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Journal of Retailing and Consumer Services 17 (2010) 492–500
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Journal of Retailing and Consumer Services
0969-69
doi:10.1
n Corr
E-m
(E. Brid1 Te
journal homepage: www.elsevier.com/locate/jretconser
Consumer innovativeness: Impact on expectations, perceptions, and choiceamong retail formats
Kendra Fowler n, Eileen Bridges 1
Department of Marketing, Kent State University, PO Box 5190, Kent, OH 44242-0001, USA
a r t i c l e i n f o
Keywords:
Retailing
Service design
Consumer innovativeness
89/$ - see front matter & 2010 Elsevier Ltd. A
016/j.jretconser.2010.08.004
esponding author. Tel.: +330 672 1252; fax:
ail addresses: [email protected] (K. Fowler)
ges).
l.: +330 672 1260; fax: +330 672 5006.
a b s t r a c t
Individual differences in innovativeness may drive consumer expectations and perceptions regarding
retail environments, influencing preferences for particular store formats. This research investigates the
impact of consumer innovativeness on expectations for, and perceptions of, service design elements,
including employee performance, process design, design of physical evidence, and reliability of the
shopping experience. Findings indicate that the majority of consumers expect high performance along
all dimensions and dislike surprising stores, specifically those they perceive as risky. Moreover,
innovative consumers expect even higher levels of store attributes and in fact perceive stores differently
than do less innovative consumers.
& 2010 Elsevier Ltd. All rights reserved.
1. Introduction
Today’s economy continues to make profitable retailingdifficult. According to recent data from the U.S. Census Bureau,retail sales as recently as September 2009 were a dismal 6.4%below the previous year (Advance Monthly Sales for Retail andFood Service September 2009). Although the decline appears to bestabilizing (Advance Monthly Sales for Retail and Food ServiceJanuary 2010), in this volatile climate retailers must battle toattract and retain customers. It becomes vitally important tounderstand how consumers perceive and choose among availableretail formats. Individual differences among consumers can affectexpectations of the store environment (retail or e-tail) and mayalso influence patronage intentions. We examine the expecta-tions, perceptions, and patronage intentions of innovative con-sumers, both to better understand consumers and to makerecommendations to retailers.
Personal characteristics of consumers have been shown toinfluence store perception and choice (Anderson et al., 2008).Characteristics that drive retail patronage include impulsivity(Morrin and Chebat, 2005), self-regulation (Babin and Darden,1995), self-confidence (Hisrich et al., 1972), and self-congruity(Sirgy et al., 2000). Our interest is in consumer innovativeness,which shares antecedents with other drivers of retail patronageincluding need for stimulation, independence in judgment,novelty seeking, and desire for uniqueness (Roehrich, 2004).
ll rights reserved.
+330 672 5006.
There is a rich history of research regarding the impact ofinnovativeness on adoption of goods and especially high-tech goods(for impact on aggregate-level adoption, see e.g., Norton and Bass,1987 or the excellent review by Mahajan et al., 1990; for individual-level approaches, see e.g., Im et al., 2003 or Hirunyawipada andPaswan, 2006). However, in the service literature innovativeness hasreceived inadequate attention. Key exceptions that do relate toservice adoption are offered by Bridges and Ellis (1997), by Flynn andGoldsmith (1993), and by Im et al. (2007).
Although previous research has documented some differencesbetween innovative consumers and their less innovative counter-parts when evaluating both physical and online retail environ-ments (Goldsmith, 2000; Goldsmith et al., 2001), the relationshipbetween consumer innovativeness and retail patronage has notyet been fully examined. We address this gap in the literature byinvestigating the impact of innovativeness on consumer expecta-tions, perceptions, and choice of retail formats.
2. Background and conceptual development
Because we examine the relationships between retail designelements, consumer expectations, perceptions, and store choice,considering the impact of consumer innovativeness, we brieflyreview relevant literature regarding these constructs beforedeveloping our hypotheses.
2.1. Consumer innovativeness
Consumer innovativeness is typically conceptualized as eithera general (e.g. Hirschman, 1980; Im et al., 2007) or domain
Fig. 1. Conceptual model.
K. Fowler, E. Bridges / Journal of Retailing and Consumer Services 17 (2010) 492–500 493
specific personality trait (e.g. Goldsmith et al., 2001; Goldsmithand Hofacker, 1991). In the former case, innovativeness refers to‘‘a generalized unobservable trait that reflects a person’s inher-ently innovative personality, predisposition, and cognitive styleand therefore can be applied to multiple situations’’ (Im et al.,2007, p. 64). However, because we investigate the impact ofinnovativeness in the context of retail formats, the construct isunlikely to carry the same meaning as it does in previous researchfocusing on high-tech products. As Goldsmith and Goldsmith(1996) point out, consumer innovativeness does not often transferacross consumption categories. Therefore, we adopt the latterperspective, which suggests that consumer innovativeness can bedefined as a ‘‘predisposition to learn about and adopt newproducts in a specific domain’’ (Goldsmith and Hofacker, 1991,p. 219). We take this perspective, in part, because domain specificmeasurement of innovativeness has been shown to be a betterpredictor of consumer behavior than more generalized measure-ment of the trait (Roehrich, 2004).
