≫Motivation, Capacity and Opportunity to Complain: Towards a Comprehensive Model of Consumer Complaint Behavior

ABSTRACT - In this paper, highlights of the consumer complaint behavior literature are reviewed and implications for a general theoretical framework are assessed. Inspired by models proposed in the area of consumer information processing, a relatively simple overall model is proposed. The main determinants specified by this model are motivation, capacity, and opportunity to complain. A study is reported in which the model is operationalized and assessed. The results provide some support for the hypothesis that complain behavior is a positive function of the mathematical product of the three determinants. Potential functions of the model are briefly discussed.


Kaj P.N. Morel, Theo B.C. Poiesz, and Henk A.M. Wilke (1997) ,"≫Motivation, Capacity and Opportunity to Complain: Towards a Comprehensive Model of Consumer Complaint Behavior", in NA - Advances in Consumer Research Volume 24, eds. Merrie Brucks and Deborah J. MacInnis, Provo, UT : Association for Consumer Research, Pages: 464-469.

Advances in Consumer Research Volume 24, 1997      Pages 464-469


Kaj P.N. Morel, Delft University of Technology, the Netherlands

Theo B.C. Poiesz, Tilburg University, the Netherlands

Henk A.M. Wilke, Leiden University, the Netherlands


In this paper, highlights of the consumer complaint behavior literature are reviewed and implications for a general theoretical framework are assessed. Inspired by models proposed in the area of consumer information processing, a relatively simple overall model is proposed. The main determinants specified by this model are motivation, capacity, and opportunity to complain. A study is reported in which the model is operationalized and assessed. The results provide some support for the hypothesis that complain behavior is a positive function of the mathematical product of the three determinants. Potential functions of the model are briefly discussed.

Why and how do consumers complain? In the past two decades many researchers have addressed this question, leading to an improved understanding of consumer complaint behavior (CCB). However, it seems that some of the issues raised in the early CCB studies remain unresolved. For example, in 1975, Day and Landon concluded that "a comprehensive theory of consumer complaining behavior remains to be formulated and tested" (p. 263) and "efforts to develop a useful theory of consumer complaining behavior should also go forward" (p. 268). Several years later, Krishnan and Valle (1979) state that "a systematic application of theoretical constructs is necessary for a better understanding of consumer complaint behavior" (p. 445). More recently others have come to similar conclusions: "The need has been cited for a comprehensive, integrated model that can predict complaining behavior" (Kolodinsky and Aleong 1990, p. 61). Maute and Forrester (1993) stated that "as studies of [consumer complaint behavior] emerge, unresolved definitional and taxonomic questions have resulted in a body of research that is largely atheoretical and non-empirical." (p. 219).

These various observations raise the question of what twenty years of research on CCB have yielded. Singh (1988) concluded that research has led to significant agreement on the concept of CCB. In the first place, complaint behavior is assumed to be triggered by feelings of dissatisfaction with a product or service. Secondly, CCB responses are considered to be either behavioral or non-behavioral, behavioral responses being those actions a consumer takes to express some form of dissatisfaction. "CCB, then, is conceptualized as a set of multiple (behavioral and non-behavioral) responses, some or all of which are triggered by perceived dissatisfaction with a purchase episode" (Singh 1988, p. 94). Notwithstanding the agreement, CCB research is characterized by considerable conceptual and methodological variation and differentiation. In spite of the academic efforts made so far, as of 1996 a comprehensive model of CCB is still needed. We will attempt to assess whether theoretical and empirical arguments for such a model can be proposed. First however, we will briefly review the available CCB literature.


The literature on CCB research can be divided into three categories of studies: (1) descriptive studies, (2) heuristic studies, and (3) predictive studies. Each category will be briefly summarized below, and for each category, an example in the form of a frequently cited study will be provided.

Descriptive studies do not, by themselves, produce any new theoretical or conceptual ideas; they tend to report the results of large-scale surveys on actual consumer complaint actions. For example, in a sample of 600 respondents, Day and Ash (1979) collected data on the level of consumer satisfaction, sources of consumer satisfaction, and post-dissatisfaction responses for several categories of durable consumer products. Several authors have presented conceptual models of CCB, not with the intention of subjecting them to empirical testing, but to offer a framework for the classification of the results of large-scale surveys. Building on suggestions offered by Day and Bodur (1977) and Day and Landon (1977), Day and Bodur (1978) used the #o action-private action-public action’ scheme for classifying complaint behavior as a basis for formulating questions for a 600 household survey on frequency of dissatisfaction, reasons for dissatisfaction, and post-dissatisfaction responses for a variety of consumer services.

