The Influence of Affect on Attributions For Product Failure

Lalita A. Manrai, University of Delaware
Meryl P. Gardner, University of Delaware
[ to cite ]:
Lalita A. Manrai and Meryl P. Gardner (1991) ,"The Influence of Affect on Attributions For Product Failure", in NA - Advances in Consumer Research Volume 18, eds. Rebecca H. Holman and Michael R. Solomon, Provo, UT : Association for Consumer Research, Pages: 249-254.

Advances in Consumer Research Volume 18, 1991      Pages 249-254

THE INFLUENCE OF AFFECT ON ATTRIBUTIONS FOR PRODUCT FAILURE

Lalita A. Manrai, University of Delaware

Meryl P. Gardner, University of Delaware

Consumers' cognitive and affective reactions to product failure are central to understanding postpurchase behavior. The extant research has provided many insights into the nature of these reactions and their mediating role on such post-purchase behaviors as complaining and word of mouth (e.g., Curren and Folkes 1987; Day and Ash 1979; Day and Bodur 1978; Folkes 1984, 1988; Folkes, Koletsky and Graham 1987; Folkes and Kotsos 1986; Krishnan and Valle 1979; Landon 1977; Valle and Wallendorf 1977). In all this research, disconfirmation of expectations is considered as the force that generates affective and cognitive reactions. In contrast, there is a dearth of research examining the impact of the emotional context of product failure on subsequent cognitive and emotional reactions. The term -"emotional context" is used here to refer to the consumer's feeling state prior to product failure. The purpose of this paper is to provide a conceptual model which addresses the issue of how emotional context affects attributions for product failure. Before presenting our model, we will provide an overview of the satisfaction literature. This review is meant to be representative rather than inclusive and provides a historical context for the model.

PRODUCT FAILURE AND SATISFACTION

The area of consumer satisfaction/ dissatisfaction has particularly captured the interest of researchers in the last decade. Most of the early research in this area is based on the expectancy disconfirmation paradigm (Churchill and Surprenant 1982; LaBarbera and Mazursky 1983; Oliver 1980; Oliver and Linda 1981). This conceptualization of satisfaction is based on the proposition that satisfaction is a function of prior expectancies and actual product performance. If performance exceeds expectations, consumers will be satisfied; if performance falls below expectations, consumers will be dissatisfied. In the context of product failure, this suggests that disconfirmation is the primary determinant of (d s)satisfaction and is depicted in Model-A of Figure A.

Weiner's (1980) work extends this paradigm. It suggests that disconfirmation does not lead directly to satisfaction, and that the effects of disconfirmation are mediated by attributional processing. In marketing, Folkes and her colleagues (Curren and Folkes 1987; Folkes 1984; Folkes, Koletsky and Graham 1987; Folkes and Kotsos 1986) have extensively studied product failure, using attribution theory to predict consumers' postpurchase behavior. Using the categorization system suggested by Weiner (1980), Folkes (1984) studied how the three dimensions of attributions - i.e., stability, locus and controllability - affect consumer reactions. Her findings support the prediction that stable attributions lead to certainty about product failure and preference for a refund rather than an exchange. In addition, she found that locus, is related to market equity reactions: Consumers felt that the firm owes them an apology and refund when product failure was firm-related. Finally, she found that controllability, in conjunction with locus, influences "anger" reactions: Consumers felt angry and wanted to hurt the firms' business when they felt that the firm could have controlled the failure. In another study, Curren and Folkes (1987) found these three dimensions were related to both positive and negative consumer reactions. These reactions were studied in terms of communications such as complaining/complementing and negative/positive word of mouth. The results indicated that the desire to communicate was greater for seller-controlled causes, with seller-related stable causes leading to more positive communications and stable causes (irrespective of locus leading to more negative word of mouth than unstable causes. Thus the work of Folkes and her colleagues (Curren and Folkes 1987; Folkes 1984; Folkes Koletsky and Graham 1987; Folkes and Kotsos 1986) clearly establishes the utility of Weiner's (1980) attribution framework in the context of product failure and satisfaction. A simplified conceptualization of this work is represented by Model B in Figure A.