The domain we investigate is the selection of retail format forclothing purchases. Thus, the ‘‘predisposition to learn about andadopt new products’’ refers to products which are various retailformats, so the product studied here is actually a service. Further,because innovators have been shown to shop frequently both inbricks-and-mortar stores and online (Goldsmith and Flynn, 2005),six retail formats, including a website option, are considered.
2.2. Expectations and perceptions
One route by which consumer innovativeness may impactstore choice is through its influence on expectations. We knowthat expectations can affect perceptions of and preferences forservices (Parasuraman et al., 1988); this has been empiricallytested in industries as varied as banking (Donthu and Yoo, 1998)and restaurants (Bridges, 1993). Thus, expectations of retailercharacteristics may drive perceptions and judgments regardingthe appropriateness of a particular store format for a shoppingneed. A handful of studies of retail environments have looked atexpectations regarding focused issues: Gagliano and Hathcote(1994) measured expectations of specialty store quality andGrewal et al. (2003) assessed effects of expected wait times onbuying intentions. No studies, to our knowledge, have examined acomplete range of consumer expectations of the retail environ-ment while measuring how perceptions of and choice amongavailable retail formats depend on individual innovativeness.Thus, this study extends the literature by addressing this topic.
2.3. Shopping situation
In addition to the influence of consumer innovativeness,preferences for where to shop may also be impacted by thesituation; in other words, they may depend on the reason for theshopping trip (Holbrook and Hirschman, 1982). Usage situationinfluences consumer expectations in both goods (Cote et al., 1985)and services (Bridges, 1993; Stayman and Deshpande, 1989), andspecific differences can be observed between hedonic andutilitarian reasons for shopping (Babin et al., 1994). Therefore,we consider the impact of usage situation in examining howconsumer innovativeness influences expectations and preferencesamong both commonly available and innovative new types ofretailers.
2.4. Service design elements
Service designers have available and must consider a broadarray of marketing mix variables. In addition to the traditional
‘‘4 Ps’’, available tactics include human resource policies (espe-cially front-line provider selection, training, and motivation),process design (development of the activities involved in servicedelivery), and design of physical evidence (the environment inwhich the service takes place). These service-specific tactics canbe altered to meet the needs of target customers (Booms andBitner, 1981). The impact of people on the service experience hasbeen empirically tested; for instance, committed relationshipsbetween customer and service provider have been shown toimpact perceptions of service quality (Bove et al., 2009). Serviceprocess research was inspired largely by the work of Shostack(1987), who was among the first to recognize that the consumerexperience is important in strategically positioning a service.Subsequent research assesses the influence of process onconsumer perceptions, including perceived convenience (Berryet al., 2002) and wait time (Weijters et al., 2007).
To assess the influence of the physical environment on theservice experience, Bitner’s (1992) framework is often used as aspringboard because it illustrates how the environment in whichthe service takes place can impact both the consumer and theservice worker. A host of related research expands on Bitner’sinitial framework. For example, empirical studies show that theenvironment in which the service takes place can impactconsumer emotions and consequent loyalty (Lee et al., 2008),especially when the environment and the consumer share somepertinent characteristics such as a cognitive or affective orienta-tion (Morrin and Chebat, 2005). Other research considers theimpact of the environment on the service worker and finds thatthe servicescape can be designed in ways which increase theservice worker’s job satisfaction and commitment (Parish et al.,2008). The framework has even been extended to examine howpersonal characteristics might moderate the effectiveness of theservicescape (Babin and Darden, 1995).
Perceived reliability is also a potent retailer characteristicwhich may be influenced through service design (Furrer et al.,2000). Reliability can be evidenced through consistent positiveservice performance (Parasuraman et al., 1988), and by contrast,consumers may view perceived inconsistency as indicative of arisky place to shop. Roberts and Urban (1988) suggest thatperceived risk depends on uncertainty and inherent variability ofproduct (or service) attributes – and consumers’ uncertaintyabout the shopping experience might influence where they decideto shop. In fact, research indicates that consumers perceive therisk associated with store choice to be greater than that associatedwith selection of specific products or brands (Hisrich et al., 1972).
2.5. Conceptual model
Based on the literature described above, current thought mightbe reflected by the conceptual model in Fig. 1. We utilize thismodel as the basis for our theory development in the next section.
