hrm practices, organizational citizenship behaviour, and

HRM Practices, Organizational Citizenship Behaviour,and Performance: A Multi-Level Analysisjoms_911 1219..1247

Ed Snape and Tom RedmanHong Kong Baptist University; Durham Business School

abstract We examine the relationship between HRM practices, conceptualized at theworkplace level, and individual employee attitudes and behaviour. We focus on two possibleexplanations for the relationship: social exchange and job influence/employee discretion.Findings from a study of employees in North-East England suggest that there is a positiveimpact of HRM practices on organizational citizenship behaviour, through an effect onperceived job influence/discretion. There was no such effect for perceived organizationalsupport. These findings provide support for a job influence and opportunity explanation ofHRM effects on employee attitudes and behaviour.

INTRODUCTION

Much of the early work evaluating the impact of human resource management (HRM)practices on performance focused on the organizational level of analysis, and examinedthe effect of systems of HRM practices on organizational outcomes such as employeeturnover, productivity, machine efficiency, scrap rates, customer alignment, customersatisfaction, and financial and perceptual measures of firm performance (Arthur, 1992,1994; Becker and Gerhart, 1996; Delaney and Huselid, 1996; Delery and Doty, 1996;Huselid, 1995; Rogg et al., 2001; Youndt et al., 1996). This body of work is nowextensive, with a meta-analysis of the HRM–organizational performance relationshipdrawing on 92 studies conducted between 1990 and 2005 (Combs et al., 2006).

More recently, attention has turned to the effects of systems of HRM practices onindividual employee attitudes and behaviours (Allen et al., 2003; Kuvaas, 2008; Wrightet al., 2003; Zacharatos et al., 2005). Allen et al. (2003) show that the positive relation-ship between ‘supportive human resource practices’ and organizational commitment,job satisfaction, and employee turnover is mediated by perceived organizational support,whilst Zacharatos et al. (2005) show that a ‘high-performance work system’ is associatedwith trust in management and safety climate, which mediate relationships with personal

Address for reprints: Tom Redman, Durham Business School, Durham University, Mill Hill Lane, DurhamDH1 3LB, UK ([email protected]).

The authors have contributed equally to this paper.

© 2010 The AuthorsJournal of Management Studies © 2010 Blackwell Publishing Ltd and Society for the Advancement of ManagementStudies. Published by Blackwell Publishing, 9600 Garsington Road, Oxford, OX4 2DQ, UK and 350 Main Street,Malden, MA 02148, USA.

Journal of Management Studies 47:7 November 2010doi: 10.1111/j.1467-6486.2009.00911.x

safety orientation and safety incidents. Kuvaas (2008) found that the positive relationshipbetween ‘developmental human resource practices’ and work performance was notmediated by perceived organizational support, affective commitment, or organizationaljustice (procedural or interactional).

Most of the studies adopt a single unit of analysis, either individual employees or theorganization/business unit. For example, Allen et al.’s (2003) two studies were conductedentirely at the individual level of analysis, using single-organization samples, withindividual-level perceptual measures of HRM practices. Zacharatos et al.’s (2005)employee-level study involved respondents from two organizations, treated as a singlesample, and again with individual-level perceptual measures of HRM practices. Kuvaas(2008) gathered data across 64 savings banks, but this was an employee-level study, usingperceptual measures of HRM.

There are a small number of multi-level studies of HRM (Holman et al., 2009; Liaoand Chuang, 2004; Sun et al., 2007; Takeuchi et al., 2009; Whitener, 2001; Wu andChaturvedi, 2009). Most of these examine the effect of organization- or establishment-level HRM practices on individual employee outcomes, focusing on the effects of HRMon individual attitudes such as job satisfaction (Takeuchi et al., 2009; Wu andChaturvedi, 2009), trust in management (Whitener, 2001), and organizational commit-ment (Takeuchi et al., 2009; Whitener, 2001; Wu and Chaturvedi, 2009). To ourknowledge, no study has examined the effect of organizational or establishment-levelHRM on individual organizational citizenship behaviour and in-role performance. Thisis an important omission, since evidence suggests that employee behaviours may haveimplications for organizational performance (e.g. Organ et al., 2006), and can there-fore provide an explanation for the relationship between HRM and organizationalperformance.

In this paper, we are concerned with the relationship between HRM practices, andemployees’ organizational citizenship behaviour (OCB) and in-role performance. Weexplore the nature of the HRM practices–behaviours linkage. In addition to the socialexchange explanation implied by earlier HRM studies (e.g. Allen et al., 2003; Takeuchiet al., 2009; Takeuchi et al., 2007; Zacharatos et al., 2005), we examine an additionalexplanation for the effects of HRM: that HRM practices enhance employee perfor-mance by providing greater intrinsic motivation and opportunity to perform throughhigher levels of perceived job influence and discretion. In so doing, we address the widelyrecognized need for a richer understanding of the linkages between HRM and outcomes(Evans and Davis, 2005; Wright and Nishii, 2007), and the suggestion that researchexamining the intermediate-linkages in HRM–performance research ‘should be given ahigh-priority by HRM scholars’ (Ferris et al., 1999, p. 394). We are also responding tocalls for researchers to diversify their attention away from social exchange in analysingthe antecedents of OCB (e.g. Restubog et al., 2008; Zellars and Tepper, 2003), and tosuggestions that employees’ job influence and discretion may be a significant element inthe link between high-commitment HRM practices and performance (Delbridge andWhitfield, 2001; MacDuffie, 1995).

In the extant literature, HRM–outcomes relationships have been under-theorized(Guest, 1997). They have been addressed in terms of social exchange theory, but recentlythis framework in general has been criticized (Coyle-Shapiro and Conway, 2004;

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© 2010 The AuthorsJournal of Management Studies © 2010 Blackwell Publishing Ltd andSociety for the Advancement of Management Studies

Cropanzano and Mitchell, 2005; Kiewitz et al., 2009). We provide a complementaryperspective by examining job characteristics theory explanations of HRM–outcomeslinkages. In so doing, we contribute towards a deeper understanding of the specificpsychological mechanisms that may mediate the relationship between HRM and indi-vidual employee performance. Furthermore, given that employee performance has beenshown to be associated with organizational performance (Ilgen and Pulakos, 1999), webelieve that our analysis provides additional insights into the underlying processes andmechanisms involved in HRM effects, thereby addressing the so called ‘black box’problem (Paauwe, 2009; Ramsay et al., 2000).

In an organizational context, discretion has been defined as an individual’s right tomake choices based on an authoritative assessment of the situation (Feldman, 2001, p.164). Following this approach, we define perceived job influence/discretion as theamount of freedom of choice employees perceive they have over important aspects oftheir work, such as the range of tasks undertaken, the pace of work, how the job is done,working hours, when breaks are taken, and such like. According to job characteristicstheory the core characteristic of autonomy/discretion produces a ‘critical psychologicalstate’ of experienced responsibility for the work, which in turn leads to improved workeffectiveness (Hackman and Oldham, 1980). Job discretion is argued to enhance employ-ees’ sense of responsibility for work outcomes and increases their willingness to go the‘extra mile’ to complete tasks. Conversely, low job discretion may foster a sense of‘learned helplessness’, ‘reduced industriousness’, or ‘going through the motions’(Eisenberger, 1992; Seligman, 1975), which is likely to decrease employee performanceand participation in citizenship behaviours. There is evidence suggesting a strong asso-ciation between job characteristics and employee attitudes and behaviours (Humphreyet al., 2007), and we take this further by examining the mediating role of job influence/discretion in the HRM–performance relationship, so that our paper also contributes toa more complete understanding of the antecedents of OCBs.

In this study, we sample across a range of workplaces, using managers’ ratings ofHRM practices at the workplace level to predict employees’ individual-level attitudesand behaviours. Such an approach allows us to go beyond individual perceptions ofHRM and specifies practices at the workplace level of analysis. We begin by discussingthe issues associated with conceptualizing and measuring HRM. We then review therelatively small number of HRM studies that have used multi-level designs. We arguethat there is a need to extend this research to consider organizational citizenship andperformance behaviours as outcomes and also to assess alternative mediating mecha-nisms in the HRM–employee outcomes relationship. Next, we examine social exchangeand perceived job influence explanations for HRM effects, which provides the basis forthe development of our hypotheses. We then present our methodology and findings,concluding the paper with a discussion of the implications and limitations of the study.

