Impact of Human Capital Management on Organizational Performance ...

European Journal of Economics, Finance and Administrative Sciences ISSN 1450-2275 Issue 34 (2011) © EuroJournals, Inc. 2011 http://www.eurojournals.com

Impact of Human Capital Management on Organizational Performance Waseef Jamal Department of Management Sciences, Foundation University Islamabad, Pakistan Tel: (92) (91) 9217451-2 or (92) (314) 5122033 E-mail: [email protected] M. Iqbal Saif Department of Management Sciences, Foundation University Islamabad, Pakistan Abstract The study attempts to explain the relationship between human capital management and organizational performance. Hypotheses were developed to test the impact of HCM on the performance of organizations. Data was collected from 16 firms (knowledge intensive industry segment) located in Peshawar (Pakistan) in where source of competitive advantage is human capital namely higher education institutions and pharmaceutical firms. Employing sample size of 316 employees and 16 executives on HCM score card and organizational performance constructs data were collected. The reliability of the constructs is validated by Cronbach’s Alpha value. Pearson correlation and linear regression were used to test hypotheses. Results of the study show that firm’s HCM has a significant positive impact on organizational performance. Study results provide support to strategy of investment in human capital and its management for competitive advantage at organizational and national level.

Introduction There are many arts among men, the knowledge of which is acquired bit by bit by experience. For it is experience that causeth our life to move forward by the skill we acquire, while want of experience subjects us to the effects of chance. (Plato) The new economic order, or the informational era, will do for human capital what the Industrial Revolution did for physical capital. Human capital and knowledge-based industries are emerging as the key to wealth creation. Every human have intrinsic value; this idea is as old as the written history. The history of human capital traced back to 24th century B.C. (Friedman, hatch and walker 1998, p.4). Kiker (1966) described the methods of measuring the money value of human beings and the motives behind this. Two methods are commonly used are the cost of production and the capitalized earning procedures. While motives behind the measurement of money value of human were to demonstrate the power of nation, to determine the economic effect of education, health investment and migration, for the proposal of more equitable tax schemes, for the determination of total cost of war , for public advocacy for the health conservation and significance of economic life for the prosperity of an individual for his family and country, for the support of courts in the decision of compensation in the case of personal injuries. Impact of human capital can be measured from individual point of view (investment in education) as increase in individual return. From organizational point of view (investment in general

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European Journal of Economics, Finance and Administrative Sciences - Issue 34 (2011)

and specific trainings) an enhancement in the market returns and from countries point of view (investment in education, health and migration) as economic growth models. World Bank (1995m) study based on the assessments of 192 countries conclude that global wealth constitutes of 16% of physical capital, 20% of natural capital and 64% attributed to human and social capital. Waetherly (2003) concluded that today the new vision is human capital management. Nothing happens unless human being makes a concise decision to act. Johnson (2002) expressing the importance of human capital said that all innovations are human innovations. In the end, the economy and business are people’s systems. Therefore there is no structural capital without intellectual capital and no intellectual capital without humans. Boxall (1998) described that the sources of superiority depend on the quality of interest alignment and employee development in firm compared with the industry rivals. “People are our greatest assets. Yet few practice what they preach, let alone truly believe it” (Drucker, 1992). Pfeffer (1994) is strong proponents of the contribution of human in strategic context. He suggested that human resource need to be treated as permanent rather then contingent resources. The organization must capture the benefits of any firm- specific competencies and capabilities that they develop. The work of Mincer, Schultz, and Becker on human capital provides brief description about investment in human beings. Schultz (1971, p 8, 26, 68) classified investment in human capital in five categories: Schooling and higher education, on the job training, migration, health and economic information. Schultz described that by investing in themselves people can improve enlarge the range of choices available to them. It is the one way free men can enhance their welfare through. Becker’s model (1962) gives birth to the following predictions: Firms are willing to invest in human capital to develop firm specific skills that are productive at the current firm but not at other firms. Firms are unwilling, however, to invest in human capital to develop general skills (as they cannot recoup their investment in general skills training because worker can simply move to new firms if they are paid less then their marginal value product). As a result, worker themselves must bear the cost of any general skills training that they receive, either directly or by accepting lower wages. According to Weisbrod (1962) the principal forms of direct investment in the productivity and well-being of people are: health, learning (both in school and on the job), and location (immigration). Chen and Lin(2005) defined investment in human capital as input made by company in talents and technology that benefit competitive advantages, are valuable and unique, and should be kept out of reach of other companies. In other words, only employees possessing these qualities are qualified as human capital. Khandekar and Sharma (2003) concluded that firm that make greater use of HR capabilities are likely to gain a sustainable advantages and enjoys superior performance. Kannan and Akhilesh (2002) described that to enhance the organizational performance in IT industry in India the managers have to understand the characteristic and behaviors of higher performing employees. Brooks, Hairston and Nafukho (2006) showed the clear relation of organizational HRD and organizational productivity. Hitt, Hoskisson, Harrison and Summers (1994) described that for US firm to attain competitive advantage, they have to focus on the development and retention of human capital with a culture of creativity and life-long learning. Bassi, Harrison, Ludwig and McMurrer (2004) concluded that investments in HC (Training Investment) are positively related to stock market performance. They stated that investors would be well served by considering firms’ human capital investment strategies as an integral part of their investment decision. Friedman, Hatch and Walker (1998, p-14, Box 1.4) described the studies had success in finding the relation between investment in human capital and company performance. Bontis, Koew and Richardson (2000) concluded that for organization it is not enough to hire and promote the brightest individual it find. The organizations must nurture and support them into sharing their human capital through organizational learning and externalities into information system to positively affect the business performance. Saenz (2005) concluded that the human capital have a clear bearing on the value reflected by its market-to-book ratio. Chen, Cheng and Hwang (2005) proved that greater human capital efficiency of organization tend to have higher market-to-book value ratios. Almeida and Carneiro (2006) concluded that investments in human capital have on average

