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CHAPTER 1 INTRODUCTION 1

March 30, 2019 0 Comment

CHAPTER 1
INTRODUCTION
1.0 Introduction
Absenteeism is nowadays a happening subject that is present in most organisations regardless the size of the latter or whether public or private. For many organisations, it is an issue of concern. Absenteeism is caused by numerous factors. While some people perceive absenteeism as a good thing others do not. Absenteeism has been investigated for decades by numerous research researchers in an assortment of ways.
Likewise, employee turnover also is one of the major problems being tackled by organisations nowadays. With unemployment rates being high, employees are seen to be one among the major challenges confronting the industry. There is a need to understand the potential employees and their career expectations (Ghiselli et al, 2005), as turnover level is high and there exist more challenges for recruitment and retention of qualified and well trained employees.
Indeed, these are difficult moments faced by the Civil service also. Rendering basic services to its inhabitants is one of the utmost responsibilities of Local Authorities. But, unfortunately, the uproar of the public against the above- mentioned Authorities is noted. What is more questionable nowadays is the attitude and ineffectiveness of its personnel. It is perceived at a great extent that the Local Government has an increase rate of people being absent from their respective duty and turnover affecting negatively its power to meet the demands of the people regarding services in terms of quality and time.

The Council
Legal Body The District Council of Savanne is established in conformance with Section 7 (2)(g) of the Local Government Act 2011 and is under the portfolio of the Ministry of Local Government.

Constitution Within the District Council, direction is given by the Chief Executive and overall strategy rules of the council are issued by the chairperson. The District Council of Savanne comprises of 17 villages and is found in the southern costal part of Mauritius. Except for villages of Surinam and Chemin Grenier which have two members each, the rest of the fifteen villages have only one member each, and thus, there is a sum of nineteen members. Moreover, a chairperson is chosen among the nineteen members through voting for a period of two years.

The Mission ?Provide high quality services to the locality and its stakeholders
?Boost up fiscal, sociable, cultural, value-oriented growth
The Vision ?To motivate a prosperous and developing society in a liberal environment where public can reach their maximum capability in satisfaction of their individual rights, with due respect to gender fairness.

Core Values Integrity: Managing our partners in a continuous manner and more precisely with our customers and our teammates in a reasonable and moral manner, gaining confidence through the activities.

Respecting people: Supporting a respectful, sincere, equal and reasonable work environment. Figuring out cultural various concerns and esteeming the perspectives of our interlocutors in the execution of the everyday obligations.

Value staff: Preparing them for giving the most noteworthy excellence service and giving due acknowledgment of worker fulfilment, empowering and assisting profession improvement.

Professionalism: Devotion to work with integrity, privacy, fairness and strictness.

Service Excellence: To be devoted at each level to give an exceptional service.

To nurture cooperation between all workers, sections and the Council for objective accomplishment.

Punctuality: Focus on conveying services within the recommended delay is placed on.

Table 1: About the Council
Background of Study
As pressures rise on the national budget, the need for organisations to be more competitive and in line with government vision of “Putting People First”, various initiatives are being undertaken at all levels to cut cost and improve productivity. The Government identified one major initiative which is to deal with the problem of tardiness and to curb absenteeism and turnover in the public service. The rate of absences and turnover from duty can be considered as a viral contamination which influences and is influenced by the whole system of the institution. Therefore, it is defended that in developing an effective remedy for this condition, it is important that to focus on and identify the reasons causing absenteeism.

Thus this project will aim at focusing on the reasons leading to a high rate of absenteeism and turnover in the Local Authorities more precisely at The District Council of Savanne. This research argues that organisations must adopt a holistic and systemic approach so as to find out effective remedies to reduce absences and turnover bug. This will consequently create a more conductive environment to work as it will meet new challenges with positive effects as demanded by the ever changing international environment.

Research Problem
During several years, many researchers have been interested with the theory of absenteeism and turnover intention. Turnover and absenteeism harms to company are well-recorded (Mirvis & Lawler, 1977; Steers & Rhodes, 1978; Wanous, 1980); such harms are the reasons why scholars have shown interest in the concept of absenteeism and turnover. Job-related mentalities, particularly fulfillment features, are commonly the concentration in turnover and absenteeism study (Mobley, Griffeth, Hand, & Meglino, 1979; Steers & Rhodes, 1978). The level of dissatisfaction itself represenst a high rate (more than 15%) of fluctuation in turnover & absenteeism has prompted other different approaches. These approaches incorporate utilizing withdrawal discernments to foresee turnover (Mobley, 1977), or concentrating on other job-related perspective, for example, work association and organizational dedication as autonomous indicators of turnover and absenteeism.

Past studies have inspected the connection between workers’ employment fulfillment (job satisfaction) and leadership conduct in different settings (Cook, Wall, Hepworth, ; Warr, 1989; Bass, 1990; Chen ; Silversthorne, 2005). These studies normally demonstrate that the importance of job satisfaction is essential in both public and private sector.

Many studies showed that a worker’s potential and job satisfaction is influenced by job stress because better job results are the requirement that companies are asking. Actually, present day times have been called as the “time of uneasiness and stress” (Coleman, 1976). According to Stamps & Piedmonte (1986), there is a significant relationship job satisfaction and job stress.

However, there are not enough studies that have been done for the relationship of job fit with job satisfaction, turnover and absenteeism. Very few new data was obtained for our knowledge concerning job fit because of replicated findings of previous studies by recent researches.

Actually, for the better understanding of the impact of job fit/adaptation on turnover and absenteeism intention, a special model has been suggested in this study. Through, this model, it has been demonstrated that job fit/adaptation has an impact on job satisfaction firstly and this ultimately lead to a change in the turnover & absenteeism intention.
Research Objectives
This research will particularly focus on the influence of transformational leadership styles, job fit, job stress and job satisfaction and ultimately on turnover intention and absenteeism intention. Below are the main objectives of this research:
1. Identify the causes of absenteeism and turnover of employees at The District Council of Savanne
2. To assess the views of The DCS’s leaders and employees with respect to the impact of absenteeism and turnover
3. To test for effect of identified determinants of absenteeism and turnover on absenteeism rate and turnover rate
Outline of the approach
For this study, a quantitative approach has been put into service whereby questionnaire will be given and filled in by employees of The DCS. A Quota sample will be adopted comprising of 100 employees.

CHAPTER 2
LITERATURE REVIEW
Introduction
In any industrial unit, absenteeism at the workplace is known to be a prevalent issue, whether in a small or big, private or Government undertaking. “People became aware of the phenomenon of absenteeism in 1904, the year in which the term “absenteeism” was published in New York Times” (Patton, 2005). From then onwards, absenteeism has been found to be one of the most recurring problems faced by managerial employees and this is considered as a serious issue due to its effects on service delivery, staff morale as well as it could cause financial losses. According to Ezane (2009), the lack of interest and motivation to work usually leads to absenteeism, which can hamper competitiveness of enterprises.

Likewise, employee turnover stands as a capital challenge for organization nowadays. Hom and Griffeth (1995) shows that the costs incurred when employees leave the company and the employment for the replacement of staff left, training of new employees and administrative expenditures are significant ones as employees are identified as important organizational assets. Therefore, employee turnover and its effects should be looked into, given that the latter poses a major threat to organizations.
2.1 defining the concept of Absenteeism and Turnover Intention
2.1.1 Absenteeism
Absenteeism occurs when an employee chooses to be absent at his working place during a period where he was supposed to be present and carrying out assigned duties by the organization. (Ramsey and Punnett, 2007). Originated from the Latin word, “absentia”, absenteeism is generally defined as non-attendance of employees from scheduled work (Banks et al. 2012).

However, no standard definition of absenteeism exists. Absenteeism can be defined through various expressions, all permitted by law. Seven strategies of absenteeism were determined by Bennett and Robinson (2000) namely:
•Work for individual issue as opposed to doing your activity
•Arriving late to work without authorization
•Daydreaming as opposed to working
•Performing slower than recommended
•Leaving work ahead of scheduled without approval
•Letting another person finish your work
• Hanging up on your work in order to do extra time
These strategies have different meanings to different people. In the opinion of Avey, Pater ; West (2006), absenteeism can either be involuntary or voluntary. The assumption that employees have chosen to be absent from work is to be made while examining the motivation behind engaging in absenteeism and this raises volition as a crucial feature in the subject matter. As a result, there is a need for distinction between voluntary and involuntary absences which are the two categories of absences from work. Within absenteeism investigation, there is a drive to “purify” the amount of absenteeism as voluntary absence from the job, implying that there is a need for involuntary absence to be seriously excluded to avoid “tainting” the measure (Steel, 2003).

