A framework for evaluating relationship among HRM practices, project success and organizational benefit

Qual QuantDOI 10.1007/s11135-014-0033-8

A framework for evaluating relationship among HRMpractices, project success and organizational benefit

Li-Ren Yang · Jieh-Haur Chen · Kun-Shan Wu ·Di-Man Huang · Cheng-Hao Cheng

© Springer Science+Business Media Dordrecht 2014

Abstract Human resource management (HRM) practices have been recognized increasinglyas a basis for achieving competitive advantage. However, conceptualizing HRM in the projectcontext is still underdeveloped. The primary purpose of this study is to validate a frameworkfor assessing the associations among HRM practices, project success, and organizationalbenefit in new product development (NPD) firms. The study also evaluates the moderatingrole of working environment factors in the relationship between HRM practices and NPDproject success. The analyses of HRM practices and relationships with NPD project successand organizational benefit are based on an industry-wide survey in the Taiwanese high-techindustry. The results suggest that implementation of HRM practices contribute significantlyto NPD project success, which subsequently bringing a number of potential benefits to a firm.In addition, the findings indicate that the positive relationship between HRM practices andNPD project success depends on work hours and time availability.

Keywords Human resource management · New product development · Project success ·Organizational benefit

L.-R. Yang (B) · K.-S. Wu · C.-H. ChengDepartment of Business Administration, Tamkang University, 151 Ying-chuan Rd., Tamsui Dist.,New Taipei City 251, Taiwane-mail: [email protected]

J.-H. ChenInstitute of Construction Engineering and Management,National Central University, Jhongli 320, Taoyuan, Taiwan

D.-M. HuangDepartment of Management Sciences, Tamkang University, 151 Ying-chuan Rd., Tamsui Dist.,New Taipei City 251, Taiwan

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1 Introduction

In order to respond rapidly to market needs and increase profits, companies must shortenproduct development and reduce time-to-market for new products. New product develop-ment (NPD) projects have received substantial attention in the industry as they help thecompanies in achieving important business goals. Many product development firms attemptto use project management techniques to attain certain predetermined objectives (Hyväri2006). Since more and more companies become project-based organizations, the field ofproject management is quickly expanding. Projects are temporary organizations. When start-ing a new project, the organization must change the human resource configuration. Humanresource management (HRM) is important in any organization, including project-orientedcompanies. The project-oriented companies adopt temporary work processes to deliver prod-ucts and services to clients, which creates a dynamic work environment, where additionalpressures can be imposed on the employee from fluctuating work-loads, uncertain require-ments, and multiple role demands (Turner et al. 2008). Because there has been a shift fromtechnical to more human project management (Turner et al. 2003), some researchers havebeen active in exploring HRM in the project-oriented companies. HRM can be viewed ascore processes of the project-oriented companies, affecting the way the organization acquiresand uses human resources, and how employees experience the employment relationship(Huemann et al. 2007). HRM policies, processes, and practices in the project-oriented com-panies are in some way supportive of project-oriented working and are different from moretraditional HRM processes and practices (Wright and Boswell 2002) which are designed forthe classically-managed organization where the emphasis is not on projects but instead onroutine products and services and where the job requirements are well defined and stable(Keegan and Turner 2003). In this dynamic environment, the human resource configurationfor the project-oriented companies is constantly changing. Thus, the challenges of ensuringemployee well-being and ethical treatment of workers are important for the project-orientedcompanies. Ideal project-oriented companies have a specific management culture expressedin the empowerment of employees, process orientation and teamwork, continuous and dis-continuous organizational change, customer orientation, and networking with clients andsuppliers (Huemann et al. 2007). In addition, HRM policies, practices, and processes needto be designed to meet the specific needs of the project-oriented companies (Huemann et al.2004). Previous studies suggested that research on human resource management at the projectlevel is not well developed (Huemann et al. 2007). Most models explaining project successwere based on theory rather than on empirical proof. The literature stated that the problemsrelated with HRM practice adoption are one of the main reasons for project failures (Belout1998).

Human resource management may be seen as a source of sustained competitive advantagefor organizations (Cascio and Bailey 1995). Thus, research in HRM has made considerableprogression exploring the relationship between HRM practices and organizational perfor-mance. These practices include recruitment and selection, personnel planning, training anddevelopment, performance management, teamwork, performance-related pay, employmentsecurity, internal career possibilities, participation, communication, and job descriptions (VanDe Voorde et al. 2012; Boselie et al. 2005). The literature indicates that HRM is one of themost important elements in organizational success (Cascio and Bailey 1995). Previous stud-ies have also suggested that adopting HRM practices can improve firms’ competitiveness,thus enhancing their legitimacy (Patel and Cardon 2010).

Although HRM appears to be related to desirable performance outcomes, research haspoorly explained the role of HRM practices in achieving NPD project success. Most NPD

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A framework for evaluating relationship

studies have focused more on the product rather than on the development process (Funk 1992;Page 1993). Additionally, conceptualizing HRM in the project context is still rudimentary(Huemann et al. 2007). This lack of information regarding uncertain competitive advantagefrom human resource management has resulted in a manager’s reluctance to develop humanresource strategy. There is thus a need to examine how HRM practices influence projectsuccess in the NPD domain. On the other hand, working environment is also central toimproving project success (Mustapha and Naoum 1997). Working environment can be definedas the perception of the work environment and can differ from project to project (Pheng andChuan 2006). The working environment factors can be categorized into two main categories:job condition related variables and project characteristic related variables (Pheng and Chuan2006). One approach to HRM research is contingency approach. The contingency approachimplies that working environment factors moderate the relationship between HRM practicesand project success (Akhtar et al. 2008). Although theoretical arguments have been made infavor of the contingency approach, there is relatively weak empirical support for the approach(Patel and Cardon 2010).

To address these limitations and advance the understanding of HRM practices in the NPDproject context, the primary purpose of this study is to empirically validate a model forassessing the relationships among HRM practices, NPD project success, and organizationalbenefit. The study also examines the moderating role of work environment factors (includingjob condition related variables and project characteristic related variables) in the relationshipbetween HRM practices and NPD project success. This study reveals the importance ofdeveloping HRM practices to enhance cross-functional cooperation in NPD project teams.The results offer guides to improve NPD project success and further gain a number of potentialbenefits to a firm.

