Dimensions of Consumer Search Behavior in Services

Jou rnal of Services Marketing Marketing Dimensions of consumer search behavior in services Janet R. McColl-Kennedy Richard E. Fetter Jr

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Dimensions of consumer search behavior in services Janet R. McColl-Kennedy McColl-Kennedy Senior Lecturer, Graduate School of Management, The University of Queensland, St Lucia, Queensland, Australia

Richard E. Fetter Jr Associate Professor of Marketing, College of Business, Butler University, Indianapolis, Indiana, USA

Keywords Consumer behaviour, Information, Risk, Services marketing Abstract Develops a seven-item scale to assess consumers’ external search activities and assessed the scale’s construct validity. Moreover, Moreover, to examine the scale’s scale’s generalizability across various services, both things-directed and people-directed service settings are used. The findings suggest there are two identifiable aspects of consumers’ search activities, source and effort. Evidence of the construct validity of the seven-item scale is based on exploratory factor analysis, calculation of Cronbach’s alpha, and a nomological assessment of the scale.


Introduction

Consumer search behavior

Consumer search behavior has emerged as an important field of study, and this is not surprising given that information search is an integral aspect of consumer decision making (Malhotra, 1983; Moore and Lehmann, 1980; Newman, 1977). The importance of search is borne out by numerous models of consumer behavior where search activity is considered central to consumer behavior decision-making models (see Engel et al., 1995; Howard and Sheth, 1969). Search is thought to be especially effective as a means of reducing uncertainty and perceived risk (Urbany et al., 1989). Furthermore, Schmidt and Spreng (1996) note that understanding search behavior is important at the micro level for marketing management decisions, and at the macro marketing level for public policy decisions. Moreover, they point out that for marketing managers, understanding search is “crucial for designing effective marketing communication campaigns” because it represents the first stage at which marketing can provide information and, therefore, influence consumers’ decisions. Although search has received considerable attention, both conceptual and empirical, in the marketing literature to-date, most of the research has focused on search for physical goods (see Beatty and Smith, 1987; Bloch et al., 1986; Brucks, 1985). A number of researchers, however, have noted that services are generally perceived to be riskier than goods (see Eiglier and Langeard, 1977; Murray, 1991; Zeithaml, 1981). Iacobucci’s Iacobucci’s (1992) comparison of consumers’ perceptions perceptions of a set of goods and services empirically supports the notion that consumers view services as more risky than goods. Her empirical study demonstrated that consumers view many service activities as more complex and less standardized than goods. Given the generally risky nature of services, and the basic tenet that consumers engage in search activities as a means to reduce risk, it seems that understanding consumer search behavior may be especially important in a

The authors wish to acknowledge those who have provided useful comments on previous drafts of this manuscript. 242

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services marketing context. Murray (1991) demonstrates that consumers’ search activities differ between goods and services, in that consumers tend to search more for services than for goods. Specifically, he found that people are more inclined to search for information when shopping for services than when they are shopping for goods, and that t hey tend to avoid making outright purchases for services, again implying extended information acquisition for services.

Initial evidence


While the limited research to-date on consumers’ search activities in service contexts provides some initial evidence as to the causes and consequences of search across various services (see Bunn, 1994; Dawes et al., 1991; Murray, 1991), much remains to be done. For example, a review of the services literature yielded no empirical studies which validated a scale to measure external search. Brown et al. (1994) recommended that for substantive progress to occur in services marketing, we first need research aimed at issues such as measurement, scale development, and modeling. Therefore, given: (1) the importance of search in consumer decision making; (2) that there appears to be some evidence that search differs between goods and services; and (3) following up on the recommendations of Brown et al. (1994), the current study was conducted to develop a multi-item scale to measure external search across various service settings. Although search has been defined as both internal (retrieving information from memory) and external (obtaining information from various outside sources), this study focuses solely on external search.

Construct validity

After first discussing the conceptual framework for this paper, we report on the results of an empirical study which we conducted to assess the construct validity of a seven-item external search scale. We developed the scale by following the suggestions of Churchill (1979) and Schwab (1980). Moreover, we assessed the generalizabity of our seven-item scale by administering it across six different service settings based on one of Lovelock’s (1983) service classification taxonomies. Lovelock (1983) discusses why it is important to distinguish between services directed at people from services directed at things. Therefore, three of the services included in our study are directed at people: (1) movies; (2) haircuts; and (3) exercise club, and the other three services are oriented toward things: (1) life insurance; (2) auto repair; and (3) lunch at a fast food restaurant. Briefly, we found that the dimensionality of our newly-developed sevenitem external search scale is not invariant across service settings. A twofactor structure: (1) source; and (2) effort,

THE JOURNAL OF SERVICES MARKETING, VOL. 13 NO. 3 1999

243

was supported for the things-directed services, but the people-directed services yielded less conclusive results. Finally, we discuss our findings from both academic and management practitioner perspectives, along with some directions for future research. Conceptual framework General overview of the external search literature

Addressing external search


Given the conceptual evidence that links consumer search to important consequences (e.g. lower perceived risk and uncertainty, higher knowledge, satisfaction with the search process, etc.), it is not surprising that quite a number of studies have addressed external search both conceptually and empirically. Much of the prior research has been directed at external search for goods, not services. Prior research on external search can be grouped into three general categories. First, search has been studied in terms of sources of external information. For example, Beatty and Smith (1987) identified four sources of search information: (1) media; (2) retailer; (3) interpersonal; and (4) neutral. More recently, Olshavsky and Wymer (1995) suggest that sources can be classified as: (1) marketer controlled (e.g. personal selling, advertising, good information on the package, good brochures); (2) reseller information (e.g. catalogs, consultants); (3) third-party independent (e.g. consumer report); (4) interpersonal sources (e.g. friends, acquaintances); and (5) by direct inspection of the good by the consumer (e.g. observation, inferencing).