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negative returns for those firms which do not provide training, while estimate of returns for firms providing training are quite high, with lower bound being of 17% and our preferred estimate being 24%. Such high returns suggest that company job training is a sound investment in human capital for firms and for the economy as a whole, possibly yielding higher returns than either investments in physical capital or investments in schooling. Seleim, Ashoure, Bontis (2007) proved a positive relation in human capital and organizational performance. Hitt, Bierman, Shimizu and Kochhar (2000) concluded by empirical analyses of 93 firms with a data span of 1987-91 that leveraging human capital has positive impact on the performance and having a curvilinear effect. While human capital also plays a moderating role between firm strategy and performance. Shah and Bandi (2000) concluded that to enhance the capabilities of organization in knowledge intensive IT enabled services in India the HR practices has to be focused on the core asset of human capital. Wiesberg (1996) studied the impact general human capital (GHC) and firm specific human capital (SHC) by analyzing performance of 65 workers in 20 groups and found significant positive correlation between GHC, SHC and firm performance. Black & Lyunch (1997) examined the relationship between work practice, information technology and investment in human capital and firm performance. Study covered the period of 1987-1993. Study concluded that impact of practices is in its implementation not adoption, and the higher education level and greater use of computer of production worker has a positive impact on firm productivity. Seleim, Ashour and Bontis (2006) empirically studied 38 software development organization of Egypt and found a positive correlation between human capital and organizational performance. Bassi and Mcmurrer (2004) analyzed S&P companies for data span (1996-98) to assess the impact of training on firm stock price. The study concluded that firm stock return increases by 1 basis point for each additional dollar invested in training have a positive correlation. Wan (2007) concluded by analyzing 4 MNC’s globally and locally owned that human capital development policy have an effect on employee’s satisfaction and organization policy. Chen, Chang and Hwang (2005) found empirical support for the hypothesis that the companies having greater human capital efficiencies have higher market to book value and also that intellectual capital efficiency affect the financial performance of the companies. Hurwitz, Lines, Montogomery and Schmidt (2002) concluded that vital role has been played by human capital for the driving intangible performance and stock return. Switzer and Huang (2007) finding suggests that variances in fund performance is attributed by managerial human capital characteristics. Bart (2001) analyzed data set of 559 organization and found significant correlation between firm mission statement and human intellectual capital, ultimately effect the performance of the firm. Huselid, Jackson and schuler (1997) analyzed 293 U.S based firm to measure the impact of human resource manger on human resource effectiveness and its impact on performance of the firm. Study concluded that human resource effectiveness is associated with the capabilities of the employees also having a relationship with productivity, cash flow and firm market value. Barrett & O’Connell (2001) used data obtained from survey of Ireland enterprises to estimate the impact of training on productivity of firm. Result of the study showed a statistically significant positive correlation between training and productivity of the firm. Collins & clark (2003) study investigated the relationship of network building HR practices and firm performance. It was found that the relation is mediated through top management social networks. Guest,Michie, Conway and Sheehan (2003) examined 366 UK companies using subjective and objective measure of performance to investigate the relationship of HRM and performance. It was found that by using objective measure of performance turnover and financial performance showed association with HRM. HRM have no higher association with productivity, using subjective measure HRM have an association with productivity and financial performance. Huselid (1995) study linkage between HRM practices, turn over, productivity and financial performance of the firms. It was found that high performance work practices have an economically and statistically significant impact on productivity, turnover and financial performance. Patterson, West, Lawthom and Nickell (1998) concluded that HR practices contribute 18%, 19% variation in companies productivity, financial performance respectively. HR practices are the main reason for variation in comparison to Strategy, R&D, Quality and technology. Molina & Ortega (2002) analyzed 405 North American firms to

