The impact of self-efficacy, ease of use and usefulness on e-purchasing: An analysis of experienced e-shoppers

The objective of the present research is to study the Internet purchasing behaviour of consumers who are experienced with the channel, employing a dual perspective for the analysis: (1) present e-purchasing behaviour and (2) future repurchasing behaviour measured through repurchasing intentions. On the basis of this approach, we attempt to understand the effect of perceived self-efficacy, ease of use and usefulness on both types of behaviour and the links between them. Furthermore, the research includes other variables related to Internet experience, extracted from models widely tested in the literature. These variables, namely, acceptance, frequency of use and satisfaction with the Internet, act as antecedents of e-purchasing behaviour and permit a deeper analysis of the consumer. The results obtained show that self-efficacy and usefulness are important perceptions in explaining the behaviour of experienced consumers, while ease of use does not have a significant influence.

[1]  June Lu,et al.  Personal innovativeness, social influences and adoption of wireless Internet services via mobile technology , 2005, J. Strateg. Inf. Syst..

[2]  Mun Y. Yi,et al.  Understanding information technology acceptance by individual professionals: Toward an integrative view , 2006, Inf. Manag..

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

[4]  Xiao Liu,et al.  An empirical study of product differences in consumers' E-commerce adoption behavior , 2003, Electron. Commer. Res. Appl..

[5]  David Mazursky,et al.  A Longitudinal Assessment of Consumer Satisfaction/Dissatisfaction: The Dynamic Aspect of the Cognitive Process , 1983 .

[6]  Tino Fenech,et al.  Web retailing adoption: exploring the nature of internet users Web retailing behaviour , 2003 .

[7]  Thompson S. H. Teo,et al.  Intrinsic and extrinsic motivation in Internet usage , 1999 .

[8]  Dale Goodhue,et al.  Is Attitudes: toward Theoretical and Definition Clarity , 1986, ICIS.

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

[10]  Gary M Olson,et al.  Human-computer interaction: psychological aspects of the human use of computing. , 2003, Annual review of psychology.

[11]  E. McKinney,et al.  Extending the Technology Acceptance Model Extending the Technology Acceptance Model and the Task and the Task-Technology Fit Model to Technology Fit Model to Consumer E Consumer E- -Commerce Commerce , 2004 .

[12]  Chee-Sing Yap,et al.  Impact of consultants on computerization success in small businesses , 1992, Inf. Manag..

[13]  Tibert Verhagen,et al.  Online store image: conceptual foundations and empirical measurement , 2004, Inf. Manag..

[14]  Dale Goodhue,et al.  I/S attitudes: toward theoretical and definitional clarity , 2013, DATB.

[15]  Younghwa Lee,et al.  The Technology Acceptance Model: Past, Present, and Future , 2003, Commun. Assoc. Inf. Syst..

[16]  R. Goldsmith Explaining and Predicting Consumer Intention to Purchase Over the Internet: An Exploratory Study , 2002 .

[17]  Heikki Karjaluoto,et al.  Consumer acceptance of online banking: an extension of the technology acceptance model , 2004, Internet Res..

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

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

[20]  Detmar W. Straub,et al.  Inexperience and experience with online stores: the importance of TAM and trust , 2003, IEEE Trans. Engineering Management.

[21]  Chorng-Shyong Ong,et al.  Factors affecting engineers' acceptance of asynchronous e-learning systems in high-tech companies , 2004, Inf. Manag..

[22]  Fred D. Davis User Acceptance of Information Technology: System Characteristics, User Perceptions and Behavioral Impacts , 1993, Int. J. Man Mach. Stud..

[23]  Patrick Y. K. Chau,et al.  An Empirical Assessment of a Modified Technology Acceptance Model , 1996, J. Manag. Inf. Syst..

[24]  I. Ajzen,et al.  Intention, perceived control, and weight loss: an application of the theory of planned behavior. , 1985, Journal of personality and social psychology.

[25]  Donna L. Hoffman,et al.  New metrics for new media: toward the development of Web measurement standards , 1997, World Wide Web J..

[26]  M. A. Quaddus,et al.  Roles of formal/informal networks and perceived compatibility in the diffusion of World Wide Web: the case of Indonesian banks , 2003, 36th Annual Hawaii International Conference on System Sciences, 2003. Proceedings of the.

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

[28]  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..

[29]  M MarakasGeorge,et al.  The Multilevel and Multifaceted Character of Computer Self-Efficacy , 1998 .

[30]  Donghee Don Shin Understanding purchasing behaviors in a virtual economy: Consumer behavior involving virtual currency in Web 2.0 communities , 2008 .

