臺灣電子化人力資源實務及組織績效:以競爭程度、策略領導、及資訊能力為前因

全文

(1)Electronic Human Resource Practices and Organization Outcomes in Taiwan: Competitive Tension, Strategic Leadership, and Information Technology Capability as Antecedents. by Hsueh-Chi Yen. 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: Chu-Chen Rosa Yeh, Ph.D.. National Taiwan Normal University Taipei, Taiwan July, 2013.

(2)

(3) ACKNOWLEDGEMENET At the beginning of my acknowledgement, I would like to express my deepest appreciation to my thesis advisor, Dr. Chu-Chen Rosa Yeh, for her valuable guidance and advices. She always encouraged me when I felt upset and gave me lots of constructive advices to help me learning from the process of writing thesis. In addition, I also want to thank my committee members, Dr. Tao and Dr. Chang, they gave me many useful comments and inspire me to work hard on my thesis. My appreciation also goes to other professors in IHRD, Dr. Tsai, Dr. Lai, Dr. Shih, and Dr. Lin, they gave me lots of learning opportunities and HR-related knowledge. Furthermore, my gratitude also goes to the assistant of IHRD, Sandra Chen, without her help I could not finish my thesis and other tasks so smoothly. Secondly, I want to thank my parents and my brothers, who always support me and believe in me, they gave me confidence to overcome all difficulties. Without them, I could not go this far, they are my motivation to moving forward. Then I would like to thank my relative, uncle Martin Yen, for helping me collect research data. Third, I would like to express my gratitude to the senior students, classmates, and first-year students in IHRD. The senior students gave me lots of help, especially Matthew Wei, who taught me statistical knowledge and gave me useful learning material, he taught me with patient and let me have better understanding on conducting research. For my dear classmates, I want to thank my fellow members, Carmen, Council, Fabee, Karen, and Rossana, we shared knowledge and had lots of fun together, and they gave me many opportunities to improve my English speaking. For Alan Yu and Cheryl Hsieh, thanks for giving me happy memories and working hard with me in Linkou. For Howard Tung and Kelly Hung, thank you for accompanying me at the final stage of writing thesis. For other Taiwanese students, Annie Hsu, Carol Chien, Karen Liu, Roy Huang, Ryan Wei, and Ximena.

(4) Chen, thanks for your encouragements and supports, you enriched my graduate school life! Then I want to thank junior students at IHRD, especially for Carol Lin and Shaun Hsiao, without them I could not send out the research questionnaire. I appreciated that Pou Chen Enterprise could offer me the internship opportunity in Vietnam, I learned human resource practices from my line manager, Oliver Chiang. I was thankful to meet Karen Wu, Kenny Chang, and all members in HR department, without their assistances and cares I could not finish my project and have an unforgettable memory. I also want to thank my intern partner, Gary Lo, for introducing me how to use the TEJ database. Last but not least, I would like to thank You-Sin Lin and his family, they always provided helps when I needed, and gave me lots of cares during the past two years. I’m so appreciate to have them in my life..

(5) ABSTRACT The research on electronic human resource (e-HR) systems has been extensively investigated, while the antecedents and consequences of e-HR adoption in a country are relatively unexplored. This research aims to study the usage of e-HR practices in Taiwan and detect. the. possible. antecedents. and. outcomes.. Applying. the. technology-organization-environment framework, this research selected competitive tension, strategic leadership, and IT capability as the antecedents, while HR efficiency, ROA, and EPS as organizational level outcomes of e-HR adoption. This study focused on companies listed in Taiwan Stock Exchange as the samples. Human resources professionals in those listed companies were the primary informants to provide data on strategic leadership, IT capability, e-HR practices and HR efficiency. These data were collected by implementing a census-approach with mail survey as the main instrument. For higher rate of responses, the questionnaires were also distributed at campus recruitment activities and to personal networks. A total of 204 responses were kept for data analysis after screening out invalid responses. Data on competitive tension, ROA and EPS of these 204 companies were retrieved from public sources. Partial least square (PLS) structural equation modeling (SEM) technique was used to examine the relationship of antecedents and outcome variables of e-HR practices. The result indicated that strategic leadership and IT capability positively affect the usage of e-HR practices, while competitive tension showed no effect. As for the outcomes, only EPS as the organizational outcome was supported. ROA was not affected by the use of e-HR practices. Contrary to the study hypothesis, e-HR practices showed a negative effect on HR efficiency as measured by employee to HR personnel ratio. Implications and suggestions for future research were discussed in the study.. Keywords: e-HR practices, TOE framework, competitive tension, strategic leadership, IT capability, financial outcome. I.

(6) II.

(7) TABLE OF CONTENTS Abstract ................................................................................................................... I Table of Contents .................................................................................................... III List of Tables ............................................................................................................................ V List of Figures ........................................................................................................................ VII. CHAPTER I INTRODUCTION ........................................................................ 1 Background of the Study ................................................................................................... 1 Problem Statement ............................................................................................................. 3 Research Purpose ............................................................................................................... 4 Research Questions ............................................................................................................ 4 Definition of Key Terms .................................................................................................... 6. CHAPTER II LITERATURE REVIEW ........................................................... 7 Technology-Organization-Environment Framework......................................................... 7 Electronic Human Resource Practices ............................................................................. 15 Organization Outcomes ................................................................................................... 18 Competitive Tension and Usage of e-HR Practices ......................................................... 23 Strategic Leadership and Usage of e-HR Practices ......................................................... 23 IT Capability and Usage of e-HR practices ..................................................................... 24 Usage of e-HR Practices and Organizational Outcomes ................................................. 25. CHAPTER III RESEARCH METHOD .......................................................... 27 Research Framework ....................................................................................................... 27 Research Hypotheses ....................................................................................................... 29 Research Procedure .......................................................................................................... 29 Research Design............................................................................................................... 30 Measurement .................................................................................................................... 36. CHAPTER IV DATA ANALYSIS AND RESULT ....................................... 53 Descriptive Statistics of e-HR Practices .......................................................................... 53 Correlations ...................................................................................................................... 60 PLS Model Testing .......................................................................................................... 62. CHAPTER V CONCLUSIONS AND DISCUSSION .................................... 69 Conclusions ...................................................................................................................... 69 Discussion ........................................................................................................................ 70 Research Implications ...................................................................................................... 72 Practical Implications....................................................................................................... 73 Research Limitations ....................................................................................................... 74 Future Research Suggestions ........................................................................................... 75 III.

(8) REFERENCES.................................................................................................... 76 APPENDIX A RESEARCH QUESTIONNAIRE.............................................. 82 APPENDIX B INDUSTRY SECTOR ............................................................... 92 APPENDIX C MEASUREMENT ...................................................................... 93 APPENDIX D EXPLORATORY FACTOR ANALYSIS ................................. 99. IV.

