ABSTRACT
This study examines the relationships between a number of personal attributes, public service motivation (PSM) and employee performance. Both formal and informal performance measures have been utilised.
Structural equation modelling (SEM) outcomes indicate that age is the only personal attribute that significantly and directly influences PSM. The results of this study show that those individuals who have PSM tendencies leaning towards public interest, compassion and self-sacrifice have a more altruistic disposition. Furthermore, the findings suggest that the attraction to policy making PSM dimension has a positive relationship with all the dimensions of the informal performance measure, and indicates that individuals who have this particular PSM tendency are inclined to be more self-seeking and self-centred.
Moreover, the findings suggest that informal performance measures may be suitable for assessment purposes in a public sector administrative environment. The paper finalises by identifying the limitation of the research in relation to the use of ordinal variables in conjunction with SEM.
Impact of Personal Characteristics and Public Service Motivation on
the Performance of Public Sector Employees in Malta
INTRODUCTION
The purpose of the paper is to investigate the impact of personal characteristics and public service motivation (PSM) of public service employees on their performance. Since high levels of PSM is important for the successful implementation of operational and organisational change, knowledge about the relationship between personal attributes and PSM on the one hand, and their impact upon performance on the other, is considered to be valuable for organisations.
PSM is defined by Perry (1997, p. 182) as ‘the individual predisposition to respond to motives primarily or uniquely grounded in public institutions and organizations’. This suggests that PSM is directly applicable to the specific mission of government. Moreover, research studies indicate that public sector entities are more likely to employ individuals whose ideals and desires are compatible with the public service mission of the organisation (Crewson 1997; Perry 1997). Wright (2003) also argues that the composition of the public workforce is expected to reflect the nature of the work in the public sector by attracting employees who desire greater opportunities to fulfil higher-order needs and altruistic motives by performing public service. Wright (2003) posits that it is these individual attributes that are often viewed as the key to motivating public sector employee behaviour. Wittmer (1991, p. 369) suggests: ‘understanding the values and reward preferences of public managers is essential in structuring organizational environments and incentive systems to satisfy those preferences’. Hence, there is some agreement that the values emanating from PSM appear to have potentially significant consequences for public service organisational performance.
An important issue to be addressed when considering performance is the performance measurement method. The literature indicates that most Public Service organisations tend to use formal performance measures. However, these measures ignore dimensions of work behaviour such as, organisational citizenship or more informal duties that are not an integral part of one's work, for instance, doing a better job, making an effort above and beyond formal requirements. Therefore, in addressing performance both formal and informal measures should be considered.
THEORETICAL FRAMEWORK
Understanding the Concept of Public Service Motivation
PSM focuses on motives linked to public institutions and organisations. In fact, Perry (1996) specifically makes reference to ‘motives’ when defining PSM, where these motives refer to a sense of psychological needs. He posits that public service is a special calling. Furthermore, he argues that the level and type of an individual’s PSM and the motivational composition of a public service organisation’s workforce affect individual job choice, job performance, as well as organisational effectiveness.
Perry’s conceptualisation of PSM is based on a multifaceted dimensional construct that includes: (a) Attraction to policy making, referring to the employee’s strong desire to participate in the formulation of public policy; (b) Commitment to public interest, which concerns an employee’s unique sense of civic duty; (c) Compassion denoting an employee’s strong desire for patriotism and benevolence; and (d) Self-sacrifice referring to an employees’ strong desire to act for causes that protect, advocate, and work for the good of the public regardless of personal consequences.
Perry (2000) explains PSM theoretically by expanding on Shamir’s (1991) work regarding different types of socialisation. He defines four premises that form the basis of the so-called alternative theory of motivation: (1) rational, normative and affective processes motivate humans; (2) people are motivated by their self-concepts; (3) values are endogenous to any theory of motivation; and (4) preferences are learnt in social processes.
