電子化人力資源資訊系統導入對人力資源部門的影響：一個實證研究

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(1)An Empirical Study of E-HR Adoption and HR Department Outcomes in Taiwan. by Matthew, Liang Yu, Wei. A Thesis Submitted to the Graduate Faculty in Partial Fulfillment of the Requirements for the Degree of. MASTER OF BUSINESS ADMINISTRATION. Major: International Human Resource Development. Advisor: C. Rosa Yeh, Ph. D. National Taiwan Normal University Taipei, Taiwan June, 2012.

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(3) ACKNOWLEDGEMENT At the beginning of my acknowledgement, I would like to thank my dearest and most special person in the world, my mom, Phoenix Lee. Without her help, I would not be the way I am today. All my achievement and accomplishment were all based on her effort, devotion and love. Thank my mom for all the things she has done for me and my brother Oscar. My all other family has treated me very well. Thus, I would like to thank them for being there for me. Secondly, my warmest thanks go to Dr. Yeh, for her inspiring guidance and encouragement throughout my research for this work. I have learned so many things from her during the past two years. Also, I want to thank my two lovely committee members, Dr. Lin from IHRD and Dr. Uen from National Sun Yat-Sen University. They were very nice to me during my thesis proposal and defense. I feel very lucky to have them as my mentors on the thesis writing. Also, I feel very lucky to meet Dr. Tsai in graduate school, who persistently answers my questions not only in academic research, but also in career development. He taught me patience and good virtue. Hope I would be as great as Dr. Tsai one day.. My gratitude is also. extended to all the IHRD faculties, Dr. Chang, Dr. Tony, Dr. Lai for their instruction during my study at IHRD, NTNU. I would like to thank Lynn Wu, Sandra Chen, for they are kind, adorable persons that tolerate my temper and stubborn during the semesters. I would like to thank my classmates, for them taught me so much and shared information with me. You all are my classmates, friends and my keepers. I would like to thank William Kuo, for his joyful and humor indeed add lots of fun in my life; thank Ashley Feng, for her always keep her smile and warm heart; thank Millie Huang, for her curious and serious way of dealing with schoolwork; thank Lena Hsu and Grace Ou, always be there and always find good things in life, bring happiness in my graduate life; thank James Chou, for.

(4) his strong technical support and dig information; thank Vic Tu, always think the big picture and still are the funniest person in the class; thank Winni Cheng and Anita Su, friends and everything that we can talk to each other. Thank Alan Kuo, Felicia Tsai, and Evelyn Lee, for you are part of my graduate life and the events happened in graduate life are memorable to me. Special thanks to Maggie Wu, a loving manager I met in my internship Medtronic. She taught me professionally and personally how to be a good leader. I grew very fast when I did my internship with her. She is patient and pay attention to details. Another special thanks to Nancy Wei, my summer internship director in Taiwan Semiconductor Manufacturing Company. She is always fun and emotional intelligent in dealing with employee relationship. I feel very grateful to have the great mentors in my professional life. My friends for lifetime, Michelle Weng, Melin Chen and Tzu-Hsian Lu, for them being there from the beginning I went to college to I finished my graduate school; they have listened so much rambling and murmuring that I had during the past years. Also, I want to thank my junior classmates, especially Annie Hsu and Agnes Yen. Without their support, I could not finish my thesis and questionnaire. They gave me power when I tried to do my thesis. The last but not the least, Ivan Lu, for his great support and great tolerance behind the scene. I feel very lucky to have him as part of my graduate life..

(5) ABSTRACT The study was conducted in Taiwan to explore the antecedents and outcomes of e-HR adoption. Convenient sampling was adopted to collect organizational response from multiple data sources, and data from 182 companies were included in the analysis. This study used descriptive data analysis to examine current status of e-HR practices in Taiwan, and partial least square (PLS) based structural equation modeling (SEM) to explore the relationship among e-HR practices and other variables. The result showed non-significant effect from the hypothesized antecedents of e-HR practices, i.e., HR role complexity and task complexity as predictors and IT capability as the moderator. The level of e-HR practices, on the other hand, was proven to be significant predictors of two outcome variables, strategic focus and competence of the human resource department. Implications of these findings were discussed in the research. Keywords: E-HR adoption, HR roles, IT capability, partial least square. I.

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(7) TABLE OF CONTENTS Abstract ................................................................................................................................I Table of Contents ................................................................................................................III List of Tables .......................................................................................................................V List of Figures ......................................................................................................................IX CHAPTER I INTRODUCTION .............................................................................................. 1 BACKGROUND OF THE STUDY ............................................................................................ 1 PROBLEM STATEMENT ....................................................................................................... 3 OBJECTIVES OF STUDY ....................................................................................................... 5 RESEARCH QUESTIONS ....................................................................................................... 6 LIMITATION AND DELIMITATION ........................................................................................ 7 CHAPTER II LITERATURE REVIEW ................................................................................... 9 ELECTRONIC HUMAN RESOURCE PRACTICES ..................................................................... 9 COMPLEXITY OF HR ROLE EXPECTATION ........................................................................ 16 TASK COMPLEXITY .......................................................................................................... 23 IT CAPABILITY ................................................................................................................. 26 STRATEGIC FOCUS ........................................................................................................... 29 HUMAN RESOURCE COMPETENCIES ................................................................................. 31 PARTIAL LEAST SQUARES STRUCTURAL EQUATION MODELING ...................................... 36 CHAPTER III METHODOLOGY .......................................................................................... 43 RESEARCH FRAMEWORK .................................................................................................. 43 RESEARCH DESIGN ........................................................................................................... 44 MEASUREMENT ................................................................................................................ 47. III.

(8) CHAPTER IV DATA ANALYSIS AND RESULT ............................................................... 67 DESCRIPTIVE STATISTICS OF E-HR PRACTICES ................................................................ 67 MODEL TESTING .............................................................................................................. 82 ALTERNATIVE MODEL AND MODEL TESTING .................................................................. 85 CHAPTER V CONCLUSIONS AND DISCUSSIONS .......................................................... 87 CONCLUSIONS .................................................................................................................. 87 DISCUSSIONS .................................................................................................................... 88 RESEARCH IMPLICATIONS ................................................................................................ 89 PRACTICAL IMPLICATIONS ............................................................................................... 91 LIMITATIONS .................................................................................................................... 92 FUTURE RESEARCH SUGGESTIONS ................................................................................... 93 REFERENCES ........................................................................................................................ 95 APPENDIX A: The Comparison of the Original Questionnaire and the Revised Questionnaire after Expert Review and Focus Group Interview ..................................... 103 APPENDIX B: Research Questionnaire ................................................................................ 109. IV.

