Successful IS innovation: the contingent contributions of innovation characteristics and implementation process

This paper unifies two apparently competing theories of information systems (IS) implementation by developing a model in which the contributions of innovation characteristics and implementation process theories are contingent upon the implementation context. To do this, we identify the different assumptions regarding the implementation context implicit in the two theories and, based on these differences, develop a contingent model within which to integrate the two theories. A partial test of the model within one particular context is reported using data collected from the end-users of an IS innovation introduced in a State health system in Australia. As hypothesized, we find that, within the context, characterized by high individual level impact and low group level impact, the contribution of innovation characteristics to implementation success is higher than that of implementation process.

[1]  Izak Benbasat,et al.  Development of an Instrument to Measure the Perceptions of Adopting an Information Technology Innovation , 1991, Inf. Syst. Res..

[2]  Geoffry S. Howard,et al.  Discretionary Use of Computers: An Empirically Derived Explanatory Model* , 1991 .

[3]  Anol Bhattacherjee,et al.  Explaining the Effect of Incentives and Control Mechanisms on Information Technology Usage: A Theoretical Model and an Empirical Test , 1996, ICIS.

[4]  Robert W. Zmud,et al.  The Nature and Determinants of IT Acceptance, Routinization, and Infusion , 1993, Diffusion, Transfer and Implementation of Information Technology.

[5]  E. Rogers.  Diffusion of Innovations , 1962 .

[6]  Denis M. S. Lee.  Usage Patterns and Sources of Assistance for Personal Computer Users , 1986, MIS Q..

[7]  Michael J. Ginzberg,et al.  Early Diagnosis of MIS Implementation Failure: Promising Results and Unanswered Questions , 1981 .

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

[9]  Randall L. Schultz.  The implementation of forecasting models , 1984 .

[10]  E. F. Stone-Romero,et al.  Relative power of moderated multiple regression and the comparison of subgroup correlation coefficients for detecting moderating effects. , 1994 .

[11]  Neil C. Ramiller,et al.  Perceived compatibility of information technology innovations among secondary adopters: Toward a reassessment , 1994 .

[12]  Jr. Henry C. Lucas,et al.  Performance and the Use of an Information System , 1975 .

[13]  James C. Wetherbe,et al.  The Adoption of Spreadsheet Software: Testing Innovation Diffusion Theory in the Context of End-User Computing , 1990, Inf. Syst. Res..

[14]  T. Bikson,et al.  Factors in Successful Implementation of Computer-Based Office Information Systems: , 1985 .

[15]  Dale Goodhue,et al.  Task-Technology Fit and Individual Performance , 1995, MIS Q..

[16]  Alexander M. Maish.  A User's Behavior Toward His MIS , 1979, MIS Q..

[17]  R. Zmud.  An Examination of Push-Pull Theory Applied to Process Innovation in Knowledge Work , 1984 .

[18]  A. Meyer,et al.  Organizational Assimilation of Innovations: A Multi-Level Contextual Analysis , 1988 .

[19]  Tor Guimaraes,et al.  The Determinants of DSS Success: An Integrated Model* , 1992 .

[20]  F. Damanpour.  Organizational Innovation: A Meta-Analysis Of Effects Of Determinants and Moderators , 1991 .

[21]  J. Dutton,et al.  The Adoption of Radical and Incremental Innovations: An Empirical Analysis , 1986 .

[22]  Maryam Alavi,et al.  Revisiting DSS Implementation Research: A Meta-Analysis of the Literature and Suggestions for Researchers , 1992, MIS Q..

[23]  Chris Sauer,et al.  Why information systems fail: a case study approach , 1993 .

[24]  D. Whetten.  What Constitutes a Theoretical Contribution , 1989 .

[25]  Judy Bayer,et al.  A critique of diffusion theory as a managerial framework for understanding adoption of software engineering innovations , 1989, [1988] Proceedings of the Twenty-First Annual Hawaii International Conference on System Sciences. Volume II: Software track.

[26]  Philip Yetton,et al.  Computer-aided architects: A case study of IT and strategic change , 1994 .

[27]  T. H. Kwon,et al.  Unifying the fragmented models of information systems implementation , 1987 .

[28]  J. Nunnally.  Psychometric Theory (2nd ed), New York: McGraw-Hill. , 1978 .

[29]  James D. Thompson.  Organizations in Action , 1967 .

[30]  James F. Courtney,et al.  A Field Study of Organizational Factors Influencing DSS Success , 1985, MIS Q..

[31]  M. Ginzberg.  An organizational contingencies view of accounting and information systems implementation , 1980 .

[32]  K. Klein,et al.  The Challenge of Innovation Implementation , 1996 .

[33]  Dorothy Leonard-Barton,et al.  Implementing Structured Software Methodologies: A Case of Innovation in Process Technology , 1987 .

[34]  Henri Barki,et al.  Change, attitude to change, and decision support system success , 1985, Inf. Manag..

[35]  Jane M. Howell,et al.  Personal Computing: Toward a Conceptual Model of Utilization , 1991, MIS Q..

[36]  D. Leonard-Barton,et al.  Managerial influence in the implementation of new technology , 1988 .

[37]  Jacob Cohen,et al.  Applied multiple regression/correlation analysis for the behavioral sciences , 1979 .

[38]  Sundeep Sahay,et al.  Transforming Work Through Information Technology: A Comparative Case Study of Geographic Information Systems in County Government , 1996, Inf. Syst. Res..

[39]  Paul H. Cheney,et al.  Concepts, Theory, and Techniques: FACTORS AFFECTING THE PERCEIVED UTILIZATION OF COMPUTER-BASED DECISION SUPPORT SYSTEMS IN THE OIL INDUSTRY , 1982 .

[40]  Robert G. Fichman,et al.  International Conference on Information Systems ( ICIS ) 1992 INFORMATION TECHNOLOGY DIFFUSION : A REVIEW OF EMPIRICAL RESEARCH , 2017 .

[41]  Albert H. Segars,et al.  Re-examining perceived ease of use and usefulness , 1993 .

[42]  Robert W. Zmud,et al.  The Effectiveness of External Information Channels in Facilitating Innovation Within Software Development Groups , 1983, MIS Q..

[43]  AttewellPaul.  Technology Diffusion and Organizational Learning , 1992 .

[44]  J. Cockcroft.  The process of technological innovation , 1965 .

[45]  C. R. Franz,et al.  ORGANIZATIONAL CONTEXT, USER INVOLVEMENT, AND THE USEFULNESS OF INFORMATION SYSTEMS* , 1986 .

[46]  R. Zmud,et al.  Information technology implementation research: a technological diffusion approach , 1990 .

[47]  Henry C. Lucas,et al.  The use of an interactive information storage and retrieval system in medical research , 1978, CACM.

[48]  Wanda J. Orlikowski,et al.  Implementing Radical Change: Gradual Versus Rapid Pace , 2018, ICIS.

[49]  P. Attewell.  Technology Diffusion and Organizational Learning: The Case of Business Computing , 1992 .

[50]  Michael Hammer,et al.  Reengineering Work: Don’t Automate, Obliterate , 1990 .

[51]  Henri Barki,et al.  Explaining the Role of User Participation in Information System Use , 1994 .

[52]  L. G. Tornatzky,et al.  Innovation characteristics and innovation adoption-implementation: A meta-analysis of findings , 1982, IEEE Transactions on Engineering Management.

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

[54]  Rajiv Sabherwal,et al.  Overcoming the problems in information systems development by building and sustaining commitment , 1995 .