Perry (2000) presents a process theory of PSM that applies Bandura’s (1986) concept of reciprocal causal relationships among three factors, namely, environmental influences; cognitive and other personal factors; and behaviour. He divides the critical variables into four domains: (1) Socio-historical, referring to the environmental variables that shape individual preferences and motives related to life events, such as education, parental relations, career qualifications, and religion; (2) Motivational, concerning situational factors that influence one’s behaviour in organisations, such as, job attributes, the work environment, and organisational incentives; (3) Individual attributes denoting some conceptually distinct components, including: ability and competencies; self-concept based on the individual’s values and identity that entail creating incentives to respond to one’s behaviour; and self-regulation referring to the individual’s self-directive capabilities that may originate from social and cultural cues,
including evaluative standards modelled by others; and (4) Individual behaviour flowing either from a logic of consequence or from a logic of appropriateness and is dependent on the nature of the self-regulatory effect. It should be noted that logic of consequence is consistent with rational choice and allows the individual to weigh costs and benefits, seeking to maximise utility. Whereas, logic of appropriateness brings into motion non-consequentialist options, whereby, the individual determines attractiveness of different actions according to how consistent they are with their internal standards. Thus, the primary motivators for public sector employees are the interests that attract them to public service.
The literature suggests that the Perry’s PSM scale has been utilised in various studies, particularly in the United States, and has been found to be valid and reliable (Perry & Coursey, 2005; Wright & Pandey, 2005).
Understanding the Concept of Performance
The literature suggests that work performance may be dependent on organisational structuring. For instance, in individual-oriented settings, performance reflects both production output and mitigating components, such as, the availability of appropriate resources (Starcher, 1996). On the other hand, group-oriented systems are characterised by the empowerment of employees to take decisions, giving them larger work latitude (Lawler, 1992) by having lower control rules accompanied by an innovator mentality, participation in decision making, loyalty and altruism leading to higher productivity (Long, 2001; Kim, 1998). Furthermore, under an organisational-oriented system, loyalty is valued as immediate performance, with the entity expecting the individual to defend the organisation at all times. However, irrespective of the organisational work performance structuring the major concern confronted by researchers and practitioners alike is the performance measurement method.
Some researchers distinguish between two types of individual performance, namely in-role (formal), and extra-role (informal). Vigoda (2001) views formal performance as a set of required behaviours one is expected to display in one's job and for which one is directly rewarded. However, he suggests that an alternative pattern of performance evaluation takes into consideration other, more informal obligations that are not an integral part of one's work, reflecting the so-called pro-social activities and altruism in the workplace, such as, doing a better job, making an effort above and beyond formal requirements.
The literature suggests that generally Public Service organisations adopt formal performance measures. For instance, senior managers are normally assessed through a pay-for-performance (PFP) scheme, where individuals are rated on a progression of scales, with each scale providing the basis for a performance bonus. However, Eisenberg and Ingraham (1993) argue that PFP systems may not be compatible with the Public Service operating environment, since these systems stress decentralisation of decision-making and individual discretion, while Public Service operating environments have typically stressed equal treatment of employees, centralisation and standardisation.
For middle management, a Performance Management Programme (PMP) is normally used. This system provides regular feedback to employees about their performance; allows the supervisor and employee to jointly develop a training plan to resolve identified weaknesses; and links the reward to the provision of a permanent pay increment based upon merit. However, Taylor and Pierce (1999) found that employees assessed under a PMP system tended to report lower ratings compared with expectations, and expressed concern with inequity in ratings and payout.
Furthermore, the lower Public Service grades are usually assessed annually based on performance of duties; personality and character; and discipline. However, empirical evidence conducted by Varma et al. (1996) and Bain (2001) suggest that these systems are very subjective; are strongly influenced by interpersonal affect; and supervisors develop a positive or negative attitude towards employees based upon the performance they observe over a period of time.
Welbourne et al. (1998) argue that formal performance measures do not take into account dimensions of work behaviour that reside beyond the scope of the specific job itself, thus creating problems for organisations that wish to reward organisational citizenship. However, Vigoda (2001) argues that an informal performance measure takes into account the pro-social activities and altruism in the workplace.
Welbourne et al. (1998) propose an informal performance measure based upon role theory known as role-based performance. This concept treats employee performance as a function of both the individual and the organisation, thus combining the psychological and sociological viewpoint. However, this concept has difficulties, in that: organisations are different; organisations have disparate expectations of their employees; and role saliency is likely to vary across organisations. These factors make it problematic to construct a generalised performance measure using the role-based approach.