(9) LIST OF TABLES Table 2. 1. Benefits of E-recruiting ......................................................................................... 13 Table 2. 2. Benefits of E-learning ............................................................................................ 14 Table 2. 3. Benefits of E-performance ..................................................................................... 14 Table 2. 4. Benefits of E-compensation ................................................................................... 15 Table 2. 5. Benefits of employee self service .......................................................................... 15 Table 2. 6. Historical evolution of HRM ................................................................................. 18 Table 2. 7. Different dimensions of human resource roles ...................................................... 21 Table 2. 8. Different dimensions of IT capability.................................................................... 26 Table 2. 9. Different dimensions of human resource competences ......................................... 33 Table 2. 10. The rules of thumb for evaluating reflective measurement ................................. 37 Table 2. 11. The rules of thumb for evaluating formative measurement ................................. 38 Table 2. 12. The rules of thumb for structural model testing .................................................. 41 Table 3. 1. Descriptive information concerning the HR respondents ...................................... 45 Table 3. 2. Descriptive information concerning the company participants ............................. 47 Table 3. 3. The exploratory factor analysis of the usage of E-HR practices in SPSS ............. 49 Table 3. 4. The Cronbach’s alpha value for usage of E-HR practices in SPSS ....................... 51 Table 3. 5. The factor loadings and t-values for E-HR practices in SmartPLS ....................... 52 Table 3. 6. The variance inflation factor (VIF) for the usage of E-HR practices .................... 52 Table 3. 7. The discriminant validity between the usage of E-HR practices and the other V.

(10) constructs ........................................................................................................................... 53 Table 3. 8. The Cronbach’s alpha for the IT capability ........................................................... 54 Table 3. 9. The factor loadings and t-values of the IT capability in SmartPLS....................... 55 Table 3. 10. The variance inflation factor for IT capability..................................................... 55 Table 3. 11. The Cronbach’s alpha for HR role expectation ................................................... 56 Table 3. 12. The overview of factor loading, composite reliability for role complexity ......... 57 Table 3. 13.. The cross loadings among all constructs ............................................................ 58 Table 3. 14. The overview of composite reliability, AVE and discriminant validity testing among all variables ............................................................................................................ 59 Table 3. 15. The Cronbach’s alpha for task complexity .......................................................... 60 Table 3. 16. The overview of factor loading, composite reliability for task complexity......... 61 Table 3. 17. The Cronbach’s alpha for the strategic focus ...................................................... 62 Table 3. 18. The overview of factor loading, composite reliability for strategic focus in SmartPLS ........................................................................................................................... 62 Table 3. 19. The Cronbach’s alpha for competence ................................................................ 64 Table 3. 20. The overview of factor loading, composite reliability for competence ............... 65 Table 4. 1. The overview of E-HR practices for employee benefits ........................................ 69 Table 4. 2. The overview of E-HR practices for compensation and rewards .......................... 71 Table 4. 3. The overview of E-HR practices for performance management ........................... 73 Table 4. 4. The overview of E-HR practices for human resource planning and career development ....................................................................................................................... 75 VI.

(11) Table 4. 5. The overview of E-HR practices for staffing......................................................... 77 Table 4. 6. The overview of E-HR practices for training and development ............................ 79 Table 4. 7. The overview of E-HR practices for employee relationship ................................. 81 Table 4. 8. The overview of hypotheses testing....................................................................... 84. VII.

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(13) LIST OF FIGURES Figure 2. 1. HR roles as theorized by Ulrich ........................................................................... 21 Figure 2. 2. Relationship of department technology with structure and information required for task accomplishment. .................................................................................... 25 Figure 3. 1. Research structure ................................................................................................ 44 Figure 4. 1. General pattern of e-HR practices in employee benefit function ......................... 68 Figure 4. 2. General pattern of e-HR practices in compensation and rewards function .......... 70 Figure 4. 3. General pattern of e-HR practices in performance management ......................... 72 Figure 4. 4. General pattern of e-HR practices in human resource planning and career development ........................................................................................................ 74 Figure 4. 5. General pattern of e-HR practices in staffing ....................................................... 76 Figure 4. 6. General pattern of e-HR practices in training and development .......................... 78 Figure 4. 7. General pattern of e-HR practices in employee relationship................................ 80 Figure 4. 8. The hypotheses testing with path coefficient and R square ................................. 83 Figure 4. 9. The alternative analysis on e-HR adoption model ............................................... 86. IX.

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(15) CHAPTER I INTRODUCTION This chapter introduces the background, rationale, research questions, objectives and definition of each variable of this study. The background focuses on describing the current workforce and two important human resource practices due to the change of economy. The rationale provides the reasons for conducting this study. Finally, research questions and objectives of the study are addressed.. Background of the Study One of the prominent features in the 21st century is the wide application of IT innovation in business (Panayotopoulou, Vakola, & Galanaki, 2007), and IT application in human resource is no exception (Mishra & Akman, 2010; Strohmeier & Kabst, 2009). E-HR system has been helpful to leverage organizational resources. E-HR system can contribute to HR professionals in many perspectives, such as streamlining the administrative processes, lowering the HR costs on administration, competing effectively for talents from the globe, improving accessibility to employees and managers in organization, providing timely information for decision makers and enabling HR professionals to transform themselves into a more strategy-focused in business (Johnson & Gueuta, 2011). Earlier in the late 1990, literatures have been settled on the strategic need to strategic human resource management. The necessity for strategic human resource management to meet organizational challenges has brought the necessary change. Ulrich (1997) proclaims that technology should be helpful to shift human resource management role from transactional activities into transformative activities. The role of strategic planning has been expected to deprive more time from human resource (HR) professionals in the future. Meanwhile, the urgency to maintain transactional activities does not shrink or disappear. 1.

(16) Thus, information technology has been cited as one of the dominant forces driving HR to transition from purely personnel administrator to multiple roles (Bell, Lee, & Yeung, 2006; Huub, Tanya, & Jan Kees, 2004) with additional expectation to guide organization to change (Ulrich, 1997). Traditionally, the role of human resource (HR) department was regarded as the legal compliance, payroll and personnel data maintainer. Later in the historical revolution of human resource management (HRM), human resource department was demanded and urged to add values to organizations, and thus created additional roles and responsibility to HR department and staffs. The new roles for HR to fulfill are company’s strategic partner, change agent and employee advocate (Panayotopoulou et al., 2007; Ulrich, 1997). To perform the additional roles, tasks and responsibilities, human resource department hence turns to human resource information technology for solutions. The automation in the HR transactional activities has streamlined the process and saved time for human resource department (Dulebohn & Marler, 2005). Originally, HR department needed to do single task in specific single function, such as payroll or record keeping. Later in the development HR professionals are given more help to deal with multiple tasks in the organization through technological innovation, outsourcing and off-shore activities. Hence, organizations require more from the human resource professionals than before. As the electronic automation has been applied to a variety of HR practices, more are advocating for HR automation on the basis of improved productivity, which has been proven valid (Kovach & Cathcart, 1999). With increasing emphasis on human resource management in corporations, the human resource department is urged to perform additional roles, implementing a variety of tasks and processing massive amount of data. All of these happen while information technology 2.

