Industry CharIndustry characteristics and consumer dissatisfactionacteristics and Consumer...

8/10/2019 Industry CharIndustry characteristics and consumer dissatisfactionacteristics and Consumer Dissatisfaction

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2 0 THE JOURNAL OF CONSUMER AFFAIRS

ing the relationship between industry characteristics and consumers'

responses to dissatisfaction. Specifically, the paper utilizes a con-

ceptual framework, based largely on Hirschman's (1970) model, to

propose several hypotheses for the impact of industry characteristics

on consum ers' responses to perceived dissatisfaction (e.g., complaint

behaviors), sellers' responsiveness to complaints, and consumers'

satisfaction with sellers' response (e.g., redress). Hirschm an's model

has received extensive attention in the political science literature (see

Laver 1976 for review), and its applications in psychology (e.g.,

Rusbult, Johnson, and Morrow 1986), organizational behavior (e.g..

Spencer 1986), and consumer behavior (e.g., Andreasen 1985; Singh

1990) have begun to appear. A s such, H irschm an's model is likely to

offer a solid foundation for developing the conceptual framework

and positing testable hypotheses. Following this, the paper empir-

ically examines the proposed hypotheses utilizing a purposive selec-

tion of three service industries. Because services usually entail higher

consumer dissatisfaction than manufactured products (Best and

Andreasen 1977;Marketing News 1980), it is desirable to focus on

service industries. In addition, the hypotheses are tested under

several different contingencies so as to ascertain the stability and

validity of the underlying processes. Moreover, this allows delinea-

tion of dissatisfaction responses into one of three categories: (a)

macro-drivenresponses, i.e ., where industry characteristics play a

dominant role on consumers' responses, (b)micro-drivenresponses,

i.e., where individual factors play a dominant role, and (c)

mixed

responses, i.e., where both industry and individual factors interplay

in affecting dissatisfaction responses. Finally, several implications

for researchers, managers, and public policy officials are elaborated.

The paper begins with a discussion of the conceptual framework.

CONCEPTUAL FRAMEWORK


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SUMMER 1991 VOLUM E 25, NUM BER 1 2 1

corrected within the marketing system. For such reparable lapses,

Hirschman posited that no external (e.g., government) regulation is

necessary in the interest of societal and consumer welfare. Alterna-

tively, some industries may be characterized by a general status of

irreparable lapses, thatis,when atrophy in firms and their outputs

goes uncorrected within the system; resulting in continued decline in

the performance of firms, product quality, consumer satisfaction,

and , consequently, societal welfare. Some form of regulation is man-

datory in this case to stem the deterioration of consumer and social

welfare.

Interestingly, the key mechanisms identified by Hirschman as

underlying reparable or irreparable lapses are closely related to con-

sumer dissatisfaction. In particu lar, processes related to , ho w con-

sumers respond to perceived dissatisfaction? and how sellers in

different industries react to dissatisfied consum ers' resp onses? are

thought to be central to an understanding of the general, long-term

status (i.e., reparable or irreparable) of lapses within a given industry

(Andreasen 1988). Because of Iheir centrality, each of

these

processes

is discussed in greater detail.

Consumers' Responses to Dissatisfaction

A dissatisfied consumer, according to Hirschman, has three poten-

tial options: (a) exit, (b) voice, and (c) loyalty. By exit a consumer

voluntarily terminates an exchange relationship such as by switching

patronage to another product, service, and/or retailer. Exit is per-

ceived as pain fu l since it involves certain am ount of effort, such as

switching costs and searching for alternatives. In contrast, voice is

conceptualized as an attempt to change rather than escape from an

objectionable state of affairs. Most voice attempts are directed at

sellers and entail effort and motivation on the part of consumers.

Interestingly, Hirschman views the loyalty option passively because

lo yal consumers neither exit nor

voice.

They continue to stick with


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to unsatisfactory experiences, ranging from complaining to friends

and relatives (negative word-of-mouth, W-O-M) to seeking redress

from third parties (e.g., consumer protection agencies, courts, etc.).

Recently, Singh (1988) found that a parsimonious structure underlies

the various dissatisfaction responses. His results show that a three-

dimensional structure appears to be congenial with data and evi-

dences discriminant and external validity. Specifically, this structure

consists of: (a) voice dimension, encompassing responses directed

towards parties directly involved in the dissatisfying experience (e.g.,

salesperson, retailer, seller),

(h)private

dimension, including negative

W-O-M communication (e.g., to friends and relatives) and exit from

exchange relationship, and (c)third-partydimension, involving com-

plaints to formal agencies not directly involved in the exchange rela-

tionship (e.g., consumer agencies).

Furthermore, CCB literature suggests that consumers often utilize

a wide variety of responses that can be successfully categorized into

the preceding three dimensions (Singh 1988). For this reason, it

appears desirable to explicitly recognize and consider voice, private,

and third-party responses. Although Hirschman's model does not

include such a diversity of responses, the key hypotheses in his frame-

work easily submit themselves to such extension (cf., Singh 1990).

Note that these dimensions are not posited as mutually exclusive

responses. Instead, the framework accepts that consumers may often

engage in multiple responses; such as voice and private responses.

