The impact of service level on the acceptance of application service oriented medical records

Service level is considered to be the most important criterion in evaluating application services. In our study we empirically investigated how perceived service level (PSL) influenced healthcare workers' willingness to use application service oriented medical records. In particular, we extended the technology acceptance model (TAM) by embedding PSL as a causal antecedent. We found that PSL explained 61% of the variation in ease of use, which is twice as much as our current understanding. We also found that TAM was validated when tested in isolation but failed within the larger nomological network. We provided an explanation based on the notion of conditional independence. We further applied TETRAD III to explore the phenomenon and discovered two spurious associations in TAM, successfully confirming the explanation.

[1]  Ian Foster,et al.  The Grid 2 - Blueprint for a New Computing Infrastructure, Second Edition , 1998, The Grid 2, 2nd Edition.

[2]  Mark Keil,et al.  Usefulness and ease of use: field study evidence regarding task considerations , 1995, Decis. Support Syst..

[3]  P ? ? ? ? ? ? ? % ? ? ? ? , 1991 .

[4]  Michael Stal,et al.  Web services: beyond component-based computing , 2002, CACM.

[5]  P. Wilton,et al.  Models of Consumer Satisfaction Formation : An Extension , 1988 .

[6]  Peter M. Bentler,et al.  Practical Issues in Structural Modeling , 1987 .

[7]  R. Sturm,et al.  Foundations of Service Level Management , 2000 .

[8]  Fred D. Davis.  A technology acceptance model for empirically testing new end-user information systems : theory and results , 1985 .

[9]  Detmar W. Straub,et al.  Gender Differences in the Perception and Use of E-Mail: An Extension to the Technology Acceptance Model , 1997, MIS Q..

[10]  Thomas K. Landauer,et al.  The trouble with computers , 1995 .

[11]  Charles D. Barrett.  Understanding Attitudes and Predicting Social Behavior , 1980 .

[12]  D. Leonard-Barton,et al.  Implementation as mutual adaptation of technology and organization , 1988 .

[13]  Thomas K. Landauer,et al.  Trouble with Computers: Usefulness, Usability, and Productivity , 1996 .

[14]  Lawrence Loh,et al.  Diffusion of Information Technology Outsourcing: Influence Sources and the Kodak Effect , 1992, Inf. Syst. Res..

[15]  P. Spirtes,et al.  Causation, prediction, and search , 1993 .

[16]  Ami Marowka,et al.  The GRID: Blueprint for a New Computing Infrastructure , 2000, Parallel Distributed Comput. Pract..

[17]  Peter A. Todd,et al.  Assessing IT usage: the role of prior experience , 1995 .

[18]  Fred D. Davis,et al.  User Acceptance of Computer Technology: A Comparison of Two Theoretical Models , 1989 .

[19]  Alina M. Chircu,et al.  Trust, Expertise, and E-Commerce Intermediary Adoption , 2000 .

[20]  Olivia R. Liu Sheng,et al.  Examining the Technology Acceptance Model Using Physician Acceptance of Telemedicine Technology , 1999, J. Manag. Inf. Syst..

[21]  Gregory F. Cooper,et al.  A Bayesian Method for the Induction of Probabilistic Networks from Data , 1992 .

[22]  Michael D. Johnson.  Customer Orientation and Market Action , 1997 .

[23]  Varun Grover,et al.  The Effect of Service Quality and Partnership on the Outsourcing of Information Systems Functions , 1996, J. Manag. Inf. Syst..

[24]  Sir Ronald A. Fisher.  Smoking: The Cancer Controversy , 1960 .

[25]  Fred D. Davis.  Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology , 1989, MIS Q..

[26]  Daniel L. Sherrell,et al.  Communications of the Association for Information Systems , 1999 .

[27]  D. A. Kenny,et al.  The moderator-mediator variable distinction in social psychological research: conceptual, strategic, and statistical considerations. , 1986, Journal of personality and social psychology.

[28]  M. S. Dixon,et al.  Values , 2000, Pediatrics.

[29]  Liping Liu,et al.  Emerging e-business technologies for electronic medical records , 2003 .

[30]  Paul Jen-Hwa Hu,et al.  Investigating healthcare professionals' decisions to accept telemedicine technology: an empirical test of competing theories , 2002, Inf. Manag..

[31]  Waegemann Cp.  The vision of electronic health records. , 2002 .

[32]  John Ingham,et al.  Why do people use information technology? A critical review of the technology acceptance model , 2003, Inf. Manag..

[33]  Anol Bhattacherjee,et al.  Understanding Information Systems Continuance: An Expectation-Confirmation Model , 2001, MIS Q..

[34]  Rohan Jayasuriya,et al.  Determinants of microcomputer technology use: implications for education and training of health staff , 1998, Int. J. Medical Informatics.

[35]  Detmar W. Straub,et al.  The Effect of Culture on IT Diffusion: E-Mail and FAX in Japan and the U.S , 1994, Inf. Syst. Res..

[36]  P. Kidwell,et al.  The trouble with computers: Usefulness, usability and productivity , 1996, IEEE Annals of the History of Computing.

[37]  Wynne W. Chin,et al.  Adoption intention in GSS: relative importance of beliefs , 1995, DATB.

[38]  I. Ajzen,et al.  Belief, Attitude, Intention, and Behavior: An Introduction to Theory and Research , 1977 .

[39]  Jon Kleinberg,et al.  The Structure of the Web , 2001, Science.

[40]  Daniel E. Sichel,et al.  The Computer Revolution: An Economic Perspective , 1997 .