Heuristic studies differ from purely descriptive studies in their emphasis on theoretical progress. These studies review the relevant literature on CCB, present some kind of conceptual model of CCB, and offer suggestions for future research. Some of these studies yield new empirical data. Studies which provide no new data use secondary analyses to support or clarify their respective arguments. A model of complaining behavior is presented by Day and Landon (1977); this model not only describes the behavioral alternatives dissatisfied consumers have (no action, private action, public action), but also proposes factors that influence choices among these alternative actions (marketing factors, consumer factors, circumstantial factors). Other heuristic studies have been reported by Day (1980), Day et al. (1981), and Jacoby and Jaccard (1981). Day and Landon (1975) distinguished four major factors underlying complaining behavior: (1) propensity to complain, (2) opportunities to become dissatisfied, (3) opportunities to complain, and (4) disparity in consumer knowledge. They mention these factors to support their argument that traditional complaint data (i.e. complaints received by third party complaint agencies) are biased and inaccurate because of consumer differences on each of the determinants.

Finally, predictive studies present a theoretical framework for predicting future CCB which is subsequently tested. In several experiments Kolodinsky (1992, 1993, 1995) and Kolodinsky and Aleong (1990) used an operational model based on economic theory to predict CCB for services. According to this model a consumer is assumed to maximize some kind of short-term utility. The level of utility determines whether a consumer will undertake a particular complaint action. On the basis of previous research and economic theory, predictors were selected and incorporated in several logistic models, with dependent variables ranging from various complaint actions (no action, public action, private action) to number of complaints, degree of complaint resolution, and intention to repeat purchase. The logistic models predicted CCB quite well, the percentage of correct predictions ranging from 8% to 100%, with an average of about 80%. The authors observed that, although predictions based on a combination of predictors were quite accurate, very few of the isolated predictors were significant. Another predictive study was reported by Maute and Forrester (1993). Here a different economic model, the investment model, provided the conceptual framework. In this case the predictors were magnitude of the dissatisfaction problem, exit barriers, and attractiveness of alternatives. Consumer complaint actions were predicted using Hirschmann’s (1970) three-dimensional classification scheme: exit, voice, and loyalty. The results showed that the three predictors were all significantly associated with the three types of complaint action.

Our review of the literature supports the conclusion that CCB research has led to many interesting and valuable insights. First, extensive survey research has resulted in a large body of data on consumer dissatisfaction and real complaints for a vast array of products and services. In the second place, the structure of consumer complaint actions has been studied intensively, resulting in two accepted taxonomies of post-dissatisfaction behavior: Hirschmann’s (1970) voice-exit-loyalty taxonomy, and Day and Landon’s (1977) no action-private action-public action classification scheme, both of which seem valid and useful. Third, many factors that influence CCB have been examined, which has shed considerable light on the conceptual structure of the consumer complaining process. Finally, promising results have been reached in predicting CCB using econometric logistic models (Kolodinsky 1992, 1993, 1995; Kolodinsky and Aleong 1990). Consequently, Kolodinsky and Aleong (1990) cnclude that "It is possible to build on previous research to develop an integrated model of consumer complaining behavior [based on a theory of complaining behavior] that can be empirically estimated to explain variation in, and predict when complaints are most (or least) likely to occur" (p. 62). With regard to Kolodinsky and Aleong’s conclusion, however, it may be argued that an integrated model of consumer complaint behavior is not (yet) available, and that the research reported in the literature is still too fragmented. Determinants of CCB have been studied in isolation or in relatively small groups. More recent experiments have addressed several factors at the same time (Kolodinsky 1992, 1993, 1995; Kolodinsky and Aleong 1990), but the combination of variables employed to predict complaint behavior seems quite arbitrary and incomplete. For example, Kolodinsky (1995) used 15 predictors, divided over four categories intended to cover the whole array of CCB determinants mentioned in the literature. Closer inspection of these variables reveals that none of these variables represent motivational aspects of complaint behavior, which suggests that the selection of behavioral determinants is not based upon an underlying theory of complaint behavior. Lack of a solid theoretical foundation tends to be accompanied by lack of conceptual clarity, resulting in CCB researchers examining "the effect of haphazardly chosen predictors on dissatisfaction responses" (Maute and Forrester 1993, p. 224). The problem that may arise is illustrated in the research of Kolodinsky (1992, 1993, 1995) and Kolodinsky and Aleong (1990), which indicated that few of the isolated predictors were significant, while the combined variables in the overall model significantly predicted CCB. Apparently, it is not clear which variables contribute to the prediction of CCB and which ones do not. There also arises the question of whether the observed significance is simply due to the large number of predictors incorporated in the model.