Sellers' Reactions to Consumers' Responses

Hirschman posits that sellers' reactions to consumers' responses

will vary significantly depending upon the nature of the industry

involved in the dissatisfying experience. In order to highlight these

effects, he identified three typical industry structures: (a) competi-

tive,(b) monopolistic, and (c) loose monopoly. A

com petitive

struc-


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SUMMER 1991 VOLUME 25, NUMBER 1

2 3

Not surprisingly, competitive firms are alert and responsive to con-

sumer complaints should dissatisfaction be voiced. Hirschman likens

this mechanism to the Invisible Hand, th e sort of mechanism eco-

nomics thrives o n (15).

On the other hand, am onopolisticstructureisdescribed by a single

firm, no alternatives for consumers, and very high switching costs

because the only other option is to go without the focal product/

service. In this situation , dissatisfied consum ers have no choice but to

voice. In tu rn, voice provides the key mechanism for comm unicating

dissatisfactions to management, and collective voice sets in motion a

process that could repair lapse s in such firms.

Andreasen (1985, 137) observes that most contemporary industries

are neither fully competitive nor completely monopolistic markets.

Instead, they are characterized by loose monopoly conditions. For

this reason, Hirschman especially focused on such industry structures

(as will this study). Although Hirschman did not explicitly identify

the key attributes of loose monopoly markets, based on his original

work and subsequent expositions by Andreasen (1984; 1985) six key

characteristics can be deduced. These are shown in Table 1.

Ideally, theloosemonopolycondition occurs when consumers per-

ceive that: (a) few alternatives to the offending product/service are

available (AALT), (b) their knowledge about different offerings is

limited (RINFO), (c) they are unable to detect poor product/service

(CKNO), (d) the time gap between buying a product/service and

finding out that it was of poor quality is long (LRCY), (e) complaint

actions (voice/private) leave little impact on the sellers/providers

(LIMP), and (f) several psychological inhibitions dissuade them from

complaining about poor product/service (PCOS). Andreasen's

research shows that the physician care indust ry meets most of

these criteria.

When consumer dissatisfaction occurs in such loose monopoly

markets, Hirschman posits that consumers would tend to neither


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TABLE 1

KeyDimensionsof Loose Monopoly Construct and itsOperational Measures

(Listed Itemsare for Auto-RepairCategory)

Dimension Definition/Operational Items

Availability of Alternatives (AALT)

Definition.

Consumers' beliefs about availability of alternative providers/sellers wh

would provide better product/service and/or care more about customer satisfaction

Hirschman notes that in a loose monopoly although alternatives are available they are no

perceived as providing better product/service (1970, 24-25, 44-45).

Operational

Items.

(1) One could change the auto-repair shop one goes to , but there is n

guarantee that the other shop would care more about customer satisfaction. (2) One can

always find another auto-repair shop which provides comparable or better parts and/o

service (reversed).

Restricted Information (RINFO)

Definition.

Consumers' perceptions about the customs (or norms) prevalent in an industr

that restrict the amount of information available to customers. Examples of such custom

are discouragement of advertising and comparison shopping practices. Such restrictive

customs are usually common in loose monopolies (Hirschman 1970, footnote 27; Andrea

sen 1985).

Operationai

Items.

(1) Most auto-repair shops advertise about the parts and services the

provide (reversed). (2) It is appropriate to visit an auto-repair shop just to check prices

(reversed). (3) Auto-repair shops provide customers with enough information about the

parts/services needed (reversed).

Consumer Knowledge (CKNO)

Definition.

Consumers' beliefs about their ability to judge the quality (e.g., if it is poor) o

the various products/services offered by different industries. Hirschman observes that for

loose monopolies, buyers are usually unable to detect poor product/service (1970, 24-25)

Operationai

Items.

(1) One can obtain published evaluations for the service quality pr

vided by different auto-repair shops (reversed). (2) Most consumers are able to detect if the

parts and/or service they obtained from an auto-repair shop were of poor quality

(reversed).

Long Repurchase Cycle (LRCY)

Definition.

Consumers' perceptions about the time it takes between buying a product

service and finding out that it was of poor quality in different industries. Andreasen (1984

notes that loose monopolies are generally characterized by longer LRCY, thus making pro

viders less responsive to customer problems.

Operationai Items.

(1) It often takes a long time (e.g., several months) to find out that wh

you got fixed from an auto-repair shop was of poor quality. (2) It is easy to tell when a par


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SUMMER1991 VOLUME25,NUMBER1 2 5

TABLE 1 {continued)

Dimension Definition/Operational Items

Operational

Items.

(1) Most auto-repair shops are eager to satisfy you if you tell them that

you are dissatisfied (reversed). (2) Many auto-repair shops would not care even if you told

them that you would never come to them gain.

Psychological Costs (PCOS)

Definition.Consumers' perceptions about the psychological costs or inhibitions involved in

taking some action in response to poor quality product/service in different industries.

Loose monopolies are usually characterized by psychological inhibitions on the part of con-

sumers to take voice and/or exit actions (Hirschman 1970, 26).

Operational

Items.

