Contemporary Management: Issues and Challenges

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PERSPECTIVE published: 30 November 2018

doi: 10.3389/fpsyg.2018.02414

Edited by: Montgomery Anthony,

University of Macedonia, Greece

Reviewed by: Sebastian Molinillo,

Universidad de Málaga, Spain Marinella Coco,

Università degli Studi di Catania, Italy

*Correspondence: Justin Craig Field

[email protected]

Specialty section: This article was submitted to

Organizational Psychology, a section of the journal Frontiers in Psychology

Received: 27 July 2018 Accepted: 16 November 2018 Published: 30 November 2018

Citation: Field JC and Chan XW (2018)

Contemporary Knowledge Workers and the Boundaryless Work–Life

Interface: Implications for the Human Resource Management of the

Knowledge Workforce. Front. Psychol. 9:2414.

doi: 10.3389/fpsyg.2018.02414

Contemporary Knowledge Workers and the Boundaryless Work–Life Interface: Implications for the Human Resource Management of the Knowledge Workforce Justin Craig Field1* and Xi Wen Chan2

1 UNE Business School, University of New England, Armidale, NSW, Australia, 2 School of Management, College of Business, RMIT University, Melbourne, VIC, Australia

In the last decade, knowledge workers have seen tremendous change in ways of working and living, driven by proliferating mobile communication technologies, the rise of dual-income couples, shifting expectations of ideal motherhood and involved fatherhood, and the rise of flexible working arrangements. Drawing on 54 interviews with Australian knowledge workers in the information technology sector, we argue that the interface between work and life is now blurred and boundaryless for knowledge workers. By this, we mean that knowledge workers are empowered and enslaved by mobile devices that bring work into the home, and family into the workplace. Knowledge workers take advantage of flexible working to craft unique, personal arrangements to suit their work, family, personal and community pursuits. They choose where and when to work, often interweaving the work domain and the home–family domain multiple times per day. Teleworkers, for example, attain rapid boundary transitions rending the work–home boundary, thus making their experience of the work–life interface boundaryless.

Keywords: work–life theories, boundaryless work–life interface, knowledge workers, human resource management, organizational psychology

INTRODUCTION

Ways of working and living have changed dramatically in post-industrial economies in the last decade. First, proliferating information and communication technologies (ICT), often mobile, are connecting people, but also intensifying work beyond traditional offices and working hours (Ciolfi and Lockley, 2018). Second, more women are working. Dual-income couples are now the norm (Abele and Volmer, 2011). Third, expectations of parenthood are changing. Mothers are working more, while balancing parenting with working. Fathers are increasingly more involved in parenting, shifting from exclusively being breadwinners (McGill, 2014). Finally, companies are offering flexible working arrangements (FWAs), so that employees can vary the time, schedule and location of work, to suit their needs.

Knowledge work is dominating in post-industrial economies. Knowledge work involves manipulating and transmitting ideas, rather than goods. In particular, knowledge workers use

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ICT to exchange meaning. Knowledge processes are unconstrained, occurring in any location and at any time (Nelson et al., 2017), but they are subject to the influence of organizational culture, technological support, and supervisory arrangements, as well as the agency of knowledge workers to subvert or comply with organizational norms.

Considering rapid technological change, demographic change, societal change and the rise of knowledge work, we propose a new appreciation of the boundaryless work–life interface for flexible knowledge workers. Despite intense work and non- work activities, we contend flexible knowledge workers do not emphasize the distinction between work and non-work. Rather, they work at any place and time, but also manage to achieve harmonious balance in their lives. Existing work–life theories do not present the work–life experiences of flexible knowledge workers accurately. Hence, we describe a richer conceptualisation of the work–life interface for this group and discuss implications for human resources (HR) policies and management methods in the digital economy.

EXISTING THEORIES ON THE WORK–LIFE INTERFACE

Work–life theories can be classified into three streams: (1) negative side of the work–life interface, stemming from role strain theory, (2) positive side of work–life interface, stemming from role accumulation theory, and (3) blurred boundaries between work and non-work, stemming from boundary and border theory.

Negative Side of the Work–Life Interface Role strain theory, which originated from Goode’s (1960) scarcity perspective, contends that multiple roles lead to role strain and subsequently interrole conflict (work–family conflict) as it becomes difficult to perform each role due to conflicting demands on time, energy and attention among the roles (Greenhaus and Beutell, 1985). Defined as “an individual’s experience that work and family roles are incompatible in some respect, as a result of which participation in one role is made more difficult by virtue of participation in the other role” (Greenhaus and Beutell, 1985, p. 77), work–family conflict had dominated work– life research owing to the rise of dual-income households with children. However, Marks (1977) argued that role strain was not a result of incompatible role demands, but by role imbalance, as there is a difference in the importance of roles assumed. Marks (1977) added that no role strain would occur if all commitments were equally positive or negative. Barnett and Hyde (2001) also reasoned that having several roles was not the issue, it was the quality and combination of roles that contributed to role strain.

Positive Side of the Work–Life Interface As research on work–family conflict matured, Greenhaus and Powell (2006) responded to calls to examine the positive side of the work–life interface. Drawing on role accumulation theory, Greenhaus and Powell (2006, p. 73) proposed the concept of work–family enrichment, defined as “the extent to which

an individual’s experiences in one role improve his or her quality of life in other roles.” Role accumulation theory was jointly developed by Sieber (1974) and Marks (1977), both of whom argued that having multiple roles is more rewarding than stressful, and that the more roles individuals took on, the more resources they possessed, and the more opportunities they were exposed to. Research on work–family enrichment increased drastically in the past decade in large part due to the positive psychology movement and demographic trends which have given rise to workplace policies that seek to enhance employees’ work and life (Brough and O’Driscoll, 2015). The strongest criticism on work–family enrichment is it does not acknowledge the negative side of the work–life interface, which many researchers argue cannot be dismissed since people tend to struggle with managing their work and non-work responsibilities.

Blurring of Boundaries Between Work and Life In this research, we use “work–life” as opposed to “work– family” or “work–home” to acknowledge non-work roles (e.g., community, social and personal pursuits) (Moen, 2011). Alongside work–family enrichment and conflict are several theories on work–life balance, including Ashforth et al.’s (2000) boundary theory and Clark’s (2000) border theory. However, research on work–life balance has not advanced theoretically because of inconsistent definitions of work–life balance (Kalliath and Brough, 2008). Border theory and boundary theory contribute to the study of work–life linkages by describing how varying levels of work–life integration affect well-being, and addressing how people construct and cross boundaries between work and life.

Boundary Theory Boundary theory focuses on the meanings people assign to work and life (Nippert-Eng, 1996) and the ease and frequency of transitioning between roles (Ashforth et al., 2000). Boundaries are clearer when roles are separated, while role transitions are easier when roles are integrated. Role blurring is the experience of confusion or difficulty in distinguishing work from non-work roles, especially when roles are highly integrated (Desrochers et al., 2005). Boundaries can be classified by their flexibility and permeability. Flexibility is the “extent to which the physical time and location markers, such as working hours and workplace, may be changed”; permeability is “the degree to which a person physically located in one domain may be psychologically concerned with the other” (Hall and Richter, 1988, p. 215). Roles can be arranged along a segmentation– integration continuum: when role boundaries are inflexible and impermeable, the roles are segmented; when boundaries are flexible and permeable, roles are integrated (Ashforth et al., 2000). Studies (e.g., Hyland and Prottas, 2017) using boundary theory have found that permeability is asymmetrical—work demands tend to spill over into non-work domains. Individuals with strong segmentation preferences face challenges crossing boundaries; while those with strong integration preferences face challenges in creating and maintaining boundaries. Drawing on Weiss and Cropanzano (1996) affective events theory, Hunter et al. (2017)

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extended boundary theory by incorporating goal obstruction as the explanatory mechanism linking work-to-family conflict and job satisfaction. Specifically, boundary violation events (e.g., taking a phone call from a family member at work) occurring at work were appraised as obstructing one’s work goals due to time and attention redirected from meeting work goals to meeting family needs.

Boundaryless work–life interface of knowledge workers Knowledge work tends to involve a high degree of both flexibility and permeability, facilitating role blurring or, increasingly, a state of “boundarylessness” (Albertsen et al., 2010). Unlike traditional “9-to-5” jobs, knowledge work is characterized by a less rule-based and more flexible regulation, especially in terms of time, space, and jobscope (Allvin, 2008). That is, knowledge workers typically have individualized schedules, temporal and geographical flexibility, and more job autonomy (Albertsen et al., 2010). “Boundarylessness” does not necessarily suggest the complete absence of boundaries between different life domains, but it illustrates weak to virtually absent domain boundaries (Ezzedeen and Zikic, 2017). Since the concept of “boundarylessness” is a new and novel phenomenon, we focus on understanding the boundaryless nature of knowledge workers’ work–life interface. Accordingly, the pursuit of empirical observations is important as it contributes to theory development and decision-making for employees, managers and organizations (Albertsen et al., 2010).

Border Theory Border theory is devoted only to work and family domains. Work–family balance is the outcome of interest, defined as “satisfaction and good functioning at work and at home, with a minimum of role conflict” (Clark, 2000, p. 751). It differs from boundary theory in that definition of borders includes psychological categories and also tangible boundaries that divide the time, place and people associated with work and life. Borders are characterized by their strength, from weak to strong. Weak borders are more likely to be permeable and flexible, facilitating blending between roles. Strong borders are more likely to be inflexible and impermeable, preventing role blending (Clark, 2000). Border-keepers are members of a domain who are influential in defining the border and the domain. Conflict may arise when border-keepers and border-crossers do not agree on the exact boundaries of a domain. They may also disagree about the flexibility and permeability of the boundary.

Research Question In this study, our goal is to illuminate the poorly understood boundaryless nature of knowledge workers’ work–life interface. Existing work–life theories do not adequately and accurately account for knowledge workers’ work and non-work experiences. Therefore, we seek a deeper understanding of how flexible knowledge workers perceive and navigate their life domains, and to discover various contextual and socio-cognitive factors that influence their perceptions and decisions. Therefore, a qualitative design is particularly apposite for our research. We interpretively explored three questions: (1) How do flexible

knowledge workers perceive, think about, and experience the interface between their work and non-work domains? (2) How do flexible knowledge workers perceive and manage role boundaries between their work and non-work domains? (3) What contextual and socio-cognitive factors account for flexible knowledge workers’ differing perceptions and decisions when managing their work–life interface? In sum, we qualitatively explored the perceptions and decisions of flexible knowledge workers with the understanding that these have implications for their individual, work and family functioning (Ashforth et al., 2000).

METHODS

To answer our research questions, we conducted an exploratory case study, using an embedded single-case design (Yin, 2009) to examine knowledge workers’ perceptions about balancing work and life. Each participant represented an embedded sub-case within the case study. We adopted an interpretive research approach, giving voice to participants’ interpretations and perceptions of the work–life interface. The participants’ point of view is the foundation of our analysis. This section provides a detailed description of our method, to support dependability and transferability (Lincoln and Guba, 1985).

Data Collection The research site was the Australian affiliate of a multi- national technology company (referred to as “Tech”). Tech had around 130,000 employees worldwide at the time of the study, with around 2,100 employees in Australia. Access to employees at the research site was negotiated with the HR director. Before we approached Tech, we sought ethics approval from the University of New England’s Human Research Ethics Committee. The HR director allowed us to gather data in two ways. First, semi-structured interviews were the principal source of information about participants’ thoughts, feelings and perceptions about work–life balance and how they arranged their working and personal lives. Confidentiality was protected by a written informed consent agreement with each participant. Second, we gathered policy documents, people directory entries and corporate broadcast emails from Tech’s intranet, and we downloaded Tech’s statutory reports to government agencies, as triangulation sources. In addition, the principal researcher wrote field notes after each interview to document researcher responses and states, using ongoing reflective commentary (Shenton, 2004) to capture assumptions, emotional states and possible bias.

Semi-Structured Interviews The lead researcher conducted all interviews to maintain a consistent data collection approach. He conducted pilot interviews with five participants drawn from Sales, Human Resources and Research & Development departments at Tech. Pilot participants used FWAs in different ways: three were teleworkers, one was part-time, and one was full-time, about to begin parental leave. The purpose of the pilot interviews was to test the interview template (see Appendix 1) against the research

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questions, across different jobs and different demographic attributes, and to enhance dependability by following a consistent procedure, per guidelines of Miles et al. (2014).

We developed the interview template for the pilot interviews from a study of the literature, focusing on satisfying the research questions. Prior to the pilot interviews, we reviewed the interview template with academic colleagues, to enhance objectivity and confirmability (Lincoln and Guba, 1985). Sample questions included: What triggered your request for flexible working? How do you balance work versus home and family? How do you define what is work time and what is non-work time?

Following the pilot interviews, the interview template was revised with supplementary questions. For teleworkers, we found it useful to ask: Do you ever work very early or very late? Is this your choice or has your manager directed you? How do you blend work tasks and home or childcare tasks, when working from home? For part-time participants, we asked: To what extent do you work on a non-working day? Is this your choice or has your manager directed you? We also found it useful to ask all participants about availability: When do you make yourself strictly unavailable? Do you ever disconnect? These questions explored richer detail about participants’ methods of forming and dismantling boundaries, and their perceptions of organizational norms and their personal responses to such expectations.

Document Gathering We gathered relevant documents from Tech’s intranet, including people directory entries for all participants, copies of published policies, and corporate broadcast emails from business leaders or Tech HR team. We also gathered Tech’s statutory reports to the Workplace Gender Equality Agency.

Sampling and Saturation To identify participants accessing FWAs, Tech’s HR team provided reports listing Tech employees with part-time hours, with flexible or remote working arrangements, and with completed leaves of absence (other than annual and sick leave). We used non-probability purposive and snowball sampling techniques (Bernard and Ryan, 2010). We used the reports to identify the population of all employees using FWAs, and we invited all employees in the population to participate in interviews. We also asked Tech HR managers and interviewees to recommend other employees who might have relevant experiences to share. This was productive because we discovered some employees using informal FWAs (e.g., working at home as a personal arrangement with the manager) did not appear on Tech’s official records.

Overall, we interviewed 54 participants at Tech (Field, 2017). Participants fell into three categories: part-time, teleworkers, and sabbaticals. Some participants had multiple experiences, so they fell into multiple categories. Participants represented 39% of all part-time employees at Tech Australia, and 40% of all teleworkers at Tech Australia, giving credibility and depth to the findings of this case study. Because sabbaticals were infrequent and episodic, it was not possible to calculate a participation rate.

Saturation for part-time participants was achieved after 12 of 24 interviews. After the twelfth interview, we heard repeated

themes of work expanding into non-work time and efforts to juggle work and family. Saturation for teleworker participants was achieved after 15 of 30 interviews. After the fifteenth interview, we heard repeated themes of blending work and home/family during the work day and being available outside of conventional working hours. Turning to sabbatical participants, it was not possible to establish whether saturation was reached. Only five interviews were conducted, because employees going on sabbaticals are rare at Tech.