In view of the preceding arguments, we propose an approach that may contribute to an improved understanding of the complaint behavior of consumers. This approach is intended to provide a useful alternative, or a supplement, to the approaches that have been employed so far. In the next section the approach-referred to as the Triad model-will be introduced. The results of an experimental test of this model will be presented and discussed.


The basic idea of the model was inspired by theoretical developments in an area that is essentially unrelated to consumer complaint behavior: advertising processing. In the latter field, several authors proposed that the problem of fragmentation be solved by using simplifying models focusing on a very limited set of explanatory factors. Petty and Cacioppo (e.g. 1986) proposed motivation and ability to process as the central determinants of processing; Andrews (1988), Batra and Ray (1986), MacInnis, Moorman, and Jaworski (1991), and Poiesz and Robben (1996) focussed on motivation, capacity or ability, and opportunity as the critical factors for explaining the behavior under consideration. The use of such general factors decreases the richness of detail but increases the likelihood that the general determinants of the criterion behavior will be taken into account. In the area of information processing this general approach proved to stimulate theoretical integration (e.g. in the form of the Elaboration Likelihood Model, Petty and Cacioppo 1986). As it was concluded in the previous section that CCB research is ragmented, a simplified heuristic approach will be pursued in the present study. It is for this reason that we propose a model in which consumer complaint behavior is explained by three general factors: motivation, capacity, and opportunity to complain. With this model an attempt is made to avoid an approach that is incomplete, considers isolated variables, or employs an arbitrary combination of variables (these being the shortcomings of existing approaches). We will refer to the model as the 'Triad’ model, thereby emphasizing the need to consider the three factors simultaneously when attempting to explain complaint behavior. The Triad model is based on several assumptions:

1. The main assumption of the Triad model is that all determinants of behavior can be 'captured’ by three variables: motivation, capacity, and opportunity. People will engage in a specific behavior when their motivation, perceived capacity, and perceived opportunity to execute this behavior are sufficiently high, that is, above some critical subjective minimum level. Motivation refers to the need, interest, or desire to engage in a particular behavior. Capacity is defined as the person’s capability, instrumentality, and skill to engage in a certain behavior and to achieve the stated goal. Opportunity concerns the extent to which external circumstances-in the broadest meaning of the word-stimulate or inhibit a particular behavior (viz. complaint behavior).

2. The three determinants are exhaustive concepts. All (potentially) relevant behavior determinants can be represented in terms of these general concepts.

3. The three determinants constitute necessary, but not sufficient factors. For a particular behavior to take place all three Triad factors have to reach some minimum level simultaneously. In other words: the Triad model assumes a multiplicative relationship among the three determinants.

4. A person’s subjective assessments of the Triad factors determine whether he or she will engage in a particular behavior. Subjective assessments and objective constraints (objective capacity and opportunity levels) together determine whether the behavior does actually take place and to what extent.

The Triad model is proposed as a framework for CCB research, because the model (a) is based on existing theory; (b) can be applied to all possible complaint actions; (c) includes all possible behavioral antecedents; and (d) can be operationalized and empirically tested.

Goal and hypothesis

The present study constitutes an initial attempt to assess how well complaint behavior may be predicted by the three general determinants of the Triad model. More concretely, it is hypothesized that the subjective probability of complaint behavior can be predicted by the mathematical product of a person’s perceived motivation, perceived capacity and perceived opportunity to perform a specific complaint behavior.


