CC BY
22
Organizational Psychology, 2023, Vol. 13, No. 2, P. 78-99. DOI: 10.17323/2312-5942-2023-13-2-78-99
ORGANIZATIONAL PSYCHOLOGY
www.orgpsyjournal.hse.ru
Linking aspects of human capital management, employee engagement, perceived organizational support, and self-reported employee job performance
Abel DESTA
ORCID: 0000-0002-4259-0809
Worku TADESSE Wubshet MULUSEW
Addis Ababa University, Addis Ababa, Ethiopia
Abstract. Purpose. The primary intangible asset of firms and the main factor determining their competitive advantage has emerged as human capital. This paper examined the effect of the selected aspects of human capital management on self-reported employee job performance and the mediating role of employee engagement. Likewise, this study tested the moderation role of perceived organizational support on the human capital management with self-reported employee performance link. Method. This paper is structured on a quantitative approach, with stratified and simple random sampling techniques. The research model analysis method applies structural equation modeling with AMOS to test the hypothesized relationships. Findings. The aspects of human capital management were positively related to self-reported employee job performance. Moreover, employee engagement partially mediates the relationship, and perceived organizational support positively moderates the association between knowledge accessibility, learning capacity, leadership practice, career advancement, and self-reported employee job performance. Conversely, it has an insignificant moderation between workforce optimization and employee job performance, optimization and self-reported employee job performance. Implications for practice. This paper has an implication for policymakers, organizational managers, investors in general, and the banking sector in particular in their effort towards creating strategies for matching human capital management strategies, employee engagement, perceived organizational support, and self-reported employee job performance. Thus, aspects of human capital management are the determinant factors of employee engagement and self-reported employee job performance. Moreover, the perception of employees towards organizational support contributes to the relationship.
Keywords: human capital management, employee engagement, perceived organizational support, employee job performance.
In this challenging knowledge-based economy, human capital has emerged as the major intangible asset of organizations and the basic determinant of their competitive advantage (Wright, 2011). Managing the company's human capital (HC) is increasingly important to its success as the business environment grows more competitive (Unger et al., 2011). Managing HC through acquiring
Introduction
Address: PO Box 1176, Addis Ababa, Ethiopia.
E-mail: abelgebremedhn30@gmail.com
and retaining the best employees is only half the battle (Hatch, Dyer, 2004). The acquisition and alteration of new knowledge in organizations is an inherently human process (Khan, Chaudhry, 2019), making it imperative to understand the contribution that human capital management (HCM) practices make to the aspect of employee job performance.
There is a lack of evidence in analyzing the relationship between human capital management and its outcome factors, despite the prominent literature centering on human resource management and outcome variables in the management discourse. Additionally, among the research that looked at this connection (e.g., Crook et al., 2011; Kuchar et al., 2015; Delery, Roumpi, 2017; Minbaeva, Shell, 2018), none considered the outcome variables of self-reported employee job performance (EMJP) and the effect of the intervening effect of employee engagement and the moderating role of perceived organizational support (POS). Although these studies are important first steps, there is a general dearth of research, especially in developing countries, including Ethiopia, on the interaction of the aspects of human capital management, employee engagement (EYE), POS, and self-reported EMJP. Furthermore, while researchers have concentrated on the direct effect of HC or HCM on performance (Abualoush et al., 2018, Cania et a., 2016, Nderitu, et al., 2019), the interaction of human capital management practices on self-reported EMJP, POS, and employee engagement constructs has been overlooked. M. Namazi and N. Namazi argued the nature of multifarious business organizational problems (Namazi, Namazi, 2016). Without specifying these intervening variables, business frameworks are not complete and thus are not able to solve real business difficulties. This research is an effort toward providing insight into the study of HC and HCM on job employee performance, EYE, and POS in the Ethiopian banking sector.
With this precept in mind, this study was designed to examine the effect of selected aspects of HCM on self-reported EMJP, the mediating role of employee engagement, and the moderation effect of POS. HCM is mainly a planned and strategic approach to managing the most vital of the organization's employees (Kuchar et al., 2015; Hatch, Dyer, 2004). It deals with obtaining, developing, and retaining employees in a strategic people management approach (Wright et al., 2014). It is argued that when an organization develops a better.
The better they can implement HCM in a way that aligns with their larger system, the better they will be able to harness engagement and performance for competitive advantage (Khan, Chaudhry, 2019; Jacobson, Sowa, 2015). Therefore, managers need to devise strategies as well as make better investments in the aspects of human capital management, POS, and engagement to enhance employee performance. Despite the strategic value of the HCM components and related outcome factors, few academic studies have attempted to take these streams into account (Boon et al., 2018; Wright et al., 2014). The lack of a well-defined HCM framework and issues with aligning desired HCM with business strategy and performance, particularly in the Ethiopian context (Boon et al., 2018; Schleicher et al., 2017), is what calls for further research. This is true of Ethiopia's banking sector, which is losing inept HCMP and less committed staff and is consequently ill-equipped to compete in the globalized world.
Moreover, to increase and maintain business profitability, leaders of business organizations need to work hard to have engaged employees and create better employee perceptions of organizational support (Eder, Eisenberger, 2008). Employee engagement (EYE) is a typical construct in work relations and it has received great attention among the academic community and business consultants in recent years (Bhatnagar, Biswas, 2013). Similarly, for the benefit of employees and organizations alike, organizations must recognize employees as valuable sources of human capital, which is the main theme of POS (Kurtessis et al., 2017). R. Eisenberger with colleagues (2002) defined POS as the degree to which employees consider that their organization values their contributions, cares about their well-being, and fulfills their socio-emotional needs. This article proposes that EYE
plays a positive mediating and POS has a moderating role in the relationship between the selected aspects of HCM and self-reported EMJP. HCM practices are important preconditions for employee engagement, which is defined as workers who take pride in their work, feel that their efforts count, and strive to improve their performance (Gruman, Saks, 2011).
