho13: There is no significant cadre difference in the relative contribution of job demand, work-family conflict and social supports to the prediction of well-being of Nigerian polytechnics’ non- academic staff.

1.6. Significance of the Study

· The findings of this study would expand the frontier of knowledge on the theme of the study, although, there are existing literature on some of the variables being explored in this work but findings on their inter-relatedness especially among non-academic staff are far from being conclusive.

· It is hoped that the study will provide vital information and empirical data which are necessary to further facilitate an understanding of the major variables of the study.

· This study has a great prospect of facilitating efforts of stakeholders such as the Non-academic staff, Polytechnics Administrators, Management and Government towards formulating policies that will enhance polytechnics staff job satisfaction and well-being.

· To the Non-academic staff, the study will afford them the opportunity to self–examine the extent to which job satisfaction can ensure well-being bearing in mind his or her job demand, work-family conflict and social support in performing its duties.

· To the Polytechnic Administrators, the study will be beneficial to the Polytechnic Administrators to know the extent to which the non-academic staff job satisfaction could enhance well-being to bring out the best performance in the Polytechnic job assigned to the non-academic staff. Also, to ensure smooth running of the Polytechnic system.

· To the Government, especially in Nigeria it is always difficult to provide acceptable salaries and wages for Polytechnics staff especially the members of non-academic staff. Hence, a careful consideration and implementation of the findings and recommendations of this study will help to achieve industrial harmony that can promote conducive learning and working environment.

· It will also assist the government in the manpower and National development. Also, focusing attention on the outcomes of this study by government and other stakeholders in Polytechnics community will help to stimulate personnel training services that can further enhance non academic staff job satisfaction and well- being in public and private Polytechnics.

· To parents and guidances the results of the study will provide information, especially to parents and guardians, on how to manage their job demand, work-family conflict and social support with a view in enhancing their job satisfaction and well-being.

· To personnel psychology, the study will be of immense benefit to scholars in the field of personnel psychology.

· The findings will also serve as a data base for other researchers and investigators through publication in both local and international journals.

1.7. Scope of the Study

The research work has investigated job demand, work- family conflict and social support to the prediction of job satisfaction and well-being of non- academic staff in public and private polytechnic in the South-West, Nigeria. The study area covers six states including Lagos, Oyo, Osun, Ondo, Ogun and Ekiti. The study also explores the moderating influence of gender and staff cadre on the independent and dependent variables.

1.8. Operational Definition of Terms

The following terms were defined as used in this study.

(a) Job demand: This is the excessive work load and pressure experienced by workers in the cause of performing their duties.

(b) Work-family Conflict: This is a situation where work roles affect family roles or family roles affect work roles.

(c) Designation: This is the post an individual occupies in a place of work

(d) Non-Academic staff: Categories of workers who perform administrative work in an institution.

(e) Social support: This is the support received from people around us.

(f) Job Satisfaction: This refers to individual feelings and reactions about his or her job.

(g) Well- being: This is the feelings and experience of individual about his or her life.

(h) Management cadre: Categories of non- academic staff working in Polytechnics which were on salary scale from contedis 14 and above

(i) Senior cadre: Categories of non-academic staff working in Polytechnics which were on salary scale from contedis 8 to 13.

(j) Junior cadre: Categories of non-academic staff working in Polytechnics which were on salary scale from contedis 3 to 7

CHAPTER TWO

LITERATURE REVIEW

A comprehensive and exhaustive review of literature is indispensible in the provision of sufficient theoretical and empirical background to any study. Consequently, chapter presents the review of the vast volume of literature materials that are of importance and relevance to this study under the following sub headings.

2.1 Theoretical framework.

2.2 Theoretical Literature Review

2.3 Empirical Findings

2.4 Conceptual Framework of the Study

2.5 Appraisal of Literature

2.1 Theoretical Framework

2.1.1 Role Conflict Theory

2.2 Conceptual Theoretical Review

2.2.1 Concept of Job Satisfaction

2.2.2 Concept of Well–being

2.2.3 Concept of Job Demand

2.2.4 Concept of Work–family Conflict

2.2.5 Concept of Social Support.

2.3. Empirical Review

2.3.1 Job Demand, Job Satisfaction and Well-being

2.3.2 Work – family Conflict, Job Satisfaction and Well-being

2.3.3 Social Support, Job Satisfaction and Well-being

2.3.4 Gender, Staff Cadre, Job Satisfaction and Well-being

2.4. Appraisal of Literature

2.5. Conceptual Model

2.1. Theoretical Review

2.1.1 Role theory

Role theory was postulated by Ralph Linton, an American Anthropologist, in the 1930s (Gordon, 1998). The theory was a means for analyzing social system, in which, roles were conceived as the dynamic aspets of societal recognized social positions or status. It is believed that individuals generally have many roles which they are expected to perform. Role theory suggests that within social settings, various social structures are formed (e.g., families, communities, work) that require various roles that individuals fulfill (Parsons & Shils, 1951). With each social role, there are certain duties, rights, norms, and behaviours expected (Biddle, 1986). Involvement in multiple roles (e.g., spouse, mother, father, manager, and worker) can lead to what is sometimes referred to as role conflict, role strain (Barnett & Baruch, 1985; Kopelman, Greenhaus, Connolly, & Thomas, 1983), or role overload (Baruch & Barnett, 1986). Role conflict occurs when a person is unable to fulfill the responsibilities within each of their roles. This perceived “conflict” can be a result of external constraints prohibiting an individual from fulfilling his multiple role responsibilities (Barnett & Baruch, 1985; Coverman, 1989; Kopelman et al., 1983).

Role strain has been defined by Goode (1960) as “felt difficulty in performing role obligations.” Role overload is often experienced as a result of having too little time to fulfill various role demands (Barnett & Baruch, 1985). Work-role conflict theory by Kahn, Wolfe, Ouinn, Snoek & Rosenthel (1964) suggests that as a result of multiple role (work and non-work) responsibilities, a conflict (work-family conflict) may be experienced when a worker is unable to fulfill various role obligations. These conflicts may be experienced either because the time available to fulfill one role obligation makes it difficult to fulfill other role obligations or because engagement in one role depletes energy and makes it difficult to meet other role obligations. In other words, limited resources in terms of time and energy to meet various role obligations, result in the experiences of time-based or strain-based work-family conflict. Some researchers posit that engaging in multiple roles may leave insufficient time to fulfill the various demands and responsibilities inherent to an individual’s roles, resulting in a depletion of time and energy (Coverman, 1989).

Role conflict and role overload have been shown to have negative effects on psychological well-being, job satisfaction, and marital satisfaction (Coverman, 1989). Competing demands may require additional time, energy, and resources, and thus can result in the experiences of strain and conflict, if the individual does not have enough resources to meet multiple demands (Goode, 1960). Using role theory, Goode (1960) developed the scarcity hypothesis to understand the conflict. The scarcity hypothesis states that people have limited time, energy, and resources. Involvement in multiple roles means responding to multiple role obligations. As such, accomplishing various role responsibilities requires time, energy, and various types of resources. The scarcity hypothesis posits that when the demands from these multiple roles exceed the supply of time, energy, and other resources that help to meet with various role responsibilities, strain may be experienced in form of role conflict or role overload (Coverman, 1989; Goode, 1960). The scarcity hypothesis was the basis for early studies of work-role and work-family conflict.

Greenhouse’s conceptualization of time-based conflict and strain-based conflict was used in this study because it helps to better understand the effects of job demands on non -academic staff experiencing work-family conflict. When workers are required to work for long hours at demanding jobs, they may be more likely to experience time-based and strain-based work-family conflict due to the challenges they would face in multiple role responsibilities. The role conflict theory which is the framework on which the study is anchored on explains that human beings only have a fixed amount of energy to be used for multiple roles. Role conflict results when an individual encounters tensions as a result of incompatible roles. It can also be seen as a form of social conflict which takes place when an individual is forced to do two different and incompatible roles at the same time. Previous studies on work-role conflict done by Kahn, Wolfe, Ouinn, Snoek & Rosenthel (1964) was rooted in role theory.

They found out that conflict arises as a result of various roles that an individual may assume: “Simultaneous occurrence of two (or more) sets of pressures such that compliance with one would make more difficult compliance with the other,” thus making it difficult for an individual to fulfill the responsibilities within one domain as a result of demands in another domain.The application of role conflict theory to this study, therefore suggest that there is strong indication that non-academic staff in Nigerian polytechnics may experinces conflicts in balancing their work and family responsibilities.For example, non-academic staff may find conflict between picking up his or her son from school as a result of extended academic board meeting which demand extra hours and attention. Resting on this theory also, it can be assumed that female married non- academic staff would experience role conflict in the process of occupying various status.For instance, role conlict would occur while trying to be a mother, wife in the family and no-academic staff at work.

For non-academic staff, literature suggests that they are likely to work long hours (Ajao, 2014). Peters (2010) observes that time-based and strain-based work to family conflict often affect the performance of workers in an organisation Thus, it is important to understand the experience of both of these types of work-family conflict among non-academic staff in order to prevent losses on the part of the organizations, workers and the country at large. Expanding on this idea of inter-role conflict and applying it to work-family domains, Greenhaus and Beutell (1985) define inter-role conflict as a form of role conflict in which participation in different roles leads to opposing pressures, and “role pressures from the work and family domains are mutually incompatible in some respect.

Based on work-role conflict theory, Greenhaus and Beutell (1985) identify the three specific types of work-family conflict previously discussed: time-based, strain based, and behaviour-based conflicts. Time-based conflict refers to the conflict that arises when time assigned to fulfill one role responsibility makes it hard to fulfill another role responsibility (Greenhaus & Beutell, 1985). For example, occurrence of an important work meeting at the same time as one’s child’s soccer match may stress the individual as he/she has to prioritize one event over the other. The individual is not able to fulfill both of the roles at the same time. Strain-based conflict refers to the stress experienced when the fulfillment of one role leads to a difficulty in the fulfillment of a role in another domain (Greenhaus & Beutell, 1985). An example of strain-based conflict is a working mother who finds it difficult to attend to the needs of her children because she is exhausted from her physically demanding job (Grzywacz et al., 2007). The third type of conflict, behaviour based conflict, refers to situations when an individual is expected to carry out diverse behaviours in different domains, and specific behaviour requirements in one domain may make it difficult to fulfill the role requirement in another domain (Greenhaus & Beutell 1985).

This experience is likely to cause conflict as the individual is unable to conform to the expected roles to be played in different domains. For example, a person may be expected to behave with impersonality, logic, and authority at work. At home, these very same behaviours may not be appreciated by family member.

2.2.0 Conceptual and Theorectical Review

2.2.1 Concept of Job Satisfaction

Spector, (1997) defines, job satisfaction as a measure of workers contendeness with their job, whetheror not they like the job or individual aspect or facets of jobs, such as supervision. Locke, (1976) defines job satisfaction as “pleasurable or positive emotional state resulting from the appraisal of one’s job or job experiences.” Job satisfaction can be seen within the broader context of the range of isues which affect an individual’s experience of work or their quality of working life (Illies & Judge 2003). Job satisfaction can be undersood in terms of its relationship with key factors, such as control at work, general well-being, stress at work, home-work interface and working conditions (Thompson & Phuma, 2012). Siang (2015) describes job satisfaction as the feelings regarding one’s job and how happy such a person feels within that job. This can be affected by many factors such as company policies and interpersonal relationships. Job satisfaction, as an organisational factor, is interconnected with various internal and external motivators (Ajobi, 2015). In the same vein, Olorunsola (2012) clarifies that job satisfaction is a compound of internal and external factors that employees consider. These factors refer to employees’ welfare in their private and social life. Job satisfaction, as an organisational factor, has different levels (high and low levels) that are determined by various motivators. Each of these levels illuminates the amount of employees’ feeling towards their job. It also, shows their reaction at workplace. In other words, high level of job satisfaction would lead to high level of productivity. In contrast, low level of job satisfaction leads to low turnover and absenteeism amongst employees (Wan, Ahmad, & Abdurrahman, 2015). Robin and Judge (2013) define job satisfaction as positive feelings about a job resulting from evaluation of its characteristics. A person with high level of job satisfaction holds positive feeling about his or her job, while a person with low level holds negative feelings.

Job satisfaction is the collection of feeling and beliefs that worker have about their current job. Worker’s levels of degrees of job satisfaction can range from extreme satisfaction to extreme dissatisfaction. Workers also can have attitude about various aspects of their jobs such as the kind of work they do, their coworkers, supervisors or subordinates and their salary (George & Jones, 2008). Job satisfaction is a yardstick for quality work experience. It is a positive emotional feeling, a result of one’s evaluation of his job experience by comparing what he expects from his/her job and what he actually gets. Generally, job satisfaction describes how happy employees are with their jobs and the feelings that they have towards the various aspects of their jobs. Job satisfaction has become a very significant feature in every organisation because of its importance to the behaviour of employees in the work place. Therefore, human resources managers tend to seek for total reward programme that could enhance employees’ job satisfaction and in turn increase organisational performance and productivity (Galanou, Georgakopoulos, Sotiropoulos & Dimitris, 2010; Mujtaba & Shuaib, 2010).

The most widely accepted theory of job satisfaction was proposed by Locke (1976) He defines job satisfaction as “a pleasurable or positive emotional state resulting from the appraisal of one’s job or job experiences” (Locke, 1975). Job satisfaction is a very important part of an organisational job attitude which represents attitude and feelings about various aspects of their jobs such as their coworkers, supervisors or subordinates, work load and the salary of workers in an organisation. In an organisation many, people are working for the sake of money and profit.

Nguyen & Nguyen, (2011) affirm that an employee is a vital asset for an organisation. To them“employees own knowledge, skills and capabilities and companies do not own them”. Job satisfaction has emotional, cognitive, and behavioural components (Bernstein & Nash, 2008). The emotional component refers to job-related feelings such as boredom, anxiety, acknowledgement and excitement. The cognitive component of job satisfaction pertains to beliefs regarding one’s job whether it is respectable, mentally demanding or challenging and rewarding. Finally, the behavioural component includes people’s actions in relation to their work such as tardiness, working late, faking illness in order to avoid work. Bernstein & Nash, 2008). Job satisfaction refers to the positive attitudes or emotional dispositions people may gain from work or through aspects of work. Employees’ job satisfaction becomes a central attention in researches and discussions in work and organisational psychology because it is believed to have relationship with job performance.

There are essentially two types of job satisfaction based on the level of employees’ feelings regarding their jobs. The first, and most analyzed, is global job satisfaction, which refers to employees’ overall feelings about their jobs (e.g., “Overall, I love my job.”) (Mueller & Kim, 2008). The second is job facet satisfaction, which refers to feelings regarding specific job aspects, such as salary, benefits, work hierarchy (reporting structure), growth opportunities, work environment and the quality of relationships with one’s co-workers (e.g., “Overall, I love my job, but my schedule is difficult to manage.” (Mueller & Kim 2008). Judge & Klinger (2008) assert that job satisfaction is a pleasurable or positive emotional state resulting from appraisal of one’s job or job experiences. Chughati & Perveen (2013) define job satisfaction as one’s feeling or state of mind related with the work while Sypniewska (2013) confirms that it is an employee’s positive attitude towards the company, co-worker and finally, the job. Clearly, job satisfaction is an important aspect in the lives of employees and enhancing it can bring benefit for the organization as well. For instance, job satisfactions can moderately increase job performance. Moreover (Luthans, 2011) asserts that increasing job satisfaction of the employees can reduce occupational stress.

Thus, employers should rather be interested in how they can improve job satisfaction among their employees. For instance, having fair salaries and wages, benefits, and offering promotion opportunities have proved to be important factors enhancing job satisfaction (Luthans, 2011). Stride, Wall and Catley (2007) affirm that job satisfaction is an intuitive concept that consists of employee’s experience of emotional reactions. The evaluation of employees’ level of job satisfaction is of utmost importance both for individuals and for institutions. If an employee is not satisfied with his or her job, he or she experiences a decline in job satisfaction. Therefore, he or she decreases the efficiency of the institution due to low contribution along with the problems in his or her personal life. Aziri (2011) opines that when employees are adequately rewarded with what they feel is equitable they will be satisfied and it will likely result in greater performance. Olorunsola (2012) confirms that job satisfaction is a combination of internal and external factors that staff contact when doing their work and which change their attitudes and feelings toward their jobs.

Job satisfaction is one of the most studied concepts in industrial and organisational psychology and in the sociology of work and occupations (Mulinge, 2000). Job satisfaction is one of the factors that play a central role in the organisation. It has the potential to affect a wide range of behaviour in organisations and contribute to employees’ levels of well-being (George & Jones, 2012). According to Wann-Yin, and Htaik (2011), job satisfaction is one of the most widely studied and measured constructs in organisational behaviour and management literature. Job satisfaction deals with the feelings that an individual employee has about his/ her job. As such, ‘organisational behaviour research has revealed that individuals who express high satisfaction in their jobs are likely to be more productive, have higher involvement and are less likely to resign than employees with less satisfaction (Qasim & Syed, 2012).

There are various channels through which job satisfaction can affect productivity. Firstly there is direct impact on a person measuring the productivity of employees (supervisor ratings).This may be as a result of a lower tendency to slow down work concoiusly or unconciously. Secondly, satisfied employees may also exhibit more organizational citizenship and less counterproductive organisational behaviour. They may also have lower tendency to go on strike or engage in other industrial actions. Thirdly, there are positive productivity effects through decreased absenteeism. Employees that are not satisfied with their jobs may have a greater tendency to develop illness or even remain absent from work without illness. Fourthly, job dissatisfaction leads to quit intention and actual separations. Quit and subsequent replacement hiring create cost for firms that may show up as lower productivity, even when it is the least productive employee who leaves (Tella, Ayeni, & Popoola, 2007). Job satisfaction is an employee’s general perception about the job or the compilation of attitudes toward various aspects of the job (Bakotic, 2014) and the level of contentment a person has with his or her job ( Lu, Barriball, Zhang &While (2012). In the broader context, job satisfaction is the emotional response that people have about their jobs, and the various aspects associated with their jobs (Spector, 1997).

Hajiha, Jasbi, and Ghaffari (2014) define job satisfaction separate from its facet definitions. Their opinion on job satisfaction is that it refers to a worker’s overall attitude towards his job. They contend that when an employee is satisfied with his job, he will have positive attitude on the job and vice versa. However, an employee may be satisfied with a particular facet and may be dissatisfied with another different facet of his job. In this case, an employee may be satisfied or dissatisfied with one or more other facets like the work itself, organizational policies, advancement, responsibility, and achievement, organizational policies, interpersonal relationship, pay, working conditions, supervision, job content and social readjustment. Moreover, job satisfaction reflects the extent to which workers are contended with their jobs and the sense of fulfillment that is derived from their job tasks (Griffin and Moorhead, 2007).

Onukwube (2012) opines that job satisfaction is the sense of well-being, good feeling and positive mental state that emerge in an employee when he obtains a reward consequent upon his performance. Factors such as working conditions, below competitive salary, lack of promotional opportunities and lack of recognition are some of the contributing factors to employee’s dissatisfaction. Job satisfaction of non-academic staff in higher institutions is important because it influences their motivation and performance which are very influential in delivering quality services within the institutions. Daft (2009) emphasise that managers of knowledge workers and other workers in an institution of learning rely on job satisfaction to keep both motivation and enthusiasm at high level when performing their duties. Job satisfaction has been defined simply as a workers’ positive or negative attitude toward ones job (Ucar & Otken, 2010).

Failure in designing appropriate reward has continued to have a negative effect on employees’ job satisfaction and overall effectiveness of many organizations (Neo, Hollenbeck, Gerhart, & Wright, 2006). Similarly, Chepkwony and Oloko (2014) assert that rewards and job satisfaction of employees currently remain a problem for most organisations. Extant literature has effectively shown the relationship between rewards and employees’ job satisfaction (Abayomi & Ziska, 2014: Nazir, Khan, Shah & Zaman, 2013, Kalleberg &Loscocco, 1983). Nevertheless, employees’ job satisfaction is critical for the success of any organisation as well as the quality of products or services provided by the organisation to their customers or clients respectively. According to Miao (2011), job satisfaction is an employee’s overall sense of well-being at work. It is an internal state based on assessing the job and job-related experiences with some degree of favour or disfavour. Job satisfaction is ones positive feeling about his or her job.

Also state that the assessment was based on an evaluation of the job characteristics (Robbins & Judge, 2007). Each individuals’ values, attitudes and expectations differ, thus, motivational factors can be quite different.

Researchers have found out that the most researched definition of job satisfaction is that by Hakkak, Gashti, and Nawaser (2014). In their study of the relation between job satisfaction and perceived organisational commitment, job satisfaction is divided into two categories, namely, internal and external satisfaction. External satisfaction is related to factors such as payment, promotion, admiration and interaction with colleagues; while employee’s satisfaction related to values, social status, position and professional res ponsibility indicate internal satisfaction (Robbins & Judge, 2007). Taylor & Westover (2011) assert that job satisfaction represents an interaction between workers and work environment and between what they want from their jobs, what they perceive and receive. Recent survey has identified job insecurity as one of the significant factors that drive workers to develop poor attitude and withdrawal tendencies in their organizations and reduce employees’ job satisfaction (Fapohunda 2012; Yih & Htaik 2011; Suleiman, 2013; Preuss & Lautsch, 2002). Furthermore, Fatimah, Noraishah, Nazir and Khairuddin (2012) assert that threat to employees’ job security negatively affects their job satisfaction and well-being as well as job performance.

Davis (2012) affirms that a perceived work element provides positive emotion and this process results in job satisfaction. However, Zhu (2013) posits that if the employees have negative and unpleasant feelings at work, their attitudes to work are defined as dissatisfaction. Lu, Barriball, Zhang &While (2012) assert that job satisfaction is an important variable that is often discussed in studies on organisational behaviour. Dessler and Hurt (2006) indicate that job satisfaction refers to the level of satisfaction with regards to personal safety, health, relationships, growth and esteem that could be obtained from work experience . Job satisfaction is also believed to be dispositional in nature. This dispositional view point assumes that measuring personal characteristics can aid in the prediction of job satisfaction (Staws and Ross, 1985). The disposition approach of job satisfaction is not a mirage and individual dispositions indeed affect job satisfaction (Staw and Cohen-Charash, 2005). Arokiasamy, Tat and Abdullah (2013) recognise that lack of promotion and mundane work has significantly contributed to employee’s lack of satisfaction and intention to leave the organisation.

