Highlight, copy & paste to cite:
Edgar, F. & Geare, A. (2004). Employee Demographics in Human Resource Management Research, Research and Practice in Human Resource Management, 12(1), 61-91.
Employee Demographics in Human Resource Management Research
Despite a prominent perspective of the literature that employees are consumers of HRM, only recently has HRM been evaluated from the employees’ viewpoint. Whilst these studies have helped to develop our understanding of the HRM ‘experience’ from an employee perspective, they frequently ignore the issue of employee demography. This study contributes to understanding in this area by establishing areas of difference in employee views based upon their characteristics about the importance and application of HRM practice. Specifically, the demographic categories of gender, ethnicity, age, occupation, length of service, and employment sector are examined. Fndings indicate that employee demography, especially gender, ethnicity and employment sector, does influence employee attitudes towards HRM, and should be given consideration in HRM research. The findings are discussed in terms of their relevance for the Asia Pacific region.
The view that best practice models of Human Resource Management (HRM) have universal applicability is an assumption that is often made in the literature (Wood 1995, Purcell 1999). This implicitly suggests that employees are homogenous, and hence, would have similar views towards HRM policies and practices. However, there is little actual evidence to support this view as few studies in HRM have researched employees themselves. As Bowen and Ostroff (2004) point out in a recent paper:
In past research on HRM practices and systems, scholars have typically relied on reports from a higher-level manager or HR executive ... we suggest that a better alternative is to assess these characteristics of the HRM system from employees themselves. (p.216)
If employees, as a group, have been largely ignored in HRM research, it is not surprising that employee demographics have apparently been deemed irrelevant. This paper takes an alternative view, and argues that there are logical reasons why employee demographics should be given consideration and presents data in support of that argument.
Employee demography can be defined as “the study of the composition of a social entity in terms of its members’ attributes” (Pfeffer 1983: 303). Demographics include such factors as gender, age, ethnicity, occupation, seniority, salary levels, marital and family status. The researcher normally includes those factors which are assumed to have explanatory value in the research.
Research outside the discipline of HRM frequently considers employee demographics, accepting that they can explain significant differences in attitudes and beliefs (Cianni & Romberger 1995, Mor Barak, Cherin & Berkman 1998). However, in the specific area of HRM research a high proportion of researchers ignore employees altogether, let alone consider demographics. This lack of attention afforded to employee demographics in HRM research has created what some now refer to as a ‘black box’ (Pfeffer 1985, Lawrence 1997). Lawrence (1997:2) points out that despite the important, sometimes critical role of demography, researchers often leave demographic variables “loosely specified and unmeasured, creating a ‘black box’ filled with vague, untested theories”.
Somewhat belatedly, in the last few years there have been calls for more employee ‘voice’ in HRM research. In addition to Bowen and Ostroff (2004), the most persistent calls have come from Guest (1999, 2001, 2002). If employees are to be given a voice in HRM research, then it is arguable that employee demographics should also be considered, rather than it be implicitly assumed employees are a homogenous group with similar attributes and beliefs.
While work forces have always had a degree of diversity in terms of age and skill, this diversity has grown markedly over the last two to three decades. The number of women in the work force has increased significantly, as have the proportion of different ethnic groups (Shenhav & Haberfeld 1992). Anti-discrimination legislation and the emergence of a dynamic, competitive global marketplace have played a major role in this change. Given a diverse work force, it is reasonable to assume that differences in views and attitudes could exist, which hence, justifies examining demographics.
A further reason for considering demographics is that some HRM policies and practices target specific groups within a work force. For example, ‘Equal Employment Opportunity’ (EEO) initiatives in New Zealand target, in particular, women and Maori. So, again, it is not unreasonable to assume that groups targeted for preferential treatment may have different attitudes (about particular policies) to the views held by other, non-targeted, groups. As Pfeffer (1985:74) suggests, “sensitivity to demographic effects can help provide a context to understand organisational behaviour”.
Few studies even touch on demographics in HRM research and even less consider it in a comprehensive manner. For example, Gibb (2001) makes a passing reference to demographic differences in employee evaluations of HRM, and while Guest (1999) goes further, he simply considers demographic differences in relation to the number of HRM practices employed by the organisation, and does not report on specific HRM practices. Where studies have examined specific practices they have been very limited in scope. For example, Konrad and Hartmann (2002) examined the impact of gender and ethnicity on employee attitudes towards EEO initiatives. The findings of the study demonstrated that differences did exist, with women and members of ethnic minority groups holding more favourable attitudes towards EEO than males.
