Human Resource Management and Performance of Public Organizations: A Study of HRM, Employee Attitude and Behavior and Public Service Quality of Dutch Municipalities
Paper to be presented at the EGPA conference, September 2-5 2009, Saint Julian’s, Malta
***Draft version: please do not quote***
Brenda Vermeeren MSc. Erasmus University Rotterdam
[email protected]
Dr Ben Kuipers Erasmus University Rotterdam
[email protected]
Prof.dr Bram Steijn Erasmus University Rotterdam
[email protected]
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Abstract
During the last two decades, public sector performance has become more and more of an issue. Our aim is to gain insight into the relationship between HRM and the quality of public service in order to help public organizations improve their performance by means of better HRM policies. For the analysis two different data bases were used. The data bases provide us with data about employee well being and data about the performance of municipalities. The data of both surveys were aggregated on the organizational level, with the result that data can be compared among 35 different municipalities in the Netherlands. Because of the fact that organizational performance has been measured independent of the measurement of HRM, the often found problem of common method bias has been obviated. Based on the secondary data analysis both hypotheses were confirmed, showing that a) in organizations with a more performance oriented HRM system employees have a more positive attitude and behavior towards their job and b) organizations in which employees show a more positive attitude and behavior towards their job will reach better organizational public service performance. However, the effect of job satisfaction seems to be somewhat ambiguous. More satisfied employees seem to have a negative influence on organizational performance in efficiency terms (waiting time increase), but a positive influence on customer satisfaction with respect to service delivery (customers’ satisfaction with respect to employee’s empathy increase). In the context of New Public Management both performance indicators are pursueded, but because of the tension between these two performance indicators there raise some questions about the value of these criteria.
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1. Introduction With the rise of New Public Management the public sector is confronted with a growing demand to show its efficiency and cost effectiveness (Osborne and Gaebler, 1992; Boyne and Chen, 2006; Meier, O’Toole, Boyne and Walker, 2006). This results in more awareness of public performance. This is clearly also true on the local level. During the last few years the idea of municipalities as being public service providers has become more popular. Municipalities are forced to meet the requirements and wishes of citizen customers as much as possible. In 2005, a Dutch commission of an important public sector organization representing municipalities (the so-called Vereniging Nederlandse Gemeenten) formulated the objective that in 2015 municipalities need to be the frontoffice
for
citizens
and
companies
on
behalf
of
the
whole
government
(Kwaliteitshandvesten, 2009). Based on this, performance outcomes such as customer satisfaction become more important. Human Resources Management (HRM), which has proven to contribute to improving organizational performance outcomes (e.g., Wright, Gardner, Moynihan & Allen, 2005) in the private sector, could play a significant role in improving public service efficiency and quality. However, research on the contribution of HRM to support these developments in the public sector has been scarce (GouldWilliams, 2003).
With respect to public service delivery of municipalities, customer satisfaction is closely related to individual employee’s behavior (Guest, 1997; Fountain, 2001). The service delivery takes place during the contact moments between employee and customer. Employee behavior and attitude are of particular relevance with respect to customer satisfaction. With respect to this there is a considerable chance that dissatisfied employees will perform worse (Goodall, 1987; Van Yperen, De Jong, 1997 in Van Wijk, 2007). In the literature is in other words often stated that a happy worker is a productive worker. The role that HR practices may play is that of building the human capital pool and stimulating the kinds of human behavior that actually constitute an advantage (Boxall and Steeneveld, 1999:445 in Boselie, Dietz & Boon, 2005). Although Paauwe and Richardson (1997) recognized that employee attitude and behavior play a significant role in explaining the HRM-performance link, the function of employee perceptions as a key
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construct in explaining the link between HRM and performance outcomes has not been addressed extensively (Bowen & Ostroff, 2004). This study will therefore focus on HRM in relation to employees’ job satisfaction and customer satisfaction. Our main research question is: To what extent and under which conditions is there a relation between HRM, employees’ attitude and behavior and the organization’s public service performance?
We will first discuss the relation between HRM, employee’s attitude and behavior and organizational performance as stated in the literature. This discussion leads to two hypotheses. Second, we will discuss the research design and methods and present the measurement of the main variables. Third, we will test the hypotheses using structural equation modeling and we will present our findings. Fourth, we will discuss the implications of our findings for theory and practice.