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investigate the relationship of Human Capital Resource policies and firm performance. It was concluded that effective human capital management enhance employees satisfaction resulted in customer loyalty which, in turn enhance the financial performance. Strother, Koven, Howerth and Pan (2004) tested the hypothesis to measure the impact human capital program on the human capital growth and found a significant positive impact. Zula & Chermack (2007) concluded that proper human capital planning effect the organization profits. Employees (intangible assets) add value to bottom line through enhance knowledge. Bontis & Serenko (2009) concluded that measurement and strategic management of intellectual capital will be the lone important management activity in knowledge era for drawing performance. Glade & Ivery (2003) concluded that work climate, HR practices and business performance have a significant correlation. Singh (2004) studied 82 Indian organizations to investigate the relation of HR practices and firm performance. Study concluded that HR practices (Compensation and training) have a significant relationship with firm performance. Bhattacharya, Gibson and Doty (2005) concluded that HR practices of the firm have a significant relationship with firm financial performance. Wright, Gardner, Moynihan & Allen (2005) concluded that HR practices have a high correlation with firm performance. The above literature elaborates the significance of investment in human capital, development of HR practices and its relationship with organization productivity and performance at macro and micro level. These researches are conducted at developed part of the world. The study is being undertaken to analyze the situation of an under developed country to investigate the relationship of human capital management practices and organizational performance. After analyzing the above literature one of the reasons of the third world generally and Pakistan specifically to be poor, is it’s under investment in human capital. Divergence between economic growth and human development is greater in Pakistan than in most of other third world countries. Pakistan presents a fascinating combination of many contradictions. The country literacy rate is among one of the lowest in the world, yet some of its highly educated people have dominated many international forums, weak institution and strong individual, economic growth without human development, private greed and lack of social compensation and election rituals without real democracy (Mahbubul haq, 1997, p-37). Human capital development remains a major structural challenge. Despite the recent rise in pro-poor spending, historical under investment in human capital has critical implications for growth and competitiveness. Public spending on education was only 2.0% of GDP in 2004, compared with 6.0% in Malaysia, 4.0% in Thailand (Asian Development Outlook, 2007, 193). Pakistan has human development index rank of 134, having HDI 0.539 (Human development report, 2006). World Economic Forum ranked Pakistan 92 out 133 countries (The global competitiveness Report 2007-2008). Educational and health expenditures of Pakistan are 2.4%, 0.6% of GNP (Economic survey of Pakistan 2006-2007). Nearly half of the population of Pakistan is illiterate i.e. 47%, with participation rate of 32.2%, having 50.05million labor force which is small number and also include 18.43% of children of age of 10-14 of both sex (FBS, 2005-2006). The educational investment in Pakistan in the last 60 year did not reach to 3% of the GDP. According to National education census 2005 only 51.6% of the educational institution have satisfactory situation according to building condition (Education census, 2005). Inadequately educated labor force having score of 10.7 is one of the most problematic factor in doing business in Pakistan (The global competitiveness Report 2007-2008). Mustafa, Abbas and Saeed (2005) stated that there is serious mismatch between the job demands in the emerging economy and supply of human capital in the country. Technical and Vocational training as well as the formal education is not standard enough to fill the skill gap and the problem of brain drain is adding to the country miseries. All these show how poorly Pakistan has translated its income in the lives of its people. Khan (2005) stated that for Pakistan investment in human capital will serve the dual purpose by having productive worker and a tool for elimination of poverty. Pakistan had achieved even higher growth rates, had it invested more in its human capital. This paper will empirically investigate the relationship of human capital management and organizational performance.

