Survey
* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
ASSOCIATION FOR CONSUMER RESEARCH Labovitz School of Business & Economics, University of Minnesota Duluth, 11 E. Superior Street, Suite 210, Duluth, MN 55802 The Moderating Effects of Past Experience on Behavioral Intentions Blair Kidwell, University of Kentucky, USA Robert D. Jewell, Kent State University, USA Despite considerable research on the impact of past behavior on decision making over past two decades, little remains known about how experience moderates decision theoretic factors within models of behavioral intent. This research explores the implications of past behavior within the theory of planned behavior (TPB) and how it influences key decision making variables. We develop and test a theoretical model of how high vs. low levels of past behavior can induce deliberative versus heuristic processing of information. Consumer implications of the impact of past behavior on behavioral intentions are discussed highlighting the importance of addressing one’s experience when making a decision. [to cite]: Blair Kidwell and Robert D. Jewell (2007) ,"The Moderating Effects of Past Experience on Behavioral Intentions", in NA Advances in Consumer Research Volume 34, eds. Gavan Fitzsimons and Vicki Morwitz, Duluth, MN : Association for Consumer Research, Pages: 555-556. [url]: http://www.acrwebsite.org/volumes/12878/volumes/v34/NA-34 [copyright notice]: This work is copyrighted by The Association for Consumer Research. For permission to copy or use this work in whole or in part, please contact the Copyright Clearance Center at http://www.copyright.com/. The Moderating Effects of Past Experience on Behavioral Intentions Blair Kidwell, University of Kentucky, USA Robert D. Jewell, Kent State University, USA EXTENDED ABSTRACT Despite the growing body of research on the positive association (i.e., main effect) of past behavior on intention, key questions remain as to whether specific components (i.e., predictors) of intentions are enhanced or diminished when past behavior is included as a moderator in behavioral intention models (cf. Orbell, Hodgkins & Sheeran, 1997). Further, little is known about how past behavior might induce changes in people’s deliberative and heuristic processing of information within these models (cf. Wood, Tam & Witt, 2005). For example, it is possible that people with very little experience may be motivated to engage cognitive resources such as considering their evaluations of salient beliefs when making a decision. In contrast, those with extensive experience may be less motivated to process cognitive information, relying instead on heuristic information such as their past success performing the behavior (i.e., confidence in their ability) and their perceptions of how easy or difficult behavioral performance will be (i.e., external facilitators of behavior). These possibilities are investigated in this research. We make predictions that the level of past behavior will change the nature of the relationship between attitude and intent at low levels of past behavior, and between internal and external control at high levels of past behavior. Thus, the purpose of study one is to test the predicted moderating effects of past experience on attitude and perceived internal and external control with respect to behavioral intent. Study One. In study one, hypothesis 1 was supported indicating that past behavior accounted for a significant amount of variance beyond the effects of attitude, subjective norm, external and internal control. This is consistent with other research indicating the explanatory power of past behavior within the framework of the TPB. Further, it was shown that for participants with low levels of past experience, attitude was predictive of intention while internal and external control were not, in support of hypothesis 2. At higher levels of past behavior, internal control and external control were predictive of intention while attitude was not, in support of hypotheses 3 and 4. These findings support our theoretical model that past behavior can have a moderating effect on the other variables within the TPB. More importantly, we provide a framework for establishing the rationale as to why such moderating effects occur. Specifically, our framework suggests that those with lower levels of past behavior are more likely to engage cognitive resources when formulating a behavioral intent than those with higher levels of past behavior and thus, when past behavior is low, attitude is the primary driver of behavioral intent. Additionally, these findings support the view that when past behavior is higher individuals are more likely to utilize less cognitively demanding inputs such as perceived control. Despite this support of the influence of past experience on decision making