Some researchers view employee loyalty as a good measure of informal performance. However, the lack of a universal definition of loyalty is leading to confusion since a close scrutiny of various scales suggests an association with Organisational Commitment and Organisational Citizenship Behaviour (Powers, 2000; Eskildsen & Nussler 2000). For instance, Solomon (1992) defines employee loyalty as a willingness to remain with the organisation; Mowday et al. (1982) views loyalty as going beyond the call of duty; while Laabs (1996) defines loyalty as behaving altruistically. An alternative measure of informal performance is fairness and justice
assessed by the perception of organisational politics (POPS).
Both Kacmar et al. (1999) and Vigoda (2000) argue that individuals who perceive that organisational politics have cheated them out of a deserved opportunity are likely to exhibit unconstructive reactions, such as, apathy, dissatisfaction, anxiety and turnover, thus negatively affecting their performance. However, organisations that create a culture and ambiance of equity and fair distribution of social and political resources may increase an employee’s formal performance and their willingness to engage in organisational citizenship behaviour (Vigoda, 2000). Finally, Kacmar et al. (1999) contend that reward distribution in political work environments is at odds with equity theory, in that receipt of organisational rewards due to political manoeuvring is likely to be perceived as unfair, and accordingly de-motivate employees to perform well.
Relationships between Personal Attributes, PSM and Performance
The personal attributes included in this study consist of organisation tenure, age, gender, job grade, job tenure, education, salary, and family life-cycle status. In a study of the antecedents of PSM, Perry (1997) found relatively low correlations between the dimensions of PSM on the one hand and education, age, income and gender on the other. Furthermore, the regression for these variables with PSM indicates that education had a positive relationship with overall PSM and the public interest dimension, whilst age had a positive relationship with only public interest. Moreover, income had a negative relationship with public interest, while gender had a negative relationship with both public interest and self-sacrifice. It should be noted that the significance level of these relationships were mostly boarder-line cases (ranging from .01 to .04). These findings were generally confirmed by Naff and Crum (1999). In the Naff and Crum (1999) study PSM was found to be positively related to education, age, job level, and organisational tenure, with women having slightly higher PSM.
Perry and Wise (1990) formulated three propositions regarding PSM, one of which specifically states that in public organisations, PSM is positively related to performance. Naff and Crum (1999) provide some evidence to support this proposition. They found a significant positive relationship between the PSM of federal government employees on the one hand and job satisfaction, performance, intention to remain in the government, and support for the government’s reinvention efforts on the other. Furthermore, Brewer and Selden (2000) found PSM to be a modest but important predictor of organisational performance. Moreover, Kim (2005) in a study of the South Korean public service confirms these results in that PSM is positively related to organisational performance. However, Alonso and Lewis (2001) argue that the association between PSM and performance is noticeably not yet robust. Furthermore, if the equity and procedural justice motivation theories are taken into consideration, the results suggest a significant relationship between equity perceptions and performance (Schappe, 1996). These findings support the argument that perceptions of fair treatment sway an employee's general affective response to the organisation.
Research Model: Personal Attributes, PSM and Performance
Based upon the above literature review a theoretical model as shown at Figure 1 forms the basis of this empirical study. The research question is: What are the relationships between an individual’s personal attributes, PSM and performance? Hence, the primary hypothesis is: An employee’s performance is a consequence of both the individual’s personal attributes and PSM.
RESEARCH METHODOLOGY
Sample and Design of the Study
The model at Figure 1 was tested by administering a questionnaire. The research population consisted of over 3,400 public officers occupying administrative grades that cover the full spectrum of administrative jobs in all Government Ministries. Two pilot
PSM Performance
Personal Attributes
studies consisting of 25 and 250 respondents respectively were conducted to test the psychometric qualities of the instruments. The questionnaire was administered on a census basis during paid working hours, and was incorporated in a series of change management seminars. Employees were guaranteed anonymity and their participation was voluntary. The overall response rate was 71.5% of which 51% were female.