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Theoretical Frame Work This study is being undertaken to investigate the relationship between human capital management and organizational performance. With rapidly changing environment, the art of forecasting has become complicated and uncertain in identifying core building block of organization competitive advantage. World progress from agriculture to industrial and knowledge economy change the agents for the economic growth from land to steam engine and human capital. Technology, strategy, global alliances and innovations known as source of competitive advantage in knowledge era are dependent on human talent. Sources of future organization economic power rest in effective management of best human talent in market place (Simth & Kelly 1997, p-199). The relationship of investment in human and performance at individual, organizational and economic level has been verified by empirical and theoretical studies and make the strong case for investment in human capital for regional development (Becker 1964, Shultz 1958, Mincer 1962, Lucas 1988, Roomer, 1986, 87, 90, Bontis 1999, Bontis & Fitz-enz, 2002, Huslaid 1995, etc). literature reveals that human capital management is measured by using different methodologies but still the scientist are not able to have a universal frame work for the measurement of human capital management. The present study is an effort in this direction. For current study human capital management is taken as independent variable. The human capital management is comprises of the five dimensions (Leadership practices, Knowledge accessibility, Learning capacity, Workforce optimization, Employee engagement) define by Bassi & McMurrer (2007). Performance of the organization the dependent variable is measure by using the scale developed by Bontis (1999) having ten factors to measure performance at ten point scale (Industry Leadership, Future Outlook, Profit, Profit Growth, Sales Growth, After-tax return on assets, After-tax return on sales, Overall response to competition, Success rate in new product launches and Overall business performance and success. The schematic diagram represents the formation of the indices and variables.

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Theoretical Framework Communication

Inclusiveness Supervisory Skills

Leadership Practices

Executive Skills

Systems Process

Industry Leadership

Conditions

Accountability

Work force optimization

Future Outlook

Profit

Hiring Decision Systems

Profit Growth Availability Collaboration and Team work

Knowledge access ability

Human Capital Management

Performance

Sales Growth After tax return on assets

Information Sharing Systems

After tax return on sales

Innovation Overall response to competition

Training Learning Capacity Development

Success rate in new product launches Value and Support Overall business performance and success

Systems

Job Design Commitment to employees

Employee engagement

Time

Systems

Hypothesis The preceding theoretical frame work guide for the development of the following hypothesis: H1: Human capital management is positively related to organizational performance. H2: organizational score on Human capital management significantly predict their organizational performance.

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Population Becker & Gehart (1996) suggested that firm’s level analysis is the most direct and generalizble test of HR – performance relation. The study was design to be conducted at the firm level in the knowledge intensive industry such as privately owned universities, and pharmaceuticals companies. Starbuck (1992) suggests that firms in which knowledge has more importance than other inputs and human capital, as opposed to physical or financial capital dominates can be applied as knowledge intensive. Application of expertise for the solution of the complex problems and to provide innovative solutions is another distinction of knowledge intensive firms. The reasons for the selection of knowledge intensive industry are that firms compete on the basis of intangible assets, particularly human capital and knowledge intensive industry composed mainly of knowledge workers whose work processes and contributions to the firm are relatively similar across the industry. The population for the study comprise of the private universities working in Peshawar and local pharmaceutical companies in Peshawar.

Sampling To investigate the relationship of variables, a total of 450 questionnaires were distributed to the employees in 16 organization i.e. 10 universities and 6 pharmaceuticals firms, out of which 316 questionnaires were returned. This resulted in the total usable sample size of 316 participants from employees with response rate of 70 %. A total 16 questionnaires were also completed from the executives of these organizations.

Instrument The data collection instrument for the present study was comprised of two parts: the first part served as introduction for study and instruction for the completion of the questionnaire. The second part assessed the main variables for the study. The demographic information was not acquired to minimize the bias of identification. The below paragraph explain the second part of the instrument.

