Knowledge as a mediator between HRM practices and innovative activity

Human Resource Management,Human Resource Management, July–August 2009, Vol. 48, No. 4, Pp. 485– 503

© 2009 Wiley Periodicals, Inc.

Published online in Wiley InterScience (www.interscience.wiley.com).

DOI: 10.1002/hrm.20295

KNOWLEDGE AS A MEDIATOR

BETWEEN HRM PRACTICES AND

INNOVATIVE ACTIVITY

A LVA R O L O P E Z - C A B R A L E S , A N A P É R E Z - L U Ñ O , A N D R A M Ó N VA L L E C A B R E R A

The objective of this paper is to test how human resources management (HRM) practices and employees’ knowledge infl uence the development of innovative capabilities and, by extension, a fi rm’s performance. Results con-fi rm that HRM practices are not directly associated with innovation unless they take into account employees’ knowledge. Specifi cally, our analyses establish a mediating role for the uniqueness of knowledge between collaborative HRM practices and innovative activity, a positive infl uence of knowledge-based HRM practices on valuable knowledge, and a positive con-tribution of innovations to the company’s profi t. We tested hypotheses in a sample of fi rms from the most innovative Spanish industries through struc-tural equation modeling. © 2009 Wiley Periodicals, Inc.

Keywords: HRM practices, valuable and unique knowledge, innovation

Introduction

In recent years, there has been a consider-able increase in the literature analyzing innovation and organizational change (Anand, Gardner, & Morris, 2007). This broad body of research has generated

growing interest in identifying how compa-nies can improve their innovative activity and what internal and external factors have positive effects on such behavior (Daman-pour, 1991; Galunic & Rodan, 1998; J. Zhou, 2006).

Based on the resource-based view (RBV), authors such as Wernerfelt (1984) and Barney (1991) proposed that the crucial research question concerns what kinds of corporate

resources lead to sustainable competitive advantages. Following these arguments, the types of employee knowledge, skills, and abilities (KSA) have been considered key re-sources for the improvement of existing prod-ucts and services or for the generation of new ones (innovations), which, by extension, help to achieve competitive advantages (Donnel-lon, 1996; Jackson, 1992; Nonaka & Takeuchi, 1995; Thompson, 2003). In addition, it is ar-gued that there must be coherence between an organization’s human resources manage-ment (HRM) practices and the strategies that it adopts, and this requirement would also be applicable to an innovation strategy (Balkin, Markman, & Gomez-Mejia, 2000; Gupta & Singhal, 1993; Kang, Morris, & Snell, 2007;

Correspondence to: Dr. Alvaro Lopez-Cabrales, Assistant Professor, Universidad Pablo de Olavide, Departamento de Dirección de Empresas, Ctra. Utrera, Km. 1—41013 Sevilla, Spain, Phone: (0034) 954 349 180, Fax: (0034) 954 348 353, E-mail: [email protected]

486 HUMAN RESOURCE MANAGEMENT, JULY–AUGUST 2009

Human Resource Management DOI: 10.1002/hrm

Laursen, 2002; Lopez-Cabrales, Valle, & Her-rero, 2006; Schuler & Jackson, 1987). There-fore, the research question we address is to what extent the contribution of HRM prac-tices to product innovation and performance is conditioned by the employees’ knowledge. To answer this question, the purpose of this study is to analyze, in the R&D department of innovative companies, the mediating role of the knowledge employees possessed in HRM practices, innovative activity, and perfor-mance.

Explaining how the coherence between HRM practices and knowledge enhances in-novation and performance could extend the RBV, HRM, and innovation literatures. Spe-

cifically, this paper makes three main contributions. The first con-tribution is related to the relation-ship, on the whole, among HRM practices, knowledge, and the in-novative activity in R&D depart-ments. Our findings improve the innovation literature by provid-ing new predictors of innovative capability. The second contribu-tion, which enriches the HRM literature, concerns the conse-quences of HRM practices. We as-sume that HRM practices are directly associated with employ-ees’ knowledge in a similar way to that proposed by Lepak and Snell (1999, 2002). Furthermore, we add to the Lepak and Snell argu-

ments that these practices are indirectly re-lated to organizations’ innovative activity. The third contribution is related to the lack of systematic empirical support received for the RBV (Newbert, 2007). For this reason, having demonstrated that a bundle of re-sources (knowledge) and capabilities (innova-tive activity) can be seen as good drivers of competitive advantages, this study extends the empirical support for such a theoretical approach.

The structure of this article, consistent with its objectives, is as follows. After this introduction, we present a theoretical review that enables us to delimit the relationships among knowledge, HRM practices, innova-

tion, and profits. As a result of this analysis, we formulated and empirically tested several hypotheses using a survey of firms from the most innovative Spanish industries and ap-plying structural equation modeling. Finally, we present conclusions, contributions, limi-tations, and future lines of research.

The Role of Employees’ Knowledge in Product Innovation

There is a great diversity of concepts used to define the term innovation. Kimberly and Evanisko (1981) explained that this term could have three different meanings. First, innovation can be understood as a discrete element that includes the development of products, programs, or services. Second, in-novation can be considered a process—that is, they refer to different stages of the innova-tion process. Finally, innovation can be understood as an organizational capability (innovativeness and/or innovative capabil-ity). Conceptually these three elements are mutually compatible. When a firm is de-scribed as innovative (innovation as an orga-nizational capability), it generally means that it develops or frequently adopts products, services, programs, or innovative ideas (innovation as discrete elements) that need a series of stages (innovation as a process) to be sources of competitive advantage.

While these three uses of the term innova-tion could be broadly debated, this paper only focuses on the use of innovation as an orga-nizational capability because, as mentioned, an innovative company generally develops all the stages needed to give rise to new prod-ucts. Therefore, this use of the term innova-tion includes the other two and is understood as a broad term that defines a firm’s ability to introduce new products or lines (ranges) into the market (Pérez-Luño, Valle Cabrera, & Wiklund, 2007). That is, innovation is the degree to which a company strays from exist-ing practices in creating and successfully marketing new products (Capon, Farley, Lehmann, & Hulbert, 1992).

It is accepted that a firm’s ability to obtain new products and other aspects of performance are inextricably linked to the

The research

question we address

is to what extent

the contribution of

HRM practices to

product innovation

and performance

is conditioned by

the employees’

knowledge.

KNOWLEDGE AS A MEDIATOR BETWEEN HRM PRACTICES AND INNOVATIVE ACTIVITY 487


knowledge of its human resources (Foss, 2007; Laursen, 2002). Thus, the most distinc-tive and inimitable resource available to firms is people-embodied knowledge, which en-ables them to manipulate and transform other organizational resources effectively (Argote & Ingram, 2000; Foss, 2007; Kogut & Zander, 1992). Furthermore, knowledge-based resources may be particularly important for providing a sustainable competitive advan-tage (McEvily & Chakravarthy, 2002), for playing an essential role in the firm’s ability to innovate (Galunic & Rodan, 1998), and for improving performance (Wiklund & Shep-herd, 2003). Therefore, it can be inferred that competitive advantages are increasingly de-rived from knowledge and technological skills and from experience in creating new products (Alegre, Lapiedra, & Chiva, 2006; Teece, Pisano, & Shuen, 1997).

