Master thesis

(2008-2009)

THE ASSOCIATION BETWEEN PERCEIVED

CONSEQUENCES OF ABSENTEEISM AND

ABSENTEEISM: THE MODERATING ROLE OF SUPPORT

Name:    Xuan Wang 

ARN:      S692348 

Address:    Statenlaan 249 

5042 RV, Tilburg 

 

Supervisor:Dr. Michal Biron 

 

Project period: Jan 2009 – July 2009 

Project  theme:  Support  and  Absenteeism 

 

Department  of  Human  Resource  Studies 

Faculty  of  Social  and  Behavioral  Sciences 

Universiteit  van  Tilburg 

The Netherlands 

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Table of contents 

ABSTRACT ................................................................................................................................................... 4 

1  INTRODUCTION ................................................................................................................................. 5 

2  HE RETICAL FRAMEWORK .......................... ......................................................................... 8 T O . ...

  ................................................. 8 2.1 THE MAIN EFFECT OF PERCEIVED CONSEQUENCES OF ABSENTEEISM ......

  ......................................... 9 2.2 THE MAIN EFFECT OF SUPERVISOR SUPPORT AND CO‐WORKER SUPPORT ........

  UPERVISOR SUPPORT AND CO‐WORK SUPPORT ....................................... 11 2.3 THE MODERATING EFFECT OF S

  AL CONTEXT ......................................................................................................... 13 2.4 THE CHINESE SOCI

2.5  RESEARCH MODEL ........................................................................................................................... 14 

3  ET ODOLOGY .............................................................................................................................. 15 M H

  ..................................................................................................................................... 15 3.1 SAMPLE .....

  E .................................................................................................................................... 16 3.2 PROCEDUR

3.3  MEASURES ...................................................................................................................................... 16 

3.3.1 Independent variables .................................................................................................................. 17 

3.3.2 Dependent variable ...................................................................................................................... 17 

3.3.3 Moderating variables ................................................................................................................... 17 

3  Control v

3.4  ANALYSES ....................................................................................................................................... 19 

.3.4 ariables .......................................................................................................................... 18 

4  ISC SSION AND CONCLUSIONS ............................................................................................... 24 D U

  EISM ..................................................................................... 24 4.1 PERCEIVED CONSEQUENCES OF ABSENTE

  WORKER SUPPORT ............................................................................................ 25 4.2 SUPERVISOR AND CO‐

  IABLES ....................................................................................................................... 27 4.3 CONTROL VAR

4.4  CONCLUSION ................................................................................................................................... 28 

5  IM ATIONS AND IMPLICATIONS ............................................................................................ 29 L IT

  .................................................................................................................................. 29 5.1 LIMITATIONS .

5.2  IMPLICATIONS.................................................................................................................................. 31 

5.2.1 Theoretical implications ............................................................................................................... 31 

5 Practical implications ................

5.3  SUGGESTION FOR FUTURE RESEARCH ................................................................................................. 33 

.2.2 .................................................................................................. 32 

ACKNOWLEDGMENTS ........................................................................................................................... 34 

REFERENCES ............................................................................................................................................ 35 

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APPENDIX A - THE QUESTIONNAIRE (ENGLISH VERSION) ........................................................ 40 

APPENDIX B - THE QUESTIONNAIRE (CHINESE VERSION) ........................................................ 46 

APPENDIX C – SAMPLE DESCRIPTIVE .............................................................................................. 52 

APPENDIX D – ANOVA OF 12-MONTH ABSENTEEISM DATA ........................................................ 53 

APPENDIX E – PAIRED SAMPLE TEST OF DIFFERENT SUPPORTS............................................ 53 

APPENDIX F – THE INTERACTION ANALYSIS OF PERCEIVED CONSEQUENCES OF

ABSENTEEISM .......................................................................................................................................... 53 

APPENDIX G –PAIRED SAMPLE TEST OF DIFFERENT PERIOD OF ABSENTEEISM DATA .. 54 

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Abstract 

Purpose – The purpose of this paper is to explore the relationship between perceived consequences of absenteeism and absenteeism, and the moderating effect of supervisor support and co-worker support on this relationship. Design/methodology/approach – A questionnaire survey was distributed among 404 workers, employed in a state-owned manufacturing enterprise in China. The actual response rate was 54.6%, or 261 employees. The survey data was complemented by absence data retrieved from the firm's personnel archives. Findings – Analysis of the data supports a strong negative relationship between perceived deterrent consequences of absenteeism and absenteeism. There was a strong positive relationship between perceived motivating consequences of absenteeism and absenteeism. This study also found that supervisor support and co-worker support had a negative effect on the absenteeism occurrences. Moreover, co-worker support moderated the relationship between perceived motivational consequences of absenteeism and absenteeism occurrences. Keywords：Perceived consequences of absenteeism, Absenteeism behavior, Supervisor support, Co-worker support

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1 Introduction 

Employee absenteeism is a costly organizational phenomenon (e.g. Rhodes & Steers, 1990) as well

as a chronic problem in organizations (Goodman & Atkin, 1984). For example, absenteeism in

Canada costs employers billions of dollars a year and is reported to be on the rise (Lu, 1999). In

addition to these financial costs, highly skilled employees who provide essential services might not be

able to be replaced with people of similar skills, resulting in performance and safety issuers for the

organization (Gaudine & Saks, 2001). Thus, Employee absenteeism has received substantial attention

by academic scholars and practitioners (Rhodes & Steers, 1990). More than thirty years have passed

since a comprehensive narrative review of the employee absenteeism literature appeared in a

management-related journal (Muchinsky, 1977). Over a dozen books have been written about it (e.g.,

Goodman & Atkin, 1984; Rhodes & Steers, 1990), and a number of meta-analyses have summarized

bivariate relationships of absenteeism with other variables (e.g., Hackett & Guion, 1985). Several

critiques and reorientations of the literature have been posed (e.g., Hulin, 1991; Johns & Nicholson,

1982). Moreover, the majority of absence researches have focused on the influence of individual

variables, like demographics (age, gender, etc.) and job satisfaction (Rhodes & Steers, 1990). Until

1982, Chadwick-Jones, Nicholson and Brow argued the view of absenteeism should be extended to

include the role of both group and organizational variables and further Fitzgibbons (1992) reinforced

this suggestion.

To properly manage absenteeism and control the associated costs, factors conducive to such behavior

should be identified. In this respect, one variable that received much attention is perceived

consequences of absenteeism. Defined as employees' subjective expected utilities of being absent –

the probability that they would experience positive and negative consequences for not reporting to

work (Morgan & Herman, 1976), these perceived consequences are likely to affect the level of

employee absence. Porter, Lawler and Hackman (1975) suggest that the expectancy theory model of

behavior might be helpful in understanding absenteeism. Based on the expectancy model of behavior,

Morgan and Herman (1976) indicated that the organizational policies and practices can be effective

deterrents to absenteeism. Lawler and Hackman (1969) indicate that absence can be minimized by

giving monetary rewards for attendance and by withholding such rewards for those employees with

high level of absence. Based on their findings, these researchers proposed an absenteeism policy that

both rewards attendance with consequences that usually motivate presenteeism and penalizes

absenteeism. Nevertheless, few empirical studies have examined the relationship between perceived

consequences of absenteeism and absenteeism. The current study seeks to address this gap. Perhaps

more importantly, variables potentially moderating this association have been rarely investigated.

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Based on the literature review, this study focuses on the role of work-related support. However, there

are mixed results with respect to the effect of work-related support on absenteeism. By using causal

tests, Tharenou (1993) indicated that support within organization led to less absence. In contrast,

Roelen, van der Pol, Koopmans and Groothoff (2006) reported that support at work was not

associated with sickness absence. Support, did not appear to be an effective means by which to

remove the negative influences of stress produced by conflict and ambiguity (La Rocco & Jones,

1996), which might lead to absenteeism. Thus, it might be that these mixed findings result from the

different sources of support that were considered (i.e., support from one source may be related to

more absence, while support from a different source may lead to less absence). Therefore this study,

in an effort to resolve these inconsistencies, examines work-related support from two sources, namely

supervisors and co-workers. These sources of support appear to be more pertinent to the working

environment, because supervisors and colleagues are likely to provide valuable information and

feedback on the daily work (Joiner & Bartram, 2004).

Supervisor support (leader /manager support) reflects perceptions of the leader as helping to

achieve work goals through scheduling and planning, encouraging interpersonal relationships,

providing personal support, listening to personal and work related problems, and so forth (La Rocco

& Jones, 1996). Co-worker support (peer support/ colleagues support) refers to the perceived

quality of work-group relationships in terms of the amount of cooperative effort among co-workers,

work-group esprit de corps, the level of friendliness, warmth, open communication, and trust among

members of the work group, as well as shared pride in the work group (La Rocco & Jones, 1996). It

has been suggested that, for example, supervisor support, not co-worker support, has the most

significant influence on the level of pro-organizational behavior (Ross, Altmaier & Russell, 1989),

which further may influence the attendance occurrence. Therefore, this study seeks to retest the

association between supervisor/co-worker support and the absenteeism behavior.

Cohen and Wills (1985) underlined a controversial debate around the question whether support is

more effective in an independent way (Krantz, Grunberg & Baum, 1985), or as a moderating variable

(House, 1981). The latter refer to a buffering effect of employee relationships with managers and

colleagues within the organization. The moderating variables are commonly referred to as

stress-buffering resources because they are presumed to protect or buffer people from the negative

cognitive of encouraging absenteeism (Rahim, 1996). In this respect, during the last 15 years,

empirical studies have identified several factors that act as moderators or buffers against the

deleterious effects of absenteeism, which have indicated that differences in the support system render

some employee relatively cognitive of actual absenteeism behavior (Rahim, 1996). However, there is

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still little research about variables that may buffer the association between perceived consequences of

absenteeism and actual absence behavior. Thus, this study would like to examine whether support

from supervisor and co-workers act as moderator of this association.

