High-Performance Work Systems and Work-Role Performance: A Multilevel Moderated Mediation Model

1 ACCEPTED MANUSCRIPT OF THE PAPER: High-Performance Work Systems and Work-Role Performance: A Multilevel Moderated Mediation Model Authors: García-Chas, Romina; Neira-Fontela, Edelmira; Varela Neira, Concepción Cite: García-Chas, R., Neira-Fontela, E., & Varela Neira, C. (2023). High-Performance Work Systems and Work-Role Performance: A Multilevel Moderated Mediation Model. Performance Improvement Quarterly, 32(1), 77-101. https://doi.org/10.1002/piq.21289 2 HIGH-PERFORMANCE WORK SYSTEMS AND WORK ROLE PERFORMANCE. A MULTILEVEL MODERATED MEDIATION MODEL 1 Introduction The capacity of High-Performance Work Systems (HPWS) to contribute to organizational performance has been the topic of a heated debate since the 1990s. HPWS refers to a cluster of “interconnected human resource (HR) practices designed to enhance employees’ skills and effort” (Takeuchi, Lepak, Wang, & Takeuchi, 2007, p. 1069). The majority of previous research on HPWS has focused on its impact on firm performance (Coombs, Yongmei, Hall, & Ketchen, 2006; Jyoti & Rani, 2017) and the mechanisms through which this relationship occurs. HPWS affects organizational performance through its effect on the employees (e.g., Jiang, Lepak, Han, Hong, Kin, & Winkler, 2012). Thus, some studies have recently investigated the link between HPWS and employee outcomes. For the most part, these studies have examined mediators at the organizational level, whereas fewer investigations have analyzed mediators at the individual level (Werner, 2011). In this last line of research, the most of studies have focused on the effect of HPWS on employee attitudes (e.g., Kehoe & Wright, 2013; Wu & Chaturvedi, 2009) and only a few papers have examined its effect on individual performance (e.g., Chang & Chen, 2011; Snape & Redman, 2010). To examine individual performance is especially important for organizations because “organizations do not “perform” it is the individuals in an organization who perform in ways that allow the organization to achieve desirable effectiveness and performance outcomes” (Lepak, Liao, Chung, & Harden, 2006, p. 230). Employee performance, compared to organizational outcomes, is a more immediate and proximal outcome of HR systems and the interest in its research is more consistent across 3 organizations (Jiang et al., 2012). According to Werner (2011), to show a relationship between HPWS and individual performance constitutes a relevant progress to HPWS literature. Despite recent research that examines the relationship between HPWS and individual performance, there are still gaps in the literature. Our research, which uses multisource data, expands upon existing HPWS research and knowledge in several meaningful ways. First, we integrate two previously separate streams of research by analyzing the relationship between HPWS and the three performance dimensions - proficiency, adaptivity, and proactivityproposed by Griffin et al. (2007) in their new model of work role performance. The meaning of work performance has changed over the last 40 years, as result of the changing nature of work and organizations. Today’s organizations operate in changing, dynamic environments in which the need for new employee behaviors has become increasingly important (Crant, 2000; Pulakos, Arad, Donovan, & Plamondon, 2000). For this reason, researchers must go beyond typical task performance when evaluating individual performance, and consider each performance dimension separately (Semadar, Robins, & Ferris, 2006). One means of achieving this is by using role-based performance theory (Ilgen & Hollenbeck, 1991). Second, we analyze the mediating role of employee effort in the relationships between HPWS and proficiency, adaptivity, and proactivity. Effort is considered a key determinant of employee performance (e.g., Campbell, 1990; Vroom, 1964) and has been identified as a critical mediator in theoretical models of the relationship between HR systems and individual performance (e.g., Jiang et al., 2012). According to Christen, Iyer & Soberman (2006) “from the perspective of an employee, effort is an input to work, and job performance is an output from this effort” (p. 139). In addition, its importance in the relationship between a system of human resource practices and firm performance has 4 been noted since the nineties (e.g., Appelbaum, Bailey, Berg, & Kalleberg, 2000; MacDuffie, 1995). However, to date, to the best of our knowledge, no empirical study has proposed and tested the mediating role of employee effort in the relationship between HPWS and individual