2. Theoretical framework The relation between HRM and performance has been studied for many years (e.g., Beer, Spector, Lawrence, Mills & Walton, 1984; Fombrun, Tichy & Devanna, 1984; Becker, Huselid, Pickus & Spratt, 1997; Guest, 1997; Boselie et al., 2005). A well-known model with respect to the relation between HRM and Performance is the model by Paauwe & Richardson (1997). They presented a summarizing model of the available empirical research on HRM activities (such as recruitment, rewarding and employee participation), HRM outcomes (such as employee motivation and satisfaction) and organizational performance (which involves performance indicators of the effectiveness, quality and efficiency of the organization). Although the relation between HRM and performance outcomes seems quite robust (e.g., Huselid, 1995; Wright, Gardner, Moynihan & Allen, 2005), the mechanism which explain how HRM practices and organizational performance relate remains puzzling. As mentioned before, Paauwe and Richardson (1997) recognized that employee attitude and behavior play a significant role in explaining the HRMperformance link. In the next part the relation between HRM and employee attitude and behavior and between employee attitude and behavior and organizational performance will be described as stated in the literature.
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2.1 The relation between HRM and employee attitude and behavior One of the first publications in which a relation between HR practices and HR outcomes has been conceptualized was written by Beer, Spector, Lawrence, Mills and Walton (1984). They examined the relation between HRM policy choices and HRM outcomes like job satisfaction. Also the already mentioned model by Paauwe & Richardson (1997) made a distinction between HRM and HRM outcomes. HRM outcomes are for example job satisfaction, commitment and motivation. With regard to the relation between HRM and employee’s outcomes, HRM practices can be regarded as the stimulus (or cause) and employee’s behavioral or attitudinal response (e.g., job satisfaction) as the effect. This perspective can help to clarify the relation between HR activities and attitudinal and behavioral outcomes. Inspired by Van Wijk (2007) it is interesting to examine if there is an internal fit between employees' perceptions of the HR activities and their job satisfaction.
Organizations have a special (strategic) interest in eliciting specific effects, for instance the term high performance work system (HPWS) has been used to describe a HRM system which is aimed at improving performance and gaining sustainable competitive advantage (Boxall & Purcell, 2008). To get more insight into the behavioral outcomes, Perry, Mesch & Paarlberg (2006) wrote an overview article about the findings with respect to motivating employees and increasing employees’ performance in public organizations. Based on this research overview, they stated that a motivational program consisting of four aspects is crucial. These four aspects are employee incentives, job design, employee participation and goal setting. However, they argue that in a public context financial incentives have little positive impact on employee motivation and organizational performance. This is mostly due to the fact that the conditions to use these incentives effectively are not present (e.g. a lack of adequate funding for merit pay and an absence of the organizational and managerial characteristics that are necessary to make pay for performance work). They argue that job design is much more important for employee’s motivation and performance. This observation is in line with Hackman & Oldham’s (1980) job characteristics model. According to this model, job design needs to fit the intrinsic needs of employees. They stated that jobs rich in motivating
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characteristics, like task significance, stimulate for example the experienced meaningfulness of work among employees that increase the desired personal and work outcomes. The third factor according to Perry et al. (2006) is employee participation. The research overview suggests that participation has positive effects on motivation but only small positive effects on employee’s performance. With respect to this Locke & Schweiger (1979 in Perry et al., 2006) note that numerous contextual factors could influence the relation between participation and employee’s performance as for example task complexity. The final crucial aspect according to Perry et al. (2006) is goal setting. Specifically important is the addition of feedback. If employees do not know how they do their job, they also do not know if they have to improve their performance. With respect to this appraisal is an important part of the HR-cycle. This overview brings us to the first hypothesis, namely: H1: In organizations with a more performance oriented HRM system employees have a more positive attitude and behavior towards their job.