Data Preparation All recorded interviews were transcribed into text files (one participant did not consent to audio recording). We provided the text files to participants for verification, if they had made this request before interview, to enhance credibility and authenticity of the study (Miles et al., 2014). During transcription, the lead researcher recorded transcription memos to capture generative insights, connections and themes (Sunstein and Chiseri-Strater, 2012). Each transcript was made anonymous by introducing pseudonyms and code numbers for each participant. We used MAXQDA for data coding and analysis, and uploaded interview transcripts, field memos, transcription memos, and gathered documents. The data corpus consisted of 53 interview transcripts and one interview summary (Field, 2017), plus 177 other documents including field notes, transcription memos, coding memos, company policies, company statutory reports, company emails and people directory entries. There was a total of 473,206 words in interview documents, and 106,466 words in the other documents.

Data Analysis We use the technique of thematic qualitative text analysis (Kuckartz, 2014) to examine common elements between participants and groups, differences between participants and

TABLE 1 | Deductive coding and analysis from literature review and theory.

Theoretical area Category Codes

Role strain theory Work–life conflict • Work conflict at home/family

• Home/family conflict at work

Role accumulation theory

Work–life enrichment

• Work enrichment at home/family

• Home/family enrichment at work

Boundary theory and Border theory

Boundaries and borders

• Defining work domain boundaries

• Defining home/family boundaries

• Crossing boundaries

• Perceptions of boundary keepers

• Perceptions of boundary crossers

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groups, and relationships within the data. The principal unit of analysis was each participant’s interview transcript. We read through each transcript closely multiple times, identifying segments addressing our research questions.

We began data analysis with a primarily deductive approach, in order to examine participant perceptions in light of role strain theory, role accumulation theory, boundary theory and border theory. We developed thematic categories (Kuckartz, 2014), displayed in Table 1, then coded all interviews using the broad thematic categories. We chose the unit of coding to be at the paragraph level, in interview transcripts. We also wrote individual case summaries.

In the second cycle of coding, we retrieved all segments within a category, then used an inductive method, in alignment with our research questions, to formulate sub-categories from the data. For example, when investigating ‘Crossing boundaries’ and ‘Work conflict at home/family’ for part-time participants, we coded for the health status of dependent children, the nature of the day (working or non-working), the clock time (within or beyond conventional working hours), and the organizational hierarchical status (e.g., vice president or individual contributor) of the co-workers making contact.

To enhance credibility, preliminary themes and findings were shared with academic colleagues and discussed at length, to challenge the analysis, using the peer debriefing method (Kuckartz, 2014). The purpose of this debate was so that findings would not rely on the interpretations of a single analyst alone, enhancing trustworthiness of the analysis (Miles et al., 2014). We also used negative and deviant case analysis (Richards and Hemphill, 2018), aiming to find exception cases in the data set, to bolster our understanding of participant perceptions of their work–life interface. We conducted extensive cross-case analysis, comparing cohorts (part-time, teleworkers, sabbaticals), gender, age groups, career level (individual contributors, front-line managers, middle managers), participant tenure with manager, and participant tenure with Tech.

Conducting Research as a Privileged Insider During data collection and analysis, the lead researcher was an employee of Tech. Insider status afforded privileged access to the research site and to gatekeepers within the organization. Insider status also provided an extensive network of acquaintances and co-workers as key participants of the case study. Furthermore, tacit and intrinsic knowledge of Tech’s organizational culture was useful to establish shared cultural membership with participants. Using this knowledge, the lead researcher established trust and rapport with participants, enhancing each participant’s sense of freedom to voice their stories. Conversely, the researcher’s insider status raised fears and risks for some participants. Specifically, some participants were concerned that their stories, employment history or family arrangements were unique, which allowed others to identify them. Some feared their reputation might be damaged or feared their private opinions about co-workers might damage relationships.

We addressed these fears by emphasizing arrangements for confidential treatment of interviews, anonymity and provision of pseudonyms.

FINDINGS

Sample Demographic Characteristics The sample consisted of 54 flexible knowledge workers. The sample was 62.96% female and 37.04% male. Mean age of participants was 43.24 years (SD = 7.49 years). Mean organizational tenure was 10.12 years (SD = 6.55 years). The number of individual contributors was 41; the number of front- line managers was seven and the number of middle managers was six. Five participants were single, six participants had a partner and no dependents, and 43 participants had a partner and dependent children. Dual-earner couples made up 75.93% of the sample.

The Case for the Boundaryless Work–Life Interface From our analysis, we argue that flexible knowledge workers perceive the work–life interface as fuzzy and boundaryless. Work–life balance is different for every person: subjective perceptions of demands originating from work, home–family and other life domains define how individuals measure the success of FWAs.

Despite intense work and non-work activities, we found that participants barely distinguished between work and non- work. Our finding is in line with the research findings of Hill et al. (2003) who found that virtual office workers tend to have difficulty knowing when they are at work and when they are home, due to the lack of externally imposed physical boundaries. Facilitated by ICT, our participants worked in many different locations at various times. They leveraged FWAs to take care of home–family concerns during office hours. Our participants also overwhelmingly favored an integration preference, with highly flexible and permeable boundaries. Ronald showed how he permitted family concerns to cross into the work domain, leveraging spatio-temporal flexibility.

Ronald: I’m present [for work] if I need to, if I get a phone call from school and my wife is at work, and one of the kids needs to be picked up because they’re not feeling well, it has allowed me that flexibility . . . for me to go and pick them up. (Individual contributor, full-time, age 35–39, teleworker some of the week).

Whereas segmentation was the norm decades ago (Nippert- Eng, 1996), now integration is the norm for flexible knowledge workers. Participant expectations about where and when to work are boundaryless—and the physical and technological barriers that surround these expectations have been abolished. Boundaries are so permeable they do not even matter, reinforcing fuzzy boundarylessness. With ICT in hand, knowledge workers move seamlessly from work demands to home demands and back again, not paying much attention to boundaries. Katrina focused on her children during part of the day. When she missed a work telephone call, she quickly returned it, demonstrating high permeability and high integration.

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Katrina: I’ll answer it, if I really can’t answer it I will let it go to voicemail and then I’ll call them back, 10 min later when, when I can. But generally speaking I will just, a child in one hand and I’m on the phone to them. (Individual contributor, part-time, age 25-29, office based).

When working at home, some or all of the week, or participating in global projects collaborating across time zones, participants found they needed to work earlier or later than core working hours. Yet, during the day, they used time for home– family tasks. By doing this, participants enacted home devotion and simultaneously work devotion (as defined by Blair-Loy, 2003). They were involved parents, yet also appearing as ideal workers to their managers and co-workers. They could also work the same or more number of hours each day, intersperse several hours of quality family time, without impacting their work–life balance (Hill et al., 2003). Anastasia illustrated how she interwove between work and family during core working hours, but then extended the working day into the evening.

Anastasia: Ok, well, the girls have got something on at assembly today. I’m just going to go. So I block out my diary and I go to the assembly and enjoy it and I am present for them and then I come home and log back on. Now I might have to work a few extra hours that night after they go to bed. You do it. You just juggle it. Some days I don’t even work my core hours. (Individual contributor, age 35–39, teleworker some of the week).

Likewise, Thomas took an active role as an involved father, in the late afternoon, but worked intensely during early mornings and late at night.

Thomas: One of the things that I’ve always been very careful about is to not let the work–life balance get out of kilter. Given that I’ve got two young kids, what works for me exceptionally well is the fact that because I’ve got a global job where I’m on the phone from, most days, from 06:00 till 08:00 or 09:00 in the morning, and then I’m on the phone again from 20:00 at night through till 22:00 or 23:00, means that I essentially don’t do any work in the early afternoons, which is 15:00 in the afternoon through until about 20:00 at night, so when the kids get home from school. (Individual contributor, full-time, age 45–49, teleworker all of the week).

We argue there is reduced work–life conflict in this state of boundarylessness. Thomas specifically mentioned leveraging FWAs to manage his work–life balance, to fit his expectations. Because flexible knowledge workers have more freedom to choose working arrangements to suit home–family arrangements, we argue they use the technique of crafting their work–life interface to suit their requirements. We found work–life conflict was present in a small way, but not regarded as excessive by participants. The autonomy afforded by FWAs gave participants control over work and home–family, thus they were able to meet demands from all domains under conditions of apparent work–life balance.

Participants did not take a pure work-oriented view of the world. They did not simply regard themselves as employees, above all else, as Anastasia and Thomas demonstrate. We contend that individuals make work–life balance decisions across their life-space, including all their roles (e.g., students, workers, spouses, homemakers, parents, and citizens). Their decisions vary

over the life course, as they move across generations and work and home demands shift in priority. Events such as marriage, divorce, childbirth, promotion or relocation shift perceptions about home–family demands and work demands. Choices about whether to use FWAs are not solely governed by perceptions at work, and penalties and benefits from flex-work, but are also governed by perceptions at home, and associated penalties and benefits.

Organizational expectations played a significant role in shaping participant perceptions about boundaries. We observed that managers hardly ever requested extended work hours from participants. Instead, individuals worked where and when they perceived it was necessary, either to complete their workload (especially so for managers), or, to collaborate with co-workers in distant time zones. Ethan explained how he perceived Tech’s organizational culture and the demands of his intense workload as a middle manager.

Ethan: And the company doesn’t set it as an expectation. They don’t expect me to sit, or the hundreds of other people that sit on their sofas at night, doing email for the day. It’s not expected, right. But it’s not discouraged. [. . .] It’s a self-driven, there’s no expectation, other than your personal drive to be on top of or in front of or caught up on, or, but it’s, you’re never in front of, right. You’re always [. . .] You’re never in front, yeah. So it’s just about keeping head above water in some respects, right.

Lauren explained her views about the mistaken freedom of working from home, and the requirement to be constantly available, enforced by her manager’s behavior. Organizational norms were powerful in shaping acceptable and unacceptable behaviors for participants.

Lauren: No, because if you do that, there will be him [Lauren’s manager] asking, where are you? You should always be available. So there was no hiding. There was absolutely no hiding. So even though that people say that you work from home and you’ve got all this freedom, it’s nothing like that. On the contrary, in fact. Because you felt like you had to be constantly by your computer so you can answer your chat right away, or your phone right away. Because if there was a delay there’s always that worry at the back of your head, oh, do they think I’m not working? (Individual contributor, full-time, age 40–44, teleworker some of the week).

So, fuzzy boundarylessness has a dark side. Participants framed use of ICT to craft reputations of high availability as a personal choice. Yet, participants were responding to strongly held behavioral norms in organizational culture. There was little resistance to working outside conventional hours—it seemed so ‘normal’. But, per Lauren’s remarks, participants were not truly free to decide working hours independently. Constant availability for work has become a proxy for organizational commitment. Virtual displays of employee engagement are now paramount. Individuals work within a matrix of co-worker relationships at work, and kin relationships at home. Each of these relationships constitutes border-keeper expectations, so knowledge workers must craft a careful path between competing expectations. Megan paid more attention to work than family. She worked while on vacation (an extreme example in our study), to avoid out-of-control work situations.

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Megan: No. I’ll even take meetings while I’m on leave too. And I’ve always told my team, you rather bug me while I’m on holiday and don’t let something escalate out of control, because even though I’m on holiday, I can still manage it. (Middle manager, full-time, age 40–44, teleworker all week).

DISCUSSION

Our article exposes the true nature of the work–life interface for flexible knowledge workers. In the two decades since boundary theory and border theory were first proposed, the rise of ICT has drastically altered the work–life interface. Work can now be completed at any time and in any location, meaning that domains are more likely to be blended and boundaries barely exist (as we have argued above). This implies boundary theory and border theory should now be reappraised in the context of knowledge work. Due to the difficulty in grasping the concept of boundarylessness, work–life researchers have tended to classify work and non-work domains into bounded categories (Allen et al., 2014). While firm boundaries may still apply for certain types of workers and industries, the flexible knowledge workers in our study have revealed that a new form of boundary theory must be formulated. By highlighting the work–life interface and boundary management strategies of knowledge workers, our research contributes to understanding of knowledge work, as well as the objective, subjective, and temporal experiences of knowledge workers who traverse multiple work–life boundaries in a day. Based on our findings, we also argue that the segmentation-integration continuum put forth by Ashforth et al. (2000) boundary theory may be more complicated for knowledge workers than how it is currently conceptualized. We thus call upon work–life researchers to adopt similar qualitative designs grounded in the work–life experiences of knowledge workers in future studies to advance knowledge and theory in this area.

Researchers also need to elaborate the concept of work– home conflict. Though role strain theory predicts conflict, in this study participants were less likely to regard their working lives and home lives as a source of conflict. The introduction of mobile communication technologies and the intersection with flexible working imply that conflict is differently comprehended by flexible knowledge workers. Work devotion may be more salient for individuals, but the level of work devotion does not necessarily imply greater control across the work–life interface. Individuals often prioritize work demands over home demands, suggesting that individuals have less control. This problem is exacerbated for teleworkers, where in theory it is possible for the individual to ignore work demands in favor of home demands. This does not happen: individuals make work a higher priority, most of the time, with limited exceptions for family time or personal time at specific moments of the working day.

Implications for Human Resource Management There are four important implications for HR, as flexible knowledge workers navigate the boundaryless work–life interface. First, HR must shape a positive organizational culture

that supports flexible work, advocating benefits of FWAs with leaders. HR should challenge organizational practices equating organizational commitment with face-time. Giving knowledge workers flexibility in terms of where and when to work has been shown to alleviate work–family conflict (Golden et al., 2006). Further, HR should instill new practices measuring output, mostly virtual in substance. Productivity must be measured by something different—for example, quality of presentations at virtual meetings.

Second, HR managers must provide meaningful, universal access to FWAs. HR should introduce these policies in organizations that have none, and, in organizations where FWAs are restricted, HR should rewrite policies to include all job families and management levels.

Third, HR must establish procedures making managers, not employees, accountable for tailoring suitable FWAs. Shifting focus to managerial accountability forces managers to be more engaged in making flexible working successful for both employee and supervisor. It would also ensure managers are committed to team success and flex-worker success, rather than leaving employees to muddle through and make it work individually.

Finally, HR must work with information technology (IT) leaders to ensure appropriate balance between technology provisioning, and work and home demands. ICTs are a double- edged sword: on the one hand, empowering employees and enabling work; on the other hand, forcing employees to be constantly connected and constantly available. HR and IT should define appropriate expectations about technology usage by employees. Managers should avoid unwittingly setting an expectation of 24/7 availability, by for example, answering emails late at night. HR should provide pragmatic guidelines: if employees have to collaborate across time zones, it is necessary to work early or late, but employees should feel they have time to disconnect and recover. The appropriate flexible work policy framework, situated in a flex-positive organizational culture, with leader, HR and IT role modeling and resourcing, sets the organization up for success.

Limitations and Directions for Future Research There are several limitations to this study. The cross-sectional research method did not allow investigation of the construction of the work–life interface over time. From a sampling perspective, the study did not deliberately include full-time co-workers. Given the nature of flexible work, full-time employees were the largest group within Tech, so their perceptions and behaviors influence organizational perceptions of those who work flexibly. The study did not account for the influence of cultural background such as national culture or ethnic background. Furthermore, the study did not account for generational influences on flexible working perceptions. It is reasonable to assume younger employees may have different expectations about work–life balance and how they might construct the work–life interface. Positive response bias is a particular concern when using semi-structured interviews. Though steps were taken to avoid this kind of bias, further triangulation of the findings could help to improve authenticity.

