Human Capital Resources: Reviewing the First Decade and Establishing a Foundation for Future Research

HCR Definition

Prior to 2011, most research related to the concept we now know as HCR used human capital theory (Becker, 1964) combined with the resource-based view (RBV; Barney, 1991) to explain how human capital functioned as a resource, such as considering average or total levels of knowledge, experience, or education within a firm or unit (e.g. Hatch & Dyer, 2004; Hitt, Bierman, Shimizu, & Kochhar, 2001). Early research established the positive relationship between summative human capital and collective outcomes (Coff, 1997), illustrating the importance of the collection of individuals’ knowledge, skills, abilities, and other characteristics (KSAOs) to achieving competitive parity and advantage (Barney & Wright, 1998). In parallel, strategic human resource (HR) management researchers focused on how HR policies and practices (e.g., high performance work systems; Huselid, 1995) could impact firm performance, presumably by improving the collective human capital in organizations (Jiang, Lepak, Hu, & Baer, 2012; Ployhart, 2012). However, research streams did not examine HCR as a unique construct and often assumed or inferred emergence or synergies across levels (e.g. “the black box” in strategic HR research; Nyberg, Reilly, Essman, & Rodrigues, 2018). This is not surprising given that human capital theory is an individual-level theory that was not intended to explain how changes to human capital across levels make it unique from individual human capital. Likewise, RBV largely ignored human features (for an exception, see Coff, 1997) or the microfoundations that made HCR distinct from other resources (Nyberg et al., 2014). Thus, it became clear that prior theories were ill-equipped to fully explain how human capital becomes a collective resource to affect unit outcomes (Ployhart & Moliterno, 2011).

The lack of theoretical framework led to specific challenges to defining and conducting HCR research. First, individual-level constructs often change across levels due to social processes and structures (Kozlowski & Klein, 2000), making assumptions of isomorphism between individual (e.g., human capital) and collective (e.g., HCR) constructs inappropriate (Bliese, 2000; Kozlowski & Klein, 2000). Second, the use of RBV, which encapsulates all resources, clouded the nomological network of how human capital emerges to become an HCR, meaning that there was little understanding of how HCR may be distinct from other resources (Ployhart et al., 2014). Third, the variety of topics and fields forming the field of HCR (e.g., economics, strategy, HR, psychology, sociology) leads to conflicting assumptions and perspectives, making it difficult to find agreement and necessitating a broad, flexible framework to conceptualize HCR.

Responding to these challenges, Ployhart et al. (2014: 374) integrated prior definitions to establish an inclusive HCR definition: “individual or unit-level capacities based on individual [knowledge, skills, abilities, or other characteristics (KSAOs)] that are accessible for unit-relevant purposes.” The term capacities refers to the potential to produce outcomes and keep resources distinct from firm performance, while accessible for unit-relevant purposes means that HCR exists as features of units, contributing to pursuing the unit's purpose (Ployhart et al., 2014). Recent definitions have not deviated substantially (Nyberg et al., 2019), and hence, we too remain close to the origins of the definition (see Ployhart et al., 2014, Table 1: 375).

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Table 1

Key Terms and Definitions in the Field of HCR

Term	Definition	Representative Cite(s)
Human capital resource (HCR)	Individual- or unit-level capacities based on individual KSAOs that are accessible for unit-relevant purpose.s	Ployhart et al., 2014
Human capital	“Productive capacities of human beings as income producing agents.”	Becker, 1964; Rosen, 1989
Knowledge, Skills, Abilities, and Other characteristics (KSAOs)	KSAOs underlie components of human capital because they are the individual attributes that employees must have to perform a particular task. KSAOs are as follows: knowledge—the factual or procedural information necessary for performing a specific job and the foundation on which skills and abilities are developed; skills are the individual's level of proficiency and capabilities to perform a specific job task; ability is a more enduring capability (usually cognitive) that is necessary for an individual to perform a job; and other characteristics often refer to personality traits or other attributes that affect the individual's ability to perform a specific job.	Noe, Hollenbeck, Gerhart, & Wright, 2006
Emergence
Compilation emergence	Based on cross-level combinations of different types of KSAOs.	Kozlowski & Klein, 2000; Ployhart & Moliterno, 2011
Composition emergence	Based on cross-level average of some KSAOs	Ployhart et al., 2014
Emergence enabling states	Unit characteristics “that are typically dynamic in nature and vary as a function of [unit] context, inputs, processes, and outcomes” (p. 357)	Marks et al., 2001
Cognitive EES	“The unit's climate, memory, & learning.” (Ployhart & Moliterno, 2011: 138)	Hinz, Tindale, & Vollrath, 1997; Ployhart & Moliterno, 2011
Affective EES	“The emotional ‘bonds’ that tie unit members together; they are what individuals ‘feel’ like when they are part of a group” (Ployhart & Moliterno, 2011: 139)	Hackman, 1987; Kozlowski & Ilgen, 2006; Ployhart & Moliterno, 2011
Behavioral EES	“Coordination, communication, and regulatory processes that make individuals’ behavior interdependent” (Ployhart & Moliterno, 2011: 138)	Hackman, 1987; Kozlowski & Ilgen, 2006; Ployhart & Moliterno, 2011
Fit
Single Dimension	“The compatibility between an individual and a specific aspect of the work environment.” Different fit dimensions include: Person-Vocation (PV), Person-Job (PJ), Person-Organization (PO), Person-Group (PG), and Person-Person (PP).	Jansen & Kristof-Brown, 2006
Multidimensional Fit	Person-Environment (PE) fit incorporates all five dimensions (i.e., PV, PJ, PO, PG, and PP fit)	Jansen & Kristof-Brown, 2006
Matching	Process for dynamically aligning individuals with organizations and the situations (roles, jobs, tasks, etc).	Weller et al., 2019
Complementarities	When a resource (e.g., HCR) combines with other resources (e.g., social capital) to create a surplus over the sum of the amounts of value they could create independently.	Adegbesan, 2009
Social capital	“Resources contained within, available through, and derived from the network of relationships possessed by an individual or social unit” (p. 243)	Nahapiet & Ghoshal, 1998

However, we highlight a few aspects of the definition to establish construct clarity before we discuss potential challenges of the definition and how it has been applied in the literature. First, HCRs are by definition derived from human capital—the relevant KSAOs of individuals. Second, collective HCR necessarily emerges from individual human capital such that the unit-level HCR and thus the process where synergies generated can make HCR distinct from underlying human capital are essential for the formation of HCR (Ployhart & Moliterno, 2011). Thus, this definition of HCR distinguishes it from related constructs (e.g., human capital, organizational capabilities) while remaining broad enough to capture the wide-range of possible HCRs. Although this broadness can be beneficial, the level of abstraction can also facilitate challenges in conceptualizing and measuring the construct.

