Research Project

THE RELATIONSHIP BETWEEN

LINE MANAGER BEHAVIOR,

PERCEIVED HRM PRACTICES, AND

INDIVIDUAL PERFORMANCE:

EXAMINING THE MEDIATING

ROLE OF ENGAGEMENT

K E R S T I N A L F E S , C AT H E R I N E T R U S S , E M M A C . S O A N E , C H R I S R E E S , A N D M A R K G AT E N B Y

This article examines the role played by line managers in the link between

HRM practices and individual performance outcomes. Drawing on social ex-

change theory, the authors test a mediated model linking perceived line man-

ager behavior and perceived human resource management practices with

employee engagement and individual performance. The study focuses on

two self-report measures of individual performance; task performance and

innovative work behavior. Two studies with a total of 1,796 participants were

conducted in service-sector organizations in the United Kingdom and ana-

lyzed using structural equation modeling. The data reveal that perceived line

manager behavior and perceived HRM practices are linked with employee

engagement. In turn, employee engagement is strongly linked to individual

performance and fully mediates the link between both perceived HRM prac-

tices and perceived line manager behavior and self-report task performance

(study 1), as well as self-report innovative work behavior (study 2). The fi nd-

ings show the signifi cance of the line manager in the HRM-performance

link, and the mediating role played by employee engagement. © 2013 Wiley

Periodicals, Inc.

Keywords: perceived HRM practices, perceived line manager behavior, employee engagement, self-report task performance, self-report innova- tive work behavior

Correspondence to: Kerstin Alfes, Department of Human Resource Studies, Tilburg University, Warandelaan 2,

5037 AB Tilburg, The Netherlands, Phone: + 31 13 466 2499, E-mail: [email protected].

Human Resource Management, November–December 2013, Vol. 52, No. 6. Pp. 839–859

© 2013 Wiley Periodicals, Inc.

Published online in Wiley Online Library (wileyonlinelibrary.com).

DOI:10.1002/hrm.21512

840 HUMAN RESOURCE MANAGEMENT, NOVEMBER–DECEMBER 2013

Human Resource Management DOI: 10.1002/hrm

There is a case to be

made for focusing

on attitudinal or

behavioral outcomes

at the individual

level, where the

link between

experiences of HRM

practices and a

range of outcomes

is more proximal,

and which may be

considered to be

an intermediary

outcome and core

driver of overall

organizational

performance.

Introduction

A growing body of research has per- suasively argued that there is now evidence of a causal link between certain HRM practices and firm- level outcomes, such as financial

performance and organizational effectiveness (Batt, 2002; Datta, Guthrie, & Wright, 2005; Sun, Aryee, & Law, 2007; Wright, Gardner, Moynihan, & Allen, 2005). Efforts to unlock the “black box” between HRM interventions and performance outcomes have led to a number of studies that explore the mediating role played by either employee attitudes such as job satisfaction and commitment, behav-

iors such as task performance and organizational citizenship behav- ior (OCB), or experienced organi- zational practices such as perceived organizational support, organiza- tional justice, or job design (Kuvaas, 2008; Snape & Redman, 2010; Sun et al., 2007). Most re- cent studies situate their analyses within the framework of social exchange theory, arguing that or- ganizational HRM practices send overt and implicit signals to em- ployees about the extent to which they are valued and trusted, giving rise to feelings of obligation on the part of employees, who then recip- rocate through high levels of per- formance (Allen, Shore, & Griffeth, 2003; Gould-Williams, 2007; Purcell & Hutchinson, 2007).

Although substantial progress has been made, there are several areas where research evidence remains limited. First, although it has been argued that the role of line managers as agents in imple- menting HRM practices is fun- damental to understanding how employees interpret and respond to their employer’s HRM system (Holt Larsen & Brewster, 2003), studies that examine the line manager role alongside HRM pol- icy and practice remain rare (Den

Hartog, Boselie, & Paauwe, 2004; Tekleab & Taylor, 2003).

Second, few studies have used mea- sures of perceived HRM practices from the employee perspective, yet it has been shown that intended, implemented, and perceived HRM practices differ substantially (Conway & Monks, 2008; Gratton & Truss, 2003; Snape & Redman, 2010).

Third, most studies have focused on a relatively restricted range of potential media- tors, such as affective commitment or OCB (Allen et al., 2003; Snape & Redman, 2010). The HRM-performance literature has there- fore overlooked developments in other, related areas and specifically evidence link- ing levels of employee engagement with individual performance (Christian, Garza, & Slaughter, 2011; Kahn, 1990; Rich, LePine, & Crawford, 2010; Saks, 2006; Truss et al., 2006). The multi-factorial psychological construct of employee engagement, originally defined by Kahn (1990) as the harnessing of individuals’ selves to their role performance on physical, cognitive, and emotional levels, represents an alternative and conceptually promising factor that is increasingly used as a mediator linking a range of workplace phenomena as demon- strated in a recent meta-analysis by Christian et al. (2011).

Fourth, it has been argued that aggregate outcome variables used in the extant litera- ture, such as firm financial performance and organizational effectiveness, are too distal from the micro-level of HRM interventions, and that more proximal outcome indicators at the individual level would provide a bet- ter and more reliable measure (Paauwe, 2004; Purcell & Kinnie, 2007; Wright & Haggerty, 2005). A further consideration is that a focus on purely short-term financial gains may be at the expense of potentially desirable longer-term outcomes, such as sustainabil- ity and resilience at the organizational level, and well-being at the individual level (e.g., Boxall & Purcell, 2008; Guest, 2002; Ramsay, Scholarios, & Harley, 2000). There is a case to be made for focusing on attitudinal or behavioral outcomes at the individual level, where the link between experiences of HRM practices and a range of outcomes is more

LINE MANAGERS, HRM PRACTICES, AND THEIR RELATIONSHIP WITH ENGAGEMENT AND INDIVIDUAL PERFORMANCE 841

Human Resource Management DOI: 10.1002/hrm

proximal, and which may be considered to be an intermediary outcome and core driver of overall organizational performance (Wright & Haggerty, 2005). However, very few stud- ies have focused on behavioral outcomes at all (Ostroff & Bowen, 2000; Snape & Redman, 2010; Takeuchi, 2009), or examined the link between employee experiences of HRM and behavioral outcomes such as individual per- formance, aside from intent to quit (Allen, 2006; Conway & Monks, 2009).

