簡易檢索 / 詳目顯示

研究生: 蕭新耀
Shin-Yau Hsiao
論文名稱: E-HR Usage Intention of the Net Generation: Process Virtualization Theory Versus IT Capability and Individual Attributes
E-HR Usage Intention of the Net Generation: Process Virtualization Theory Versus IT Capability and Individual Attributes
指導教授: 葉俶禎
Yeh, Chu-Chen
學位類別: 碩士
Master
系所名稱: 國際人力資源發展研究所
Graduate Institute of International Human Resource Developmemt
論文出版年: 2014
畢業學年度: 102
語文別: 英文
論文頁數: 98
中文關鍵詞: 電子化人力資源流程虛擬化對科技之態度電腦使用自信科技能力使用意圖
英文關鍵詞: E-HR, process virtualization, Attitude toward Technology, Computer Self-efficacy, IT Capability, Behavioral Intention
論文種類: 學術論文
相關次數: 點閱:161下載:9
分享至:
查詢本校圖書館目錄 查詢臺灣博碩士論文知識加值系統 勘誤回報
  • Some HR processes are more easily accepted when they go online, why? The Process Virtualization Theory provides some viable explanation. Other theoretical perspectives such as the capabilities of the technology and Individual Attributes of people may also help in explaining the acceptance of E-HR technology. This study intended to test effects of the three theories on the use of E-HR systems empirically using experimental procedures. Data was collected from 230 business majors from seven different colleges located in northern Taiwan. Students were randomly divided into two groups in a computer lab setting. Each group experienced a different E-HR process mock-up. A survey questionnaire was administered to measure student perceptions on major research variables at different stages of the experiment. Multiple regression was used to test study hypotheses. The study did not find support for the hypothesized relationship between process virtualization requirements and Behavioral Intention. On the other hand, Attitude toward Technology showed the most effect on Behavioral Intention to use E-HR technology. The IT capabilities were also significant in influencing an individual‟s willingness to use E-HR technology. The reason may be that to the younger Net generation, the virtualizability of a process may not be a key issue in their intention to use E-HR technology. Their main concern was shown in their Individual Attributes and their perception of the IT Capability. Therefore, it can be inferred that for the Net generation, Attitude toward Technology and perception of IT Capability matter the most in Behavioral Intention to use E-HR software.
    Keywords: E-HR, process virtualization, Attitude toward Technology, Computer Self-efficacy, IT Capability, Behavioral Intention

    Some HR processes are more easily accepted when they go online, why? The Process Virtualization Theory provides some viable explanation. Other theoretical perspectives such as the capabilities of the technology and Individual Attributes of people may also help in explaining the acceptance of E-HR technology. This study intended to test effects of the three theories on the use of E-HR systems empirically using experimental procedures. Data was collected from 230 business majors from seven different colleges located in northern Taiwan. Students were randomly divided into two groups in a computer lab setting. Each group experienced a different E-HR process mock-up. A survey questionnaire was administered to measure student perceptions on major research variables at different stages of the experiment. Multiple regression was used to test study hypotheses. The study did not find support for the hypothesized relationship between process virtualization requirements and Behavioral Intention. On the other hand, Attitude toward Technology showed the most effect on Behavioral Intention to use E-HR technology. The IT capabilities were also significant in influencing an individual‟s willingness to use E-HR technology. The reason may be that to the younger Net generation, the virtualizability of a process may not be a key issue in their intention to use E-HR technology. Their main concern was shown in their Individual Attributes and their perception of the IT Capability. Therefore, it can be inferred that for the Net generation, Attitude toward Technology and perception of IT Capability matter the most in Behavioral Intention to use E-HR software.
