An extension of trust and TAM model with IDT in the adoption of the electronic logistics information system in HIS in the medical industry

International Journal of Medical Informatics

Volumn 77, Issue 5, 2008, Pages 324-335

  Tung, Feng Cheng ^a,b   Chang, Su Chao ^a   Chou, Chi Min ^c  

^a NATIONAL CHENG KUNG UNIVERSITY   (Taiwan)

^b DIWAN COLLEGE OF MANAGEMENT   (Taiwan)

^c TAJEN UNIVERSITY   (Taiwan)

Author keywords

e Logistics information system; Hospital information systems; Innovation diffusion theory; Technology acceptance model; Trust

Indexed keywords

BUDGET CONTROL; COST ACCOUNTING; HEALTH INSURANCE; INFORMATION RETRIEVAL SYSTEMS; MATHEMATICAL MODELS;

E-LOGISTICS INFORMATION SYSTEM; HOSPITAL INFORMATION SYSTEMS; INNOVATION DIFFUSION THEORY; TECHNOLOGY ACCEPTANCE MODEL;

MEDICAL COMPUTING;

ARTICLE; HEALTH CARE FACILITY; HEALTH INSURANCE; HOSPITAL COST; HOSPITAL INFORMATION SYSTEM; HUMAN; INFORMATION PROCESSING; MEDICAL PRACTICE; MEDICAL RESEARCH; NATIONAL HEALTH INSURANCE; NURSE; NURSE ATTITUDE; PRIORITY JOURNAL; STRUCTURAL EQUATION MODELING; THEORETICAL MODEL;

ADULT; ATTITUDE OF HEALTH PERSONNEL; ATTITUDE TO COMPUTERS; BEHAVIOR; COMPUTER USER TRAINING; DIFFUSION OF INNOVATION; ECONOMICS, NURSING; FEMALE; HEALTH CARE SECTOR; HOSPITAL INFORMATION SYSTEMS; HUMANS; INTENTION; INTERNET; MODELS, PSYCHOLOGICAL; NATIONAL HEALTH INSURANCE, UNITED STATES; NURSES; NURSING INFORMATICS; TASK PERFORMANCE AND ANALYSIS; TRUST; UNITED STATES;

EID: 41249095009     PISSN: 13865056     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ijmedinf.2007.06.006     Document Type: Article

References (70)