External search effort

Second, a number of studies have assessed external search by measuring consumers’ external search effort. Some of the more common measures of search effort are number of stores visited, number of brands examined, and time spent in the overall shopping experience (see Newman and Lockeman, 1975). Finally, external search has also been measured by assessing for which aspects of a good consumers search, such as price, physical attributes, etc. (Brucks, 1985; Katona and Mueller, 1954; Newman and Staelin, 1971). While prior research on search in product contexts provides considerable evidence as to its role in consumer behavior, only scant attention has been paid to developing a construct-valid measure of external search. Indeed, search has often been measured as a single-item scale (Beatty and Smith, 1987). Moreover, among the studies that employed multiple-item search measures, only a few reported their scales factor structures (see Beatty and Smith, 1987; Kiel and Layton, 1981) and psychometric properties. Unfortunately, therefore, we were unable to locate a wellvalidated multiple-item search scale from the physical goods literature which

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could be used as the basis for testing its generalizability to services marketing contexts. Prior research on external search in services marketing

The only study we were able to locate which specifically addressed a multiitem scale and its psychometric properties in a service setting was reported by Dawes et al. (1991). Dawes et al. (1991) administered a 16-item search scale in an industrial service setting (consultancy services). Individual items tended to solely measure respondents’ uses of information sources, rather than other aspects of buyers’ search activities, such as effort. The 16-item scale yielded a five-factor solution: (1) impersonal advertising; ) T P ( 4 1 0 2 r e b m e c e D 6 1 1 5 : 3 1 t A I T S E R U C U B N I D E C I M O N O C E I I D U T S E D A I M E D A C A y b d e d a o l n w o D

(2) consultant’s statement of capabilities; (3) personal advertising; (4) internal network; and (5) external referral network.

Information activities

Although Dawes et al. (1991) provides some initial evidence as to consumers’ external search activities, the setting (industrial buying) and the one particular service (professional consulting) may limit t he generalizability of their 16-item scale to other service settings. Murray (1991) used a 25-item search scale developed by Andreasen (1968) in assessing consumers’ information activities across both services and goods. Although most of the items used in Murray’s (1991) study tap external search activities, several items also measured the degree to which consumers internally searched on the purchase occasion (e.g. “think about my previous involvement with this …”, “rely on past personal experience”, and “try to remember what alternative my friends use”). Of the items generally categorized as measuring external search, they measured sources of information (e.g. “ask the opinion of a friend” and “pay attention to magazine ads”), but did not assess types of information or the extent/effort aspect of search discussed in an earlier section of this text. To his credit, Murray (1991) used a range of goods and services. These included what he describes as five “low service attribute products”: (1) windbreaker jacket; (2) tennis racket; (3) barbeque grill; (4) electric vacuum cleaner; and (5) pocket camera). Five “moderate service attribute products”: (1) auto upholstery; (2) smoke/fire protection; (3) furniture rental/sofa; (4) auto muffler; and (5) fine restaurant meal)


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and five “high service attribute products”: (1) teeth cleaning; (2) tax advice preparation; (3) wheel alignment; (4) interior design advice; and (5) eye inspection. Yet, Murray (1991) did not report the factor structure or psychometric properties for the 25-item scale employed in his study. Regardless, Murray (1991) provides initial evidence that consumers search for information differently in a service setting compared to a product setting. He also found evidence that, when faced with increasing uncertainty in a services context, consumers search for more, not less, information. Thus, while Murray (1991) empirically demonstrated consumer search is important in a service setting, and certainly worthy of further investigation, his study is limited in providing evidence as to how one should measure search.


Health care provider

In a study of search for health care services, Stewart et al. (1989) used search items solely focused on types of information to which one attends when selecting a health care provider (e.g. “doctor’s formal qualifications”, “will prescribe medicine without an appointment”, and “has an X-ray machine”). Their study largely omitted any consideration of sources of external information or the extent to which one searches for such information (effort). While this study provides evidence as to attributes one uses when looking for health care, the study did not report the factor structure or psychometric properties of the search scale. Moreover, many of the items used in the study are not generalizable to non-health care service settings. Finally, Perdue (1993) investigated the search activities of recreational fishermen. Perdue (1993) was interested in the antecedents of search for recreational fishermen. He administered a multi-item scale to a group of fishermen, but did not report any of the scale’s psychometric properties. Rather, he treated his measure of search as a unidimensional construct. Definition of the external search construct

Given the above discussion, we define external search as a two-dimensional construct, dealing with consumers’ search for both sources of external information and the amount of effort they will expend in procuring that information. By source, we mean those search activities aimed at capturing the extent to which one will seek various types of sources when searching for external information. The second aspect of external search which we identify in our construct definition is effort, aimed at capturing to what extent one is willing to go, or how hard one is willing to work, to obtain external information. Not all services are alike

Multiple settings

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A number of researchers (see Brown et al., 1994; Zeithaml et al., 1985) have suggested that research in services marketing should encompass multiple settings and/or industries in order to understand how constructs differ across service settings. Therefore, we attempted to select different types of services for this study. Lovelock (1983) provides a series of approaches for THE JOURNAL OF SERVICES MARKETING, VOL. 13 NO. 3 1999

categorizing services. He contends that being able to categorize services into groups with common characteristics helps managers think strategically about their particular service and to be less likely to think myopically about their particular industry. Indeed, this assists managers in that “recognizing which characteristics their own service shares with other services, often seemingly unrelated industries, managers will learn to look beyond their immediate competitors for new ideas as to how to resolve marketing problems that they share in common with firms in other industries” (Lovelock 1983, p. 19).

Physically present


One framework provided by Lovelock (1983) to categorize services is to distinguish services directed at “people” from those directed at “things”. Lovelock (1983) notes that with people-directed services, the recipient needs to be physically present while the service is performed, while in those things-directed services, the person does not need to be present. Moreover, Lovelock (1983) notes that in people-directed services, the person essentially needs to “enter the service factory” and spend time there while the service is performed, whereas the service recipient’s presence may not be necessary with things-directed services. We decided to select Lovelock’s (1983) people-directed versus things-directed model as the framework for our study, based on: (1) our initial review of the literature (Murray, 1991), and (2) the consensus from the exploratory stage of our research (e.g. depth interviews) that consumers generally viewed “personal” services to be quite distinct from services directed at their possessions. Whether or not actual search activities differ across these settings, therefore, seemed to be an important empirical question. Selection of services for the current study

Given the advice and encouragement of others (see Brown et al., 1994; Lovelock, 1983) that we should include a variety of different services in our empirical research, we decided to include six different services in our study. Three of the services are categorized as “things-directed” and three “peopledirected”. We generated a pool of already-used services from prior research based on a review of the literature. The services were then categorized as either things-directed or people-directed based on: (1) prior classification from the literature; and (2) review by a panel of experts.