2 Theoretical background and hypotheses

HRM practice has been recognized increasingly as a basis for achieving competitive advan-tage, particularly for firms operating in challenging and rapidly changing competitive envi-ronments (Cascio and Bailey 1995). Wright and MacMahan (1992) define it as: “the plannedhuman resource deployments and activities intended to enable an organization to achieve itsgoals.” HRM is a new and special approach to personnel management, focusing on HRMoutcomes like commitment, flexibility, and quality (Guest 1987). It can be distinguishedfrom traditional conceptions of personnel management (Storey 1995). The achievement ofthese human resource outcomes was, in turn, expected to contribute to a range of positiveorganizational outcomes, including high job performance, low turnover, low absence, andhigh cost-effectiveness through the full utilization of employees (Paauwe 2009). HRM refersto all those activities associated with the management of people in firms (Boxall and Purcell2008), which stresses the inclusion of multiple management activities, in contrast to a focuson the effects of a single management activity in isolation from other management activities(Van De Voorde et al. 2012). HRM has various roles. Most studies typically cover practiceslike recruitment and selection, personnel planning, training and development, performancemanagement, teamwork, performance-related pay, employment security, internal career pos-sibilities, participation, and communication (Van De Voorde et al. 2012). On the other hand,other practices such as job design and work-life balance are less often included (Boselie et al.2005; Wall and Wood 2005). Thus, many articles were published which presented evidenceon the performance effects not only of single HRM practice, but also of bundles or combina-tions of practices (Paauwe 2009; Arthur 1994; Guest et al. 2004). Most studies group these

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various practices into a composite score which represents the overall HRM system (Wall andWood 2005).

One of the HRM models, Behavioural Perspective, was developed to explain the positiveeffect of HRM on employee behaviours, which argues that HRM activities are adoptedto elicit and control those employee behaviours which contribute to overall organizationalperformance (Wright and MacMahan 1992). Social exchange theory is another widely usedtheory, which states that employees interpret HRM activities as indicative of organizationalsupport and care for them, and reciprocate accordingly with commitment, satisfaction, andtrust (Whitener 2001). Appelbaum (2002) proposed a more comprehensive conceptual model,which views the adoption of HRM activities as increasing employees’ abilities, providingopportunities to participate, and increasing motivation (the so-called AMO theory). From thisperspective, HRM can increase job satisfaction, commitment, and trust and reduces stresslevels, which positively influence organizational performance.

From theoretical perspectives on the HRM-Performance relationship, Boselie et al. (2005)concluded that the three most commonly used theories are contingency theory, resource basedview (RBV), and the AMO framework. Contingency theory and RBV are both situated atthe organizational level, whereas the AMO framework focuses on the importance of takinginto account variables at the individual level like employees’ skills and competences, theirmotivation, and their opportunity to participate (Paauwe 2009). The performance outcomes ofHRM can be evaluated in three ways (Dyer and Reeves 1995): financial outcomes (e.g. profits,sales, market share), organizational outcomes (e.g. output measures such as productivity,quality, efficiency), and HR-related outcomes (e.g. attitudinal and behavioural impacts amongemployees, such as satisfaction, commitment, intention to quit).

Organizational benefit is one of the most stable concepts to contribute to organizationalintegration, due to its strong link to vision and to stakeholders (Machicao 2011). It can beconstrued as measures of performance (Appelbaum et al. 1994). Organizational benefit canbe defined as “an outcome of change which is perceived as positive by an organization”(Bradley 2010). Three dimensions of organizational benefit were distinguished by Eckartzet al. (2009): (1) Operational, managerial, and strategic benefits (Shang and Seddon 2002),(2) Process, customer, financial, and innovation benefits (Kallunki et al. 2011; Hunton etal. 2003; Kaplan and Norton 1993; Atuahene-Gima 1995), and (3) Benefits falling into ITinfrastructure and organizational categories (Shang and Seddon 2002; Atuahene-Gima 1995).Based on Atuahene-Gima (1995), this study focuses on five important organizational benefitsassociated with NPD: overall benefits, new market and product opportunities, new technology,new knowledge and methods, and firm reputation. Researchers have built evidence that linksHRM practices with corporate performance (Paauwe and Boselie 2005; Guest et al. 2003;Som 2008). Wright et al. (2005) identified 66 empirical studies that analyzed the relationshipbetween a set of HRM practices and organizational level performance. Nevertheless, althoughit is well accepted that HRM is positively related to organizational performance, there seems arising interest and need for additional robust and quantitative evidence to support the HRM-performance link (Gerhart 2005). Based on these arguments, the following hypothesis isproposed:

H1: Implementation of HRM practices positively influences organizational benefit in NPDfirms.

Project is an autonomous organization but connected to parent organization (Artto et al.2008). Project success has been widely discussed in the project management literature. Tra-ditional way of measuring project success is the so-called golden triangle of time, bud-get, and required quality, which can be qualified as a more ‘narrow’ view in this respect

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(Westerveld 2003). However, there are more, possibly competing, criteria that can be identi-fied (Atkinson 1999). The judgment is made by a wide range of potential stakeholders, overdifferent time horizons (Westerveld 2003). Project success criteria will differ from projectto project depending on a number of issues, for example, size, uniqueness and complexity(Wateridge 1998). Although there is no consistent interpretation of the term project success,it is recognized that the criteria for project success must be agreed at the commencement ofthe project to avoid differences amongst project teams (Baccarini 1999).

According to the PMBOK Guide published by the Project Management Institute (PMI),project success criteria shall include the golden triangle and key project stakeholders’ sat-isfaction of the project (Project Management Institute 2004). Limitations of the traditionalway of measuring success are clearly known and researchers have started to talk about intro-ducing new success measures (Al-Tmeemy et al. 2011). Thus, many studies have expandedproject success criteria into other aspects, such as organizational objectives, stakeholders’satisfaction, customer’s benefit, future potential to organization, etc. (Wang and Huang 2006).Shenhar et al. (2001) also discovered the four criteria of project efficiency, customer’s ben-efit, organizational success, and future potential to organization. Lim and Mohamed (1999)viewed project success by the use of micro and macro criteria. They contended that the macroviewpoint of project success addresses the question: Is the original project concept achieved?On the other hand, the micro viewpoint of project success deals with project achievements insmaller component levels, which referred to at the conclusion of project construction phaseand the parties involved in the construction (Lim and Mohamed 1999). Specifically, theirmicro criteria included time, cost, quality, performance and safety, and their macro criteriaincluded the micro criteria plus the project product’s actual benefit in the operation phase.

