Understanding the Balanced Effects of Belief and Feeling on Information Systems Continuance

There are innumerable studies on technology adoption as well as continuance of usage. A review of previous research shows that cognitive factors are considered prominently in information technology adoption and continuance while the affective feelings of users are not. Although attitude and user satisfaction are common factors considered in information systems research, these factors only involve partial aspects of feelings. Researchers in the marketing areas, as well as the psychology area, begin to note the importance of feelings in understanding and predicting human and customer behavior. In many modern applications, such as mobile Internet services, user feelings are expected to be important, since users are not just technology users but also service consumers. Drawing upon the support of consumer research, social psychology, and computer science, this study proposes a balanced belief–feeling model of IS continuance. In the process of developing this model, the concepts of attitude, belief, and feelings are further articulated, defined, and distinguished. The balanced model is tested in a survey of mobile Internet users. The results established the validity of the model. A comparison with the IS continuance model shows that the new model can explain significantly more variance in continuance intention, taking into account that the new model has more factors. We offer theoretical reasoning for the balanced effects of belief and feeling on IS continuance and discuss the theoretical and practical implications of this study.

[1]  E. Hirschman,et al.  The Experiential Aspects of Consumption: Consumer Fantasies, Feelings, and Fun , 1982 .

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

[3]  J. Russell.  A circumplex model of affect. , 1980 .

[4]  F. Kardes,et al.  The Effects of Physiological Arousal on Information Processing and Persuasion , 1988 .

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

[6]  R. Bagozzi.  A Field Investigation of Causal Relations among Cognitions, Affect, Intentions, and Behavior , 1982 .

[7]  R. Oliver.  Satisfaction: A Behavioral Perspective On The Consumer , 1996 .

[8]  David W. Gerbing,et al.  An Updated Paradigm for Scale Development Incorporating Unidimensionality and Its Assessment , 1988 .

[9]  Michel Tuan Pham,et al.  Affective reactions to consumption situations: A pilot investigation , 1991 .

[10]  G. Zaltman,et al.  Innovations and organizations , 2020, Organizational Innovation.

[11]  Prashanth U. Nyer.  A study of the relationships between cognitive appraisals and consumption emotions , 1997 .

[12]  Karen A. Machleit,et al.  A Comparison of Attitudes and Emotions as Predictors of Behavior at Diverse Levels of Behavioral Experience , 1992 .

[13]  Rik Pieters,et al.  Functions and management of affect: Applications to economic behavior , 1988 .

[14]  R. Zmud,et al.  Information technology implementation research: a technological diffusion approach , 1990 .

[15]  Rosalind W. Picard.  Computers That Recognize and Respond to User Emotion , 2003, User Modeling.

[16]  R. Oliver,et al.  Assessing the Dimensionality and Structure of the Consumption Experience: Evaluation, Feeling, and Satisfaction , 1993 .

[17]  Joel B. Cohen,et al.  Affect and consumer behavior , 1991 .

[18]  M. Holbrook,et al.  Assessing the Role of Emotions as Mediators of Consumer Responses to Advertising , 1987 .

[19]  J. Cacioppo,et al.  Attitudes and Persuasion: Classic and Contemporary Approaches , 1981 .

[20]  S. Fukuda,et al.  Development of man-machine interfaces based on user preferences , 2001, Proceedings of the 2001 IEEE International Conference on Control Applications (CCA'01) (Cat. No.01CH37204).

[21]  Jonathan Klein,et al.  This computer responds to user frustration: Theory, design, and results , 2002, Interact. Comput..

[22]  Anol Bhattacherjee,et al.  Understanding Post-Adoption Behavior in the Context of Online Services , 1998, Inf. Syst. Res..

[23]  Jonathan Klein,et al.  Computers that recognise and respond to user emotion: theoretical and practical implications , 2002, Interact. Comput..

[24]  Thomas J. Madden,et al.  A Closer Look at Classical Conditioning , 1985 .

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

[26]  R. Zajonc.  Feeling and thinking : Preferences need no inferences , 1980 .

[27]  Moez Limayem,et al.  Explaining Information Systems Adoption and Post-Adoption: Toward an Integrative Model , 2003, ICIS.

[28]  Marsha L. Richins.  Measuring Emotions in the Consumption Experience , 1997 .

[29]  Prashanth U. Nyer,et al.  The role of emotions in marketing , 1999 .

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

[31]  J. Cacioppo,et al.  Attitude and Attitude Change , 1981 .

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

[33]  David Gefen,et al.  Structural Equation Modeling Techniques and Regression: Guidelines for Research Practice , 2000 .

[34]  I. Ajzen.  Nature and operation of attitudes. , 2001, Annual review of psychology.

[35]  R. Batra,et al.  Affective Responses Mediating Acceptance of Advertising , 1986 .

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

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

[38]  George N. Votsis,et al.  Emotion recognition in human-computer interaction , 2001, IEEE Signal Process. Mag..

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

[40]  G. Bower.  Mood and memory. , 1981, The American psychologist.

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

[42]  E. Hirschman,et al.  Hedonic Consumption: Emerging Concepts, Methods and Propositions , 1982 .

[43]  R. Batra,et al.  Measuring the hedonic and utilitarian sources of consumer attitudes , 1991 .

[44]  W. Mischel,et al.  A cognitive-affective system theory of personality: reconceptualizing situations, dispositions, dynamics, and invariance in personality structure. , 1995, Psychological review.

[45]  Kevin E. Voss,et al.  Measuring the Hedonic and Utilitarian Dimensions of Attitude: a Generally Applicable Scale , 1997 .

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

[47]  D. Cicchetti.  Emotion and Adaptation , 1993 .

[48]  E. Deci.  Effects of Externally Mediated Rewards on Intrinsic Motivation. , 1971 .

[49]  Hans van der Heijden,et al.  ON THE COGNITIVE-AFFECTIVE STRUCTURE OF ATTITUDES TOWARD INFORMATION SYSTEMS , 2002 .

[50]  J. Rossiter,et al.  Store atmosphere: an environmental psychology approach , 1982 .

[51]  Deanna S. Kempf.  Attitude formation from product trial: Distinct roles of cognition and affect for hedonic and functional products , 1999 .

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