“Sorting procedures”

Our panel of experts was a group of faculty members from a major midwestern university who had performed similar “sorting procedures” on other research projects. In those instances for which there was uncertainty or disagreement among the literature and/or our panel of experts, the service was discarded. The remaining pool of services was then screened based on the likelihood that respondents would have at least some familiarity with the service, even if they had not procured/experienced the service. Based on this method of service selection, the things-directed services selected for the current study were life insurance, automobile service and lunch at a fast food restaurant. The people-directed services included in our current study were: •

exercise club;

•

movie; and

•

haircut.


247

Method Sample and procedure

We used a sample of 340 residents from a major midwestern US city for the study. To obtain our achieved sample, we purchased a mailing list of names and addresses for a major midwestern city. We randomly selected 1,500 names from the purchased mailing list and mailed: (1) a self-administered survey; (2) a letter explaining the purpose of the study and assurance of anonymity; and (3) a stamped envelope, addressed to one of the researchers.

Follow-up mailing ) T P ( 4 1 0 2 r e b m e c e D 6 1 1 5 : 3 1 t A I T S E R U C U B N I D E C I M O N O C E I I D U T S E D A I M E D A C A y b d e d a o l n w o D

Three weeks after the initial mailing, we sent a follow-up mailing that included the same material as the first mailing. Across both mailings, we obtained 340 usable surveys, an overall response rate of 22 percent. We compared the demographic characteristics of our achieved sample to census demographics for the city from which our sample was drawn to affirm that our sample was representative of the population from which it was drawn (United States Bureau of the Census, 1995). Of the survey’s respondents, 52 percent were male, 48 percent were female. The average age of respondents was 46.7 years, ranging from 19 to 81 years of age. Most of the survey’s respondents earned between $25,000 and $80,000 per year with a median family income of $35,000. (This compares well with the median family income for the city population from the census of $35,054, with 24.6 percent reporting that they had obtained a bachelor’s degree.) This compares with 21.4 percent for that city’s population from the census (US Bureau of the Census, 1995). We also compared the surveys received from the initial mailing to those surveys received after our follow-up mailing and found no statistical differences between the demographics of the two groups. Responses to actual survey items were also quite similar across the two groups. Measures

Multi-item scales

We developed a seven-item scale to assess respondents’ external search by following the suggestions of Churchill (1979) and Schwab (1980) for developing multi-item scales. For example, we first defined our external search construct-of-interest, developed a pool of items from a general search of the literature, and executed various purification procedures, including tests of convergent, discriminant, and nomological validities. Although our original pool of search items included 12 items, we used the scale purification process to reduce the final scale down to seven items. We were especially interested in developing a parsimonious measure of external search, because: (1) search is generally included in larger model tests (see Schmidt and Spreng, 1996); and (2) given the context-specific nature of measuring search, researchers may be inclined to make modifications to an already-validated multi-item search scale, rather than attempting to develop and validate their own multi-item search scales. As part of the scale purification process, we administered the initial pool of items to a convenience sample of 110 MBA students from a major

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midwestern university. Although we do not report the full analyses of our pilot study, it should be noted that we used t he pilot study to pare down our original pool of items to the seven items used in our current study by performing various empirical analyses (factor analysis, Cronbach’s alpha, assessing inter-factor correlations, etc.) and qualitative procedures (e.g. a series of depth-interviews and focus groups, asking the MBA students to discuss individual items, as well as the overall scale).

Two key areas

The items selected for the current study were employed because they generally tapped the two key areas of search as discussed earlier, that is: (1) sources of information; and (2) effort of search involved.


These items generally captured the sources identified by Olshavsky and Wymer (1995). For example, their notion of “marketer-controlled sources” were tapped by our item “I would be interested in reading information about how this service is performed”. Olshavsky and Wymer’s (1995) “third party independent” source of external information was captured by our item “I would be interested in reading a consumer reports article about…” Since this study was an initial attempt at validating a scale for external search in a services marketing context, we felt that developing items for inquiring about specific types of information for which consumers search was beyond the scope of this initial study. Moreover, as we earlier indicated, future studies on external search can modify our scale to the context-specific nature of the particular services-of-interest. Analytical procedures

We used a three-step approach to develop our multi-item scale and assess its construct validity. First, we assessed the seven-item scale’s face validity by assessing the items relative to the aspects of external search deemed pertinent to this study. Next, we gave items to a panel of experts (doctoral students from a major Australian university) to perform a Q-sort process. In the Q-sort process, each judge was asked to sort t he seven items based on: (1) sources of information (e.g. personal versus non-personal); and (2) effort (e.g. degree of search).

External search of interest

The Q-sort procedure very nicely suggested the seven-item scale addressed the aspects of external search of interest in this study, and the judges generally categorized each item as we expected (i.e. sorted source items with one another and effort items with one another). Others have used similar sort processes as part of the construct validation process. Finally, we conducted a series of empirical analyses, including exploratory factor analysis, t -test difference of means, and correlation analysis to assess the scale’s psychometric properties and construct validity. Essentially, to investigate t he scale’s convergent and discriminant validities, we examined the seven-item scale’s factor structures and individual items’ factor loadings across each of the aforementioned services. The factor structure of the scale was first assessed using the “eigenvalue-greater-than-one” standard (Kim and Mueller, 1978). Thus, we expected to extract at least two factors with eigenvalues of at least one. At the individual item analysis level, we expected the source external search items would load strongly on a single factor and those items intended to operationalize effort would collectively


249

load strongly on a separate factor. Thus, for evidence of convergent validity, we expected each item would load strongly on its intended underlying factor (i.e. source or effort). For evidence of discriminant validity, we expected the cross-loadings in the exploratory factor model to be small. To develop our construct validation procedures, we followed the suggestions of Schwab (1980). We also incorporated the same methods used in other studies that empirically validated newly-developed scales (Allison, 1978; Seymour and Lessne, 1984; Zaichkowsky, 1985).