As indicated by the review of literature, human resource management practices play animportant role on project success (Ling et al. 2009). However, most of the HRM strategieswere difficult to identify and some were not clear and well organized. The causes of poorperformance often originate in poor HRM practices. A review of the literature suggests thatHRM practice implementation may bring a number of potential benefits to a firm (Hassidand Fafaliou 2006; Deshpande and Golhar 1997, 1996; Deshpande et al. 1994) and furtherimprove organiztional performance (Chen and Huang 2009). The results of previous studiesalso confirmed that adoption of HRM practices may contribute to project success (Ling et al.2009; Belout 1998). The prior research indicated that organizational benefit represents theexternal success of the new product, while project success reflects internal success (Garciaand Sanzo 2008). Project success may act as an internal success, which subsequently leadsto improved organizational performance (Tatikonda and Montoya-Weiss 2001; Chen et al.2005). Thus, the second and third hypotheses are as follows:

H2: Implementation of HRM practices positively influences NPD project success.H3: NPD project success has a significant positive effect on organizational benefit.

One approach to HRM research is contingency approach. The contingency approachimplies that working environment factors moderate the relationship between HRM practicesand project success (Akhtar et al. 2008). In other words, HRM practices may influence projectsuccess positively in combination with working environment factors. Working environmentcan be defined as the perception of the work environment and can differ from project toproject (Pheng and Chuan 2006). Working environment is central to improving project suc-cess (Mustapha and Naoum 1997). The working environment factors can be categorized intotwo main categories: job condition related variables and project characteristic related vari-ables (Pheng and Chuan 2006). Katz (1971) investigated the impact of job related variableson managerial effectiveness. The variables identified in this study included involvement at

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the contract stage, team relationship, salary, job satisfaction, cost control, job security, andworking hours. The findings indicated that variables such as salary, job satisfaction, and jobsecurity affect a project manager’s motivation. According to Pheng and Chuan (2006), thisstudy focuses on five important job condition related variables: salary, job satisfaction, jobsecurity, working hours, and availability of information. On the other hand, every projectis unique in nature and does not involve any repetitive processes. Projects involve uncer-tainty and carry risk. Turbulence in the project’s environment, dynamism, uncertainty, andcomplexity tend to be important issues that affect a project and its strategy (Artto et al.2008). According to Pheng and Chuan (2006), five important project characteristic variableswere considered in this study: time availability, complexity, team relationship, materials andsupplies availability, and project duration.

Previous studies have shown that working environment factors may significantly con-tribute to project success (Mustapha and Naoum 1997; Pheng and Chuan 2006; Katz 1971).In addition, working environment factors were proposed for examination as a possible mod-erator of the relationship between HRM and project success (Akhtar et al. 2008; Müllerand Turner 2007). Working environment factors affect the performance of project managers,team relationships, time availability, and materials and supplies of projects (Pheng and Chuan2006). Overall, these factors influence coordination of efforts, resources, routines, and sys-tems (Patel and Cardon 2010). Thus, they may modify the form of the relationship betweenHRM practices and project success. In other words, HRM practices may have a positive effecton project success, particularly when the project is faced with certain working environmentfactors. This leads to the following hypothesis:

H4: Working environment factors (including job condition related variables and projectcharacteristic related variables) moderate the relationship between HRM practices andNPD project success.

3 Research design

3.1 Research instrument

The survey instrument was developed to measure adoption of HRM practices in NPD projectsand its associations with NPD performance in the Taiwanese high-tech industry. Study par-ticipants were first asked to identify a recent NPD project that they were familiar with forassessment. For the subject project, the survey requests the participant to provide informa-tion about levels of HRM practices applied on the project. The second section of the surveyassesses NPD project success and organizational benefit from various aspects. The final sec-tion obtains information concerning the project (i.e., working environment factors in termsof job condition related variables and project characteristic related variables) and the respon-dent. These projects were categorized according to five job condition related variables (Phengand Chuan 2006): salary, job satisfaction, job security, working hours, and information avail-ability. In addition, the projects were classified according to five project characteristic relatedvariables (Pheng and Chuan 2006): time availability, complexity, team relationship, materialsand supplies of project (materials and supplies availability), and project duration.

3.2 Sample selection and data collection and analysis

The Taiwanese high-tech industry includes five major sectors: integrated circuit (IC), com-munication equipment, consumer electronics, computer hardware, and precision machine.

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Most high-tech companies are located in three core science parks: Hsinchu Science Park,Central Taiwan Science Park, and Southern Taiwan Science Park, which are located in thenorthern, central, and southern parts of Taiwan respectively. The sampling frame (i.e. a listof all those within a population which can be sampled) for the study is a list of high-techfirms obtained from three main sources namely, the list of companies in Hsinchu SciencePark, Central Taiwan Science Park, and Southern Taiwan Science Park. Thus, the populationsize for the study is 602 high-tech companies.

An industry-wide survey of HRM practices, NPD project success, and organizationalbenefit was conducted between December 2010 and February 2011. The data collection toolwas developed to collect project-based data. The targeted respondents were identified asnew product development practitioners who were familiar with project HRM, NPD projectsuccess, and organizational benefit. In order to obtain a truly representative sample, not onlywas the geographic mix of projects intentionally diverse, but a diverse mix of participationwas sought with respect to sector of industry. Additionally, a specified mix of product typewas targeted in order to obtain a representative sample of the industry.

All of the companies were contacted via phone or email to identify the practitionersinvolved in NPD projects by name and title. The investigators then contacted the respondentsto confirm their participation in this study and to make sure that they have adequate back-ground and experience. This approach helped the investigators select the right respondentswho possess adequate knowledge to properly evaluate HRM practices and NPD project suc-cess and are capable of answering all of the survey questions. Project responses were collectedvia paper and online surveys. After the initial mailing a second mailing of the survey was madeto non-respondents. Non-response bias was examined using the procedures recommendedby Armstrong and Overton (1977). It was assessed by comparing early (those respondingto the first mailing) and late (those responding to the second mailing) respondents. Usinga t-test, each variable was tested to determine if there is a significant difference in meansbetween early and late respondents at the 5 percent significance level. The results from thet-tests suggest that the early respondents do not significantly differ from the late responses.Accordingly, non-response bias was not considered a problem. More than 200 projects wereinvestigated and some were not included in the analysis because they contained insufficientinformation. In addition, the projects were examined to ensure that no duplicate project infor-mation was collected. Ultimately, 205 survey responses were used in the analysis. Table 1shows industry sector of projects and profile of respondents.