THE NATURE OF HRM

The specification of the ‘bundle’ of HRM practices varies considerably across studies(Boselie et al., 2005; Dyer and Reeves, 1995; Wood and Wall, 2007). To some extent thisreflects different conceptualizations of the underlying work system. Work systems have

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© 2010 The AuthorsJournal of Management Studies © 2010 Blackwell Publishing Ltd and

Society for the Advancement of Management Studies

been conceptualized as ‘high involvement’ (Lawler, 1986), with information sharing thekey characteristic, and as ‘high commitment’ (Wood and De Menzies, 1998), with theessence being a work system that aims to encourage employees to identify with the goalsof the organization and to motivate them to work hard to accomplish those goals. Morerecently, a ‘high performance work system’ approach is beginning to dominate HRMresearch. This is conceptualized as a system of interconnected HR activities, designed toensure that employees have a broad range of superior skills and abilities, which areutilized to achieve the organization’s goals, and thereby provide sustainable competitiveadvantage (Way, 2002; Wood and Wall, 2002).

It appears that consensus is emerging on the nature of the high performance worksystem construct. Wright and Boswell (2002) identify three broad conceptual categoriesof HRM practices. First, employee skills, with HR activities aimed at attracting talentedemployees and developing their skills. Second, motivation, with practices such as per-formance related pay aimed at eliciting high levels of effort. Third, the use of empow-erment programmes to enable employee voice and influence. There appears to begrowing empirical support for the impact of HR programmes conceptualized along theselines (Combs et al., 2006). Furthermore, these HR activities are seen as interdependent‘bundles’, such that the use of one HR activity often necessitates the inclusion of others,such as performance-contingent rewards and performance appraisal. In this paper wefollow this high performance work system conceptualization and define an HRM pro-gramme as a formal integrated system of HR activities that includes selective recruitmentand selection, extensive training and development, regular performance appraisal,performance-contingent rewards, and high levels of employee involvement (Becker andHuselid, 1998; Zacharatos et al., 2005). Given our focus on social rather than economicexchange (see below), we examine collective performance-contingent rewards, based onwork group, department, team, or organization performance, rather than on individualperformance.

There have been suggestions that individual employee-rated measures of HRM maybe better predictors of employees’ attitudinal outcomes than are manager/employer-level HRM measures (Edgar and Geare, 2005; Khilji and Wang, 2006). However, anysuggestion that employee-rated, rather than employer-rated, HRM measures accountfor significant variance in employee attitudes may be attributed to common method bias.In fact, some authors have found little difference between manager ratings and employeeratings in assessing the impact of HRM on attitudinal outcomes (e.g. Takeuchi et al.,2007). In this study, given the need to minimize concerns about common method bias,we use an HR manager rating of HR practices at the workplace level of analysis.

CROSS-LEVEL HRM RESEARCH

The great majority of studies of the impact of HRM tend to focus on a single level ofanalysis, most often the organization level (Combs et al., 2006), but with a growingnumber of individual-level studies (Allen et al., 2003; Kuvaas, 2008; Zacharatos et al.,2005). Despite some theorizing on multi-level HRM models (Arthur and Boyles, 2007;Bowen and Ostroff, 2004; Ostroff and Bowen, 2000; Wright and Nishii, 2007), thereis relatively little empirical work adopting a multi-level approach. In part, this may



reflect the practical difficulties of gaining research access to a large number of internalrespondents across multiple organizations or workplaces (Wright and Boswell, 2002,p. 266).

What few multi-level studies there are have typically specified HRM as anorganization- or business-unit-level variable. Sun et al.’s (2007) study of People’sRepublic of China hotels found that high performance HR practices, evaluated bymanagers at the hotel level, were positively associated with service-oriented OCB,evaluated by supervisors but aggregated to the hotel level, and that this mediated therelationships between HR practices and hotel-level voluntary labour turnover and pro-ductivity. This was a multi-level study, with 81 hotels nested within 12 cities, but therewas no analysis at the employee level. Other studies have, however, involved the analysisof employee data nested within higher-level units. For example, in a study of 257employees in 25 units of a US restaurant chain, Liao and Chuang (2004) examined theeffects of three manager-rated store-level HR practices, employee involvement, training,and performance incentives, on individual employee service performance. They foundthat only employee involvement practices were positively associated with employeeperformance. In a study of 522 employees in 76 Japanese establishments, Takeuchi et al.(2009) reported that ‘concern for employees climate’, an aggregated establishment-levelmeasure of the extent to which employees feel that the establishment values andshows concern for them, fully mediated the relationships between manager-ratedestablishment-level high performance work systems (HPWS) and employee’s individual-level job satisfaction and organizational commitment. Wu and Chaturvedi’s (2009)cross-level study of 1383 employees in 23 Asian manufacturing and service firms foundthat individual-level procedural justice mediated the relationship between an aggregatedemployee-rated measure of establishment-level HPWS and individual employee jobsatisfaction and organizational commitment. Finally, Whitener’s (2001) study of 1689employees in 180 US credit unions found that organizational-level (HR manager-rated)HRM practices of internally equitable rewards moderated the individual-level perceivedorganizational support–organizational commitment relationship, such that it was stron-ger in organizations with high internal equity of rewards. In addition, the relationshipbetween perceived organizational support and trust in management was stronger inorganizations with highly developmental appraisal practices, but weaker in organizationswith highly comprehensive training opportunities.

These multi-level studies have focused mainly on the effects of organizational- orestablishment-level HRM on individual employee attitudes. Of the studies cited above,only Sun et al. (2007) and Liao and Chuang (2004) examine employee behaviours. In theformer, this is specified at the hotel- rather than the individual-level of analysis and in thelatter this was ‘employee service performance’, an employee self-rating of specific cus-tomer service-related behaviours. There is clearly a need to extend the multi-levelresearch to consider mainstream organizational citizenship and performance behav-iours. This is a key aim of the present study.

In addition, we go beyond the direct OCB linkages identified by Sun et al. (2007), andwe test potential mediators other than concern for employees and social exchange (Sunet al., 2007; Takeuchi et al., 2007, 2009). We follow the earlier studies by specifyingHRM at the unit level of analysis. In line with our interest in the impact of HRM on




employee attitudes and behaviours, we specify our mediator and outcome variables atthe individual level. This raises the issue of the theoretical bases for the HRM–outcomeslinkage, to which we now turn.

SOCIAL EXCHANGE THEORY

The relationship between an organization and its employees may be conceptualized asinvolving economic or social exchange. Economic exchange is based exclusively on aspecific contractual relationship, requiring specific performance of contractual obliga-tions, with no expectation of performance beyond the specified terms of the contract(Blau, 1964). Social exchange, however, involves imperfectly specified terms and a normof reciprocity, such that discretionary benefits provided to the exchange partner arereturned in a discretionary way in the longer term (Blau, 1964; Eisenberger et al., 1986).Obligations are non-specific, and trust is essential to the long-term viability of therelationship.

Employment relationships may be seen as having the characteristics of social exchange(Blau, 1964). For example, organizational justice has been seen as providing the employ-er’s side of such an exchange, with employees reciprocating through high levels ofdiscretionary OCB (Moorman, 1991). Furthermore, consistent with the social exchangeview, the justice–OCB relationship has been shown to be mediated by trust and per-ceived organizational support (Konovsky and Pugh, 1994; Moorman et al., 1998), andthe latter in particular has been used as an indicator of employees’ perceptions of afavourable social exchange (e.g. Allen et al., 2003; Eisenberger et al., 1986; Wayne et al.,1997).