The following are our work's main contributions: the study emphasizes the significance of emphasizing an organization's intangible assets in the first place (i.e., human capital). Besides, by incorporating significant elements that were previously unconnected, this study adds to the development of a new theoretical framework for the interaction between elements of HCM, employee engagement, POS, and self-reported EMJP. Further, the findings of this paper contribute to increasing the concern of administrators and business unit managers about the importance of a proper HCM so that the organization can have better EMJP and the role of EYE and POS to create value for the company.
Literature review and hypothesis development
Human capital is an important term in many academic disciplines, from basic macroeconomics, where it was first conceived (Becker, 1964), to micro-level psychology, where researchers have concentrated on individual differences in knowledge, skills, abilities, and other talents. The literature on strategy and HRM acknowledges the significance of human capital management for boosting corporate success. HCM is the planned and strategic approach to managing the most vital aspects of the organization It is a way of evaluating people as assets whose current value can be evaluated and whose future value can be enhanced through investment (Wright et al., 2014). This study focuses on aspects of HCM like knowledge accessibility, learning capacity, workforce optimization, leadership practice, and career advancement, a model tested by some scholars (e.g., Bassi, Mcmurrer, 2008; Kuchar et al., 2015; Tuzin, Ozge, 2013), to identify the practice of HCM for high employee engagement and self-reported EMJP as well as the contributing factor of POS.
Employees' perceptions of how much their employer values and cares about their contributions are known as POS. It has been defined as "the extent to which employees perceive that their contributions are valued by their organization and that the firm cares about their well-being" (Eisenberger et al., 1986, p. 501). POS can be defined as the degree to which employees consider that their organization values their contributions, cares about their well-being, and fulfills their socio-emotional needs (Eder, Eisenberger, 2008). It has been discovered that POS has a significant impact on employee performance and well-being. K. Y. Kim with colleagues suggest that POS would be influenced by praise and approval, rank, job enrichment pay, and organizational policies (Kim et al., 2016). Better POS not only satisfies the aforementioned needs of employees but also communicates to staff that the company is prepared to assist with work-related issues as they arise and to reward improved performance (Chen et al., 2009).
Moreover, business organizations need to make sure that their workers are focused and give their tasks their all to sustain high levels of productivity and functional effectiveness. To determine the level of an employee's psychological presence, the concept of employee work engagement has paramount importance (Christian, 2011). The simultaneous employment and expression of a person's 'preferred self' in task behaviors that enhance connections to work and people, personal presence, and active, full performances" is what is meant by "work engagement (Schaufeli et al., 2006). Numerous studies have pointed out that EYE has three dimensions: vigor, dedication, and absorption (Christian, 2011; Mishra et al., 2014; Schaufeli et al., 2006). Therefore, in this paper employee engagement is treated as an antecedent of self-reported EMJP.
Employee performance is typically looked at in terms of outcomes. Employee performance of job describes the overall financial or non-financial outcome of the employee that is directly
related to the effectiveness and success of the firm (Armstrong, 2010). In an organizational context, performance is typically defined as the degree to which an organizational member (employee) contributes to achieving the goals of the organization (Chang, Chen, 2011). Researchers point out that employee performance has three dimensions: task performance, contextual performance, and adaptive performance (e.g., Koopmans, 2014; Pradhan, Jena, 2017; Ramdani, 2019).
This research proposes that the use of aspects of HCM could improve the organization's human capital pool, which in turn leads to better engagement and performance. Likewise, SET is among the most influential theoretical paradigms for the conceptualization of workplace behavior (Cropanzano et al., 2017). It is stated that the SET is invoked wherein the employees, for tangible benefits of the organization, view employment as a trade-off between effort and faithfulness. Likewise, this paper adapted Resource-Based View Theory (RBVT) and social exchange theories (SET). RBVT has become the predominant theoretical underpinning used by scholars studying knowledge-based views of the firm (Bhatnagar, Biswas, 2013; Wilson, Tizikara, 2017). The crucial tenets of RBVT as advocated by researchers are resources that are unique, vital, rare, and non-substitutable leading to competitive advantage (Crook et al., 2011; Wright et al., 2014).
Linking the aspects of HCM and self-reported employee job performance
In this study, we made the argument that factors of human capital management (HCM), such as knowledge accessibility, learning capacity, workforce optimization, leadership practices, and career development, improve self-reported EMJP. Prior empirical and theoretical studies have related aspects of HCM to diverse kinds of organizational positive work outcomes. In this regard, it is found that leveraging the human capital of the organization has a positive impact on performance (Jamal, Saif, 2011). A one study showed that HCM practices, for instance, leadership practice, knowledge accessibility, and learning capability, have a positive effect on employee positive behavioral outcomes (Vij, Sharma, 2014). Accessibility to knowledge is correlated to the new firm's performance and sustainability (Tüzin, Ozge, 2013). A one more study by also found that both knowledge management practices and dynamic capabilities have a positive, significant impact on employee performance in the banking sector (Kashif, 2018). Banking managers need to manage knowledge properly and systematically to make the company more knowledge-based, which leads to improved performance. It is found that better worker learning results in them contributing original and creative ideas due to their knowledge, which boosts staff productivity (Luthans, Youssef, 2004). Moreover, general mental ability was a better predictor of performance, while conscientiousness was an improved predictor of performance for experienced workers (Sturman, Tews, 2007). Employee performance is positively impacted by improved leadership techniques, which is one of HCM's key drivers (Buil et al., 2019).