To address these various limitations in the existing literature, we examine the rela- tionship between perceived line manager behavior, perceived HRM practices, and the individual-level outcomes of self-report task performance and self-report innovative work behavior, exploring the role of employee engagement as a mediating construct. Using a social exchange framework, we argue that employee experiences of HRM practices inter- act with perceived line manager behavior to impact on levels of employee engagement and individual performance (Figure 1). We test our model through structural equation modeling on questionnaire data obtained from two studies involving service-sector organizations in the United Kingdom.

Perceived HRM, Perceived Line Manager Behavior, and Employee Engagement Previous researchers have argued that com- plementary sets of HRM practices, rather than

individual HRM practices, can lead to higher levels of organizational performance (Combs, Yongmei, Hall, & Ketchen, 2006; Takeuchi, 2009). These bundles of HRM practices, com- monly referred to as high-performance HRM practices, are built on the notion that indi- vidual experiences of clusters of HRM prac- tices shape employees’ beliefs about the na- ture of the exchange relationship they enter into with their organization (Rousseau & Greller, 1994). Hence, in order to assess the impact of HRM, the entire system of HRM practices rather than individual practices should be taken into account (Wright & Boswell, 2002). A consensus is emerging that high-performance HRM practices are broadly focused around three areas (Conway, 2004; Wright & Boswell, 2002): (1) employee skills, including selective recruitment; (2) motiva- tion, including such practices as performance- based rewards; and (3) empowerment, includ- ing participation mechanisms (Snape & Redman, 2010). Most commentators argue that these act synergistically. Snape and Redman (2010, p. 4) define such an HRM sys- tem as consisting of “interconnected HR ac- tivities, designed to ensure that employees have a broad range of superior skills and abili- ties, which are utilized to achieve the organi- zation’s goals.” In the present study, we there- fore aim to assess how employees’ overall positive perceptions of high-performance HRM practices will be related to their behav- ior such as task performance and innovative work behavior.

FIGURE 1. Model Linking Perceived Line Manager Behavior and

Perceived HRM Practices to Individual Performance

Perceived

HRM

Practices

Employee

Engagement

• Self-report Task

Performance

• Self-report

Innovative Work

Behavior

Perceived

Line Manager

Behavior

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Although most researchers have argued that certain HRM approaches can drive up organizational performance (Batt, 2002; Datta et al., 2005; Huselid, 1995; Som, 2008), oth- ers have been more circumspect (Den Hartog et al., 2004; Gooderham, Parry, & Ringdal, 2008; Guest, Michie, Conway, & Sheehan, 2003; Truss, 2001). While large-scale surveys of senior HRM practitioners have helped to develop a broad understanding of relevant HRM factors, a focus on HRM as intended by the employer may not capture employees’ lived experiences of HRM, which arguably are more relevant in the HRM-performance chain (Wright & Boswell, 2002; Wright & Haggerty, 2005). Studies have in fact found that the links between intended, imple- mented, and perceived HRM strategies are poor, due to variability in implementation and diverse individual-level cognitive sche- mas (Edgar & Geare, 2005; Khilji & Wang, 2006; Kuvaas, 2008; Wright & Haggerty, 2005). However, research that focuses on the perceived HRM-performance linkage is rare. As Nishii, Lepak, and Schneider (2008, p. 504) argue: “[E]mpirical research that begins to explore the role of employees’ perceptions of HRM practices in the causal chain is sorely needed.” We respond to this call by focusing our attention on employee experiences of HRM practices, rather than simply intended HRM strategies. In doing so, we build upon two earlier studies. First, in an investigation involving 215 salespeople in a department store and 197 insurance agents, Allen et al. (2003) showed that perceptions of support- ive HRM practices—such as participation, reward fairness, and growth opportunities— contributed to the development of perceived organizational support, which mediated their relationship with job satisfaction and organizational commitment and showed a negative relationship with turnover. Second, Conway and Monks (2009) studied 288 employees in three Irish financial services firms and found that attitudes toward HRM practices had a greater impact on affective than on other forms of commitment, regard- less of context, and also established links between perceived HRM practices, intent to quit, and job satisfaction.

While early studies tended to propose a direct link between HRM and organizational performance, recent evidence suggests that the relationship is most likely mediated by a range of attitudinal and behavioral vari- ables at the individual level, particularly job satisfaction, affective and continuance com- mitment, task performance, and OCB (Den Hartog et al., 2004; Guest, Conway, & Dewe, 2004; Kinnie, Hutchinson, Purcell, Rayton, & Swart, 2005; Kuvaas, 2008; Snape & Redman, 2010; Takeuchi, 2009).

Studies of mediation often draw on social exchange theory to provide an explanatory framework. Social exchange theory is based on norms of reciprocity within social relationships (Blau, 1964; Emerson, 1976). It is argued that employees are motivated within the employ- ment relationship to demonstrate positive attitudes and behaviors when they perceive that their employer values them and their contribution (Cropanzano, Rupp, & Byrne, 2003; Kuvaas & Dysvik, 2010; Wayne, Shore, & Liden, 1997). Certain HRM practices may be viewed as signaling an intent for long-term investment in employees that obliges them to reciprocate with discretionary role behavior and contributions (Gong, Chang, & Cheung, 2010; Shaw, Dineen, Fang, & Vellella, 2009; Sun et al., 2007). As Hannah and Iverson (2002, p. 339) note: “HRM practices are viewed by employees as a ‘personalized’ commitment to them by the organization which is then recip- rocated back to the organization by employees through positive attitudes and behavior.”

Although social exchange theory has proven a useful lens through which to view the relationship between HRM practices and organizational performance, evidence con- cerning the mediating effects of the proposed range of attitudes and behaviors has so far proved contradictory. For example, while Sun et al. (2007) showed that OCB partially mediates the relationship between high-per- formance HRM practices and organizational performance, Kuvaas (2008) found no evi- dence of the mediating effects of affective commitment in the link between develop- mental HRM practices and individual per- formance, and Snape and Redman’s (2010) findings on mediation were inconclusive.

LINE MANAGERS, HRM PRACTICES, AND THEIR RELATIONSHIP WITH ENGAGEMENT AND INDIVIDUAL PERFORMANCE 843

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There is therefore no consistent evidence as to which mediators are most relevant, nor how they operate within mediated models. For example, it could be argued that the pro- posed attitudinal mediators of job satisfac- tion and commitment have no immediate relevance to individual performance (Judge, Bono, Thoresen, & Patton, 2001), as borne out by Conway and Monks’s (2009) study. OCB clearly is relevant for individual performance, but the focus is on extra-role rather than within-role performance, and a case could be made that employees’ task performance is equally important. There would therefore appear to be scope to search for an alterna- tive, and possibly more relevant, mediator. In order to address this point, we introduce the concept of employee engagement as a poten- tially significant mediating variable.