(17) manages to change employees’ life and facilitates organizational changes. Once technology changes the organization, the structure and the people in it will have to change as well. This makes understanding the antecedents and consequences of e-HR adoption an important issue. The possible competence change following technology-enabled organizational change is also crucial for the HR professionals to detect in order to reinforce the key successful factors that lead to positive outcomes.. Problem Statement E-HR refers to HR transactions using the internet along with other technologies (Lengnick-Hall & Moritz, 2003; Panayotopoulou et al., 2007). Strohmeier and Kabst (2009) theorized three potential advantages of e-HR adoption – (1) automation of routine asks, which promises advantages in costs, time, and quality of HR processes, (2) information in planning and control, which enables a more strategic orientation of HRM, and (3) collaboration between HR and other stakeholders, which leads to more innovative ways of organizing HRM. Many scholars also agreed that e-HR leads to considerable organizational changes and therefore should be regarded as an important strategic initiative in the HR field (Lengnick-Hall & Moritz, 2003; Lepak & Snell, 1998). However, whether e-HR actually yields these potential advantages or not is an open question to be answered empirically. Empirical and anecdotal evidences have shown that firms adopt e-HR to a varying degree (Mishra & Akman, 2010; Panayotopoulou, Galanaki, & Papalexandris, 2010; Panayotopoulou et al., 2007; Strohmeier & Kabst, 2009). Attempts to understand the factors of adoption thus become a popular research interest among HR and IT academics. However, as Strohmeier and Kabst (2009) pointed out the few findings on factors of e-HR system adoption are rather scattered and inconsistent; the only consistent determinant of adoption is the organizational size (Ball, 2001; Thompson S.H. Teo, Lim, & Fedric, 2007). Furthermore, 3.

(18) some literatures have investigated the outcomes of e-HR consequences (Leidner, Preston, & Chen, 2010; Strohmeier, 2007), such as individual consequences (Voermans & Veldhoven, 2007), operational consequences, relational consequences and transformational consequences. Despite the great volume of theoretical foundations on the technological influence on HRM, little empirical evidence has suggested to link the e-HR adoption antecedents with the e-HR adoption outcomes. As a result, the necessity to empirically examine the antecedents of e-HR adoption and link the potential e-HR adoption outcome is thus generated. Furthermore, scholars from the field of contextualism argue that e-HR application is exposed to cross-national differences, as in many HR activities (Brewster, Mayrhofer, & Morley, 2004; Strohmeier & Kabst, 2009). Under the influence of globalization, e-HR systems development in Taiwan is interesting, relevant and timely. First, the developing countries in Asia can refer Taiwan as an indicator to forecast the technological advancement upcoming. Second, the technological influence on the workers in non-western culture is also noticeable since Taiwan has a great reputation for information technology design and manufacturing. Third, as a non-western culture, different language and cultural usage in the e-HR adoption might cause other effects. While both researchers and practitioners have argued that firms should adopt IT innovations to alleviate administrative burdens of the HR department (Kovach & Cathcart, 1999), some firms lag behind in adopting e-HR innovations. The exploration of the factors causing the variance of the e-HR application remains an important phenomenon of interest. Still, there is a lack of theory-driven empirical research that systematically investigates the factors that possibly influence a company’s strategic choice to adopt e-HR and the influence of e-HR on firm performance. This study attempts to bridge the existing gap by using role expectation theory and task complexity theory to explain the e-HR adoption phenomenon and 4.

(19) the possible linkage with HR professional’s outcome assessment. Since HR professionals facilitate and use the e-HR systems, they are expected to be the best source to understand the process and rationale for examining e-HR adoption antecedents and outcomes. This study hence chose representatives from companies as the source of data to examine potential association in departmental level.. Objectives of Study The study adopted HR role complexity and task complexity as the antecedents of e-HR practices. Also, the changes in HR’s competence and the shift to strategic focus are to be addressed as the possible outcomes of e-HR practices. Therefore, with the purpose of understanding the adoption of e-HR practices and its antecedents and consequences, three research objectives are listed as follows: 1) Empirically test HR departmental strategic focus and competence as the departmental level outcome of e-HR practice. 2) Empirically test role complexity and task complexity as the antecedents of e-HR adoption. 3) Empirically test IT capability as the moderator of the relationship between the antecedents and e-HR adoption. The study hopes to contribute to e-HR workplace application. HR professionals, as one of the major direct stakeholders, can be a great source to collect the data from. Therefore, the main source to collect the variables associated with the e-HR application lies greatly in the HR professional. The research further analyzes the relevant factors and variables once the data collection complete.. 5.

(20) Research Questions Derived from the purposes stated above, the research questions are hence addressed to investigate and analyze e-HR application usage and its antecedents and possible outcomes in departmental level. Though many scholars have addressed the importance for human resource professionals to adopt electronic human resource systems for better strategic focus (Brockbank, 1999; Lengnick-Hall & Moritz, 2003; Panayotopoulou et al., 2007; Ulrich, 1997), some companies have not applied extensive e-HR practices yet. However, limited literature has shed light on the phenomenon. For human resource professionals, information technology will assist in reducing the time devoted to routine work and thus will be able to gain better recognition by focusing more on the company’s competitive advantage. Therefore, the researcher intended to fill the gap on the antecedents and outcomes of the e-HR application by analyzing the relationship in departmental level. In order to understand the relationship among the complexity of HR role expectation, task complexity, IT capability, the usage of e-HR practices and departmental outcomes, the following questions are investigated. 1. Does complexity of role expectation of HR department predict the usage of e-HR practices? 2. Does task complexity of HR department predict the usage of e-HR practices? 3. Does IT capability affect the relationship between complexity of HR role expectation and the usage of e-HR practices, as well as that between task complexity and the usage of e-HR practices? 4. Does the usage of e-HR practices contribute to HR departmental strategic focus? 5. Does the usage of e-HR practices contribute to HR departmental competence?. 6.

(21) Limitation and Delimitation First of all, the data collection is delimited to HR practitioners working in different companies in Taiwan as the source to gather data and later analyze the potential relationships among variables. Therefore, the non-human resource professional shall be excluded from the survey and shall not be the research subject in the research. Second, the research intended to study the relationships among complexity of HR role expectation, task complexity, IT capability, the usage of e-HR practices and HR departmental outcomes. Third, the research aims to study the variables using the concept of the electronic human resource application. Therefore, the other factors, such as the non-electronic human resource efficiency or possible outcomes, shall not be considered in the research framework. Due to the accessibility of our sample, multi-source data collection was used for the researcher to obtain response. Method such as sending requests through HR forums in the internet or BBS, requesting to fill out the questionnaire in campus recruitment activities, distributing the questionnaire through networking and collecting questionnaires from in-service master program were adopted. As a result, the research did not use the random sampling technique and thus representativeness of the research sample is a limitation in the research.. 7.