The present study aims to explore the social dynamics of absenteeism in the People's Republic of

China. Although absence from work is a universal phenomenon (Martocchio & Harrison, 1993), the

vast majority of absence research has been conducted in the West (Steers & Rhodes, 1984). China has

become integrated into the world economy since it undertook economic reform in the 1980s. Hence,

the relevance of Western theories to China becomes a practical matter as much as a theoretical issue

(Shenkar & Von Glinow, 1994).

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2 Theoretical framework   

2.1 The main effect of Perceived Consequences of Absenteeism 

Absence is a socially defined event and leads to social attributions and responses (Johns & Nicholson,

1982). Important practical and theoretical implications emerge: absence not only affects employee

attitudes and behaviors, but is also considered a counter-productive attitudinal and behavioral

outcome (Tharenou, 1993). Cognitive processes of attribution and self-justification are used to explain

how consequences of absence occur (Fichman, 1984). Employees’ absence decisions can be affected

by their weighting the deterrent versus motivating consequences of being absent (Morgan & Herman,

1976). Such cognitive processes have received empirical support (Hackett, Bycio, & Guion, 1989).

For example, individuals have been found to adjust their perception to make unjustified absence

appear justified (Hackett, et al., 1989). Thus, cognitive processes may be elicited before absence

occurs.

According to the research of Morgan and Herman (1976) the consequences of absenteeism can be

divided into two categories: the deterrent consequences that can be controlled by the organization and

are directly associated with the job (e.g., loss of pay) and the motivating consequences that are

controlled by the employee and not directly associated with the job (e.g., being absent to recover from

illness or to have more leisure time). Employees will decide whether or not to attend work by

weighing the deterrent and motivating consequences of being absent (Morgan & Herman, 1976). If

the employees perceive that organization exercise deterrent outcome, such as absence-related policies

and practices they are more likely to exhibit low absenteeism rate. If absenteeism provides employees

with the opportunity to experience motivating outcomes that are not offset by organizationally

deterrent outcomes, then more absenteeism is likely to occur. Thus, this study expects that

absenteeism behavior is associated with the perceived consequences of absenteeism. A higher

deterrent consequences and lower motivating consequences of absenteeism will lead to lower

absenteeism occurrences, and vice versa.

Hypothesis 1a. Perceived deterrent consequences of absenteeism are negatively related to

absenteeism.

Hypothesis 1b. Perceived motivating consequences of absenteeism are positively related to

absenteeism.

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2.2 The main effect of Supervisor Support and Co­worker Support 

One of the most direct ways to improve the performance of employees is through human resource

development (Bhanthumnavin, 2003). Supervisors are often responsible for such efforts

(Bhanthumnavin, 2000). Supervisor support can be defined as the degree to which supervisors’ value

subordinates’ contributions and care about subordinates’ well-being (Kottke & Sharafinski, 1988).

Support from supervisors has therefore been suggested to be one of the most powerful tools of

impacting subordinates directly and indirectly. (e.g. Cromwell & Kolb, 2002). This importance stem

both from notions of the effects of social support in general and from the works of industrial and

organizational psychologists, who indicated supervisors to be among the most significant sources of

feedback for employees on their performance (Van der Klink, Blonk, Schene & Van Dijk, 2001).

Employees develop general views concerning the degree to which supervisors value their

contributions and care about their well-being (Kottke & Sharafinski, 1988). For example, support

from supervisor was generally reported that be positively related to subordinates’ work motivation,

such as job satisfaction (Mayfield, Mayfield, & Kopf, 1998), commitment to work (Littrell,

Billingsley, & Cross, 1994), and quality of work life (Bhanthumnavin & Vanintananda, 1997). It was

also found to reduce job stress (Stephens & Long, 2000), burnout (Eastburg, Williamson, Gorsuch, &

Ridley, 1994), health problems related to work (Blau, 1981). In addition, low level of supervisor

support has been related to organizational problem, such as decreased performance, increased

accidents, and absenteeism (Cropanzano, Rupp & Byrne, 2003; Stordeur, D’hoore & Vandenberghe,

2001; Eisenberger, Stinglhamber, Vandenberghe, Sucharski & Rhades, 2002). Thus, this study expects

that supervisor support has a negative association with absenteeism behavior.

On the aspect of co-worker support, similarly, several studies have highlighted the importance of this

kind of support. For example, perceived co-workers support has been shown to positively predict a

lower risk of sickness absence (Väänänen, Toppinen-Tanner, Kalimo, Mutanen, Vahtera & Peiró,

2003), more opportunities to use new knowledge, skills and attitudes (Kahn, Wolfe, Quinn, Snoek, &

Rosenthal, 1964), lower levels of burnout (Schwab, Jackson & Schuler, 1984) and distress (Joiner &

Bartram, 2004), and higher levels of job satisfaction and personal accomplishment (Kruger, Botman

& Goodnow, 1991). Apart from that, many workers rely on their colleagues to be sensitive and

supportive of personal and family difficulties (Galinsky, 1989; Lambert & Hopkins, 1995), and

colleagues also are key people to whom workers go for assistance when they experience personal

problems (Hopkins, 1997; Rodgers & Rodgers, 1989). Because supportive colleagues tend to share

their knowledge and expertise (Scott & Bruce, 1994), thus new ways of doing things are possible

(Woodman, Sawyer & Griffin, 1993) making employees feel comfortable to move on with their job.

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In this context, working with helpful, supportive colleagues helps reduce stress and maintain

standards of practice within a safe environment (Schroeder & Worrall Carter’s, 2002).

The aforementioned arguments suggest that the more support employees perceive from their

supervisor and colleagues, the more pro-organization behaviors they are likely to exhibit. Thus, the

present study expects that supervisor and co-workers support negatively affect absence occurrences.

Hypothesis 2a. Supervisor support is negatively related to absenteeism.

Hypothesis 2b. Co-workers support is negatively related to absenteeism.

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2.3 The moderating effect of Supervisor Support and Co­work Support 

Several researches suggested that situational variables that might moderate the role

perceptions-response relationships (Abdel-Halim, 1981, 1982; Beehr, 1976; Beehr and Love, 1980).

In their pioneering research, Kahn et al. (1964) suggested that the quality of interpersonal

relationship―an important situational variable in the workplace―might have a buffering effect on the

individual’s responses to these role stressors. Further, Caplan, Cobb, French, Harrison and Pinneau

(1975) and Cobb (1976) have emphasized that supervisor support represents one of the most likely

and effective means of alleviating the negative effects on work situation. Abdel-Halim (1982)

indicated that supervisor support, apart from directly effect on employees’ responses on their job, has

the potential to mitigate the impact on employee responses.

According to the Social Influence Theory, directly or indirectly, intentionally or unconsciously, people

influence the thoughts and actions of others (Van Avermaet, 2001; Turner, 1993). Social groups play

an important role in work-based behaviors (Deborah & Michael, 2000). For example, colleagues

comprise essential sources of support, encouragement, knowledge, etc. Employees often share

personal and work-related concerns with their co-workers in order to acquire assistance. Thus, Social

Influence Theory suggests that as be influenced by the work members, through processes of

convergence, workers perceive themselves as having to conform to the informal guidelines within the

organization. As a result, attendance or absence takes place in the frame of social dynamics (Mathieu

& Kohler, 1990) and co-worker support buffers on this judgment.

Previous researches about the moderating role of support are somewhat mixed. Studies by Caplan et

al. (1972), Cobb (1976) and Wells (1977) established supportive evidences of moderating role only

from supervisory support. However, House and Wells’ (1977) and Well’s (1977) studies were obtained

that supportive evidence from co-worker support only. Moreover, to date, how such moderating

effects of supervisor and peer support on the association between perceived consequences of

absenteeism and absence is still not clear (Beehr, 1976; Blau, 1980; LaRocco and Jones, 1978). Thus,

this study was intent on exploring whether both sources of support have different or same buffering

mechanism in workplace.

For example, on the one hand, employee who perceives high level of supervisor support may feel

pressure to be absent, regardless of perceived positive consequences of absenteeism, because he

believes that his supervisor will evaluate him upon his performance. Similarly, if employee did not

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feel his supervisor back him up enough, he may choose do not take the responsibility to present,

regardless of perceived negative consequences of absenteeism, because he may think his leader do not

like or just ignore him. On the other hand, employee who perceives high level of co-worker support

may feel less comfort to be absent, regardless of perceived positive consequences of absenteeism,

because he does not want his colleagues to suffer the extra work-load resulting from his absence.

However, employee who perceives low level of peer support may feel more comfortable to stay away

from job, regardless of perceived negative consequences of absenteeism, because he may feel be push

out of the peer group. Accordingly, this study posits:

Hypothesis 3a1. Supervisor support moderates the association between perceived motivating

consequences of absenteeism and actual absenteeism, such that a smaller association is expected

under conditions of high supervisor support.

Hypothesis 3a2. Supervisor support moderates the association between perceived deterrent

consequences of absenteeism and actual absenteeism, such that a stronger association is expected

under conditions of high supervisor support.

Hypothesis 3b1. Co-worker support moderates the association between perceived motivating

consequences of absenteeism and actual absenteeism, such that a smaller association is expected

under conditions of high co-workers support.

Hypothesis 3b2. Co-worker support moderates the association between perceived deterrent

consequences of absenteeism and actual absenteeism, such that a stronger association is expected

under conditions of high co-workers support.

