Relationship between job satisfaction & job performance: a meta-analysis.
Job satisfaction plays an important role for an employee in terms of health and well being (Kornhaurser, 1965; Khaleque, 1981) and for an organization in terms of its productivity, efficiency, employee relations, absenteeism and turnover (Vroom, 1964; Locke, 1976; khaleque, 1984). Job satisfaction is a complex variable and influenced by situational factors of the job as well as the dispositional characteristics of the individual (Sharma & Ghosh, 2006). It can be captured by either a one dimensional concept of global job satisfaction or a multi faceted construct capturing different aspects of job satisfaction that can vary independently.
Research examining the relationship between job satisfaction and job performance has been conducted since at least as early as 1945 (e. g., Brody, 1945) and methodology utilized has varied greatly. Some researchers used established scales to measure job satisfaction, while some developed their own. Some used self-report ratings to assess performance, while others used peer or supervisor ratings.
The idea that job satisfaction leads to better performance is supported by Vroom's (1964) work which is based on the notion that performance is natural product of satisfying the needs of employees. The study relating to the relationship between job satisfaction and job performance has now become a research tradition in industrial-organizational psychology. The relationship between job satisfaction and job performance has been described as the "Holy Grail" of industrial psychologists (Landy, 1989). Many organizational theories are based on the notion that organizations that are able to make their employees happy will have more productive employees. Over the years, scholars examined this idea that a happy worker is a productive worker; however, evidence is not yet conclusive in this regard. Empirical studies have produced several conflicting viewpoints on the relationship between job satisfaction and job performance. Strauss (1968) commented, "Early human relationists viewed the morale--productivity relationship quite simple: higher morale would lead to improved productivity". Siegel & Bowen (1971) and Bagozzi (1980) suggested that job performance leads to job satisfaction but not the reverse. Anderson (1984) indicated that autonomy and feedback from the job is significantly correlated with the performance. Keaveney and Nelson (1993) found a non-significant correlation coefficient between job satisfaction and job performance. Manjunath (2008) found job satisfaction of agricultural scientists significantly correlated with their scientific productivity. Ravindran (2007) found that job satisfaction is non-significantly correlated with job performance.
There are conflicting viewpoints on the relationship between job satisfaction and job performance. The proposed study is to synthesize the results of different studies relating to the relationship between job satisfaction and job performance.
Petty et al (1984) provided a limited meta-analysis of the job satisfaction-job performance relationship. They confined their analysis to 16 studies that were published in five journals from 1964 to 1983. Higher and more consistent correlations between overall job satisfaction and performance were indicated than those previously reported. Relationships between job descriptive index measures of job satisfaction and performance were not as high or as consistent as those found between overall job satisfaction and performance. They reported a mean corrected correlation of 0.31 between the constructs.
Laffaldano and Muchinsky (1985) analyzed 217 correlations from 74 studies and found a substantial range in satisfaction-performance correlations across the job satisfaction facets, ranging from a mean "true score" correlation of 0.06 for pay satisfaction to 0.29 for overall job satisfaction. For their primary analysis they averaged the facets performance correlations and reported an average true score correlation of 0.17 between job satisfaction and job performance. In discussing their findings, the authors only made reference to the 0.17 correlation, concluding that job satisfaction and job performance were "Only slightly related to each other".
Because of limitations in the prior analysis, Judge et al. (2001) conducted a new meta analysis on 312 samples. The true correlation between overall job satisfaction and job performance was estimated to be 0.30. Meta analysis was conducted by five facets in the job descriptive index (Smith, Kendall & Hulin, 1969) and found that the average corrected correlation was 0.18 a figure identical to Laffaldano and Muchinsky's (1985) overall estimate. Even with updated meta analysis the facet substantially underestimate the relationship of overall job satisfaction to job performance.
What is Meta-analysis?