2.2 The relation between employee attitude and behavior and organizational performance As already mentioned in the introduction, a famous statement is that a happy worker is a productive worker. This assumes a relation between employee’s attitude or behavior and organizational performance. However, in 1992 Ostroff observed that little work has investigated the relationship between job satisfaction and performance at the organizational level of analysis and this seems to be still the case. Organizational performance can be subdivided into three categories: financial performance (e.g., profit), internal non-financial performance (e.g., productivity) and external non-financial performance (e.g., customer satisfaction). The market value of public sector services is often not known. For this reason it is difficult to express the public sector services in financial indicators. Private sector organizations strive for good financial results whereas public organizations are aimed at non-financial aims like delivering good public services to citizens (Van Loo & De Grip, 2002:17). As already mentioned, within the (public) service sector, performance outcomes as customer satisfaction are closely related to individual employee behavior (Guest, 1997). In 1997 Heskett, Sasser & Schlesinger
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introduced the 'satisfaction mirror'. According to them there is a positive relation between front line service provider job satisfaction and customer satisfaction. This theory of Heskett et al. (1997) is relevant for this research because the public service delivery takes place during the contact moments between employee and customer. This is called the transaction moment of the transactional fit (Van Wijk, 2007:58). The transactional fit refers to the alignment between customers’ demands and the delivery of public service by front office employees. In this research the assumption is that employee job satisfaction influences the quality of the transaction moment and thus the quality of the service delivery. This brings us to the second hypothesis: H2: Organizations in which employees show a more positive attitude and behavior towards their job will reach better organizational performance.
Performance oriented HRM system
1
Employee Attitude and Behavior
2
Organizational Performance
Contingency/Control variables: Individual level: gender, age and educational level employee; gender, age and educational level customer Organizational level: Population size municipality
Figure 1: Conceptual model 3. Research methods 3.1 Analysis A quantitative study was carried out to address our research question. In the first step, the measurement model was tested via confirmatory factor analysis and was modified based on the test results. In the second step a structural equation model (SEM) positing causal relations among the variables was tested. All the estimates were produced using AMOS version 16.
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3.2 Data and Sample For our analysis we used a data base that is the result of the cooperation between a research organization that works for the Dutch Ministry of Internal and Kingdom Relations (the so-called ICTU Program InternetSpiegel) and an important public sector organization representing municipalities (the so-called Vereniging Nederlandse Gemeenten). The data base provides us with data about employee well being (employee satisfaction) and data about the performance of municipalities (customer satisfaction).
In 2008, InternetSpiegel approached 1450 front office and back office employees of public service counters of Dutch municipalities to fill in a questionnaire about employee well
being
by
means
of
Internet
(this
part
of
the
research
is
called
‘Medewerkerstevredenheidsonderzoek’). Of them, 902 respondents cooperated in the research (response rate 62 percent). Of them, only the front office employees were selected, resulting in a file with 590 respondents. The respondents with missing data on the analyzed variables were removed (listwise deletion), resulting in a file with 583 front office employees of 35 different municipalities. The respons rate within each municipality needed to be at least 40 percent otherwise the data had been removed from the data base.
In the same periode as front line employees were asked about their well being, customers of public service counters were interviewed. After their public service counter visit they were asked about their satisfaction with respect to the public service delivery (this part of the research is called ‘Benchmarking Publiekszaken’). The sample consists of 4392 respondents of 35 different municipalities. The minimum required respons within each municipality had been fixed at 100 respondents. There were two restrictions with respect to the respondents: first, they needed to have the minimum age of 18 years old and second, they did not live in a nursing home or in a home for the elderly. The data collection took place in a period of two weeks.
The data of both surveys were aggregated on the organizational level, with the result that data can be compared among 35 different municipalities in the Netherlands. Because of
8
the fact that organizational performance has been measured independent of the measurement of HRM, the problem of common method bias has been obviated.
3.3 Measures In this paragraph, the measurement of the main variables, HRM, employee attitude and behavior, organizational performance and the control variables, will be discussed. Because the sample size is rather small, we used only one latent variable to include not to many parameters.
3.3.1 HRM In existing HRM and Performance research, HRM is often measured through single respondents (the organizations HR officer). In this survey employees were asked about their satisfaction with HRM related activities within their organization. We have tried to fit the measurement of HRM to the factors that are important for employee’s motivation and performance according to Perry et al. (2006)1. Employee incentives is measured by the question ‘how satisfied are you with your secondary rewards?’. Job design is measured by the question ‘how satisfied are you with your job content?’ and role of the supervisor (proxy for the goal setting variable) is measured by the question ‘how satisfied are you with your direct supervisor?’. The answers were given on a five-point Likert scale, ranging from very dissatisfied (1) to very satisfied (5). The different questions were put into the model as being three different constructs measuring HRM.
