Perceived High-performance Work System and ...

Article

Perceived High-performance Work System and Employee Performance: Role of Self-efficacy and Learning Orientation

Metamorphosis 15(2) 115–133 © 2016 Indian Institute of Management, Lucknow SAGE Publications sagepub.in/home.nav DOI: 10.1177/0972622516688392 http://met.sagepub.com

Jeeven Jyoti1 Manisha Dev1

Abstract The present study focuses on exploring the role of self-efficacy between high-performance work system (HPWS) and learning orientation. Further, the role of learning orientation between HPWS and employee performance (EP) has also been evaluated. Additionally, the impact of HPWS on employee when moderated by self-efficacy and mediated by learning orientation has been studied. The model has been tested in the service sector (banking sector). The data obtained have been duly validated with the help of confirmatory factor analysis. Structural equation modeling has been used for hypotheses testing. The results indicate that self-efficacy moderates the relationship between the HPWS and learning orientation. In addition, learning orientation mediates the relationship between the HPWS and EP relationship. The results further reveal that the learning orientation mediates the interaction effect of HPWS and self-efficacy on EP (moderated mediation). Finally, the managerial implications, limitations and scope for future research have been discussed.

Keywords High-performance work system, self-efficacy, learning orientation, employee performance

Executive Summary High demand and competition for employee and managerial talent has led to increased interest in understanding the potential benefits of using high-performance work systems (HPWS) as a means of maximising organization’s competitive advantage. The earlier research on outcomes of HPWS has focused on managerial perspective and organizational related outcomes like organizational performance. But it has been found that HPWS affect employee related outcomes more than organizational related outcomes. So working on these lines the present study, focused on HPWS based on AMO model and the role of self-efficacy (as moderator) and learning orientation (as mediator) between perceived HPWS and employee performance. The model has been tested on the data collected from employees (530) working in six banks operating in Jammu province in Jammu & Kashmir (North India). The constructs have been duly validated with the help of Confirmatory factor analysis (CFA). Reliability has been assessed through Cronbach’s alpha and composite reliability (> 0.70). Structural

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equation modeling (SEM) has been used for hypotheses testing. In order to test the moderation effect, the product indicator approach has been used (Little et al., 2007, p. 223; Jyoti & Dev, 2015). Further, Preacher and Hayes (2004) methodology has been adopted for checking mediation. The moderated-mediation has been checked by conducting multi-group analysis. The results indicate that self-efficacy act as a moderator between perceived HPWS and learning orientation. Further, learning orientation mediates the relationship between perceived HPWS and employee performance relationship. Finally, the results also revealed that interaction of HPWS and self-efficacy indirectly affects employee performance through learning orientation (Moderated-Mediation). Managerial implications highlight that implementation of HPWS is imperative for banking sector. Ability, motivation and opportunity related activities should be provided simultaneously to improve employee performance. Management should organise extensive training and re-training programmes regarding new product and processes. Management should

Department of Commerce, University of Jammu, Jammu (J&K), India.

Corresponding author: Manisha Dev, Research Scholar, Department of Commerce, University of Jammu, Jammu (J&K), 180006, India. E-mail: [email protected]

116 ensure that employees, who solve customers’ problem and exhibit effective recovery efforts, should be rewarded and recognised. Management should empower employees by providing them responsibility and authority to deal with customer requests and problems quickly. The limitation of study is that it is a cross-sectional study, which can not reveal true cause-effect relationship. Longitudinal designs are needed in future research to extend the findings.

Introduction Complex and dynamic business has compelled the organization to continuously explore and exploit new opportunities for long-term survival1Dizgah et al. 2011. So, there is a paradigm shift in thinking world regarding the contribution of human resources (HR) department towards the organizational success. For this, organizations need proactive employees who are willing to take initiatives in solving organizational problems2. High demand and competition for employees and managerial talent has led to an increased interest in understanding the potential benefits of using high-performance work systems (HPWS) as a means of maximizing organization’s competitive advantage3. It increases employee’s adaptability towards dynamic environment, which in turn enhances competitiveness4. The flexible nature of HR practices in HPWS enhances organizational performance through employee involvement and empowerment5,6,7,8. HPWS focuses on enhancing intellectual capital and motivating employees for achieving organizational goals, and provide employees with opportunities to do so9,10. Hence, HPWS enhances employees’ ability, motivation and opportunities to develop11. It is an important contributor to organizational success as it shifts the responsibility from managers to employees (Boxall and Purcell, 2013),12 to increase business performance13. It plays a synergistic role by integrating the organizational strategies with HR strategies that in turn lead to higher performance.

The Review of Literature Various researchers have studied high-performance human resource (HPHR) practices1,6,14,15,16,17, Kaveri and Prabakaran, 2013. Human resource management (HRM) literature has identified best HR practices, such as recruitment and selection3,18, extensive training, Bartram, 20146,19,20, performance management3,18,20, performance appraisal14,21, performance-based compensation19,20,22, empowerment3,14,23, competency development24, information sharing20, teamwork,3,23,25,26 and job security19,20. So, there is lack of consensus regarding HPHR practices which help systems to become HPWS. In this context, Appelbaum et al.27 gave the ability, motivation and opportunity (AMO) model, which has been further supported by Boxall and Purcell11 and stresses on the fact that HPWSs encompassing AMO lead to better employee performance (EP) and, ultimately, organization performance. Further,