Voluntary Absences
In most studies, voluntary absence is measured as absence frequency (i.e., the number of absence episodes. Even if some researchers find aid for this dichotomy (e.g., Bakker, Demerouti, de Boer, ; Schaufeli, 2003; Chadwick-Jones et al., 1982; Schaufeli et al., 2009), researchers’ accord about the measuring voluntary absence is divided; some argue that absence frequency the same as voluntary absenteeism is fake and misguiding (e.g., Farrell & Stamm, 1988; Shapira-Lishchinsky & Rosenblatt, 2009; ten Brummelhuis, ter Hoeven, de Jong, & Peper, 2013).

While an indispensable voluntary absenteeism is an absence that is utilized as a plan to avoid a situation from worsening, an unneeded voluntary absenteeism however, is a type of absence that a worker could have prevented if he/she was willing to do so (Guttormsen & Saksvik, 2003). Similar studies, known as the `black absenteeism or `illegal absenteeism` were carried out by Sanders and Nauta (2004). This relates to absenteeism whereby the employee does not report to work due to sickness despite being in good health.

Involuntary Absences
Sanders and Nauta, (2004) explained this type of absence as `white absenteeism`. Moreover, many researchers (Guttormsen & Saksvik, 2003; Avey et al., 2006; Chadwick, Nicholson & Brown 1973) classified types of absenteeism as needed (unavoidable) or unneeded (avoidable) absenteeism. A compulsory involuntary absenteeism is whereby a worker is usually unwell or hurt, whereas a needless involuntary absenteeism takes place when a worker has over estimated not harmful symptoms and thus, not report to work.

Authentic leave taken by a worker under unavoidable circumstances, as in cases where the employee is sick for instance, is referred to as involuntary absenteeism. This means that employees having a legitimate excuse for absenting themselves from work would be described as involuntary absence. Such absences are generally planned such that necessary measures and precautions have been taken beforehand so as to cause minimum disturbance in work. Examples of involuntary absences include maternity leave, annual leave, vacation leave, casual leave and any other approved or authorized absences from the workplace.
2.1.2 Turnover Intention
Turnover intention which is described as intentional desire to quit the company (Tett and Meyer, 1993) is considered to be one of the most notable predictors of existing turnover (Griffeth et al, 2000). Voluntary turnover is defined as an action of leaving an organization willingly and involuntarily.

(Bluedon, 1978) Consistent research evidence indicates that employee’s intention to leave the organization can explain the existence of voluntary turnover. And their dissatisfaction at work
Significant aspects were used to study the forecast and understanding of employees’ turnover intention. The key in order to better comprehend turnover comportment and appropriately control it is the study of antecedents of turnover comportment. (Vandenberg and nelson, 1999). There are many factors that affect turnover intention, for example, help from supervisor, satisfaction of doing that job, organizational dedication, stress related to the work and self-respect (Siong et al, 2006). Nevertheless, Firth et al (2004) demonstrated that turnover intention is primarily influenced by employees’ commitment and their dissatisfaction at work.

2.2 Relationship between Turnover Intention and Absenteeism
It is found that the problems of turnover intention and absenteeism are interlinked to a great extent and can be debated jointly since when an employee does not come to work is considered as a small decision to compared to the significant choice he does when leaving the job (Herzberg, Mausner, Peterson ; Capwell, 1957, p. 103). In the light of these discoveries, high tardiness ad absences are meant to be the early stage and leaving the company or being dismissed from job are meant to be the last stage of a lengthy process of leaving (Melbin, 1961, p. 15). This can be illustrated in the figure below:
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3697357281526157435890695 Transfer Transfer PolicyRate
412577329278600
Turnover
Rate
40745654787900
33416386360029324568824000
157435855549Absence Policy Absence Rate

Figure 2: Model of an interdependent perspective
Two presumptions can be derived from the above perspective. Foremost, the existence of a fair interchange between what employees give the company and what they get from the company is of utmost importance in the relationship between the organization and the employee. Secondly, absenteeism and turnover are highly used methods by employees to bring back fairness in their employment bond.

A current tendency in factual research on absenteeism and turnover intention is to do research on these behaviours from the views of social exchange theory (Blau, 1964) and equity theory (Adams, 1965; Walster, and Berscheid, 1978).

2.3 Consequences of Absenteeism and Turnover Intention
In fact, absenteeism affects both production and productivity due to the interdependence between these two. As observed by several researchers (Dalton ; Mesch, 1991; Mayfield ; Mayfield, 2009), absenteeism is a significant cause of worry in any organization.

According to Mowday, Porter and Steers (1982), favourable or unfavourable outcomes may be created by absenteeism as shown in the table below. The feasible constituencies include the individual who is absent from work, individual workmate, the work group and the organization itself.
Table2: Consequences of Absenteeism (Mowday, Porter, and Steers (1982)
FavourableUnfavourableIndividual • Job-related pressure is reduced
•Compliance with standards to be absent
• Meeting of nonwork-part commitment
•Non-work exercises are compensated •Decrease in salary
•Increased in level of injuries
•Changed job appreciation
Workmate •Work diversity
•Talent growth
•Payment for doing overtime •Unwanted extra hours worked
•Work stack is increased
•Fights with the worker who is absent
•Increased in the level of mischances
Work Group •Greater team adaptability in reacting to absenteeism and production problems
•Crew understanding of many jobs •Rise in coordination issues
•Increased in the level of injury
•Fall in efficiency
Employee turnover has become a very important issue in today’s working environment. This problem can have serious consequences upon resource practices of recruitment and selection, training and sustaining the workforce.

Moreover, if a sizeable number of workers leave the company, existing employees will be burdened with greater workload and overtime, which may in turn result to lower employee morale and reduced levels of productivity. It is found that public sector organizations make more use of strict policy to tackle the problem of absenteeism. Nevertheless, the latter have shown not to be effective as authority by itself normally cannot find and deal with the causes of absenteeism. Actually, each worker who is absent is likely to justify himself and legitimacy of his actions through reasons, whether these are genuine ones or not.

2.4 Measurement of Absenteeism and Turnover Intention
Among the first ones to utilize multiple indices of absenteeism was Behrend’s (1951) research. The unique, most troubling issue related with absenteeism as significant idea involves the computation of absenteeism. According to Gaudet (1963), before, there were not less than 41 different evalautions of absenteeism that have been used. The psychometric properties of the different indicators of absenteeism have been analysed by not many studies.

2.4.1 Indices of Absenteeism / Scale of Voluntary Absenteeism
• Indices of Absenteeism
Seven indices of absenteeism were analysed by Chadwick-Jones et al. (1971) namely:
Worst day
Rate of occurrence
Attitudinal
Time lost-amount of scheduled work days missed in a week for any reason other than leave
Alternative causes-amount of scheduled work days missed in a week for any causes other than day off or proven illness
Tardiness-amount of occasion of lateness in any week
Blue Monday-the amount of absence on a Monday less the amount of absences on a Friday for whichever week
The trouble faced in considering conclusions from absenteeism researchers will remain until significant attention is given to the measurement of absenteeism.

•Scale of Voluntary Absenteeism
The questionnaire provide measures of the following variables for the scale of voluntary absenteeism intention asd follows:
I think a lot about being absent from work
I intend to be absent from work on one or more days within the next two months
As soon as possible, I will absent myself from work
2.4.2 Indices of Turnover Intention
The computation of turnover intention is normally based on questionnaire by Rosin and Korabick’s Turnover Intention Scale ( Tannover, 2005). All the components are marked on a deconstructed rating scale, varying from “strongly disagree” to “strongly agree”.

2.5 The Conceptual Framework
In the opinion of (Hackman & Oldham, 1975), low worker turnover rate, low absenteeism percentage and increasing production capacity are the results of higher job satisfaction. Thus, this conceptual framework should foremost look upon the effect of transformational leadership styles, job/fit adaptation and job stress on job satisfaction.

This is so, because these three dimensions have a direct impact on job satisfaction rather than directly on turnover intention and absenteeism intention. Here, job satisfaction acts like a mediating variable between transformational leadership styles, job/fit adaptation and job stress with turnover intention and absenteeism intention.