Inadequate or lack of promotion opportunities into positions of higher responsibility has caused lack of satisfaction and negative consequences such as lower commitment, high employee turnover and absenteeism among employees. Similarly, those employees who remain in one position with no opportunities for moving to higher positions have been said to exhibit negative attitude towards their work and their organisations (Arokiasamy et al., 2013). Odinioha and Nwaeke (2015) conducted a research to examine the association between non-financial incentives and job satisfaction among hotel workers in Port Harcourt, Nigeria. The results of the study revealed that there was a significant relationship between promotion and employee job satisfaction. Job satisfaction in workplace is valuable to study for multiple reasons: increased satisfaction is suggested to be related to increase productivity, and promoting employee satisfaction has inherent humanitarian value (Smith, 1969)

In addition, Job Satisfaction is also related to other positive outcomes in the work place, such as increased organisational citizenship behaviour (Organ, and Ryan, 1995) increased life satisfaction (Judge, 2000), decreased counter productive work behaviours (Dalal, 2005), and decreased absenteeism (Hardy, Woods, and Wall 2003). Each of these outcomes is desirable in organisations and, as such, shows the value of studying and understanding job satisfaction. According to Spector (1997; 2008), facets that have been frequently studied include pay, promotion opportunities, fringe benefits, supervision, co-workers, job conditions, nature of the work, communication and security. According to Davey, Obst and Sheehan (2001), low job satisfaction is a result of inconsistent promotional opportunity and lack of organizational support including recognition from supervisors and peers. Job pressures, positive life changes, feeling life as whole and sources of biggest problems in life (Sanchez, Bray,Vincus,& Bann 2004), supportive work climate on board ship, teamwork and absence of feeling about disruption inter-personal life (Fairbrother & Warn, 2003) have also been researched.

Furthermore, workers have reported to have low job satisfaction in industrial relations, feedback, rate of pay, skill variety, organizational management, autonomy, promotion chances and supervisors (Blair & Phillips, 1983; Alpass, Long, Chamberlain, & Mac Donald, 1997).

2.2.2 Herzberg’s Two-Factor Theory.

Herzberg’s Two-Factor Theory comprises two factors namely hygiene factors and motivational factors. Hygiene factors include salary, interpersonal relations with superiors, subordinates and peers, organization policies and administration, supervision, status, job security, working conditions, and personal life. Motivational factors include achievement, recognition for achievement, advancement, responsibility, work and possibility of growth (Herzberg, 1968). This theory suggests that the presence of motivation factors can potentially create great motivation and greater job satisfaction while in the absence of motivators, dissatisfaction often does not occur. Also, the absence of hygiene factors will create great dissatisfaction and the presence of hygiene factors does not provoke high levels of job satisfaction. It is a known fact that compensation plays a vital role in job satisfaction of workers.

In a study conducted by Salisu, Chinyio and Suresh (2015), questionnaire was developed, pilot tested and administered to gather data on workers’ job satisfaction regarding four compensation variables namely; salary, allowance, gratuity and pension. A total of 260 employees were administered the questionnaire. The respondents were selected using the stratified random sampling technique. The study found that there was significant relationship between gratuity payment, which is part of fringe benefits, and job satisfaction of public sector construction workers in Jigawa State, Nigeria. This implies that when workers receive reasonable lump sum in form of gratuity it leads to the satisfaction of their various needs on retirement. However, salary paid in public sector workers in Nigeria has no significant relationship with job satisfaction. This has led to consistent agitation for salary review in the sector. Tomazevic, Seljak &Aristoumik (2014) suggest that to understand job satisfaction factor require review on well-being, stress at work, control at work, home and work interface, and working conditions.

A variety of factors affect job satisfaction. This is in addition to the experiences people have on the job (Thompson & Phua, 2012). From a business perspective, job satisfaction is important to enhance organisational performance (Ismail, Romle & Azmar 2015). For health care organi zations, job satisfaction directly relates to better job performance which results in optimized health care (Correia, Dinis & Fronteira, 2015). Because nurses play an important role in the care of patients, their job satisfaction is fundamental to health care organizations (Kaddourah, Khalidi, Abu- Shahem and Al- Tamir 2013). When job satisfaction is high, employees remain in the organization, when worker’s job satisfaction is low; the result is often employee turnover. Employee turnover occurs when an employee involuntarily quits or leaves an organization (Hom, Mitchell, Lee & Grifffeth, 2012). Results of previous studies revealed that nurses’ job dissatisfaction influences their intention to stay with the organization (Lu, Barriball, Zhang & While, 2012).

Poor job satisfaction has a negative influence on the intention of workers to stay with organisations, resulting in loss of profitability to the organization (Cimiotti, Aiken, Sloane & Wu, 2013). Effective job satisfaction measures are necessary for workplace retention (Gounaris & Boukis, 2013). Positive leadership affects the work environment and job satisfaction (Bhatti, Maitlo, Shaikh, Hashmi, & Shaikh, 2012; Spence-Laschinger & Fida, 2014) while tyrannical or negative leadership reduces subordinates’ job satisfaction (Skogstad, Assland, Nielson, Hetland &Einarson 2014). Authentic leadership significantly and positively influences staff nurses’ structural empowerment, which increases job satisfaction and self-rated performance (Wong & Laschinger, 2013). Hocine, Zhang, Song and Ye (2014) found that subordinates of supportive leaders expressed higher job satisfaction and demonstrated more trust to the company management than subordinates of leaders who were not supportive. Girma, (2016) states that supportive leadership directly influences an employees’ job satisfaction.

Leadership trust relates indirectly to job satisfaction because it facilitates transformational leadership, and transformational leadership has a positive effect on job satisfaction (Yang, 2014) an assertion supported by another study (Khan, Asghar, & Zaheer, 2014). Scholars believe that instrumental leadership and individual empowerment influence job satisfaction (Mulki, Caemmerer, & Heggde, 2015; Wagner, Warren, Cummings, Smith, & Olson, 2013). Regardless of the style of leadership, ethical leadership exerts a profound positive influence on employee (Yang, 2014). Frankel and PGCMS (2017) posit that workers’ roles have become more specialized, and therefore require autonomy. Empowering employees (i.e., autonomy, responsibility, information, and creativity) has a positive effect on job satisfaction (Abraiz, Tabassum, Raja, & Jawad, 2012). In general, empowerment contributes to job satisfaction (Ivey & Vance, 2014; Roberts-Turner, Hinds, Nelson, Pryor, Robinson, & Wang, 2014). Workers with a higher degree of autonomy have a higher level of job satisfaction (Kaddourah, Khalidi, Abu-Shaheen & Al-Tannir 2013).

Galbany-Estragués and Comas-d’Argemir (2016) found that autonomy is important in health care because care has become technologised and bureaucratised.

Roberts-Turner et al. (2014) found that nurses with more influence over their work environment felt empowered and more satisfied with work. Teams with high levels of organisational tenure diversity serving under transformational leaders demonstrate greater organisational commitment, engage in creative behaviour, and have higher job satisfaction (De, Poel ,Stoker and Vander-Zee,-2014). The leader-member exchange demonstrates the connection between leaders and followers. An integral component of the leader-member exchange is communication. The frequency of communication affects job satisfaction in the low client leader relationship (Vidyarthi, Erdogan, Anand, Liden, & Chaudhry, 2014). In contrast, job satisfaction is higher when direct supervisors provide employees with concrete feedback than when hierarchically distant leaders share their abstract views (Berson & Halevy, 2014). Relationships within the workplace play a role in job satisfaction with findings suggesting supervisor subordinate relationships. Team member relationships also play a role in job satisfaction (Malik, 2013).

Gender, age, and education also play a role in job satisfaction. Women tend to be more satisfied at work than their male colleagues are. Differences in job satisfaction exist because of an employees’ age. More educated employees are more satisfied at work than their less educated counterparts (Bakotic, 2014). Finally, income affects job satisfaction, despite the lack of reporting detailing the cause (Bakan & Buyukbese, 2013).

2.2.3 The Effect of Job Satisfaction

The amount of effort put into work is an important factor that determines individual performance. When an employee is satisfied with his/her job, there is a spur up or motivation to put on greater amount of effort than before and this enhances performance and productivity. This will invariably rub off on the overall performance and productivity of the organisation. Thus, it can be affirmed that a satisfied employee is critical to the success of the organisation. Job satisfaction is a multifaceted concept which can mean different things to different people. However, it is an innate thing or attitudinal in nature. Social factors (i.e relationship with co-worker s, group working and norms and opportunity for interaction) cultural factors (i.e attitude, beliefs and values).organisational factors (i.e nature and size, formal structure, personnel policies and procedures, employee relations, nature of the work, supervision and styles of leadership, management system, and working conditions). Environmental factors (i.e economic, social, technical and governmental influences. Thus, an individual overall job satisfaction is the cumulative result of comparisons that he/she makes between what the job provides and what he or she desires in various areas.

2.2.4 Benefits of Job Satisfaction

Job satisfaction has tremendous benefits to an organization when all conditions are fulfilled by the management of the organisation. When all conditions by the management are geared towards satisfying an employee, the wholesome outcome will rub off well on the organisation, though there are other conditions when not put in place that can results, in employee’s dissatisfaction and low work output. High job satisfaction may lead to improved productivity, decreased turn over, improved attendance, reduced accidents, less job stress and less unionisation. Job dissatisfaction on the other hand produces low morale, absenteeism, grief and depression at work and so on. The benefits of job satisfaction are explained as follows:

Job satisfaction enhances productivity: – when a worker is happy, he will be productive as condition of service put in place by the management motivates employees to do his or her best for the organisation. This motivation or rewards, which are both intrinsic and extrinsic in nature and value, make the employees feel satisfied which invariably lead to greater job performance and productivity.

– It also influences employee turnovers: – In every organisation, high employee turnover is a matter of concern for the management as it disrupts and punctures the normal operations. Continuous replacement of employees, who leave the organisation, is costly and technically undesirable. This is precipitated by employees’ job dissatisfaction. In this view, the employer tries all possible best to keep the employees satisfied on their jobs to minimize the turnover.

– Job satisfaction discourages absenteeism: – When there is high job satisfaction in an organisation, absenteeism and commitment to work is low but on the other hand when satisfaction is low, absenteeism and worker’s morale is high. When an employee’s dissatisfied, he/she will be absent from work overtimes due to obvious and avoidable reasons.

– Job satisfaction de-emphasises union activities: When employees are satisfied with work, t hey will not be interested in union activities. Job dissatisfaction is a major cause of unions in workplace because an individual employee cannot sufficiently fight his or her battle or influence changes individually.

– Job satisfaction promotes safety: – When there is gross dissatisfaction in an organisation or company, supervisors and the employees are prone to avoidable accidents. The dissatisfaction takes an employee’s mind away from tasks or duties which results into losses for the organisation. However, a satisfied worker will always be careful and pay attention to task and duties which help reduce avoidable accidents.

Locke (2012) refers to job satisfaction as “a pleasurable or a positive emotional state resulting from the appraisal of one’s job or job experience,” Job satisfaction can be viewed as an employee’s observation of how well their work presents those things which are very important to them. It is an attitude people have about their jobs. Balzer (2012) defines job satisfaction as “the feelings a worker has about his or her job experience in relation to previous experience, current expectations and available alternatives.” Elaborating on this, Camp (2010) defines job satisfaction with reference to the needs and values of an individual and the extent to which these needs and values are satisfied in the work place.

Brief and Weiss (2002) refer to job satisfaction as the pleasurable and positive emotional state realised from an appraisal of the employee’s job experiences. Hence job satisfaction is a situation where an employee is contented with the affairs of his job. Hajiha, Jasbi and Ghaffari (2014) define job satisfaction separate from its facet definitions. Their opinion on job satisfaction is that it refers to a worker’s overall attitude towards his job. They contend that when an employee is satisfied with his job he will have positive attitude on the job and vice versa. For example, an employee may be satisfied or dissatisfied with one or more other facets like the work itself, organisational policies, advancement, responsibility, and achievement, organisational policies, interpersonal relationship, pay, working conditions and supervision.

In their contribution, Greenberg and Baron (2003) define job satisfaction as a worker’s affective, cognitive, and evaluative emotional reactions regarding their jobs. Moreover, job satisfaction reflects the extent to which workers are contended with their jobs and the sense of fulfillment that is derived from their job tasks (Griffin and Moorhead, 2007). Similarly, Griffin and Morehead (2007), and Greenberg and Baron (2003) definitions view job satisfaction cumulatively that is the overall reaction of an individual to his job. Robbins (2001) defines job satisfaction as a worker’s general attitude towards his job. In parallel to these explanations, Mohammad, Quoquab, Habib, & Alias (2011) describe job satisfaction as an agreeable emotion that originates from work experience and is generated by diverse motivators. In reality, job satisfaction includes worthy feelings and emotions that employees consider within their work environment. Peretomode (2006) sees job satisfaction as fulfillment acquired in terms of job experience, activities and rewards. He states further that job satisfaction is the feeling about responses to the aspects of the work environment. A recent definition of the concept of job satisfaction is from Hulin and Judge (2013), who have noted that job satisfaction includes multidimensional psychological responses to an individual’s job, and that these personal responses have cognitive (evaluation), affective (or emotional), and behavioural components. Job satisfaction scales vary in the extent to which they assess the affective feelings about the job or the cognitive assessment of the job. Affective job satisfaction is a subjective construct representing an emotional feeling individuals have about their job.

Hence, affective job satisfaction for individuals reflects the degree of pleasure or happiness their job in general induce. Cognitive job satisfaction is a more objective and logical evaluation of various facets of a job. Job satisfaction can also be seen within the broader context of the range of issues which affects an individual’s experience of work, or the quality of working life. From previous studies it can be concluded that job dissatisfaction is associated with many negative structural outcomes, which includes high labour turnover rated, diminished work performance and low assurance level towards the corporate entities. (Rahman et al., 2017; 2018). Job satisfaction can be understood in terms of its relationships with other key factors, such as general well-being, stress at work, control at work, home-work interface, and working conditions.

2.2.5 Concept of Well-being

Worker ‘well-being’ refers to the extent to which workers perceive that their lives are going well. It incorporates the degree to which they enjoy good physical and mental health and are resilient. Well-being involves workers’ level of engagement in living and involvement in a broad range of human activities including intellectual endeavours, social relations and emotional attachment (Centers for Disease Control and Prevention, 2016). From this perspective, worker’s well-being stems from feeling stimulated, rewarded and secured (Andrews & Withey, 1976; Campbell, 1976; Centers for Disease Control and Prevention, 2016; Ryff & Singer, 1998; World Health Organization Quality of Life Assessment Group, 1995). At the core of these perspectives is a focus on the individual’s perception of their life circumstances and expectations (Veenhoven, 2010).

2.2.6 The Emerging Field of Worker Well-being

Over the recent years, changes have occurred in our understanding of worker well-being: Worker well-being has multiple determinants. Historically, workplace health and well-being-related activities have focused on a single illness, risk factor or behaviour change (e.g., stress management heart disease prevention, smoking cessation). Increasingly, more holistic approaches to worker well-being are being adopted and more comprehensive approaches that acknowledge the combined influence of personal, environmental, organisational policy, community and societal factors on employee well-being are being employed (World Health Organisation 2016). Worker health and workplace injury link state that the relationship between health-related behaviours problems and workplace injuries are now better understood. For example, obesity is associated with an increased rate of workplace injury (Dong, Wang, & Largay, 2015). Enhancing the well-being of workers is not only a worthy aim in its self, it can also reduce the risk of injury. Worker resilience refers to the ability to maintain personal and professional physical and emotional well-being in the face of on-going work stress and adversity (McCann et al., 2013).

Resilience-promoting work environments for health and welfare workers can reduce the negative, and increase the positive outcomes stemming from working in potentially demanding environments (McCann et al., 2013). It is well established in literature that employees with high level of psychological well-being are better, more committed and more productive than employees with low level of psychological well-being (Wright and Bonett 2007, Wright and Cropanzano, 2004). Employees are likely to have higher well-being if they are satisfied with their work and organisation and they perceive their quality of work life positively, that is when an employee’s experiences in the workplace have influence on his or her health and psychological well-being (Chan &Wyatt (2007); Srivastava (2007); Aziri, (2011).

Kaur (2013) opines that well-being refers to how people evaluate their lives. These evaluations may be in form of cognitions or in form of affect. The cognitive part is an information based appraisal of one’s life, that is, when a person gives conscious evaluative judgments about one’s satisfaction with life as a whole. The affective part is a hedonic evaluation guided by emotions and feelings such as frequency with which people experience pleasant/unpleasant moods in reaction to their lives. The assumption behind this is that most people evaluate their life as either good or bad, so they are normally able to offer judgments. Furthermore, people invariably experience moods and emotions which have a positive effect or a negative effect.Thus, people have a level of subjective well-being even if they do not often consciously think about it, and the psychological system offers virtually a constant evaluation of what is happening to the person. Well-being is not just the absence of disease or illness. It is a complex combination of a person’s physical, mental, emotional and social health factors (Kaur, 2013).

Well-being is measured as happiness or satisfaction with life. The search for happiness is often confused with the pursuit of pleasure, but well-being is about more than living the good life. It is about having meaning in life, about fulfilling our potential and feeling that our lives are worthwhile (Bond, 2003). A few other terms like subjective wellbeing, quality of life, mental health and life satisfaction have been used as being synonymous with psychological well-being (PWB). Psychological well -being is a multi-dimensional concept. Results of factor analysis done by researchers confirm this and instruments have been produced to measure it. Cheerfulness, optimism, playfulness, self-control, a sense of detachment and freedom from frustration, anxiety, and loneliness has been accepted as indicators of psychological well-being by certain researchers (Sinha & Verma, 1992).

Employees’ psychological well-being is a state of happiness at workplace. It is a predictor of worker’s performance. According to Fisher and Hanna (2016) employees’ well-being is responsible to a much greater extent for labour turnover than is commonly realised. Wright (2010) emphasises the importance of the more recent and expanded research which shows that there is a significant relationship between employee well-being and psychological well-being on the one hand and Job performance and staff retention on the other. Psychological well-being is very important in the workplace to reduce the number of turnover intention or the intention to leave, especially in the higher educational sector. Well-being at work is a changeable term (Hone, Schfield & Jarden, 2015). However, it has often focuses on attributes of individuals at work rather than incorporating the work environment, the role of the regulatory environment or other external influences affecting employee well-being (Ravenswood, 2011). The focus of individual well-being and mental health has identified factors such as positive work relationships (Roche, Haar & Luthans 2014), relationships (Diener et al., 2010) and trust in leadership (Roche et al., 2014) as well as individuals’ resilience.

Measures of employee well-being have included fatigue, job-induced stress, job satisfaction and work-life balance (Macky & Boxall, 2008). Fewer studies have connected individual attributes with the context within which employee well-being takes place (Baptiste, 2008). However, some have included aspects of work environment such as supportive management (Gilbreath, & Benson, 2004; Hone, Jarden, & Schfied, 2015; Wood & de Menezes, 2011) and supportive colleagues (Hone et al., 2015) and physical factors such as green spaces (Lottrup, Grahn & Stigsdotter, 2013). The organisation of work can also be crucial with workload and deadlines impacting on people’s well-being and ability to gain adequate sleep (Moen, Kelly, Tranby, & Huang, 2011), and their ability to detach from work. Employment relations research into well-being has often focused on employee control (or lack of it) and voice in the workplace. Control over work and its flexibility has been found to be a vital key in employee well-being (Wood & de Menezes, 2011). This voice or control extends to organisational policies; for example, how patterns of work are decided, the predictability or un-predictability of work commitments and the timing of work (Wooden, Warren, & Drago, 2009).

It is often the collective process in which these decisions are made that makes the difference in how employees view the policies (Bailyn, 2011). However, this research often fails to take a gendered analysis of employee well-being at work. The one key area that broadly relates to gender and well-being has centered upon work-life balance (Gröpel & Kuhl, 2009) and the burden of care work that women still carry: women spend more time on domestic work and child care tasks than men (Walsh, 2013; Statistics New Zealand, 2015). Attempts to reconcile domestic and care work with paid work can backfire for women who may ‘choose’ occupations that are more flexible (such as within the medical professions – Walsh, 2013), and women may be judged more harshly than their male counterparts and seen as less committed to their jobs when they ask for flexible work (Allen, 2005).

2.2.7 Theory of Psychological Well-being

Carol Ryff’s model of psychological well-being theory is considered a powerful means of organizing one’s life as well as generating ideas about how to live better. It is scientifically validated and the model includes medical, biological and philosophical consecrations (for instance Aristoltle, Mill, Abraham Maslow and Carl Jung.) It has six criteria of well – being which are summarily discussed as follows:

 Self-acceptance

•High self-acceptance:- positive attitude towards oneself; accept multiple aspects to oneself (both good and bad); feel positive about your past life.

•Low self-acceptance:- dissatisfied with oneself; disappointed about what has occurred in the past; troubled by certain personal qualities; wish to be different than what you are.

 Personal Growth

Strong personal growth:- a feeling of continued development; see yourself as growing and expanding; open to new experiences, sense of realizing your potential; changing in ways that reflect more self-knowledge and effectiveness.

•Low personal growth: – a sense of personal stagnation; lacking a sense of expansion or improvement over time; feel bored (uninterested with life; feel unable to develop new attitudes or behaviours about life; see improvement in yourself and your behaviour overtime.

 Purpose in Life

• Strong purpose: – have goals and a sense of direction; feel there is meaning in the past and present life; hold beliefs that give life purpose; have aims and objectives for living.

• Weak purpose: – lack a sense of meaning or direction in life; few goals or objectives; do not see any purpose in your own life in the past or presently; no out look or belief that gives life meaning.

 Positive Relations with Others

• Strong positive relations:- Warm, satisfying, trusting relationships with others; once read about the welfare of others; capable of strong empathy, affection and intimacy with others; understands the give and take of human relationship

• Weak relations:- few, close trusting relationships with others; find it difficult to be warm, open and caring/ concerned about others ; isolated and frustrated in inter- personal relationships; not willing to make compromises to sustain important ties with others.

 Environmental Mastery

• High environmental Mastery:- possess a sense of competence, able to control a complex array of external circumstances; make effective use of external opportunities; create contexts suitable to personal needs and values

• Low environmental mastery:- have difficulty in managing everyday affairs; feel unable to improve or change surrounding contexts; unaware of surrounding opportunities; lack a sense of control over the external environment.

 Autonomy

•High autonomy:- self-determination and independence; resist social pressures; regulate behaviour from within; environment its self by personal standards.

•Low autonomy:- concerned about expectation and evaluation of others; rely on judgment of others.

2.2.8 Enhancing Worker Well-being

Employer responsibilities organisations have a role to play in worker well-being. This may be on moral, ethical or compassionate grounds recognizing that supporting good mental health has significant benefits to both the business and workers alike. Organizations also have legal responsibilities to ensure workplaces do not cause harm to the health of employees. Under the Health and Safety at Work Act 2015 (HSWA), Persons Conducting a Business or Undertaking (PCBUs) ‘have a primary duty of care to provide a work environment that is without risk to health and safety, so far as it is reasonably practicable. While focus is typically given to reducing the risk of physical harm, HSWA defines health as being both ‘physical and mental. Work safe New Zealand, the government body enforcing workplace health and safety legislation provides a range of information and guidance about health and safety in the workplace. It sets expectations of organizations to have effective systems of protecting the physical and mental health of workers from work-related factors and activities to promote general health and wellbeing.

2.2.9 Contemporary Approaches to Worker Well-being

• Enhancing the physical safety of workers

• Enhancing the physical welfare of workers

• Reducing the impact of psychological risks

• Worker-focussed health promotion

• Supportive environments to encourage positive health-related behaviour change.