Scope of Review

To better understand the current state of HCR research and outline a path forward, we conducted a detailed literature review from 2011 through 2020 using EBSCO to search the terms: Human capital*, human capital resource*, and strategic human capital* in the Academy of Management Journal, Academy of Management Review, Academy of Management Annals, Academy of Management Perspectives, Administrative Science Quarterly, Harvard Business Review, Human Relations, Human Resource Management, Journal of Applied Psychology, Journal of Management, Journal of Management Studies, Management Science, Organizational Behavior and Human Decision Processes, Organizational Science, Organizational Studies, Sloan Management Review, and Strategic Management Journal. Additionally, we reviewed the references of these publications and in-press articles in these journals for additional articles.

From the 489 potential articles, we eliminated articles that fell outside the scope of this review based on several conditions [details of the review process, including PRISMA flow diagram (Page et al., 2021) can be found in the online appendix]. First, we eliminated articles that were unrelated to HCR. The term human capital can refer to human capital or HCR research given that some scholars have not adopted the term human capital resources. Thus, while it was necessary to include the term human capital in our search, if the article did not conceptualize human capital as a resource that could be used by the unit (e.g., articles that do not address how individuals’ KSAOs combine to form a collective construct), or if it did not link human capital to a collective outcome (e.g., unit or firm performance), it was not included in the review (examples of excluded articles: Goldenberg, Saguy, &d Halperin, 2014; Howard-Grenville, Metzger, & Meyer, 2013). To make this determination, the first two authors read each article in detail and discussed any disagreements. Additionally, we also included articles that examined the creation or outcomes associated with collective KSAOs (e.g., “collective intelligence”; McHugh et al., 2016), even if they did not explicitly use the term human capital resources. This approach allowed us to seek all research that contributes to our understanding of the field of HCR given that the term is relatively new compared to individual-level work on human capital (e.g., Becker, 1964) and to account for the fact that literature that informs HCR cuts across domains where terminology may differ. Second, we did not review research on the potential contained in individuals’ KSAOs, or the KSAOs that are part of individuals but may not be relevant or accessible for unit-level purposes (Ployhart et al., 2014). While relevant to the creation of HCR, this individual-level research rarely focuses on HCR (Ployhart, 2015). Potential may also refer to potential generated through systems, policies, or practices. Research on HR systems is vast, and to focus directly on the subset of research that examines the relationship between HR systems and HCR, we review research on how HR systems impact HCR but not how HR systems develop individual-level human capital (examples of excluded articles: Chen, Zhang, & Fey, 2011; Horwitz, 2013). Third, because we want to understand the relationship between HCR as a resource and business unit and/or firm outcomes, our review focuses on HCR research that conceptualizes HCR as existing at the business unit level. While individual-level human capital and team levels can sometimes be classified as HCR because they can be linked directly to collective outcomes (Moliterno & Nyberg, 2019), the bulk of research and thus the focus of our review is on understanding collective HCR, or the unit-based capacities that are accessible for unit-relevant purposes (Ployhart et al., 2014). These issues are most core to understanding HCR because they necessitate an understanding of the complex multilevel processes that are required to effectively combine and utilize individuals as resources in groups. So while some rare individuals (e.g., CEOs, stars) and teams (e.g., top managment team (TMT)) can sometimes be conceptualized as HCR, they are generally situated in their own robust literatures and have already been extensively reviewed (e.g., Call, Nyberg, & Thatcher, 2015b) and therefore are not included in this review (examples of excluded articles: Bidwell, Won, Barbulescu, & Mollick, 2015; Bonner & Baumann, 2012; Giordano, Patient, Passos, & Sguera, 2020).

After reading each article, we included 194 articles, 120 of which are empirical. Our review was developed iteratively from our past knowledge of this research combined with a detailed review of the 194 articles. As we conducted our review, it became clear that there were three areas or domains within HCR research (creation, conceptualizations and measurement, and outcomes). Consequently, in the following sections we structure our review, beginning with a discussion of the theoretical advancements in HCR research around these three domains. In doing so, we highlight the research silos that exist, highlight critical gaps in each of these silos, and identify opportunities where future researchers can integrate across these topics. We provide a table of commonly used terms and definitions in the field of HCR (Table 1).

HCR Creation

Prior to 2011, the origins of HCR were virtually unknown because research did not distinguish between collective human capital and HCR. To challenge prior summative approaches to human capital, multilevel theories were incorporated to identify the process of HCR emergence that distinguished HCR as a unique multilevel construct. Multilevel theory refers broadly to theories or perspectives that span multiple levels of analysis (e.g., individual, collective; Chan, 1998; Kozlowski & Klein, 2000), and specific topics within multilevel theory have been used to explain how HCR originates from individuals’ human capital but is distinct due to changes that transform or amplify human capital across levels. Specifically, micro scholars tend to focus on emergence—“the result of bottom-up processes whereby phenomenon and constructs that originate at a lower-level of analysis, through social interaction and exchange, combine, coalesce, and manifest at a higher collective level of analysis” (Kozlowski 2012: 267)—and macro scholars have used the term microfoundations to unpack collective constructs to understand how individual-level constructs impact organizations (Felin, Foss, & Ployhart, 2015). Ployhart and Moliterno (2011) built from these perspectives to develop the HCR emergence process. Later research built on this approach by identifying specific models of HCR emergence, further distinguishing HCR from human capital (Ployhart et al., 2014). Recently, Wolfson and Mathieu (2018) extended theory on HCR emergence to incorporate the role of multilevel complementarities in their theory of human capital resource complementarity (HCRC). They suggest that the alignment between individuals and dynamic situational features (i.e., task type) across levels predict an individual's performance. Their work suggests that the synergies generated through HCR emergence can exert a top-down influence on the behaviors and outcomes of individuals. In tandem, theoretical advancements on emergence have emphasized the importance of a multilevel view of HCR and consideration of the synergies generated as human capital combines across levels.