The proposed framework is as follows:
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Transformational Turnover
37869962768362639683793030204446079303Leadership Styles Intention
1639027670300
263968317899827254328415600 Job Fit/Adaptation
172528374163Job Satisfaction
433881121386263968321386263904821386
4455795208585002755901510700
2034540187960 Job StressAbsenteeism Intention
Figure 3: Proposed Framework
2.5.1 Defining Job Satisfaction
Job satisfaction is described by Locke (1976) as a favourable psychological state from the assessment one’s job. By considering feelings, point of views and conducts, workers develop their attitude towards their job (Robbins, 2005; Akehurst, Comeche, ; Galindo, 2009). Spector (1985) observed that employees are more pleased with their jobs if they find their job satisfying and remunerating. Lee and Ahmad (2009) discovered that the level of job satisfaction greatly influences lateness, low confidence, levels of work disappointment, cooperation in basic leadership and high turnover. These in turn influence the general production of the company (Klein Hesselink, Kooij-de Bode, ; Koppenrade, et al).

2.5.2 Transformational leadership styles and Job satisfaction
Researchers view transformational leadership as a device to improve follower contentment by empowering worker’s growth, collaboration and encouraging determination ( Avolio, 1999). Among numerous determinants of work contentment, the supervisor or leaders of a worker has the highest impact on whether the worker will be satisfied with his job or not (Avolio, Bass & Jung, 1999; Mardanov, Heischmidt, & Henson, 2008). From the different styles of leadership, current study proposes that transformational leadership (Bass, 1985) has a more positive influence on job satisfaction of employees compared with other leadership styles (Awamleh & Gardner, 1999; Bogler, 2001; Cicero & Pierro, 2007; Top, Tarcan, Tekingunduz, & Hikmet, 2013; et al).

Basically there are four interrelated behavioural segments of idiolized impact of transformational leadership which consists of:
fascinating role model
individualized thought
inspiration that expresses an engaging vision
smart encouragement that stimulates imagination and development (Bass & Avolio, 1994)
The equivalent literature shows that features of transformational leadership have favourable effects on job satisfaction (Judge & Bono, 2000; Krishnan, 2012). Especially, intellectual incitement drives workers to see their job as more fascinating because of increased self-comprehension and development (Jung & Sosik, 2002). Leader charisma produces faithfulness and thankfulness from supporters (Bass & Avolio, 1994) and inspirational motivation drives workers to feel associated with their duties and comprehend the vision of the company (Kerfoot, 2001). Individualized thought includes kind administration through individual consideration and treatment (Slater, 2003). From these factors, we expect that the employee will feel higher job satisfaction when the follower perceives his or her leader as more transformational.

H1a: there is a positive relationship between transformational leadership styles and satisfaction.

2.5.3 Job Fit/Adaptation and Job satisfaction
The attraction-selection-attrition (ASa) framework (Schneider, 1987) is a principal structure that helps to describe how Person-Organisation (P-O) fit might conduct to the aim to move. The fundamental thought of this structure is that companies lure, select and hold those individuals who share their goals and target. Besides, individuals are well chosen to form part of the company and stay in the event that they fit with the company or qui if they do not fit. That is, the ASA structure hypothesizes that fit will surely lead to retention (Schneider, 1987; Schneider et al., 1995) and is sustained by numerous studies outside of (e.g Hoffman and Woehr, 2006; wheeker et al., 2007) and inside the educational context (e.g Pogodzinski et al., 2013; Skaaalvik and Skaalvik, 2011). As far as the connection between P-O fit and job satisfaction, Kristof (1996) estimated that the greater the level of P-O fit, the more fulfilled workers will be in their work. Moreover, Chatman (1991) theorized that job satisfaction brings retention, which has likewise been supported within instructive writing (e.g Perrachione et al., 2008). In this way, the following hypothesis is drawn:
H1b: There is positive relationship between job fit and job satisfaction.

2.5.4 Job Stress and Job Satisfaction
Employment life is one of the essential part of our everyday lives which create a lot of stress. According to Beehr (1995) work stress is characterized as a “circumstance in which a few characteristics of the work circumstances are thought to cause poor mental or physical health, or to cause risk factors making poor health more probable.”
According to Stamps & Piedmonte (1986), there is a significant relationship between job satisfaction and job stress. Vinokur-Kaplan (1991) expressed that work factors such as workload and working conditions has a negative relationship with job satisfaction. Fletche & Payne (1980) distinguished that an absence of satisfaction can be a reason for stressing, while high satisfaction can reduce the level of stress. This examination uncovers that, both of employment stress and job satisfaction were observed to be interrelated. On basis on the above discussion and stipulated links, the following hypothesis can be deduced:
H1c: There is negative relationship between job stress and job satisfaction.

2.5.6 Job Satisfaction, Turnover Intention and Absenteeism Intention
In the point of view of Oshagbemi, (2003) one of the main roles of managers who are in the human resource department is to ensure that their workers are pleased and happy.

• Job Satisfaction and Turnover Intention
A research by Ali stated that not catering for employees’ dissatisfactions might be hampering a dissatisfied employees would eventually leave the organizations and in so doing, the knowledge brought in by him will be lost. An examination directed by Hay. M (2001) discovered that most of the workers consider profession openings, learning and growth as the prime variables prompting job satisfaction and which incite them to remain in a company. In addition, the organization could be stuck in a vicious cycle of turnover rate if ever the new replacement employees’ dissatisfaction is not considered as well.

Thus, based on the above discussion, the hypothesis drawn is as follows:
H2: There is a negative relationship between job satisfaction and turnover intention.

•Job Satisfaction and Absenteeism Intention
In the point of view of Hanisch and Hulin (1991) absenteeism and the other withdrawal practices (e.g. tardiness, turnover) indicate “unseen” point of views such as work disappointment, fall in organizational dedication or an aim to leave the job. From this point of view, an employee who is not present to work is deliberately or unknowingly portraying unfavourable connection towards the company. Furthermore, for a poorly dedicated or disappointed worker, absenteeism can play a positive part (Rosse & Miller, 1984). It might give the latter a chance to stay away from the negative feelings linked with the job. Conversely, workers who are exceedingly happy with their occupations or firmly dedicated to the company will evade withdrawal practices and keep up continued connection to work. (Blau & Boal, 1987). Thus, these literatures direct to the following hypothesis:
H3: there is a negative relationship between job satisfaction and absenteeism intention.

2.6 Conclusion
In the light of the above, it can be rightly stated that absenteeism and turnover intention is far from being a simple phenomenon. Its complexity is due to its interconnection with a plurality of causes as well as its negative impacts on community, monetary and especially, organizational efficiency. The human science for work evaluates absenteeism as the record of a poor organizational atmosphere and of a broken and demotivating organization. Thus, absenteeism and turnover intention can be considered as a sociological occurrence straightforward associated with the individual and friends conduct and to the usual work state. Therefore, creating a healthy job environment conducive to satisfied and motivated employees is essential for a fall in absenteeism and turnover level while the inverse conditions such as dissatisfaction and a lack of organization directions which support the occurrence should be avoided.

CHAPTER 3
RESEARCH METHODOLOGY
3.0 Introduction
In the opinion of Collis and Hussey (2009), methodology is interpreted as the global stratagem administered to the entire progress of the study which is being researched. Questionnaire survey at the DCS was carried out to collect data on turnover intention, prior voluntary absenteeism, voluntary absenteeism, leadership styles, job stress, adaptability and job satisfaction. In order to test to which extent these components have an impact on absenteeism, both qualitative and quantitative methods will be combined and used for this study.

3.1 Research Approach
Bryan & Bell (2007) explained that there are two exploration methods namely deductive (quantitative) methods and inductive (qualitative) methods.

? Numerical data collected through questionnaire was involved when using the quantitative approach. Questionnaire is the instrument that accumulates data from an extensive number of respondents in this way, thus allowing a more inclusive knowledge of the situation. Here, investigators construct their study on hypothesis.

? Qualitative approach helps in giving a rich and right presentation of people’s know-hows, attitudes and beliefs. Through the use of this strategy, authentic data about individuals’ states of mind, ancient, current and future practices ca be obtained. Using the individual interview, it was conceivable to clear up things which were not clarified toward the participants and furthermore to follow the progression of the enquiries.

3.2 Determine Data Collection Methods
Data collected can be of two categories of information sources namely:
Primary information
Secondary information
3.2.1 Primary Data
Primary data can be gathered through perceptions, reviews, individual meetings, telephone interviews and self-managed questionnaires. A questionnaire was used for this study. The questionnaire has been devised, pre-tested, reconsidered and conducted to the workers of the DCS. The questionnaire was picked in view of its flexibility that is practically every issue of the research can be approached from the questionnaire point of view and as such, it would be easier to access the respondents.