A meta-analysis is used to synthesize the results of different studies relating to the relationship between job satisfaction and job performance. Glass (1976) defined meta-analysis as "The statistical analysis of a large collection of studies results for the purpose of integrating the findings". Meta-analysis is regarded as an accurate and objective way to assimilate research findings in the present era. It is a way to summarize, integrate and interpret selected descriptive statistics (e.g., sample correlations) produced by sample studies or experimental outcomes (e.g., d- statistics). There are different methods of meta- analysis. The framework of Rosenthal and Rubin's (1978), Hunter, Schmidt and Jackson (1982), Hedges and Olkin (1985); Davar (2004). Hunter, Schmidt and Jackson (1982) is a popular method used to compute true variance i.e. observed variance net of the measurement error, sampling error and range-restriction. Davar (2004) modified the formulas given by HSJ (1982) framework and provided us with 'An Improved Version' of HSJ (1982). The formulas for two models are given below:
The formulas for true variance models Hunter, Schmidt and Davar (2004) Jackson (1982) framework [bar.r] [[summation][N.sub.i] [sigma] = [[summation] [r.sub.i]/[summation][N.sub.i]] [[r.sub.i]/k [[sigma].sup.2.sub.r] = [[summation] [N.sub.i]([r.sub.i] - [bar.r]).sup.2]/ [summation][N.sub.i] [[sigma].sup.2].sub.r] = [[[summation].sup.k.sub.i=1] [([r.sub.i] - [rho]).sup.2]/k] [[sigma].sup.2.sub.e] [[(1 - [[bar.r].sup.2]).sup.2]/k]/N] [[sigma].sup.2.sub.e] = [[(1 - [[rho].sup.2]).sup.2]/k] [[sigma].sup.2] = [[sigma].sup.2] = [[sigma].sup.2.sub.r] - [[sigma].sup.2.sub.r] - [[sigma].sup.2.sub.e] [[sigma].sup.2.sub.e]
[r.sup.-] = Mean correlation; [[sigma].sup.2.sub.r] = Observed variance; [[sigma].sup.2.sub.e] = Sampling error variance; [[sigma].sup.2] = True variance and k= number of studies; N = [summation] [N.sub.i]; [N.sub.i] = number of observations in a sample study.
Objectives of the Study
The first objective of the study is to generate a meta-analtic estimate for the general relationship between job satisfaction and job performance. This estimate indicates the general magnitude of relationship and is computed as a mean estimate from a set of sample studies. Generally, moderator variables cause differences in sample correlations i.e the extent of relationship may vary from one setting to another. Therefore, we need to know the moderator or contextual factors. Hence, the second objective is to find out the contextual variables that influence the magnitude of relationship.
The data-set for the study has been collected from journals incorporating business and psychological studies, Psychological Bulletin, Indian Applied Psychology & Psychological Abstracts from the Journals section of Kurukshetra University, Kurukshetra. Various online journals like JSTORE, QUESTA, and The Free Online Library have also been visited. 49 correlations have been found from 12 studies from 1971 to 2008. One of the studies reported a negative correlation which has been ignored for two reasons. First, we cannot find the logic for a negative relationship between job satisfaction and job performance. Second, it is incorrect to perform mathematical operations on bipolar coefficients for the determination of mean correlation, observed variance and sampling error variance (Davar, 2004).
Results & Discussion
Table-1 shows the results of a comparative analysis of the above two meta-analysis procedures.
Mean Correlation: HSJ (1982) Procedure uses weighing- based formula of mean correlation. But Davar (2004) gave non weighing based formula of mean correlation. Both methods suggest that correlation coefficients should be corrected for measurement error. HSJ (1982) procedure produces a mean correlation ([bar.r]) =0.24818 (when sample correlations were uncorrected for measurement error) and [bar.r] =0.29222 (when sample correlations were corrected for measurement error). In the same way, Davar (2004) procedure produces a mean correlation (r-bar) =0.25083(when sample correlations were not corrected for measurement error) and p =0.29729 (when sample correlations were corrected for measurement error). The above analysis shows that correction of the individual correlation coefficients for measurement error improves the mean correlation. In the same way weighing of sample correlations (HSJ method) distorts the mean value. It can be explained by taking the figure of mean correlations as computed with Davar (2004) and HSJ (1982) procedure.
The respective t-values for non-weighted corrected mean correlation coefficient is 2.112 and for weighted corrected mean correlation is 2.072 are more than the table value i.e. 1.96 at [a..sub.05], Thus we can conclude that there is a significant association between job satisfaction and job performance. Estimates of t-value of mean correlation coefficient based on uncorrected sample correlation coefficients in both cases suggest that there is no (insignificant) relationship between job satisfaction and job performance. These results suggest that in order to obtain a correct picture of the mean correlation, we must use the measurement corrected correlation coefficients.