While the most meaningful theoretical advancement to understanding the creation of HCR has been the integration of multilevel theory, researchers are beginning to incorporate additional theories to build more nuanced understandings of how HCR is created. One such theoretical advancement involves applying fit and matching theories to HCR. Matching refers to the process by which individuals are dynamically aligned with organizations and the situations (Weller, Hymer, Nyberg, & Ebert, 2019). To this end, Weller and colleagues developed a conceptual model that explains how dynamic matches between individuals and their environment (i.e., job, situation, role, task) contribute to the generation of human capital-based value. Using attraction, selection, attrition (ASA)–based logic (Schneider, 1987), they posit that at different stages of firm adjustment (selection, adaptation, deselection), both individuals and organizations can negotiate optimal roles for individuals within units through development or reconfiguration (e.g., transfer), and those with poor fit may be pushed or pulled out of the firm. Thus, their model suggests that the potential value gained through individuals’ KSAOs changes based on context. Integrating theory on fit and matching into research on HCR recognizes that who the individuals are (including their KSAOs) matter and results in different forms of HCR development.

Theory on the creation of HCR has also been advanced by considering how human capital inflows and outflows contribute to the formation of HCR. These perspectives explicitly consider the temporal fragility of HCR, examining ways that the loss or gain of human capital may have rippling effects on HCR. One such theory, context-emergent turnover (CET) theory, explains how collective turnover can deplete HCR (Nyberg & Ployhart, 2013). HCR researchers have used CET to explain how collective turnover is linked to losses in the quantity or quality of HCR (Call, Nyberg, Ployhart, & Weekley, 2015a) and to the creation of HCR, including how replacements may (or may not) replenish the stock of HCR (Reilly, Nyberg, Maltarich, & Weller, 2014). Another contribution involves research that explains how mobility can enhance or deplete KSAOs contained in HCR to affect unit outcomes (Mawdsley & Somaya, 2016).

Lastly, theory on HCR creation has been advanced by incorporating social capital theory into research on HCR emergence. Recently, Ray, Nyberg, and Maltarich (in press) introduced Human Capital Resources Emergence theory to address the social component of HCR emergence. Specifically, the authors argue that the structure and content of the social relationships within units determines the amount of HCR that emerges. This work suggests that emergence is dependent not only on the task environment but also on the nature of the social relationships that may develop. This work completements prior work that has recognized the connection between human and social capital theories. For instance, researchers have contributed theory on the role of social capital in the formation of human capital (Methot, Rosado-Solomon, & Allen, 2018) and called for attention to the relationship between social capital and HR systems and practices (Soltis, Brass, & Lepak, 2018). While these advancements have brought more attention to the link between human and social capitals, social mechanisms play a central role in transforming human capital into HCR (Kozlowski, 2012), and thus, continued pursuit of research explaining how social relationships form, alter, or change HCR will help provide additional clarity to our understanding of the HCR emergence process.

HCR Outcomes

In the past decade, most theoretical work relating HCR to collective outcomes continues to rely on RBV as a theoretical framework (e.g. Liu, Van Jaarsveld, Batt, & Frost, 2014). However, some recent work has tried to disentangle HCR's effect on performance from other constructs and to understand the relationship between HCR and other collective constructs. One way researchers have disentangled HCR from related constructs is by incorporating theories that acknowledge unique features of HCR and how those unique features are related to outcomes. For instance, some scholars have used knowledge-based view (KBV; Grant, 1996) to explain how HCR is related to firm outcomes. For instance, Sung and Choi (2018) use KBV to explain why the stock and flow of unit knowledge can be used to improve firm innovation. The diversity of knowledge in HCR can also be used to improve firm performance (Demirkan & Demirkan, 2012), suggesting that both the flows and content of knowledge-based HCR can uniquely affect outcomes. Researchers have also made progress distinguishing HCR from other resources, such as organizational capabilities. For instance, Collins (2020) distinguishes HCR from firm strategy and suggests that HCR can only be used toward competitive advantage when well aligned with CEO's understandings and efforts toward achieving firm strategies. Additionally, conceptual work has also begun to explain how isolating mechanisms may protect potential competitive advantages gained from HCR (Mahoney & Kor, 2015). For instance, some researchers have drawn on theories on firm specificity (e.g., Coff and Kryscynski, 2011) to explain how it acts as an isolating mechanism to keep HCR intact. However, the role of firm specificity in HCR remains contentious.

In the future, research should continue moving beyond RBV to expand our understanding of how HCR is connected to collective outcomes. A strength of the HCR field is that it has been built through the diverse combination of scholars in different interest areas. Understanding HCR requires understanding how the full complexity of individuals affects unit value, or the collective contributions made toward performance. However, while the HCR field has been inclusive of a wide range of literatures, future theory needs to be clearer about how literatures and new theories fit in the HCR field. Specifically, literature on HR systems is often integrated into HCR literature without explaining how it applies to HCR research. For example, HR research may focus on selecting or training as they relate to the accumulation of individual human capital (e.g., how recruiting or hiring practices can attract employees with more or better KSAOs; Ployhart, Schmitt, & Tippins, 2017); however, few articles focus specifically on HR practices or systems and how they impact the HCR emergence (Nyberg et al., 2018). Also, future research should follow the example of researchers who use KBV to explain how knowledge-based HCR relates to collective outcomes by providing greater specificity in developing HCR theory—for instance, by building or extending theory to link other pieces of HCR, such as skills-based HCR or abilities-based HCR, to collective outcomes. More specific attention to unique theories and mechanisms that drive the relationship between skill, ability, and other aspects of HCR will be useful for better understanding how HCR relates to outcomes.