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2.4 The Chinese social context 

The theories underlying this study originated in the West, but the assumption on which they are

based—that cognition influences the behaviours of individuals—has been shown to be universally

applicable (Triandis, 1989). Moreover, it is likely that this effect would be particularly strong in

cultures with a collectivist orientation. Specifically, collectivist cultures promote stronger links

between social cognition and behaviors than individualist ones (Martocchio & Harrison, 1993).

Cross-cultural research has designated the Chinese culture as typically collectivist (Hofstede, 1991).

In general, due to their work ethic, Chinese employees are loyal to their organizations and tend to be

concerned about the impact of their behavior on members within organization, to feel interdependent

with in-group members, and to feel more obliged to reciprocate the support they receive from their

organization/supervisors/co-workers (Hui & Triandis, 1986). Accordingly, the occurrence of negative

organizational behavior, for example: absenteeism, between China and Western could be different.

Moreover, according to the cultural dimensions made by Hofstede (1980), China is a high power

distance country. It indicates the extent to which a society accepts the fact that power in institutions

and organizations is distributed unequally (Hofstede, 1980). The status (hierarchy-related) differences

between supervisor and employee could be more acceptable in China than in most western countries.

In addition, in a collectivist culture, interdependent relationships between people are very strong.

In-group goals have priority to the individual goals, so individuals care more about the common

interest of group members rather than individual achievements (Hofstede, 1980). Consequently, it is

particularly interesting to examine the main and moderating effects of supervisor and co-workers

support in China. Because to the author’s knowledge, no previously research has been conducted in

China, it is valuable to explore this moderating role of supports and preliminarily conjecture the

mechanism behind. 

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2.5 Research Model 

 All the hypotheses were combined to formulate the conceptual model. It is presented in Figure 1.

Figure 1: Proposed Research Model

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3 Methodology 

3.1 Sample 

The firm under study is one of China's middle-sized state-owned manufacturing enterprises, located in

the Jiangsu Province, which contains about 577 employees, of whom 487 worked in the headquarter

and the rest worked in different provinces. The sample was comprised of full-time employees who

work more than one year and only focuses on the population who worked in headquarter. Eventually,

the total number of employees who meet the above mentioned criteria was 404. Within these

employees, 371 workers completed the survey. The response rate in total is 91.8%. However 110

questionnaires had more than 33.3% missing values, so the final sample consisted of 261 workers

(actual response rate of 54.6%) from which 62.1% were males. Although more than half the

enterprise's workforce was surveyed, a risk of sample bias remained. In order to assess the risk of

such bias, using t-test, this study compared the 261 employees participating in the study with the 143

employees not included in the sample along the outcome absenteeism variable. Further T-test shows

that there is no significant absenteeism difference between employees who answered the

questionnaires properly and who did not (see Table 1).

Table 1 T-test between response and non-response

Variable N Mean SD F Sig. df Sig. (2-tailed)

Non-response 110 4.52 7.74 1.80 .18 37 .122

Response 261 6.04 9.01

The demographic characteristics of the sampled employees are similar to those of the entire workforce

of the firm. The average age of staff was about 32 years old; the average organizational tenure was

about 9.7 years, with 62.5% employees worked more than 10 years for the organization; 42.5%

employees accepted more than 10 years education and 52.1% employees responsible for supervising

other people at work. More than half of workers (65.5%) were married and the rest lived in single.

55.2% workers’ spouse had their own job, while 10.4% employees’ spouse were not employed and

34.5% employees did not have spouses. The details have been listed in Appendix C

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3.2 Procedure 

Data were collected through a questionnaire survey and by accessing the absenteeism records from

the firm's personnel department. Employee surveys were administrated in the period between

Feb-26-2009 and May-10-2009. The conventional method of back-translation (Brislin, Lonner, &

Thorndike, 1973) was used to translate the questionnaire items from English to Chinese. Furthermore,

the research team (advisor and student) and the Personnel officer of the firm discussed each

questionnaire item to assure clarity and appropriateness. Later on, a further interview was carried out

in order to get more absenteeism information about the organization.

The cover page of the questionnaire assures the confidentiality of the data provided by all respondents.

All employees were informed that their participation in this study was voluntary. The questionnaires

were completed during the respondent's leisure time (out of work). The Personnel department

managers gave the questionnaires to a third party who has no relationship with the company to

distribute and collect sealed questionnaires from the employees, and then handed them to the

researchers. Participants were asked to identify themselves through fulfilling the Employee ID

Number in the questionnaires so their survey responses could be matched with the absenteeism

records. Also, after participants have handed in the questionnaires, they were notified that they will be

given a small gift prepared by the organization.

3.3 Measures 

The questionnaires of this study were based on literature and the concept definitions set at the

beginning of this study. All the scales have been used previously with satisfactory reliabilities. By

using back-translation (Brislin, et al., 1973), the scales were translated from English to Chinese. Then,

all the items were judged by a panel of experts to eliminate the less appropriate items. All the

questionnaires are presented in Appendixes A and B. Confirmatory factor analyses with Varimax

rotation and item analyses were conducted to check their validity and reliability. The results of

inter-correlation matrix and Cronbach’s alpha from item analyses are presented in Table 3.

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3.3.1 Independent variables 

The items of perceived consequences of absenteeism, based on the existing scale by Morgan and

Herman (1976), referring to perceived motivating consequences of absenteeism (α=.77) and deterrent

consequences of absenteeism (α=.66) were included (Morgan & Herman, 1976), with a five-point

Likert-type response scale (1=Not important and 5=Very important). Perceived motivating

consequences of absenteeism include 8 items. An example item is: "To what extent do you think

personal illness is an important reason for being absent?" Perceived deterrent consequences of

absenteeism include 7 items. An example item is: "To what extent do you think loss of wages is an

important reason for not being absent?” Higher scores indicated a higher degree of both

sub-dimensions of the scale. Presently, Cronbach’s α for the positive and negative expectancies

sub-dimensions was 0.730 and 0.742, respectively.

3.3.2 Dependent variable 

Absence occurrences were assessed for a 12-month period (Jan-01-2008 to Dec-31-2008) and exclude

long-term disabilities. Consistent with the way absenteeism is defined in Chinese organizations, the

leaves granted by Chinese organizations to all employees for maternity, wedding, and attending the

funeral of immediate family members are not be counted as absenteeism. Absence occurrences are

recorded as being primarily due to personal illness or outside injury, and problems with transportation,

family illness, personal reasons, injury while working, job disciplinary action, authorized absence

with pay, and authorized absence without pay.

3.3.3 Moderating variables 

A scale developed by Caplan et al. (1975), was employed in this study for measuring support. The

same 8-item scale was used to measure both supervisor and co-worker support. The response options

range from 1 to 5 (1 = Not at all and 5 =Very often). Sample items include: ‘‘Talked you through

work-related problems, helping you come up with solutions’’ and ‘‘Offered to assist you with work

when you where having a stressful shift’’. Higher scores indicated a higher degree of both

sub-dimensions of the scale. Currently, Cronbach’s α for the sub-dimensions of supervisor support

and co-worker support was 0.854 and 0.808, respectively.

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3.3.4 Control variables 

It was confirmed that when employees are in bad health status, they are likely to be more absent. This

study controlled for general health-related and well-being variables, namely somatic symptoms,

burnout and need for recovery. Somatic symptoms were assessed on the basis of the measure

developed and validated by Derogatis (1977) (α = 0.96). Respondents were asked to indicate

symptoms during the past month (1=Not at all; 5=Extremely) (e.g., "headaches", "pains in lower

back") by using the 13 items scale. The 13th item asked about the general health status: How would

you describe your health status over the past month? (Scale ranged from 1=Very poor to 5=Very

good).Cronbach’s α for somatic symptoms was 0.860 in this study. As well, respondents were asked to

indicate to what extent they feel job burnout in the past month by 9 items burnout scale (1=Not at all;

5=Extremely) developed by Maslach, Jackson and Leiter (1996) (α=0.84). An example item is: “I feel

emotionally drained from my work". Cronbach’s α for job burnout was 0.724 in this study. Further, 10

item scale was used toe test to what extent do employees' need for recovery (1=Not at all;

5=Extremely) used by Sluiter, van der Beek, and Frings-Dresen (1999) (α = 0.86). An example item is:

“I find it difficult to relax at the end of a working day". In the present study, Cronbach’s α for job

burnout was 0.720 for this scale.

Moreover, previous researches have confirmed that demographic variables (e.g. gender, age, and job

tenure) were associated with absenteeism. For example, absence behavior has been associated with

younger (Tsui, Egan, & O’Reilly III, 1992), lower tenured (Chadwick-Jones, et al., 1982), lower

educated (Tsui, et al., 1992) and female. Thus this study controlled for gender, age, responsible for

management or not, years of education, marital status, employment status of spouse, organizational

tenure, and personal characteristics in the model. By controlling for such variables, absence

researchers are able to account for possible demographic confounds and demography-as-proxy effects

(Price, 1995).

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3.4 Analyses 

Data was analyzed using the SPSS 16.0 Software. An alpha level of .05 was used for all statistical

tests.

Means, standard deviations and correlations for all respondents for each of the study variables are

reported in below (Table 3). First, factor analysis and reliability test were carried out to test the

questionnaires that used in this study. It can be seen that the reliability of all the scales are larger than

0.7. It can be concluded that the scales are all reliable. Second, bivariate correlation analyses were

carried out. There were significant positive correlation between perceived motivating consequences of

absenteeism and absenteeism (MC) (r=.25**, p<.05), and significant negative correlations between

perceived deterrent consequences of absenteeism (DC) (r=-.25**, p<.05), supervisor support (SS)

(r=-.21**, p<.05) and co-worker support (CS) (r=-.21**, p<.05) and absenteeism. Therefore, the main

effects (Hypotheses 1 and 2) have been supported. Further, as can be seen in Table 3, all the control

variables have no significant correlation with absenteeism.