The research aims of this study are to establish the demographic differences in attitudes towards the importance and application of four specific functional areas of HRM amongst a sample of employee groups in New Zealand. Six demographic variables are examined – gender, ethnicity, age, occupation, length of service and employment sector. These variables are those commonly cited as significant in the broad area of employee demographic research. Employee attitudes towards the importance and application of HRM policy and practice are assessed across four functional areas:
- The provision of a good and safe working environment.
- Training and development.
- Recruitment and selection.
These four areas of HRM have been chosen because they are those that commonly feature in best practice models of HRM (Ferris, Hochwarter, Buckley, Harrell-Cook & Frink 1999). The study reported in this paper draws on the limited applicable literature available to generate a number of hypotheses about the relationship between employee demography and attitudes towards HRM. These hypotheses are then examined. There are some areas in which neither the literature nor logic clearly suggest testable hypotheses (for example, the relationship between some demographic groups and attitudes towards a good and safe working environment). In these cases the research is purely exploratory.
A large number of studies comparing the behaviour and attitudes of males and females report that gender differences do exist (Mor Barak et al. 1998, Konrad & Hartmann 2002). These differences are often attributed to the discriminatory treatment experienced by women (Mai-Dalton & Sullivan 1981, Kirton & Greene 2000), and it is suggested that these experiences in turn shape an individual’s attitudes and behaviour in the workplace (Cianni & Romberger 1995). Where HRM policies and practices are seen to promote equality in the workplace, such as EEO, research findings demonstrate women are more likely than men to hold favourable attitudes towards them (Konrad & Linnehan 1995).
However, a commitment to equity and fairness in employment is not limited to an overt EEO policy. It should also be reflected in impartial recruitment and selection practices, and the impartial provision of training and development opportunities to all employees, including women. These are areas where women have felt disadvantaged in the past (Kirton & Greene 2000). Thus, these three areas of HRM (training and development, EEO, recruitment and selection) are likely to be perceived as being more important to women than to men, and the application of equitable practice in these three areas is also likely to be viewed more favourably by women than by men. Consequently, these imperatives provide the foundation for the following two hypotheses:
H01 Perceptual differences towards HRM policies and practice are likely to exist between genders. Specifically, it is predicted women will consider the importance of the three HRM areas of (1) training and development, (2) EEO, and (3) recruitment and selection, to be greater than the level of importance perceived by men.
H02 Women will rate the application of HRM practices in the three HRM areas of (1) training and development, (2) EEO, and (3) recruitment and selection, more favourably than will men.
Ethnicity and Cultural Background
People from ethnic minority groups have experienced a history of discrimination (Kirton & Greene 2000). As a result, these community units are considered to experience barriers in the workplace in much the same way as women (Mai-Dalton & Sullivan 1981). This means that issues of equity and fairness in HRM policies and practices are likely to be considered more important by members of ethnic minority groups than the dominant group, which in this study, comprises those people of European backgrounds. Hence, it is suggested that EEO will be considered a more important area of HRM practice for members of ethnic minority groups than for those with a European background.
Issues of equity and fairness influence a range of HRM functions. Some studies show that ethnic minority groups experience discrimination during the recruitment and selection process. For example, research in the UK (Kirton & Greene 2000) has shown that despite ethnic group members making more job applications, this group received fewer job offers than members from the dominant group. Hence, recruitment and selection is an area likely to be considered more importantly by ethnic minority group members than is likely to be perceived by Europeans.
Members of ethnic minority groups also tend to be disproportionately represented in jobs that attract low pay, and are of lower status (Shenhav & Haberfeld 1992, Kirton & Greene 2000). Consequently, when they do gain entry into professional occupations, their progress in terms of promotion, better paid jobs and more challenging work is often slow (Kirton & Greene 2000). An argument can then be made it is likely an individual’s mobility in employment is best enhanced through training and development. Thus, this condition is also likely to be a HRM area considered more important by ethnic minority group members than Europeans.