Measures
The items for both the PSM and Informal Performance scales have been measured by using a five-point rating scale, ranging from ‘definitely agree’ to ‘definitely disagree’.
Personal Attributes included demographic data consisting of one-item measures as described previously.
Public Service Motivation was measured using Perry’s (1996) instrument consisting of 24 items: attraction for public policy making (3 items); public interest (5 items); compassion and self-sacrifice (8 items each).
Informal Performance was measured by the Perception of Organisational Politics Scale (Kacmar et al., 1999): political-behaviour (2 items) measured the degree of internal politics perceived to be present in the organisation, in terms of power of individuals or groups of individuals; go-along-get-ahead (5 items) measured the degree the organisation is perceived to give individuals the opportunity to express their feelings without repercussions to their careers; and pay and promotion (5 items) measured the degree the organisation is perceived to be equitable in awarding pay or promotions.
Formal Performance was measured by: supervisor and self rating. Supervisor rating was based on having the respondents recall the rating their supervisor awarded them in the most recent annual performance appraisal review; whilst self-rating performance was based on having the respondents grading themselves out 10.
Data Analysis
Structural equation modelling (SEM) is the major statistical method applied. SEM allows studying simultaneously the relationships for each of a set of dependent variables and provides the most suitable and efficient estimation technique for a series of separate multiple regression equations estimated concurrently. Unlike multivariate analysis of variance and canonical correlation that allow only a single relationship between dependent and independent variables, SEM allows multiple relationships, hence permitting the model at Figure 1 to be tested holistically.
Furthermore, SEM using confirmatory factor analysis was utilised to determine the validity of the PSM and POPS constructs. For a construct to be valid it must be shown that both convergent and discriminant validity have been achieved. Anderson and Gerbing (1988) suggest that an appropriate method for evaluating convergent validity in SEM is to examine the construct loadings and determine whether each indicator’s estimated coefficient is significant, that is, whether the estimated coefficients are greater than twice their standard error. The results indicate that all the estimated coefficients were found to be far greater than twice their standard error. Therefore convergent validity was achieved. Moreover, Bagozzi and Phillips (1982, p. 476) suggest that
discriminant validity in SEM is achieved if the unconstrained models have a significantly lower Chi-square than constrained models. The unconstrained models for both constructs appeared to have a significantly lower Chi-square compared with the constrained models. Hence, discriminant validity has been achieved.
Composite reliability measuring internal consistency for path analysis was adopted. High composite reliability indicates high reliability with normally acceptable threshold of ≥0.50 (Hair et al., 1998, p. 612). Table 1 illustrates that the composite reliabilities for both the PSM and POPS scales are ≥0.50.
Table 1. Scale Reliabilities: Composite Reliability of Exogenous Constructs
Exogenous Constructs Composite Reliability
Exogenous Constructs Composite Reliability
Informal Performance (POPS) Public Service Motivation
Political Behavior .67 Attraction to Policy Making .59
Go Along-Get Ahead .66 Public Interest .70
Pay and Promotion .66 Compassion .72
Self-sacrifice .83
Predictive validity of measures, that is, the ability to predict what theoretically should be predicted in the model was tested by evaluating the correlation between dependent and independent variables. EQS 6.0 has been used in the SEM analysis to test simultaneously the hypothesised relationships between model variables. EQS provides weights indicating strength and direction of the relationship among the hypothesised variables. The SEM methodology adopted in this study adheres to the seven-stage approach suggested by Hair et al. (1998).
Model validity was achieved through cross-model validation attained in three phases. The first phase consisted of randomly dividing the collected data into two data
sets. One data set comprised a 20% random selection of the data collected from respondents, whereas the second data set comprised the remaining 80% of the data collected. The second phase consisted of conducting SEM analysis by calculating the structural fit index (measured by R2) for both data sets. The third phase consisted of examining the differences of the calculated structural fit indices obtained for each data set (Bluedorn, 1982). The closeness of the explained variances for each data set determined the extent of the validity of the model. Furthermore, the estimated parameters have been tested for feasibility and acceptability (Bentler, 1995, p. 610). No negative error variances have been found and all standardised coefficients appear to be less than 1.0 (Hair, 1998, p. 610).
