Consumer Complaint Intentions and Behavior: Definitional and Taxonomical Issues

Consumer Complaint Intentions and Behavior: Definitional and Taxonomical IssuesAuthor(s): Jagdip SinghSource: Journal of Marketing, Vol. 52, No. 1 (Jan., 1988), pp. 93-107Published by: American Marketing AssociationStable URL: http://www.jstor.org/stable/1251688 .

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Jagdip Singh

Consumer Complaint Intentions and Behavior: Definitional and

Taxonomical Issues Researchers and practitioners recently have given increasing attention to the antecedents and consequences of postpurchase consumer complaint intentions and behaviors. Issues pertaining to the nature and structure of the consumer complaint behavior (CCB) concept, however, have not received such attention. The author assesses the validity of the three current operationalizations and taxonomies of CCB using intentions data from four different and independent CCB situations. None is an adequate representation of the empirical observations. Consequently a taxonomy is proposed that is based on exploratory analysis of one of the CCB situations. Confirmatory analysis of the other three CCB situations supports the proposed taxonomy. A validity analysis using complaint behavior data for the four CCB situations also supports the proposed CCB taxonomy.

THE study of consumer complaint intentions and corresponding behaviors (CCB) has received in-

creasing attention in the last 10 years from researchers and practitioners alike (Bearden and Teel 1983; Busi- ness Week 1984; Day 1984; Resnik and Harmon 1983; Richins 1983; TARP 1979, 1986). Practitioners find these constructs useful in understanding the extent of marketplace dissatisfaction and in devising programs to alleviate consumer complaints (Lewis 1982; Ross and Oliver 1984; TARP 1979, 1986). In terms of theory, the study of CCB and its consequences appears to be critical in the explanation and prediction of consumer repurchase intentions and brand loyalty (Day 1984; Engel and Blackwell 1982; Richins 1983). Fur- ther, in terms of macromarketing, the nature and extent of CCB prevalent in an industry seem to affect consumer and social welfare (Andreasen 1984, 1985).

Despite the obvious importance of the CCB concept, its development has been minimal. Previous work in marketing has attempted to understand how CCB

Jagdip Singh is Assistant Professor of Marketing, Weatherhead School of Management, Case Western Reserve University. The author thanks the anonymous JM reviewers for their helpful suggestions. The research was made possible by a grant from Furr's, Inc., of Lubbock, Texas.

results from marketplace dissatisfactions (e.g., Day's 1984 notions of benefits/costs, attitudes, and consumer knowledge) as well as the psychological and behavioral reactions to CCB (e.g., Gilly and Gelb 1982). Relatively little work has been done, however, to understand the nature and structure of the CCB concept itself. Because consumers usually engage in multiple CCB responses (e.g., voice and word of mouth), CCB definitional and taxonomical issues are critical for understanding CCB and for developing models that explain CCB. Bearden and Teel (1983) noted that a lack of proper conceptualization and measurement of the CCB concept may have contributed to their inability to model the complaining process (i.e., identify its antecedents). Similarly, Landon (1980) observed that research in the understanding of antecedents/consequences of CCB would be more useful if issues relating to their definition, taxonomy, and dimensions could be thoroughly addressed.

Some attempts have been made in that direction. The call for a definition and taxonomy of CCB has been addressed by Day (1980) and Day and Landon (1977). Though encouraging, the proposed classification schemata do not unambiguously resolve CCB taxonomical issues. For instance, these schemata nei-

Journal of Marketing Vol. 52 (January 1988), 93-107. Consumer Complaint Intentions and Behavior /93



ther have similar rules for classification nor show why a particular schema is more valid and/or useful than another. Efforts to operationalize CCB also are fraught with inconsistencies. Bearden and Teel (1983) proposed a 5-item Guttman operationalization, which seems to have had some acceptance (Day 1984). Such an operationalization is at best arbitrary, however, and is at odds with each of the preceding CCB taxonomies.

As research on the antecedents and consequences of CCB accumulates, it would be helpful to integrate past research systematically, resolve conceptualization/taxonomy/operationalization inconsistencies, and thereby enrich our understanding of the concept of CCB. The purpose of the study reported here was to address this gap in the CCB research. However, unlike much of past research, the study examined this issue on an empirical basis. That is, the research is not deductivist in proposing yet another taxonomy and/ or operationalization of the CCB concept. Instead, it is an attempt to examine such questions as: "Are the consumer self-report data consistent with the current realizations of the CCB concept (e.g., classification schemata, operationalizations, etc.)?" and "What taxonomy do the data suggest for the CCB concept?" The investigation of these issues would provide an understanding of the nature and structure of the CCB concept that is relatively more valid and hence more useful in the task of theory-building.

A two-step strategy was followed to address the preceding issues. First, consumer complaint intentions were analyzed in an attempt to resolve the afore- mentioned conceptualization/taxonomical issues. Be- cause intentions data are obtained on a graded scale (e.g., Likert), they are more appropriate for such analysis than are binary (e.g., yes/no) behavior data. More importantly, the delineation of unique dimensions that underlie CCB responses must be based on the relative intensity with which consumers evaluate different CCB options (i.e., intentions), not simply on the behaviors they did/did not engage in. Once a satisfactory structure for CCB was determined, the second step was to subject this taxonomy to a validation check by using the consumer complaint behavior data. This strategy was followed with data from four different and independent consumer complaint situations (medical care, grocery, auto repair, bank). None of the currently available taxonomies/operationalizations were found to be an adequate representation of the empirical observations. Consequently an exploratory study of one of the CCB situations was used to propose a taxonomical structure suggested by consumer complaint intentions. Confirmatory analysis of the other three CCB situations supported the proposed taxonomy. In the second step, validity analysis using behavior data for the four CCB situations appeared to

support the proposed taxonomy as well. Finally, the proposed classification schema for CCB was formal- ized.