within the TPB, further direct evidence is needed to assess the boundary conditions under which past experience can influence a consumer’s likelihood to engage cognitive resources to assist in the deliberative processing of information. Study 2 seeks to address this issue. Study Two. In our conceptual model, different levels of past behavior result in differential levels of cognitive processing. Thus, study two examines the processes related to past behavior in an experimental paradigm in which the extent of cognitive processing of information is explicitly considered. We argue that when past behavior is low, individuals will be more likely to engage cognitive resources to access additional information to make up for their lack of actual experience. Thus, we predicted that if low past-behavior participants are likely to engage cognitive resources, they should demonstrate discrimination between strong and weak message arguments. Conversely, when past behavior is high, individuals will be unlikely engage additional cognitive resources because of the small gap between their perceived level of personal resources and the threshold-level of personal resources believed to be necessary to form a behavioral intent. Thus, we predicted that if high pastbehavior participants are unmotivated to engage cognitive resources, they should demonstrate little discrimination between strong and weak message arguments. Findings in study 2 suggest that those in the low past-behavior condition engaged in greater elaboration of the issue-relevant arguments contained in the message than those in the high pastbehavior condition, as evidenced by their discrimination between the argument quality of the message. That is, participants with low levels of past behavior were more motivated to engage cognitive resources to the processing of the issue-relevant components of the message than those in the high past-behavior condition. These findings are generally supportive of our theoretical model and more specifically are supportive of hypotheses five and six. These findings have important implications for both marketers and consumer educational interventions for the prevention of debt. Our research demonstrates that, based on the nature of the interactions, it would be useful for researchers to segment the target population based on experience as suggested in past research (e.g., Beale & Manstead, 1991). For marketers, communications focusing on engaging cognitions of consumers may be quite effective for inexperienced consumers since their attitudes are typically formed through beliefs about the advantages of credit cards (e.g., build credit history, precaution for emergencies, etc.) and reducing disadvantages (e.g., risk of future debt, damaged FICA score, etc.). Thus, marketing campaigns could highlight these salient cognitions and provide positive consequences that are likely to strengthen intention through a favorable attitude (Fishbein & Ajzen, 1975). Marketers could also target experienced consumers with communications about the ease with which products and services, such as credit cards, can be acquired and the conveniences that they offer, in order to increase the consumer’s external control. Also, for experienced consumers, communicating information that builds confidence in their ability to acquire a given product or service can be effective. For example, increased perceptions of one’s ability to select the best product might be based on past successes and favorable outcomes associated with a particular brand. REFERENCES Aarts, H., Verplanken, B., & van Knippenberg, Ad. (1998). Predicting behavior from actions in the past: Repeated decision-making or a matter of habit. Journal of Applied Social Psychology, 28, 1355-1374. Ajzen, I. (1988). Attitudes, Personality and Behavior. Milton Keynes, England: Open University Press. Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50, 179-211. 555 Advances in Consumer Research Volume 34, © 2007 556 / The Moderating Effects of Past Experience on Behavioral Intentions Ajzen, I. & Fishbein, M. (1980). Understanding Attitudes and Predicting Social Behavior. Englewood Cliffs, NJ: PrenticeHall. Ajzen, I, & Madden, T. J. (1986). Prediction of Goal-Directed Behavior: Attitudes, Intentions, and Perceived Behavioral Control,” Journal of Experimental Social Psychology, 22, 453-474. Albarracin, D., & Wyer, R. S. Jr. (2000). The cognitive impact of past behavior: Influences on beliefs, attitudes, and future behavioral decisions. Journal of Personality and Social Psychology, 79, 5-22. Armitage, C. J., Conner, M., Loach, J., & Willetts, D. (1999). Different perceptions of control: Applying an extended theory of planned behavior to legal and illegal drug use. Basic and Applied Social Psychology, 21, 301-316. Bagozzi, R. P., & Kimmel, S. K. (1995). A