Other organizational inputs into the employment relationship have also been consid-ered in a social exchange context. Wayne et al. (1997) considered the quality of leader–member exchange as an input into a social exchange, and terms of employment may alsobe seen in this way. Thus, Van Dyne and Ang (1998) found that contingent workers havelower levels of OCB, which they interpret as evidence that ‘. . . when individuals likecontingent workers feel that organizations view them as short-term, temporary, ordispensable, they reciprocate by performing only required duties and minimizing citi-zenship behaviors’ (p. 694).

There is strong evidence that individual HRM practices impact on employee percep-tions of organizational support. Providing training and development and the investmentof managerial time in appraising the performance and training needs of employees sendsstrong messages that they are valued organizational assets (Rhoades and Eisenberger,2002; Tansky and Cohen, 2001). Reward strategies, for example pay for performancewhich often pay above market rates (Pfeffer, 1998), can increase feelings of beingsupported and valued by the organization. Employee involvement practices can alsosignal that employee contributions are valued and that the organization seeks to build asocial exchange relationship with employees (Allen et al., 2003).

Human resource management policies in general may be seen as an input into thesocial exchange process, as the evidence of positive effects of bundles of ‘high perfor-mance’ or ‘high commitment’ work practices on employee attitudes, behaviour, andturnover suggests. More specifically, HRM practices which demonstrate that the orga-



nization is committed to employees in the long term, wishes to invest in them, and isconcerned about their welfare and development are likely to result in employees feelingthat the organization is being supportive, and so be positively associated with OCB.Thus, Allen et al. (2003) found that ‘supportive human resource practices’ (i.e. partici-pation in decision making, fairness of rewards, and growth opportunities) contributed toemployees’ perceived organizational support, which mediated the relationships betweenHRM practices and organizational commitment, job satisfaction, and employee turn-over. They argue that this is because perceived organizational support creates feelings ofobligations to repay the benefits and support received from the organization, based onthe norm of reciprocity (Eisenberger et al., 1986). In other words, perceived organiza-tional support reflects the strength of the employee’s perceived social exchange relation-ship with the organization.

There is evidence at the business establishment level that high performance worksystems are associated with employee perceptions of social exchange. In a Japanesestudy, Takeuchi et al. (2007) found that high performance work practices, rated by bothemployees and managers, were positively associated with collective human capital andestablishment-level social exchange, which mediated the relationship with a subjectivemeasure of establishment performance. Similarly, in their hotel-level study, Sun et al.(2007) argue that the mediating role of service-oriented citizenship behaviours in therelationship between high performance human resource practices and both productivityand turnover reflects a relational view of the employment relationship, with employeesreciprocating the organization’s favourable treatment.

Social exchange envisages the employee reciprocating the employee’s supportivetreatment, and one possible form of reciprocation is organizational citizenship behav-iour. Two of the most commonly-cited dimensions of OCB are compliance and altruism(Organ et al., 2006). Compliance involves cooperative behaviours which help increasedefficiency, such as volunteering for things that are not absolutely required by the job.Such behaviours go beyond the basic performance of job requirements, to includediscretionary behaviours which reflect a cooperative adherence to the spirit as well as theletter of organizational requirements. Altruism refers to discretionary helping behav-iours, such as assisting others with their work when they have been absent or areoverloaded. Such behaviours benefit specific individuals, although they may also indi-rectly benefit the organization as a whole by increasing the effectiveness of the workgroup.

A review of the literature reports over 30 dimensions of OCBs, with considerablevariation in the nature of behaviours (Podsakoff et al., 2000). However, ‘helping’ behav-iours have been described by Podsakoff et al. (2000, p. 516) as being an important formof citizenship behaviour by ‘virtually everyone who has worked in this area’. Our focuson compliance and altruism is consistent with this ‘helping’ conceptualization of OCB,helping the organization in general (compliance) and specific individuals such asco-workers (altruism). Furthermore, in a study of the consequences of HRM, helpingbehaviours targeted at the organization and individuals who work there are of particularinterest, given the strong linkage of these dimensions to organizational performance(Organ et al., 2006).

Based on the above, we offer the following hypotheses:




Hypothesis 1a: Perceived organizational support will mediate the positive relationshipbetween HRM practices and OCB (compliance).

Hypothesis 1b: Perceived organizational support will mediate the positive relationshipbetween HRM practices and OCB (altruism).

In contrast to OCB, in-role behaviour has been characterized as non-discretionaryand thus as not providing currency in a social exchange relationship. However, recentdebates have questioned the degree to which the discretionary–non-discretionary dis-tinction can be neatly drawn when differentiating OCB and in-role behaviours. Harrisonet al.’s (2006) meta-analytic findings suggest that behaviours typically seen as in-role,such as absence and lateness, may be better interpreted as controllable forms of inputreduction and thus subject to the same motivations as OCB. Therefore, consistent withthis, we suggest that Hypothesis 1 will also apply in the case of in-role behaviour.

Hypothesis 1c: Perceived organizational support will mediate the positive relationshipbetween HRM practices and in-role behaviour.

JOB INFLUENCE AND EMPLOYEE DISCRETION

Social exchange theory has become a strong theme in the OCB literature. However,there have recently been calls for researchers to diversify their attention away from socialexchange in analysing the antecedents of OCB (Zellars and Tepper, 2003). Perceived jobcharacteristics may provide an explanation for OCB, which lies outside the traditionalsocial exchange explanation.

The job influence/discretion construct has been used in a wide range of studies. Jobinfluence has been found to be an antecedent of organizational commitment (Sherer andMorishima, 1989; Snape and Chan, 2000), job and pay satisfaction (Cappelli and Sherer,1988), job demands, stimulating work, skill development, and involvement (Pettersonet al., 1995). It has also been used as a measure of ‘psychological workload’ in predictingweight gain (Overgaard et al., 2004). Holman et al. (2009) conducted a multi-levelanalysis (establishments nested within countries) of work design variation in call centres,finding that job discretion was negatively associated with quit rates and labour costs.Closely related concepts, such as job autonomy, task control, and decision latitude(Hackman and Oldham, 1980; Karasek, 1979), have been found to be positively relatedto employee wellbeing and motivation (Parker and Wall, 1998), and meta-analyticstudies report relationships between job autonomy and behaviour (e.g. performance,absenteeism, and turnover intent), attitudes (e.g. job satisfaction and organizationalcommitment), role perceptions (e.g. role conflict and role ambiguity), and wellbeing (e.g.stress, burnout, and overload) (Fried and Ferris, 1987; Humphrey et al., 2007). Inaddition, job influence has been studied as an outcome variable, for example of employeeinvolvement and participation programmes (Delbridge and Whitfield, 2001), and offamily-friendly management practices (Ortega, 2009). In these studies, perceived jobinfluence/discretion is typically seen as a job autonomy-type variable, tapping the



amount of influence employees perceive they have over aspects of their work, such as therange of tasks undertaken, the pace of work, how the job is done, working hours, whenbreaks are taken, etc.

In this paper, we are interested in the link between HRM practices and job influence/discretion. There are suggestions that high levels of job influence are necessary for suchpractices to impact positively on organizational performance. For example, MacDuffie(1995, p. 198) argues that flexible production systems require an ‘enriched’, ‘motivated,skilled and adaptable’ workforce, whilst Appelbaum and colleagues’ manufacturingstudies draw on sociotechnical theory and job characteristics theory to argue that workerself regulation is the primary mechanism through which job design influences outcomes(Appelbaum et al., 2000; Berg et al., 1996).

Most recently, Ortega (2009) has examined the relationship between employees’ratings of their involvement in performance pay, job rotation, continuous improvement,teamwork, and vertical communication on the one hand, and employee discretion on theother. The latter was measured by asking employees whether they could choose theorder in which they conduct tasks, the methods with which they work, the speed of work,timing of breaks, and working hours. Findings suggested that performance pay andvertical communications were positively associated with discretion, but other practices,such as teamwork and job rotation, were either unrelated or even negatively associatedwith some aspects of discretion (Ortega, 2009, p. 21).