[41]  Frederick G. Conrad,et al.  A heuristic evaluation of a World Wide Web prototype , 1996, INTR.

[42]  Gregory F. Cooper,et al.  A Bayesian method for the induction of probabilistic networks from data , 1992, Machine Learning.

[43]  Fred D. Davis,et al.  A Model of the Antecedents of Perceived Ease of Use: Development and Test† , 1996 .

[44]  Sammy W. Pearson,et al.  Development of a Tool for Measuring and Analyzing Computer User Satisfaction , 1983 .

[45]  Andrew B. Whinston,et al.  Discovery and Representation of Causal Relationships in MIS Research: A Methodological Framework , 1997, MIS Q..

[46]  W. DeSarbo,et al.  Response Determinants in Satisfaction Judgments , 1988 .

[47]  Franz von Kutschera,et al.  Causation , 1993, J. Philos. Log..

[48]  Gilbert A. Churchill,et al.  An Investigation into the Determinants of Customer Satisfaction , 1982 .

[49]  Qingxiong Ma,et al.  The Technology Acceptance Model: A Meta-Analysis of Empirical Findings , 2004, J. Organ. End User Comput..

[50]  Richard Scheines,et al.  Discovering Causal Structure: Artificial Intelligence, Philosophy of Science, and Statistical Modeling , 1987 .

[51]  Kalle Lyytinen,et al.  THE POVERTY OF SCIENTISM IN INFORMATION SYSTEMS , 2000 .

[52]  E. A. Locke.  The nature and causes of job satisfaction , 1976 .

[53]  Christopher Ferris,et al.  What are Web services? , 2003, CACM.

[54]  R. Scheines.  Inferring causal structure among unmeasured variables , 1994 .

[55]  Young-Gul Kim,et al.  Extending the TAM for a World-Wide-Web context , 2000, Inf. Manag..

[56]  R. Oliver.  Measurement and evaluation of satisfaction processes in retail settings. , 1981 .

[57]  L. Beach,et al.  A Contingency Model for the Selection of Decision Strategies , 1978 .

[58]  Detmar W. Straub,et al.  Structural Equation Modeling and Regression: Guidelines for Research Practice , 2000, Commun. Assoc. Inf. Syst..

[59]  Dennis Gannon,et al.  A Revised Analysis of the Open Grid Services Infrastructure , 2002, Comput. Artif. Intell..

[60]  Hai Zhuge,et al.  China's E-Science Knowledge Grid Environment , 2004, IEEE Intell. Syst..

[61]  H. Simon,et al.  Spurious Correlation: A Causal Interpretation* , 1954 .

[62]  Albert L. Lederer,et al.  The technology acceptance model and the World Wide Web , 2000, Decis. Support Syst..

[63]  R. Hirschheim,et al.  Information systems outsourcing : myths, metaphors, and realities , 1993 .

[64]  Lori Mac Vittie.  Business applications , 2002 .

[65]  J. Pearl.  Causality: Models, Reasoning and Inference , 2000 .

[66]  Jie Liu,et al.  Flexible retrieval of Web Services , 2004, J. Syst. Softw..

[67]  Dawna Travis Dewire.  Application Service Providers , 2000, Inf. Syst. Manag..

[68]  Lada A. Adamic,et al.  Power-Law Distribution of the World Wide Web , 2000, Science.

[69]  G. G. Stokes.  "J." , 1890, The New Yale Book of Quotations.

[70]  Detmar W. Straub,et al.  The Relative Importance of Perceived Ease of Use in IS Adoption: A Study of E-Commerce Adoption , 2000, J. Assoc. Inf. Syst..

[71]  Richard Scheines,et al.  Simulation Studies of the Reliability of Computer-Aided Model Specification Using the TETRAD II, EQS, and LISREL Programs , 1990 .

[72]  Magid Igbaria,et al.  Personal Computing Acceptance Factors in Small Firms: A Structural Equation Model , 1997, MIS Q..

[73]  N. Wermuth,et al.  Graphical and recursive models for contingency tables , 1983 .

[74]  Sonja Wiley-Patton,et al.  Does the extended technology acceptance model apply to physicians , 2003, 36th Annual Hawaii International Conference on System Sciences, 2003. Proceedings of the.

[75]  이훈,et al.  지각된 유용성(Perceived Usefulness)의 영향분석 , 2004 .

[76]  James R. Evans,et al.  The management and control of quality , 1989 .

[77]  William J. Doll,et al.  The Measurement of End-User Computing Satisfaction , 1988, MIS Q..

[78]  H C Triandis,et al.  Values, attitudes, and interpersonal behavior. , 1980, Nebraska Symposium on Motivation. Nebraska Symposium on Motivation.

[79]  Gilbert A. Churchill.  A Paradigm for Developing Better Measures of Marketing Constructs , 1979 .

[80]  Andrew B. Whinston,et al.  Understanding the Service Component of Application Service Provision: An Empirical Analysis of Satisfaction with ASP Services , 2003, MIS Q..

[81]  David Gefen,et al.  The impact of developer responsiveness on perceptions of usefulness and ease of use: an extension of the technology acceptance model , 1998, DATB.

[82]  Richard Scheines,et al.  TETRAD II : tools for causal modeling , 1994 .

[83]  David Hartman,et al.  Multisource effects on the satisfaction formation process , 1994 .

[84]  Viswanath Venkatesh,et al.  Determinants of Perceived Ease of Use: Integrating Control, Intrinsic Motivation, and Emotion into the Technology Acceptance Model , 2000, Inf. Syst. Res..