comparison of leading theories for the prediction of goal-directed behaviors. British Journal of Social Psychology, 34, 437-461. Bagozzi, R. P., Wong, N., Abe, S., & Bergami, M. (2000). Cultural and situational contingencies and the theory of reasoned action: Application to fast food restaurant consumption. Journal of Consumer Psychology, 9(2), 97-106. Bandura, A. (1997). Self Efficacy: The exercise of control. New York, NY: Freeman. Beale, D. A. & Manstead, A. S. R. (1991). Predicting mother’s intentions to limit frequency of infants’ sugar intake: Testing the theory of planned behavior. Journal of Applied Social Psychology, 21, 409-431. Bentler, P. M., & Speckart, G. (1981). Attitudes “cause” behaviors: A structural equation analysis. Journal of Personality and Social Psychology, 40, 226-238. Burnkrant, R.E., and Howard, D. J. (1984). Effects of the use of introductory rhetorical questions versus statements on information processing. Journal of Personality and Social Psychology, 47 (6), 1218-1230. Cacioppo, J.T., Harkins, S. G., and Petty, R. E. (1981). The nature of attitudes and cognitive responses and their relationship to behavior. In R. Petty, T. Ostrom, and T. Brock (eds.), Cognitive responses in persuasion. Hillsdale, NJ: Erlbaum. Conner, M., & Armitage, C. J. (1998). Extending the theory of planned behavior: A review and avenues for further research. Journal of Applied Social Psychology, 28, 1429-1464. Eagly, A., & Chaiken, S. (1993). The Psychology of Attitudes. Harcourt, Brace and Jovanovich, New York. Fazio, R. H. (1990). A practical guide to the use of response latency in social psychological research. In Clyde Hendricks, Margaret S. Clark, eds., Research Methods in Personality and Social Psychology: Review of personality and social psychology, 11, (pp. 74-97). 351pp. Feinberg, R. (1986). Credit card as spending facilitating stimuli: A conditioning interpretation. Journal of Consumer Research, 13, 348-356. Fishbein, M. & Ajzen, I. (1975), Belief, attitude, intention, and behavior: An introduction to theory and research. Reading, MA: Addison-Wesley. Kidwell, B., & Jewell, R. D. (2003). The moderated influence of internal control: An examination across health related behaviors. Journal of Consumer Psychology, 13(4), 100-125. Lea, S., Webley, P., & Walker, C. M. (1995). Psychological factors in consumer debt: Money management, economic socialization, and credit use. Journal of Economic Psychology, 16 (4), 681-702. Nataraajan, R., & Angur, M. G. (1998). Perceived control in consumer choice: A closer look. In Basil Englis & Anna Olofsson (Eds.), European Advances in Consumer Research Conference Proceedings, 3, 288-292. Orbell, S., Hodgkins, S., & Sheeran, P. (1997). Implementation intentions and the theory of planned behavior. Personality and Social Psychology Bulletin, 23, 945-954. Petty, R. E. & Cacioppo, J. T. (1986), “The elaboration likelihood model of persuasion,” Advances in Experimental Social Psychology, 19,123-204. Pindyck, R. S. & Rubinfeld, D. L. (1991). Econometric Models & Economic Forecasts, 3rd edition, McGraw-Hill Inc. New York. Prelec, D., & Simester, D. (2001). Always leave home without it: A further investigation of the credit-card effect on willingness to pay. Marketing Letters, 12, 5-12. Schwarz, N. & Clore, G. L. (1996), “Feelings and phenomenal experiences,” E. T. Higgins and A. W. Kruglanski, eds. Social Psychology: A handbook of basic principles, (pp. 433465), New York: Guilford Press. Soman, D. (2001). Effects of payment mechanism on spending behavior: The role of rehearsal and immediacy of payments. Journal of Consumer Research, 27, 460-474. Soman, D., & Cheema, A. (2002). The effect of credit on spending decisions: The role of the credit limit and credibility. Marketing Science, 21, 32-53. Sutton, S., McVey, D., & Glanz A. (1999). A comparative test of the theory of reasoned action and the theory of planned behavior in the prediction of condom use intentions in a national sample of English young people. Health Psychology, 18(1), 72-81. Trafimow, D. (1994). Predicting intentions to use a condom from perceptions of normative pressure and confidence in those perceptions. Journal of Applied Social Psychology, 24, 2151-2163. Trafimow, D. (2000). Habit as both a direct cause of intention to use a condom and as a moderator of the attitude-intention and subjective norm-intention relations. Psychology & Health, 15, 383-393. Triandis, H. C. (1977). Interpersonal Behavior. Monterey, CA: Brooks/Cole. Verplanken, B., Aarts, H. and van Knippenberg, A. (1997). Habit, information acquisition, and the process of making travel mode choices. European Journal of Social Psychology, 27(5), 539-560. Wood, W., Tam, L. and Witt, M.G. (2005). Changing circumstances, disrupting habits. Journal of Personality and Social Psychology, 88(6), 918-933.