The literature on high-commitment HRM practices has suggested that employees’degree of job influence and discretion is a significant element in the causal link betweensuch practices and performance (Delbridge and Whitfield, 2001; MacDuffie, 1995).HRM practices which build employees’ skills and involvement provide them with theability and opportunity to exercise a higher degree of perceived influence over decisionmaking in the job. This in turn may bring a heightened sense of self efficacy and intrinsicmotivation to perform (e.g. Hackman and Oldham, 1980). In addition, job holders withhigher levels of job influence may have greater potential for task-related interaction withsupervisors and co-workers, and thus have a work environment more conducive toperforming discretionary OCB. There is some support for the latter in Settoon andMossholder’s (2002) finding that relationship quality is associated with interpersonalcitizenship behaviour.

The literature on individual HR practices and employee influence and discretionreinforces these arguments. Thus, skill development and employee involvement arepositively associated with job influence (Petterson et al., 1995), and employee involve-ment practices provide employees with increased ‘role-making’ opportunities toexpand and enrich their job roles and thus increase their positive perceptions of jobinfluence (Evans and Davis, 2005; Wood and Wall, 2007). There is also evidence of alink between job characteristics and OCB. Studies have reported that task feedback,task routinization, intrinsically satisfying tasks, and task scope all have significant cor-relations with OCB (Podsakoff and Mackenzie, 1995; Podsakoff et al., 1996), and Pod-sakoff et al.’s (2000, p. 551) review of the literature demonstrates a consistentrelationship between task variables and OCB. The suggestion is that employees whoare able to exercise a high degree of influence in their jobs are motivated and enabledto perform.




The above arguments may be expected to apply to performance in general, bothOCBs and in-role behaviours. As we noted in our discussion of Hypothesis 2c, we mayquestion the extent to which OCBs are entirely and unambiguously discretionary andin-role behaviours non-discretionary. It is more likely that both aspects of performancewill be seen by employees as having discretionary and non-discretionary elements, whichopens up the possibility for motivational factors, as well as social exchange, to influenceboth. The argument developed above suggests that job discretion provides the ability,opportunity, and motivation to perform in general. We hypothesize as follows:

Hypothesis 2a: Perceived job influence will mediate the positive relationship betweenHRM practices and OCB (compliance).

Hypothesis 2b: Perceived job influence will mediate the positive relationship betweenHRM practices and OCB (altruism).

Hypothesis 2c: Perceived job influence will mediate the positive relationship betweenHRM practices and in-role behaviour.

The hypothesized model is shown in Figure 1. We included control variables at theindividual (organizational tenure, gender, and managerial and professional job status)and workplace (age of workplace, public or private sector, and natural logarithm of totalworkplace employment) levels.

METHOD

Sample

The data came from a study of human resource management in North-East England.The sample was identified through the Arbitration, Conciliation and Advisory Service(ACAS). We used the ACAS North-East officers’ contacts list to approach HR officers or

HRM Practices

Compliance.Altruism.In-role behaviour.

Perceived organizational support.Perceived job influence.

Workplace level

Individual level

Figure 1. Hypothesized modelNote: We also included control variables at the individual (workplace tenure, gender, managerial andprofessional job status) and workplace levels (sector, log of employment, and age of workplace).



senior managers to request participation in the study, and 114 workplaces initially agreedto participate. A survey facilitator was identified in each establishment, typically locatedin the HR department, and provided with guidance on how to distribute the surveys.Each workplace was sent a pack consisting of a questionnaire to be completed by theon-site manager responsible for HRM, a questionnaire for the senior general manageron site, and 50 questionnaires to be distributed to a sample of employees. Questionnaireshad a workplace identifier and were returned direct to the university. We received atleast partial responses from 60 workplaces, a 53 per cent response rate. The respondentsare broadly representative of the main employers in North-East England, with anemphasis on manufacturing (for example, light engineering, defence industries, pro-cessed food, brewing, pharmaceuticals, commodity and specialist chemicals, and steel)and the public sector (NHS, local government, universities, civil service, and uniformedservices – police, fire, and ambulance), and rather less emphasis on private services (e.g.TV media, distribution, privatized utilities, legal, and accountancy); small companieswere underrepresented. We received 867 responses from employees in these workplaces,representing a 29 per cent response rate.

In this paper, we used data only from those workplaces for which we had responsesfrom an on-site manager responsible for HRM and a general manager. We also excludedthose workplaces for which we had fewer than three individual employee respondents(Ambrose and Schminke, 2003). Along with missing values, this reduced the sample foranalysis to 28 workplaces, and 519 employees. In this sample, the number of employeerespondents per workplace ranged from 7 to 40. The analysis reported is based on datafrom the employee, HR, and general manager questionnaires.

In this employee sample, mean organizational tenure was 12.15 years, average agewas 40.25 years, 38 per cent were female, 76 per cent were married or living as married,17 per cent were in managerial or supervisory jobs, and 20 per cent were in professional-level jobs. Looking at the workplaces, average total employment was 639, averageestablishment age was 47 years, and 75 per cent were in the private sector, of which 16were in manufacturing.

Measures

The measures of perceived job influence, perceived organizational support, OCB, in-rolebehaviour, and the individual-level control variable (managerial status) were included inthe employee questionnaire. The measure of HRM practices and the workplace-levelcontrols (sector and employment) were taken from the HRM manager questionnaire.

Perceived organizational support was measured with four items from Eisenbergeret al. (1986), responding on a seven-point scale from ‘strongly disagree’ (= 1) to ‘stronglyagree’ (= 7). In selecting the items for perceived organizational support we followed therecommendations of Rhoades and Eisenberger (2002) that short forms of POS shouldcapture the key facets of the definition of POS. Thus items 8, 9, 20, and 25 from theoriginal scale (Eisenberger et al., 1986) were used. These are high loadings items (allbetween 0.72 and 0.83), which have been used in the various short forms of the scale andare drawn from the core facets of employee wellbeing (e.g. ‘the organization really caresabout my well being’) and contribution (e.g. ‘the organization cares about my opinions’).




Perceived job influence/discretion was based on Magneau and Hunt’s (1996) scale,responding to the question ‘Thinking about your present job, how much say do youactually have in the following decisions?’ (‘No say’ = 1 to ‘A lot of say’ = 4), with fouritems covering the tasks to be performed, the amount of work to be performed each day,establishing work rules and procedures, and deciding how exceptional issues are to bedealt with.

Organizational citizenship behaviour (OCB) was measured with nine items. Fiveitems, based on Podsakoff et al. (1990), represented altruism (e.g. ‘Help others who haveheavy workloads’), and four items, drawn from Smith et al. (1983), represented compli-ance (e.g. ‘Volunteer for things that are not absolutely required’). In-role behaviour (IRB)was measured with three items from Williams and Anderson’s (1991) scale, selectingbased on their high factor loadings (e.g. perform all the tasks that are expected of you[0.87]). Responses for OCB and in-role behaviour were on a five-point scale, reflectingthe frequency of engagement in the activity (‘never’ [= 1] to ‘always’ [= 5]).

Whilst self-reported OCBs and IRBs are quite common in the literature (Podsakoffet al., 2000), it is more usual to use supervisor reports. However, in the present study, wealready had a complex research design – gathering data from employees, HR managers,and general managers across multiple establishments – and it was neither feasible norcost-effective for us to gather supervisor ratings of individual employee behaviours. Inparticular, our initial discussion with employers suggested that research access andresponse rates were likely to be compromised by requesting supervisor ratings. Onbalance, we felt that it was preferable to use self reports of employee behaviour, as wasdone in at least one earlier multi-level study of employee performance (Liao and Chuang,2004). It should be noted that questionnaires were completely anonymous and weremailed back directly to the university by respondents, which may reduce the incentive forindividuals to overstate their own citizenship and in-role behaviours. Furthermore, ourconcern was with the variance in such behaviours across individuals and workplaces,rather than with their overall mean levels in the sample, so that any tendency for selfreports to systematically overstate such behaviours is unlikely to affect our findings.