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(23) CHAPTER II LITERATURE REVIEW Electronic Human Resource Practices E-HR refers to conducting human resources related business transactions electronically and specifically on the internet (Lengnick-Hall & Moritz, 2003). Bell et al. (2006) posited that an e-HR system “allows managers to timely access information and data for analyses and to make decisions. Johnson and Gueuta (2011) in Society for Human Resource Management practice series for human resource professionals urges that human resource shall evolve into a more technology-based profession since the technology can help human resource practitioners with the following advantages: reducing administrative burdens and streamlining the administrative processes, lowering HR costs spent on administration and compliance, competing effectively for talents from the world, improving accessibility to employees and managers in organization, providing timely information for decision makers and enabling HR professionals to transform themselves into a more strategy-focused mindset in business. The issue of HR innovative adoption has long been a research interest in the academic society. The literature can be traced to Jenkins and Lloyd (1985) who elaborated on the influence of corporate philosophy and strategy on the use of HR information systems. Wolfe (1995) who attempted to describe and define HRM innovations (HRMIs) developed a model of HRMI implementation after reviewing three studies of HRMI implementation. Lin (1997) devised a study to examine the factors that ensure successful HR information system (HRIS) implementation in Taiwan. These factors included top management support, support of information system (IS) department, involvement of human resource leaders, support of HR staff, level of computer knowledge of the HR staff, and HRIS training. The interest continues 9.

(24) in current day with many new factors explored. For example, Panayotopoulou et al. (2007) studied E-HR adoption and the role of HRM in Greece focusing on strategy, process and HRM issues. The study concluded that Greece lagged behind other European countries in e-HR adoption. Strohmeier and Kabst (2009) conducted a large-scale sample-based evaluation of cross-national influence factors that drive organizational adoption of e-HRM in Europe, which uncovered size, work organization, and configuration of HRM to be the major general determinants of e-HRM adoption. Strohmeier and Kabst (2009) also found major cross-national differences in e-HRM adoption. A later research conducted by Panayotopoulou et al. (2010) introduced national background of the firm as a relevant factor in the adoption of electronic systems in HRM. Using data from 13 European countries, they found that the adoption of e-HRM is region-specific and affected by multiple factors. They also supported the existence of two distinct sets of HRM technological systems, that is, back-end and front-end ones. Several studies in 2010 continued the international theme. Wickramasinghe (2010) conducted a study on employee perceptions towards web-based human resource management systems in Sri Lanka. The research surveyed 30 firms in the service and manufacturing sectors with web-based HRM systems as a stand-alone automation serving employees' HRM needs. The findings suggested that system usage is high and user satisfaction is moderate. The level of complexity of the system is moderate and it significantly correlates with system usage. If the operation system is relatively new, the users were likely to be satisfied with the system. Further, users did not perceive web-based electronic HRM system as a method of shifting administrative responsibilities of HRM activities to them. Mishra and Akman (2010) conducted a survey in Turkey among 106 IT managers and professionals from various sectors which shows that IT is used extensively in the organizations to perform HRM functions in 10.

(25) Turkey's dynamic economy. The results also indicated that, while IT has an impact on all sectors in terms of HRM to certain extent, the types of IT used vary significantly between recruitment, maintenance, and development tasks. However, the empirical results here reveal that these organizations are not applying these technologies systematically and maturely in the performance of HRM functions. A few studies have devoted their efforts to building a more comprehensive framework or an integrated model of the factors of HR innovation adoption. Lippert and Michael Swiercz (2005) attempted to model the relationship between human resource information systems (HRIS) and technology trust using organizational, technological, and user factors to generate a set of testable propositions. Eleven propositions were offered to suggest that organizational trust, pooled interdependence, organizational community, organizational culture, technology adoption, technology utility, technology usability, socialization, sensitivity to privacy, and predisposition to trust influence an individual's level of trust in the HRIS technology (technology trust) and ultimately the success of an HRIS implementation process. Although e-HR was not the specific subject of this study, Lai (2008) conducted a related study on the information system strategies of MNC affiliates using the technologyorganization- environment model as the organizing framework. The results indicated that IT maturity, parent resource dependency, cultural distance, restrictive regulations, and local competition are significant determinants of global information system (GIS) strategy. The study also found that the integration- responsiveness model can be applied to explain GIS strategies and their implementation. Leidner et al. (2010) developed and tested an integrated model that seeks to understand why certain hospitals are IT innovators. Using IT innovation theory as their theoretical 11.

(26) foundation, they examine three antecedents, including the chief information officer (CIO) strategic leadership, the top management team's (TMT) attitude toward IT, and the hospital's climate. Further, they examine the influence of IT innovation on the impact of IT within the hospital and the influence on the hospital's financial performance. The research model was tested using both survey and archival data from 70 matched pairs of hospital CIOs and executives. The results suggest that the CIO strategic leadership and the TMT's attitude toward IT are key factors that influence IT innovation; however, the influence of a hospital's climate on organizational IT innovation is contingent upon the CIO's level of strategic leadership. The results also suggest that hospitals that are IT innovators can generate greater impact from IT, which in turn results in greater performance for the hospital. Martin and Reddington (2010) developed and partially tested a model of e-human resources (e-HR) focusing on the relationship between HR strategy, e-HR goals and architectures, and positive and negative e-HR outcomes. They proposed many moderators of this relationship, including the organization and resources of the HR function, the absorptive capacity of HR, the skills and preferred styles of HR professionals, the levels of technology acceptance among employees and line managers and the models of change used in implementing e-HR programs. They tested certain features of this model using data from a case study of a leading international oil field services provider. These data provided a partial confirmation of the model's validity but showed the need for a more dynamic understanding of the links between e-HR variables and the importance of context in explaining differences between line managers' acceptance of e-HR. Noe, Hollenbeck, Gerhart, and Wright (2003) point out that the human resource management included the function that would influence the employee behavior, attitude, performance policy, application and the systems. Human resource function include analysis 12.

(27) and design for jobs, determine the demand for human resource (human resource planning), attracting high-potential employee (recruiting), choose the right employees (selection), teaching the employees how to perform the current jobs and for future jobs (training and development), giving the employees the paychecks (compensation), evaluating the employees’ performance (performance management) and creating a positive job environment (employee relationship). The e-HR application, therefore, is based on actual human resource tasks. As mentioned earlier, the usage of E-HR system can bring about some benefits. The benefits of the E-HR practices are organized in HR functional categorization. The benefits of e-recruiting are listed in Table 2. 1. Table 2. 1. Benefits of E-recruiting Benefits of E-recruiting. Citations. Reaching large numbers of qualified applicants Reducing recruitment cost Decreasing cycle time Streamlining burdensome administrative processes. Cappelli, 2001; Galanaki, 2002 Cappelli, 2001; Johnson & Gueuta, 2011 Cober, Brown, Levy, Cober, & Keeping, 2003; Robert & Janice, 2003 Johnson & Gueuta, 2011; Stone, Lukaszewski, & Isenhour., 2005. Enabling the organization to evaluate the success of its recruitment strategy Better internal advancement opportunities to enhance employee satisfaction and commitment levels Establish brand identities. 13. Stone et al., 2005 Stone et al., 2005. Allen, Mahto, & Otondo, 2007; Johnson & Gueuta, 2011; Stone et al., 2005.