Subjects and design

The sample of respondents was drawn from the population of a mid-size town in the Netherlands. In view of the critical behavior that was investigated in the present study-" complaining during a dinner in a foreign restaurant"-subjects who could be expected to have some experience with dining in foreign restaurants were recruited. For this reason inhabitants of three neighborhoods with more than average income and educational levels were invited to participate. An analysis of actual income and education levels revealed that (1) all respondents had at least completed secondary school, and 72% also had a higher vocational education or university degree; (2) 88% of the respondents had at least an average income (more than the Dutch equivalent of $25,000) of whom 46% earned an above average income (more than the Dutch equivalent of $50,000). The design was a 2x2x2 factorial design with two levels ('high’ and 'low’) for each of the three between-subjects factors motivation, capacity and opportunity. A total of 235 respondents received the questionnaire; 210 were dropped off and picked up at their home; another 25 subjects received and returned the questionnaire by mail. Of the returned questionnaires a total of 106 were filled in and could be used for analysis. Subjects were randomly assigned to one of the eight experimental conditions. To control for possible order-of-question effects in each condition, two differently ordered questionnaires were constructed for each condition, resulting in a total of sixteen different questionnaires.

Stimulus material

Considering the fact that written descriptions of scenarios were presented to respondents, several operational and validity issues had to be considered. First, the operationalization of each of the three determinants had to be feasible, in the sense that both a high and a low level condition could be created. Second, both the object of the complaint and the situation had to be selected in such a way that the complaint was perceived by subjects as an actual behavior option. The third consideration was that the scenario had to be as realistic as possible: respondents had to be able to imagine themselves in the circumstances described. Finally, the complaint action had to be relevant behavior for the respondents. They had to have the impression that the complaint action actually would matter. Respondents were told to imagine themselves having dinner with friends in a restaurant in Paris, and that they were disappointed with the wine that was served.

Independent variables

The high and low motivation capacity, and opportunity conditions were operationalized in the scenarios using positively or negatively formulated motivation, capacity, and opportunity related aspects (see Table 1). The operationalization of the different aspects was subject to several considerations. Most importantly, every aspect had to operationalize the corresponding determinant as specifically as possible. After all, the three independent variables had to be operationalized independently. Also, the manipulations had to be equally strong: none of the three independent variables should be a priori dominant over the others. Results of a pilot study showed that the manipulations of motivation and opportunity resulted in two significantly different response patterns; the manipulation of capacity did not. The scenarios were subsequently adjusted by situating the restaurant in a foreign country (in this case France)-the original scenarios were not situated abroad-so that the typical capacity-related aspect 'knowledge of culture and language’ could be used.

Dependent variables

The main dependent variable was the subjective probability of engaging in a specific complaint action, described as follows: 'You don’t accept the wine. You tell the restaurant personnel that the wine does not meet your expectations and you ask them if something can be done about it, for example getting another wine instead.’ The dependent measure was subjects’ probability of complaining (scale 0% to 100%).


The questionnaire consisted of an introduction, a scenario, and 28 questions. The introduction told the respondents what they were expected to do. The instructions emphasized that subjects were to imagine themselves in the specific situation described by the scenario. The scenarios covered two pages: the actual description and a summary of the most important issues in this description. The respondents were urged to use the summary to remind them of the situation. The majority of the questions in the questionnaire was aimed at measuring the respondentss subjectively perceived motivation, capacity, and opportunity. Perceived motivation, for example, was determined by asking the respondent to indicate on a 9-point scale to which extent he or she would want to do something about his or her dissatisfaction. Participation took about 45 minutes.



Two respondents showed very deviant response patterns. There was stron, but not conclusive, evidence that these deviations were caused by misinterpretation of the response scales (reversal of the scale end-points). These two respondents were excluded from all analyses.

Manipulation checks

Three 2x2x2 ANOVAs were carried out with the independent variables Motivation (high, low), Capacity (high, low), and Opportunity (high, low), and the dependent variables Perceived Motivation, Perceived Capacity and Perceived Opportunity. One case was missing for each dependent variable, so N=103.

Perceived Motivation. Main effects of Motivation (F(1,95)=73.60, p<.001) and Capacity (F(1,95)=14.85, p<.001) and interaction effects of Motivation x Capacity (F(1,95)=7.28, p<.01) and Motivation x Opportunity (F(1,95)=8.33, p<.01) were found. With regard to the interaction effects, it was observed that when motivation was high, perceived motivation hardly differed for high (M=8.64) versus low (M=8.23) capacity. However, when motivation was low, there was a significant difference, perceived motivation being higher for high capacity (M=6.54) than for low capacity (M=4.19). The same held for the Motivation x Opportunity interaction. In a high-motivation condition perceived motivation was almost equal for high (M=8.19) and low (M=8.68) opportunity, but in the low-motivation condition a significant difference in perceived motivation was observed between the high- and low-opportunity conditions (Mhigh=6.15, Mlow=4.58).