We estimated a measurement model for the employee sample, including all the scalesmeasured in the employee questionnaire: perceived job influence, perceived organiza-tional support, compliance, altruism, and in-role behaviour. The hypothesized five-factor model provided a reasonable overall fit (c2 = 748.589; d.f. = 160; GFI = 0.886;AGFI = 0.850; CFI = 0.908; RMSEA = 0.078). All indicators loaded significantly(p < 0.001) on their latent variables. A single-factor model provided a poor fit(c2 = 4102.531; d.f. = 170; GFI = 0.511; AGFI = 0.396; CFI = 0.386; RMSEA = 0.197),with a significant deterioration in chi-square relative to the hypothesized model (changein c2 = 3353.942; change in d.f. = 10; p < 0.01). We also found a significant deteriorationin chi-square relative to the hypothesized model for 4-factor models which combinedaltruism and compliance (change in c2 = 695.234; change in d.f. = 4; p < 0.01), andperceived job influence and organizational support (change in c2 = 922.122; change ind.f. = 4; p < 0.01), and also for a 3-factor model combining altruism, compliance, andin-role behaviour (change in c2 = 1019.116; change in d.f. = 7; p < 0.01).

Table I shows the item loadings for the 5-factor model, along with the varianceextracted, construct reliabilities, and squared correlations amongst constructs. All factor



loadings exceeded 0.5, apart from one in-role behaviour item. The variance extractedwas at least 0.5, apart from in-role behaviour, which is close to that level, and constructreliability estimates all exceeded 0.7. These findings suggest convergent validity. There isalso evidence of discriminant validity. We examined the modification indices associatedwith the 5-factor model, and none of these indicated standardized cross loadings inexcess of 0.3. Furthermore, as shown in the bottom section of Table I, for all constructsthe variance extracted substantially exceeded the squared correlations with otherconstructs.

Ratings of HRM practices in the workplace were collected in the HR managerquestionnaire. Respondents were asked to assess the percentage of employees or jobs intheir workplace which were covered by a range of specified HRM practices. The specificpractices included in the system of HRM practices have varied between studies (Dyerand Reeves, 1995). However, the common theme is that the practices address therecruitment, development, motivation, and involvement of employees. Accordingly, we

Table I. Standardized factor loadings, variance extracted, reliabilities, and squared correlations for the5-factor measurement model (employee-rated variables)

Item Perceived org. support Perceived job influence Compliance Altruism In-role behaviour

POS1 0.86POS2 0.84POS3 0.79POS4 0.73PJI1 0.81PJI2 0.84PJI3 0.83PJI4 0.88COMP1 0.83COMP2 0.92COMP3 0.88COMP4 0.50ALT1 0.65ALT2 0.72ALT3 0.74ALT4 0.74ALT5 0.69IRB1 0.42IRB2 0.87IRB3 0.64

Variance extracted 0.65 0.70 0.64 0.50 0.45Construct reliability 0.72 0.89 0.84 0.79 0.77

Interconstruct squared correlations

POS – 0.23 0.04 0.00 0.00PJI 0.23 – 0.18 0.05 0.01COMP 0.04 0.18 – 0.26 0.01ALT 0.00 0.05 0.26 – 0.03IRB 0.00 0.01 0.01 0.03 –




include multiple practices which are likely to address each of these areas, as shown in theAppendix. The items describe a HPWS approach which selects staff carefully, appraisestheir performance regularly, motivates them with performance related rewards, andprovides them with formal induction, training, and promotion opportunities, and withinformation and opportunities to give their views. The HR manager was asked toprovide a rating for managers and professionals as one group and also for all otheremployees. Separate HRM practices ratings by the HR manager for the job groups ofmanagers and professionals and for other employees were computed by averaging the 12items, and an overall workplace rating was computed from these, weighted by theproportion of managers and professionals and other employees.

We had only a small sample of HR managers (one per workplace), with 50 workplacesfor which all HR data was available, so that with 12 items in the HRM measure, the ratioof subjects to variables (STV) was only 4.17. This is less than the minimum recom-mended STV ratio of 5:1 often cited for exploratory factor analysis (e.g. Hair et al.,2006). Nevertheless, we performed a factor analysis, and the results are summarized inthe appendix. The first four factors each had eigenvalues greater than 1 and accountedfor 59 per cent of variance. A fifth factor had an eigenvalue of 1.003, but this fell belowan ‘elbow’ point in the scree test and did not add to the interpretability of the solution.The rotated factor loadings for the four-factor solution are shown in the Appendix.Factor 1 related to the provision of off-the-job training, performance appraisal, qualitycircles, attitude surveys and formal induction for new recruits, and so appeared torepresent a developmental approach to HRM (‘Development’). The second factorrelated primarily to the use of a rigorous selection process (‘Selection’), although theprovision of employee newsletters and briefings also loaded on this factor. Factor 3related to the use of group and organization-wide incentive pay (‘Rewards’). The finalfactor was concerned with on-the-job training and internal promotion, representing aninternal labour market approach to HRM (‘Internal labour market’).

These findings, although they should be treated with caution given the small samplesize, provide some evidence for multidimensionality. However, where separate dimen-sions have been identified, it has been common to combine them into a single HRMpractices dimension (e.g. Bae and Lawler, 2000; Sun et al., 2007). Such an approach isconsistent with the argument in the literature that it is the system of practices as a wholethat constitutes a strategic asset for the organization (Becker and Huselid, 1998; Dattaet al., 2005). In the case of our measure, it is significant that careful selection, employeedevelopment and involvement, internal development and promotion of employees(‘make’ rather than ‘buy’), and group-based incentives have all been identified as char-acteristic of the high performance work system approach to HRM (Combs et al., 2006),providing some theoretical rationale for combining them into a single measure. Finally,using a unitary measure has the advantage of model parsimony.

Following on from such arguments, and in order to provide for comparison withprevious findings, we initially followed the single-dimension approach, aggregatingacross all 12 items to produce a single measure of HRM practices. This provides the basisfor our core analysis. However, in light of the findings of the factor analysis and mindfulof the possibility that job characteristics and social exchange might be differentiallyrelated to our four dimensions, we also conducted a post hoc analysis using the four



HRM dimensions separately: development, selection, rewards, and internal labourmarket. Given the exploratory nature of this dimensional analysis, we offer no specifichypotheses here.

The level 1 control variables were organizational tenure (measured in years), gender(female = 1; male = 0), and managerial or professional job status (= 1; other job = 0), alltaken from the employee questionnaire. The level 2 controls were sector (public ser-vices = 1; private sector = 0), the natural logarithm of total workplace employment, bothtaken from the HR manager questionnaire, and establishment age, taken from thegeneral manager questionnaire.

RESULTS

Means, standard deviations, and correlations for the individual-level variables are shownin Table II. We evaluated the impact of HRM practices on employees’ organizationalcitizenship and in-role behaviours using hierarchical linear modelling (HLM). Compli-ance, altruism, and in-role behaviours were modelled separately as individual-leveldependent variables, with HRM practices as the workplace-level independent variable.

HRM Practices, Perceived Job Influence, and Organizational Support

A condition for mediation by perceived organization support and job influence is thatHR practices are positively associated with these variables. Therefore, before estimatingthe models for compliance, altruism, and in-role behaviour, we estimated models withperceived organization support and perceived job influence as dependent variables. Weadopted a staged approach to the HLM analysis, as shown in Tables III and IV. Webegan with a null model, with no level 1 or level 2 predictors. The ratio of between-groupto total variance provided an intra-class correlation coefficient (ICC) of 0.128 for per-ceived job influence and 0.136 for perceived organizational support, suggesting that 12.8and 13.6 per cent of the variance in perceived job influence and perceived organizationalsupport resides between groups. Although the ICCs were small, there was statisticallysignificant between-group variance in perceived job influence and perceived organiza-tional support, suggesting that it was appropriate to examine level 2 predictors.

We then estimated model 2, including the level 1 control variables only. The resultssuggest that managers, professionals, and women had higher levels of perceived jobinfluence (Table III) and perceived organizational support (Table IV), with organiza-tional tenure negatively associated with perceived organizational support only. Therandom error variance on the constant was significant for both dependent variables. Wethen proceeded with model 3, which included the level 2 predictors. According to theseresults, none of the level 2 controls was significant in the perceived job influence analysis(Table III), but perceived organizational support was higher in public sector workplaces(Table IV). HRM practices was positively associated with both perceived job influence(Table III), and perceived organizational support (Table IV).