2.3.0 Concept of Job Demand

Job demand represents the total quantity of work required from employee (Bakker, Demerouti, & Schaufeli, 2003). This is the extent to which an employee has to work under time and pressure and the degree to which an employee is expected to complete conflicting demands (Karasek, 1979). When an employee is unable to fulfill the job duties, work assignment and responsibilities that are assigned to him or her then he or she feels the job stress as a result of job demand. Ismail and Hong (2011) state that employees suffer from higher level of job-related stress if there are existences of job related demand factors are more in the working environment. Job demand factors are work load, long working hours, having no information about the work assignment, role ambiguity, unsupportive supervision and not good relationship with colleagues and supervisors. If these factors are not resolved by organisations then they lead to job stress and reduce the employee commitment to the organisation. Akinmade (2015) opines that job demand is the work pressure and work load experienced on the job. General (2008) asserts that the problems of job stress arise because of differences between employee job demand and the amount of control over gathering these demands.

Ajobi (2015) views job demand as a multidimensional concept that comprises three salient characteristics; role ambiguity, role conflict and role-overload. Firstly, role ambiguity manifest when an employee does not have clear information about his or her work objective, work scope, supervisor’s expectations and responsibilities of his or her job w hich may lead to higher job related tension. Secondly, role conflict usually occurs when an employee feels that there are traces of dilemma with his or her job demand; doing things he or she does not want to do, or doing things that are not considered to be part of his or her job. Being in between these two things requires an individual to make decision and making decision under conflicting demand is demanding and strenuous. Finally, role-overload normally refers to when an employee associates with heavy work burden which is beyond his ability to cope with and which often results in stress which usually affects the physical, psychological and emotional being of an employee.

Ogungbamila (2013) found out that work demand is a predictor of emotional, physical and psychological exhaustion. If nothing is done to reduce or moderate these demands, employees may become mentally and physically exhausted (Bakkers, Demerouti, Schaufeli, 2003). This may result to health problems such as Occupational Overuse Syndrome (Bakkers, Demerouti, Schaufeli, 2003), which may lead to job dissatisfaction and high turnover intention (Sarooj & Nazia, 2008: Kabungaidze, Mahlatshana, & Ngirande, 2013). In a study conducted by Noraani, Aminah, Jegede, and Khairuddin (2010) among a sample of single mothers in Malaysia, it was reported that there is posive relationship between job demand and intention to leave an organisation. It is not out of place to say that workers experiencing higher job demands have higher tendencies to quit their job.

Voydanoff (2005) posits that job demand is a structural and psychological claim associated with role requirements, expectations and norms, which individuals are required to respond to by utilizing physical and mental ability to meet the job requirement. Bakker & Geurts (2004) assert that job demand includes anything pertaining to the physical and psychosocial aspects of work in an organisation that require mental and physical efforts at the same time related to the cost associated with physiological and psychological costs. Examples of job demand include time pressure, physical and psychological demands that are related to individual responsibility for certain jobs, role overload and unfavourable environmental conditions. Mauno, Kinnunen & Rukolainen (2006) posit that job demand can deplete resources, for example, time, energy and emotions that are needed to perform. Excessive job demand leads to strain reaction, for example burnout and stress which result in increasing number of absenteeism and turnover intention. Mauno et.al (2006) define job demand as physical, psychological, social and organisational features of the job requiring physical or psychological efforts and energy from employee and are consequently related to physiological and psychological costs.

Job demand has also been categorized into physical, social and psychological demands (Schaufeli &Baker, 2004). Bakker and Demerouti (2007) confirm that job demand is not necessarily negative affirmation that when employees fail to meet their job demands it will lead to a negative outcome such as work-family conflict, job strain, burnout, and turnover intention. The physical job demand encompasses aspects of job that affects employee tasks directly (for example, task duration and frequency), the instrument used in a task, or the intensity of the labour during task execution. An example of this is when employees find it hard to keep up with the pace of work, when their time is too limited, or when there is just too much work to do (Bakker & Demerouti, 2007). Reactions to workload include negative emotion (Miles, Borman, Spector, & Fox, 2002) fatigue and other feelings such as anger and frustration. Other psychological strains are depression, work anxiety, and decreased job satisfaction. (Spector,2006).

Social job demand is considered to be the stress that the employees experience based on their working relationship with others in the organization. Work relationship may be sources of anxiety. When they are strongly emotion-laden and marked by high levels of interpersonal conflict is an example of social job demands as it refers to negatively charged interactions with others in the work place (Spector &jex, 1998). Emotional demand is a psychological job demand which refers to the degree to which a job requires employees to comply with specific display rules governing their emotional expressions in order to influence their clients’ feelings, attitudes and behaviours (Grandy & Fisk, 2005, Heuven, Bakker, Schaufeli & Huisman 2006). (Meng and Liu, 2008) affirm that the job demand of teaching profession as researchers is too much to the extent that it has negative impact on their well-being. Fajana (2006) affirms that learning organisations now take better care of their employees. They have realized that employees’ value perceiving them as stakeholders and partners with whom long terms goals are achievable rather than a mere “factor of production” from classical perspective.

Meng and Liu, (2008) affirm that the job demand of the teaching profession as researchers is too much to the extent that it has negative impact on their well-being. Akinde and Alamutu (2016) assert that the consequences of job demand include sickness, absence from work and work disability. Salleh (2008) confirms that the effects of job demand and job pressure are not only destructive to the individual employee but also to the organisation. Many employees are experiencing long working hours, intensified workloads, constant changes in work practices and job insecurities (Haworth & Lewis, 2005). Working long hours has been associated with high levels of anxiety and low levels of job satisfaction resulting in employees not trusting their co-workers to do their jobs well (Jex & Gudanowski, 1992). Employee health is affected not only by a job’s physical environment, but also by its psychological environment (Gilbreath, 2004). It has been found that job demand, an aversive or unpleasant emotional and physiological state (Judge, & Colquitt, 2004). Individuals who experience chronic work stress as a result of job demand have been found to be positively associated with an increased risk of atherosclerotic disease (Kang, et al., 2010.

Job demands, together with role conflict, make up role strain, which refers to persistent conditions within various roles of participation that require daily re-adjustments and repeatedly threaten to interfere with performance in other role-related activities. Pealin, 2003) confirms that if job demand is not control it threatens to interfere with performance in other role-related activities. Perceptions of job demand serve as a chronic stressor for non –academic staff, defined by Lazarus and Folkman, (2004) as physical and social environmental conditions that the average person could perceive as actually or potentially threatening, damaging, harmful or depriving. Bird & Ford (2005) view job demand as an intrinsic phenomenon of their existence, although past research has explored the perceived daily role conflict aspect of role strain more in depth. As workers are allocated too many tasks to accomplish without sufficient time, there is a constant sense of rushing and hurrying that takes place on a daily basis.Some researchers have argued that role strain increases with the amount of activities associated with family and non-family (work, social) involvements.

(Burr; 2003) contend that there are advantages of multiple role involvements as a result of increasing resources and contacts (Burn, 2003). Recent job demand research trends have evolved from focusing on people’s deficits and vulnerabilities to placing increasing emphasis on adaptive strategies and constructive action during job demand periods. This study assumes a combination of positive personal impact on non -academic staff as a result of participation in both work and family roles, as well as the acknowledgement of the difficulty of living with the increased stress associated with job demand. Previous research has demonstrated that job demands such as long work hours, work role ambiguity, work role conflict, shift work, and physical and psychological effort contribute to job strain which results in role overload and feeling overwhelmed which contributes to work–family conflict. High demand at work increases the risk of experiencing work family conflicts (Chung, 2011; Fagan and Walthery, 2011).

2.3.1 Concept of Work-family Conflict

Work and family roles are indispensable for people nowadays. Once an individual experiences a high level of work and family conflict, it will definitely influence his job satisfaction and well-being. When work role conflicts with a non-work role occurs, it will reduce the role satisfaction (Boyar, Maertz, Pearson, & Keough, 2003; Zhao & Namasivayam, 2012). Work-family conflict takes place when one is forced to handle two different and incompatible roles at the same time (Gearson, 2011). For instance, there may be conflict when a person finds it hard to strike a balance betwee n his or her role and the role as an employee especially when his or her child’s demand for time and attention distracts him or her from fulfilling the role for which he or she is employed. Zhao and Namasivayam (2012) demonstrated that when a hotel employee felt that his job interfered with his role at home, his job satisfaction reduced.

In addition, Boyar et al. (2003) pointed out that when an individual experience their work interfering with non-work, it would reduce job evaluation, and result in the reduction of job satisfaction. In other words, when family roles which do not belong to the range of work roles are influenced by the job, it may lead to the reduction in job satisfaction. Some work arrangements, such as shift work, overtime, and working on holidays can reduce or deprive an individual’s family time or deprive them of the opportunity to be with their family (Tsaur, Liang, & Hsu, 2012). As a consequence, employees may feel dissatisfied with their work because aspects of their work factor make it impossible for them to fulfill their familial demands. Some researchers have also proved that non-work role aspects interfering with work role could also reduce job satisfaction. Zhao and Namasivayam (2012) pointed out that when the requirements of the family role of an employee made him unable to effectively achieve his job objectives, he would become frustrated, and thus feel dissatisfied.

Boyar et al. (2003) believed that when a non-work role interferes with a work role, an individual would blame the company system for causing such uncomfortable feelings, and the individual’s job satisfaction would be reduced. In other words, when the work role is interfered with by the family role, when the family interferes with the work, it will also reduce the employee’s job satisfaction. When an individual spends more time and effort on his family role, it will definitely reduce the time and effort he invests in his work (Tsaur et al., 2012). Therefore, an individual may not be able to obtain the expected feedbacks and respect from his work, and will gradually become dissatisfied with his work

Changes in the demographic make up of the work force and family structures have created a situation where a significant number of employees have difficulties in joggling work and family responsibilities.Work and family issues have been long discussed in academic and practices where work often affects family and personal life and vice versa. Greenhaus & Beutell (1985) define work–family conflict as “a form of inter-role conflict in which the role pressures of the work and family domains are mutually incompatible in some respect. That is, participation in the work (family) role is made more difficult by virtue of participation in the family (work) role. The conflict of work and family could lead to positive or negative consequences to employees such as satisfaction (Rathi and Barath, 2013). Work – family conflict is a form of inter-role conflict in which work and family demands are mutually incompatible. (Higgins, Duxbury, & Lyons, 2007).

Work-family conflict is experienced when an employee has difficulty in balancing work and family demands (Aryee, Luk, Leung, & Lo, 1999; Ahmed & Masood, 2011; Carmeli, 200; Noor, 2003) or when performing work roles reduces the time and energy needed to successfully performs family responsibilities (Grandey & Cropanzano, 1999; Jawahar, Stone, & Kisamore, 2007). For example, the inflexible long working hours in the higher institutions in Nigeria may prevent non-academic staff from picking his or her child from school based on the fact that non–academic staff ought to be at their duty post from 8.30am till any time they close from work. This always brings about work-family conflict. Work-family conflict (WFC) is a type of inter-responsibility clash in which the responsibility demands from the occupational and family spheres are unable to mutually coexist in such manner that involvement in the occupational (or family) role is made additionally hard by virtue of involvement in the family (or occupational) role (Greenhaus & Beutell, 1985).

This definition proposes a bidirectional facet in which the sphere of work can meddle with the sphere of family and vice versa (Koekemoer & Steyl, 2011).

Therefore, if an employee is experiencing high levels of family-work role conflict, their roles and responsibilities in family life are interfering with the work domain. Meanwhile, because the employee is more committed to the welfare of the family, this will take priority, reducing or minimizing the resources of time and energy to be spent in the work domain. Thus, employees who experience high family role conflict should experience less affective commitment to the organization. Work-to-family conflict occurs when the domain of work interferes with the family demands and vice versa for work-family conflict (Ajiboye, 2008).

According to Boyars, Maetz, & Carr (2008) there exists a relationship between lengthy working periods, obligations, and heavy labour on work-family conflict. In the recent times, arguments on work-family role conflict as it affects workers` behaviour at workplace pervade existing literature. Various researchers have investigated the relationship between work-family role conflict and organizational efficiency and productivity. In most of these studies, it was found that a significant relationship exists among work-family role conflict and managerial efficiency of the managers (Popoola, 2008; Akinjide, 2006; Collins and George, 2004; Akinboye, 2003). Similarly, Poele (2003) reported that efficiency in managing organizational resources for results could be better guaranteed when various variables other than one, such as leadership style, self-efficiency, personality, work-family role conflict, job satisfaction and motivation are jointly combined by the managers in work organizations. The finding of the study is very unique because it establishes the relevance of work-family conflict as an important factor in the consideration of effective management of organizational resources for results.

Initially, scholars focused on work-to-family conflict and family-to-work conflict. Hughes & Bozionelos (2007) assert that the issue of work–family conflict is more complicated owing to changes in economic, globalization and equal employment opportunities. Allen (2012) suggests that work-family conflict consists of two constructs, work family conflict and family work conflict. Work and family roles are indispensable for people nowadays. Tsaur, Liang &Hsu (2012) affirm that when an individual spend more time and effort in his family role, it will definitely reduce the time and effort he invests in his work. They assert that some work arrangements, such as shift work, overtime, and working on holiday can reduce or deprive an individual family. Consequently, employees may feel dissatisfied with work because some aspects of their work factor make it impossible for them to fulfill their family demand. Cesnauskas & Lazauskaite-Zabielske, (2014) opine that work–family conflicts appear when the needs of work and family do not correlate with the needs of family and work. The nature of such conflict contains negative consequences for all – an employee, his/her family and organization to which he or she belongs.

Outlasting conflict causes stress, depression, as well as increases sickness rate or decreases self-satisfaction with work accomplished, or even family life. Simultaneously, an organisation is affected by inadequate employees’ involvement in the implemented activities, increased intention to change working place, decrease in quality of the achieved results.Therefore, executives and administration of diverse organizations attempt to decrease work-family conflict by the different means creating flexible work schedules, supporting maternity/paternity leave or child care services (Moen, 2003;Kempe & Otonkorpi-Lehtoranta, 2006; Vuga & Juvan, 2013; Cesnauskas & Lazauskaite-Zabielske, 2014). Beauregard (2006) claims that it is natural and widespread to witness the extra time spent in the job sphere unavoidably result in less time on hand to be spent at the home domain, making it exceedingly difficult to meet family obligations. From the study of Alam, Sattar and Chaudhary (2011) conducted in Dhaka, it was exposed that prolonged office hours influenced work family balance directly and off springs were the most awful sufferers of this work-family conflict.

Work–family conflict constitutes a major source of stress with adverse effect on employee’s well-being and attitudes (Matthew, Winkel and Wayne, 2014; Nohe and Sonntag, 2014) as well as on families and organisations in terms of diminished family and organisational performance (Nohe and Sonntag, 2014; Van – Steenbergen and Ellemers, 2009.) Result of the analysis of Komarraju (2006) puts forward that dual-career workers who experienced their family commitments interfering with their job activities were likely to face job dissatisfaction. Recently, the findings of Wang, Fu and Wang (2012) attested to the fact that work interfering family conflict and family interfering work conflict were positively related with emotional exhaustion and cynicism among Chinese female nurses.

2.3.2 Effort-recovery Model and Work-family Conflict

The effort-recovery model (E-R Model) proposed by Meijman (1989) asserts that employees build up negative load effects during the week day. This does not necessarily lead to negative consequences for employee’s health and well-being as long as employees are given sufficient time to recover from these effects. If the individual does not have ample private time to recover, load effects built up at work resulting from long hours, cause health problems. Furthermore, due to a lack of recovery time, the demands made in the private situation, such as domestic and private tasks, may add to the work-non-work interference. Therefore, individuals need sufficient unwinding time to recover from strain and tiredness carried from the work environment. The relevance of the effort-recovery model to the work-home interface is clear. It is plausible that high levels of job-related effort and over-commitment to the job role might result in perceived conflict between work and home. It is also likely that employees will believe that their efforts and achievements at work are not counter balanced by the rewards which they receive. It may be less likely to tolerate an intrusion into their home lives rather than those who work under more equitable conditions.

Moreover, previous studies have found out that the effort-reward imbalance may lead to negative affective reactions (Van Vegchel, De Jonge, Bosma, & Schaufeli, 2005 as cited in Kinman & Jones, 2007) as perceived inequality could also manifest itself as strain-based work-family conflict.

2.3.3 Concept of Social Support

Employee relationship at work and at home is very important for satisfaction and wellbeing. A consistent body of research has emerged over recent decades to show that close relations with family, friends, and significant others is a protective factor that helps guard against the deleterious mental and health effects of unemployment (Bjarnason & Sigurdardottir, 2003). Thus, lack of social support is positively related to depressive and anxious symptomatology, both in the general population (Siedlecki, Salthouse, Oishi & Jeswani 2014) and among the unemployed population (Rey, Extremera & Pela´ez-Ferna´ndez, 2015). Social support is an informal social network that provides individuals with expressions of emotional concern or empathy, practical assistance, informational support or appraisal (Etzion, 1984).

Mc–Terman, Dollard, Tuckey & Vandenberg, (2016) affirm that social support may aid in preventing the stress response by functioning as a resource that provides alternate means to address the stressor. Increased social support (both by work and non-work sources) is related to increased health and well-being (Adams, King, & King, 1996). Individuals with different sources of support (ex-coworkers, community and financial resources) create a buffering effect that helps individuals deal with work-family conflict (Martins, Eddleston & Veiga, 2002; Cinamon & Rich, 2010). Social support can be regarded as important factors in dealing with job as it provides a supportive work environment to reduce the level of stress in the lives of their employees. This can be done formally by recognising the importance of an employee’s family and supporting other activities not directly related to career success (Boles, Johnston & Hair, 1997).

Social support refers to “an interpersonal transaction that involves emotional concern, instrumental aid, information, or appraisal” (Carlson & Perrewé, 1999). It is also defined as the help or care from other persons that individuals can accept, feel or notice (Wang, Cai, Qian & Peng, 2014). Good social support can help in maintaining a good emotional experience and protect an individual who is under stress (Maulik, Eaton & Bradshaw, 2011). Previous research on work pressure done by Cohen and Wills (1985) emphasizes that social support can play a vital role in a workplace pressure environment. The researchers highlight that employee may be less affected by stressful workplace event if they feel organisationally supported. Supporting this view, Hur, Moon and Jun (2013) emphasise the importance of employees’ perceptions about their organisational support to ensure the success of business operations and how organisational support may influence workers, who often feel they are under stressful conditions.

Van-Daalen (2006) asserts that social support is the exchange of resources between at least two persons with the goal of helping the person who receives the support a supportive work environment and providing the employee with emotional resources such as understanding, advice and recognition. Several studies have also found evidence to link negative work conditions to increased levels of stress at home, less satisfying family relationship, poorer mental well-understanding, advice and recognition. Gillespie and Grzywacz (2001) found out that social support from colleagues at work was reported by half of the academic staff in their study as valuable in moderating stress, and that many reported the importance of support from their manager and senior management. Martins, Eddleston and Veiga (2002) found that it is very important for employers that would like to develop a motivated and committed workforce to fully understand the contributing factors that can influence their employee’s satisfaction in their caree. Such employer should provide social supports to its workers so that they could cope with the multiple roles they performed.

According to Seiger and Wiese (2009) social support helps individual to retain existing resources and gain new resources. With an increasing number of women in the workforce, Maxwell and Dougall (2004) found that organisations are more likely to offer more work-life balance programmes due to individual’s home responsibilities. Boden (1999) suggests that employers should seek to create working conditions that are more accommodating of workers personal lives by creating flexible work schedules. In providing work-life balance programmes, there is the potential to better support employees (Milliken, Martins & Morgan, 1998). Research has demonstrated that supportive work-family culture and informal support have a greater effect on work-family conflict than do formal family-friendly organizational policies (Major & Lauzun, 2010). The supervisor can determine how satisfying a job can be by influencing how demanding is the job (Gilbreath & Benson, 2004). Support from supervisors has been reported to reduce work role conflict, role ambiguity, and resultant work-family conflict (Major& Lauzun, 2010).

When supervisors are perceived to be supporting employees, there will be improvement in employees “commitment to the organization (Thornhill and Saunders, 1998) and reduced reported levels of stress and work-family conflict (Cinamon and Rich, 2010; Judge and Colquitt, 2004).Working mothers with supportive bosses report being less irritable and experience reduced stress levels. This also determines how much autonomy the employee has in the job and the sense of achievement that comes from doing the job (Purcell & Hutchinson, 2007). The relationship between front line managers and their own managers is important and has been shown as the most influential variable explaining front line manager’s own levels of affective commitment and job satisfaction (Purcell & Hutchinson, 2007).

It has been explained that a supervisor’s support expands individual’s psychological resource base, such as confidence, which may enhance performance in the family domain (Baral & Bhargava, 2010). Hossam, Asayesh, Ghorbani, Shariati & Nasiri (2011) investigated the association between perceived social support, mental health and life satisfaction among Shahed students in state universities in Gorgan. Social support, as a very important source in both work and family life can reduce the negative effects of job and family stressors. Generous, Parasuraman, and Greenhaus (1992) argue that social support, as an adjustment source, can play a significant role in the face of job and family stressors. First, social support can directly affect pressure and other negative consequences of these stressors in different spheres of life and reduce pressure level experienced. Also, social support can moderate the effects of stressors on individuals’ health profiles and welfare in both family and career life.

A review of studies on the relationship between social support and work-family conflict shows that lack of social support in both work and family life leads to higher levels of work-family conflict (Matthews, Bulger, Barnes & Farrell, 2010; Cortes, Colombo, & Gilsiri, 2010, Blanch & Aluja, 2012; Seeger & Weiss, 2009). In explaining the components of the two variables under study, it should be noted that if a person receives sufficient support from family, friends, and others (such as peers in the workplace), he can effectively manage time-based work interference with family, debilitation-based work interference with family, behaviour-based work interference with family, time-based family interference with work, debilitation-based family interference with work, and behaviour-based family interference with work.)

2.3.4 Social Support Theory

The theoretical perspective on social support research indicates that the availability of social support contributes to overall well-being (Lakey & Cohen, 2000). More commonly, social support has been operationalised and conceptualised in perceptual, dynamic, and structural terms. The perception that one is loved for, cared for, and valued are examples of perceptual social support variables (Cobb, 1976) whereas the exchange of resources to enhance the well- being of recipient has been identified as dynamic process of social support (Schumaker & Brownell, 1994). Four categories of social support in terms of emotional social support (for example, empathy, love, caring, trust, etc.), appraisal social support (for example affirmation, feedback), informational social support (for example, guidance, suggestion, direction, etc.) and instrumental social support (e.g., help in terms of time, in-kind assistance) have been recognized as structures and categories of social support (House, 1981; Nelson & Quick, 1991). The strain-reducing effect of social support changes with its theoretical placement in the model. Social support has been used as an independent, intervening, antecedent, moderating, and mediating variable (Carlson & Perrewé, 1999).