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There are interesting future directions for research involving flexible knowledge workers and their work–life interface. First, researchers should compare and contrast full-time workers with flexible workers who vary hours, schedule or location of work in future studies. Second, seeing that manager support was essential to positive flexible working perceptions, it would be worthwhile to investigate the specific role of managers and supervisors. Some sample questions include: How do effective managers support subordinates and what do less effective managers do or not do?

Another direction for future research is to look more closely at the host location of the supervisor compared to the subordinate. If supervisor and subordinate are in the same office location, then there is more opportunity for interaction, but it also carries an expectation that the employee will be present in the office, unless they have an agreement with the manager for remote or flexible working. If the supervisor is in a different office location, then face-to-face supervision is not possible and expectations might be different. Furthermore, the employee might be forced to work outside conventional hours in order to have discussions with the direct supervisor who may be on the other side of the world.

Conceptual definitions of flexible working are also problematic. The precise definition of flexibility, and the intensity and duration of flexible working are important factors in studying the work–life interface. Conceptual definitions are not consistent in the literature so future studies could work toward a consistent and widely accepted definition. Also, given that teleworking appears to have fewer negative consequences compared to working reduced (part-time) hours, future studies should look at the mechanisms that drive these varying outcomes across different cohorts and types of FWAs.

Finally, future research should investigate other industries and other countries, to expand research and scholarship about flexible working into new sectors. It is simple for an IT firm to offer flexible working to knowledge workers, because knowledge work is portable—other types of industries such as retail, manufacturing and healthcare would have to offer FWAs to selective occupational groups. Comparative research between industries presents novel opportunities for theory building and analysis.

CONCLUSION

In the last decade, work and life have been transformed by technology, fragmenting time. Now, knowledge workers can work anywhere, at any time. This brings unprecedented empowerment—yet, simultaneously, enslavement. Existing boundaries are no longer salient for flexible knowledge workers. They perceive their work–life interface as fuzzy and boundaryless. Knowledge workers use ICTs combined with FWAs to craft their ideal lives. In bringing attention to fuzzy boundarylessness, we hope to guide HR practitioners, and leaders, to develop new HR approaches for flexible knowledge workers. We encourage future studies to examine the fuzzy boundaryless nature of the work– life interface and explore the different ways flexible knowledge workers navigate work and home, family and life.

ETHICS STATEMENT

This study was carried out in accordance with the recommendations of the Human Research Ethics Committee of the University of New England, with written informed consent of all subjects.

AUTHOR CONTRIBUTIONS

JF conceptualized the boundaryless work–life interface and collected the qualitative data. XC analyzed the literature and came out with the overall structure. Both authors made a substantial, direct and intellectual contribution to the work.

ACKNOWLEDGMENTS

The authors would like to thank Dr. Theresa Smith-Ruig and Prof. Alison Sheridan for their feedback which enhanced the quality of this research article.

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Conflict of Interest Statement: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2018 Field and Chan. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

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APPENDIX 1: INTERVIEW TEMPLATE

Questions regarding absences, flexible working and ICT:

1. What type of absence did you take? (maternity, paternity, leave of absence, other types) 2. OR, What type of flexible working arrangement did you seek? (part-time in the office, work from home part-time or full-time) 3. What event or scenario triggered your request for absence or flexible working? 4. When and how did you involve your manager? What happened? 5. What information and communication technologies do you use? Why? Which ones do you avoid and why? 6. If demographic information indicates that the employee has caring responsibilities for family, ask: at home, what household or

caring responsibilities do you have? How do you balance work versus home and family? 7. When you were absent, did you feel you needed to try to keep in touch and how did you do this? What happened? 8. What happened when you returned to work after absence? What did your manager say and do? 9. If you’re working part-time and/or working at home all of the time or some of the time, how do you define what is work time and

what is non-work time? Have there been any times when you’ve felt under pressure from one side or the other? What happened? What does your manager say and do? What do your family and friends say and do?

For participants who indicated they were working from home:

1. Do you ever work very early in the morning or very late at night? Why? Is this your choice or has your manager directed you? 2. Where are you more productive, at home or in the office? 3. Where do you receive more interruptions? 4. Where do you feel more distracted? 5. What health concerns do you have about working from home? 6. To what extent do you feel lonely working from home? 7. To what extent do you feel isolated working from home? 8. To what extent do you feel you are missing out on office gossip, the grapevine or other informal communications? How important

is this to you? 9. How do you blend work tasks with housework and childcare duties, when working from home?

10. For participants with dependent children: who does pickup and drop-off? 11. What do your family and friends say when you mention you work from home? 12. When do you make yourself strictly unavailable? 13. Do you ever disconnect or turn off your laptop or mobile phone?

For participants who indicated they were working part-time:

1. What days of the week do you work and how did you choose those days? How has this arrangement changed over time? 2. To what extent do you have time to socialize on a working day? 3. To what extent do you feel you are missing out on office gossip, the grapevine or other informal communications? How important

is this to you? 4. To what extent do you work on a non-working day? Why? Is this your choice or has your manager directed you to work on a

non-working day? 5. What is the value, to you, of your non-working day? 6. What pressure have you had to change to full-time employment? 7. How many other part-time employees do you know? 8. For participants with dependent children: who does pickup and drop-off? 9. When do you make yourself strictly unavailable?

10. Do you ever disconnect or turn off your mobile phone?

For participants who mentioned an unpaid leave of absence, usually in the form of a sabbatical:

1. What was the response of co-workers when you announced the leave of absence? 2. What happened during the time away from work? 3. How important was it to keep in touch with work while you were away? What did you do to keep in touch? 4. What benefits did the leave of absence give you? 5. What negative consequences did the leave absence give you? 6. How did you arrange to come back to work? 7. What was the response of co-workers when you returned to work?

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The Indirect Effects of Ethical Leadership and High Performance Work System on Task Performance through Creativity

Author(s): Inju Yang, Jee Young Seong and Doo-Seung Hong

Source: Journal of Asian Sociology , September 2020, Vol. 49, No. 3 (September 2020), pp. 351-370

Published by: Institute for Social Development and Policy Research (ISDPR)

Stable URL: https://www.jstor.org/stable/10.2307/26940214

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The Indirect Effects of Ethical Leadership and High Performance Work System on Task Performance through Creativity: Exploring a Moderated Mediation Model*

inJu Yang | RmiT uniVeRSiTY Jee Young Seong | JeonBuK naTional uniVeRSiTY** Doo-Seung Hong | Seoul naTional uniVeRSiTY

The present study explores the interaction effects of ethical leadership (EL) and high performance work system (HPWS) on creativity and task performance in a Korean public sector firm. Data were collected in two stages, first from team members on the perceptions of EL and HPWS (Stage 1), followed by their leaders’ evaluations of team members’ creativity and performance (Stage 2). This study found the interaction effects of EL and HPWS, such that their effects are negative on creativity and positive on task performance. We argue that compensatory effects of HPWS and EL on creativity exist, such that HPWS is the most effective on task performance via creativity when EL is low. In the presence of a low EL level, creativity is significantly enhanced, mainly when HPWS is high, which leads to a high level of task performance. Implications and future research directions are discussed.

Keywords: Ethical leadership, high performance work system, creativity, task performance

Journal of asian sociology Volume 49 | number 3 | september 2020, 351-370 Doi 10.21588/dns.2020.49.3.004 Article

* This work was supported by the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea (NRF-2018S1A5A8029361).

** All correspondence regarding this paper should be addressed to Jee Young Seong.

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352 Journal of asian sociology, Vol. 49 no. 3, september 2020

Introduction

Over the years, ethical concerns in the work environment (Stouten, van Dijke, and De Cremer 2012) and the occasional exposure of corporate scandals have drawn attention to ethical leadership (EL). EL addresses how leaders use their social power by demonstrating personal morality and using communication and reward systems to guide ethical behavior (Brown and Treviño 2006; De Hoogh and Den Hartog 2008).

Alongside leadership, which is an essential organizational procedure, high performance work system (HPWS) has become widespread, especially in the interactions between supervisors and subordinates. HPWS has appeared to be the most widely accepted human resource management (HRM) policy worldwide, although it originated in the United States and Great Britain (Lawler, Chen, Wu, Bae, and Bai 2011).

Most studies on EL and HPWS independently have reported their positive effects on organizational processes and outcomes (e.g., Boxall and Macky 2009; Brown, Treviño, and Harrison 2005; Chughtai, Byrne, and Flood 2015; Piccolo, Greenbaum, Den Hartog, and Folger 2010; Harney and Trehy 2016; Walumbwa and Schaubroeck 2009). However, as it seems likely that the effects of explicit (e.g., HPWS) and implicit (e.g., EL) organizational processes co-occur, knowledge about how their effects interact to influence employees’ attitudes and behavior would be beneficial. Therefore, by integrating consideration of explicit (e.g., HRM) and implicit (e.g., leadership) organizational processes into a single analysis, this study provides insight into their interactive effects that may be detrimental to work-related attitudes and outcomes of employees. It challenges conventional wisdom that mainly highlights their individual (positive) effects.

This study contributes to HRM and leadership literature, both of which have emphasized contextual features of organizations. Although research shows that organizational processes affect employees most (Folger, Cropanzano, and Goldman 2005), studies that investigate HRM and leadership together have been somewhat limited, especially those concerning creativity and performance. The present study illustrates the importance of the context in which a negative interaction is likely to occur between EL and HPWS, despite the fact that they are perceived as positive organizational practices in general.

This study also complements the discussion on the substitute for leadership (Kerr and Jermier 1978) as our research shows that HPWS and EL

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353Ethical Leadership and High Performance Work System

did not replace each other per se. HPWS and EL ‘interact negatively’ and HPWS ‘compensates’ rather than replaces EL, particularly when it comes to their effects on creativity. Finally, while our study was conducted using data from a Korean public sector firm, this study joins in the call for more research using non-US contexts to examine practices and theories developed mostly in the contexts of private corporations and individualistic culture (Aycan, Kanungo, Mendonca, Yu, Deller, Stahl, and Kurshid 2000).

The purpose of this paper is threefold. First, we will examine the interaction effects of EL and HPWS on creativity and task performance in a Korean firm. Second, by adopting the job demands-resources (JD-R) model (Demerouti, Bakker, Nachreiner, and Schaufeli 2001) as an overarching framework for the moderated mediation effects between EL and HPWS on task performance via creativity, we discuss whether the interaction patterns compensate or complement each other in leading to creativity and task performance. Third, we explore the feasibility of theories and practices first developed in private firms and/or individualistic culture in other contexts such as public sector firms and/or collectivistic cultural environments.

Literature Review

The Importance of Interaction Effect between EL and HPWS

HRM and organizational culture/leadership are two leading practices influencing human factors, and it is suggested that HRM is, at least in part, determined by a leader’s values and behaviors (Blakeley and Higgs 2014). Over and above psychological attitudes (e.g., well-being), employees’ creativity, and task performance are discretionary behaviors that require skill, motivation, and effort. Therefore, by adapting the JD-R theory (Demerouti et al. 2001), which suggests that certain work contexts are associated with job stress demanding (personal) resources, we argue that the contrasting interacting effects of EL and HPWS could demand or protect employee’s resources. In the present study, we look at perceptions of HPWS, in line with the view that performance does not stem from HR practices per se but rather from how they are perceived by employees (Jiang, Takeuchi, and Lepak 2013).

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354 Journal of asian sociology, Vol. 49 no. 3, september 2020

Creativity and Task Performance in Public Sector Firms

Looking at the relationship with creativity and performance, research has shown that HPWS or EL has positive direct effects on them. Creativity refers to the generation of new and useful ideas by individual workers (Amabile 1983). Job p erformance describ es the individual’s activities in the organization over a defined period (Borman and Motowidlo 1993).

Creativity is said to be the source of innovation that facilitates competitiveness (Liu et al., 2017). In today’s world, organizations, including public firms, compete in a dynamic and uncertain environment where creativity is highly valuable (Zhou and Hoever 2014). Previous studies have suggested that leadership and HRM influence the creative behavior of employees (Zhang and Bartol 2010). Skills (e.g., actual competence and belief in one’s ability) and attitudes (e.g., motivation and psychology safety) were suggested to be crucial in the link between HRM and leadership to creativity and performance.

When it comes to skills and beliefs, for example, ethical leaders' altruistic behavior and credible feedback can facilitate growth and confidence in employees’ job-related skills (Brown et al. 2005; Walumbwa, Mayer, Wang, Wang, Workman, and Christensen 2011). Ethical leaders also influence followers’ behaviors through a role-modeling process (Brown et al. 2005) and create an environment where individuals can actively offer new ideas to improve performance (De Hoogh and Den Hartog 2008). Moreover, trust in a supervisor produced by EL (Chughtai et al. 2015) can reduce burnout and deviant behavior (Mo and Shi 2017), strengthen a sense of self-efficacy (Renzl 2008), and improve work engagement (Chughtai et al., 2015), all of which further influence task performance (Mo and Shi 2017). In a similar vein, HPWS, such as training, can develop broader competencies, including novel thinking, problem-solving ability, and divergent thinking skills in employees, which could further increase their self-efficacy to perform (Evans and Davis 2015).

Individuals' behavior within a public organization is critical and has a high magnitude of consequence, and public sectors are becoming more sensitive to ethical issues (Stouten et al., 2012; Zhang, Fletcher, Gino, and Bazerman 2015). Research has found more substantial effects of EL in public sector organizations than their private sector counterparts (Bedi, Alpaslan, and Green 2016). However, some argue that bureaucracies such as political control, red tape, and low levels of managerial autonomy (Boyne 2002) would make leadership (i.e., transformational leadership) less effective in public

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355Ethical Leadership and High Performance Work System

sector organizations than private sector organizations (Moynihan, Wright, and Pandey 2012). On the other hand, public service motivation literature argues that HPWS with performance pay could be detrimental to public sector employees who are more likely to be intrinsically motivated (Alonso and Lewis 2001). It may cause a crowding-out effect on employee motivation, resulting in perceived stress, demotivation, or even burnout (Kellough and Nigro 2002). Some have also found negative attitudes toward performance appraisal by supervisors and employees (Kim and Rubianty 2011) with low confidence in its efficacy, integrity, and fairness (Kellough and Nigro 2002). These studies and the discussions earlier (about EL and HPWS) suggest that the possible boundary or interactive systems would be even more complex in public organizations where the relationships between leadership or HPWS and employee outcomes are not straightforward.

The Interaction Effect of EL and HPWS on Creativity

In proposing our first hypothesis, we consider the interaction effects between EL and HPWS on creativity. As creativity is cognitively demanding and time- consuming (Shalley and Gilson 2004), psychological resources become crucial as described in the broaden and build theory (Fredrickson 2001). The broaden and build theory further emphasizes the importance of expanding and building capacities and resources that are required for creativity. Connecting it with the JD-R theor y, work environments that protect individuals’ resources would contribute to creativity, whereas work environments that demand resources would undermine creativity. Therefore, environmental factors such as pressure could negatively influence the creativity process (Amabile, Conti, Coon, Lazenby, and Heandrron 1996) as it drains psychological resources.

