Read the two articles attached and complete an annotated bibliography for each article. Annotated Bibliography's should be ½ to ¾ pages long for each article. It should be double-spaced, and you are t

Organizational capital contributes to social capital which in turn leads to improvement in human capital. In terms of the impacts of the three human resource management bundles on the type of intellectual capital, it should be on human capital alone. One additional mediator is organizational commitment, which has been shown to be closely linked to both the exo genous and dependent variables based on previous research. Organizational commitment is defined as degree of the employees’ identification with the organization (Porter, Steers, Mowday and Boulian, 1974). The dependent variable in this study is employee p erformance. Literature Review HRM Bundles, Intellectual Capital and Organizational Outcomes) International Journal of Management, Accounting and Economics Vol. 6, No. 8, August, 2019 ISSN 2383 -2126 (Online) © Authors, All R ights Reserved www.ijmae.com 584 In this study, we have three exogenous variables, four mediator variables and one dependent variable. The exogenous variables are ability -enhancing HRM, motivation - enhancing HRM and empowerment -enhancing HRM. The four mediators are human capital, social capital, organizational capital and organizational commitment. The dependent variable is employee performance. The relationship between HRM bundles, intellectual c apital and organizational outcomes has been found in many studies. However, some of the earlier studies did not combine the HRM practices into HRM bundles using the AMO framework but used HRM practices like training, performance appraisal and staffing as t heir independent variables. Longo and Mura (2011) found that human capital impacted job satisfaction and turnover through structural and relational capital based on data from a large Italian company. Kianto, Saenz and Arumburu (2017) in a study of 180 Sp anish firms established that intellectual capital positively mediates knowledge based HRM and innovation. They measured intellectual capital as comprising 3 components, human, structural and relational capital. Chen, Liu, Chu and Hsiao (2014) found that hu man capital and organizational capital impacted new product performance through customer capital in a sample of 93 firms. Jiang, Lepak Hu and Baer (2012) in a meta -analytic investigation found that the ability - enhancing, motivation -enhancing and opportuni ty-enhancing HRM bundles had impacts on both operational outcomes like productivity, operational performance and customer service and financial outcomes like market performance and return on equity, mediated by human capital and employee motivation. Hauff, Alewell and Hansen (2018) found evidence for the universal applicability of the ability, motivation and opportunity -enhancing high performance work systems and financial performance, mediated by human capital, employee attitudes, employee performance and operational performance. Blom, Kruyen, Van der Heijden and Thiel (2018) compared the effects of ability - enhancing, motivation -enhancing and opportunity -enhancing HRM bundles between public and private sector employees and found that they were equally affec ted by the 3 bundles, without significant differences. Ali, Lei and Wei (2018) found that strategic HRM resulted in organizational performance mediated by employee relations climate. Al -Refaie (2015) found that HRM practices were positively related to serv ice quality, employee satisfaction and customer satisfaction, which in turn contributed to hotel performance. Batarliene, Cizinene, Vaiciute, Sapalaite, and Jarasuniene (2017) concluded that HRM practices assisted organizations to achieve greater income an d better market position. Beltran -Martin and Bou -Llusar (2018) found that skill -enhancing and opportunity -enhancing HRM bundles contributed to employee abilities and motivation whereas the opportunity -enhancing HRM also resulted in employee participation. Ozbag, Esen and Esen (2013) based on primary data collected from 122 medium and large organizations, found that HR capabilities influence knowledge management (KM) International Journal of Management, Accounting and Economics Vol. 6, No. 8, August, 2019 ISSN 2383 -2126 (Online) © Authors, All R ights Reserved www.ijmae.com 585 capability, which contributes to innovation. Moreover, HRM capabilities have both direct and indirect effects on innovation, mediated by knowledge management capabilities. Cabello -Medina, Lopez -Cabrales and Valle -Cabrera (2011) found that HRM practices influenced firm innovativeness and performance through both human and social capital, with soc ial capital having an indirect effect to firm performance through human capital. Yang