performance. By doing so, we respond to Den Hartog, Boon, Verburg, and Croon’s (2013) call for research on motivation-related variables to explain the mechanisms underlying the relationship of Human Resource Management (HRM) with outcomes in contexts with skilled jobs. Third, although the contingency perspective on Human Resource Management (HRM) has been primarily studied at the organizational level, the effectiveness of HRM may also be dependent on individual employees’ characteristics. Hence, we argue that the positive relationships between effort resulting from HPWS and the dimensions of performance are moderated by organizational tenure, strengthening these links. We hope to address the question of the underlying mechanisms influencing employee reactions to HPWS, as well as respond to the call for research on potential individual-level moderators of HR systems effects (Jiang et al., 2012; Snape & Redman, 2010). As the employee’s attitudinal and behavioral response is based on his/her perception of the human resource practices (e.g., Wright & Nishii, 2013), we examine HPWS from the employee perspective (Choi, 2014). In doing so we respond to the call of Jiang et al. (2012, p. 83) “to investigate how employee perceptions may affect the effects of HR practices”. Finally, given the need to differentiate the workforce (e.g., Becker, Huselid, & Beatty, 2009), the multilevel moderated mediation model proposed in this research (see Figure 1) is tested on engineers, an especially relevant professional group to companies and society (UNESCO, 2010). ‘Figure 1 approx here’ 5 2 Theory and Hypotheses In the field of HRM, HPWS is the HRM system that has received more attention in recent literature. Although there is great diversity in the HR practices considered in previous studies, according to Takeuchi, Chen, and Lepak (2009), HPWS usually includes “comprehensive recruitment and selection procedures, incentive, compensation and performance management systems, and extensive employee involvement and training” (p. 1). 2.1 Mediating role of effort in the relationship between HPWS and work role performance at individual level (proficiency, adaptivity, and proactivity) Work performance nature and dimensionality have interested organizational scientists for decades. Traditionally, work performance “was evaluated in terms of the proficiency with which an individual carried out the tasks that were specified in his or her job description” (Griffin et al., 2007, p. 327). However, this measure is limited because it ignores other dimensions of work performance. Recently, Griffin et al. (2007) have posited a new model of work performance based on role theory (Ilgen & Hollenbeck, 1991) and existing performance frameworks, most notably the distinction between task and citizenship performance (Borman & Motowidlo, 1993). This model identifies three levels –task individual, team member, and organization member- and three forms of behavior: proficiency, adaptivity, and proactivity. Proficiency at individual level reflects “the degree to which an employee meets the known expectations and requirements of his or her role as an individual” (Griffin, et al., 2007, p. 331). Individual task proficiency integrates “job-specific”, “non-job- specific”, and “written and oral” task proficiency of Campbell, McCloy, Oppler, and Sager’s (1993) model. This dimension has been deeply analyzed in previous research and traditional performance assessment systems have focused on this performance dimension. 6 Adaptivity at individual level is a construct that “reflects the degree to which individuals cope with, respond to, and/or support changes that affect their roles as individuals” (Griffin et al. 2007, p. 331). If an employee responds to these changes, he/she is altering his/her competencies and applying new competencies. A core element of this construct is dealing with uncertain work situations (Griffin et al., 2007; Pulakos et al., 2000). Adaptive performance is especially relevant in today’s dynamic business environment. Proactivity at individual level reflects “the extent to which individuals engage in self-starting, future-oriented behavior to change their individual work situations, their individual work roles, or themselves” (Griffin et al., 2007, p. 332). According to Grant and Ashford (2008), proactive behavior refers “to anticipatory action that employees take to impact themselves and/or their environments” (p. 4). Individual proactivity is an important dimension in highly uncertain work environments where employees who anticipate changes are needed (Beltrán-Martín, Bou-Llusar, Roca-Puig & Escrig-Tena, 2017). In this study, we argue