With the assertion that social support promotes coping by reducing the effects of stressors on the strain experienced, the proposition is that the strain which is experienced in form of work-family conflict as a result of increased job demands (stressors) can be reduced with the availability of social support. This suggestion about the relationship between job demands, work-family conflict and social support purports that there is an indirect relationship between social support and work-family conflict. Although some studies indicate that social support mediates the relationship between job demands and work – family conflict (Anderson, Coffey & Byerly, 2002; Frone, Yardley & Markel, 1997; Warren & Johnson, 1995) a few studies have examined social support as antecedent to job demand variables (Fisher, 1985; Frone, Yardley and Markel 1997). Social support has indirect and intervening relationship with job demands and work-family conflict. Another possible way in which the availability of social support may influence the level of work-family conflict experienced is through direct effect whereby its presence is associated with reducing the negative consequences of work-family conflict (Thomas & Ganster, 1995).

2.3.5 Empirical Review

2.3.6 Job Demand, Job Satisfaction and Well-Being

Tsai, Chang & Chang (2010) conducted a study to investigate the relationship between job satisfaction and job demand. The study included 604 employees from 13 well-known hospitality companies in Taipei City, Taiwan. The path coefficients of the Structural Equation Modeling (SEM) analysis showed that job satisfaction was positively related to job demand. In another study, Gunlu, Aksarayi & Percin (2010) also extended research on work related attitude to the hospitality industry by examining the effect of job satisfaction on organizational commitment among 123 hotel managers in Turkey. The finding from multiple regression analysis indicated that overall job satisfaction was positively related to both normative and affective commitment. However, overall job satisfaction did not significantly have relationship with continuance commitment. They emphasised that the non–significant relationship between job satisfactions was due to mobility characteristics of the hospitality where employees find it much easier to work in many different hotels.

Similarly, Tella, Ayeni & Popoola (2007) investigated the relationship among work motivation, job satisfaction and organisational commitment among 200 library personnel in academic and research libraries in Oyo State, Nigeria. The finding of this study revealed that both perceived work motivation and job satisfaction were significant predictors of organizational commitment. Rita, Atindanbila, & Abepuoring (2013) conducted a study among the nurses of two different Ridge and Pantang hospitals of Ghana to identify the level of job satisfaction and job demand. The study proves that different factors of job demand have impact on job satisfaction. 105 nurses were selected from both hospitals as a sample. The results showed that the level of job demand and job satisfaction is same in both hospitals. The result also shows that the level of workload was higher in Ridge Hospital and there was weak negative relationship between job demand and job satisfaction among these two hospitals.

Hans, Mubeen, & Saadi (2014) conducted a study on job demand, job satisfaction and well- being among the headmasters of Building School in Muscat, Sultanate of Oman. Simple random sampling technique was used to select the participants. They took 40 headmasters of that school as sample. The result of the study showed that the headmasters of the Building School felt high level of job satisfaction in their challenging work and were more likely to experience stress at their work which affected their well-being. Another study on the influence of wage on job satisfaction found that changes in wage correlated with job satisfaction. “The Impact of Wage Increases on Job Satisfaction – Empirical Evidence and Theoretical Implications” by Grund & Sliwka (2001), found out that job satisfaction “strongly depends on the relative wage increase as well as the absolute wage level,” (Grund et al., 2001). The goal of Grund & Sliwka’s (2001) study was to establish the idea that job satisfaction depended on wage level.

Grund & Sliwka also analyzed both absolute and relative wage, something that most other studies did not do. Grund & Sliwka included change in wage in its empirical analyses. It was argued that perceived utility was not only dependent on absolute wage but relative wage. Both studies found similar results; change in wage was positively correlated with job satisfaction.

2.3.7 Work- family Conflict, Job Satisfaction and Well-being

. Boles, Howard, & Donofrio, (2001) investigated the relationship of work-family conflict and different facets of job satisfaction (i.e., satisfaction with pay, work itself, co-w orker and supervision). They attempted to identify the direction of conflict that was more important as a predictor of job satisfaction. They found that both WFC and FWC were significantly related to all aspects of job satisfaction. They also found that WFC could be more important and powerful to use as predictor of various aspects of job satisfaction. Previous studies work –family conflict shows that work-family conflict has negative relationship towards job satisfaction (Boles et al. 2001; Anderson et al.2002) and organizational commitment (Carlson, et al, 2000). In the study conducted by Wright and Cropanzano (2000) on job satisfaction and psychological well-being as a predictor of job performance, report that psychological well-being had a predictive effect upon job performance; however, psychological well-being had no predictive effect upon the job satisfaction.However, In the study conducted by Witte (1999) on 336 iron workers, He found out that there is a strong relationship between unreliability against the job and psychological well-being of the workers.

Also in another study conducted by Terry, Nielsen and Perchard (1993) carried out on 153 public workers, found out that job stress have a negative effect upon the psychological well-being and job satisfaction. Several organisational researchers have identified a number of possible antecedents to job satisfaction. This is because job satisfaction is an important workplace construct and one that is of great concern for effective management. Some of the antecedents of job satisfaction include a variety of perceptions and attitudes. For example, supportive supervision is related to job satisfaction. Johansson (2002) and Anafarta (2011) claimed that there was a reciprocal link between work family conflict and family work conflict and that work family conflict had an authority on determining job satisfaction while family life conflict did not have an effect on job satisfaction. Beauregard (2006) claimed that it was natural and widespread to witness that the extra time spent in the job sphere unavoidably resulted in fewer time on hand to be spent at the home domain, making it exceedingly difficult to meet the family obligations.

Anafarta and Kuruüzüm (2012) found out that the degree of work family conflict experienced by both men and women was soaring, and there was no statistically significant difference between their averages. In both men and women, the WFC was negatively associated with education. However, in men work family conflict was negatively related with marital status whereas, in women it was positively related with itNamayandeh, Juhari and Yaacob (2011) concluded that work family conflict among wedded female nurses in Shiraz (Iran) was associated with work satisfaction and family unit satisfaction. Nadeem and Abbas (2009) found from their research that occupational strain coupled with work life conflict resulted in variation in the work satisfaction of the workers. Work to family intervention, family to work intervention and strain were negatively connected with work satisfaction.

Job independence and work burden is positively related with job satisfaction. The relation between work-family conflict and the big five individuality model was investigated by Blanch and Aluja (2009) and it was uncovered that work requirement, work and family unit encouragement and neuroticism were the most crucial factors which meddled with work life. Noor and Maad (2008) looked at the association between work-family conflict, strain and turnover intentions experienced by Pakistani employees working in marketing area. They found that work-family conflict and strain had positive liaison with employees’ turnover intentions. Dealing with work and family roles involves emotional labour, and this is taxing making conflict between the two domains inevitable (Daalen et al., 2009). Several researches have attested to the fact that employees who experience work-family conflict are more vulnerable to job burnout (Burke, & Greenglass, 2001; Anand, Nagle, Misra & Dangi, 2013). Montgomery, Panagopolou, Wildt, and Meenks (2006) for example, found that work-family interference had a significant effect on burnout among workers in a Dutch government organisation.

Noor and Zainuddin (2011) reported that work-family correlated positively and significantly with emotional exhaustion and depersonalization. Recently, the findings of Wang, Chang, Fu, and Wang (2012) confirmed that work interfering family conflict and family interfering work conflict were positively related with emotional exhaustion and cynicism among Chinese female nurses. Work-related demand has been linked to a host of physical illness (such as heart disease, cancer, and pain), emotional and psychological distress (e.g., depression, anxiety) and several negative work attitude and behaviours such as job dissatisfaction, burnout, poor commitment and high turnover intention among service workers (Jamals & Bada, 1992; Jamal & Bada, 2000;Alves, Chor, Faerstein, & Werneck, 2004). In the Nigerian context, Salami (2011) found that job stress increased lecturers’ vulnerability to emotional exhaustion, depersonalization, and personal accomplishment.

Recently, Ogungbamila & Nwankwo, (2013) found that workload predicted emotional exhaustion among bank employees. Therefore, it is not out of place to posit that non- academic staff in Nigerian polytechnics that experience work-family conflict and high level of job demand are likely to be more vulnerable to lack of job satisfaction.

2.3.8 Social Support, Job Satisfaction and Well-being

Several theoretical models attempt to explain the process through which social support may impact job satisfaction and well-being of workers. The main-effects model posits that social support has important implications for individual’s job satisfaction and well-being regardless of the presence or absence of life stress (Cohen, Underwood, & Gottlieb, 2000). They compared social support of physically battered and verbally abused women recruited from shelters and other community settings cross-section ally and found that women’s perceived support had positive effects on job satisfaction and well-being regardless of the type of abuse experienced, despite the initial hypothesis that social support is a protective, buffering factor.

Ogunyemi and Awoyele (2014) investigated the buffering effects of critical life event, organisational climate and social support on Subjective Well-Being (SWB) of bank workers. The participants were five hundred and forty (540) bank workers (mean age 35.4) selected from 108 banks through stratified and simple random sampling techniques from the 18 senatorial districts in the six states (Ogun, Oyo, Osun, Ondo, Ekiti, Lagos) of Southwest Nigeria. Four instruments, subjective happiness scale, impact of event scale, organizational climate descriptive questionnaire and Duke- UNC functional social support questionnaire were utilised for data generation. The data collected were analyzed using multiple regressions (stepwise) and t-test statistics. Findings showed that the three predictor variables (critical life event, organisational climate and social support) combined and individually, predicted the criterion variable (SWB). Finding also indicated that critical life event was the most potent contributor to the prediction of SWB of bank workers. The implications of these findings for the government, policy makers and employers of labour, who may be interested in effective functioning and general well-being of workers, were discussed.

Research has demonstrated that the availability of social support at work helps to reduce the negative experience of work –family conflict (Andrson et al 2002; Greenhaus & Parasuraman, 1986; Thomas & Gaster, 1995). A study by Karatepe and Kilic (2009) found that supervisor support reduced wor –family conflict among frontline employees in Northern Cyprus Hotel and this was comfirmed by empirical data. This finding was supported by the study of Frye and Breaugh (2004), which indicated that the supervisor support gave important consequences to work–family conflict and reduced work-family conflict. Muse and Pichler (2011) suggested that the supervisor support and family support were the key predictors to work –family conflict. Edwins, Buffardi, Casper, & Brien (2001) also suggested that social support can be seen as a resource that has been found to be associated with reduced work- family conflict. Findings of Wadworth and Owen (2007) in public organization sectors in two western cities in the U.S.A confirmed that social support, especially from work sources, reduced the possibility of work interference with family, which was one of the directions of work- family conflict.

Lai (2011) in his study among hotel employees in Beijing and Hong Kong reported that family support can reduce work-family conflict among Chinese family, which is known by its Confucian ideology and familistic collectivism society. The familistic collectivism society study revealved that support from family was more effective in reducing work–family conflict by employees than support from work Jo and Shim (2015) found that work related characteristics, especially coworkers and supervisors support, significantly affect police officer’s job satisfaction. They also found out that neither demographics nor community characteristics influenced job satisfaction. The study once again proved that a positive relationship exists between job satisfaction and managerial support. Jonjil and Choi (2017) investigated how and whether different sources of social support influence quality of life and job satisfaction among teachers. The findings revealed that director-colleague support predicted job satisfaction. The results proved that managerial support is of the utmost importance in job satisfaction among teachers. Pohl and Galleta (2017) investigated supervisors’ emotional support as a strong determinant of job satisfaction.

The results showed that cross-level interactions were significant for job satisfaction. The employees with high levels of work engagement showed high level of job satisfaction and this relationship was stronger when the supervisors’ emotional support at group level was high. This also proved that managerial support is very important for job satisfaction among employees.Unavailability of social support from supervisors has been associated with higher incidence of work-family conflict, job dissatisfaction (Anderson et,al. 2002) Increased supervisor’s social support and co- worker’s support have been associated with lower incidence of work-family conflict, and lack of social support has been related to higher level of work–family conflict.( Greehaus et al., 1987; Stephenss & Sommer 1995). Garcia-Izquierdo, Albar-Marin and Garcia-Ramirez (2008) investigated the role of three sources of social support in a sample of 210 nurses at three hospitals in Seville. Each of the three sources of social support (family, co-workers and supervisor) had significant relationships with emotional exhaustion. Albar Marin and Garcia-Ramirez (2005) in a sample of 210 nurses from hospitals in Seville, reported that higher levels of social support were associated with lower levels of emotional exhaustion.

Meadows, Kaslow, Thompson, and Jurkovic (2005) found that social support was negatively related to the likelihood of suicide attempts for women with histories of abuse. Coker, Smith, et al. (2002) found that social support was beneficial for women’s overall mental health. Social support has also been theorized as a moderator, or buffer for people experiencing stress (Cohen et al., 2000). For survivors, this model suggests that social support functions as a protective factor, mitigating the impact of abuse on women’s well-being. Thus, abuse may have a differential impact on women’s well-being, depending on their perceived level of social support. Several researchers have cross examined the buffering effects of social support on survivors’ mental health, job satisfaction and well- being. Kaslow et al. (1998) investigated social support, abuse, and suicidal behaviour among African American women recruited from a public health care system, finding that abused women with greater social support were less likely to attempt suicide than those with low levels of support.

Carlson, McNutt, Choi, and Rose (2002) examined social support and other protective factors (self-esteem, education, income, employment, and good health) as buffers against negative mental health impacts of recent IPV, lifetime IPV, and child abuse among women from primary care settings. When coupled with other protective factors, social support moderated the relationship between abuse and anxiety but not in the expected direction. The buffering effects were less pronounced at higher levels of lifetime abuse, suggesting that protective factors such as social support may be insufficient for women experiencing the most severe abuse. The underlying theoretical construct is the demand control/support model which suggests that the demands of work can be balanced by the level of control experienced as well as by the level of social support (Dollard, 2001; Guglielmi & Tatrow, 1998). Ismail et al. (2012) carried out a study to scan the association between the humanistic social support from workplace and work-family conflict. The results explained that the willingness of supervisors and colleagues to sufficiently present material and moral cooperation in performing jobs had lessen the work-family conflict faced by workers.

Most employees spend majority of their lives at the work place and by extension tend to form interpersonal relationships and friendships at the workplace. Most research studies have reported the importance of recognition and feedback for retaining valuable employees (Allen, Shore & Griffeth, 2003; Morrow, 2011). Jongil and Choi (2017) investigated how and whether different sources of social support influence quality of life and job satisfaction among teachers. The finding revealed that the director-colleague support predicted job satisfaction of teachers. Some research studies have demonstrated that a positive relationship exists between job satisfaction and supervision (Smucker, Whisenant & Pedersen, 2003; Mafini & Dlodlo, 2013). Robbins (2003) reveals that supervision forms a critical role in relating to job satisfaction. This satisfaction may arise from the supervisors’ ability to provide emotional and technical support and guidance on work related duties.

Some study findings have indicated that supervision is a predictor of job satisfaction (Labedo, 2008 cited in Mafina & Dlodlo, 2013). Mafini & Dlodlo (2013) reported a positive and moderate association between supervision and job satisfaction. It was further revealed that supervision is a statistically significant predictor of job satisfaction. Tabassum (2012) had proposed and analyzed a research model that attempted to investigate the relationship between social support and job satisfaction. The results of her study revealed that support from family and cooperations from colleague were negatively allied with job satisfaction. However, no negative association was noticed between supervisor and colleague support and job satisfaction. Researchers identified the relationship between social support at work and employee’s health and well-being (Nabavi & Shahriari, 2012). Studies by McCall, Lombardo and Morrison (1998) found out that supervisor support facilitates employee’s job satisfaction, staff development, on the–job learning and organisational commitment. According to Boyar and Monley (2007) the support of the immediate supervisor has a central impact on the experience and perception of workplace well-being.

Diriwaechter and Shvartsmana (2018) analysed how individual job satisfaction is affected by salary changes. The results showed that wage increase have statistically significant positive effect on job satisfaction for up to four years after increase. The study proved that salary plays an important role in job satisfaction. Also Thies and Serratt (2018) found that factors that contributed to nursing degree faculty job satisfaction were interpersonal interaction, professional status, autonomy, dissatisfaction associated with salary, organisational policies and the workload. These authorss findings proved that professional status which can be linked to great growth and promotional opportunities, often lead to better satisfied employees.

2.3.9 Gender, Staff Cadre, Job Satisfaction and Well-being.

. French-Canadian sample of physical therapists and psychologists, Senecal, Vallerand, and Guay (2001) found no differences between male and female persons in their levels of work family conflict. Gender differences in job satisfaction have attracted attention of researchers. Greenhaus, Parasuraman and Wormley (1990) found no significant differences in gender but they justified this outcome explaining that all the male participants have a higher position (managerial professional jobs) than female, who had more clerical jobs.

Liu and White (2011) reported that the primary determinants of job satisfaction were intrinsic factors that the work that they did made employees to be satisfied and that gender, job positios, educational level, work experience and hospital size were not siginificant in determining job satisfaction. Fu and Shaffer (2001) observed gender differences with women displaying higher levels of FWC and men more WFC. Matai, Nishikido and Murashima (2008) reported no significant gender difference in the total level of WFC, and that the level of work interference with family was significantly higher in male than female and the level of family interference with work was significantly higher in female. Many researches have been carried out to examine the job satisfaction of non–academic staff with effect of sex differences. Findings regarding sex differences are inconsistent. Some studies (Nadjla & Hasan, 2009; Ogunlana, Okunlaya, Ajani, Okunoye& Oshinaike 2013; Wahba, 1975) reported that male are more satisfied than female, but some studies (Amune, 2014) reported that female are more satisfied that male.

Some researchers (Ghaisi & Limoni, 2015; Onuoha, Samuel & Ojo, 2014; Mirfakhai, 1991; Somvir & Kaushik, 2012) have reported that there are no differences between sexes regarding job satisfaction. Results in a study by Ansari (2011) indicate no significant gender difference with regard to work-family interference and family-to-work interference. Research conducted by Carrillo-Garcia, Carmen Solano-Ruiz, Marinez-Roche and Gomez-Garcia (2013) emphasise the relationship between job satisfaction and gender differences. They found a significant relationship between the two variables. The sample consisted of 246 health care professionals at a university hospital in Murcia. Remarkably, they observed that women expressed more satisfaction than men (Carrillo-Garcia et al, 2013). Likewise, Kim (2005) found the same outcomes of Carrillo-Garcia and colleagues’ study; women experienced a higher level of job satisfaction than men despite the fact that, according to the researcher, they were recompensed with lower salaries. Moreover, he emphasised the datum that women also received less autonomy and promotional opportunity be compared to male subjects (Kim, 2005).

A study of bank employee in the U.K by Emslie, Hunt & Macintyre (2004) found that whilst there were no significant gender differences in perceptions of work-home conflict, there were gender differences in predictors of this conflict. Having children and working in a senior position were found to be a predictor of work-home conflict for women but not for men, while working unsociable hours was a stronger predictor of work home conflictfor men than women. Sangeeta, Bhatnagar and Jain (2014) examined the impact of the demographic variables on the work-life balance of software professionals in metro cities. Data were collected from 100 employees of five Information Technology companies of Delhi and CR, using questionnaire. There is evidence from the analysis that there is significant indifference between age, marital status and work load, but there is significant difference between gender and work load of Information Technology professionals and there is significant indifference between gender, marital status and losing of temper. There is also significant difference between age and losing of temper of Information Technology professionals.

The study suggests that Information Technology companies should take care of employee’s work load to balance the work-life. The Information Technology companies should consider every individual as unique and precious and should give time for their own personal needs. The Information Technology companies should increase work-life balance programme to reduce family-work conflict and promote well-being of its workforce. Another study that delved on the details that could be behind the significant relationship between job satisfaction and gender was the one conducted by Kifle and Desta (2012). They found out that male persons are more satisfied that female with the hours of work, promotion opportunities and workload. They found out that the relationship with co-workers and the contribution to society was associated to women’s satisfaction. Therefore, they drew the conclusion that male are satisfied with intrinsic dimensions of job satisfaction; women, instead, are more satisfied with extrinsic aspects of job satisfaction (Kifle and Desta, 2012). Conversely, Ghazzawi (2010) and Gumbang, Suki and Suki (2010) found a no significant relationship between gender and job satisfaction.

Rajadhyaksha and Ramadoss (2012) reported that of the various work-to-family conflict variables examined, there was a significant difference between men and women in work-to-parent conflict and energy-based strain but not in work spouse conflict, work-leisure conflict or work homemaker conflict. Matai, Nishikido and Murashima, (2008) remarked that some research studies found no gender difference, while other studies found that female reported higher levels of some dimensions of work-family conflict and that several studies carried out in Japan showed that female workers experienced higher work interfering with family and family interfering with work than male worker. Osagbemi (2003) found out that there is no significant difference between men and women in terms of expectations on pay, fringe benefit and nature of job. Malik (2011) revealed that overall gender differences can be seen as women do not have high expectations on pay, fringe benefit, nature of job e.t.c. Some studies found that the overall job satisfaction of hotel employees is related to age with a positive linear function (Frye and Mount, 2007; Sarker, et al., 2003).

Maturity, work experience and tenure advantages can lead the employee to adjust his/her work expectations to a more realistic level. Other empirical studies posited that there is no significant relationship between gender and job satisfaction among hotel industry employees (Frye and Mount, 2007; Jabulani, 2001; Shinnar, 1998). In a study conducted by Owoeye (2014) on emotional intelligence on job satisfaction of employees in Oyo State found out that there is no significant difference in job satisfaction of male and female senior and junior, as well as between single and married employees but there is a significant difference in job satisfaction of old and new employee. Furthermore, Hasnain, Ansari, & Sethi (2011) found significantly greater life satisfaction and lower self-esteem for working women than- for non- working women. It, therefore, becomes pertinent to explore the gender-differences in job satisfaction, well-being vis-a-vis job demand, work-family conflict and social support. The study of professional employees in Canada by (McElwain, Korabik, & Rosin, 2005) found that while there were no gender differences in family-work conflict, women experienced higher levels of work-family conflict.

Some of the studies examining gender and work-family conflict used general population samples. However, due to the gender structure of the labour market, gender comparisons within general population samples are problematic as they do not tend to compare with findings (Lundberg, 1996;Emslie et al., 2004; Winslow, 2005; Emslie & Hunt, 2009). Some studies have found evidence of gender differences in work-family conflict. The predominant finding is that women experience higher work-to-family conflict than men (Berntsson, Lundberg & Krantz, 2006; Burke, Lundberg, Mardberg, & Frankenhaeuser, 1994; Duxbury, Higgins, & Lee, 1994; Greenglass, Williams & Alliger, 1994; Marshall & Barnett, 1993). However, a study of employed people in the Netherlands (Jansen, Kant, Kristensen, & Nijhuis, 2003) and a study of working students in the United States (Eagle, Icenogle, Maes, & Miles, 1998) found that men experience significantly higher levels of work-to-family conflict than women. Bond (2003) stressed that wellbeing is often measured as happiness or satisfaction with life.