Further examined


Once the dimensionality of the seven-item scale was determined, items loadings on each factor were further examined by calculating their Cronbach’s alpha and correlation with the other factor (i.e. created a scale score for each factor and conducted correlation analysis between the two factors for each service). A scale that is caused by a single underlying factor should have an adequately high measure of internal consistency (Nunnally, 1978). Thus, Cronbach’s alpha was used as additional evidence as to the scale’s convergent validity. The inter-factor correlation was used as further evidence of the scale’s discriminant validity. Essentially, moderate-to-low inter-factor correlations (along with small cross-loadings) provide evidence that the factors (multi-item scales) are distinct. We then assessed the nomological validity of our seven-item external search scale using a series of correlation analyses and difference of means tests. Specifically, we identified a set of variables with which external search should be related: (1) involvement; and (2) perceived differences across vendors (Zaichkowsky, 1985) and should not be related (gender, education, and income) (Zaichkowsky, 1985). Results Descriptive statistics

Tables I and II report individual items’ descriptive statistics.

External search scale

Recall that our external search scale was measured using a seven-point semantic differential scale. Inspection of Tables I and II shows the average scores for individual items varied measurably within each service and across services. In general, Tables I and II demonstrate that there is less variation within things-directed services, but considerable variation within peopledirected services. For example, for haircut, average scores varied from a low of 2.91 (“interested in reading information about this service”) to a high of 4.24 (“talk about this service with other people”). Looking across the various services in Tables I and II, one can see that an individual item’s average score also varied considerably. For example, “interested in reading information” varied from a low of 2.91 for haircut to a high of 4.01 for movies. The item, “talking about this service with other people” ranged from a low of 3.03 for life insurance to a high of 5.63 for movies. Scale dimensionality

Tables III and IV report the varimax maximum-likelihood factor loadings, eigenvalues, percent-of-variance accounted, inter-factor correlations, and Cronbach’s alpha for each of the services included in the study. Specifically, Table III reports the results for the “things-directed” services (i.e. life insurance, routine auto repair, and lunch at a fast food restaurant). Table IV 250


n o i t a h i c v e n d u l d d r a o d o f n a t s t a S F n a e M

n o i t e i c a i v v e r d e s d r r i a a d p n e a r t o S t u A n a e M


n o i t a i e v e c d n d a r r a u s d n n i t a e S f i L n a e M

m e t I

0 2 . 2

5 3 . 2

4 9 1 . 8 . 2 1

6 0 . 2

0 7 9 . . 9 1 1

3 3 . 3

7 2 . 4

4 7 4 . . 9 4 3

2 1 . 3

6 7 1 . . 0 3 3

1 1 . 2

9 1 . 2

1 9 9 . 9 . 1 1

4 9 . 1

9 4 9 . 8 . 1 1

8 4 . 3

9 2 . 4

8 8 4 . . 8 4 3

9 2 . 3

9 6 0 . . 1 4 3

7 8 . 1

5 0 . 2

1 9 2 . 8 . 2 1

3 1 . 2

4 9 8 . 8 . 1 1

6 1 . 3

5 0 . 4

0 3 6 . 0 . 3 3

5 8 . 3

4 1 8 . 3 . 4 4

e d t i s s i u v i r h o o h t t p s b a t i g g a h n n e h t l i s i t c a s i w t a y s h h u o r c b m h a r c r r i t t o u f t u r e p u p d l o o n o e n b p e p t r i a e e o r r e o k f w n r o p i e t o e t r a e r i b t e p m b t h a u s h e w t n s m c o l n i r p u g t o o o o c i n s h f t i c e i s n a r p c i e a o w o g g t c e r o e t h a n n c t h n c i i r i d d a v o i e a a h r s e e c e m m r r r i s o t t e s o n n r c c i d i i i f a f o h e f d e d v r t e e c m t y t e o t t i r u v n l s s o s o d a a e e d r f r b a m d e r e e e t r e a k t p n e a e n n c c i s i i p i k l e k e e i a a p e e v t s e t m v e s b e b r o r e e y y y i c c c y c s s l l l i i d d l l v l l l v l s e s l a a v a r a r u r u i i v h u u e u e u o e o h a s s s s w s w t h t u u s u s u I I I I I I I

Table I. Descriptive statistics for search items for things-directed service encounters THE JOURNAL OF SERVICES MARKETING, VOL. 13 NO. 3 1999

251

n o i t a i b v e u d l c d r e a s d i c r n a e t x S E n a e M

n o i t a i v e d t u d c r a r i a d n a H t S


n a e M

n o i t a i v e d d e r i a v d o n a M t S n a e M

m e t I

2 2 . 2

2 2 . 2

9 7 1 . 0 . 2 2

6 1 . 2

8 7 0 . 0 . 2 2

3 6 . 3

4 9 . 3

0 5 2 . 4 . 3 3

7 4 . 3

6 2 2 . 6 . 4 3

9 0 . 2

0 1 . 2

5 7 1 . 3 . 2 2

2 4 . 2

3 9 4 . 3 . 2 2

1 9 . 2

8 9 . 2

7 4 3 . 2 . 4 4

0 5 . 3

0 9 1 . 5 . 4 3

7 1 . 2

9 1 . 2

6 5 0 . . 5 2 1

3 8 . 1

9 5 8 . . 0 1 2

1 0 . 4

6 6 . 3

5 3 4 . 6 . 3 5

9 7 . 4

5 6 2 . 9 . 4 3

e d i t s s i u v i r h o o h t t b p s a t i g g h e a n n t i l h s i c t a s w i a y s t h u o r h b c h a m c r r r t i t o u f t u r e p u p d o o n l p p o b e e o t e n r i a r e e r o k w f n r o p e t o e t r a e r i i t h b e p b t a m h u s e n w s m c t o l n i r p u g t o o o o n s h c i f t c i i e s r c n i a t a e w p o o g g c e r o e t h n i n a c h i c r i n t i d d a v o e a a h r s e e c e m m r r r i s o t e s r o t n d i n i c f c i f i a o h e f d e d v r t e m e c t y t e o t t i s u v n l s r s o o a e e a f d d r r r b a m d e e t e e a r t e e k e n n p i n c a c k i p i l e k e s i a e a p v e i e v t s e t m r o r e s b e b e e y y y i c c c y c s s l l l i i d d l v l v l l l v l s e s l a a a r a u r u i v i u u r u u e e o e o h h a s s s s w s w t h t u u s u s u I I I I I I I