3.2.2 Secondary data
The compilation of the literature reviews were the main secondary data used in the research. The secondary data utilized originated from productions of different authors, magazines, diaries, web and reports.

3.3 Design Data Collection Forms
In view of existing writing on the element factors of turnover intention, voluntary absenteeism intention, prior voluntary absenteeism, leadership styles, fit/adaptation, job stress and job satisfaction, the questionnaire was planned. A 7 point Likert scale has been utilized to accumulate information since it would be less confusing for the respondents to answer. Likert scale has settled options from which the respondents needs to choose one answer per statement. It is simple and reasonable to utilize. The questions were sated in a basic way; no specialized terms were utilized, in view to advance a superior comprehension of what was inquired.

3.4 Questionnaire Structure
There were eight sections which were used in this questionnaire namely:
Section A: Turnover Intention
Here, questions were set to be able to pick up knowledge in the matter of whether the employees are considering to leave the organisation or not.

Section B: Voluntary Absenteeism Intention
This section has been created to know if the employees are being absent intentionally and do they think a lot about being absent from work.

Section C: Prior Voluntary Absenteeism
In this section, information has been gathered about whether during the past 12 months employees have been absent once or more because of absence of motivation.

Section D: Leadership Styles:
Numerous researches have utilized the multi factor management methods to test different leadership styles. Nevertheless, in order to devise the questionnaire less demanding to be replied; just transformational leadership style was considered which comprises of:
? A person’s charm that can inspire devotion-charisma
? Designated to fit the special needs of a particular person-individualized
? Critical thinking (intellectual) incentive (stimulation).

Section E: Fit/Adaptation
The rationale of this section is to gather data about regardless of whether employees can adjust in the workplace and fit with the organisation’s culture.

Section F: Job Stress
This segment was developed to know whether employees are being influenced adversely or not because of work conditions, unrecognition for their performance and failure to use their capabilities and abilities to the highest at work.

Section G: Job satisfaction
This section was utilized to evaluate personal development, reward and job prospect, working conditions and relationship at work.
Section H: Respondent’s profile
The final part collected some demographic and individual data about the respondents, which was used for the research. It comprised of 8 questions which depended in gender, age group, level of operation, status, division where posted, length of service, highest educational level and income group.

3.5 Pilot Testing
Michael J Campbell (2004) stated that pilot study can be alluded to as an untimely kind of the principal research which is anticipated as smaller than normal to know if the components of the principal research would all be able to cooperate. Before utilizing the questionnaire to gather data and information, a pilot testing was undertaken in order to distinguish if there were any inadequacies. Comment was collected from the participants if at any point they came across troubles in noting the questionnaire and whether the questions were justifiable and understandable. A specimen of 10 respondents was used for the pilot test. The discoveries allow to check the following:
? Number of time the questionnaire has taken to finish?
? Whether the directions were sufficiently straightforward?
? Which questions made the participant uncomfortable and hesitant to reply?
? Which polls were not straightforward and dubious?
3.6 Target population, Sample Design and Data Collection
? Target Population
As indicated by Saunders et al (2008, p. 212), population is characterized as “the full arrangement of cases from which a sample is taken.” The employees of The DCS are the targeted population in this study. The population component was any employee from the various departments of The DCS which are as follows:
Departments Number of Employees
Administration Department 77
Finance Department 11
Public Infrastructure Department 66
Land Use ; planning Department 9
Public Health Department 157
Welfare Department 6
Table 3: Targeted Population

The sample units were chosen arbitrarily inside every stratum after having acquired the total list of all staffs in the different divisions. Despite being the employees of the DCS, there are many workers who work outside the office such as refuse collector, burial ground attendant, field supervisor and others. Therefore, it would have been difficult to meet them. As a result, 100 questionnaires were administered to employees as follows: 40 to the administration department, 11 to the finance department, 20 to the public infrastructure departments, 9 to the land use ; planning department, 15 to the public health department and 5 to the welfare department.

? Sample Design
For this study, probability sampling was utilized whereby all components in the population have a similar chance to be chosen in the sample. The stratified sampling technique was used to decide the content of the targeted population. Simon (2008) states that a stratified random sampling is a substitute to a simple random sample that gives more exactness. In a stratified random sample, considerable pools of objects were separated into different groups (strata) and subjects were chosen at random from each group.

? Data Collection
The agreed copies of the questionnaire which are included in Appendix were therefore given to 100 employees of all the departments of The District Council of Savanne. A period of one week was given to the participants in order to fill in the questionnaire. Out of the 100 questionnaires submitted, only 70 were returned.

3.7 Data Processing and Analysis
After the gathering of information, the data has been prepared and it has been done using Microsoft Excel and the SPSS programming. Information have been entered and coded. After this progression, the information were tested for reliability through Cronbach Alpha Testing.

Preceding the analysis stage, the crude information must be revised, summarised and classified in a respectable and explicit form. Moreover, adjustment and check were likewise done to ensure finish, dependable and true information. Quantitative data was recovered from devices, for example, SPSS through test, for instance, Pearson connection, Multiple Regression which aided in investigating connections between various factors. This is in accordance with related studies (Hassan, 2009; Norazah, 2015). In addition, one way anova and independent sample t-test were done for the testing for difference. These information investigations are additionally talked about more clearly in the fourth chapter. Lastly, results of the study were exhibited in types of bar chart, pie chart and frequency tables.

3.8 Limitations of the research
The issues which were experienced when gathering data and pre analysis of the questionnaires were done are as follows:
? Some respondents were hesitant to take part in the survey and out of the 100 questionnaires which were circulated, only 70 were returned.

? Every one of the respondents was given one week to fill in the questionnaire; however a large portion of them filled in the survey when the gathering was being made.

3.9 Ethical Considerations
It is pivotal to guarantee that great study morals are kept when doing the research since virtue is esteemed in studies. In the opinion of Cooper and Schindler (2003) morals in study ensure that no damage should be caused or endured by different participants with respect to the research. Indeed, an unbending code of morals was taken after to shield against the latter. Namelessness and secrecy of the members were conserved and this was conveyed to them in advance both verbally and in composed (incorporated in questionnaire).

3.10 Conclusion
This chapter defined the methodology used for questionnaire design and the exploration approach used for gathering information. A description of the statistical tool was utilized for testing and analyzing the hypotheses and the questionnaire. The issues cropped and experienced during the research process and constraints were highlighted and the moral contemplations were underlined.

CHAPTER FOUR
ANALYSIS OF FINDINGS
4.0 Introduction
This chapter involves the scrutiny of raw data which has been compiled through distribution of questionnaires to the employees of The District Council of Savanne. SPSS was used to depict information. Legitimate demonstration and explanation was executed with the use of pic graphs, bar charts and by utilizing proper theory for the statistical tests adopted. Only 70 questionnaires were taken into consideration.

4.1 Demographic factors
The demographics factors namely age group, gender, status, at what level do you operate in the organisation, section/department where posted, duration of service, highest educational level and income group were collected so as to know the characteristics of the respondents.

4.1.1 Age group
As shown in the figure, the majority employees were in the age group of 26 to 33 and 34 to 41.
While 16 respondents were in the age group of 18 to 25, 5 answerers were in the age group of 42 to 49. Lastly, above 50 years old, only 13 respondents were obtained.

Age Group Number of participants %
18-25 16 22.9
26-33 18 25.7
34-41 18 25.7
42-49 5 7.1
50 and above 13 18.6

4.1.2 Gender
As shown in the above figure, male participation in this survey is 51.4 % while that of female is 48.6 %.

Gender Number of respondents %
Female 34 48.6
Male 36 51.4
4.1.3 Status
The study declared that 65.7 % of the employees are married. This might be clarified by the way that in the majority of the family units in Mauritius both the couple works to earn a living.
31.4 % of the employees were found to be single while 2.9 % were divorced as illustrated in the figure below.

Status Number of respondents %
Single 22 31.4
Married 46 65.7
Divorced 2 2.9
Widowed 0 0

4.1.4 At what level do you operate in the organisation?
The table below distinctly shows that 47.5 % of the respondents are from the operational level. 11.4 % were allocated to supervisory and senior management level. Middle management level was 28.6 % and the least was 2.9 % that of manual grade level. The information can be displayed as below.