(1) It is appropriate to complain to auto-repair store manager about

poor par ts or service (reversed). (2) It is important to build a relationship with auto-repair

personnel (e.g., manager) to obtain good service. (3) No explanation is necessary if one

decides to stop patronage of an auto-repair shop.

edge to complain effectively (Andreasen 1984). As such, in loose

monopoly markets, channels for communicating quality declines are

relatively blo ck ed . A mechanism tha t can correct for lapses in

such markets is largely absent, resulting in higher levels of consumer

dissatisfaction and lower societal welfare.

Furthermore, Hirschman (1970) observes that because there are

some competitors, a loose monopoly further blunts the impact of

market forces in regulating the industry. This occurs because the more

knowledgeable and sophisticated consumers, who might normally

voice complaints and regulate the actions of sellers (e.g., as in a

monopolistic condition), tend to exit because they are aware of alter-

natives and are sufficiently aggressive to switch (Andreasen 1984). At

the same time, other consumers swallow their dissatisfacion believing

that they have few options and, consequently, appear to be lo ya l

to the seller. This flight of sophisticated consumers combined with

the loyal ty of the majority affords sellers in loose monopolies

many of the benefits of a t r u e monopoly without the aggravation

of voice that the latter must endure (Hirschman 1970; Andreasen


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those industries that were highly likely to exhibit different am ounts

of loose monopoly conditions. This variation is germane to fully

understanding the impact of industry structure on consumer dissatis-

faction. A combination of secondary (i.e., published studies) infor-

mation and a pilot study were utilized to facilitate this selection.

PILOT STUDY: SELECTING SERVICE INDUSTRIES

The aim was to select three service industries that were at the

high

(i.e., depicts most, if not all, features of loose monopoly markets),

low

(i.e., portrays few characteristics of loose monopoly markets)

and

midpoints

along the loose monopoly continuum. This selection

was arrived at by implementing the following steps. First, secondary

data and published studies were collected for several service indus-

tries. Second, these data were analyzed with a view to formulate a

preliminary choice for three industries that met the preceding cri-

terion. This analysis narrowed the choice to

medicalcare, automotiv

repair, andgrocery retailingservices. Third , a profile for the select

industries on each of the loose monopoly characteristics (Table 1)

was developed. This profile is summarized in Table 2.

Table 2 reveals that while medical care and grocery retailing denote

the high and low points, respectively, on the loose monopoly con-

tinuum, automotive repair falls somewhere in between. Andreasen's

research offers support for the location of medical care industry. For

automobile repair, note that consumer knowledge about (and ability

to judge) service problems is usually limited (Day and Landon 1976),

long repurchase cycles are common, and few be tter alternatives

are available. By contrast, few psychological barriers exist since

research shows that consumer complaints are highest for auto-repair

problems (Best and Andreasen 1977). For grocery industry, a review

suggests that it exhibits few, if any, features of loose monopoly

markets (Reese and Alexander 1985). Consumers have significant


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SUMMER 1991

VOLUME25,>fUMBER 1

27

TABLE 2

Evaluative Sum mary ofThree Service Categories

on Loose MonopolyCharacteristics

BasedonSecondaryData)

Industry

Characteristic Grocery Auto-Repair Medical Care

LT

RINFO

KNO

LR Y

LIMP

P OS

Many competing

firms with no

dominant player

{Progressive Grocer

1983)

Few, if any, restric-

tions in the flow of

information(Pro-

gressive Grocer 1981)

Easy to judge quality

Relatively small

because of its

perishable nature

No information

available

No inhibitions in

complaining

Many options are

available (Webbink

1978)

Effort is required to ob-

tain information (e.g.,

quotes) (Ritchie, Clax-

ton, and Claxton 1979)

Relatively difficult to

ascertain quality

because of technical

nature (Day and

Landon 1976)

Varies from long to

very long

Little impact because

complaints about

auto repair to third

parties are highest

(Bearden, Crocket,

and Graham 1979)

Few hindrances in

complaining (Bearden,

Crocket, and Graham

1979)

Supply of physicians is

restricted (Andreasen

1985)

Advertising and price

communication is not

customary (Cahal

1962)

Complex service; very

difficult to assess

quality (Benham and

Benham 1975)

Varies; generally

relatively long

(Andreasen 1984)

Many consumers per-

ceive doctors to be

unresponsive to

patient problems

(Andreasen.1985)

Complaining is

generally considered

inappropriate

(Andreasen 1984)

Operationalization

of the Loose M onopoly Construct and

ResearchDesign

Initially 18 items were developed (based on definitions in Table 1)


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nonrandom sample of faculty and staff (excluding marketing faculty).

Two reasons suggest why this sample may not produce overly biased

results: (1) as household members, the focal sample has had some

experience with the three service categories selected, and (2) giving

equal representation to staff and faculty reduces, to some extent, the

effect of certain systematic biases (e.g., highly educated sample).

Nevertheless, the limitation of a systematic sample is recognized. A

total of51 responses were received (90 percent response rate). None

had missing values. All responses were confidential. A five-point

Strongly Agree-Strongly Disagree Likert scale was utilized, with

higher numbers representing greater agreement with the prevalence

of a loose monopoly characteristic.