The search for happiness is often confused with the pursuit of pleasure, but wellbeing is about more than living ‘the good life; it is about having meaning in life, about fulfilling our potential and feeling that our lives are worthwhile. Sinha & Verma, 1992 and McCulloch (1991) have shown that satisfaction, morale, positive affect and social support constitute psychological wellbeing. Olatunde and Odusanya (2015) conducted a study on job satisfaction and psychological wellbeing among mental health nurses. The researchers made use of systematic random sampling technique in selecting 110 mental health nurses in Neuro-psychiatric Hospital, Aro Abeokuta. A well-structured questionnaire was administered to collect data from the nurses. Data collected were analysed with the use of Chi-Square statistical analysis. The findings from the study revealed that job satisfaction had a positive significant relationship with psychological wellbeing. Job satisfaction also significantly relate to older age of respondents. The result also shows that there is no cadre difference in job satisfaction and well –being of nurses. There was a significantly positive relationship between job satisfaction and psychological well-being.

The researchers concluded that continuous efforts should be made to examine other factors in the work environment that can impact positively on the psychological wellbeing and job satisfaction of mental health nurses. Lisa (2014) also conducted a study on the employees who worked in several fields ranging from customer service, accounting and finance, administration, information technology, marketing, underwriting and also sales and claims. It was found out that management and supervisor support (supportive work- family culture) effectively reduce perceptions of work-family conflict, which helps to reduce some of the negative effects of work–family conflict on employees’ well-being. Duxbury and Higgins, (2003) examined cadre as a predictor of job satisfaction and well-being. It was established that employees in managerial and professional positions report higher level of work–family conflict than those working in non- managerial and non-professional position. Carnicer, deLuis, Sanches, Perez & Jimenez (2004) discovered that there were differences in the job category level with respect to work- family conflict.

Hurlbert (1991) found that social support do has some effect on job satisfaction, but the results were not “overwhelming.” There is an increase in job satisfaction of members which are benefiting from co-worker’s suport.

2.4.0 Appraisal of Literature

Despite numerous opinions and research findings by several authors and researches, job satisfaction and well-being problems appear to be worsening among workers. Although attempts have been made by scholars to identify the factors contributing to this problem and to proffer solution, the problem of lack of job satisfaction and well-being among non-academic staff still prevails. Certain important variables have been largely ignored. In particular, available literature relating to job demand, work-family conflict and social support on job satisfaction and well-being among non – academic staff is scanty although many studies have been carried out on the impact of job involvement and workload. Yet little has been said about job demand, its relationship with job satisfaction and well-being among non- academic staff.

Almost all literature sources are from studies carried out in countries outside Sub-Saharan Africa, Nigeria in particular. Most of the research problems were undertaken in the developed and developing countries. The literature reviewed revealed that job demand, as well as work-family conflicts and social support, have been identified as potential independently influential factors in workers’ job satisfaction and well-being. job demand, in particular, is described as essential factor which has attracted the attention of researchers and owners of organizations because it is believed that reduction in job demand of workers will not only promote their well-being, it will go a long way in the realisation of the organisational goal and maximising profit,similarly,work-family conflict as potential influential factors in job satisfaction and well- being has been described as the incompatibility of family demand and job demand of workers. Even, social support is reported to be critical to workers’ job satisfaction and well-being.

2.5.0 Conceptual Model

Independent Variables Moderating Variables Dependent Variable

Job Demand

(JD)

Job Satisfaction

(JS)

Cadre

. Management

. Senior

. Junior

Gender

. Male

. Female

Work–family

Conflict

(WFC)

Well- being

(WB)

Social Support

(S S)

Fig 2.3.6: Conceptual Model of the Study

The conceptual model was developed by the Researcher

Figure 2.3.6 illustrates the conceptual model on which this study was built. The model showed the independent variables (job demand, work-family conflict, and social support) and the dependent variables (job satisfaction and well-being). It also showed the moderating variables (cadre and gender). The model showed the path diagram for the combined and relative contribution of the independent variables to the combination of the dependent variables and each of the dependent variables

CHAPTER THREE

METHODOLOGY

This chapter describes the method and procedure that was used in carrying out this study under the following sub-headings: research design, target population, sample and sampling techniques, instrumentation, method of data collection and method of data analysis.

3.1 Research Design

This study adopted the descriptive survey research design. This design is considered appropriate because it can be used when a researcher intends to reach a sizeable portion of the target population as sample from which data may be collected while the findings are generalised on the entire population. In this study, the target population is relatively large and a survey would be effective at collecting necessary data that could be used in exploring the factors that may contribute to job satisfaction and well-being of non –academic staff including job demand, work- family conflict and social support.

3.2 Population of the Study

The target population of this study is non-academic staff working in public and private polytechnics in South-West, Nigeria. Available data indicates that there are thirteen private polytechnics and fourteen public polytechnics as at June 2017 that are spread across the geographical zone with 9,621 non-academic staff. Details of the distribution of non-academic staff across the polytechnic are contained in appendix (1) Source Establishment unit of various institution.

3.3 Sample and Sampling Technique

The sample consisted of 1,312 non–academic staff randomly selected from six (6) public and six (6) private polytechnics. This represents 13.64 percent of the total number of non-academic staff in all the public and private polytechnics in South-West, Nigeria. The sample was selected using the multi-stage sampling procedure. This procedure was considered appropriate because of the need to ensure probability sampling at the various stages involved in the selection of the sample. The first stage has to do with the stratification of polytechnic according to the state where the polytechnics are situated. Stratified sampling technique was used to ensure that the polytechnic from each state from south west are selected for the study. Second stage selection has to do with the selection of polytechnics the two categories of polytechnics in this country are included in the study, stratified sampling technique was used to ensure that the two categories of polytechnics in this country are included in the study. Hence, the list of polytechnics was stratified into two that is; public and private polytechnics six private and six public polytechnics were selected using balloting method.

At the third stage, proportional stratified sampling was used to ensure that male and female non-academic staff was selected to reflect their proportion in the target population. At the fourth stage each group, male or female was again stratified into three groups: management non -academic staff Contedis 14 and above, senior non- academic staff (Contedis 8 – 13) and junior non- academic staff (Contedis 3- 7). Thereafter, simple random sampling of the participants was done. Out of the (1,312) questionnaire distributed, (1,252) were returned.(see Apendix 11 for details).

3.4 Instrumentation

The following validated instruments were used for data collection.

(a) Biographical Data Form designed by the researcher (BDF)

(b) Job Content Questionaire (JCQ) by Karasek (1985) was adopted by the researcher.

(c) Work-Family Conflicts Scale (WFCS) by Carlson, Kacmar, and Williams (2000) and was re-validated by Amazue Lawrence.O (2012) was adopted by the researcher.

(d) Multidimensional Scale of Perceived Social Support Assessment (MSPSSA) by Zimet, Powell, Farley, Werkman & Berkoff, 1990) was adopted by the researcher.

(e) Job Satisfaction Scale (JSS) by Warr, Cook and Wall (1979) and re-validated by Perminas, Vaitkevicius and Astraukaite, (2010) was adopted by the researcher.

(f.) Satisfaction with Life Scale – by Diener, Emmons, Larsen, and Griffin, (1985) and re-validated by Ezeokoli and Ayodele, (2013) was adopted by the researcher.

3.4.1 Biographical Data Form (BDF)

A biographical data form was used to gather information regarding participants’ demographic variables. Participants were asked to provide information regarding (a) polytechnic status (b) cadre (c) age (d) qualification (e) sex (f) work experience, (g) hours worked per week (see appendix A).

3.4.2 Job Content Questionnaire (JCQ)

Job content questionnaire is a sub-scale of job demand and decision latitude (job control) developed by Karasek’s ( 1985) Job content questionnaire sub scale was adopted by the researcher to measure job demand. It is a six item scale which described psychological stressors such as workload and time pressure. Responses are measured on a 5 point Likert scale ranging from 0 = never, 1 to 5 extremely often. Sample items on the scale are “to what extent does your job require you working fast?” “To what extent does your job require a great deal of work to be done?” The Coefficient’s alpha values for job demands range from .79 to 88 (Chay 1993; Fortunato, Jex &Heinish 1999; Moyle & Parkes, 1999; Westman & Eden 1997: Xie, 1996 Zohar 1997). Evidence criterion validity was obtained from cross-correlations of scales demographic distribution of the scale and inter correlations were consistent with the English version. Results of factor analysis were consistent with the two dimensions expected from the theory. Mean score and variations in the prevalence of high psychological demands combined with low decision latitude by age, sex, education and job category support the discriminant validity of the instrument. In Nigeria, the instrument has been used by Oluwole, Adetunji, and Awosiyan (2012).

3.4.3 Work-Family Conflicts Scale (WFCS)

Work-family conflict was measured with items from Carlson, Kacmar, and Williams (2000). The eighteen-item scale anchors its response on a 5-point Likert scale where “5” represents “always” and “1” represents “never”. The respondent is expected to circle the degree to which work-family conflict is experienced. Work family conflict was measured using the Work-Family Conflicts Scale (Carlson, Kacmar, and Williams, 2000). This scale measures the strain that non-academic staff experience as they try to fulfill their home roles while meeting their work role at the same time. Sample items are “My work keeps me from my family activities more than I would like” and “When I get home from work I am often extremely tired to participate in family activities.” This scale was developed using rigorous psychometric procedure (Herst & Brannick, 2004). It is consistent with the definition of work family conflict adopted by this study, which is that work family conflict occurs when a person’s performance of roles in the family is hindered by the performance of his/her role in the work domain (Akintayo, 2006; Britt & Dawson, 2005; Haar, 2004; Hill et al., 2004; Noor, 2004; Tatman et al., 2006; Wallis & Price, 2003). For the work-family conflict sub-scale, the Cronbach’s coefficient alpha value was 0.93. The scale has been used in Nigeria by Amazue Lawrence. O (2013) therefore, the scale was adopted by the researcher.

3.4.4 Multidimensional Scale of Perceived Social Support Assessment (MSPSSA)

Multidimensional Scale of Perceived Assessment (MSPSSA) developed by Zimet, Powell, Farley, Werkman and Berkoff (1990) was adopted by the researcher to measure social support. MSPSSA is a 12-item scale of perceived social support from family and friends and does not refer to deployment. Participants indicated how much they agreed or disagreed with each of the 5 items using 7-point scales that ranges from 7 strongly agree to 1 strongly disagree. Total is sum of all 12 items, possible range for total is 7-84. The algorithm of the scale shows that a score between 69 and 84 is of high acuity, 49-68 is moderate acuity, and 12-48 is low acuity. The internal consistency measured by Cronbach alpha for MSPSSA was 0.89 (Zimet, Powell, Farley, Werkman & Berkoff, 1990). In Nigeria, the instrument has also been used by Oluwole, Adetunji, and Mbang (2008).

3.4.5 Job Satisfaction Scale. (JSS)

Job Satisfaction scale was developed by Warr, Cook and Wall in 1979. The scale was adopted to measure job satisfaction. It consists of 15 items where respondent were asked to rank on 1 to 7 scale as to their satisfaction using a 7-point scale that ranges from 1= Extremely Dissatisfied to 7= Extremely Satisfied. The survey is divided into two, 7 intrinsic and 8 extrinsic job satisfaction item. The internal consistency measured by Cronbach alpha for job satisfaction scale is 0.86- 0.87. Though scoring should be kept continuous (sum score across item).Thus the range of possible job satisfaction was 15-105 (all items), for intrinsic job satisfaction 7-49 (all seven even numbered (items) for the extrinsic job satisfaction 8-56 (all eight odd numbered items. Furthermore, the scale shows discriminant validity measures both Intrinsic and Extrinsic characteristic of the job. (Wang, 2006, Stride, Wall, & Catley, 2007, Perminas, Vaitkevicius and Astraukaite, 2010). The instrument has also been used in Nigeria by Kolo (2017).

3.4.6 Satisfaction with Life Scale (SWLS).

The Satisfaction with Life Scale (SWLS) is a 5-item scale designed to measure global cognitive judgments of one’s life satisfaction (not a measure of either positive or negative affect). This is used in this study to ascertain the extent to which the participants perceive or assess their well- being. Participants were asked to indicate how much they agree or disagree with each of the 5 items using 7-point scales that range from 7 strongly agreed to 1 strongly disagreed. Though scoring should be kept continuous (sum up scores on each item), here are some cut-offs to be used as benchmarks: 31 – 35 Extremely satisfied; 26 – 30 Satisfied; 21 – 25 Slightly satisfied; 20 Neutral; 15 – 19 Slightly dissatisfied; 10 – 14 Dissatisfied; and 5 – 9 Extremely dissatisfied. Higher scores indicate more positive perceptions of respondents’ satisfaction with their lives. The internal consistency of scale is .87. SWLS showed sufficient sensitivity to be potentially valuable to detect change in life satisfaction during the course of clinical intervention. Furthermore, the scale shows discriminant validity from emotional well-being measures (Pavot, et al., 1993, Ezeokoli & Ayodele, 2013).

3.5 Procedure for Data Collection.

The researcher with the help of two trained research assistants visited the selected polytechnics to administer the instruments. Necessary permission was requested from the authorities of the polytechnics after which the researcher visited the selected non- academic staff in their offices to distribute the instruments. Knowing fully well that non -academic staff of polytechnics have tight job schedules, the researcher appealed to the participants to spare part of their time in order to ensure the success of the study. Hence, once their consent was obtained, the instruments were left for them and were retrieved within five working days.

3.6 Method of Data Analysis

The demographic data of participants were analyzed by means of descriptive statistical techniques of frequency distribution and percentages. Independent T-test statistics and analysis of variance (ANOVA) was used. Also, Pearson Product Moment Correlation was used to determine the relationships among the study variables. Since there are several factors for both the dependent and the independent variables, canonical correlation analysis was used for analyses. Canonical Correlation Analysis (CCA) is a multivariate statistical approach which generates multiple regression, factor analysis, and multivariate analysis of variance. It has been barely utilised until much recently when advancement in computer programming permitted its usage. Canonical correlation analysis, use both continuous and discrete variables, creates a composite of the dependent variable set and a composite of the independent variable set. The two composites are then correlated producing a coefficient, the canonical correlation, that when squared represents the amount of variance explained by the two variate. Among the interpretable statistics are the canonical correlation, canonical variates, canonical loading (also called canonical structure correlations), the canonical correlation (Rc), R2c, and Redundancy Index.

The canonical loadings are more interpretable data than the canonical coefficients. These are the correlations between a variable in a set and its own canonical variate. They reflect the loading on a factor. According to the guiding principle presented by Hair, Anderson, Tatham, and Black (1998), loadings equal to .30 to .39 are viewed as significant, .40 to 4.9 as more important, and .50 and above as very significant. The redundancy index is the amount of variance that one set of variables (either the independent or dependent set) that is explained by the other set. Because one set of variables is considered as dependent and the other set as independent, this study sought after knowing how much variation in the dependent set that is explained by the independent variable set and vice versa. All tests were carried out at the .05 level of significance, and all analyses were executed by means of the IBM SPSS Version 23 software.

CHAPTER FOUR

RESULTS AND DISCUSSION

This chapter presents the results of data analysis. The data collected for this study were subjected to descripitive and inferential statistical analysis using the Statistical Packages for Social Sciences, version 23. The first section of the report present the demograghic data of the respondents for the study followed by the descriptive analysis of the variables of the study while the second section deals with testing of the formulated null hypotheses considered at .05 level of significance. The results are presented in order of research hypotheses formulated. Each is followed with the interpretations of the results. A summary of the major findings of the study is presented to conclude the chapter.

4.1 Demographic Data of the Respondents

Table 4.1:

Gender distribution of the respondents

Sex Frequency Percentage (%)
Male 728 58.1
Female 524 41.9
Total 1252 100.0

As shown in table 4.1, 728 of the respondents representing 58.1% of the sample were male, and about 524 of the respondents representing 41.9% were female. This is further illustrated in figure below.

Figure 4.1: Gender Distribution Chart of the Respondents

Figure 4.1 depicts the distribution of the respondents by gender. Male respondents were more than the female respondents.

Table 4.2:

Respondents’Cadre distribution

Cadre Frequency Percentage (%)
Junior 388 31.0
Senior 695 55.5
Management 169 13.5
Total 1,252 100.0

Table 4.2 also presents the variuous cadre held by the respondents who participated in the study. The results revealed that respondents on senior cadre were the majority with 695 representing 55.5%; Followed by respondents on the status of junior cadre represented by 388 which is 31.0% while 169 respondents representing 13.5% were on the status of management cadre. This is further illustrated in the figure below

Figure 4.2: Cadre Distribution Chart Of The Respondents

Table 4.3:

Ownership of Institution Distribution

Institution Type Frequency Percentage (%)
Private 536 42.8
Public 716 57.2
Total 1,252 100.0

The results in Table 4.3 revealed that respondents from the private polytechnics were 536 (42.8%) while those from the public were 716 (57.2%). This implied that majority of the respondents were from public polytechnics. This is further illustrated in the figure below.

Figure 4.3: Institution Type Distribution Chart of the Respondents

4.2 General Description of Data

One thousand, two hundred and fifty two (1252) non-academic staff of Nigeria polytechnics participated in this study. The descriptive statistics for job demands, work-family conflict, social support, job satisfaction and well-being of non-academic staff of Nigerian polytechnics were presented in Table 4.4

Table 4.4:

Descriptive Statistics of the Variables of the Study

N Mean Std. Dev.
Job Demands 1252 17.3323 5.29677
Work-Family Conflict 1252 40.3858 17.84745
Social Support 1252 57.2236 10.06928
Job Satisfaction 1252 76.8778 14.18476
Well-being 1252 26.5990 6.59728

The result in Table 4.4 revealed the mean and standard deviation job demand, work-family conflict, social support, job satisfaction and well-being of non-academic staff of Nigerian polytechnics. For job demand (Mean = 17.332; SD = 5.297); for work-family conflict (Mean = 40.386; SD = 17.847); for social support (Mean = 57.224; SD = 10.069); for job satisfaction (Mean = 76.878; SD = 14.185); and for well-being (Mean = 26.599; SD = 6.597).

4.3 Research Questions

Research Question OneWhat is the level of job demand of non-academic staff of Nigerian polytechnics?

Table 4.5:

Descriptive Statistics of Workers’ Job Demand

Job Demands Statistic Std. Error
Mean 17.3323 .14970
95% Confidence Interval for Mean Lower Bound 17.0386
Upper Bound 17.6260
5% Trimmed Mean 17.2652
Median 17.0000
Variance 28.056
Std. Deviation 5.29677
Minimum 8.00
Maximum 28.00
Range 20.00
Interquartile Range 10.00
Skewness .083 .069
Kurtosis 1.170 .138

The result in Table 4.5 revealed scores for job demand of non-academic staff of Nigerian polytechnics. Mean (17.332); median (17.000); variance (28.056); standard deviation (5.297); minimum score (8.00); maximum score (28.00); range (20.00); interquartile range (10.00); skewness (-.083); and kurtosis (-1.170) were revealed. The results are graphically presented in Figures 1 and 2 below.

Figure 4:4 Histogram Showing the Nature of Job Demand

The chart in Figure 4.4 indicated that the level of job deamnd of non-academic staff was negatively skewed with non-academic staff having high score of job demand.

Figure 4:5 Box Plot Showing the Nature of Job Demand

The boxplot in Figure 4.5 showed no outliers. This implies that no participant has scores on job demand which is extremely far from the general distribution.

Research Question Two: What is the level of work-family conflict of non-academic staff of Nigerian polytechnics?

Table 4.6:

Descriptive Statistics of Work-Family Conflict

Work-Family Conflict Statistic Std. Error
Mean 40.3858 .50440
95% Confidence Interval for Mean Lower Bound 39.3962
Upper Bound 41.3753
5% Trimmed Mean 39.5790
Median 45.0000
Variance 318.531
Std. Deviation 17.84745
Minimum 18.00
Maximum 81.00
Range 63.00
Interquartile Range 36.00
Skewness .132 .069
Kurtosis -.974 .138

The result in Table 4.6 revealed scores for work-family conflict of non- academic staff of Nigerian polytechnics. Mean (40.386); median (45.000); variance (318.531); standard deviation (17.847); minimum score (18.00); maximum score (81.00); range (63.00); interquartile range (36.00); skewness (.132) and kurtosis (-.974) were revealed. The results are graphically presented in Figures4:4 and 4: 5 below.

Figure 4:6 Histogram Showing the Nature of Work-Family Conflict

The chart in Figure 4.6 indicated that the level of work-family conflict of non-academic staff was positively skewed with non-academic staff having low score of work-family conflict.

Figure 4:7 Box Plot Showing the Nature of Work-Family Conflict

The boxplot in Figure 4.7 showed no outliers. This implies that no participant has scores on work-family conflict which is extremely far from the general distribution.

Research Question Three: What is the level of social support of non-academic staff of Nigerian polytechnics?

Table 4.7:

Descriptive Statistics of Workers’ Social Support

Social Support Statistic Std. Error
Mean 57.2236 .28457
95% Confidence Interval for Mean Lower Bound 56.6653
Upper Bound 57.7819
5% Trimmed Mean 57.8784
Median 57.0000
Variance 101.390
Std. Deviation 10.06928
Minimum 24.00
Maximum 79.00
Range 55.00
Interquartile Range 17.00
Skewness -.736 .069
Kurtosis .227 .138

The result in Table 4.7 revealed scores for social support of non-academic staff of Nigerian polytechnics. Mean (57.224); median (57.000); variance (101.390); standard deviation (10.069); minimum score (24.00); maximum score (79.00); range (55.00); interquartile range (17.00); skewness (-.736); and kurtosis (.227) were revealed. The results are graphically presented in Figures 5 and 6 below.

Figure 4:8 Histogram Showing the Nature of Social Support

The chart in Figure 4.8 indicated that the level of social support of non-academic staff was negatively skewed with non-academic staff having high score of job demands.

Figure 4:9 Box Plot Showing the Nature of Social Support

The boxplot in Figure 4.9 showed some outliers. The outliers were on the lower side of the distribution of scores on social support indicating that some non-academic staff has extremely low social support.

Research Question Four: What is the level of job satisfaction of non-academic staff of Nigerian polytechnics?

Table 4: 8

Descriptive Statistics of Workers’ Job Satisfaction

Job Satisfaction Statistic Std. Error
Mean 76.8778 .40088
95% Confidence Interval for Mean Lower Bound 76.0913
Upper Bound 77.6643
5% Trimmed Mean 77.8802
Median 79.0000
Variance 201.207
Std. Deviation 14.18476
Minimum 28.00
Maximum 98.00
Range 70.00
Interquartile Range 23.00
Skewness -.780 .069
Kurtosis .035 .138

The result in Table 4.8 showed scores for job satisfaction of non-academic staff of Nigerian polytechnics. Mean (76.878); median (79.000); variance (201.207); standard deviation (14.185); minimum score (28.00); maximum score (98.00); range (70.00); interquartile range (23.00); skewness (-.780); and kurtosis (.035) were revealed. The results are graphically presented in Figures 8 and 9.

Figure 4:10 Histogram Showing the Nature of Job Satisfaction

The chart in Figure 4.10 indicated that the level of job satisfaction of non-academic staff was negatively skewed with non-academic staff having high score of job satisfaction.