RESULTS Descriptive statistics
Table 2 provides basic descriptive statistics, reliability coefficients (where relevant), and bivariate correlations for model variables. Generally, the findings show relatively high positive correlation between PSM and the personal attributes with the exception of position tenure, gender, family life cycle status, and education.
Table 2. Means, Standard Deviations, Reliability Coefficients (Cronbach’s alpha at the diagonal), and Correlations between Variables
Variable M Sd Kurtosis 1 2 3 4 5 6 7 8 1 PSM 3.67 0.64 0.560 .88 2 Policy 2.40 1.03 -0.783 .37** .55 3 Public-Interest 3.75 0.75 0.887 .68** .24** .69 4 Compassion 3.95 0.72 0.625 .61** .08** .42** .73 5 Self-Sacrifice 3.63 0.76 0.420 .80** .24** .57** .51** .83 6 Salary 4932 1393 8.492 .24** .05* .21** .22** .24** n/a
7 Organisation tenure 16.85 11.19 -0.952 .32** .06** .29** .27** .32** .74** n/a
8 Age 38.18 11.79 -1.254 .36** .09** .32** .28** .37** .68** .89** n/a 9 Gender 1.47 0.50 -1.984 -.10** -.05* -.08** -.05* -.10** -.43** -.43n -.45** 10 Grade 2.63 1.75 2.366 .24** .05* .21** .22** .24** 1.00** .74** .68** 11 Position tenure 5.06 3.21 4.185 .08** -.02n .10** .10** .09** -.14n .24** .19** 12 Education 1.81 0.77 -0.110 -.13** -.05* -.14** -.06* -.11** .10** -.26** -.29** 13 Family status 3.30 2.09 -1.581 .22** .04n .21** .18** .21** .46** .59** .63** 14 Supervisor rating 1.77 0.60 1.365 -.09** .01n -.09** -.11** -.10** -.03n -.04n .00n 15 Self rating 8.05 1.11 6.252 .03n -.05* .06* .06* .05* .07** -.01n -.02n 16 Political 2.55 1.03 -0.584 -.02n .09** -.01n -.08** -.02n .05* .02ns .05* 17 Go-Along To-Ahead 2.70 0.86 -0.321 .10** .18** .11** -.03n .10** .11** .08** .10** 18 Pay & promotion 3.01 0.81 0.076 .14** .23** .13** .03n .12** .02n -.02n .02n 19 POPS 2.80 0.71 0.054 .11** .25** .11** -.03n .09** .08** .04n .07** Note. ** p < .01; * p < .05; n = not significant. N=2135.
Table 2. Means, Standard Deviations, Reliability Coefficients (Cronbach’s alpha at the diagonal), and Correlations between Variables (Continued)
Variable 9 10 11 12 13 14 15 16 17 18 19
9 Gender n/a
10 Grade -.43** n/a
11 Position tenure -.02n -.14** n/a
12 Education .05* .10** -.18** n/a
13 Family status -.41** .46** .12** -.22** n/a
14 Supervisor rating -.11** -.03n -.10** -.04n .04n n/a
15 Self rating .08** .07** .02n .15** -.01n -.37** n/a
16 Political .03n .05* -.02n -.02n .02n .01n -.02n .67
17 Go-Along-to-Ahead .03n .11** .01n -.01n .06** -.02n -.03n .49** .66
18 Pay & promotion .05* .02n -.05* -.03n -.02n .04n -.05* .30** .36** .66
19 POPS .04* .08** -.03n -.03n .03n .02n -.05* .63** .73** .66** .79
Note. ** p < .01; * p < .05; n = not significant. N=2135.
Furthermore, PSM has a low correlation with the formal performance measures of
self-rating and supervisor rating, and the dimensions of informal performance (POPS). The attraction to policy making PSM dimension appears to have low correlation with the personal attributes, but moderate correlations with the informal performance dimensions of go-along-get-ahead, and pay and promotion.