(9) LIST OF TABLES Table 2.1 Summary of researches based on TOE framework ................................................... 9 Table 2.2 Variables Used to Measure Financial Performance ................................................. 20 Table 3.1 Descriptive Information on the Respondents........................................................... 32 Table 3.2 Descriptive Information Regarding the Participating Companies ......................... 344 Table 3.3 Year of Implementing Integrated Software ........................................................... 355 Table 3.4 Range of HR Personnel Number and Employee Number of Companies ................ 40 Table 3.5 The Exploratory Factor Analysis for Strategic Leadership in SPSS ..................... 433 Table 3.6 The Overview of Factor Loading, Composite Reliability, t-value, and AVE for Strategic Leadership............................................................................................... 444 Table 3.7 The Overview of Composite Reliability, AVE and Discriminant Validity Test among All Variables .............................................................................................. 445 Table 3.8 The Cross Loading for All Variables ..................................................................... 455 Table 3.9 The Exploratory Factor Analysis of IT capability in SPSS ................................... 466 Table 3.10 The Overview of Factor Loading, Composite Reliability, t-value, and AVE for IT Capability ........................................................................................................ 477 Table 3.11 The Exploratory Factor Analysis of the Practices of e-HR in SPSS ................... 488 Table 3.12 The Overview of Factor Loading, Composite Reliability, t-value, and AVE for e-HR Practices ....................................................................................................... 50 Table 4.1 Descriptive Statistics of e-HR Practices- Training and Development ................... 544 Table 4.2 Descriptive Statistics of e-HR Practices- Performance Management ................... 566 Table 4.3 Descriptive Statistics of e-HR Practices- Human Resource Planning ................... 577 Table 4.4 Descriptive Statistics of e-HR Practices- Recruiting and Selection ...................... 588 Table 4.5 Descriptive Statistics of e-HR Practices- Employee Benefits ............................... 588 Table 4.6 Descriptive Statistics of e-HR Practices- Compensation and Rewards ................. 599 Table 4.7 Correlation Analysis Results ................................................................................... 61 Table 4.8 The Rules of Thumb for Structural Modeling Testing .......................................... 633 Table 4.9 Path Coefficients, Error, t-values and R square ..................................................... 634 Table 4.10 The Overview of Hypotheses Testing ................................................................. 677. V.

(10) VI.

(11) LIST OF FIGURES Figure 2.1 Technology, organization, and environment framework ......................................... 8 Figure 3.1 Research framework ............................................................................................. 288 Figure 3.2 Research procedure ................................................................................................ 30 Figure 4.1 Hypotheses testing with path coefficient and R square ........................................ 666. VII.

(12) VIII.

(13) CHAPTER I. INTRODUCTION. This chapter introduces the background, purpose of the study, and research questions of this study. The background focuses on describing the current business situation and the changing human resource practices due to the technology adoption, and interprets the finding of problem which is worth researching. The purpose of this study describes the significance of this study, and research questions of the study are addressed. Lastly, key terms are defined.. Background of the Study The rapid development and change of information technology (IT) has been influencing the way organizations are managed. The information revolution was seen as one of the prominent features in 21st century and leads to the extensive application of IT innovation in business (Panayotopoulou, Vakola, & Galanaki, 2007). The IT application also influenced the human resource department as well (Mishra & Akem, 2010). Lengnick-Hall and Mortiz (2003) suggested that information technology had a great impact on HR functions and gave HR professional enough time and capability to think strategically through the use of electronic or web-based human resource management system (e-HR) to facilitate organizational strategy. With the increasing emphasis on human resource in companies, the human resource department was urged to perform additional roles and yield better financial performance. Meanwhile, the information technology had been cited as one of the dominant driving forces that changed HR’s role from personnel administrator to strategic partner (Bell, Lee, & Yeung, 2006; Huub, Tanya, & Jan Kees, 2004). To satisfy every aspect of organization needs, the importance of electronic human resource information system adoption was mentioned to assist human resource professionals in fulfilling organizations’ strategic goals, for instance, 1.

(14) company reputation, goal alignment, and cost reductions (Panayotopoulou, et al., 2007). Later, some studies focused on the antecedents and consequences of adopting e-HR to figure out the premises and possible benefits of e-HR adoption with e-HR treated as a new technology to many companies. The adoption was discussed from individual context to organizational even national context. For instance, the technology-organization-environment framework was applied for discussing the process of a company adopting and implementing innovation technology (Tornatzky & Fleisher, 1990). In technological context, the IT infrastructure and supports were widely applied to detect the adoption of new technology. Meanwhile, the top management support in organizational context and perceived competitive tension in environmental context were also viewed as other important forces to implement innovation technology in a company. Moreover, general factors like company size and industry sector in national context, or contextual factors such as economic development had been used as the predictors to test the e-HR adoption (Strohmeier & Kabst, 2009). With more and more adoptions of e-HR, it was known that e-HR information systems can function at the organizational and the individual levels, and thus may also cause some dysfunctional outcomes for both levels (Stone, Stone-Romero, & Lukaszewski, 2006). Recently, many organizations sensed the benefits from adopting e-HR, and attempted to use e-HR systems for the advantages of decreasing HR personnel (Lengnick-Hall & Moritz, 2003) and cost reduction (Panayotopoulou, et al., 2007). Therefore, more and more scholars advocated that organizations should take adoption of e-HR into consideration (Panayotopoulou, et al., 2007; Strohmeier & Kabst, 2009). According to the above discussion, technology indeed changes how companies run their business and makes leaders face the challenge of emerging advanced technology tools. However, without leader’s awareness and foreseeable benefits after huge investments on the technology adoption, the e-HR systems could not be realized. Therefore, it is a pivotal issue 2.

(15) to understand the antecedents and consequences of the e-HR systems. In order to achieve positive outcomes, it is necessary to strengthen the key success factors of adopting innovation technology. Furthermore, HR professionals and top management leaders should recognize the significance to embrace new technology.. Problem Statement E-HR was defined as the application of information technology in building network and supporting HR department to perform at least two actors (Strohmeier, 2007) or referred to the use of internet along with other technologies to conduct human resource management transactions (Lengnick-Hall & Moritz, 2003). These definitions pointed out the core concept of e-HR which includes human resource and information technology. Thus there has been an increasing interest in understanding the factor of adoption among HR and IT academics. It has been shown that firms adopt e-HR to a varying degree (Mishra & Akman, 2010; Panayotopoulou et al., 2007; Strohmeier & Kabst, 2009) and yielded different consequences. Operational consequence was one of the common topics in current research, the efficiency and effectiveness related to macro-level consequences of e-HRM was included. However, Strohmeier (2007) pointed out that findings regarding the efficiency and effectiveness of e-HRM are limited and mixed. Although the automation of routine activities provided some help for productivity, it was still difficult to measure and balance the overall gains and losses of efficiency. In spite of many theoretical foundations on the technological influenced on HRM, few empirical studies were conducted to link the antecedents and consequences of e-HR adoption. In addition, those empirical researches were conducted in the Western world. Some scholars thus raised the cultural difference issues of e-HR like other HR activities (Strohmeier & Kabst, 2009). 3.

(16) With the trend of globalization, research on e-HR system in Taiwan is critical, becuase Taiwan is a non-western country that is famous for its high-tech and IT capability. Therefore, it generates the necessity to examine the antecedents and consequences of e-HR adoption empirically in Taiwan.. Research Purpose Previous literature posited that the factors of e-HR adoption were rather scattered and inconsistent (Strohmeier & Kabst, 2009), and past research rarely investigated the consequences of e-HR adoption. In order to provide more empirical evidence in our knowledge, this study applies the technology-organization-environment framework (TOE framework) to investigate technology adoption and possible organizational consequences in Taiwan. This study adopts an organizational approach to examine possible association in organization level. Thus, the purpose of this research is to delineate the relationship of selected antecedents and organizational outcomes of e-HR adoption in Taiwan. In addition, this research also attempts to benchmark knowledge for companies which already adopted e-HR systems or companies which still try to decide whether to adopt e-HR systems. Through the empirical research, this study will be able to provide evidences and explanations for the selected antecedents and consequences of e-HR adoption in organizations.. Research Questions Derived from the purposes addressed above, the research questions revolve around the factors that affect the usage of a firm’s e-HR and its possible outcomes in organization level. As it was mentioned, many scholars have pointed out the significance for human 4.