(28) Potential benefits of e-learning discussed by scholars (Burgess & Russell, 2003; Johnson & Gueuta, 2011; José, Juan, & González, 2004; Kirsty & Anna, 2004; Salas, DeRouin, & Littrell, 2005; Steve et al., 2001) are listed in Table 2. 2. Table 2. 2. Benefits of E-learning Benefits of E-learning        . Increasing employee flexibility from long distance learning Cost saving The ability to train employees efficiently and quickly Using the most knowledgeable instructors for high-quality training Providing timely updates to training material as necessary Increasing the responsibility trainees have for learning Adding trainees or instructors without much supplementary cost Reducing the indirect costs of training (for example, costs associated with travel to training facilities, hotel accommodations for trainees, lost work time for employees attending training) According to Cardy and Miller (2005), potential benefits of e-performance management,. when appraisal satisfaction is well maintained, may include: Table 2. 3. Benefits of E-performance Benefits of E-performance .   . Computerized performance monitoring permits greater span of control because it facilitates accurate collection of performance data without requiring managers to spend significant time observing each individual worker’s actual job performance. Feedback is more clearly related to work output and less to superiors’ biased impressions Greater performance improvement, increasing productivity and enhancing competitiveness Improving appraisal satisfaction, thus helping organizations retain, motivate, and develop their employees 14.

(29) According to Dulebohn and Marler (2005), potential benefits of e-compensation are listed in Table 2. 4. Table 2. 4. Benefits of E-compensation Benefits of E-compensation . Increasing access to critical compensation information electronically on an as-needed basis. . Enabling round-the clock availability of meaningful compensation information to managers and employees Streamline cumbersome bureaucratic tasks through the introduction of workflow functionality and real-time information processing.. . According to Gueutal and Falbe (2005), potential benefits of HR portal and employee self-service are listed in Table 2. 5. Table 2. 5. Benefits of Employee Self Service Benefits of employee self service   . Data is available to employees 24/7 and 365 days per year. Managers have much easier access to information and are able to more rapidly and efficiently manage their staffs. Reducing the cost of call centers and HR specialists to handle HR services requests. With all the potential benefits, the human resource management professionals may urge. the organizations to utilize e-HR adoption to further facilitate organizational competitive advantages. Haines and Lafleur (2008) conducted a literature review on vendor packages and business solution packages to develop a comprehensive list of 78 e-HR application within 9 human resource functions: 1. HR audits and survey, 2. Employee benefits, 3. Compensation and rewards, 4. Health and safety, 5.Performance management, 6. HR planning and career development, 7.staffing, 8. Training and development, and 9. Employee relations. 15.

(30) Complexity of HR Role Expectation Role Expectation The behavior researchers have studied roles in different perspective. For example, sociological researchers are concerned with the individual expectation and the actual behavior changes; for psychological researchers, how the psychological changes of one’s perception and its perceived role expectation are emphasized. Gross, Mason, and McEachern (1958) defined the roles as the series of role expectation given by shareholders regarding specific position in organization. The shareholders might be the relevant supervisors, colleagues, subordinates, customers and some others. According to Sarbin and Allen (1968), role expectation is a cognitive concept, which includes beliefs, expectations, subjectivity and rights and obligation performed. Westwood (1967) also agree that the role expectation is cognitive concept, and further address the behaviors that a role shall perform. Above all the definitions, the roles are defined as the person perceived some expectations and the behavior that might be changed according to the norms or social codes. Role expectation indicates that people were assumed to perform certain behaviors in certain locations. If the role expectation is perceived in general norms, role stereotypes are hence formed. Some other scholars believe that role expectation include 1). the self-image of the role performer, and 2). the expectation from other.. 16.

(31) HR Role Evolution The HR role has gone through tremendous transition in the past decades with greater role expectations. Early in the 70s and 80s, human resource professionals were regarded as the personnel employees. The traditional view of human resource function lies in the administration. With environment changes, the personnel function cannot fully support organizational needs and therefore transform itself into a larger scope, human resource management department. Later, some scholars suggest that human resource management should elevate its importance from transactional activities to transformational activities (Ulrich, 1997). However, the evolution of human resource management urged its functions to become more dynamically interactive with the environment (Sherman, Bohlander, & Snell, 1996). Recruiting, selection, performance appraisal, training and development, and compensation are further included in human resource management systems. As a result, human resource management function can fully engage in the organizational strategy design and stimulate organizational performance. Consequently, human resource management is viewed as one of the important roles in organizations. The historical evolution of human resource management is summarized in Table 2. 6.. 17.

(32) Table 2. 6. Historical Evolution of HRM Period. Important historical changes. Pre-world war II (20th century to World War II). . Post-World War II (1945-1960). . Social issues era (1963-1980). . . Implication for HR professionals. Promotion of scientific management Maximize productivities and work Distribution.. . Record keeping is one of the important function without the technological automation. Trade unions power bargains for better work conditions.. . More administration tasks and record keeping Air Force Human Management Laboratory uses computer in human resource department Management information systems appears, but does not widely applied in HR department. . . . Cost effectiveness era (1980 to early 1990). . Technology advancement era (1990 to present). . .  . Prohibition of discriminatory practice Promote for employee health, safety and retirement benefits Decreasing cost of technology and increasing costs of employee compensation and benefits Growing of legitimate requirement People costs is majority in management budgets Business process reengineering became common and frequent Autonomy of work teams Outsourcing. .  . Cost justify the HRM function HR functional focus shifts to employee development and involvement. . Emergency of strategic human resource management (SHRM) Rightsizing of employee numbers, reducing layer of management and bureaucratic organizational structure. . Note. Adapted from Human resource information systems: basics, applications, and future directions, 7-11, by Kavanagh and Thite (2009) 18.

(33) HR Role Expectation Categorization Different scholars have categorized HR role from different perspectives. Storey (1992), after exploring the emerging impact of workplace change on personnel practices in UK, proposed the typology of human resource roles as: advisors, handmaidens, regulators and changemakers. Advisors are the counselor of the company, suggesting the future orientation of the company management. However, the role does not involve in the management in the company. The handmaidens are only involved in the operational work. The regulators involve in coordination and response with the departments, and involve no strategic decisions. The changemakers are proactively involved in the management of the departments, and participate in the strategic decisions. Kesler (1995), on the other hand, provided other roles that HR shall participate in organization: partnering role and transactional role. Partnering roles shall perform three functions: catalytic influence, diagnostic assessment and innovating processes and structures; transactional role shall provide administrative services, assurance of standards and problem solving. Schuler and Jackson (2001) indicated that the six main roles human resource play in the leading companies are: partnership, change facilitator, strategy implementer, strategy formulator, innovator and collaborator. Wright, McMahan, Snell, and Gerhart (2001) borrowed the concepts of Ulrich (1997) and proposed five roles: strategic partner, tailoring practices, providing HR services, providing change consulting and developing organization skills. The role of strategic partner role emphasizes the influence and participation made by the employees. The role of tailoring practices focus on the strategy execution. The role of providing HR service role includes HR serviced delivered to employees. The role of providing change consulting indicates that human resource professionals are responsible in effective management of changes in 19.