that employee effort mediates the relationship between HPWS and the three dimensions of work role performance –proficiency, adaptivity, and proactivityat individual level. Effort is one of the most significant constructs in motivation theory. Mohr and Bitner (1995) define effort as “the amount of energy put into a behavior or series of behaviors” (p. 240). Therefore, effort refers to how hard an employee works (Mitchell & Daniels, 2002). The relationship between HPWS and employee effort is supported by signaling (e.g., Ostroff & Bowen, 2000) and social exchange (Blau, 1964) theories. Signaling theory argues that observable actions from an organization or person are perceived as signals of less observable characteristics (Spence, 1973), while social exchange theory 7 (Blau, 1964) posits that when employees perceive organizational support, they will show greater affective attachment and stronger feelings of obligation toward the organization. Human resource practices perceived as favorable and convenient “contribute to the establishment of high-quality exchange relationships … that create obligations for employees to reciprocate in positive, beneficial ways” (Settoon, Bennett, & Liden, 1996, p. 219). A behavior of reciprocity is to make a bigger effort in line with the organization’s objectives. An HPWS, characterized by rigorous selection and recruitment procedures, an evaluation system based on merit, extensive training and development programs, and contingent pay and opportunities for participation, signals a supportive work environment to the employee (e.g., Sun et al., 2007). Consequently, the employee makes a greater effort to help the organization reach its objectives (e.g., Appelbaum et al., 2000). Several empirical studies show a positive relationship between specific human resource practices, and employee effort (Gilley, Gilley, Jackson & Lawrence, 2015). Walsh and Tseng (1998) have showed that employees’ participation has a positive effect on their effort. Den Hartog and Verburg (2004) have found positive relationships between a set of practices labeled “employee skills and direction” –involving strict selection, an emphasis on employee development and internal promotions, and having an overarching philosophy in terms of a mission statement and HR strategy- and employee willingness to go beyond contract. Kuvaas and Dysvik (2009) have found a relationship between perceived investment in employee development and work effort. Recently, McClean and Collins (2011) have shown significant relationships between the use of high-commitment HR practices and employee effort in small professional services firms. Moreover, employee effort is related to work role performance. An increase of the energy that employees are willing and able to devote to their tasks (i.e., more effort) will 8 contribute to proficiency. A number of previous empirical studies (e.g., Brown & Peterson, 1994; Karatepe, Uludag, Menevis, Hadzimehmedagic, & Baddar, 2006; Piccolo, Greenbaum, Den Hartog, & Folger, 2010) have found a positive relationship between individual effort and performance. We also argue, in a similar way to proficiency, that effort will affect adaptivity. Dealing effectively with unpredictable and changing work situations, and learning new tasks, technologies and procedures, reflects adaptive performance (Ployhart & Bliese, 2006). When an individual works hard and strives to succeed in his/her work, he/she may be willing to modify and use new competencies. Then, we posit that more effort will lead to a more adaptive performance. Effort may contribute to proactivity. When employees display high levels of effort, they work with intensity and energy (Brown & Leigh, 1996) and they actively engage themselves in broader work roles (Khan, 1990). Then, individuals will be more likely to set and strive for proactive goals (Parker, Bindl, & Strauss, 2010). In this line, Zhang and Bartol (2010) argue that when an individual displays effort to better identify a problem, he/she will acquire as much information as possible, and produce abundant ideas and alternatives. Based on the previous arguments we posit the following hypothesis: H1: Employee effort mediates the relationship between HPWS and employee (a) proficiency, (b) adaptivity, and (c) proactivity at individual level. 