(17) resources to adopt electronic human resource systems for more strategic focus (Brockbank, 1999; Lengnick-Hall & Moritz, 2003; Panayotopoulou, Vakola, & Galanaki, 2007; Ulrich, 1997). Moreover, some literature has discussed how organizations that experience more competitive tension will feel more threatened and begin to apply advanced technologies. The style of leadership is also a key factor that shapes a company’s internal environment (Cannella, Finkelstein, & Hambrick, 2009). Under the influence of a strong leader, employees may feel obligated to use e-HR systems and increase the usage of company’s e-HR. However, some companies still have not implemented intensive e-HR practice, and limited literature has revealed on the phenomenon. For organizations, information technology could help to save time and budget, and have a best number of HR staff (Strohmeier, 2007). In order to understand the relationship among the competitive tension, strategic leadership, IT capability, usage of e-HR and organization outcomes, the following questions are investigated. 1.. What is the relationship between competitive tension and the usage of a firm’s e-HR practices?. 2.. What is the relationship between strategic leadership and the usage of a firm’s e-HR practices?. 3.. What is the relationship between IT capability and the usage of a firm’s e-HR practices?. 4.. What is the relationship between the usage of e-HR and organizational outcomes?. 5.

(18) Definition of Key Terms Electronic Human Resource Systems (e-HR) Strohmeier (2007) defined “e-HRM as the (planning, implementation and) application of information technology for both networking and supporting at least two individual or collective actors in their shared performing of HR activities” (p. 20). Competitive Tension Carroll and Hannan (1992) posited that a new company is hard to survive in industry with lots of existing companies since it feels more competitive tension, and the company number has positive influence on the establishment of new company. Thus, the competitive tension is measured by the total company number in an industry, and more companies in an industry means the industry is more competitive. Strategic Leadership Ireland and Hitt (2005) posited that “the strategic leadership means a person who has the ability to anticipate, envision, maintain flexibility, strategic thinking, and be able to work with others to create a better future for the organization” (p.63). IT Capability Bharadwaj (2000) suggested that “IT capability refers to the firm’s ability to mobilize and display IT-based resources in combination with other resources and capabilities” (p.171).. 6.

(19) CHAPTER II. LITERATURE REVIEW. The chapter reviews literatures for developing the framework and selecting variables. Based on the Technology-Organization-Environment framework of technology adoption, e-HR is treated as the innovation technology for organization to adopt, while the independent variables are the antecedents for organization-level e-HR adoption from the TOE framework, namely competitive tension, strategic leadership, and IT capability. The dependent variables are organizational outcomes after adopting e-HR. Indicators related to the usage of e-HR and possible organizational outcomes are reviewed. Hypotheses are proposed according to existent researches and theories.. Technology-Organization-Environment Framework The technology-organization-environment framework (TOE framework) was developed by Tornatzky and Fleisher in 1990. The framework explains the process of company adopting and implementing technology innovations. They posited that the technology adopting process is affected by the technological context, organizational context, and the environmental context (Tornatzky & Fleisher, 1990). In the TOE framework, the technological context includes both the internal and external technologies related to the company, while the organizational context refers to the resources or features of the company, company size, degree of centralization, degree of formalization, managerial structure, quality of human resources, available resources, and connection between employees. In addition, the environmental context is composed of the size and structure of the industry, competitors of company, the macroeconomic context, and the regulatory environment. TOE framework was suitable for investigating the information system adoption in organization-level research, and its framework is shown in Figure 2.1. 7.

(20) Figure 2.1. Technology, organization, and environment framework. Adapted from “ The Processes of Technological Innovation,” by Tornatzky and Fleischer, 1990, Lexington, Massachusetts: Lexington Books.. TOE framework has been adopted in many researches as shown in the following Table 2.1. Based on the above description, the study adopted the TOE framework to select the possible antecedents of the e-HR adoption in organization level.. 8.

(21) Table 2.1. Summary of researches based on TOE framework IT Adoption. Analyzed Variables. EDI Technological context: perceived direct benefits; (Electronic Data perceived indirect benefits. Interchange) Organizational context: perceived financial cost; perceived technical competence.. Author(s) (Kuan & Chau, 2001). Environmental context: perceived industry pressure; perceived government pressure. Internet Web site E-commerce. Technological context: technology readiness; technology integration; security applications.. (Martins & Oliveira, 2009). Organizational context: perceived benefits of electronic correspondence; IT training programs; access to the IT system of the firm; internet and e-mail norms. Environmental context: internet competitive pressure; web site competitive pressure; e-commerce competitive pressure. Controls: Services sector.. ERP. Technological context: IT infrastructure; technology readiness.. (Pan & Jang, 2008). Organizational context: size; perceived barriers. Environmental context: production and operations improvement; enhancement of products and services; competitive pressure; regulatory policy. e-commerce development level. Technological context: support from technology; human capital; potential support from technology.. (Liu, 2008). Organizational context: management level for information; firm size. Environmental context: user satisfaction; e-commerce security. Controls: firm property. (continued). 9.

(22) Table 2.1. (continued) IT Adoption E-business. Analyzed Variables. Author(s) (Zhu et al., 2003). Technology competence: IT infrastructure; e-business know-how. Organizational context: firm scope, firm size. Environmental context: consumer readiness; competitive pressure; lack of trading partner readiness. Controls: industry and country effect. Deployment of B2B e-commerce: B2B firms versus non-B2B firms. Technological inhibitors: unresolved technical issues; lack of IT expertise and infrastructure; lack of interoperability.. (Teo et al., 2006). Organizational inhibitors: difficulties in organizational change; problems in project management; lack of top management support; lack of e-commerce strategy; difficulties in cost-benefit assessment. Environmental inhibitors: unresolved legal issues; fear and uncertainty.. Note. Adapted from “Literature Review of Information Technology Adoption Models at Firm Level,” by T.Oliveira & M. F. Martins. 2011, The Electronic Journal Information Systems Evaluation, 14(1), p.110-121.. Tornatzky and Fleischer referred to the environment context as the macro-environment and the related factors surrounding the organizational. In the environment context, it was pointed out that company may adopt a technology due to influences of its business partners and/ or its competitors. Furthermore, it had been found that pressure from business partners or competitors was an important factor in EDI adoption.. Thus, the external industry. pressure was used to investigate the pressure from the industry, for example, business partners and competitors (Kuan & Chau, 2001). While in the organization context, it was shown that these indicators were related to 10.

(23) organizations’ features, such as the available financial resources, management emphasis on adoption, the competitive attitude of company (Matopoulos et al., 2009). In addition, in the technology context, it described the new technologies relevant to the company (Oliveira and Martins, 2010), support from technology (Liu, 2008), IT infrastructure and technology readiness (Pan & Jang, 2008; Zhu et al., 2003). Thus, taking previous studies as reference, in this study, the competitive tension stood for the environmental context, strategic leadership represents the organizational context, and IT capability serves as a substitute for the technological context.. Competitive Tension Kuan and Chau (2001) posited that firm may feel the pressure to adopt technology because of its business partner’s suggestion or requisition. Besides, the fact that more and more companies in the industry adopted the technology also makes the company top-management team feel stressful, and lead the company to adopt technology to maintain its competitive status. The organizational ecology theory which was developed by Hannah and Freeman (1977) could be used to explain the competitive tension in an industry, and one of the research themes of this theory is density dependence model. Hannan and Freeeman (1988) reported a strong relationship between density and deaths of social organizations. This theory was proved in these three populations, American labor unions, newspapers, and semi-conductor firms by Carroll and Hannan (1992). And they later posited that in the low density condition, which meant low competitive tension, each increment of company lessens the probability of failing, while each increment of company in high density situation raises the death rate. Hence, it is known that new company is hard to survive in industry with lots of existing companies, and the company number has negative influence on the establishment of new company (Carroll & Hannan, 1992). 11.