A Review of the CCB Concept

Conceptualization Issues

Though several definitions have been proposed (Day 1980; Jacoby and Jaccard 1981; Landon 1980), there is considerable agreement about the conceptual meaning of the consumer complaint behavior construct. First, the CCB phenomenon is believed to be triggered by some feelings or emotions of perceived dissatisfaction (Day 1984; Landon 1980). Without perceptions of dissatisfaction, consumers' responses cannot qualify as CCB (see Jacoby and Jaccard 1981 for "satisfied" complainers).1 Second, CCB responses generally are considered to fit into two broad categories, behavioral and nonbehavioral. Behavioral responses, which tra- ditionally have been the focus of complaint behavior studies, constitute any or all consumer actions that convey an "expression of dissatisfaction" (Landon 1980). Conceptually, these responses need not be limited to those directed toward the seller (i.e., manufacturer, retailer, etc.). Behaviors involving third parties (e.g., Better Business Bureau, legal actions, etc.) or even friends and relatives (e.g., negative word-of- mouth communication) are also regarded as being in the category of behavioral responses (Day 1984; Richins 1983). In fact, conceptualizing CCB as complaints received by the seller is viewed as overly restrictive (Best and Andreasen 1977; Day and Ash 1979; Day et al. 1981; Richins 1983). Further, Day et al. (1981), among others, contend that nonbehavioral responses, such as when the consumer forgets about a dissatisfying episode and does nothing, should be considered as le- gitimate CCB responses. To the extent that some people choose behavioral responses whereas others elect nonbehavioral responses in relatively similar dissatisfying episodes (as has been reported in the literature), the inclusion of nonbehavioral responses appears to be not only justified but necessary to understand the process underlying the CCB response.

CCB, then, is conceptualized as a set of multiple (behavioral and nonbehavioral) responses, some or all of which are triggered by perceived dissatisfaction with a purchase episode. This multiplicity raises questions

'Jacoby and Jaccard's (1981) notion of "satisfied" complainers is

mainly related to "purported product defects when in actuality, there is no verifiable [product] defect" (p. 19). In the context of our definition, purported defects are within the scope of "perceived" dissatisfaction.

94/ Journal of Marketing, January 1988



about the dimensionality of the CCB concept.2 At the two extremes are the possibility of unidimensional or an n-dimensional (where n are all possible CCB actions) taxonomy for CCB responses. The following section addresses this issue.

Classification Issues A review of the CCB literature shows two major attempts to address taxonomical issues related to the CCB construct. In the first attempt, Day and Landon (1977) proposed a two-level hierarchical classification schema (see Figure 1). The first level distinguishes behavioral (i.e., action) from nonbehavioral (i.e., no action) responses. The second level represents the distinction between public and private action. Public actions include seeking redress or refund from the seller, complaining to a consumer organization, and legal actions. Some typical examples of private actions are word-of-mouth communication to friends and relatives and ceasing to patronize a store. Whereas the no action/action distinction follows directly from the conceptualization of CCB, Day and Landon seem to justify the public/private dichotomy on the grounds of the nature and importance of the product involved in the dissatisfaction. That is, for complex and ex- pensive products (e.g., durable goods), consumers are

FIGURE 1 Day and Landon's (1977) Classification of

Consumer Complaint Behavior

Seek Redress Directly from Business

Complain to Boycott Warn Friends Legal Action Public or Seller or and Relatives

Private Agen- Manufacturer cies

2Because consumers generally engage in multiple complaint behaviors, the issue of dimensionality is also important in relation to the models that attempt to explain CCB. In other words, such models must specify antecedents at the level of individual dimensions of CCB. In this sense, complaint behaviors are unlike the usual consumer purchase behaviors (bought/not bought), for which dimensionality issues are perhaps irrelevant.

expected to engage more often in public actions. In addition, Day and Landon suggest that in such a situation, "the chances that the consumer will do nothing at all or take only private actions are lower but still appear to be substantial" (p. 432).

Empirical support for the validity of the preceding distinction is limited, however. For instance, Day and Ash (1979) report some typical findings for complaint behaviors in the case of nondurable and durable goods. After dissatisfaction with durable goods, 32.5% of the respondents reported warning family and friends (i.e., private action). For nondurable goods, the compara- ble value was reported to be 33.3%. In contrast, the percentage of respondents who complained to the seller for a replacement or a refund (i.e., public action) was 48.8% and 57.9% for durable and nondurable goods, respectively. That is, as the product complexity in- creased (nondurable -> durable), the extent of private actions remained about the same but public actions actually decreased. This finding is inconsistent with the hypothesis of Day and Landon (1977). Other studies, however, do tend to support that hypothesis (e.g., Day et al. 1981). Though these contradictory findings do not invalidate Day and Landon's taxonomy per se, they do raise some doubts about the basis of the proposed classification schema.

Day (1980) suggested another basis for classification at the second level of Day and Landon's taxonomy. He noted that consumers complain (or do not complain) to achieve specific objectives. In fact, consumers can provide various "explanations" (p. 212) for the complaint action they take. Day proposed that the "purpose" of complaining can be used to classify behavioral CCB into three broad categories.

1. Redress seeking. The motive is to seek specific remedy(ies) either directly or indirectly from the seller (e.g., complain to manufacturer, take legal actions, etc.).

2. Complaining. The motive is to communicate dissatisfaction for reasons other than seeking remedy (e.g., to affect future behavior, to per- suade others by word-of-mouth communication, etc.).

3. Personal boycott. The motive is to discontinue purchase of the offending service (including product, brand, store, and/or manufacturer).

Though Day suggests that the preceding taxonomy can be considered with that of Day and Landon, the issue of which classification (individually or com- bined) is recommended for future research in CCB re- mains unaddressed. Resolving this issue would entail an evaluation of (1) the basis of classification and (2) the usefulness of the resulting taxonomy (e.g., its validity) (Hunt 1983). The preceding CCB taxonomies

Consumer Complaint Intentions and Behavior / 95



have entirely different bases for categorization. Fur- ther, these "bases" were developed deductively, that is, they represent the respective researchers' subjec- tive notion of a good classification basis. An objective evaluation of a deductively derived "basis" is difficult at best. A reasonable evaluation strategy seems to be to confront real-world data and observe which "basis" is more valid. Such an empirical approach also would address the "usefulness" criterion, because the resulting taxonomy would better represent reality and suggest more accurate operationalization of the CCB construct.

Operationalization Issues Research attempting to operationalize CCB explicitly as a construct is limited (for an exception, see Bearden and Teel 1983). For instance, Day et al. (1981) suggest a 9-item operationalization but do not report any psychometric properties of the CCB construct (e.g., its alpha reliability, dimensions, etc.). Instead, these researchers treat the nine items as individual CCB responses (for similar examples, see Day and Ash 1979; Day and Landon 1977).