Generally, the PSM public interest, compassion and self-sacrifice dimensions appear to have high positive correlation with the personal attributes except for gender. However, both gender and education have a negative correlation. Moreover, these PSM dimensions have a low correlation with the dimensions of POPS and both the formal performance measures. Table 3 provides a comparison of the correlation findings between the current and the Perry (1996) studies. Generally, the current study shows higher correlation between the PSM dimensions and the personal attributes.
Table 3. Comparison of Correlation Findings between Current Study and Perry (1996)
P S P S P S P S P S P S P S P S Variable 1 1 2 2 3 3 4 4 5 5 6 6 7 7 8 8 1 PSM 2 Policy .30* .37** 3 Public Duty .70* .68** -.17* .24** 4 Compassion .56* .61** .19* .08** .16* .42** 5 Self-Sacrifice .70* .80** -.22* .24** .61* .57** .02* .51** 6 Education .06* -.13** -.04* -.05* .08* -.14** .02* -.06* .07* -.11** 7 Age .06* .36** .03* .09** .15* .32** -.08* .28** .05* .37** .14* -.29** 8 Salary .00 .24** -.02* .05* .05* .21** -.07* .22** .02* .24** .33* .10** .66* .68** 9 Gender -.03* -.10** -.02* -.05* -.08* -.08** .08* -.05* -.03* -.10** .11* .05* -.20* -.45** -.24* -.43** Note. P = Perry (1997); S = Current Study (** p < .01; * p < .05)
Both studies show gender as having a negative correlation with PSM and all its dimensions, except for the compassion dimension, where in Perry’s study this dimension had a positive correlation.
Model testing
Various SEM revisions have been tested in the light of the cross-validation process. After removing offending linkages, the revised model depicted at Figure 2 showing the standardised coefficients, appeared to provide the best-fit indices for each data set.
The maximum likelihood method has been used to investigate the covariance matrix of the items. The goodness-of-fit of the model was evaluated using absolute and relative indices. The absolute goodness-of-fit indices that have been calculated were the goodness-of-fit index (GFI), adjusted goodness-of-fit index (AGFI), comparative fit index (CFI) and the root mean square error of approximation (RMSEA). Furthermore, GFI, AGFI and CFI values ≥0.90 and RMSEA values ≤0.08 are indicative of an acceptable fit (Cudeck and Browne, 1993).
Since the χ2 goodness-of-fit statistic is sensitive to sample size, in that the probability of rejecting the hypothesised model increases with increasing sample size
Go-Along Get-Ahead Formal Performance: Supervisor Rating Politics 0.15* Age 0.31* 0.31* 0.09* 0.06* -0.10* 0.13* 0.23* 0.16* 0.77* 0.12* Compassion Attraction to Policy Making Self Sacrifice Public Interest 0.22* 0.06* 0.68* -0.08* 0.52*
Figure 2. Revised Model Showing both Formal and Informal Performance Measures
Pay & Promotion
Informal Performance:
(Byrne, 2001), it was decided to rely on another fit index, namely the normed-fit index (NFI). As a rule of thumb, NFI values ≥0.90 indicate a good fit (Hoyle, 1995).
Table 4 illustrates that model fit is very good for all data sets. As an indicator of a good fit, Bentler (1990) proposed the comparative fit index (CFI) as a means of taking sample size into account. Although a value ≥0.90 was originally considered typical of a well-fitting model (Bentler, 1992), a revised cut-off value close to .95 has recently been advised (Hu and Bentler 1999). The results show that the CFI for the three samples is ≥0.99, with RMSEA values ≤0.05 (.034, .035, .017 respectively), thus it may be concluded that the resultant model is a very good fit. Generally, the indices for overall model goodness-of-fit provide ample support for accepting the hypothesised model.
Table 4. Performance Model Fit Indices: Antecedents and Consequences of PSM and OC
Model N χ2 Df GFI AGFI RMSEA NFI CFI Full sample 80% sample 20% sample 1217 958 259 38.85 34.49 17.19 16 16 16 .993 .992 .986 .981 .978 .960 .034 .035 .017 .984 .982 .967 .990 .990 .998
The closeness of the explained variances (R²) in the different samples determines the extent of model validity (Bluedorn, 1982). Table 5 suggests that cross-validation has produced very good results with all variables having very small differences in the explained variances.