Table II. Descriptive statistics for search items for people-directed service encounters 252


t h r o c f n f u E l d o o e f c t s r a u F o S

e t c r i o f v r f e E s r i a p e r e c o r t u u o S A


t r o f f e E c n a r u s n i e f i e L c r u o S

m e t I

7 4 . 0 3 8 . 0

7 8 . 0

8 8 . 0

1 5 7 9 8 8 . 8 . 0 . . 0 0 2 4 0 0 . 5 . 1 0 7

2 6 . 0

1 7 . 0

8 7 . 0

9 8 . 0

1 9 . 2

2 8 . 0

8 8 5 7 . 8 . 2 . 0 0 2

9 4 . 0

7 1 8 . 8 . 0 0

7 8 . 0 3 0 . 5 . 1 0 7 2 5 7 7 . . 2 0

8 5 . 0

2 6 . 0

4 7 . 0

3 8 . 1

0 7 . 0

6 0 . 3 . 7 0 5 4 8 . 0

2 8 . 0

3 5 . 0

9 1 . 2

4 6 . 0

e d t i s s i u v i r h o o h t t p s b a t i g g a h n n e h t l i s i t c a s i w t a y s h h u o r c b m h a r c r r i t t o u f t u r e p u p d l o o n o e n b p e p t r i a e e o r r e o k w f n r o p i e t o e t r a r e i b t e p h m b a u s t h e t w n s m c o l n i r p u g t o ) o o o c i n s h s f t i c e i r s r c n p i a t o e w r a o t o c g g c e e t o h a a n n c h f i i c r i n t i d d a v o e o a a h r s e e c e w m t m r r r i s o ( t t e s o n n r c c i d i i i f e n a f o h e f c i o d e d v t r t n t e e c m t i y l e o a l t t r a i s u v n s o s r e a o d a a e f e a d r r b a m d r h v r e r e e p e t r e a k t o l f e n p e e n i n c a a c k o c e k i p l i i s s e e r a e a p ’ v e i e v t s t s o m u t h e y e y l g b e b r o r e e a y y c c c c c s l t a c l l d d a l i l l i l a l i l s n f s e i s l b a a v a v a v r u i r r n u v e r v u u u u c e n o e o h a h s s e s e s e o g r r w s w t h t u u s u s u i e t n C I I I I I I I E P I

Table III. Exploratory factor analysis of search items for things-directed service encounters THE JOURNAL OF SERVICES MARKETING, VOL. 13 NO. 3 1999

253

t r b f o u l f c E e s i c r e e c x r E u o S

t r o f f t E u c r i a H e c r u o S


5 0 6 . 8 . 0 0 0 9 . 0

t r o f f E e i v o M e c r u o S

m e t I

2 7 9 7 8 8 . 7 . 9 . . 0 0 1 4 0 0 . 6 . 4 0 7

2 9 . 0

0 0 4 . 8 . 0 0

0 8 . 0

3 8 . 0

7 1 . 3

0 8 . 0

4 6 0 8 . 8 . 1 . 0 0 2

8 6 . 0

7 2 8 . 8 . 0 0

9 8 . 0 8 0 . 5 . 2 0 7 7 6 9 7 . . 0 2

0 0 9 . 6 . 0 0

1 1 5 . 5 . 0 0

8 7 . 0

7 1 . 2

7 7 . 0

9 0 . 4 . 6 0 6 9 8 . 0

8 1 8 . . 5 0 0

4 4 . 2

7 7 . 0

t s s i u i h o h t t s b a i g g h n n e t l i s i c a s i w t a y s h u o r h c b m h a r c r r i t t o u t f e u u r l p p d o o n o e n b p e p t r i a e e o r r e o k w f n r o p i e t o e t r a r e i b t e p h m b a u s t h e t w n s m c o l n i r p u g t o ) o o o c i n s h s f t i c e i r s r c n p i a t o e w r a o t o c g g c e e t o h a a n n c h f i i c r i n t i d d a v o e o a a h r s e e c e w m t m r r r i s o ( t t e s o n n r c c i d i i i f e n a f o h e f c i o d e d v t r t n t e e c m t i y l e o a l t t r a i s u v n s o s r e a o d a a e f e a d r r b a m d r h v r e r e e p e t r a k t o l f e n p e e n i n c a a k o c e k i p l s i s e e r a e a p ’ e i e v t s t s o m u t h e y l g b e b r o y y e e a y c c c c c l l t a c l d d a l i l l i l a l i l s n f s e l b a a v a v a v r u i r r n u v e r v u u u u c e n o e o h a s s e s e s e o g r r w s w t h u u s u s u i e t n C I I I I I I I E P I

Table IV. Exploratory factor analysis of search items for people-directed service encounters 254



provides the results for the “people-directed” services (i.e. movie, haircut, and exercise club). For the sake of clarity and ease of interpretation, only factor loadings equal-to-or-greater-than 0.35 are reported in the tables. Initial inspection of both tables very nicely suggests a t wo-factor solution across all three “things-directed” service encounters. The factor structure for the “people-directed” services is not quite as encouraging, given that some items had rather large cross-loadings. All six service encounters met Guttman’s (1954) “eigenvalue-greater-than-one” criteria. Variance accounted by the two-factor solutions ranged from about 55 percent-75 percent, intercorrelations between the factors were generally quite acceptable, ranging from 0.36 to 0.64, and inspection of the Cronbach’s alphas were quite encouraging. Indeed, only one of the scales (source for life insurance) failed to meet Nunnally’s (1978) recommended 0.70 level of internal consistency for a scale under development. Most of the other Cronbach’s alphas reported in Tables III and IV ranged from 0.75-0.85. As is evident in Table III, the seven-item external search scale yielded a twofactor structure across all three things-directed service contexts: (1) life insurance; (2) routine auto repair; and (3) lunch at a fast food restaurant.