Figure 4:11 Box Plot Showing the Nature of Job Satisfaction

The boxplot in Figure 4.11 showed some outliers. The outliers were on the lower side of the distribution of scores on job satisfaction indicating that some non-academic staff having extremely low job satisfaction.

Research Question Five: What is the level of well-being of non-academic staff of Nigerian polytechnics?

Table 4:9

Descriptive Statistics of Workers’ Well-Being

Well-being Statistic Std. Error
Mean 26.5990 .18645
95% Confidence Interval for Mean Lower Bound 26.2333
Upper Bound 26.9648
5% Trimmed Mean 26.8472
Median 26.0000
Variance 43.524
Std. Deviation 6.59728
Minimum 7.00
Maximum 35.00
Range 28.00
Interquartile Range 14.00
Skewness -.146 .069
Kurtosis -1.038 .138

The result in Table 4.9 showed scores for well-being of non-academic staff of Nigerian polytechnics. Mean (26.599); median (26.000); variance (43.524); standard deviation (6.597); minimum score (7.00); maximum score (35.00); range (28.00); interquartile range (14.00); skewness (-.146); and kurtosis (-1.038) were revealed. The results are graphically presented in Figures 4: 9 and 4:10.

Figure 4:12: Histogram Showing the Nature of Well-Being

The chart in Figure 4.12 indicated that the level of well-being of non-academic staff was negatively skewed with non-academic staff having high score of well-being.

Figure 4:13 Box Plot Showing the Nature of Well-Being

The boxplot in Figure 4.13 showed no outliers. This implies that no participant has scores on well-being which is extremely far from the general distribution.

Research Question Six: What is the relationship among job demand, work-family conflict, social-support, job satisfaction and well-being of Nigerian polytechnics non- academic staff?

Table 4.10

Correlation Matrix of the Relationship among Job Demand, Work-Family Conflict, Social-Supports, Job Satisfaction and Well-Being of Nigerian Polytechnics Non- Academic Staff

Job Demands Work-Family Conflict Social Support Job Satisfaction Well-being
Job Demands 1 .652** -.323** -.426** -.406**
Work-Family Conflict .652** 1 -.399** -.536** -.554**
Social Support -.323** -.399** 1 .599** .590**
Job Satisfaction -.426** -.536** .599** 1 .687**
Well-being -.406** -.554** .590** .687** 1

**. Correlation is significant at the 0.01 level (2-tailed).

The results in Table 4.10 revealed that there are significant and positive relationships between job demands and work-family conflict (r = .652; p <.05); social support and job satisfaction (r = .599; p <.05); social support and well-being (r = .590; p <.05); j ob satisfaction and well-being (r = .687; p <.05). However, there are significant but negative relationships between job demands and social support (r = -.323; p <.05); job demands and job satisfaction (r = -.426; p <.05); job demands and well-being (r = -.406; p <.05); work- family conflict and social support (r = -.399; p <.05); work-family conflict and job satisfaction (r = -.536; p <.05); work-family conflict and well-being (r = -.554; p <.05).

Research Question Seven: Would there be any significant differences in the job demand of Nigerian Polytechnic non- academic staff?

Table 4.11:

Independent T-Test Statistics and Analysis Of Variance (Anova) Of Differences among the Job Demand of non- academic staff of Nigerian polytechnics

Job demand Group N Mean Std. Deviation Statistics
Gender Male 728 17.2335 5.23903 t =-.777; df = 1250; p>.05
Female 524 17.4695 5.37797
Ownership of Institution Private 536 17.3694 5.20978 t = .215; df = 1250; p>.05
Public 716 17.3045 5.36443
Cadre Senior 388 17.1160 5.31241 F (2,1249) = 3.415; p< .05
Middle 695 17.6446 5.30934
Junior 169 16.5444 5.13039

The results in Table 4.11 revealed differences in job demand of non-academic staff of Nigerian polytechnics. No significant difference existed in the job demand of male and female non-academic staff of Nigerian polytechnics (t =-.777; df = 1250; p > .05). Also, no significant difference in the job demand of non-teaching staff in private and public Nigerian polytechnics (t =.215; df = 1250; p > .05). There was a significant cadre difference in the job demand of non-academic staff of Nigerian polytechnics (F (2,1249) = 3.415; p < .05) with middle staff having highest job demand, followed by senior staff while junior staff had lowest job demand.

Research Question Eight: Would there be any significant differences in the work-family conflict of Nigerian Polytechnic non- academic staff?

Table 4.12:

Independent T-Test Statistics and Analysis Of Variance (Anova) Of Differences among the Work-Family Conflict of non-academic staff of Nigerian polytechnics

Work-Family Conflict Group N Mean Std. Deviation Statistics
Gender Male 728 40.0838 17.71787 t = -.706; df = 1250; p>.05
Female 524 40.8053 18.03450
Ownership of Institution Private 536 37.2836 16.03658 t = -5.380; df = 1250; p<.05
Public 716 42.7081 18.76897
Cadre Senior 388 39.5567 16.66324 F (2,1249) = 4.212; p< .05
Middle 695 41.5597 18.67272
Junior 169 37.4615 16.61540

The results in Table 4.12 revealed differences in work-family conflict of non-academic staff of Nigerian polytechnics. No significant difference existed in the work-family conflict of male and female non-academic staff of Nigerian polytechnics (t =-.706; df = 1250; p > .05). A significant difference existed in the work-family conflict of non- academic staff in private and public Nigerian polytechnics (t =-5.380; df = 1250; p < .05) with public polytechnics’ non-academic staff having higher work-family conflict than their counterpart in private polytechnics in Nigeria. There was a significant cadre difference in the work-family conflict of non-academic staff of Nigerian polytechnics (F (2,1249) = 4.212; p < .05) with middle staff having highest work-family conflict, followed by senior staff while junior staff had lowest work-family conflict.

Research Question Nine: Would there be any significant differences in the social support of Nigerian Polytechnic non-academic staff?

Table 4.13:

Independent T-Test Statistics and Analysis Of Variance (Anova) Of Differences Among The social support of non-academic staff of Nigerian polytechnics

Social Support Group N Mean Std. Deviation Statistics
Gender Male 728 57.5714 9.61703 t = 1.441; df = 1250; p>.05
Female 524 56.7405 10.65635
Ownership of Institution Private 536 58.8601 8.29261 t = 5.023; df = 1250; p<.05
Public 716 55.9986 11.06491
Cadre Senior 388 57.3144 10.15686 F (2,1249) = 1.291; p> .05
Middle 695 57.4518 10.09852
Junior 169 56.0769 9.72234

The results in Table 4.13 revealed differences in social support of non-academic staff of Nigerian polytechnics. No significant difference existed in the social support of male and female non-academic staff of Nigerian polytechnics (t =1.441; df = 1250; p > .05). A significant difference existed in the social support of non-academic staff in private and public Nigerian polytechnics (t = 5.023; df = 1250; p < .05) with private polytechnics’ non-academic staff having higher work-family conflict than their counterpart in public polytechnics in Nigeria. There was no significant cadre difference in the social support of non-academic staff of Nigerian polytechnics (F (2,1249) = 1.291; p > .05).

Research Question Ten: Would there be any significant differences in the job satisfaction of Nigerian Polytechnic non- academic staff?

Table 4.14:

Independent T-Test Statistics and Analysis Of Variance (Anova) Of Differences among the Job Satisfaction of non-academic staff of Nigerian polytechnics

Job Satisfaction Group N Mean Std. Deviation Statistics
Gender Male 728 77.7692 13.27682 t = 2.627; df = 1250; p<.05
Female 524 75.6393 15.28423
Ownership of Institution Private 536 77.9757 11.85652 t = 2.374; df = 1250; p<.05
Public 716 76.0559 15.66126
Cadre Senior 388 76.6314 14.61445 F (2,1249) = .085; p > .05
Middle 695 76.9827 14.00112
Junior 169 77.0118 14.00977

The results in Table 4.14 revealed differences in job satisfaction of non-academic staff of Nigerian polytechnics. Significant difference existed in the job satisfaction of male and female non-academic staff of Nigerian polytechnics (t = 2.627; df = 1250; p < .05) with male staff having higher job satisfaction than the female non-academic staff. Also, a significant difference existed in the job satisfaction of non-academic staff in private and public Nigerian polytechnics (t = 2.374; df = 1250; p < .05) with private polytechnics’ non-academic staff having higher work-family conflict than their counterpart in public polytechnics in Nigeria. There was no significant cadre difference in the job satisfaction of non-academic staff of Nigerian polytechnics (F (2,1249) = .085; p > .05).

Research Question Eleven: Would there be any significant differences in the well-being of Nigerian Polytechnic non- academic staff?

Table 4.15:

Independent T-Test Statistics and Analysis Of Variance (Anova) Of Differences among the Well-Being of non-teaching staff of Nigerian polytechnics

Well-being Group N Mean Std. Deviation Statistics
Gender Male 728 26.8283 6.61389 t = 1.450; df = 1250; p >.05
Female 524 26.2805 6.56716
Ownership of Institution Private 536 27.0093 6.59353 t = 1.906; df = 1250; p>.05
Public 716 26.2919 6.58797
Cadre Senior 388 26.9149 6.62783 F (2,1249) = .845; p > .05
Middle 695 26.3871 6.66369
Junior 169 26.7456 6.24788

The results in Table 4.15 revealed differences in well-being of non-academic staff of Nigerian polytechnics. No significant difference existed in the well-being of male and female non-academic staff of Nigerian polytechnics (t =1.450; df = 1250; p > .05). Also, no significant difference in the well-being of non-academic staff in private and public Nigerian polytechnics (t =1.960; df = 1250; p > .05). There was no significant cadre difference in the well-being of non-academic staff of Nigerian polytechnics (F (2,1249) = .845; p > .05).

4.3 Test of Hypotheses and Discussion

Hypothesis One

Job demands, work-family conflict and social-supports will not significantly correlate with job satisfaction and well-being among Nigerian polytechnics non-academic staff. The Canonical Correlation Analysis was performed to test this hypothesis. Results are as provided in Table 4.16

Table 4.16:

Canonical Correlation, significance, coefficients, and canonical variate loadings

Function 1 Function 2
Canonical Correlation .745 .061
SquareCanonical Correlation .554 .003
Wilks .444 .996
F – Ratio 208.142 2.260
Df 6.002 2.001
Sig .000 .105
SCC CAL SCC CAL
Dependent variables
Job Satisfaction .542 .918 1.265 – .397
Wellbeing .547 .919 1.263 .393
Independent variables
JobDemand -.083 – .608 1.126 .436
Work Family -.482 -.797 -1.226 -.357
Social support .650 .869 -.334 -.209

Among the interpretable statistics are the canonical correlation, canonical variates, canonical loading (also called canonical structure correlations), the canonical correlation (Rc), R2c, and Redundancy Index.

The results of the canonical correlation analysis in Table 4.16 indicated that there are two dependent variables and three independent variables. Two factors were composed but only one factor was interpretable. The canonical correlation for Factor 1 was statistically significant (Rc = .745, F = 208.142; p <.05). Factor 2 was not significant and thus not interpreted. The relatively most important variables based on the standard canonical coefficients are for the first factor, job satisfaction (.542) and wellbeing (.547) in the case of dependent variables and work family conflict (-.482), and social support (.650) for independent variables.

The canonical loadings are more interpretable data than the canonical coefficients. These are the correlations between a variable in a set and its own canonical variate. They reflect the loading on a factor. According to the guiding principle presented by Hair, Anderson, Tatham, and Black (1998), loadings equal to .30 to .39 are viewed as significant, .40 to 4.9 as more important, and .50 and above as very significant. The two dependent variables vis-à-vis job satisfaction (.918) and well- being (.919) are very significant. Among the three independent variables, job demands (-.608), work family conflict (-.797) and social support (.869) are very important. These findings mean that job satisfaction and well-being are related with job demands, work family conflict and social support.

The redundancy index is the amount of variance that one set of variables (either the independent or dependent set) that is explained by the other set. Because one set of variables is considered as dependent and the other set as independent, this study sought to know how much variation in the dependent set that is explained by the independent variable set and vice versa. The results of the redundancy analysis are presented in Table 4.17

Table 4.17:

Redundancy Analysis of Dependent and Independent Variates for the Canonical Functions

Standardized Variance of the Dependent Variables Explained by
Their Own Canonical Variate (Shared Variance) The Opposite Canonical

Variate (Redundancy)

CanonicalFunction Percentage Cumulative Percentage Canonical R2 Percentage Cumulative Percentage
1 84.352 84.352 55.44 46.764 46.764
2 15.648 100.000 . 36 . 057 46.820
Standardized Variance of the Independent Variables Explained by
Their Own Canonical Variate (Shared Variance) The Opposite Canonical

Variate (Redundancy)

CanonicalFunction Percentage Cumulative Percentage Canonical R2 Percentage Cumulative Percentage
1 58.680 58.680 55.44 32.531 32.531
2 12.071 70.750 .36 .044 32.575

The results of the redundancy analysis in Table 4.17 indicated that with job satisfaction and wellbeing set as the dependent variables, a redundancy index of .468 was revealed, indicating that about 46.8% of the total variance in job satisfaction and wellbeing is accounted for by job demand, work family conflict and social support. Job demand, work family conflict and social support set as dependent variables revealed a redundancy index of .325 thereby predicting 32.5% of the variance in job satisfaction and wellbeing. The findings of the first hypothesis revealed that there was a composite contribution of job demands, work-family conflict, social-support to the prediction of job satisfaction and well-being among Nigerian polytechnics non-academic staff. This implies that job demand, work family conflict and inadequate social support have a greater effect on job satisfaction and well -being of non- academic staff of polytechnics in Nigeria. This finding lends credence to (Popoola, 2008; Akinjide, 2006; Collins, and George, 2004; Akinboye, 2003) that found out there is a relationship between work-family role conflict and organisational efficiency. Their studies found out that a significant relationship exists between work-family role conflict and managerial efficiency of managers.

Furthermore, Poele (2003) reported that efficiency in managing organisational resources for results could be better guaranteed when various variables other than one, such as leadership style, job demand, self-efficient, personality, work-family role conflict, job satisfaction and motivation are jointly combined by the managers in work organisations. The finding of the study is very unique in the sense that it establishes the relevance of work-family conflict as an important factor in the consideration of effective management of organizational resources for results. Also Tsaur, Liang & Hsu (2012) affirmed that when an individual spends more time and effort in his family role, it will definitely reduce the time and effort he invests in his work. They assert that some work arrangements, such as shift work, overtime, and working on holiday can reduce or deprive employees from enjoying holiday with families and friends together, such employees may feel dissatisfied with work because aspects of their work factor make it impossible for them to fulfill their family demand. Norway (2013) also confirmed that the effect of job demand is not only destructive to individual employee but also for the organization.

Hypothesis Two

There is no significant composite contribution of job demand, work-family conflict and social support to the prediction of job satisfaction among Nigerian polytechnics non- academic staff.

Table 4.18:

Model Summary of the Multiple Regression Analysis for the Combined Contributions of Job Demand, Work-Family Conflict and Social-Support to the Prediction of Job Satisfaction among Nigerian Polytechnics Non- Academic Staff

Sum of Squares Df Mean Square F Sig.
Regression 117659.029 3 39219.676 365.130 .000b
Residual 134051.274 1248 107.413
Total 251710.303 1251
Model Summary R = .684a; R2 = .467; R2(adj) = .466

a. Dependent Variable: Job Satisfaction

b. Predictors: (Constant), Social Support, Job Demand, Work-Family Conflict

The results in Table 4.18 indicated that with all the predictor variables (job demand, work-family conflict and social support) entered into the regression model at once, there was a significant prediction of job satisfaction of non-academic staff of Nigerian polytechnics (R = .684; R2 = .467; Adj R2 = .466; F (3,1248) = 365.130; p < .05). This showed that all the variables accounted for 46.6% of the variance in job satisfaction of non-academic staff of Nigerian polytechnics.

A stepwise multiple regression analysis was also performed to determine the complementary contributions of the independent variables to the prediction of job satisfaction of non-academic staff of Nigerian polytechnics. Results are as presented in Table 4.19.

Table 4.19:

Model Summary of the Stepwise Multiple Regression Analysis for the Combined Contributions of Job Demand, Work-Family Conflict and Social-Support to the Prediction Of Job Satisfaction among Nigerian Polytechnics Non- Academic Staff

Model R R Square Adjusted R Square Std. Error of the Estimate Change Statistics
R Square Change F Change df1 df2 Sig. F Change
1 .599a .359 .358 11.36259 .359 699.605 1 1250 .000
2 .681b .463 .463 10.39911 .105 243.354 1 1249 .000
3 .684c .467 .466 10.36402 .004 9.473 1 1248 .002

a. Predictors: (Constant), Social Support

b. Predictors: (Constant), Social Support, Work-Family Conflict

c. Predictors: (Constant), Social Support, Work-Family Conflict, Job Demand

The results in Table 4.19 indicated that when social support was entered into the regression model as the firnst predictor variable based on the strength of its relationship with job satisfaction, there was a significant contribution to the prediction of job satisfaction of non-academic staff of Nigerian polytechnics (R = .599; R2 = .359; Adj R2 = .358; F (1,1250) = 699.605; p < .05). By this, social support alone accounted for 35.8 percent of the variance in job satisfaction of staff. When work-family conflict was introduced into the regression model as the second predictor variable, together with social support, it revealed a significant effect on job satisfaction of staff (R = .681; R2 = .463; Adj R2 = .463; F (1,1249) = 243.354; p < .05). This revealed that social support and work-family conflict together predicted 46.3 percent of the job satisfaction of staff. In effect, work-family conflict was able to add about 10.5 percent to the prediction of job satisfaction of non-academic staff of Nigerian polytechnics.

When job demands was introduced into the regression model as the third predictor variable, together with social support and work-family conflict, it revealed a significant effect on job satisfaction of staff (R = .684; R2 = .467; Adj R2 = .466; F (1,1248) = 9.473; p < .05). This revealed that social support, work-family conflict and job demand together predicted 46.6 percent of the job satisfaction of staff. In effect, job demand was able to add about 0.3 percent to the prediction of job satisfaction of non- academic staff of Nigerian polytechnics.

The null hypothesis, which stated that there is no significant composite contribution of job demands, work-family conflict and social-support to the prediction of job satisfaction among Nigerian polytechnics non- academic staff, was rejected by this finding. This implies that there was a significant combined contribution of job demands, work-family conflict and social-supports to the prediction of job satisfaction among Nigerian polytechnics non- academic staff. In the order of the strength of contribution, social support alone account for 35.8 percent of the variance. Therefore, social support was the most potent predictor of job satisfaction followed by work-family conflict while job demand was the least predictor among the three variables.

This finding implies that to improve job satisfaction of non-academic staff of polytechnics premium attention must be placed in ensuring social support followed by introduction of workers friendly programmes and policies to reduce work-family conflict and job demand of non-academic staff of polytechnic. This findings support Thomas & Ganster’s (1995) conclusion that social support not only has indirect and intervening relationship with job demands and work-conflict. Another possible way in which the availability of social support may influence the level of work-family conflict experienced is through direct effect whereby the presence of social support is associated with reducing the negative consequences of work-family conflict. Social support as a very important source in both work and family life, can reduce the negative effects of job and family stressors. Generous, Parasurama, and Greenhaus (1992) argue that social support, as an adjustment source, can play a significant role in the face job and family stressors. First, social support can directly affect pressure and

other negative consequences of these stressors in different spheres of life and reduce pressure level experienced. Also, social support can moderate the effects of stressors on ‘individual’ health profiles and welfare in both family and career life.

Hypothesis Three

There is no significant relative contribution of job demand, work-family conflict and social-support to the prediction of job satisfaction among Nigerian polytechnics non- academic staff.

Table 4.20

Beta Coefficients and t Ratio for Relative Contributions of Job Demand, Work-Family Conflict and Social-Support to the Prediction of Job Satisfaction among Nigerian Polytechnics Non- Academic Staff.

Unstandardized Coefficients Standardized Coefficients T Sig.
B Std. Error Beta
(Constant) 54.005 2.398 22.523 .000
Job Demand -.225 .073 -.084 -3.078 .002
Work-Family Conflict -.239 .022 -.300 -10.642 .000
Social Support .636 .032 .452 19.968 .000

a. Dependent Variable: Job Satisfaction

The results in Table 4.20 revealed that social support (β = .452; t = 19.968; p < .05) was the most potent of the three predictor variables in predicting job satisfaction of non-academic staff of Nigerian polytechnics. This is followed by work-family conflict (β = -.300; t = -10.642; p < .05) and then job demands (β = -.084; t = -3.078; p < .05).

The null hypothesis, which stated that there is no significant relative contribution of job demand, work-family conflict and social-support to the prediction of job satisfaction among Nigerian polytechnics non- academic staff, was rejected by the findings of this study. This implies that there was a significant relative contribution of job demand, work-family conflict and social-support to the prediction of job satisfaction among Nigerian polytechnics non-academic staff. In the order of the strength of contribution, social support is the most potent of the three predictor variables followed by work-family conflict while job demand was the least predictor among the three variables. This finding implies that to improve job satisfaction of non-academic staff of polytechnics premium attention must be placed on social support from people around such as family, friends, co-workers and the supervisors. Social support from supervisors, as it relates to meeting work role obligations and thus managing work-family conflict, is described as the assistance employees receive from supervisors to manage work and family role obligations (Anderson, Coffey & Byerly, 2002; Thompson & Prottas, 2005).

The availability of social support from supervisors and coworkers is likely to reduce perceived job demands, as employees are more likely to meet the work role and family role expectations with the social support received and increases workers job satisfaction. Moreover, Luthans (2011) assert that increasing job satisfaction of employees can reduce occupational stress. Thus employers should rather be interested in how they can improve job satisfaction among their employees. For instance, having fair salaries and wages, benefits and offering promotion opportunities have proved to be important factors enhancing job satisfaction (Luthan 2011).

Hypothesis Four

There is no significant gender difference in the composite contribution of job demand, work-family conflict and social support to the prediction of job satisfaction of Nigerian polytechnics non- academic staff.

Table 4.21:

Model Summary, Analysis Of Variance And Test Of Significant Sex Differences In The Composite Contribution Of Job Demand, Work-Family Conflict And Social Support To The Prediction Of Job Satisfaction of Nigerian Polytechnics Non- Academic Staff.

Sex Source of Variation Sum of Squares Df Mean Square F Sig.
Male Regression 57848.309 3 19282.770 198.580 .000b
Residual 70302.922 724 97.103
Total 128151.231 727
Model Summary R = .672a; R2 = .451; R2(adj) = .449;

Std. Error of the Estimate = 9.85411

Female Regression 59333.632 3 19777.877 163.653 .000b
Residual 62843.198 520 120.852
Total 122176.830 523
Model Summary R =.697a; R2 = .486; R2(adj) = .483;

Std. Error of the Estimate = 10.99328

Test of Significant Difference t-value = 0.002; df = 1,248; p = 0.988

a. Dependent Variable: Job Satisfaction

b. Predictors: (Constant), Social Support, Job Demands, Work-Family Conflict

The results in Table 4.21 indicated that with all the predictor variables (job demand, work-family conflict and social supports) entered into the regression model for male participants at once, there was a significant prediction of job satisfaction (R = .672; R2 = .451; R2(adj) = .449; F (3,724) = 198.580; <.05). This showed that all the variables accounted for 44.9% of the variance in the job satisfaction of male participants.