Moderated regression analysis using ordinary least squares was employed to test the studies

hypothesis 3. Tests on the adequacy of the regression models employed indicated that the assumptions

of the models were partly satisfies by the data.

Table 3. Descriptive statistics and correlations (Person) of measured variables (Cronbach’s α along the diagonal)

Variable M SD 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17

1 Absenteeism 6.04 9.10 —

2 Age 3.34 1.73 .06 —

3 Gender 1.38 .49 .01 .06 —

4 Management 1.52 .50 .03 .50** -.09 —

5 Marital status 1.87 .77 .10 .35** .00 .17** —

6 Tenure 9.69 8.14 .16 .62** .06 .51** .27** —

7 Education level 10.84 3.67 .09 -.05 .00 .11 -.11 -.14* —

8 Employment status of

spouse 1.21 .93 -.01 .34** -.01 .30** .23** .26** -.11 —

9 Personal

characteristics 4.17 .93 .08 .11 -.02 .15* .05 .13* .18** .05 (0.72)

10 Somatic symptoms 3.98 .87 -.10 -.05 -.03 -.10 -.03 -.11 .12 -.02 .13* (0.86)

11 Health status 2.33 .83 .01 .18** .00 .02 .23** .11 -.17** .00 -.10 -.18** —

12 Burnout 2.82 .64 .01 .23** .05 .02 .19** .21** -.17** .01 .01 -.06 .52** (0.72)

13 Need for recovery 2.89 .68 .04 .19** .03 .11 .13* .22** -.10 .09 .07 -.08 .51** .49** (0.72)

14 Supervisor support

(SS) 3.20 0.85 -.21** -.18** -.05 .08 -.12 -.14* -.29** -.12 .07 .06 -.23** -.31** 1.15* (0.85)

15 Co-worker support

(CS) 3.54 0.73 -.21** .04 .07 .14* -.06 -.04 .13* -.06 -.06 -.05 -.05 .08 .08 .02 (0.81)

16 Motivation

consequences (MC) 3.08 0.70 .25** .14* -.03 .08 .-.03 .16* .12* .00 -.01 -.21** .11 .15* .104 -2.5** .02 (0.73)

17 Deterrent

consequences (DC) 3.15 0.82 -.25** -.03 .04 .03 .01 .09 .13* -.08 .18** .15* -.08 -.03 -.03 .25** .09 -.27** (0.74)

Note: *p<0.05; **p<0.01.

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Firstly, on the aspect of motivational consequences of absenteeism (MC), this study entered the control variables in Step 1 by linear regression, which would show the effects of control variables on the absenteeism occurrences. As can be seen in Table 4, there were no significant relationships between all the control variables and absenteeism. In Step 2, as entered motivational consequences (MC), the results would show whether motivational consequences of absenteeism has effect on absenteeism (Hypotheses 1a). It can be seem in the Table 4 that this main effect was reached the significant level (α=3.315, p<.05). Thus, there was a significant positive relationship between perceived motivational consequences of absenteeism and individual absenteeism behavior. Next step, this study entered supervisor support (SS) and co-worker support (CS), the results would answer whether perceived supervisor support and co-worker support had positive or negative effects on absenteeism (Hypotheses 2a and 2b). It can be seen from the table below (see Table 4), the main effects between both variables and absenteeism are significant, which are consist with the above findings, within which, there are a significant negative relationships between supervisor and co-worker support and absenteeism occurrences (respectively α=-2.330; α=-2.818, p<.01). Thus, the Hypotheses 2 have been proved. Then, the Step 4 would be possible to conclude about Hypothesis 3a1 and 3b1: whether SS or CS plays a buffering role on the relationship between MC and absenteeism. This buffering effect of supervisor support was not significant, whereas, the moderating effect of co-worker support achieved a statistical significant level (α=-2.229, p<.05), such that a weaker association between MC and absenteeism was expected under condition of high co-worker support. Thus, the hypothesis 3b1 has been proved. Table 4. The linear regression of Motivation consequences of absenteeism and

support

Variable Step 1 Step 2 Step 3 Step 4

B SE B SE B SE B SE Step 1 Symptoms -1.211 .666 -.712 .658 -.893 .630 -.870 .629

Health -.204 .873 --.210 .847 -.830 .821 -.804 .816

Burnout -.334 1.090 -.700 1.061 -.792 1.036 -1.111 1.052

Recovery .346 1.035 .306 1.004 .797 .966 .754 .969

Age -.112 .456 -.277 .444 -.354 .428 -.376 .426

Gender -.194 1.169 .058 1.136 .278 1.089 .308 1.093

Manager -1.551 1.420 -1.538 1.378 .003 1.352 .066 1.345

Marriage 1.276 .795 1.619 .776 1.408 .743 1.413 .740

Tenure .175 .095 .157 .092 .100 .089 .092 .089

Education .310 .164 .364 .160 .524** .156 .549** .156

Spouse -.399 .666 1.278 .647 -.416 .620 -.537 .619

Personality .569 .629 .532 .611 .357 .587 .254 .588

Step 2 MC 3.315** .817 2.791** .796 2.995** .798

Step 3 SS -2.330** .690 -2.673** .724

CS -2.818** .749 -2.648** .779

Step 4 MC×SS -.451 .961

MC×CS -2.229* 1.086

R2 0.054 0.113 0.196 0.212 F 1.187 2.431 3.992** 3.841 ∆ R2 0.009 0.067 0.147 0.157 Note: Age, gender, management, tenure, education level, employment status of spouse, personal characteristics, somatic symptoms, health status, need for recovery were entered as Step 1; MC as Step 2; SS and CS as Step 3, and MC×SS and MC×CS as Step 4. *p<0.05; **p<0.01

Secondly, on the aspect of deterrent consequences of absenteeism (DC), in Step 1, this study entered the control variables by linear regression (see Table 5). Still, there were no significant relationships between all the control variables and absenteeism. In Step 2, as entered deterrent consequences (DC), the results would show whether perceived deterrent consequences of absenteeism has effect on individual absence behavior (Hypotheses 1b). It can be seem in the Table 5 that this main effect has reached the significant level (α=-2.986, p<.05). Thus, there was a significant negative relationship between perceived deterrent consequences of absenteeism and individual absenteeism behavior. Then, in the next step, as entered supervisor support (SS) and co-worker support (CS), similarly, the results would answer whether perceived supervisor support and co-worker support had positive or negative effects on absenteeism (Hypotheses 2a and 2b). It can be seen that, in Table 5, the main effects between both variables and absenteeism are significant, which are consist with the above findings. There were significant negative relationships between supervisor and co-worker support and absenteeism occurrences (respectively α=-2.284; α=-2.626, p<.01). Again, the Hypotheses 2 have been proved. Third, the Step 4 would be possible to conclude about Hypothesis 3a2 and 3b2: whether SS or CS plays a buffering role on the relationship between DC and absenteeism. As can be seen in below list, both buffering effect of supervisor support and co-worker support have not reached the significant level. Thus, the moderating hypotheses of both kinds of supports were failed to be proved.

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Table 5. The linear regression of Deterrent consequences of absenteeism and support

Variable Step 1 Step 2 Step 3 Step 4

B SE B SE B SE B SE Step 1

Symptoms -1.211 .666 1.900 .647 -1.061 .623 -1.177 .626

Health -.204 .873 1.459 .846 -.990 .822 -.922 .825

Burnout -.334 1.090 -.361 1.053 -.525 1.035 -.525 1.042

Recovery .346 1.035 .710 1.003 1.086 .969 1.115 .970

Age -.112 .456 -.089 .440 -.199 .427 -.168 .427

Gender -.194 1.169 .076 1.131 .258 1.090 .215 1.089

Manager -1.551 1.420 -2.093 1.375 .277 1.353 .361 1.354

Marriage 1.276 .795 1.445 .769 1.261 .740 1.253 .745

Tenure .175 .095 .128 .092 .082 .090 .078 .089

Education .310 .164 .339 .159 .495 .156 .496** .158

Spouse -.399 .666 -.626 .645 -.685 .622 -.733 .623

Personality .569 .629 .970 .615 .717 .595 .654 .597

Step 2 DC -2.986** .687 -2.342** .678 -2.413** .686

Step 3 SS -2.284** .694 -2.391** .707

CS -2.626** .751 -2.837** .764

Step 3 DC×SS 1.282 .846

DC×CS .376 .972

R2 0.054 0.122 0.195 0.204

F 1.187 2.631** 3.965** 3.671

∆ R2 0.009 0.075 0.146 0.149

Note: Age, gender, management, tenure, education level, employment status of spouse, personal characteristics, somatic symptoms, health status, need for recovery were entered as Step 1; MC as Step 2; SS and CS as Step 3, and MC×SS and MC×CS as Step 4. *p<0.05; **p<0.01

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4 Discussion and conclusions This study examined how support from supervisor and coworker influence the association between perceived consequences f absenteeism and individual absence.