2.2. Moderating role of organizational tenure on the mediated relationship between HPWS and work role performance at individual level (proficiency, adaptivity, and proactivity) Organizational tenure is defined as the length of an employee’s continuous service in an organization (Gordon & Johnson, 1982). The length of an employee’s continuous service in an organization is related to his or her knowledge of the work (e.g., Quiñones, Ford, & 9 Teachout, 1995) and the organization (Bird, 1994). Long-tenured workers can accumulate human capital through work experiences; those employees with more years of service are generally familiar with a broader set of work processes and are often skillful in performing multiple jobs within the firm. Job performance has been traditionally conceptualized as a function of both ability and effort (e.g., Campbell, 1990). Therefore, organizational tenure can interact with effort in the relationship with performance. We posit that effort will have a stronger effect on proficiency for long-tenured employees. Organizational tenure enhances the positive effect of effort on proficiency as it increases declarative and procedural knowledge (Campbell et al., 1993). In addition, organizational tenure promotes the acquisition of social knowledge. Rollag (2004) demonstrated that relative organizational tenure (years of tenure relative to colleagues) significantly predicted employees’ networking and communication behaviors. Relationship ties encourage joint efforts in problem solving (Ahuja, 2000), provide psychosocial support via friendship and intimacy, which fosters trust and cooperation, and facilitate the exchange of valued resources (Brass, 1995). These networks help obtain scarce resources needed for the job and facilitate knowledge sharing, a process that enables people to benefit from existing knowledge bases within the organization, and to make effort more effective. In the same line, we consider that the relationship previously posited between effort and adaptivity, is also moderated by organizational tenure. Chen, Ployhart, Thomas, Anderson, and Bliese (2011) argue that, according to sense-making theory, employees need to acquire sufficient knowledge about their organization and work role in the firm to meaningfully interpret changes in work experiences. Organizational tenure is associated with the extent to which employees develop a clear cognitive framework of their work roles, organization norms and consistent reputation (Rollag, 2004). Since 16 the magnitude of this effect does not depend on the moderator. However, the potency of the mediating process depends on the moderator” (Muller, Judd & Yzerbyt, 2005, p. 856). To assess the moderated mediation process, steps outlined by Preacher, Rucker, and Hayes (2007) were followed. Therefore, several MSEM analyses were carried out (see Table 2) to ensure that four conditions were satisfied: (i) significant relationship between HPWS and the performance dimensions, (ii) significant relationship between effort and the performance dimensions, (iii) interaction between effort and organizational tenure is significantly associated with the performance dimensions, and (iv) different conditional indirect relationships between HPWS and the performance dimensions via effort across low and high levels of organizational tenure. The last condition, which is the essence of moderated mediation, establishes whether the strength of the mediation via effort differs across the two levels of the moderator. MSEM offers the possibility to model the relationships among multiple independent and dependent constructs simultaneously. SEM permits complex variable relationships to be expressed through hierarchical or nonhierarchical, recursive or non-recursive structural equations, showing a more complete picture of the whole model (Bullock et al., 1994). MSEM, a synthesis of multilevel and structural equation modeling, is required for valid statistical inference when the units of observation form a hierarchy of nested clusters and some variables of interest are measured by a set of items of fallible instruments (Rabe-Hesketh, Skrondal & Zheng, 2007), which is the case of this study. As shown by table 2, HPWS has a positive significant impact on the mediator and on the dependent variables when the mediator is not included. Condition 1 was therefore confirmed. Moreover, effort has a significant positive impact on the performance dimensions (see table 2), hence, supporting condition 2. Finally, the interaction of effort 17 with organizational tenure was significantly and positively related to the dimensions of performance. This indicates a stronger positive relationship between effort and the performance dimensions when organizational tenure is high than when it is low, supporting H2 and condition 3. The interactions are plotted in Figure 2, 3 and 4 (Aiken and West, 1991). The simple slopes for both the long tenure (proficiency: b=.6518, t=8.33, p<.001; adaptivity: b=1.0248, t=4.95, p<.001; proactivity: b=.5474, t=6.938, p<.001) and the short tenure (proficiency: b=.3482, t= 3.17, p<.01; adaptivity: b=.7853, t=4.04, p<.001; proactivity: b=.23225, t=2.10, p<.05) are significantly different from 0. Also the two slopes were significantly different from each other (proficiency: t=2.24, p<.05; adaptivity: t=2.10, p<.05; proactivity: t=2.31, p<.05). ‘Figure 2 approx here’ ‘Figure 3 approx here’ ‘Figure 4 approx here’ To further assess moderated mediation, condition 4 was examined. Hence, the significance of the indirect relationships between HPWS and the performance dimensions via effort for employees with low organizational tenure and employees with high organizational tenure was calculated using bootstrapped 95 per cent CIs (see table 3). As the 95% CIs are positive and do not include zero, HPWS is positively and indirectly related to the performance dimensions (via effort) when organizational tenure is low (1 SD below the mean) as well as high (1 SD above the mean). Moreover, the results show that the more organizational tenure the employees have, the greater the positive indirect effect of HPWS on the performance dimensions via effort. 18 Table 2. MSEM results for the hypothesized relationships Proficiency Adaptability Proactivity Independent Model 1 Model 2 Model 3 Model 4 Model 5 Model 1 Model 2 Model 3 Model 4 Model 5 Model 1 Model 2 Model 3 Model 4 Model 5 EFFORT Control variables Company size .046 -.401 -.381 -.390 -.394 .046 -.401 -.401 -.395 -.401 .046 -.401 -.392 -.385 -.401 Industry -1.233 .257 .268 .264 .262 -1.233 .257 .257 .261 .257 -1.233 .257 .263 .266 .257 E_Gender .354 -.064 -.045 -.054 -.058 .354 -.064 -.064 -.059 -.064 .354 -.064 -.055 -.049 -.064 E_Age -.108 -.160 -.189 -.176 -.171 -.108 -.160 -.160 -.169 -.160 -.108 -.160 -.174 -.184 -.160 Job position -.537 -1.085 -1.015 -1.046 -1.059 .537 -1.085 -1.085 -1.063 -1.085 -.537 -1.085 -1.050 -1.027 -1.085 Strat. Group .285 -.056 -.065 -.062 -.060 .285 -.056 -.056 -.059 -.056 .285 -.056 -.061 -.064 -.056 S_Age .299 -.075 -.052 -.063 -.067 .299 -.075 -.075 -.068 -.075 .299 -.075 -.064 -.056 -.075 S_Gender -.691 .441 .475 .459 .453 -.691 .441 .441 .451 .441 -.691 .441 .457 .468 .441 Level 2 predictors HPWS .472** .468** .470** .471** .472** .472** .471** .472** .472** .470** .469** .472** PERFORMANCE DIMENSION Control variables Company size .527* .362 .579** .527** .546** .596 .224 .600** .550** .566** .552* .440* .614** .543** .564** Industry -1.659** -.989* -1.128** -1.003* -1.020** -2.141* -.804 -1.044** -.915** -.928** -1.546** -1.076* -1.187** -1.037** -1.055** E_Gender .212 .132 .166 .261 .365 .189 -.136 -.077 .019 .101 .154 .116 .143 .259 .367 E_Age .023 -.088 -.002 -.161 -.104 -.041 -.152 -.002 -.149 -.104 .031 -.059 .010 -.213 -.153 Job position -.085 -.576 -012 -042 -.011 -.640 -1.092 -.076 -.048 -.090 -.014 -.485 -.016 .027 -.029 Strat. Group -.039 -.082 -.052 -.001 .033 .145 -.116 -.064 -.004 .022 -.080 -.082 -.058 -.010 .026 S_Age .123 -.044 -.003 -.003 .049 .240 -.055 .015 .026 .066 .119 -.017 .016 -.003 .050 19 S_Gender -.436 .060 -.179 -.154 -.041 -.694 .298 -.115 -.071 .018 -.677 -.298 -.489 -.492 -.376 Level 2 predictors HPWS .179** -.077 -.075 -.075 .389** -.054 -.050 -.051 .130** -.074 -.074 -.075 Level 1 predictors Effort .542** .549** .500** .936** .943** .905** .433** .440** .390** Tenure .247 .239 .226 .220 .347 .339 Effort x Tenure .132* .104* .137* Log Likelihood -553.120 -521.430 -495.180 -490.999 -488.368 -587.652 -547.500 -474.817 -470.058 -467.670 -543.160 -514.306 -496.564 -492.464 -489.196 **p< .01; *p< .05 Note: E_Gender refers to the engineer’s gender, E_Age refers to the natural logarithm of the engineer’s age, S_Gender refers to the supervisor’s gender and S_Age refers to the natural logarithm of the supervisor’s age. Table 3. Conditional indirect effects of HPWS on the performance dimensions via effort Moderator Proficiency Adaptability Proactivity Indirect effect Bootstr ap SE Bias-corrected 95% CI Indirect effect Bootst rap SE Bias-corrected 95% CI Indirect effect Bootstr ap SE Bias-corrected 95% CI Low organizational tenure .17** .061 (.075, .325) .38** .064 (.273, .539) .12* .059 (.021, .260) Moderate organizational tenure .24** .046 (.160, .349) .43** .056 (.340, .572) .18** .044 (.116, .299) High organizational tenure .30** .053 (.201, .411) .48** .059 (.383, .618) .25** .050 (.165, .369) **p< .01; *p< .05 Note: Bootstrapped confidence intervals were derived from 2,000 replications. Low = 1 SD below the mean, Moderate = mean, High = 1 SD above the mean. 20 5 Discussion The primary goal of this study was to examine the relationship between HPWS and employee work role