Library mobile applications in university libraries

Purpose – This research aims to integrate the unified theory of acceptance and usage of technology (UTAUT) with task technology fit to explain users' behavioral intention of using library mobile applications in university libraries. Design/methodology/approach – By integrating the unified theory of acceptance and usage of technology (UTAUT) and the moderator of task-technology fit, this research proposes a library mobile applications usage intention model. The study data come from a convenience sample of 363 undergraduate and graduate students. A structural equation modelling (SEM) technique was conducted to identify causal relationships. Findings – Results showed that the UTAUT model fits the data well. The empirical data reveal that performance expectancy, effort expectancy, social influence, and facilitating conditions determine users' behavioral intention of using library mobile applications. As a determinant in the UTAUT model, the moderating effect of task-technology fit is also significant. Moreove...

[1]  P. Bentler,et al.  Cutoff criteria for fit indexes in covariance structure analysis : Conventional criteria versus new alternatives , 1999 .

[2]  Ludwig Christian Schaupp,et al.  E-file adoption: A study of U.S. taxpayers' intentions , 2010, Comput. Hum. Behav..

[3]  Diane M. Strong,et al.  Extending the technology acceptance model with task-technology fit constructs , 1999, Inf. Manag..

[4]  Christer Carlsson,et al.  Adoption of Mobile Devices/Services — Searching for Answers with the UTAUT , 2006, Proceedings of the 39th Annual Hawaii International Conference on System Sciences (HICSS'06).

[5]  Aleda V. Roth,et al.  B2B seller competence: Construct development and measurement using a supply chain strategy lens , 2007 .

[6]  Yuan Sun,et al.  Extending technology usage to work settings: The role of perceived work compatibility in ERP implementation , 2009, Inf. Manag..

[7]  Jayashree Sreenivasan,et al.  A conceptual framework on mobile commerce acceptance and usage among Malaysian consumers: the influence of location, privacy, trust and purchasing power , 2010 .

[8]  Gordon B. Davis,et al.  User Acceptance of Information Technology: Toward a Unified View , 2003, MIS Q..

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

[10]  M. Browne,et al.  Alternative Ways of Assessing Model Fit , 1992 .

[11]  Héctor San Martín,et al.  Influence of the user's psychological factors on the online purchase intention in rural tourism: integrating innovativeness to the UTAUT framework. , 2012 .

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

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

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

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

[16]  Peter M. Bentler,et al.  EQS : structural equations program manual , 1989 .

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

[18]  Chang-Bong Kim,et al.  Exploring the Black Box of Task-Technology Fit , 2014 .

[19]  P. Bentler,et al.  Comparative fit indexes in structural models. , 1990, Psychological bulletin.

[20]  Jochen Schiller,et al.  Location Based Services , 2004 .

[21]  Xinran Y. Lehto,et al.  Adoption of Mobile Technologies for Chinese Consumers , 2007 .

[22]  Richard T. Watson,et al.  Location-based services , 2008, CACM.

[23]  Tung-Ching Lin,et al.  Understanding knowledge management system usage antecedents: An integration of social cognitive theory and task technology fit , 2008, Inf. Manag..

[24]  Edward Iglesias,et al.  Mobile website development: From site to app , 2011 .

[25]  Catherine E. Connelly,et al.  Identifying the ideal fit between mobile work and mobile work support , 2010, Inf. Manag..

[26]  Yan Xu,et al.  Examining user acceptance of SMS: An empirical study in China and Hong Kong , 2008, PACIS.

[27]  P. Bentler,et al.  Significance Tests and Goodness of Fit in the Analysis of Covariance Structures , 1980 .

[28]  Aleda V. Roth,et al.  New service development competence in retail banking: Construct development and measurement validation , 2007 .

[29]  Heshan Sun,et al.  The role of moderating factors in user technology acceptance , 2006, Int. J. Hum. Comput. Stud..

[30]  Tao Zhou,et al.  Integrating TTF and UTAUT to explain mobile banking user adoption , 2010, Comput. Hum. Behav..

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

[32]  Hsing Kenneth Cheng,et al.  An empirical study of mobile commerce in insurance industry: Task-technology fit and individual differences , 2007, Decis. Support Syst..

[33]  Tao Zhou,et al.  Examining Location-Based Services Usage from the Perspectives of Unified Theory of Acceptance and Use of Technology and Privacy Risk , 2012 .

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

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

[36]  J. S. Long,et al.  Testing Structural Equation Models , 1993 .

[37]  Subhash Sharma,et al.  Identification and Analysis of Moderator Variables , 1981 .

[38]  Yu-Chen Chen,et al.  Why People Blog? An Empirical Investigations of the Task Technology Fit Model , 2007, PACIS.