3.3.2 Employee attitude and behavior With respect to the employee attitude and behavior, we included the construct ‘job satisfaction’. This is measured by one item: ‘how satisfied are you with your job?’ The answers were given on a five-point Likert scale, ranging from very dissatisfied (1) to very satisfied (5).
1
There were no items in the data base to measure the ‘participation’ aspect of the model of Perry et al. (2006).
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3.3.3 Organizational performance To measure organizational performance we distinguish two different performance indicators. The first one is the latent variable called ‘service delivery’. There were seven items to measure this latent variable. However, after an analysis of the modification indices, significance tests and standard errors of the confirmatory factor analysis, measuring service delivery with the next four items was regarded as best fitting to the data. The four items we used to measure ‘service delivery’ are the perception of the customer with respect to 1) the kindness of the employee, 2) the knowledge of the employee, 3) the empathy of the employee and 4) the clarity of the employee. The answers were given on a ten-point scale ranging from 1 (extremely bad) to 10 (excellent). The second variable we used to measure organizational performance is called ‘waiting time’. After the customers had visited the public service counters they were asked how long they had been waiting before the service delivery took place. They could answer: 1) less than 5 minutes, 2) between 5 and 15 minutes, 3) between 15 and 30 minutes, 4) between 30 and 60 minutes or 5) more than 60 minutes.
3.3.4 Control variables Of course, other variables can affect the relation between HRM and performance. Therefore, several control variables were included in the analysis. Inspired by Paauwe and Richardson (1997), these control variables are divided into two groups. In the first group, we controlled for personal characteristics (gender (dummy), age and educational level both of the employees and of the customers). Second, we controlled for one important organizational characteristic: the population size of the municipality. We coded gender as 0 (male) and 1 (female). Age was subdivided into five classes (1 = 15-24 years; 2 = 25-34 years; 3 = 35-44 years; 4 = 45-54 years; 5 = 55 years and older). Educational level was also subdivided into five classes (1 = primary education; 2 = lower vocational education; 3 = higher general secondary education, preparatory scientific education; 4 = higher vocational education, candidate exam; 5 = scientific education). Finally, municipality size was ranging from 15,306 to 209,699 inhabitants. Due to using secondary data analysis, we were restricted to the aforementioned answer categories for measuring the control variables. 10
4. Results To test the proposed relations between the variables, a causal structure is posited among the concepts. The structural equation model in figure 2 is the result.
Kindness employee
Job content
e4
.954 .282 Incentives
Knowledge 1.013 employee
.328
.592
Service delivery
.134 Role of the supervisor
.587
-.298
.869
Empathy employee
e6
.966
Clarity employee
e7
e2
.174 Gender employee
Job satisfaction
.390 .199 .408
Age employee
e1
-.570
Waiting time .235 Educational level employee
e5
.222 -.362 .132 e3
Gender customer
Figure 2: Result of Structural Equation Modeling
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After an intensive analysis of the modification indices, significance tests, standard errors and several intermediate model modifications the model in figure 2 is regarded as the best fitting model. The overall model fit was tested using several fit indices. In general, the chi-squared test is used to assess sample data in proportion to implied population data. The result of the chi-squared test was CMIN 59,637, DF 58, P .416 and CMIN/DF 1,026, where a CMIN/DF between 1,0 and 3,0 indicates a good fit. However, also a number of alternative fit measures have been developed2. The Root Mean Square Error of Approximation (RMSEA), with a value of .028 and a Pclose of .595 indicate a good fit. The Comparative Fit Index (CFI) and the Tucker-Lewis Index (TFI) values were .995 and .993 whereas the popular cutoff level in social sciences is .900, implying that the model was a good fit. The information theoretical measures (AIC, BIC, BCC and CAIC) showed all a better fit in the default model than in the saturated model also indicating a good fit. Figure 2 shows only the statistically significant relations (significance level 0.05). The numerical scores on all lines indicate standardized regression coefficients (beta).