Bearden and Teel (1983) were the first (and the only) researchers to view CCB explicitly as a construct, propose an operationalization (i.e., Guttman scale), and report some psychometric properties. They operationally defined CCB as a Guttman scale (i.e., a one-factor, deterministic model)3 in which the items can be ordered to reflect increasing "intensity" of complaints (Torgerson 1958). The data collected by Bearden and Teel on a 5-item CCB scale have coef- ficients of reproducibility and scalability of .98 and .78, respectively (see Appendix A for items used).

In terms of theory, however, several issues can be raised about the Guttman operationalization. First, despite the well-documented theoretical reasons (see section on classification issues) for the inclusion of nonbehavioral responses (i.e., do nothing), this particular operationalization does not include such responses in the CCB construct. Further, whereas other classification schemata involve a two-dimensional (e.g., Day and Landon's public vs. private actions) or three- dimensional (e.g., Day's redress vs. complaint vs. boycott) conceptualization, Bearden and Teel's operationalization posits a unidimensional structure for CCB. Though Bearden and Teel give no a priori basis for proposing a one-factor operationalization, the em-

3A Guttman scaling model subsumes a combination of the one-factor criterion and the criterion of complete determination by one factor (i.e., no measurement error) for dichotomous responses (Hattie 1985; Kim and Rabjohn 1980). Because of such restrictive assumptions (especially no measurement errors), "a perfect Guttman scale is not likely to be found" (Kim and Rabjohn 1980, p. 130). When the deterministic assumption is relaxed and one uses continuous variables, the Guttman model reduces to the familiar one-factor model in factor

analysis (Kim and Rabjohn 1980).

pirical support they provide affords confidence in their view. Thus, for instance, Day (1984) suggests that CCB responses be "operationalized as a Guttman scale as reported by Bearden and Teel (1983)."

Some caution in the interpretation of Bearden and Teel's findings is warranted. In the proposed 5-item operationalization (see Appendix A), private actions are measured by a single item and the other four items appear to tap public CCB actions. To the extent that single items provide inadequate measurements (Nunnally 1978), the possibility that the operational items measure only one dimension (i.e., public actions) of the CCB construct cannot be ruled out. In other words, the reported findings of a unidimensional Guttman structure of CCB may be an artifact of the kind of items selected and not a tenable operationalization of the complete range of the CCB construct.

The preceding discussion enumerates some of the initial steps in the conceptualization, classification, and operationalization of the CCB construct. The next steps appear to be to consolidate and integrate the findings so as to resolve satisfactorily the stated inconsistencies. Such an endeavor was undertaken to provide a classification schema and operationalization of the CCB construct that researchers can employ with a reasonable assurance of its validity.

Research Design In designing a research study to address the preceding issues, some additional desiderata were considered. First, the proposed operationalization of CCB should be comprehensive (i.e., include the breadth of the phenomenon reflected in the classification schema). Second, the number of items in the proposed CCB scale should be sufficient for empirical assessment of its dimensionality (i.e., to resolve the one/two/three- dimension controversy). Third, the study should be conducted in several different complaint situations so that the veracity of the claims about the nature and structure of the CCB construct can be investigated in some rigorous sense.

Fifteen items were collected from published research reports to measure the diversity of the CCB construct (Best and Andreasen 1977; Day and Bodur 1977; Richins 1983). A pretest with a convenience sample of university staff and faculty indicated that some of the items were repetitious and appeared to degrade respondent interest. On the basis of the analysis of pretest results, a revised scale of 10 items was developed (see Appendix B).4 A subsequent pretest

4Unlike attitudinal constructs, CCB items must be restricted to behaviors that are currently exercisable (and not those that could be desirable). Though 10 items appear to represent a relatively small set, they include most complaint behaviors obtained in previous studies (Best and Andreasen 1977; Day and Bodur 1977). As marketers




with the revised scale appeared to provide satisfactory results.

Robinson (1979) and Singh and Howell (1985), in their reviews of CCB literature, reported that most empirical studies are based on recall of a past dissatisfaction and the complaint actions undertaken. In the present study, respondents also were asked to recall a dissatisfying experience that they remember most clearly. CCB actions were measured by asking respondents to recall their various complaint behaviors. These responses were obtained on a dichotomous (yes/ no) scale of seven items. Further, in an effort to re- duce the effects of memory retention and recall, respondents were asked what they would do if a similar incident happened again. The intentions data were obtained on a most likely/least likely Likert scale (coded 1 through 6). The intentions and behavior questions were separated by several other questions in an effort to control for responses bias.

Four different complaint situations were considered. Specifically, dissatisfaction resulting from experiences with grocery stores, automobile repair shops, medical care providers (e.g., physicians/hospitals), and banks and financial services was examined. Pre- vious research findings suggest that the specific situations considered afford substantial variation in the extent of dissatisfaction as well as in CCB responses (see Best and Andreasen 1977; Day and Bodur 1977).

Data A questionnaire consisting of CCB intentions and behavior items, several other questions pertaining to dissatisfaction, and some background questions was mailed to a random sample of households in Southwest Texas. Four different questionnaires were developed to represent each of the four complaint situations. For each CCB situation, a random sample of 1000 households was selected to receive the questionnaire. Hence, a total of 4000 questionnaires were sent out. Followup was accomplished by sending a reminder card as well as by telephone callbacks using the criss-cross direc- tory. Responses obtained were between 15.5% (automobile repair) and 17.6% (grocery shopping). Ap- pendix C summarizes the demographic characteristics of the sample from the four surveys. Because the survey instructions asked that the questionnaire be an- swered by that person in the household who deals most frequently with a particular industry (e.g., grocery shopping), Appendix C shows variability in some demographic characteristics. For instance, grocery shopping and medical care have a large proportion (70- 73%) of female respondents, whereas automotive repair has the smallest (33%). Age and income also show

proactively open new channels of complaining, such items must be included.

significant variability. The variability in Appendix C, however, is not inconsistent with the findings in CCB research (Warland, Hermann, and Willits 1975).