Second Part The second part of the instrument measure organizational position on human capital management (leadership practices, workforce-optimization, learning capacity, knowledge accessibility) and organizational performance. The respondents of the study were knowledge worker, helping in comprehension and understanding of the questionnaire. The items were asked in continuity without any distraction, because all items were asked on same 5 point rating scale (likert scale) to measure variables of interest. The used of separators avoided to hold respondent attention and get responses in natural flow.

Human Capital Management Human capital management was assessed through a scale developed by Bassi & McMurrer (2007) based on human capital management frame work. Human capital management assessed through 23 HCM practices that fall within five broad categories of HCM drivers. Leadership Practices: Managers’ and leaders’ communication, performance feedback, supervisory skills, demonstration of key organizational values, efforts and ability to instill confidence. Tool contain 12 items to measure 5 HCM practices (Communication, inclusiveness, supervisory skill, executive skill and system) using 5 point rating scale, where 1 represent “strongly disagree” and 5 present “strongly agree”. The total score of 12 items than can be range from 12 to 60. The higher the

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score indicate organization higher ability in management of HCM driver of leadership practices. The Cronbach’s alpha reliability value of 0.689 Workforce Optimization: The organization’s success in optimizing the performance of its workforce by establishing essential processes for getting work done, providing good working conditions, establishing accountability, and making good hiring choices. Tool contain 16 items (13 to 28 on scale) to measure 5 HCM practices (process, conditions, accountability, hiring decision and system) using 5 point rating scale (Likert scale), where 1 represent “strongly disagree” and 5 represent “strongly agree”. The total score for the 12 items range from 12 to 60. The higher score indicate organization higher ability in management of HCM driver of workforce-optimization. The Cronbach’s alpha reliability value of 0.843. Knowledge Accessibility: The extent of the organization’s “collaborativeness” and it capacity for making knowledge and ideas widely available to employees. Tool contain 8 items (29 to 36 on scale) to measure 4 HCM practices(availability, collaboration & team work, information sharing and system) using five point rating scale, where 1 represent “strongly disagree” and 5 represent “ strongly agree”. Total score for the 8 item ranges from 8 to 40. The higher score indicate organization higher ability in management of HCM driver of knowledge accessibility. The Cronbach’s alpha reliability value of 0.795. Learning Capacity: The organization’s overall ability to learn, change, innovates, and continually improves. Tool contain 10 items(37 to 46 on scale)to measure 5 HCM practices (Innovation, Training, Development, Value & Support and Systems) using 5 point rating scale, where 1 represent “strongly disagree” and 5 represent “strongly agree”. Total score for 10 items ranges from 10 to 50. The higher score indicates organization higher ability in management of HCM driver of learning capacity. The Cronbach’s alpha reliability value of 0.829. Employee Engagement: The organization’s capacity to engage, retain, and optimize the value of its employees hinges on how well jobs are designed, how employees’ time is used, and the commitment that is shown to employees. Tool contain 10 items(47 to 56 on scale) to measure 4 HCM practices (innovation, commitment to employees, time and system) using 5 point rating scale, where 1 represent “strongly disagree” and 5 represent “strongly agree” total score for 10 items range from 10 to 50. The higher score indicates organization higher ability in management of HCM driver of employee engagement. The Cronbach’s alpha reliability value of 0.826. The systems questions have been asked from executive because they would in good position of elaboration. To have equal weight age for all the drivers those having five factors are multiplied by 0.8 (Bassi & McMurrer, 2007) Organizational Performance Organizational performance is assessed through scale developed by Bontis(1999). The organizational performance is measured with 10 item scale 10 point rating scale which was reduced to 5 point rating scale where 1 represent “poor” and 5 represent “excellent”. Total score on 10 item scale ranges from 10 to 50. The higher score indicates the higher organizational performance. The Cronbach’s alpha reliability value of 0.86.

Result and Discussion The result of table#1,2 shows that human capital management is positively correlated with organizational performance (r=0.297,0.797 p=.00) for both employees and executive data sets.

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Table 1:

Showing correlations between dependent and independent variable (for Employees) Performance 1

Performance

Pearson Correlation Sig. (2-tailed) N HCM Pearson Correlation Sig. (2-tailed) N ** Correlation is significant at the 0.01 level (2-tailed).

Table 2:

HCM .297(**) .000 316 1

316 .297(**) .000 316

316

Showing correlations between dependent and independent variable (for Executives) Performance 1

Performance

Pearson Correlation Sig. (2-tailed) N HCM Pearson Correlation Sig. (2-tailed) N ** Correlation is significant at the 0.01 level (2-tailed).