HCR Creation

The first category in our model is HCR creation, or research focused on understanding how HCR is formed within units. We reviewed 73 empirical articles in this category, the bulk of which focused on understanding HCR emergence, the internal process that transforms individual-level human capital into collective HCR, and potential influences on the HCR emergence process. Recent relevant research has also started exploring whether HCR may be obtained from external sources, such as comobility, where individuals move to a new unit as a group (Campbell, Saxton, & Banerjee, 2014; Marx & Timmermans, 2017). Together, research in this category focuses on the processes that create HCR within units. Hence, our review led us to focus on three primary areas within the HCR creation space: emergence, influences of the emergence process, and comobility or obtaining HCR from external sources.

Conceptualizations and Measurement

The second aspect of Figure 1 is HCR conceptualizations and measurement (46 articles), or the specific features researchers include in conceptualization, measurements, and definitions of HCR. Research in this area focuses on the type of HCR (e.g., KSAOs that compose the HCR) and the specificity of the HCR (e.g., firm-specific, unit-specific). Although defining and understanding HCR is an overlapping interest shared by both those interested in the creation of HCR and the outcomes associated with HCR, research rarely provides precise HCR definitions, depictions, and measurements (Nyberg et al., 2014). Instead, researchers typically use proxies, such as education or experience, or do not directly measure HCR, and instead assume that changes to the unit (such as turnover) change the HCR (e.g., Call et al., 2015a; Reilly et al., 2014). We found that in many cases, the HCR is not directly measured but assumed to exist. These inconsistencies can be partially attributed to the newness of the field and the integration of terminology and empirical approaches across a variety of disciplines that contribute to the field. However, it remains clear that most research lacks precision in conceptualizations of collective KSAOs, inhibiting our ability to understand what HCR is and how it is measured.

HCR Outcomes

The third section in Figure 1 is the outcomes of HCR (86 articles). Research in this category refers to the collection of research focused on explaining the relationship between HCR and collective outcomes. Research focuses on how HCRs are connected to outcomes, why they are valuable, and external pressures that may shape the value of HCR. This work is grounded primarily in RBV and focuses on the relationship between HCR and objective performance (e.g. Ganco et al., 2020; Jansen, Simsek, & Cao, 2012), behavioral outcomes (e.g. Avery, Mckay, & Hunter, 2012), as well as boundary conditions between HCR and collective outcomes. This includes research examining how individuals (Fu, Flood, Rousseau, & Morris, 2020) or environments (Makarius & Stevens, 2019) directly or indirectly shape how HCR is used within units or firms. Our review revealed that two outcomes, objective performance and behavioral outcomes (i.e., collective behaviors), were frequently explored in HCR literature, and we highlight several influences between the relationship between HCR and these outcomes.

Creation

Overall, our review identified that empirical research on HCR creation lags behind conceptual work. Hence, a general recommendation for future research is to empirically test existing conceptual and theoretical HCR work. Beyond this broad recommendation, we identify five specific research directions involving the creation of HCR, of which understanding the nature and processes associated with HCR emergence is the most underserved and most pressing.

First, future research would benefit from increased precision in theoretical and empirical examinations of the nature of HCR emergence. Ployhart and Moliterno (2011) provide the foundation for theorizing about HCR emergence by asserting that individual-level human capital is transformed into HCR through an emergence process. However, our understanding of HCR emergence has not moved much beyond this perspective, limiting our ability to understand complex conceptions of HCR emergence (Eckardt & Jiang, 2019; Cannella & Sy, 2019). For instance, future research should investigate the possibility of simultaneous HCR emergence processes. Ployhart et al. (2014) suggest that because HCR is based on a variety of KSAOs, it is likely that multiple HCRs exist in a unit. Yet we found no empirical work that tested the existence of multiple HCR emergence processes. This leaves lingering possibilities regarding whether the HCR process needed to create collective knowledge differs from processes that create collective abilities and whether these separate emergence processes occur simultaneously or if a multidimensional HCR encompassing all the units’ KSAOs can emerge from a singular emergence process. Investigation into the existence of multiple HCR emergence processes also allows comparisons of multiple HCR dimensions (e.g., knowledge-based HCR, skill-based HCR) or types of multilevel combinations (e.g., compilation, composition) in the HCR emergence process, including the unique mechanisms that may be required in each of these processes.

Second, future research should carefully consider what facilitates HCR emergence; for instance, by incorporating individual autonomy in considering HCR creation. While individual human capital provides the foundation for HCR, research rarely considers decisions to share (or not) relevant KSAOs. Some literatures distinguish between potential and actual resources and behaviors (e.g., social capital; Adler & Kwon, 2002) and show that individuals often differ in their willingness to participate and share their human capital (Belenzon & Schankerman, 2015). For instance, individuals sometimes hide knowledge if they are distrustful (Connelly, Zweig, Webster, & Trougakos, 2012) or may downplay their skills or abilities to avoid hostile reactions from envious others (Exline, Single, Lobel, & Geyer, 2004). Thus, even when companies select and retain employees with high levels of human capital, there is no guarantee that the human capital will be shared or put to productive use. Compensation research shows that companies can use incentives to overcome barriers to motivate individuals to leverage their skills on behalf of the unit (Brown, Nyberg, Weller, & Striver, in press; Gerhart & Feng, 2021), yet it is unclear how individuals’ motivation and incentives combine to alter how potential human capital may be made available to be transformed into HCR (Gerhart, 2019; Nyberg & Reilly, 2019). A meta-analysis combining the ability-motivation-opportunity model and HR practices illuminates one connection between autonomy and human capital development by examining relationships among human capital, motivation, and HR practices. Different types of HR practices impact human capital development and motivation in different ways, suggesting that the HR practices needed to develop motivation are distinct from the practices needed to build human capital (Jiang et al., 2012). However, future research should go much further in developing and testing theory that explains when and how human capital is made available to the unit for emergence.