Responses in the range obtained here,(15-18%) are not uncommon in dissatisfaction research with a random sample of households. For instance, Robinson (1979), in his review of the CCB literature, noted that the relevant population of interest is households who have had a dissatisfying experience (for which there are no sampling frames) and not the set of all households. Hence, response rates obtained are of the same order as the level of dissatisfaction, between 15 and 25% (Best and Andreasen 1977; Day and Ash 1979; Westbrook, Newman, and Taylor 1978).

Results Because behavioral and nonbehavioral CCB actions are non-overlapping phenomena, the item measuring nonbehavioral CCB (i.e., "forgot about the incident and did nothing") was reverse scored. Such a procedure takes the action/no-action distinction as an es- sential but trivial fact and focuses attention on the richer behavioral CCB.

As an initial analysis, Table 1 summarizes the mean and standard deviation for each of the 10 CCB intentions items. An examination of the values in Table 1 shows considerable variations across the four complaint situations. The hypothesis that the var-covari- ance matrix is identical across the four samples (i.e., E1 = '2 = 3 = 4) is rejected resoundingly (X2 (165) = 385, p = .000). This outcome is not surprising because the questionnaire asked respondents to provide CCB for one and only one complaint situation. The implication is that each of the four data sets can be treated as independent and distinct measures of CCB intentions and behaviors.

Confirmatory Analysis To examine Bearden and Teel's (1983) proposition of a Guttman scale, the less restrictive condition of uni- dimensionality for the CCB construct was first investigated. Obviously, if the data do not satisfy the unidi- mensionality criterion, they would fail the more restrictive Guttman property (Kim and Rabjohn 1980). A confirmatory factor analysis was performed to test the hypothesis that a unidimensional, congeneric, common factor model underlies CCB responses in the data sets. The LISREL V program was used (Joreskog and Sorbom 1982). Table 2 summarizes the results. The stated hypothesis is rejected strongly with chi square values ranging from x2 (35) = 158 (p = .000) for grocery CCB to x2 (35) = 224 (p = .000) for medical care CCB. Other statistics, such as the goodness-of-fit index (GFI) and root mean square error (RMSE), also suggest that a unidimensional concep-




TABLE 1 Means and Standard Deviations of CCB Items'

Grocery Auto Medical Bank CCB1 5.05 (1.52) 5.51 (1.04) 4.92 (1.61) 5.17 (1.40) CCB2 4.63 (1.75) 5.21 (1.34) 4.88 (1.71) 4.84 (1.59) CCB3 3.08 (1.79) 4.24 (1.68) 4.10 (1.95) 3.27 (1.98) CCB4 4.70 (1.74) 5.25 (1.35) 4.46 (1.73) 4.71 (1.81) CCB5 3.85 (1.76) 4.74 (1.49) 4.83 (1.53) 4.01 (1.79) CCB6 2.20 (1.36) 3.70 (1.76) 3.61 (1.94) 2.53 (1.58) CCB7 2.18 (1.56) 3.31 (1.88) 2.80 (1.84) 2.25 (1.54) CCB8 1.48 (.97) 1.91 (1.38) 2.17 (1.59) 1.73 (1.37) CCB9 1.97 (1.49) 3.00 (1.86) 2.82 (1.80) 2.28 (1.55) CCB10 1.51 (1.03) 2.11 (1.58) 2.05 (1.64) 1.59 (1.23) "Standard deviations are in parentheses.

TABLE 2 Confirmatory Analysis of Competing CCB Schemas

Bearden and Teel's (1983) Operationalization Day and Landon's (1977) Schema Day's (1980) schema

Auto Auto Auto Grocery Repair Medical Bank Grocery Repair Medical Bank Grocery Repair Medical Bank

X2 statistic 157.88 160.28 224.38 173.87 108.06 89.99 147.33 119.68 150.89 130.43 215.49 171.11 Degrees of

freedom 35 35 35 35 32 32 32 32 32 32 32 32 P-value .0000 .0000 .0000 .0000 .000 .000 .000 .000 .000 .000 .000 .000 GFI .780 .759 .699 .738 .826 .830 .777 .782 .793 .792 .720 .733 RMSE .123 .121 .132 .141 .107 .100 .120 .125 .121 .117 .126 1.41 Coefficient

of determination .610 .422 .235 .276 .935 .930 .906 .937 .836 .657 .104 .152

tualization is not appropriate to describe the structure underlying the CCB responses.

As a next step, the two-dimensional conceptualization proposed by Day and Landon (1977) was investigated. The 10 CCB items were classified into seven items measuring public actions and three items measuring private actions.5 A confirmatory factor analysis then was performed with the null hypothesis that a two-dimensional (specifically public and private actions), congeneric, common factor model describes the CCB responses. Table 2 shows the results from the LISREL V program. The two-factor hypothesis is clearly rejected in each of the four CCB situations. For instance, grocery data show a X2 (32) = 108 (p = .000) and the medical care data a X2 (32) = 147

(p = .000). Other statistics in Table 2 seem to support the same conclusion. A comparison with the

preceding analysis, however, suggests that the less restrictive two-factor model is a better (though not

appropriate) representation of CCB responses than a one-factor model (X2 difference ranges from 77 for

5Five judges were used to assist in classifying the 10 items. All of them are faculty members in the School of Management, but only two are in the Marketing Department. Each was given the Day and Landon schema, the 10 items, and an instruction sheet. There was complete agreement among the five judges on categorizing nine of 10 items. Four of five judges categorized all of the 10 items identically.

medical to 49 for grocery, d.f. = 3, p < .01). This finding supports the multidimensional conceptualization of the CCB construct and appears to reject the unidimensional operationalization of Bearden and Teel (1983).

The three-dimensional structure of Day (1980) was investigated next. On the basis of the definitions of the individual CCB facets, the 10 items were categorized into four items for "redress" responses, three items for "complaining" responses, and another three items for the "boycott" responses.6 The null hypothesis was that the proposed three-dimensional, congeneric, common factor model can adequately explain the observed CCB responses in the four data sets. LISREL V was used to test this hypothesis and the results are summarized in Table 2. The chi square statistic is significant with values ranging from X2 (32) = 130.43 (p = .000) for automobile repair data to X2 (32) = 215.49 (p = .000) for medical care CCB responses. This finding suggests that the proposed null

6The same five judges were asked to classify the 10 items into the three groups proposed by Day (1980). A procedure similar to the previous one was followed. Four of five judges agreed completely in categorizing items into the redress-seeking group. Three judges had consistent classification for the boycott actions group and the other two judges agreed on two of three items. Four of five judges agreed completely in categorizing items into the complaining group.