[31]  Viswanath Venkatesh,et al.  Why Don't Men Ever Stop to Ask for Directions? Gender, Social Influence, and Their Role in Technology Acceptance and Usage Behavior , 2000, MIS Q..

[32]  Richard D. Johnson,et al.  The Multilevel and Multifaceted Character of Computer Self-Efficacy: Toward Clarification of the Construct and an Integrative Framework for Research , 1998, Inf. Syst. Res..

[33]  Hokey Min,et al.  E-purchasing: profiles of adopters and nonadopters , 2003 .

[34]  Paul A. Pavlou,et al.  Predicting E-Services Adoption: A Perceived Risk Facets Perspective , 2002, Int. J. Hum. Comput. Stud..

[35]  Ángel Herrero Crespo,et al.  Explaining B2C e-commerce acceptance: An integrative model based on the framework by Gatignon and Robertson , 2008, Interact. Comput..

[36]  J. Liker,et al.  User acceptance of expert systems: a test of the theory of reasoned action , 1997 .

[37]  Dale Goodhue,et al.  Understanding user evaluations of information systems , 1995 .

[38]  Moez Limayem,et al.  What makes consumers buy from Internet? A longitudinal study of online shopping , 2000, IEEE Trans. Syst. Man Cybern. Part A.

[39]  Susan Wiedenbeck,et al.  The mediating effects of intrinsic motivation, ease of use and usefulness perceptions on performance in first-time and subsequent computer users , 2001, Interact. Comput..

[40]  J. Beckmann,et al.  Action control : from cognition to behavior , 1985 .

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

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

[43]  Geoffrey S. Hubona,et al.  The influence of external variables on information technology usage behavior , 1996, Proceedings of HICSS-29: 29th Hawaii International Conference on System Sciences.

[44]  Deborah Compeau,et al.  Computer Self-Efficacy: Development of a Measure and Initial Test , 1995, MIS Q..

[45]  Detmar W. Straub,et al.  Information Technology Adoption Across Time: A Cross-Sectional Comparison of Pre-Adoption and Post-Adoption Beliefs , 1999, MIS Q..

[46]  Lei-da Chen,et al.  Enticing online consumers: an extended technology acceptance perspective , 2002, Inf. Manag..

[47]  I. Ajzen Perceived behavioral control, self-efficacy, locus of control, and the theory of planned behavior. , 2002 .

[48]  R. Feinberg,et al.  E-tailers versus retailers , 2004 .

[49]  Gordon C. Bruner,et al.  Explaining consumer acceptance of handheld Internet devices , 2005 .

[50]  Dong Hee Shin,et al.  User acceptance of mobile Internet: Implication for convergence technologies , 2007, Interact. Comput..

[51]  A. Bandura Social learning theory , 1977 .

[52]  Hung-Pin Shih,et al.  An empirical study on predicting user acceptance of e-shopping on the Web , 2004, Inf. Manag..

[53]  Jan-Benedict E. M. Steenkamp,et al.  The use of LISREL in validating marketing constructs. , 1991 .

[54]  Gerald L. Lohse,et al.  Consumer Buying Behavior on the Internet: Findings from Panel Data , 2000 .

[55]  K. Jöreskog Statistical analysis of sets of congeneric tests , 1971 .

[56]  Shu-Sheng Liaw,et al.  An investigation of user attitudes toward search engines as an information retrieval tool , 2003, Comput. Hum. Behav..

[57]  Francisco Muñoz-Leiva,et al.  Web Acceptance Model (WAM): Moderating effects of user experience , 2007, Inf. Manag..

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

[59]  Marios Koufaris,et al.  Applying the Technology Acceptance Model and Flow Theory to Online Consumer Behavior , 2002, Inf. Syst. Res..

[60]  Susan Lukose,et al.  Information Extraction Agents for Service-Oriented Architecture Using Web Service Systems: A Framework , 2008, J. Comput. Inf. Syst..

[61]  M. Koufaris,et al.  CUSTOMER TRUST ONLINE: EXAMINING THE ROLE OF THE EXPERIENCE WITH THE WEB SITE , 2002 .

[62]  Richard A. Spreng,et al.  A Reexamination of the Determinants of Consumer Satisfaction , 1996 .

[63]  Doyle Yoon,et al.  Building Relationships with Portal Users , 2002 .

[64]  A. Bandura Social Foundations of Thought and Action: A Social Cognitive Theory , 1985 .

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

[66]  Lei-da Chen,et al.  Technology Adaptation in E-Commerce: Key Determinants of Virtual Stores Acceptance , 2004 .

[67]  Sang-Gun Lee,et al.  Validating E-learning factors affecting training effectiveness , 2007, Int. J. Inf. Manag..