(24) In conclusion, this research adopted the density dependence model to measure the degree of competition in industry, and it was assumed that the competitive tension could be investigated by the number of company.. Strategic Leadership Child (1972) addressed that the top managers could make decision flexibility and their decision-making results affect the organization outcome. While reviewing the theory of leadership, lots of studies have been researched with various approaches in this field. The trait approach and the charismatic/transformational leadership approach were thought to be the two main roads for discussing leadership concept (Yukl, 1994). In terms of strategic leadership, the upper echelon theory was seen as the antecedent and the main concept is that the executives have to take responsibility for the entire organization outcomes (Hambrick & Mason, 1984). Moreover, Finkelstein and Hambrick (1996) stated the importance of top managers to organization outcomes. After that, researches based on the perspective of top management are generally called strategic leadership theory. According to the definition of strategic leadership from Ireland and Hitt (2005), the strategic leadership meant a person who has the ability to anticipate, envision, maintain flexibility, strategic thinking, and be able to work with others to create a better future for the organization. The definition was adopted in Crossan, Vera, and Nanjad’s research (2008) as well. While discussing the influences of strategic leadership, Chen and Wu (2008) pointed out that many empirical studies focused on and showed evidences that leadership affects every aspect of organization variables. Furthermore, the strategic leadership was treated as the predictor to investigate the technology acceptance, and it was shown that leader’s behavior influences individual’s perception of using technology (Schepers, Wetzels, & Ruyter, 2005).. 12.

(25) IT Capability IT capability referred to the firm’s ability to mobilize and display IT-based resources in combination with other resources and capabilities (Bharadwaj, 2000). Bharadwaj (2000) also proposed the IT-based resources are classified into three parts: IT infrastructure, human IT, and IT-enabled intangibles. From the definition of Tippins and Sohi (2003), the IT capability was seen to be “the extent to which a firm is knowledgeable about and effectively utilizes IT to information within the firm”. Based on these two definitions, the IT capability referred to how the IT department processes and manages the information. Moreover, Tippins and Sohi (2003) also grouped IT capability into three dimensions: IT knowledge, IT operations, and IT objects. Ross, Beath, and Goodhue (1996) defined IT capability as “the ability to control IT-related costs, deliver systems when needed, and affect business objectives through IT implementations”. Furthermore, three dimensions of IT assets were proposed to measure IT capability: IT human asset, IT technology asset and IT relationship asset to investigate the strategic merits contributed by IT construction. To sum up, the IT capability denoted the abilities in a company to manage information technological related abilities, for instance, assets, competencies, knowledge, processes and the human relationship that lead the company to acquire, display and management the services and products that provided by IT which helped to form innovation and business strategies (Feeny & Willcocks, 1998). Goodhue and Thompson (1995) developed the task-technology fit theory and they posited that IT was 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. Measures of task-technology fit may include quality, locatability, authorization, compatibility, ease of use/training, production timeliness, systems reliability, and relationship with users (Goodhue 13.

(26) & Thompson, 1995). Moreover, Goodhue and Thompson (1995) found that task-technology fit measures could be applied to predict the improvement of job effectiveness through investigating on how employees use the system. Since the technology-organization-environment model is the main conceptual framework of this study, according to the research conducted by Lai (2008), the TOE framework was used as the conceptual structure to design its framework then researched on the information system strategies of MNC affiliates. The results indicated that IT maturity, parent source dependency, cultural distance, restrictive regulations, and local competition are significant decisive factors of global information system (GIS) strategy. It was also found that the integration-responsiveness model could be applied to explain the strategies and implementation. Furthermore, Leidner, Preston, and Chen (2010) developed and tested an integrated model to understand why certain hospitals administrators are IT innovators. The IT innovation theory was used to be the theoretical foundation and three antecedents including the chief information officer (CIO) strategic leadership, the top management team's (TMT) attitude toward IT, and the hospital's climate were examined. Moreover, they examine the effects of IT innovation on the IT in the hospital and the hospital's financial performance. The results pointed out that the CIO strategic leadership and the top management team’s attitude toward IT were critical factors to influence IT innovation. The study also mentioned about if the hospitals are IT innovators, they can generate better effects from IT, and achieve better performance for the hospitals. However, a hospital’s climate on organizational IT innovation was influenced by the level of CIO’s strategic leadership.. 14.

(27) Electronic Human Resource Practices Follow up on previous discussion of the TOE framework, the electronic human resource practices are treated as the technology innovation of companies in this study. Definition and miscellaneous functions are introduced in this section.. Definition and of e-HR Strohmeier (2007) defined that “e-HRM is the (planning, implementation and) application of information technology for both networking and supporting at least two individual or collective actors in their shared performing of HR activities.” (p.20). Also, Bell, Lee and Yeung (2006) posited that the e-HR allows managers to timely access information and data for analyses and to make decisions. The use of e-HR benefits both employees and HR professionals. Employees can better manage and control their personal information anytime anywhere. Moreover, the HR professionals can be free from the administrative tasks, and focus on more strategic-oriented decisions for companies.. Previous Studies of e-HR The issue of HR innovation adoption has been a research interest in the academic society. Johnson and Gueuta (2011) urged that human resource should keep up with the current trend to become a more technology-based profession. Technology provides human resource practitioners advantages such as releasing them from administrative burdens, simplifying work processes, reducing administrative costs, attracting worldwide talents, increasing accessibility to employees and managers in organization, and providing timely information for decision makers, all of which allow HR professionals to focus on more strategic-oriented businesses. The related literature of HR innovation adoption can be traced to Jenkins and Lloyd 15.

(28) (1985), who explained that corporate philosophy and strategy affected the company use of HR information systems. Besides, Wolfe (1995) developed a model of HRMI implementation and tried to describe and define HRM innovations (HRMIs) after reviewing three related studies. Lin (1997) conducted a study to investigate the human resource information system (HRIS) implementation in Taiwan to figure out the successful factors to adopt HRIS; these factors were support of top management, support of IT department, involvement of human resource heads, support of HR staff, computer literacy of the HR staff, and training of HRIS. Some studies attempted to find new factors or confirm factors that people know, for instance, the key success factors in Greece were organizational culture and employees’ IT skill (Panayoutopoulou, Vakola, & Galanaki, 2007). But, they also mentioned that the e-HR adoption in Greece was lagging behind other European countries. Another research theme in e-HR was cross-national influences, Strohmeier and Kabst (2009) conducted a large-scale research in Europe to investigate the driving factors for organization to adopt e-HR, and the result showed that the major general determinants were company size, work organization, and configuration of HRM. Furthermore, Panayotopoulou, Galanaki, and Papalexandris (2010) found the national background of the firms was related to the adoption of electronic systems in HRM. This research included 13 European countries, and they found the e-HRM adoption was region-specific and affected by multiple factors. Also, they supported the two separate sets of HRM technological systems which included back-end and front-end ones. Some researches in 2010 continued to discuss the international issues. Wickramasinghe (2010) conducted a study on employee perceptions towards web-based human resource management systems in Sri Lanka. The 30 firms were surveyed in the service and manufacturing sectors with web-based HRM systems as a stand-alone automation to serve employees' HRM needs. The findings revealed that system usage was high in Sri Lanka, 16.