Additionally, future researchers should more clearly consider additional antecedents to the creation of HCR. While some research suggests that HR systems and practices may be an antecedent of human capital (Kehoe & Collins, 2017), literature on HCR is much less clear in establishing whether HR systems and practices can act as antecedents to the HCR emergence process or as an influence on the HCR emergence process. It remains unclear how other potential antecedents affect the creation of HCR, such as compensation, CEOs, or managers. Thus, while we know that practices, systems, and managers play a role in how HCR is deployed or used once it emerges, there is limited attention to these influences as antecedents to the creation of HCR. Future research should more fully investigate the creation of HCR.

Third, research claiming HCR emergence has primarily focused on the creation of positive synergies through the HCR emergence process. While we found growing empirical evidence of positive synergies in HCR emergence (e.g., Crocker & Eckardt, 2014; Eckardt, Crocker, & Tsai, 2020), it is unclear when or if HCR emergence can lead to negative synergies (Sundaramurthy et al., 2014), where the combination of individuals leads to an HCR that creates lower levels of collective outcomes than would be expected from the aggregate of individuals alone (see Steiner, 1972, on process loss). Because HCR emergence relies on interactions between individuals, it is possible that increased interactions may not always lead to higher levels of shared emergence enabling states but could lead to less HCR emergence (or more negative HCR emergence) if individuals engage in negative social interactions (e.g., Labianca & Brass, 2006). Thus, it is possible that the HCR emergence process could result in HCR that may be less than the sum of their individual parts (Ray et al., in press). Additionally, researchers should be careful not to assume that synergies necessarily occur because of the HCR emergence process (Gerhart & Fang, 2021). Though the idea of synergies is intuitively appealing, there is little empirical evidence of its existence. Future research should investigate the HCR emergence process more fully, including the distinct conditions that may shape both the existence and valence of the synergies that result from HCR emergence.

Fourth, there are also opportunities to better understand influences of HCR creation. Social capital is one such influence (Ray et al., in press). While most HCR research treats social capital as distinct from human capital, disagreement exists regarding whether these are distinct resources (Wright & Essman, 2019). Researchers have begun to reconcile the distinctions between human capital and social capital (Brymer & Hitt, 2019), but because HCR creation typically requires a social component (Cannella & Sy, 2019; Kozlowski & Klein, 2000; Marks, Mathieu, & Zaccaro, 2001; Morris & Snell, 2019; Park, Grosser, Roebuck, & Mathieu, 2020; Ray et al., in press; Wolfson & Mathieu, 2020), it is unclear whether social capital acts as an influence on HCR emergence or if it is a necessary component of HCR and thus should be considered part of HCR in a similar manner as human capital. While recent theoretical work has suggested that social capital plays a significant role in the HCR emergence creation process (Ray et al., 2021), this issue becomes increasingly complex as researchers incorporate various types of social capital (e.g., internal, external) at multiple levels (e.g., dyadic social capital, collective social capital resources), preventing researchers from understanding where human and social capital intersect. Therefore, researchers should continue to distinguish, integrate, and understand how these two constructs are related to fully understand their joint role in the creation of HCR.

Fifth, our review found a lack of clarity regarding how fit influences the HCR emergence process and only minimal attempts at explicitly explaining the theoretical connection. Although Weller et al. (2019) provide a framework of dynamic matching that proposes that the value of HCR may be determined by dynamic fit between individuals and their environments, empirical research is needed. It is also clear that fit and complementarities are related concepts. While fit refers to the degree of alignment between individuals and their jobs, roles, tasks, or organizations (Jansen & Kristof-Brown, 2006), complementarities are the synergistic effects that occur when the value of one item is enhanced by the presence of another (Ennen & Richter, 2010). While it is assumed that fit often results in complementarities, it is unclear precisely why and how fit may lead to synergistic effects in HCR. Future research should investigate the relationship between fit and complementarities by drawing from the well-developed fit literature. For instance, fit researchers distinguish between types of fit (e.g., person-environment, -organization, -supervisor, -job), conceptualizations of fit (complementary, supplementary), measurement (e.g., perceived, subjective, or objective fit), and content (e.g., needs, values). HCR research has not incorporated such features; thus, there may situations when fit more effectively generates synergies or times where fit reduces complementarities. For instance, if individuals and their groups hold similar values but those values are self-interested (e.g., both parties value competing for large bonuses), fit may reduce the amount of HCR that emerges by reducing collaboration. Additionally, because fit between HCR is dynamic (Weller et al., 2019), the relationship between fit and complementarities is also likely to be dynamic, meaning that changes to either may alter their effectiveness on HCR emergence. Thus, the implications of the relationship between fit and complementarities in the HCR emergence process requires greater consideration. Future research on fit should both empirically test its role in the HCR emergence process and better delineate the boundaries and dependence between fit and complementarities in HCR emergence.

Conceptualizations and Measurement

Conceptualizing, measuring, and empirically testing HCR remains a challenge. HCR is dynamic and multidimensional, evolves over time, and is multilevel, and there are substantial differences and an overall lack of precision in defining, selecting, and justifying choices regarding what HCR is and how it should be measured and tested. The lack of clarity around measuring the construct begins with the reluctance to adopt the term human capital resources. Our review included all articles that theorized or empirically tested the link between collective KSAOs and collective outcomes, yet researchers frequently do not explicitly use the HCR terminology. This is a strength of the HCR field because it reflects the diversity of areas that contribute to HCR understanding. However, as the field grows, it will be increasingly useful for researchers to adopt common terminology to avoid construct proliferation and to build collective knowledge.