[68]  Margaret Tan,et al.  Factors Influencing the Adoption of Internet Banking , 2000, J. Assoc. Inf. Syst..

[69]  Jen-Her Wu,et al.  Empirical evaluation of the revised end user computing acceptance model , 2004, Comput. Hum. Behav..

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

[71]  Maarten Gelderman,et al.  The relation between user satisfaction, usage of information systems and performance , 1998, Inf. Manag..

[72]  W. Bearden,et al.  Selected Determinants of Consumer Satisfaction and Complaint Reports , 1983 .

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

[74]  E. B. Swanson,et al.  Measuring user attitudes in MIS research: a review , 1982 .

[75]  Daniel Robey,et al.  User Attitudes and Management Information System Use , 1979 .

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

[77]  Adelina Broadbridge,et al.  Students' views of retail employment – key findings from Generation Ys , 2007 .

[78]  R. Oliver A Cognitive Model of the Antecedents and Consequences of Satisfaction Decisions , 1980 .

[79]  A. Satorra,et al.  Scaled test statistics and robust standard errors for non-normal data in covariance structure analysis: a Monte Carlo study. , 1991, The British journal of mathematical and statistical psychology.

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

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

[82]  Jinsook Cho,et al.  Likelihood to abort an online transaction: influences from cognitive evaluations, attitudes, and behavioral variables , 2004, Inf. Manag..

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

[84]  Wendy Wood,et al.  Habit and intention in everyday life: The multiple processes by which past behavior predicts future behavior. , 1998 .

[85]  Jaejeung Rho,et al.  Extending the TAM for a t-commerce , 2005, Inf. Manag..

[86]  Chao-Min Chiu,et al.  Understanding e-learning continuance intention: An extension of the Technology Acceptance Model , 2006, Int. J. Hum. Comput. Stud..

[87]  Kar Yan Tam,et al.  The Effects of Post-Adoption Beliefs on the Expectation-Confirmation Model for Information Technology Continuance , 2006, Int. J. Hum. Comput. Stud..

[88]  J. Hair Multivariate data analysis , 1972 .

[89]  R. Feinberg,et al.  The Impact of Electronic Commerce as a Mode of Product Purchase on Consumer Retail Shopping Alternatives , 2004 .

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

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

[92]  Ping Zhang,et al.  Satisfiers and dissatisfiers: a two-factor model for website design and evaluation , 2000 .

[93]  William H. DeLone Determinants of Success for Computer Usage in Small Business , 1988, MIS Q..

[94]  R. Bagozzi,et al.  On the evaluation of structural equation models , 1988 .

[95]  Dianne Cyr,et al.  The role of social presence in establishing loyalty in e-Service environments , 2007, Interact. Comput..

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

[97]  Ephraim R. McLean,et al.  Information Systems Success: The Quest for the Dependent Variable , 1992, Inf. Syst. Res..

[98]  Susan M. Keaveney,et al.  Customer switching behavior in online services: An exploratory study of the role of selected attitudinal, behavioral, and demographic factors , 2001 .

[99]  Icek Ajzen,et al.  From Intentions to Actions: A Theory of Planned Behavior , 1985 .

[100]  A. Bandura Self-efficacy mechanism in human agency. , 1982 .

[101]  G. Cowan Statistical data analysis , 1998 .

[102]  H. Kaiser,et al.  Little Jiffy, Mark Iv , 1974 .

[103]  Jane M. Howell,et al.  Influence of Experience on Personal Computer Utilization: Testing a Conceptual Model , 1994, J. Manag. Inf. Syst..

[104]  Leo R. Vijayasarathy,et al.  Predicting consumer intentions to use on-line shopping: the case for an augmented technology acceptance model , 2004, Inf. Manag..

[105]  Richard Shepherd,et al.  The dimensional structure of the perceived behavioral control construct , 1997 .

[106]  Yi-Shun Wang,et al.  DETERMINANTS OF USER ACCEPTANCE OF INTERNET BANKING: AN EMPIRICAL STUDY , 2003 .

[107]  Mun Y. Yi,et al.  Predicting the use of web-based information systems: self-efficacy, enjoyment, learning goal orientation, and the technology acceptance model , 2003, Int. J. Hum. Comput. Stud..

[108]  Mary Ann Eastlick,et al.  An online prepurchase intentions model: The role of intention to search , 2001 .

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

[110]  Allison W. Pearson,et al.  Measuring Information System Usage: Replication and Extensions , 2006, J. Comput. Inf. Syst..

[111]  Dirk Van den Poel,et al.  Predicting online-purchasing behaviour , 2005, Eur. J. Oper. Res..