Level of Operation Number of respondents %
Manual Grade Level 2 2.9
Operational Level 32 45.7
Supervisory Level 8 11.4
Middle Management Level 20 28.6
Senior Management Level 8 11.4

4.1.5 Department/ Section where posted
The majority of the respondents were from the administration department as displayed in the figure below. 15.7 % were from the finance department while 10.0 % were from the public health department. The percentage seemed to decrease as from the public infrastructure section from 8.6 % to the welfare department reaching a percentage of only 5.7.

Department Number of respondents %
Administration 37 52.9
Finance 11 15.7
Planning 5 7.1
Public Health 7 10.0
Public Infrastructure 6 8.6
Welfare 4 5.7

4.1.6 Length of Service (Years)
The figure below specifies the duration of service of the participants. The maximum participants have works less than 7 years. 10.0 % of the participants have work experience more than 30 years.

lefttop
Duration of service Number of participants %
Less than 7 22 31.4
8 to 15 19 27.1
16 to 23 14 20.0
24 to 31 8 11.4
32 and above 7 10.0

4.1.7 (1) Highest Educational Level
The education history of the participants can be illustrated in the figure below. Most of the participants have acquired a degree pointing out that they have an effective educational history. 8.6 % specifies that some of the participants have got the primary certificate while 20 % of them have studied till higher certificate level.

Level of Study Number of participants %
Primary 6 8.6
Secondary 14 20.0
Tertiary 49 70.0
Technical/Vocational 1 1.4
(2) If Other Educational Level, Specify
4 respondents were found to have other educational level such as ACCA as illustrated in the figure below. The other 66 respondents did not have other educational level apart from primary to technical educational background. It can be revealed in the above figure.

Qualification Number of respondents %
Others (Primary to Tertiary) 66 94.3
ACCA 1 1.4
ACCA Level One 1 1.4
ACCA Level Two 2 2.9

4.1.8 Income Group
The above figure describes the income group of participants. Most of the participants’ salary lies between 10001 and 20000. With the acquired results, it can be shown that the employees at the DCS do obtain a good salary.

Income Group Number of participants %
Below 10000 1 1.4
10001 to 20000 26 37.1
20001 to 30000 20 28.6
30001 to 40000 17 24.3
40001 and above 5 7.1
4.2 Reliability
The Cronbach Alpha for every variable has been computed so as to measure their reliability. Figures greater than 0.70 were viewed for Cronbach’s Alpha ( Nunally , 1978 referred to in Hair et al., 2006). As it can be noted from the table underneath, the Cronbach Alpha is higher than 0.7. Consequently, the estimation scale is reliable.

Cronbach Alpha Summary Table
Section Cronbach Alpha
A: Turnover Intention 0.938
B: Voluntary Absenteeism Intention 0.796
D: Leadership Styles
D.1: Charisma/Inspiration
D.2: Individualised Consideration
D.3: Intellectual Stimulation 0.901
0.787
0.864
E: Fit/Adaptation 0.929
F: Job Stress 0.849
G: Job Satisfaction
G.1: Personal Development
G.2: Reward and Job Prospect
G.3: Working Conditions
G.4: Relationship at work 0.930
0.905
0.759
0.948

4.3 Exploratory Factor Analysis (EFA)
The EFA was done with an aim to evaluate the effectiveness of the 35 items. To confirm the appropriateness of the EFA, the Kaiser-Meyer-Olkin (KMO) test and Bartlett’s of Sphericity were performed. The KMO which is adopted to compute the sampling adequacy had the range of 0.500 to 0.834. On the other hand, the test of sphericity which measures the null hypothesis was rejected for all 11 constructs as it was below 0.05. Below are the results of factor analysis for the constructs.

Table: EFA for Charisma/Inspiration
Factors (Eigenvalue : %
variance explained) Dimensions Factor
Loading
1709419282575Charisma/Inspiration
1728470104457500 ( 2.679, 66.9%) Superior gets staff to cooperate
Superior motivates employee to talk about
Instruction
Objectives in my organisation provides me a sense
-7810519684900of direction
Aims set by superior are well understood 0.562
0.887
0.857
0.917
KMO 0.728 Barlett’s Test of Sphericity0.000 As per the table, the value for KMO 0.728 is acceptable. Having factor loadings above 0.50 indicates that the factor contribute to the variable.

Table: EFA for Individualised Consideration
Factors (Eigenvalue : %
variance explained) Dimensions Factor
Loading
Individualised Consideration
172846913239751728470104457500(3.560, 71.2%) -59690282575Superior lets me know what is expected
Superior considers my suggestions
Superior lets me know when I am doing a good
-6858018859500 job
Superior provides feedback on job performance
Superior treats me with respect 0.864
0.859
0.908
0.832
0.747
KMO 0.837 Barlett’s Test of Sphericity0.000
In accordance with the table, the greater the factor loading is, the higher contribution will be to the variable. And in this case factor loading of 0.747 to 0.908 gives a clear indication that it has a big impact on the variable. The KMO being 0.837 is acceptable.

Table: EFA for Intellectual Stimulation
Factors (Eigenvalue : %
variance explained) Dimensions Factor
Loading
1709419282575 Intellectual Stimulation
1728470104457500 (2.589, 86.3%) Employees take part in decision making
Opportunities are given to help developing
the organisation’s enhancement plan
Superior motivates me to come up with new
thoughts 0.886
0.939
0.960
KMO 0.707 Barlett’s Test of Sphericity0.000 No items were deleted pertaining to intellectual stimulation as per the table as the factor loading is above 0.05. Having factor loading above 0.90 shows that the values are superb. 0.707 is an acceptable KMO.

Table: EFA for Job Fit/AdapationFactors (Eigenvalue : %
variance explained) Dimensions Factor
Loading
1709419282575 Fit/Adaptation
1728470679450 (3.281, 82.0%) My job utilizes my skills and talents well
-6858061595000I like my work schedule (e.g, flextime, shift)
I fit with this organisation’s culture
I like the authority and responsibility I have at this organisation0.862
0.864
0.971
0.921
KMO 0.760 Barlett’s Test of Sphericity0.000 As stated in the table, with an eigenvalue of 3.281 and 82.0% of total variances, the table indicates that all items loadings ranged between 0.862 and 0.971. In other words, this is a good sign. Thus, retention of all items of the independent variable for future scrutiny.

761936520383500071240651648460Table: EFA for Job Stress
Factors (Eigenvalue : %
variance explained) Dimensions Factor
Loading
Job Stress
172847051117500 (1.737, 86.9%) Conditions at work are unpleasant or
sometimes even unsafe
I feel that my job is negatively affecting
my physical or emotional well being 0.932
0.932
KMO 0.500 Barlett’s Test of Sphericity0.000 The table describes 86.9 % of the total variances in job stress with an eigenvalue of 1.737. Likewise, retention of all items was made since they all loaded significantly with values of 0.932.

Table: EFA for Personal Development
Factors (Eigenvalue : %
variance explained) Dimensions Factor
Loading
Personal Development
171894550165000(2.155, 71.8%) Level of satisfaction related to the degree of
independence
Level of satisfaction with the chance to learn
-59056290830new skills
Level of satisfaction with flexible schedule 0.814
0.865
0.864
KMO 0.702 Barlett’s Test of Sphericity0.000 In the above table, the existence of three dimensions with Eigenvalues of more than 1 is revealed, explaining 67 %. Factor loading being high enough shows that the factor contributes a lot on the variable.

Table: EFA for Reward and Job Prospect
Factors (Eigenvalue : %
variance explained) Dimensions Factor
Loading
Reward and Job Prospect
171894599822000 (2.468, 82.3%) Level of satisfaction with monetary rewards
(Pay)
Level of satisfaction with your chance for
Promotion
Level of satisfaction with chances to make use
of your skills and talents-6858061595000 0.894
0.919
0.907
KMO 0.745 Barlett’s Test of Sphericity0.000 As shown by the above table, items were retained as the factor loading is way beyond 0.05. Moreover, the items of reward and job prospect had an eigenvalue of 2468 explaining a total variance of 82.3 %. This is considered as a meaningful factor as per Gaur et al., 2009.

8503920201930000Table: EFA for Working Conditions
Factors (Eigenvalue : %
variance explained) Dimensions Factor
Loading
Working Conditions
172847047307500 (2.063, 68.8%) Level of satisfaction with hours worked each
week
-6858023495000Level of satisfaction with location of work
Level of satisfaction with amount paid vacation
Time/sick leave offered 0.909
0.675
0.885
KMO 0.606 Barlett’s Test of Sphericity0.000 As claimed by the table, 68.8 % of total variances in working conditions were accounted for with an eigenvalue of 2.063. The table also denoted that ll loadings had a range between 0.675 and 0.909. All the items of the independent variable were kept.