The previous assumptions lead us to wonder which characteristics of knowledge enable product innovation. Knowledge can be analyzed from different perspectives. The intellectual capital literature distinguishes three different aspects of knowledge: human, organizational, and social capital (Subrama-niam & Youndt, 2005). Human capital is defined as the knowledge, skills, and abilities individuals have and use (Schultz, 1961). Organizational capital is the institutionalized knowledge and codified experience contained in and used through databases, patents, manuals, structures, systems, and processes (Youndt, Subramaniam, & Snell, 2004). Finally, social capital is the knowledge embed-ded within, available through, and used by interactions among individuals and their net-works of interrelationships (Nahapiet & Ghoshal, 1998). As Subramaniam and Youndt (2005) pointed out, each of these compo-nents accumulates and distributes knowledge in a different way—human capital through individuals, organizational capital through firm structures and processes, and social capi-tal through relationships and networks. Based on these conceptual issues, we focus on the impact of employees’ knowledge (human capital) on product innovation. Considering the human capital approach, the value and uniqueness of employees’ knowledge

are the most relevant features for product innovation (Lepak & Snell, 1999; Subrama-niam & Youndt, 2005).

The value of knowledge refers to “its po-tential to improve the efficiency and effective-ness of the firm, exploit market opportunities, and/or neutralise potential threats” (Lepak & Snell, 2002, p. 519). As Barney and Wright (1998) suggested, any resource creates value through either decreasing product/service costs or differentiating product/service in a way that allows the firm to charge a premium price; thus, valuable knowledge will yield high returns in markets, increasing the ratio of ben-efits to customers relative to their associated costs (Snell, Lepak, & Youndt, 1999; Werner-felt, 1984). Nevertheless, to be good at doing something does not mean that knowledge is valuable, as Leng-nick-Hall and Lengnick-Hall (2002) pointed out. The cited authors de-fined value as “the degree to which the human capital lowers costs or provides increased services or prod-uct features that matter to custom-ers” (p. 50). An example is the case of Sony, which possesses valuable knowledge in designing, manufac-turing, and selling miniaturized electronic technology; such knowl-edge gives it a competitive advan-tage (Barney, 1995). The second feature is the uniqueness of a per-son’s knowledge and skills. This means that an employee must be irreplaceable and idiosyncratic with rare and firm-specific Knowledge (Barney, 1991) that is difficult to transfer to other positions or even difficult for other firms to duplicate (Lepak & Snell, 1999).

Given the fact that creative people must deal with novel and ambiguous problems, they tend to display strong, valuable, and ir-replaceable knowledge and skills (Mumford, 2000). In addition, product innovation con-sists of successful exploitation of new ideas. Therefore, it implies two conditions: novelty and use (Alegre et al., 2006). These condi-tions can only be produced by useful or valuable knowledge. Valuable knowledge is positively associated with product innova-

Considering the

human capital

approach, the value

and uniqueness

of employees’

knowledge are

the most relevant

features for product

innovation.



tions because it contributes to identification of new market opportunities, and employees with such knowledge are willing to experi-ment and apply new knowledge (Costa & McCrae, 1992; Taggar, 2002). Moreover, scholars studying innovative activity have addressed the importance of individuals’ ex-pertise and valuable knowledge that allows them to obtain novel ideas and gives rise to innovations (Anand et al., 2007). Neverthe-less, it must be said that valuable knowledge is a necessary but not sufficient condition for

developing product innovations. That is, R&D departments will take advantage of their employ-ees’ valuable knowledge, but they will also need other features such as creativity, entrepreneurship, and unique knowledge to develop product innovations. Based on these arguments, we propose our first hypothesis:

H1: Valuable knowledge is positively associated with innovation.

The second characteristic of knowledge associated with inno-vation is uniqueness. This unique knowledge can create a competi-tive differentiation because valu-able but common (i.e., not rare)

resources and capabilities are sources of competitive parity (Barney, 1995; Snell et al., 1999). Furthermore, uniqueness refers to the degree of content specificity of the knowl-edge and its difficulty in being transferred to other organizations (Lengnick-Hall & Lengnick-Hall, 2002). That could be why it is very difficult to be innovative on the basis of generic knowledge (Nonaka & Takeuchi, 1995). So, people with unique KSA are con-sidered rainmakers, and their specialized knowledge contributes to the development of new ideas or products (James, 2002). Amar (2002) suggested that these employees possess rare KSA not commonly distributed in the labor market. Therefore, their knowl-edge is also new to any competitor firm and is an intangible resource for firm innovation. Based on these arguments, we propose our second hypothesis:

H2: Unique knowledge is positively associated with innovation.

HRM Practices as Facilitators of Knowledge and Product Innovation

Based on the RBV, some authors note that not only should a firm’s resources be valuable and unique to facilitate superior performance, but also the firm must have an appropriate organization in place to take advantage of these resources (Barney & Wright, 1998; Foss, 2007; Peltokorpi & Tsuyuki, 2006). Empirical studies have mainly focused on the direct link between individual strands or configurations of resources and performance, while less atten-tion has been devoted to how management can use its resources more effectively (Wiklund & Shepherd, 2003). Therefore, HRM practices can explain, in part, the managerial processes that allow firms to ob-tain valuable and unique knowledge and how it leads to innovative activity and higher performance.

These valuable and unique characteristics of employees’ knowledge create a “human capital advantage” (Boxall, 1996). Neverthe-less, any human capital advantage may decrease in the long term. Therefore, organi-zations must define and apply appropriate HRM practices for managing people and link them to the firm’s core capabilities (Amit & Belcourt, 1999; Peltokorpi & Tsuyuki, 2006; Purcell, 1996). As Paauwe and Boselie (2005) indicated, “the search for the Holy Grail in HRM is the search for those best practices or best-fit practices that ultimately result in sustained competitive advantage for the organization” (p. 72). In our case, as we focus on innovative firms, their core capabilities and competitive advantage are related to in-novations. In other words, HRM practices can (a) increase the value and uniqueness of the knowledge through internal develop-ment and (b) influence employee behavior in the desired direction—in this case, to im-prove firm innovation. Lepak, Liao, Chung, and Harden (2006) argued that HRM practices directly influence employees’ ability to perform by affecting their KSA. The next

HRM practices can

explain, in part,

the managerial

processes that

allow firms to obtain

valuable and unique

knowledge and how

it leads to innovative

activity and higher

performance.



step is to assess the extent to which HRM practices increase the value and uniqueness of knowledge.

One way of obtaining valuable and unique knowledge is through a system of HRM knowledge-based practices that enable the internal development of human resources (Lepak & Snell, 2002) with specific selection, training, development, appraisal, and com-pensation practices. The aim of selection is to attract the best people to the company in terms of their inherent potential (Doorewaard & Meihuizen, 2000; Huselid, 1995). Informal contacts that favor socializing among the workforce are encouraged (Arthur, 1994), and firm-specific training and career develop-ment are offered within the company (Lepak & Snell, 1999). Individuals receive feedback concerning what they do and how perfor-mance can be improved, thus promoting au-tonomy. Incentives are also used as a form of reward (Huselid, 1995).

This model of HRM practices enables valuable and firm-specific knowledge to be generated by internal development. In addi-tion, developing HRM practices internally helps firms to obtain the benefits of employ-ees’ value-creating potential and firm-specific human capital (Lepak & Snell, 1999, 2002; Youndt et al., 2004; Youndt, Snell, Dean, & Lepak, 1996). Previous authors have shown all of the above HRM practices motivate employees to develop opportunities and improve their personal stock of knowledge and skills (Lepak et al., 2006; Snell & Dean, 1994; Ulrich & Lake, 1991). Thus, we try to confirm the Lepak and Snell (2002) proposi-tion by our third hypothesis:

H3a: Knowledge-based HRM practices are posi-tively associated with the value of knowledge.

H3b: Knowledge-based HRM practices are posi-tively associated with the uniqueness of knowl-edge.