    Keywords: E-HR, process virtualization, Attitude toward Technology, Computer Self-efficacy, IT Capability, Behavioral Intention

    ABSTRACT I TABLE OF CONTENTS III LIST OF TABLES V LIST OF FIGURES VII CHAPTER I INTRODUCTION 1 Background of Study 1 Problem Statement 4 Research Purpose 6 Research Questions 6 Definition of Terms 7 CHAPTER II LITERATURE REVIEW 9 E-HR (Electronic Human Resource) and its Functions 9 Behavioral Intention to use Technology 13 Process Virtualization Theory 20 IT Capability 25 Individual Attributes 30 CHAPTER III RESEARCH METHOD 35 Research Framework 35 Research Hypothesis 36 Research Design 36 Sample and Data collection 41 Measurement 42 Validity and Reliability Analysis 47 Revised Framework 52 Revised Hypotheses 53 CHAPTER IV FINDINGS AND DISCUSSIONS 55 Influence of Treatment on Variables 55 Relationship between variables 57 Hypotheses testing 59 CHAPTER V CONCLUSIONS AND SUGGESTIONS 63 Conclusions 63 Research Implications 64 Practical Implications 66 Contribution of the Study 67 Limitations 68 Suggestions for Future Research 69 REFERENCES 71 APPENDIX A: PICTURES OF EXPERIMENT 79 APPENDIX B: SCRIPT FOR PROCESS DESCRIPTION 81 APPENDIX C: QUESTIONNAIRE (English/Chinese) 83

    Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179-211.
    Ajzen, I. (2002). Perceived behavioral control, self‐Efficacy, locus of control, and the theory of planned behavior. Journal of Applied Social Psychology, 32(4), 665-683.
    Barnes, S. J., & Vidgen, R. T. (2002). An integrative approach to the assessment of e-commerce quality. J. Electron. Commerce Res., 3(3), 114-127.
    Bell, B. S., Lee, S. W., & Yeung, S. K. (2006). The impact of e‐HR on professional competence in HRM: implications for the development of HR professionals. Human Resource Management, 45(3), 295-308.
    Bondarouk, T., Ruel, H., & van der Heijden, B. (2009). E-HRM effectiveness in a public sector organization: a multi-stakeholder perspective. The International Journal of Human Resource Management, 20(3), 578-590.
    Brockbank, W. (1997). HR's future on the way to a presence. Human Resource Management, 36(1), 65-69.
    Buckley, P., Minette, K., Joy, D., & Michaels, J. (2004). The use of an automated employment recruiting and screening system for temporary professional employees: A case study. Human Resource Management, 43(2‐3), 233-241.
    Cappelli, P. (2001). On-line recruiting. Harvard Business Review, 79(3), 139-146.
    Cardy, R. L., & Miller, J. S. (2005). eHR and Performance Management: A Consideration of Positive Potential and the Dark Side. San Francisco, CA: Jossey-Bass.
    Chauhan, A., Sharma, S., & Tyagi, T. (2011). Role of HRIS in Improving Modern HR Operations. Review of Management, 1(2), 58-70.
    Compeau, D., Higgins, C. A., & Huff, S. (1999). Social cognitive theory and individual reactions to computing technology: a longitudinal study. MIS Quarterly, 23(2), 145-158.
    Compeau, D. R., & Higgins, C. A. (1995). Computer self-efficacy: Development of a measure and initial test. MIS Quarterly, 19(2), 189-211.
    Culiberg, B., & Rojšek, I. (2011). Identifying service quality dimensions as antecedents to customer satisfaction in retail banking. Economic and Business Review, 12(3), 151-166.
    Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-340.
    Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1992). Extrinsic and intrinsic motivation to use computers in the workplace1. Journal of Applied Social Psychology, 22(14), 1111-1132.
    Davis Jr, F. D. (1986). A technology acceptance model for empirically testing new end-user information systems: Theory and results. Cambridge, MA: Massachusetts Institute of Technology.
    Dishaw, M. T., & Strong, D. M. (1999). Extending the technology acceptance model with task–technology fit constructs. Information & Management, 36(1), 9-21.
    Dulebohn, J. H., & Marler, J. H. (2005). e-Compensation The Potential to Transform Practice? In H. G. Gueutal and D. L. Stone (Eds.), The brave new world of eHR :human resources management in the digital age (pp. 166-189), San Francisco, CA: Jossey-Bass.
    Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention and behavior: An introduction to theory and research. MA, USA: Addison-Wesley.
    Goodhue, D. L. (1998). Development and measurement validity of a task‐technology fit instrument for user evaluations of information system. Decision Sciences, 29(1), 105-138.
    Goodhue, D. L., & Thompson, R. L. (1995). Task-technology fit and individual performance. MIS Quarterly, 19(2), 213-236.
    Greengard, S. (1995). Catch the wave as HR goes online. Personnel Journal, 74(7), 54-69.