Career development prospects of HCM are positively linked to employee well-being and negatively related to employee deviant behavior (Hamid et al., 2017). Career advancement as part of HCM practice within the organization is one of the significant motivational tools to absorb employees in positive job-related activities (Briggs et al., 2011). In contrast, some argue that the relationship between HCM and employee performance is influenced by context and that HCM practices (e.g., leadership practices such as communication, inclusiveness, influence, workforce optimization, and learning capacity) do not always result in better employee performance that benefits the organization (Parker, Griffin, 2011). Human capital competence was not found to have a statistically significant association with positive behavioral and work-related outcomes (Maditinos et al., 2011). Based on empirical data and the supporting ideas, the following hypotheses are put forth:
H1a. Knowledge accessibility is positively related to self-reported employee job performance.
H1b. learning capacity is positively related to self-reported employee job performance.
H1c. workforce optimization is positively related to self-reported employee job performance.
H1d. leadership practice is positively related to self-reported employee job performance.
H1e. career advancement is positively related to self-reported employee job performance.
The mediating role of employee engagement
Work engagement mediates the positive association between leadership, helping behavior, and employee job performance(Lai et al., 2020). Employee engagement mediated the association between high-performance work practices and employee performance (Song et al., 2014). One research was conducted to examine the mediating role of employee engagement in human capital management, such as employee training, accessibility of knowledge, leadership practices, learning capacity, and performance (Witasari, Gustomo, 2020). The findings revealed that employee engagement positively mediates the relationship between HCM practices and performance. Moreover, employee engagement positively mediates the association among the practices of HCM, such as employee learning practices, employee career growth, and competitive advantage (Kerdpitak, Jermsittiparsert, 2020). These findings advise managers to improve HC's best practices to include workers in their work, increase productivity, and gain a competitive edge. Employee engagement has been found to act as a mediator between performance, learning and development, and the organizational working environment (Chaudhry et al., 2017). Employee work engagement mediated the relationship between HR and job performance.
EYE mediates the relationship between HRM practices and both employee satisfaction and performance outcomes to some extent (Sattar et al., 2015). Similar to how EYE mediates how human capital influences employee performance, it has a big and favorable impact on employee performance (Ngwenya, Pelser, 2018). According to a study by Jiang et al. (2012), employee inspiration and involvement functions are linked to career development, ongoing feedback, and job stability, all of which have an impact on workers' performance.
Employees' work engagement mediates the positive relationship between leadership practice, helping behavior, and employee job performance (Lai et al., 2020). Furthermore, followers' work engagement mediates the main effect of leadership and the collaborating effect of leadership on followers' task performance and organizational citizenship behavior (Wei et al., 2018). Thus, leaders are more likely to engage followers in being dedicated to these goals, enthusiastic about making individual sacrifices for the interest of collective goals, and eventually executing their performance beyond the call of duty.
Although the majority of studies focus on the effects of some HR practices on EYE and its mediating role (Gruman, Saks, 2011), scholars call for future researchers to include employee engagement as a mediator variable between HCM and performance relationships in a business organizational context (Truss et al., 2013; Shantz, Alfes, 2014). The following hypotheses are proposed based on the foregoing discussions and the indicated supporting theories:
H2a. Employee engagement significantly mediates the relationship between knowledge accessibility and self-reported employee job performance.
H2b. Employee engagement significantly mediates the relationship between learning capacity and self-reported employee job performance.
H2c Employee engagement significantly mediates the relationship between workforce optimization and self-reported employee job performance.
H2d. Employee engagement significantly mediates the relationship between leadership practice and self-reported employee job performance.
H2e. Employee engagement significantly mediates the relationship between career advancement and self-reported employee job performance.
Perceived organizational support as a moderating role
Perceived organizational support moderates the relationship between the link between HR, emotional labor, and job performance (Kim et al., 2017). When employees believe that their company values and cares about their well-being, they give back by helping the firm succeed. POS can be used to assess a company's benevolent intentions (Kim et al., 2016). This paper sought to assess the moderating role of POS, which is argued to positively change the strength of an effect of aspects of HCM on self-reported EMJP. SET and the reciprocity norm are the sources of POS (Chen et al., 2009). Employees who willingly perform duties in anticipation of earning some sort of perceived reward, typically a reward, are engaging in social exchange. According to the SET and the rule of reciprocity, individual employees who perceive receiving organizational aid put in a greater effort because of their enhanced loyalty to the company (DeConinck, Johnson, 2009).
According to previous research findings, POS has been revealed to play a significant role in moderating organizational relationships among job design, career development, and performance relationships (Cheng, Yang, 2018); it boosts an employee's ability to handle the responsibilities of their job (Kurtessis et al., 2017). Z. Chen with colleagues claimed that better support of an organization involves helping workers not only socio-emotionally but also by offering technology, equipment, thoughts, and other provisions (Chen et al. (2009). Moreover, high POS promotes collaboration, productivity, and communication among coworkers, typically assuming the kind of cooperation (Erdogan, Bauer, 2009). Consequently, colleagues engage in mutually beneficial actions.
Figure 1. Hypothetical relationship research framework
POS moderates the connection between management of the work-family interface and job performance (Witt, Carlson, 2006), and high POS levels result in sentiments of trust, organizational affiliation, and long-term commitment. POS takes into account employees' dedication to helping the company achieve its goals as well as their expectation of rewards for better performance (Eder, Eisenberger, 2008; Gavino et al., 2006). Key effects of POS include lower withdrawal behavior and higher productivity (Eisenberger et al., 2002). Furthermore, researchers found that POS is related to citizenship behaviors in an organization, organizational commitment, job performance, extra-role performance, and the nurturing of enthusiastic and productive employees (Chen et al., 2009; Caesens, Stinglhamber, 2014; Gottman et al., 2016; Noruzy et al., 2011).