98 / Journal of Marketing, January 1988



hypothesis of Day's three-dimensional representation for CCB responses is strongly rejected. In fact, a chi square difference test for the results in Table 2 suggests that Day and Landon's (1977) two-dimensional structure is a better representation of CCB responses than the three-dimensional classification proposed by Day (1980) (X2 difference ranges from 68 for medical to 40 for auto repair, d.f. = 0, p < .01). As discussed before, the two-dimensional conceptualization, by itself, is not particularly satisfactory.

The preceding analysis shows that the current classification schemata and operationalization for the CCB responses are not a satisfactory representation of the structure underlying the CCB responses. That the results obtained are similar across four independent and distinct complaint situations seems to add confidence to such a conclusion.

What, then, is an appropriate representation of CCB

responses? In the absence of any other suitable guide- line, the best strategy seems to be to investigate the nature and structure of CCB responses in any one CCB situation data (say, randomly selected). This approach clearly is exploratory data analysis. However, once a reasonable structure of CCB responses is uncovered, confirmatory investigation can show whether that particular structure of CCB is also a satisfactory explanation of responses obtained in the other three CCB situations. To the extent that the four CCB data sets are independent and distinct, such a procedure affords a reasonable test of the validity of the proposed structure of CCB responses.

Exploratory Analysis of Auto Repair CCB Data

The automobile repair data were selected (randomly) for exploratory data analysis. As a first step, the correlation matrix for the 10 intention items was examined (see Table 3). With the exception of a single negative correlation (between items 8 and 1), all values in Table 3 are positive. However, wide variation is

present in the observed correlations, which range from .05 to .70. The Kaiser-Mayer-Olin measure of sam-

Correlations for the

pling adequacy (.76) and the Bartlett's test of spheric- ity (X2 = 401.64, p = .0000) indicate the presence of some shared variance among the 10 CCB items (Kai- ser 1974).

In Table 4 are the results of factor analysis on the reduced correlation matrix (i.e., squared multiple correlations on the diagonals in place of ones). Three eigenvalues are greater than 1.0 and together explain 67% of the total variance (values 3.76, 1.61, and 1.33). A scree plot of the eigenvalues (see Figure 2) seems to support the three-factor solution. A chi square test for the goodness of fit of a three-factor hypothesis shows X2 = 26.899 (p = .08), indicating that the null hypothesis cannot be rejected at p = .01. A two-factor hypothesis, however, is rejected at the same level of significance (X2 = 83.69). The varimax-rotated factor pattern reflects a reasonably clear loading structure with all cross-loadings less than .3. The first factor, representing items CCB7 through CCB10, seems to sig- nify actions directed at some formal third parties (e.g., newspaper, Better Business Bureau, legal systems, etc.) for a variety of purposes, such as seeking redress, warning other people, or simply "getting it off one's chest." These actions appear to be a subset of Day and Landon's (1977) public actions category and do not include CCB directed at the seller. This factor therefore can be referred to as the third party CCB.

Items CCB3, CCB5, and CCB6 clearly load on factor 2 (see Table 4). Two of these items constitute communication with friends and relatives about "the bad experience" and to convince them "not to go to that auto repair shop." The third item represents exit action, that is, a self decision to change patronage of the auto repair shop. This factor seems to combine the notions of word-of-mouth communications (Richins 1983) and exit from an exchange relationship (Andreasen 1985; Forell and Didow 1980). In addition, this factor appears to be consistent with Day and Landon's (1977) private CCB actions category and is referred to as such hereafter.

The third factor in Table 4 shows significant load-

TABLE 3 CCB Intentions Items' (automobile repair data)

CCB1 CCB2 CCB3 CCB4 CCB5 CCB6 CCB7 CCB8 CCB9 CCB10

CCB1 CCB2 368 CCB3 128 286 CCB4 378 540 242 CCB5 113 080 544 075 CCB6 190 137 571 235 609 CCB7 096 321 387 329 346 444 CCB8 -108 062 242 049 111 297 382 CCB9 123 295 322 331 291 353 702 481 CCB10 034 230 354 199 170 327 395 419 564

"All values are multiplied by 1000.




TABLE 4 Varimax-Rotated Factor Structure for

Auto Repair Data

Factor 1 Factor 2 Factor 3 CCB1 -.04 .13 .519 CCB2 .17 .05 .708 CCB3 .22 .654 .22 CCB4 .18 .082 .721 CCB5 .17 .743 .02 CCB6 .25 .762 .13 CCB7 .673 .29 .24 CCB8 .559 .14 -.08 CCB9 .878 .14 .22 CCB10 .574 .18 .12 Eigenvalue 1.77 1.74 1.48

ings for items CCB1, CCB2, and CCB4. Whereas CCB2 and CCB4 pertain to seller-related responses, CCB1 pertains to doing nothing about the felt dissatisfaction. Though it is difficult to base a conclusion on a single item (CCB1), Hirschman's (1970) observations suggest why "no action" may sometimes reflect predominant feelings toward the seller. He suggests that people may take no action even when dissatisfied if they are loyal to the seller or if they perceive that complaining to the seller is probably fruitless. Both possibilities reflect feelings toward the

seller. However, these suggestions should be viewed with caution because of the single-item measure of the no-action category. As the first item is reverse scored, all of these items appear to represent CCB directed specifically toward the seller (i.e., repair shop). Some researchers have discussed the notion of "voicing" complaints to the involved party (e.g., manufacturer/ retailer) and this particular factor seems to be consistent with such a notion (Singh and Howell 1985). This factor therefore can be referred to as voice CCB actions.