4.1  Perceived consequences of absenteeism 

As suggested by Morgan and Herman (1976), two dimensions of perceived absence outcome were identified: motivating and deterrent. In this study, the correlation between the encouraging and deterrent consequences of absenteeism was negatively significant (r=-.27, p<.01), which indicates that, on average, individuals believed that both types of contradictory perceptions existed at the same time. Employees are sensitive to the possible costs and benefits of being absent from work. Both perceptions about absenteeism seem to have a rival and coexistent effect with each other on individual absence. Consisting with the economic research on the effects of absence taking (e.g., Dalton & Perry, 1981), individuals are assumed to strive toward the goal of making themselves as happy as they can given the limited resources available (Ehrenberg & Smith, 1985). So the advantages of absence seem to be more likely recognized by employees than the negative outcomes. However, despite emerging beliefs about the positive outcomes of absence, traditionally, absence has been treated as an occurrence with negative implication for interest groups in the organization (Rhodes & Steers, 1990). It is possible that the negative outcomes of absence are more salient to employees in general than the positive outcomes. Thus, this logic provided workers with the speculation of maximizing the perception of motivating consequences or minimizing the deterrent outcomes of absenteeism. However, referring to the Table 3, even though the correlation between both perceived consequences of absenteeism is negatively significant (r=-2.7**), this coefficient is still quiet low. Thus, by using hierarchical multiple regressions, this study further tested whether there is an interaction effect between both perceived consequences of absenteeism. As can be seen in the Appendix F, the main effects of perceived consequences of absenteeism and absenteeism behavior were extremely significant; however, there was no significant interaction effect between motivational consequences and deterrent consequences of absenteeism. Thus, in the statistical level, the interaction effect between both kinds of perceived consequences of absenteeism will not significantly influence the individual absenteeism behavior. In the current study, the relationship between perceived consequences of absenteeism and individual absenteeism were examined. After controlling for the demographics, general health-related variables and personal characteristics in the model, the perceived motivating and deterrent consequences of absenteeism explained a significant amount of variance, 6.7% and 7.5% respectively, of absenteeism occurrences (in the hypothesized directions). On the one hand, based on the results, if the employees apparently found absenteeism rewarding, mostly his/her absence will be predicted in the future. On the other hand, if there was a high absenteeism cost, that employees were perceived, it might act as deterrents to absenteeism. Based on the general expectancy-theory model of behavior (Vroom, 1964) the main effects of perceived consequences

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of absenteeism on individual absence can be explained. According to this theory, employees will think about the valences of his/her absence behavior first. The valences in this study are the perceived consequences of absenteeism. He/she will calculate the costs and benefits from this action. If it worth, they will be motivated to stay away from the daily job. Contrarily, if the

alence is low (high deterrent and/or low motivating consequences), the expectancy f absenteeism would be low and further lead to less absenteeism behavior.

vo 

4.2  Supervisor and Co­worker support   

The present study shows that the correlation between supervisor and peer support was as low as 0.02 (see Table 3). This indicates that, on average, individuals believed that both types of support were either existed. For example, when an employee received support from his/her co-works, then mostly, he/she just depends on this kind of support resource and would not seek for or be given the support of up-level colleagues. Similarly, if one depends on the supervisor support, it can be deduced that he/she conquered little co-worker support, because the perception of supervisor support can not predict the appearance of peer support. Moreover, by paired sample test of both kinds of support (Appendix E), it can be seen that there was a significant difference between co-worker support and supervisor support (t=-4.835, p<.01). The level of peer support in this study was significant higher than the level of supervisor support. This happens maybe because of the Chinese culture background－the high sense of hierarchy. Since the existing of high power distance, the communication between different hierarchies becomes difficult. When employees try to seek support from up-level colleagues, they are likely disappointed, then, they would transfer their expectation and efforts to the same level peers. Similarly, the management level is more likely to depend on the same supervisor groups. That’s to say supervisor or peer support happens more within the same level of hierarchy, instead of between levels. Further deducing, in this Chinese organization, the relationship between hierarchies may be tight and formal. Moreover, according to Appendix F, the level of co-worker support is much higher than manager support. It suggested that both kinds of supports were not balanced. It seems like that the capacity of peer support was compartmentalized into two parts: support to the same level employees and support to their up-level managers at the same time. Because consciously or unconsciously, employees in the Chinese organization need to show obey or respect to the up-level members (Shenkar & Von Glinow, 1994). Moreover, previous research demonstrated that employees pay close attention to the attitudes and beliefs of managers as evidenced through their expectations and actions (O’Dea & Flin, 2001). Further, Rhoades and Eisenberger (2002) suggested that employees feel an obligation to the organization’s welfare and hold the belief that good performance will be recognized and rewarded by the managers. Thus, it can be deduced that the common employees offer the support to their supervisors maybe due to this hierarchical system. However, it needs further study to explore this assumption. On the aspect of the individual absence behavior, as expected (Hypothesis 2), the support, from managers and peer, had directly negative influences on absenteeism (r=-.21, p<.01). Consisting

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with the social exchange theory (Blau & Peter, 1964), supervisor and co-worker support might motivate employees to direct their reciprocation efforts to the source of any benefit they have received. Thus, both kinds of supports motivate employees to show more pro-organizational behavior in the workplace. However, based on the social psychological and organizational research on legitimacy, certain patterns of actions within the social unit are governed by norms, which are upheld by higher level members (Walker, Thoms, & Zelditch, 1986). In 1975, Dornbusch and Scott developed a theory of organizational authority that views social support as the transfer of positive sanctions among employees. When an employee receives enough positive sanctions over time, his or her activities or position becomes a “validated” part of the system in two distinct ways: authorization (positive sanctions from someone in a higher organizational position) and endorsement (the transfer of sanctions from one’s peers or subordinates). In effect, authorization comes from “higher up,” whereas endorsement comes from someone of equal or lower status. Research generally indicates that, given the strong hierarchical nature of most organizations, authorization is more powerful than endorsement (Walker et al., 1986). Thus, considering the Chinese social context—a high power distance culture, employees who are supported by their supervisor are viewed as more authorization to feel comfortable to be absent. Based on finding, this authorization expectation was failed to be supported. Referring to the above argument, there maybe just exists a unidirectional support from employees to their supervisors, as managers show no reaction to their staff’s support. Thus, employees do not receive enough positive sanctions and their absence behavior was not legitimacy in this organization. Further, it can be deduced that the peer support was seem to be more bidirectional than manager support, since it not only offer its help to the same-level employees, but also show respect to their up-level leaders in this Chinese state-owned enterprise. Although the literature has suggested that co-worker/ supervisor support act as buffers against the negative effects of work-related outcomes, the present study almost failed to support the buffering hypothesis (see Table 4 and Table 5), except for the moderating role of co-worker support which significantly buffered the relationship between the motivational consequences of absenteeism and absenteeism occurrences. Based on this finding, high peer support seems to weaken the association between perceived absence advantage and individual absence behavior. To that extent, employees’ tie-ins to colleague social networks may offer greater explanatory potential with respect to absenteeism than their connection with supervisors. Similar to the above mentioned deducing, this maybe because of the significant higher and handy co-worker support than supervisor support. Thus, Chinese employees more turned to same-level colleagues for support. For the up-level workers, they received this kind of support by force or just by their upper status. This research suggests that employees’ perception of the benefits of absence influences individual behavior. Thus, managers should focus their absence management efforts on the emergent absence culture that affects absence patterns and levels. Moreover, the absence management measures can be changed from traditional ones based on behavior modification principles to ones that operate through social influence processes, such as enhancing the communication and trust between peers.

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In contrast to the above indications of direct effects, there was no evidence that leader support was able to alleviate the undesirable outcomes. The buffering effect of supervisor support on the relationship between perceived consequences of absenteeism and individual absence behavior was not significant in this study. Since the moderated regression procedure suggested a straightforward rejection of the buffering hypothesis, this kind of supportive behaviors may have a direct impact on absenteeism instead of buffering effect. Additionally, Wells’ (1977) study suggested that supervisor support might be more effective in alleviating the deterioration in positive work outcomes (such as satisfaction and self-esteem) than in mitigating the effects of negative work outcomes (such as pressures). Thus, in this absenteeism research, the power of supervisor support maybe is hindered. Further, in 1976, Beehr reported both positive and negative evidence of buffering role of supervisor support. Especially, in Chinese culture, as mentioned before, the moderating variable of supervisor support maybe only show its unitary effect to the same level fellows, therefore, the buffering power became weaken. In all, the effect of supervisor support is still mixed. It might be profitable for future research to explore whether supervisor support has differential effects upon absenteeism in Chinese social context.

4.3  Control variables 

According to the previous research, the relationship between health status or pressure and absenteeism rate, under the western culture background, mostly should be as high as 0.7 (Bertera, 1991). However, in this study these relationships were not significant at all. This unusual phenomenon happened, first and uppermost, may be because of the time lagging in this study. The health status and pressure-related control variables were measured between the periods from 02-2009 to 05-2009, but the data of dependent variable was the whole year of 2008. That’s to say, both sides of data were not symmetrical on the timing level. Thus, on the theoretical level, the deducing power of health and pressure related variables were doubtful. Secondly, According to the Chinese culture background, the society emphasized the collectivism instead of individualism (Hofstede, 1980). This culture difference maybe was another cause of the unusual situation. Moreover, the average score of health and pressure related variable is around 3.0, that means, most employees maybe under a sub-health status instead of un-health. For example, in Western context, when people feel sick, they may more care about their health and absent from job. However, Chinese people may care more about the performance of their organization. If there was not a big health problem, they still choose to stay in their position, especially in the traditional stated-owned enterprises (Zhao, 2005). It should also be noticed that the existence of policy differences between Asian and Western corporations. There exists a strict regulation to against absence in stated-owned firms (Zhao, 2005), such as: deduct wages and fire, which maybe prevents this kind of behavior. Moreover, human right is less developed in China than in Western countries (Nham, 2007). Thus, people may feel afraid to rise up their own opinion. The last consideration is the social preference effect. It can not be excluded that employees did not report their own individual information honestly. Apart from that, referring the Table 3, the correlation between health-related variables and stress related variable was not significant, that’s to say, in the statistical level, stress was not health status

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related in this study, which was quiet contradictory to the previous findings (Stewart, Cianfrini & Walker, 2005). Instead of saying they did not related to each other, this study would like to say health status was not weighted that strong to be arouse employee’s sensation of pressure, and employees’ stress feeling may be come from other kinds of sources. The reason behind, similarly, may be the culture and policy difference play important roles. Employees may pay more attention to the external environment, like the principle of the society and organizational performance, instead of internal well-being. All in all, the above mentions are some deduction. It is valuable for further research to elaborate the complicated relationship in the Chinese social context.