(29) while the user satisfaction was medium. In addition, the web-based HRM system was medium complexity; and it was highly correlated to system usage, meaning the younger the system the more users were satisfied with the system. It also concluded that users did not perceive HR department transfer HRM tasks to them by using web-based electronic HRM system.. Advantages and Usage of e-HR Strohmeier and Kabst (2009) summarized three major advantages of e-HR adoption, automation, information, and collaboration. Automation means to transfer entire or part of HR tasks to technology systems, thus making more efficient HR processes. The advantages include saving cost, time, and raising quality of HR processes. Information refers to providing HR-related knowledge, which benefits the planning and controlling HR processes, thus make HRM become more strategic-oriented. Collaboration refers to building network for HR professionals, line managers, employees, applicants, or consultants. Then, these separated roles are coordinated together to take more innovative ways to organize HRM. With the current development of technology, the possible capabilities of electronic functions may include e-recruiting and selection, e-training/e-learning, e-performance management, e-compensation, HR portal and employee self-service (ESS), and other functions (Yeh, Lu, & Tan, 2011). In addition, based on the literature review by Haines and Lafleur (2008), they developed a list with 78 e-HR application within nine human resource functions from vendor package and business solution package, and these nine functions are: 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.. 17.

(30) Organization Outcomes There are various possible consequences after companies adopt technology innovation. The e-HR is treated as a technology innovation tool for the company in this study, meaning the organizational outcome of e-HR adoption can be analyzed in various ways. In this study, the human resource efficiency, return on assessment (ROA), and earning per share (EPS) were designed as the outcome variables to examine consequences after using e-HR practices.. Human Resource Efficiency The operational consequences was one of the research concerns of e-HRM adoption and it was composed of both efficiency and effectiveness related macro-level consequences of e-HRM (Strohmeier, 2007). Some studies supported the proposition that the efficiency of e-HRM was raised because e-HRM increased productivity; besides, these studies indicated the reduction of HR staffs, faster processes, and relief from administrative tasks by automation (Hawking et al., 2004; Ruël et al., 2004; Ruta, 2005). According to these researches, the adoption of e-HRM may lead to various operational results. In another perspective, efficiency was also one of the consequences of e-HR adoption, a number of literatures supported that the HR efficiency can be improved by adopting e-HR, because e-HR helps company reduce cost and accelerate working processes. For example, Lepak and Snell (1998) and Hendrickson (2003) advised that using e-HRM can simplified transaction processes and raise efficiency of HR department. Ruel et al. (2006) also found that the main purposes to adopt e-HRM were increasing production efficiency or decreasing cost by cutting down the headcount or diminishing administration tasks. Some researchers supported that e-HR can improve HR efficiency (Enshur, Nielson, & Grant-Vallone, 2002; Lengnick-Hall & Moritz, 2003; Martin et al., 2008). 18.

(31) According to the research report which was published by Watson Wyatt Consulting Firm in 2002 (http://www.watsonwyatt.com/research/printable.asp?id=W-524), two variables are used to test human resource effectiveness, one is cost efficiency and the other is staffing efficiency. Cost efficiency means the proportion of human resource operating budget to total company revenue. Similarly, the staffing efficiency is represented by the employee to HR personnel ratio. Furthermore, Parry (2011) used ratio of HR to employees as the measure to examine whether electronic human resource management make human resource department become more efficient.. Financial Performances When analyzing the organizational outcomes, lots of studies use financial performance as the indicator of firm performance. It is also appropriate to examine whether technology help organizations increase profits. In fact, there is a wide range of financial measures. Nevertheless, two broad categories contain the most measures of financial performance: investor returns and accounting returns (Cochran & Wood, 1984). The basic idea of investor returns is to measure the returns according to shareholders’ perspective, while the accounting returns focus on company earnings of different managerial policies. The earnings per share (EPS) or price/earnings (P/E) ratios are the most commonly used indicators (Cochran & Wood, 1984). The financial performance is also examined by indicators such as return on assets (ROA) and return on sales (ROS). These two ratios have been widely adopted to measure the profitability of company (Cron & Sobol, 1983; Hitt & Brynjolfsson, 1996; Weill, 1992). Others like earnings per share (EPS) are also used as the measure of financial performance of company (Vance, 1975). In addition, Griffin and Mahon (1997) listed all the financial measure in 51 studies, and six categories remained after classification process; these are profitability, asset utilization, growth, liquidity, risk/market measures, and other. The following table summarizes indicators 19.

(32) which were used in past researches to investigate the financial performance. Table 2.2. Variables Used to Measure Financial Performance Variables Profitability Return on equity (ROE)  Mean, median . Risk adjusted (Net income + depreciation) /owner’s equity. Subtotal. Number of Occurrences. 11 1 1. Asset utilization Return on assets (ROA) (net income/ unit assets). 8. . 2. . Before taxes and interest expenses Operating income/assets Risk adjusted. . Average. 1.  13. Return on sales (ROS)  Net income/unit sales  Operating profit/ unit sales. 6 3. Subtotal. 9. Subtotal  Asset age (net fixed assets/ gross fixed . Profitability Net income (earnings) Return on investment (ROI) Earnings per share Profit margin (net income/ sales). 5 3 2 1. Sales/employee Equity. 1 1. Number of Occurrences. Variables. assets) Asset turnover (sales/total assets). Risk/market measures Excess market valuation/ abnormal returns-means and SDs Beta Alpha Net losses (capital market losses-direct cost losses) Share price Price /earnings ratio Returns to portfolios Market share Dividends/share % change dividends. 2 1 14 3. 1 23. 13 8 1 7 5 1 1 1 1 (continued). 20.

(33) Table 2.2. (continued) Variables. Number of Occurrences Other. Growth Size Return on assets- 2,3,4,or 5 years average Return on equity-5-year average Return on sales-3-or 5-year average Return on assets-5-year average Return on assets-5-year average, risk adjusted Asset turnover (sales/total assets)-5-year average. Number of Occurrences. Variables. 37 6 4 2 2 1 1. Ownership  % local ownership  % institutional ownership Perceptual measures  Self-reported long-term profitability Advertising level  % change in advertising  Advertising expenditure/revenue. 1 1. 1. 1 1. Return on investment-5-year 1 average Earnings per share 1 growth-10-year average Liquidity Acid test (cash + receivables/liabilities) Change in cash flow-1-year. 2. Current ratio (current assets/current liabilities) Current assets/total assets Cash flow/interest expense Pay-out ratio. 1. 1. 1 1 1 (continued). 21.

(34) Table 2.2. (continued) Variables Other Executive/employee compensation  Cash and bonus  Cash and bonus and long-term   . compensation % change in benefits % change in pensions % change in officer compensation. Diversification  Acquisition expenditures/revenues  R&D expenditures/sales. Number of Occurrences. 1 1. 1 1 1. Leverage  Long-term debt/equity  Long-term debt/net income    . 1 1. Number of Occurrences. Variables. . 1 1. Long-term debt/assets 1 Long-term debt-%change 1 Total liability/net worth 1 Capital expenditures/long-ter m debt Assets/equity.  Operating leverage Others Grand total. 1. 1 1 11 208. Note. Adapted from “The Corporate Social performance and Corporate Financial Performance Debate,” by J. J. Griffin & J. F. Mahon. 1997, Business and Society, 36(1), p.5-31.. 22.