As per the pieces of literature discussed above, and using the lens of the underpinning theories, the following hypothesis is predicted:
H3. POS positively moderates the association between the aspects of human capital management and self-reported employee job performance.
Research method
Sample and procedure
This paper used a quantitative research approach and was designed to provide empirical evidence about the effect of aspects of human capital management on self-reported EMJP through or mediated by employee engagement and the moderation role of perceived organizational support in the Ethiopian banking sector. By the end of the 2020/21 fiscal year, Ethiopia will have 18 private and public banks. However, the accessible population for this study was managerial and non-managerial employees of 12 banks operating in Addis Ababa, Ethiopia. Stratified and simple random sampling methods have been applied. The stratified probability sampling method is supposed to be proper because it excludes bias in selecting participants for the study (Creswell, 2018). During the distribution of questionnaires, respondents were informed about the agreement, confidentiality, anonymity, and the right to withdraw from participation (Quick, Hall, 2015).
This study employed a survey method, so out of the 601 paper questionnaire surveys distributed, 461 were returned, with a response rate of 78.3%. After removing missing values and outlier cases, 426 responses remained for data analysis purposes, with a response rate of 70.89%, which can be considered a very good rate of response (Corbetta, 2013). In doing so, IBM SPSS version 25 was used to conduct Mahalanobis Distance to find multivariate outliers, which is a measure to evaluate the position of each observation compared with the center of all observations in a set of the specified variable (Cleff, 2019). A large Mahalanobis distance value indicates the case as having extreme values for one or more variables. It is advised that a very statistical test of significance at 0.001 is the threshold rule (Morgan, Rubin, 2017).
Measures
Questions from existing measuring instruments that had proven reliable and valid in previous research studies were adopted and adapted. The survey questionnaire comprises demographic information, HCM practice, EYE, EMJP, and POS. A total of 83 questionnaire items were adapted in this study and used in the English language version. To measure knowledge accessibility as HCM practice, eight-item scale items were adapted from L. J. Bassi and D. P. Mcmurrer (2008). Nine items for learning capacity, eight items for workforce optimization, and twelve items for leadership practice have been used to measure the variables, which were adapted from L. J. Bassi and D. P. Mcmurrer (2008). While five items measuring the level of career advancement were adapted from Y. Gong and S. Chang (2008) and J. E. Marineau (2017). Moreover, employee engagement was assessed with nine-item scales adapted from W. Schaufeli et al. (2006), and POS was measured using eight high-loading items (Eisenberger et al., 2002; Eder, Eisenberger, 2008). Finally, to test self-reported EMJP twenty-four (24) items were adapted from Koopmans (2014) and Pradhan and Jena (2017). A 6-point Likert scale was used to measure all the items, where "1" showed strongly disagree and "6" specified strongly agree.
Data analysis and result
This paper focuses on the effects of human capital management on self-reported EMJP. Besides, it tests the mediating role of EYE and the moderating influence of POS. Data was analyzed employing structural equation modeling (SEM) and Amos to test the hypotheses. Both the procedural and statistical corrections suggested by S. B. Mackenzie and P. M. Podsakoff (2012) were used to test the common method bias (CMB). Techniques like temporal separation, a time lag, and random ordering
of corresponding scales were applied via procedural treatments. As a result, questions on the predictor and moderator factors were addressed first, and then the criteria and mediating variable questions were addressed two weeks later. Furthermore, as a statistical cure for CMB S. B. Mackenzie and P. M. Podsakoff suggested Harman's single-factor test.
Principal component factor analysis with an un-rotated solution has been used with Harman's single-factor test. The factor of multiple eigenvalues explains 24.72 percent of the variance. A single factor extracted 24.762% of the total variance. Thus, it is far less than 50% (Podsakoff et al., 2003), so it is determined the common method of variance is unlikely to be a serious problem. Moreover, non-response bias was examined by comparing the Likert scale data collected in the first wave to that received in the second wave, as recommended by S. G. Rogelberg and J. M. Stanton (2007). Individuals who completed the survey between the first and second contact were compared to those who completed the survey between the second contact and the end of the study. Two-way t-tests were used to compare the mean value of each construct between the two groups. The results showed no significant differences in means, indicating that non-response bias did not appear to be a problem.
Correlation analysis
A statistical technique used in research to determine the association between two variables and determine the strength of their linear relationship is correlation analysis. in other words, the magnitude of change in one variable as a result of the change in the other is determined using correlation analysis. The findings show that study variables correlate with each other sufficiently and they can be reviewed adequately. Further, multicollinearity does not exist in the study variables because correlation levels are less than 0.7 (Hair et al., 2010).
Table 1. Means, standard deviations, correlations, and reliabilities
Variable KA LC WO LP CA EYE POS EMJP Mean Std. dev. Reliability
KA 1 3.92 1.113 .810
LC .456** 1 3.42 1.080 .812
WO .586** .489** 1 4.25 1.230 .921
LP .667** .503** .661** 1 3.83 1.168 .728
CA .421** .476** .592** .539** 1 3.32 1.101 .825
EYE .662** .701** .232** .426** .228** 1 4.33 .996 .821
POS .231** .361** .331** .126** .440** .207** 1 3.86 1.118 .801
EMJP .407** .296** .551** .584** .392** .332 .499** 1 4.62 .945 .791
Note: N = 426; KA = Knowledge Accessibility; LC = Learning Capacity; WO = Workforce Optimization; LP = Leadership Practice; CA = Career Advancement; POS = Perceived Organizational Support; EYE = employee engagement; EMJP = Employee Job Performance; ** — p < .05. Scale reliabilities (coefficient alpha) are ** — p < .05. Scale reliabilities (coefficient alpha) are on the main diagonal.