Findings andDiscussion

Several conclusions can be drawn from the results of pilot study

(Table 3). First, the null hypothesis that the mean values are equiva-

lent for the three service categories is rejected for the overall measure

(F = 54.33,p < .001) as well as for the various dimensions (F-values

range from 5.79 to 52.46) of the loose monopoly construct. The only

exception is the AALT dimension for which the F-statistic is border-

line.This suggests that the service categories differ significantly along

the loose monopoly continuum. Second, medical care depicts the

highest mean value for individual dimensions as well as overall sum-

mary measure, with the only exception lack-of-impact (LIMP)

dimension. This pattern supports the contention that, of the three

industries investigated, medical care service is most like a loose

monopoly.

Third, the lowest mean values occur consistently for grocery ser-

vice category. For the summary measure and five of the six dimen-

sions, consumer perceptions concerning grocery industry were low-

est. The only exception is CKNO, for which the mean value for

grocery category is higher in magnitude than that for automotive


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SUMMER1991 VOLUME

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NUMBER1 3 1

H i: The incidence of voice actions will vary significantly across the

three service industries investigated.

H2:

The incidence of voice actions will be the lowest in medical care

industry, and the highest in grocery retailing. For autoniotive

repair, the use of voice would lie somewhere in hetween the pre-

ceding extremes.

It can be deduced from Hirschman's theorythat privateresponses

(i.e.,

exit and negative W-O-M) would tend to be more frequently

utilized the less a given industry manifests loose monopoly condi-

tions.When dissatisfaction involves grocery products, exit is a likely

response. This is so because better alternatives (e.g., competing

grocery stores) are available and psychological inhibitions for exit are

absent. Negative W-O-M responses are generally uninhibited for

markets such as grocery retailing. By contrast, private responses are

likely to be less prevalent in medical care dissatisfaction because the

nature of the industry presents few payoffs from such actions. Thus,

the following hypotheses were proposed.

H3:

The incidence of private action s will vary significantly across the

three service industries investigated.

H4:

The incidence of private actions will he lowest in the medical

care industry. For grocery retailing industry, private actions

would he the most frequent response, and somewhere in be-

tween for automotive repair.

In the preceding hypotheses, private actions are considered as a

combination of exit and negative W-O-M CCB, Although consistent

with previous research (Singh 1988), important differences between

these CCB should be noted in terms of m arket signals.^ Exit provides

a direct market signal to the seller via loss of market share. In con-


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3 2 THE JOURNAL OF CONSUMER AFFAIR

W-O-M is likely to be powerful market signal. Because of these di

ferences, hypotheses H3 and H4 were examined separately for ex

and W-O-M actions.

Unfortunately, Hirschman did not consider third-party action

Key concepts in his model can be extended to subsume such action

Most likely consumers will utilize third-party channels for resolvin

their dissatisfaction when direct mechanisms (e.g., voice) are n

fruitful or are perceived to be unresponsive. It follows tha t con

sumers would tend to use more third-party actions the more a give

industry displays loose monopoly conditions. This is because voic

actions in such industries are either discouraged or lack much impac

Consequently, third-party actions provide an alternative, and i

some circumstances, the only avenue for redress. Previous studi

have not focused on the variation in third-party behaviors acros

industries with different market structures. Therefore, the followin

hypotheses were proposed.

H5:

The incidence of third-party actions will vary significan

across the three service categories.

Hfi:

The incidence of third-party action s will be highest in the med

cal care industry. For grocery retailing industry, third-par

actions would be the least frequent response, and somewhere

between for automotive repair.

Perceived Responsiveness

The extent of loose monopoly conditions in an industry is also lik

ly to impact on consumers' perceptions about the responsiveness o

providers to their just complaints. Specifically, in industries depic

ing high levels of loose monopoly conditions (e.g ., medical care), di

satisfied consumers might perceive that providers are not general

receptive to complaints, and the likelihood of obtaining redress


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1991 VOLUME 25, NUMBER 1 3 3

monopoly conditions (e.g., grocery retailing) are more likely to foster

a sense of responsiveness to customer complaints in order to survive.

Unfortunately, the preceding aspect of H irschman's theory has not

been directly tested. Instead, there is considerable indirect evidence.

In many service and product industries, managers have attempted to

thwart the threat of increasing competition with increasing respon-

siveness to customer com plaints. The autom obile industry is a case in

po int. After several years of languishing in a state of

loose

monopoly,

this industry was awakened by increasing foreign competition. In

response to this competition, the U .S. auto industry focused on con-

sumer satisfaction and responsiveness to customer problems as the

pivotal point for a co m eb ac k strategy (e.g., M urtha 1989). Sellers

(1988,

94) documents similar changes in other industries and con-

cludes, with consumers smarter, choosier, and more demanding

than ever before, courting the complainers has become an essential

part of bus iness. Based on the preceding discussion, the following

hypotheses were examined.

H?: The perceived responsiveness of providers to consum ers' com -

plaints will vary significantly across the three service industries

investigated.

Hs: The responsiveness of providers to consum ers' complaints were

perceived to be the lowest in medical care industry, and the

highest in grocery retailing. For automotive repair, providers'

responsiveness would lie somewhere in between the preceding

extremes.