(34) organization. The role of developing organization skills and capabilities highlights the human resource professionals’ responsibility in identifying and developing the core competencies or capabilities critical to organizations. Ulrich (1997) proposed an integrated human resource model, using two axes representing human resource professionals’ focus and activities. Human resource professionals can have short-term/operational focus or have long-term/strategic focus. Moreover, the human resource professionals can become people oriented or process oriented. Combining the two axes, Ulrich (1997) proposed four principal human resource roles: strategic partner, change agent, employee champion and administrative expert. The strategic expert helps the organization through combining the human resource practice with the organizational strategy. In other words, the role of the human resource professionals is to deliver organizational strategy, accomplish business objectives and produce desired outcome. In order to attain the goal, the primary action for human resource professionals is to set priorities based on the organizational strategies. The change agent, on the other hand, is to deliver the necessary transformation that the organization desires. The administrative expert helps to provide professional services to internal customers, including chief executive officers, line managers and regular employees. The last but not the least, the role of employee champion helps to retain the employees, to build excellent employee benefits and to take care of the employees. The HR role model of Dave Ulrich (1997) is organized in Figure 2. 1.. 20.

(35) Figure 2. 1. HR roles theorized by Ulrich The summary of HR roles theorized by different scholars are organized in Table 2. 7. Table 2. 7. Different Dimensions of Human Resource Roles Author Storey (1992) Kesler (1995). Schuler and Jackson (2001). Source. Dimensions. Developments in the Management of Human Resources A model and process for redesigning the HRM role, competencies, and work in a major multi-national corporation HR issues and activities in mergers and acquisitions. advisors, handmaidens, regulators and changemakers partnering role and transactional role. Wright et al (2001). Comparing line and HR executives' perceptions of HR effectiveness: Services, roles, and contributions. Ulrich (1997). Human Resource Champions: the Next Agenda for Adding Value and Delivering Results 21. partnership, change facilitator, strategy implementer, strategy formulator, innovator and collaborator strategic partner, tailoring practices, providing HR services, providing change consulting and developing organization skills strategic partner, change agent, employee champion and administrative expert.

(36) Complexity of Role Expectation and E-HR Practices As mentioned earlier in this chapter, Ulrich (1997) conceptualized that the business partner is the fulfillment of multiple human resource roles, such as strategic partner, administrative expert, employee champion and change agent. Moreover, Ulrich advocated that all four roles are essential to the overall partnership of the human resource as an entire ensemble to the business operation, and the strategic orientation of HR being a business partner often contributes to a high-performance culture. According to Jackson and Harris (2003), high-performance culture is more prone to accept change, and consequently electronic tools adoption. Moreover, a study in Greece also indicates the practitioners agree with the statement that the e-HR adoption have a beneficial impact on achieving organizational strategic goals such as company image, goal alignment and cost reduction (Panayotopoulou et al., 2007). In order to seek for greater performance to cope with the complexity of roles expectations, the human resource professionals would turn to tools that could help to fulfill the role expectations. Thus, Hypothesis 1: Complexity of HR role expectation imposes a positive influence on the departmental usage of e-HR practices.. 22.

(37) Task Complexity The nature of the task dimension has long been a topic of interest in group research. However, scholars do not agree on a single method for determining the complexity of a task or that of a group of tasks (Campbell, 1988; Wood, 1986). Daft and Macintosh (1981) analyze task complexity from four dimensions: task variety, task analyzability, amount of information, and equivocality of information. Task variety refers to the frequency of unexpected and novel events that occur in the process of task completion. Task analyzability refers to the degree to which individuals must spend time to respond to problems that arise and introduce uncertainty for the participants in the task performing experience. Amount of information is the volume or quantity of data about organizational activities that is gathered and interpreted by organizational participants. Equivocality of information is the multiplicity of meaning conveyed by information about organizational activities. Daft and Macintosh (1981) argue that the complexity is a function of amount and equivocality of information processed in completing the task. They believe the amount of information would lead to increase in task variety and analyzability, while activities that are not analyzable tend to have more equivocal information. Campbell (1988) has organized the definition across different fields and synthesized into the following three job characteristics: 1). primarily psychological experiences, 2). person-task interaction, and 3). subject task characteristics. The primarily psychological experience emphasizes the task psychological dimensions that the task doers possibly perceive such as task significance, feeling of variety, feedback and autonomy (Campbell, 1988; Ganster, 1980; Taylor, 1981). Person-task interaction portrays that the perceived task complexity is more or less relative to task doers’ capability (Campbell, 1988; March & Simon, 1958). In other words, 23.

(38) the perceived task complexity is associated to the task doers’ own capability. Subjective task characteristics have been identified with three subjective qualities that make contribution for subjective task complexity: 1). complex tasks are characterized for its unknown alternatives, 2). complex tasks are characterized by uncertain alternatives and inexact means-end combination, 3). complex tasks often can be divided into smaller subtasks. Similarly, Campbell (1988) also proposed that one of the attributes of task complexity rises from high cognitive demands, which arise from the nature of task but not from the characteristics of the individual. According to Perrow (1967), two dimensions were identified regarding to organizational technology: number of exception and analyzability. Later, Withey, Daft and Cooper (1983) developed a scale, using Perrow’s dimensions of work unit technology. The developed scale is widely used with proven validity (Keller, 1994; Mangos & Steele-Johnson, 2001; Rice, 1992). Although Campbell (1988) has divided task complexity into objective task complexity and subjective complexity, the study do not distinguish the two task complexity. However, the nature of the respondents determines that the responded task complexity would be close to subjective complexity, which has been proven to affect the performance (Mangos & Steele-Johnson, 2001). Task Complexity and Usage of E-HR Practices Based on the analysis of task variety and task analyzability, Daft and Lengel (1986) developed a four-quadrant model that delineates the relationship of department technology with structure and information required for task accomplishment, as depicted in Figure 2.2.. 24.

(39) Figure 2. 2. Relationship of department technology with structure and information required for task accomplishment As e-HR can be designed to handle all four kinds of technology (craft, nonroutine, routine, and engineering technology) as defined by Daft and Lengel (1986), it is plausible that HR staffs will adopt more e-HR practices when they are asked to perform an assortment of tasks from all four quadrants. The perceived task complexity thus may contribute to the urge to adopt the e-HR practices. Thus, Hypothesis 2: Complexity of tasks performed by HR staff has a positive influence on the staff’s usage of e-HR practices.. 25.

(40) IT Capability A number of varying definitions have emerged concerning the IT capability. Bharadwaj (2000) have proposed that the IT capability can be defined as “a firm’s ability to mobilize and deploy IT-based resources in combination or co-present with other resources and capabilities”. Bharadwaj (2000) further proposed that the IT-based resources can be divided into three categories: IT infrastructure, human IT, and IT-enabled intangibles. Correspondently, IT capability is considered to be “the extent to which a firm is knowledgeable about and effectively utilizes IT to information within the firm (Tippins & Sohi, 2003). That is, the IT capability refers to how the information is processed and managed in the IT department. Likewise, Tippins and Sohi (2003) classify IT capabilities into three dimensions as well: IT knowledge, IT operations, and IT objects. Ross, Beath, and Goodhue (1996) have set the definition for IT capability as the “the ability to control IT-related costs, deliver systems when needed, and affect business objectives through IT implementations”. They proposed that the three IT assets as the dimensions to measure IT capability: IT human asset, IT technology asset and IT relationship asset to investigate the strategic merits contributed by IT construction. Table 2. 8. Different Dimensions of IT Capability Author Bharadwaj (2000). Tippins and Sohi (2003) Ross et al. (1996). Source. Dimensions. A resource-based perspective on information technology capability and firm performance: An empirical investigation IT competence and firm performance: Is organizational learning a missing link? Develop long-term competitiveness through IT assets 26. IT infrastructure, human IT, and IT-enabled intangibles. IT knowledge, IT operations, and IT objects IT human asset, IT technology asset and IT relationship.