Control variables
To examine the stated model while accounting for the impact of demographic data, a control variable was used (Collier, 2020). The outcome is resented in table 2 following the inclusion of the demographic variables as control variables in the structural model using AMOS, the results are found and stated in table 4.
Table 2. Results of control variables
Variable Demographic characteristics Estimate Stand. err. C.R. p-value Label
EMJP Gender 1304 .1429 .9128 .3614
EMJP Age -.0248 .0546 -.4548 .6493
EMJP <--- Education .0855 .1123 .7612 .4465
EMJP <--- Experience -.0111 .0453 -.2459 .8058
EMJP <--- Gender -.0659 .1209 -.5454 .5855
EMJP <--- Age .0000 .0462 .0004 .9997
EMJP <--- Education .0279 .0951 .2930 .7696
EMJP <--- Experience -.0139 .0383 -.3640 .7159
Note: EMJP = employee job performance.
As we can see in table 2 the p-value of the demographic characteristics (i.e. gender, age, education, and experience) are above 0.05 and they found to be are non-significant (Kline, 2011). This demonstrates that these variables do not obscure the relationship that the whole structural model specifies. As a result, these factors are not included in the study that follows.
Data exploration using exploratory factor analysis (EFA) provides insight into the optimal number of components to represent the data (Hair et al., 2010). EFA was conducted for all of the observed variables using Principal Components Analysis as the extraction method and the Promax rotation method. Because the oblique method allowed factors to correlate and was more persuasive than the orthogonal solution, the Promax rotation method was chosen (Conway, Huffcutt, 2003). Moreover, oblique rotation methods often give more accurate results in research. Factor loadings of. 50 or above were considered significant (Hair et al., 2010). Accordingly, a total of thirty-two items were deleted, either because of low loading or unfavorable cross-loading on their intended construct and the other constructs, and fifty-one remained for factor analysis. The principal component analysis (PCA) extraction approach and Promax rotation were used. The Kaiser — Meyer — Olkin (KMO) measure of sample adequacy and Bartlett's Test of Sphericity were used prior to extracting the variables. The result of the KMO index was .92, and Bartlett's test was significant at the .05 level, indicating that the data can be used for factor analysis (Williams et al., 2010).
33
(gV-»»fHCMka_q1
(Sy-^-fHCMka_q3 (e9)-*-|TcMLcj? (eS)-*-[HCMLc
I EYE_q2 I | EYE_q3 | | EYE_q4 | [~EYE_q5 |
EYE q7
HCMLp_2l »| HCMLp_31 ^-»•j HCIvlLp.
EYE_q8
EMPtp ^
EM Pap_qiÖ|^—^ EMPapqiä}-^—fi^
EMPcp_q24j^ @
| POS_q1 | | POS_q5 | I POS_q6 I
Last Overall Measurnment Model
Figure 2. Test of the last measurement model
Confirmatory factor analysis (CFA) was performed for each construct, and then an overall CFA was assessed by examining standardized factor loadings and modification indices. In doing so, the standard loading of less than 0.5 has been excluded, and an overall of 29 items has been retained.
Table 3. Model fit indices
Measure Estimate Threshold Interpretation
CMIN / df 2.680 > 3 Excellent
Goodness-of-Fit Index (GFI) .911 > .90 Acceptable
Comparative fit index (CFI), .929 > .90 Acceptable
Tucker — Lewis index (TLI) .924 > .90 Acceptable
RMSEA .062 < .07 Excellent
As we can see in table 3, the measurement model above the universal cutoff looks to represent the data quite well.
Table 4. Convergent validity
Construct Items Sta. load. Square of SL The Sum STL No. Ind. AVE The squ. AVE
Aspects of HCM HCMk_q3 .9585 .9187
HCMk_q2 .9620 .9254
HCMk_q1 .8167 .6670 2.5111 3 .8370 .915
HCML_q16 . 7456 .5559
HCML_q10 .7882 .6213
HCML_q9 .7857 .6173 1.7945 3 .5982 .860
HCMw_q26 .7112 .5058
HCMw_q19 .6526 .4259
HCMw_q27 .8748 .7653 1.697 3 .5657 .752
HCML_33 .7531 .56716
HCML_31 .7081 .501406
HCML_28 .8307 .690062 1.75863 3 .5862 .765
HCMc_q41 .8277 .6851
HCMc_q40 .7551 1.2553 2 .6277 .792
EYE EYE_q2 .9045 .8181
EYE_q3 .9335 .8714
EYE_q4 .8293 .6877
EYE_q5 .8514 .7249
EYE_q7 .8077 .6524
EYE_q8 .7723 .5964 4.3509 6 .7252 .852
POS POS_q5 .8934 .7982
POS_q1 .8940 .7992
POS_q6 .6892 .4750 2.0724 3 .6908 .831
EMJP EMPtp_q2 .8413 .7078
EMPtp_q3 .9074 .8234
EMPap_q10 .9347 .8737
EMPap_q13 .9425 .8883
EMPcp_q15 .8635 .7456
EMPcp_q24 .7051 .5001 4.5389 6 .7565 .869
Note: HCM = human capital management; POS = perceived organizational support; EYE = employee engagement; EMJP = employee job performance.