The construct of employee engagement was first proposed by Kahn (1990) to signify the expression of self in-role, involving physi- cal, cognitive, and emotional dimensions, and has since been the focus of extensive the- oretical and empirical research (Alfes, Truss, Soane, Rees, & Gatenby, 2010; Christian et al., 2011; Macey & Schneider, 2008; May, Gilson, & Harter, 2004; Rich et al., 2010; Rothbard, 2001; Truss et al., 2006). Engagement is con- ceived as a multi-factorial behavioral, atti- tudinal, and affective individual differences variable (Macey & Schneider, 2008; May et al., 2004; Rich et al., 2010). Researchers have argued that engagement differs from other attitudinal and behavioral constructs, includ- ing those most commonly used as mediators in many HRM practice studies: commitment, job satisfaction, and OCB. Engagement is seen as more than job satisfaction, since it implies activation and not merely satiation (Macey & Schneider, 2008). Equally, it differs from commitment, which is merely attitudi- nal, in that engagement additionally implies attentiveness to work and absorption in its performance (Saks, 2006). Engagement has some associations with discretionary effort and OCB (Campbell & Pritchard, 1976), but additionally refers purely to someone’s state of mind in, and behavior in relation to, the performance of their formal work role, while OCB is concerned with extra-role activities

(Bateman & Organ, 1983; Griffin, Parker, & Neal, 2008; Macey & Schneider, 2008).

There have been no prior studies examin- ing whether there is a link between HRM, or perceived HRM, and engagement. However, it would be reasonable to extrapolate, from the studies referred to earlier that have established a link between perceived HRM practices and a variety of other attitudinal or behavioral con- structs, that perceived HRM practices may be linked with employee engagement. This gives rise to our first hypothesis:

Hypothesis 1: Perceived HRM practices are posi- tively related to employee engagement.

Prior research has also acknowledged that line managers have a significant role to play in the HRM-performance chain (Bredin & Söderlund, 2007; Den Hartog et al., 2004; Kuvaas & Dysvik, 2010; Purcell & Hutchinson, 2007). They signal to employees the value placed upon them by the employer, both in terms of the way they implement HRM practices and through their leadership style (Den Hartog et al., 2004; McGovern, Gratton, Hope Hailey, Stiles, & Truss, 1997; Snape & Redman, 2010). As Purcell and Hutchinson (2007, p. 6) note, line manager behavior “has to be included in any causal chain seeking to explain and measure the relationship between HRM and organizational performance.”

In a multinational study, Holt Larsen and Brewster (2003) showed that line man- agers are taking on increasing responsibil- ity for HRM implementation. There have been a small number of previous studies on the role of line managers in implementing HRM. For example, in an exploratory study involving structured interviews in 12 orga- nizations, Purcell and Hutchinson (2007) found a symbiotic relationship for employees between HRM and front-line manager behav- ior. Kuvaas and Dysvik (2010), in a study of 331 employees in a Norwegian telecoms com- pany, similarly found that perceived invest- ment in employee development only led to increased work effort, work quality, and OCB when associated with high levels of perceived supervisor support. Equally, Kuvaas (2008) showed that employees can only respond

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positively to developmental HRM initia- tives when there is a high-quality employee- organization relationship in place.

While some prior studies have therefore suggested that perceived line manager behav- ior interacts with HRM practices in their impact on individual-level outcomes, a separate body of research has similarly shown that perceived line manager behavior can act as an anteced- ent to engagement (Bates, 2004; De Mello e Souza Wildermuth & Pauken, 2008; Frank, Finnegan, & Taylor, 2004). Line managers can foster trust relationships between them- selves and their direct reports, for example, through encouraging open communication, sharing critical information, and providing support (Settoon, Bennett, & Liden, 1996). This, in turn, will lead to positive emotional states and higher levels of employee engage- ment (Avolio, Gardner, Walumbwa, Luthans, & May, 2004). For instance, Robinson, Perryman, and Hayday (2004) showed how increased opportunities for upward feed- back led to higher levels of engagement, and Blizzard (2003) demonstrated that effective interpersonal relationships between employ- ees and managers raised engagement levels. This gives rise to our second hypothesis:

Hypothesis 2: Perceived line manager behavior is positively related to employee engagement.

Studies of engagement, like those of high- performance HRM practices, draw on social exchange theory to suggest that employees will become engaged with their work when antecedents are in place that signal to them that they are valued and trusted (Rich et al., 2010; Saks, 2006). Although no research has examined the link between HRM practices and engagement, empirical studies have demonstrated a link between high levels of engagement and the same outcomes as the high-performance HRM practices literature. Engaged employees invest themselves fully in their roles (Rothbard, 2001), which may lead to the enactment of active in-role per- formances (Ho, Wong, & Lee, 2011; Macey & Schneider, 2008). Engaged employees may achieve higher performance because they focus their efforts on work-related goals, are

cognitively vigilant, and are emotionally and socially connected to their work (Kahn, 1990). Since engaged employees feel more spirited, they can accomplish their in-role tasks with less effort (Hockey, 2000), and additionally invest time and resources in seeking new ways of delivering their work or changing and improving their environment (Ramamoorthy, Flood, Slattery, & Sardessai, 2005).

These findings have been supported by further recent studies. In a study of 245 fire- fighters, Rich et al. (2010) found that engage- ment mediated the relationship between value congruence, perceived organizational support, core self-evaluations, task perfor- mance, and OCB, while Sonnentag (2003) demonstrated that engagement leads to pro- active behavior, initiative taking, and the pursuit of learning goals. These findings are consistent with Christian et al.’s (2011) meta- analysis, which found support for a mediat- ing effect of engagement on the relationship between job characteristics, leadership, per- sonal traits, task performance, and OCB. This leads to our final set of hypotheses:

Hypothesis 3a: Employee engagement is positively related to task performance and mediates the re- lationship between perceived HRM practices and task performance.

Hypothesis 3b: Employee engagement is positively related to innovative work behavior and mediates the relationship between perceived HRM practices and innovative work behavior.

Hypothesis 4a: Employee engagement is positively related to task performance and mediates the rela- tionship between perceived line manager behavior and task performance.

Hypothesis 4b: Employee engagement is positively related to innovative work behavior and mediates the relationship between perceived line manager behavior and innovative work behavior.