Folkes' (1984) finding that the controllability dimension, in conjunction with locus, influences "anger" reactions suggests that attributions can lead to specific types of emotional reactions. This link between attributions and emotions is amply researched and supported in psychology. In particular, the work of Weiner and his colleagues (Weiner 1985; Weiner, Russell and Lerman 1978, 1979) investigates the link between many specific attributions and resulting specific emotions. Westbrook (1987) suggests that emotions affect consumer satisfaction. Thus the next development in consumer researchers' conceptualizations of satisfaction includes emotions as mediating between attributions and satisfaction. This is depicted in Model C in Figure A.

Oliver (1989) provides a comprehensive conceptual framework which integrates the cognitive consequences of disconfirmation (attributions) and the affective consequences of disconfirmation (emotions) enabling both to mediate the effects of disconfirmation on consumer satisfaction. In his model, disconfirmation is viewed as having both a direct effect on attributions and an indirect effect i.e., through primary evaluation (success/failure) processing. Consistent with Weiner (1985), attribution processing is viewed as affecting satisfaction/dissatisfaction through distinct emotions (guilt/anger). In addition, primary evaluations also affect satisfaction/dissatisfaction (through primary affect - i.e., happy/sad). Basic conceptualization of Oliver's (1989) work is depicted in Model D in Figure A.

FIGURE A

CURRENT MODELS OF PRODUCT FAILURE AND CONSUMER SATISFACTION

Note that models A - D in Figure A all posit disconfirmation as the major determinant of attributional processing. It is possible that factors other than disconfirmation may account for the extent and content of attributional processing. For example, a cycle-recycle pattern of emotion-attribution-emotion may mediate the effects of disconfirmation on consumer satisfaction. Such a multistage model of the relationship between achievement outcomes, outcome related affect, attribution and emotion was supported in two studies conducted by Stephan and Gollwitzer (1981). These studies showed that achievement outcome created an affect which caused attributions, and attributions in turn resulted in emotions. Thus, emotions may precede attributions instead of (or in addition to) resulting from attributions. It is also possible that emotions prior to an outcome may affect reactions to the outcome. Thus in the context of product failure, prior mood or emotional context of product failure may affect subsequent cognitive and affective reactions. Differential emotion theory suggests that emotion is constantly present in consciousness and influences attribution processes (Izard 1982). One possible way in which the effects of differential emotions on attributions can be captured is as an individual difference. Consider two individuals: one in a happy mood and the other in a sad mood. When confronted with a product failure situation, they may react differently. The work of Beck and his colleagues studying depression (Beck 1967; Kovacs and Beck 1977) suggests that depressed individuals tend to negatively view outcomes.

Further evidence for the conjecture that emotions affect cognitions is offered in the area of memory research. Findings indicate that prior affective states influence memory processes (Bower 1981; Clark & Isen 1982; Isen and Daubman 1984; Isen, Shalker, Clark and Karp 1978). While quite a few of these studies are based on mood congruency effects, two other possible influences of mood states were suggested by Wyer and Carlston (1979). One was the informational function of mood - i.e., an individual may treat a mood as an informational input for making judgments. The other was the directive function of mood - i.e., an individual's attention may be directed towards specific information to explain a mood. These effects of prior mood states suggest that the emotional context in which product failure takes place may affect subsequent information processing. For example, a consumer may blame a restaurant for poor service not only because his/her soup was cold but also due to the fact that s/he had a bad day at work or was stuck in the traffic jam. The emotional context of product usage situations thus may influence attributional processing.

CONCEPTUAL MODEL AND HYPOTHESES

With this in mind, we propose a two-stage model in which emotional context affects satisfaction and other post-purchase processes in the context of product failure. The basic conceptual model is given in Figure B. I s first stage relates the emotional context of product failure to resulting attributions, and its second stage examines the effects of these attributions on satisfaction and other post purchase behavior. The model integrates four issues: 1) how different mood states affect the number of attributions, 2) how different mood states affect the type of attributions, 3) how quantity of attributions affects post purchase behavior and 4) how type of attributions affects post purchase behavior. Before these issues are discussed, we need to define some terminology for examining emotional context and provide a framework for discussing types of attributions.