It follows that practices aimed at removing discriminatory barriers and at promoting equity and fairness are likely to be viewed favourably by those whom they intend to benefit. Thus, it is suggested that ethnic minority group members are more likely to rate the application of equitable and fair practices across these three HRM areas more favourably than will Europeans. From these underpinnings the following two hypotheses are generated:
H03 Attitudinal differences towards HRM policies and practice will exist between Europeans and Non-Europeans. It is postulated Non-Europeans will consider the three HRM areas of (1) training and development, (2) EEO, and (3) recruitment and selection, to be greater than the level of importance perceived by Europeans.
H04 Non-Europeans will rate the application of HRM practices in the three areas of (1) training and development, (2) EEO, and (3) recruitment and selection, more favourably than will Europeans.
Prior research exploring the impact of the demographic variable of employee age shows that it is also associated with attitudinal and behavioural difference (Pfeffer 1985, Lawrence 1988, Zenger & Lawrence 1989, Wehrmeyer & McNeil 2000, Konrad & Hartmann 2002). Indeed, stereotypical beliefs about age are found to impact significantly on outcomes for certain age categories within an organisation (Wagner, Pfeffer & O’Reilly 1984, Lawrence 1988). For example, Kirton and Greene (2000) claimed that older employees received less training and development in the workplace, because employers thought they did not want it, and because older employees are seen as less of an investment (Kirton & Greene 2000). However, because job security is no longer a guaranteed feature of employment, older employees need opportunities for training and development so that they can maintain their employability in the wider marketplace (Tornow 1988). It is, therefore, suggested that older employees will consider training and development to be very important. Nevertheless, because older employees supposedly receive fewer such opportunities, it is likely they will rate the application of HRM practice in this area less favourably than younger employees.
The demographic attribute of age has importance through linkages with individual experience and personal accumulated knowledge. Indeed, Wagner and colleagues (1984) reported that a long-term experience may influence attitudes and belief systems which can be substantially different across cohorts of age dissimilarity. In terms of HRM dimensions, Konrad and Hartmann (2002) found that age also influences employee attitudes towards Affirmative Action policies, with increased age being associated with more positive attitudes towards these policies. This suggests older employees will consider EEO to be more important than will younger employees.
There is some evidence older people face greater recruitment and selection barriers than younger people. For example, a recent study (McKay 1998) found that 25 per cent of employers considered a person aged over 50 too old to recruit. Arguably, it is suggested that age-related differences will exist for employee attitudes towards the importance of recruitment and selection, with older employees considering this area to be more important than younger employees. These imperatives provide the foundation for the following two predictions:
H05 Attitudinal differences towards the importance of the HRM areas of (1) training and development, (2) EEO, and (3) recruitment and selection will exist across age classifications. It is predicted older employees will consider the importance of these HRM areas to be greater than the level of importance as perceived by younger employees.
H06 Older employees will rate the application of HRM policies and practices in the area of training and development less favourably than will younger employees.
Occupation, position in the organisational hierarchy, and salary level, are considered as factors that influence employee attitudes (Guest 1999, Dole & Schroeder 2001, Ely & Thomas 2001). Amongst other things, universal models of best practice HRM are thought to comprise policies and practices that provide for uniformity of treatment amongst different employee groups in an organisation (Wood & Albanese 1995). Moreover, uniformity of treatment promotes equity and fairness in employment and leads employees to hold positive perceptions about the environment in which they work (Wood 1995).
Uniformity of treatment means consistency is evident in the application of terms and conditions of employment across the work force. For example, all employees would have access to benefits, such as health insurance and superannuation schemes. Arguably, uniformity in terms and conditions of employment will not provide any real direct benefit for those employed in the higher echelons of employment (i.e., professionals), because this group usually receives full access to benefits offered by an organisation. For a considerable period it has been recognised these systems of tangible rewards (i.e., forms of fringe benefits), which have incentive potential, are likely to benefit those employed at lower levels (i.e., non-professionals), because it enables them to access benefits usually reserved for managers. So it is reasonable to speculate that occupational differences in employee attitudes towards the importance of a good and safe working environment, as functional area of HRM, may exist. The following prediction is, therefore, made.
H07 Attitudinal differences towards the importance of the HRM area of a good and safe working environment will exist across occupational classifications, with non-professionals considering this area to be more important than professionals.