Methods

Overview of the Research Process

We employed a cross-sectional research design in two case study organizations operating in

LINE MANAGERS, HRM PRACTICES, AND THEIR RELATIONSHIP WITH ENGAGEMENT AND INDIVIDUAL PERFORMANCE 845

Human Resource Management DOI: 10.1002/hrm

We employed a

cross-sectional

research design

in two case study

organizations

operating in the

service sector in the

United Kingdom.

the service sector in the United Kingdom (Bryman & Bell, 2007). This methodology was chosen because we were interested in explor- ing the patterns of associations within organi- zational settings between perceived HRM practices and line manager behavior, and their relationship with engagement and self- report individual performance. We used a questionnaire survey of employees in both organizations, which enabled us to gather data on the constructs of interest from a vari- ety of employees in each organization. The cases were chosen as they were fairly similar with regard to the range of different staff em- ployed, their size, and the sector they were operating in. Both online and paper versions of the questionnaire were created and admin- istered by the authors, and sent to a selection of employees with and without Internet ac- cess. In both organizations employees were selected in collaboration with the HR man- ager to ensure that the sample was representa- tive of the whole workforce. Employees were informed about the purpose of the study and its confidentiality, and encouraged to partici- pate in the survey within two weeks. In both organizations, employees were given time to complete the questionnaire during work. While the online responses were stored on a secure server, the paper questionnaires were returned directly to the researchers to ensure confidentiality. For study 1, we analyzed the relationships between perceived line manager behavior, perceived HRM practices, employee engagement, and self-report task perfor- mance. For study 2, we examined those rela- tionships with self-report innovative work behavior as a dependent variable.

Samples

Organization A is a support services partner in the United Kingdom providing business solutions for clients across the local govern- ment, transport, education, and defense sec- tors. A total of 2,500 employees from differ- ent locations were asked to take part in the survey. From this sample, 1,157 question- naires were returned. Listwise deletion of missing data led to a usable sample of 924 respondents, a response rate of 37 percent.

The sample comprised 72.5 percent men; the average age was 40.79 years (SD = 12.15); and the average tenure was 4.04 years (SD = 4.11). Respondents were from different levels in their organization and represented a range of occupational backgrounds, including profes- sionals (51.6 percent); administration (10.7 percent); managers or senior officials (14.9 percent); retail, customer, and personal ser- vices (2.3 percent); skilled trades (5.9 percent); machine operators (8.5 percent); and elemen- tary occupations (6.1 percent).

Organization B is a recycling and waste management company. The sample com- prised 2,217 employees, ensuring an accu- rate representation of workforce population. A total of 1,153 questionnaires were completed. Listwise dele- tion of missing data led to a usable sample of 872 respondents, which resulted in a slightly higher response rate of 39 percent. There were 25.9 percent female respon- dents within this sample. The average age was 41.42 years (SD = 11.56), and the average tenure was 5.92 years (SD = 5.72). Again, the respondents represented dif- ferent levels in the organization and diverse occupational backgrounds including professionals (12.3 per- cent); administration (21.4 percent); managers or senior officials (19.0 percent); retail, customer, and personal ser- vices (5.0 percent); skilled trades (4.3 per- cent); machine operators (33.0 percent); and elementary occupations (5.0 percent).

Measures

Perceived HRM Practices

Perceived HRM practices were measured based upon Gould-Williams and Davies’s (2005) HRM practices scale. This was chosen as it has been found to demonstrate high reli- ability and validity in previous studies of high-performance HRM systems (Gould- Williams, 2003; Gould-Williams & Davies, 2005), but at the same time is of a reasonable length to be included in an employee survey

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including different occupational groups. Specifically, we asked employees to assess six HRM practices identified by the high-perfor- mance HRM practices literature—namely, the selection process, training opportunities, re- wards systems, career management, develop- ment opportunities, and feedback mecha- nisms. A sample item was “I am provided with sufficient opportunities for training and development.” The response scale ranged from 1 (“strongly disagree”) to 5 (“strongly agree”). The alphas were 0.83 for Organization A and 0.85 for Organization B.

Perceived Line Manager Behavior

Perceived line manager behavior was measured using four items derived from Cook and Wall (1980) and Unden (1996). The items asked for employee perceptions of the effectiveness, eq- uity, and integrity of their line manager. A sam- ple item was “I think my line manager is fair in his/her treatment of me.” The response scale ranged from 1 (“strongly disagree”) to 5 (“strongly agree”). The alphas were 0.93 for Organization A and 0.94 for Organization B.

Employee Engagement

We measured engagement using a scale devel- oped by Soane et al. (2012). The scale was chosen because it operationalizes Kahn’s (1990) original conceptualization of engage- ment as the extent to which employees invest themselves fully in their role by establishing meaningful connections to others, and expe- riencing positive cognitive and emotional re- actions to the task. In line with the multidi- mensional nature of engagement, the scale encompasses three subscales of engagement. Intellectual engagement focuses on the extent to which employees are cognitively involved in their work. There were three items (e.g., “I get completely absorbed in my work”). Affective engagement measures the extent to which employees are emotionally involved with, and attached to, their work. There were three items, including “I am happy when I do a good job.” Social engagement was assessed with three items and measures the extent to which employees talk to their colleagues

about how to improve their work. Items in- cluded “I talk to people at work about how to improve the way I do my job.” Response op- tions ranged from 1 (“strongly disagree”) to 5 (“strongly agree”) for all subscales. Because we were interested in an overall measure of en- gagement, the three subscales were aggregated to form an overall measure of engagement, resulting in alpha values of 0.81 for Organization A and 0.86 for Organization B.

Individual Task Performance

A five-item scale from Janssen and Van Yperen (2004) was used to assess individual task per- formance. We slightly altered the wording of the original scale to reflect the fact that em- ployees were asked to self-rate their perfor- mance. A sample item was “I always complete the duties specified in my job description.” The response scale ranged from 1 (“strongly disagree”) to 5 (“strongly agree”). The alpha was 0.81 for Organization A.

Innovative Work Behavior

We measured innovative work behavior with a five-item scale based on Janssen and Van Yperen (2004). Similarly to task performance, we changed the wording of the original items to enable employees to self-rate their innova- tive work behavior. A sample item was “Transforming innovative ideas into useful applications.” The response scale ranged from 1 (“never”) to 5 (“daily”). The alpha was 0.96 for Organization B.

The difficulties in gaining individual- level performance data have been thoroughly discussed in previous literature (Huselid & Day, 1991; Mannheim, Baruch, & Tal, 1997). We took additional steps to limit problems associated with common method variance as described next.

Data Analysis

Because all our variables were collected from a single source only, we had to deal with two concerns prior to proceeding to hypothesis testing: common method variance and dis- criminant validity.