True variance estimate tells whether there are moderator factors that dilute or increase the relationship between job satisfaction and performance. Zero true variance implies that there are no moderator or contextual factors. If there is a true variance, it suggests that one or more moderator/extraneous factors influence the relationship between two specified postulates.
It is clear from Table 2 that meta-analysis of uncorrected correlation coefficients with Davar (2004) procedure as well as with HSJ (1982) procedure generates lesser value of true variance as compared to meta-analysis of corrected correlation coefficients. Table 2 shows that once the observed correlation coefficients are corrected for measurement error, true variance rises to the level of 0.02041visa-vis 0.0081in the case of Davar (2004) procedure, and 0.02261vis-a-vis0.01501 in case of HSJ (1982) procedure. Significant true variance indicates that there is a significant variation in effect sizes of job satisfaction. It means there could be one or more moderators which influence the level of effect size of job satisfaction.
As stated earlier, the true variance in the case of corrected correlations for Davar (2004) procedure is 0.02041 and as per HSJ (1982), it is 0.02261. Significant true variance suggests that one or more moderator variables do exist. It means there is substantial variation in the individual correlations across 48 studies, Here, we examine five possible moderators (for example, foreign vs. Indian studies to know the reasons of such variation in the individual correlations. These are shown in further tables.
Foreign Studies vs. Indian Studies: Table 3 shows that out of the 48 studies 34 are foreign and 14 are Indian. The mean correlation for foreign studies is 0.25715 and for Indian studies it is 0.39479. Thus Indian studies have a significant correlation between job satisfaction & job performance and foreign studies find insignificant average correlation. Further, foreign studies reveal a negative true variance (-0.00773) whereas Indian studies show a positive true variance (0.0215). It means one subset generates significant true variance and other subset generate insignificant true variance. Overall, the difference in mean correlation and true variance indicates that there is great likelihood that foreign studies vs. Indian studies act as important moderator for the relationship between job satisfaction & job performance. The relationship varies across foreign settings vis a vis Indian settings.
Occupation Type: Table 4 shows the differences in the satisfaction-performance relationship across occupations of employees. The most significant mean correlation was observed for managers and officers i.e. 0.35705. The weakest correlation was observed by mixed employees (executives and non-executives) i.e. 0.23635. True variance 0.0046 is positive for managers and officers and the rest four subsets (categories) show negative true variance i.e. -0.32593 for telephone operators, -0.00926 for mixed employees (executives and non-executives), -0.05141 for teachers and researchers, 0.06616 for nurses. We treat them as insignificant estimates (negative value of true variance is assumed to be close to zero and hence insignificant). Thus one subset shows significant positive relationship and other subsets show insignificant relationship between job satisfaction and job performance. It means occupation type (managers vs. others act as a moderator variable for the relationship between job satisfaction and job performance.
Overall Satisfaction vs Facet Satisfaction
In the column of 'Facet Satisfaction' in Table 5, we include those studies which found the relationship between different facets of satisfaction and performance individually like security need, social need, esteem need, autonomy need, self actualization need, work itself, promotion, pay, co-workers, supervision etc. And in the column of overall job satisfaction those studies are included which measures the relationship between overall job satisfaction and job performance. Table 5 shows that both the subsets generate negative true variance i.e. -0.0632 for overall job satisfaction and -0.0211 for facet satisfaction. It reveals that both the subsets show insignificant relationship between job satisfaction and job performance. Therefore, variable used for measuring job satisfaction cannot be taken as moderator variable for the relationship between job satisfaction and job performance.
The studies measured job satisfaction with JSQ, JDI, JSS and MSQ. Both MSQ and JDI show different values of mean correlations. True variance is positive only when job satisfaction is measured through JSS scale. And it is negative for all other subsets i.e. -0.07424 when job satisfaction is measured with JSQ scale, -1.55182 with JDI scale, -0.11444 with MSQ scale, -0.27551 with both MSQ and JDI and -0.07375 with other scales. As one subset in the last column of Table 6, scales for two studies are not known and for other two studies, JAS (J&B) & INDSALES (C, F&W) scales were used respectively.