Here, we should note that what differentiates EL from other leadership styles (e.g., transformational and authentic leadership) is the hands-on approach that characterizes the moral manager dimension emphasizing compliance (Brown et al., 2005; Piccolo et al. 2010). Taken EL and HPWS together then, we also note that HPWS tends to recommend high levels of employee involvement (Tzafrir 2005), leading to increased workloads and reduced quality of work-life (White et al. 2003). When HPWS is seen to enhance workers’ demands without increasing their sense of empowerment (Macky and Boxall 2008), work practice may be perceived to focus on managerial compliance, and employees will experience HPWS as coercive and punitive (Wouters and Wilderon 2008). Such perceptions of HPWS lead

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356 Journal of asian sociology, Vol. 49 no. 3, september 2020

to emotional exhaustion or the lack of work engagement (Zhang, Zhu, Dowling, and Bartram 2013) and lower creativity-related intrinsic motivation (Avey, Luthans, Hannah, Sweetman, and Peterson 2012).

Therefore, the interaction effects of EL and HPWS would produce a stressful context that reduces attention and lower intrinsic motivation, which limits individual creativity (Avey et al. 2012). Their interaction effects would impose physiological and psychological costs (JD-R theory: Demerouti et al. 2001) and increase employee pressure, stress (Yang 2014), and emotional exhaustion (Lawler et al. 2011), which further reduce creativity. Moreover, along with HPWS, a signal by EL emphasizing compliance with rules and procedures would lead employees to contain their acts within set-boundaries. That is, they think inside the box rather than outside of the box, which is detrimental to creativity. Thus, E L’s p ot e nt i a l f or c re at i v it y c a n b e activated among individuals with low HPWS because they are not strongly constrained by normative pressures to comply with current practices. Thus, HPWS will negatively moderate the relationship between EL and individual creativity, such that the relationship will be stronger when HPWS is low than when it is high. Based on the discussion so far, we present the first hypothesis for the negative interaction effect between EL and HPWS on creativity as follows:

Hypothesis 1. HPWS will moderate the relationship between EL and creativity such that the relationship is stronger when HPWS is low than when it is high.

The Effect of EL on Task Performance through Creativity

The Mediating role of Creativity

Researchers have shown that employee creativity is critical for organizations’ competitiveness, innovation, and success (Anderson, Potočnik, and Zhou 2014). It is also positively related to various work outcomes, such as overall job performance (Gong, Huang, and Farh 2009; Zhang and Bartol 2010; Zhou and Hoever 2014). Previous studies' findings revealed that creativity can improve task performance (Liu, Gong, Zhou, and Huang 2017; Zhu, He, Treviño, Chao, and Wang 2015). Based on earlier theoretical arguments and empirical findings, we propose that creativity mediates ethical leadership’s effects on task performance. EL may engender high-level task performance

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357Ethical Leadership and High Performance Work System

by inducing employees to refine existing procedures and to discover improved methods to deliver ser vices and products. Ethical leaders encourage their followers to incorporate novel and beneficial ideas, eventually leading to creativity and innovation (Chen and Hou 2016; Gilson 2008; Humphrey et al. 2007). This increased level of creativity may facilitate the path towards the successful performance of a task.

The Moderating role of HPWS

This study presents HPWS as a moderator of the EL–creativity–performance relationship. For employees who perceive a low level of HPWS, EL may stimulate their creative minds to a greater extent than those who sense a high level of HPWS. Employee creativity can foster the individual learning process through which employees grasp new skills, make fewer mistakes, and improve routine tasks (Bandura 1997).

Given such differences in achieving creativity and task performance, we consider how the interaction effects between EL and HPWS affect task performance. Contrary to their impact on creativity, we suggest that the impact of EL on task performance will be stronger when HPWS is high than when it is low. Looking back to our earlier discussion about EL and HPWS, their interactive effects would further ‘reinforce and converge’ employees’ behaviors toward set requirements.

While people perform better in response to their workload when they believe that they have been rewarded fairly for their efforts (Colquitt, Wesson, Porter, Conlon, and Ng 2001), and employees work on the norms of reciprocity with HPWS (Hansen and Alewell 2013), high EL signals that such expectations will be met. That is, EL magnifies the influence of direct incentives and rewards that help employees to work toward specific work roles by HPWS (Lepak, Liao, Chung, and Harden 2006) and extensive training to increase the knowledge and skills of employees contributing to task performance (Jiang et al. 2013). Such interactive forces would focus and protect employees’ resources toward task performance (Demerouti et al. 2001).

Although there may be different mechanisms for creativity and task performance, especially in the short term, we expect that creativity will have positive influences on performance. Prior empirical research supports the connection between engaging in the creative process and task performance with significant correlations between them assessed by co-workers and supervisors (e.g., Gong et al. 2009; Ng and Feldman 2009).

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358 Journal of asian sociology, Vol. 49 no. 3, september 2020

Specific antecedents such as domain-relevant skills could determine what employees can do in the creative process (Amabile and Pillemer 2012) and task performance. Also, the removal of uncertainty, anxiety, and fear by EL and HPWS is associated with promoting innovation and increased outcomes (e.g., Agarwal and Farndale 2017; Detert et al. 2007; Ng and Lucianetti 2016). Therefore, there is a direct connection between creativity and task performance. We consider the interaction effects between EL and HPWS on task performance through creativity. Thus, we present the second hypothesis as follows:

Hypothesis 2. HPWS moderates the relationship between EL and task performance through the mediating effect of creativity. EL influences task performance through creativity; the indirect effect will be stronger when HPWS is high rather than it is low.

Methods

Data and Sample Data were collected from a public sector firm in Korea, one of the largest electric power companies. The survey was carried out in two stages. In Stage 1, individual team members were asked to fill out an online questionnaire about their perceptions of EL and HPWS. In Stage 2, a month after the survey of te am me mb e rs, te am l e a d e rs were aske d to f i l l out t wo s e t s of questionnaires, one for evaluating their team as a whole and the other for assessing individual team members' performance. A total of 177 individual team members filled out the questionnaire. As some leaders did not evaluate the performance of their team members, and some teams consisted of less than two members, these cases were excluded, leaving 106 dyads for analysis. The mean age of team members was 35.64 (s.d. = 9.59) years, with an average team tenure of 4.16 (SD = 3.42). Males comprised 90.4% of the sample. Education levels were high school (12.3 %), two-year college (8.5%), bachelor’s degree (70.8%), and graduate degree (8.5%).

Measures

Ethical leadership (EL): A ten-item scale (α = .98) assessing the team members’ perception of EL by Brown et al. (2005) was adopted in our study. A sample item includes the following: “Our team leader disciplines

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359Ethical Leadership and High Performance Work System

employees who violate ethical standards.” High performance work system (HPWS): Five different HR practices

were conceptualized and measured using Delery and Doty’s (1996) method. The five dimensions are training programs, results-oriented appraisal, profit sharing, staffing, and employee participation. Since there is little consensus regarding which HPWS practices should be included, previous research has provided several theoretical and methodological arguments for why a systems approach is preferable in HPWSs research (Delery 1998; Huselid and Becker 1997). This paper adopts the notion of a “unitary index” used in Way’s (2002) research. The unitary index was created by adding the standardized scores of the five equally weighted components of the HPWSs by team members’ ratings.

Creativity: Creativity was assessed by team leaders using four items (α = .96) from Zhou and George (2001). A sample item is: “This team member comes up with new and practical ideas to improve team performance.”

Task performance: Team leaders measured task performance with a two- item scale (α = .79) adapted to Williams and Anderson (1991). Team leaders completed items such as, “This team achieves its goals.”

Control variables: Studies show that age and team tenure are essential factors that influence individual outcomes, such as creativity (Seong and Choi 2019). Therefore, they were used as control variables in the analyses.

Results

We first performed confirmatory factor analyses to examine our scales' distinctiveness for EL, HPWS, creativity, and task performance using AMOS 23.0. To reduce the number of parameters, we used the item parceling method recommended by Bagozzi and Edwards (1998) on two variables: EL and HPWS. We compared this four-factor model with plausible alternative models. Overall, these results demonstrated that the expected four-factor model provides substantially improved fit over these relevant alternative models (χ2 (df = 98) = 188.06, p < .001; comparative fit index = .96, Tucker– Lewis Index (TLI) = .95, Standardized root mean squared residual = .069).

Table 1 presents the means, standard deviations, and correlations among the study variables.

Since crucial study variables were measured by different sources (i.e., EL and HPWS by team members and creativity and task performance by team leaders), we used hierarchical linear modeling (HLM; Raudenbush and Bryk

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360 Journal of asian sociology, Vol. 49 no. 3, september 2020

2002) to remove the leaders’ effect for testing hypotheses, as shown in Table 2.

Table 2 provides a summary of the HLM results for testing all the hypotheses simultaneously. The results of our analysis using the Preacher, Ruker, and Hayes (2007) macro are shown in Table 3. Table 3 shows the indirect effect of EL on task performance through creativity at high and low levels of HPWS. In testing Hypothesis 1, as shown in Table 2, after controlling for age and team tenure, EL and HPWS interacted with each other (γ = -.15, p

Table 1 Means, standard deviations, and correlations among study variables

Variable Mean s.d. 1 2 3 4 5 6

1 Age 35.64 9.59 – 2 Team tenure 4.16 3.42 .18 – 3 Ethical leadership 5.28 1.40 .29** -.09 (.98) 4 HPWS 4.67 1.43 .22* .02 .62** (.95) – 5 Creativity 6.56 .65 -.08 -.16 -.06 .02 (.96) 6 Task performance 6.72 .53 .01 -.14 .04 -.00 .31** (.79)

Notes.― n = 106. The alpha internal-consistency reliability coefficients appear in parentheses along the main diagonal. HPWS = High performance work system. *p < .05, **p < .01.

Table 2 Hierarchical linear models: individual-level relationships between

ethical leadership, HPWS, creativity, and task performance Creativity Task Performance

Variable Step 1 Step 2 Step 3 Step 1 Step 2 Step 3 Step 4

Intercept 6.56***(.07) 6.56***(.07) 6.56***(.07) 6.72***(.05) 6.73***(.02) 6.72***(.05) 6.73***(.05) Age .03(.01) .03(.02) .03(.02) -.01(.01) -.01(.01) -.01(.01) -.02(.02) Team tenure -.01(.03) -.02(.03) -.01(.03) -.01(.02) -.01(.02) -.01(.02) .00(.01) Ethical leadership (EL)

-.09(.12) -.22(.13) -.05(.05) -.05(.05) .03(.07)

HPWS .04(.12) .04(.12) .11(.06) .11* (.06) .10 (.06) EL × HPWS -.15*(.07) -.01(.02) .03(.03) Creativity .54***(.10)

ơ2 0.41 0.42 0.40 0.28 0.28 0.28 0.19 Peudo r2 change Δ.02 Δ.04 Δ.00 Δ.01 Δ.30

Notes.― n = 106. *p < .05. HPWS = High performance work system. Unstandardized coefficients are reported. Standard errors in parentheses.

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361Ethical Leadership and High Performance Work System

< .05). Creativity was, in turn, positively related to task performance (γ = .54, p < .001). These findings meet an important condition for Hypothesis 2, which predicts a moderated mediation effect (Preacher et al. 2007). The interactive effect of EL and HPWS is indirectly related to task performance through creativity.

Therefore, we proceeded to test the conditional indirect effects of EL through creativity on task performance at different levels of HPWS (Hypothesis 2). We used a bootstrapping procedure to probe the indirect effect to varying levels of the moderator variable, such as HPWS. As shown in Table 3, when HPWS is high, EL had an indirect effect on task performance (b = -.08, boot SE = .039). The 95% bias-corrected confidence interval around the bootstrapped indirect effect excludes zero [CI = -.178, -.017]. When HPWS is low, EL did not have an indirect effect on task performance (b = -.02, boot SE = .027). The 95% bias-corrected confidence interval includes zero [CI = −.084, .031]. Thus, Hypotheses 2 was supported.

Discussion

This study sheds light on the interaction effects between EL and HPWS on creativity, which indirectly influence performance. A leader is closely involved in HPWS processes, which can be ambiguous; having a more objective HPWS should benefit both employee creativity and performance. This study suggests that an organization should pay attention to the HR system and leadership at the same time to develop and preserve employees' resources. The study illustrated the importance of considering interaction effects between EL and HPWS since both are fundamental work contexts for employees concerning organizational processes, including creativity, which requires psychological resources. In this study, we found a negative interaction effect of EL and HPWS on creativity.

In contrast, the indirect interaction effect of EL and HPWS on task

Table 3 Conditional indirect effects of ethical leadership on task

performance at the level of HPWS Path Moderator Effect Boot SE Boot LLCI Boot ULCI

Simple path for low HPWS 3.24 -.02 .0273 -.0839 .0312 Simple path for high HPWS 6.10 -.08 .0389 -.1780 -.0174

Notes.― 95% bias-correlated CI.

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362 Journal of asian sociology, Vol. 49 no. 3, september 2020

performance was significantly positive through creativity. That is, EL, together with HPWS ‘cost and reverse’ individuals’ resources on creativity and ‘protect and magnify’ individuals’ resources on task performance at the same time. With the findings in this study, we point out the paradoxical effects of EL and caution against the universalistic approach toward EL or HPWS, which has emphasized each system’s positivity without considering the possible interactions they have with each other.

Regarding our finding that the effects of EL are conditional upon HPWS, we suspect this is because stand-alone-well-functioning EL may not be apparent to employees as it may pass undetected by employees. This is because EL with integrity and morality are some of the fundamental elements of a leader (Brown et al. 2005), which is one of the employees’ basic needs at work (cf. Hygiene factor: Herzberg 1964) and is taken for granted (e.g., like the air we breathe). One may only notice it when the expectation of fairness is violated (cf. Yang 2013). This may be even more the case for employees of public organizations as they are less vulnerable to the influence of leadership directly (with a high level of job security). Our stand is reflected in studies showing that relations between EL and organizational citizenship behavior (OCB) disappear when perceived organizational politics (POP) is low for a state government (Kacmar, Bachrach, Harris, and Zivnuska 2011).

Limitations and Suggestions for Future Studies

This study’s longitudinal research design answers the call in HRM research to collect data at different time points to test better causal effects (e.g., Wright, Gardner, Moynihan, and Allen 2005). However, while using supervisors' judgment is an accepted approach in creativity research (Shalley, Zhou, and Oldham 2004), future research may want to measure creativity and task performance using more objective data.

Despite its strengths, this paper has several limitations. First, the data used in this study were collected from a Korean public sector firm. To test whether the negative interaction effects of EL and HPWS on creativity can be generalized across different cultural and organizational contexts, we need further comparative studies (Detert, Treviño, Burris, and Andiappan 2007; Ng and Feldman 2015; Piccolo et al. 2010; Walumbwa and Schaubroeck 2009). High power distance or power centrality in Korean culture and rule- based HPWS, which are different from traditional relations-based HRM in Korea, may have amplified the burden from EL and HPWS on Korean employees (Ng and Feldman 2015).