After attaining a good match between the measurement model and the data, the validity and reliability of the measures are evaluated. By measuring the degree of factor loadings of observed variables on the suggested latent constructs, convergent validity was examined. In convergent validity, the average variance extracted (AVE) was used and evaluated with a threshold of above 0.5 (Kline, 2011). Table 4 showed that the AVE was greater than 0.5 and that all the factor loadings were higher than 0.5. (Hair et al., 2010). The degree of factor loadings of observed variables on the suggested latent variables or constructs was used to examine convergent validity. The average variance extracted (AVE) needs to be above and beyond 0.5 for convergent validity (Hair et al., 2010).
The square root of each variable's average variance should be larger than the correlations between latent constructs, indicating sufficient discriminant validity (Byrne, 2010). The square root of AVE is depicted in table 4. It is checked that values are larger than correlations between latent constructs, confirming the discriminant validity of the model (Kline, 2011).
Hypothesis testing
The first hypothesis postulates that the perceived system of knowledge accessibility procedures has a favorable direct impact on self-reported EMJP. The structural model demonstrates a strong relationship between information accessibility and worker performance (standardized path coefficient = .1377, t = 5.3715, p = .001). This H1a was therefore supported. Hypothesis 2 suggests a positive direct effect of learning capacity on employee performance. The results confirmed that learning capacity has a marginally significant positive effect on self-reported EMJP (standardized path coefficient = .1124, t = 3.0820, p = .059). J. E. Collier (2020) suggested that if a p-value is a little larger than 0.05, it is possible to report the result as "marginally significant", signifying that there could still be some kind of real effect going on. This leads to the acceptance of Hypothesis H1b as almost significant. As per the findings, learning capacity has a negligibly favorable impact on an employee's ability to perform their work (standardized path coefficient = .1124, t = 3.0820, p = .059). According to J. E. Collier (2020), results may be reported as "marginally significant," indicating that there may still be a true impact present if the p-value is a little bit higher than 0.05. As a result, hypothesis H1b is accepted as being almost significant.
The practice of workforce optimization is hypothesized to have a favorable impact on self-reported EMJP in Hypothesis 1c. The findings supported the hypothesis by showing that workforce optimization significantly improves self-reported EMJP (standardized path coefficient =.1736; t = 3.0820; p = .0014). The positive direct impact of perceived system leadership practices on self-reported EMJP was proposed by Hypothesis 1d, and the positive impact of employee career advancement on self-reported EMJP was projected by Hypothesis 5. The model provided support for Hypotheses 1d by demonstrating that the degree of leadership practices has a significant positive effect on self-reported EMJP (standardized path coefficient = .0907; t = 9.2237, p = .001) and that career advancement has a significant positive effect on employee performance (standardized path coefficient = .0849; t = 11.4237, p = .001). Table 5 below summarizes the findings from this section and shows that, as expected, all five suggested hypotheses are supported.
Table 5. Summary of direct effect hypotheses
Depend variable Independ variables Stand. estimate f-value p Decision
Self-reported EMJP <-- Knowledge accessibility .1377 10.4517 *** Accepted
Self-reported EMJP <-- Learning capacity .1124 3.0820 .061 Accepted
Self-reported EMJP <-- Workforce optimization .1736 3.0820 .0014 Accepted
Self-reported EMJP <-- Leadership practice .0907 9.2237 *** Accepted
Self-reported EMJP <-- Career advancement .0849 11.4237 *** Accepted
Note: EMJP — employee job performance; **** — p < .000.
The mediation effects were analyzed by using an AMOS bootstrapping iteration (n = 5000), as suggested by K. J. Preacher and A. F. Hayes (2008). According to J. E. Collier (2020), a bootstrap technique treats the data sample as if it were a pseudo-population, then takes a random sample with replacement to see if your indirect effect is within a confidence interval. As suggested by K. J. Preacher and A. F. Hayes (2008), the AMOS bootstrapping iteration (n = 5000) was used to investigate the mediation effects. To determine whether your indirect impact is inside a confidence interval, the bootstrap technique treats the data sample as though it were a pseudo-population and then takes a random sample with replacement (Collier, 2020).
This study examined how employee involvement affected the relationship between information accessibility and worker productivity. The lower bound confidence interval obtained using the bootstrap is .0243, while the upper bound is .0692, according to the results of the bias-corrected percentile technique. J. E. Collier (2020) asserts that the indirect effect is considerable if the range of the upper and lower bound estimations does not exceed zero (p. 176). Consequently, it has a significant indirect impact. Additionally, according to the results, there was a positive and significant indirect effect of information accessibility on employee job performance, supporting hypothesis H2a, and there was a significant direct effect of knowledge accessibility on employee engagement in the presence of the mediator.
Hypothesis H2b proposes the mediating role of employee engagement in the relationship between learning capacity and employee job performance. The results from the bias-corrected percentile method show that the lower bound confidence interval via the bootstrap is .0233 and the upper bound is .1039, since the range for the upper and lower bound estimates does not cross over zero, then the indirect effect is considered significant (Collier, 2020). Moreover, the results revealed a positive and significant indirect effect of learning capacity on employee job performance (^ = .045, t = 363, p = .027). Hence, Hypothesis 7 is supported and concludes that employee engagement is positively mediated by the relationship between learning capacity and employee performance.
As per the above methods and procedures, the hypotheses on the mediating role of employee engagement in the relationship between the dependent variables (workforce optimization, leadership practice, and career advancement) and employee job performance were found to be supported. Table 6 below provides the summary of the mediation analysis.