4.4  Conclusion 

In conclusion, based on the present findings, the results suggested that (a) perceived low level of motivating consequences or/and high level of deterrent consequences would predict a low absenteeism occurrences, (b) high levels of support were related to the low absenteeism occurrence and (c) support from peers appeared to be an effective means of removing the negative influences of perception of motivation consequences of absenteeism.

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5 Limitations and implications 

5.1  Limitations 

The contributions of this study must be considered in light of the limitations. First, it should be noticed that there was a time difference between the absenteeism records (from 2008 to 2009) and the survey (from 02-2009 to 05-2009). So this about 4 month’s time lagging, which was the biggest design drawback in this study, may have effect on the dependent variable. In respect of this limitation, on the organizational level, a further discussion with the personnel manager was carried out in order to find indirect support. As far as he knows, there were no big policy changes in the company which would influence the absenteeism rate. Even when the economic crisis is coming, this organization, as a state-owned enterprise which more depends on the government, is still stable and not easy to change. In addition, this study compared the 12-month individual absenteeism data (Appendix D). In Table 6, the between groups compare was not significant, which means the individual absenteeism occurrence seems stable. Later, this study compared the absence level on the first 6 month with the level of absence in the second 6 months in 2008 by paired sample test (see Appendix G). Then, this study collected the absenteeism data from January 2009 to June 2009 and compared it with the data of 2008. It can be seem in the Appendix G, there were no significant differences between these three paired data. Moreover, previous researches confirmed that absence levels seem to be stable over time (e.g.: Cohen & Golan, 2007; Rosenblatt & Shirom, 2005). Sum up, the above mention just gave out some indirect support to this study and it can not cover the limitation of survey design, which caused by the time lagging. There was a high invalid rate of questionnaire, which taken about 1/3 among the entire subjects. In state-owned corporations, surveying is one of the easiest and most efficient ways (Hang & Deng, 1998). A valid questionnaire can effectively gather feedbacks from employees. However, there were four main pitfalls should be concerned in the compared low valid rate: 1) Clarity and Simplicity (Hang & Deng, 1998). In order to make employee corporate, a good questionnaire must be precise and straight to the point. In this study, the all the items were translated from English to Chinese, so this may influence the clarity of the expression. Further, the total number of final items is 72, which is comparatively long. This will result in non-return and incomplete or inaccurate responses; 2) Content. The early appearance of unsettling questions may result in respondents discontinuing the questionnaire, such as personal illness and loss job; 3) Timing. Timing is an important issue for making a questionnaire. Giving out questionnaire in busy period would just be ineffective (Hang & Deng, 1998). The survey was carried out just after the Spring Festival, which in the biggest festival in China. So there were accumulated jobs need to fulfill. This may further cause frustrations for respondents; and 4) the difference between different target groups. For example, the valid rate of professional group can be higher than 70%, whereas the control group was compared lower than 60% (Hang & Deng, 1998). So this target group difference may influence the valid rate of subjects.

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The sample in this study was drawn from the China's middle-sized state-owned manufacturing enterprises. Even though a sample size of 261 responses was quite appropriate, the generalizability may only be generalizable to this kind of organization because of the nature differences within different industries and between state-owned and non-state-owned enterprises. In addition, this study examined excessive absenteeism within one year period. As referring to the definition by Harrison and Martocchio (1998), it is a long periods of data collection and generally preferable. However, collecting absence data from a longer period may help avoid the problems of skewness and leptokurtosis, which typically associated with short-term absence records. Fifth, participants may have evaluation apprehension. They may have a desire to maintain a positive self-image may underlie the conformity and subjective utility effects, especially under the Chinese culture. Chinese are more sensitive to the losing face. Thus, in able to avoid this, they are more likely to cater to the social preference (Yu, 2002) and show to be a good participant. Even though, there was a third party, who has been hired to connect the personnel department and employees, this study still can not guarantee that there was no conformity effect. Also, this study measured support along two types (supervisor and co-worker support) instead of more, such as: organizational support (Greenhaus & Parasuraman, 1994) or subordinates support (Caplan, et al., 1975) crystallizes another limitation. The relationship between different kinds of work-related support is still not clear, thus the mixed results with respect to the effect of work-related support on absenteeism still need further discuss.

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5.2  Implications 

5.2.1 Theoretical implications

Notwithstanding the limitations discussed above, the study provides some contributions to the literature. First, this study examined the perceived consequences of absenteeism behavior and secondly, the buffering effects of supervisor and co-worker support. Evidence from this study supports a strong positive relationship between perceived encouraging consequences of absenteeism and individual absence behavior, and a significant negative relationship between perceived deterrent consequences and absenteeism occurrences. Consistent with previous research on the absenteeism relationship, this study has confirmed the previous findings about the direct effect of perceived consequences of absenteeism on individual absence. Referring to the role of supports, the present study demonstrates that both supports have significant negative power on individual absenteeism. This finding reinforces the importance of both supports within the organization units. More specifically, this study also found that an environment of co-worker support within the organization reduces the negative organization performance. That is, although this result supported that high supervisor and co-worker support have a direct main effect on enhancing present occurrences, only an environment of co-worker support provides a significant buffering power on the perceived motivational consequences of absenteeism and individual absence behavior under the Chinese culture context. This finding is novel to the social support literature. It highlights the value of integrating consideration of harmoniousness within employees into human resource management practices in order to reinforce employees’ motivation and reduce the deterrent factors to improving the quality of organizational performance. Further, further research could consider a number of other kinds of supports related practices to elaborate the interactive effect that practice on the relationship between perceived consequences of absenteeism and absenteeism occurrences. As an exploration, this study focused on the Chinese social context. So the following deducing was based on its culture background. Within this context, human resource practices of potential consideration could include: reinforce the relationship within co-workers and develop an informal relationship between different interest groups. Organizations should develop a non- hierarchical employment system to “boost” the effect of supervisor support. In this process, human resource management practices should act as main role.

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5.2.2 Practical implications

Considering the practical implications, in order to reduce the absenteeism occurrences, in 1976, Morgan and Herman suggested that the organization could simply change the contingencies of both consequences of absenteeism that it controls. In the respect of the deterrent consequences of absenteeism, for example, organizations could increase the absolute amount of loss of wages or enforce discharges contingent on absences for those employees whose attendance record is poor. Morgan and Herman (1976) indicated that this strategy may be worked in short-term, because it does not account for the encouraging consequences that simulate absenteeism. Thus, an alternative strategy for the angel of encouraging consequences of absenteeism, also based on a general expectancy-theory model of behavior, seems more appropriate. Organizations could provide employees with the requirements, which employees considered to be justifiable. Such as giving more free time and flexible work to employees, contingent on their good attendance records, synchronously, adopt the above-mentioned deterrent policy. Then, organizations would both reward attendance with opportunities to experience consequences that usually motivate absence, penalize employees who have a bad record and enforcement of penalties for absence. Moreover, some researchers (Rhodes & Steers, 1990; Hammer & Landau, 1981) suggested that employee attendance is influenced by the employee’s motivation to attend as well as ability to attend (Hammer & Landau, 1981). Employees received pressures to attend may include economic, social or personal reasons. So the human resource management practices should give a deeper attention to these factors, in order to not only satisfy the internal desire of employees, such as: community and safety, but also remove the external anxious, such as: housing and child. Also, the present study emphasizes the importance of enhancing co-worker support based on the results of this study. Because an environment of support derived from the colleagues may have a buffering effect to prevent absenteeism. When employees got large peer support, they may feel more comfortable and be accepted in the working situation; even when they have a high absenteeism motivation, they will still prefer moving on with their jobs. Thus, individuals would be having better performance when they are allowed to make an informed choice about absence with their colleagues. Even though the moderating role of manager support was not significant in this study, this study still suggested paying attention to the role of supervisor support in the organization. This buffering effect was failed to be proved, maybe because Chinese have not got used to feel and accept this origin of support under this culture context, instead of it did not works. As mentioned above, in this context, the power distance between employee and employer is larger than Western. It is not easy to really get to know each part. However, within a context of ever increasing globalization and the competition among firms, manager support shown a more and more important status to maintain a sustainable improvement. Especially during the crisis time, in order to keep competition advantage, it is important that leaders shown more open support to decrease employees’ insecurity and make them keep focusing on their own job. If employees do not feel there is acknowledgement and support from the leaders, then the outcome may be sub-optimal.

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Apart from that, it would be better if there is a third party bridge the employment relationship, for example the labor union, the government or management consulting company. The potential insights gained from these issues may provide further useful information for managing absence. Thus, this study motivates managers to invest more time and resources to employees in order to develop an environment or “culture” of support to further enhance the performance outcomes. Moreover, this study shows an unexpected finding that education played a role both on the main hypothesizes and the moderating hypothesizes. Organizations should pay attention to employees’ education level as one very important variable on performance indicator. Thus, based on this study, the organization can make more salient performance outcomes through supervising the employees’ educational level.