We examine relationships between consumer innovativeness,retail expectations and perceptions, and store choice. We confirmthat reliability should be considered alongside more widelyaccepted service design attributes related to people, process,and physical evidence, both because it is steered by retailersthrough similar tactical decisions and because expectationsregarding reliability can influence consumer judgments of shop-ping environments. Most importantly, we improve understanding
K. Fowler, E. Bridges / Journal of Retailing and Consumer Services 17 (2010) 492–500494
of the impact of consumer innovativeness, by providing evidencethat innovative consumers hold different expectations andperceptions of retail formats than do their less innovativecounterparts.
3. Hypotheses
Customer perceptions of front-line employees, the serviceprocess, the physical environment, and the consistency of theretail encounter are integral to the overall evaluation of a serviceexperience, and reflect on the service provider. Numerous studiesobserve a link between service design elements and consumerevaluations of retail environments (e.g. Babin et al., 2004; Grewalet al., 2003; Kotler, 1974). However, for new or unfamiliar storetypes, consumers possess neither experience from which to drawreference points, nor a prior opportunity to observe reliableperformance; therefore, they may view the provider as risky.Hawes and Lumpkin (1986) studied performance risk across sixdifferent patronage modes, and concluded that perceived risk canvary significantly. Therefore, differences in service design relatedto people, process, physical evidence, and reliability are importantto consumer evaluation of a retail environment.
Customer expectations come into play through their impact onproduct perception and choice. For instance, consumer expecta-tions influence both price perception and choice of consumerpackaged goods (Kalwani et al., 1990), market share of high-techproducts (Bridges et al., 1995), perceived characteristics ofrestaurants (Bridges, 1993), and in combination with performanceuncertainty, theoretical likelihood of purchase (Bordley, 2001).Customer expectations can be viewed as a distribution, with boththe mean and variance affecting perceived quality and preference(Rust et al., 1999). Because this variance is related to customerperceptions of consistency or reliability, these findings providefurther support for including perceived store reliability in thecurrent research.
Some of the above-mentioned researchers used predictivemodels to estimate customer expectations, whereas others mea-sured them along attitude scales. The latter method is used in theSERVQUAL model (Parasuraman et al., 1988), and is also adopted inthe present research. This requires that customers be asked toprovide their expectations along the same attitude scales thatmeasure quality of service attributes. Then, gaps can be calculatedas differences between perceived and expected service attributelevels, allowing assessment of where a particular service might fallshort. Our first hypothesis is included to demonstrate consistencywith previous research findings:
H1a. Consumers judge retail environments on the basis of front-line service providers, the service process, physical evidence, andperformance reliability. Thus, preferred environments offer higherlevels of these constructs.
H1b. Consumers compare their perceptions of retail environ-ments to expectations in developing preferences. Thus, preferredenvironments have a greater positive difference between percep-tions and expectations.
Customer expectations of a retail store might depend on thesituation that drives the perceived need to shop. Babin andDarden (1995) suggest that consumers engaged in hedonicpursuits are more susceptible to contextual influences andconsequently evaluate shopping environments along differentcriteria than do shoppers driven by more utilitarian objectives.Michon et al. (2007) build on this research, finding that innovativeshoppers respond more strongly to retailer efforts to createfunctional improvements than to efforts to increase hedonic
appeal. Perhaps this occurs because these shoppers selectenvironments already offering high levels of hedonic attributes.The impact of situational expectations has also been observed forrestaurants (Bridges, 1993; Stayman and Deshpande, 1989), andtherefore may apply to other services. This potential impact ofusage situation on customer expectations of retailers is addressedin our second hypothesis:
H2. Consumer expectations regarding retailer characteristicsdepend on the planned shopping situation. Shoppers engagedin hedonic pursuits expect higher levels of physical evidence, inorder to create the desired ambience, than do those engaged inutilitarian pursuits.
As noted above, personal characteristics of consumers candrive retail expectations and preferences. For instance, moreinnovative consumers expect online shopping to be fun, fast, andinexpensive, expectations which are not shared by less innovativeconsumers (Goldsmith, 2000). Therefore, innovativeness may leadto increased expectations regarding various elements of the retailshopping environment. Our third hypothesis relates to thesedifferences in expectations:
H3. More innovative consumers expect higher levels of physicalevidence, process, front line service, and reliability than do lessinnovative consumers.
Expectations regarding service attributes have been found toinfluence perceptions, such that consumer perceptions tend toassimilate to expectations (Bridges, 1993; Iglesias, 2004). Further,Bridges finds that this occurs to a greater degree for servicedimensions that consumers tend to consider less important. Thus,because innovativeness may influence consumer expectations, itmay also impact perceptions of retail formats. Greater impact isanticipated for less important dimensions. Therefore, we hy-pothesize:
H4. Compared to less innovative consumers, more innovativeconsumers perceive stores as offering higher levels of physicalevidence, process, front line service, and reliability.
We anticipate that innovative consumers expect and perceivehigher levels of physical evidence, process, front line service, andreliability than do less innovative consumers (H3 and H4).Therefore, we further hypothesize that their preferences forvarious store formats reflect higher levels of store attributes thando those of less innovative consumers.