Bagozzi (1983) identified some specific conditions that, if the hypothesized dimensions are distinct, must be satisfied: (1) all correlations among the items in each dimension must be high, statistically significant, and of approximately the same magnitude and (2) all correlations among items across dimensions must be significantly lower in value than the within-dimension correlations and uniform in their pattern. Apply- ing these criteria to the correlations in Table 3 shows that they are largely supported. For instance, the average within-dimension correlation is .495. In contrast, the average across-dimension correlation is only .21 and is statistically different from the within-dimension value at the .01 level of significance. In addition, the alpha reliability for the voice, private, and

FIGURE 2 Scree Plot for Correlation Matrix from Auto Repair CCB Data

0

0

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0 O c

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0 1 2 3 4 5 6 7 8 9

NUMBER

100/Journal of Marketing, January 1988

4

3.5 -

3 -

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Z z w LiJ 0 LJ

2.5 -

2-

1.5 -

1 -

0.5 -

, u

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third party CCB dimensions is .70, .80, and .80, respectively, further supporting the presence of three distinct factors.

The preceding exploratory analysis of auto repair CCB data appears to suggest that Day and Landon's (1977) classification could be an adequate representation of the structure underlying the CCB responses, if the public actions category is considered as two distinct dimensions (voice actions and third party CCB). The resulting (and proposed) classification schema for CCB is three dimensional (but inconsistent with Day's 1980). This proposed schema is shown in Figure 3.

Confirmatory Analysis of the Proposed Taxonomy

Initially a confirmatory factor analysis with the null hypothesis of a three-dimensional, congeneric structure (based on Figure 3) of CCB responses for auto repair was performed. The fitted structure is shown in Figure 4 and the estimated maximum likelihood parameter estimates are reported in Table 5. As expected, the hypothesized classification schema appears to be a reasonably good fit of observed responses with x2 (32) = 49.60 (p = .024). The goodness-of- fit index (.892) and the root mean square residual (S - S) (.065) further support such a conclusion. In comparison with Day and Landon's (1977), the schema shows a significant improvement (X2 difference = 40, d.f. = 0, p < .01).

To examine the validity of the proposed classification schema (Figure 3), a confirmatory factor analysis was performed on the other three sets of CCB data (grocery, medical care, and bank). The null hypothesis was identical to that for the auto repair data (Figure 4). The LISREL V results are summarized in Table 5. The chi square values range from 51.07 to 69.23 with 32 d.f. (p = .018 to p = .001). Statisti-

FIGURE 3 Proposed Taxonomy of CCB Responses

FIGURE 4 Three-Dimensional Congeneric Model for

CCB Responses

I CCB _ 1 | x

cally, the null hypothesis cannot be rejected only for the bank CCB (at p = .01), but the chi square values, in comparison with those of competing schemata (Ta- ble 2), suggest a reasonably good fit irrespective of the CCB situation. For instance, in comparison with Day and Landon's (1977) schema, chi square difference ranges from 83 (medical) to 38 (grocery), d.f. = 0, p < .01, indicating that the proposed taxonomy affords a significant improvement. Further, the prob- lems with the overall chi square test, in this context, are well documented (Bagozzi 1983; Bentler and Bonnet 1980; Forell and Larcker 1981).7

Table 5 affords several insights into the proposed classification schema. First, the T-values for factor

7An examination of residuals indicated the presence of two substantially large values, perhaps representing correlated measurement error. This evidence was found in each of the CCB situations, though the items involved appeared to be random (e.g., CCB5 and CCB4 in grocery, CCB9 and CCB 1 in medical). Bagozzi (1983) identified some possible causes for such correlated error terms (e.g., that a single questionnaire is used). Allowing these measurement errors to be correlated resulted in chi square values with d.f. = 30 of grocery 42.08

(p = .07), medical 43.52 (p = .053), and bank 30.56 (p = .437). No significant difference (compared with standard error) was found in the structural parameters, X,, as well as 4), by allowing correlated measurement error, however. The revised parameters are available from the author.




Estimated Maximum

Auto Repair .49C .72 .73C .76 .73 .81 .78c .53 .90 .61 .32 .44 .54 .69 .80 .80 .44 .58 .52 .892 .815 .065

49.60 32

(4.20)

(4.17) (6.76) (7.05)

(5.50) (8.78) (6.44) (2.26) (2.87) (3.87)

.93C

.39

.50c

.62

.56

.91

.79C

.63

.93

.55

.14

.21

.71

.80

.53

.83

.47

.28

.545

.869

.775

.079 69.23 32

aT-values are in parentheses. bStandardized parameter value. CCorresponding X set to 1.0 to fix the scale of measurement.

loadings are significant and high in each CCB situation. This finding suggests that the items effectively tap the corresponding latent construct. Second, the scale reliability values (pij, p2, and p3) range from .70 to .85, indicating reasonably good measurement of the latent constructs. There is one exception, however. The reliability for the private CCB scale is only .53 for grocery data and .68 for bank data (in comparison with .80 for auto repair and medical data). Thus the lack of fit in chi square, especially for grocery data, may be attributed in part to the poor reliability of the private dimension. Probable causes could include idiosyncracies of the question wording and/or pecul- iarities of the CCB phenomenon in the grocery situation.8

The Fornell and Larcker (1981) criterion for discriminant validity, Pvc(Si) > 4)2 shows that in all four CCB situations the variance extracted by individual dimensions is substantially greater than the variance shared with other dimensions. For instance, for medical CCB, the variance extracted by the voice dimension (p,c(il)) is .57. In contrast, this dimension shares

only .046 and .068 of its variance with the private and

8One reviewer points out that one such possibility is high/low involvement of the CCB situation itself. In particular, if grocery CCB can be categorized as low involving, one could attribute poor reliability to the low involvement of the CCB situation. This explanation is plausible and can be subjected to empirical investigation.

(3.03)

(3.55) (4.49) (5.02)

(7.22) (10.46) (6.10) (1.25) (1.97) (3.83)

.69c

.78

.73C

.79

.71

.86

.83c

.74

.83

.68

.42

.45

.54

.80

.80

.85

.57

.57

.60

.867

.772

.061 63.69 32

(6.93)

(6.95) (7.15) (7.75)

(8.68) (9.97) (7.94) (3.27) (3.60) (4.16)

Bank .70C .90 (6.54) .43C .69 (6.31) .53 (3.56) .93 (3.10) .83c .69 (7.17) .82 (8.69) .71 (7.42) .09 (.78) .37 (2.82) .39 (2.30) .81 .68 .85 .59 .44 .59 .883 .799 .066

51.07 32

third party CCB dimensions, respectively. Compari- sons of variance extracted and variance shared across the three dimensions yield values of the same order irrespective of the CCB situation (see Table 5). This finding clearly supports the view that the proposed CCB dimensions are distinct and have discriminant validity. Further, the magnitude of pvc(ki) for all three constructs is of the order of .5 or more, indicating that about 50% or more of the variance extracted is valid. The only singular exception is the private CCB dimension in grocery data, which has poor reliability as well. Thus the data on CCB intentions for grocery shopping, medical care, and banks and financial services appear to support the proposed three-dimensional taxonomy for the CCB construct (Figure 3).