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363Ethical Leadership and High Performance Work System

Second, as the methods adopted in this study are based on the JR-D theory, the negative interaction effects between EL and HPWS on creativity may not be culturally or organizationally specific. Also, firm ownership (state versus private) could be fundamental to a firm's operations and moderate the impact of HR systems, including performance-oriented HR systems (Liu, Gong, Zhou, and Huang 2017). With a growing appreciation for EL and HPWS across different cultures and organizations, more studies are needed to examine subtle nuances and variations in recognition of them.

Third, the small sample size of the teams used in this study inhibits bold generalization. An extensive research design expanding the number of sample teams is needed in future research. The use of small samples for testing hypotheses may create some interpretative problems (e.g., Caldwell and O’Reilly 1990). Prior research has also reported problems of linking small sample size to more elaborated statistical tests (Hollenbeck, DeRue, and Mannor 2006; Mone, Mueller, and Mauland 1996; Peterson, Smith, Martorara, and Owen 2003).

Fourth, this study has cross-industrial and cross-cultural implications in that it focuses on a public sector firm in Korea. It is generally believed that Koreans are more collectivism-oriented than Westerners. Scales based on individualism versus collectivism as people’s traits have been used to measure societies’ cultural dimensions (e.g., Hofstede, 1980; Christie, Kwon, Stoeberl, an d B au m h ar t 2 0 0 3 ) . In ge n e r a l, c ol l e c t iv i st c u ltu re st re ss e s t h e interdependence between people, while individualist culture emphasizes the independent roles and functions of individuals (Triandis 2001). Our study found significant interaction effects of EL and HPWS on creativity and task performance. These interactive relationships might be more likely to be an essential factor in determining creativity and task performance in private sector firms. Stated in this way, we conclude that EL and HPWS are highly influential among employees in other cultures, such as individualistic Western cultures. We suggest that future studies conduct comparative research so as to encompass other industrial sectors (e.g., manufacturing, service, etc.) and other cultural contexts to verify the tentative conclusion drawn in this study.

(Submitted: August 9, 2020; revised: September 28, 2020; Accepted: September 28, 2020)

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364 Journal of asian sociology, Vol. 49 no. 3, september 2020

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iNJu YANG is a lecturer in the School of Management at RMIT University. Her research interests include business ethics, diversity management practices, human resource management, leadership, and social networks. Her research has appeared in Work, Employment and Society, Organization, International Journal of Human resource Management, International Journal of Manpower, Employee relations, European Management Journal, Asia Pacific Journal of Management, and others. [Email: [email protected]]

JEE YOuNG SEONG is an Associate Professor in the Department of Business Administration at Jeonbuk National University. Her research interests include person-environment fit and diversity within organizations, work-life balance, and cultural differences in the organization. Her research has appeared in Journal of Management, Journal of Applied Psychology, Human resource Management Journal, Journal of Managerial Psychology, and Group and Organization Management, among others. [Email: [email protected]]

DOO-SEuNG HONG is a Professor Emeritus of Sociology at Seoul National University. His research interests include social stratification, sociology of work and occupations, and militar y sociology. He has published articles in American Sociological review, Work and Occupations, Current Sociology, Social Indicators research, Journal of Management, and Human resource Management Journal. [Email: [email protected]]

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r Academy of Management Journal 2018, Vol. 61, No. 5, 2000–2019. https://doi.org/10.5465/amj.2015.1101

FROM EMPLOYEE-EXPERIENCED HIGH-INVOLVEMENT WORK SYSTEM TO INNOVATION: AN EMERGENCE-BASED

HUMAN RESOURCE MANAGEMENT FRAMEWORK

YIXUAN LI Purdue University

MO WANG University of Florida

DANIELLE D. VAN JAARSVELD University of British Columbia

GWENDOLYN K. LEE University of Florida

DENNIS G. MA University of British Columbia

The influence of human resource management on innovation has attracted considerable research attention over the last decade. However, existing studies have primarily fo- cused on the macro-level human resource management architecture, limiting our un- derstanding about the cross-level origin of innovation. Developing an emergence-based human resource management framework, we propose that an employee-experienced high-involvement work system (HIWS) promotes innovation by eliciting collective in- teractions for knowledge exchange and aggregation. Further, we investigate the emergence-enabling process that facilitates an employee-experienced HIWS to give rise to organization-level innovation. Specifically, we probe three distinct emergence en- ablers that amplify the positive influence of HIWS on innovation by shaping the con- certedness, direction, and adaptability of collective interactions: (1) the homogeneity of HIWS experiences as the internal mechanism, (2) the strategic importance of innovation as the external mechanism, and (3) the churn in human resources as the temporal mechanism. We tested our theoretical model using data from a nationally representative sample of workplaces in Canada (n 5 2,639). Our results suggest that an employee- experienced HIWS was positively related to innovation. In addition, this positive effect was amplified by all three emergence enablers (i.e., the homogeneity of HIWS experi- ences, the strategic importance of innovation, and the churn in human resources).

Considering the dynamic market environment and short product life cycles, “innovation”—defined as the intentional introduction and application of new ideas, processes, products, or procedures (West & Farr, 1990)—is crucially important in helping firms discover new market opportunities, adapt to envi- ronmental changes, and sustain competitive ad- vantage. Yet, the management of innovation is challenging, because the knowledge creation pro- cess is discontinuous. In particular, although knowledge creation arises from the coalescence of human resources, this macro phenomenon cannot be reduced to its constituent elements (Kozlowski &

We would like to thank our action editor Dr. Riki Take- uchi and the three anonymous reviewers for their con- structive and insightful comments. We are also grateful to Dr. Cheri Ostroff for her helpful feedback on an earlier version of this article. Mo Wang’s work on this research was supported in part by the Lanzillotti-McKethan Emi- nent Scholar Endowment. Research funding from the So- cial Sciences and Humanities Research Council of Canada supported Danielle D. van Jaarsveld and Dennis G. Ma.

Correspondence regarding this article should be addressed to Yixuan Li, Organizational Behavior and Human Resource Management, Krannert School of Man- agement, Purdue University, West Lafayette, IN 47907. Email: [email protected].

2000

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Klein, 2000). As such, articulating the process that enables the discontinuous emergence of knowledge creation contributes much to our understanding about the origin of innovation in organizations (Felin & Hesterly, 2007).

Despite the considerable research attention that strategic human resource management (HRM) scholars have devoted to examining the connection between HRM and innovation, existing research has primarily focused on the macro-level HRM archi- tecture, investigating the influence of HRM systems on innovation-related activities, capability, and performance (e.g., Chang, Jia, Takeuchi, & Cai, 2014; Collins & Smith, 2006; Patel, Messersmith, & Lepak, 2013). While this macro focus informs organizations how to design HRM architecture to promote inno- vation, our understanding of the emergence pro- cess whereby human resources aggregate to generate innovation is still limited. As noted by Kozlowski and Klein (2000), there might be a danger of super- ficiality and triviality inherent in adopting a single- level perspective to account for organizational phenomena. Investigating the emergence process (i.e., the amplifying process whereby lower-level elements are aggregated to form higher-level phe- nomena; Kozlowski & Klein, 2000) linking the micro level to the macro level can engender a more in- tegrated science of organizations. Thus, it is impor- tant for strategic HRM research to move beyond HRM architecture to uncover how organizations advance innovation by managing the emergence of human resources.

According to Ployhart and Moliterno (2011), organization-level human capital resources are cre- ated from the emergence of individuals’ knowledge, skills, abilities, and other characteristics (KSAOs) via collective interactions (i.e., interpersonal exchange of information, affect, and resources; Kozlowski & Klein, 2000). Through this process, the KSAOs em- bedded in individual employees represent elemental raw materials, the collective interactions denote the amplifying process whereby raw materials are com- binedand aggregated,andthehumancapital resources embody the emergent macro reservoirs (Kozlowski & Klein, 2000). However, directly examining collective interactions, which is the key driver in the emer- gence process, is nearly impossible due to the sheer complexity of capturing dynamic social interactions (Colbert, 2004). Recognizing the missing ingredient connecting the micro and macro organizational re- search, Ployhart and Moliterno (2011) proposed a new theoretical account—the emergence-enabling process (i.e., the mechanisms through which individual-level

KSAOs are amplified to become organization-level human capital resources)—to explicate the features of collective interactions.

Building on the human capital resource emer- gence perspective (Ployhart & Moliterno, 2011), we propose an emergence-based HRM framework to investigate how employees’ HRM experiences give rise to organization-level innovation. Specifically, we propose that employees’ experiences with a high- involvement work system—that is, an employee- experienced high-involvement work system (HIWS)— can promote innovation, as HIWS-based collective interactions serve as the primary source for knowledge exchange and aggregation (Argote & Ingram, 2000). Further, drawing on the complex adaptive system (CAS) theory from complexity science (Colbert, 2004; Dooley, 2004), we propose three distinct emergence- enabling mechanisms that may amplify the positive influence of a HIWS on innovation by shaping the features of collective interactions (i.e., concerted- ness, direction, and adaptability). First, the internal mechanism reflects the internal implementation of HRM systems. It centers on the “concertedness” of collective interactions, which captures the extent to which HRM systems manage employees properly to facilitate implicit and explicit coordination in accomplishing work tasks. In this study, we con- sider the homogeneity of employees’ HIWS expe- riences (i.e., employees’ consensus regarding their general experiences of HIWSs) as an important en- abler for a HIWS to induce concerted interactions. Second, the external mechanism examines an or- ganization’s strategic needs based on the business environment it encounters. It represents the “di- rection” of collective interactions, manifested as the strategic goals and values that organizations communicate to their employees. In this study, we use the strategic value that an organization attaches to innovation (i.e., the strategic importance of in- novation) to probe the extent to which collective efforts are channeled toward innovation. Third, the temporal mechanism concerns the dynamics of hu- man resources, including both its inflow (i.e., em- ployees joining the organization; joiners) and outflow (i.e., employees leaving the organization; leavers). It evaluates the “adaptability” associated with collec- tive interactions, manifested as the extent to which human resource flow reduces stagnation and in- creases responsiveness. We probe this temporal mechanism using the churn in human resources (i.e., the total quantitative flow of human resources into and out of the focal organization), which is a fundamental means for organizations to reshape

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collective interactions for innovative changes in adapting to the dynamic environment.

Our study contributes to the existing literature in several ways. First, by closely examining three dis- tinct types of emergence-enabling mechanisms that facilitate an employee-experienced HIWS to give rise to innovation, we contribute to the multilevel per- spective of strategic HRM. As Jiang, Takeuchi, and Lepak (2013) suggested, the influence of HRM on organizational performance is fundamentally a mul- tilevel phenomenon, because organization-level HRM systems impact organization-level outcomes by influencing individual-level employees’ HRM experiences and reactions. Embracing this multi- level perspective, one recent trend in strategic HRM research is to adopt a top-down approach to in- vestigate the cascading effects of HRM systems on individual attitudes and behaviors (e.g., Chang et al., 2014; Liao, Toya, Lepak, & Hong, 2009; Takeuchi, Chen, & Lepak, 2009). Far less research, however, has examined the bottom-up process whereby in- dividuals’ HRM experiences and reactions lead to organization-level outcomes. One exception is Nishii, Lepak, and Schneider (2008), who showed that employees’ attributions regarding HRM prac- tices had important consequences for their col- lective attitudes and behaviors, and, ultimately, unit performance. Another exception is Liu, Gong, Zhou, and Huang (2017), who demonstrated that employee-experienced HRM systems could influ- ence employee creativity, which in turn promoted firm innovation. Building upon these ideas, we propose an emergence-based HRM framework to examine the emergence-enabling process that fa- cilitates employees’ HIWS experiences to give rise to innovation, complementing previous multilevel HRM research by providing a novel lens for eval- uating the bottom-up HRM process.

Further, by establishing three enablers that corre- spond to the emergence-enabling mechanisms, we contribute to the contingency perspective of strategic HRM. To date, studies that investigated the connec- tion between HRM and innovation mainly focused on universalistic predictions, implying that imple- menting “high road” HRM enhances innovation in an isomorphic manner across organizations (Colbert, 2004). Recognizing this research oversight, HRM researchers increasingly call for the investigation of contingent factors for the HRM–innovation re- lation to understand the boundary conditions un- der which organizations may benefit more from adopting “high road” HRM systems (e.g., Chang, Gong, Way, & Jia, 2013; Collins & Smith, 2006).

Answering this research call, our study investigates three emergence enablers that allow organizations to extract additional value from HRM in facilitating innovation, providing an effective integration of the multilevel HRM perspective with the contingency HRM perspective.

In addition, to explicate the emergence-enabling process linking HRM to innovation, we draw on the CAS theory in developing the taxonomy for the emergence-enabling mechanisms. Although the CAS theory was introduced to the organizational literature in theorizing organizational change (Dooley, 2004) and HRM architecture (Colbert, 2004), the features of the emergence process in the organizational system have received little research attention, limiting our understanding about the core premise of the CAS theory. By examining the internal, external, and temporal emergence- enabling mechanisms that facilitate employees’ HRM experiences to give rise to innovation, the current study delineates patterns of collective in- teractions (i.e., concertedness, direction, and adapt- ability) that enrich the emergence process in the CAS theory.

THEORETICAL BACKGROUND

The emergence perspective focuses on the bottom- up process wherein the aggregate influence of lower-level elements leads to higher-level holistic phenomena (Kozlowski & Klein, 2000). The theo- retical foundation of this perspective is rooted in complexity science, which combines general system theory with basic principles and characteristics of living systems (Dooley, 2004). The work organiza- tion can be categorized as one type of complex living system, in which individuals’ affect, cognition, and behaviors unfold over time to yield collective phe- nomena (Kozlowski & Klein, 2000). Adopting this complexity lens, Colbert (2004) introduced the CAS theory from complexity science to the strategic HRM field to explain how and why HRM created sustain- able competitive advantage by generating causal am- biguity and social complexity in human resources.

According to Colbert (2004), a CAS is character- ized by two features: (1) a large number of interacting agents and (2) the presence of stable emergent pat- terns and properties. As basic elements of a CAS, “agents” are defined as semi-autonomous units (e.g., cells in a biological system or sellers in an economic system) that seek to optimize their fitness level by evolving over time (Dooley, 2004). In the organizational system, “agents” refer to individual

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employees who interact with one another for the exchange of information and resources. The in- teractions of agents, in turn, give rise to emergent macro-level phenomena. The interactive dyna- mism is complex and unpredictable, because it arises from many linear and nonlinear interre- lations among agents. Due to causal ambiguity and social complexity, inimitable competitive advan- tage is afforded by the emergence process (Colbert, 2004).