(41) To synthesize the definition mentioned above, the IT capability means the abilities within a firm to manage information technological related abilities, such as assets, competencies, knowledge, processes and the human relationship that spur the company to acquire, deploy and manage the services and products provided by IT which helps to shape innovation and business strategies (Feeny & Willcocks, 1998). Task-technology fit theory holds that IT is more likely to have a positive impact on individual performance and be used if the capabilities of the IT match the tasks that the user must perform (Goodhue & Thompson, 1995). Measures of task-technology fit may include quality, locatability, authorization, compatibility, ease of use/training, production timeliness, systems reliability, and relationship with users.. IT capability, HR Role Expectation and Task Complexity When the technology meets the user needs and features that support user’s requirement to perform tasks, the performance impacts will occur (Cane & McCarthy, 2009). In agreement with the statement, task-technology fit theory holds that IT is more likely to have a positive impact on individual performance and be used if the capabilities of the IT match the tasks that the user must perform (Goodhue & Thompson, 1995). That is, seminal work on technology has proven positive effects on task performance (Gebauer, Shaw, & Gribbins, 2010) and end-user performance (Goodhue, 1995; Goodhue & Thompson, 1995; Teo & Men, 2008). In order to seek better performance, the human resource professionals are likely to pursue solutions that could be used to increase their performance. Task-technology fit measures, in conjunction with utilization, can be significant predictors of improved job effectiveness that is attributable to the use of the system under investigation. In agreement with IT’s ability to maintain relationship with users in 27.

(42) task-technology fit theory, Panayotopoulou et al. (2007) also point out that collaboration of HRM and IT and investment in IT training have been identified as critical success factors in e-HR adoption and use. These factors can ensure successful integration of technology into HR process aiming at responding to the need for quality HRM services. Therefore, this research hypothesizes IT capability as a significant moderator of the relationship between HR staff and their usage of e-HR, in that when IT capability is high, the relationship is stronger between complexity of HR roles or tasks and the usage of e-HR. Thus, Hypothesis 3: IT capability positively moderates the relationship between the complexity of role expectation on HR staff and staff’s usage of e-HR practices. Hypothesis 4: IT capability positively moderates the relationship between the complexity of tasks performed by HR staff and staff’s usage of e-HR practices.. 28.

(43) Strategic Focus As noted in the previous definition, the role for human resource management professionals to become strategic partners is promoted and prospered in the last decade (Ulrich, 1997; Ulrich & Brockbank, 2005; Ulrich & Conner, 1996). This trend continues in recent years, which urged the human resource professionals to become even more strategic focused or business aligned (Becker & Huselid, 2006; Fairbairn, 2005; Ulrich, Younger, & Brockbank, 2008). As a strategic partner, the human resource professionals can lead dramatic transformation that contribute to significant impact on a company’s operations and performance (Fairbairn, 2005) One of the ways to implement the strategic focus is to adopt new structure of the human resource organization which cooperates with the structure and strategies of the business (Ulrich et al., 2008). Human resource professional has benefited from the promotion of human resource as a strategic partner (Wright; 2008). The broader scope of human resource as strategic partners has encouraged the implementation of human resource information systems in order to complete HR tasks of different functions more efficiently (Wright; 2008). Scholars indicate that the time and resources saved from administrative work will allow human resource professionals to focus more on strategy implementation. Therefore, the time and resources spent on strategy relevant issues can be an indicator to measure human resource professionals’ strategic focus.. Strategic Focus and E-HR Usage Human resource practitioners urge that human resource professionals shall be a more technology-based profession since technology enables human resource professionals to transform into a more strategic role in business (Johnson & Gueuta, 2011). As technology 29.

(44) advancement can free the human resource professionals from routine tasks, the chance is greater for human resource professionals to perform as strategic partners (Brockbank, 1999; Ulrich, 1997). Ensher, Nielson, and Grant-Vallone (2002, p. 238) argued that E-HR can bring about an “increased emphasis on HR as a strategic business partner whose primary challenge is to recruit, develop and retain talented employees for the organizations”. Panayotopoulou et al. (2007) agreed with this argument that the shift from traditional HRM to e-HR enables HR employees to focus on more strategic, value-added activities. They believe that the time and resources saved from less administrative and paperwork will allow the HR specialists to devote their effort to other more strategic functions of the profession. Lengnick-Hall and Moritz (2003) believe e-HR system can be beneficial to HR in strategy participation and strategy design. The human resource function in the organization can play a more consultative role to the line managers, and take proactive approach to participate in the strategy formulation and strategy implementation (Lengnick-Hall & Moritz, 2003). Moreover, the decision support tools are the key for human resource professionals to provide essential information that can be used to help with complicated benefits issues, and to drive strategies (Lengnick-Hall & Moritz, 2003). Transformational consequences concern the overall changes of the HRM function that centrally aim at the role the HRM plays in company performance and strategy support (Barney & Wright, 1998). Thus, Hypothesis 5: The increase of e-HR practice usage will positively contribute to HR staff’s strategic focus.. 30.

(45) Human Resource Competencies The competence is first brought up by the Harvard professor, McClelland (1973) in the early 1970. He criticizes the phenomenon that the higher education generally screen the students based on the intelligence test. He further proposes that the main screening criteria shall be the factors that affect the learning performance, competence, such as attitude, perception and personal characteristics instead of purely on the intelligence (McClelland, 1973). McClelland (1973) develops Job Competence Assessment based on evaluating the high-performers to find the key successful abilities. Spencer and Spencer (1993) indicate that the competency is the underlying characteristics of a person. The basic attribution is the deepest and unchangeable part of the personal characteristics. The competence is associated with the job or position that a person performs; the competencies can be further predicted to the response and the influence to the behavior and performance. Spencer and Spencer categorize the competencies into extrinsic and intrinsic (Spencer & Spencer, 1993). The extrinsic attributes include knowledge and skills. The intrinsic attributes include motivation, self-concept and personal characteristics. Ulrich, Brockbank, Yeung, and Lake (1995) and Quinn, Faerman, Thompson, and McGrath (1990) regard that competence is work-related knowledge, skills and ability. According to their definition, competence does not include the intrinsic attributes. From human resource development perspective, intrinsic attributes, such as attitude or personality, is relatively hard to change or acquire by training or learning in organization. Therefore, the definition for competence is inclined to adopt the definition in Ulrich et al. (1995) and Quinn et al. (1990). Therefore, the competence shall be the part that can be continuously grow and intensify by training and development, apply to workplace and increase work performance. Spencer and Spencer (1993) indicate in the “Competence at work” that the employees in different positions shall possess with different competencies. The competencies for 31.