Structural equation modeling (SEM) is a statistical method for testing causal relationsusing a combination of statistical data and qualitative causal assumptions. The SEM approachwas used to validate the research model and to test Hypotheses H1 to H3. On the other hand,cluster analysis was used in an exploratory mode to develop an objective classification ofprojects. In order to identify homogeneous projects clusters with the same kinds of perceptionsof HRM practices, a K-means cluster analysis was performed on the basis of the dimensionsof HRM practices. To validate the results of the cluster analysis, a discriminant analysis wasalso conducted. The two-way ANOVA was then utilized to determine the joint effects ofHRM practices and environmental factors on project success and to test hypothesis H4.

3.3 Measurement and content validity

The study measured six HRM practices identified in the literature as being potentially rel-evant to project HRM: participation, work design, performance management, training anddevelopment, personnel planning, and teamwork. A 12-item multidimensional scale was usedto measure how respondents perceived HRM practices in their projects. Thus, the 12 items

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Table 1 Industry sector of projects and profile of respondents

Variable Category Percentage

Industry sector Computer hardware 36.4

Industry sector Communication equipment 12.7

Industry sector Consumer electronics 17.5

Industry sector Integrated circuit (IC) 12.7

Industry sector Precision machine 4.8

Industry sector Other 15.9

Position Product manager 25.3

Position R & D personnel 74.7

Age >45 9.5

Age 41–45 28.6

Age 36–40 30.1

Age 31–35 27.0

Age < 31 4.8

Years of experience in NPD >20 6.3

Years of experience in NPD 16–20 28.6



Years of experience in NPD <6 1.6

Education Master’s or Ph.D. degree 44.4

Education Bachelor’s degree 50.8

Education Associate’s degree 4.8

represent the mentioned six HRM practices. The survey used these items because the liter-ature and recommendations of ten product managers has shown that these items are closelylinked to project HRM. These professionals averaged 18 years of experience. The items usedto measure HRM practices were based on the items developed by Schuler (1994). In orderto evaluate the impact of the HRM practices on performance, this analysis had to reduce the12 items into fewer dimensions. Factor analysis with Varimax rotation was used to decidethe grouping of HRM practices construct. Only variables with a factor loading greater than.5 were extracted (Hair et al. 2006). The 12 items of HRM practices construct are classifiedinto two factors. They are “member empowerment and development” and “member expertiseand training.” All of the factor loadings range from 0.583 to 0.873, indicating a high level ofinternal consistency among the HRM practices items.

According to the PMBOK Guide published by the Project Management Institute (PMI),project success criteria shall include the golden triangle (time, budget, and required quality)(Project Management Institute 2004). In addition, many studies (Garcia and Sanzo 2008;Tatikonda and Montoya-Weiss 2001; Atuahene-Gima 1995) have expanded NPD projectsuccess criteria into innovation success. Thus, in this study, project success was measuredby the four dimensions of schedule success, cost success, quality success, and innovationsuccess. Questions from Chen and Huang (2009); Freeman and Beale (1992); Keller (1994);Ling et al. (2009), and Pinto and Mantel (1990) were adapted to measure NPD project success.The survey used these items because the literature and recommendations of the ten seniorNPD practitioners has shown that these items were applicable to NPD project success.

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Organizational benefit was measured with six items that required respondents to indicatethe extent to which the company had improved its sales, profitability, proprietary advantage,product opportunities, and cost efficiencies. Items used to rate organizational benefit werebased on the surveys developed by Atuahene-Gima (1995). The survey used these itemsbecause the literature and recommendations of the ten senior NPD practitioners has shownthat these items were applicable to organizational benefit in new product development firms.

Although some of the items used in evaluate NPD project success and organizationalbenefit have similar concept (for example, cost efficiency). They focus on different levels.The mediator variable (NPD project success) is at the project team level. On the other hand,the outcome variable (potential benefits to a firm) is at the organizational level. Responsesare given on 7-point scale to reduce error of central tendency, from 1 (strongly disagree) to7 (strongly agree). The content validity of the survey used in this study was tested througha literature review and interviews with the ten new product development practitioners. Therefined assessment items were included in the final survey. Finally, copies of a draft surveywere sent to three professors to pre-test for the clarity of questions. Their insights were alsoincorporated into the final version of the survey.

4 Results and analysis

4.1 Confirmatory factor analysis

Prior to estimating the structural model, a confirmatory factor analysis (CFA) was conductedto verify the measurement models. Multiple fit criteria were used to assess the overall fit ofthe models. The data were analyzed using the AMOS/SPSS statistical package. For HRMpractices, this study conducted three confirmatory factor analyses: the two-factor model(Model 1), the second order model (Model 2), and the model in which all 12 items loadedon one factor (Model 3). The models are shown in Fig. 1. To evaluate the goodness-of-fit ofthree alternative measurement models for HRM practices, CFA was first run for the two-factorsolution (Model 1) and subsequently run for other models. In order to determine which of thethree proposed models is the “best” model, this study examined goodness-of-fit statistics. InModel 1, the goodness-of-fit index (GFI) is a measure of the discrepancy between predictedand observed covariances (Delisi and Hochstetler 2003). Values should exceed 0.90. Thecurrent GFI = 0.846. The adjusted goodness-of-fit index (AGFI) adjusts the GFI for degreesof freedom. Critical values should exceed 0.80. The current AGFI = 0.773. RMSEA valuesof 0.08 or less are acceptable. The current RMSEA is 0.089. The root mean square residual(RMR) measure is the square root of the average squared amount by which the samplecovariances differ from the estimates in the model (Delisi and Hochstetler 2003). Criticalvalues should be less than 0.10. The current RMR = 0.104. The next component of the CFAis a second-order factor structure with three latent variables: the two separate dimensionsof HRM practices in addition to the overall latent trait. The GFI = 0.846, AGFI = 0.773,RMSEA = 0.089, and RMR = 0.104. Finally, the model with all 12 items on a singlelatent factor had the worst fit among the confirmatory factor models. The GFI = 0.825,AGFI = 0.748, RMSEA = 0.099, and RMR = 0.111. On the basis of the criteria associatedwith GFI, AGFI, RMSEA, and RMR, the two-factor and second order models provide abetter fit of the data than the one-factor model. In addition, the second order approach wasused to maximize the interpretability of both the measurement and the structural models(Hair et al. 2006). Thus, Model 2 is preferred to Model 1 because of parsimony; it providesan adequate description of the sample data, and provides a better description than the other