Satisfaction with Response

Consistent with the preceding arguments, it follows from Hirsch-

m an 's model that the more an industry displays loose monopoly con-

ditions, the greater the likelihood that consumers will remain dissatis-


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satisfaction (than the case for loose monopolies) in customers wh

voice their dissatisfaction.

Research has not systematically evaluated the preceding hypothe

sis.

However, some early studies are suggestive of empirical suppo

for these arguments (Andreasen 1988). Best and Andreasen (1977

report that far fewer people (34.5 percent) perceived that their voice

problems were satisfactorily addressed for medical/dental problem

when compared to other services (44 percent). Consequently, th

following hypotheses were proposed.

H9: The consum ers' satisfaction w ith providers' response to vo i

will vary significantly across the three service industries inves

tigated.

Hio: The consum ers' satisfaction level w ith providers' respons

would be the lowest in m edical care industry, and the highest i

grocery retailing. For automotive repair, this satisfaction leve

would lie somewhere in between the preceding extremes.

Evaluating Hypotheses Hi to Ho

Under

Different Contingencies

The results obtained for the preceding hypotheses were furthe

evaluated by exploring the effects of several contingencies. In pa

ticular, effects due to sex, age, education, income, and level of per

ceived dissatisfaction were examined. These variables were selecte

because previous CCB research suggests that they have importan

influences on consumers' responses to dissatisfaction (e.g., Sing

and Howell 1985). For each variable (e.g., sex), the sample wa

divided into two groups (e.g., male and female), and the variou

hypotheses were then tested individually. Differences in results acros

the two groups for each hypothesis were noted. This offered a

opportunity for deeper understanding since the vjiriability in result

due to different contingencies can be empirically ascertained. I


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SUMMER

1991

VOLUME25,NUMBER

1

3 5

under different contingencies (e.g., for males and females separately

in the case of sex contingency) for each hypothesis. If results

under different contingencies are generally consistent with aggregate

results, then they imply that the underlying process is relatively insen-

sitive to variation in individual differences; instead, they may reflect

stable characteristics of the industries investigated. In this instance,

the underlying process is categorized as macro-driven. On the other

hand, if results are highy sensitive to individual differences (i.e.,

aggregate results are largely inconsistent with those obtained under

each of the different contingencies), the underlying process is cate-

gorized as

micro-driven.

Finally, where aggregate results are consis-

tent with findings for some, but not all, of the contingency variables,

the underlying process is thought to reflect a combination of indi-

vidual and industry characteristics; in this sense, it ismixed.It should

be noted that the preceding categorization is based on the contin-

gency variables investigated. Use of other contingency variables

might yield different categorizations. Because it is nearly impossible

to include all potential contingency variables in a single study, read-

ers should note this as a limitation of the study and a point for fur-

ther research.

THE STUDY

Data Collection

Different mail questionnaires were developed for each of the three

service industries. Per usual practice, items (see measures below)

were modified somewhat to be relevant to each industry. The popula-

tion of interest was defined as households that had a dissatisfying

experience with a given service category (e.g ., medical care). Because

sampling frames of such a popu lation are not easily available, a sub-

stitute procedure, suggested by Robinson (1979) where a random


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Response rates cannot be precise because this involves estimatin

the proportion of the number of respondents to the number o

households who had experienced a dissatisfaction with a specific ser

vice category. The denominator of this proportion, households tha

had a dissatisfying experience, is an elusive number. However, tele

phone callbacks provided some estimate for this term. In all 1,50

telephone callbacks were made, 500 for each service category. Tele

phone numbers were obtained from the crisscross directory. A con

tact rate of about 80 percent was achieved (up to three calls wer

made to those not initially reached). Of those contacted, at least 7

percent stated that they had not responded because they could no

recall a dissatisfying experience with the specific service category. I

contrast, those who had experienced a recen t problem were eage

to participate and let some one kn ow about their dissatisfaction

The dissatisfaction experience rate of 30 percent based on telephon

callbacks is consistent with research (Best and Andreasen 1977). Bes

and Andreasen (1977) report that 21 percent of their sample ha

experienced some dissatisfaction with automotive repair. For othe

categories, the rate was much lower. Thus, the 30 percent estimat

appears to be rather liberal. Based on this liberal estimate for the per

centage of households that had experienced some dissatisfaction,

pessimistic estimate of response rates for the three surveys are auto

mobile repair = 52 percent; medical care = 54 percent; and grocer

shopping = 59 percent. Some responses had to be excluded becaus

of incomplete data. Usable responses range from 116 in automotiv

repair to 125 in medical care. Table 4 summarizes the demographi

characteristics from the three surveys.

Measures

Respondents were asked to describe a dissatisfying experience i

the service category that they remembered most clearly. Measures fo


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plained to the store on my next trip , (2) went back to the store imme

diately and asked them to take care of the problem, (3) called up th

store and told them about the problem); private actions by two item

(e.g ., for auto repair: (1) decided never to shop again at that store, (2

told friends and relatives about my bad experience); and third part

actions by two items (e.g., for auto repair: (1) complained to a con

sumer agency (e.g.. Better Business Bureau), (2) took some forma

action against the store). For all seven items, a dichotomous (Yes

No) scale was utilized. Multiple responses were allowed. Response

were coded as either 0 (No) or 1 (Yes). Specifically, if an individua

reported Y es to any one or more voice items, the voice measur

was coded as 1, otherwise a zero was recorded. Similar coding wa

implemented for private and third-party measures.