1. Ammenwerth E., Gräber S., Herrmann G., Bürkle T., and König J. Evaluation of health information systems-problems and challenges. Int. J. Med. Inform. 71 (2003) 125-135
2. Reuss E., Menozzi M., Büchi M., Koller J., and Krueger H. Information access at the point of care: what can we learn for designing a mobile CPR system?. Int. J. Med. Inform. 73 (2004) 363-369
3. Bång M., Larsson A., Berglund E., and Eriksson H. Distributed user interfaces for clinical ubiquitous computing applications. Int. J. Med. Inform. 74 (2005) 545-551
4. Lu Y.C., Xiao Y., Sears A., and Jacko J.A. A review and a framework of handheld computer adoption in healthcare. Int. J. Med. Inform. 74 (2005) 409-422
5. Smith A.D., and Manna D.R. Exploring the trust factor in e-medicine. Online Inform. Rev. 28 (2004) 346-355
6. Berglund M., Nilsson C., Révay P., Petersson G., and Nilsson G. Nurses' and nurse students' demands of functions and usability in a PDA. Int. J. Med. Inform. 76 (2007) 530-537
7. Kluge E.W. Secure e-health: managing risks to patient health data. Int. J. Med. Inform. 76 (2007) 402-406
8. Scott R.E. e-Records in health-preserving our future. Int. J. Med. Inform. 76 (2007) 427-431
9. Croll P.R., and Croll J. Investigating risk exposure in e-health systems. Int. J. Med. Inform. 76 (2007) 460-465
10. Agrawal R., and Johnson C. Securing electronic health records without impeding the flow of information. Int. J. Med. Inform. 76 (2007) 471-479
11. Sucurovic S. Implementing security in a distributed web-based EHCR. Int. J. Med. Inform. 76 (2007) 491-496
12. Knaup P., Garde S., and Haux R. Systematic planning of patient records for cooperative care and multicenter research. Int. J. Med. Inform. 76 (2007) 109-117
13. Lacramioara S., and Vasile S. Human-computer interaction reflected in the design of user interfaces for general practitioners. Int. J. Med. Inform. 75 (2006) 335-342
14. F.D. Davis, A Technology Acceptance Model for Empirically Testing New End-user Information System: Theory and Results, Ph.D. Dissertation, Cambridge, MA, MIT Sloan School of Management, 1986.
15. Davis F.D., Bagozzi R.P., and Warshaw P.R. User acceptance of computer technology: a comparison of two theoretical models. Manage. Sci. 35 (1989) 982-1002
16. Ong C.H., Lai J.Y., and Wang Y.S. Factors affecting engineers' acceptance of asynchronous e-learning systems in high-tech companies. Inform. Manage. 41 (2004) 795-804
17. Luarn P., and Lin H.H. Toward an understanding of the behavioral intention to use mobile banking. Comput. Hum. Behav. 21 (2005) 873-891
18. Closs D.J., and Savitskie K. Internal and external logistics information technology integration. Int. J. Logist. Manage. 14 (2003) 63-76
19. Gulati R., and Garino J. Get the right mix of bricks and clicks. Harvard Bus. Rev. 78 (2000) 107-114
20. Natesan C.N. The impact of the Internet on health care services. J. Am. Acad. Bus. 7 (2005) 247-251
21. Dutta-Bergman M.J. The impact of completeness and web use motivation on the credibility of e-health information. J. Commun. 54 (2004) 253-269
22. Mukherji A., and Mukherji J. Structuring organizations for the future: analyzing and managing change. Manage. Decis. 36 (1998) 265-273
23. Feraud G.J.S. Improving strategic decision making in logistics information management-a framework. Logist. Inform. Manage. 11 (1998) 232-243
24. Christopher M. Marketing Logistics (1997), Butterworth-Heineman, Oxford
25. Murphy P.R., and Wood D.F. Contemporary Logistics. 8th ed. (2004), Prentice-Hall, Upper Saddle River, NJ
26. Langley C.J.J., Carlisle D.P., Probst S.B., Biggs D.F., and Cail R.E. Microcomputers as a logistics information strategy. Int. J. Phys. Distrib. Logist. Manage. (Bradford) 25 (1995) 61-72
27. Bowersox D.J., and Closs D.J. Logistics Management (1996), McGraw-Hill Companies Inc., Singapore
28. Prindezis N., and Kiranoudis C.T. An internet-based logistics management system for enterprise chains. J. Food Eng. 70 (2005) 373-381
29. Gunasekaran A., and Ngai E.W.T. Information systems in supply chain integration and management. Eur. J. Oper. Res. 159 (2004) 269-295
30. Ajzen I., and Fishbein M. Belief, Attitude, Intention, and Behavior: An Introduction to Theory and Research (1975), Addison-Wesley, Reading, MA
31. Ajzen I. The theory of planned behavior. Organ Behav. Hum. Decis. Process. 50 (1991) 179-211
32. Taylor S., and Todd P.A. Understanding information technology usage: a test of competing models. Inform. Syst. Res. 6 (1995) 144-176
33. Segars A.H., and Grover V. Re-examining perceived ease of use and usefulness: a confirmatory factor analysis. MIS Quart. 17 (1993) 517-525
34. Chin W.C., and Todd P.A. On the use, usefulness and ease of use of structural equation modeling in MIS research: a note of caution. MIS Quart. 19 (1995) 237-246
35. Doll W.J., Hendrickson A., and Deng X. Using Davis's perceived usefulness and ease-of-use instruments for decision making: a confirmatory and multi-group invariance analysis. Decis. Sci. 29 (1998) 839-869