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Fig. 1 Alternative models of HRM practices: Models 1–3

alternative model (Vahedi et al. 2011). Following modification indices, this study refined thesecond order model. A large modification index (> 3.84) suggests that a large improvementin model fit as measured by chi-square can be expected if a certain fixed parameter is freed(Lei 2007). Scale items exhibiting high modification indices were subsequently removedfrom the variable list (Christodoulides et al. 2006). Following modification indices, this studyperformed the model refinement to improve the fit to its recommended levels. Based on severaltrials resulting in elimination of two of the items, all of the scales met the recommended levels(GFI = 0.907 > 0.90; AGFI = 0.849 > 0.80; CFI = 0.928 > 0.90; RMSEA = 0.072 <

0.80; RMR = 0.093 < 0.10). Table 2 reported the standardized factor loadings for Model2.

For project success, this study also conducted three confirmatory factor analyses: the four-factor model (Model 4), the second order model (Model 5), and the model in which all 16 itemsloaded on one factor (Model 6). The models are presented in Fig. 2. In model 5, the currentGFI = 0.807, AGFI = 0.704, RMSEA = 0.097, and RMR = 0.140. The next model of theCFA is a second-order factor structure with five latent variables: the four separate dimensionsof project success in addition to the overall latent trait. The GFI = 0.807, AGFI = 0.704,

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Table 2 Results of CFA

Construct and item Standardized factor loading

Model 2: HRM practices: member empowerment and development (MED) –

MED1: team members were encouraged to be responsible for their workand to contribute to the project

0.737

MED2: the work environment was based on personal satisfaction foreveryone

Elimination

MED3: the work environment was based on growth opportunities foreveryone

0.730

MED4: an effort has been made to involve the team members in decisionmaking

0.700

MED5: the team members were given the freedom they need to do theirjobs

0.599

MED6: the project manager dealt effectively with performance problems Elimination

Model 2: HRM practices: Member expertise and training (MET) –

MET1: continuing education was an ongoing commitment that involveseveryone

0.687

MET2: a variety of human resources were involved in the project 0.766

MET3: the team members had the necessary skills 0.718

MET4: enough people were involved in the project 0.694

MET5: the project manager avoided wasting time or resources 0.602

MET6: the team members were encouraged to collaborate on workassignments

0.686

Model 5: project success: innovation success (IS) –

IS1: new methods and inventions were obtained in the project 0.782

IS2: creative deliverables were developed in the product 0.756

IS3: innovative knowledge and know-how was produced in the project 0.573

IS4: new professional knowledge and problem solving techniques weregenerated in the project

Elimination

Model 5: project success: cost success (CS) –

CS1: the actual total development cost of the project was significantlyunder authorized budget

0.815

CS2: the budget for each phase of the project was essentially the same asplanned

0.892

CS3: the cost objectives were met for the project 0.911

CS4: the overall budget for the project was essentially the same as planned 0.666

Model 5: project success: quality success (QS) –

QS1: capabilities of the project’s deliverables fit well with customer or userneeds

0.831

QS2: the project’s deliverables complied with the requirements 0.882

QS3: the project’s deliverables met customer expectations 0.827

QS4: the project ransmoothly 0.821

Model 5: project success: Schedule success (SS) –

SS1: the project team responded quickly to requirements change Elimination

SS2: all project assignments were proceeding as planned Elimination

SS3: the schedule for each phase of the project was essentially the same asplanned

Elimination

SS4: the project was completed ahead of schedule Elimination

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Table 2 continued

Construct and item Standardized factor loading

Organizational benefit (OB) –

OB1: provide your firm with proprietary advantage suchas patents or trade secrets

0.680

OB2: enhance the sales and customer use of the firm’sother products

0.678

OB3: enhance the profitability of the firm’s otherproducts

0.962

OB4: open new market and product opportunities forthe firm

0.760

OB5: achieve important cost efficiencies for the firm 0.722

OB6: substantially lower costs for the firm Elimination

RMSEA = 0.097, and RMR = 0.140. Finally, the model with all 16 items on a singlelatent factor had the worst fit among the confirmatory factor models. The GFI = 0.604,AGFI = 0.428, RMSEA = 0.176, and RMR = 0.191. The statistics indicate that the modelis completely unacceptable. Thus, the four-factor and second order models provide a better fitof the data than the one-factor model. The second order approach was used to maximize theinterpretability of both the measurement and the structural models (Hair et al. 2006). Model5 is preferred to Model 4 because of parsimony; it provides an adequate description of thesample data, and provides a better description than the other alternative model (Vahedi et al.2011). The best model (Model 5) was then refined using modification indices and was used inan SEM. Model improvements based on modification indices suggested the removal of fiveitems. After these refinements, the measurement model’s fit is greatly improved, as evidencedby the following goodness-of-fit statistics: GFI = 0.918 > 0.90; AGFI = 0.860 > 0.80;CFI = 0.966 > 0.90; RMSEA = 0.044 < 0.80; RMR = 0.082 < 0.10. Table 2 presentedthe standardized factor loadings for Model 5.

Furthermore, the composite reliability for all constructs was above the .7 level suggested byHair et al. (2006), indicating adequate reliability for each construct. Thus, the results provideevidence that the scales are reliable. All of the factor loadings were statistically significantat the five percent level and exceeded the 0.5 standard (Fornell and Larcker 1981), as shownin Table 2. In addition, all constructs have an average variance extracted (AVE) greater than0.5. Accordingly, these constructs demonstrate adequate convergent validity. Discriminantvalidity assesses whether the constructs are measuring different concepts (Hair et al. 2006).The procedure requires comparing the set of models where each pair of latent constructs has aconstrained correlation of one with the correspondent models where such pairs of constructsare freely estimated (Bagozzi et al. 1991). The results show that the chi-square values aresignificantly lower for the unconstrained models at the five percent level, which suggests thatthe constructs exhibit discriminant validity.

4.2 Results of structural model test and regression analyses

The final analysis includes the refined second order models with one dependent variable:organizational benefit. Figure 3 presents results of the overall model fit in the structural model.A feasible model was selected based on the recommended goodness-of-fit (GOF) measures.The model that satisfies both theoretical expectations and GOF was selected for SEM analysis.