(46) executives shall include strategic thinking, change leadership, relational management; the competencies for managers shall include flexibility, change execution, internal enterprise innovation, interpersonal understanding, empowerment, team building; the general employee shall include flexibility, information searching, learning capability, motivation to success, work under time pressure, cooperation and customer orientation. Conner and Wirtenberg (1993) define the human resource professional competencies as the following: the transformation of effective human resource work and the professional and organizational performance. The transformation of the human resource work shall include the ability to understand the employee demand, innovation, strategy ability, team work, result orientation. The professional and organization performance include the ability to share organizational profit, the customer orientation, the value-added business partner, question solving, creative and strategic human resource management ability, altering and coping with organizational culture, the ability to deal with emergency, supporting and developing global organization. Yeung and Broockbank (1994) conclude the four competencies that human resource management shall possess through the deep interview with fifty high-level managers. The four competencies include expertise at business function and human resource management, change management and credibility. Ulrich and his colleagues (1995) consider that the human resource professional competencies can be divided into three categories: business knowledge, field expertise and change management. The business knowledge includes the strategic capability, financial capability, technical capability and organizational capability. The field expertise includes the functional knowledge and ability in human resources, such as recruiting, selection, training and development, performance appraisals, compensation and benefits, organizational design and communication. The change management includes problem solving skills, influence, 32.

(47) innovation and relationship building. Warren (1995) proposes the Northern America competence model, indicating the core competencies shall be included in America human resource professionals: the enterprises competencies, the human resource professional competencies, and change management competencies. Lawson and Limbrick (1996) construct strategy-orientated higher level human resource professional benchmark competence model through telephone interview and questionnaire survey, and result in the following competences: goal action orientation, HR technical proficiency, functional and organizational leadership, influence management and business knowledge. Unlike the traditional research, Yeung (1996) reports high-performance human resource competencies clusters based on practical experience and empirical evidence from an interview. The three competence clusters include goal and action management abilities cluster, interpersonal/people management cluster and analytic reasoning or cognitive cluster. The information of different dimensions of human resource competences is organized in Table 2. 9. Table 2. 9. Different Dimensions of Human Resource Competences Author. Source. Dimensions. Spencer and Spencer (1993). Competence at. Walker (1992). Human Resource Strategy. Conner and. Managing the transformation of human. Work. strategic thinking, change leadership, relational management human resource managerial system, the information system and company goal and change management the transformation of (Continued). 33.

(48) Table 2. 9. (continued) Author. Source. Dimensions. Wirtenberg (1993). resources work. Yeung and Broockbank (1994). Labor cost, high value: Human Resource Function in Transformation. effective human resource work and the professional and organization performance expertise at business function and human resource management, change management and. Ulrich and his colleagues (1995). Human Resource Competencies: An Empirical Assessment. Wilhelm (1995). Response to "Reexamining Professional Certification in Human Resource Management," by Carolyn Wiley. Lawson and Limbrick (1996). Critical Competencies and Developmental Experiences for Top HR Executives. Yeung (1996). Competencies for HR professionals: An interview with Richard E. Boyatzis. credibility business knowledge, field expertise and change management the enterprises competencies, the human resource professional competencies, and change management competencies goal action orientation, HR technical proficiency, functional and organizational leadership, influence management and business knowledge goal and action management abilities cluster, interpersonal/people management cluster and analytic reasoning or cognitive cluster. 34.

(49) HR Competence and E-HR Adoption Although the literatures suggest that there is a link between e-HR and technological competence, Bell et al. (2006) could not get significant result on their interviews with HR practitioners. However, Bell et al. (2006) suggests that the end systems used by HR practitioners is a result of simplified platform. Therefore, the competence for technology expertise does not necessarily be demanding for HR professionals. On the contrary, Bell et al. (2006) proclaims that the HR professionals shall develop other competencies such as program management and partnering in addition to expertise in technology competence. Since e-HR entails increased involvement of employees and line managers in administering self-service HR activities, the general knowledge of HR practices are transferred to employees and line managers. Ulrich (2000) believes that this distributed knowledge will become a driving force for the HR professionals to consistently keep up with new developments in their field, in order to maintain their advisory-consulting role. Thus, Hypothesis 6: The increase of e-HR practice usage will positively contribute to HR competence.. 35.

(50) Partial Least Squares Structural Equation Modeling Structual equation modeling (SEM) is a statistical technique for simultaneously testing and estimating the causal relationships across all the independent and dependent constructs (Gefen, Straub, & Boudreau, 2000). Partial least squares SEM (PLS SEM) is a casual modeling appraoch which aims at maxmizing the explained variance of the dependent latent constructs (Hair, Ringle, & Sarstedt, 2011), different from the Covariance based SEM (CB SEM), which aims to reproduce the theoretical covariance matrix, instead of focusing on the explained variance. Although the CB SEM has been popular in these years, the PLS SEM is now getting more and more popular for the following traits: 1). The sample size rquired is less than the CB SEM (Hair et al., 2011). The suggested sample is ten times the number of items in the variable with the largest number of items (Barclay, Higgins, & Thompson, 1995; Chin, 1998). 2). It can accommodate simantanously the reflective and formative measures (Hair et al., 2011). Based on the current study, reflective and formative measurment are both used in the study. In addition, the organizational samples are more difficult to collect. Therefore, the research adopts the PLS SEM to be the statistical method to evaluate the research model. PLS testing Before tesing the structual model, the measurement shall go through several procedures to ensure the validity and reliability of the measurment. Measurment are categorized as reflective measurement and formative measurement in PLS. Reflective measurement testing Reflective measurement needs to ensure the internal consistency reliability, indicator reliability, convergent validity and discriminant validity (Hair et al., 2011). The internal consistency reliability refers to the composite reliability and it should be higher than .7 (in exploratory research, .6 or .7 acceptable). Indicator reliability is measured by the indictor 36.

(51) loading, which proves that each indicator is valid and measures how much the indicator’s variance is explained by the corresponding variable (Chin, 1998). In addition, convergent validity is measured through average variance extracted (AVE), which tries to measure the amount of variance that a variable retrieves from the indicators relative to the amount due to measurement error (Fornell & Larcker, 1981). The discriminant validity tests the component scores of each latent variable with the items in other component. If the cross loading only scores high in its construct but not in other constructs in the model, it can be inferred that the construct is sufficiently different from the other constructs. The other way to test the discriminant validity is to use the Fornell-Larcker criterion (Fornell & Larcker, 1981); that is, the AVE of each latent variable shall be greater than the other latent variable’s highest squared correlation with each of the other variables. The reflective constructs need to comply with these tests before actually being put through the model testing. The rules of thumb for evaluating reflective measurement are organized in Table 2.10. Table 2. 10. The Rules of Thumb for Evaluating Reflective Measurement Testing. Standard. 1. Internal consistency reliability CR>0.7 (Composite Reliability, CR) 2. Indicator reliability (Indicator Indicator loading >0.7 loading) 3. Convergent reliability (Average AVE>0.5 variance extracted, AVE) 4. Discriminant validity a. Fornell-Larcker criterion AVE > highest squared correlation with the other latent constructs b. Cross loading Indicator loading shall be higher than all of its cross loadings. 37.