H5. More innovative consumers prefer store formats offeringhigher levels of performance in terms of physical evidence,process, front line service, and reliability than do less innovativeconsumers.
We next develop our methodology and explain how thesehypotheses are tested.
4. Methodology
Our goal was to test how consumer innovativeness influencesstore expectations, perceptions of store design elements (physicalevidence, process, front-line providers, and reliability), and theresulting preferences for retail modes, among a range of storetypes. The hypotheses were tested in a population of under-graduate students: although some may criticize the use ofstudents as respondents, the sample was appropriate for thisstudy because young adults are among the primary target marketfor the retail formats under consideration. The survey instrument
K. Fowler, E. Bridges / Journal of Retailing and Consumer Services 17 (2010) 492–500 495
was administered online with respondents receiving course creditfor their participation.
Table 1Innovativeness/market maven combined scale items.
I like introducing new brands and products to my friends.
I like helping people by providing them with information about many kinds of
products.
People ask me for information about products, places to shop, or sales.
If someone asked where to get the best buy on several types of products,
I could tell him or her where to shop.
My friends think of me as a good source of information when it comes to new
products.
Think about a person who has information about a variety of products and
likes to share this information with others. This person knows about new
products, sales, stores, and so on, but does not necessarily feel he or she is an
expert on one particular product. How well would you say this description
fits you?
In general, I am the last in my circle of friends to know the names of the latest
products on the market (R).
Compared to friends, I do little shopping (R).
In general, I am among the last in my circle of friends to purchase a new
product (R).
I know more about new products before other people do.
Notes: (R) indicates reverse coding; Cronbach’s alpha 0.85.
4.1. Sample and survey instrument
Data were collected in several sections of an introductorymarketing course; a total of 421 students were eligible and 257participated. Two respondents were removed due to incompleteresponses, making the final response rate 61%. Upon accessing thesurvey, respondents received a situational motivation for shop-ping, as they were randomly assigned to view one of two possiblescenarios, designed to be either hedonic or utilitarian in nature.
Two separate scenarios were used in the study to ensure that arange of store expectations would be collected. The first scenariopresented the respondents with a hedonic situation: ‘‘Unexpect-edly, one of your best friends calls and asks you to meet for theafternoon to spend some time together shopping. You haven’tbeen able to see your friend in a while and you always have agood time when you’re together. You have the afternoon free, soyou decide to go.’’ The second, utilitarian, scenario presented therespondent with a specific need: ‘‘You have been invited to athemed party. You need to wear something that fits the theme.The party is very soon and nothing in your closet seems right. Youdecide to go shopping to find something to wear to the party.’’
Of the 255 respondents, 116 were assigned to the hedonicscenario and 139 were assigned to the utilitarian scenario. Apretest among 253 different undergraduate students assessed thescenarios for realism. The same pretest was also used to evaluatea total of 26 five-point Likert scale items for use in measuringstore expectations and perceptions. The resulting data were factoranalyzed using principal components analysis, and two items thatloaded on more than one factor were removed. The reportedstudy, therefore, included only 24 items.
After reading the assigned scenario, participants were asked torespond to the scale items regarding their expectations forshopping. Respondents were told to imagine a store where theymight shop given the scenario presented and to indicate theirexpectations regarding store attributes along the 24 scale items.Following this, respondents were asked to indicate their percep-tions of six retail formats along the same 24 items.
The six retail formats were chosen to represent a full range ofpossible shopping options and to achieve differences in perceivedstore characteristics. In particular, it was desirable to include avery innovative, edgy store format. Although some shoppers mayconsider e-retailing innovative and possibly unreliable, accep-tance of online shopping is increasing rapidly (E-Stats, 2009). Forthis reason, we selected a more unusual, unfamiliar store type,which consumers might view as unreliable: the ‘‘pop-up,’’ or shortterm storefront. Pop-up stores are a relatively new format, asnoted recently in Business Week (Fine, 2009), and we anticipatedthey would be viewed as highly risky. Pop-ups appear seeminglyout of nowhere and are designed to quickly capture both attentionand shopping dollars. Most commonly used to showcase newlines of merchandise and generate excitement, they are char-acterized by very short life spans, some as little as three days.
Store formats were briefly described, and were presented torespondents in random order to eliminate order bias. Specifically,thrift stores were described as selling used merchandise, depart-ment stores as selling a large assortment of new clothing, shoes,and housewares, discount stores as selling new basic merchandiseincluding clothing, online stores as allowing customers to selectclothing and place an order for home delivery, and specialty storesas selling a limited assortment of clothing and accessories.Because respondents were unlikely to be familiar with the sixthretail format, the pop-up store, a more detailed description was
offered: ‘‘temporarily located in a previously vacant storefrontand unaffiliated with any major chain store, the store is scheduledto be open for only two weeks.’’