5.3  Suggestion for future research 

Based on the previous findings, the future research should examine the temporal characteristics of perceived consequences of absenteeism (Martocchio, 1994). Whether it is relatively invariant to change or relatively malleable? As well, examining the antecedents of perceived absenteeism culture and mediating mechanisms (e.g., Nicholson & Johns, 1985) that may be operating. Also, the social support in this study was only derive from two types—supervisor and co-worker support, however, other more related supports should be integrated, for example, Caplan et al. (1975) suggested the subordinates support should be considered into to elaborate different kinds of work-related supports. Similarly, the dependent variable in this study could include more comprehensive organization performance factors, rather than only focus on the absenteeism occurrences. In future research, it is better to have a larger size of sample which can better represent the Chinese population and help to draw conclusions about the impact of supports on the relationship between perceived consequences of absenteeism and individual absence behavior. A cross-comparison quantitative research is suggested to be used to test the moderating effects of supervisor support and co-worker support between the state-owned and non-state-owned enterprise or between Eastern and Western culture. Perhaps, by using a longitudinal design, it will be more interesting to test the time difference before and after the economic crisis. Thus, these will be good ideas to have a deeper understanding about the effects of different supports under different situation, especially, the mechanism behind supervisor support. For the control variables in this study, it should be noticed that the variable of educational level played an important role in the present study, so further, a perusal of factor management should be carried out to explore more related variables. Apart from that, there still need further exploration to clarify the relationship between health or pressure related variables and absenteeism in state-owned enterprises in China.

33

Acknowledgments

The author grate fully acknowledges Dr. Michal Biron’s and Prof. M.J.P.M. van Veldhoven’s expertise in assistance and supervision during the whole process of this study. I would also like to thank Yang Qianjing and Li Lianqi for their help during the data collection, and Lei Lei and Nguyen Thi Nguyet Chi for their insightful comments.

34

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39

Appendix A ­ The questionnaire (English version) 

Introduction letter:

Dear Employee,

Thank you for participating in our research. The information you provide

will help to further understand the effect of different working conditions.

The following questionnaire should take just a few minutes of your time

to complete.

The confidentiality of participants is guaranteed, and seen as priority of

the researchers. Individual survey responses will never be reported. Only

overall totals of all respondents will be used in this research for reporting

purposes.

The completed survey may be returned to the Personal Department before

10th May.

Thank you again for your cooperation.

The research team: Dr. Michal Biron, Tilburg University, the Netherlands

Xuan Wang, Master Student, Tilburg University, the Netherlands

Tel：＋31681777859

E-mail: s692348@uvt.nl

40

(A) RELATIONS WITH SUPERVISOR/CO-WORKERS Think about your supervisor AND about 2 or 3 co-workers to whom you feel closest to at work. Please indicate how often during THE PAST MONTH your supervisor / co-workers:

Your direct supervisor

Your co-workers

Not at all Very often Not at all Very often

1) Talked you through work-related problems, helping you come up with solutions

1 2 3 4 5 1 2 3 4 5

2) Gave you suggestions for easier ways of accomplishing tasks

1 2 3 4 5 1 2 3 4 5

3) Supported you in disagreements or confrontations with supervisor

1 2 3 4 5 1 2 3 4 5

4) Offered you information on unfamiliar policies or procedures

1 2 3 4 5 1 2 3 4 5

5) Provided you with encouragement (positive feedback) about your work

1 2 3 4 5 1 2 3 4 5

6) Offered to assist you with work when you where having a stressful shift

1 2 3 4 5 1 2 3 4 5

7) Listened to your work-related problems 1 2 3 4 5 1 2 3 4 58) Shared his/her professional knowledge

with you 1 2 3 4 5 1 2 3 4 5

41

(B) JOB ATTITUDES

(1) Motivation consequences of absenteeism

Below is a list reasons for missing work. To what extent do you think each of these is an important

reason for being absent?

Not important Very important1. Break from routine 1 2 3 4 5

2. Family activities 1 2 3 4 5

3. Personal illness 1 2 3 4 5

4. Break from supervisor 1 2 3 4 5

5. Family illness 1 2 3 4 5

6. Time with friends 1 2 3 4 5

7. Leisure time 1 2 3 4 5

8. Break from co-workers 1 2 3 4 5

(2) Deterrent consequences of absenteeism Below is a list reasons for not being missing work. To what extent do you think each of these is an important reason for not being absent?

Not important Very important 1. Loss of wages 1 2 3 4 5

2. Co-workers work harder 1 2 3 4 5

3. Heavier work load 1 2 3 4 5

4. Disciplinary time off 1 2 3 4 5

5. Loss of promotional opportunities 1 2 3 4 5

6. Loss of job 1 2 3 4 5

7. Loss of production 1 2 3 4 5

42

(C) HEALTH & GENERAL WELL-BEING The next set of questions has to do with your health. The information that you provide will be helpful for improving health services and the work conditions that affect employees' health. We realize that these questions may concern personal matters. However, please keep in mind that your responses cannot be linked to your name. (1) Somatic symptoms How frequently have you experienced any of the following during the PAST WEEK?

Not at all Extremely

1. Headaches 1 2 3 4 5 2. Faintness or dizziness 1 2 3 4 5 3. Pains in your heart or chest 1 2 3 4 5 4. Pains in your lower back 1 2 3 4 5 5. Nausea or upset stomach 1 2 3 4 5 6. Soreness of muscles 1 2 3 4 5 7. Trouble getting your breath 1 2 3 4 5 8. Hot or cold spells 1 2 3 4 5 10. Numbness or tingling of your body 1 2 3 4 5 11. A lump in the throat 1 2 3 4 5 12. Feeling weak in part of your body 1 2 3 4 5 13. Heavy feelings in arms or legs 1 2 3 4 5 14. How would you describe your health status OVER THE PAST MONTH? Very poor Very good

1 2 3 4 5

43

(2) Burnout For each of the following statements below please circle the number which best indicates how much the statement applied to you OVER THE PAST MONTH.

Not at all Extremely

1. I feel emotionally drained from my work 1 2 3 4 5 2. I feel used up at the end of the workday 1 2 3 4 5 3. I feel burned out from my work 1 2 3 4 5 4. I feel I treat some recipients as if they

were impersonal ‘objects’ 1 2 3 4 5

5. I’ve become more callous towards people since taking this job

1 2 3 4 5

6. I worry that this job is hardening me emotionally

1 2 3 4 5

7. I feel I’m positively influencing other people’s lives through my work

1 2 3 4 5

8. I have accomplished many worthwhile things in my job

1 2 3 4 5

9. I feel good after working with people at work

1 2 3 4 5

(3) Need for Recovery For each of the following statements below please circle the number which best indicates how much the statement applied to you OVER THE PAST MONTH.

Not at all Extremely 1. I find it difficult to relax at the end of a working day. 1 2 3 4 5 2. By the end of the working day, I feel really worn out. 1 2 3 4 5 3. Because of my job, at the end of the working day I feel

rather exhausted. 1 2 3 4 5

4. After the evening meal, I generally feel in good shape. 1 2 3 4 5 5. In general, I only start to feel relaxed on the second

non-working day. 1 2 3 4 5

6. I find it difficult to concentrate in my free time after work. 1 2 3 4 5 7. I cannot really show any interest in other people when I

have just come home myself. 1 2 3 4 5

8. Generally, I need more than an hour before I feel completely recuperated after work.

1 2 3 4 5

9. When I get home from work, I need to be left in peace for a while.

1 2 3 4 5

10. Often, after a day’s work I feel so tired that I cannot get involved in other activities.

1 2 3 4 5

44

(D) DEMOGRAPHICS In this last section, we ask a number of questions about your job, yourself, and your family. Please circle the appropriate response to each question. 1. Employee ID #: ____________ 2. How old are you? (please circle one answer) 21-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60 or older 3. Are you? (please circle one answer) MALE FEMALE 4. Does your work involve supervising other people at work? NO YES 5. What is your marital status? (please circle one answer)

1. Single 2. Married/Living with a Partner 3. Widowed 4. Separated 5. Divorced

6. How many years have you been working in this company? _______ years 7. How much schooling have you had? _______ years 8. Is your spouse currently employed? (please circle one answer) NO YES 9. Below is a list of personal characteristics. How well does each one describe the

kind of person you are?

Not true

Mostly not true

Slightly not true

UncertainSlightly

true Mostly

true Very true

(a) My first impressions of people usually turn out to be right.

1 2 3 4 5 6 7

(b) It would be hard for me to break any of my bad habits.

1 2 3 4 5 6 7

(c) I don’t care to know what other people really think of me.

1 2 3 4 5 6 7

(d) I have not always been honest with myself.

1 2 3 4 5 6 7

(e) I always know why I like things.

1 2 3 4 5 6 7

(f) When my emotions are aroused, it biases my thinking.

1 2 3 4 5 6 7

(g) Once I’ve made up my mind, other people can seldom change my opinion.

1 2 3 4 5 6 7

45

Appendix B ­ The questionnaire (Chinese version) 

亲爱的员工,

感谢您在百忙之中热心参与此项研究. 您所提供的信息将帮忙

我们更好的了解不同工作环境对于绩效所产生的影响.

本研究调查问卷将花费您几分钟时间, 每部分问题都无时间限

制, 无对错之分. 请独立填写, 不要过多的思考. 请务必做完每一题．

问卷说明：该份问卷一共分成四个部分：(A)与上级/同事的关系；

(B)工作态度；(C)健康和总体幸福感；(D)人口统计学特征．

评定方法：问卷采用等级评分，请在每题后面代表相应分数的方

框内划钩。

问卷中涉及的信息将严格保密, 公司其他职员不会看到问卷中

的相关资料，请放心填写, 所收集的数据只用做整体统计分析, 且仅

作为此次研究报告分析之用．

问卷填写完毕后,请于 2009 年 5 月 10 日前交至人事部.

本研究希望能得到您的配合和支持，谢谢！

科学研究组:

米沙尔 白朗 博士, 荷兰蒂尔堡大学

王璇 研究生, 荷兰蒂尔堡大学

联系电话：＋31681777859

E-mail: s692348@uvt.nl

46

(A)与上级/同事的关系 回想一下在工作场合,你的直系上级和在工作场合与你关系最紧密的 2-3 个同事. 请选择在

过去的一个月内,你分别与他们就某些事相互交流的频率.