In another system of HRM practices, named collaborative or partnership/alliances (Lepak & Snell, 1999, 2002), the HRM practices have a group orientation that is different from the orientation of the knowl-edge-based practices discussed previously.

The literature also stresses the importance of working in groups or teams to enhance the uniqueness of the knowledge members of these groups possess (Lepak & Snell, 1999, 2002; Nonaka & Takeuchi, 1995). In the col-laborative system, skills for teamwork are necessary to pass any selection procedure, and such skills are the objective of training initiatives. In addition, evaluation and remu-neration processes always comply with group criteria (Helleloid & Simonin, 1994; Lepak & Snell, 1999). There-fore, a teamwork design is critical for disseminating specialized knowledge throughout the orga-nization.

These collaborative HRM prac-tices have been found to be an efficient means of increasing the uniqueness of knowledge (Lepak & Snell, 1999, 2002). Communi-cation mechanisms, exchange programs, group-based rewards, and appraisals may be established to facilitate information sharing and to equip these group members with firm-specific knowledge (Lepak et al., 2003). The fourth hypothesis is as follows:

H4: Collaborative HRM practices are positively associated with the uniqueness of the knowl-edge.

The preceding arguments suggest two critical points for this research. First, HRM practices may facilitate valuable and unique knowledge. Second, valuable and unique knowledge may mediate the relationship be-tween HRM practices and innovative capabil-ity. Therefore, to close the cycle, we explore the possibility of a direct impact of HRM prac-tices on product innovation independently of the characteristics of employees’ knowledge.

As we pointed out, Paauwe and Boselie (2005) suggested that one way HRM practices can generate core capabilities is by influenc-ing employee behavior in the desired strate-gic direction. According to this reasoning, any firm may adopt concrete HRM practices in job design, training, development, and/or appraisal compensation to improve the firm’s innovation.

Valuable and

unique knowledge

may mediate

the relationship

between HRM

practices and

innovative capability.



Regarding job design, in cases where jobs are broadly defined and discretion and self-direction are allowed, employees are able to find new solutions to problems and opportu-nities that arise in the workplace (Kang et al., 2007; Lepak & Snell, 1999). It is also claimed that empowerment practices increase the level of decentralization, and such an envi-ronment may better allow new solutions at the shop-floor level (Laursen, 2002). In other words, increased delegation may better facili-tate the discovery of new design and prod-ucts that top levels are unable to see (Drucker, 1999).

Firm-specific training is necessary because it improves technical abilities to solve prob-lems (Barton & Delbridge, 2001; Beatty & Schneier, 1997; Gupta & Singhal, 1993;

Laursen & Foss, 2003). The firm must reorganize training activities in ways that generate new under-standing and new ideas. Thus, training in core skills is useful for product innovation (Mumford, 2000).

Another strongly recommend-ed practice entails employee development. It maximizes em-ployees’ commitment to innova-tion and their potential for learning (Mak & Akhar, 2003; Schuler & Jackson, 1987). Em-ployee development includes HRM practices such as career

management, mentoring, and coaching. Employees should be given guidance in establishing career paths that help them ex-perience various job opportunities beyond the boundaries of a single expertise in order to be innovative (Kang et al., 2007). In addition, to promote the growth of requisite skills, the organization must establish and manage effective mentoring relation-ships for new employees (Mumford, 2000). Also, managers should provide coaching and feedback to help employees over-come performance problems (London & Smither, 1999). These are effective ways to foster ongoing knowledge development and assessment of new solutions (J. Zhou, 1998).

Compensation practices must also in-clude employee incentives that reward the search for new solutions (Balkin & Mon-temayor, 2000; London & Smither, 1999; Mumford, 2000). As the behaviors required for innovating are difficult to identify a priori (Adler & Kwon, 2002), result- or output-based incentives are more useful in managing and rewarding joint contributions (Snell & Dean, 1994). In addition, incentives need to be ac-companied by the acquisition of knowledge or new ideas—for example, by paying for knowledge or reputation, which may moti-vate employees to develop innovations con-tinuously.

In summary, all these HRM practices can be included in the knowledge-based system, and they positively affect firm innovation. As a result, we formulate the fifth hypothesis as follows:

H5: Knowledge-based HRM practices are posi-tively associated with innovation.

One of the organizational variables tradi-tionally related to innovation is the use of work teams. The basic argument is simple: Innovation normally begins in a creative in-dividual’s mind, and a work team collectively analyzes and develops that initial idea (Tang, 1998). Such groups are considered a powerful means of creating and circulating innovative ideas (Denison, Hart, & Kahn, 1996; Griffin, 1997). Work teams represent one of the most important recent trends in organizational design and are considered a key element in the creation and improvement of products and services (Donnellon, 1996; Jackson, 1992; Thompson, 2003).

From the list of HRM practices that could be considered as having a team orientation, we focus on selection of individuals accord-ing to their team competencies, training ac-tivities explaining how to work in teams, and team-based appraisals and compensation practices (collaborative HRM practices). Team design requires reciprocal interdependence among employees who work together and seek new solutions to existing problems (Kang et al., 2007). As a consequence of de-signing jobs around work teams, the organi-zation must value a candidate’s capacity for

Innovators have

the potential to

create markets,

shape customer

preferences, and

even change

consumers’ basic

behavior.



working in a team during the staffing process (Lepak & Snell, 1999). Another option also included in the collaborative model is train-ing individuals in developing interpersonal skills. This type of training has a positive effect on innovation because it facilitates employee interaction with colleagues and encourages the flow of new ideas and per-spectives within work teams (Lepak et al., 2003; Ulrich, 1998).

Team-based appraisals and compensation practices have a powerful motivating role on individuals’ innovation behavior (Eisenberger & Armeli, 1997; Kunkel, 1997). Thus, Barczak and Wilemon (2003) demonstrated that work team members have a strong interest in being remunerated on the basis of their innovative activity. In this context, Balkin et al. (2000) empirically demonstrated a positive relation-ship in companies between long-term incen-tives and innovation.

In conclusion, because we consider these HRM practices to be collaborative practices and they are related to innovations, we for-mulate the sixth hypothesis as follows:

H6: Collaborative HRM practices are positively associated with innovation.

From Product Innovation to Higher Performance

The final stage of our discussion is to learn whether firms with the appropriate stocks of knowledge and HRM practices obtain not only innovations, but also the best market performance. According to the literature, in-novation is one of the main sources of com-petitive advantages (Li & Atuahene-Gima, 2001). From an RBV perspective, if a company develops innovations based on valuable, rare, inimitable, and nonsubstitut-able resources such as value and unique knowledge, this will lead to higher levels of competitive advantages (Barney, 1991). Firms that offer products adapted to target custom-ers’ needs and wants and that market these products faster and more efficiently than their competitors are in a better position to obtain higher performances and create sus-tainable competitive advantages (Alegre et al., 2006; Nonaka & Takeuchi, 1995; Prahalad

& Hamel, 1990). Furthermore, given that or-ganizational capabilities such as innovative capability can be seen as a proxy of competi-tive advantages (Lopez-Cabrales et al., 2006), there is a very close link between innovative activity and competitive advantages and per-formance.

It has been proposed that the develop-ment of an innovation contributes to the company’s performance (Capon et al., 1992; Damanpour, 1991; Pérez-Luño et al., 2007). That is, innovators have the potential to create markets, shape customer preferences, and even change con-sumers’ basic behavior (K. Z. Zhou, 2006), which leads to higher prof-its. From the above, we argue that innovative activity represents an important capability that en-hances the company’s perfor-mance. These assumptions lead us to establish our last hypothesis:

H7: Innovation is positively associated with a higher level of performance.

