A comparison of competing theoretical models for understanding acceptance behavior of information systems in upscale hotels

This study investigated which intention-based model, namely: (1) the technology acceptance model (TAM; Model 1); (2) the theory of planned behavior (TPB; Model 2); and (3) the decomposed TPB (DTPB; Model 3) is best for predicting and explaining employees’ behavioral intention to use hotel information system (HIS). Data were obtained from employees of 13 upscale hotels in Jeju, South Korea, and structural equation modeling (SEM) was employed to examine and compare the three competing theoretical models (CTMs) in terms of overall model fit, explanatory power, and paths significance. The findings of this study revealed that if the key objective is to predict behavioral intention to use HIS, the TAM is preferable. However, if the key objective is to explain behavioral intention to use HIS, the DTPB is preferable.

[1]  Roland T. Rust,et al.  Comparing covariance structure models: A general methodology , 1995 .

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

[3]  Peter A. Todd,et al.  Understanding Information Technology Usage: A Test of Competing Models , 1995, Inf. Syst. Res..

[4]  Paul Jen-Hwa Hu,et al.  Information Technology Acceptance by Individual Professionals: A Model Comparison Approach , 2001, Decis. Sci..

[5]  Jae Hyoung Lee,et al.  An empirical examination of the acceptance behaviour of hotel front office systems: An extended technology acceptance model , 2008 .

[6]  T. Lam,et al.  A study of hotel employee behavioral intentions towards adoption of information technology , 2007 .

[7]  Hsiu-Fen Lin,et al.  Predicting consumer intentions to shop online: An empirical test of competing theories , 2007, Electron. Commer. Res. Appl..

[8]  E. Rogers,et al.  Diffusion of Innovations , 1964 .

[9]  H. Akaike.  Factor analysis and AIC , 1987 .

[10]  Richard G. Moore,et al.  The Internet as a Distribution Channel , 1998 .

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

[12]  Echo Huang,et al.  Extending the theory of planned behaviour as a model to explain post-merger employee behaviour of IS use , 2004, Comput. Hum. Behav..

[13]  Fred D. Davis,et al.  Extrinsic and Intrinsic Motivation to Use Computers in the Workplace1 , 1992 .

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

[15]  Thomas J. Page,et al.  The structure and antecedents of the normative and attitudinal components of Fishbein's theory of reasoned action , 1988 .

[16]  James H. Dulebohn,et al.  PERFORMANCE FEEDBACK EFFECTS IN TRAINING: THE ROLE OF PERCEIVED CONTROLLABILITY , 1994 .

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

[18]  M. Browne,et al.  Single Sample Cross-Validation Indices for Covariance Structures. , 1989, Multivariate behavioral research.

[19]  R. Law,et al.  A study of hotel information technology applications , 2005 .

[20]  Fred D. Davis,et al.  A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies , 2000, Management Science.

[21]  I. Ajzen.  The theory of planned behavior , 1991 .

[22]  Cristian Morosan,et al.  Users’ perceptions of two types of hotel reservation Web sites , 2008 .

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

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

[25]  Yong-Ki Lee,et al.  Testing the Determinants of Computerized Reservation System Users’ Intention to Use Via a Structural Equation Model , 2006 .

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

[27]  Peter A. Todd,et al.  Perceived Usefulness, Ease of Use, and Usage of Information Technology: A Replication , 1992, MIS Q..

[28]  Ulrike Gretzel,et al.  Tourism Managers’ Adoption of Marketing Decision Support Systems , 2000 .

[29]  Christine A. Vogt,et al.  A Structural Analysis of Destination Travel Intentions as a Function of Web Site Features , 2006 .

[30]  Judy A. Siguaw,et al.  Best Practices in Information Technology , 1999 .

[31]  James C. Anderson,et al.  STRUCTURAL EQUATION MODELING IN PRACTICE: A REVIEW AND RECOMMENDED TWO-STEP APPROACH , 1988 .

[32]  César Camisón.  Strategic attitudes and information technologies in the hospitality business: an empirical analysis. , 2000 .

[33]  Rolph E. Anderson,et al.  Multivariate data analysis with readings (2nd ed.) , 1986 .

[34]  C. Fornell,et al.  Evaluating structural equation models with unobservable variables and measurement error. , 1981 .

[35]  W. Qualls,et al.  Towards a theoretical model of technology adoption in hospitality organizations , 2007 .

[36]  I. Ajzen,et al.  Understanding Attitudes and Predicting Social Behavior , 1980 .

[37]  Shin-Yuan Hung,et al.  User acceptance of WAP services: test of competing theories , 2005, Comput. Stand. Interfaces.

[38]  Nava Pliskin,et al.  Information Technology in the Hospitality Industry: The Israeli Scene and Beyond , 2001, J. Inf. Technol. Tour..

[39]  Rolph E. Anderson,et al.  Multivariate Data Analysis with Readings , 1979 .

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

[41]  Raduan Che Rose,et al.  The relationship between information technology acceptance and organizational agility in Malaysia , 2005, Inf. Manag..