你的直系上级 你的同事

从未 常常

联系 联系

从未 常常 联系 联系

1) 与你商讨跟工作相关的问题,并帮助你找到

解决方法 1 2 3 4 5 1 2 3 4 5

2) 就某项任务, 给予你建议,使你用更简洁的

方法完成它 1 2 3 4 5 1 2 3 4 5

3) 当你与上级有分歧和争议时,给予你支持 1 2 3 4 5 1 2 3 4 5

4) 当你遇到不熟悉的政策或程序时,给你提供

信息 1 2 3 4 5 1 2 3 4 5

5) 对你的工作,给予鼓励和正性评价 1 2 3 4 5 1 2 3 4 5

6) 当你遇到压力情境时,向你提供帮助 1 2 3 4 5 1 2 3 4 5

7) 认真倾听你的与工作相关的问题 1 2 3 4 5 1 2 3 4 5

8) 与你分享他的专业知识 1 2 3 4 5 1 2 3 4 5

47

(B)工作态度 (1) 缺勤的动因 下述是员工缺勤的一些原因，你认为它们在多大程度上是一个重要的缺勤原因?

完全不重要 非常重要

1. 打破常规 1 2 3 4 5

2. 家庭活动 1 2 3 4 5

3. 自己生病 1 2 3 4 5

4. 与上级关系决裂 1 2 3 4 5

5. 家庭成员生病 1 2 3 4 5

6. 与朋友共处 1 2 3 4 5

7. 休闲娱乐 1 2 3 4 5

8. 与同事关系决裂 1 2 3 4 5

(2) 缺勤的阻力

下述中是促使员工不缺勤的一些原因，你认为它们在多大程度上是一个重要的不缺勤的原

因?

完全不重要 非常重要

1. 扣工资 1 2 3 4 5

2. 同事工作更努力 1 2 3 4 5

3. 更重的工作负担 1 2 3 4 5

4. 留职查看 1 2 3 4 5

5. 失去升职机会 1 2 3 4 5

6. 丢掉工作 1 2 3 4 5

7. 公司生产受损 1 2 3 4 5

48

(C) 健康和总体幸福感 接下来的问卷涉及您的健康状况. 你所提供的信息将帮助改善保健服务和影响员工健康的

工作条件. 以下的问题可能会涉及您的个人信息,但请不用担心,你的回答是在匿名情况下完

成的.

(1) 一般躯体症状 在过去的一周内, 您经历以下所列症状的频率是？

完全不符合 非常符合

1. 头痛 1 2 3 4 5 2. 晕眩/眼花 1 2 3 4 5 3. 胸痛及心脏疼痛 1 2 3 4 5 4. 腰部疼痛 1 2 3 4 5 5. 反胃或胃痛 1 2 3 4 5 6. 肌肉疼痛 1 2 3 4 5 7. 呼吸困难 1 2 3 4 5 8. 身体发冷/发热 1 2 3 4 5 10. 躯体刺痛或麻木 1 2 3 4 5 11. 喉咙哽住 1 2 3 4 5 12. 身体某部分感觉乏力 1 2 3 4 5 13. 手脚感觉沉重 1 2 3 4 5 15. 您怎样评价您在过去一个月内的健康状况?

非常差 非常好

1 2 3 4 5

49

(2) 疲倦 请在下述最符合您近一个月内的感受的数字上画圈.

完全没有 经常发生 1. 我在工作中感觉萎靡不振 1 2 3 4 5 2. 在每天工作日结束时,我感觉疲惫不堪 1 2 3 4 5 3. 我的工作让我累坏了 1 2 3 4 5 4. 我觉得我对待一些接收者像对待无生

命的事物一样 1 2 3 4 5

5. 从事这项工作让我变得对人越来越冷

漠 1 2 3 4 5

6. 我担心这项工作让我情感冷酷 1 2 3 4 5 7. 通过我的工作,我觉得我能够对他人的

生活产生积极的影响 1 2 3 4 5

8. 在我的工作中,我完成了许多有价值的

事情 1 2 3 4 5

9. 与同事一起工作我觉得很愉快 1 2 3 4 5 (3) 休整需要 请在下述最符合您近一个月的感受的数字上画圈.

完全不符合 非常符合

1. 一天的在工作结束后,我觉得很难放松 1 2 3 4 5 2. 一天的在工作结束后,我觉得精疲力竭 1 2 3 4 5 3. 我的工作让我觉得在工作结束后非常的疲

惫 1 2 3 4 5

4. 一般而言,在晚餐后,我都觉得状态良好 1 2 3 4 5 5. 一般而言,我只在第二天休息日才开始觉得

放松 1 2 3 4 5

6. 在工作后之后的闲暇时间,我很难集中注意

力 1 2 3 4 5

7. 当我刚下班回家时,我对任何人都没有兴趣 1 2 3 4 5 8. 一般而言,我需要一个小时以上才能从工作

中完全恢复过来 1 2 3 4 5

9. 刚下班回家后,我需要安静一会 1 2 3 4 5 10. 通常在工作结束后,我觉得非常的疲劳,以至

于无法参加其他活动 1 2 3 4 5

50

(D) 人口统计学特征 最后,我们将问些关于您自己,您的工作及家庭情况的问题. 请如实填写．其中涉及的信息将

严格保密． 1. 您的员工编号: 2. 您的年龄是? (请选一项) 21-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 大于 60 3. 您的性别? (请选一项) 男 女 4. 您的工作包括管理其他员工吗? 不包括 包括 5. 您的婚姻状况? (请选一项)

1). 单身 2). 已婚/与男或女朋友住在一起 3). 丧偶 4). 分居 5). 离婚

6. 您在这个公司工作了多少年?_______ 年 7. 您上学上过多少年? _______ 年 8. 您的配偶目前有在工作吗? (如果您没有配偶，请跳过该题) 没有 有 9. 下面是一些关于个人特征的描述. 请选择与您相符的描述.

完全

不符

基本

不符

有点

不符不确定

有些 相符

基本 相符

完全

相符

(a) 我对其他人的第一感觉往往

是对的 1 2 3 4 5 6 7

(b) 要我改变我的坏习惯很难 1 2 3 4 5 6 7 (c) 我不在乎别人怎么看我 1 2 3 4 5 6 7 (d) 我并不总是对自己诚实 1 2 3 4 5 6 7 (e) 我总是知道为什么我喜欢某

些东西 1 2 3 4 5 6 7

(f) 我的情绪会使我对事物产生

偏见 1 2 3 4 5 6 7

(g) 一旦我下定决心,别人很难改

变我的想法 1 2 3 4 5 6 7

51

Appendix C – Sample descriptive 

Table 2 Sample descriptive Variables M SD Frequency Percent 1-Age group 3.34 1.73

(1) 21 to 24 43 16.5% (2) 25 to 29 53 20.3% (3) 30 to 34 48 18.4% (4) 35 to 39 53 20.3% (5) 40 to 44 35 13.4% (6) 45 to 49 14 5.4% (7) 50 to 54 12 4.6% (8) 55 to 59 3 1.2% (9) >=60 0 0%

2-Gender 1.38 0.49

(1) Male 162 62.1% (2) Female 99 38%

3- Job level 1.52 0.52

(1) Non management 125 47.9% (2) Management 136 52.1%

4-Marriage 1.87 0.77

(1) Single 72 27.6% (2) Married/Living with a Partner 171 65.5% (3) Widowed 5 1.9% (4) Separated 7 2.7% (5) Divorced 6 2.3%

5- Tenure: 9.69 8.14

1 to 5 106 40.6% 6 to 10 69 26.4% 11 to 15 31 11.9% 16 to 20 32 12.3% 21 to 25 9 3.4% >=26 15 5.7%

6- Education level 10.84 3.67

1 to 5 15 5.7% 6 to 10 106 40.6% 11 to 15 108 41.4% >=16 32 12.3%

7- Employment status of Spouse 1.21 0.93

(0) Do not have spouse 90 34.5% (1) Do not have job 27 10.4% (2) Have job 144 55.2%

52

Appendix D – ANOVA of 12­month absenteeism data 

Table 6 One-way ANOVA of 12 month

Sum of Squares df Mean Square F Sig. Between Groups 33.322 12 2.777 .656 .794 Total 13281.995 3144

Appendix E – Paired Sample Test of different supports 

Table 7 Paired Samples Test of different supports

Pairs Mean SD t df Sig. (2-tailed) SS & CS -.331 1.107 -4.835 260 .000

 

Appendix  F  –  The  Interaction  Analysis  of  perceived 

consequences of absenteeism 

Table 8 The interaction effect analysis between MC &DC and Absenteeism

Level Variable Descriptive statistics of hierarchical multiple regression

Descriptive statistics of variables

R R2 df F SE β t Sig.

1 0.25 0.06 1 16.96 Constant 2.46 -1.56 0.12 MC 0.78 0.25 4.12 0.00**

2

0.31 0.10 2 13.82 Constant 3.69 1.36 0.18 MC 0.78 0.20 3.18 0.00**DC 0.68 -0.195 -3.18 0.00**

3

0.31 0.10 3 9.32 Constant 9.89 -0.06 0.95 MC 3.07 0.34 1.42 0.16 DC 2.95 -0.04 -0.13 0.90 MC*DC 0.94 -0.19 -0.61 0.54

53

54

Appendix  G  –Paired  Sample  Test  of  different  period  of 

absenteeism data 

Table 9 Paired Samples Test of different period of absenteeism data

Pairs M SD t df Sig.

Pair 1 01-06，2008 & 06-12，2008 -.27011 4.93231 -.885 260 .377Pair 2 01-06，2008 & 01-06，2009 .03065 3.72737 .133 260 .894Pair 3 06-12，2008 & 01-06，2009 .30077 3.05283 1.592 260 .113