    Groe, G., Pyle, W., & Jamrog, J. (1996). Information technology and HR. Human Resource Planning, 19(1), 56-61.
    Haines, V. Y., & Lafleur, G. (2008). Information technology usage and human resource roles and effectiveness. Human Resource Management, 47(3), 525-540.
    Hasan, B., & Ahmed, M. U. (2007). Effects of interface style on user perceptions and behavioral intention to use computer systems. Computers in Human Behavior, 23(6), 3025-3037.
    Hawking, P., Stein, A., & Foster, S. (2004). E-HR and employee self service: A case study of a victorian public sector organisation. Journal of Issues in Informing Science and Information Technology, 1, 1019-1026.
    Hill, T., Smith, N. D., & Mann, M. F. (1987). Role of efficacy expectations in predicting the decision to use advanced technologies: The case of computers. Journal of Applied Psychology, 72(2), 307.
    Ho, C.I., & Lee, Y. L. (2007). The development of an e-travel service quality scale. Tourism Management, 28(6), 1434-1449.
    Hsiao, C.C., & Chiou, J.sS. (2012). The effects of a player’s network centrality on resource accessibility, game enjoyment, and continuance intention: A study on online gaming communities. Electronic Commerce Research and Applications, 11(1), 75-84.
    Hu, P. J., Chau, P. Y., Sheng, O. R. L., & Tam, K. Y. (1999). Examining the technology acceptance model using physician acceptance of telemedicine technology. Journal of Management Information Systems, 16(2), 91-112.
    Hussain, Z., Wallace, J., & Cornelius, N. E. (2007). The use and impact of human resource information systems on human resource management professionals. Information & Management, 44(1), 74-89.
    Jenkins, M. L., & Lloyd, G. (1985). How corporate philosophy and strategy shape the use of HR information systems. Personnel, 28-38.
    Jourard, S., & Lasakow, P. (1958). Some factors in self-disclosure. Journal of abnormal psychology, 56(1), 91-98.
    Jun, M., Yang, Z., & Kim, D. (2004). Customers' perceptions of online retailing service quality and their satisfaction. International Journal of Quality & Reliability Management, 21(8), 817-840.
    Katz, D., & Kahn, R. L. (1978). The social psychology of organizations. NY:Wiley
    Kavanagh, M. J., Gueutal, H. G., & Tannenbaum, S. I. (1990). Human resource information systems: Development and application. Boston, Massachusetts: PWS-Kent.
    Kennedy, G., Dalgarno, B., Gray, K., Judd, T., Waycott, J., Bennett, S. J., Chang, R. (2007, February). The net generation are not big users of Web 2.0 technologies: Preliminary findings. Paper presented at the Annual Conference of the Australasian Society for Computers in Learning in Tertiary Education. Singapore
    Kim, S., & Garrison, G. (2009). Investigating mobile wireless technology adoption: An extension of the technology acceptance model. Information Systems Frontiers, 11(3), 323-333.
    Kumar, D., & Pandya, S. (2012). Leveraging Technology towards HR Excellence. Information Management and Business Review, 4(3), 205-216.
    Lawler, E., & Mohrman, S. A. (2003). Creating a strategic human resources organization: An assessment of trends and new directions. Stanford, CA:Stanford University Press.
    Lee, Y., Kozar, K. A., & Larsen, K. R. (2003). The technology acceptance model: Past, present, and future. Communications of the Association for Information Systems, 12(1), 50.
    Lengnick-Hall, M., & Moritz, S. (2003). The impact of E-HR on the human resource management function. Journal of Labor Research, 24(3), 365-379. doi: 10.1007/s12122-003-1001-6
    Leonard, B. (1996). Distance learning: Work and training overlap. HR Magazine, 41, 41-47.
    Leso, T., & Peck, K. L. (1992). Computer anxiety and different types of computer courses. Journal of Educational Computing Research, 8(4), 469-478.
    Lin, C. (1997). Human resource information systems: Implementation in Taiwan. Research and Practice in Human Resource Management, 5(1), 57-72.
    Lin, Y., Lin, G. Y., & Laffey, J. M. (2008). Building a social and motivational framework for understanding satisfaction in online learning. Journal of Educational Computing Research, 38(1), 1-27.