Metamorphosis 15(2) Boxall and Macky28 argued that the process of HRM is actually a chain of links in which intended HR practices lead to actual HR practices that develop employees’ perception about HR practices, and hence generate positive employee reactions, which finally enhance organizational performance. HR strategies, such as high-performance, high-commitment or high-involvement work practices, lead to better organizational performance29. The metaanalysis conducted by Subramony30 revealed that bundled HRM practices focused towards empowerment, motivation and skill enhancement of employees that have a greater impact on business outcomes as compared to individual HR practices and the same has been reconfirmed by Jyoti et al.31 Further, Bowra et al.32 found positive relationship between HR practices and employees’ perceived performances. Boxall and Purcell33 and Boxall et al. (2011) demonstrated the centrality of employee attitudes in mediating the relationship between HPWS and individual performance. Wood and Menezes34 and Jensen et al.3 revealed that the negative outcomes like anxiety and overload get reduced by adequately empowering employees job control. Further, some studies have revealed that HPWS results in positive employee attitudes like job satisfaction35,36, organizational commitment37 and organizational citizenship behaviour (Dizgah et al., 2011), but there are studies that revealed negative outcomes such as burnout38 (Kroon et al., 2009), anxiety106, emotional exhaustion31 and intention to leave39. Several researchers have also discussed the presence of the missing link, that is, “Black-box” between HPWS and its outcomes. In this context, Jiang et al.40 have reviewed 74 studies out of which 69 studies have focused on mediating variables between HPHR practices and its outcomes. Besides this, Arefin et al.2 illustrated that HPWS psychologically empower employees (mediator), which motivate them to display proactive behaviour. Bartram et al.41 revealed that social identification act as a mediator between HPWS and psychological empowerment relationship. Further, Mostafa and Gould-Williams36 empirically proved that Person-organization fit (P-O fit) partially mediates the relationship between HPWS and job satisfaction and organizational citizenship behaviour. The study by Garcia-Chas et al., 2014 revealed that job satisfaction mediates the relationship between HPWS and intention to leave, while procedural justice and intrinsic motivation mediates the relationship between HPWS and job satisfaction. Moreover, Fabi et al., (2015) demonstrated that job satisfaction and organizational commitment mediates between the relationship HPWS and intention to quit. Further, the relationship between HRM practices (selection, development practices, competence-based appraisals and rewards) and organizational learning capability is partially mediated by human capital42. Lopez et al.17 have explored the impact of four HPHR practices (selective hiring, strategic training, participation of the employees in decision-making and contingent compensation) on business performance through organizational learning. Raj and Srivastava43 revealed partial

Jyoti and Dev 117 mediation effect of organizational learning in between the relationship of organizational culture and innovativeness, and HRM practices and innovativeness. In Indian context, a series of empirical work has explored the linkage of HRM practices and their impact on employee-related outcomes and organizational performance. For example, Singh44 proved that strategic HR-oriented organizations perform better than those with less emphasis on HR practices. Som45 revealed that innovative HRM enhances corporate performance during the change process in the context of economic liberalization in India. Chand and Katou46 suggested that HR practices enhance organizational performance in the Indian hotel industry. Muduli47 studied formulation and implementation of Strategic Human Resource Management (SHRM) in the public sector in India and proved significant relationship among business strategy, SHRM practices, HR outcomes and organizational performance. Muduli48 examined the mediating role human resource development (HRD) climate between HPWS and organizational performance in the Indian power sector. Chahal et al.49 explored the role of organizational learning between HPHR practices and business performance in context to telecommunication industry in India. Further, Muduli et al.50 examined the relevance of HPWS in Indian context and suggested that Indian organization should adopt HPWS by suitably aligning with employee engagement to improve organizational performance and so on. Further, studies have been conducted on HPHR practices in Indian banking sector too. For example, Goyal and Babel51 identified specific issues and challenges in worklife balances in banking industry and revealed that output of the banking sector is dependent on the quality of HR. Singh52 studied the administrative skills, competitive advantage and HRD policies in the banking sector and revealed that bank managers have good administrative skills for industrial competitiveness as well as for managing HRD policies. Further, Shrivastava and Rai53 studied the essentials of performance appraisal in Indian banking sector and suggested the relevance of performance appraisal in analyzing employees’ recent successes and failures, personal strength and weaknesses. Shukla54 focused on rising issues and challenges of HRM faced by HR managers in the public sector banks in Indian. Rainke55 examined the role of human capital management (HCM) practices followed by the banks and identified the factors affecting HCM and suggested that HCM is responsible for the people dimension of an organization. Chahal and Bakshi56 empirically tested the intellectual capital scale in the banking sector that helps bank managers in determining how to generate value using human, structure and rational capital. Further, Chahal and Bakshi57 proved the mediating role of innovation between intellectual capital and competitive advantage relationship in the banking sector. So, it can be concluded that there is lack of empirical research, specifically on HPWS in Indian banking

industry. In this context, the objectives of the present study are to evaluate the AMO model-based HPWS in India and also to examine the role of self-efficacy and learning orientation between HPWS and EP.

Need of the Study Based on the review of literature, it can be summed up that HR practices/HPWS enhances organizational performance. Further, earlier research on outcomes of HPWS has focused on managerial perspective and organizational-related outcomes like organizational performance. But, it has been claimed in earlier research that HPWS affect employeerelated outcomes more than organizational-related outcomes (Zhang et al. 2014). So, working on these lines, the present study proposes to evaluate the effect of perceived HPWS on EP (from employee perspective). Further, Boxall and Purcell11 and Messersmith et al.16 have stressed the need to explore the black-box between HR practices and its related outcomes. On these lines, Jiang et al.40 have reviewed 74 papers out of which 69 papers focused on mediating variables between HPHR practices and organizational performance. But, there is lack of studies that have focused on the role of self-efficacy and learning orientation between HPWS and EP relationship. So, in the present study, we have focused on HPWS based on the AMO model (as recommended by Jiang et al.40) and EP relationship. Further, the moderating role of self-efficacy between perceived HPWS and learning orientation will be evaluated, and the mediating role of learning orientation between HPWS and EP will also be explored (both are unexplored till now). The integrated model will trace the impact of the interaction of HPWS and self-efficacy on EP in the presence of learning orientation for high and low groups of moderating variable (self-efficacy).

Objective of the Study The review of literature led to the research gap, which helped in framing the objectives of the study as follows: • To validate the HPWS (the AMO model) scale in Indian context. • To study the role of self-efficacy between HPWS and learning orientation. • To evaluate the role of learning orientation between HPWS and EP. • To examine the combined impact of self-efficacy and learning orientation between HPWS and EP equation.

Theoretical Framework and Hypotheses Development Figure 1 represents the conceptual model, which helped in generation of hypotheses. The model shows self-efficacy

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Figure 1. Theoretical Framework Source: Authors’ own.

as a moderator between HPWS and learning orientation relationship. Further, learning orientation mediates the relationship between HPWS and EP.