Table 7 shows that mean correlation is stronger i.e. 0.35576 for those studies which measure job performance through self rating and weaker i.e. 0.24602 for those studies which measure job performance through supervisor's rating. True variance is negative for all four subsets i.e. -0.01901 for peer rating, -0.12474 for other measures, 0.02842 for supervisor's rating, -0.03573 for self rating. There are insignificant variations between all the subsets. Thus measuring job performance through different raters cannot be taken as moderator variable for the relationship between job satisfaction and job performance.
The mean corrected correlation improves when it is computed with corrected correlations i.e. 0.29222. On the basis of t-value of mean corrected correlation computed with both HSJ and Davar formulae, we may say that there is positive and significant relationship between job satisfaction and job performance. Moderator variables: foreign studies vs. Indian studies, occupation type and measurement-scale for job satisfaction with different scales affect the magnitude of the relationship between job satisfaction and job performance. The present review, however, has been based on a limited number of studies. To generalize the results number of studies may be increased for a meta-analysis. In the same way, limited moderator analysis could be made due to limited number of studies. Some other moderators like sex of sample, job complexity, job permanency etc. may also be analyzed in future research. According to Rosenthal (1995:190), the overall goal of a meta-analysis is to answer the question: "Where are we now that this meta-analysis has been conducted?".
Statistical Terms & Notations
Sample statistics--The statistics (e.g. correlation co-efficient) based on the sample data is called a sample statistics.
Meta-analytic statistics--The statistics computed with the help of sample statistics produced by different studies is known as metaanalytic statistics, e.g., common correlation (p).
Measurement error--It is the error in the measurement of postulates (variables). Generally, the measurement error arises on account of the lack of construct validity and attenuates the magnitude of a sample correlation coefficient.
Observed variance--It is meta-analytic statistics that measures the extent of variation in the sample correlation coefficients across studies.
Sampling error variance--It is meta-analytic statistics that reflects the amount of sampling error in the data-set of sample correlation coefficients.
True variance--The observed variance net of the sampling error variance ([[sigma].sub.r.sup.2] - [[sigma].sub.e.sup.2]) is termed as true variance (see HSJ, 1982). It is a meta-analytic statistic.
Annexure I Summary of Studies Included in Meta-analysis Sr. No Study N R [r.sub.xx] for [r.sub.yy] for J.S. J.P. 1 Slocum jr. 87 0.13 0.80 0.87 (1971) 2 Slocum jr. 123 0.11 0.80 0.87 (1971) 3 Slocum jr. 87 0.17 0.80 0.87 (1971) 4 Slocum jr. 123 0.19 0.80 0.87 (1971) 5 Slocum jr. 87 0.17 0.80 0.87 (1971) 6 Slocum jr. 123 0.26 0.80 0.87 (1971) 7 Slocum jr. 87 0.19 0.80 0.87 (1971) 8 Slocum jr. 123 0.38 0.80 0.87 (1971) 9 Slocum jr. 87 0.24 0.80 0.87 (1971) 10 Slocum jr. 123 0.39 0.80 0.87 (1971) 11 Wanaus 80 0.3 * 0.84 0.87 (1974) 12 Wanaus 80 0.21 0.76 0.87 (1974) 13 Wanaus 80 0.24 0.83 0.87 (1974) 14 Baird 51 0.35 ** 0.84 0.96 (1976) 15 Baird 116 0.01 0.84 0.96 (1976) 16 Baird 51 Nega- n.a. n.a. (1976) tive 17 Baird 116 0.22 ** 0.84 0.96 (1976) 18 Baird 51 0.28 * 0.84 0.96 (1976) 19 Baird 116 0.24 ** 0.84 0.96 (1976) 20 Baird 51 0.07 