(35) Competitive Tension and Usage of e-HR Practices According to the research which was conducted in Greece, the key success factors of HRM development were discussed. The critical factors included external environmental factors, for instance, external competition, participation in the European Monetary Union, the higher educational level of professional management, and the way that multi-national companies based in Greece have developed and used HRM (Panayoutopoulou et al., 2007). It was found that the condition of e-HR adoption is different by industries. For instance, Galanaki (2002) detected that the reason of companies in IT sector adopted IT tools earlier was being afraid of falling behind their competitors. Similar phenomena manifest different competition level between industries. The more competitive tension in a company’s industry, the more possibility the company will adopt state-of-the-art technologies to gain the leading status in the industry. Human resources and information technology were seen as strategic tools to compete with other companies (Jenkins & Lloyd, 1985; Lin, 1997). Therefore, the competitive tension of a company in the industry should affect the usage of e-HR functions. Thus, the following hypothesis is derived from the above discussion: Hypothesis 1: Competitive tension of the firm in the industry has a positive influence on the practices of e-HR.. Strategic Leadership and Usage of e-HR Practices Strategic leadership means the leadership style and behaviors of the general managers or CEOs in the company, and it is viewed as the critical factor to form a company’s internal environment (Cannella, Finkelstein, & Hambrick, 2009). Strategic leadership affects how companies build the organization structure, allocate resources, and deliver strategic vision to 23.

(36) the whole company. In addition, strong leader could influence subordinates’ willingness to use new technologies, because they may feel obligated to perform extra roles and responsibilities by using new systems. According to a previous study, the management support and training courses have positive influences on technology acceptance (Schepers et al., 2005). According to Chen and Wu (2008), many empirical studies focused on and showed evidences that leadership affects every aspect of organization variables. Thus, the following hypothesis is proposed: Hypothesis 2: Strategic leadership of the firm has a positive influence on the practices of e-HR.. IT Capability and Usage of e-HR practices Panayotopoulou et al., (2007) pointed out that the key success factor in e-HR adoption and utilization is to make HRM, IT, and investment in IT training, these three arts work together. In addition, according to the task-technology fit theory, it was known that IT impacts individuals’ performance when IT capability match the tasks that user need to perform (Goodhue & Thompson, 1995). Thus, the following hypothesis is derived: Hypothesis 3: IT capability of the firm has a positive influence on the practices of e-HR.. 24.

(37) Usage of e-HR Practices and Organizational Outcomes According to previous discussion, the organizational outcomes can be measured by HR efficiency and financial performances such as ROA and EPS. It was posited that with the use of e-HR, the need of HR professionals is reduced (Lengnick-Hall & Moritz, 2003), because the tasks of middleman are replaced or eliminated by e-HR system. Besides, Strohmeier and Kabst (2009) also believed that the number of HR staff can be decreased by shifting the labor-intensive administrative tasks to self service. The decrease in HR staffs means higher HR efficiency in the company to deliver HR service. Furthermore, Parry (2011) posited that the use of e-HRM is a more efﬁcient way to deal with administrative HRM tasks and may lead to lower numbers of HR staff, since the technology can perform simple tasks quickly and accurately. Hence, Parry (2011) further suggested that using e-HRM to perform routine tasks would diminish the number for HR staff. Financial performance has been discussed and investigated in various field of research. According to HR experts, e-HR adoption has great influences on organizations’ strategic goals, for instance, company reputation, goal alignment, and cost reductions (Panayotopoulou, et al., 2007), and thus resulting in better financial performance. Therefore, the following hypotheses are proposed: Hypothesis 4: Practices of e-HR has a positive influence on the organization outcomes. Hypothesis 4a: Practices of e-HR has a positive influence on HR efficiency. Hypothesis 4b: Practices of e-HR has a positive influence on the ROA of a firm. Hypothesis 4c: Practices of e-HR has a positive influence on the EPS of a firm.. 25.

(38) 26.

(39) CHAPTER III. RESEARCH METHOD. In this chapter, research framework and research design are described. Procedures and hypotheses are introduced in the research framework section. The method of sampling and data collection and measurements of each variable are illustrated in research design section.. Research Framework According to the previous literature review, the possible antecedents were inspected by adopting the technology-organization-environment framework. This framework is applied for investigating innovation adoption at the organizational level, thus, the information technology capability, strategic leadership, and competitive tension are selected as the antecedents to examine the practices of e-HR adoption in the research. These three components are the independent variables as declared in the prior chapter, while organizational outcomes are the dependent variables to test the possible consequences of e-HR practice usage. TabIn addition, as mentioned in the previous chapter, organization size and industry sector are factors that may impact firm performance. Thus, they are designed as control variables in the research framework. Figure 3.1. shows the research structure of this study.. 27.

(40) Figure 3.1. Research framework. The quantitative method was adopted to test the direct effects of competitive tension, strategic leadership, and IT capability on practices of e-HR and also to examine the effects of e-HR on organizational outcomes. A questionnaire was designed to collect data on participating organizations’ strategic leadership, IT capability, and practices of e-HR. To minimize the effect of common method variance, data on competitive tension and organizational outcomes were compiled from secondary information sources.. 28.

(41) Research Hypotheses Based on the previous literature review, the hypotheses of this research are as followings: Hypothesis 1: Competitive tension of the firm in the industry has a positive influence on the practices of e-HR. Hypothesis 2: Strategic leadership of the firm has a positive influence on the practices of e-HR. Hypothesis 3: IT capability of the firm has a positive influence on the practices of e-HR. Hypothesis 4: Practices of e-HR has a positive influence on the organizational outcomes. Hypothesis 4a: Practices of e-HR has a positive influence on the HR efficiency. Hypothesis 4b: Practices of e-HR has a positive influence on the ROA of a firm. Hypothesis 4c: Practices of e-HR has a positive influence on the EPS of a firm.. Research Procedure The first step of the research procedure was developing the research topic. After reviewing HR literatures, the researcher narrowed down the research topic to investigate the e-HR adoption and organizational outcomes in Taiwan. Second, through reviewing the relevant literatures, the researcher determined the questions that should be answered in this study. Third, the researcher continued reviewing relevant literature to get better understanding of the e-HR field. Other review focuses were strategic leadership, IT capability, competitive tension, practices of e-HR, and organizational outcomes. Forth, the research framework was drawn and instruments were selected to examine study variables. Next, in the stage of data collection, publicly listed companies in Taiwan were selected as the sample to 29.

(42) test the research framework. Once data were collected, SPSS and SmartPLS were adopted to analyze the data. The final step included the formation of conclusions and discussion; the outcomes of hypotheses testing were interpreted and research questions were answered. The procedure of this research is shown below in Figure 3.2.. Figure 3.2. Research procedure. Research Design This research adopted a quantitative survey method to examine the hypotheses. The publicly listed companies in Taiwan were the sample of this study, and a census approach was applied for collecting data. The HR professionals of listed companies were the respondents to answer the questionnaire. The measurements of variables went through exploratory factor analysis (EFA) and confirmatory factory analysis (CFA) to ensure the validity and reliability.. 30.