Ability, Motivation and Opportunity-based HPWS The HR system that enhances employees’ competencies, commitment and productivity are called HPWS (Dutta et al. 2005). HPWS is a mechanism that is designed to enhance employees’ skills and efforts by participative form of work16. In other words, HR system impacts on the skills and knowledge of employees, their willingness to exert effort and provide them opportunities to express their talents at workplace58. Although there remains substantial question regarding the specific practices that constitute HPWS59, in this context, one of the most influential theory is AMO theory put forth by Appelbaum et al.27. It contends that the HPWS is a mix of key practices, that is, more rigorous selection and better training systems to increase ability levels, more comprehensive incentives to enhance motivation and participative structure that improves opportunity to contribute. Further, Boxall and Purcell11 also stressed on the fact that HPWPs are a product of AMO. The fundamental tenet of the AMO model is that HPWS develops employee’s abilities and enhances their motivation by providing training, rewards and empowerment60. The AMO model has divided HPWS into three dimensions: ability enhancing, motivation enhancing and opportunity enhancing HR practices39,61. Ability enhancing practices includes training and competence development that affect the type and level of the knowledge, skills and abilities of the employees27,30,58. Motivation enhancing practices include performance-based pay, performance management, feedback and incentives that motivate employees’ efforts and behaviour. Opportunity enhancing practices include empowerment, job autonomy and participation in decision-making62. So, on the basis of above discussion, it can be concluded that HPWS is reflected through AMO.

HYP1:  HPWS is reflected through ability, motivation and opportunity (AMO).

High-performance Work System, Selfefficacy and Learning Orientation HPWS is a set of specific combination of HR practices that maximize employee knowledge, skills, ability as well as commitment towards accomplishment of goals.49 While, self-efficacy is conceptualized as the confidence in one’s own coping skills and capacity to organize and execute the course of action to attain designated goals63. It is a form of internal motivation that influences an individual’s choice of activities, the level of achievements, persistence as well as performance64. Further, self-efficacious individuals tend to exercise control over their own level of functioning by weighing, integrating and evaluating information about their own capabilities65. Lastly, learning orientation is an internal drive that stimulates individual to develop their own competence by acquiring new skills and knowledge66. HPWS plays a significant role in boosting learning quotient of the employees67, as HRM practices provide employees an opportunity to develop both hard and soft skills that are crucial for an organization to attain better place in the market. HPWS based on the AMO model stresses on enhancing the AMO quotient of the employees. The ability quotient of the employees is to be enhanced by providing a clear understanding of organizational aims and goals to ensure the right direction for learning processes68. For instance, training and development not only enhance the learning orientation of employees by delivering desired skill but also encourage employees to align their knowledge and skills with the organization’s goals69. Further, the HPWS motivates employees towards continuous learning by establishing performance-based compensation and performance management for the achievement of the organizational objective. Similarly, HPWS significantly enhance learning culture by empowering the employees

Jyoti and Dev 119 through participation in decision-making23 that enhances their vision and knowledge. It also provides opportunities to employees by designing broad career paths and promotions within the organization, and guarantee of job security with the help of long-term and results-oriented performance appraisal system (Carvalho and Chambel, 2013). Therefore, HPWS helps in generating, distributing, transferring and utilizing the knowledge in an organization by enhancing general, technical and managerial capabilities24. The review of literature revealed that previous research has shown that HPWS70 and self-efficacy (Culbertson et al. 2011) are determinants of learning at the workplace. Further, studies like Huang and Weng71 and Pan et al.72 stated that self-efficacy moderates the relationship between mentoring (can be considered as performance management initiative) and personal learning, which gave us clue to hypothesize self-efficacy as a moderator between HPWS and learning orientation. Self-efficacy is the personal judgement about one’s capability to adopt certain behaviours and actions in order to accomplish certain objectives and expected outcomes73. It also encompasses employees’ level of self-confidence, capability and competence that enhance the relationship between HPWS and employees’ learning. Further, ability enhancement activities when coupled with the high-efficacy level of the employees lead to better learning (the individual as well as the organizational level). HPWS when associated with self-efficacy helps to enhance the level of learning as these HR practices enhance the skills of the employees, encourage participation in decision-making and motivates employees to expend discretionary efforts. For example, extensive training programmes provide a wide range of development activities that enhances employees’ knowledge, skills and abilities7. Training coupled with the efficacy level of employees enhances the learning quotient. So, HPWS enhances the level of learning among employees by encouraging skill improvement34, and self-efficacious employees have the confidence in their abilities to grasp the imparted knowledge in a better way. Similarly, empowerment provides employees with responsibility and authority to think, behave and take decisions26 which enhances the knowledge, vision and competence of employees to deal with work-related problems (Karatepe et al. 2014). Self-efficacious employees take this opportunity to learn more and use self-regulated strategies to make learning meaningful. Similarly, the combined impact of performance-based compensation and self-efficacy is essential to motivate the employees to take the challenging work, generate and utilize the knowledge effectively. Selfefficacious employees have greater confidence and motivation to learn how to do their job in a better way (Hanham et al. 2014). Finally, HPWS associated with self-efficacy helps to enhance the level of learning as self-efficacious employees think and act in self-enhancing ways and exert considerable efforts to improve their

performance level74. Thus, self-efficacy compliments the efforts of HPWS as employees with strong self-efficacy have higher motivation, make great efforts, persist longer and achieve more, which in turn boost their learning capabilities. So, on the basis of above discussion, it can be concluded that self-efficacy provides an additional boost to the positive relationship between HPWS and learning orientation by leading the flow of information and knowledge in the right direction. HYP2:  Self-efficacy moderates the relationship between perceived HPWS and learning orientation.

High-performance Work System, Learning Orientation and Employee Performance HPWS are designed to enhance the skills and efforts of employees16,36 and it ensures the success of learning by encouraging and fostering continuous learning among employees. It promotes positive learning attitude among employees by providing comprehensive training programmes and supportive learning culture43. It is associated with providing opportunities for employee involvement and participation to all employees so that they can think of better ways of doing their jobs34. Learning orientation drives employees to improve their skills which further promotes their job proficiency75. Further, learning-oriented employees through self-regulation strategies develop their knowledge and achieve higher levels of performance76. Many authors have asserted relationship between HPWS and EP77, Wilson and Mampilly, 201432, HPWS and organizational learning6 and learning orientation and employee performance75. The learning quotient of employees in HPWS and performance relationship continuously updates the technical capabilities of the employees for remaining ahead in the competitive business environment43. HPWS paves way for enhancing employee performance12 by improving their competence, attitude, skill and motivation19. HPWS consisting of training, selective staffing and rewards enhance performance78 by increasing the knowledge and skills of employees. In this context, ability enhancing practice like training programmes stimulate the employees to generate new knowledge and utilize the gained knowledge79, which develop employees’ ability to meet higher performance standards. Similarly, motivation enhancing practice such as performance-based compensation and effective reward system encourages employees to learn more to do their job effectively. Competence-based appraisal also motivates the employees to acquire the knowledge and share it with their colleagues42 that can be applied in a context of openness and shared vision, which are essential for employee performance in the workplace1. Finally, opportunity enhancing practice like empowerment gives employees opportunity to participate in decision-making23, enhances their vision and knowledge

120 (components of learning orientation), which in turn leads to superior Employee Performance. Thus, it can be concluded that the rationale of the HPWS and performance linkage is that HPWS promotes the value, uniqueness and distinctiveness of employees’ knowledge and skills80, which in turn generates better Employee Performance. So, based on above discussion, we hypothesize that: HYP3: Learning orientation mediates the relationship between perceived HPWS and employee performance.