Perceived responsivenesswas assessed by asking the respondent

rate the likelihood that the provider would take remedial actio

assuming the respondent had complained to the provider (i.e., voic

action). In all, four items were used to assess this measure utilizing

six-point Very Likely-Very Unlikely Likert scale. These items ar

listed in Table 7 (first column).

Satisfaction with response was measured by utilizing a ten-poin

N ot Satisfied at Ail-Completely Satisfied scale. Respondents wer

asked to record how they felt about the whole incident after they ha

taken a complaint action.

Perceived level of dissatisfaction

with the reported unsatisfacto

experience was assessed by utilizing a ten-point N ot at All Satisfied

Completely Dissatisfied scale. Respondents were asked, Overal

how dissatisfied were you

before

you did anything about the prob

lem? (emphasis original). Finally, information regarding severa

demographic variables (e.g., age, sex, education, and income) wa

obtained for classification purposes. The specific variables utilize

and the distribution of respondents across these variables is provide

in Table 4.


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SUMMER 1991 VOLUM E25,NUMBER 1 3 9

ing a contingency table. A x^ statistic provided a basis to test these

hypotheses. In addition, Cramer's V was calculated to obtain mea-

sures of association in the contingency tables (Kendall and Stuart

1979,588). Followingthis,hypotheses Hz, H4, and

He

were tested by

examining frequency counts for each service category. This testing

focused on ascertaining the match between the pattern of variation

for actual CCB with the hypothesized pattern based on Hirschman's

theory.

Results are summarized in Table 5. For voice and private re-

sponses, the variation across three service categories is significant (x^

values of 41.2 and 32.04, p


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SUMM E R 1991 VOL U ME 2 5 , NUM BE R 1 4 1

ferent levels of dissatisfaction, age, educational background, income

levels, and sex of the respondents are summarized in Table 6. In this

table, the support for the individual hypothesis is evaluated as being

consistent (indicated by Y ES ) or as being inconsistent ( N O )

with the aggregated results of Table 5. In terms of overall support

(see Table 6), hypothesis Hi is strongly supported because, under all

contingencies, the results are consistent with aggregated results.

Variation in

voice

response across the service categories appears to

stem from systematic differences in the three industries, rather than

as an effect due to individual differences. Likewise, results for

hypothesis Hs (Table 5) also evidence strong support under different

contingencies. In this case, lack of systematic variation across the ser-

vice categories is reaffirmed. For/>r/vfl/e responses, results are mixed.

In three of the ten levels of contingencies (i.e., low level of dissatis-

faction, high age group , and male respondents), the results for

H3

are

inconsistent with aggregated data. Similar results emerged when exit

and W-O-M were analyzed separately (for this reason, they are not

shown in Table 6). Variation in private responses appears to be a

joint function of underlying structural factors of industries and sev-

eral individual variables.

In order to further understand these joint effects. Table 6 also

evaluates the overall effect of different contingencies. The effect is

categorized as s tr ong if the results differ substantially for low and

high levels of a contingency variable. For instance, the effects for

level of dissatisfaction are s tr ong since while H3 is not supported

under low dissatisfaction (x^ = 1.2, p = .54), it is strongly sup-

ported when dissatisfaction is h ig h (x^ = 32.0, p < .01). In addi-

tion , the effects for H , are much stronger under h ig h dissatisfac-

tion (x^ = 37.7, p < .001) than under the low condition (x^

= 9.4, p < .01). This suggests that under h ig h dissatisfaction

level, the hypothesized effects of loose monopolies become more

prominent.


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42 THE JOURNAL OF CONSUMER AFFAIRS

TABLE 6

Effects on the

Results

for Hypotheses

H,, H3,

a nd

H5,

under

Different

Contingencies

Contingency

LeveP

Level of

Dissatisfaction

Low

High

Age

Low

High

Education

Low

High

Income

Low

High

Sex

Male

Female

Overall

Support

H ,

Support

Yes

(

Yes

(

Yes

(

Yes

Yes

(

Yes

(

Yes

(

Yes

(

Yes

(

Yes

(

Strong

x

9.4


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44 THE JOURNAL OF CONSUMER AFFAIR

TABLE7

Results for Variance

in

Perceived Responsiveness

(Test of Hypotheses

H,and H,)

Responsiveness Item F-value''

Mean Values'

Grocery

Assume you reported the incident to the store.

how likely is it that the store

1. apologize but do

nothing

^

2.

take appropriate action

to take care of your

problem

3. solve your problem and

give better service to

you in the future

4. be more careful in

future and everyone

would benefit

Multivariate Results

Wilks'X

F-value

p-value

'would. .