Length of Service
The length of time spent in an organisation leads to the development of shared understandings and experiences (Wiersema & Bird 1993). Studies suggest that increased tenure in an organisation is positively related to employee well-being and employee performance (Finkelstein & Hambrick 1990, Wiersema & Bantel 1992, Pfeffer 1993). These positive outcomes supposedly result from the implementation of effective HRM policies and practices. Those areas of HRM, considered integral to effective HRM, and generally reported to comprise best practice HRM, include (1) a good and safe working environment, (2) training and development, (3) EEO, and (4) recruitment and selection. It is, therefore, reasonable to surmise that employees who remain working for the same organisation over a considerable period of time do so because they are happy with the HRM policies and practices in these areas. This leads to the following hypothesis.
H08 Employees with long tenure will rate the application of HRM policies and practices in the four HRM areas of (1) good and safe working environment, (2) training and development, (3) EEO, and (4) recruitment and selection, more favourably than will employees with short tenure.
Employees who work in the public sector have been found to be different from employees who work in the private sector along a number of dimensions. For example, public sector employees supposedly have different values, are less flexible, and have lower levels of well-being than employees who work in the private sector (Murray 1975, Solomon 1986). Whilst there is now some debate about whether or not these sectoral differences still exist (Boyne, Jenkins & Poole 1999), there is a compelling reason why sector differences in employee attitudes towards HRM are likely to be found in this study. For instance, in the New Zealand public sector employers are required by law to be ‘good employers’ (s.56 State Sector Act 1988).
The Act defines a ‘good employer’ as one which (1) provides good and safe working environment, (2) provides all employees with opportunities for training and development (3) promotes EEO, and (4) has fair recruitment and selection procedures. The overall objective of this requirement is to ensure best practice HRM is conducted in the public sector, so it is likely operationalised HRM practice in this sector will be better than HRM practice in the private sector. Furthermore, because of the increased importance public sector employers must attach to HRM practices in these four areas it is also reasonable to surmise that this will result in increased awareness for employees about what constitutes good practice in these areas. This heightened awareness of good HRM practice means that it is likely that public sector employees will consider some, if not all of these areas of HRM, to be of greater importance compared with employees who work in the private sector. From these underpinnings the following two hypotheses are presented.
H09 Attitudinal differences towards HRM policies and practice will exist between employment sectors, with public sector employees considering the four HRM areas of (1) good and safe working environment, (2) training and development, (3) EEO, and (4) recruitment and selection, to be more important than do private sector employees.
H010 Public sector employees will rate the application of HRM practices in the four HRM areas of (1) good and safe working environment, (2) training and development, (3) EEO, and (4) recruitment and selection, more favourably than will private sector employees.
This paper reports on one aspect of a research project into HRM practice in New Zealand, where the major focus was on public and private sector differences in HRM practices. A significant aspect of the investigation was the assessment of employee attitudes to HRM, as measured by data obtained by the administration of a questionnaire. Hypotheses pertaining to the relationship between employee demographics and attitudes towards HRM, as developed from the literature, were developed and were examined. The results of the data evaluations are reported in this study.
Site and Subjects
Employee participants for this study were secured by firstly writing to all those employers in the Wellington and Christchurch regions, located in the New Zealand Business Who’s Who, who were listed as employing 50 or more staff. In total some 234 organisations were originally contacted, with 40 organisations agreeing to participate. Employers were requested to distribute the surveys to a representative sample of their work force in terms of occupational classification, ethnicity, and gender. Participation was voluntary, confidentiality was guaranteed, and endorsed by the company. The number of employees in each organisational sample was based on organisational size, with 10 per cent (a minimum of 20 and a maximum of 50) of employees from each organisation being requested to participate. The targeted population consisted of 1075 full-time and part-time employees. The usable response rate was 56 per cent (607 responses). This response rate compares very favourably for survey research in this area (Scandura & Williams, 2000). A profile of the respondents is shown in Table 1.
The survey used in this study comprises a range of statements relating to the importance and application of HRM practice. The survey questionnaire contains two sections. The first section comprises the demographic questions – relating to gender, ethnicity, age, occupation, length of service and employment sector. The second section of the questionnaire, which was in two parts, was designed to capture perceptual responses about four areas of HRM practices in terms of:
- Their importance to the respondents.
- The extent of that HRM practice in the respondent’s workplace.
|Gender||Ethnicity||Age (Years)||Occupation||Length of Service (Years)||Employment Sector|
|Males||46||European||78||Under 20||2||Professional||53||Less than 1 year||16||Public||55|
|Polynesian||5||Over 35||58||Clerical/Administration||24||5 plus years||37|
The four assessed HRM functions were:
- Good and safe working environment.