Survey items were drawn from three established scales: (1) theRetail Service Quality Scale (Dabholkar et al., 1996), (2) theConsumer Image of Retail Stores Scale (Dickson and Albaum,1977), and (3) the Perceived Risk Scale (Kaplan et al., 1974). Thelatter was supplemented with additional items pertaining touncertainty and reliability. Only items that were applicable to allsix store formats were included. After completing these scales,participants were asked to choose among the six retail formats byranking each store format in order of their preference, given thesituation presented.
Near the end of the survey, participants were asked forinformation about their personal characteristics. In particular,they responded to a series of Likert-scaled items concerning theirpropensity to engage in innovative consumer behavior. Innova-tiveness items were drawn from the Market Maven Scale (Feickand Price, 1987) as well as the Domain Specific InnovativenessScale (Goldsmith and Hofacker, 1991). The literature suggests thatmarket mavens and innovative consumers have many similarities,and that the constructs are positively correlated (Goldsmith et al.,2003). Analysis confirmed that the items could be combined intoa single construct (Cronbach’s alpha 0.85) (see Table 1). Therefore,the final study includes ten items that measure consumerpropensity to purchase new products (or services) relativelyearlier than and to provide shopping information to otherconsumers.
4.2. Data analysis and results
Because our study concerns the potential influence onpreference of the gap between store perceptions and shopperexpectations (H1b), a common perceptual field was necessary inwhich to compare the responses. Therefore, exploratory factoranalysis was conducted using principal components analysis toreduce the data for expectations and store evaluations (Green,1978). Three factors with eigenvalues exceeding 1.0 wereextracted, explaining 62% of the variance (see Table 2). The firstfactor includes eight items related to employee performance,describing the employees’ ability to handle customer transactionsquickly and courteously with minimal error. Physical evidenceand service process items did not emerge as separate dimensions,but combined to form the second factor, which we term
K. Fowler, E. Bridges / Journal of Retailing and Consumer Services 17 (2010) 492–500496
‘‘atmosphere.’’ These eight items describe the ambience andlayout of the store and its merchandise, and the ease with whichthe shopping task can be accomplished. The third factor includeseight items describing store reliability, or the consumer’suncertainty about what will be provided. The resulting factor
Table 2Results of exploratory factor analysis.
Factor
loading
Employee performanceEmployees are able to handle customer complaints directly and
immediately.
0.80
The behavior of employees instills confidence in customers. 0.73
Employees give prompt service to customers. 0.71
Employees are consistently courteous with customers. 0.68
Employee performs the service right the first time. 0.67
Store insists on error-free sales transactions and records. 0.65
Employee gives customers individual attention. 0.61
Store willingly handles returns and exchanges. 0.59
Store atmosphereStore has the latest, most up-to-date products and services. 0.79
Store offers high quality merchandise. 0.76
Store has modern-looking equipment, fixtures, and displays. 0.74
Store is attractive. 0.67
Store is worth talking about. 0.64
Store layout makes it easy for customers to move around and
shop.
0.58
Store is messy. (R) �0.58
Store layout makes it easy for customers to find what they
need.
0.51
Reliability (R)Customers don’t feel safe in their transactions. 0.77
Store is not a secure place to purchase items. 0.76
Something will go wrong. 0.74
Store is unpleasant to shop in. 0.66
Store is dull. 0.63
Employees lack the knowledge to answer customers’ questions. 0.59
The physical facilities are not visually appealing 0.57
The checkout is slow. 0.55
Notes: Extraction method for store dimensions was principal component analysis
with varimax rotation; eigenvalues were 11.616 (employee performance), 1.895
(store atmosphere), and 1.404 (reliability); total variance explained was 62%. (R)
indicates reverse coding.
Hig
h
Discount
Empl
oyee
Per
form
ance
ThriftPop Up
Online
Low
ReliaLow
Fig. 2. Perceived employee perf
scores were used to construct perceptual maps visually position-ing the retail formats along the key dimensions identified (Dillonet al., 1985).
Respondents provided expectations for the shopping excursionas well as data on all six store formats, so seven sets of threefactor scores were computed for each respondent. The factorscores for perceptions of each store type were subjected to meancomparison using ANOVA. Significant differences between thevarious retail formats were observed along all three dimensions,including employee performance (F¼24.15, po0.001), storeatmosphere (F¼153.75, po0.001), and reliability (F¼24.05,po0.001). This indicates that respondents are faced with arealistic choice situation.
Multiple comparison tests, using Dunnett’s C, were conductedon the factor scores for shopper expectations and perceptions ofeach store format, and mean scores were plotted on a commonperceptual field. Consumer perceptions of most store types alongthe dimension of employee performance were not dissimilar,although department and specialty stores scored significantlyhigher on this dimension than did the other store types (seeFig. 2). In terms of atmosphere, each store format was viewed asunique; with online retailers, specialty stores, and departmentstores scoring higher than other retail formats (see Fig. 3). Whencompared along the reliability dimension, the stores are notviewed as distinctly different, but most are clustered near themiddle of the map (see Figs. 2 and 3). Pop-ups are seen as themost risky; thrift stores are also viewed as risky.