HRM Practices and Employee Behaviour

Turning now to the analyses for compliance, altruism, and in-role behaviour, we used asimilar staged approach, as shown in Tables V, VI, and VII. Beginning with the null




Tab

leII

.M

eans

,sta

ndar

dde

viat

ions

,cor

rela

tions

,and

relia

bilit

ies

(indi

vidu

al-le

velv

aria

bles

)

Mea

nS.

D.

12

34

56

78

Ten

ure

12.1

59.

81Fe

mal

e0.

380.

49-0

.25*

**M

anag

er0.

170.

380.

12**

-0.1

1*Pr

ofes

sion

al0.

200.

40-0

.05

-0.0

8-0

.23*

**Pe

rcei

ved

orga

niza

tiona

lsup

port

4.06

1.44

-0.1

1*0.

16**

*0.

15**

0.05

Perc

eive

djo

bin

fluen

ce2.

790.

960.

010.

030.

35**

*0.

19**

*0.

42**

*C

ompl

ianc

e3.

020.

91-0

.05

0.02

0.24

***

0.06

0.18

***

0.37

***

Altr

uism

3.28

0.87

-0.0

40.

19**

*0.

11**

-0.0

50.

030.

16**

*0.

46**

*In

-rol

ebe

havi

our

4.75

0.54

-0.0

50.

15**

-0.0

1-0

.17*

**0.

02-0

.07

0.22

***

0.19

***

Not

e:2-

taile

dte

sts.

n=

519.

*p

<0.

05,*

*p

<0.

01,*

**p

<0.

001.



Tab

leII

I.R

esul

tsof

HL

Man

alys

isfo

rth

ean

tece

dent

sof

perc

eive

djo

bin

fluen

ce

Inde

pend

ent

vari

able

Nul

lm

odel

Mod

el2

Mod

el3

Mod

el4

Mod

el4

Mod

el6

Mod

el7

Lev

el1

Con

stan

t2.

78**

*(0

.12*

**)

2.42

***

(0.1

3**)

2.37

***

(0.1

1*)

2.45

***

(0.1

1*)

2.75

***

(0.1

4**)

2.76

***

(0.1

3**)

2.22

***

(0.1

2**)

Ten

ure

0.00

(0.0

0)0.

00(0

.00)

0.00

(0.0

0)0.

00(0

.00)

0.00

(0.0

0)0.

00(0

.00)

Fem

ale

(=1;

mal

e=

0)0.

13*

(0.0

0)0.

13*

(0.0

1)0.

13*

(0.0

1)0.

13*

(0.0

1)0.

13*

(0.0

1)0.

13*

(0.0

1)M

anag

er(=

1;ot

her

=0)

1.07

***

(0.0

8)1.

05**

*(0

.06)

1.07

***

(0.0

6)1.

08**

*(0

.06)

1.06

***

(0.0

6)1.

05**

*(0

.06)

Prof

essi

onal

(=1;

othe

r=

0)0.

68**

*(0

.01)

0.67

***

(0.0

1)0.

67**

*(0

.01)

0.69

***

(0.0

1)0.

68**

*(0

.01)

0.69

***

(0.0

1)

Lev

el2

Sect

or(p

riva

te=

0;pu

blic

=1)

0.15

0.06

-0.0

80.

100.

02

Log

empl

oym

ent

-0.0

7-0

.06

-0.0

3-0

.07

-0.0

4A

geof

esta

blis

hmen

t0.

000.

000.

000.

000.

00H

RM

prac

tices

0.01

*H

RM

dim

ensi

ons

Dev

elop

men

t0.

01*

Sele

ctio

n-0

.00

Rew

ards

0.00

Inte

rnal

labo

urm

arke

t0.

01*

With

in-g

roup

resi

dual

vari

ance

0.81

0.65

0.66

0.66

0.66

0.66

0.66

Mod

elde

vian

ce14

00.3

013

00.8

813

23.8

413

24.4

513

26.3

013

25.7

613

23.8

5

Not

es:

Uns

tand

ardi

zed

coef

ficie

ntes

timat

esw

ithro

bust

stan

dard

erro

rs.E

stim

ates

ofth

era

ndom

erro

rva

rian

ceco

mpo

nent

sare

inpa

rent

hese

s.n

=51

9fo

rin

divi

dual

-leve

lvar

iabl

es.

n=

28fo

rgr

oup-

leve

lvar

iabl

es.

†p

<0.

10,*

p<

0.05

,**

p<

0.01

,***

p<

0.00

1.




Tab

leIV

.R

esul

tsof

HL

Man

alys

isfo

rth

ean

tece

dent

sof

perc

eive

dor

gani

zatio

nals

uppo

rt

Inde

pend

ent

vari

able

Nul

lm

odel

Mod

el2

Mod

el3

Mod

el4

Mod

el4

Mod

el6

Mod

el7

Lev

el1

Con

stan

t3.

98**

*(0

.29*

**)

3.66

***

(0.4

0**)

3.00

***

(0.3

9*)

3.22

***

(0.3

8*)

3.32

***

(0.4

5**)

3.84

***

(0.3

9*)

3.04

***

(0.4

1**)

Ten

ure

-0.0

1†(0

.00)

-0.0

1†(0

.00)

-0.0

1†(0

.00)

-0.0

1†(0

.00)

-0.0

1†(0

.00)

-0.0

1†(0

.00)

Fem

ale

(=1;

mal

e=

0)0.

39*

(0.0

6)0.

35*

(0.0

4)0.

36*

(0.0

4)0.

37*

(0.0

5)0.

36*

(0.1

1)0.

36*

(0.0

4)M

anag

er(=

1;ot

her

=0)

0.70

**(0

.30)

0.62

**(0

.32)

0.64

**(0

.30)

0.66

**(0

.26)

0.59

**(0

.39)

0.64

**(0

.28)

Prof

essi

onal

(=1;

othe

r=

0)0.

36*

(0.1

9)0.

30†

(0.2

0)0.

30†

(0.1

8)0.

32†

(0.1

7)0.

26(0

.21)

0.32

†(0

.18)

Lev

el2

Sect

or(p

riva

te=

0;pu

blic

=1)

0.60

**0.

40†

0.54

*0.

76**

0.40

†

Log

empl

oym

ent

-0.0

30.

010.

00-0

.08

0.02

Age

ofes

tabl

ishm

ent

-0.0

0-0

.00

-0.0

0-0

.00

-0.0

0H

RM

prac

tices

0.01

*H

RM

dim

ensi

ons

Dev

elop

men

t0.

01Se

lect

ion

0.00

Rew

ards

0.01

**In

tern

alla

bour

mar

ket

0.01

†

With

in-g

roup

resi

dual

vari

ance

1.81

1.65

1.65

1.65

1.65

1.64

1.65

Mod

elde

vian

ce18

19.5

817

96.8

018

11.9

218

14.6

018

15.1

018

10.5

118

14.3

1

Not

es:

Uns

tand

ardi

zed

coef

ficie

ntes

timat

esw

ithro

bust

stan

dard

erro

rs.E

stim

ates

ofth

era

ndom

erro

rva

rian

ceco

mpo

nent

sare

inpa

rent

hese

s.n

=51

9fo

rin

divi

dual

-leve

lvar

iabl

es.

n=

28fo

rgr

oup-

leve

lvar

iabl

es.

†p

<0.

10,*

p<

0.05

,**

p<

0.01

,***

p<

0.00

1.