To uncover the inner workings of interactive dy- namism in organizations, Ployhart and Moliterno (2011) proposed a new theoretical account—the emergence-enabling process—to describe the mech- anisms through which lower-level KSAOs are aggregatedandtransformedintovaluableorganization- level human capital resources. Importantly, through repeated interactions among organizational members, emergence-enabling states (i.e., emergent cognitive states, emergent behavioral processes, and emer- gent affective states) arise and gradually regularize, crystallize, and stabilize to guide subsequent col- lective interactions (Ployhart & Moliterno, 2011). Despite its valuable insight, the human capital resource emergence perspective offers us little guidance about how organizations can effectively manage the emergence process of human resources. Thus, Ployhart and Moliterno (2011) underscored the importance of future studies to investigate the role of HRM in facilitating human capital resource emergence.

Answering the research call sounded by Ployhart and Moliterno (2011), we propose an emergence- based HRM framework to study the linkage between the employee-experienced HIWS and organization- level innovation. According to strategic HRM re- searchers, a HIWS includes a set of management practices implemented to create opportunities for collective interactions through increasing em- ployees’ discretion, coordination, and collaboration (Batt & Colvin, 2011; Lawler, 1986, 1992). Thus, employees’ experiences with the HIWS play a cen- tral role in eliciting collective interactions in the organizational system. Further, applying an agent- centered approach specified by the CAS theory, we derive three emergence-enabling mechanisms that may amplify the effect of a HIWS on innovation by shaping the features of collective interactions (i.e., concertedness, direction, and adaptability) among employees (i.e., agents in the organizational system).

Specifically, the internal mechanism focuses on agent concertedness and examines how the internal

implementation of HRM systems in an organization facilitates interconnected employees to exhibit con- certed actions in pursuing collective goals. We consider the homogeneity of employees’ HIWS ex- periences to be an important enabler for a HIWS to induce concerted interactions. According to Nishii et al. (2008), meaningful variability exists within organizations in terms of employees’ experiences with and reactions to HRM systems. Nishii and Wright (2008) further pointed out that variability in employees’ HRM experiences should be captured when examining the relation between HRM and or- ganizational performance, because such variability might operate as an important boundary condition for the HRM-performance linkage. Consistent with previous studies, we consider the homogeneity of employees’ HIWS experiences as a contingent factor that shapes the relation between HIWS and in- novation. In particular, we propose that homoge- neous experiences amplify the positive effect of HIWS on innovation by facilitating the concertedness of collective interactions via developing implicit coordination, explicit coordination, and emotional “bonds” for the collective.

The external mechanism focuses on agent direction, which depends on the business environment-based strategic needs that organizations communicate to employees. As organizations vary in terms of strategic values and goals, their HRM systems are deployed to elicit different employee behaviors in support of corresponding business strategies (Delery & Doty, 1996; Wright & Snell, 1998). For organizations seeking to achieve innovation, employees’ syner- gistic efforts need to be directed toward knowledge creation. To elicit relevant employee behaviors, organizations ought to clearly express to employees their strategic need and priority regarding innova- tion. In this study, we use the strategic importance that an organization attaches to innovation to probe the extent to which collective efforts are channeled toward innovation. This conceptualization is ap- propriate, because, when an organization places higher importance on innovation, employees are more likely to engage in innovation-related activi- ties (e.g., knowledge generation, knowledge ex- change, and knowledge aggregation), as these activities are more likely to be recognized and rewarded by the organization (Tsui, Pearce, Porter, & Tripoli, 1997).

The temporal mechanism focuses on agent adapt- ability. We consider the churn in human resources as a fundamental organizational dynamism that re- shapes collective interaction patterns in adapting to

2018 2003Li, Wang, van Jaarsveld, Lee, and Ma

the unstable and turbulent competitive environment. This construct focuses on the quantity of human resource flow regardless of the quality, which is aligned with the labor economics literature viewing employee mobility as reallocation or churning of labor in the labor market (e.g., Burgess, Lane, & Stevens, 2000; Franco & Filson, 2006). Indeed, the CAS theory suggests that the churn in human resources is associated with changes in schema (i.e., mental templates that define how reality is interpreted and what appropriate responses are for a given stimulus; Holland, 1995), information and resource flow, and agent connectivity in the orga- nizational social networks (Dooley, 2004). As such, the churn in human resources serves as the basic means for organizations to shift the patterns of collective interactions. In this study, we submit that the churn in human resources can facilitate HIWS to give rise to innovation by shaping the nature of human capital resources that HIWS leverages. We base our logic on the fact that functional human resource flow can refresh the human resource pool with updated KSAOs and reduce the stagnation of collective interactions (Hannan & Freeman, 1984). Consequently, innovation is more likely to happen when HIWS leverages churning human resources. We present our theoretical model in Figure 1.

HYPOTHESES DEVELOPMENT

An Employee-Experienced HIWS and Innovation

In contrast to Taylorized work design emphasiz- ing narrow job specifications and constricted work autonomy, the high-involvement approach to work design combines employee discretion with group problem-solving, assuming that employees need discretion to solve problems with problem-solving best achieved through collaboration (Batt & Colvin, 2011). Correspondingly, a HIWS refers to a set of HRM practices that are designed to promote em- ployee empowerment, collective collaboration, and relational coordination (Lawler, 1986, 1992). Typical high-involvement work practices include team-based design (e.g., problem-solving teams and self-directed teams), information sharing (e.g., employee suggestion program), aggregate compen- sation strategy (e.g., gainsharing), flexible job de- sign (e.g., job rotation), and employee training (von Bonsdorff, Zhou, Wang, Vanhala, von Bonsdorff, & Rantanen, 2016; Zatzick & Iverson, 2006). Impor- tantly, in this study, we focus on employees’ actual HIWS experiences rather than managerial reports of a HIWS. Stated by Jiang et al. (2013), HRM systems designed at the organizational level needed to be experienced by individual employees to exert an

FIGURE 1 An Emergence-Based HRM Framework for Innovation

Workplace-Level

Employee-Level

Innovation

Innovation)(Employee-Experienced HIWS

Employee-Experienced High-Involvement Work System

B o

tt o

m -u

p H

R M

P ro

ce ss

Emergence Enabling Mechanisms

Internal Mechanism: The Homogeneity of HIWS Experiences

External Mechanism: The Strategic Importance of Innovation

Temporal Mechanism: The Churn in Human Resources

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actual impact on the organization. Similarly, Wright and Nishii (2013) argued that HRM practices must be perceived and interpreted subjectively by in- dividuals to elicit their affective, cognitive, and behavioral reactions. As we investigate how a HIWS and its associated emergence-enabling mecha- nisms facilitate the aggregation of human resources for innovation, focusing on an employee-experienced HIWS aligns more closely with the current re- search goal.

We propose that an employee-experienced HIWS promotes innovation by eliciting collective in- teractions. First, team-based high-involvement ac- tivities provide employees with the opportunity to collaborate with other team members in problem- istic search (i.e., the type of search that is stimulated by a problem and aimed at finding a solution for that problem), a fundamental mechanism that gen- erates innovation (Greve, 2003). Through frequent collaboration in problem-solving, team members are able to develop relational coordination for group learning and creativity (Gittell, Seidner, & Wimbush, 2010). Second, employees’ participation in information sharing, training, and job rotation can help them accumulate a sufficient level of knowledge overlap for effective communication and increase knowledge exchange between in- dividuals with diverse repertoires of local knowl- edge (Collins & Smith, 2006). As such, efficient knowledge aggregation is more likely to take place. Third, employee discretion and gainsharing con- tribute to innovation by reducing the stickiness in knowledge transfer (i.e., the difficulty experienced in the knowledge transfer process; Szulanski, 2000). Specifically, increasing employee discre- tion can release employees from the confines of narrow job specifications and enable them to capi- talize on their tacit knowledge for knowledge generation and knowledge exchange, in turn facil- itating the knowledge transfer process. Further, adopting gainsharing practices can align individual and organizational objectives to cope with agency problems (Gomez-Mejia & Balkin, 1989). In pursu- ing common goals that move beyond individual goal optimization, employees are more motivated to exchange their knowledge to improve the overall work process and are more likely to develop mutual trust and psychological safety through the knowl- edge transfer process (Gong, Cheung, Wang, & Huang, 2012).

Hypothesis 1. An employee-experienced HIWS is positively related to innovation.

The Internal Mechanism: The Homogeneity of HIWS Experiences

According to Ployhart and Moliterno (2011), three emergent enabling states are the determinants of concerted collective actions: (1) emergent cognitive states, (2) emergent behavioral processes, and (3) emergent affective states. Accordingly, we expect the homogeneity of employees’ HIWS experiences to amplify the positive influence of an employee- experienced HIWS on innovation by influencing these three emergent states, respectively. First, when employees’ HIWS experiences are homogeneously high, they cultivate concerted emergent cognitive states for knowledge aggregation. Specifically, when employees are uniformly exposed to a HIWS, they are more likely to hold overlapping cognitive repre- sentations of work tasks and develop shared un- derstandings regarding organizations’ expectations (Bowen & Ostroff, 2004). Such shared perceptions, in turn, facilitate the formation of shared mental models and promote the synchronization, pacing, and quality of organizational processes, thus im- proving the effectiveness of knowledge exchange and aggregation. Further, homogeneous HIWS ex- periences benefit organizational learning by de- veloping a high-quality transactive memory system for the organization (i.e., a shared organizational system for encoding, storing, and retrieving information; Wegner, 1986). In particular, they pro- mote or generate broad and intensive intercon- nections among employees, and in turn facilitate the development of organization-level knowledge ar- chitecture with a specialized division of labor from different knowledge expertise, reducing individuals’ cognitive load and providing organizations with full access to a large reservoir of knowledge (Argote & Ingram, 2000).

Second, when employees’ HIWS experiences are homogeneously high, they cultivate concerted emergent behavioral processes for knowledge ex- change. The collective behavioral processes of an organization are manifested as employees’ overt communication and explicit coordination in the work process (Ployhart & Moliterno, 2011). When employees are uniformly exposed to a HIWS, they are more likely to be involved in the communication and coordination process in accomplishing inter- dependent work tasks. Through the communication process, involved employees can exchange task- relevant information and knowledge, which are important sources of innovation (Argote & Ingram, 2000). In addition, through explicit coordinating

2018 2005Li, Wang, van Jaarsveld, Lee, and Ma

activities, involved employees are able to aggregate their discretionary behaviors toward the formation of a unified workforce, removing the barriers for the creation and implementation of creative ideas.

Third, when employees’ HIWS experiences are homogeneously high, they cultivate concerted emergent affective states for knowledge transfer. The collective affective states of an organization largely depend on the strength of emotional “bonds” that tie its members together (Ployhart & Moliterno, 2011). Homogeneous HIWS experiences can strengthen the emotional “bonds” by cultivating social capital in the workforce (Tsai & Ghoshal, 1998). In particular, through HIWS-based interactions, employees can develop mutual understanding regarding one an- other’s expectations, needs, and goals, and adjust their communication and behavioral patterns ac- cordingly to fit the social situation. Over time, such unfolding social interactions can help the workforce develop collective trust and cohesion, facilitating knowledge exchange and aggregation (Jones & George, 1998).

Hypothesis 2. The homogeneity of HIWS experi- ences moderates the relation between an employee- experienced HIWS and innovation, such that this positive relation is more (vs. less) pronounced when HIWS experiences are more (vs. less) homogeneous.

The External Mechanism: The Strategic Importance of Innovation

The contribution of HRM practices to organiza- tional performance is contingent on the extent to which they align with the business strategy (Becker & Gerhart, 1996; Wright & Snell, 1998). To achieve in- novation, organizations ought to clearly communi- cate to the employees their strategic need for innovation to direct collective efforts toward in- novation. As such, we expect the strategic impor- tance that organizations attach to innovation to amplify the positive influence of a HIWS on in- novation. In particular, we argue that the amplifying effect of the strategic importance of innovation can be explained by the complementarity between em- ployees’ HRM experiences and organizations’ stra- tegic needs. On the one hand, if organizations value innovation, an employee-experienced HIWS can better elicit organization-desired collective behav- iors that satisfy the strategic need for innovation (Delery & Doty, 1996). This line of logic is based on the idea that, when innovation is important to orga- nizations, organizations are more likely to recognize

and reward employee behaviors that benefit in- novation through HRM (Tsui et al., 1997). As such, emergent human capital resources garnered by a HIWS are more likely to be channeled toward knowledge creation. On the other hand, organiza- tions emphasizing the strategic importance of in- novation may facilitate collective efforts directed toward innovation to materialize as new products or processes by providing a beneficial context for knowledge creation. Specifically, organizations that value innovation tend to be learning oriented, en- couraging divergent thinking and knowledge ex- change. Thus, employees are more motivated to criticize existing routines, challenge one another’s opinions, and express their novel insights. As such, high-involvement work practices are more likely to result in innovative ideas when the strategic impor- tance of innovation is higher. Further, organizations that emphasize the strategic value of innovation are more tolerant of errors and may even encourage employees to learn through a trial-and-error process (Levitt & March, 1988). Therefore, when employees are involved in problem-solving, they are less guarded about new ideas and are more willing to develop potential solutions progressively through multiple trial-and-error learning processes.

Hypothesis 3. The strategic importance of innova- tion moderates the relation between an employee- experienced HIWS and innovation, such that this posi- tive relation is more (vs. less) pronounced when the strategic importance of innovation is high (vs. low).

The Temporal Mechanism: The Churn in Human Resources

As mentioned above, a HIWS benefits innovation by eliciting collective interactions for knowledge exchange and knowledge aggregation. As such, the extent to which a HIWS contributes to innovation largely depends on the nature of human capital re- sources that a HIWS leverages. In particular, to create new knowledge, a HIWS needs to leverage a human resource pool that contains updated knowledge and presents low rigidity to changes. Following this logic, we expect the churn in human resources to amplify the positive effect of a HIWS on innovation for three reasons. First, the churn inhuman resources facilitates a HIWS to generate innovation by contin- uously updating organizations’ knowledge reser- voir, with employee mobility serving as a powerful mechanism for tacit and explicit knowledge transfer across organizations. According to prior studies,

2006 OctoberAcademy of Management Journal

labor mobility can facilitate innovation through the learning-by-hiring effect (i.e., knowledge accumula- tion through new employees due to knowledge dif- fusion; Song, Almeida, & Wu, 2003) and the social network effect (i.e., departing employees remain in contact with former colleagues for knowledge ex- change; Shipilov, Godart, & Clement, 2017). Conse- quently, a churning labor force can update the knowledge reservoir by infusing new knowledge, reducing information redundancy, and expanding the knowledge network. Owing to the increased va- riety of perspectives associated with the quickly updated knowledge reservoir, the effect of a HIWS on innovation may be strengthened.

Second, the churn in human resources also re- duces organizational stagnation, an obstacle that impedes a HIWS from generating innovation. Spe- cifically, stable and long-term employment tends to develop a shared schema that locks organizational members into the existing interest, culture, and re- lations embedded in the organization (Hannan & Freeman, 1984). Consequently, organizations with stagnant human resources tend to rely heavily on established routines and are less open to novel so- lutions (Sørensen & Stuart, 2000). As such, the churn in human resources can be viewed as a revitalizing process that increases the flexibility and adaptability of collective interactions (Shaw, 2011). Through the inflow and outflow of human resources, the work- force may reshape its collective interaction patterns and discover creative ways for resource deployment, facilitating a HIWS to promote innovation.