36. Venkatesh V., and Davis F.D. A theoretical extension of the technology acceptance model: four longitudinal field studies. Manage. Sci. 46 (2000) 186-204
37. Agarwal R., and Karahanna E. Time flies when you're having fun: cognitive absorption and beliefs about information technology usage. MIS Quart. 24 (2000) 665-694
38. Karahanna E., Straub D.W., and Chervany N.L. Information technology adoption across time: a cross-sectional comparison of pre-adoption and post-adoption beliefs. MIS Quart. 23 (1999) 183-213
39. Rogers E.M. The Diffusion of Innovation. 4th ed. (1995), Free Press, New York
40. Agarwal R., and Prasad J.A. Conceptual and operational definition of personal innovativeness in the domain of information technology. Inform. Syst. Res. 9 (1998) 204-215
41. Paré G., and Trudelb M.C. Knowledge barriers to PACS adoption and implementation in hospitals. Int. J. Med. Inform. 76 (2007) 22-33
42. Moore G.C., and Benbasat I. Development of instrument to measure the perceptions of adopting an information technology innovation. Inform. Syst. Res. 2 (1991) 192-222
43. Chen L.D., Gillenson M.L., and Sherrell D.L. Enticing online consumers: an extended technology acceptance perspective. Inform. Manage. 39 (2002) 705-719
44. Wu J.H., and Wang S.C. What drives mobile commerce? An empirical evaluation of the revised technology acceptance model. Inform. Manage. 42 (2005) 719-729
45. Wu J.H., Wang S.C., and Lin L.M. Mobile computing acceptance factors in the healthcare industry: a structural equation model. Int. J. Med. Inform. 76 (2007) 66-77
46. Doney P.M., Cannon J.P., and Mullen M.R. Understanding the influence of national culture on the development of trust. Acad. Manage. Rev. 23 (1998) 601-620
47. Garbarino E., and Johnson M.S. The different roles of satisfaction, trust, and commitment in customer relationships. J. Mark. 63 (1999) 70-87
48. Moorman C., Deshpande R., and Zaltman G. Factors affecting trust in market research relationships. J. Mark. 57 (1993) 81-102
49. Luhmann N. Trust and Power (1979), Wiley, Chichester, England
50. Grabner-Kraeuter S. The role of consumers' trust in online-shopping. J. Bus. Ethics 39 (2002) 43-50
51. Gefen D. What makes an ERP implementation relationship worthwhile: linking trust mechanisms and ERP usefulness. J. Manage. Inform. Syst. 21 (2004) 263-288
52. Gefen D., Karahanna E., and Straub D. Trust and TAM in online shopping: an integrated model. MIS Quart. 27 (2003) 51-90
53. Gefen D., Karahanna E., and Straub D. Inexperience and experience with online stores: the importance of TAM and Trust. IEEE Trans. Eng. Manage. 50 (2003) 307-321
54. Pavlou P.A. Consumer acceptance of electronic commerce-integrating trust and risk with the technology acceptance model. Int. J. Electron. Commerce 7 (2003) 69-103
55. Saeed K.A., Hwang Y., and Yi M.Y. Toward an integrative framework for online consumer behavior research: a meta-analysis approach. J. End User Comput. 15 (2003) 1-26
56. Wu I.L., and Chen J.L. An extension of Trust and TAM model with TPB in the initial adoption of online tax: an empirical study. Int. J. Hum. Comput. Stud. 62 (2005) 784-808
57. Smith A.D. Barriers to accepting e-prescribing in the USA. Int. J. Health Care Qual. Assur. 19 (2006) 158-180
58. Mathieson K., Peacock E., and Chin W.W. Extending the technology acceptance model: the influence of perceived user resources. Data Base Adv. Inform. Syst. 32 (2001) 86-112
59. Venkatesh V., and Davis F.D. A model of the antecedents of perceived ease of use: development and test. Decis. Sci. 27 (1996) 451-481
60. Ding L., Velicer W., and Harlow L. Effects of estimation methods, number of indicators per factor and improper solutions on structural equation modeling fit indices. Struct. Equat. Model. 2 (1995) 119-143
61. Bagozzi R.P., and Yi Y. On the evaluation structural equation models. Acad. Mark. Sci. 16 (1988) 74-94
62. Hair J.F., Anderson R.E., Tatham R.L., and Black W.C. Multivariate Data Analysis with Reading. 3rd ed. (1992), Macmillan, New York
63. Fornell C., and Larcker D.F. Evaluating structural equation models with unobervables and measurement error. J. Mark. Res. 18 (1981) 39-50
64. Bentler P.M., and Bonett D.G. Significance tests and goodness of fit in the analysis of covariance structures. Psychol. Bull. 80 (1980) 594-606
65. MacCallum R.C., Browne M.W., and Sugawara H.W. Power analysis and determination of sample size for covariance structure modeling. Psychol. Methods 1 (1996) 130-149
66. Jöreskog K.G., and Sörbom D. Recent developments in structural equation modeling. J. Mark. Res. 19 4 (1982) 404-416
67. Bentler P.M., and Bonett D.G. Significance tests and goodness of fit in the analysis of covariance structures. Psychol. Bull. 88 (1980) 588-606
68. Tucker L.R., and Lewis C. A reliability coefficient for maximum likelihood factor analysis. Psychometrika 38 (1973) 1-10
69. Bentler P.M. Comparative fit indexes in structural models. Psychol. Bull. 107 (1990) 238-246
70. Browne M.W., and Cudeck R. Alternative ways of assessing model fit. In: Bollen K.A., and Long J.S. (Eds). Testing Structural Equation Models (1993), Sage, Thousand Oaks, CA 136-162