Table V. Results of HLM analysis for the antecedents of OCB (compliance)

Independent variable Null model Model 2 Model 3 Model 4

Level 1

Constant 3.01*** (0.05**) 2.80*** (0.09*) 2.23*** (0.06†) 2.68*** (0.02†)Tenure -0.00 (0.00) -0.00 (0.00) -0.00 (0.00)Female (= 1; male = 0) 0.09 (0.03) 0.08 (0.02) 0.04 (0.02)Manager (= 1; other = 0) 0.68*** (0.03) 0.64*** (0.01) 0.32*** (0.03)Professional (= 1; other = 0) 0.29* (0.11) 0.24* (0.11) 0.05 (0.04)Perceived organizational support 0.01 (0.00)Perceived job influence 0.30*** (0.08†)

Level 2

Sector (private = 0; public = 1) -0.06 -0.15†

Log employment 0.06 0.04Age of establishment -0.00 -0.00HRM practices 0.01† 0.00

Within-group residual variance 0.79 0.73 0.73 0.62Model deviance 1370.94 1345.34 1366.02 1313.88

Notes: Unstandardized coefficient estimates with robust standard errors. Estimates of the random error variance compo-nents are in parentheses. n = 519 for individual-level variables. n = 28 for group-level variables.† p < 0.10, * p < 0.05, ** p < 0.01, *** p < 0.001.

Table VI. Results of HLM analysis for the antecedents of OCB (altruism)

Independent variable Null model Model 2 Model 3

Level 1

Constant 3.29*** (0.05***) 3.11*** (0.07) 3.17*** (0.05)Tenure 0.00 (0.00) 0.00 (0.00)Female (= 1; male = 0) 0.35*** (0.01) 0.34*** (0.01)Manager (= 1; other = 0) 0.27** (0.07) 0.11 (0.07)Professional (= 1; other = 0) -0.05 (0.22*) -0.16 (0.16)Perceived organizational support -0.03 (0.00)Perceived job influence 0.15** (0.02)

Level 2

Sector (private = 0; public = 1)Log EmploymentAge of establishmentHRM practices

Within-group residual variance 0.71 0.65 0.62Model deviance 1319.21 1301.73 1296.02





models, we calculated ICCs of 0.055 for compliance, 0.065 for altruism, and 0.053 forin-role behaviour. Although the ICCs were smaller than for perceived job influence andorganizational support, there was still significant between-group variance in compliance,altruism, and in-role behaviour.

We then estimated model 2, with level 1 control variables only (compliance, altruism,and in-role behaviour – Tables V, VI, and VII, respectively). These results suggest thatcompliance was higher for managers and professionals, altruism was higher for managersand for women, and in-role behaviour was for higher for women and lower for profes-sionals. For compliance and in-role behaviour, but not for altruism, the model 2 resultsshowed significant random variance components for the intercept, so that we proceededto include the level 2 controls and HRM practices in model 3 for compliance and in-rolebehaviour only. According to these results (Table V and VII), of the level 2 controls onlysector was significant. There was a positive direct relationship of HRM practices oncompliance, but no such direct HRM relationship for in-role behaviour.

Moving to model 4 for compliance and in-role behaviour, we added the hypothesizedmediators, perceived job influence, and organizational support. In the case of compli-ance (Table V), perceived job influence was significant, with a positive coefficient, andthe coefficient for HRM practices was no longer significant. Perceived organizationalsupport was non-significant. Taken along with the earlier results on the associationsbetween HRM and the potential mediators, these findings suggest that perceived jobinfluence, but not perceived organizational support, fully mediated the relationshipbetween HRM practices and compliance, providing support for Hypothesis 2a, but notfor Hypothesis 1a. For in-role behaviour (Table VII), there was no direct HRM practices

Table VII. Results of HLM analysis for the antecedents of in-role behaviour

Independent variable Null model Model 2 Model 3 Model 4

Level 1

Constant 4.76*** (0.02**) 4.72*** (0.05**) 4.54*** (0.04**) 4.51*** (0.05**)Tenure -0.00 (0.00) -0.00 (0.00) -0.00 (0.00)Female (= 1; male = 0) 0.19** (0.05*) 0.19** (0.05*) 0.17** (0.05†)Manager (= 1; other = 0) -0.01 (0.04) -0.00 (0.06) -0.02 (0.12)Professional (= 1; other = 0) -0.19* (0.09) -0.19* (0.10) -0.21* (0.10)Perceived organizational support 0.02 (0.00*)Perceived job influence -0.00 (0.01)

Level 2

Sector (private = 0; public = 1) -0.16* -0.24**Log Employment 0.05 0.06Age of establishment 0.00 0.00HRM practices -0.00 -0.00

Within-group residual variance 0.27 0.25 0.25 0.23Model deviance 820.48 807.40 834.23 836.01




effect and neither perceived organizational support nor perceived job influence weresignificant, providing no support for Hypotheses 1c or 2c.

Although it was inappropriate to include level 2 predictors for altruism, we didexamine the effects of the mediators, perceived organizational support and perceived jobinfluence (model 3 of Table VI). There was no significant effect for perceived organiza-tional support, providing no support for Hypothesis 1b, but there was a significantpositive effect of perceived job influence on altruism. According to Baron and Kenny(1986), the lack of a direct effect from HRM practices to altruism in the previous modelrules out mediation. However, Seibert et al. (2004) argue that a significant direct rela-tionship between the independent and dependent variables is not required for mediation,and that only relationships between the independent and mediator, and between themediator and dependent variables are necessary, referring to this as an ‘indirect rela-tionship’. Mathieu and Taylor (2006) suggest that the lack of a direct relationshipbetween independent and dependent variable rules out mediation, because ‘[i]f no suchrelationship exists, then there is nothing to be mediated’ (p. 1038), but they also acceptthat an ‘indirect relationship’ does not require an initial relationship between indepen-dent and dependent variable. They recommend a sequence of decision rules, beginningwith a test for full mediation and then proceeding to assess partial mediation and anindirect relationship. We followed their recommended sequence, according to whichperceived job influence was not a mediator, but it did intervene in the indirect relation-ship between HRM practices and altruism. HRM practices were significantly associatedwith perceived job influence, which was significantly associated with altruism; the Sobeltest of this indirect relationship was significant (Sobel test statistic = 1.95; two-tailedp = 0.05). Whilst not strictly supporting the mediation Hypothesis 2b, this finding sug-gests that job influence plays a role in transmitting the effects of HRM practices toaltruism.

Post Hoc Analysis of the HRM Dimensions

Finally, as explained earlier, we also conducted a post hoc analysis using the four HRMdimensions identified in the factor analysis: development, selection, rewards, and internallabour market. As shown in Table III, the development and internal labour marketdimensions were positively associated with perceived job influence, the selection andrewards dimensions having no significant association. As shown in Table IV, only therewards and internal labour market dimensions were positively associated with perceivedorganizational support. These results suggest that job influence was associated with adevelopmental approach to HRM, with an emphasis on employee training, appraisal,involvement, and internal career development. In contrast, perceived organizationalsupport was associated with collective incentive pay and internal career development,implying that such HRM practices in particular are interpreted by employees as inputsinto a social exchange process.

The results for HRM dimensions were not included in Tables V, VI, and VII forreasons of space. The only significant direct association between HRM dimensions andemployee behaviours was for the internal labour market dimension in the case ofcompliance, and this was fully mediated by perceived job influence.




DISCUSSION

Our findings suggest that HRM practices had a positive association with compliance,mediated by perceived job influence, and that perceived job influence intervened in asignificant indirect association between HRM practices and altruism. HRM practiceswere significantly associated with perceived organization support, suggesting that suchpractices are seen by employees as demonstrating that the organization is concernedabout their welfare and values their contribution. However, there was no associationbetween support and OCB/IRB, so that there was no evidence that perceived organi-zational support mediated the relationship between HRM and employee behaviour. Theimplication is that the impact of HRM practices on compliance and altruism is trans-mitted via perceived job influence only, providing support for an intrinsic motivation andopportunity view of HRM effects on employees’ organizational citizenship behaviour.

The study has implications for theory and research. Our findings on the importanceof perceived job influence in the HRM practices–compliance relationship support theview that it is time to look beyond purely social exchange explanations of OCB (Zellarsand Tepper, 2003). HRM practices are significant, not just as currency in a socialexchange relationship with employees, but also for their role in enhancing employees’sense of job influence. The latter may provide intrinsic motivation, a sense of selfconfidence, and the opportunity to perform OCB. We have not examined intrinsicmotivation, a sense of self confidence, and the opportunity to perform OCB, separatelyin the current study, but our findings suggest that the role of these issues in the HRMpractices–performance linkage represents a fruitful area for further research. Studieswhich can examine these links in more detail would be useful.