The perceptual maps are helpful in visualizing the gapsbetween shopper expectations and store perceptions. Specialtystore perceptions are most closely aligned with shopper expecta-tions, as they tend to offer the expected high levels of employeeperformance, superior atmosphere, and reliability.
Following this visual understanding of shoppers’ expectationsand perceptions regarding the various retail formats, we testedour hypotheses. First, we used a series of preference regressions(Hauser and Koppelman, 1979) to assess the relative influence ofeach store dimension (factor score) on consumer preference. Thisis done by setting the shoppers’ rank ordering of the store formatsas the dependent variable. Because participants evaluated all sixstore formats, potential within-subject correlation was examinedby clustering the standard errors (Wooldridge, 2003). Thisadditional analysis did not lead to any changes in outcomes.
Specialty
ExpectationsDepartment
bility High
ormance� store reliability.
Hig
h
OnlineExpectationsSpecialtySpecialty
Department
Pop Up
Stor
e A
tmos
pher
e
DiscountDiscount
ThriftThrift
Low
Low HighReliability
Fig. 3. Perceived store atmosphere� store reliability.
Table 3Results of base and full model preference regressions.
Base model Unstandardized coefficients t p-value Collinearity statistic
Variable B Std. error VIF
Constant 3.57 0.02 172.43 0.00
Employee performance 0.24 0.04 6.19 0.00 1.00
Atmosphere 0.42 0.05 9.23 0.00 1.00
Reliability 0.24 0.04 6.18 0.00 1.00
Full Model Unstandardized coefficients t p-value Collinearity statistic
Variable B Std. error VIF
Constant 3.70 0.03 140.91 0.00
Employee performance 0.13 0.03 4.15 0.00 2.09
Atmosphere 0.32 0.05 6.96 0.00 2.77
Reliability 0.17 0.03 4.82 0.00 1.91
Employee performance gap 0.14 0.03 4.95 0.00 2.11
Atmosphere gap 0.11 0.02 4.77 0.00 2.79
Reliability gap 0.10 0.03 3.75 0.00 1.93
Notes: R2¼0.10; F¼38.27, po0.001.
Notes: R2¼0.11; F¼21.36, po0.001.
K. Fowler, E. Bridges / Journal of Retailing and Consumer Services 17 (2010) 492–500 497
The first preference regression tests H1a, which posits thatconsumers form perceptions of store attributes and use them intheir evaluations of retailers. The regression equation thereforedefines preference as a function of the factor scores representingperceptions of employee performance, store atmosphere, andreliability
Rank¼ aþb1Pþb2Aþb3Rþe ð1Þ
where Rank is the retail format’s rank order as reported by theshopper; P the employee performance factor score; A the atmo-sphere factor score and R the reliability factor score.
The results, provided in Table 3, have a significant omnibustest result (F¼38.27, po0.001) and show strong support for H1a.(At the individual variable level, single-tailed t-tests were used, toreflect hypothesized directions of effects.) Next, we extended themodel to test H1b, by including the impact of expectations alongeach of the three dimensions. This was done by calculating thegap between each shopper’s expectations and store perceptions(for all six store types), and using these differences as indepen-
dent variables. The regression equation therefore definespreference as a function of perceptions of employee performance,atmosphere, and reliability, and gaps along the same threedimensions:
Rank¼ aþb1Pþb2PGapþb3Aþb4AGapþb5Rþb6RGapþe ð2Þ
where PGap is the gap between the performance factor score andexpectations; AGap the gap between the atmosphere factor scoreand expectations; RGap the gap between the reliability factorscore and expectations.
The findings are significant, for the omnibus test (F¼21.36,po0.001) and at the individual variable level, indicating thatstore perceptions as well as the gaps between perceptions andexpectations significantly impact consumer preference. Thus,these results provide strong support for H1b. The studiedvariables explain 11% of the variance in the preference scores,with perceptions of store atmosphere and reliability having thegreatest impact. To appraise any potential issues due to multi-collinearity between store perceptions and performance gaps,
K. Fowler, E. Bridges / Journal of Retailing and Consumer Services 17 (2010) 492–500498
appropriate diagnostic tests were run. The maximum reached bythe condition index was 3.68 and the VIF values were well withinthe acceptable ranges recommended by Hair et al. (2006). Detailsare provided in Table 3.
After confirming that preference is influenced by both shopperperceptions of store formats and the gaps between perceptionsand expectations, we went on to consider the impact of the gapson store choice. Comparing the full model (2) to the base model(1), by placing both equations in a nested model and calculatingthe change in R2, we confirmed that including the gap variablesmade a significant contribution to the explanation of store choice(F change¼3.985, p¼0.008).