Validity Check Using Behavior Data

Complaint behaviors that consumers recalled having engaged in were categorized first into the three dimensions of CCB (Figure 3): voice, private, and third party. For each dimension, responses were coded as 0 (no) or 1 (yes). Within each behavior dimension, means and standard deviations were calculated for CCB intentions by summing over the items in each dimension. Table 6 summarizes the results. Further, so that the sources of variation in each dimension of CCB intentions could be identified, a MANOVA analysis

Parameterb

TABLE 5 Likelihood Parameters of the Model in Figure 4'

Grocery Medical

x2l

A32

X41

A52

X62

.73

A83

X93

K10.3

)21

(31

432

Pk1 PA2 PA3 Pvcl1 Pvck2 Pvck3 GFI Adj. GFI RMSE X2 d.f.

102 / Journal of Marketing, January 1988

I



Means and Standard Deviations for TABLE 6

r Examining Intentions-Behavior Consistency8 Behaviors

Voice Private Third Party Intentions No Yes No Yes No Yes Voice

Grocery 3.82b 5.11b 4.66 5.13 4.76 5.83 (1.55) (0.92) (1.34) (1.06) (1.29) (0.33)

Auto repair 4.44b 5.48b 5.09 5.51 5.31 5.42 (1.57) (1.01) (1.05 (.90) (1.01) (.79)

Medical 4.24b 5.33b 4.45 4.99 4.76 4.52 (1.59) (0.91) (1.51) (1.32) (1.40) (1.86)

Banks 3.55b 5.34b 4.97 4.80 4.89 5.33 (1.54) (.97) (1.36) (1.38) (1.37) (1.15)

Private Grocery 3.21 2.99 2.69b 3.93b 3.01 4.08

(1.23) (1.31) (1.21) 1.05) (1.26) (1.87) Auto repair 3.94 4.28 3.51b 4.77b 4.16 4.91

(1.67) (1.34) (1.36) (1.16) (1.43) (.82) Medical 4.20 4.15 3.22b 4.91b 4.11b 5.33b

(1.61) (1.46) (1.40) (1.19) (1.53) (1.07) Banks 2.99 3.35 2.91b 3.87b 3.22b 5.00b

(1.34) (1.34) (1.31) (1.17) (1.32) (.57) Third Party

Grocery 1.74 1.80 1.56 2.34b 1.73b 3.50b (1.10) (1.01) (.87) (1.20) (.99) (.58)

Auto repair 2.28 2.64 2.22 2.86 2.51 3.27 (1.43) (1.31) (1.13) (1.41) (1.33) (1.17)

Medical 2.42 2.50 2.04 2.78 2.36b 4.14b (1.49) (1.39) (1.11) (1.57) (1.39) (1.14)

Banks 1.59 2.08 1.98 1.93 1.92b 3.33b (.74) (1.27) (1.18) (1.20) (1.16) (1.42)

"Standard errors are in parentheses. blndicates that mean differences across the columns of no/yes level of significance.

was performed with the three CCB behavior categories as the treatment variables. The results are summarized in Table 7.

TABLE 7 Sources of Variation in CCB Intentions

(F values)

Behaviors Difference Dependent Third Due to

Variable Voice Private Party Industry Voice 124.0a 9.4a .77 3.5b

inten- (.000) (.002) (.378) (.016) tions

Private .29 174.4a 10.44a 13.46a inten- (.591) (.000) (.001) (.000) tions

Third party 2.74 18.79a 34.01a 10.18a inten- (.09) (.000) (.000) (.000) tions

"p < .01. bp < .05.

behavior are statistically significant for a one-tailed test at the .05

Taken together, Tables 6 and 7 afford interesting insights into CCB intentions-behavior consistency, as well as the validity of the proposed taxonomy. Though a complete correspondence is not expected (because of situational variables), the data suggest a close relationship. For instance, mean values for private intentions are significantly higher when respondents said they actually engaged in private actions (Table 6). This consistency is also observed in voice and third party CCB. More importantly, the intention-behavior consistency is present at the level of an individual CCB dimension but is not present across dimensions (e.g., private intentions and voice behaviors). Thus, for voice intentions, only voice behaviors represent the major source of variation (Table 7), whereas variability due to private, third party, and across-industry behaviors is relatively small (1:10). Private and third party intentions also have this characteristic (Table 7). These

findings not only appear to support the expectations of CCB intentions-behaviors (i.e., modest consis-

tency), but also lend credence to the contention of three distinct dimensions for CCB.




Limitations The findings should be evaluated in the light of cer- tain limitations. The results obtained are based on CCB responses in four specific situations from respondents in Southwest Texas. To the extent these respondents are substantively different from persons in other areas, the generalizability of findings would be affected. Further, though grocery, automobile repair, medical care, and bank experiences seem to reflect the variation in CCB responses (Best and Andreasen 1977; Day and Bodur 1977), more evidence must be accu- mulated before a claim for invariant CCB structure can be made. In addition, the reliability of the CCB dimensions, particularly private, tends to vary across the CCB situations. Researchers may want to address these issues.

In addition, responses of the order of 15 to 18%, though not unusual in dissatisfaction research (Robin- son 1979), may affect the validity of the results. Fi- nally, the preceding assessment of the CCB construct is based on an empirical analysis of 10 items. Though the items included reflect the nature of complaints examined in almost every study in CCB (Best and An- dreasen 1977; Day and Bodur 1977; Jacoby and Jac- card 1981; Richins 1983), other items can be developed that represent other means of complaining. Though the latter task is in the realm of psychometric development, such a line of research may suggest a different taxonomy for CCB.