(43) Sample and Data Collection The sample for this study targeted at the publicly listed companies in Taiwan and the sampling frame was the companies listed in the Taiwan Stock Exchange to ensure accessibility of organizational performance data. According to the public report from the Taiwan Stock Exchange, there were 843 listed companies in 2012 (Taiwan Stock Exchange, 2012). Data availability and accuracy were main considerations for the researcher to choose companies listed in the Taiwan Stock Exchange. A census-approach was implemented to collect data from all companies in the sampling frame, and mail survey was the main instrument to gather information. The questionnaires were mailed to the HR department of all listed companies in April 2013, with a cover letter that explained the purpose of this research and a coupon in the value of NT$100 for appreciation and it took one month to gather the responses. To boost the responses, the researcher also attended campus recruitment activities to solicit participation from HR personnel at each company booth. Personal networks were also tapped to increase the response rate. HR managers and professionals of listed companies were targeted to fill out the survey. If there were multiple copies of the survey completed for one company, the researcher used the following criteria to select the most representative response: 1) human resource working experience, 2) seniority in the company, 3) functional content, and 4) computer literacy.. Sample Profile A total of 258 responses were collected, and 204 responses were kept to do data analysis after screening out invalid data. The valid response rate of census approach was 16%, while other 79 valid responses were gathered from campus recruitment activities and personal networks. To briefly describe the distribution of total 204 participants, 68.6% of them were 31.

(44) females, while the male accounted for 30.4%. In the age segmentation, most of the participants ranged from 26 to 35 years old with 42.6% and 40.2% of them ranged from 36 to 45 years old. As for the seniority in company, 40.2% of the participants had 1 to 5 years experiences, and followed by 19.6% of the participants with 6 to 10 years experiences in the same company, the others accounted for the rest 40.2%. In the section of human resource working experience, 34.3% of the participants had 1 to 5 years in HR related work, 26.0% of the participants had 6 to 10 years in HR related work, and 21.2% of the participants had 6 to 10 years in HR related work; the others accounted for the rest 18.5%. In general, participants are confident of their computer skills, the majority of the participants rated themselves good as to the computer skills; the other 31.4% rated themselves as normal. As for the functional expertise, 31.9% of the HR professionals perform at least three functions, 25% of the HR professionals perform at other functions like general management office or personnel office, and 14.2% of the HR professionals perform at recruiting function; the others functions accounted for 28.9%. Sample information regarding the research respondents are reported in the following tables. Table 3.1 shows the personal information toward the respondents. Table 3.1. Descriptive Information on the Respondents Sample characteristics Gender. Age. Frequency. Percentage. 1. Male. 62. 30.4%. 2. Female Missing value. 140 2. 68.6% 1%. 1. 25 and below. 3. 1.5%. 2. 26-35. 87. 42.6%. 3. 36-45. 82. 40.2%. 4. 46-55. 27. 13.2%. 5. 56-65. 5. 2.5%. Missing value. 0. 0% (continued). 32.

(45) Table 3.1 (continued) Sample characteristics Company seniority. Human Resource seniority. Computer skill. Functional department. Frequency. Percentage. 1. Below1 year. 17. 8.3%. 2. 1 year to 5 years. 82. 40.2%. 3. 6 years to 10 years. 40. 19.6%. 4. 11 years to 15 years. 33. 16.2%. 5. 16 years to 20 years. 12. 5.9%. 6. 21 years and above. 20. 9.8%. Missing value. 0. 0%. 1. Below 1 year. 6. 2.9%. 2. 1 year to 5 years. 70. 34.3%. 3. 6 years to 10 years. 53. 26.0%. 4. 11 years to 15 years. 43. 21.1%. 5. 16 years to 20 years. 22. 10.8%. 6. 21 years and above. 10. 4.9%. Missing value. 0. 0%. 1. Very poor. 1. 0.5%. 2. Poor. 3. 1.5%. 3. Average. 64. 31.4%. 4. Good. 119. 58.3%. 5. Excellent Missing value. 16 1. 7.8% 0.5%. Recruiting. 29. 14.2%. Training. 15. 7.4%. Compensation and benefit. 16. 7.8%. Other functions. 57. 28.0%. Two functions. 17. 8.3%. Multiple functions. 65. 31.9%. Missing value. 5. 2.5%. In addition, respondents were from different industries. The majority of the respondents were from manufacturing industries. More detailed information was organized in Table 3.2. 33.

(46) Table 3.2. Descriptive Information Regarding the Participating Companies Sample characteristics. Industry. Employee number. HR personnel number. Capital (Hundred million NT$). Frequency. Percentage. Manufacturing Service Others Manufacturing and Service Missing value. 145 23 32 1 3. 71.1% 11.3% 15.7% 0.5% 1.5%. Below 100 101 to 300 301 to 500 501 to 1000 1001 to 2000 2001 to 4000 4001 to 10000 10001 and Above Missing value. 12 30 24 39 27 30 33 8 1. 5.9% 14.8% 11.8% 19.1% 13.2% 14.7% 16.2% 3.9% 0.5%. Below 3 4 to 6 7 to 10 11 to 20 21 to 100 101 to 400 Missing value. 55 42 35 35 23 3 11. 27.0% 20.6% 17.2% 17.2% 11.3% 1.5% 5.4%. Below 15 16 to 50. 64 74. 31.4% 36.3%. 51 to 150 151 and Above Missing value. 31 33 2. 15.2% 16.2% 0.9%. Participants were also asked to answer the year that company implemented integrated software. Most of the participants did not answer this item due to a lack of knowledge of the specific time of implementation, thus, the missing value accounted for the most proportion. The distribution of implementing year was organized in Table 3.3, and it showed most of the 34.

(47) sample company implemented integrated software after the year 2000. Table 3.3. Year of Implementing Integrated Software Year. Frequency. Percent. missing value. 76. 37.3. 1990. 1. 0.5. 1995 2000. 2 10. 1.0 4.9. 2001 2002 2003 2004. 8 1 6 5. 3.9 0.5 2.9 2.5. 2005 2006 2007 2008 2009. 4 3 7 10 2. 2.0 1.5 3.4 4.9 1.0. 2010 2011 2012 2013 long time ago Company did not implement integrated software Total. 10 9 1 3 1 45 204. 4.9 4.4 0.5 1.5 0.5 22.1 100.0. Questionnaire Design The portion of the questionnaire related to the current study was divided into four parts to collect data on IT capability, strategic leadership, practices of e-HR, and demographic information. The HR practitioners were the sample to fill out the questionnaire. Taking common method variance issue into consideration, data of competitive tension and organization outcomes were acquired from secondary information. The first part of questionnaire is IT capability which included two dimensions and 13 35.

(48) items. Moreover, three reverse coded items were applied to screen out invalid responses. The items adopted the 7-point Likert scale from strongly disagree (1) to strongly agree (7), and participants were guided to answer questions based on their interaction with IT department. The second part is strategic leadership which included 12 items; the visionary leadership and strategic execution of high-level leader in company were examined. The items adopted the 7-point Likert scale from strongly disagree (1) to strongly agree (7) to indicate the level of strategic leadership of the company leader. The third part is the scale for e-HR practices. There are 51 items of HR activities and participants were guided to answer each item based on their actual work practice. The scale ranged from 1 to 5 to show different degree of automation. The last part of the questionnaire contains demographic questions, participants were asked to answer age, company seniority, HR seniority, computer skill, functional department, and other company information such as the number of HR personnel, employee number, capital, and industry sector. Since the study was conducted in Taiwan, the questionnaire adopted the Chinese translation version from a previous study to make it easier to understand by the participants. The Chinese translation version had gone through expert review to ensure the validity of its content. The questionnaire can be seen in Appendix A.. Measurement This section reports the measures used in this study, source of these measures, as well as the analysis and results of validity and reliability testing of latent measures. In order to validate major variables, exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) were applied to examine the validity, and Cronbach’s alpha for reliability respectively. Furthermore, the secondary information was acquired from the Taiwan Economic Journal (TEJ) Database, which was founded in 1990, and keeps updated public financial report that 36.