- Training and development.
- Recruitment and selection.
This list of HRM areas and practices was developed by the authors using the HRM literature on best practices (Wood 1995, Guest 1999). The survey was piloted prior to the final study being completed, with some minor modifications being made to the statement wording.
Respondents were required to indicate how they perceived the relative importance of the four HRM functions. There was one item for each HRM function.
Respondents were also required to report the extent to which HRM practices relating to these four HRM functions were employed in their workplace. This scale had 20 items (five for each HRM function) and an arithmetic mean was constructed for each HRM function. There were no reverse items.
Five-point Likert instruments were employed to assess the importance and application of the four HRM functions. The scales ranged from 1 = strongly disagree to 5 = strongly agree. Construct validation for the four constructs in the 20 item scale was undertaken using a panel of seven HRM experts. The alpha reliability assessments for the four HRM functions were (1) good and safe working environment = 0.862, (2) training and development = 0.882, (3) EEO = 0.845, and (4) recruitment and selection = 0.832. A reliability above .800 is considered highly satisfactory (Bryman & Cramer 1990).
The analysis involves establishing if any significant differences exist between employee demographic variables and their attitudes towards HRM policy and practice. Independent samples t-tests are used to detect differences in means between the demographic variables examined. To enable independent samples t-tests to be completed data had to be collapsed to form dichotomous variables for each demographic area examined (i.e., Male/Female, European/Non European, less than 35 years of age, 35 plus years of age, Professional/Non Professional, less than five years of service/five plus years of service, public/private sector). Partitioning of the employee sample in relation to these classifications is shown in Table 2 and Table 3.
For ease of reference when reporting these results, the predicted direction of difference in employee attitudes towards the importance of HRM, as developed in the hypotheses for this study, are summarised as Figure 1. Where the result supports the prediction, this is highlighted in bold, and statistically significant differences are marked with an ‘*’.
|Importance||Good & Safe Working Environment||Training & Development||EEO||Recruitment & Selection||Hypothesis Number|
|Gender||Women higher||Women higher*||Women higher||H01|
|Ethnicity||Non-European higher||Non-European higher*||Non-European higher||H03|
|Age||Older employees higher||Older employees higher||Older employees higher||H05|
|Occupation||Non-professionals higher||Professionals higher*||Professionals higher*||H07|
|Sector||Public higher||Public higher||Public higher*||Public higher||H09|
Table 2 reports the results of the t-tests for the perceived importance of the examined four functional areas of HRM. It is predicted that differences will be evident for the demographic variables of gender, ethnicity, age, occupation and sector (H01, H03, H05, H07 and H09).
The results in Table 2 indicate the main area of employee demographic difference is in relation to employee attitudes towards EEO. Whilst differences exist across all six demographic variables examined for EEO, it is not surprising to find that, as predicted, the statistically significant differences are between those groups generally considered to be beneficiaries of EEO and the opposing dominant group, with women (Mean (M) = 4.19, Standard Deviation (SD) = 0.890) and non-European (M = 4.19, SD = 0.889) groups perceiving EEO practices a significantly higher rate of importance. As predicted, statistically significant differences are also found for sector, with public sector employees (M = 4.25, SD = .814) attaching a higher level of importance to EEO, than do employees in the private sector (M = 3.84, SD = .903). These findings provide some support for the hypothesis H01, H02 and H09
To see if the sector in which one works has the potential to influence the attitudes of dominant group members towards EEO, a further analysis of the data was completed. This analysis revealed this was indeed the case. Males in the public sector are found to consider EEO to be statistically more important at the p < 0.05 level (M = 4.04, SD = .872) than do males in the private sector (M = 3.76, SD = .961) and statistically less important at the p < 0.05 level than do females in the public sector (M = 4.42, SD = .754). Statistically significant differences are also found for three areas where no hypotheses are formulated. Firstly, employee attitudes towards recruitment; and secondly, selection and training and development by occupational classification reveals professionals consider these functions to be more important than do non-professionals. Lastly, less tenured employees considered a good and safe working environment to be more important than employees who had been tenured for more than five years.
|Variable||Gender||Ethnicity||Age (Years)||Occupation||Length of Service (Years)||Employment Sector|
|Good and Safe Working Environment||4.82||4.83||4.85||4.79||4.79||4.86||4.82||4.84||4.80||4.88||4.87||4.80|
|Training and Development||4.79||4.81||4.82||4.77||4.80||4.80||4.85||4.71||4.79||4.81||4.84||4.77|
|Recruitment and Selection||4.63||4.70||4.69||4.62||4.69||4.65||4.73||4.55||4.65||4.71||4.71||4.64|
Notes: a. n = number of respondents.
b. values in parentheses are the F value of the means comparison tests.
c. * p < 0.05.