Third, the churn in human resources can improve organizations’ receptivity to creative solutions that are distant from or incompatible with the current routines. This is because the human resource flow can mitigate the tendency of local search, reduce the escalation of commitment in ongoing routines, and improve orga- nizational openness to divergent solutions (Rietzschel, Zacher, & Stroebe, 2016; Staw, 1981). Furthermore, the churn in human resources can reduce the formation of “groupthink” (Schneider, Goldstein, & Smith, 1995). As such, churning organizations are less narrow- minded or constricted in evaluating, processing, and absorbing knowledge and information. Therefore, in- novative changes are more likely to happen when a HIWS leverages churning human resources.

Hypothesis 4. The churn in human resources mod- erates the relation between an employee-experienced HIWS and innovation, such that this positive relation is more (vs. less) pronounced when the churn in hu- man resources is high (vs. low).

METHOD

Sample

We tested our hypotheses with the Workplace and Employee Survey (WES) data collected by Statistics Canada (Statistics Canada, 2009). The workplaces are akin to “establishments,” which refer to stand-alone entities with a business address (Takeuchi et al., 2009). The advantage of surveying establishments over firms is that multiple establishments of the same firm may pursue distinct business strategies and adopt different HRM systems. In addition, respondents in an estab- lishmentaremorelikelytoaccuratelyassessthespecific situations within the unit (Batt & Colvin, 2011). The WES consists of two parts: the Workplace Survey and the Employee Survey. This unique dataset links em- ployees to workplaces, enabling us to study the effect of employee-experienced HRM on workplace outcomes. Different sampling frames were used in the two parts of the WES. For the Workplace Survey, Statistics Canada used stratified random sampling by industry, region, and size to build a representative sample of workplaces in Canada. The sampled locations were followed over time, with new locations added every two years to re- place those that ceased to participate due to attrition. The primary respondent for the Workplace Survey was a workplace HR manager, except in small locations, where a general manager or business owner completed the survey. For the Employee Survey, Statistics Canada sampled participants from the surveyed workplaces and followed them for two years. Thus, fresh samples of employeesweredrawneveryotheryear.Amaximumof 12 employees were sampled at each workplace using a probability mechanism. Previous HRM researchers have published several studies using the WES data set (e.g., Shin & Konrad, 2017; Yanadori & van Jaarsveld, 2014; Zatzick & Iverson, 2006).

From the multi-wave WES data set (1999–2006), we selected the 2005–2006 waves to test our hypotheses, because the 2005–2006 waves included the most recent and complete set of variables used in the study and had the largest sample size across all the surveyed years. Specifically, the independent variables and control variables were measured in 2005 and the dependent variable (i.e., innovation) was measured in 2006. In or- ganizing the data for the current analyses, we excluded employees who did not provide answers to questions about HRM practices (16.28%). Further, guided by Yanadori and van Jaarsveld (2014), we excluded Em- ployee Survey responses from managerial employees (10.48%), because our research focuses on leveraging human resources of frontline employees. In addi- tion, we excluded workplaces with fewer than three

2018 2007Li, Wang, van Jaarsveld, Lee, and Ma

employee reports (5.37%), to obtain a more robust assessment of the within-workplace homogeneity in employees’ HIWS experiences. Finally, we excluded non-profit workplaces (14.01%), because our study focuses on for-profit organizations. Applying the above exclusion criteria, our research sample included 2,753 workplaces and 13,032 employees. After deleting ob- servations with missing values in variables of interest, our final sample consisted of 2,639 workplaces and 12,519 employees. The mean workplace size was ap- proximately 49 employees (SD 5 100.09) and the av- erage length that workplaces had been located at their current address was 19.32 years (SD 5 17.56).

Measures

Innovation (Workplace Survey in 2006). To mea- sure innovation, previous studies have adopted various approaches, including measuring innova- tion activities (e.g., patents; Sørensen & Stuart, 2000), innovation capability (e.g., Patel et al., 2013), and in- novation launches (e.g., Greve, 2003). We used two items from the Workplace Survey to measure in- novation launches: (1) product innovation—the work- place has introduced new products or services that differ significantly from previously produced goods or services; and (2) process innovation—the workplace has introduced new processes, including the adoption of new methods of goods production or service de- livery. Specifically, we coded workplaces that reported no product or process innovation as 0, workplaces that reported either product or process innovation as 1, and workplaces that reported both product and process innovation as 2.1,2

An employee-experienced HIWS (Employee Survey in 2005). Following Zatzick and Iverson (2006), we measured a HIWS with six HRM practices that are commonly used by organizations to involve employees: flexible job design, information sharing, problem-solving teams, self-directed teams, gain- sharing, and training (1 5 yes, 0 5 no). According to Zatzick and Iverson (2006), the six HRM practices were observed indicators that reflected the high- involvement approach to work design. However, in contrast to Zatzick and Iverson (2006), who used the Workplace Survey reported by managers to measure HIWSs, we used the Employee Survey reported by employees to evaluate employees’ experiences with a HIWS. To assess the construct validity of our measure, we performed a categorical indicator-based confirmatory factor analysis. The one-factor model resulted in a good fit to the data, x2 5 210.38, df 5 9, p , .01, comparative fit index 5 .97, Tucker–Lewis index 5 .95, and root mean square error of approxi- mation 5 .04. Cronbach’s alpha for the scale was .71, indicating that this is an acceptable measure. We calculated the employee-experienced HIWS for each workplace ( �X) by aggregating employees’ ratings of their individual HIWS experiences to the workplace level, using the formula listed below. In support of aggregation, rWG(J) was calculated for each work- place. The mean rWG(J) across workplaces was .57, indicating that the majority of workplaces displayed moderate to high within-workplace agreement in HIWS ratings (LeBreton & Senter, 2008). Further support for aggregating employee responses to a HIWS to the workplace level was provided by the interrater correlation coefficients: ICC(1) 5 .24, ICC (2) 5 .61. The one-way random-effect analysis of variance showed that there were significant vari- ances in the workplace-level means of HIWS ratings, F(2,752, 10,279) 5 2.53, p , .01.

�X 5 +

n i51Xi N

,       Xi 5 +

6 j51Xij

6 (1)

where i is the ith employee, j is the jth item, and N is the number of employee reports.

The homogeneity of HIWS experiences (Em- ployee Survey in 2005). The homogeneity of em- ployees’ HIWS experiences captures the extent to which employees present low variability in their HIWS experiences in the focal workplace. This measure was derived from employee responses to a HIWS using a dispersion model, a type of compo- sition model that specifies the functional relation- ships among constructs at different levels of analysis

1 Alternatively, innovation could be coded as a dichoto- mous measure (0 5 no product or process innovation, 1 5 had product or/and process innovation). We conducted a robustness check with this dichotomous innovation mea- sure using probit regression. The result pattern was virtually the same as the one reported here.

2 Our emergence-based HRM framework cannot suffi- ciently differentiate the influence of HRM on product in- novation and process innovation, as the mechanisms we propose are not specific to different types of knowledge creation (i.e., product vs. process). Therefore, in this study, we adopted a general innovation measure combining product innovation and process innovation to capture or- ganizations’ knowledge creation. We conducted a robust- ness check by treating product innovation and process innovation as two separate outcomes using probit re- gressions. The result patterns of both product and process innovation were virtually the same as the one reported here.

2008 OctoberAcademy of Management Journal

in multilevel research (Chan, 1998). In accordance with previous researchers, homogeneity can be assessed by either standard deviation or rWG(J) sta- tistics (Harrison & Klein, 2007; James, Demaree, & Wolf, 1993). Accordingly, we used both standard deviation and rWG(J) to measure the homogeneity of HIWS experiences. When standard deviation was used, to represent homogeneity and facilitate in- terpretation of our findings, we followed Koopmann, Lanaj, Wang, Zhou, and Shi (2016) by multiplying the standard deviation by 2 1 so that higher values represent higher levels of homogeneity. Our results were virtually the same for the two measures. Due to space constraints, we only present our findings using the first measure. It is noteworthy that, as our ho- mogeneity measure was derived from employee re- sponses to a HIWS, the range of homogeneity was restricted by that of an employee-experienced HIWS. As explained by Harrison and Klein (2007: 1214):

. . . because the SD of a within-unit distribution is of- ten lower when the mean is near the lower or upper bound . . . there may be an artifactual overlap of means and SDs across units. In short, mean and SD can be confounded.

Therefore, guided by Harrison and Klein (2007), we modeled the employee-experienced HIWS and the homogeneity of HIWS experiences simultaneously to address this range restriction issue.

The strategic importance of innovation (Work- place Survey in 2005). We measured the strategic importance of innovation with three items that re- flect the importance of innovation to the workplace business strategy. Specifically, in the Workplace Survey, managers rated the importance (from 1, of no importance, to 6, crucial) of the following innovative activities to the general business strategy of their workplaces: (1) undertaking research and develop- ment, (2) developing new products/services, and (3) developing new production/operating techniques. Cronbach’s alpha was .81 for this scale.

The churn in human resources (Workplace Survey in 2005). According to the labor economics literature (e.g., Burgess et al., 2000; Burgess, Lane, & Stevens, 2001), two groups of employees constitute the churn- ing labor force for a focal workplace (w) at a specific year (t): joiners (i.e., workers who were not employed at the workplace w at time t 2 1 and joined at time t) and leavers (i.e., workers who were employed at the workplace w at time t 2 1 and left at time t). Therefore, we measured the churn in human re- sources using the total number of joiners and leavers scaled by the total number of employees in

the workplace. Our measure corresponds closely with thedefinition of the churn in human resources, which captures the aggregate level of human re- sources that flow into and out of an organization. It is important to note that the churn in human re- sourcesis anemergentcollective construct describing the total quantitative flow of human resources. As such, this measure captures periodic changes in hu- man resources, a type of resource stock that orga- nizations need to manage across times (Barney & Wright, 1998).

Control variables (Workplace Survey in 2005). Based on previous HRM studies (e.g., Guthrie, 2001; Zatzick & Iverson 2006), we controlled for numerous workplace-level variables. Specifically, we con- trolled for workplace age (i.e., the length of years for which the workplace had been located at the current location), because workplaces that are able to endure may have a higher level of management quality (Guthrie, 2001). We controlled for workplace size (i.e., the total number of employees in the workplace) and profitability (i.e., workplace profit scaled by the total number of employees), because organizations with a larger operating scale and higher profitability are more likely to possess slack resources and man- agerial capability to implement a HIWS and launch innovation (Shin & Konrad, 2017). In addition, we controlled for union density (i.e., the proportion of employees covered by a collective agreement), be- cause workplaces with a higher degree of unioniza- tion may provide employees with more opportunities for involvement in the management process (Guthrie, 2001). Finally, following previous research (e.g., van Dalen, Henkens, & Wang, 2015; Zatzick & Iverson, 2006), we controlled for dichotomous industry sec- tors, to tease out establishment-level effects from potential industry-level effects.3

Analytical Strategy

Because the dependent variable—innovation—is ordinal, we conducted ordered probit regressions.

3 There were 14 dichotomous industry sectors: forestry, mining, oil and gas extraction; labor intensive tertiary manufacturing; primary product manufacturing; second- ary product manufacturing; capital intensive tertiary manufacturing; construction; transportation, warehousing and wholesale; communication and other utilities; retail trade and consumer services; finance and insurance; real estate, rental and leasing operations; business services; education and health services; and information and cul- tural industries.

2018 2009Li, Wang, van Jaarsveld, Lee, and Ma

To test the moderating effects (Hypotheses 2–4), three-step hierarchical regressions were used. In Step 1, only the control variables were entered into the regression model. In Step 2, we entered the control variables, the employee-experienced HIWS, and the three emergence enablers to gauge the main effects of independent variables. In Step 3, we en- tered the variables in Step 2 and the interaction terms to test the hypothesized moderating effects. For ease of interpretation, the control variables and inde- pendent variables were grand mean-centered. The interaction terms were the products of grand mean- centered independent variables. In estimating these models, we used the workplace survey weights pro- vided by Statistics Canada for the representativeness of sample estimates. We used Mplus 7.11 to conduct analyses (Muthén & Muthén, 1998-2012).4

RESULTS

Table 1 presents the descriptive statistics and correlations of our studied variables. Table 2 pres- ents the results of ordered probit regression models for innovation. Together, employee-experienced HIWS, the homogeneity of HIWS experiences, the strategic importance of innovation, and the churn in human resources accounted for 10.8% variance in predicting innovation above and beyond the control variables.

As shown in Model 2 (Table 2), HIWS was posi- tively and significantly related to innovation, b 5 1.55, p , .01. For employee-experienced HIWS, a one standard deviation increase from its mean resulted in a 2.2-percentage-point increase in the probability of having either product or process in- novation and a 7.5-percentage-point increase in the probability of having both product and process in- novation, supporting Hypothesis 1.

Further, the strategic importance of innovation was positively and significantly related to innova- tion, b 5 .20, p , .01. For the strategic importance of innovation, a one standard deviation increase from its mean resulted in a 2.4-percentage-point increase in the probability of having either product or process innovation and an 8.5-percentage-point increase in the probability of having both product and process innovation, demonstrating that workplaces were more likely to innovate when their strategic impor- tance of innovation was higher. In addition, the

churn in human resources was also positively and significantly related to innovation, b 5 .06, p , .01. A one standard deviation increase from its mean resulted in a 0.8-percentage-point increase in the probability of having either product or process in- novation and a 2.1-percentage-point increase in the probability of having both product and process innovation.

Model 3 presents the results for the hypothesized moderating effects. In Model 3.1 (Table 2), the three hypothesized interaction terms were entered into the regression models. In Model 3.2 (Table 2), we con- trolled for the three interaction terms among the moderators so that all six interaction terms were entered into the regression model simultaneously. Our main findings were virtually the same for the two models. For the purpose of brevity, the results we discuss focus on Model 3.2.

In Hypothesis 2, we expected that, when the ho- mogeneity of HIWS experiences was higher, the pos- itive relationship between employee-experienced HIWS and innovation would be stronger. As shown in Model 3.2, the interaction between employee- experienced HIWS and the homogeneity of HIWS experience was positive and significant, b 5 7.95, p , .01. To further examine this moderating effect, we plotted the interaction pattern in Figure 2. As shown in this figure, when the homogeneity of HIWS experience was higher, the positive effect of HIWS on the probability of innovation was stronger, providing support for Hypothesis 2.5

In Hypothesis 3, we hypothesized that the positive relationship between employee-experienced HIWS and innovation would be stronger when workplaces placed more emphasis on the strategic importance of innovation. According to Model 3.2, the interaction term between HIWS and the strategic importance of innovation was positive and significant, b 5 .45, p , .01. Further, as shown in Figure 3, when the strategic importance of innovation was higher, the positive effect of HIWS on the probability of having both product and process innovation was stronger. There- fore, we found general support for Hypothesis 3.