Various types of sources

The first factor, which we term “source”, generally taps those search activities aimed at capturing the extent to which one will seek various types of sources when searching for external information. For example, reading information and comparing service characteristics are (potentially) important sources of information. The second aspect of search, which we named “effort”, captures those search activities identifying how much effort one would be willing to expend in obtaining information. For example, the items “I usually seek advice from other people”, and “I spend a lot of time choosing what kind to buy”, generally capture the notion of expended effort in the search process. The factor structures for the people-directed services were somewhat contrary to our original expectations. Although the factor structures generally appear to yield two-factor solutions, inspection of Table IV suggests that two of the items (“compared service characteristics” and “talk about this service”) tended to cross-load. Further, for exercise club, “compared service characteristics” actually loaded rather strongly on the “wrong” factor (effort factor, rather than the source factor). Thus, the empirical evidence provided by our study suggests the two-dimensional view of external search (source and effort) is generally supported for thingsdirected services. However, the dimensionality of external search for peopledirected services warrants further investigation. Evidence of convergent validity

Factor loadings

As mentioned earlier in the text, we use the size of the factor loadings (i.e. correlations between individual items and their underlying factor) as evidence of convergent validity. Inspection of the factor loadings in Tables III and IV are generally quite encouraging, with six of the seven items generally loading quite strongly on their intended factor. These loadings ranged from about 0.50 to 0.90. In fact, both measures of search, source and effort, appear to have met the test of convergent validity across both


255

things-directed and people-directed services. Each factor has three to four items with adequately large factor loadings across all three things-directed service encounters and at least two items had large loadings on each factor across the people-directed service encounters. Thus, the large factor loadings, along with the already-discussed Cronbach alpha levels suggests that the items used to measure each dimension of the seven-item scale possess an adequate level of convergent validity across the things-directed services. As noted earlier, the evidence of convergent validity for the peopledirected services is somewhat more tenuous. Discriminant validity

Tables III and IV also provide evidence of discriminant validity. Recall that, for purposes of this study, discriminant validity was assessed by:


(1) inspection of cross-loadings; and (2) inter-factor correlations (Allison, 1978).

Large cross-loadings

Tables III and IV indicate that only two of the items had large crossloadings, and the problems with cross-loadings was only problematic for people-directed services. The item, “I have compared service characteristics among firms that provide this service”, failed the test of discriminant validity, since it loaded quite strongly on both source and effort aspects of external search. One other item, “I talk about this service with other people”, surprisingly, had a large cross-loading for movies. Other than those two items, all of the other items’ cross-loadings were quite small (i.e. smaller than 0.35). Nevertheless, we felt the cross-loadings that are evident in Table IV are sufficient to conclude there are substantive problems with the discriminant validity of our seven-item scale in people-directed service encounters. Further evidence of discriminant validity was also provided by the generally low-to-moderate inter-correlations among the factors, especially for the things-directed service encounters. Indeed, the largest inter-correlation reported in Table III is r = 0.54 for lunch at a fast food restaurant. Even with an observed correlation of r = 0.54, the two dimensions of external search (source and effort) only share about 30 percent of their variance. The intercorrelations reported in Table IV, however, are not quite as encouraging. For example, the correlation among source and effort was r = 0.64 for exercise club, while the other correlations reported in Table IV range from about r = 0.50-0.60. Thus, interpretation of the inter-factor correlations from Tables III and IV appear to yield similar evidence to our previous conclusions regarding discriminant validity from the factor analyses. That is, the seven-item scale’s discriminant validity seems to be quite acceptable for things-directed services, but the evidence of discriminant validity for peopledirected services is, once again, somewhat tenuous. Nomological validity

External search scale

256

Our final empirical assessment of the construct validity of our seven-item external search scale was to investigate how it performed nomologically (Childers, 1986; Schwab, 1980). Table V provides encouraging evidence that our seven-item external search scale’s nomological validity is quite THE JOURNAL OF SERVICES MARKETING, VOL. 13 NO. 3 1999

e c n s r e r o e d f f i n d e v d s e s v o r i e c c r a e P


t n e m e s l v i s o y l v a I n n a n o i t a l e r r e o C m o c n I

n o i t a c u d E

e s e l a c m n e e r r F e e f f i d d n f e o G t e s e l a T M

e c i v r e S

o t d e * * * * * * * * * r * * * * * * * * * * * * * * * * * * * * * * a 7 4 1 6 7 4 3 9 5 4 8 7 p 2 2 4 4 3 4 4 1 2 5 3 3 . . . . . . . . . . . . m 0 0 0 0 0 0 0 0 0 0 0 0 o d c e , 5 v r 6 . e s 3 b s o a e w h o r ) t e e t a z c h n t m a o r s a r u s d f t n a n i r r e e e * * * * * * * * * * * * * * f e * * * * * * * * * * * i e f l 3 0 3 1 5 7 2 7 4 4 9 3 ( b f i 5 3 3 4 1 5 . 2 . . 2 . . 5 . . 1 . . 4 . . 4 . e t o d 0 0 0 0 0 0 0 0 0 0 0 0 c y r i l u s l a o s c s i i h t n b t s i o ; t a s t t e n s l e * t a r * * * e o * * * f n 2 7 9 0 8 9 3 9 9 3 3 5 m f r i 0 0 0 1 3 0 s . 0 . . 1 . . 3 . . 1 . . 3 . . 0 . f o d i 0 0 0 0 0 0 0 0 0 0 0 0 , y 6 – – – – – – – – – – e l r t 0 o n . c a 0 s i c = n f r a i , e n g n i m s i o d y t a e l l v l a e r b c r r 6 1 1 5 6 9 2 4 8 7 6 4 e s i t 0 0 0 1 0 0 0 1 0 0 1 0 b s o . . . . . . . . . . . . o i c t d 0 0 0 0 0 0 0 0 0 0 0 0 a e – – – – – e t s v h t t t o r a n e s h t i s b o s e a e h c d n t , a e e * * e r c a * * r e 6 2 6 3 3 0 9 6 8 4 2 4 e f n 5 7 9 9 3 8 i a . 8 . . 4 . . 3 . . 7 . . 8 . . 2 . b f s 3 3 3 3 3 3 3 4 3 4 3 4 o d t n t n i s a s i e i s m h i t h d n t a e I ; v . 5 3 1 4 1 6 4 9 4 7 4 9 1 r e 6 2 8 3 3 4 . 1 . . 5 . . 0 . . 4 . . 8 . . 2 . 0 e s c 3 4 4 3 3 3 3 4 2 2 3 3 0 . b n r 0 o a t e u a h s n e T i c . e n ) f i a l l c e i a f c r o i s f n t g 6 i n 0 s i . * o 0 * p * - s ; i 1 n e l 0 . v e v 0 e e s l t ( a 6 n t 5 o n . i a 3 t c f a c i f u i o d n h e g c i t s r d n * a n * e a a r ; s e u 5 r o c a 0 r t s . f s s u e e 0 e e c c t r o i r i s a o v v d r r c n t r i s o e e n e a s s e o a e f p c g w d d i e t t f a e r e e s i r e t t b c a c o n e b c f u n t e e g v n l r a u i r a a o c i i r a S ’ t d d u e * t t a s i e s s s e e e e t l e t i e t : a u e l n e t t t n e h s l c c c c c c i c c g i i r r r r r r e t c p e r r r r r r a r r n f r o u u f o n u f o o v o o o i t e u f u u u i e r f a o f f x o f f o m h i o f o o f u o f e o o f e c T L S E R S E L S E P M S E H S E E S E N f o