To test H2, which proposes that the shopping situationcan influence consumer expectations, we examined differencesbetween the responses obtained from consumers presented withhedonic versus utilitarian situations. Factor scores representingstore expectations for those assigned a hedonic situation werecompared to those for a utilitarian situation via mean comparisonusing ANOVA. Usage situation was found to have a significanteffect on expectations regarding atmosphere (F¼60.78, po0.001) –respondents assigned to the hedonic situation expressed expecta-tions of higher levels of atmospherics. Interestingly, the groupdifferences in factor scores for both the employee and reliabilitydimensions were not significant (F¼2.33, p¼0.13; F¼0.18,p¼0.67). Therefore, differences in expectations between thehedonic and utilitarian shopping groups are observed, but only forstore atmospherics. (The two groups have similar expectations foremployees and for store reliability.) Because differences areobserved for atmospherics, H2 is supported.
Next, we examined the impact of consumer innovativeness onexpectations, to test H3. The ten Likert-scaled items for innovative-ness were summed for each consumer and the results, ranging from13 to 49, adequately covered the possible range of 10–50. Theresulting distribution was approximately normal with a mean of36.11 (standard deviation¼6.37; kurtosis¼0.53; skewness¼�0.58).To test the impact of innovativeness on expectations, a series of threelinear regressions were run. Expectations for the store dimensions(employee performance, atmospherics, and reliability) served asdependent variables, and the summed innovativeness scale providedthe independent variable. The results, in Table 4, are significant foremployee performance (t¼3.04, p¼0.001), atmospherics (t¼10.93,po0.001), and reliability (t¼6.16, po0.001) and thus show strongsupport for H3.
We next examine the impact of innovativeness on storeperceptions. H4 hypothesizes that consumers perceive stores in amanner consistent with their expectations; in other words, moreinnovative consumers perceive stores as offering higher levels of allthree store dimensions. A second series of linear regressionequations were run with the perceptions of the stores (the factor
Table 4Impact of consumer innovativeness on expectations and perceptions.
Expectations regarding: Unstandardized coefficients
B
Employee performance 0.010
Atmosphere 0.030
Reliability 0.020
Perceptions regarding: Unstandardized coefficients
B
Employee performance 0.007
Atmosphere 0.002
Reliability 0.023
scores pertaining to employee performance, atmospherics, andreliability) as the dependent variables and the summed innova-tiveness score as the independent variable. Results, provided inTable 4, are significant for employee performance (t¼1.72,p¼0.043), and reliability (t¼5.69, p¼o0.001), but are notsignificant for atmospherics (t¼0.39, p¼0.350). Therefore, H4was partially supported. The insignificant result for atmosphericssuggests that this dimension is most important to consumers, asprevious research indicates that perceptions along more importantdimensions are less likely to be assimilated toward expectations.
Finally, to investigate the impact of innovativeness on storechoice, we examined the correlations between perceptions ofselected store formats and innovativeness. The first choice of eachrespondent was isolated and bivariate correlations were runbetween the innovativeness score and perceptions of each of thechosen store dimensions. The results indicate that more innova-tiveness is positively correlated with improved perceptions ofemployee performance (r¼0.16, p¼0.006) and atmospherics(r¼0.12, p¼0.029), but not reliability (r¼0.06, p¼0.171). Thus,innovativeness influences two of the three dimensions of storesthat could influence choice, and we find partial support for H5.
5. Discussion and conclusions
Our findings contribute to the literature in several ways,offering both theoretical and managerial implications. Perhapsour most interesting findings are those related to innovativeconsumers and how they select retail venues – although they tendto like trendy store designs, reflected in their preferences forhigher levels of atmospherics than less innovative consumers –they are even more concerned than less innovative consumersabout shopping in stores they perceive as reliable. Therefore,retail managers who wish to attract more innovative consumersmust find ways to reduce perceptions of risk while preserving thesense of an interesting environment in which to shop. This mightbe done through use of attractive, easy-to-navigate store layout,high quality, up-to-date merchandise, and modern displays.
Our results extend previous research outcomes demonstratingthat consumer expectations, store design features, and perceivedreliability jointly contribute to choice. Whereas previous researchconsiders the impact of these elements on choice of a specificstore, we broaden the scope to consider the impact whenchoosing among store formats. Specific results related to ourhypotheses include strong support for effects of consumerperceptions of crucial retail design dimensions of employeeperformance, service process, and physical evidence on storepreference. Our findings are also consistent with those of Kayandeet al. (2007), who suggest that mismatched attribute combina-
t p-value
Std. error
0.003 3.041 0.001
0.003 10.925 0.000
0.003 6.156 0.000
t p-value
Std. error
0.004 1.719 0.043
0.004 0.386 0.350
0.004 5.685 0.000
K. Fowler, E. Bridges / Journal of Retailing and Consumer Services 17 (2010) 492–500 499
tions may increase perceptions of risk; we observe that storechoice is directly related to perceived reliability associated witheach retail format. Together the traditional service designelements (people, process, and physical evidence) and theperceived reliability of the store explain 11% of the variance inchoice. This is substantial considering that we did not includesuch important store features as brand name, merchandiseselection, locational convenience, and other marketing mixelements (e.g., price and advertising), which would certainly havean impact but were outside the scope of this study.