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To examine and control for the influ- ence of common method bias in our study, we performed a series of confirmatory factor analyses (CFA) on both datasets. Following established recommendations (Hair, Black, Babin, Anderson, & Tatham, 2005) we cal- culated five fit indices to determine how the model fitted our data: χ2, goodness of fit index (GFI), comparative fit index (CFI), root mean square error of approximation (RMSEA), and standardized root mean square residual (SRMR). For GFI and CFI, values greater than .9 represent a good model fit, and for SRMR and RMSEA, values less than .07 indicate a good model fit (Hu & Bentler, 1998; Kline, 2005).

We initially performed a CFA on the full measurement model (Anderson & Gerbing, 1988) including all latent variables. Overall, the measurement models exhibited good psy- chometric properties (Organization A: χ2 = 407, df = 129, GFI = .95, SRMR = .04, RMSEA = .05, CFI = .96; Organization B: χ2 = 379, df = 129, GFI = .95, SRMR = .04, RMSEA = .05, CFI = .98) and all standardized regres- sions coefficients in the measurement mod- els were significant at the 0.001 level. To test for common method variance, we then con- ducted Harman’s single-factor test (Podsakoff, MacKenzie, Jeong-Yeon, & Podsakoff, 2003), which involves a CFA where all variables are allowed to load onto one general factor. The model exhibited very poor fit for both organi- zations (Organization A: χ2 = 3,595, df = 135, GFI = .56, SRMR = .15, RMSEA = .17, CFI = .44; Organization B: χ2 = 6,973, df = 135, GFI = .44, SRMR = .21, RMSEA = .24, CFI = .41), which provided a good indication that a sin- gle factor did not account for the majority of variance in our data.

Additionally, we conducted a second test as recommended by Podsakoff et al. (2003), introducing an unmeasured latent methods factor to our original measurement model allowing all items to load on their theoretical constructs, as well as on the latent methods factor. A comparison of both models revealed that including the method factor in the model significantly improved the overall fit of the model (Organization A: Δχ2(df) = 80(12); Organization B: Δχ2 (df)= 40(12)). However,

the χ2 difference test is distributed χ2, and researchers argue that χ2 values are very sen- sitive to large sample sizes and a high num- ber of observed variables, leading to biased results (Bentler, 1990; Bentler & Bonett, 1980; Bollen, 1989; Hair et al., 2005; Hu & Bentler, 1995; Kline, 2005). We therefore assessed the change of CFI values for both models as an indicator of significance as recommended by Byrne (2001). The change of CFI between both models was 0.02 for Organization A and 0.03 for Organization B, which is below the suggested rule of thumb of 0.05 (Bagozzi & Yi, 1990).

To determine whether the constructs in our model were distinct from each other, we performed a test of the scales’ discriminant validity following Fornell and Larcker (1981). We first calculated the average variance extracted for each scale variable. According to Fornell and Larcker (1981), scale variables are sufficiently different from one another if a scale’s average variance extracted is greater than its shared variance with any other scale variable in the model. This condition was met in both datasets, and we concluded that all scales were distinct from one another. The values are portrayed along the diagonals of Tables I and III, together with interscale cor- relations and descriptive statistics for all scale variables in both organizations.

Results—Study 1

Descriptive Statistics

Table I presents the means and standard de- viations for each scale, and interscale correla- tions, for all study variables for Organization A. The interscale correlations show the ex- pected direction of association and are all sig- nificant at the p < .01 level. Specifically, per- ceived HRM practices are positively related to perceived line manager behavior (r = .52). Moreover, employee engagement is positively associated with perceived HRM practices (r = .35), perceived line manager behavior (r = .34), and self-report task performance (r = .32). The relationships between perceived HRM practices (r = .11) and perceived line manager behavior (r = .18) and self-report

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performance are positive and significant, but weaker compared to the relationship between engagement and self-report performance. Gender is positively, but weakly, associated with self-report task performance (r = .11), while age is negatively associated with per- ceived line manager behavior (r = −.09), and management responsibilities is positively as- sociated with engagement (r = .21).

Tests of Hypotheses

We employed latent variable structural equa- tion modeling (Jöreskog & Sörbom, 1993) using maximum likelihood estimation in AMOS 18.0 (Arbuckle, 2006) to evaluate our model. Structural equation modeling simul- taneously estimates the structure within a se- ries of dependent relationships between la- tent variables with multiple indicators, while correcting for measurement errors (Bollen & Long, 1993; Hair et al., 2005). This approach seemed the most appropriate for testing our empirical model. Given that perceptions of HRM practices and line manager behavior are likely to be positively associated, both con- structs were allowed to correlate in the struc- tural model. Overall, the model provided a good fit for our data (χ2 = 414, df = 131, GFI = .95, SRMR = .05, RMSEA = .05, CFI = .96).

As the sample in Organization A consists of a diverse range of employees, we carried out multigroup analyses to test for the reliability

of our proposed model across different gen- ders, age groups, and hierarchical levels. Our results1 showed that although there were dif- ferences with regard to the strength of the association between the groups, we did not find any significant differences with regard to the overall model proposed. We therefore con- cluded that the proposed model was a consis- tent reflection of the relationships between perceived HRM, perceived line manager behavior, employee engagement, and self- report performance within Organization A.

Our hypothesized model implied that engagement mediates the link between the antecedents of engagement and self-report task performance. To analyze whether media- tion according to Baron and Kenny (1986) could be found in our model, we examined whether an alternative model would lead to a significant improvement in the model fit compared to our hypothesized model by test- ing a series of nested models (Anderson & Gerbing, 1988; Mayer & Davis, 1999). Table II presents the fit statistics for three alterna- tive models compared to our hypothesized model. We used the same five fit indices as described earlier and carried out sequential χ2 difference tests to compare all models to our hypothesized model.

In model 2, we added a direct path from perceived HRM practices to self-report task performance to test whether there was a direct association between both variables,

T A B L E I Means, Standard Deviations, and Correlations for Scale Variables—Organization Aa

Mean SD 1 2 3 4 5 6 7

1. Gender .27 .45 n/a

2. Age 40.79 12.15 −.16** n/a

3. Management

Responsibilities .50 .50 −.21** .15** n/a

4. Perceived HRM

Practices 3.05 .69 .04 −.05 .02 .67

5. Perceived Line

Manager Behavior 3.67 .87 .06 −.09** .03 .52** .87

6. Engagement 3.75 .47 .00 0.00 .21** .35** .34** .67

7. Self-Report Task

Performance 4.09 .51 .11** −0.04 .02 .11** .18** .32** .69

an = 924. The values reported on the main diagonal in italics are square roots of the average variance explained. According to Fornell

and Larcker’s (1981) discriminant validity test, this value must be larger than a focal variable’s zero-order correlations in the same row

and column.

