臺灣博碩士論文加值系統

Personnel Management Information System (PMIS) is one of the most popular software which has been using in Vietnam schools. PMIS has been piloting to about 70% upper secondary schools in Vietnam and in the coming time it will be deployed to all primary and secondary schools.
The main goal of this study is to research the factors which affect user acceptance of PMIS. Based on Technology Acceptance Model (TAM), this study examines the relationship between Information Quality, System Quality, Services Quality, Perceived Usefulness, Perceived Ease of Use, Behavioral Intention to Use and Actual Use of PMIS factors. In order to examine proposed research model, the author conducted a survey by delivering and sending email questionnaires to 250 users came from 75 secondary schools in Dienbien province. After eliminating poor quality responses, there were 222 effective samples. The results indicated the 3 factors: Information Quality, System Quality and Services Quality have positively related to Perceived Usefulness and Perceived Ease of Use, and then Perceived Usefulness and Perceived Ease of Use has positively related Behavioral Intention to Use, and then Behavioral Intention to Use has positively related to Actual Use of PMIS use in the schools.

Abstract i
Acknowledgment iii
Table of Contents iv
List of Tables vi
List of Figures vii
Chapter 1 Introduction 1
1.1 Research Background 1
1.2 Research Motive 4
1.3 Research purposes 5
1.4 Research procedures 5
Chapter 2 Literature Review 7
2.1 Personnel Management in Schools in Vietnam 7
2.2 Personnel Management Information System (PMIS) 9
2.2.1 Management Information System 9
2.2.2 Personnel Management Information System in Vietnam 10
2.3 Technology Acceptance Model 13
Chapter 3 Research Design and Methodology 21
3.1. Research Framework 21
3.2. Research Hypotheses 21
3.3. Operational Measurement for the Research Constructs 22
3.4. Sampling Process 25
3.5. Research Methodology 25
3.5.1. Descriptive Statistics 25
3.5.2. Factor Analysis 26
3.5.3. Reliability Analysis 26
3.5.4. Regression Analysis 26
Chapter 4 Data Analysis and Result 28
4.1. Descriptive Analysis of Sample Demographics 28
4.2. Factor Analysis 31
4.3. Reliability Analysis of the Variables 32
4.3.1 Information Quality of PMIS (INF) 33
4.3.2 System Quality of PMIS (SYS) 34
4.3.3 Service Quality of PMIS (SER) 34
4.3.4 Perceived of usefulness (PER) 35
4.3.5 Perceived ease of use (USE) 36
4.3.6 Behavioral intention to use (BEH) 36
4.3.7 Actual use of the system (ATC) 37
4.3.8 Reliability Analysis of all Variables 38
4.4. Hypothesis testing 38
4.4.1 Linear Regression Analysis for Testing H1 and H3 hypothesis 39
4.4.2 Linear Regression Analysis for Testing H2, H4 and H5 hypotheses 40
4.4.3 Linear Regression Analysis for Testing H7 and H8 hypothesis 41
4.4.4 Linear Regression Analysis for Testing H9 hypothesis 42
Chapter 5 Conclusions and Suggestion 44
5.1. Conclusions 44
5.2. Implications 45
5.3. Limitations 46
References 47
Appendix 53