Both micro and macro scholars meaningfully advance the field in distinct ways. The diversity of methodological traditions used by micro and macro scholars, which sometimes contributes to a proliferation of terms, also creates opportunities. For instance, individual-level data collection through surveys may be better equipped to capture HCR origins, and the emergence process may be tracked by collecting multiple surveys to assess the emergence process over time. Alternatively, the use of multiple proxies may help distinguish among multiple HCR types. By making progress through researchers’ unique perspectives and methodological skill sets, the collective body of literature on HCR will become stronger and more robust. These scholars may be contributing to different parts, levels, or time periods of HCR and so the pursuit of a single measure of HCR may constrain or limit the creativity needed to capture the complex and dynamic aspects of HCR. Therefore, the emphasis for scholars should be on the rigorous pursuit of precision in the aspects of HCR we are measuring, conceptualizing, and testing. To unite researchers toward this aim, we make four research suggestions to facilitate robust future empirical research.

First, future research should explore HCR as a multidimensional construct. While we know HCR is based on individuals’ collection of KSAOs (Sackett, Lievens, Van Iddekinge, & Kuncel, 2017), researchers often use a single KSAO or an aggregate measure encompassing KSAOs. While convenient, the approach's prevalence means that the complexity of individuals’ contributions to HCR is currently missing from most HCR research. Without incorporating this complexity or at least specifying the aspect of the KSAOs tested, it is likely unidimensional conceptions of the construct that obscure important differences that contribute to the HCR emergence process. For instance, prior research suggests that KSAOs can be causally related (Jensen, 1989) and differ in their relative importance (Lang & Kell, 2000). Without considering the collection of KSAOs that contribute to HCR including their relationships to one another, it is unclear how the totality of the unit's HCR connects to valuable outcomes. Therefore, future research should include complete collections of KSAOs to fully capture the dimensionality of HCR. At a minimum, future researchers should theoretically justify why they choose a specific KSAO in their HCR conceptualization and should be precise in discussing and labeling the portion of the construct they are measuring and testing. For instance, Oh et al. (2015) examine the emergence of personality as HCR and are explicit in calling it personality-based HCR (not broadly referring to it as HCR) to clarify the portion of HCR being investigated. These steps will bring precision to the construct to better understand which aspects of a unit's HCR creates value.

Second, HCR is seldom directly measured. In many cases, we found that the HCR is assumed to exist based on the relationship between individual-level factors and collective outcomes without directly measuring HCR. This assumption is justified based on the definition that HCR represents the difference between the actual outcome and the expected outcome of simply aggregating human capital. However, researchers often skip examining the links between individual-level human capital, HCR, and collective performance, only measuring the connection between aggregate individual-level human capital and collective performance (Nyberg et al., 2014). Researchers also frequently avoid directly measuring HCR when examining the relationship between an organizational practice, system, or event and collective outcomes. This practice is commonly used in research on HR management when researchers examine the relationship between an HR system and a collective outcome, such as performance (Wright & Ulrich, 2017). This approach necessarily implies that the HR system changes the existing HCR in some (often positive) way, but failure to directly measure the change to the HCR generated by the HR system creates a “black box,” which makes it difficult to fully understand the direct impact HR systems have on the HCR they are presumed to change (Lepak, Liao, Chung & Harden, 2006). Researchers have also assumed, rather than measured, changes to HCR in turnover research. For instance, Reilly et al. (2014) equate the reduction (or increase) in the quantity of employees with a reduction (or increase) in the total HCR even though theoretical work suggests that turnover and HCR should not be equated (Nyberg & Ployhart, 2013). Future research should distinguish the HCR (not individual human capital) from outcomes and potential antecedents (e.g., HR systems, turnover) to avoid mistakenly equating the two and to avoid making methodological errors across levels.

Third, using a single proxy is common in HCR research. For example, education and tenure are frequently used to represent some collection of KSAOs that are not measured directly (i.e., knowledge and/or skills are assumed to accumulate over time). Such proxies can be informative, but there is confusion regarding what proxies are appropriate for which specific aspect of HCR. For instance, tenure is sometimes used as a measure of knowledge and other times as a measure of skills, which is troublesome given that knowledge, skills, and abilities are distinct constructs that can have distinct antecedents and outcomes (c.f. Sackett et al., 2017). Still others do not specify what KSAO is captured with a proxy. This fungible use of measures harms construct validity, making it difficult to understand lessons or implications of those lessons and impossible to offer actionable and practical implications.

Research using proxies should be clearer in aligning the proxy to their conceptualization of HCR. One way to do this could be by providing more details of the proxy. For instance, if using collective tenure in departments, interviews with top-level managers could illuminate the types of training, socialization, or tasks employees typically work on over time to determine the types of KSAOs that may be developed during their tenure. Another way to better align proxies and HCR could be by combining the proxy with additional variables to assess evidence of emergent processes in the collective HCR. For instance, combining education (a proxy) with a measure of network density may generate insight into the extent that knowledge will be shared or distributed throughout the unit, creating higher levels of HCR emergence (Ray et al., in press). Another way to use proxies more effectively would be to specify how they relate to relevant aspects of HCR, rather than attempting to justify their use as a proxy of the total HCR. For instance, Ployhart et al. (2011) differentiate between general and unit-specific HCR by measuring general HCR as the proportion of applicants who scored in the top distribution of a selection test and measuring unit-specific training as a proxy for the development of unit-specific KSAOs. Their use of multiple proxies distinguishes between two types of HCR, and their measure of unit-specific training aligns with their conceptualization of a unit-specific HCR. Additionally, research that examines HCR composition (e.g., diversity, size, flows in and out) without specifying the content and qualities of the HCR makes assumptions about what those attributes mean relative to HCR. Future research that explains these assumptions will bring greater clarity to HCR, the emergence process, and the importance of HCR.