Oliver (1989) integrates research on emotion typologies in his conceptual model. Three typologies discussed by Oliver (1989) are those of Russell (1978, 1979, 1980), Plutchick (1980) and Watson and Tellegen (1985). While these typologies differ, they suggest a common underlying dimensional structure for emotions. Two orthogonal dimensions most commonly accepted by these and other researchers (Mehrabian and Russell 1974) are pleasure and arousal. We believe these two dimensions provide a staring point for exploring the effects of emotional context on attribution processing. Russell, Weiss and Mendelsohn (1989) describe the specific mood states on a two dimensional affect grid with pleasure and arousal as the two dimensions. Depression/gloominess is characterized as a low arousal-negative mood state, anger/stress as high arousal-negative, excitement/ecstacy as high arousal-positive and relaxation/serenity as low arousal-positive. Each of these mood states is a specific one differing from each other along either or both of the dimensions of emotions, i.e., arousal and pleasure. Against these specific moods, an "average, every day, normal" mood is depicted as the very center of the affect grid - i.e., moderate arousal and neither pleasure nor displeasure.

As regards the attributional framework, Weiner's (1980) three--dimensional taxonomy provides a conceptual framework of proven value in consumer behavior (Curren and Folkes 1987; Folkes 1984; Folkes, Koletsky and Graham 1987; Folkes and Kotsos 1986; Oliver 1989). We believe this three dimensional framework will also prove useful in examining the effects of emotional context on attribution processing. The first causal dimension is locus of control, where causes such as ability, effort, mood and patience are identified as internal causes and task difficulty and luck are identified as external causes. The second dimension suggested by Weiner is variance of causes, where causes such as ability, task difficulty and patience are considered to be relative invariant or stable and causes such as luck, effort and mood are considered as variant or unstable. Finally the third dimension deals with controllability, where causes such as effort are considered as intentional or controllable and causes such as ability, task difficulty or mood are considered unintentional or uncontrollable.

Turning back to the four issues in our model, we now develop hypotheses pertaining to the first issue - i.e., how different emotional states affect the extent or quantity of attributional processing. Specific mood states may lead to more attributional processing than normal, less distinct mood states because the former are likely to have more readily identifiable, elaborate associative networks than the latter. Work of Clark and Isen (1982) suggests that when something positive or negative happens to a person, the affective tone associated with that experience may be stored in memory with other things associated with that experience. Things that produce a given feeling tone may be linked together in memory as a category. If this is so, the associative network for an event that takes place in a specific emotional context would include both those things directly linked to the particular experience and those things indirectly related through their sharing of a common affective tone. For example, if one is in an angry mood and has a bad experience in a restaurant, both one's restaurant schema and set of experiences related to anger may be triggered. In contrast, a person in a normal mood having a bad experience in the restaurant will have a smaller activated network consisting primarily of restaurant-related things.

FIGURE B

PROPOSED MODIFIED MODEL OF PRODUCT FAILURE AND CONSUMER SATISFACTION

The elaborate network activated by product failure in an emotional context is expected to lead to greater attributional processing. More specifically, the four mood states discussed earlier - i.e., depression, anger, excitement, and relaxation are expected to have more elaborate networks and thus lead to greater attributional processing than a normal mood state. Thus we hypothesize that:

H1: Attributional processing is higher when product failure is experienced in an emotional context than when no emotional context is present.

Next we examine the two dimensions of emotions, i.e., pleasure and arousal as they relate to the extent of attribution 11 processing. Existing research in psychology and related areas suggests that negative affect results in more attributional processing. Schwartz and Clove (1983) studied how judgments of happiness and satisfaction with one's life are influenced by mood at the time of judgment. Unpleasant affective states led to greater search for and greater use of information to explain the emotional state than pleasant affective states. In another study by Gilovich (1983), gamblers were found to spend more time explaining their losses than their wins. These findings suggest that negative affective states are associated with more attributions than positive affective states. We propose that this would apply in case of product failure and hypothesize that:

H2: Attributional processing in response to product failure is higher when the emotional context is negative than when it is positive.

As regards the second dimension of emotions, i.e., arousal, work by Pyszczynski and Greenberg (1981) suggests that individuals engage in more thorough attributional processing for unexpected events than they do for expected events. Since unexpected or unusual events are likely to be high in arousal, this suggests that high arousal may be associate with greater attributional processing than low arousal. This conjecture is also consistent with the work of Oliver (1989). A comparison of the five different types of satisfaction response models suggested by Oliver (1989) indicates that a specific satisfaction response such as surprise, which is high in arousal, has very active attributional processing in contrast to contentment, which is low in arousal. We, therefore, hypothesize that:

H3: Attributional processing in response to product failure is higher when the emotional context is high in arousal than when it is low in arousal.

Research to test these hypotheses and the proposed models is underway. We hope the findings will contribute to our understanding of consumer satisfaction processes by adding the effects of affective state prior to product failure.

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