Socionormative influence in software adoption and usage

Each year, companies will spend millions of dollars developing or migrating to new software systems in their business processes. Much of the focus of development and implementation has been based upon customer need (i.e., requirements), and rightly so. Equally important to requirements, however, are the users' perceptions of the software. Does a user actually think a piece of software would help them meet the need identified? Does the user think it would be easy for them to implement this software as a solution? What do the people around the user think and how does that opinion affect theirs? It is important to understand what factors determine whether a potential user will adopt a software application and how much they will use it? A commonly used model for explaining this is the Technology Acceptance Model. Davis (1989) found that subjective belief about a software system is most closely related to the actual intention to use it. Specifically, Davis uses Perceived Usefulness and Perceived Ease of Use in the Technology Acceptance Model to model intention to use a software system statistically. Neither of these subjective views are formed by a potential user in isolation. The opinions and behavior of others can potentially exert a great deal of influence on an individual's perception of these factors. Davis himself points out the omission of social influence in the original Technology Acceptance Model was due to measurement difficulties rather than to its potential value in the model. Difficulty in measuring social influence is evidenced by the lack of a definitive scale of social influence. By its common use in many studies, Subjective Norm has become the “defacto standard” for measuring social influence but this has not resulted in a consistently significant measure of social influence. The goal of this current study is two-fold. The primary goal is to incorporate a validated scale of social influence into the original Technology Acceptance Model which preserves the model's parsimony while significantly increasing its explained variance. Secondarily, in doing so, a modified scale based upon Subjective Norms will be verified and tested. In response to a recognized shortcoming of Subjective Norm, a cognitive element will be included into the modified scale. In this current study the modification of Subjective Norm was developed based upon existing research on the topic. The Technology Acceptance Model is augmented by the proposed scale and tested over four surveys. Two systems are chosen for study because of the nature of their use; use of one (Filebox) is voluntary, and use of the other (Blackboard) is compulsory. The results of the survey were consistent across all four surveys, with the model predicting over 40% of the variation in behavior every time. Including the modified scale of Subjective Norm significantly increased the explained variance of the model (i.e., R2) in every survey. The results verify the reliability and validity of the modified scale of Subjective Norm. These four studies make a strong case for including this scale of social influence as a regular scale in the Technology Acceptance Model for future research. Future directions for studying the scale and the resulting model are also discussed. The resulting behavioral model is a valuable tool that will give software developers and managers more forethought and insight into the development of and migration to specific software systems.

[1]  R. Kraut,et al.  Varieties of Social Influence: the Role of Utility and Norms in the Success of a New Communication Medium , 1998 .

[2]  Deborah Compeau,et al.  A Social Cognitive Theory Perspective On Individual Reactions To Computing Technology , 1991, ICIS.

[3]  P. Homer,et al.  Values, Susceptibility to Normative Influence, and Attribute Importance Weights: A Nomological Analysis , 2001 .

[4]  María G. Cisneros-Solís,et al.  MEDICAL ANNUAL , 1958, Journal of The Royal Naval Medical Service.

[5]  August E. Grant,et al.  Individual and network influences on the adoption and perceived outcomes of electronic messaging , 1990 .

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

[7]  A. Adam Whatever happened to information systems ethics? Caught between the devil and the deep blue sea , 2004 .

[8]  S. Fiske,et al.  Social Psychology , 2019, Encyclopedia of Evolutionary Psychological Science.

[9]  T. Cook,et al.  Quasi-experimentation: Design & analysis issues for field settings , 1979 .

[10]  G. Kok,et al.  The Theory of Planned Behavior: A Review of its Applications to Health-Related Behaviors , 1996, American journal of health promotion : AJHP.

[11]  Dominic Abrams,et al.  Social Identification, Self-Categorization and Social Influence , 1990 .

[12]  E. Rogers,et al.  Diffusion of innovations , 1964, Encyclopedia of Sport Management.

[13]  Weidong Xia,et al.  The influence of persuasion, training and experience on user perceptions and acceptance of IT innovation , 2000, ICIS.

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

[15]  J. Richard Eiser,et al.  Social psychology and behavioral medicine , 1982 .