Table: EFA for Relationships at work
Factors (Eigenvalue : %
variance explained) Dimensions Factor
Loading
Relationships at Work
172847051117500 (1.777, 88.8%) How satisfied are you with our relationships
591883522098000with co-workers
How satisfied are you with your relationship
with supervisor 0.943
0.943
KMO 0.606 Barlett’s Test of Sphericity0.000 According to the above table, no items were cut out relating to the dependent variable job satisfaction since all item loadings were 0.943 exceeding 0.40, a conception put forward by Hair et al. (2010).

4.4 Descriptive Statistics
The descriptive statistical evaluation were conducted for all the statements of the turnover intention and absenteeism intention as well as for leadership styles, job fit, job stress and job satisfaction. The mean and standard deviation (SD) for every single item were computed which were assessed on a 7 point-Likert scale, representing 1 as strongly disagree (strongly disagree/strongly dissatisfied, to 7 as being strongly agree/strongly satisfied). Computation of composite score was also carried out.

Table: Turnover Intention
Statements Mean SD Strongly
Disagree Slightly
Disagree Disagree Neutral Agree Slightly
Agree Strongly
Agree
I think a lot about
leaving the
organisation3.59 1.655 14.3% 8.6% 31.4% 14.3% 15.7% 12.9% 2.9%
I am actively
searching for an
alternative to the
organisation3.64 1.579 11.4% 12.9% 22.9% 18.6% 25.7% 4.3% 4.3%
As soon as it
is possible, I
will leave the organisation3.39 1.600 15.7% 12.9% 27.1% 17.1% 20.0% 2.9% 4.3%
Composite Score
Score 3.54 1.61 According to the Table, the ‘I am actively searching for an alternative to the organisation’ is giving a radically higher importance than others with the highest mean of 3.64 and standard deviation of 1.579 while the statement’.

As soon as it is possible, I will leave the organisation and ‘I think a lot about leaving the organisation’ had the least contribution. The overall mean for Turnover Intention is 3.54 with 1.61 as standard deviation.

Table: Absenteeism Intention
Statements Mean SD Strongly
Disagree Slightly
Disagree Disagree Neutral Agree Slightly
Agree Strongly
Agree
I intend to be absent (unexcused) from work on one or more days within the next two months 3.33 1.327 10.0% 11.4% 44.3% 8.6% 21.4% 4.3% –
I think a lot about being absent from work
3.51 1.567 11.4% 15.7% 24.3% 20.0% 20.0% 4.3% 4.3%
As soon as it
is possible, I
will absent myself from work 2.86 1.365 24.3% 11.4% 32.9% 18.6% 11.4% 1.4% –
During the past 12 months, I have been absent once or more due to lack of motivation 3.91 1.380 7.1% 8.6% 25.7% 7.1% 47.1% 4.3% –
Composite Score
3.40 1.41 The above table clearly shows that all the statements of absenteeism intention are of moderate consideration since all their means are less than 4. Nevertheless while the statement “During the past 12 months I have been absent once or more due to lack of motivation” has a high mean of 3.91, the statement “As soon as possible, I will absent myself from work” has the lowest mean of 2.86.

Table: Charisma/Inspiration
Statements Mean SD Strongly
Disagree Slightly
Disagree Disagree Neutral Agree Slightly
Agree Strongly
Agree
Superior gets staff to cooperate 4.80 0.894 – 1.4% 10.0% 10.0% 67.1% 8.6% 2.9%
Superior motivates employees to talk about instruction 4.61 0.822 – 1.4% 8.6% 24.3% 60.0% 4.3% 1.4%
Objectives in my organisation provides me a sense of direction 4.61 1.171 4.3% – 7.1% 25.7% 48.6% 10.0% 4.3%
Aims set by superior are well understood 4.63 1.144 1.4% 2.9% 15.7% 7.1% 61.4% 7.1% 4.3%
Composite Score
Score 4.66 1.00 The table for charisma/inspiration concluded that all the statements do have a consequence on turnover intention and absenteeism turnover with mean above 4. On one hand, the statement “Superior gets staff to cooperate” had the highest contribution with a high mean of 4.80 and standard deviation of 0.894. Also, the statement “Superior motivates employees to talk about instruction and objectives in my organisation provides me a sense of direction” had the least contribution.

Table: Individualised Consideration
Statements Mean SD Strongly
Disagree Slightly
Disagree Disagree Neutral Agree Slightly
Agree Strongly
Agree
Superior lets me know what is expected 4.99 0.852 – – 8.6% 7.1% 62.9% 20.0% 1.4%
Superior considers my suggestions 4.91 1.087 – 1.4% 11.4% 15.7% 41.4% 25.7% 4.3%
Superior lets me know when I am doing a good job 5.10 1.052 – – 8.6% 11.4% 54.3% 12.9% 12.9%
Superior provides feedback on job performance 5.19 1.146 1.4% – 7.1% 8.6% 48.6% 21.4% 12.9%
Superior treats me with respect 5.45 1.051 – 1.4% – 10.1% 52.2% 13.0% 23.2%
Composite Score
Score 5.128 1.03 The table shows that the five statements influenced heavily in determining the main variables since the mean was over 4.50. The statement “Superior treats me with respect” showed the highest influence on turnover intention and absenteeism intention as it has a mean of 5.45 and standard deviation of 1.051. To summarise, individualized consideration was found to have an overall mean of 5.13 with SD of 1.03 implying that most of the respondents have a high view of individualized consideration.

Table: Intellectual Stimulation
Statements Mean SD Strongly
Disagree Slightly
Disagree Disagree Neutral Agree Slightly
Agree Strongly
Agree
Employees take part in decision making 4.24 1.488 8.6% 2.9% 18.6% 12.9% 44.3% 8.6% 4.3%
Opportunities are given to help developing the organisation’s enhancement plan 4.56 1.293 4.3% – 17.1% 15.7% 44.3% 14.3% 4.3%
Superior motivates me to come up with new thoughts 4.44 1.510 5.7% 2.9% 20.0% 12.9% 38.9% 11.4% 8.6%
Composite Score
Score 4.41 1.43 All the above statements had a fair contribution towards depicting the intellectual stimulation at the DCS. However, while the statement “Opportunities are given to help developing the organisation’s enhancement plan” had the highest mean of 4.56 and standard deviation of 1.293, the statement “Employees take art in decision-making has least contributed with mean 4.24 and standard deviation 1.488.

Table: Job Fit/Adaptation
Statements Mean SD Strongly
Disagree Slightly
Disagree Disagree Neutral Agree Slightly
Agree Strongly
Agree
My job utilizes my skills and talents well 5.04 1.221 – 1.4% 14.3% 7.1% 45.7% 18.6% 12.9%
I like my work schedule (e.g, flextime, shift) 4.86 1.376 2.9% – 18.6% 5.7% 44.3% 17.1% 11.4%
I fit with this organisation’s culture 5.06 1.062 – – 8.6% 17.1% 44.3% 20.0% 10.0%
I like the authority and responsibility I have at the organisation5.07 1.094 – – 11.4% 8.6% 54.3% 12.9% 12.9%
Composite Score
Score 5.00 1.19 Regarding the variable job fit/adaptation, it is surely understood from the above table that all the above statements contributed reasonably in identifying the job fit of employees at the DCS with a maximum mean more than 5. With the composite score of 5.00 and 1.19, approximately all employees are well adapted in the organisation.

Table: Job Stress
Statements Mean SD Strongly
Disagree Slightly
Disagree Disagree Neutral Agree Slightly
Agree Strongly
Agree
Conditions at work are unpleasant and sometimes even unsafe 3.60 1.527 7.1% 17.1% 31.4% 11.4% 21.4% 8.6% 2.9%
I feel that my job is negatively affecting my physical or emotional well being 3.53 1.491 7.1% 18.6% 30.0% 15.7% 18.6% 7.1% 2.9%
Composite Score
Score 3.97 1.42 The statistics in the above table of job stress points out that all the two statements related to job stress had quite an effect. In fact, the indicator “Conditions at work are unpleasant or sometimes even unsafe” is the highest with mean 3.60 and standard deviation 1.527. Besides, there was a slight difference in the highest and lowest mean. To conclude, job stress had an overall mean of 3.97 with standard deviation of 1.42.