Table 3 reports demographic attitudinal differences relating to the application of HRM practice. Only three analyses had significant differences between means. Non-professionals reported their workplaces to be substantially better in terms of a good and safe working environment than what was experienced by the professional respondents. Also, employees of the private sector expressed a view their workplace to be significantly better and safer than did employees of the public sector. This finding may have been linked with a finding private sector employees perceived the HRM dimension of training and development substantially greater in their workplace than was experienced by the public sector incumbents. These observations provide some support for H07 and H09.
The results of this study may suggest that employee demography has a role in HRM research. Whilst the results do not suggest all demographic variables significantly impact employee attitudes towards HRM, there is some evidence to suggest that demography should be a consideration for both sample selection and statistical analysis. The results may have been contaminated by dissimilarity of respondent numbers within categories (e.g., European versus non-European is 3.5:1).
Demographic difference in employee attitudes towards the importance of HRM is most evident for the functional area of EEO. Gender and ethnicity, along with sector, are the variables where the greatest differences exist, with age having very little impact. This study also found attitudinal differences towards the application of some HRM practice to exist. Significant differences in employee attitudes are found for the HRM areas of a good and safe working environment and training and development, with the demographic category of sector and across occupational level for former HRM dimension.
|Variable||Gender||Ethnicity||Age (Years)||Occupation||Length of Service (Years)||Employment Sector|
|Good and Safe Working Environment||4.07||4.02||4.06||3.98||4.05||4.04||3.99||4.15||4.04||3.99||3.93||4.13|
|Training and Development||3.84||3.91||3.88||3.84||3.90||3.86||3.91||3.79||3.86||3.88||3.82||3.98|
|Recruitment and Selection||3.52||3.59||3.58||3.48||3.90||3.86||3.56||3.54||3.57||3.51||3.55||3.61|
Notes: a. n = number of respondents.
b. values in parentheses are the F value of the means comparison tests.
c. * p < 0.05.
Previous studies on EEO have concentrated on assessing the impact of gender and ethnicity on employee attitudes towards policy and practice in this area. These studies suggest that the differences found are attributable to, and a reflection of, how these particular groups experience HRM in the workplace. However, the sector in which an individual works appears to also impact significantly on employee attitudes towards EEO, and hence, is a variable that should be included in further studies of this nature. Wiersema and Bird (1993) caution researchers about ‘blindspots’ that can occur when studies ignore political, social or cultural factors within a setting. The result of ‘blind spots’ is that incorrect assumptions or inferences may be made. The results of this study suggest this caution is warranted.
The few significant differences for the four assessed HRM areas across demographic profiles suggest the levels of homogeneity might be more a feature of organisational factors. Policies, procedures and culture may have a greater impact on the application of HRM dimensions, rather than how these initiatives are perceived by different demographic units.
This study finds demographic differences between employee groups to exist, thus confirming Pfeffer’s (1985) belief that demography is an important consideration in management research. As employee demographics are supposedly linked to employee attitudes and behaviour, developing understanding about areas of difference amongst employee groups has the potential to be benefit practitioners, policy-makers and academics.
Demographic attributes have powerful predictive qualities for employee behaviour (Pfeffer 1985, Stewman 1988), so developing knowledge about areas of employee demographic difference has the potential to assist practitioners in the development of their HRM policies and practices by making them more cognisant of the ways in which different groups of employees may respond to them (Shenhav & Haberfeld 1992). For example, research finds dissimilarity amongst group members to be associated with outcomes such as increased employee turnover (Jackson, Brett, Sessa, Cooper, Julin & Peyronnin 1991).