0.89 0.96 (1976) 21 Baird 116 0.11 0.89 0.96 (1976) 22 Baird 51 0.21 0.89 0.96 (1976) 23 Baird 116 0.26 ** 0.89 0.96 (1976) 24 Anand & 116 0.22 * 0.77 0.87 Sohal (1981) 25 Anand & 24 0.43 0.77 0.87 Sohal (1981) 26 Anand & 22 0.24 0.77 0.87 Sohal (1981) 27 Anand & 116 0.26 ** 0.77 0.87 Sohal (1981) 28 Anand & 24 0.5 ** 0.77 0.87 Sohal (1981) 29 Anand & 22 0.52 0.77 0.87 Sohal (1981) 30 Anand & 116 0.18 0.77 0.87 Sohal 31 Anand & 24 0.19 0.77 0.87 Sohal (1981) 32 Anand & 22 0.05 0.77 0.87 Sohal (1981) 33 Md. 440 0.64 ** 0.87 0.87 Mosharraf 34 Michell 80 0.14 0.68 0.81 (2006) 35 Michell 81 0.07 0.68 0.89 (2006) 36 Michell 80 0.08 0.68 0.9 (2006) 37 Jayan 204 0.04 0.84 0.84 (2006) 38 S,G, H & 35 0.5 ** 0.83 0.87 Natikar (2007) 39 S,G,H & 65 0.71 ** 0.83 0.87 Natikar (2007) 40 Ravindran 75 0.03 0.76 0.87 C. (2007) 41 Turner 115 0.2 0.89 0.87 (2007) 42 Al- Ahmadi 923 0.31 ** 0.87 0.83 (2008) 43 Al- Ahmadi 923 0.24 ** 0.87 0.83 (2008) 44 Al- Ahmadi 923 0.2 ** 0.87 0.83 (2008) 45 Al- Ahmadi 923 0.08 * 0.87 0.83 (2008) 46 Al- Ahmadi 923 0.2 ** 0.87 0.83 (2008) 47 Al- Ahmadi 923 0.32 ** 0.87 0.83 (2008) 48 Al- Ahmadi 923 0.27 ** 0.87 0.83 (2008) 49 Tapan K. 150 0.69 * 0.75 0.87 Panda Sr. No Sex Ave-rage Citizen Occu- Instrument Age (yea -ship pation used for rs) measuring J.S. 1 M&F Un-known Foreign First-line JSQ Managers (Porter) 2 M&F Un-known Foreign Middle & JSQ Top level (Porter) Managers 3 M&F Un-known Foreign First-line JSQ Managers (Porter) 4 M&F Un-known Foreign Middle & JSQ Top level (Porter) Managers 5 M&F Un-known Foreign First-line JSQ Managers (Porter) 6 M&F Un-known Foreign Middle & JSQ Top level (Porter) Managers 7 M&F Un-known Foreign First-line JSQ Managers (Porter) 8 M&F Un-known Foreign Middle & JSQ Top level (Porter) Managers 9 M&F Un-known Foreign First-line JSQ Managers (Porter) 10 M&F Un-known Foreign Middle & JSQ Top level (Porter) Managers 11 F Un-known Foreign Telephone MSQ Operator & JDI 12 F Un-known Foreign Telephone MSQ Operator & JDI 13 F Un-known Foreign Telephone MSQ Operator & JDI 14 M&F 41 Foreign Mixed JDI Emplo- (S,K&H) yees 15 M&F 41 Foreign Mixed JDI Emplo- (S,K&H) yees 16 M&F 41 Foreign Mixed JDI Emplo- (S,K&H) yees 17 M&F 41 Foreign Mixed JDI Emplo- (S,K&H) yees 18 M&F 41 Foreign Mixed JDI Emplo- (S,K&H) yees 19 M&F 41 Foreign Mixed JDI Emplo- (S,K&H) yees 20 M&F 41 Foreign Mixed JDI Emplo- (S,K&H) yees 21 M&F 41 Foreign Mixed JDI Emplo- (S,K&H) yees 22 M&F 41 Foreign Mixed JDI Emplo- (S,K&H) yees 23 M&F 41 Foreign Mixed JDI Emplo- (S,K&H) 24 M&F Un-known Indian Resear- JSS chers (P&A) 25 M&F Un-known Indian Teachers JSS (P&A) 26 M&F Un-known Indian Extension JSS Workers (P&A) 27 M&F Un-known Indian Resear- JSS chers (P&A) 28 M&F Un-known Indian Teachers JSS (P&A) 29 M&F Un-known Indian Extension JSS Workers (P&A) 30 M&F Un-known Indian Resear- JSS chers (P&A) 31 M&F Un-known Indian Teachers JSS (P&A) 32 M&F Un-known Indian Extension JSS Workers (P&A) 33 M&F Un-known Indian Mixed JSS Bank (B&R) Employee 34 M&F 28.2 Foreign Mixed JDI Employees (S,K&H) 35 M&F 28.2 Foreign Mixed JDI Employees (S,K&H) 36 M&F 28.2 Foreign Mixed JDI Employees (S,K&H) 37 M 43 Indian Managers JAS (J&B) 38 M&F 40 Indian Officers Unknown 39 M&F 40 Indian Inspectors Unknown 40 M&F 37 Indian Mixed JSS Emplo- (Likert) yees 41 M&F 41 Foreign Insurance INDSALES agents (C,F&W) 42 M&F 35 Foreign Nurses MSQ 43 M&F 35 Foreign Nurses MSQ 44 M&F 35 Foreign Nurses MSQ 45 M&F 35 Foreign Nurses MSQ 46 M&F 35 Foreign Nurses MSQ 47 M&F 35 Foreign Nurses MSQ 48 M&F 35 Foreign Nurses MSQ 49 M&F 35 Indian Executives JSS (B&R) Sr. No