Table V. Tests of differences and correlation analysis THE JOURNAL OF SERVICES MARKETING, VOL. 13 NO. 3 1999

257

adequate. We selected three variables with which our seven-item scale should not be empirically related: (1) gender; (2) education; and (3) income. Prior research on the relationship between search and education is mixed (Schmidt and Spreng, 1996). However, in this instance, the range of services that we selected are not among those where relationships between external search and education were found. Inspection of Table V indicates that we generally satisfied the assumption of “no statistical significance”, with the exception of haircut. One’s level of search (for both source and effort) appears to differ between men and women. In both instances, women appear to search more than men. The level of search was also empirically correlated with income.


We also selected two variables with which we felt external search should be empirically related: (1) involvement; and (2) perceived difference across vendors.

Performed as expected

Again, these variables (i.e. involvement and perceived differences across vendors) have been shown, both empirically and conceptually, to be related to external search (Schmidt and Spreng, 1996; Zaichkowsky 1985). The last two columns of Table V provide strong evidence that our sevenitem scale performed nomologically as expected. All of the empirical correlations across all of the service contexts were statistically significant with one exception, search effort for movies. The observed correlation between search effort and involvement was only r = 0.17, nonsignificant at the 0.05 level (but significant at 0.10). Therefore, we concluded that there is strong evidence that our seven-item scale performed quite well nomologically, given that most of the empirical relationships (Table V) were as expected. Discussion

This article addresses an issue that is important to both marketing practitioners and academic researchers by developing a multi-item scale to measure consumer external search in a services marketing environment. The scale was developed and purified following the recommendations of Churchill (1979) and Schwab (1980). Moreover, our employed methods are consistent with those used in other studies that developed multi-item scales and assessed their construct validities (see Allison, 1978; Childers, 1986). Our seven-item scale was administered to a sample of adults in a major midwestern city and empirically assessed using exploratory factor analysis, Cronbach alpha, and correlation analysis. The results of the empirical analysis generally support two distinct search activities: (1) source; and (2) effort for things-directed service encounters. The empirical evidence for the construct validity of our seven-item scale is less certain for people-directed 258


services, given the prominence of cross-loadings in the factor structures and rather large inter-factor correlations (Table IV). Contributions

External search activities


Our study provides an initial attempt at empirically validating a scale to measure consumers’ external search activities. The generalizability of the scale’s properties was examined by assessing the validity of our scale across various services, both things-directed and people-directed services (Lovelock, 1983). We found that our seven-item search scale is not invariant across services. Although we obtained a two-factor solution for external search in things-directed services, this was not the case with peopledirected services. More work is required, given the presence of cross loadings and somewhat larger-than-expected inter-correlations between dimensions of external search for the people-directed services. Notwithstanding, the current study can now be used to build our understanding of consumers’ external search in service encounters. This initial effort at developing a scale for search in services marketing demonstrates that there are two aspects of external search, source and effort. Given Murray’s (1991) initial evidence that, at least in service encounters, consumers faced with increased uncertainty increase external search activities, it is especially important that we employ a construct-valid external search instrument which captures the full domain of potential search activities. Limitations

Confirmatory factor analysis

While the current study certainly provides some insight necessary for better understanding the role of consumers’ search in services marketing, this study has a number of limitations. For example, despite the fact that six services were employed across both “things-directed” and “peopledirected” categories, the scale must be administered across other service settings to more fully establish its generalizability. Also, other methods may be used to more fully assess the scale’s construct validity. For example, future research which further refines measures of search may use confirmatory factor analysis (Fornell and Larcker, 1981) or the multi-trait multi-method (Cook and Campbell, 1979) to more rigorously assess the scale’s construct validity. It should be noted that the data used in the current study were obtained from single sources at single points in time. Newman and Lockeman (1975) empirically demonstrated that self-reports of search are deficient when compared to unobtrusive observation techniques. Therefore, obtaining information from other sources (e.g. salespeople, friends, etc.) regarding an individual’s external search activities may be useful in more fully understanding consumer search in services contexts. Also, given the suspect performance of our seven-item scale in people-directed service encounters, additional efforts are needed to refine our scale so that it performs better in those services which directly impact a person. Finally, there may be other aspects of search in a service setting not currently captured by the seven-item scale. Among the other possibilities are internal versus external sources (Beales et al., 1981; Murray, 1991), prepurchase versus ongoing external search (Bloch et al., 1986), specific aspects of the service being sought (Stewart et al., 1989), and modality, such


259

as print versus electronic delivery of non-personal forms of communication (Bunn, 1994), including the Internet. Future research

Additional scale development


While the current study provides an important tool for better understanding search in services marketing, much remains to be done. Although this study provides evidence of the newly-developed seven-item scale’s construct validity, additional scale development is warranted. Recall that for the people-directed services, two of the items did not load on the expected factor, and the inter-correlations between source and effort was relatively high. Thus, additional refinement of the scale for the people-directed services is required. Also, the additional scale refinement is needed to more fully and adequately tap various sources of external search, i.e. marketer controlled, reseller, etc., as suggested by Oshavsky and Wymer (1995). Future research, no doubt, can also be undertaken to tailor the scale to more specific contexts (see Dawes et al., 1991; Stewart et al., 1989).

Managerial implications

This research suggests a number of implications for managers. First, it is clear that the nature of search differs between people-directed services and things-directed services. Specifically, managers should be aware of the differences, such as, consumers tend to be more interested in reading about movies than they would life insurance, automobile repairs, or lunch from a fast food restaurant. This suggests that marketers of movies should devote considerable time and effort to providing information about the movie, reviews, documentaries, etc., in written form.