Moderated Mediation On the basis of above discussion, it can be concluded that the interaction of HPWS and self-efficacy affects learning orientation, which in turn leads to employee performance. The combined impact of HPWS and self-efficacy increases the learning level among employees which in turn enhances their performance standards. HPWS orient the employees towards learning by boosting employee’s confidence, skills, abilities and competences by motivating and empowering them to contribute, which in turn raises the level of employee performance. The interaction of HPWS and self-efficacy affects learning orientation which in turn leads to employee performance. So, it can be concluded that learning orientation mediates the relationship between interaction effect of HPWS and self-efficacy on employee performance.

Research Design and Methodology This research is evaluative in nature. It evaluates the relationship between HPWS, self-efficacy, learning orientation and EP. Following steps have been undertaken to make this research objective and more accurate:

Generation of Scale Items All scales in the model have been measured with the help of multiple items on the five-point Likert scale, ranging from 1 (strongly disagree) to 5 (strongly agree) for the sake of uniformity. HPWS construct comprised three dimensions, namely, ability (3 items from Jensen et al.3 and 2 items from Pare and Tremblay81), motivation (5 items from Jensen et al.3) and opportunity (5 items from Pare and Tremblay81). Sixteen items of learning orientation have been adapted from Jyoti and Dev82. This construct comprised four dimensions, namely, commitment to learning (4 items), shared vision (4 items), open-mindedness (4 items) and intra-organizational knowledge sharing (4 items). The seven items of the self-efficacy scale have been adapted from the study by Sujan et al83. Five items of EP have been adapted from Fuentes et al84. (cited in Jyoti and Sharma85).

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Pilot Survey A pilot survey has been conducted on 100 employees (selected conveniently) working in the six banks operating in Jammu province. Exploratory factor analysis (EFA) has been applied for factor identification of the HPWS (the AMO model) scale in Indian settings. Initially, the HPWS scale comprised 15 items that were reduced to 11 items and converged under three factors, namely, ability (4 items), motivation (4 items) and opportunity (3 items), which together explained about 69 per cent of the total variance and the KMO value is 0.951, which is excellent as compared to the threshold value (0.50). Similarly, the learning orientation scale comprised 16 items that converged under four factors, namely, commitment to learning (4 items), shared vision (4 items), open-mindedness (4 items) and intra-organizational knowledge sharing (4 items). These four factors are responsible for 69.27 per cent of total variance and have a meritorious KMO value (0.963). Same procedure has been followed for self-efficacy and EP scales, which resulted into one-factor solution with five and four items, respectively. The self-efficacy scale is explaining 63.52 per cent of the total variance with excellent KMO value (0.924). Similarly, 66.20 per cent variance is being explained by the EP scale. The KMO value (0.807) of this scale is also very good. The items that emerged after EFA have been used for final data collection.

Sample Design and Data Collection Indian banking sector is one of the largest banking network in the world and the fastest growing sector in India53. It has emerged as one of the strongest drivers of India’s economic growth86. As far as the current scenario is concerned, the Indian banking sector is in the transition phase as the banking sector across the globe is facing greater challenges in terms of technological advancement, service diversification, employing and retaining skilled employees as well as re-training of the existing workforce87. The banking sector, like other sectors, has become one of the highly competitive sectors in India and requires more skilled and knowledgeable employees. In this regard, banks have been heavily investing in recent management practices like talent management to manage their HR88. Further, employees’ behaviour in banks is the product of continuous training programmes, performance management, coaching, performance-based compensation, bonus or rewards programmes, and consistent and fair evaluation of employee productivity and performance. This is the result of efforts taken by the management to implement HPWS in banks to transform average employees to better performing employees. So, the banking sector has been selected to test the hypothesized theoretical framework. The population consisted of 1,225 employees working in six banks, namely, PNB, SBI, J&K, ICICI, HDFC and Axis operating in Jammu province. These six banks have

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Measurement Validation

Table 1. Results of Independent T-test Scale HPWS Self-efficacy Learning Orientation EP

Public Banks Private Banks Mean Mean T-Value

Significant Value

4.150 4.168 4.089

4.194 4.179 4.056

0.666 0.143 0.462

0.506 0.887 0.644

4.135

4.161

0.333

0.739

Source: Authors’ own.

been selected on the basis of their market share. All employees have been contacted to generate research information. Only 538 employees returned back the questionnaires. Out of which, 8 questionnaires were incomplete and not included in the study. Thus, final sample came to 530. Further, the data were checked for normality through inspection of box plots, which revealed 20 outliers that were excluded from the sample89. The value of skewness (0.206) and kurtosis (0.664) established the normality of the data89. Thus, responses of 510 employees have been used for the analysis. As sample size consists of both public and private bank employees, before analysis, we have conducted preliminary test to examine the perceptual mean difference between public and private banks’ employees. Independent t-test has been used to assess the significance of difference in the mean scores of two set of respondents. The results revealed that there exists no significant difference in the responses of public and private banks’ employees (p > 0.05) for all the study variables, namely, HPWS, selfefficacy, learning orientation and EP (Table 1).