Figure 1 summarizes the main relation-ships and hypotheses outlined in this paper.

Methodology

Research Design and Sample

To examine the innovative capability of R&D departments, we needed a sample of firms that were actually involved in these activities to some extent. We therefore started with a sam-pling frame covering the most innovative companies in Spain. There were two criteria for the population selection: presence in in-novative industries and a minimum number of employees. The industries with the most patents, according to data of the Spanish Of-fice of Patents, are the following: manufacture of machinery; manufacture of motor vehicles; manufacture of radios, TVs, and telecommu-nications equipment; and the chemical indus-try. We used the 2004 edition of the DUNS 50,000 database to obtain a list of the compa-nies in those industries with more than 50 employees. Using this procedure, we obtained

We argue that

innovative activity

represents an

important capability

that enhances

the company’s

performance.



a total valid population of 619 companies. To obtain the best information about the compa-nies’ innovative activities, we used the firms’ R&D departments as our unit of analysis.

We adopted the methodology of contact-ing the firms, mailing the questionnaire, and following up, as proposed in the literature (Dillman, 1991). We identified the R&D departments of the companies in our popula-tion and telephoned the manager responsible for this unit to explain the study, request col-laboration, and discuss the mailing of the questionnaire. Over six months, we sent periodic reminders to the participating companies that had not returned the ques-tionnaire. In total, 88 firms responded to this questionnaire; of this number, 86 were con-sidered valid. This corresponds to a response rate of 14 percent of the firms in our target population. To check for nonresponse bias, we compared the respondents with the non-respondents, via mean difference, based on their general features (industry membership, number of employees, and revenue), which were available in the DUNS 50,000 database. This test showed no significant differences between the two groups (respondents versus nonrespondents).

Measures

As we mentioned in the previous section, the instrument used to collect the required infor-

mation was a questionnaire with more than 40 items to obtain information about the R&D department of the companies in our popula-tion. Responses for the different items were obtained using a 7-point Likert scale except for performance, for which we used objective data, and the size and R&D expenditures, for which we used direct questions. To assess con-tent validity, after a thorough review of the literature, we formed a panel of 12 academic experts. Once their suggestions were incorpo-rated into the questionnaire, the latter was sent to each company’s R&D manager.

Dependent Variables

Firm performance may be assessed in terms of how effectively the firm achieves a variety of financial benchmarks (an objective mea-sure) or by the firm’s position on various in-dicators of effectiveness and success relative to competitors’ ratings for these indicators (a subjective measure). In our case, we used the objective measure to reduce the common method variance error. That is, we used the ratio of total revenues divided by total assets as an objective measure of profits.

After conducting a full literature review of the scales used to measure an organiza-tion’s product innovative activity (Avlonitis, Papastathopoulou, & Gounaris, 2001; Orga-nisation for Economic Co-Operation and Development [OECD/Eurostat], 1997), and

Performance

Knowledge-basedHRM Practices

CollaborativeHRM Practices

InnovativeActivity

Valuable Knowledge

Unique Knowledge

H7

H3a

H4

H3b

H5

H6

H1

H2

H5H1

H2

H1

H2

FIGURE 1. Model of Theoretical Relationships



based on the recommendations by Churchill (1979), we devised a scale of measurement with eight items, of which the last two con-stitute a direct measure for determining the scale’s convergent validity (see Table I).

We adapted the measure of valuable and unique knowledge from the work of Lepak and Snell (2002). Following the recommendations of our 12 academic experts and keeping the content validity conditions, we used a scale of 9 items from the 22 the original authors pro-posed. The first 5 items measure valuable knowledge, while the remaining 4 items mea-sure unique knowledge (see Table I).

Independent Variables

The measures of HRM practices were adapted from those developed by Lepak and Snell (2002) in their analysis of human capital architecture (1999, 2002). The items specifi-cally used were those forming their knowl-edge-based employment system and their collaborative system with respect to group work. We used these items because both models include HRM practices that the litera-ture has shown to be generators of innova-tive behavior and closely linked to the value and uniqueness of human capital.

Control Variables

We used size and internal and external R&D expenditures as control variables. Research has demonstrated that a company’s size may be linked to a greater or lesser tendency for innovation (Bantel & Jackson, 1989). Some scholars have established that an increase in the organization’s size implies a higher number of resources and higher innovative potential, while others argued that small or-ganizations can be more innovative because they have more flexibility, a higher ability to adapt, and less difficulty in accepting and implementing changes (Damanpour, 1991). Following these arguments, we assume that the firm’s size has an influence on an organi-zation’s innovative activity. We measured the organization size variable by the number of employees in the firm. The value of this vari-able ranges from 50 to 5,000 workers. Because

of its wide dispersion, we used a Napierian logarithm of the number of workers in the firm to estimate it in order to avoid the scale effect.

Following several authors (Bierly & Chakrabarti, 1996; Cohen & Levinthal, 1990), we decided to include internal and external R&D expenditures as control variables in our study. We measured these variables by two items in which the respondents were asked for information on the internal and external expenditure on R&D as average percentages of the sales turnover of the company for the previous three years.

Analyses and Results

We tested the hypotheses using the structural equation modeling method. We followed the two-stage procedure recommended by Ander-son and Gerbing (1988). In the first stage, after conducting exploratory factor analysis (EFA), we estimated the measurement model using confirmatory factor analysis (CFA) to test the goodness of fit of the measurement scales (Anderson & Gerbing, 1988; Fornell & Larcker, 1981). A number of studies have used CFA to test the psychometric properties of measurement scales (Alegre et al., 2006; Gerbing & Anderson, 1988); Montoya-Weiss and Calantone (1994) recommend it to assess the construct validity and reliability of subjective measurement instruments. The purpose of CFA was also to test the unidi-mensionality of multi-item constructs and to eliminate unreliable items. We deleted items that loaded on multiple constructs and had low item-to-construct loadings. Table I lists the individual measurement items for the study’s dependent, independent, and control variables.

We obtained the results presented in Table I as follows. We began by analyzing the establishment of scale dimensionality by checking the factorial structure of each of the concepts we wanted to measure. We then tested the scale reliability by assessing both the individual reliability of each indicator (R ² > 0.5) and the composite reliability of each factor (CR > 0.7). Finally, we analyzed the scale validity by focusing on content validity,



T A B L E I Measurement Model

Performance Total sales divided by total assets

F1: Product innovative activity (CR 0.82)

I1. Market introduction of technologically new products developed by the company (totally or in part).

I2. Market introduction of technologically improved products developed by the company (totally or in part).

(I3) Extensions of existing product lines (that do not only entail changes to aesthetic aspects). (I4) Changes introduced to existing products, entailing signifi cant improvements. I5. Development of new lines/ranges of products. I6. Frequency of replacement of old products by others with important changes. (I7) Proportion of technologically new or improved products in the turnover of the company. I8. Product innovation performed by the company.

F2: Value (Lepak & Snell, 2002) (CR 0.92)

V1. Employees have skills that contribute to development of new market/product/services/opportu-nities.

V2. Employees have skills that create customer value. V3. Employees have skills that are instrumental in creating innovations. V4. Employees have skills that are needed to maintain high-quality products/services. V5. Employees have skills that enable our fi rm to provide exceptional customer value.

F3: Uniqueness (Lepak & Snell, 2002) (CR 0.80)

U1. Employees have skills that are not available to our competitors. (U2) Employees have skills that are developed through on-the-job experiences. U3. Employees have skills that are diffi cult for our competitors to buy away from us.