According to our first hypothesis, we expected that in organizations with a more performance oriented HRM system employees have a more positive attitude and behavior towards their job. The results of our analysis indicate that there is a significant direct effect of HRM related activities on job satisfaction. With respect to this, our first hypothesis is confirmed. However, not all the HRM activities appear to have a significant effect on job satisfaction. There appears to be no significant direct effect of incentives on job satisfaction. However, the incentive variable is strongly correlated with the role of the supervisor indicator. This can be explained by the fact that the question of getting specific incentives is often answered by the supervisor. The role of the supervisor shows to be very important for job satisfaction as can be concluded from its high beta weight. This underlines the importance of the role of the supervisor in organizations as already mentioned in the literature (e.g. Podsakoff, MacKenzie and Bommer, 1996; Perry, Mesch and Paarlberg, 2006; Purcell and Hutchinson, 2007). Also job design has a high beta
2
Not all fit measures have been taken into account because some fit measures are sensitive to a small sample size (e.g. GFI and NFI).
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weight indicating that this is an important aspect for employees to be satisfied with their job. The results of this analysis are in line with the conclusions in the article of Perry et al. (2006) that jobs rich in motivating characteristics (e.g. task significance) can stimulate psychological states. When we look at the different HRM activities as stimulus and job satisfaction as the response we have seen now that employees perceive two aspects as very important in causing their response (role of the supervisor and job design). The independent variables and the control variables explain together .666 of the variance in job satisfaction. Although this is rather high, the result indicates that other things are also important for job satisfaction. With respect to this we were forced to leave one important indicator of our theoretical framework (Perry et al., 2006) out of the analysis, namely employee participation. This could explain the results, but as we know from other literature (Steijn, 2004) there are more aspects important for job satisfaction such as the relation with colleagues.
The data also provide some support for the second hypothesis that organizations in which employees show a more positive attitude and behavior towards their job will reach better organizational public service performance. However, these results are somewhat more complicated. In our model there are two indicators of organizational performance. The first one is waiting time. The results show us that there is an important effect of job satisfaction on the waiting times of customers as can be concluded from its high beta weight. However, the results implicate that if employees are more satisfied with their job, the waiting times will increase. A possible explanation for these results can be found in the literature about active and passive performance (Frese & Fay, 2001). In this literature there is stated that employees can be really satisfied with, for example, having nice conversations with customers and paying more attention to customers; however, by doing this, they do not make a contribution to the organizational performance in terms of efficiency because waiting time increase. But on the other hand, when we do not look to organizational performance in terms of efficiency but in terms of customer satisfaction with respect to the service delivery, the results show us another picture. The relation between job satisfaction and the latent variable service delivery seemed not to be significant. In other words, there appears to be no direct relation between employee
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satisfaction and customer satisfaction with respect to the service delivery. However, there is an effect of job satisfaction on service delivery, namely on one of the indicators of service delivery: the perception of customers with respect to the degree of empathy of the employee. This indicates that when employees are more satisfied, customers perceive more empathy of the employee. A possible explanation for these results can be that when employees are more satisfacied, they pay more attention to customers with the result that customers are more satisfied with the empathy of the employee but at the same time, waiting time will increase.
Besides the effects of the main variables there are also some interesting effects of the control variables. When we look in more detail at the effects of the control variables in figure 2, the results show us that a part of the control variables (age customer, educational level customer and population size municipality) has been removed from the model as a result of the significance tests. Next to this, the results show us that there are some significant correlations between the variables, but more interesting is the effect of the control variables on the main variables. First, the educational level of the employee. The results show us that employees are more satisfied with their job when they have a higher educational level. A second result is that customers are more satisfied with the kindness of the employee when the employee is a woman. Next to this, a third result is that customers are more satisfied with the clarity of the employee as employees are older. A possible explanation is that employees have more working experience when they are older with the result that they are clearer when they give information to customers. Finally, the gender of the customer. These results seem to be somewhat more complicated, because there are three different effects of gender on the main variables. First, the results show us that employees are more satisfied with their job when there are more female customers. Second result is that there is a negative effect of the gender of the customer on the customer satisfaction with respect to the service delivery. This implies that male customers are more satisfied with the service delivery. However, there is also a third relation. There appears to be also a significant relation between the gender of the customer and the customer satisfaction with respect to the knowledge of the employee. Knowledge of the employee is an indicator of the latent variable service delivery and we
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have just seen that men are more satisfied with the service delivery, but the results show us that on the contrary women are more satisfied with the knowledge of the employee.