We assessed the validity and reliability of the constructs with the help of CFA. The HPWS scale has not been validated in Indian context, so we validate it with the help of CFA. Factors that emerged after EFA have been used to design the first order factor model with dimensions AMO. All the model fit criteria, that is, χ2/df = 3.156, RMR = 0.028, GFI = 0.955, AGFI = 0.928, NFI = 0.960, CFI = 0.972 and RMSEA = 0.065 are close to or surpass the recommended levels. After this, the second order factor model has been generated and the results indicate that all the dimensions are significantly loaded on latent construct, that is, HPWS. The second order factor model results reveal that the model fit statistics as χ2/df = 3.156, RMR = 0.028, GFI = 0.955, AGFI = 0.928, NFI = 0.960, CFI = 0.972 and RMSEA = 0.065. Further application of chisquare difference test (as suggested by Arnold et al. 2007; Kelloway94) revealed that there are no difference between the two models as well as their goodness-of-fit indices. So, we compared the correlations of the first order factor model with the standardized regression weight of the second order factor model and results revealed that standardized regression weights are better than correlations (see Figures 2 and 3). Hence, we retained the second order factor model which leads to the acceptance of our first hypothesis, that is, HPWS is reflected through AMO. Further, the second order factor model have been designed for learning orientation construct as multiple factors emerged after EFA and zero order factor models

Common Method Variance The data were self-report in nature, which can cause the problem of common method variance90. Therefore, in order to remove this problem, Harman’s91 one-factor test was applied where EFA was conducted using principal component analysis and varimax rotation for all independent and dependent variables. The results revealed that no single factor was explaining majority of the variance, providing preliminary evidence that no substantial common method bias exists in the data92. Further, confirmatory factor analysis (CFA) helps to remove the problem of common method bias.

Results A two-step approach to structural equation modeling (SEM) using AMOS (16 version) has been applied as suggested by Anderson and Gerbing93. CFA was conducted in the first step to assess the proposed measurement model fit and construct validity, while the second step aimed at developing and estimating the structural model for testing the significance of theoretical relationship.

Figure 2. First Order Factor Model of HPWS Source: Authors’ own. Notes: HPWS = High-performance work system, A= Ability, M = Motivation and O = Opportunity.

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Figure 3. Second Order Factor Model of HPWS Source: Authors’ own. Notes: HPWS = High-performance work system, A = Ability, M = Motivation and O = Opportunity.

have been designed for the self-efficacy and EP constructs. The fit indices of measurement models are within the prescribed limit (Table 1). The goodness-of-fit indices like GFI, CFI and AGFI are greater than 0.90 and the badnessof-fit criteria like RMSEA and RMR are less than 0.80 and 0.50, respectively (Hair et al. 2010). For evaluation of

internal consistency among the items, Cronbach’s alpha has been assessed95. The scale reliability has been also assessed through composite reliability measure and the average variance extracted (AVE). Convergent and discriminant validity have been assessed as a part of construct validity since the multiple items used to measure the same construct should be in agreement, while items between different constructs should be distinct96. Using CFA, we established convergent validity by the magnitude of standardized estimates (> 0.5) and significance of the factor loadings97. Further, for assessment of discriminant validity, we compared the variance extracted with squared correlation of different scales (Table 3) as recommended by Forrell and Lacker (1981). The results of the scale-level reliability and validity assessment are summarized in Table 2. All standardized estimates are significant (SRW > 0.50, P < 0.05), indicating good quality of the measurement items. Cronbach’s alpha and composite reliability for all the scales are above the conventional cut-off limit (> 0.7) and AVE is also greater than 0.50. Further, cross-validation of measurement models has also been done splitting the sample into two groups, that is, public and private bank employees. The results matched with the results of overall tested measurement models with slight variation in regression weights. Further, the chi-square difference test also gave insignificant results (P > 0.05), thereby supporting our measurement models.

Hypotheses Testing SEM has been used to check various relations; it is a multivariate technique that seeks to explain the relationship

Table 2. The Results of Scale-level Reliability, Validity and Goodness of Model Fit Construct

SRW

HPWS 1. Ability 2. Motivation 3. Opportunity Self-efficacy

0.990 0.924 0.948

1. SE2 2. SE4 3. SE5 4. SE6 5. SE7 Learning Orientation

0.791 0.774 0.764 0.777 0.794

1.  Commitment to learning 2.  Shared Vision 3. Open-mindedness 4. Intra-organizational knowledge sharing

0.874 0.983 0.914 0.783

AVE

CR

CA

0.988

0.995

0.922

Goodness of Model Fit |2/df = 3.156, RMR = 0.028, GFI = 0.955, AGFI = 0.928 CFI = 0.972, RMSEA = 0.065

0.946

0.988

0.902

|2/df = 2.701, RMR = 0.022 GFI = 0.980, AGFI = 0.960, CFI = 0.9687, RMSEA = 0.058

0.975

0.993

0.953

|2/df = 2.638, RMR = 0.037 GFI = 0.925, AGFI = 0.903 CFI = 0.966, RMSEA = 0.057

Jyoti and Dev 123 Construct

SRW

EP

1.  EP1 2. EP2 3. EP3 4. EP4

AVE

CR

CA

0.927

0.980

0.862

Goodness of Model Fit |2/df = 1.587, RMR = 0.013 GFI = 0.997, AGFI = 0.984 CFI = 0.998, RMSEA = 0.034

0.759 0.655 0.759 0.792

Source: Authors’ own. Notes: SRW = Standard regression weight, AVE = Average variance extracted, CR = Composite reliability, CB = Cronbach’s alpha, |2 = chi-square, df = degree of freedom, GFI = goodness of fit index, AGFI = adjusted goodness of fit index, CFI = comparative fit index, RMR = root mean residual, RMSEA = residual mean square error of approximation.

Table 3. Discriminant Validity and Correlation Matrix HPWS HPWS Self-efficacy Learning Orientation EP

0.988 0.232 (0.482**) 0. 230 (0.480**) 0.300 (0.548**)

Selfefficacy

Learning Orientation

EP

0.946 0.212 (0.461**) 0.260 (0.510**)

0.975 0.243 (0.493**)

0.927

Source: Authors’ own. Notes: Values on the diagonal axis represent AVE, squared correlations are given below the diagonal axis and values within the paranthesis represent correlation. ** p < 0.01.