The results also indicated that with all the predictor variables (job demand, work-family conflict and social support) entered into the regression model for female participants at once, there was a significant prediction of job satisfaction (R = 697a; R2 = .486; R2(adj) = .483; F (3,520) = 163.653; <.05). This showed that all the variables accounted for 48.6% of the variance in the job satisfaction of female participants.

A test of significant difference in the coefficients of the prediction of job satisfaction between male and female participants revealed that there was no significant difference between the two groups (t-value = 0.002; df = 1,248; p = 0.988). The null hypothesis which stated that there is no significant gender difference in the composite contribution of job demand, work-family conflict and social supports to the prediction of job satisfaction of Nigerian polytechnic non- academic staff, was accepted by this finding. This implies that the composite contribution of job demand, work-family conflict and social support to the prediction of job satisfaction will be similar for male and female non-academic staff of Nigerian polytechnics. This finding implies that job demand work-family conflict and social support are not gender sensitive, which corroborates Osagbemi findings (2003) that there is no significant difference between men and women in terms of pay, fringe benefits and nature of job. To corroborate this, a general population study of professional employees in Canada by (McElwain, Korabik, & Rosin, 2005) found that whilst there were no gender differences in family-work conflict, women experienced higher levels of work-family conflict. Some of the studies examining gender and work-family conflict used general population samples.

However, due to the gendered structure of the labour market, gender comparisons within general population samples are problematic as they do not tend to compare with findings (Lundberg, 1996; Emslie et al., 2004; Winslow, 2005; Emslie & Hunt, 2009). Whilst women and men experience similar levels of conflict findings has shown that women experienced the greatest increase of conflict over time. Furthermore, gender stratification of the labour market may have an impact. This finding also corroborates the study carried out by a French-Canadian on sample of physical therapists and psychologists (Senecal, Vallerand, and Guay (2001) who found that there are no differences between male and female in their levels of work family conflict. Furthermore, Ansari’s study (2011) indicates no significant gender difference with regard to work-family interference and family-to-work interference.

Hypothesis Five

There is no significant gender difference in the relative contribution of job demand, work family conflict and social support to the prediction of job satisfaction of Nigerian polytechnics non- academic staff.

Table 4.22:

Model Summary, Analysis of Variance and Test of Significant Sex Differences in the Relative Contribution of Job Demand, Work-Family Conflict and Social Support to the Prediction of Job Satisfaction of Nigerian polytechnics Non- Academic Staff.

Sex Model Unstandardized Coefficients Standardized Coefficients t Sig
B Std. Error Beta
Male (Constant) 55.146 3.083 17.887 .000
Job Demands -.199 .095 -.078 -2.100 .036
Work-Family Conflict -.227 .029 -.303 -7.945 .000
Social Support .611 .041 .442 14.764 .000
Female (Constant) 53.325 3.795 14.053 .000
Job Demands -.263 .115 -.092 -2.284 .023
Work-Family Conflict -.255 .036 -.300 -7.114 .000
Social Support .657 .050 .458 13.185 .000
Test of Differences in Coefficients Between Male and Female Participants
(Constant) .372 .710
Job Demands .429 .66
Work-Family Conflict .606 .545
Social Support .711 .477

a. Dependent Variable: Job Satisfaction

Results in Table 4.22 revealed that for male participants, all the predictor variables (job demand, work family conflict and social support) were potent in the prediction of job satisfaction: Social support (coeff = .661; t = 14.764; p <.05), work family conflict (coeff = -.227; t = -7.945; p <.05) and job demand (coeff = -.199; t = -2.100; p <.05).

In the same direction, results showed that for female participants, all the predictor variables (job demand, work family conflict and social support) were potent in the prediction of job satisfaction: Social support (coeff = .657; t = 13.185; p <.05), work family conflict (coeff = -.255; t = -7.114; p <.05) and job demand (coeff = -.263; t = -2.284; p <.05).

The test of differences in coefficients, however indicated that there are no significant differences in the relative contribution of social support (t = .771; p = .477), work family conflict (t = .606; p = 545) and job demand (t = .429; p = 668) to the prediction of job satisfaction of Nigerian Polytechnic non- academic staff.

The null hypothesis which stated that there is no significant gender difference in the relative contribution of job demand, work family conflict and social support to the prediction of job satisfaction of Nigerian polytechnics non- academic staff was by the findings of this study accepted for all the predictor variables. In effect, job demand, work family conflict and work-family conflict will similarly influence the prediction of job satisfaction of Nigerian polytechnics non- academic staff. This finding implies that the relative contribution of job demand, work family conflict and social support will similarly influence job satisfaction of both male and female Nigerian polytechnics non-academic staff. This finding corroborates the studies of Osagbemi (2000), Sousa-Poza (2003), Frye & Mount (2007) Jabulami (2001) Shinar (1998) which found that there were no Gender differences in job satisfaction between men and women.

Hypothesis Six

There is no significant cadre difference in the composite contribution of job demand, work-family conflict, and social support to the prediction of job satisfaction of Nigerian polytechnics non-academic staff.

Table 4.23:

Model Summary, Analysis of Variance and Test of Significant Cadre Differences in the Composite Contribution of Job Demand, Work-Family Conflict and Social Support to the Prediction of Job Satisfaction of Nigerian Polytechnics Non- Academic Staff.

Sum of Squares Df Mean Square F Sig.
Junior Regression 44624.927 3 14874.976 150.192 .000a
Residual 38031.370 384 99.040
Total 82656.296 387
Model Summary R = .735a; R2 =.540; R2(adj) =.536;

Std. Error of the Estimate = 9.95189

Senior Regression 59249.803 3 19749.934 177.707 .000b
Residual 76795.990 691 111.137
Total 136045.793 694
Model Summary R = .660a; R2 =.436; R2(adj) =.433;

Std. Error of the Estimate = 10.54218

Management Regression 15088.769 3 5029.590 46.400 .000c
Residual 17885.208 165 108.395
Total 32973.976 168
Model Summary R = .676b; R2 =.458; R2(adj) =.448;

Std. Error of the Estimate = 10.41130

Test of Significant Difference Between Junior and Senior Staff

Between Junior and Mgt Staff Between Senior and Mgt Staff

t-value = 0.007; df = 1079; p = 0.994

t-value = 0.006; df = 553; p = 0.995

t-value = 0.000; df = 860; p = 0.999

a. Dependent Variable: Job Satisfaction

b. Predictors: (Constant), Social Support, Job Demands, Work-Family Conflict

c. Predictors: (Constant), Social Support, Work-Family Conflict, Job Demand

The results in Table 4.23 indicated that with all the predictor variables (job demand, work-family conflict and social support) entered into the regression model for junior staff at once, there was a significant prediction of job satisfaction (R = .735a; R2 =.540; R2(adj) =.536; F (3,384) = 150.192; <.05). This showed that all the variables accounted for 53.6% of the variance in the job satisfaction of junior staff

The results also indicated that with all the predictor variables (job demand, work-family conflict and social support) entered into the regression model for senior staff at once, there was a significant prediction of job satisfaction (R = .660a; R2 =.436; R2(adj) =.433; F (3,691) = 177.707; <.05). This showed that all the variables accounted for 43.3% of the variance in the job satisfaction of senior staff. The results also indicated that with all the predictor variables (job demand, work-family conflict and social support) entered into the regression model for management staff at once, there was a significant prediction of job satisfaction (R = .676b; R2 =.458; R2(adj) =.448; F (3,165) = 46.400; <.05). This showed that all the variables accounted for 44.8% of the variance in the job satisfaction of management staff.

A test of significant difference in the coefficients of the prediction of job satisfaction revealed that there was no significant difference between junior and senior staff (t-value = 0.007; df = 1079; p = 0.994), between junior and management staff (t-value = 0.006; df = 553; p = 0.995) and between senior and management staff (t-value = 0.000; df = 860; p = 0.999). The null hypothesis which stated that there is no significant cadre difference in the composite contribution of job demand, work-family conflict, and social support to the prediction of job satisfaction of Nigerian polytechnic non-academic staff was accepted by this finding. This implies that the composite contribution of job demand, work-family conflict and social supports to the prediction of job satisfaction will be similar for all cadres of non- academic staff of Nigerian polytechnics. This finding implies that there is no significant cadre difference in the composite contribution of job demand, work-family conflict and social support to the prediction of job satisfaction was not differentiated by staff cadre. This finding lends credence to Ogunlade’s (2007) finding which concluded that cadre would not significantly predict commitment as well as job satisfaction of the respondents.

Hypothesis Seven

There is no significant cadre difference in the relative contribution of job demand, work-family conflict, and social support to the prediction of job satisfaction of Nigerian polytechnics non-academic staff

Table 4.24

Model Summary, Analysis of Variance and Test Of Significant Cadre Differences in the Relative Contribution of Job Demand, Work-Family Conflict and Social Support to the Prediction Of Job Satisfaction of Nigerian Polytechnics Non- Academic Staff.

Cadre Model Unstandardized Coefficients Standardized Coefficients T Sig.
B Std. Error Beta
Junior (Constant)

Job Demands

Work-Family Conflict

Social Support

58.355

-.197

-.329

.604

4.421

.130

.044

.058

-.071

-.375

.420

13.200

-1.513

-7.403

10.464

.000

.131

.000

.000

Senior (Constant) 55.304 3.206 17.252 .000
Job Demands -.256 .097 -.097 -2.646 .008
Work-Family Conflict -.213 .028 -.284 -7.500 .000
Social Support .610 .043 .440 14.253 .000
Management (Constant) 42.620 6.735 6.328 .000
Job Demands .011 .229 .004 .046 .963
Work-Family Conflict -.237 .069 -.281 -3.451 .001
Social Support .769 .090 .533 8.528 .000
Test of Differences in Coefficients Between Junior and Senior Participants
(Constant) 0.559 .577
Job Demands 0.364 .176
Work-Family Conflict 2.224 .026
Social Support 0.083 .934
Test of Differences in Coefficients Between Junior and Management Participants
(Constant) 1.953 .051
Job Demands 0.790 .430
Work-Family Conflict 1.124 .261
Social Support 1.541 .124
Test of Differences in Coefficients Between Senior and Management participants
(Constant) 1.700 0.089
Job Demands 1.074 .283
Work-Family Conflict 0.322 .747
Social Support 1.594 .111

Results in Table 4.24 revealed that for junior staff, not all the predictor variables (job demand, work family conflict and social support) were potent in the prediction of job satisfaction. Social support (coeff = .604; t = 10.464; p <.05) and work family conflict (coeff = -.329; t = -7.403; p <.05) but not job demand (coeff = -.197; t = -1.513; p >.05).

Results revealed that for senior staff, all the predictor variables (job demand, work family conflict and social support) were potent in the prediction of job satisfaction: Social support (coeff = .610; t = 14.253; p <.05), work family conflict (coeff = -.213; t = -7.500; p <.05) and job demand (coeff = -.256; t = -2.646; p <.05). Results also indicated that for management staff, not all the predictor variables (job demand, work family conflict and social support) were potent in the prediction of job satisfaction: Social support (coeff = .769; t = 8.528; p <.05) and work family conflict (coeff = -.237; t = -3.451; p <.05) but not job demand (coeff = .011; t = .046; p >.05).

The test of differences in coefficients indicated that for junior and senior staff, there was no significant difference in the relative contribution of social support (t = .083; p = .934) and job demand (t = .364; p = .575) to the prediction of job satisfaction of Nigerian polytechnics non-academic staff but not work family conflict (t = 2.224; p = .026) which was different. However, for junior and management staff, there are no significant difference in the relative contribution of social support (t = .1.541; p = .124), work family conflict (t = 1.124; p = .261) and job demand (t = .790; p = .430) to the prediction of job satisfaction of Nigerian polytechnics non-academic staff. Again, for senior and management staff, there was no significant difference in the relative contribution of social support (t = .1.594; p = .111), work family conflict (t = .322; p = .747) and job demand (t = 1.074; p = .283) to the prediction of job satisfaction of Nigerian polytechnic non-academic staff.

The null hypothesis which stated that there is no significant cadre difference in the relative contribution of job demand, work-family conflict, and social support to the prediction of job satisfaction of Nigerian polytechnic non- academics staff was by the findings of this study accepted. (for the predictor variables except for the significant difference in the coefficient in work family conflict between junior and senior staff). In effect, in most of the cases, the relative contribution of job demand, work-family conflict, and social support to the prediction of job satisfaction of Nigerian polytechnics non- academic staff will not be significantly differentiated by staff cadre. This is consistent with the study of Abd-el-fattah (2010) on longitudinal effect of pay increase of teachers across the cadre. The result of the finding showed that cadre did not have effect on job satisfaction of teachers.

Hypothesis Eight

There is no significant composite contribution of job demand, work-family conflict and social-support to the prediction of well-being among Nigerian polytechnics non-academic staff.

Table 4.25:

Model Summary of the Multiple Regression Analysis for the Combined Contributions of Job Demand, Work-Family Conflict and Social-Support to the Prediction of Well-being among Nigerian Polytechnics Non- Academic Staff

Sum of Squares df Mean Square F Sig.
Regression 25534.656 3 8511.552 367.379 .000b
Residual 28914.063 1248 23.168
Total 54448.719 1251
Model Summary R = .685a; R2 = .469; R2(adj) = .468

a. Dependent Variable: Well-being

b. Predictors: (Constant), Social Support, Job Demands, Work-Family Conflict

The results in Table 4.25 indicated that with all the predictor variables (job demands, work-family conflict and social support) entered into the regression model at once, there was a significant prediction of well-being of non-teaching staff of Nigerian polytechnics (R = .685; R2 = .469; Adj R2 = .468; F (3,1248) = 367.379; p<.05). This showed that all the variables accounted for 46.8% of the variance in well-being of non-academic staff of Nigerian polytechnics.

A stepwise multiple regression analysis was also performed to determine the complementary contributions of the independent variables to the prediction of well-being of non-academic staff of Nigerian polytechnics. Results are as presented in Table 4.26.

Table 4.26:

Model Summary of the Stepwise Multiple Regression Analysis for the Combined Contributions of Job Demand, Work-Family Conflict and Social-Support to the Prediction of Well-being among Nigerian Polytechnics Non- Academic Staff

Model R R Square Adjusted R Square Std. Error of the Estimate Change Statistics
R Square Change F Change df1 df2 Sig. F Change
1 .590a .348 .348 5.32851 .348 667.682 1 1250 .000
2 .684b .468 .468 4.81386 .120 282.562 1 1249 .000

a. Predictors: (Constant), Social Support

b. Predictors: (Constant), Social Support, Work-Family Conflict

The results in Table 4.26 indicated that when social support was entered into the regression model as the first predictor variable based on the strength of its relationship with well-being , there was a significant contribution to the prediction of well-being of non-academic staff of Nigerian polytechnics (R = .590; R2 = .348; Adj R2 = .348; F (1,1250) = 667.682; p < .05). By this, social support alone accounted for 34.8 percent of the variance in well-being of staff. When work-family conflict was introduced into the regression model as the second predictor variable, together with social support, it revealed a significant effect on well-being of staff (R = .684; R2 = .468; Adj R2 = .468; F (1,1249) = 282.562; p < .05). This revealed that social support and work-family conflict together predicted 46.8 percent of the well-being of staff. In effect, work-family conflict was able to add about 12.0 percent to the prediction of well-being of non-academic staff of Nigerian polytechnics.

The null hypothesis, which stated that there is no significant composite contribution of job demand, work-family conflict, social-support to the prediction of well-being among Nigerian polytechnics non- academic staff, was rejected by this finding. This implies that there was a significant combined contribution of job demand, work-family conflict and social-support to the prediction of well-being among Nigerian polytechnics non- academic staff. The finding of the eighth hypothesis revealed that there was significant combined contribution of job demand, work-family conflict and social support to the prediction of well-being among Nigerian polytechnics non-academic staff. In order of strength of the contributions; social support was the most potent predictor of well-being, followed by work- family conflict. This implies that to increase the well- being of Nigerian polytechnics non-academic staff, premium attention must be placed in ensuring adequate social support, reduction in work-family conflict and reduction of job demand among Nigerian polytechnics non-academic staff. The findings support the main-effects model that postulates that social support has important implications for individual’s job satisfaction and well-being regardless of the presence or absence of life stress (Cohen et al., 2000).

In the context, this model suggests that emotional and material support received from family, friends, and others has a positive impact on job satisfaction and well-being regardless of the amount or severity of abuse experienced. (Kemp et al. 1995). Also, the relationship between social support at work, employee’s health and well-being has been established (Nabavi & Shahriari, 2012). Studies by McCall, Lombardo and Morrison (1998) found out that supervisor’s support facilitates employee’s job satisfaction, well-being and organizational commitment. According to Boyar and Monley (2007) the support of the immediate supervisor has a central impact on the experience and perception of workplace well-being.

Hypothesis Nine

There is no significant relative contribution of job demand, work-family conflict and social support to the prediction of well-being among Nigerian Polytechnics non- academic staff.

Table 4.27:

Beta Coefficients and t Ratio for Relative Contributions of Job Demand, Work- Polytechnics Non-Academic Staff.

Unstandardized Coefficients Standardized Coefficients T Sig.
B Std. Error Beta
(Constant) 16.253 1.114 14.596 .000
Job Demands – .038 .034 -.031 -1.124 .261
Work-Family Conflict – .133 .010 -.359 -12.743 .000
Social Support .286 .015 . 437 19.325 .000

a. Dependent Variable: Well-being

The results in Table 4.27 revealed that social support (β = .437; t = 19.325; p < .05) was the most potent out of the three predictor variables in predicting the well-being of non-academic staff of Nigerian polytechnics. This is followed by work-family conflict (β = -.359; t = -12.743; p < .05). Job demand (β = -.031; t = -1.124; p > .05) was not a good predictor variable of well-being of non-academic staff of Nigeria polytechnics.

The null hypothesis, which stated that there is no significant relative contribution of job demand, work-family conflict and social-support to the prediction of well-being among Nigerian polytechnics non- academic staff, was rejected by the findings of this study.This implies that there was a significant relative contribution of job demand, work-family conflict and social-support to the prediction of well-being among Nigerian polytechnics non- academic staff. In order of strength of the contributions, social support was the most potent predictor of well-being, followed by work-family conflict while job demand was not a good predictor. The finding is consistent with Lisa findings (2014) who conducted a study on the employee’s who worked in several fields ranging from customer service, accounting and finance, administration, information technology, marketing, underwriting, sales and claims. The finding suggested that management and supervisor support (supportive work- family culture) effectively reduced perceptions of work-family conflict, which helps to reduce some of the negative effects of work–family conflict on employees well-being. Also, studies have found out that individuals who experience work-family conflict are generally unsatisfied with their job and that work-family conflict and job demand are associated with diminished satisfaction and lower level of psychological well-being (Fryean, Breaugh; Anderson et.al.,2002; Carson and Perrewe,1999; Kinnumen and Mauno,1998; Kossek and Ozeki, 1998).

Hypothesis Ten

There is no significant gender difference in the composite contribution of job demand, work-family conflict and social support to the prediction of well-being of Nigerian polytechnics non- academic staff.

Table 4.28:

Model Summary, Analysis of Variance and Test of Significant Sex Differences in The Composite Contribution of Job Demand, Work-Family Conflict and Social Support To The Prediction of Well- being of Nigerian Polytechnics Non- Academic Staff.

Sex Source of Variation Sum of Squares df Mean Square F Sig.
Male Regression 14675.711 3 4891.904 206.807 .000b
Residual 17125.826 724 23.654
Total 31801.537 727
Model Summary R = .679a; R2 =.461; R2(adj) = .459;

Std. Error of the Estimate = 4.86358

Female Regression 10838.952 3 3612.984 160.347 .000b
Residual 11716.809 520 22.532
Total 22555.761 523
Model Summary R =.693a; R2 = .481; R2(adj) =.478;

Std. Error of the Estimate = 4.74682

Test of Significant Difference t-value = 0.003; df = 1248; p = 0.998

a. Dependent Variable: Well-being

b. Predictors: (Constant), Social Support, Job Demands, Work-Family Conflict

The results in Table 4.28 indicated that with all the predictor variables (job demand, work-family conflict and social support) entered into the regression model for male participants at once, there was a significant prediction of well- being (R = .679a; R2 =.461; R2(adj) = .459; F(3,724) = 206.807; <.05). This showed that all the variables accounted for 45.9% of the variance in the well-being of male participants. The results also indicated that with all the predictor variables (job demand, work-family conflict and social supports) entered into the regression model for female participants at once, there was a significant prediction of well-being (R =.693a; R2 = .481; R2(adj) =.478; F (3,724) = 163.653; <.05). This showed that all the variables accounted for 47.8% of the variance in the well -being of female participants.

A test of significant difference in the coefficients of the prediction of well-being between male and female participants revealed that there was no significant difference between the two groups (t-value = 0.003; df = 1248; p = 0.998).

The null hypothesis which stated that there is no significant gender difference in the composite contribution of job demand, work-family conflict and social support to the prediction of well- being of Nigerian polytechnics non-academic staff was accepted by this finding. This implies that the composite contribution of job demand, work-family conflict and social support to the prediction of well- being will be comparable for male and female non- academic staff of Nigerian polytechnics. The finding of the tenth hypothesis revealed that there was no significant gender differences in the composite contribution of job demand, work-family conflict and social support to the prediction of well-being among Nigerian polytechnics non-academic staff .The finding corroborates the findings of Owoeye (2014) who found out that there was no gender differences in emotional intelligence of workers in public sectors in Oyo State.

Hypothesis Eleven

There is no significant gender difference in the relative contribution of job demand, work family conflict and social support to the prediction of well -being of Nigerian polytechnics non- academic staff.

Table 4.29:

Model Summary, Analysis of Variance and Test of Significant Sex Differences in the Relative Contribution of Job Demand, Work-Family Conflict and Social Support to the Prediction of Well-being of Nigerian Polytechnics Non- Academic Staff.

Sex Model Unstandardized Coefficients Standardized Coefficients T Sig.
B Std. Error Beta
Male (Constant) 15.268 1.522 10.033 .000
Job Demands -.002 .047 -.001 -.033 .974
Work-Family Conflict -.142 .014 -.379 -10.019 .000
Social Support .300 .020 .436 14.685 .000
Female (Constant) 17.334 1.639 10.579 .000
Job Demands -.079 .050 -.065 -1.595 .111
Work-Family Conflict -.123 .015 -.338 -7.959 .000
Social Support .270 .022 .439 12.568 .000
Test of Differences in Coefficients Between Male and Female Participants
(Constant) .924 .356
Job Demands 1.122 .262
Work-Family Conflict .926 .353
Social Support 1.009 .313

a. Dependent Variable: Well-being

Results in Table 4.29 revealed that for male participants, all the predictor variables (job demand, work family conflict and social support) were potent in the prediction of well-being: Social support (coeff = .300; t = 14.685; p <.05) and work family conflict (coeff = -.142; t = -10.019; p <.05) but not job demand (coeff = -.002; t = -033; p >.05). In the same direction, results showed that for female participants, all the predictor variables (job demand, work family conflict and social support) were potent in the prediction of job satisfaction: Social support (coeff = .270; t = 12.568; p <.05), work family conflict (coeff = -.123; t = -7.959; p <.05) but not job demand (coeff = -.079; t = -1.595; p >.05).