Perceived Capacity. For Capacity only a main effect was found (F(1,95)=27.13, p<.001). High capacity resulted in a higher perceived capacity (M=7.43) than did low capacity (M=5.17).

Perceived Opportunity. Two main effects were ascertained, Capacity (F(1,95)=22.23, p<.001) and Opportunity (F(1,95)=16.64, p<.001). Perceived opportunity was higher under high-capacity conditions (M=6.88) than under low-capacity conditions (M=5.00). Also, high opportunity resulted in higher perceived opportunity (M=6.75) than did low opportunity (M=5.10).

Two conclusions can be drawn from these results. The experimental manipulations did produce differing levels ('high’, 'low’) of each of the Triad components. However, respondents in the low conditions scored unexpectedly high, their average score lying around the mid-point of the scale (5.00). Apparently, the manipulations did not result in conditions experienced as 'low’ in an absolute sense. Secondly, the effects found other than the intended main effects seem to suggest that the manipulations of the Triad variables were not independent. However, interdependence of the experimental manipulations is just one possible explanation for the observed results. These results can also be explained by assuming that the Triad variables influence each other. For example, higher capacity can evoke higher motivation (someone who is good at doing something might be more motivated to do it), and lower opportunity (someone who is good at doing something will need less time to do it).

Probability of complaint behavior

Experimental model. The probability of complaint behavior was examined using ANCOVA with Motivation (high, low), Capacity (high, low) and Opportunity (high, low) as independent variables, and (non-manipulated) prior familiarity with the French language and customs as a covariate (F(1,93)=8.05, p<.01). Two cases were missing, so N=102.

Probability of Complaint Behavior was significantly associated with Motivation (F(1,93)=45.46, p<.001), Capacity (F(1,93)=58.78, p<.001), Opportunity (F(1,93)=5.36, p<.05), and Motivation x Opportunity (F(1,93)=4.60, p<.05). In Table 2 the means for the Motivation x Opportunity interaction are presented. As predicted, respondents in the high-capacity condition were more likely to complain than respondents in the low-capacity condition (Mhigh=84.00, Mlow=44.52). The same was true for motivation: respondents scoring high on motivation were more likely to complain than respondents scoring low on motivation. This prediction held independent of the level of opportunity, but in the case of low opportunity the probability was lower (Mhigh=58.08, Mlow=33.80). For opportunity the effect was more variegated. The probability of complaining was higher for high opportunity than for low opportunity (Mhigh=58.08, Mlow=33.80), but only when motivation was low. When motivation was high, there was no significant difference between the high-opportunity and low-opportunity conditions (Mhigh=81.73, Mlow=81.40).

To get an impression of the goodness of fit of the experimental model, the percentage of variance in complaint behavior explained by the model was computed. The total percentage of variance explained (R2=SSExplained / SSTotal) was 58.1, motivation explaining 20.5%, capacity 26.5%, opportunity 2.4%, Motivation x Opportunity 2.1%, and the remaining effects 6.6%. Capacity is the Triad variable that contributed most to the prediction of the subjective probability of complaint behavior, motivation being a good second and opportunity playing only a minor role.



Logistic model. There are two reasons justifying use of another statistical model to analyze the data from this experiment. The first reason is the conceptual complexity of the elements in the Triad model. The manipulation checks showed that the operationalizations of the Triad variables may not have been independent. The observed intercorrelations may have been caused by interaction or dynamic effects, but it is equally possible that the correlations between the Triad variables are the result of inaccurate operationalizations. If the latter is the case, the operationalizations of motivation, capacity, and opportunity were not accurate realizations of the subjectively perceived Triad factors they were intended to induce. From this perspective it might be preferable to predict complaint behavior on the basis of the subjectively perceived instead of the induced Triad variables. The second reason to employ a model based on perceived variables is theoretical in nature. The Triad model emphasizes that motivation, capacity, and opportunity as they are perceived by the person who is about to engage in a given behavior may be more important than their objective counterparts for the prediction of behavior initiation.