In Hypothesis 4, we expected the churn in human resources to strengthen the positive relation be- tween employee-experienced HIWS and innovation. According to Model 3.2, the interaction term between

4 We conducted a sensitivity analysis by controlling for the innovation baseline (2005) during the analysis. The results were similar to the ones reported here.

5 Following Hoetker (2007), we also examined Hypoth- eses 2–4 by plotting the marginal effects of the interactions. The results were consistent with the ones reported here. For the purpose of brevity, we only present cumulative probabilities in the figures.

2010 OctoberAcademy of Management Journal

T A B L E 1

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2018 2011Li, Wang, van Jaarsveld, Lee, and Ma

HIWS and the churn in human resources was positive and significant,b 5 .57, p , .01. The interactionplot is presented in Figure 4. As shown, when the churn in human resources was higher, the positive effect of HIWS on the probability of innovation was stronger. Thus, Hypothesis 4 was also supported.

DISCUSSION

Moving beyond HRM architecture, our study at- tempts to uncover the origin of innovation by in- vestigating the emergence-enabling process for an employee-experienced HIWS to give rise to in- novation. Developing an emergence-based HRM framework, our study reveals three distinct emer- gence enablers (i.e., the homogeneity of HIWS ex- periences, the strategic importance of innovation, and the churn in human resources) that facilitate an

employee-experienced HIWS to yield innovation. Below, we discuss the theoretical and practical im- plications of our research.

Theoretical and Practical Implications

Our emergence-based HRM framework furthers our understanding about the resource-based view in the HRM field (Barney & Wright, 1998). According to Colbert (2004), HRM can serve as a source of sus- tainable competitive advantage by cultivating het- erogeneous human capital resources through developing and nurturing interpersonal relations with causal ambiguity and social complexity. Nev- ertheless, we have limited understanding about the process through which HRM yields knowledge- based value creation, partly because it is nearly im- possible to directly explicate the configuration of

TABLE 2 Ordered Probit Regression Models for Innovation (2006)

Predictors (2005)

Model 1 Model 2 Model 3.1 Model 3.2

Estimate SE Estimate SE Estimate SE Estimate SE

Control variables Workplace age 20.01** .00 20.01** .00 20.01** .00 20.01** .00 Workplace size 0.26** .10 0.20* .10 0.20* .10 0.20* .10 Multi-plant firm 0.29 .18 0.28 .18 0.28 .17 0.28 .16 Profitability 20.004** .00 20.01** .00 20.01** .00 20.01** .00 Union density 20.28 .33 20.20 .32 20.20 .32 20.20 .32 Percentage of male employees 20.63 .39 20.61 .34 20.59 .32 20.58 .30 Percentage of full-time employees 0.32* .13 0.11 .24 0.08 .20 0.06 .20 Percentage of on-site employees 0.59** .16 0.57** .12 0.58** .11 0.57** .11 Average employee wage 20.10** .04 20.19** .04 20.22** .03 20.22** .03

Main effects Employee-experienced HIWS (HIWS) 1.55** .07 1.45** .07 1.45** .07 The homogeneity of HIWS experiences (Internal) 20.17 .14 20.36* .16 20.35* .14 The strategic importance of innovation (External) 0.20** .04 0.18** .04 0.18** .04 The churn in human resources (Temporal) 0.06** .01 0.01 .01 0.02 .01

Interaction terms Internal 3 External 20.30 .17 Internal 3 Temporal 20.17* .08 External 3 Temporal 20.02 .03 HIWS 3 Internal 7.68** .73 7.95** .69 HIWS 3 External 0.47** .06 0.45** .07 HIWS 3 Temporal 0.55** .12 0.57** .19

Intercepts Intercept 1 20.26** .01 20.27** .01 20.27** .01 20.27** .01 Intercept 2 20.81** .04 20.86** .04 20.87** .04 20.87** .04 R2 15.7% 26.5% 27.8% 28.0%

Notes: n 5 2,639. Unstandardized regression coefficients are reported. The workplace survey weights were used during the analyses. R2 was calculated using the continuous latent response variable approach (Snijders & Bosker, 2012), which is better than model fit-based pseudo R2

(e.g., Cox–Snell R2 andMcFaddenR2) in terms of indicating the effect sizes of the predictionin orderedprobit regression. Dichotomous industry sectors were controlled, but are not listed in the table (for brevity).

*p , .05 **p , .01

2012 OctoberAcademy of Management Journal

complex collective interactions. As Colbert and Kurucz (2011: 401) noted, the core of the resource- based view includes a paradox:

. . . those features of resources which create and pro- tect the essence of a sustained resource-based ad- vantage (i.e., characterized by causal ambiguity, based upon socially embedded, complex knowledge and capabilities), also make them inscrutable and unpredictable, and therefore difficult if not impossi- ble to engineer and manage.

However, our findings suggest that, although the “re- verse engineering” of collective interactions is almost impossible, organizations can manage the emergence of human resources by shaping the features of col- lective interactions(i.e., concertedness,direction, and adaptability), furthering our understanding about the microfoundations of the resource-based view.

For the internal mechanism, we investigated how the homogeneity of employees’ HIWS experiences shaped the HIWS–innovation relation. Our result demonstrated that the positive relation between a HIWS and innovation was stronger when em- ployees’ HIWS experiences were more homogeneous.

As Wright and Nishii (2013) stated, strategic HRM researchers primarily focus on examining the vari- ances across organizations, with far less attention be- ing paid to the variances within organizations (e.g., variability in employees’ HRM experiences), limiting our understanding about the cross-level na- ture of organizational phenomena. As one of the first empirical studies examining the moderating role of homogeneity in employees’ HRM experiences, we demonstrated the importance of introducing within- organization variances in understanding the process for HRM to impact organizational outcomes. In addi- tion, it is important to note that our focus on the ho- mogeneity of employees’ HRM experiences diverges from Bowen and Ostroff’s (2004) focus on HRM sys- tem strength. Specifically, “HRM system strength” refers to the extent to which an HRM system sends unambiguous messages about the responses and be- haviors that are expected, rewarded, and valued by the organization (Ostroff & Bowen, 2016). In other words, it is based on whether employees share an understanding about organizations’ desired work be- haviors. By contrast, our study focuses on the vari- ability of employees’ HRM experiences, rather than

FIGURE 2 The Interaction between Employee-Experienced HIWS and the Homogeneity of HIWS

Experiences on Innovation

50%

45%

40%

35%

30%

25%

20%

15%

10%

5%

0% Low High

Probability (Innovation = 2) at Low Homogeneity of HIWS Experiences (M – 1SD)

Probability (Innovation = 1) at Low Homogeneity of HIWS Experiences (M – 1SD)

Probability (Innovation = 2) at High Homogeneity of HIWS Experiences (M + 1SD)

Probability (Innovation = 1) at High Homogeneity of HIWS Experiences (M + 1SD)

Employee-Experienced HIWS

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their shared understanding of desired work behaviors signaled by the HRM system.

For the external mechanism, our finding demon- strated that high strategic importance of innova- tion amplified the positive relation between an employee-experienced HIWS and innovation. Prior studies on the strategic contingency of HRM have mainly focused on the alignment of HRM systems with competitive strategies (e.g., differentiation vs. cost leadership; Huselid, 1995). As summarized by Jackson, Schuler, and Jiang (2014), empirical find- ings on the moderating roles of competitive strate- gies have been inconsistent, which might reflect the fact that firms achieve their strategy through various ways (e.g., firms can pursue a differentiation strategy by focusing on innovation or quality management) and the measures of business strategies often ignore different strategic priorities. Our study distinguishes from previous research in that we push beyond competitive strategies to directly capture organiza- tions’ strategic need and priority regarding innova- tion. By directly examining the strategic importance of innovation, our study contributes to the strategic contingency of HRM.

For the temporal mechanism, we introduced the concept of churn to the HRM literature to investigate how human resource flow shaped the relation be- tween HIWSs and innovation. It is important to note that the churn in human resources is an emergent construct that describes the total quantitative human resource flow, regardless of the qualitative changes associated with employee departures and re- placements (Nyberg & Ployhart, 2013). Our finding demonstrated that the churn in human resources amplified the positive effect of an employee- experienced HIWS on innovation by improving the adaptability associated with collective interactions. Our findings suggest that the departures of existing employees and the addition of new employees may benefit innovation by reducing organizational stag- nation and increasing the variety of perspectives in the organization. However, it is also possible that employee mobility has a negative influence on op- erating efficiency, due to the disruption of existing routines and the loss of accumulated experience and expertise (Burmeister & Deller, 2016; Shaw, 2011; Shaw, Park, & Kim, 2013). Therefore, when it comes to organizational performance, the churn in human

FIGURE 3 The Interaction between Employee-Experienced HIWS and the Strategic Importance of

Innovation on Innovation

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Probability (Innovation = 2) at High Strategic Importance of Innovation (M + 1SD)

Probability (Innovation = 1) at High Strategic Importance of Innovation (M + 1SD)

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resources may function as a double-edged sword. One relevant study that helps explain the tension between efficiency and innovation was conducted by Argote, Insko, Yovetich, and Romero (1995), who found that the negative effect of human resource churn on work group performance was less pro- nounced for complex (vs. simple) tasks. They attrib- uted this difference in the human resource churn’s effect to the fact that performing complex tasks re- quires a greater level of innovation.

For managerial practice, this study informs the central role that HRM plays in promoting innovation. For organizations that are actively competing by in- novating, we demonstrated the importance of apply- ing a HIWS to elicit collective interactions for knowledge exchange and aggregation. Further, in fa- cilitating a HIWS to generate innovation, we suggest that organizations need to systematically manage the emergence-enabling process for the aggregation of human resources. Specifically, according to our re- searchfindings,thehomogeneityof employees’ HIWS experiences amplifiedthe positive effect of a HIWSon innovation, indicating that organizations could ex- tract additional value from HRM by implementing a HIWS uniformly across employees. Yet, if an

organization is trying to compete on the basis of in- novation, simply focusing on HRM systems is far from enough. In particular, based on our research findings, a HIWS could better promote innovation when orga- nizations attached more strategic value to innovation. As such, organizations should have clear strategic goals and recognize the potential value of innovation in support of their goals. In addition, organizations ought to clearly communicate their strategic needs to the workforce to ensure that employees’ collective efforts are channeled toward the right direction. Fi- nally, this study demonstrated the importance of maintaining a dynamic workforce to refresh the knowl- edge reservoir and improve organizational adapt- ability. Therefore, firms should take a dynamic perspective and actively manage the inflow and out- flow of employees over time.

Limitations and Future Directions

Our study has several limitations. First, we ana- lyzed archival data collected by Statistics Canada, so our measures were constrained by the survey ques- tions in the WES. In particular, with a dichotomous measure, we only evaluated the existence of

FIGURE 4 The Interaction between Employee-Experienced HIWS and the Churn in Human Resources on Innovation

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Probability (Innovation = 1) at Low Churn in Human Resources (M – 1SD)

Probability (Innovation = 2) at High Churn in Human Resources (M + 1SD)

Probability (Innovation = 1) at High Churn in Human Resources (M + 1SD)

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employees’ experiences with a HIWS and were un- able to adequately capture the extent to which each HRM practice was implemented across employees. Nevertheless, by aggregating employee responses to the workplace level, our measure reflected the cov- erage of a HIWS among employees. Further, when examining human resource flow, we only focused on the quantity of employee mobility and were unable to evaluate the quality of employee mobility, limiting our understanding about the inner workings of hu- man resource flow (Nyberg & Ployhart, 2013). In ad- dition, our measure for innovation was also restricted by the available survey questions. Because the two items used to measure innovation were dichotomous, we were unable to adequately capture the level of product and process innovation.

Second, the scope of the WES measures restricted our ability to directly test the mediating processes for proposed emergence enablers to amplify the benefi- cial influence of a HIWS on innovation. Therefore, to gain in-depth understanding regarding the emer- gence process of human resources, we suggest that researchers conduct field studies to empirically test the inner workings of the three emergence enablers. For example, researchers could build a moderated mediation model to examine the potential mediators (e.g., transactive memory system, interpersonal com- munication, and collective cohesion) through which the emergence enablers shape the HIWS–innovation relation.

Third, due to the limitation of the WES data set, we were unable to distinguish between exploitative in- novation and explorative innovation, both of which are critical for organizational adaptation. Whereas “exploitative innovation” seeks to exploit existing products or services by leveraging current knowl- edge and competencies, “explorative innovation” develops new products or services by pursuing fun- damentally new knowledge and capabilities (Benner & Tushman, 2003). Therefore, we raise an important research question about whether the two types of innovation differ in terms of their human capital re- source emergence processes.

In this study, we used the homogeneity of HIWS experiences, the strategic importance of innovation, and the churn in human resources to probe and test the emergence-enabling mechanisms for innovation. We acknowledge that other organizational factors might also shape the patterns of collective in- teractions. Thus, an important area for future re- search will be to move beyond the three studied variables to identify other factors that can either fa- cilitate or inhibit the emergence of human resources

cultivated by HRM systems. For example, future re- search might consider the developmental stages of organizations and investigate how organizational life cycles (e.g., organizational initiation, functional growth, controlled growth, and strategic integration; Milliman, Von Glinow, & Nathan, 1991) shape the HIWS–innovation relation by influencing the adaptability associated with collective interactions. For example, compared with those at later develop- mental stages, organizations at earlier developmen- tal stages may be more sensitive to environmental changes and open to knowledge transfer. Thus, these organizations are more likely to innovate when tak- ing advantage of a HIWS. We hope our emergence- based HRM framework can stimulate more in-depth work adopting the lens of emergence to study organization-level phenomena.

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Yixuan Li ([email protected]) is an assistant pro- fessor in the Krannert School of Management at Purdue University. She received her PhD in Management from Warrington College of Business at the University of

Florida. Her research interests include strategic human resource management, learning and innovation, work groups and teams, and workplace diversity.

Mo Wang ([email protected]) is the Lanzillotti- McKethan Eminent Scholar chair at the University of Florida. He received his PhD in industrial–organizational psychology and developmental psychology from Bowling Green State University. His research interests include older worker employment and retirement, newcomer and expatriate adjustment, occupational health psychol- ogy, teams and leadership, and advanced quantitative methods.

Danielle D. van Jaarsveld ([email protected]) is the E.D. MacPhee chair in Management at the University of British Columbia’s Sauder School of Business. She re- ceived her PhD from Cornell’s ILR School. Her research interests include organizational and employee outcomes in services, nonstandard work arrangements, and strategic human resource management.

Gwendolyn K. Lee ([email protected]) is the Chester C. Holloway professor at the University of Florida. She holds a PhD in business administration from the University of Cal- ifornia at Berkeley, and MS and BS degrees in chemical en- gineering from the Massachusetts Institute of Technology. Focusing on entry and exit dynamics, her research examines strategies for competition, cooperation, innovation, and entrepreneurship.

Dennis G. Ma ([email protected]) is a doctoral student in the Organizational Behavior and Human Re- sources division at the Sauder School of Business at the University of British Columbia. His research interests in- clude technology, innovation, entrepreneurship, labor mar- ket dynamics, and resource distributions.

2018 2019Li, Wang, van Jaarsveld, Lee, and Ma

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