performance, to do so we conceptualized and tested a multilevel moderated mediation model. Lepak and Snell (2002) consider that firms should rely upon different HR configurations to manage different employee groups and invest more in key workers. If companies apply different human resource practices depending on the group they are addressed to, to collect undifferentiated data could provide average information that does not represent any specific group and, thus, that will be misleading (e.g., Boxall, 2012). Therefore, this paper has focused on engineers, a unique and crucial group of employees (UNESCO, 2010). For this professional group, it is especially important to analyze not only proficiency but also the adaptivity and proactivity dimensions of work role performance. According to Vincenti (1990), engineering involves significant uncertainty. Then, engineers need to show an adaptive behavior to face the changes in his/her work roles as consequence of especially dynamic work environment and of rapidly changing technologies. Finally, as engineers have responsibility of deliver real products and services of benefit to society (UNESCO, 2010), to know the antecedents of proactivity is especially relevant for organizations and society. Our findings provide support for the hypothesized relationships. We found that the engineers’ shared perception of HPWS is significantly and positively related to the three dimensions of work role performance at individual level: proficiency, adaptivity, and proactivity. This is an important contribution because “at the highest level, the immediate and direct goal of HR systems is to obtain desired employee performance 21 which, conceptually, directly impacts organizational performance” (Jiang et al., 2012, p. 77). As expected, consistent with previous studies (e.g., Brown & Peterson, 1994; Karatepe et al., 2006), this research also found that effort is a significantly and positively associated with performance. Engineer effort fully mediates the relationship between HPWS and the performance dimensions, hence supporting the beneficial effects of HPWS on the dimensions of work role performance at individual level and explaining a process through which these relationships happen. This result indicates that HPWS can lead to positive engineer reactions, in particular to a greater effort, and significantly enhance engineer performance. This result is important because only a few recent studies (e.g., Shin et al., 2013) have examined mediating effects on the relationship between HPWS and individual performance; moreover, to our knowledge, there are no studies that analyze either the relationship between HPWS and the three dimensions of work role performance identified by Griffin et al. (2007), or the mediating role of effort on the HPWS-individual performance relationship. From a theoretical perspective, the findings are consistent with the signaling (Spence, 1973) and social exchange (Blau, 1964) theories. If employees perceive job security, training and promotion opportunities, the possibility to participate in the decision making process (HPWS components), they will show stronger feelings of obligation toward the organization, performing with greater effort, or in other words, working harder (Mitchell & Daniels, 2002). A second goal of the current study was to analyze the potential role of organizational tenure in the relationships between individual effort and proficiency, adaptivity, and proactivity. Results also find general support for the proposed moderating role of organization tenure. The relationships between effort and the three dimensions of 22 performance are stronger for long-tenured employees. These results contribute toward addressing the knowledge gap regarding the role individual differences play in the relationship between HPWS and its outcomes. Our findings have important implications for management practice. Clearly, they indicate the need for organizations to focus on their HR practices and invest in engineers. Engineering relates to “the understanding, design, development, invention, innovation and use of materials, machines, structures, systems and processes for specific purposes” (Marjoram & Zhong, 2010, p. 24). Consequently, engineers need to be adaptable to be effective in dynamics contexts (Hoyer et al., 2010) and show proactivity behaviors to innovate and to look for solutions to job problems (Beltrán-Martín et al., 2017). Our results suggest that engineers’ performance can be improved by implementing a HPWS. Finally, since organizational tenure moderates the link between engineer effort and proficiency, adaptivity and proactivity, managers should pay attention to the development and strengthening of connections between engineers with different organizational tenure. One possibility is to take advantage of social networking technology to connect short-tenure engineers with long-tenured employees, even if they are in different locations. 