Social influence and end-user training

axiom that user training is a key element in MIS success [3, 16]. Included among positive outcomes afforded by user training are improved user attitudes, behavior, and performance. Although the typical focus of training programs is their technical content, many practit ioners have demonstrated that social factors could be instrumental in the target system’s success or failure. Indeed, it is recommended that researchers examine how methods of training can enhance motivation to learn and use software [3, 16, 17]. Unfortunately, there is little or no literature that includes actual manipulation of such “soft” variables [16]. The study presented in this article provides such manipulation. More specifically, we wanted to discover the extent to which training outcomes such as attitudes, behavior, and performance are influenced by peers through informal, verbal, word-of-mouth (WOM) communication, rather than derived solely through direct experience or formal channels. This article reports on a deception experiment that employed confederates in three experimental groups.

[1]  Allen Newell,et al.  The psychology of human-computer interaction , 1983 .

[2]  P. Wilton,et al.  Models of Consumer Satisfaction Formation : An Extension , 1988 .

[3]  Richard G. Netemeyer,et al.  Measurement of Consumer Susceptibility to Interpersonal Influence , 1989 .

[4]  Kieran Mathieson,et al.  Predicting User Intentions: Comparing the Technology Acceptance Model with the Theory of Planned Behavior , 1991, Inf. Syst. Res..

[5]  Lorne Olfman,et al.  The Importance of Learning Style in End-User Training , 1990, MIS Q..

[6]  Robert P. Bostrom,et al.  Training End Users: An Experimental Investigation of the Roles of the Computer Interface and Training Methods , 1993, MIS Q..

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

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

[9]  L Olfman,et al.  End‐user software training: an experimental comparison of methods to enhance motivation , 1991, Inf. Syst. J..

[10]  P. Herr,et al.  Effects of Word-of-Mouth and Product-Attribute Information on Persuasion: An Accessibility-Diagnosticity Perspective , 1991 .

[11]  John M. Carroll,et al.  The Minimal Manual , 1987, SGCH.

[12]  J. Cacioppo,et al.  The Elaboration Likelihood Model of Persuasion , 1986 .

[13]  Robert P. Bostrom,et al.  Conceptual models in training novice users of computer systems: effectiveness of abstract vs. analogical models and influence of individual differences , 1988 .

[14]  Dennis F. Galletta,et al.  An empirical study of spreadsheet error-finding performance , 1993 .

[15]  Lorne Olfman A comparison of applications-based and construct-based training methods for dss generator software , 1987 .

[16]  John T. Cacioppo,et al.  The Elaboration Likelihood Model of Persuasion , 1986, Advances in Experimental Social Psychology.

[17]  Cynthia M. Webster Influences Upon Consumer Expectations of Services , 1991 .

[18]  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..

[19]  Thomas P. Moran,et al.  Guest Editor's Introduction: An Applied Psychology of the User , 1981, CSUR.

[20]  Marsha L. Richins Negative Word-of-Mouth by Dissatisfied Consumers: A Pilot Study , 1983 .

[21]  Lawrence Feick,et al.  The Effects of Preference Heterogeneity and Source Characteristics on Ad Processing and Judgements about Endorsers , 1992 .

[22]  Dennis F. Galletta,et al.  Cognitive Fit: An Empirical Study of Information Acquisition , 1991, Inf. Syst. Res..

[23]  W. DeSarbo,et al.  Response Determinants in Satisfaction Judgments , 1988 .

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