It is possible that consideration may need to be given to the composition of the work force when designing and developing HRM systems (for example, ageing and retirement policies, EEO policies and the implications of recruitment and selection policies and practice) in an organisation. Indeed, some form of internal fit may be required between the demographics characteristics of employees and HRM policies and practices within organisations. This approach would, in effect, lend support for models of HRM, such as the contingency model or the configurational model. These models suggest best practice HRM results from an organisation aligning its HRM policies and practices with the needs of the organisation, and ensuring some form of fit or congruence is achieved between these two (Wright & McMahan 1992, Arthur 1994, Youndt, Snell, Dean & Lepak 1996).
Along with establishing areas of demographic difference in employee attitudes towards HRM, a further contribution of this study has been the identification of those areas of HRM employees in New Zealand consider most important. It seems reasonable to suggest effective policy and practice in all these four areas is likely to have a positive impact on optimising an organisation’s human resource capability by promoting employee wellbeing. This in turn should enhance employee performance and provide the organisation with a competitive advantage.
Academics can also benefit from a better understanding of employee demography. Studies that assess the contribution of, for example, EEO policies and practices to organisational performance using a predominantly male or European employee sample are likely to produce results that are quite different from those that would be obtained if the employee sample had been skewed differently. Thus, the consequences of failing to recognise areas of employee difference in HRM research could lead to spurious explanations being put forward and flawed assumptions being drawn – this will not aid progress in the development of HRM as an academic and practitioner discipline.
Practitioners and academics working in the Asia and Pacific regions should view these findings with interest because countries in these regions have a high degree of diversity across employee groups. Thus comparative studies comparing employee demographics across different countries are now required to see if the findings obtained for the employee sample used in this study are similar to those found in other countries. Theory development in this area is inadequate and this type of investigation would also help establish why many of the demographic differences found in this study are not in the direction suggested by prior theory and research in this area. This would help to further develop our understanding about the universality or otherwise of best practice HRM.
is a Lecturer in the Department of Management, at the University of Otago. She completed her Ph.D in HRM/Industrial Relations on a Fellowship granted by the Foundation for Research, Science and Technology. Her current research interests include examining the relationship between HRM practice and its impact on employees.
is the Professor of Management, University of Otago. His Ph.D was in the area of Industrial Relations. Alan has authored a number of books and many articles in industrial relations, industrial law and HRM. He has worked as a consultant to companies and unions and has been a government appointed mediator and adjudicator.
Arthur, J. (1994). Effects of human resource systems on manufacturing performance and turnover. Academy of Management Journal, 37(3), 670-687.
Bowen, D. E., & Ostroff, C. (2004). Understanding HRM – firm performance linkages: the role of the “strength” of the HRM system. Academy of Management Review, 29(2), 203-221.
Boyne, G., Jenkins, G., & Poole, M. (1999). Human resource management in the public and private sectors: An empirical comparison. Public Administration, 77(2), 407-420.
Bryman, A., & Cramer, D. (1990). Quantitative data analysis for social scientists. Routledge: London.
Cianni, M., & Romberger, B. (1995). Perceived racial, ethnic, and gender differences in access to developmental experiences. Group and Organisation Management, 20(4), 440-459.
Dole, C., & Schroeder, R. (2001). The impact of various factors on the personality, job satisfaction and turnover intentions of professional accountants. Managerial Auditing Journal, 16(4), 234-245.
Ely, R., & Thomas, A. (2001). Cultural diversity at work: the effects of diversity perspectives on work group processes and outcomes. Administrative Science Quarterly, 24, 229-273.
Ferris, G. R., Hochwarter, W. R., Buckley, R., Harrell-Cook, G., & Frink, D. D. (1999). Human resources management: Some new directions. Journal of Management, 25(3), 385-432.
Finkelstein, S., & Hambrick, D. C. (1990). Top management-team tenure and organizational outcomes: The moderating of managerial discretion. Administrative Science Quarterly, 35(3), 484.
Gibb, S. (2001). The state of human resource management: Evidence from employees’ views of HRM systems and staff. Employee Relations. 23(4), 318-336.
Guest, D. E. (1999) Human resource management – the worker’s verdict. Human Resource Management Journal, 9(3), 5-25.
Guest, D. E. (2001). Human resource management: When research confronts theory. International Journal of Human Resource Management, 12(7), 1092-1106.
Guest, D. E. (2002). Communicating the psychological contract: An employer perspective. Human Resource Management Journal, 12(2), 22-38.
Jackson, S. E., Brett, J. F., Sessa, V. I., Cooper, D. M., Julin, J. A., & Peyronnin, K. (1991). Some differences make a difference: Individual dissimilarity and group heterogeneity as correlates of recruitment, promotions, and turnover. Journal of Applied Psychology, 76(5), 675-689.