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Fig. 2 Alternative models of project success: Models 4–6

Thus, the model refinement was performed to improve the fit to its recommended levels.Based on several trials resulting in elimination of some of the items, the overall fit statisticsindicated a very good fit for the model. The Chi-square statistic for the full measurementmodel was nonsignificant (p = 0.062 > 0.05), indicating a good fit between the data andthe proposed model. The normed fit index (NFI), comparative fit index (CFI), and goodnessof fit index (GFI), with values of 0.960, 0.986, and 0.957 respectively, were all above therecommended acceptable 0.90 level (Chau 1997). In addition, the adjusted goodness of fitindex (AGFI = 0.909) was above the .80 minimum recommended value. Finally, the root

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HRM Practices

NPD Project Success

Innovation success

Cost success

Quality success

Member Empowerment

Member Expertise

Organizational Benefit

OB1 OB2MET4

MET5

MET3

MET6

MET1

MET2

MED4

MED5

MED3

MED1

IS1 IS2 IS3 CS2 CS3CS1 CS4 QS2 QS3QS1 QS4

0.90*** 0.64*

0.10

OB3 OB4 OB5

Fig. 3 Research model estimation results

Table 3 Results of regression analyses

Independent variable Dependent variable

Innovation success Cost success Quality success

Member empowerment and development 0.511∗∗∗ 0.461∗∗∗ 0.384∗∗∗Member expertise and training 0.235∗∗ 0.203∗ 0.333∗∗∗

R2 0.480 0.382 0.432

Adjusted R2 0.473 0.373 0.424

F 65.153∗∗∗ 43.596∗∗∗ 53.703∗∗∗

∗ Significant at the 0.05 level; ∗∗ Significant at the 0.01 level; ∗∗∗ Significant at the 0.001 level

mean square error of approximation (RMSEA) is 0.060, which is below the cut-off level of.08 recommended by Browne and Cudeck (1993). The overall fit measures of the structuralmodel indicate adequate fit of the model to the data. The standardized parameter estimatesfor the proposed model is presented in Fig. 3. Concerning the hypothesized relationships, thecoefficient on the path from HRM practices to organizational benefit is 0.10 (p > 0.05). Thus,the positive relationship suggests that H1 is not supported. The path coefficient from HRMpractices to NPD project success is 0.90 (p < 0.001), which supports H2. Finally, the directimpact from NPD project success to organizational benefit is significant (coefficient = 0.64,p < 0.05), and therefore H3 is supported.

This study further evaluates the impact of “member empowerment and development” and“member expertise and training” on innovation success, cost success, and quality success.Table 3 presents the regression results for the degree to which innovation success, costsuccess, and quality success were influenced by “member empowerment and development”and “member expertise and training.” These analyses reveal that increased levels of “memberempowerment and development” and “member expertise and training” lead to improvedinnovation success, cost success, and quality success.

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Table 4 Mediating effect of project success

Structural path Model 1 Model 2 Model 3 Model 4

HRM→OB 0.65∗∗∗ – – 0.10

HRM→PS – 0.91∗∗∗ – 0.90∗∗∗PS→OB – – 0.72∗∗∗ 0.64∗

∗ Significant at the 0.05 level; ∗∗∗ Significant at the 0.001 level

Table 5 Cluster means of discriminating variables

Variable Projects with high levelsof HRM practices

Projects with low levelsof HRM practices

t-statistic p-value

Number Mean Number Mean

Memberempowerment anddevelopment

130 5.56 75 3.92 12.875 0.000

Member expertise andtraining

130 5.57 75 4.24 10.928 0.000

4.3 Mediating effect of project success

To test the mediating role of project success, four additional analyses were conducted (Frazieret al. 2004). The results are presented in Table 4. First (Model 1), a direct positive relationshipbetween HRM practices (HRM) and organizational benefit (OB) was established with a coef-ficient value of 0.65 (p < 0.001). Second (Model 2), the direct link between HRM practices(HRM) and project success (PS) was found with a coefficient value of 0.91 (p < 0.001).Third (Model 3), the direct link between project success (PS) and organizational benefit (OB)was also exhibited (coefficient = 0.72 and p < .001). Finally (Model 4), the links betweenHRM practices and project success, between project success and organizational benefit, andbetween HRM practices and organizational benefit were simultaneously considered. The sig-nificant relationship between HRM practices and organizational benefit was not significantafter including project success, that is, the existence of complete mediation by project successin the effect of HRM practices on organizational benefit.

4.4 Moderating role of job condition and project characteristic related variables

In order to identify homogeneous project clusters with the same kinds of perceptions of HRMpractices, a K-means cluster analysis was performed on the basis of the two dimensions ofHRM practices (i.e. “member empowerment and development” and “member expertise andtraining”). To validate the results of the cluster analysis, a discriminant analysis was alsoconducted. The cluster analysis has identified two clusters for HRM practices, with the clustermean values of discriminating variables given in Table 5. The discriminant analysis classified97.2 % of the projects as the cluster analysis did, indicating extremely good differentiationand a correct classification. In addition, the independent-samples t tests shown in Table 5confirm that the two variables of “member empowerment and development” and “memberexpertise and training” do significantly differentiate across the two clusters. The first clusterwas labeled projects with high levels of HRM practices. The second cluster consisted ofprojects with low levels of HRM practices. On the other hand, these subject projects were

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Table 6 Results of ANOVAs for job condition related variables

Independent Moderator

variable Salary Job Fob Working Informationsatisfaction security hours availability

(SA) (JS) (FS) (WH) (IA)

HRM (NPD project success as dependent variable) 1.191 0.036 0.574 3.752∗ 0.385

HRM (Innovation success as dependent variable) 1.516 0.078 0.946 3.233∗ 0.729

HRM (Cost success as dependent variable) 1.542 0.542 0.041 1.434 0.192

HRM (Quality success as dependent variable) 0.004 1.154 0.591 2.866 0.048

∗ Significant at the 0.05 level

Table 7 Results of ANOVAs for project characteristic related variables

Independent Moderator

variable Time Complexity Team Materials Projectavailability relationship & supplies duration(TA) (CO) (TR) (MS) (PD)

HRM (NPD project success as dependent variable) 4.547∗ 0.003 0.692 0.773 0.142

HRM (Innovation success as dependent variable) 1.617 0.049 0.640 0.019 0.021

HRM (Cost success as dependent variable) 6.392∗ 1.205 0.187 2.808 0.784

HRM (Quality success as dependent variable) 1.471 1.879 1.244 0.113 0.433

∗ Significant at the 0.05 level

categorized according to five job condition related variables and five project characteristicrelated variables. Thus, for example, to test for the moderating influence of time availabilityon the relationship between HRM practices and project success, 2 (HRM practices) × 2(time availability) analysis of variance (ANOVA) was performed. The two-way ANOVAwas utilized to determine the joint effects of HRM practices and time availability on projectsuccess.