Table 5. Results of Model Cross-Validation Showing R² for the Three Samples
Predicted Variable Full Sample
20% Sample 80% Sample Difference in R² for 20-80% Sample Formal Performance Supervisor Rating .014 .017 .006 .011 Informal Performance Political Behaviour .485 .475 .521 .046 Go-Along Get-Ahead .638 .651 .620 .031
Pay & Promotion .326 .332 .321 .011
Public Service Motivation
Attraction to Policy .110 .116 .090 .026
Public Interest .568 .557 .610 .053
Compassion .396 .408 .357 .051
Figure 2 offers a potential reply to the research question being examined: What are the relationships between an individual’s personal attributes, PSM and performance?
Of the eight personal attributes only age entered the model. The path coefficients of the revised model illustrate that, like previous empirical outcomes, age is positively related to the PSM dimensions. Age did not have a direct link with any of the performance measures. Hence, the hypothesis that performance is a consequence of both the individual’s personal attributes and PSM is rejected.
DISCUSSION
The SEM outcomes show that age is the only personal attribute that has a relatively strong positive influence on the PSM dimensions, particularly, public interest and self-sacrifice, followed by compassion. These findings partly confirm previous studies. The findings suggest that as employees get older their level of PSM increases. Furthermore,
organisation tenure and position tenure did not enter the model, suggesting that it is age
that influences the PSM dimensions and not an employee’s length of membership in the organisation.
Moreover, the SEM findings indicate the self-rating performance did not enter the model. However, almost half the respondents did not reply this single item question, indicating that the respondents did not feel comfortable with rating themselves. This could be attributed to the national culture, where a Mediterranean mentality normally associates performance rating as being a supervisory function.
The supervisor rating performance measure required respondents to recall the rating their supervisor awarded them in the most recent annual performance appraisal. Once again, a large number of respondents did not reply this question. However, the SEM outcomes indicate that supervisor rating had a low positive relationship with only the compassion PSM dimension. The findings show consistency, in that as one would expect, the compassion PSM dimension appears to be negatively related to both the
political behaviour and go-along-get-ahead informal performance dimensions, with no relationship with pay and promotion equity, thus depicting an altruistic tendency.
Furthermore, the compassion and self-sacrifice PSM dimensions are both related to the go-along-get-ahead informal performance dimension but they are not related to pay and promotion equity. These findings suggest that respondents that have compassion
As one may recall, the attraction to policy making PSM dimension is associated with individuals who have a strong desire to participate in the formulation of public policy thus reinforcing one’s image of self-importance. The results appear to support this notion since the attraction to policy making is shown to have a moderate to high positive relationship with all the dimensions of the informal performance measure, particularly, the pay and promotion equity dimension. These findings suggest that individuals with strong attraction to policy making tendencies appear to be more self-centred or self-seeking.
CONCLUSION
There is no doubt that the informal performance measure is a useful and important topic to take into account in a public sector environment. In the absence of formal output standards, it is difficult to have an objective measure of employee performance that may be consistently and reliably applied across a wide variety of jobs. This study implies that informal performance measures may indeed be appropriate for research and assessment purposes in a clerical and administrative environment, since the same construct and operationalisation is applicable across all kinds of jobs, irrespective of job level and complexity. However, research is needed to establish their applicability in a working environment.
The use of ordinal data is a limitation in the study. Joreskog and Sorbom (1996, p239) take a rigorous position regarding SEM and consider that using ordinal variables may lead to distorted parameter estimates; and incorrect chi-square, goodness-of-fit indices and standard errors. However, Byrne (1998, p73) has identified that irrespective of the scaling assumptions it has been common practice by researchers using SEM and other multivariate techniques to treat polychotomous ordinal variables as if they were continuous variables. However, the use of large sample sizes becomes imperative.
Finally, the study is about the Maltese Public Service, hence caution should be used with the generalisation and interpretation of results due to cultural differences considering the fact that the PSM scale was developed for the United States.
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