Kirton, G., & Greene, A. (2000). The dynamics of managing diversity: A critical approach, Oxford: Butterworth Heinemann.
Konrad, A. M., & Hartmann, L. (2002). Gender differences in attitudes toward affirmative action programs in Australia: Effects of beliefs, interests, and attitudes towards women. Gender Roles, 45(5-6), 415-432.
Konrad, A. M., & Linnehan. F. (1995). Race and gender differences in line managers’ reactions to equal employment opportunity and affirmative action interventions. Group and Organization Management, 20(4), 409-439.
Lawrence, B. S. (1988). New wrinkles in the theory of age: Demography, norms, and performance ratings. Academy of Management Journal, 31(2), 309-337.
Lawrence, B. S. (1997). The black box of organizational demography. Organization Science, 8(1), 1-22.
Mai-Dalton, R., & Sullivan. J. J. (1981). The effect of manager’s sex on the assignment to a challenging or dull task and reasons for the choice. Academy of Management Journal, 24(3), 603-612.
McKay, S. (1998). Older workers in the labour market. Labour Market Trends, July, 365-369.
Mor Barak, M. E., Cherin, D. A., & Berkman, S. (1998). Organisational and personal dimensions in diversity climate. Journal of Applied Behavioral Science, 34(1), 82-104.
Murray, M. A. (1975). Comparing public and private management: An exploratory essay. Public Administration Review, 35(4), 364-371.
Pfeffer, J. (1983). Organizational demography. In L. L. Cummings & B. M Staw (Ed.), Research in organizational behavior (Vol 2, 299-357). Greenwich, C.T: JAI Press.
Pfeffer, J. (1985). Organizational demography: Implications for management. California Management Review, 28(1), 67-81.
Pfeffer, J. (1993). Barriers to the advance of organizational science: paradigm development as a dependent variable. Academy of Management Review, 18(4), 599-620.
Purcell, J. (1999). Best practice and best fit: Chimera or cul-de-sac? Human Resource Management Journal, 9(3), 26-41.
Scandura, T. A., & Williams. E. A. (2000). Research methodology in management: Current practices, trends, and implications for future research. Academy of Management Journal, 43(6), 1248-1264.
Shenhav, Y., & Haberfeld, Y. (1992). Organizational demography and inequality. Social Forces, 71(1), 123-143.
Solomon, E. (1986). Private and public sector managers: An empirical investigation of job characteristics and organizational climate. Journal of Applied Psychology, 71(2), 247-250.
Stewman, S. (1988). Organizational demography. Annual Review of Sociology, 14, 173-202.
Tornow, W. W. (1988). Contract redesign. Personnel Administrator, October, 97-101.
Wagner, W. G., Pfeffer, J., & O’Reilly, C. A. 111. (1984) Organisational demography and turnover in top-management groups. Administrative Science Quarterly, vol. 29, pp. 74-92.
Wehrmeyer, W., & McNeil, M. (2000). Activists, pragmatists, technophiles and tree huggers? Gender differences in employees’ environmental attitudes. Journal of Business Ethics, 28, 211-222.
Wiersema, M. F., & Bantel, K. A. (1992). Top management team demography and corporate strategic change. Academy of Management Journal, 35(1), 91-108.
Wiersema, M. F., & Bird, A. (1993). Organisational demography in Japanese firms: Group heterogeneity, individual dissimilarity, and top management team turnover. Academy of Management Journal, 38(5), 996-1026.
Wood, S. (1995). The four pillars of HRM: Are they connected? Human Resource Management Journal, 5(5), 49-60.
Wood, S., & Albanese, M. T. (1995). Can we speak of a high commitment management on the shop floor? The Journal of Management Studies, 32(2), 213-248.
Wright, P. M., & McMahan, G. C. (1992). Theoretical perspectives for strategic human resource management. Journal of Management, 18(2), 295-320.
Youndt, M. A., Snell, S. A., Dean, J. W., & Lepak, D. P. (1996). Human resource management, manufacturing strategy, and firm performance. Academy of Management Journal, 39(4), 836-866.
Zenger, T. R., & Lawrence, B. S. (1989). Organisational demography: The differential effects of age and tenure distributions on technical communication, Academy of Management Journal, 32(2), 353-376.