U4. Employees have skills that are diffi cult for our competitors to imitate or duplicate.

F4: Knowledge HRMP* (Lepak & Snell, 2002) (CR 0.95)

(HRK1) Employees perform jobs that have a high degree of job security. (HRK2) Employees perform jobs that empower them to make decisions. (HRK3) Employees participate in the decision-making process. (HRK4) Selection process focuses on selecting the best all-around candidate. (HRK5) Selection process places priority on employee potential to learn. (HRK6) Training activities strive to develop fi rm-specifi c skills/knowledge. HRK7. Firm emphasizes promotion from within. HRK8. Firm emphasizes tutoring and mentoring activities. HRK9. Firm possesses a socialization program for newcomers. HRK10. Performance appraisals include developmental feedback. HRK11. Performance appraisals emphasize employee learning. (HRK12) Compensation/rewards provide incentives for new ideas.

F5: Collaborative HRMP (Lepak & Snell, 2002) (CR 0.91)

(HRC1) Employees perform jobs that require them to participate in cross-functional teams and networks.

(HRC2) Employees perform jobs that involve job rotations.



convergent validity, and discriminant valid-ity. As we explained earlier, we reviewed pre-vious literature in depth and used 12 experts to ensure content validity. Convergent valid-ity is accepted when factorial loads are higher than 0.4 and t coefficients are significant. We also took into account the fact that the CFI, robust CFI, GFI, and AGFI statistics were above 0.9, the p-value for the Satorra–Bentler χ² was not significant (p > 0.05), and the ro-bust RMSEA was significant (RMSEA < 0.05). With the exception of the AGFI, which is sensitive to sample size and GFI, all fit indices had optimal values. We could therefore as-sume that our measurement scales had con-vergent validity (Hair, Anderson, Tatham, & Black, 1999) and that the goodness of fit of our causal approach was acceptable (Bagozzi, 1994; Bakker, Demerouti, & Verbeke, 2004). Following Fornell and Larcker (1981), we also demonstrated discriminant validity, given that the average variance extracted (AVE) of the constructs is higher than their squared multiple correlations with the rest of the con-structs (see Table II).

The scale developed to measure innova-tive activity contained eight items. After

conducting CFA, however, we were forced to eliminate three of the items because their standardized loadings were too low. These eliminations did not harm the content valid-ity of the scale. Our CFA achieved a 5-item solution for the valuable knowledge scale, as was proposed, and a 3-item solution for unique knowledge. That is, we had to elimi-nate one of the proposed items of the unique knowledge scale because its standardized loadings were too low. Finally, our measure-ment of HRM practices comprised two factors: (1) the HRM practices of the knowl-edge-based system, corresponding to the indicators HRK1 to HRK12, and (2) the prac-tices of the collaborative system, indicators HRC1 to HRC9, as established by the mea-surement proposed by Lepak and Snell (2002). After conducting CFA, however, our results provided a 5-item scale for measuring knowl-edge-based HRM practices. The items remain-ing included internal promotions, tutoring, and mentoring activities, socialization pro-grams, and performance appraisals. After conducting CFA, we measured collaborative HRM practices with a 4-item scale through selection processes based on interpersonal

T A B L E I Continued

(HRC3) Selection process assesses industry knowledge and experience. HRC4. Selection process assesses the ability to collaborate and work in a team. HRC5. Training activities focus on team building and interpersonal relations. HRC6. Appraisals are based on team performance. HRC7. Appraisals focus on employees’ ability to work with others. (HRC8) Compensation/rewards place a premium on employees’ industry experience. (HRC9) Compensation/rewards have a group-based incentive.

Internal R&D

Internal expenditure on R&D as average % of the sales turnover of the company for the previous three years.

External R&D

External expenditure on R&D as average % of the sales turnover of the company for the previous three years.

Size

Napierian logarithm of the number of workers

CR = Composite reliability (analogous to Cronbach’s alpha).() = Eliminated items appear in parentheses.*HRMP: Human Resource Management Practices.



abilities, training focus on team building, and appraisals based on team performance and/or employees’ ability to work in groups. We should mention that the original study was devised with the organization as the unit of analysis, while our study takes as its unit of analysis the R&D department. This difference in the unit of analysis could be a reason for the differences between Lepak and Snell’s (2002) results and ours.

The two-stage procedure recommended by Anderson and Gerbing (1988) identified the structural model that best fit the data and tested the hypothesized relationships be-tween the constructs. As shown in Table III, we used two structural models to test the hypothesized relationships between the constructs. In Model 1, we presented all the possible equations. In the adjusted Model 1, we only employed the equations that best match the data.

With respect to Hypotheses 1 and 2, in which we related valuable and unique knowl-edge with higher innovative activity, it has to be mentioned that only unique knowledge positively and significantly influences inno-vative behavior (t value, 2.181), which sup-ports Hypothesis 2. In Hypothesis 3, we proposed that knowledge-based HRM prac-tices would positively influence valuable and unique knowledge. In this case, we only found partial support, because such practices only influence the value of knowledge (t value, 3.531). On the other hand, we found support for Hypothesis 4. That is, collabora-tive HRM practices significantly and posi-tively influence unique knowledge (t value, 1.648), although the significance is only at p ≤ 10%. In addition, we did not find support

for Hypotheses 5 and 6. That is, none of the HRM practices directly influences innovative activity.

Last, as we can see in Model 1 Adjusted, innovative activity has a significant positive influence on the company’s profits (t value, 2.638). This result supports our Hypothesis 7. The only significant control variable is exter-nal R&D expenditures that have a negative influence on the innovative activity (t value, –8.333) and a positive influence on the company’s performance (t value, 3.212).

Conclusions

Although innovation has attracted substan-tial attention in the literature, only a few studies have analyzed how employees’ knowl-edge and HRM practices, on the whole, can enhance organizations’ innovative activity. Therefore, this paper contributes to the litera-ture by theoretically and empirically investi-gating such relationships.

Our results showed that collaborative HRM practices increase the uniqueness of knowledge, and this firm-specific knowledge is positive and significantly associated with innovative activity. On the other hand, although knowledge-based HRM practices contribute to the value of knowledge, this characteristic of knowledge had no impact on innovation. As a result, it can be said that the uniqueness of knowledge mediates con-tribution of collaborative HRM practices to innovative capability, as our analyses showed that neither of the two systems of HRM prac-tices (knowledge-based and collaborative) had a significant direct effect on innovative activity.

T A B L E I I Squared Correlation Matrix

F1 F2 F3 F4 F5

F1: Product innovative activity 0.50

F2: Value 0.005 0.56

F3: Uniqueness 0.062 0.012 0.59

F4: Knowledge HRMP* 0.003 0.217 0.002 0.67

F5: Collaborative HRMP* 0.031 0.212 0.022 0.393 0.56

CR 0.82 0.92 0.80 0.95 0.91

Signifi cant at p < 0.05; AVE is represented in the principal diagonal; CR is composite reliability.*HRMP: Human Resource Management Practices.