    Lin, J.C., & Lu, H. (2000). Towards an understanding of the behavioural intention to use a web site. International Journal of Information Management, 20(3), 197-208.
    Liu, I. F., Chen, M. C., Sun, Y. S., Wible, D., & Kuo, C. H. (2010). Extending the TAM model to explore the factors that affect Intention to Use an Online Learning Community. Computers & Education, 54(2), 600-610.
    Luarn, P., & Lin, H. H. (2005). Toward an understanding of the behavioral intention to use mobile banking. Computers in Human Behavior, 21(6), 873-891.
    Maier, C., Laumer, S., Eckhardt, A., & Weitzel, T. (2013). Analyzing the impact of HRIS implementations on HR personnel’s job satisfaction and turnover intention. The Journal of Strategic Information Systems, 22(3), 193-207. doi: http://dx.doi.org/10.1016/j.jsis.2012.09.001
    Marakas, G. M., Mun, Y. Y., & Johnson, R. D. (1998). The multilevel and multifaceted character of computer self-efficacy: Toward clarification of the construct and an integrative framework for research. Information Systems Research, 9(2), 126-163.
    Marler, J. H., & Fisher, S. L. (2013). An evidence-based review of E-HRM and strategic human resource management. Human Resource Management Review, 23(1), 18-36.
    Martin, G., & Reddington, M. (2010). Theorizing the links between E-HR and strategic HRM: a model, case illustration and reflections. The International Journal of Human Resource Management, 21(10), 1553-1574.
    Martin, G., Reddington, M., & Alexander, H. (2008). Technology, outsourcing and transforming HR. MA, USA:Elsevier, Ltd.
    Mohite, B. J. (2012, January). Impact of Managing Personnel Records in an Electronic Environment (HRIS) on Business Organizations and Related Problems. Paper presented at the Ninth AIMS International Conference on Management. Pune, India
    Moon, J. W., & Kim, Y. G. (2001). Extending the TAM for a World-Wide-Web context. Information & Management, 38(4), 217-230.
    Moore, G. C., & Benbasat, I. (1991). Development of an instrument to measure the perceptions of adopting an information technology innovation. Information Systems Research, 2(3), 192-222.
    Murphy, K. R., & Cleveland, J. (1995). Understanding performance appraisal: Social, organizational, and goal-based perspectives. Thousand Oaks, CA, USA: Sage.
    Nunnally, J. C. (1978). Psychometric theory (2nd ed.). New York: McGraw-Hill.
    Overby, E. (2008). Process virtualization theory and the impact of information Technology. Organization Science, 19(2), 277–291.
    Overby, E., & Konsynski, B. (2010). Task-technology fit and process virtualization theory: An integrated model and empirical test. Emory Public Law Research Paper(10-96).
    Panayotopoulou, L., Galanaki, E., & Papalexandris, N. (2010). Adoption of electronic systems in HRM: is national background of the firm relevant? New Technology, Work and Employment, 25(3), 253-269. doi: 10.1111/j.1468-005X.2010.00252.x
    Panayotopoulou, L., Vakola, M., & Galanaki, E. (2007). E-HR adoption and the role of HRM: evidence from Greece. Personnel Review, 36(2), 277-294.
    Parry, E. (2011). An examination of E-HRM as a means to increase the value of the HR function. The International Journal of Human Resource Management, 22(05), 1146-1162.
    Prensky, M. (2001). Digital natives, digital immigrants part 1. On the horizon, 9(5), 1-6.
    Ramayah, T. (2006). Interface characteristics, perceived ease of use and intention to use an online library in Malaysia. Information Development, 22(2), 123-133.
    Razali, M. Z., & Vrontis, D. (2010). The reactions of employees toward the implementation of human resources information systems (HRIS) as a planned change program: A case study in Malaysia. Journal of Transnational Management, 15(3), 229-245.
    Ruël, H., Bondarouk, T., & Looise, J. K. (2004). E-HRM: innovation or irritation: an explorative empirical study in five large companies on web-based HRM. Management Revue, 15(3), 364-380.
    Ruta, C. D. (2005). The application of change management theory to HR portal implementation in subsidiaries of multinational corporations. Human Resource Management, 44(1), 35-53.