**p < .01.

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as suggested in early strategic HRM research (Arthur, 1994; Huselid, 1995; Koch & McGrath, 1996; MacDuffie, 1995). As Table II shows, the model fit was lower; hence, we found no support for this model. For alternative model 3, we added a direct path from perceived line manager behavior to self- report task performance to examine whether perceived line manager behavior had a direct impact upon individual performance, as research indicates that managerial behavior may have a direct influence on performance (De Jong & Den Hartog, 2007). However, the fit statistics in Table II reveal that this additional path did not improve the overall model fit. For model 4 we combined both modifications and added direct paths from perceived HRM practices and perceived line manager behavior to self-report task perfor- mance, respectively. Again results in Table II show that we did not find an improvement in model fit. Hence, data from our nested model comparison suggested that the hypothesized

model fitted the data best and engagement mediated the link between perceived HRM practices, perceived line manager behavior, and self-report task performance. The stan- dardized path coefficients for this model are shown in Figure 2.

Results—Study 2

Descriptive Statistics

Table III shows the descriptive statistics for, and interscale correlations among, all study variables for Organization B. All correlations show the expected direction of association and are significant at the p < .01 level. Perceived HRM practices are positively corre- lated with perceived line manager behavior (r = .53). Furthermore, engagement is positively associated with perceived HRM practices (r = .37) and perceived line manager behavior (r = .36), and all three variables are positively correlated with self-report innovative work

T A B L E I I Structural Equation Model Comparisons—Organization Aa

Models χ2 (df) GFI SRMR RMSEA CFI Comparisons

Hypothesized: Model 1 414 (131)** .951 .045 .048 .964

Alternative Model 2b 411 (130) .952 .045 .048 .964 Model 2 compared to Model 1

Alternative Model 3c 414 (130) .951 .045 .049 .964 Model 3 compared to Model 1

Alternative Model 4d 407 (129) .952 .044 .048 .964 Model 4 compared to Model 1

an = 924. bDirect path from perceived HRM practices to self-report task performance. cDirect path from perceived line manager behavior to self-report task performance. dDirect paths from perceived HRM practices and perceived line manager behavior to self-report task performance.

**p < .01.

FIGURE 2. Standardized Path Estimates: Final Model Organization A

Perceived HRM

Practices

Employee Engagement

.37***

.31***

.25***

.57*** Self-report Task

Performance

Perceived Line Manager

Behavior

***p < 0.001.

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behavior (r between .21 and .39). The data also show a positive association between management responsibilities and our study variables (r between .09 and .26), and between being female and perceived line manager be- havior (r = .13) and engagement (r = .18), while the relationship between being female and self-report innovative work behavior is weak and negative (r = −.11).

Tests of Hypotheses

As for Organization A, we tested our hypoth- eses with structural equation modeling (Jöreskog & Sörbom, 1993) in Amos 18.0 (Arbuckle, 2006). Again we allowed perceived HRM practices and line manager behavior to correlate. The model revealed a very good overall fit (χ2= 385, df = 131, GFI = .95, SRMR = .05, RMSEA = .05, CFI = .98) for our hypothesized model. As for Organization A, we carried out multigroup analyses to test our proposed model across different genders, age groups, and hierarchical levels. As we did not find any significant differences with regard to the model proposed, we concluded that the model was overall an accurate reflection of the relationships between perceived HRM, perceived line manager behavior, employee engagement, and self-report innovative work behavior within Organization B.

Again, we aimed to determine whether an alternative model would better represent our data. We therefore tested and compared the same series of nested structural models as for Organization A using sequential χ2 difference tests. Five fit statistics and the model compar- isons are depicted in Table IV.

For the nested model comparisons we found substantively similar results for Organization B. As Table IV demonstrates, model 2, where we added a direct path from HRM practices to self-report innovative work behavior, fitted the data equally well as our hypothesized model ( Δχ2 (1) = 6.3, p < 0.025). This indicates that HRM practices might have a direct influence on innovative work behav- ior (Collins & Smith, 2006). However, the first model was superior to model 2, as it was more parsimonious. Table IV also demonstrates that the other two alternative models fitted our data less well than the hypothesized model. The stan- dardized path coefficients for the best-fitting model for Organization B are shown in Figure 3.

Discussion

Key Findings and Theoretical Implications

The purpose of this research was to develop and test a more complete model of how

T A B L E I I I Means, Standard Deviations, and Correlations for Scale Variables—Organization Ba

Mean SD 1 2 3 4 5 6 7

1. Gender .26 .44 n/a

2. Age 41.42 11.56 −.24** n/a

3. Management

Responsibilities .38 .49 −.14** .14** n/a

4. Perceived HRM

Practices 2.99 .76 .04 −.03 .11** .70

5. Perceived Line

Manager Behavior 3.53 .96 .13** −.08 .09** .53** .89

6. Engagement 3.63 .59 .18** −.03 .18** .37** .36** .72

7. Self-Report Innova-

tive Work Behavior 2.11 1.10 −.11** −.09 .26** .26** .21** .39** .91

an = 872. The values reported on the main diagonal in italics are square roots of the average variance explained. According to Fornell

and Larcker’s (1981) discriminant validity test, this value must be larger than a focal variable’s zero-order correlations in the same row

and column.

**p < .01.

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perceived line manager behavior, together with employees’ experiences of HRM prac- tices, affect levels of employee engagement and, further, how the relationship between HRM practices, perceived line manager behavior, and individual performance is me- diated through engagement. We thereby re- sponded to calls for studies analyzing the role of line managers in the HRM-performance chain (Guest, 2011; Purcell & Hutchinson, 2007). Data from 1,796 employees in two or- ganizations largely supported our theoretical framework. In both organizations, perceived HRM practices were positively associated with employee engagement (β = .31), lending sup- port to Hypothesis 1. Furthermore, perceived line manager behavior was positively associ- ated with engagement in both organizations (β = .25 and .26), supporting Hypothesis 2. Moreover, perceptions of HRM practices and

line manager behavior were positively corre- lated, supporting the notion of a joint effect on individual levels of engagement (r = .57 and .54). Engagement, in turn, led to higher levels of task performance (β = .37) and in- novative work behavior (β = .45), as measured by self-report questionnaires, and mediated the link between line manager behavior, HRM practices, and individual performance. Hence, Hypotheses 3 and 4 were fully supported. These results have several theoretical implica- tions, which we consider in turn.