T A B L E I I I Estimated Coeffi cients and Model Fit Indices

Latent Factors

Dependent Variables Independent Variables Model 1

Coeff1a(t value)

Model 1*

Coeff1a*(t value)

Performance

Product innovative activity 0.191 (2.285) 0.173 (2.638)Value 0.022 (0.234) –Uniqueness - 0.056 (- 0.598) –

Knowledge HRM practices 0.036 (0.218) –Collaborative HRM practices - 0.055 (- 0.268) –Size - 0.046 (- 0.838) –Internal R&D expenditures - 0.017 (- 1.016) –External R&D expenditures 0.023 (3.810) 0.020 (3.212)

Product Innovative

Activity

Value 0.199 (1.201) –Uniqueness 0.385 (1.904) 0.379 (2.181)Knowledge HRM practices - 0.604 (- 1.450) –Collaborative HRM practices 0.801 (1.492) –Size - 0.185 (- 1.514) –Internal R&D expenditures 0.027 (0.817) –External R&D expenditures - 0.060 (- 1.538) - 0.061 (- 8.333)

Value

Knowledge HRM practices 0.276 (1.069) 0.331 (3.531)Collaborative HRM practices 0.148 (0.438) –Size 0.040 (0.525) –Internal R&D expenditures - 0.001 (- 0.026) –External R&D expenditures - 0.007 (- 1.538) –

Uniqueness

Knowledge HRM practices - 0.182 (- 0.705) –Collaborative HRM practices 0.276 (0.822) 0.183 (1.648)Size 0.044 (0.640) –Internal R&D expenditures 0.021 (0.818) –External R&D expenditures 0.011 (1.572) –

Overall Fit Index Model 1 Model 1*

�² (df) 399.632 (276) 255.055 (248)p-value 0.00000 0.36553Satorra–Bentler �² 368.1039 255.4539p value 0.00017 0.35895GFI 0.755 0.824AGFI 0.689 0.770CFI 0.870 0.993Robust CFI 0.862 0.989RMSEA (90% CI) 0.072 (0.055, 0.086) 0.018 (0.000, 0.047)Robust RMSEA (90% CI) 0.062 (0.044, 0.078) 0.019 (0.000, 0.048)

coeff1a = Model 1 parameters; * = adjusted.If t value > 1.64 relation is signifi cant at 10%; if t value > 1.96 relation is signifi cant at 5%; if t value > 2.576 relation is signifi cant at 1%.



For scholars researching the RBV, this finding is consistent with the literature con-firming that with the appropriate manage-ment of a key resource (unique knowledge), firms enhance their innovative capability and, by extension, their competitive advan-tage and performance (Barney, 1991, 1995; Lengnick-Hall & Lengnick-Hall, 2002; López-Cabrales et al., 2006; Pérez-Luño et al., 2007). Furthermore, in a similar manner to that pro-posed by Barney and Wright (1998), the firm

must also have an appropriate managerial strategy to take advan-tage of these resources, as collab-orative HRM practices do in our study. Our results also confirm the thesis that HRM practices facili-tate knowledge. Specifically, HRM practices based on knowledge are very important for the procure-ment of valuable knowledge, while collaborative HRM practices influence unique knowledge. This result is interesting because it con-firms that there is no universal HRM model for improving both the value and the uniqueness of knowledge. Each of the two knowledge characteristics is asso-ciated with a different and specific design of HRM practices.

With respect to the control variables, only external R&D ex-penditures have a significant ef-fect on our dependent variables. These expenditures have a dou-ble and opposite influence. That

is, they significantly and negatively affect innovative activity, and they significantly and positively influence performance. These findings are not surprising if we consider that to be innovative, a company should be able to develop new products or services by itself, departing from the internal develop-ment of new ideas (for example, those from its R&D department). For this reason, we consider it appropriate that these external expenditures harm such innovative behav-ior because they are a way of externalizing the innovative activity. It is presumably expensive, however, to develop internal

ideas. Therefore, the positive influence of external R&D expenditures on perfor-mance can be an indication of the utility, in terms of efficiency, of outsourcing such expenses.

Finally, it is interesting to remember that we focused and conducted our study on R&D units. According to our results, unique knowledge from these employees is the most outstanding resource for innovation. On the other hand, we found that certain knowl-edge-based and collaborative HRM practices are not relevant in such contexts (such as empowerment, participation in decision-making processes, or job rotations), as they were eliminated from the original HRM practice measurement scales.

These results also have practical implica-tions. First, the type of knowledge employ-ees in R&D departments possess is a key factor for product innovation. Managers interested in developing innovations must identify and procure employees with unique and firm-specific knowledge that is hard to copy and determine its competitive advan-tage. Second, managers must manage these employees by means of collaborative HRM practices such as selection processes based on interpersonal abilities, training activities focused on team building, and appraisals based on team performance and/or employ-ees’ ability to work in groups. These prac-tices drive the skills and attitudes that allow the employee interactions and knowledge sharing that are necessary for product in-novation. Third, with respect to the positive relationship of external R&D expenses with performance and the negative one with in-novative activity, we propose that compa-nies should balance their R&D expenditures to take advantage of their effects on perfor-mance but should not forget their damage to innovative behavior. Finally, it is very important to recall that we found a positive relationship between innovative capability and performance. While this finding is use-ful for academics analyzing the role of orga-nizational capabilities on performance, it is even more important in its practical impli-cations. That is, supporting the view that investing in innovation is profitable can

This result is

interesting because

it confirms that there

is no universal HRM

model for improving

both the value and

the uniqueness of

knowledge. Each of

the two knowledge

characteristics is

associated with

a different and

specific design of

HRM practices.



motivate managers to devote resources to this activity.

Despite the contributions cited, our study does have certain limitations. We have focused our research on human capital but missed the relationships with other as-pects of knowledge such as social capital (knowledge used by networks of employees) and organizational capital (institutionalized and codified knowledge). These relation-ships could be taken into account for future research, as it would be interesting to assess whether social and organizational capital may enhance the value and uniqueness of human capital. Second, even when we had enough data to conduct our research with sufficient robustness, the sample size was not ideal to test relationships with struc-tural equation modeling (Hair et al., 1999) and did not allow for segmentation accord-ing to the industries considered in the pop-ulation. Certain homogeneity among firms exists, however, because they were all from innovative sectors, according to the Spanish Office of Patents. Third, we conducted a transactional study. In the future, it would be interesting to analyze data in a longitudi-nal way to gather information about the different cycles that the innovative activity requires. Finally, only one person in each firm, the manager responsible for each R&D unit, answered our questionnaire. Neverthe-less, as we focused our research on R&D units, the pretest and expert panel con-ducted before sending the questionnaires ensured that this manager was the person most qualified to assess the knowledge of his or her employees and the department’s HRM practices. In addition, we used an ob-

jective measure of profits to reduce com-mon method variance error.

We also assumed that all hypotheses that were not supported could be considered limitations but also future lines of research. For that reason, it could be interesting to investigate thoroughly each of the relation-ships that did not appear to be significant. It is also important to analyze why valuable knowledge has no influence on innovative capability, although such knowledge is con-sidered relevant for sustaining human capi-tal. Last, although we focused on two groups of HRM practices, it would be interesting to complete this analysis by including other groups of practices. It would also be interest-ing to open a new line of research based on the findings about the usefulness of invest-ing in internal or external R&D expenditures, depending on the ultimate aim of the com-panies (innovation or performance).

In conclusion, this study demonstrated the existence of two objectives that HRM should pursue to achieve innovative capa-bility. On the one hand, management should incorporate HRM practices as selec-tion processes based on interpersonal abili-ties and training activities, and appraisals based on employees’ ability to work in groups. On the other hand, organizations should bear in mind that the success of these practices, in terms of innovation and performance, depends on their employees’ unique knowledge.

Acknowledgment

Financial support for this paper was provided by the Spanish MEC Project 2006-15105 .

ALVARO LOPEZ-CABRALES, Ph.D., is an assistant professor of human resource management in the Business Administration Department, Universidad Pablo de Olavide (Seville, Spain), where he obtained his doctorate in 2003. His current work focuses on research in human capital, employment relationships, and organizational capabilities and innovation, and on publishing his research in several Spanish and international journals. He teaches human resource management courses to under-graduate, MBA, and PhD students.