12.21

(


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SUMMER

1991

VOLUME25,NUMBER1

45

o

X

I

2

o o

z z

o

O

>-z

* *

s

I

I

U3

a

^- a

g a

I 5

3 I

-a

3

s

g'.g I 5

ill

1-2 I

If

H I .2

11

S Sb

9

o


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of overall support, the results for item 2 (i.e., take appropriate

action to take care of your problem ) are strongly supported, while

item

1

(i.e., apologize but do no thing ) receives mixed support. I

contrast, support for item 3 is weak since in four of the ten levels the

results are inconsistent with aggregate data. Likewise, for item 4,

results are inconsistent for six of the ten levels, indicating weak sup-

port. Note that items 3 and 4 pertain to responsiveness in the future

(for instance, item 4 is, be more careful in future and everyone

would benefit ; Table 7), unlike items

1

and 2 which focus solely o

perceived responsiveness to the specific problem. This indicates that

perceptions of providers' responsiveness to a specific problem are

robust and stable reflections of underlying structural factors of ser-

vice categories. However, for providers' responsiveness to future

problems, these perceptions appear to reflect individual differences

as well as underlying structural factors.

Results for overall effects (Table 8 last column) provide greate

insights into these joint relationships. These effects are mostly due to

differences in the support for items 3 and 4 for different contingen-

cies.

For items

1

and 2, such differences are marginal, with educatio

and dissatisfaction levels as the exceptions. As such, the analysis

focuses on items 3 and 4.

Strong effects are obtained for age and sex of the respondent

Younger respondents are more likely to depict variability in pro

viders' responsiveness to future problems (i.e., items 3 and 4) across

industries (F = 5.2 and 6.58, p < .01) than older consumers (F =

1.93 and 0.8 , p > .05). Females perceive greater differences in pro

viders' responsiveness (F = 5.6 and 6.7, p < .01) than their male

counterparts (F = 2.7 and 1.5, p > .05). Consistent with the effects

for age and sex, consumers with lower income level perceive greater

variation across service categories. This effect is categorized as

w ea k because the variation in items 3 and 4 for low income

respondents is borderline (statistically). Finally, mixed effects are


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SUMMER1991 VOLUME

25,

NUMBER1 4 7

various alternatives and sellers' responses to marketplace dis-

satisfaction.

Satisfaction with Response

Consistent with the preceding analyses, hypothesis Hg was tested

utilizing an ANOVA design with satisfaction as the dependent varia-

ble and service categories as the three-level treatm ent. Following this,

hypothesis H,o was tested by implementing three-pairwise compari-

sons with per comparison error rate set at .0167 in accord with the

preceding discussion.

Consumers' satisfaction with providers' response to their voiced

problem s varies significantly across service categories (F = 15.82, p

< .001). This strongly supports hypothesis Hg. In addition , con-

sumers are most satisfied with grocery retailers' response (mean =

7.01,

standard error - .33), and least satisfied with medical care pro -

viders (mean = 4.42, standard error = .33). For automotive repair,

consumers are moderately satisfied (mean = 5.53, standard error =

.33). The pairwise comparison between grocery retailers and each of

the other categories is significant at p = .0167. However, the com-

parison between automotive repair and medical care is borderline (p

= .0179). These results generally support hypothesis Hio. It appears

that the extent of consumer satisfaction, even when they voice their

problems, is intimately linked to structural factors within an

industry.

Additional evidence in support of preceding results follows from

the analysis of different contingencies (see Table9).In terms of over-

all support. Table 9 suggests that the aggregated results presented are

upheld in nine of the ten contingencies, indicating strong support.

The only exception is low dissatisfaction level, for which the satisfac-

tion evaluations do not differ significantly (F = 0.67, p = .51). The

manifestation of structural factors (of industries) in consumers' satis-


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SUMMER1991 VOLUME25,NUMBER1 4 9

DISCUSSION AND IMPLICATIONS

Certain limitations of this study should be noted. The findings are

based on responses from households in the Southwest United States.

To the extent that these respondents are idiosyncratic, the generaliza-

bility of results may be affected. The test of hypotheses was limited

to dissatisfactions resulting from grocery, automotive repair, and

medical care problems. For a more rigorous examination, more

product/service categories need to be examined. Purposive selection

of service categories with varying loose monopoly conditions

afforded a reasonable basis for examining the key propositions. At

the same time, it is recognized that the results obtained not only

reflect the effects of greater or fewer loose monopoly conditions

(which was intended) but also of unique features of the specific in-

dustries selected (which was not intended). Additionally, the research

design adopted (i.e., recall of a dissatisfying experience) is likely to

highlight the more serious dissatisfactions. As such, the results may

not be generalizable to the entire set of marketplace dissatisfactions.

Moreover, the study is based on cross-sectional data. Usual caveats

for determining sequential effects from such data are applicable. One

particular limitation of the cross-sectional design is that behaviors

and cognitions leading up to those behaviors are collected at the same

time. How the complaint was actually handled by the service pro-

vider may have affected responses.

The motivation for this study lies in understanding the impact of

loose monopoly conditions at the industry level on dissatisfaction-

related responses at the individual level. The specific contribution

stems from the fact that while previous studies have been preoccu-

pied with documenting variation in dissatisfaction responses across

industries, this paper examines a theoretical model that attempts to

explain such variations. Based largely on Hirschman's model, it was

hypothesized that certain measurable structural differences among

industries (i.e., loose monopoly conditions) would likely manifest in


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play a dominant role, and (c)

mixed

responsesboth structural and

individual factors interplay in affecting dissatisfaction responses.