We also observe that, when given a specific shopping task,consumers form expectations for store design dimensions. Theseexpectations are found to impact both store perception andchoice. Further, our results suggest that store expectations canvary depending on the usage situation for which the shopping isbeing done, but only along the atmospherics dimension. Inparticular, shoppers engaged in hedonic pursuits expect storesto provide higher levels of atmospheric attributes than doshoppers focused on functional outcomes. It is important forretailers to manage shoppers’ expectations, as they impact bothperceptions of store attributes and consumer choices of where toshop. To reduce gaps between consumer perceptions andexpectations, retailers should avoid either over-promising orunder-promising in marketing communications.
Our findings also clarify how individual differences in innova-tiveness impact consumer expectations, perceptions of, andchoice among, retail formats. We observe that increasingconsumer innovativeness leads to higher expectations regardingstore atmosphere, which in our study combined elements relatingto the service process and physical evidence. We also find thatmore innovative consumers expect retailers to provide morereliable, less risky, service than do their less innovative counter-parts. This finding is interesting, because it suggests that risktolerance is lower among more innovative consumers. Perhapsthese individuals are comfortable taking on increased purchaserisk when they are in an environment that indicates other risksare reduced, thereby balancing their total risk (Thaler, 1985.)
Regarding perceptions, we find that more innovative consumersgenerally perceive stores as offering more reliable service andhigher levels of employee performance, in line with their greaterexpectations. However, we do not find a difference in perceptionsof atmospherics between more and less innovative consumers. Thismay be due to the importance of store atmosphere to the consumerchoice, as mentioned earlier. Alternatively, the lack of assimilationto expectations may be because atmosphere is the most tangibledimension associated with a particular store format, and thereforeis more fixed in the consumer’s mind. Reliability and employeeperformance, on the other hand, are not always easily observed, soconsumers unable to verify actual performance along thesedimensions may find it easier to assume the store performs in amanner consistent with their expectations.
One limitation of this research is that store formats wereselected to be consistent with choices typical of the young adulttarget market that we studied. Thus, although a full rangeof fashion shopping alternatives was identified, our findingsmay not be applicable to other types of retail establishmentsfor which young adults are not a primary target market, such ashome improvement or home furnishing stores. Further, whereasstore design elements and perceived reliability are importantdeterminants of shopping venue selection (explaining 11% of thevariance in choice), there are other drivers that we did notconsider, as noted above, that could be included in futureresearch. Finally, further examination of the dimensions identifiedwould be useful: in particular, we would like to refine the scalesand test them for their external validity in different populationsor service settings.
In conclusion, we draw together several elements of a retailshopping trip that have not been considered previously withinone study. We include the shopping situation (hedonic orfunctional motivation), consumer innovativeness, shopper ex-pectations, perceptions of store design elements, and the gapbetween perceptions and expectations in predicting store pre-ferences. Strong support is obtained for Hypotheses 1a and 1b,confirming the importance of consumer perceptions of storedesign elements and the additional contribution made byconsidering consumer expectations in explaining store choice.
Partial support for Hypotheses 2 and 3 indicates that usagesituation as well as individual consumer innovativeness canimpact expectations of retail venues under some conditions. Inparticular, consumers engaged in hedonic shopping tend toexpect higher levels of store atmosphere than do utilitarianshoppers, probably because atmosphere is important in creatingthe pleasurable ambiance desired in a hedonic situation. Thisfinding may be particularly important to retailers consideringopening pop-up outlets to showcase new product lines andgenerate consumer interest, as it suggests that retailers mustmake certain that they are providing enticing servicescapes toappeal to those shoppers pursuing hedonic experiences.
When positioned to appeal to more innovative shoppers,stores must invest in both atmosphere and reliability, asinnovative consumers expect higher levels of both designelements. Thus, store managers must consider the situationalmotivations to which they wish to appeal, as well as whether theywish to focus on more innovative early adopters of fashion itemsor larger groups of mass-market shoppers who tend to adoptlater. These management decisions ultimately affect the impor-tance attached to the various service design elements and thetactics selected to appeal to the targeted group of consumers.
Acknowledgements
The authors wish to express their appreciation to Dena Haleand Mark Rosenbaum for their helpful comments and sugges-tions; they also wish to thank the Editor, Professor HarryTimmermans, and three anonymous reviewers for thoughtfulinput during the review process.
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