Recent years have seen a decline in the amount of research on work design. Accordingto Humphrey et al. (2007, p. 1332) this reflects a ‘case closed’ attitude amongst research-ers, in that the motivational approach is so widely accepted that there seems to be littleneed for more research in this area. Wood and Wall (2007) have also emphasized thatdespite the prominence given to work design in seminal accounts of HRM (e.g. Walton,1985), work design items are not common in studies of HPWS. Our findings point to theimportance of work design, represented by the degree of perceived job influence anddiscretion, in transmitting the effects of HRM practices to individual employee behav-iour and performance. There is a view that jobs in the new knowledge economies havebecome less uni-dimensional, less tightly defined, and less routinized (e.g. Cascio, 1998),with a greater need for employees to exert influence and use their discretion. Given suchdevelopments, along with our findings, we suggest that it would be premature to neglectthe role of work design.

Our findings suggest that high performance work practices provide workers with theautonomy and discretion needed to meet to the demands of the modern workplace. Jobinfluence and discretion may remove the need for workers to constantly check withmanagers for permission to act, something that is likely to be important in more complexorganizational contexts. High performance work practices may have the potential toreduce the ‘under-utilization’ of employees in high-discretion work environments bytapping employees’ citizenship behaviours (Huselid, 1995, p. 637). Jobs that are struc-tured so that employee discretion and influence is limited run the risk of squeezing out



employees’ capacity to use their skills and abilities to the full in engaging in behavioursthat help both the organization and their colleagues to find better ways of working.

Multi-level designs have the potential to bridge the gap between the hitherto largelyseparate research traditions of strategic human resource management (SHRM), with itsemphasis on organizational level analysis of HRM system and performance outcomes,and micro-level organizational behaviour, which focuses on individuals’ attitudinal andbehavioural responses. Reviews of the SHRM literature have recently called for moremulti-level studies (Paauwe, 2009, p. 133), and HRM researchers are now beginning torespond (Takeuchi et al., 2009; Wu and Chaturvedi, 2009). Multi-level research designshave the potential to open up the ‘black-box’ of the HRM performance linkage, sinceHRM is essentially a unit-level management intervention that must surely transmit toorganizational-level outcomes via some kind of effect on employees’ attitudes and behav-iours. In this paper, we have demonstrated that company-level HRM may have an effectthrough an association with individual employee behaviour, and that perceived jobinfluence is an intervening variable in this process. Multi-level studies that examine otherpotential mediators of the HRM–outcomes linkage would also be valuable. For example,it would be useful to consider other job characteristics as potential mediators, includingfeedback from the job and task identity. In addition, there are other potential alternativesto social exchange, aside from job characteristics, including the possibility that HRM hasits effects through work intensification (Ramsay et al., 2000), and organizational trustand identification (Restubog et al., 2008). The former promises a stronger link with theindustrial relations research tradition, stepping away from the unitarist assumptions ofmuch of the HRM research and emphasizing the implications for employee wellbeing,whilst the latter introduces social identity perspectives as an alternative to exchange-based explanations of HRM.

Studies examining potential moderators of the relationships between HRM, jobcharacteristics, and outcomes would also be of interest, and again such studies arelikely to need to examine cross-level effects. Aside from early work on HR ‘fit’ withbusiness strategy, research on contextual moderators is in the relatively early stages,although with some encouraging results to date (e.g. Datta et al., 2005; Sun et al.,2007). We need to learn more about the potential boundary conditions of HRMeffects, and organizational or environmental moderators such as environmental uncer-tainty or change turbulence (Herold et al., 2007; Waldman et al., 2001), would beworthy of investigation by HRM researchers. There would also be merit in investi-gating potential individual-level moderators of HRM effects, including variables suchgrowth needs strength, for example.

Our post hoc analysis of the dimensions of HRM suggested that the developmentand internal labour market dimensions were positively associated with perceived jobinfluence, whilst the rewards and internal labour market dimensions were positivelyassociated with perceived organizational support. These findings suggest that the jobcharacteristics effects of HRM are especially associated with an approach that empha-sizes internal careers and employee development, which may be seen as involving a‘make’ rather than ‘buy’ approach to staffing, whilst social exchange is associated withfinancial rewards and internal careers, which may be seen as employer inputs into asocial exchange process. This analysis was exploratory and post hoc rather than




theory-driven, but these findings suggest that future studies should pay more attentionto the potentially differential effects of specific HRM dimensions. We are not callingfor the ‘unbundling’ of HRM practices, but rather a recognition that HRM mayconsist of more than a unitary bundle, something which was recognized in Huselid’s(1995) pioneering study, but which has perhaps been neglected in some of the morerecent work on SHRM.

Our findings should be interpreted in light of the limitations of the study. First, thesample is based on one English region, which may limit the potential generalizability ofthe findings. North-East England was traditionally an area of heavy industry with highlevels of unionization and industrial militancy, and in recent years it has been charac-terized by structural change and a relatively high level of unemployment. Whethersimilar results, particularly on the non-significance of perceived organizational support,would be found in an area with a different industrial relations tradition is an interestingarea for further research.

Second, the use of HRM managers’ ratings of HRM practices rules out commonmethod bias in the prediction of self-reported employee attitudes and behaviour.However, our mediator variables (perceived organizational support and job influence)came from the same employee questionnaire as OCB and in-role behaviour, raising thepossibility of common method bias in the relationships between these variables.However, our measurement model (reported above) provided evidence for the discrimi-nant validity of the employee attitudes and behaviours, including perceived organiza-tional support and job influence, which suggests that common method bias didnot account entirely for the observed relationships amongst the employee-reportedconstructs.

Third, we have not measured social exchange perceptions directly and studies that doso may provide a fruitful line of further research in the SHRM field (e.g. Takeuchi et al.,2007). Fourth, given that our study was conducted at the establishment level andincluded a mixed sample of public and private organizations, as well as manufacturingand services based firms, it was not possible to gather common establishment-levelperformance data of an objective nature. Future studies could usefully attempt this,perhaps in less diverse samples. Finally, our study had a cross-sectional research design,which means that we cannot draw firm conclusions about causality. Future studies mightusefully adopt a longitudinal element, but given the problems of research access formulti-level studies, we must recognize that this will be very demanding.

The question of how HRM practices impact on employee attitudes and behaviour isimportant for management. Our conclusion, that such effects are transmitted throughperceived job influence, suggests that issues of job influence and discretion are key todesigning effective HRM strategy. Managers need to think beyond providing HRMpractices aimed at providing benefits and support, and should consider the effect of suchpractices on the degree of influence employees may exert in their daily work. This willrequire HRM practices that build employees’ skills and knowledge via training anddevelopment, provide promotion opportunities to higher level jobs, and give employeesdeeper and more frequent opportunities to exercise discretion in their work throughemployee involvement practices such as problem solving and quality improvementgroups and through the design of the work itself.



APPENDIX: HRM PRACTICES ITEMS AND EXPLORATORY FACTORANALYSIS RESULTS

What percentage of jobs/employees. . . ? 1 2 3 4

Involve off-the job training, arranged and financed by the organization 0.76Are covered by a regular (e.g. annual or 6-monthly) formal performance

appraisal0.72

Are involved in regular quality circles or similar problem solving groupsdiscussing quality and/or workflow issues

0.66

Are asked to complete an employee attitude survey on a regular basis (e.g.annually)

0.57

Have a formal induction programme for new recruits 0.57 0.31Are covered by an information sharing programme (e.g. employee

newsletter or briefings)0.74 0.32

Involve a sequence of two or more interviews before recruitment 0.63Involve a formal psychological selection test before recruitment 0.34 0.59 -0.43Are covered by a bonus scheme based on the performance of the work

group, department, or team0.76

Are covered by a bonus scheme based on the performance of theestablishment or organization as a whole

0.76

Involve on-the-job training 0.79Are normally (in more than half the cases) filled by internal promotion

from within the organization rather than by recruiting from outside0.38 0.58

Note: The extraction method was principal components analysis. Varimax rotation with Kaiser normalization.

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