among multiple variables98. It is superior to ordinary regression models as it incorporates multiple independent and dependent variables as well as hypothetical latent constructs. It also provides a way to test the specified set of relationships among observed and latent variables as a whole99. Before checking the moderation and mediation, we have checked the direct relationships between the variables, for example, the relationship between HPWS and learning orientation is significant (SRW = 0.48, p < 0.05). Further, we also checked the dimension-wise relationship between HPWS and learning orientation and found that ability affects shared vision (0.76, p < 0.05); openmindedness (0.73, p < 0.05); commitment to learning (0.66, p < 0.05); and intra-organizational knowledge sharing (0.60, p < 0.05). Motivation is highly related to commitment to learning (0.71, p < 0.05); open-mindedness (0.60, p < 0.05); shared vision (0.55, p < 0.05) and intra-organizational knowledge sharing (0.51, p < 0.05). Similarly, opportunity leads to shared vision (0.77, p < 0.05); openmindedness (0.70, p < 0.05); commitment to learning (0.66, p < 0.05); and intra-organizational knowledge sharing (0.60, p < 0.05). Further, the relationship between learning orientation and EP is also significant (0.63, p < 0.05). Similarly, the dimension-wise relationship between learning orientation and EP was also checked. The result revealed that shared vision leads to EP (0.630, p < 0.05)

followed by intra-organizational knowledge sharing (0.521, p < 0.05); open-mindedness (0.500, p < 0.05) and commitment to learning (0.404, p < 0.05). Finally, we have checked the relationship between HPWS and EP and the result revealed the significant relationship between the two variables (0.52, p < 0.05). Further, the dimension-wise relationship between HPWS and EP was checked and found that opportunity highly affects EP performance (0.597, p < 0.05) followed by ability (0.559, p < 0.05) and motivation (0.500, p < 0.05).

Test of Moderation In the first part of the present study, the relationship between HPWS, self-efficacy and learning orientation have been assessed. Therefore, in order to check the moderating effect of self-efficacy between HPWS and learning orientation, product indicator approach has been used82,100. There are three manifest variables of the predictor HPWS (AMO) and five manifest variables of the moderator self-efficacy (SE2, SE3, SE4, SE5 and SE6), therefore, 15 manifest variables have been generated that represent the interaction variable. The result revealed that the interaction of HPWS and self-efficacy is significantly predicting learning orientation (SRW = 0.52, p < 0.01, see Figure 4). Therefore, we can conclude that self-efficacy moderates between HPWS and learning orientation relationship. Hence, Hypothesis 2 is accepted. Further, model has been cross validated by checking the same in both the sectors. The results revealed that the interaction of HPWS and self-efficacy is significantly predicting learning orientation in both the sectors, namely, the public sector (SRW = 0.193, p < 0.05) and the private sector (SRW = 0.394, p < 0.01). Further, to explore the nature and form of the significant interactions between HPWS and self-efficacy, we conducted simple slope analysis using one standard deviation above and below the mean of moderating variable. These slopes reveal that the high level of self-efficacy strengthens the relationship between HPWS and learning orientation (see Figure 5).

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Figure 4. Moderating Impact of Self-efficacy between HPWS and Learning Orientation Source: Authors’ own. Notes: HPWS = High-performance work system (independent variable), A = Ability, M = Motivation, O = Opportunity, SE = Self-efficacy (moderating variable), HP*ES = Interactive effect, LO = Learning orientation (outcome), CL = commitment to learning, SV = Shared vision, OM = Openmindedness, IOK = Intra-organizational knowledge sharing.

Figure 5. Simple Slope Analysis Source: Authors’ own.

Test of Mediation In the second part of the study, we checked the mediation of learning orientation between HPWS and EP. Preacher and Hayes’101 methodology has been adopted for mediation. They recommended that mediation analysis be based on formal significance test of indirect effect of which the Sobel test102 is the best known. This approach is more powerful than the stepwise procedure of Baron and Kenny

(1986) because it more directly addresses mediation103. In the present study, the two steps were followed to check the following hypotheses: First, all the direct paths in the structural model were checked. The results revealed the significant relationship between HPWS and learning orientation (SRW = 0.48, P < 0.001) and between learning orientation and EP (SRW = 0.63, P < 0.001; see Figures 6 and 7). In the second step, we checked indirect effect of HPWS on EP through learning orientation with the help of Sobel statistics. The results revealed significant indirect effect of learning orientation between HPWS and EP (Sobel statistics = 8.08, p < 0.01), which proves mediation (Figure 8). Further, indirect effect has been re-evaluated by bootstrapping the data by re-sampling to 1,000 samples. Bootstrapping results yielded significant indirect effect of HPWS on EP through learning orientation with 95 per cent confidence. In order to test the type of mediation, the direct and indirect effect in presence and absence of mediator has been examined (see Table 4). So, on the basis of above results, it is clear that learning orientation mediates the relationship between HPWS and EP, which satisfies our Hypothesis 3. Further, the results of cross-validation also revealed that learning orientation

Jyoti and Dev 125

Figure 6. Impact of HPWS on Learning Orientation Source: Authors’ own. Notes: HPWS = High-performance work system, A = Ability, M = Motivation, O = Opportunity, LO = Learning orientation, CL = Commitment to learning, SV = Shared vision, OM = Open-mindedness, IOK = Intra-organizational knowledge sharing.

e4

1

e3

1

e2

1

e1

1

CL

e9 0.83

SV

0.94

OM

0.82

IOK

0.76

1 LO

0.63***

EP

0.72

EPI

0.64

EP2

0.72 0.76

EP3 EP4

1 1 1 1

e5 e6 e7 e8

Figure 7. Impact of Learning Orientation on Employee Performance Source: Authors’ own. Notes: LO = Learning orientation, CL = Commitment to learning, SV = Shared vision, OM = Open-mindedness, IOK = Intra-organizational knowledge sharing, EP = Employee performance, EP1 to EP4 = Manifest variables.

Figure 8. Mediation Model Source: Authors’ own. Notes: HPWS = High-performance work system (independent variable), A = Ability, M = Motivation, O = Opportunity, LO = Learning orientation (mediating variable), CL = Commitment to learning, SV = Shared vision, OM = Open-mindedness, IOK = Intra-organizational knowledge sharing, EP = Employee performance (outcome), EP1 to EP4 = Manifest variables.

126

Metamorphosis 15(2) Table 4. Bootstrapped Results for Mediation

Hypothesis HPWS–LO–EP

Direct b without Mediator (HPWS–LO) 0.480***

Direct b with Mediator (HPWS–LO–EP) 0.404***

Indirect Effect 0.144***

LL95%–UL 95% 0.181–0.416

Mediation Type Partial Mediation

Source: Authors’ own. Notes: ***p < 0.001, N = 1,000 bootstrapping resample, LL BCA and UL BCA = Lower level and upper level of the bias corrected and accelerated confidence interval.

mediates the relationship between HPWS and EP as the indirect effect is significant in both the sectors, namely, the public sector banks (indirect effect = 0.134, p < 0.01) and the private sector banks (indirect effect = 0.140, p < 0.01).