Table 6. Summary of hypotheses on the mediation effects
Relationship Direct effect Indirect effect Confidence interval Lower bound Upper bound p-value Conclusion
Knowledge accessibility — Employee engagement — Employee performance .1004 (5.372) .0442 .0243 .0692 < .001 *** Partial Mediation
Learning capacity — Employee engagement — Employee performance .1019 (5.363) .0451 .0233 .1039 Partial Mediation
Workforce optimization — Employee engagement — Employee performance .1526 (3.4385) .0681 .1431 .1992 < .001 *** Partial Mediation
Leadership practice — Employee engagement — Employee performance .0919 (5.269) .0406 .0232 .3711 < .001 *** Partial Mediation
Career advancement — Employee .1029 .0432 .0749 .1872 < .001 Partial
engagement — Employee performance (5.371) *** Mediation
Note: Unstandardized coefficients reported. Values in parentheses are t-values. Bootstrap sample = 5,000 with replacement.
In testing for moderation using interaction, the followed following procedures as recommended by J. E. Collier (2020) and J. F. Dawson (2014) have been followed. First, to assess this interaction, it needs to form a product term independent and moderator variable. Thus, mean-centering the variables in the data is one of the most vital techniques to circumnavigate this problem (Dawson, 2014). Once the new centered variable is created, it needs to produce a product term (i.e., multiply the two centered variables). Moreover, we build an SEM Model, including the path from the moderator and interaction variable to the dependent variable. Therefore, the paths contain independent variables, moderator variables, and mean-centered interactions.
Concerning moderation testing, this paper examined the moderating role of perceived organizational support (POS) on the relationship between the aspects of human capital management (summation effect) and employee job performance (EMJP). The results revealed that positive and significant moderating effect of POS on the relationship between HCM practices and EMJP (^ = .0901, t = 2.8450, p = 0.0044), to lend support for Hypothesis 2. The moderation analysis summary is
presented in table 6. Results of the slope analysis showed to better understand the nature of the moderating effects is shown in figure 4. As can be seen in the figure the line is much steeper for high POS, this shows that at the high level of POS, the impact of HCMP on EMP is much stronger in comparison to low POS. As the level of POS increased, the strength of the relationship between HCMP and EMP increased. POS strengthens the positive relationship between HCMPs and EMP.
Table7. Moderation analysis summary
Relationship ß St. er. C.R. P Label
Ave_ _EMP Hcmps_aver .3707 .0483 7.6812 ***
Ave_ _EMP Pos_aver .1731 .0327 5.2989 ***
Ave_ _EMP <--- Int_HCMPXPOS .0901 .0317 2.8450 .0044
Note: Aver EMP — summed and an average of aspects ofhuman capital management; Pos_aver — a summed average ofperceived organizational support; and Int — the interaction effect of both HCM and POS.
Hcmps_aver
Pos_aver 23
Figure 3. Interaction effect model
5 4.5 4 3.5
Q. 3
£ 2.5
m 2
1.5
1
y = 0.9216x + 1.790;
Moderator
LoOTTÜS-
High POS -Linear (Low POS)
Low HCMPs
High HCMPs
Figure 3. Moderating effect of POS on the relationship between aspects of HCM and EMP
Discussion
The results demonstrate a positive association between employee work performance and knowledge of accessibility practices, indicating that where knowledge of accessibility practices is strong, performance is more likely to be improved. It follows that it is obvious that an organization's ability to make information more transparent, "collaborative," and capable of making knowledge and ideas widely available to employees will likely improve those employees' performance. This result supports the findings of previous empirical studies, which discovered knowledge accessibility to be a critical predictor of job performance (Tuzin, Ozge, 2013). Besides, the results of this study are consistent with those of earlier studies, which demonstrate that employees' capacity for learning and
innovation (learning capacity) and their ability to adapt to new ideas have a direct positive impact on how well they perform on the job (Salau et al., 2016; Wright et al., 2014). This demonstrates how making investments in the training and development of human capital has a favorable impact on both employee and organizational performance.
The study's findings revealed a significant link between self-reported EMJP and workforce optimization in a sample of Ethiopian bank employees. This shows that employee performance improves as banking institutions try to optimize their personnel by building crucial work processes, establishing responsibility, offering suitable working circumstances, and making smart recruiting decisions. This conclusion is consistent with that of J. E. Delery and D. Roumpi (2017), who discovered that maximizing talent (knowledge, skills, competencies, abilities, and so forth) and directing and managing its application on the job are key factors in a company's ability to maximize employee performance. According to social exchange theory, those who get favorable treatment from others are expected to return the favor.
Consistent with previous pieces of literature (Vij, Sharma, 2014; Wright et al., 2014; Walumbwa et al., 2011), it is found that managers' and leaders' communication, inclusivity, performance feedback, supervisory abilities, presentation of core organizational principles, and capacity to build confidence (leadership practice) have a positive significant effect on self-reported. Leaders do not create performance; rather, they facilitate it by influencing others positively (Armstrong, 2010). Perception of career advancement opportunities was found to have a significant positive effect on employee performance. This finding suggests that organizations that provide employees with opportunities to extend their potential and build up their capabilities, which help meet employees' needs for personal advancement, are likely to be regarded as the best and lead to better self-reported EMJP. This result is related to P. M. Bal with colleagues, who conclude that an opportunity for career advancement is positively related to employee well-being and negatively related to employee unacceptable behavior (Bal et al., 2013). Similarly, E. Briggs with colleagues found that career advancement as an aspect of HCM within the organization is one important motivational strategy to engage employees in positive job-related activities and better performance (Briggs et al., 2011).