The findings of this study reveal that while voice is largely a macro-

driven response, private actions are probably mixed responses. Dis-

satisfied consumers are significantly less likely to use voice actions

when their problems involve medical care instead of either grocery or

automotive-repair problems, in accord with Hirschman's theory.

Additionally, the variation in voice actions remained significant

under all analyzed contingencies. The notion that the more an indus-

try manifests characteristics of loose monopolies, the m ore it is likely

to be perceived to restrict voice actions, appears to be a valid por-

trayal of real-life processes. For private actions a different picture

emerges. First, variation in private actions, while significant, is in a

direction opposite to that of voice actions and stated hypotheses. In

other words, the findings indicate that the more an industry mimics

a loose monopoly, the more likely consumers would use private

actions. Second, the variation in private actions is influenced by

industry as well as individual characteristics (i.e., mixed response). In

particular, this variation is enhanced (diminished) for the case when

the level of dissatisfaction is high (low), and the respondent is female

(male) or younger (older).

Preceding differences between patterns for voice and private re-

sponses are intriguing. A potential explanation for these patterns

could be that consumers utilize compensatory mechanisms to relieve

their dissatisfaction; that is, where voice is inhibited due to psycho-

logical or external reasons (e.g., as in medical care problems), con-

sumers attempt to compensate for this restriction on voice with

greater use of private (i.e., exit and negative W-O-M) actions. Pre-

sumably this underlies consum ers' motivation to do something

about their dissatisfaction, and hopefully get even with the pro -

vider . Conversely, when voice is uninhibited and serves to redress

dissatisfactions, consumers may compensate by less frequent use of


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SUMMER 1991 VOLUM E 25, NUM BER

1

5 1

Automotive repair presents an anomalous case, with both voice (84

percent) and private (60 percent) responses at a high level (also exit =

34 percent, W-O-M = 57 percent). A likely reason for this anom aly

is that while automotive-repair industry does not present conditions

which might inhibit voice (Tables 2 and 3), consumers neither per-

ceive auto-repair providers as responsive sellers (Table 7) nor are

satisfied with their actual response. As such, while voice is possible, it

lacks potency. Probably this lack of potency interferes in the opera-

tion of a compensatory mechanism between voice and private

responses. Nevertheless, it cannot be ruled out that the selection of

service categories and/o r idiosyncracies stemming from the nature of

the responding sample could be confounding factors. More research

to understand CCB patterns is needed.

If supported, such compensatory mechanisms offer significant

implications. Practitioners may find that the encouragement of voice

has an all around positive effect. When consumers voice their dis-

satisfactions and sellers are responsive, the use of private actions (exit

and negative W-O-M) is likely to be less frequent. By facilitating

voice, managers may not only reduce the indirect impact of negative

W-O-M concerning their products and services, but may also retain

the loyalty of their customer base (i.e., because of reduced exit).

Recent TARP (1986) studies appear to support this prescription. For

instance, over 46 percent of the consumers indicated that they would

not exit when voice was feasible, even though their complaints were

not satisfactorily addressed. In instances where managers were

responsive and tended to satisfy voiced complaints, the portion of

consumers indicating that they would remain loyal (i.e., not exit)

increased to 70 percent. Consequently, the counter-intuitive notion

that the effective encouragement and facilitation of complaints (i.e.,

voice) may actually help increase brand loyalty (and profitability)

and contain the negative effects of other private actions appears to

hold considerable merit.


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several contitigency variables. The level of dissatisfaction appears to

have a strong effect on voice and private responses, as well as on

satisfaction with response. Much research has suggested tha t the level

of dissatisfaction has a marginal, if any, role in consumers' com-

plaint responses (Day 1984). This study refines previous thinking

because the dissatisfaction level appears as a significant moderating

variable. Likewise, effects of age and sex were significant, especially

for private actions and perceived responsiveness. Researchers may

wish to incorporate such contingencies in attempts to understand dis-

satisfaction responses. Third, clear differences appear to underlie

consumers' choice of voice and private responses. Notably, voice ac-

tions are relatively macro-driven; private actions are mixed. An im-

plication is that researchers are likely to find important differences in

the psychological process that predict (and explain) voice and private

responses (Day 1984). Finally, this study provides sufficient evidence

to conclude that industry characteristics appear to influence con-

sumers' choice of dissatisfaction response. The proposed conceptual

framework provides an initial approach for understanding this pro-

cess.

Future research which enhances this model and seeks to inte-

grate it with other psychological variables appears to prom ise fruitful

returns.

CONCLUSION

This study aimed to empirically investigate several hypotheses that

attempt to tie structural factors in different industries (i.e ., loose

m onopoly conditions) to individual consumers' responses (and per-

ceptions) concerning marketplace dissatisfaction. This hypothesized

manifestation of macrolevel factors in microlevel behavior was based

largely on Hirschman's Exit, Voice and Loyalty framework (1970),

although findings from CCB literature were also incorporated. Sub-

stantively, this study moves away from the usual descriptions of the


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