Fourth, although HCR is a multilevel construct, there is limited empirical attention to examining multilevel differences between individual-level human capital and collective HCR (Ray et al., in press). More work is needed to explain theoretically, and demonstrate empirically, how and why aggregate human capital is distinct from HCR. For instance, Crocker and Eckardt (2014) distinguished between expected aggregate human capital, HCR, and performance and theoretically and empirically described the expected differences between individual and collective levels of analysis. However, studies rarely make the distinction between aggregate human capital and the additional emergence gained through the HCR emergence process (Ray et al., in press). By failing to do so, these studies conceptually assume perfect isomorphism across levels (e.g., HCR equates to the sum or average of individual human capital). While the very definition of HCR notes that HCR are not isomorphic with human capital, future work should do much more to clarify theoretically and empirically when and why this occurs, and when HCR and human capital are, if ever, perfectly isomorphic. To make progress in this area, researchers should use longitudinal approaches, such as repeated surveys, to measure the evolution of emergence over time. Such an approach will help distinguish between human capital and HCR and will also address HCR emergence questions, such as, Does HCR ever stop emerging? At what stage in the emergence process is HCR most valuable? When (if ever) does emergence result in negative synergies, where HCR is less valuable than the aggregate human capital?

Outcomes

Our review also identifies four opportunities for better understanding the link between HCR and collective outcomes. First, researchers should examine the relationship between HCR and more proximal behaviors. Of the 120 empirical articles reviewed, we found that 62 focused on firm or unit performance. Future research should focus on behavioral outcomes, which may be more proximal to HCR and act as the mechanism between HCR and financial outcomes—this could increase the scope of HCR research and result in a greater understanding of why HCR leads to high unit performance. For example, Clark and Maggitti (2012) examined the relationship between HCR and group decision speed, a collective behavior, so future research could extend work by theorizing if and why decision speed is related to financial performance. Alternatively, most of the relevant articles looked at financial performance without explaining the collective behaviors that explain why or how HCR is linked to financial performance (Ployhart, 2021); thus, future research connecting collective behaviors to collective outcomes could help better explain the relationship between HCR and financial performance.

Second, research would benefit from studies that consider conditions where HCR has a negative relationship to performance or other outcomes. As it stands, the current state of HCR research mostly assumes that more or better HCRs always leads to better performance but has not done enough to clarify which HCRs are better and in which contexts. Specifically, there are likely situations where HCR may lead to negative performance, such as where shared knowledge may result in groupthink that negatively impacts performance. Alternatively, the positive effect of HCR may be partially dependent on contextual factors. For instance, collective personality traits (e.g., high levels of extraversion) could lead to high performance in the retail industry when all employees have high levels of interaction with customers but may be distracting and lead to low performance in industries that require more solitary work (e.g., scientist). Incorporating more contextual factors in HCR research may reveal circumstances where the same HCR may be beneficial in some situations and harmful in others. Thus, future HCR research should explore the boundaries of established positive relationships between HCR and collective outcomes to determine where and why the relationship may not hold. A conceptual framework developed by Ployhart, Schepker, and McFarland (in press) should help specify these contextual factors.

Third, our review shows that CEOs or managers can influence the relationship between HCR and outcomes, but additional research is needed to understand where, when, and how this occurs. Managers are likely both to be critical to the creation of HCR, through development and training, and to impact the relationship between HCR and outcomes because of their ability to configure and orchestrate resources (e.g., Story, Youssef, Luthans, Barbuto, & Bovaird, 2013; Zhang, Tsui, & Wang, 2011). For example, extensive research shows that CEOs’ experiences can influence their decision making, including how they interact with and develop their TMT (Essman, Schepker, Nyberg, & Ray, 2021; Hambrick, 2007). Thus, the configuration of the TMT-level HCR and its relationship to performance is likely to depend on the CEO's experience and expertise. Consequently, it is possible that there is an interactive effect between unit-level HCR and managerial HCR, but research is unclear regarding how, when, or why these occur.

Fourth, it is clear there is confusion regarding how HCR intersects with HR management practices (Delery & Roumpi, 2019). While HR management practices can influence HCR value (Abdulsalam, Maltarich, Nyberg, Reilly, & Martin, 2021; Aguzzoli & Geary, 2014; Call & Ployhart, 2020; Fu et al., 2020; Nyberg, Shaw & Zhu, 2021) and more so in tumultuous times (Collings, McMackin, Nyberg, & Wright, in press; Collings, Nyberg, Wright, & McMackin, 2021), research often conceptually equates the two or use HR management systems as a proxy for HCR. These typically occur when research equates a particular training or system as similarly influencing all HCR. However, HR management practices may not influence every HCR in the same way (Trevor & Nyberg, 2008). Certain HR management systems may have the ability to change the composition (DeVos & Cambré, 2017) or the in- and outflows of the HCR (Li et al., 2018), but it is less clear how the distribution of the collective KSAOs within the unit may change the effectiveness of HR management practices and differentially impact the relationship between HCR and collective outcomes (Trevor & Piyanontalee, 2020). Therefore, future research should explore how the effectiveness of practices may be dependent on qualities of the HCR itself.

Integration

Our review found that the field of HCR is developing in relatively isolated silos (creation, outcomes). Therefore, one of the most promising future research directions comes from taking an integrated view of the connections between creation and outcomes and considering the HCR in totality. In general, research focusing on HCR creation generally treats HCR as if it is the outcome of interest without distinguishing between the creation of HCR and different outcomes. In contrast, HCR outcomes research frequently treat HCR, theoretically and empirically, as if it is just aggregate human capital, failing to account for synergies created through emergence—this is particularly egregious since it negates the importance of identifying HCR. Thus, any work on integrating these topics must take a multilevel perspective, looking more broadly across research disciplines. We identify five promising areas for future research.