References

Adler, P. S., & Kwon, S. (2002). Social capital: Prospects for a new concept. Academy of Management Review, 27(1), 17–40.

Alegre, J., Lapiedra, R., & Chiva, R. (2006). A measure-ment scale for product innovation performance. European Journal of Innovation Management, 9(4), 333–346.

Amar, A. D. (2002). Managing knowledge workers: Unleashing innovation and productivity. Westport, CT: Quorum.

Amit, R., & Belcourt, M. (1999). Human resource management processes: A value-creating source of competitive advantage. European Management Journal, 17(2), 174–181.

Anand, N., Gardner, H. K., & Morris, T. (2007). Knowledge-based innovation: Emergence and embedding of new practice areas in management consulting fi rms. Academy of Management Journal, 50(2), 406–428.

Anderson, J. C., & Gerbing, D. W. (1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological Bulletin, 103(3), 411–423.

Argote, L., & Ingram, P. (2000). Knowledge transfer: A basis for competitive advantage in fi rms. Organizational Behavior and Human Decision Processes, 82(1), 150–169.

Arthur, J. B. (1994). Effects of human resources systems on manufacturing performance and turnover. Academy of Management Journal, 37(3), 670–687.

Avlonitis, G. J., Papastathopoulou, P. G., & Gounaris, S. P. (2001). An empirically-based typology of product innovativeness for new fi nancial services: Success and failure scenarios. Journal of Product Innovation Management, 18(5), 324–342.

Bagozzi, R. P. (1994). Structural equation models in marketing research: Basic principles. In R. P. Bagozzi (Ed.), Principles of marketing research. Oxford, UK: Blackwell.

Bakker, A. B., Demerouti, E., & Verbeke, W. (2004). Using the job demands-resources model to predict burnout and performance. Human Resource Management, 43(1), 83–104.

Balkin, D., Markman, G., & Gomez-Mejia, L. (2000). Is CEO pay in high technology fi rms related to innovation? Academy of Management Journal, 43(6), 1118–1129.

Balkin, D., & Montemayor, E. (2000). Explaining team-based pay: A contingency perspective based on the organizational life cycle, team design and organizational learning literatures. Human Resource Management Review, 10(3), 249–269.

Bantel, K., & Jackson, S. E. (1989). Top management and innovations in banking: Does the composi-tion of the top team make a difference [Special issue]? Strategic Management Journal, 10, 107–124.

Barczak, G., & Wilemon, D. (2003). Team members’ experiences in new product development, views from the trenches. R & D Management, 33(5), 463–479.

ANA PÉREZ-LUÑO, Ph.D., is an assistant professor of management in the Business Admin-istration Department, Universidad Pablo de Olavide (Seville, Spain), where she obtained her doctorate in 2007. Her current work focuses on research in innovation, knowledge, competitiveness, and resource-based theory, and on publishing her research in several Spanish and international journals. She teaches organization theory and business admin-istration to undergraduate students, and entrepreneurship and innovation to MBA and Ph.D. students.

RAMÓN VALLE CABRERA is a professor of human resource management in the Busi-ness Administration Department, Universidad Pablo de Olavide (Seville, Spain). He obtained his doctorate at the Universidad de Sevilla in 1983. His teaching and research interests focus on strategic human resource management and innovation. He is head-ing several research projects on innovation, organizational capital, and employment relationships, and he is coauthor of several HRM textbooks and papers in international journals.



Barney, J. B. (1991). Firm resources and sustained competitive advantage. Journal of Management, 17(1), 99–120.

Barney, J. B. (1995). Looking inside for competitive advantage. Academy of Management Executive, 9(4), 49–60.

Barney, J. B., & Wright, P. M. (1998). On becoming a strategic partner: The role of human resources in gaining competitive advantage. Human Resource Management, 37(1), 31–46.

Barton, H., & Delbridge, R. (2001). Development in the learning factory: Training human capital. Journal of European Industrial Training, 25(9), 465–472.

Beatty, R. W., & Schneier, C. E. (1997). New HR roles to impact organizational performance: From partners to players. Human Resource Management, 36(1), 29–50.

Bierly, P., & Chakrabarti, A. (1996). Generic knowledge strategies in the U.S. pharmaceutical industry [Special issue]. Strategic Management Journal, 17, 123–135.

Boxall, P. (1996). The strategic HRM debate and the resource-based view of the fi rm. Human Resource Management Journal, 6(3), 59–75.

Capon, N., Farley, J. U., Lehmann, D. R., & Hulbert, J. M. (1992). Profi les of product innovators among large U.S. manufacturers. Management Science, 38(2), 157–169.

Churchill, G. A. (1979). A paradigm for developing better measures of marketing constructs. Journal of Marketing Research, 16(1), 64–73.

Cohen, W. M., & Levinthal, M. D. A. (1990). Absorp-tive capacity: A new perspective on learning and innovation [Special issue]. Administrative Science Quarterly, 35(1), 128–152.

Costa, P., & McCrae, R. (1992). Neo PI-R professional manual. Odessa, FL: Editorial Psychological Assess-ment Resources.

Damanpour, F. (1991). Organizational innovation: A meta-analysis of effects of determinants and moderators. Academy of Management Journal, 34(3), 555–590.

Denison, D., Hart, S., & Kahn, J. (1996). From chimneys to cross-functional work teams: Developing and validating a diagnostic model. Academy of Management Journal, 39(4), 1005–1024.

Dillman, D. A. (1991). The design and administration of mail surveys. Annual Review of Sociology, 17(1), 225–249.

Donnellon, A. (1996). Crossfunctional teams in product development: Accommodating the structure to the

process. Journal of Product Innovation Manage-ment, 10(5), 377–392.

Doorewaard, H., & Meihuizen, H. (2000). Strategic performance options in professional service organizations. Human Resource Management Journal, 10(2), 39–57.

Drucker, P. (1999). Knowledge worker productivity: The biggest challenge. California Management Review, 41(2), 79–94.

Eisenberger, R., & Armeli, S. (1997). Can salient rewards increase creative performance without reducing intrinsic creative interest? Journal of Personality and Social Psychology, 72(3), 652–663.

Fornell, C., & Larcker, D. F. (1981). Structural equation models with unobservable variables and measurement error: Algebra and statistics. Journal of Marketing Research, 18(3), 7.

Foss, N. J. (2007). The emerging knowledge govern-ance approach: Challenges and characteristics. Organization, 14(1), 29–52.

Galunic, C., & Rodan, S. (1998). Resource recombina-tions in the fi rm: Knowledge structures and the potential for Schumpeterian innovation. Strategic Management Journal, 19(12), 1193–1201.

Gerbing, D. W., & Anderson, J. C. (1988). An updated paradigm for scale development incorporating unidimensionality and its assessment. Journal of Marketing Research, 25(2), 186–192.

Griffi n, A. (1997). The effect of project and process characteristics on product development cycle time. Journal of Marketing Research, 34(1), 24–35.

Gupta, A., & Singhal, A. (1993). Managing human resources for innovation and creativity. Research Technology Management, 36(3), 41–48.

Hair, J. F., Anderson, R. E., Tatham, R. L., & Black, W. C. (1999). Multivariate data analysis. Englewood Cliffs, NJ: Prentice Hall.

Helleloid, D., & Simonin, B. (1994). Organizational learning and a fi rm’s core competence. In G. Hamel & A. Heene (Eds.), Competence-based competition. New York: Wiley.

Huselid, M. A. (1995). The impact of human resource management practices on turnover, productivity and corporate fi nancial performance. Academy of Management Journal, 38(3), 635–672.