Further, the paper revealed that employee engagement partially mediates the relationship between the selected aspects of human capital management (knowledge accessibility, learning capacity, workforce optimization, leadership practice, and career advancement) and self-reported EMJP. This shows both a close connection between HCM and job performance as well as a significant association between employee engagement and job success. In other words, there is a stronger correlation between certain HCM practices and self-reported EMJP the higher the level of employee engagement.
Conclusions
The findings of this paper show that POS moderates the relationship between HCM practices and self-reported EMJP in a positive way. This demonstrates that the influence of knowledge accessibility, learning capacity, leadership practice, and career development on employee work performance is significantly larger at high levels of POS than at low POS. Put another way, the link between KA and EMP became stronger as POS rose. This result is in line with some previous scholars (e.g. Conway, Coyle, 2012; Hur, 2014), who stated that POS significantly moderated the relationship between knowledge sharing, learning and leadership style, and job performance. Nevertheless, inconsistent with previous findings (e.g., Conway, Coyle, 2012; Hur, 2014), the study findings showed that POS does not significantly moderate the relationship between workforce optimization and self-reported EMJP.
Theoretical and practical implications
This research advances the body of knowledge in the field in many ways. First, it emphasizes how crucial it is to concentrate on an organization's intangible asset — its human capital — because academic research only treats human capital at a contemporary level. Second, a new theoretical framework on the relationship between HCM practices (knowledge accessibility, learning capacity, workforce optimization, leadership practice, and career advancement), POS, employee engagement, and self-reported EMJP is developed in this study by integrating seven significant factors that have not previously been linked. This study highlights the specific HCM practices towards self-reported EMJP, and this study proposes the mediating influence of employee engagement and POS as a moderating role. The results of this study also provide evidence for using the resource-based view, social exchange theory, and human capital theory to understand the relationship between the HCM, EYE, POS, and EMJP. In short, this paper tried to fill the existence of knowledge gaps that was uncovered by the previous studies or the contradicting issues of prior research, uncover the overlooked issues, and be input for academicians who want to pursue related construct variables.
From a practical point of view, it contributes to increasing the concern of administrators or business unit managers about the significance of a proper HCM so that the organization can have better EMJP and the role of EYE and POS to create value for the company. Today's leaner business organizations must have more responsible and engaged employees to accomplish their desired goals. Technology development, deregulation, and globalization make it difficult for managers to enhance their subordinate's performance. In addition, practitioners should consider the tenet of human capital management, which signifies an approach whereby people in an organization need to be seen as intangible assets creating a part of an organization's value, not as a cost item. Managers by encouraging employee engagement may focus more on performance facilitation. As only change is permanent, the manager should develop strategies to facilitate employees to deal with the ever-changing environment through better HCM practices, better POS, and engagement strategies.
Limitations and future research
Despite contributing to the existing literature on human capital, human capital management, employee engagement, and self-reported EMJP, our study is not free from limitations. First, the data for this study were gathered in two rounds at a single point in time, which might limit the implications of the causality. As a result, future researchers are encouraged to conduct a longitudinal study. Second, the results of this study are limited to the Ethiopian banking sector; future studies should replicate the model in other industries. Finally, future researchers could extend the model by taking other aspects of HCM like knowledge management, talent management, and compensation, and incorporating variables like organizational identification and firm performance.
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Received 24.07.2022
Взаимосвязь между аспектами управления человеческим капиталом и вовлечённостью сотрудников, воспринимаемой организационной поддержкой и самооценкой сотрудниками своей производительности
ДЕСТА Абель
ORCID: 0000-0002-4259-0809
ТАДЕССЕ Ворку МУЛУСЕВ Вубшет
Университет Аддис-Абебы, Аддис-Абеба, Эфиопия
Аннотация. Цель. Основным нематериальным активом организаций и основным фактором, определяющим их конкурентное преимущество, стал человеческий капитал. В этой статье рассмотрена взаимосвязь отдельных аспектов управления человеческим капиталом и самооценки производительности своего труда у сотрудников, опосредованная вовлечённостью. Аналогичным образом в этом исследовании проверялась опосредующая роль воспринимаемой организационной поддержки в связи между управлением человеческим капиталом и производительностью труда, о которой сообщают сами сотрудники. Метод. Эта статья построена на основе количественного подхода с использованием стратифицированной и простой случайной выборки. Для анализа исследовательской модели и проверки предполагаемых взаимосвязей было использовано моделирование структурными уравнениями с помощью программы AMOS. Выводы. Различные аспекты управления человеческим капиталом положительно связаны с самооценкой сотрудников своей производительности. Более того, вовлечённость сотрудников частично опосредует эту связь, а воспринимаемая организационная поддержка положительно влияет на связь между доступностью знаний, способностью к обучению, практикой лидерства, карьерным ростом и самооценкой сотрудников своей производительности. И наоборот, она незначительно опосредует связь между оптимизацией рабочей силы и производительностью труда сотрудников, между оптимизацией рабочей силы и самооценкой сотрудниками эффективности своей работы. Последствия для практики. Это исследование имеет значение для политиков, руководителей организаций, инвесторов в целом и банковского сектора в частности в их усилиях по созданию стратегий для сопоставления методов управления человеческим капиталом, вовлечённости персонала, воспринимаемой организационной поддержки и самооценки сотрудниками своей производительности труда. Таким образом, аспекты управления человеческим капиталом являются определяющими факторами вовлечённости сотрудников и производительности сотрудников в их самооценке. Более того, воспринимаемая организационная поддержка способствует установленным связям и отношениям.
Ключевые слова: управление человеческим капиталом, вовлечённость сотрудников, воспринимаемая организационная поддержка, эффективность работы сотрудников.