A typical project from each of the clusters identified (projects with high levels of HRMpractices and projects with low levels of HRM practices) is described to help understandthe nature of the projects and the differences in the projects. Each of the typical projectsshows the nature of most projects in that cluster. For the project with high levels of HRMpractices, the duration of the project was 3–5 months. The complexity of the project wasmedium. Availability of time needed to execute the project was medium. The project hadenough materials and supplies. Additionally, information from all participants, stakeholders,and customers needed to conduct the project was enough. The team members had mediumworking hours. They were satisfied with their job, job security, and pay. The team relationshipof the project was excellent. On the other hand, for the project with low levels of HRMpractices, the duration of the project was 3–5 months. The complexity of the project was alsomedium. The project had enough materials and supplies. Information from all participants,stakeholders, and customers needed to execute the project was enough. The team memberswere satisfied with their job and job security. However, availability of time needed to conductthe project was unrealistic. The team members had long working hours. They were notsatisfied with their pay. Overall, the team relationship of the project was medium.

Sharma et al. (1981) provided a framework for identifying moderator variables: homolo-gizers, quasi moderators, or pure moderators. This study examines the type of moderator in

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4.0

4.5

5.0

5.5

6.0

Low HighInno

vatio

n Su

cces

s

HRM Practices(a) Moderating role of working hours

Very long Long Regular

3.5

4.0

4.5

5.0

5.5

hgiHLow

Cos

t Suc

cess

HRM Practices(b) Moderating role of time availabilty

Unrealistic schedule More realistic schedule

Fig. 4 Moderating role of working hours and time availability

the relationship between HRM practices and NPD project success. Tables 6 and 7 summarizethe results of the ANOVAs. The results indicate a significant interaction of HRM practices(HRM) and working hours (WH) for NPD project success (F = 3.752, p < 0.05) and innova-tion success (F = 3.233, p < 0.05). There is also a significant interaction of HRM practices(HRM) and time availability (TA) for NPD project success (F = 4.547, p < 0.05) and costsuccess (F = 6.392, p < 0.05). However, the main effect of the moderators (WH and TA) isnot significant at 0.05 level. Working hours (WH) and time availability (TA) can be classifiedas a pure moderator because they are not directly related to the criterion (project success) andpredictor (HRM practices) but interact with the predictor. Thus, the results support H4. Sincethe interaction term was significant, the form of interaction was graphically represented toevaluate the direction of the differences within each of the conditions.

Figure 4a shows the relationship between HRM practices and innovation success at differ-ent levels of working hours. It is clear that project teams who have regular working hours aremore likely to be successful in project innovation when they experience a high level of HRMpractices than project teams who have longer working hours. Figure 4b graphically presentsthe relationship between HRM practices and cost success for time availability. Analysessuggest that projects with unrealistic schedule are more likely to be successful in projectcost when they experience a high level of HRM practices than projects with more realisticschedule.

5 Discussion

While most of the previous studies concentrated on project execution tools and techniques, thefindings indicate that HRM practices in terms of “member empowerment and development”and “member expertise and training” are associated with NPD project success, which supportsH2. These results are in line with previous studies (Ling et al. 2009), which have shownthat HRM effort plays a crucial role in project success. The research findings also implythat HRM effort may improve NPD project success in terms of cost success and qualitysuccess, while it also helps enhance innovation success. Thus, project managers shoulddevelop a comprehensive HRM strategy and provide other leaders with guidelines for howto manage project teams. For member empowerment and development, project managersneed to encourage team members to be responsible for their work and to contribute to theproject. More importantly, the work environment should be based on growth opportunities foreveryone. They should also be committed to involving team members in decision making.Giving the team members the freedom they need to their job is also important for newproduct development. On the other hand, for member expertise and training, continuing

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education should be an ongoing commitment that involves everyone. Project managers mustbe dedicated to including a variety of human resources in NPD projects. In addition, enoughpeople should be involved in NPD project teams. If the team members are not capableof executing the project work, project managers should set goals for them to develop thenecessary skills and expertise. Finally, project managers must engage in practices that avoidwasting time or resources. They should also encourage the team members to collaborate onwork assignments.

The research result also shows that NPD project success has a significant positive impacton organizational benefit, which supports H3. NPD project success may act as a catalyst forproprietary advantage and greater success in the market. The results are in line with previousfindings (Tatikonda and Montoya-Weiss 2001; Chen et al. 2005) in that project successmay result in organizational performance and product success in the market. However, thedirect impact from HRM practices to organizational benefit is not significant. Thus, thepositive relationship suggests that H1 is not supported. The results of this research furtherprove that project success fully mediates the effects of HRM practices on organizationalbenefit, which indicates that implementation of HRM practices influences organizationalbenefit via NPD project success. This explains why the direct impact from HRM practices toorganizational benefit is not significant. This result also confirms the suggestion in literaturethat mediators may exist between HRM practices and final examined outcomes (Garciaand Sanzo 2008; Tatikonda and Montoya-Weiss 2001; Chen et al. 2005). This study hasseveral implications concerning project success improvement. In order to be successful inproject innovation, project managers should set goals for innovation activities and conductan evolutionary improvement strategy. Involving product users in the innovation process isalso important for new product development. In addition, project managers must measurethe impact of innovation efforts on NPD performance. They should also conduct just-in-timetraining to get product development teams to apply the innovation in practice. To achieveproject success in meeting the project cost objectives, project managers should use newtechnology and equipment that can reduce development cost. They need to be committed toreducing total development cost of the project and improving human resource utilization rate.More importantly, they must be dedicated to improving operational efficiency and controllingdevelopment cost. To be successful in project quality, project managers should gain theorganization’s support for a NPD project. They should also focus on quality control and bededicated to a quality management policy. In addition, they should be committed to achievingquality objectives and meeting project requirements.