[16]  S. Mulaik,et al.  EVALUATION OF GOODNESS-OF-FIT INDICES FOR STRUCTURAL EQUATION MODELS , 1989 .

[17]  I. Ajzen Attitudes, Traits, and Actions: Dispositional Prediction of Behavior in Personality and Social Psychology , 1987 .

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

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

[20]  I. Ajzen,et al.  A Comparison of the Theory of Planned Behavior and the Theory of Reasoned Action , 1992 .

[21]  J. Nunamaker Proceedings of the 53rd Hawaii International Conference on System Sciences , 1999 .

[22]  A. Bandura Social Foundations of Thought and Action , 1986 .

[23]  I. Ajzen Constructing a TpB Questionnaire: Conceptual and Methodological Considerations , 2002 .

[24]  H. Kelman Compliance, identification, and internalization three processes of attitude change , 1958 .

[25]  Joseph P. Forgas,et al.  Social Influence: Direct and Indirect Processes , 2001 .

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

[27]  J. Elashoff,et al.  Multiple Regression in Behavioral Research. , 1975 .

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

[29]  Predicting the use of condoms: Past behavior, norms, and the sexual partner , 1992 .

[30]  M. Hogg,et al.  Group Norms and the Attitude-Behavior Relationship: A Role for Group Identification , 1996 .

[31]  Jerold L. Hale,et al.  The Theory of Reasoned Action , 2002 .

[32]  Deborah Compeau,et al.  Application of Social Cognitive Theory to Training for Computer Skills , 1995, Inf. Syst. Res..

[33]  D. Campbell,et al.  Convergent and discriminant validation by the multitrait-multimethod matrix. , 1959, Psychological bulletin.

[34]  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..

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

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

[37]  D. Dulany Hypotheses and habits in verbal "operant conditioning". , 1961, Journal of abnormal and social psychology.

[38]  Ricky W. Griffin,et al.  Objective and social sources of information in task redesign: A field experiment. , 1983 .

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

[40]  Mark T. Dishaw,et al.  Extending the Technology Acceptance Model , 1997 .

[41]  L. Delbeke Quasi-experimentation - design and analysis issues for field settings - cook,td, campbell,dt , 1980 .

[42]  Cindy Gallois,et al.  The theory of reasoned action: Its application to AIDS-preventive behaviour , 1993 .

[43]  References , 1971 .

[44]  Dennis F. Galletta,et al.  Extending the technology acceptance model to account for social influence: theoretical bases and empirical validation , 1999, Proceedings of the 32nd Annual Hawaii International Conference on Systems Sciences. 1999. HICSS-32. Abstracts and CD-ROM of Full Papers.

[45]  James Price Dillard,et al.  The Persuasion Handbook: Developments in Theory and Practice , 2002 .

[46]  Blair H. Sheppard,et al.  The Theory of Reasoned Action: A Meta-Analysis of Past Research with Recommendations for Modifications and Future Research , 1988 .

[47]  J. Grube,et al.  Attitudes and normative beliefs as predictors of smoking intentions and behaviours: a test of three models. , 1986, The British journal of social psychology.

[48]  J Tudor-Hart,et al.  On the nature of prejudice. , 1961, The Eugenics review.

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

[50]  J. Miller,et al.  Development of an Instrument To Measure Hope , 1988, Nursing research.

[51]  A. Tenbrunsel,et al.  Organizational Behavior and Human Decision Processes , 2013 .

[52]  R. Bagozzi The self-regulation of attitudes, intentions, and behavior , 1992 .

[53]  M. Fishbein A theory of reasoned action: some applications and implications. , 1980, Nebraska Symposium on Motivation. Nebraska Symposium on Motivation.

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

[55]  Janet Fulk,et al.  Organizational Colleagues, Media Richness, and Electronic Mail , 1991 .

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

[57]  C. Gallois,et al.  Influences on condom use among undergraduates: Testing the theories of reasoned action and planned behaviour , 1993 .

[58]  M. Lynne Markus,et al.  Toward a “Critical Mass” Theory of Interactive Media , 1987 .

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

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

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

[62]  I. Ajzen,et al.  Prediction of goal directed behaviour: Attitudes, intentions and perceived behavioural control , 1986 .