Finally, based on the modification indices there appears to be also a significant error correlation between the error of job satisfaction and the error of service delivery. An error correlation can have different explanations such as respondents’ inability to answer questions, lack of requisite effort to obtain correct answers or other psychological factors or weakness of the wording of survey questionnaires.
5. Conclusion and Discussion In this paper we have studied the relationship between HRM and the quality of public service in order to support public organizations in improving their performance by means of better HRM policies. In this research the main assumption was when customers get bad service there is a real chance that employees also experience bad internal service in terms of HRM or in other words do not get the work facilities they want. In this situation employees do not get the support they need to deliver the desirable service what resulted in lower customer satisfaction (organizational performance). The analysis shows some starting points from which to positively influence organizational performance in public organizations. First, the analysis shows that employees who perceive a more performance oriented HRM system, especially focused on job content and the role of the supervisor, also show a more positive attitude and behavior towards their job. Moreover, this study demonstrates that employee job satisfaction has a positive influence on customer satisfaction with respect to the service delivery.
With respect to this, the results show some support for the existence of the satisfaction mirror of Heskett, Sasser & Schlesinger (1997) because there appears to be some positive relation between front line service provider job satisfaction and the quality of the transaction moment in terms of customer satisfaction. This supports the idea that it is relevant to focus on HRM to influence employees’ attitude and behavior and subsequently the organizational performance. However, in this research job satisfaction appears to have both a positive and a negative influence on organizational performance.
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More satisfied employees seem to have a negative influence on organizational performance in efficiency terms (waiting time increase), but a positive influence on customer satisfaction with respect to service delivery (customers’ satisfaction with respect to employee’s empathy increase). Based on this, there raise some questions with respect to the use of different performance indicators in the context of New Public Management (Fountain, 2001). With respect to this it is important to realize that the social political context of the public sector brings about that purely customer-oriented acting is not desirable. Sometimes government has to take unpopular measures. On the other hand customer satisfaction becomes more and more important. With respect to this, there seems to be some tension between the use of different performance indicators to evaluate the quality of public service delivery. Based on the nature of the public sector, public organizations need to perform at different aspects because of the diversity of stakeholders (Boyne, 2003). On the other hand should we evaluate the performance of public organizations on incompatible performance indicators?
A second point resulting in recommendations for further research is based on the observation that there appears to be no significant relation between job satisfaction and the latent variable service delivery. However, the latent variable service delivery consists of four indicators. Job satisfaction appears to have a significant effect on one of these indicators, namely on the customer satisfaction with respect to the empathy of the employee. The first impression is that this is somewhat strange, but when we look at the results in more detail there is a plausible explanation for this result. By drawing an arrow between job satisfaction and service delivery we suppose an effect of job satisfaction on the four indicators of service delivery (kindness, knowledge, empathy and clarity of the employee), but why should we suppose a relation between job satisfaction and knowledge and clarity of the employee? With respect to this it seems to be more suitable that HRM activities aimed at the increase of employee’s competences will influence employee’s knowledge and abilities and that can have a positive effect on customer’s satisfaction with respect to knowledge and clarity. This pleas for taking more HRM activities and more HRM outcomes into account, to get a more profound view of the relation between HRM and organizational performance.
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A third point is that in this research the perception of employees with respect to HRM related activities has been examined, what refers to HRM implementation. In previous research on the link between HRM and performance, there has been little attention to HRM implementation as a necessary condition for its effectiveness. However, only the focus on employee’s perception of HRM as an indicator of HRM implementation is rather small. Therefore, future research should focus on more aspects of HRM implementation. For example, further research could address whether there is a relation between the degree of internalization of HRM activities within the organization and organizational performance and what with respect to this the influence of the role of supervisor is, who is increasingly charged with the implementation of HRM activities.
Finally, an important limitation of this research is that the sample size is rather small. Sample size affects the statistical power and precision of the model’s parameter estimates as well as the indices of overall model fit. This research is based on a survey executed in 2008. In spring 2010 the same survey will be executed. The assumption is that there will be approximately 30 new municipalities participating in the research. The analysis in this paper will be reiterated then to examine if the conclusions in this paper can be extended.
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