Test of Moderated Mediation Further, we tested the integrated model whereby the strength of the relationship between HPWS on EP through learning orientation is conditional on the value of a moderator, that is, self-efficacy. The moderated mediation is demonstrated when the indirect effect of HPWS on EP in presence of moderating variable is significant. The interaction effect of HPWS and self-efficacy on EP through learning orientation for both the groups is significant as the conditional indirect effect is significant as revealed by bootstrapped results (Figures 9 and 10). Hence, Hypothesis 4 got accepted (Table 5).

Discussion HPWS has been researched for more than two decades and recognized equally by academicians and practitioners. The study takes into account the moderating variable (selfefficacy) and mediating variable (learning orientation). The study evaluates four issues: • HPWS is reflected through AMO. • Moderating role of self-efficacy between HPWS and learning orientation relationships. • Mediating role of learning orientation between HPWS and EP relationship. • Interaction effect of HPWS and self-efficacy on EP through mediation of learning orientation. The first part of this article validates the HPWS (the AMO Model) scale in Indian context. Our result revealed that HPWS is reflected through AMO. This finding is in line

Figure 9. Moderated Mediation Model (High Self-efficacy) Source: Authors’ own. Notes: HP*ES = Interactive effect, LO = Learning orientation (outcome), CL = Commitment to learning, SV = Shared vision, OM = Openmindedness, IOK = Intra-organizational knowledge sharing, EP = Employee performance.

Jyoti and Dev 127

Figure 10. Moderated Mediation Model (Low Self-efficacy) Source: Authors’ own. Notes: HP*ES = Interactive effect, LO = Learning orientation (outcome), CL = Commitment to learning, SV = Shared vision, OM = Open-mindedness, IOK = Intra-organizational knowledge sharing, EP = Employee performance.

Table 5. Bootstrapped Result of Moderated Mediation Moderator (self-efficacy) High Low

HPWS*SE–LO 0.383*** 0.302***

LO–EP 0.490*** 0.225***

Conditional Indirect Effect 0.188** 0.068**

Boot SE 0.066 0.029

Boot LL 95% 0.067 0.023

Boot UL 95% 0.323 0.134

Source: Authors’ own.

Notes: ***p < 0.001, N = 1,000 bootstrapping resamples, LL BCA and UL BCA = Lower level and upper level of the bias corrected and accelerated confidence interval.

with the AMO theory 11,27,61,Fabi et al, 2015 that HPWS focuses on developing employees’ ability to perform, improving their motivation to perform and creating opportunities for them to make contributions. Moreover, employees perform best when they have the motivation and when their work environment provides the necessary support and avenues for expression. According to the AMO framework, HPWS organize work processes in such a manner that encourage employees to take advantage of initiative, creativity and job-specific knowledge in the best interest of the organization. The components comprising HPWS, that is, AMO appropriately reflect the construct as these are performance oriented. Further, MacDuffie104 extended additive approach to combining HR practices and suggested that organizations should use appropriate bundles of HPWS to realize their synergistic effects. Chahal et al.49 also proved that the impact of bundled HPHR practices is higher than individual HR practices. On these lines, we have combined the HR practices into three dimensions, that is, AMO to work together leading to multiplicative

higher performance than individual practices. Further, it is stated that, ability dimension of HPWS assess an employee’s ability to fulfil the technical requirements of the job and to facilitate the acquirement and development of new skills. The motivational aspect of HPWS establishes a specific mechanism in which high-performing employees are properly recognized and rewarded for their achievement and expresses the degree to which employees’ capabilities are actually utilized. Finally, the HPWS is also reflected through opportunity dimension, which empower employees to use their skills and motivation to achieve overall objectives. Therefore, it can be concluded that the HPWS achieves the highest effectiveness through the AMO model and works as a system. The second part of this article empirically proves that self-efficacy moderates the relationship between HPWS and learning orientation. Our result demonstrates that HPWS is positively related to learning orientation. It has been observed that learning behaviour of employees is the result of ability, motivation and opportunities provided to

128 them at workplace. HPWS makes employees knowledgeable through proper communication and information. It further motivates and empowers them to learn to their full potential and break through learning boundaries. Selfefficacy acts as a moderating variable in between HPWS and learning orientation relationship. The rationale behind this is that the HPWS orient the employees more towards learning by proper training and development programmes and opportunities for personal as well as professional growth, which enhance their knowledge, skills and competencies. When the system is learning oriented and if it is coupled with employee’s self-efficacy, the impact on learning capability will be better. Moreover, the efficacious employees learn more through various training programmes, have the urge to gain more and more which motivate them to grow and learn new skills and knowledge which enhance the learning orientation. Further, the interactive effect of HPWS and self-efficacy helps to increase the level of learning among employees as highly efficacious employees use the system resources (training and competency development) for broadening their learning horizons. The combined effect of HPWS and self-efficacy boosts the leaning orientation among employees as efficacious employees have internal urge to achieve excellence. They are capable of absorbing more from the work experience, which enhances their vision, knowledge sharing, competence and commitment towards learning. Thus, selfefficacy complements the efforts of HPWS to strengthen the learning quotient as self-efficacious employees are more open to new ideas; they think out of the box and are always ready to learn. Such employees are more responsible for their own job-related learning and have a propensity to demonstrate their ability in overcoming difficult tasks and consistently learn from their mistakes. The third part of the study shows that learning orientation mediates the relationship between HPWS and EP. We examined the relationship between HPWS and learning orientation, which is significant. It has been observed that HPWS through training, competency development, reward and empowerment improves employees’ competencies, skill and knowledge and provides them with opportunities to participate in decision-making process and exert extra efforts. Further, learning orientation has a positive impact on EP, which is consistent with the previous studies75. The reason behind is that learning-oriented employees improve and master their skills and abilities which enhance efficiency and enables them to improve their performance. Moreover, learning-oriented employees are more committed towards learning and capable of generating valuable ideas to enhance productivity. It drives employees to improve their skills, promote their proficiency on the job thereby enhancing their performance standards. Further, result revealed that learning orientation mediates the relationship between HPWS and EP. The rationale behind this indirect effect is that HPWS (AMO-oriented) provides a strong base to improve EP by enhancing their competence,