First, we show that employees’ experi- ences of perceived line manager behavior are an essential element in the HRM-performance linkage. Viewed through the lens of social exchange theory, our data suggest that line managers have an important role to play, not just in the way they implement and enact HRM policy (Bowen & Ostroff, 2004), but also

T A B L E I V Structural Equation Model Comparisons—Organization Ba

Models χ2 (df) GFI SRMR RMSEA CFI Comparisons

Hypothesized: Model 1 385 (131)** .953 .046 .047 .978

Alternative Model 2b 378 (130) .953 .040 .047 .978 Model 2 compared to Model 1

Alternative Model 3c 384 (130) .953 .044 .047 .978 Model 3 compared to Model 1

Alternative Model 4d 379 (129) .953 .040 .047 .978 Model 4 compared to Model 1

an = 872. bDirect path from perceived HRM practices to self-report innovative work behavior. cDirect path from perceived line manager behavior to self-report innovative work behavior. dDirect paths from perceived HRM practices and perceived line manager behavior to self-report innovative work behavior.

**p < .01.

FIGURE 3. Standardized Path Estimates: Final Model Organization B

Perceived

HRM

Practices

Employee

Engagement

.45***

.31***

.26***

.54*** Self-report

Innovative Work

Behavior

Perceived Line Manager

Behavior

***p < 0.001.

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through their daily behavior toward their staff, which sends signals about the extent of the value placed upon them. Hence, employ- ees’ experiences of HRM occur along at least two dimensions, first their experiences of HRM policies and practices, and second the way they are treated by their line manager. Positive experiences of HRM practices alone appear insufficient to generate high lev- els of engagement and performance; rather, our data suggest that it is the combination of positive perceived line manager behavior and positive experiences of HRM practices together that is associated with an engaged and high-performing workforce. These find- ings support the argument that a systemic approach is needed when examining the HRM-performance linkage, one that focuses on the general working climate experienced by employees, which will inevitably include their perceptions of their line manager as well as HRM policy implementation (Purcell & Hutchinson, 2007).

Our findings also lend support to the small number of other studies that have dem- onstrated a link between positive experiences of HRM practices and individual-level perfor- mance outcomes. Data from our study show that where employees’ experiences of HRM practices are positive, self-report individual performance in terms of task performance and innovative work behavior is enhanced. This can be understood through the lens of social exchange theory, which suggests that where employees feel that their organiza- tion is investing in them through the posi- tive experiences they have of HRM policy and line manager behavior, they are more willing to reciprocate through high levels of engage- ment and performance. A focus on intended HRM strategy alone will not capture the lived experiences of employees and will omit critical dimensions of the exchange relationship. This reflects the findings of other studies that have suggested that it is not the HRM strategies intended by the organization that are most significant in the HRM-performance chain, but rather how employees experience those HRM practices (Gratton & Truss, 2003; Kinnie et al., 2005; Nishii et al., 2008). Consequently, this lends further weight to the argument that

studies of the HRM-performance linkage need to seek the views not just of HRM managers, but also of individual employees (Den Hartog et al., 2004).

Finally, we bring together two hitherto disparate bodies of literature by demon- strating that employee engagement acts as a mediator linking perceived HRM practices and perceived line manager behavior to self- report individual performance. No prior stud- ies have examined the link between HRM, employee engagement, and individual per- formance. Some earlier research has shown that attitudes are an important element in the HRM-performance chain, focusing on other attitudinal constructs such as commit- ment, job satisfaction, and OCB (Allen et al., 2003; Batt, 2002; Sun et al., 2007). Equally, several prior studies have argued that there is a link between perceived line manager behav- ior and engagement (May et al., 2004), and between engagement and individual perfor- mance (Rich et al., 2010). By bringing these lines of argument together, consistent with our predictions, our data suggest that engage- ment acts as an important mediator between HRM and individual performance. Although this is a new finding, it is in line with our predictions based on the engagement litera- ture (Christian et al., 2011; Halbesleben & Wheeler, 2008; Rich et al., 2010), and on the literature linking perceived HRM with attitudinal and behavioral outcomes (Allen et al., 2003; Snape & Redman, 2010). Within a social exchange relationship, employees’ positive perceptions of organizational invest- ments in them, communicated through line manager behavior and perceived HRM prac- tices, give rise to a willingness to engage cog- nitively, affectively, and behaviorally, and to consequent high levels of task performance and innovative work behavior.

Implications for Practitioners

Our data provide further support to the grow- ing interest in the changing relationship be- tween line managers and HRM professionals in the management of employees. The current study shows that line managers play an impor- tant role in creating and maintaining a positive

LINE MANAGERS, HRM PRACTICES, AND THEIR RELATIONSHIP WITH ENGAGEMENT AND INDIVIDUAL PERFORMANCE 853

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Our study

demonstrates that it

is through effective

partnership that

HRM practitioners

and line managers

are able to elicit

positive responses

from their workforce.

environment in which employees are willing to engage and perform. This emphasizes the importance of a symbiotic relationship be- tween HRM professionals and line managers (Purcell & Hutchinson, 2007). Collaboration between both parties will enable the effective implementation of HRM practices, which are positively perceived by employees and encour- age them to reciprocate by enacting desired be- haviors. Our study demonstrates that it is through effective partnership that HRM practi- tioners and line managers are able to elicit posi- tive responses from their workforce.

Our findings have specific implications for HRM professionals. Arguably, the goal of strategic HRM is to evoke positive employee attitudes and improve performance. The cru- cial question for HRM practitioners is how to achieve these objectives. A key challenge is to ensure that HRM policies and practices are enacted in a consistent way by different line managers across the organization. One focus for HRM professionals should be the align- ment of line managers’ performance goals and objectives with desired strategic HRM outcomes, and the assessment of line manag- ers’ performance based on their approach to managing people.

Moreover, our data show that employee perceptions of HRM practices play an impor- tant role in determining individual perfor- mance and, in conjunction with perceived line manager behavior, are associated with higher levels of employee engagement. Creating a highly engaged workforce has become a significant focus for many organi- zations recently (MacLeod & Clarke, 2009; Truss, Soane, Alfes, Rees, & Gatenby, 2010), and our study indicates to HRM profession- als that line managers have to be integrated in any strategies designed to maintain or increase engagement levels.