Jackson, S. (1992) Team composition in organizational settings: Issues in managing an increasingly diverse force group. In S. Worchel, W. W ood, & J. Simpson (Eds.), Group processes and productiv-ity. Newbury Park, CA: Sage.



James, W. (2002). Best HR practices for today’s innovation management. Research Technology Management, 45(1), 57–60.

Kang, S.-C., Morris, S. S., & Snell, S. A. (2007). Relational archetypes, organizational learning, and value creation: Extending the human resource architecture. Academy of Management Review, 32(1), 236–256.

Kimberly, J. R., & Evanisko, M. J. (1981). Organization-al innovation: The infl uence of individual, organizational, and contextual factors on hospital adoption of technological and administrative innovations. Academy of Management Journal, 24(4), 689–713.

Kogut, B., & Zander, U. (1992). Knowledge of the fi rm, combinative capabilities, and the replication of technology. Organization Science, 3(3), 383–397.

Kunkel, G. (1997). Rewarding product development success. Research Technology Management, 40(5), 29–31.

Laursen, K. (2002). HRM practices for innovation per-formance. International Journal of the Economic Business, 9(1), 139–166.

Laursen, K., & Foss, N. (2003). New HRM practices, complementarities and the impact on innovation performance. Cambridge Journal of Economics, 27(2), 243–263.

Lengnick-Hall, M., & Lengnick-Hall, C. (2002). Human resource management in the knowledge economy: New challenges, new roles, new capabilities. San Francisco: BK.

Lepak, D. P., & Snell, S. A. (1999). The human resource architecture: Toward a theory of human capital allo-cation and development. Academy of Management Review, 24(1), 31–48.

Lepak, D. P., & Snell, S. A. (2002). Examining the human resource architecture: The relationships among human capital, employment and human resource confi guration. Journal of Management, 28(4), 517–543.

Lepak, D. P., Liao, H., Chung, Y., & Harden, E. (2006). A conceptual review of human resource manage-ment systems in strategic human resource management research. Research in Personnel and Human Resources Management, 25(1), 217–271.

Lepak, D. P., Takeuchi, R., & Snell, S. A. (2003). Employment fl exibility and fi rm performance: Examining the interaction effects of employment mode, environmental dynamism and techno-logical intensity. Journal of Management, 29(5), 681–703.

Li, H., & Atuahene-Gima, K. (2001). Product innovation strategy and the performance of new technology ventures in China. Academy of Management Journal, 44(6), 1123–1134.

London, M., & Smither, J. (1999): Empowered self-development and continuous learning. Human Resource Management 38(1): 3–15.

López-Cabrales, A., Valle, R., & Herrero, I. (2006). Contribution of core employees to organizational capabilities and effi ciency. Human Resource Management, 45(1), 81–100.

Mak, S., & Akhar, S. (2003). HRM practices, strategy orientations and company performance: A correlation study of publicly listed companies. Journal of American Academy of Business, 2(2), 510–515.

McEvily, S. K., & Chakravarthy, B. (2002). The persistence of knowledge-based advantage: An empirical test for product performance and technological knowledge. Strategic Management Journal, 23(4), 285–305.

Montoya-Weiss, M. M., & Calantone, R. (1994). Determinants of new product performance: A review and meta-analysis. Journal of Product Innovation Management, 11(5), 397–417.

Mumford, M. (2000). Managing creative people: Strat-egies and tactics for innovation. Human Resource Management Review, 10(3), 313–351.

Nahapiet, J., & Ghoshal, S. (1998). Social capital, intellectual capital, and the organizational advantage. Academy of Management Review, 23(2), 242–266.

Newbert, S. L. (2007). Empirical research on the resource-based view of the fi rm: An assessment and suggestions for future research. Strategic Management Journal, 28(2), 121–135.

Nonaka, I., & Takeuchi, H. (1995). The knowledge creat-ing company. Oxford: Oxford University Press.

OECD/Eurostat. (1997). Proposed guidelines for col-lecting and interpreting technological innovation data (Synthesis Report No. 2: Country Studies). Paris: Author.

Paauwe, J., & Boselie, P. (2005). HRM and perform-ance: What next? Human Resource Management Journal, 15(4), 68–83.

Peltokorpi, V., & Tsuyuki, E. (2006). Knowledge govern-ance in a Japanese project-based organization. Knowledge Management Research & Practice, 4(1), 36–45.

Pérez-Luño, A., Valle Cabrera, R., & Wiklund, J. (2007). Innovation and imitation as sources of sustainable competitive advantage. Management Research, 5(2), 67–79.



Prahalad, C. K., & Hamel, G. (1990). The core compe-tence of the corporation. Harvard Business Review, 68(3), 79–91.

Purcell, J. (1996). Best practice and best fi t: Chimera or cul-de-sac? Human Resource Management Journal, 9(3), 26–41.

Schuler, R., & Jackson, S. (1987). Linking competitive advantage with human resource management practices. Academy of Management Executive, 1(3), 207–219.

Schultz, T. W. (1961). Investment in human capital. American Economic Review, 51(1), 1–17.

Snell, S., & Dean, J. (1994). Strategic compensation for integrated manufacturing: The moderating effects of jobs and organizational inertia. Academy of Management Journal, 37(5), 1109–1140.

Snell, S., Lepak, D., & Youndt, M. (1999). Managing the architecture of intellectual capital: Implications for strategic human resource management. Research in Personnel and Human Resource Management, (Suppl. 4), 175–193.

Subramaniam, M., & Youndt, M. A. (2005). The infl u-ence of intellectual capital on the types of innova-tive capabilities. Academy of Management Journal, 48(3), 450–463.

Taggar, S. (2002). Individual creativity and group abil-ity to utilize individual creative resources: A mul-tilevel model. Academy of Management Journal, 45(2), 315–330.

Tang, H. K. (1998). An integrative model of in-novation in organizations. Technovation, 18(5), 297–309.

Teece, D. J., Pisano, G., & Shuen, A. (1997). Dynamic capabilities and strategic management.

Strategic Management Journal, 18(7), 509–533.

Thompson, L. (2003). Improving the creativity of organizational work groups. Academy of Manage-ment Executive, 17(1), 96–111.

Ulrich, D. (1998). Intellectual capital = competence × commitment. Sloan Management Review, 39(2), 15–26.

Ulrich, D., & Lake, D. (1991). Organizational capabil-ity: Creating a competitive advantage. Academy of Management Executive, 5(1), 77–92.

Wernerfelt, B. (1984). A resource-based view of the fi rm. Strategic Management Journal, 5(2), 171–180.

Wiklund, J., & Shepherd, D. (2003). Knowledge-based resources, entrepreneurial orientation, and the performance of small and medium-sized busi-nesses. Strategic Management Journal, 24(13), 1307–1314.

Youndt, M., Snell, S., Dean, J., & Lepak, D. (1996). Human resource management, manufacturing strategy and fi rm performance. Academy of Man-agement Journal, 39(4), 836–866.

Youndt, M. A., Subramaniam, M., & Snell, S. A. (2004). Intellectual capital profi les: An examination of investments and returns. Journal of Management Studies, 41(2), 335–362.

Zhou, J. (1998): Feedback valence, feedback style, task autonomy, and achievement orientation: Interactive effects on creative performance. Journal of Applied Psychology, 83(2), 261–276.

Zhou, K. Z. (2006). Innovation, imitation, and new product performance: The case of China. Industrial Marketing Management, 35(3), 394–402.

Documents

Knowledge as a mediator between HRM practices and innovative activity