6 Limitations and Future Research Despite its strengths, including the occupational group analyzed, the multilevel methodology utilized, the use of engineers HPWS perceptions, and the assessment of engineers’ performance by their supervisor, the present study has limitations that future research should consider. First, because of the cross-sectional nature of the research design, we cannot definitively establish a causal direction from HR practices to employee outcomes. 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For each item indicate the extent of your agreement or disagreement as a description of the practices employed by your firm related to engineers (1= strongly disagree, 7= strongly agree). Selective Staffing (AVE=.684, CR= .865) Great effort is taken to select the right engineer. .845 Engineers’ long-term potential is emphasized. .715 Considerable importance is placed on selective staffing. .907 Extensive Training (AVE=.697; CR= .871) Extensive training programs are provided for engineers. .981 Engineers will normally go through training programs every few years. .825 There are formal training programs to teach newly hired engineers the skills they need to perform their job. .669 Internal mobility (AVE=.562; CR= .791) Engineers have few opportunities for upward mobility. .635 Vacancies at executive levels are filled by engineers from the organization. .847 Promotion in this organization is based on seniority. .752 Employment security (AVE=.689; CR= .812) Engineers in this job can be expected to stay with this organization for as long as they wish. .786 Job security is almost guaranteed to engineers in this job. .872 Clear job description (AVE=.713; CR= .882) The duties in engineers’ jobs are clearly defined. .811 Engineers’ job has an up-to-date description. .853 The job description for a position covered by an engineer describes all the duties performed. .869 Results-Oriented Appraisal (AVE=.667; CR= .857) Engineers’ performance is most often measured with objective quantifiable results. .828 Engineers’ performance assessment follows a formal process. .861 Engineer appraisals emphasize group based achievement. .757 Incentive Reward (AVE=.544; CR= .693) Engineers in this job receive bonuses based on the profit of the organization. .550 Pay is closely tied or matched to individual/group performance. .886 Participation (AVE=.533; CR= .772) Engineers in this job are often asked by their supervisor to participate in decisions. .637 Engineers in this job are allowed to make decisions. .824 Engineers are provided the opportunity to suggest improvements in the way things are done. .718 9. HPWS (AVE=.500; CR= .879) Selective staffing. .730 Extensive training. .620 Internal mobility. .591 Employment security. .269 Clear job description. .722 Results-oriented appraisal. .909 Incentive reward. .837 35 Participation. .770 Indicate your level of agreement or disagreement with the following statements (1=strongly disagree, 7=strongly agree) Effort (AVE=.769; CR= .909) When I work, I do so with intensity. .893 I work at my full capacity in all of my job duties. .871 I strive as hard as I can to be successful in my work. .867 Regarding the following statements about the performance level of the engineer with ID…. during the last year, indicate your level of agreement or disagreement with each statement (1=strongly disagree, 7=strongly agree) Proficiency (AVE=.699; CR= .874) Carried out the core parts of your job well. .875 Completed his/her core tasks well using the standard procedures. .826 Ensured his/her tasks were completed properly. .806 Adaptivity (AVE=.778; CR=.913) Adapted well to changes in core task. .920 Coped with changes to the way he/she has to do his/her core tasks. .938 Learned new skills to help him/her adapt to changes in his/her core tasks. .780 Proactivity (AVE=.862; CR=.949) Initiated better ways of doing his/her core tasks. .917 Came up with ideas to improve the way in which his/her core tasks are done. .924 Made changes to the way his/her core tasks are done. .945 (*) All standardized loadings are significant (p < .01) 36 Appendix B. Discriminant validity: AVE and squared correlations among variables HPWS Effort Proficiency Adaptivity Proactivity HPWS .500 Effort .134 .769 Proficiency .010 .073 .699 Adaptivity .088 .092 .591 .778 Proactivity .004 .036 .425 .487 .863