(49) companies disclose to meet legal requirements. The TEJ database is widely used by companies or universities to collect various financial reports.. Competitive Tension Competitive tension aimed to measure the level of competition within an industry. Carroll and Hannan (1992) posited that new company is hard to survive in industry with lots of existing companies, and the number of company has negative influence on the establishment of new company. Thus, the competitive tension of company was measured by the total number of companies in the same industry category in this study. The higher the number of companies in one industry category, the higher the competitive tension a company faces. The classification of industry sector organized by the Taiwan Stock Exchange (TSE) was adopted, and the information was gathered from the TEJ database. The detail classification was reported in Appendix B.. Strategic Leadership The study adopted the scale developed by Chen and Wu (2008) as the measurement of strategic leadership. Chen and Wu developed and validated the measurement through different tests included reliability, discriminant validity, convergent validity, and nomological validity. Then, the pilot test was conducted for gathering data to do exploratory factor analysis (EFA), confirmatory factor analysis (CFA), and reliability analysis. Two dimensions of strategic leadership were applied as the instrument for this study. These two were visionary leadership with a published Cronbach’s alpha of 0.92 and strategic execution of 0.90. These provided evidence of a well-developed instrument for measuring strategic leadership. Each dimension consisted of 6 items. One sample item for visionary leadership was “Manager draws the blueprint for our team.”, and for strategic execution was “Manager builds relationships inside and outside the organization.” 37.

(50) IT Capability IT capability in this study aimed to measure the ability of IT department to cooperate with HR practitioners. This measure was based on Goodhue and Thompson’s research in 1995, which proposed and constructed the task-technology fit theory based on users’ perspective. The validity was tested later by Goodhue in 1998 based on users’ evaluation of information system. After testing the reliability and discriminant validity of the items, the measurement was reduced from 48 to 34 items. This measurement included eight components: quality, locatability, authorization, compatibility, ease of use/training, production timeliness, systems reliability, and relationship with users to measure how well these characteristics of technology fit the tasks of the users. The components of systems reliability and relationship with users were adopted in this research because these factors were more appropriate for accessing IT capability or the ability of IT to support other functional areas in the company. The published Cronbach’s alphas of each dimension were 0.71, and 0.88. A sample item for systems reliability is: “I can count on the system to be "up" and available when I need it”. And the sample item for relationship with users is: “The IS people we deal with understand the day-to-day objectives of my work group and its mission within our company”. A complete list of items can be found in Appendix C.. Practices of e-HR Items related to practices of e-HR were intended to gauge how widely the HR staff uses e-HR functions. The measurement of practices of e-HR adopted the comprehensive list of e-HR practices that was developed by Haines and Lafleur in 2008 after reviewing professional literature and vendor package. There were 78 applications in human resource activities and covered nine dimensions: HR audits and survey, employee benefits, 38.

(51) compensation and rewards, health and safety, performance management, HR planning and career development, staffing, training and development, and employee relations. In addition, Yeh and Wei (2011) translated Haines and Lafleur’s measurement for companies in Taiwan and validated the Chinese version measurement through focus group interview, expert review, and pilot test to make sure the validity and reliability of this measurement. Two dimensions were deleted after the validation process, the HR audits and survey, and the health and safety. Thus, seven dimensions were left and formed a new measurement. Hence, this study adopted the Yeh and Wei’s (2011) version of the measurement to investigate the practices of e-HR usage in Taiwan. The revised measurement and entire items were listed in Appendix C. This scale ranged from 1 to 5 to represent the usage of e-HR practices. The higher the score is, the higher the level of automation of an HR activity. The scale of 1 to 5 follow a progression from none to high level of automation, with 1 indicating the company does not have the activity, 2 the activity is carried out manually, 3 the activity involves the use of office software, 4 the activity involves the use of packaged software, and 5 the activity involves the use of integrated software. A sample item is: “Allowing employees to access pay data information.” Participants were guided to answer from 1 to 5 of each practice based on their actual work experience. When aggregating the score for e-HR practices from these activities, the values were recoded with no such practice as missing values, manual operation as 1, the use of office software as 2, the use of packaged software as 3, and the use of integrated software as 4.. Organization Outcomes HR efficiency The employee to HR personnel ratio (Watson Wyatt, 2002; Lenngnick-Hall & Moritz, 2003; Parry, 2011) was adopted as the measurement of HR efficiency. The item for HR 39.

(52) efficiency was asked by open-ended questions, the questions include “How many HR personnel are in your company?” and “How many employees are in your company?” Since the number of employee was hugely different among companies, the logarithm of the numbers of HR personnel and employees were used in the calculation to better examine the impact of e-HR practices on the employee to HR personnel ratio. HR efficiency was calculated by the log value of employee number divided by the log value of HR personnel number. That is, the higher the value, the higher the HR efficiency of a company. The range of HR personnel number and employee number of participating companies is organized in the following Table 3.4. Table 3.4. Range of HR Personnel Number and Employee Number of Companies N. Min.. Max.. Mean. S. D.. Employee number. 203. 5. 95000. 3590.09. 9580.95. HR personnel. 193. 1. 400. 15.41. 36.020. Financial performance Financial performance was applied as the dependent variable many times in various research fields. To measure the influence of e-HR use on organization financial performance, return on asset (ROA) and earnings per share (EPS) were used as two measures to examine the financial result. ROA and EPS were two of the most important financial indices that publicly listed companies need to disclose. The information of ROA and EPS were collected from the TEJ database, hence, survey participants did not have to answer these items.. 40.

(53) Control variables The control variables were included to control variance that might cause estimation bias. Two control variables of company background were applied in this research. The first control variable is the size of an organization. Firm size is viewed as a source of organizational cost (Shepherd. 1972). In addition, scholars posited that firm size is an indicator of the diversification of an organization based on the strategy perspective (Rumelt, 1982; Porter, 1987). Thus, organization size can be one of the general factors that influence the cost and strategy selection of a firm. The organization size was measured by the company capital; the information was provided by participants or acquired from Taiwan Stock Exchange. The log value of capital was used due to a substantially wide range of company capital in the study sample. The second control variable is the industry sector. Schmalensee (1985) stated that the majority of variances among business unit performances could be explained by different industry sector. Thus, industry sector can be another factor to influence the performance of firms among different industries. In this study, two main industries were selected, manufacturing and service, to separate participants’ companies generally. However, most of the sample belonged to the manufacturing industry. Hence, manufacturing industry and non-manufacturing industry were coded in a dummy variable to control the industrial variance.. Validity and Reliability Testing for Measurement The latent measures in this study, namely strategic leadership, IT capability, and e-HR practices, went through several statistical analysis procedure to ensure their validity and reliability. These procedures included exploratory factor analysis, confirmatory factor analysis, and internal consistency reliability testing. SPSS was used to perform exploratory factor analyses and internal consistency reliability testing using Cronbach’s alpha. SmartPLS 41.