Table: Personal Development
Statements Mean SD Strongly
Dissatisfied Slightly
Dissatisfied Dissatisfied Neutral Satisfied Slightly
Satisfied Strongly
Satisfied
Level of satisfaction related to the degree of independence 4.84 1.002 – 4.3% 7.1% 10.0% 58.6% 18.6% 1.4%
Level of satisfaction with the chance to learn new skills 4.76 1.256 2.9% 4.3% 8.6% 10.0% 50.0% 21.4% 2.9%
Level of satisfaction with flexible schedule 4.71 1.169 – 4.3% 14.3% 15.7% 38.6% 25.7% 1.4%
Composite Score
Score 4.77 1.142 The table clearly shows that all the statements of personal development are of huge consideration since all their means are more than 4. Personal development had an overall mean of 4.77 with a standard deviation of 1.14.

Table: Reward and Job Prospect
Statements Mean SD Strongly
Dissatisfied Slightly
Dissatisfied Dissatisfied Neutral Satisfied Slightly
Satisfied Strongly
Satisfied
Level of satisfaction with monetary rewards (Pay) 4.89 1.257 4.3% 1.4% 7.1% 7.1% 52.9% 22.9% 4.3%
Level of satisfaction with your chance for promotion 4.69 1.470 7.1% – 12.9% 12.9% 35.7% 27.1% 4.3%
Level of satisfaction with chances to make use of your skills and talents 4.80 1.400 4.3% – 15.7% 10.0% 40.0% 21.4% 8.6%
Composite Score
Score 4.80 1.38 The statement “Level of satisfaction with monetary rewards (Pay)” had the highest contribution with a high mean of 4.89 and standard deviation of 1.257. In addition, the statement “Level of satisfaction with your chance for promotion” had the least contribution.

Table: Working Conditions
Statements Mean SD Strongly
Dissatisfied Slightly
Dissatisfied Dissatisfied Neutral Satisfied Slightly
Satisfied Strongly
Satisfied
Level of satisfaction with hours worked each week 4.79 1.166 1.1% 2.9% 10.0% 15.7% 44.3% 22.9% 2.9%
Level of satisfaction with location of work 4.39 1.662 8.6% 5.7% 15.7% 11.4% 32.9% 18.6% 7.1%
Level of satisfaction with amount of paid vacation time/sick leave offered 4.90 1.181 1.4% 1.4% 8.6% 18.6% 41.4% 21.4% 7.1%
Composite Score
Score 4.70 1.34 The “Level of satisfaction with amount of paid vacation time/sick leave offered” is giving a higher importance than others with the highest mean of 4.90 and standard deviation of 1.181 while the statement “Level of satisfaction with location of work” had a lower contribution. The overall mean of working conditions is 4.70 with standard deviation of 1.34

4.5 Correlation Testing
4.5.1 Pearson Correlation (PC)
To measure the relationship between the variables, a bivariate correlation (Pearson) was performed. The results are shown as below:
Variables Job Satisfaction
Transformational Leadership Styles r = 0.773
Sig = 0.0000
Job Fit/Adaptation r = 0.705
Sig = 0.0000
Job Stress r = 0.525
Sig = 0.0000
The relationship between transformational leadership styles, job fit/adaptation, job stress and job satisfaction was scrutinised through the Pearson Correlation. It was found that there is a strong relationship between transformational leadership styles, job fit/adaptation and job satisfaction since the r is close to 1 ( r = 0.773, p< 0.05), (r = 0.705, p< 0.05). As such, if transformational leadership styles or job fit/adaptation increases, job satisfaction also will increase and vice-versa. On the other hand, the Pearson correlation showed that there is a negative relationship between job stress and job satisfaction. (r = -0.525, p< 0.05). This signifies if the independent variable decreases, the dependent variable will increase.

Variables Turnover Intention
Personal Development r = -0.435
Sig = 0.0000
Reward and Job Prospect r = -0.271
Sig = 0.023
Working Conditions r = -0.196
Sig = 0.104
Relationship at work r = -0.144
Sig = 0.235
It can be noted from the above table that the Pearson Correlation for all dimensions is negative which implies that as one variable increases in value, the other will tend to decrease. Personal Development and reward and job prospect having a Sig of 0.000 and 0.023 indicates that there is a statistically significant correlation with turnover intention. However, on the other hand, working conditions with Sig 0.104 and relationship at work with Sig 0.235 conclude that there is statistically no significant correlation.

Variables Absenteeism Intention
Personal Development r = -0.196
Sig = 0.105
Reward and Job Prospect r = -0.107
Sig = 0.377
Working Conditions r = -0.194
Sig = 0.108
Relationship at work r = -0.113
Sig = 0.351
From the above table it can be deduced that there is a negative correlation as r is negative and since they are close to 1, a strong relationship between the variables was found. In other words, personal development, reward and job prospect, working conditions and relationship at work and absenteeism intention are strongly correlated.

4.5.2 Multiple Regression Analysis
i. Multiple Regression for Job Satisfaction
Model Summary
Model R R
Square Adjusted R
Square Std. Error of the Estimate Durbin-Watson
1 .820 .673 .658 5.76791 1.909
Predictors: (Constant): Leadership Style, Job fit, Job Stress
Dependent Variable: Job Satisfaction
Table: Model Summary
ANOVA
Model Sum of
Squares dfMean
Square F Sig.

1 Regression
Residual
Total 4380.606
2129.203
6509.809 3
64
67 1460.202
33.269 43.891 .000
Dependent Variable: Job Satisfaction
Predictors: (Constant): Leadership Style, Job fit, Job Stress
Table: Anova
COEFFICIENT
Model Unstandardised CoefficentsStandardisedCoefficients t Sig.

1 B Std.

Error Beta (Constant) 18.412 5.826 3.160 0.002
Leadership Style 0.458 0.104 0.474 4.386 0.000
Fit/Adaptation 0.668 0.239 0.292 2.798 0.007
Job Stress -0.648 0.280 -0.188 -2.314 0.024
Table: Coefficient
Multiple regressions were carried out with job satisfaction as the dependent variable, and transformational leadership styles, job fit and job stress a the independent variables. The tables above indicate the regression, whereby R square value is 0.673 specifying that the independent variables namely transformational leadership styles, job fit and job stress explained 67.3 % of the variance of job satisfaction. F having a value of 43.891 shows that the model is significant at 5% level indicating the suitability of the model. This points out the fact that it fits the data collected. Transformational leadership styles, job fit and job stress appeared to be significant (P<0.05) affecting job satisfaction. Transformational leadership styles have the largest beta value of 0.474. If the sig is less than 5%, the result reflects a valid effect. To sum up, the regression coefficients that describe job satisfaction better are s follows:
? Transformational leadership styles (?=0.474, p<0.05)
? Job fit (?=0.292, p<0.05)
? Job stress (?= -0.188, p<0.05)
Thus, the derived linear equation is:
Y= b0 + b1x1 + b2x2 + b3x3
JS = 18.412 + 0.458 (TFL) + 0.668 (JF) -0.648 (JS)
Where Y = Job Satisfaction, TFL = Transformational leadership styles, JF = Job fit, JS = Job Stress
ii. Multiple Regression for Turnover Intention
Model summary
Model R R
Square Adjusted
R Square Std. Error of
The Estimate Durbin-Watson
1 .330 .109 .096 4.33575 1.939
Predictors: (Constant): Job satisfaction
Dependent Variable: Turnover intention
Table: Model summary
ANOVA
Model Sum of
Squares dfMean
Square F Sig.

1 Regression 156.275 1 156.275 8.313 .005
Residual 1278.311 68 18.799 Total 1434.586 69 Dependent Variable: Turnover I:ntention
Predictors: (Constant): Job Satisfaction
Table: AnovaCOEFFICIENT
Model UnstandardisedCoefficients StandardisedCoefficients t Sig.

1 B Std.

Error Beta (Constant) 18.925 2.929 6.462 0.000
Job satisfaction -0.155 0.054 -0.330 -2.883 0.005
Table: Coefficient
Another multiple regression was performed to test the second model. It comprises of turnover intention as a dependent variable with job satisfaction as independent variable. The R square value of 0.109 indicates that 10.69 % of variances in turnover intention can be clarified by the regression model.

According to the above tables, there is a significant and negative relationship between turnover intention and job satisfaction (? = -0.330, t = -2.883 and p = 0.005<0.05).