The test of differences in coefficients however indicated that there are no significant difference in the relative contribution of social support (t = 1.009; p = .313), work family conflict (t = .926; p = 353) and job demand (t = 1.122; p = .262) to the prediction of well- being of Nigerian polytechnics non-academic staff. The null hypothesis which stated that there is no significant gender difference in the relative contribution of job demand, work family conflict and social supports to the prediction of well- being of Nigerian polytechnics non-academic staff was, by the findings of this study accepted for all the predictor variables. In effect job demand, work family conflict and social supports will correspondingly influence the prediction of well- being of Nigerian polytechnics non- academic staff. The finding laid credence to Brandley (2013) who asserted that a growing amount of research has revealed that some aspects of work environment can contribute to higher level of sickness, absence from work; for example, working in the service industry involves constant interaction with customers and the requirement to regulate emotion at work.

Work-family conflict is primarily caused by excessive work demands and this predicts negative family outcomes, whereas family-work conflict is primarily determined by family demands and predicts negative work outcomes (Adebola, 2005). Therefore, if an employee is experiencing high levels of family-work role conflict, their roles and responsibilities in family life are interfering with the work domain. Meanwhile, because the employee is more committed to the welfare of the family, this will take priority, reducing or minimising the resources of time and energy to be spent in the work domain. Thus, employees who experience high family role conflict should experience less affective commitment to the organisation.

Hypothesis Twelve

There is no significant cadre difference in the composite contribution of job demand, work-family conflict, and social support to the prediction of well-being of Nigerian polytechnics non- academic staff

Table 4.30:

Model Summary, Analysis of Variance and Test of Significant Cadre Differences in the Composite Contribution of Job Demand, Work-Family Conflict and Social Support to the Prediction of well- being of Nigerian Polytechnics Non- Academic Staff.

Sum of Squares df Mean Square F Sig.
Junior Regression 7639.642 3 2546.547 104.468 .000b
Residual 9360.551 384 24.376
Total 17000.193 387
Model Summary R = 670a; R2 = .449; R2(adj) = .445;

Std. Error of the Estimate = 4.93725

Senior Regression 14481.025 3 4827.008 204.180 .000b
Residual 16335.858 691 23.641
Total 30816.883 694
Model Summary R = .685a; R2 = .470; R2(adj) = .468;

Std. Error of the Estimate = 4.86219

Management Regression 3973.418 3 1324.473 84.553 .000c
Residual 2584.641 165 15.664
Total 6558.059 168
Model Summary R = .778b ; R2 = .606; R2(adj) = .599;

Std. Error of the Estimate = 3.95784

Test of Significant Difference Between Junior and Senior Staff

Between Junior and Mgt Staff Between Senior and Mgt Staff

t-value = 0.003; df = 1079; p = 0.998

t-value = 0.025; df = 553; p = 0.980

t-value = 0.022; df = 860; p = 0.982

a. Dependent Variable: Well-being

b. Predictors: (Constant), Social Support, Job Demands, Work-Family Conflict

c. Predictors: (Constant), Social Support, Work-Family Conflict, Job Demands

The results in Table 4.30 indicated that with all the predictor variables (job demand, work-family conflict and social support) entered into the regression model for junior staff at once, there was a significant prediction of well- being (R = 670a; R2 = .449; R2(adj) = .445; F (3,384) = 104.468; <.05). This showed that all the variables accounted for 53.6% of the variance in the well -being of junior staff. The results also indicated that with all the predictor variables (job demand, work-family conflict and social support) entered into the regression model for senior staff at once, there was a significant prediction of well -being (R = .685a; R2 = .470; R2(adj) = .468; F (3,691) = 204.180; <.05). This showed that all the variables accounted for 43.3% of the variance in the well-being of senior staff.

The results also indicated that with all the predictor variables (job demand, work-family conflict and social support) entered into the regression model for management staff at once, there was a significant prediction of well -being (R = .778b ; R2 = .606; R2(adj) = .599; F (3,165) = 84.553; <.05). This showed that all the variables accounted for 44.8% of the variance in the well-being of management staff. A test of significant difference in the coefficients of the prediction of well -being revealed that there was no significant difference between junior and senior staff (t-value = 0.003; df = 1079; p = 0.998), between junior and management staff (t-value = 0.025; df = 553; p = 0.980) and between senior and management staff (t-value = 0.022; df = 860; p = 0.982). The null hypothesis, which stated that there is no significant cadre difference in the composite contribution of job demand, work-family conflict, and social support to the prediction of well- being of Nigerian polytechnics non-academic staff, was accepted by this finding. This implies that the composite contribution of job demand, work-family conflict and social support to the prediction of well-being will be alike for all cadres of non-academic staff of Nigerian polytechnics.

By this finding there was no significant cadre difference in the composite contribution of job demand, work-family conflict, and social support to the prediction of well-being of Nigerian polytechnics non- academic staff. This implies that the composite contribution of job demand, work-family conflict and social support to the prediction of well- being will be alike for all cadres of non- academic staff of Nigerian polytechnics. This finding finds consistency with the findings of Ogunsipe (2012) that the general well-being of workers is not differentiated by cadre.

Hypothesis Thirteen

There is no significant cadre difference in the relative contribution of job demand, work-family conflict, and social support to the prediction of well-being of Nigerian polytechnics non- academic staff.

Table 4.31:

Model Summary, Analysis Of Variance and Test of Significant Cadre Differences in the Relative Contribution of Job Demand, Work-Family Conflict and Social Support to the Prediction of Well-being of Nigerian Polytechnics Non- Academic Staff.

Model Unstandardized Coefficients Standardized Coefficients T Sig.
Cadre B Std. Error Beta
Junior (Constant)

Job Demands

Work-Family Conflict

Social Support

19.607

.027

-.169

.236

2.193

.064

.022

.029

.021

-.425

.362

8.939

.413

-7.678

8.245

.000

.680

.000

.000

Senior (Constant) 17.678 1.478 11.957 .000
Job Demands -.084 .045 -.067 -1.874 .061
Work-Family Conflict -.131 .013 -.368 -10.034 .000
Social Support .272 .020 .413 13.796 .000
Management (Constant) 2.885 2.560 1.127 .261
Job Demands .097 .087 .079 1.110 .269
Work-Family Conflict -.089 .026 -.237 -3.419 .001
Social Support .457 .034 .711 13.329 .000
Test of Differences in Coefficients Between Junior and Senior
(Constant) 0.729 .466
Job Demands 1.419 .156
Work-Family Conflict 1.487 .137
Social Support 1.022 .309
Test of Differences in Coefficients Between Junior and Management Participants
(Constant) 4.961 .000
Job Demands 0.048 .517
Work-Family Conflict 2.349 .019
Social Support 4.945 .000
Test of Differences in Coefficients Between Senior and Management Participants
(Constant) 5.004 .000
Job Demands 1.848 .065
Work-Family Conflict 1.445 .149
Social Support 4.690 .000

a. Dependent Variable: Well-being

Results in Table 4.31 revealed that for junior staff, not all the predictor variables (job demand, work family conflict and social support) were potent in the prediction of well-being: Social support (coeff = .236; t = 8.245; p <.05) and work family conflict (coeff = -.169; t = -7.678; p <.05) but not job demand (coeff = .027; t = .413; p >.05). Results revealed that for senior staff, all the predictor variables (job demand, work family conflict and social support) were potent in the prediction of well- being: Social support (coeff = .272; t = 13.796; p <.05) and work family conflict (coeff = -.131; t = -10.034; p <.05) but not job demand (coeff = -.084; t = -1.874; p >.05).

Results also indicated that for management staff, not all the predictor variables (job demand, work family conflict and social support) were potent in the prediction of well- being. Social support (coeff = .457; t = 13.329; p <.05) and work family conflict (coeff = -.089; t = -3.419; p <.05) but not job demand (coeff = .097; t = 1.110; p >.05). The test of differences in coefficients indicated that for junior and senior staff, there was no significant difference in the relative contribution of social support (t = 1.022; p = .309), work family conflict (t = 1.487; p = .137) and job demand (t = 1.419; p = .156) to the prediction of well- being of Nigerian polytechnics non- academic staff was not different. However, for junior and management staff, there was no significant difference in the relative contribution of job demand (t = 0.048; p = .517) to the prediction of well -being of Nigerian polytechnics non- academic staff but not social support (t = 4.945; p = .000) and work family conflict (t = 2.349; p = .019) where significant differences existed.

Again, for senior and management staff, there was no significant difference in the relative contribution of work family conflict (t = 1.445; p = .149) and job demand (t = 1.848; p = .065) to the prediction of well- being of Nigerian polytechnics non- academic staff but not for social support (t = 4.690; p = .000) which was significantly different.The null hypothesis, which stated that there is no significant cadre difference in the relative contribution of job demand, work-family conflict, and social support to the prediction of well-being of Nigerian polytechnics non-academic staff was by the findings of this study accepted for the predictor variables except for the significant difference in the coefficient in work-family conflict between junior and senior staff. In effect, in most of the cases, the relative contribution of job demand, work-family conflict, and social support to the prediction of well -being of Nigerian polytechnics non-academic staff will not be significantly differentiated by staff cadre.

The finding of the thirteen hypothesis revealed that there was no significant cadre difference in the relative contribution of job demand, work-family conflict, and social support to the prediction of well-being of Nigerian polytechnics non-academic staff. In effect, in most of the cases, the relative contribution of job demand, work-family conflict, and social support to the prediction of well- being of Nigerian polytechnics non- academic staff will not be significantly differentiated by staff cadre. This finding lends credence to Anthony’s (2014) findings that cadre will not significantly predict well-being of workers. Furthermore, the finding finds consistency with the findings of Ogunlade (2007) who concluded that cadre will not significantly predict job satisfaction and well –being of workers.

CHAPTER FIVE

SUMMARY, CONCLUSION AND RECOMMENDATIONS

This chapter presents a summary of the study. The sequence of the summary is in order of the whole exercise and the research hypotheses. The chapter also highlights the implications of the findings, while recommendations, limitation of the study as well as suggestions for further study were made.

5.1. Summary

Job satisfaction and well-being among employees have been the focus of organisations, management strategists and human relations departments in Nigeria and perhaps globally. Workers tend to have several challenges when performing their duties but when satisfied with their job they are committed to their organisationSiang (2015) noted that job satisfaction as the feelings regarding one’s job and how happy such a person feels within that job. This can be affected by many factors such as company policies and interpersonal relationships. Robin and Judge (2013) clarify that job satisfaction is a positive feelings about one’s job resulting from evaluation of its characteristics.

The following objectives were set and achieved for this research work:

The major objective of this study is to determine the extent to which job demand, work–family conflict and social support predict job satisfaction and well- being of non- academic staff of polytechnics in South-West Nigeria.

The specific objectives are as follows:

i. To find the extent of the combined contribution of job demand, work-family conflict, and social-support will jointly and individually predict job satisfaction and well-being of Nigerian polytechnics non- academic staff.

ii. To explore the moderating influence of gender and staff cadre on the joint and individual contributions of job demand, work-family-conflict and social support in the prediction of job satisfaction and well-being of Nigerian polytechnics non-academic staff.

iii. To establish the interrelationship among job demand, work-family conflict, social-support, job satisfaction and well-being of Nigerian polytechnics non- academic staff.

It is a known fact that much attention have not been given to reduction of job demand and work-family conflict among non–academic staff of Polytechnic in Nigeria. Improper placement, long working hours, intensified workloads, constant changes in work practices and job insecurities, these are major problem in most establishment. Failure to identify and manage worker’s job demand and work- family conflict can eventually lead to loss of man power and can also affect job satisfaction and well-being of workers which inturn have negative iimpact on overall productivity of organisations, communities and the country at large. Unfortunately, job satisfaction and well-being of worker’s is under recognised and mostly unattended to in the Nigerian societies. There seems to be no or few effective structures or programmes for worker’s experiencing job dissatisfaction and ill-being. It is against this background that this study investigated the influence job demand, work-family conflict and social support on job satisfaction and well-being of non-academic staff of polytechenics in South West Nigeria Furthermore, for possibility of gender and staff cadre variation in workers job satisfaction and well-being, the two factors are carried along in this study as moderating variables.

Eleven Research Questions were raised for the study these are

i. What is the level of work-family conflict of non-academic staff of Nigerian polytechnics?

ii. What is the level of job demands of non-academic staff of Nigerian polytechnics?

iii. What is the level of social support of non-academic staff of Nigerian polytechnics?

iv. What is the level of job satisfaction of non-academic staff of Nigerian polytechnics?

v. What is the level of well-being of non-academic staff of Nigerian polytechnics?

vi. What is the relationship among job demand, work-family conflict, social supports, job satisfaction and well-being of Nigerian polytechnic non- academic staff?

vii. Would there be any significant differences in the job demand of Nigerian Polytechnics non-academic staff?

viii. Would there be any significant differences in the work-family conflict of Nigerian Polytechnic non-academic staff?

ix. Would there be any significant differences in the social support of Nigerian Polytechnics non-academic staff?

x. Would there be any significant differences in the job satisfaction of Nigerian Polytechnics non-academic staff?

xi. Would there be any significant differences in the well-being Nigerian Polytechnics non- academic staff?

Thirteen Hypotheses were formulated and tested in this study: These are;

i. Job demand, work-family conflict and social-support will not significantly

correlate with job satisfaction among Nigerian Polytechnics non -academic staff.

ii. There is no significant composite contribution of job demand, work-family conflict and social support to the prediction of job satisfaction among non-academic staff of Nigerian polytechnics.

iii. There is no significant relative contribution of job demand, work-familyconflict and social support to the prediction of job satisfaction of Nigerian polytechnics non- academic staff.

iv. There is no significant gender difference in the composite contribution of job demand, work-family conflict and social support to the prediction of job satisfaction of Nigerian polytechnics non- academic staff.

v. There is no significant gender difference in the relative contribution of work-family conflict and well-being to the prediction of job satisfaction of Nigerian polytechnics non-academic staff.

vi. There is no significant cadre difference in the composite contribution of job demand, work-family conflict, and social support to the prediction of job satisfaction of Nigerian polytechnics non- academic staff.

vii. There is no significant cadre difference in the relative contributions of job demand work-family conflict and social-support to the prediction of job satisfaction of Nigerian polytechnics no-academic staff.

viii. There is no significant composite contribution of job demand, work-family conflict and social support to the prediction of well-being of Nigerian polytechnics non- academic staff.

ix. There is no significant relative contribution of job demand, work-family conflict, and social -support to the prediction of well-being of Nigerian polytechnics non- academic staff.

x. There is no significant gender difference in the composite contribution of job demand, work-family conflict and social-support to the prediction of well-being of Nigerian polytechnics non-academic staff.

xi. There is no significant gender difference in the relative contribution of job demand, work-family conflict and social- support to the prediction of well-being of Nigerian polytechnic non- academic staff.

xii. There is no significant cadre difference in the composite contribution of job demand, work-family conflict and social support to the prediction of well-being of Nigerian polytechnics non- academic staff.

xii. There is no significant cadre difference in the relative contribution of job demand, work-family conflict and social supports to the prediction of well-being of Nigerian polytechnics non- academic staff.

The findings would serve as a guide to non-academic staff to manage their job demands to maintain healthy living and to prevent untimely death before retirement. Also, it will facilitate efforts of stakeholders such as the government, polytechnic administrators and management towards formulating policies that will enhance polytechnics staff job satisfaction and well-being. Also, the results of the study will provide information, especially to workers, parents, guardians, especially the human resources managers and the establishment unit of various organisations. The findings of this study will also expand the frontier of knowledge on the theme of the study. Although, there are existing literatures on some of the variables explored in this work, findings on their inter-relatedness, especially among non-academia, are far from being conclusive. It is hoped that the study will provide vital information and empirical data which are necessary to further facilitate an understanding of the major variables of the study. It will be of immense benefit to scholars in the field of personnel psychology. The findings will also serve as a data base for other researchers and investigators through publication in both local and international journals.

This study was delimited to investigating job demands, work- family conflict and social supports to the prediction of job satisfaction and well-being of non- academic staff in public and private polytechnics in the South-West, Nigeria. The study area covers six states including Lagos, Oyo, Osun, Ondo, Ogun and Ekiti. The study is also delimited to determine the moderating influence of gender and cadre in contributions of job demand, work-family conflict and social support in the determination of job satisfaction and well-being.

This descriptive survey research design was adopted for this study. This design is considered appropriate because it can be used when a researcher intends to reach a sizeable portion of the target population as sample from which data may be collected while the findings are generalised on the entire population. In this study, the target population is relatively large and a survey would be effective at collecting necessary data that could be used in exploring the factors that may contribute to job satisfaction and well-being of non–academic staff including job demand, work- family conflict and social support.Also measured the influence of moderating variables(gender and cadre) on the predictors (job demand, work-family conflict and social support) and the criterion variables( job satisfaction and well-being).

The population for this study comprised non-academic staff working in public and private polytechnics in South-West, Nigeria. Available data indicates that there are thirteen private polytechnics and fourteen public polytechnics as at June 2017 that are spread across the geographical zone with 9,621 non-academic staff polytechnics.

A sample of one thousand three hundred and twelve (1,312) were used for this randomly selected from six (6) public and six (6) private polytechnics. This represents 13.64 percent of the total number of non-academic staff in all the public and private polytechnics in South-West, Nigeria. The sample was selected u sing the multi-stage sampling procedure. This procedure was considered appropriate because of the need to ensure probability sampling at the various stages involved in the selection of the sample. The first stage has to do with the selection of polytechnics. Here, the stratified sampling technique was used to ensure that the two categories of polytechnics in this country are included in the study. Hence, the list of polytechnics was stratified into two that is; public and private polytechnics six private and six public polytechnics were selected using balloting method. At the second stage, proportional stratified sampling was used to ensure that male and female non- academic staff were selected to reflect their proportion in the target population. Each group, male or female was again stratified into three groups: management non -academic staff Contedis 14 and above, senior non- academic staff (Contedis 8 – 13) and junior non- academic staff (Contedis 3- 7). Thereafter, simple random sampling of the participants was done. Out of the (1,312) questionnaire distributed, (1,252) were returned.

The data for this study were collected using six major instruments.These questionnnaires were packaged into a document of under six sections as follows:

(a) Biographical Data Form designed by the researcher (BDF)

(b) Job Content Questionaire (JCQ) by Karasek (1985) was adopted by the researcher to measure job demand.

(c) Work-Family Conflicts Scale (WFCS) by Carlson, Kacmar, and Williams (2000) and was re-validated by Amazue Lawrence.O (2012) was adopted by the researcher to measure work-family conflict.

(d) Multidimensional Scale of Perceived Social Support Assessment (MSPSSA) by Zimet, Powell, Farley, Werkman & Berkoff, 1990) was adopted by the researcher to measure social support.

(e) Job Satisfaction Scale (JSS) by Warr, Cook and Wall (1979) and re-validated by Perminas, Vaitkevicius and Astraukaite, (2010) was adopted by the researcher to measure job satisfaction.

(f.) Satisfaction with Life Scale – by Diener, Emmons, Larsen, and Griffin, (1985) and re-validated by Ezeokoli and Ayodele, (2013) was adopted by the researcher to measure well-being.

The six validated instrument were administered on the participants in their various offices.The researcher and the two trained research assistants were involved in the administation of the instrument to the pespondents chosen, letter of introduction written and signed by the authority of Department of Eductional Foundations and Counselling Olabisi Onabanjo University, Ago-Iwoye, were given to the registrar’s of various institutions involved, stating the purpose and the objectives of the study.

Results indicated that;

i. There was correlation among job demand, work-family conflict, social support, job satisfaction and well-being of non–academic staff of polytechnics in South West Nigeria.

ii. There was a significant combined contribution of job demand, work-family conflict and social-support to the prediction of job satisfaction among Nigerian polytechnics non- academic staff.

iii. There was significant relative contribution of job demand, work-family

conflict and social support to the prediction of job satisfaction among non –academic staff of polytechnics in South West Nigeria. (R = .599; R2 = .359; Adj R2 = .358; F (1,1250) = 699.605; p < .05).

iv. There was no significant gender difference in the composite contribution of job demand, work- family conflict and social support to the total variance of job satisfaction of non – academic staff of Nigerian polytechnics.

v. There was no significant gender difference in the relative contribution of job demand, work-family conflict and social support to the total variance of job satisfaction of non-academic staff of Nigerian polytechnics satisfaction.

vi. There was no significant cadre difference in the composite contribution of job demand, work family conflict and social support to the total variance of job satisfaction of Nigerian polytechnics non- academic staff.

vii. There was no significant cadre difference in the relative contribution of job demand, work-family conflict, and social support to the total variance of job satisfaction of Nigerian polytechnics non- academic staff.

viii. There was no significant cadre difference in the composite contribution of job demand, work-family conflict, and social support to the variance of well-being of Nigerian polytechnics non- academic staff.

ix. There was a significant relative contribution of job demands, work-family conflict and social-support to the prediction of well-being among Nigerian polytechnics non- academic staff.

x. There is no significant gender difference in the composite contribution of job demand, work-family conflict and social-support to well-being among Nigerian polytechnics non-academic staff

xi. There was no significant gender difference in the relative contribution of job demand, work-family conflict and social support to the prediction of well-being of Nigerian polytechnics non- academic staff.

xii. There was no significant gender difference in the composite contribution of job demand, work family conflict and social support to the prediction of well- being of Nigerian polytechnics non- academic staff.

xiii. There was no significant cadre difference in the relative contribution of job demand, work-family conflict and social support to the prediction of well-being of Nigerian polytechnics non-academic staff

5.2 Conclusion

Based on the above findings of the study, it was concluded that job satisfaction and well–being are two of the most important variables for non-academic in polytechnics. An investigation of the factors influencing each of these variables is therefore worthwhile venture. This study has clearly shown that for non-acdemic staff in both private and public polytechnics, job demand, work-family conflict and social support combined to significantly predict job satisfaction and well-being jointly and individually.It was also concluded that for non-academic staff in private and public polytechnics, there were significant relative contribution job demand, work- family conflict and social support to well-being. Specifically, there was no significant gender differences in the relative contribution of job demand, work family-conflict and social support on job satisfaction of non-academic staff in public and private polytechnics and there were non-significant cadre differences in the relative contribution of job demand, work-family conflict and social support to prediction job satisfaction and well-being of non-academic staff of public and private polytechnics. Finally, for the combined contribution of job satisfaction and well-being and the relative contribution of well-being, non-academic staff in private polytechnics had an edge, while non-academic staff in public polytechnics had an edge for the relative contribution of job satisfaction.

5.3 Recommendations

The following recommendations are proffered with the hope that carefu