HCM .797(**) .000 16 1

16 .797(**) .000 16

16

Predicting Organizational Performance The presence of strong positive association between organization HCM and organizational performance suggested that organization’s future performance could be predicted on the basis of their HCM scores. The study’s second hypothesis implies that organization HCM scores significantly predict their organizational performance. As a single continuous dependent variable (Organizational performance) and a single continuous independent variable (HCM) is involved in this case, so simple linear regression analysis was applied. This test produces the significant values for hypothesis testing regarding individual regression parameters. Results given in table 3 & 4 showed a significant F value (less than .05) for the prediction relation between HCM and Organizational performance. Thus our hypothesis was supported which asserted that Organizations’ scores on human capital management significantly predict the future organizational performance. Table 3:

Showing prediction of Organizational performance through scores on HCM (for Employees)

Model 1

Regression Residual Total a. Predictors: (Constant), HCM b. Dependent Variable: Perfor

Table 4:

Df

Mean Square

F

Sig.

1 314 315

4.152 .136

30.488

.000(a)

Showing prediction of Organizational performance through scores on HCM (for Executives)

Model 1

Sum of Squares 4.152 42.761 46.913

Regression Residual Total a. Predictors: (Constant), HCM b. Dependent Variable: Perfor

Sum of Squares 3.110 1.784 4.894

Df

Mean Square

F

Sig.

1 14 15

3.110 .127

24.413

.000(a)

Table 3 & 4 proved only the presence of predictive relation between predictor (HCM) and dependent variable (Organizational performance). The strength of prediction relation is shown in table

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5 with the help of the values of intercept and slope for HCM. The coefficients are unstandardized and can be interpreted as percentage changes in organizational performance per unit change in respective independent variable (HCM). The table indicated the constant value of 3.3 and a slope of .01 for the regression line for employee’s data set. This suggested that for a one unit increase in HCM, the respective organization can significantly predict a 1% increase in organizational performance. While a slope of .30 for HCM was produced when the test utilized standardized independent and dependent variables .(for employees). Table 5:

Regression Coefficients (a) for Employees Unstandardized Coefficients B Std. Error 3.031 .132 .010 .002

Model 1

(Constant) HCM a. Dependent Variable: Performance

Standardized Coefficients Beta .297

t

Sig.

B 22.905 5.522

Std. Error .000 .000

The table 6 for the executive data set indicated the constant value of .116 and a slope of .04 for the regression line. This suggested that for a one unit increase in HCM, the respective organization can significantly predict a 4% increase in organizational performance. While a slope of .80 for HCM was produced when the test utilized standardized independent and dependent variables. (for executives) Table 6:

Regression Coefficients (a) for Executives

Model 1

(Constant) HCM a. Dependent Variable: Performance

Unstandardized Coefficients B Std. Error .116 .728 .045 .009

Standardized Coefficients Beta .797

t

Sig.

B .159 4.941

Std. Error .876 .000

The coefficient of correlation and conservative measure “coefficient of determination” was calculated for both data sets. Here, table12 indicated R, “R square” value of 0.30, .09, which asserted that 9 % of the explained variation in organizational performance can be accounted for organization scores on HCM (for employees). This further supported the study’s second hypothesis. Table 7:

Model summary showing simple regression for HCM and Organizational performance (for employees)

Model 1 a Predictors: (Constant), HCM

R

R Square

Adjusted R Square

.297(a)

.089

.086

Std. Error of the Estimate .36903

Table#7 indicated R, “R square” value of 0.80, .64, which asserted that 64 % of the explained variation in organizational performance can be accounted for organizations scores on HCM (for Executives). This further supported the study’s second hypothesis. Table 8:

Model summary showing simple regression for HCM and Organizational performance (for employees)

Model 1 a Predictors: (Constant), HCM

R

R Square

Adjusted R Square

.797(a)

.636

.610

Std. Error of the Estimate .35695

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Discussion Correlation between HCM and Organizational Performance Based on the previous research, significant positive correlation was expected between HCM practices and organizational performance. So, study’s first hypothesis states that organization HCM practices are positively correlated with organizational performance. Pearson bivariate correlation coefficient was calculated to measure the association between HCM practices and organizational performance. The results of executive data set indicated a high positive correlation (r = .80, p