Based on the above, the following linear equation is derived:
T1 = 18.925 – 0.155 (JS)
T1 = Turnover Intention, JS = Job satisfaction
Consequently, the equation suggests that as one unit rises in job satisfaction, there will be a decrease in turnover intention by -0.155, holding other things constant.

iii. Multiple Regression for Absenteeism Intention
Model Summary
Model R R
Square Adjusted R
Square Std. error of the Estimate Durbin-Watson
1 .188 .035 .021 4.31824 1.858
Predictors: (Constant): job Satisfaction
Dependent variable: Voluntary_ prior Absenteeism
Table: Model Summary

ANOVA
Model Sum of
Squares dfMean Square F Sig.

1 Regression 46.575 1 46.575 2.498 .119
Residual 1268.011 68 18.647 Total 1314.586 69 Dependent Variable: Voluntary_Prior Absenteeism
Predictors: (Constant): Job satisfaction
Table: AnovaCOEFFICIENT
Model UnstandardisedCoefficients StandardisedCoefficients t Sig.

1 B Std.

Error Beta (Constant) 18.152 2.917 6.223 0.000
Job Satisfaction -0.085 0.054 -0.118 -1.580 0.119
Table: Coefficient
In addition, the independent variable namely job satisfaction was found to be insignificant with p>0.05 and having a standardized beta coefficient of -0.118 respectively. 35 % of variance in absenteeism intention is therefore explained by the regression model.

The following linear equation is derived as follows:
AI = 18.152 – 0.085 (JS)
AI = Absenteeism Intention, JS = Job satisfaction
Consequently, the equation suggests that as one unit rises in job satisfaction, there will be a decrease in absenteeism intention by – 0.085, holding other things constant.

4.6 Hypotheses
Table: Hypotheses for First Model
First Model
-38100144780Transformational
Leadership Styles
00Transformational
Leadership Styles

2499360355600

5052060243840Job
Satisfaction
00Job
Satisfaction
459486083820 H1a: ? = 0.474; p<0.05
-762078740Job Fit/Adaptation
00Job Fit/Adaptation

456438076200246126045720 H1b: ? = 0.292; p<0.05
442722010985583820277495Job Stress
00Job Stress

2385060229235 H1c: ? = -0.188; p<0.05

Table: Hypotheses for Second Model
4244340309880Turnover
Intention
0Turnover
Intention
-7620279400Job Satisfaction
0Job Satisfaction
Second Model
3322320863601447800177800 H2: ? = -0.330; p<0.05
Table: Hypotheses for Third Model

Third Model
4655820248920Absenteeism
Intention
00Absenteeism
Intention
1714500424180-762066040Job Satisfaction
00Job Satisfaction

393954055880 H3: ? = -0.118; p = 0.12

Relationship Hypothesis Results
224472581916Transformational Leadership Styles Job
Satisfaction H Supported
11474457556500Job Fit/adaptation Job Satisfaction H Supported
66738576836Job Stress Job Satisfaction H Supported
104838570485Job Satisfaction Turnover Intention H Supported
102552571756Job Satisfaction Absenteeism Intention H Not supported
Table: Findings
4.7 Conclusion
On a conclusive basis, evaluation of all the raw information was carried out by the use of numerous statistical tests in order to calculate the hypothesis associated with the aims and objectives of this research.

CHAPTER 5
CONCLUSION
5.0 Introduction
This chapter lays emphasis on the analysis and discussion of the results obtained and suggestions, followed by limitations of the investigation and a concluding note.

5.1 Discussion of results obtained
The investigation and research focused mainly on the reasons and causes of absenteeism and turnover. The results gained through the multiple regression scrutiny denote that transformational leadership styles, job fit and job stresses have a great impact on job satisfaction and ultimately affecting absenteeism intention and turnover intention. Transformational leadership style was found to have a higher significant effect on job satisfaction compared to the other factors. This finding is even with Felfe & Schyns (2006) who declared that leadership style has a positive correlation with employee perceptions of job, leader and organizational satisfaction. Thus, since P = 0.000 < 0.05 and ? = 0.474, H1a was acceptable.

Though further investigation, it was discovered that job fit/adaptation is also influenced by job satisfaction which supported H1b. This is so as beta = 0.292, t= 2.798 and p=0.0007<0.05. In other words, job fit/adaptation has a positive relationship with job satisfaction.

Nonetheless, discussing about job stress, it can be noted that it is negatively related to job satisfaction with beta = -0.188 and t = -2.314. It is in alignment with the study made by Igharia and Greenhaus (1992) which specified that job stress affects job satisfaction negatively. Results proved that the relationship between job satisfaction and job stress as hypothesized in H1c is not significant. With p = 0.024 <0.05, H1c is supported.

As mentioned in the conceptual framework, the effects of job satisfaction on absenteeism and turnover intention were inspected. There is a negative relationship between turnover intention and job satisfaction with ? = -0.330 and t = -2.883. H2 was accepted as it can be clearly indicated that P had a value of 0.005 which is less than 0.05.

Ultimately, while referring to the multiple correlation results obtained, a negative correlation between job satisfaction and absenteeism intention was identified. This reciprocates to the study of Farrell & Stamm (1988) and Hackett & Guion (1985) who mentioned that there is a weak negative correlation between job satisfaction and absenteeism. Since p = 0.119>0.05, H3 was not supported.

5.2 Recommendations
5.2.1 Recognition of causes
For each organisation the causes of absenteeism vary as the culture, employees and jobs are not the same. Theses disparities require various managerial tactics. A proper and ideal solution can be formed if individuals and organisations specificities are known and a strategy plan is constructed. Thus, it is of utmost importance to firstly pinpoint the causes and afterwards suggest a solution. This will help to facilitate the solution recommendation process.

5.2.2 Transformational Leadership Styles
Employees are of paramount importance in an organization. Organizations should have competent and proficient leaders to lead and inspire their employees in their everyday operation and to ensure that organizational goals are achieved. Public sector can hoist the level of commitment in the organization. This can be achieved by augmenting satisfaction with compensation, policies and better conditions at work ( Mosadegh Yarmohammadian), 2006. Moreover, actions should be taken by supervisors to improve their leadership styles and mentor staff members.

5.2.3 Job Fit/Adaptation
When employees love their work, this will automatically have a positive effect on motivation and eventually on productivity. Organization commitment can be instilled in employees to improve the job fit/adaptation. This can be done by inspiring employees, forming a desirable corporate culture, rewarding quality performance and company loyalty. Employee innovation should also be encouraged. Employees are retained when leaders let the employees fell their work is being appreciated. An interesting workplace and peaceful employment environment is essential.

5.2.4 Job Stress
It is of utmost importance that the needs of the employees are figured out and the objectives and aims of the organisation are recognized by the employees. The 5Cs can be recommended to reduce job stress. These are as follows: clarification, control, communication, condition and counselling. This can be explained in the table below.

The 5Cs Description
Clarification Each employee must have a job description and fully understands it.

Control Employees must have control as control directly has a reaction on stress
+*0Communication Effective communication at work is important to reduce stress at work thus diminishing the problem.

Condition Physical exercise can be opted as a remedy for stress.

Counselling Counselling should be made on stress-related illness. It will help employees to realise its impact in the long run.

Job satisfaction
Five suggestions for improving employee satisfaction at the workplace is explained in the table below.

Suggestions Discussions
Involve the employees in the organisationThe employees must feel that they are useful in the workplace. They should be involved in the decision making process, where their opinions are sought.

Inspire the team Inspiring the team is mainly centered on the ability to deal with feelings and emotions of the employees. That is, an environment that fits to the development of positive emotions should be established, where people will put more efforts in their work as they are highly motivated.

Strengthen team spirit The bond between the employees should be strong, where positive energy flow between co-workers will help to enhance the level of satisfaction.

Opportunities for training Training program is a win-win solution as employees are provided the chance to expand their knowledge which helps in better performance at work.

Provide feedback Feedback helps in promoting satisfaction as it is a form of recognition for the work performed.

Limitations associated with the study
In this study, some limitations were highlighted and they are as follows:
? All the employees of the DCS had not answered the questionnaire. The research work would have been more appropriate if feedback from all the employees were obtained. Moreover, workers who were on site could not participate in this survey.

? The use of transactional leadership style also could have been incorporated for this research work. However, for carrying out such a study, lots of time would have been lost.

Concluding Note
On a conclusive note, it can be said that if the four factors namely transformational leaderships styles, job fit/adaptation, job stress and job satisfaction is well monitored, this will definitely help to tackle the problem of absenteeism and turnover. No organisation should remain content with its actual state. Managers should come up with original and innovative ideas to find defaulting employees apart from simply treating fairly and compassionately and communicating properly.