Instrument Variable Variable used for used for used for measuring measuring measuring J.P. J.S. J.P. 1 JPS Security Peer rating need 2 JPS Security Peer rating need 3 JPS Social Peer rating need 4 JPS Social Peer rating need 5 JPS Esteem Peer rating need 6 JPS Esteem Peer rating need 7 JPS Autonomy Peer rating need 8 JPS Autonomy Peer rating need 9 JPS Self Peer rating actualisation 10 JPS Self Peer rating actualisation 11 JPS Intrinsic Supervisor's rating 12 JPS Extrinsic Supervisor's rating 13 JPS Overall Supervisor's J.S. rating 14 JPS Work itself Supervisor's rating 15 JPS Work itself Supervisor's rating 16 JPS Promotion Supervisor's rating 17 JPS Promotion Supervisor's rating 18 JPS Pay Supervisor's rating 19 JPS Pay Supervisor's rating 20 JPS Co- Supervisor's workers rating 21 JPS Co- Supervisor's workers rating 22 JPS Supervision Supervisor's rating 23 JPS Supervision Supervisor's rating 24 JPQ Average Selection of J.S. research problem (Peer rating) 25 JPQ Average Selection of J.S. research problem (Peer rating) 26 JPQ Average Selection of J.S. research problem (Peer rating) 27 JPQ Average Sources of J.S. selection of research problem (Peer rating) 28 JPQ Average Sources of J.S. selection of research problem (Peer rating) 29 JPQ Average Sources of J.S. selection of research problem (Peer rating) 30 JPQ Average Publication J.S. (Peer rating) 31 JPQ Average Publication J.S. (Peer rating) 32 JPQ Average Publication J.S. (Peer rating) 33 Un-known Overall Supervisor's J.S. rating 34 JPS Different Supervisor's (Wright facet rating & Bonett) 35 OCBS Different Supervisor's (Bateman facet rating & Organ 36 JPS & Different Supervisor's OCBS facet rating 37 PRS Intrinsic& Average (J&D) Extrinsic rating (Self, Peer, & Supervisor's rating) 38 JPS Overall Self rating (Sunderas- J.S. wamy) 39 JPS Overall Self rating (Sunderas- J.S. wamy) 40 JPQ Intrinsic & Unknown Extrinsic 41 Performance Overall Self rating Questionnaire J.S. 42 PAF Overall Self rating J.S. 43 PAF Supervision Self rating 44 PAF Promotion Self rating 45 PAF Pay Self rating 46 PAF Work Self rating condition 47 PAF Job itself Self rating 48 PAF Relationship Self rating at work 49 Unknown Overall Unknown J.S. * Significant at 5% ** Significant at 1% Note: -- Mixed Employees comprises executives & non-executives. JSQ(PORTER)--Porter(1961)'s job satisfaction questionnaire, measure need satisfaction, contained 12 items based upon Maslow's theory of motivation. MSQ--Minnesota Satisfaction Questionnaire contained 20 items measure overall satisfaction and intrinsic versus extrinsic satisfaction. JDI(S, K&H)--Job Description Index developed by Smith, Kendall and Hullin(1969) measure job satisfaction with five facets of the job: the work itself, their supervisor, pay, promotion opportunities and co-workers. The scores on the five sub scale can be summed to obtain an overall measure of job satisfaction. JSS (P&A)--Pelz and Andrew's (1966) job satisfaction scale measure satisfaction through different aspects of the job satisfaction. JSS (B&R)--Brayfield--Rothe Scale measures overall job satisfaction. JAS (J&B)--Job Attitude Scale of Jayan and Balachandran (2004) contains three domains of Job Attitude: Job Involvement, Job Commitment and Job Satisfaction. The items are designed to include intrinsic attributes of the job as well as extrinsic attributes. JSS (Likert)--Likert's five point scale measures both intrinsic and extrinsic job satisfaction. INDSALES (C,F &W)--INDSALES, A scale created by Churchill, Ford and Walker (1974) measures job satisfaction over several dimensions.