    Schawbel, D. (2012). Millennials vs. baby boomers: Who would you rather hire? , Retrieved from http://business.time.com/2012/03/29/millennials-vs-baby-boomers-who-would-you-rather-hire/
    Schmitt, B., Zarantonello, L., & Brakus, J. (2009). Brand experience: what is it? How is it measured? Does it affect loyalty? Journal of Marketing, 73(3), 52-68.
    Schramm, J. (2004). HR technology competencies: New roles for HR professionals. SHRM Research Quarterly, 3(51). 1-11
    Sheppard, B. H., Hartwick, J., & Warshaw, P. R. (1988). The theory of reasoned action: A meta-analysis of past research with recommendations for modifications and future research. Journal of Consumer Research, 15(3), 325-343.
    Shin, D. H. (2010). The effects of trust, security and privacy in social networking: A security-based approach to understand the pattern of adoption. Interacting with Computers, 22(5), 428-438.
    Stone, D. L., Stone-Romero, E. F., & Lukaszewski, K. (2006). Factors affecting the acceptance and effectiveness of electronic human resource systems. Human Resource Management Review, 16(2), 229-244.
    Straub, D., Keil, M., & Brenner, W. (1997). Testing the technology acceptance model across cultures: A three country study. Information & Management, 33(1), 1-11.
    Strohmeier, S. (2007). Research in E-HRM: Review and implications. Human Resource Management Review, 17(1), 19-37.
    Strohmeier, S., & Kabst, R. (2009). Organizational adoption of E-HRM in Europe: An empirical exploration of major adoption factors. Journal of Managerial Psychology, 24(6), 482-501.
    Sun, H., & Zhang, P. (2006). The role of moderating factors in user technology acceptance. International Journal of Human-Computer Studies, 64(2), 53-78.
    Sundar, S. S., & Marathe, S. S. (2010). Personalization versus customization: The importance of agency, privacy, and power usage. Human Communication Research, 36(3), 298-322.
    Tansley, C., Newell, S., & Williams, H. (2001). Effecting HRM-style practices through an integrated human resource information system: An e-greenfield site? Personnel Review, 30(3), 351-371.
    Taylor, S., & Todd, P. (1995). Assessing IT usage: The role of prior experience. MIS Quarterly, 19(4), 561-570.
    Teo, T. S., Lim, V. K., & Lai, R. Y. (1999). Intrinsic and extrinsic motivation in Internet usage. Omega, 27(1), 25-37.
    Thompson, R. L., Higgins, C. A., & Howell, J. M. (1991). Personal computing: toward a conceptual model of utilization. MIS quarterly, 15(1), 125-143.
    Tyler, K. (2007). The tethered generation. HR Magazine, 52(5), 40.
    Venkatesh, V., & Davis, F. D. (1996). A model of the antecedents of perceived ease of use: Development and test. Decision Sciences, 27(3), 451-481.
    Venkatesh, V., & Morris, M. G. (2000). Why don't men ever stop to ask for directions? Gender, social influence, and their role in technology acceptance and usage behavior. MIS Quarterly, 24(1), 115-139.
    Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425-478.
    Vijayasarathy, L. R. (2004). Predicting consumer intentions to use on-line shopping: the case for an augmented technology acceptance model. Information & Management, 41(6), 747-762.
    Voermans, M., & van Veldhoven, M. J. P. M. (2007). Attitude towards E-HRM: an empirical study at Philips. Personnel Review, 36(6), 887-902.
    Waldman, D. A. (1997). Predictors of employee preferences for multirater and group-based performance appraisal. Group & Organization Management, 22(2), 264-287.
    Wangpipatwong, S., Chutimaskul, W., & Papasratorn, B. (2008). Understanding citizen’s continuance intention to use e-government website: A composite view of technology acceptance model and computer self-efficacy. The Electronic Journal of e-government, 6(1), 55-64.
    Yeh, C. R., & Hsiao, S. (2013, November). Impact of E-HR implementation on HR presence and credibility: An employee perspective. Paper presented at the 12th International Conference of the Asia Chapter, Academy of Human Resource Development, Taipei, Taiwan.
    Yeh, C. R., & Wei, L. Y. (2012, October). An investigation of E-HR adoption in Taiwan. Paper presented at the 2012 International Conference on Human Resource Development, Taipei, Taiwan.

    下載圖示
    QR CODE