[1]Agarwal, R., &; Prasad, J. (1999). Are individual differences germane to the acceptance of new information technologies? Decision Sciences, 30(2), 361–391.
[2]Ajzen, I., &; Madden, T. J., 1986, “Prediction of goal-directed behavior: Attitudes, intentions, and perceived behavioral control”, Journal of Experimental Social Psychology, vol. 22, pp. 453-474.
[3]Ajzen, I., 1991, “The Theory of Planned Behavior, Organizational Behavior and Human,” Decision Processes, vol. 50, pp. 179-211.
[4]Al-adaileh, R, 2008. “Essentials of Management Information Systems”, Yazeed Publications, Karak-Jordan.
[5]Amoako-Gyampah, K and Salam, A. F., 2004. An Extension of the Technology Acceptance Model in an ERP Implementation Environment. Information &; Management, 41, pp. 731-745.
[6]Bakos, J. Yannis, and Erik Brynjolfsson, “Information Technology, Incentives, and the Optimal Number of Suppliers,” Journal of Management Information Systems, 10 (2), 1993b.
[7]BooYoung C., Mirosław J. S., Young H. K., 2009. Developing ERP Systems Success Model for the Construction Industry. Journal of Construction Engineering and Management, vol. 135, no.3
[8]Bowling A., (2002). Research Methods in Health. In Investigating health and health services. Second edition. Buckingham, Open University Press.
[9]Cronin, J.J., Taylor, S.A., 1994. SERVPERF versus SERVQUAL: reconciling performance-based and perceptions-minus-expectations measurements of service quality. Journal of Marketing 58, 125–131.
[10]Davis, F. D. (1986). A technology acceptance model for empirically testing new end user information systems: Theory and results. Doctoral dissertation, Sloan School of Management, Massachusetts Institute of Technology, Cambridge, MA.
[11]Davis, F. D., Bagozzi, R. P., &; Warshaw, P. R. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management Science, 35, 982-1003.
[12]Davis, F., Bagozzi, R., &; Warshaw, P. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management Science, 35(8), 982–1003.
[13]Davis, F.D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly 13 (3), 319–342.
[14]Decree No 06/2010/NĐ-CP dated 25/01/2010 of Government for stipulating on civil servant.
[15]Decree No 18/2010/NĐ-CP dated 05/3/2010 of Government for stipulating on civil servant training.
[16]Decree No 21/2010/NĐ-CP dated 08/3/2010 of Government for stipulating on civil servant regular management.
[17]Decree No 24/2010/NĐ-CP dated 15/3/2010 of Government for stipulating on recruitment and managing civil servant.
[18]Decree No 46/2010/NĐ-CP dated 27/4/2010 of Government for stipulating on retirement of civil servant.
[19]DeLone, W.H. &; McLean, E.R, 1992. “Information Systems Success: The Quest for the Dependent Variable”, Information Systems Research, Vol. 3, No. 1, pp. 60--95.
[20]DeLone, W.H. &; McLean, E.R, 1992. “Information Systems Success: The Quest for the Dependent Variable”, Information Systems Research, Vol. 3, No. 1, pp. 60--95.
[21]DeLone, W.H. &; McLean, E.R, 2003. “The DeLone and McLean Model of Information Systems Success: A ten-Year Update”, Journal of Management Information Systems, Vol. 19, No. 4, pp. 9--30.
[22]Eric T.G. Wang and Jessica H.F. Chena. (2006). Effects of internal support and consultant quality on the consulting process and ERP system quality, Decision Support Systems Volume 42, Issue 2, November 2006, Pages 1029-1041.
[23]Ferratt, T. W., Ahire, S., and De, P. (2006). “Achieving success in large projects:
[24]Fishbein, M., &; Ajzen, I. (1975). Belief, attitude, intention and behavior: An introduction to theory and research. MA: Addison-Wesley Reading.
[25]Guest, D. (1990). Human resource management and the American Dream. Journal of Management Studies, 27(4).
[26]Guest, D. (1997). Human resource management and performance: a review and research agenda. International Journal of Human Resource Management, 8(3), 263–276.
[27]Hair, J., Black, W., Babin, B., Anderson, R., &; Tatham, R. (2006). Multivariate Data Analysis (6th ed.). New Jersey: Pearson Educational, Inc.
[28]Hu, P. J., Chau, P. Y. K., Sheng, O. R. L., &; Tam, K. Y. (1999). Exploring the technology acceptance model using physician acceptance of telemedicine technology. Journal of Management Information Systems, 16(2), 91–112.
[29]Implications from a study of ERP implementations.” Interfaces, 365, 458–469
[30]Jackson, C. M., Chow, S., &; Leitch, R. A. (1997). Toward an understanding of the behavioral intention to use an information system. Decision Sciences, 28(2), 357–389.
[31]Kettinger, W.J., and Lee, C.C. Perceived service quality and user satisfaction with the information services function. Decision Sciences, 25, 5–6 (1995), 737–765.
[32]Law of the Civil servant, 2008, No 22/2008/QH12, dated 13/11/2008 of Vietnam Assembly.
[33]Mathieson, K., Peacock, E., &; Chin, W. W. (2001). Extending the technology acceptance model: The influence of perceived user resources. ACM SIGMIS Database, 32(3), 86–112.
[34]Ministry of Education and Training of Vietnam (MOET), 2010, “Educational Statistics of Vietnam”.
[35]Moon JW, Kim YG., 2001. Extending the TAM for a world-wide-web context. Inf. Manage. 38(4): 217-230.
[36]Nelson, R.R., Todd, P.A., Wixom, B.H., 2005. Antecedents of information and system quality: an empirical examination within the context of data warehousing. Journal of Management Information Systems 21, 199–235.
[37]Nunnally, J. C,. &; Bernstein, I. H. (1994). “Psychometric theory (3rd ed.)”, New York, McGraw Hill.
[38]Parasuraman, A., Zeithaml, V.A., Berry, L.L., 1988. SERVQUAL: a multiple item scale for measuring consumer perceptions of service quality. Journal of Retailing 64, 12–40.
[39]Parasuraman, A., Zeithaml, V.A., Berry, L.L., 1988. SERVQUAL: a multiple item scale for measuring consumer perceptions of service quality. Journal of Retailing 64, 12–40.
[40]Pelgrum, W. J. (2001). Obstacles to the integration of ICT in education: results from a worldwide educational assessment. Computers and Education, 37, 163–178.
[41]Secondary School Regulation, 2010, Ministry of Education and Training Vietnam.
[42]Seddon, P.B., 1997. A respecification and extension of the Delone and McLean model of IS success. Information Systems Research 240, 240–253
[43]Sedera, D., Gable, G., 2004. A factor and structural equation analysis of the enterprise systems success measurement model. In: Appelgate, L., Galliers, R., DeGross, J.I. (Eds.), Proceedings of the Twenty-Fifth International Conference on Information Systems. Association for Information Systems, Washington, DC, USA, p. 449.
[44]Sekaran, U, 2004. “Research Methods for Business: A Skill Building Approach”, 4th edition, John Willy &; Sons, Inc.
[45]Sohail, M. and Shanmugham, B., 2003. E-banking and customer preferences in Malaysia: An empirical investigation. Information Sciences, 150, 207 – 217.
[46]Straub, D., Keil, M., &; Brenner, W. (1997). Testing the technology acceptance model across cultures: A three country study. Information &; Management, 33, 1–11.
[47]Taylor, S., Todd, P.A. (1995). Understanding information technology usage: a test of competing models. Information Systems Research 6 (2), 144–176.
[48]Venkatesh, V. (1999). Creation of favorable user perceptions: Exploring the role of intrinsic motivation. MIS Quarterly, 23(2), 239–260.
[49]Wall, T., &; Wood, S. (2005). The romance of human resource management and business Performance and the case for big science. Human Relations, 58(4), 429–462.
[50]Whitrod Brown, H., &; Green, A. (2001). Human resource management in the leisure Industry. In C. Wolsey, &; J. Abrams (Eds.), Understanding the Leisure and Sport Industry. Essex: Pearson Education.