and Lin (2009) found that the human resource practices of selection and recruitment, training and development, performance appraisal and health and safet y affected organi zational performance mediated by intellectual capital. Huang and Hsueh (2007) found that human capital affected business performance though structural and relational capital. Yaseen, Dajani and Hasan (2016) found that structural and relational capital, but not human capital, influenced competitive advantage in telecommunications companies. Nieves and Quintana (2018) found that human resources affected hotel industry performance through the mediating role of human capital. Seeck and Diehl (2017) in their literature review of 33 cases on the impact of HRM on innovation, found, among other things, for the HRM -innovation link, mediated by creativity and knowledge management. Donate, Pena and Sanchez de Pablo (2016) uncovered, among other things, the positive links between collaborative HRM practices and social capital, which in turn influence innovation. Social capital acts as the medium through which networks and knowledge exchange contribute to innovation. Thus, we developed the following hypotheses for this study: Hypothesis 1: There will be direct and significant relationships between the ability - enhancing, motivation -enhancing and empowerment -enhancing HRM bundles and human capital (HC). Hypothesis 2: There will be direct and significant relationships betw een the ability - enhancing, motivation -enhancing and empowerment -enhancing HRM bundles and employee performance (EP). Hypothesis 3: There will be a direct and significant impact of organizational capital (OC) on social capital (SC). Hypothesis 4: There will be mediated and significant relationships between the ability - enhancing, motivation -enhancing and empowerment -enhancing HRM bundles and employee performance through human capital (HC). Hypothesis 5: There will be a mediated and significant relationship be tween organizational capital (OC) and human capital (HC) through social capital (SC). HRM Bundles, Organizational Commitment and Organizational Outcomes International Journal of Management, Accounting and Economics Vol. 6, No. 8, August, 2019 ISSN 2383 -2126 (Online) © Authors, All R ights Reserved www.ijmae.com 586 Organizational commitment is the psychological and emotional feeling of the employee who wants to contr ibute to the organization. The employee not only feels that the organization is a place to come to work but that he is a part of the organization and he is concerned about and wants to contribute to its improvement. There are many studies that have found positive relationships between human resource practices and organizational commitment. Ogilvie (1986) was able to demonstrate that human resource practices, more than any other factor, had a direct and positive relationship with organizational commitment. Sendogdu, Kocabacak and Guven (2013) found that there was a positive and significant relationship between human resource management practices and organizational commitment. Agarwala (2003) found that innovative HRM was the most significant predictor of or ganizational commitment. Meyer and Smith (2000) found that employees’ evaluations of HRM practices and organization commitment was mediated by perceptions of organizational support and procedural justice. Juhdi, Pa’wan and Hansaram (2013) found that HRM p ractices had an effect on employee turnover, mediated by organizational commitment and employee engagement. Bei Yu and Egri (2005) found that employee satisfaction with their HRM practices produced higher organizational affective commitment. Therefore, w e hypothesize the following: Hypothesis 6: There will be direct and significant relationships between the ability - enhancing, motivation -enhancing and empowerment -enhancing HRM bundles and organizational commitment (ORGC). Hypothesis 7: There will be a med iated and significant relationship between the ability -enhancing, motivation -enhancing and empowerment -enhancing HRM bundles and human capital though organizational commitment (OGC). Conceptual Framework The conceptual framework used in our study is shown in figure 1. International Journal of Management, Accounting and Economics Vol. 6, No. 8, August, 2019 ISSN 2383 -2126 (Online) © Authors, All R ights Reserved www.ijmae.com 587 Figure 1 : Conceptual Framework Methodology Data Collection A structured survey with two sections was distributed to 270 respondents in 8 firms in Kuala Lumpur and Selangor, who are entry -level, mid -level and senior -level managers. The first section of the survey form consisted of demographic variables like age, gender, tenure and years of education. The second section contained Likert 5 point scale items on the exogenous variables of ability -enhancing (ABIHR), motiva tion -enhancing (MOTHR) and empowerment -enhancing (EMPHR) HRM bundles, the mediating variables of organizational commitment (OC), human capital (HC), social capital (SC) and organizational capital (OC) and the dependent variable of employee performance (EP) . The sampling used was non -probability convenient sampling. A total of 201 completed forms was received. During the editing phase, it was discovered that a total of 9 survey forms contained many omissions and some illogical answers, to be of use in analys is. They were excluded from analysis. The final number of respondents included in the analysis was 192. Note: EMPHR = empowerment -enhancing HR, MOTHR = motivation -enhancing HR, ABIHR = ability -enhancing HR, HC = human capital, ORGC = organizational commitm ent, OC = organizational capital, SC = social capital, EP = employee performance. Data Collection Measures were taken from published sources. The first section of the survey form consisted of demographic variables like age, gender, tenure, years of educati on and managerial grade. The remaining questions contained Likert 5 point scale items on the International Journal of Management, Accounting and Economics Vol. 6, No. 8, August, 2019 ISSN 2383 -2126 (Online) © Authors, All R ights Reserved www.ijmae.com 588 three bundles of HRM, human capital and employee performance. The items for the three HRM bundles were taken from Subramony (2009). The items on the 3 types of cap ital are from Youndt and Snell (2004), the employee perfromance items are from Williams and Anderson (1991) and the items on OC and employee performance are from Williams and Anderson (1991). Common Method Bias To reduce common method bias since data are c ollected from one group of respondents, respondents were informed in the survey form that the survey was anonymous and confidential and to answer as honestly as possible. Secondly, items used to measure variables are taken from published sources with high reliability. Thirdly, respondents are told to select the first answer that comes to their minds as there are no right or wrong answers. Finally, a Harman One Factor test produces a result of 30.8 per cent of variance explained, which is well below that of the cut -off pint of 50 per cent. Thus, this study does not suffer from common method bias. Results Data Analysis SPSS version 23 was used to compute means and frequencies. SMART -PLS was used to test the hypotheses in the study. Means and Frequencies The re were 106 females and 86 males in the sample. The mean age is 74 years with an average job tenure of 9 years. The level of education was as follows: 4 per cent had a level qualifications, 12 per cent diploma, 42 per cent first degree, 31 per cent masters ’ degree and 5 per cent had doctoral degree. The remaining respondents did not indicate their educational level. Results of Hypotheses Tests To carry out the hypotheses tests, two models had to be assessed using SMART PLS software, the measurement model an d the structural model. Measurement Model: Reliability First, we check on the internal consistency of the model by examining the composite validity which must exceed 0.7 to be acceptable. From table 1, we can see that all our values exceed 0.7. Therefore, this study has internal consistency reliability. We next examine the average variance extracted (AVE). As can be seen from table 2 below, all our values exceed the threshold value of 0.5 for AVE. International Journal of Management, Accounting and Economics Vol. 6, No. 8, August, 2019 ISSN 2383 -2126 (Online) © Authors, All R ights Reserved www.ijmae.com 589 Table 1: Composite Reliability of Variables ABIHR 0.812 EMPHR 0.855 MOTHR 0.866 SC 0.875 OC 0.898 HC 0.925 ORGC 0.934 EP 0.960 Measurement Model: Convergent Validity Table 2: Average Variance Extracted (AVE) ABIHR 0.521 EMPHR 0.664 MOTHR 0.763 SC 0.700 OC 0.815 HC 0.711 ORGC 0.703 EP 0.875 Next, we check on the outer loadings of the constructs to make sure they meet the minimum level of 0.708 as recommended by Hair et. al. (2014). Table 3: Loadings of the Indicators to Constructs ABIHR EMPHR EP HC MOTHR OC ORGC SC Emphr1 0.711 Emphr5 0.848 Emphr6 0.8 75 Empp1 0.931 Empp2 0.948 Empp3 0.923 Empp4 0.900 Humanc1 0.901 Humanc2 0.863 Humanc3 0.859 Humanc4 0.839 Humanc5 0.748 International Journal of Management, Accounting and Economics Vol. 6, No. 8, August, 2019 ISSN 2383 -2126 (Online) © Authors, All R ights Reserved www.ijmae.com 590 Mothr1 0.841 Mothr5 0.905 OC10 0.8 12 OC3 0.760 OC5 0.832 OC6 0.894 OC7 0.847 OC8 0.878 Orgc3 0.915 Orgc4 0.891 Abihr3 0.615 Abihr4 0.741 Abihr5 0.784 Abihr6 0.736 Socialc1 0.823 Socialc2 0.890 Socialc3 0.794 As can be seen in table 3, all our outer loadings meet the minimum threshold level of 0.708 as recommended by Hair, Hult, Ringle and Sarstedt (2017) except for Abihr3.