Many factors taken into account

By contrast, for life insurance, consumers tend to take many factors into account when choosing this service, spend a considerable period of time doing so, but do not tend to talk about the various offerings with their friends and acquaintances. Yet, they are likely to seek advice from other people prior to purchasing the service. This suggests that they talk to industry consultants and salespeople from the respective life insurance firms prior to making their choice. This suggests that marketers of life insurance services should expend considerable time and energy on equipping their sales team so that they are well able to provide relevant information to potential consumers of life insurance. Second, differences were found for search between males and females for one of the people-directed services, haircut. Although this requires further investigation, managers should at least be aware that for haircuts, women tend to search more than men and expend more effort in the search process. This would suggest that marketers need to put considerable effort into providing information about hairstyles, particularly for women. The preliminary findings suggest that a lot of time is put into searching out hairdressers and that female consumers make comparisons between hairdressers. Furthermore, these consumers’ friends play a very important role in the search process and therefore it would seem that hairdressers should use testimonials from existing clients as a means of providing credible information to prospective clients. Furthermore, given the importance of word-of-mouth, care should be taken to ensure that all customers are completely satisfied.

260


Third, given that involvement and search were found to be moderately correlated, managers should identify who the more highly involved customers are, what are their specific characteristics, and for the least involved, what are their characteristics, to see if low involved consumers could be converted into more highly involved consumers. This would be particularly useful for outsuppliers, as outsuppliers want to get more consumers interested in searching for their services with the view to securing these customers for their own.

Emphasize points of difference


Finally, given that the study found that if perceived differences were identified with the service providers, then customers were more likely to search. Given this, for out-suppliers, it would be prudent to emphasize the point(s) of difference between your services and those of your competitors, and to get (potential) customers to question their current service provider. For example, with regard to haircuts, have the customer ask themselves, “Am I getting a ‘good’ cut, a ‘value for money’, a cut that will ‘always look good’ and ‘work for me’ ?” Conversely, if you are an in-supplier you would want to reinforce to your clients that the service that you provide is the best for them. This may be done by having promotional campaigns reinforce that clients are wise to stay with the firm, saying “Aren’t you glad you have an insurance policy with us? … and you are smart if you do”.

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This summ ary has been provided to allow m anagers and execut ives a rapid appreciation of the content of this article. Those w ith a particular interest in the topic covered m ay then read the article in toto t o t a k e advantage of the m ore comprehensive description of the research un dertaken and its results to get the full benefit of the m aterial present


Executive summary and implications for managers and executives The difference between people and things – selling services As services marketers we spend too little time getting to know what makes our customers tick. I do not mean individual customers but the market in general. We rightly focus on the quality of our service and stress the importance of customer care. But we seldom think seriously about how consumers make service purchases. Perhaps this reflects the domination of goods marketing over the development of theory and in the practice of marketing? McColl-Kennedy and Fetter investigate one aspect of the consumer decision-making process – described as a “… primary stage …” – the search for information about the service. We see how services are innately more involving and complicated than goods and, as a result, carry a greater degree of perceived risk. Like Mitra et al., McColl-Kennedy and Fetter see information search as an exercise in reducing perceived purchase risk.

Different kinds of service – different search patterns McColl-Kennedy and Fetter distinguish between services on the basis of their delivery – are they “personal services” like hairdressing or going to the movies or are they related to “things” – life insurance or fast food? This focus differs from that taken by Mitra et al. who stress the complexity of the service and our ability to assess that service before consumption (search, experience and credence services). What McColl-Kennedy and Fetter show is that we decide differently about services delivered to us as people and services relating to our possessions. Indeed, the authors’ seven-point scale does not fully capture the processes of information search in the two types of service. Indeed it appears that “personal services” have a more complicated search process than the authors expected. Even though the method of measurement remains open to debate, marketers can take the step of identifying their service type. In doing so we can see ways to improve the promotion of the service.

Promoting the service directed at “things” Marketers promoting life insurance, fast food and other services not related to the person need to appreciate that impersonal information sources are more important. Not necessarily more important than personal sources of information but more significant than these in comparison with the personal service. Given this situation, we need to provide information that is substantiated and detailed (without crossing over into the realm of incomprehensible small print). For the buyer of, for example, life insurance, such detail is crucial to the prospective buyer’s decision-making process. That buyer looks for information and wishes to discuss that information with others. But the buyer does not want to bore friends with endless details about different insurance options – or maybe lacks confidence in those friends as authoritative sources of opinion. 264


Thus, as McColl-Kennedy and Fetter comment, the marketers of services like life insurance should be “… well able to provide relevant information to potential consumers”. The life insurance sales person needs to be trusted enough for the potential buyer to accept the advice given. If the sales person is seen as of doubtful trustworthiness or the firm is perceived as a whole to be untrustworthy then the consumer will look elsewhere for advice and – given what we have read here – will buy from somebody else.


Promoters of services directed at “things” should emphasise ethical behaviour in sales people, invest in a strong and trusted brand and use advertising to inform as well as communicate the brand. These actions provide the basis on which consumers can develop a view of reliability and honesty suited to the decision-making approach described by McColl-Kennedy and Fetter.

Promoting personal services For personal services, consumers are more reliant on, and more trusting of their friends and relatives. We may not trust Mary to give advice on insurance or unit trusts but we will pay attention to her opinion of a hairdresser, a gym or even a doctor. This means that marketers of personal services need to take account of how word-of-mouth communications affect image and marketing performance. One crucial aspect of the difference between the two types of service lies in the interest of consumers in reading or talking about the services in general. Frankly, we find talking to friends about movies, dress shops and entertainment far more interesting that discussing life insurance or car repairs. Such personal services crop up in the course of ordinary conversation – people will say, “go and see such-and-such a film” without us asking their opinion. Given this situation, marketers of personal services should give greater attention to public relations activity rather than advertising. The film review in the paper carries greater weight than the advertisement for the film, since it gives an independent assessment of the service. When we trust the purveyor of the independent view, it is that rather than partisan information that influences our decision making.

Services marketing – it is the people, stupid The biggest lesson for services marketers from this research is the reminder that successful services marketing relies on us understanding the way in which people relate to the service. We can refer to this as “importance” if you like, but what it really means is that services marketers must understand their customers as people. Traditional quantitative research is insufficient because it provides no depth to understanding the customers and what motivates them. The whole area of services marketing is moving away from the ideas of classical marketing developed for promoting goods. From service quality through relationship marketing to consumer behaviour studies we have become aware that service success depends on how people relate to the service and experience that service once they buy.


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Dimensions of Consumer Search Behavior in Services

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