The results also show that the positive relationship between HRM practices and NPDproject success depends on environmental factors, which supports H4. The findings indicatethat working hours (job condition related variable) and time availability (project characteristicrelated variable) have a moderating effect on the relationship between implementation ofHRM practices and project success. The research results are in line with previous findings(Müller and Turner 2007) in that the relationships between the personnel factor and projectsuccess vary according to project type.

6 Conclusion

Conceptualizing HRM in the project context is still underdeveloped. Thus, this study assessedproject HRM rather than HRM at the firm level. This paper contributes in an original wayto the literature on HRM in projects by focusing on how NPD project success may bringpotential benefits to a firm. Prior research has shown that human resource management is

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one of the most important elements in an organization’s success. In addition, people issuesare also critical to project success (Lewis 1993). Project is an autonomous organization butconnected to parent organization (Artto et al. 2008). However, the previous studies indicatedthat research on human resource management in the NPD and project management context isnot well developed. Most models explaining project success were based on theory rather thanon empirical proof. While the diverse benefits of human resource management have receivedsubstantial attention, the number of studies dealing with the impacts of HRM practices onNPD performance is rather scarce. Most NPD studies have focused more on the productrather than on the development process (Funk 1992). This lack of process discipline is oftenthe most critical obstacle to successful NPD (Page 1993). In addition, the lack of researchconcerning human resource management in NPD indicates the need to use the research resultsfrom the literature in other disciplines. Although some of the prior research may be adapted tothe NPD process, the key process defined and personnel factor in NPD projects are differentfrom those in other areas. Thus, there is a need for exploring the benefits of HRM practicesin the NPD domain.

This research is the first to provide empirical evidence that supports the expectation ofimproving project success and organizational benefit by implementing HRM practices in newproduct development. This study adds to the literature in three valuable ways. First, it validatesa framework for assessing the associations among HRM practices, NPD project success, andorganizational benefit and provides implications for project HRM. Prior research examinedthe importance of HRM practices in an organization’s success or project performance, butthere has been no comprehensive study on the effects of HRM practices on NPD projectsuccess. In addition, no previous studies have empirically analyzed the effects of NPD projectsuccess on organizational benefit. This study attempts to fill the gaps in the NPD literature. Itreveals the importance of developing HRM practices to enhance cross-functional cooperationin NPD project teams. The research results also offer guides to improve NPD project successand further gain a number of potential benefits to a firm. Findings from this study are helpfulto project managers in deciding whether to adopt certain HRM practices in a NPD project.Project managers can use the research results to modify their current HRM effort. Second,it offers important results on identification of the mediating role of NPD project success inthe relationship between HRM practices and organizational benefit. Prior research indicatedthat HRM effort should improve project success (Belout and Gauvreau 2004; Lewis 1993).Additionally, project performance may be positively related to market performance (Chenet al. 2005; Tatikonda and Montoya-Weiss 2001). However, the previous studies did notprovide insights into the mediating roles of project success in the relationships betweenHRM practices and organizational benefit. The results of this research further prove thatproject success fully mediates the effects of HRM practices on organizational benefit. Inother words, HRM effort may influence organizational benefit via NPD project success.This result confirms the suggestion in literature that mediators exist between HRM practicesand final examined outcomes. Third, this research evaluates the relationship between HRMpractices and NPD project success for different working environment factors. “Workinghours” (a job condition related variable) serves as a moderator in the relationship betweenHRM practices and project innovation success. On the other hand, time availability (a projectcharacteristic related variable) plays a moderating role in the relationship between HRMpractices and project cost success. The results suggest that the positive association betweenHRM practices and project success depends on the two factors. The research results are inline with previous findings (Belout and Gauvreau 2004) in that the relationships between thepersonnel factor and project success vary according to project type. However, no previousstudies have empirically analyzed the moderating effect of job condition related variables

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and project characteristic related variables on the relationship between HRM practices andNPD project outcomes. This study attempts to fill this gap in the literature.

The targeted respondents were identified as new product development practitioners whowere familiar with project HRM and NPD project success. Some of them were senior R&Dpersonnel. Thus, this study employed a relatively narrow functional perspective to analyzethe issue. Although R&D professionals play an important role in developing new products,they are not the only stakeholders involved in a NPD project. Future research may usebroader cross-functional approach and measure HRM practices and NPD performance fromthe viewpoints of production and marketing groups. It may focus on the joint considerationof the various perspectives. Importance of HRM practices from different viewpoints shouldalso be investigated in future research.

This study is based on the perceptions of a single respondent. Thus, the reliability ofsurvey relies on the truthfulness of the respondents and the expertise of the investigators inquestionnaire design. More than 200 NPD projects were investigated in the study. Thus, it isnot an efficient way to collect the necessary data from all team members participating in aNPD project. However, this study was designed to eliminate mono-source bias. The mono-source bias was not a threat in this study for the following reasons: (1) this study attempted toselect the right respondents who possess adequate knowledge and are capable of answering allof the survey questions, (2) third-party reports have been shown to be moderately consistentwith self-reported measure (Dyne and LePine 1998), and (3) the confirmatory factor analysisshowed that the one-factor measurement model was a poor fit to the data (Podsakoff and Organ1986). In addition, because all the research data are self-reported and collected through thesame questionnaire during the same period of time, a common method variance (CMV)may result in a systematic measurement error and may further bias the estimates of thetrue relationship among the theoretical constructs (Podsakoff and Organ 1986). This studyused the Harman’s one-factor test to investigate the potential problem of common methodvariance, suggesting that common method bias was not considered a serious threat to thisstudy. However, qualitative issues can be investigated to explain these associations in futureresearch.

Furthermore, only one factor was found to underlie organizational benefit. The measurescould be improved by developing several sub-dimensions. Moreover, one limitation of thisstudy is its cross-sectional design. An objective for future study is to determine how HRMpractices are changing over time in the NPD domain. Survey with a longitudinal designmay be needed to gain deeper insights into the benefits of HRM practice implementation innew product development. In addition, the sample for this study focused on NPD projectsin the high-tech industry. Consideration should be given to investigate projects in traditionalmanufacturing industry. This could also lead to greater insights into the importance of HRMstrategy development and implementation. Finally, it would be worthwhile to examine thefactors which may influence HRM strategy development.)

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Documents

A framework for evaluating relationship among HRM practices, project success and organizational benefit