The relation between perceived Triad variables and the probability of complaint behavior was examined using SPSS-X Logistic Regression Analysis. Logistic regression analysis was used instead of standard multiple regression analysis because the dependent variable, viz. probability of complaint behavior, (1) was not normally divided; (2) showed no linear relation with the independent variables motivation, capacity, and opportunity; and (3) was heteroscedastic. Several models could be analysed, depending on the factors selected a priori for inclusion in the model. On theoretical grounds a multiplicative model was selected, the Triad Product being the predctive variable and the dichotomous variable Probability of Complaint Behavior (high, low) being the dependent variable. After all, the Triad model assumes that behavior is predicted by the mathematical product of a person’s subjective motivation, capacity, and opportunity, which we will call the Triad Product. The regression equation was as follows:


in which Z=constant + b Triad Product=-2.311 + 0.015 Triad Product. The Chi-square statistic was found to be significant (c2 (1)=69.03, p<.001), indicating that at least one of the regression coefficients (in this case there is only one coefficient) was significantly different from zero. The Wald statistic showed that both the constant (Wald(1)=17.60, p<.001) and the Triad Product coefficient b (Wald(1)=20.92, p<.001) were significant. So, the Triad product was a significant predictor of the probability of complaint behavior. The positive sign of the regression coefficient indicated that an increase in the Triad product was associated with an increase in the probability of complaint behavior, confirming the hypothesis. It should be noted, however, that the power of the Triad product in predicting complaint behavior was limited, R=.38 (The squared R-value does not indicate variance accounted for like the squared R-value in regression analysis. This value does, however, give an indication of the explanatory power of the model parameters; the closer this value is to 1 the higher the explanatory power.)


The goal of the present study was to assess whether an approach using general explanatory variables may prove useful for the study of consumer complaint behavior. In this study, the 'Triad model’ was put forward as a possible relevant approach. This model proposes three critical variables (motivation, capacity, and opportunity) as simultaneous determinants of complaint behavior. Before assessing to what extent this goal was achieved we will first consider some methodological issues.

In this study scenario descriptions were used to generate high and low levels of motivation, capacity, and opportunity. Although much care was taken to ensure that the manipulations were effective, the scenario approach is an indirect approach at best. Subjects were asked to imagine themselves in a particular situation. The obvious risk is that mental constructions may be less effective in inducing the required effect than real life experiences. Although the manipulations were successful in generating differences between conditions for each main variable, the absolute levels of the manipulations were not as intended. Respondents in the 'low’ conditions in fact experienced 'medium’ conditions. A possible reason for this is that it is more difficult for subjects to imagine themselves being in low motivation, capacity, and opportunity conditions than in high motivation, capacity, and opportunity conditions. Here we should note that most of the subjects were likely to have had the experience of having dinner in a Paris restaurant, Paris being merely five hours by car or train from the city in which the study took place.

The results found using an experimental (ANCOVA) model are not entirely in line with the assumed multiplicative prediction of the Triad model. Instead of a third order interaction of the three factors, a main effect of capacity and an interaction effect of motivation x opportunity were found. This somewhat disappointing result may be attributed to the conceptual ambiguity of the relationship between the three general factors motivation, capacity and opportunity, and the consequences of this ambiguity for experimental manipulations of these variables. For this reason we have argued that a model based on subjective perceptions of the Triad factors may be more appropriate for the purposes of explaining complaint behavior variance. The multiplicative prediction was indeed supported when the perceived Triad variables were taken as predictors in a logistic model with the probability of complaint behavior as the criterion variable.

Despite the restrictions associated with our manipulations, the study suggests potential benefits of the approach adopted here. Even though the variance explained by the logistic model is limited, the results are in the expected direction. It should be noted that our study was probably the first attempt ever to apply a three factor model of this general nature to complaint behavior. Obviously, manipulations and operationalizations should be improved in future studies aimed at assessing the model’s true explanatory power. The potential advantage of the present approach is two-fold. First, it may be useful as an explanatory model as such. For some theoretical and practical consumer complaint issues it may suffice to know to what extent behavior variance is due to motivation, capacity, or opportunity, or a combination of these. A second possible function of the model is that it may serve as a complementary approach in studies where more isolated and more specific variables are the primary focus of interest. The addition of motivation, perceived capacity and perceived opportunity as research factors would not only facilitate the interpretation of the effect of the manipulation (if any), but would also stimulate interstudy comparisons. It is for these theoretical and meta-theoretical reasons that future research in this direction is warranted.


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Kaj P.N. Morel, Delft University of Technology, the Netherlands
Theo B.C. Poiesz, Tilburg University, the Netherlands
Henk A.M. Wilke, Leiden University, the Netherlands


NA - Advances in Consumer Research Volume 24 | 1997

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