First, one area about which we can learn more through combining the two perspectives is time. Research is unclear where HCR creation stops and the relationship between HCR and outcomes begins (Ray et al., in press). Currently, HCR creation is studied as if it stops once the HCR emerges, at which point HCR is applied toward collective outcomes. However, the emergence processes necessarily occur over time (Kozlowski & Chao, 2012; Kozlowski & Klein, 2000), but the boundaries of where HCR emergence starts and ends are unclear (Kozlowski, 2019). HCR emergence may be continually ongoing, or once initial HCR emergence occurs, cycles of reemergence may occur and be unique in form and function from initial HCR emergence. Clarifying the role of time in HCR emergence would help us understand whether emergence could be triggered or interrupted by events (e.g., personnel changes) and for understanding how HCR formed in other units (e.g., through comobility) is integrated into units. For example, does HCR emergence stop or reach an asymptote? If it is ongoing, how do ongoing HCR emergence processes (not the emergent HCR) determine how HCR can be used for unit purposes? Future research on the time boundaries of HCR, including feedback loops between HCR creation and HCR outcomes, could help explain the creation and use of HCR as more of a cyclical process. Researchers may consider incorporating recent empirical advancements from the emergence literature. For instance, researchers have created the consensus emergence model (CEM) to detect emergence with longitudinal data (Lang, Bliese, & Runge, 2021; Lang, Bliese, & Adler, 2019; Lang, Bliese, & de Voogt, 2018). The CEM model is advantageous in analyzing multilevel longitudinal data because unlike other tools that have been used to detect emergence in cross-sectional data (e.g., ICC1), it uses an exponential variance function to account for the gradual increases or decreases in residual variance among unit-members. This model provides one possibility for how longitudinal data can be used to measure and test HCR emergence in future research.

As described, capturing HCR emergence is rare. One exemplar is work by Eckardt et al. (2020). Using a sample from MLB, Eckardt and colleagues use multilevel contextual effects models to test whether the relationship between the independent and dependent variables differs between levels of analysis. If the effect at the unit level is stronger than at the individual level, it suggests that an emergent effect occurred (Bliese, Maltarich, & Hendricks, 2018). However, while these results allow researchers to determine whether there is evidence of an emergent effect, it does not allow for direct examination of the HCR emergence process. Research does not fully understand the duration over which HCR emergence occurs, the longitudinal patterns of emergence as members enter and exit units, or the precise mechanisms that increase or disrupt the rate of emergence or those that disrupt emergence. For instance, work that is precise and more completely conceptualizes the forms of change that occur over time will better explain longitudinal concepts, such as HCR emergence (Ployhart & Vandenberg, 2010).

Second, although it is often implied that there is substantial social component to HCR emergence (Fulmer & Ostroff, 2016; Ray et al., 2021) and that managers’ decision making and relationships can influence how HCR relates to collective outcomes (Caza, 2011), it is unclear how the complete collection and evolution of social relationships both within and between units influence HCR. Therefore, although the role of social processes in the creation and outcomes are both crucial, it is unclear how the collection of social processes in a unit affect each other (Ray et al., in press). For instance, do the social relationships that are needed to form HCR in the emergence process interfere with the social processes that enhance HCR performance? If a group develops high levels of collective affect in the emergence enabling process, could that collective affect cause them to be less receptive to manager influence?

Third, creation and outcomes often differ in their level of analysis. HCR creation tends to use a group or unit level of analysis because such research tends to draw from literature on individual-level constructs, and thus, a unit level of analysis is more proximal than firm-level constructs. Alternatively, research on HCR outcomes tends to focus on the firm level. Currently, it is unclear what the implications of misalignment between the two are. When uniting these perspectives, we may need additional theorizing (e.g., Call & Ployhart, 2020) to bridge the gap between unit and firm levels as well as robust multilevel empirical studies.

Fourth, future research can benefit by providing more clarity about how HCR relates to other human-based constructs. Research is beginning to connect collective constructs, such as collective mood (Mitchell & Boyle, 2019) and collective energy (Cole et al., 2012), to collective outcomes. Although these constructs are not HCR, they are related to collective outcomes, though they may be more fleeting because they are based on state differences rather than stable (i.e., trait) differences that provide the foundation for human capital. Future research should explore how these constructs co-emerge and how they jointly relate to collective outcomes.

Fifth, in addition to advancing research on the process of HCR emergence, researchers from both perspectives should work to connect HCR emergence process properties to HCR conceptualizations and measurement. While our review suggests that researchers sometimes conceptualize HCR as generic (Kehoe & Collins, 2017), specific (Wang et al., 2016), one type (Grigoriou & Rothaermel, 2017), or multidimensional (Chatterjee, 2017), there is minimal research explaining how (or if) different types of HCR are created through different emergent processes. This is likely because most research adopts a one-dimensional concept of HCR and typically measures one type of KSAO or one type of HR combination. Hence, it is unclear how different types of emergence models relate to different types of HCR. This is problematic considering that different types of HCR may be more or less valuable (Ployhart et al., 2014), and thus, firms may want to facilitate processes that are likely to lead to a particular HCR. For instance, an HCR containing high levels of interdependent knowledge of legal processes would be crucial to a law firm but less valuable to a factory.

Additionally, as a final and more general recommendation, we encourage both micro and macro scholars to embrace research that is applicable to modern workplace issues and contexts. While research on HCR is growing, broad approaches and poor construct clarity hinder the development of rich, relevant, and practically grounded research. Limited research explores HCR implications within contexts that match the variety and recent evolutions in work environments. For instance, many employees are migrating to remote environments where the nature of their roles change, yet current research is ill-equipped to answer questions regarding how HCR may emerge or be leveraged differently within these environments. Similarly, HCR research rarely attends to the people that comprise the HCR. The U.S. workforce is more diverse than ever (Bureau of Labor Statistics, 2021), yet there has been little examination of the unique challenges and benefits that the people within HCR may face—that is, there has been limited attention to the human piece of HCR (Wright, 2020). This leads to questions such as: How might differences in domestic expectations impact how men and women are utilized as part of HCR? How might a variety of languages, cultures, and socioeconomic backgrounds impact the value of HCR or impact how HCR emerges within units? The consideration of these differences in the individuals that compose the HCR will improve representation of the workforce, and thus be more beneficial, to the diverse and ever-changing collection of individuals who make up the HCR.