Discussion The objective of this study was to assess the nature and structure of the CCB phenomenon. The findings indicate that the currently available taxonomies and operational definitions cannot be accepted as satisfactory representations of observed CCB responses. An exploratory psychometric investigation of automobile repair CCB data (randomly selected from four CCB situations) uncovered a structure and taxonomy that appear to be reasonably valid in three independent CCB situations. The uncovered structure, depicted in Fig- ure 3, shows that CCB is a three-faceted phenomenon consisting of voice, third party, and private actions. The evidence seems sufficient to indicate that the three dimensions of CCB are distinct, have discriminant validity, and warrant additional research attention. Hence, researchers examining the antecedents and/or consequences of CCB may benefit by investigating at the level of the individual dimension of CCB. In other words, research treating CCB not as a homogeneous, unidimensional phenomenon, but as consisting of three distinct dimensions, has the potential of affording a better explanation and prediction of CCB itself.

A case in point is the study by Richins (1983) on

the antecedents and consequences of word-of-mouth CCB (WOM). In the context of the study reported here, the dependent variable of Richins can be categorized as private CCB. Her findings provide some interesting insights about this particular dimension of CCB. For instance, data on dissatisfaction with appliances and clothing indicated that consumers who had less positive perceptions of retailer responsiveness should a complaint be registered had a greater likelihood that their action would involve WOM, that is, private CCB but not voice CCB. This finding is supportive of the contention that in addition to being distinct, the various dimensions of CCB may have differential antecedents.

In view of the implications of the proposed taxonomy, it seems appropriate to delineate carefully the basis of the schema in Figure 3 so that researchers have some guidelines for categorizing the breadth of the CCB phenomenon as well as for improving upon the suggested taxonomy (Hunt 1983). Because the private dimension is found to be ill-defined for grocery data, formalization is considered tentative to that extent.

Formalization of the Proposed Taxonomy

Figure 3 depicts the proposed classification schema for the CCB phenomenon. The criterion for classification is based on identifying the object toward which the CCB responses are directed. Three different "types" of objects are proposed. Voice CCB is directed to objects that are external to the consumer's social circle (i.e., informal relationships) and are directly involved in the dissatisfying exchange (e.g., retailer, manufacturer). The no-action responses are included in this category tentatively because they appear to reflect feelings toward the seller. In contrast, third party CCB includes objects that are external to the consumer, as in the voice CCB, but they are not directly involved in the dissatisfying transaction (e.g., Better Business Bureau, legal agencies, newspapers, etc.). Finally, for the private CCB category, the objects are not external to the consumer's social net and are also not directly involved in the dissatisfying experience (e.g., self, friends, relatives, etc.). Thus, the external/not external and involved/not involved criteria are used to cat- egorize CCB actions into the three categories of the proposed taxonomy. The not external but involved category is identified as an "empty cell" (cf. Hunt 1983) into which no specific CCB phenomenon is currently classified.

The preceding formalization of the proposed classification schema contributes to the CCB literature in several ways. It elaborates and extends the Day and




Landon (1977) two-dimensional conceptualization to a three-dimensional schema that is shown to be a better representation of consumer responses. It adds to the current research in definitional and taxonomical issues of CCB by delineating the criterion(a) for classification at each level of the proposed taxonomy. Previously proposed classification schemata lack explicit specification of the properties or characteristics for achieving the categorization of the CCB responses. However, unambiguous categorization is desirable in future research. In addition, the formalization enables researchers to criticize constructively and build upon the proposed taxonomy. As Hunt (1983) stated, an explication of the bases of classification is a desirable characteristic in evaluating a taxonomy. Thus, researchers investigating the nature and struc-

ture of the CCB construct may find the formalization a useful starting point.

In addition, the findings suggest that researchers may find it advantageous to operationalize the CCB construct at the level of its individual dimensions. Though an operationalization at that level is provided here, the formalization affords researchers ample ave- nues for improving upon the proposed operationalization. Further, some evidence seems to suggest that researchers investigating the antecedents (or consequences) of CCB may achieve higher levels of explanation and prediction if the dependent construct (CCB) is conceptualized and operationalized as a multidimensional phenomenon (e.g., Richins 1983). The proposed taxonomy and its formalization should be helpful in such research.

APPENDIX A Items Used by Bearden and Teel (1983)

to Measure CCB

1. Warned family and friends 2. Returned vehicle for rework and/or complained to management 3. Contacted manufacturer 4. Contacted Better Business Bureau, state office of consumer affairs, or private consumer agency 5. Took some legal action

APPENDIX B Items Used to Measure CCB Intentions

How likely is it that you would: CCB1 Forget about the incident and do nothing? CCB2 Definitely complain to the store manager on your next trip? CCB3 Decide not to use that repair shop again? CCB4 Go back or call the repair shop immediately and ask them to take care of your problem? CCB5 Speak to your friends and relatives about your bad experience? CCB6 Convince your friends and relatives not to use that repair shop? CCB7 Complain to a consumer agency and ask them to make the repair shop take care of your problem? CCB8 Write a letter to the local newspaper about your bad experience? CCB9 Report to the consumer agency so that they can warn other consumers? CCB10 Take some legal action against the repair shop/manufacturer?

~~~~~~~~~~~~~,




Demographic Characteristics APPENDIX C

of the Four Samples (all values in percentages)

Industry Automobile Banks and

Demographic Characteristics Grocery Repair Medical Care Financial Services Sex

Male 27 67 30 47 Female 73 33 70 53

Age (years) <25 22 8 10 9 >25, -35 30 18 22 30 >35, -50 23 39 29 27 >50 25 35 39 34

Marital Status Single 21 10 10 12 Married 66 77 70 69 Divorced/widow/sep. 13 13 20 19

Occupation Professional 14 28 25 32 White collar/teacher 27 27 21 25 Blue collar 32 26 15 15 Unemployed/retired 27 19 39 28

Education High school 27 13 23 22 Trade school 6 4 7 9 College 47 53 48 44 Graduate school 20 30 22 25

Race White 91 93 88 92 Black 2 3 3 3 Hispanic/other 7 4 9 5

Income ($) <20,000 34 17 29 31 >20,000, <30,000 19 13 23 22 >30,000, -50,000 32 39 29 31 >50,000 15 31 19 16

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Consumer Complaint Intentions and Behavior: Definitional and Taxonomical Issues

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