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S.C. Davar is Professor & Ex. Chairman, Department of Commerce, Kurukshetra University, Kurukshetra. Ranju Bala (email@example.com) is Assistant Professor & Off. Principal, M.P.M.S.D. Girls College, Ismailabad, Kurukshetra.
Table 1 Mean Correlation Coefficients for the Relationship between Job Satisfaction and Job Performance Number of Uncorrected Corrected Studies=48 Non-weighted 0.25083 0.29729 Mean Davar (2004) t-value 1.757 2.112 * Weighted Mean (HSJ 1982) 0.24818 0.29222 t-value 1.738 2.072 * * significant at 5% ([a..sub.05]=1.96) Table 2 Davar (2004) vs. HSJ (1982) Procedures: A Comparative Analysis Number of studies (k) = 48 Uncorrected Corrected for for measurement measurement error error Mean Correlation (non-wei-ghted) 0.25083 0.29729 Davar (2004) Mean Correlation (weighted) 0.24818 0.29222 HSJ (1982) Observed Variance 0.02639 0.03772 Davar(2004) 0.0191 0.02649 HSJ (1982) Sampling Error Variance 0.01829 0.01731 Davar (2004) 0.00409 0.00388 HSJ(1982) True Variance 0.0081 0.02041 Davar (2004) 0.01501 0.02261 HSJ(1982) Table 3 Moderator Analysis: Foreign Studies vs. Indian Studies Foreign Indian Studies Studies Number of Studies (k) 34 14 Mean Correlation 0.25715 0.39479 Observed Variance 0.01792 0.0724 Sampling Error Variance 0.02565 0.0509 True Variance -0.00773 0.0215 Table 4 Moderator Analysis: Occupation- Type Managers & Telephone Mixed Officers Operators Employees Number of Studies 14 3 14 Mean Correlation 0.35705 0.29721 0.23635 Observed Variance 0.05898 0.00154 0.03239 Sampling Error Variance 0.05438 0.32747 0.04165 True Variance 0.0046 -0.32593 -0.00926 Teachers & Nurses Researchers Number of Studies 9 7 Mean Correlation 0.3516 0.27234 Observed Variance 0.03393 0.00801 Sampling Error Variance 0.08534 0.07417 True Variance -0.05141 -0.06616 Table 5 Moderator Analysis: Variable Used for Measuring Job Satisfaction Overall Facet Satisfaction Satisfaction Number of Studies 21 27 Mean Correlation 0.35801 0.25007 Observed Variance 0.06495 0.01145 Sampling Error Variance 0.03619 0.03255 True Variance -0.0632 -0.0211 Table 6 Moderator Analysis: Measurement of Job Satisfaction with Different Scales JSQ JDI JSS MSQ Numbers of Studies 10 12 12 7 Mean Correlation 0.26730 0.19242 0.39926 0.27234 Observed Variance 0.01198 0.01176 0.06477 0.00801 Sampling error variance 0.08622 1.56358 0.05888 0.12245 True variance 0.07424 -1.55182 0.00589 -0.11444 MSQ & JDI OTHERS Numbers of Studies 3 4 Mean Correlation 0.29721 0.42471 Observed Variance 0.00154 0.09419 Sampling error variance 0.27705 0.16794 True variance -0.27551 -0.07375 Table 7 Moderator Analysis: Measuring Job Performance through Different Raters Peer Rating Other Measures Supervisor's Rating Number of Studies 19 3 16 Mean Correlation 0.30723 0.31290 0.24602 Observed Variance 0.02415 0.14652 0.02674 Sampling Error Variance 0.04316 0.27126 0.05516 True Variance -0.01901 -0.12474 -0.02842
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|Author:||Davar, S.C.; RanjuBala|
|Publication:||Indian Journal of Industrial Relations|
|Date:||Oct 1, 2012|
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