Metamorphosis 15(2) knowledge, skills and vision. Moreover, HPWS enhances knowledge, skills and abilities of existing and potential employees, which in turn increase their performance level. HPWS nurtures learning orientation to enhance employees’ performance by providing supportive learning environment in which employees experiment with new approaches and strategies to improve their knowledge to perform effectively. Further, it has been shown that ability quotient enhances the vision and mindset of employees that helps employees to learn new ways to make their work processes more efficient. Motivation makes employees committed towards learning and engages them in the discretionary effort required to identify and act upon inefficiencies which in turn raise the performance standards. Finally, opportunity empowers employees to think out of the box and share their views and ideas with their superiors and colleagues which enhance their learning quotient to perform better at workplace. Thus, HPWS through AMO make employees more committed towards learning and enhance knowledge sharing which enable them to find out new ideas, ways of performing their job that leads to better employee performance. Finally, the fourth part of the study discusses the moderated mediation relationship between the equation HPWS and employee performance. On the basis of foregoing discussion and support of the literature, it can be concluded that self-efficacy and learning orientation plays an important role between HPWS and EP relationship by giving employees an opportunity to expand their knowledge, learn and acquire new skills and ideas to enhance their performance. Further, the interaction of HPWS and selfefficacy enhance employee’s tendency to engage in learning activities, so that they can perform better. Thus, HPWS when associated with self-efficacy exhibit AMO for employees enhances their vision, mindset as well as commitment to learning which ultimately leads to better employee performance.

Theoretical Implications The study has several theoretical contributions. The study adds to the existing literature on HPWS by validating the HPWS (the AMO Model) scale in Indian context. This study has empirically proved moderation of self-efficacy between HPWS and learning orientation, which is the maiden contribution as it has not been checked earlier. Further, mediation of learning orientation between HPWS and EP has also been proved. This is a pioneer study regarding moderating role of self-efficacy and mediating role of learning orientation between HPWS and EP. This investigation is important to academicians and researchers. Theoretically, the study helped to identify the black-box using self-efficacy and learning orientation to understand HPWS and EP relationship. Finally, we have also proved that the interaction of HPWS and self-efficacy indirectly

Jyoti and Dev 129 affects EP through learning orientation by conducting multi-group analysis.

Managerial Implications This study has various implications which are important for practitioners as well as academicians. Implementation of HPWS is imperative for the banking sector. They need it to survive the challenges of globalization and economic diversity through the right combination of people, technology and organizational structure that makes full use of the organization’s resources and opportunities. Regarding practical contributions, the findings of this study can be used as a guideline by management to upgrade the effectiveness of HPWS in organizations. HPWS can improve performance by creating a learning culture in which employees constantly learn and share knowledge, so that they continually expand their capacity to achieve the desired results. AMO should be implemented simultaneously to improve employee performance. Management should ensure that employees view training and competency development programmes as opportunity for their career progression and promotion. Management should organize extensive training and re-training programmes regarding new product (e.g., new loans and insurance policies in the banking sector) and process (e.g., new technology and management of workplace, leadership and so on). Communication training should be provided to enhance frontline employee’s ability to address customers’ issue in a better way. Further, employees should be proactively advised to embrace change to sustain the competition. This proactive approach can be generated by providing adequate opportunities as well as motivation by fostering a supportive and favourable climate of learning and working together in the organizations. Management should ensure that employees who solve customers’ problem and exhibit effective recovery efforts should be rewarded and recognized. Moreover, organization can also offer high-performing employees monetary as well as non-monetary benefits to boost their morale which in turn leads to improved performance. Management should empower employees by providing them responsibility and authority to deal with customer requests and problems quickly. Besides this, management should also introduce flexible HR practices like flexi-place, flexi-time and preferable lunch hour for motivating employees. The AMO model suggests that the HR practices used can be balanced according to the business’s needs and employees’ willingness of using a discretionary effort. Therefore, managers need to consider practices that complement each other and work as a system to increase EP. Further, management need to strategically inculcate commitment to learning, shared vision, open-mindedness and intra-organizational knowledge sharing as a part of their business strategy for enhancing learning orientation. Participatory management techniques such as quality circle and autonomous work teams should be introduced in the

banks to encourage employees to identify, analyze, discuss work-related problems and devise solution for improvement. Moreover, management should take steps to enhance the efficacy level of employees by encouraging them to take initiative and organize personality development workshops to boost their confidence. Lastly, management as well as employees need to work professionally as strategic partners, have a visionary orientation, and also behave and act strategically to assist and ensure the effectiveness of HPWS in the organizations.

Limitations and Future Research This study examines the influence of HPWS on EP through self-efficacy and learning orientation in the banking sector. Although, all the precautionary efforts were taken to ensure the objectivity, reliability and validity of the study, yet the study is not absolutely free from the limitations, which should be kept in mind by the future researchers. First, it is a cross-sectional study where all data have been collected at a particular time, which cannot reveal true cause–effect relationship. Longitudinal designs are needed in future research to extend our findings. Second, the data were collected from the service sector only. It should be helpful to replicate these findings in other sectors to enhance its generalizability. References  [1]  Sun LY, Aryee S, Law KS. High performance human resource practices, citizenship behaviour, and organizational performance: A relational perspectives. Acad Manag J. 2007; 50(3): 558–577.   [2] Arefin MS, Arif I, Raquib M. High-performance work systems and proactive behaviour: The mediating role of psychological empowerment. Int J Bus Manag. 2015; 10(3): 132–140.   [3] Jensen JM, Patel PC, Messersmith JG. High-performance work systems and job control: Consequences for anxiety, role overload, and turnover intentions. J Manag. 2013; 39(6): 1699–1724.   [4] Beltran-Martin I, Roca-Puig V, Escrig-Tena A, Bou-Llusar J. Human resource flexibility as a mediating variable between high performance work systems and performance. J Manag. 2008; 34(5): 1009–1044.   [5] Posthuma RA, Campion MC, Masimova M, Campion MA. A high performance work practices taxonomy: Integrating the literature and directing future research. J Manag. 2013; 20(10): 1–37.   [6] Chan SCH, Mak WM. High performance human resource practices and organizational performance: The mediating role of occupational safety and health. J Chi Hum Resou Manag. 2012; 3(2): 136–150.  [7]  Khasawneh S, Alzawahreh A. High-performance work practices, innovation and perceived organizational performance: Evidence from the Jordanian service sector. Afri J Bus Manag. 2012; 6(9): 3320–3326.

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