However, because Abihr4 to Abihr6 is well above 0.708, t he AVE for ABIHR exceeds the threshold of 5.0. Because this study has met the requirements for the AVE and the cross -loadings, it has satisfied convergent validity. The last component of the measurement model is that of discriminant validity. Measurement M odel: Discriminant Validity Discriminant validity is established by using the Heterotrait -Monotrait (HTMT) Ratio, which must not exceed the stringent value of 0.85, according to Kline (2011). As can be seen in table 4, our highest value is 0.756, which is well below the threshold of 0.85 . Table 4: HTMT Results ABIHR EMPHR EP HC MOTHR OC ORGC ABIHR EMPHR 0.756 EP 0.320 0.159 HC 0.447 0.556 0.512 MOTHR 0.417 0.375 0.663 0.530 OC 0.466 0.596 0.354 0.678 0.406 ORGC 0.513 0.608 0.324 0.635 0.501 0.473 SC 0.515 0.614 0.395 0.85 0.312 0.7 0.511 International Journal of Management, Accounting and Economics Vol. 6, No. 8, August, 2019 ISSN 2383 -2126 (Online) © Authors, All R ights Reserved www.ijmae.com 591 In addition, we also performed complete bootstrapping with two tail significance to verify that the lower or upper confidence interval did not include the value of 1. Thus, the study has achieved discriminant validity. Thus, the measurement model has met all requirements. The next step in the process is to examine the structural model. Structural Model The first step in the structural model involves checking the collinearity statistic, th e Variance Inflation Factor (VIF). Diamantopoulos and Sigouw (2006) had recommend that the VIF be equal to or less than 3.3 whereas Hair, Hult, Ringle and Sarstedt (2017) had recommended the VIF be equal to 5.0 or less. Because our values are well below 3. 3 as shown in table 5, we can proceed to the next step. Table 5: VIF Values ABIHR EMPHR EP HC MOTHR OC ORGC SC ABIHR 1.686 1.74 1.659 EMPHR 1.703 1.849 1.588 EP HC 1.447 MOTHR 1.265 1.241 1.131 OC 1.000 ORGC 1.636 SC 1.394 As can be seen in table 6, the path coefficients are all significant, with two exceptions, ability - enhancing HRM bundle to human capital and empowerment -enhancing HRM bundle to human capital. The path coefficients are shown in diagrammatic form in figure 1. The strongest paths are from SC → HC (0.554), followed by OC → SC (0.547) and MOTHR → EP (0.408). To get a better understanding of why the ability -enhancing HRM bundle and empowerment -enhancing HRM bundle does not have a sign ificant relationship with human capital, there is a need to examine indirect effects, which are shown in table 7. It should also be noted that the relationship between empowerment and employee performance in row 4 is negative and this will be discussed in the discussions and conclusions section later in this paper. As can be seen in rows 10 and 11 of table 7, the ability -enhancing HRM bundle and empowe rment -enhancing HRM bundle impacts human capital only in the presence of organizational commitment. The strongest indirect paths are from OC → SC → HC (0.303), followed by SC → HC → EP (0.181) and OC → SC → HC → EP (0.099). The amount of variance explain ed is shown in table 8. As can be seen in the table, the model used was able to explain 39 per cent of employee performance, 62 per cent of human capital, 35 per cent of organizational commitment and 30 per cent of social capital. International Journal of Management, Accounting and Economics Vol. 6, No. 8, August, 2019 ISSN 2383 -2126 (Online) © Authors, All R ights Reserved www.ijmae.com 592 Rules of thumb for accept able R2 are difficult to formulate as it depends on the area of study and its complexity. However, the results obtained are generally respectable figures. Table 6: Path Coefficients Path coefficient T Statistics Significance Result ABIHR -> EP 0.186 2.369 0.009 Supported ABIHR -> HC -0.019 0.310 0.378 Not supported ABIHR -> ORGC 0.171 2.739 0.003 Supported EMPHR -> EP -0.233 3.410 0.000 Supported EMPHR -> HC 0.017 0.242 0.405 Not supported EMPHR -> ORGC 0.339 4.367 0.000 Supported HC -> EP 0.327 4.215 0.000 Supported MOTHR -> EP 0.408 5.418 0.000 Supported MOTHR -> HC 0.185 3.345 0.000 Su pported MOTHR -> ORGC 0.263 3.410 0.000 Supported OC -> SC 0.547 8.563 0.000 Supported ORGC -> HC 0.263 4.264 0.000 Supported SC -> HC 0.554 8.844 0.000 Supported Cohen (1988) has mentioned that f2 values of 0.02, 0.15 and 0.35 as small, medium and large effects. As can be seen in table 9, the ability -enhancing HRM bundle has a small effect size on employee performance and organizational commitment. Empowerment HRM bundle has a small effect on employee performance organizational commitment. Human capital has a med ium effect on employee performance. The motivation HRM bundle has a medium effect on employee performance and small effect size on human capital and organizational commitment. Organizational capital has a large effect on social capital. Organizational comm itment has a medium effect on human capital and social capital has a large effect on human capital. Figure 2: Path Coefficients Note: Significant paths in bold International Journal of Management, Accounting and Economics Vol. 6, No. 8, August, 2019 ISSN 2383 -2126 (Online) © Authors, All R ights Reserved www.ijmae.com 593 Table 7: Specific Indirect Effects Path Path coefficient T Statistics Sig . Result ABIHR -> HC -> EP -0.006 0.298 0.383 Not supported EMPHR -> HC -> EP 0.005 0.231 0.409 Not supported MOTHR -> HC -> EP 0.006 2.417 0.008 Supported ABIHR -> ORGC -> HC -> EP 0.015 1.953 0.026 Supported EMPHR -> ORGC -> HC -> EP 0.029 2.486 0.007 Supported ORGC -> HC -> EP 0.086 3.147 0.001 Supported MOTHR -> ORGC -> HC -> EP 0.023 2.034 0.021 Supported SC -> HC -> EP 0.181 3.926 0.000 Supported OC -> SC -> HC -> EP 0.099 3.22 0.001 Supported ABIHR -> ORGC -> HC 0.045 2.177 0.015 Supported EMPHR -> ORGC -> HC 0.089 3.149 0.001 Supported MOTHR -> ORGC -> HC 0.069 2.201 0.014 Supported OC -> SC -> HC 0.303 5.238 0.000 Supported Table 8: Amount of Variance Explained for Dependent Variables R Square R Square Adjusted EP 0.405 0.392 HC 0.626 0.616 ORGC 0.361 0.351 SC 0.300 0.296 Finally, this model has predictive relevance (Q2) based on the values in table 10 , that are calculated by the blindfolding procedure. Thus, this model has predictive relevance for employee performance of 32, human capital of 41, orga nizational commitment of 23 and social capital of almost 20. These are all high values because they are way above 0 (Hair, Hult, Ringle and Sarstedt, 2017). Table 9: Effect Size ABIHR EMPHR EP HC MOTHR OC ORGC SC ABIHR 0.035 0.001 0.028 EMPHR 0.0 54 0.000 0.114 HC 0.124 MOTHR 0.222 0.073 0.096 OC 0.428 ORGC 0.113 SC 0.589 International Journal of Management, Accounting and Economics Vol. 6, No. 8, August, 2019 ISSN 2383 -2126 (Online) © Authors, All R ights Reserved www.ijmae.com 594 Table 10: Predictive Relevance SSO SSE Q² ABIHR 768 768 EMPHR 576 576 EP 768 524.11 0.318 HC 960 567.377 0.409 MOTHR 384 384 OC 384 384 ORGC 1,152.00 885.164 0.232 SC 576 462.401 0.197 Discussion and Conclusion Most of the hypotheses have been confirmed. The strongest direct paths are from SC → HC (0.554), followed by OC → SC (0.547) and MOTHR → EP (0.408). The strongest indirect paths are from OC → SC → HC (0.303), followed by SC → HC → EP (0.181) and OC → SC → HC → EP (0.099). These results are expected because HC, SC and OC are all different aspects of intellectual capital. However, the ability -enhancing HRM bundle and empowerment -enhancing HRM bundle did not have a significant relationship with human capital, there is a need to examine indirect effects. This involves the quality of human capital, which is affected by not only knowledge and skills of managers, but also their attitudes. Managers may be competent but may not be willing to perform. However, as sho wn in the specific indirect effects table in Table 7, the effects of the ability -enhancing HRM bundle and empowerment -enhancing HRM bundle on employees who are organizationally committed to the organization are in the expected direction, with positive impa cts on employee performance. Most findings report positive effects of empowerment on outcomes. However, row 4 reported that the relationship between empowerment and employee performance is significant but negative. Previous literature has cautioned that em powerment does not always lead to positive outcomes. For example, Bowen (1995) commented that organizations need to change their policies, practices and culture to make empowerment a success. However, if organizations continue to use top -down structures wi th a control mindset, empowerment will fail. It cannot be assumed that all managers are skillful in empowering their subordinates. Some simply do not know how to empower. Hui, Au and Fock (2004) also raise the issue of the influence of culture on empowerm ent. They mentioned that empowerment was negatively associated with job satisfaction in one high -power distance country but that no relationship had been found between empowerment and job satisfaction in three other countries, which represented both high a nd low -power distance countries. Butts,Vandenberg, Dejoy, Schaffer and Wilson (2009) also report empowerment alone did not have a positive effect on job performance. Instead, empowerment had a positive impact on job performance International Journal of Management, Accounting and Economics Vol. 6, No. 8, August, 2019 ISSN 2383 -2126 (Online) © Authors, All R ights Reserved www.ijmae.com 595 accompanied by high perceive d organizational support and a negative effect with low perceived organizational support. This study has filled in a gap in the literature on human resource management and intellectual capital in Malaysia. It has also confirmed that there are both mediated and direct impacts of human resource management bundles. This study has a few limitations. First, it is a cross -sectional study and it would be good to replicate the study to see of the findings are stable across time and in non -profit organizations. 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