Limitations

Although our research provides interesting insights into the causal chain linking line manager behavior, HRM practices, employee engagement, and individual performance, the findings should be assessed against the background of the limitations inherent in our

study. First, we collected data in each organi- zation at one point in time, which limits the conclusions that can be made regarding the causal order of our relationships. It might, for example, be possible that employee en- gagement leads to positive perceptions of HRM practices. Second, we relied on individu- als’ self-reports on all variables of our model, which raises concerns about possible com- mon method bias. However, our analysis indi- cated that common method bias was not an issue in either organization and the results ob- tained were stable in two different organiza- tions and generalizable across a number of demographic criteria. Moreover, in terms of the current study, our focus was on employee perceptions of HRM as the first link between HRM practices and outcomes (Wright & Boswell, 2002), and so we would argue that self-report measures might actually be the most valid measurement method for most of our constructs, as individuals are best placed to re- port their own levels of engage- ment, their perceptions of HRM practices, and line manager behav- ior. Hence, the only constructs that could have been measured by multiple data sources are self- report performance and innova- tive work behavior. Although at least two data sources are required to help rule out the validity threats of self-report and single-method bias (Donaldson & Grant-Vallone, 2002), a recent review of performance appraisal research sug- gests that performance ratings by line manag- ers might be equally biased as self-rated performance (Levy & Williams, 2004). Moreover, authors have recently questioned the assumption that common-method variance causes serious problems in organizational re- search (Spector, 2006). Nevertheless, we encour- age future researchers to collect data from mul- tiple sources to investigate our findings further.

Implications for Research

In our study we shed light on the roles line managers and HRM professionals play in

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shaping employees’ attitudes and behaviors at work. We have demonstrated that it is impor- tant to consider how line managers affect em- ployees’ perceptions of HRM practices and poli- cies, which supports the notion of a symbiotic relationship between both parties for the effec- tive management of people. We encourage fu- ture research to further explore the dynamics between HRM professionals and line managers in the enactment of HRM practices and their effect on employee attitudes and behaviors.

An interesting question arising out of our research is whether different occupational groups within one organization share the same perceptions of line management behavior, HRM practices, engagement, and individual performance. Although we found some vari- ability in path coefficients between individuals with and without management responsibili- ties, we did not find a significant difference with regard to the overall model. We encour- age future research to assess whether there are differences in individuals’ perceptions based on their occupational background. Indeed, Kinnie et al. (2005) suggest that the relation- ships depicted in our model may well vary between different groups of employees.

Future research might also analyze whether different leadership styles have a differential impact on employees’ percep- tion of, and attributions to, HRM systems. For example, would an engaging leader- ship style (Chartered Institute of Personnel and Development [CIPD], 2008) lead to a more positive evaluation of the HRM system compared to traditional transactional and transformational leadership styles? We also encourage consideration of how employ- ees’ perceptions of the wider organizational climate, such as perceived organizational support and organizational trust, might be related to perceived HRM practices and line management behavior.

Our study has demonstrated that it is important to consider employee perceptions when evaluating the impact of HRM practices. Future research could assess to what extent line managers’ perceptions of HRM practices influ- ence their employees’ perceptions of HRM practices, using multilevel data from different data sources in the organization. It might be

that line managers who have positive experi- ences of HRM themselves shape their subordi- nates’ perceptions and attitudes toward HRM.

Finally, we encourage researchers to evaluate changes in the effect of line man- ager behavior and HRM practices over time. By adopting longitudinal research designs, researchers will be able to demonstrate causal effects in the HRM-performance chain and assess the impact of any intervention designed to enhance employee attitudes and performance.

Conclusion

Our study has contributed to debates around the HRM-individual performance link through the development and testing of a mediated model incorporating employee en- gagement as the key attitudinal variable, and analyzing the role of line managers in this causal chain. Through structural equation modeling on a sample of 1,796 respondents from two organizations, we tested a number of hypotheses to determine how these factors are interrelated. We found that employees’ perceptions of line manager behavior and HRM practices are positively related to levels of employee engagement, and that engage- ment, in turn, mediated the link with self- report individual performance. These find- ings are consistent with social exchange the- ory, which suggests that organizations able to cultivate a climate of reciprocity will elicit positive attitudinal and behavioral outcomes from employees. We argue that HRM’s impact on performance outcomes is therefore indi- rect rather than direct, and that the focus of HRM efforts should be first on the effective selection, deployment, and performance management of line managers, second on supporting line managers to ensure the fair and consistent enactment of intended HRM practices, and third on developing and imple- menting employee engagement strategies. These factors together will create a virtuous cycle fostering high levels of performance.

Note

1. The full results are available from the fi rst author

upon request.

LINE MANAGERS, HRM PRACTICES, AND THEIR RELATIONSHIP WITH ENGAGEMENT AND INDIVIDUAL PERFORMANCE 855

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KERSTIN ALFES is an assistant professor in the Department of Human Resource Studies

at Tilburg University. Her research interests include employee engagement, strategic hu-

man resource management, overqualifi cation, and the management of change. She has

written on these topics in journals such as Human Resource Management Journal; the

International Journal of Human Resource Management; Gender, Work & Organization;

and International Public Management Journal.

CATHERINE TRUSS is head of Group, People, Management and Organisation at Kent

Business School, University of Kent, UK. She has held research grants valued at over

£900,000 from the Economic and Social Research Council, the Chartered Institute of

Personnel and Development, the National Institute for Health Research, and Industry,

and has written or coauthored over 180 articles, papers, books, and reports. Her research

interests include strategic HRM, employee engagement, and meaningful work. She is

co-editor of Employee Engagement in Theory and Practice, published by Routledge in 2013.

EMMA C. SOANE is a lecturer in the Department of Management at the London School

of Economics. She is the academic director, CEMS MSc International Management; a

chartered occupational psychologist; and a chartered scientist. Her research interests

are centered on individual differences in leadership, personality, decision making, risk,

and engagement with work. She has written a number of journal articles, book chap-

ters, and practitioner articles. She coauthored the book Traders: Risks, Decisions, and

Management in Financial Markets published by Oxford University Press in 2006.

CHRIS REES is a senior lecturer in employment relations in the School of Management

at Royal Holloway, University of London. His current research centers on comparative

corporate governance and trade union responses to corporate social responsibility;

the cross-border transfer of employment practices in multinational corporations; and

European information and consultation regulations. His work has been published in jour-

nals such as Organization Studies, Work Employment and Society, the European Journal

of Industrial Relations, and Human Resource Management Journal.

MARK GATENBY is a lecturer in organizational behavior in the School of Management at

the University of Southampton. His research interests include public service reform, the

role of managers, and critical realism.

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