Modelling IS upgrade intention, its mediator and antecedents: a two-wave survey

The purpose of this study is to explore key determinants and mediator that drive IS upgrade intention based on information asymmetry theory. Sample subjects for our survey were drawn from the student population of a large national technology university in Taiwan. The factors in this study were measured using five-point Likert scales adapted from existing literature. Perceived usefulness, perceived ease of use, and professional influence were measured in the first survey while the other factors were measured in the second survey 2 months later. A two-step structural equation modelling procedure was employed for statistical analysis. The empirical findings show that perceived usefulness and professional influence negatively affects upgrade intention via the full mediation of perceived uncertainty. Meanwhile, upgrade intention is negatively affected by information asymmetry. This study provides an illustrative example of how to set up an upgrade intention model based on information asymmetry theory. This study also demonstrates how different an upgrade intention model can be versus usage models such as technology acceptance model and unified theory of acceptance and use of technology in previous research.

[1]  Joseph S. Valacich,et al.  Breaking the Ice in B2C Relationships: Understanding Pre-Adoption E-Commerce Attraction , 2013, Inf. Syst. Res..

[2]  Lalit Wankhade,et al.  Quality Uncertainty Due to Information Asymmetry , 2010 .

[3]  George A. Akerlof The Market for “Lemons”: Quality Uncertainty and the Market Mechanism , 1970 .

[4]  Anol Bhattacherjee,et al.  Understanding online social support and its antecedents: A socio-cognitive model , 2009 .

[5]  Moez Limayem,et al.  Understanding information systems continuance: The case of Internet-based learning technologies , 2008, Inf. Manag..

[6]  Mao-Jiun J. Wang,et al.  A comprehensive framework for selecting an ERP system , 2004 .

[7]  Daniel Roland,et al.  Information asymmetry and product valuation: an exploratory study , 2009, J. Inf. Sci..

[8]  M. T. Mathisen,et al.  University-affiliated Venture Capital funds: funding of University Spin-Off companies , 2009 .

[9]  Pin Luarn,et al.  AIS Electronic Library (AISeL) , 2017 .

[10]  Yogesh Kumar Dwivedi,et al.  Examining Adoption Behavior of Mobile Government , 2012, J. Comput. Inf. Syst..

[11]  S. Shane,et al.  The Individual-Opportunity Nexus , 2003 .

[12]  Vallabh Sambamurthy,et al.  Sources of Influence on Beliefs about Information Technolgoy Use: An Empirical Study of Knowledge Workers , 2003, MIS Q..

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

[14]  S. Wheeler The barriers to further adoption of organic farming and genetic engineering in Australia: views of agricultural professionals and their information sources , 2008, Renewable Agriculture and Food Systems.

[15]  Praveen R. Nayyar,et al.  Information asymmetries: a source of competitive advantage for diversified service firms , 1990 .

[16]  Bernadette Szajna,et al.  Empirical evaluation of the revised technology acceptance model , 1996 .

[17]  H. Raghav Rao,et al.  A trust-based consumer decision-making model in electronic commerce: The role of trust, perceived risk, and their antecedents , 2008, Decis. Support Syst..

[18]  Steven Boivie,et al.  Sorting things out: valuation of new firms in uncertain markets , 2004 .

[19]  Jinfang Niu,et al.  Documentation evaluation model for social science data , 2008, ASIST.

[20]  J. Bettman,et al.  Effects of Prior Knowledge and Experience and Phase of the Choice Process on Consumer Decision Processes: A Protocol Analysis , 1980 .

[21]  Lance A. Young,et al.  Information Asymmetry, Information Dissemination and the Effect of Regulation FD on the Cost of Capital , 2007 .

[22]  L. Izquierdo,et al.  The impact of quality uncertainty without asymmetric information on market efficiency , 2007 .

[23]  The European Road Pricing Game: How to Enforce Optimal Pricing in High-Transit Countries Under Asymmetric Information , 2011 .

[24]  Larry Hatcher,et al.  A Step-by-Step Approach to Using the SAS System for Factor Analysis and Structural Equation Modeling , 1994 .

[25]  J. Hove,et al.  Emotional Determinants of Support for the Canadian Mission in Afghanistan: A View from the Bridge , 2010, Canadian Journal of Political Science.

[26]  Laurie T. O’Brien,et al.  System-justifying ideologies and academic outcomes among first-year Latino college students. , 2011, Cultural diversity & ethnic minority psychology.

[27]  S. Jex,et al.  Coworker incivility and incivility targets' work effort and counterproductive work behaviors: the moderating role of supervisor social support. , 2012, Journal of occupational health psychology.

[28]  Anol Bhattacherjee,et al.  Elucidating Individual Intention to Use Interactive Information Technologies: The Role of Network Externalities , 2008, Int. J. Electron. Commer..

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

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

[31]  Accounting Conservatism and Information Asymmetry: Evidence from Taiwan , 2013 .

[32]  B. Ratchford,et al.  Consumer information search revisited: Theory and empirical analysis , 1997 .

[33]  P. M. Podsakoff,et al.  Self-Reports in Organizational Research: Problems and Prospects , 1986 .

[34]  Gregory Lewis Asymmetric Information, Adverse Selection and Online Disclosure: The Case of eBay Motors , 2011 .

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

[37]  A. Bandura Human agency in social cognitive theory. , 1989, The American psychologist.

[38]  Anol Bhattacherjee,et al.  Understanding Changes in Belief and Attitude Toward Information Technology Usage: A Theoretical Model and Longitudinal Test , 2004, MIS Q..

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

[40]  Richard A. Johnson,et al.  Restructuring through spin‐off or sell‐off: transforming information asymmetries into financial gain , 2008 .

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

[42]  Eric T. G. Wang,et al.  Understanding Customers' Satisfaction and Repurchase Intentions: An Integration of IS Success Model, Trust, and Justice , 2011, Internet Res..

[43]  Chialin Chen,et al.  Time-to-value, customer learning, and the development of breakthrough products , 2005 .

[44]  Szu-Yuan Sun,et al.  Understanding customers' loyalty intentions towards online shopping: an integration of technology acceptance model and fairness theory , 2009, Behav. Inf. Technol..

[45]  William M. Riggs,et al.  Choice Over Uncertainty and Ambiguity in Technical Problem Solving , 2011 .

[46]  Kathryn Waite,et al.  Online banking information: what we want and what we get , 2004 .

[47]  Gabriel J. Biehal Consumers' Prior Experiences and Perceptions in Auto Repair Choice , 1983 .

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

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

[50]  Chao Zhang,et al.  Reducing information asymmetry in the power industry: Mandatory and voluntary information disclosure regulations of sulfur dioxide emission , 2012 .

[51]  Paul A. Pavlou,et al.  Understanding and Mitigating Uncertainty in Online Exchange Relationships: A Principal-Agent Perspective , 2007, MIS Q..

[52]  Detmar W. Straub,et al.  Measuring System Usage: Implications for IS Theory Testing , 1995 .

[53]  R. Powell,et al.  Measuring the Effectiveness of Australia's Statutory-Backed Continuous Disclosure Policy on ‘Innovative’ Investment Disclosures , 2015 .

[54]  Teresa Hogan,et al.  Information asymmetry and capital structurein SMEs : new technology-based firms in theIrish software sector , 2005 .

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

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

[57]  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..

[58]  Yvonne Phillips,et al.  Landlords versus tenants: Information asymmetry and mismatched preferences for home energy efficiency , 2012 .

[59]  Peter P.J. Driessen,et al.  Eco-labeling and information asymmetry: a comparison of five eco-labels in the Netherlands , 2008 .