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Consumer product search and purchase behaviourusing various retail channels: the role of perceivedretail usefulnessJihyun Kim1 and Hyun-Hwa Lee2

1Department of Apparel, Housing, and Resource Management, Virginia Polytechnic Institute and State University, Blacksburg, VA, USA2School of Family and Consumer Sciences, Bowling Green State University, Bowling Green, OH, USA

Keywords

Customer satisfaction, multi-channel retailing,perceived retail usefulness, product search,purchase behaviour.

Correspondence

Jihyun Kim, 111 Wallace Hall, VirginiaPolytechnic Institute and State University,Blacksburg, VA 24061, USA.E-mail: [email protected]

doi: 10.1111/j.1470-6431.2008.00689.x

AbstractThe purpose of this study was to examine the influences of consumers’ perceptions of retailusefulness for product information search and their previous purchase satisfaction on theirfrequencies of product information search and product purchase behaviours for apparelproducts. These relationships were investigated in five retail settings – Internet shopping,catalogue shopping, television shopping, local retail shopping, and non-local retail shop-ping. One hundred seventy-six students in a US Midwestern university provided usableresponses. The results of causal model analyses showed that the proposed model fits thedata well for all five retail channels. Consumers who perceived a certain retail channelmore useful for product information search searched for product information more fre-quently via that retail channel, and purchased products more often via that retail channel.Consumers who were more satisfied with apparel purchases from a retail channel pur-chased the products more frequently via that retail channel. Theoretical and managerialimplications are discussed.

IntroductionThe introduction of the Internet as a new type of non-store retailchannel expanded the horizon of the retailing environment in thelate 1990s. It is not only a great addition to the previously availablenon-store retail channels such as catalogue and television shop-ping, but also a very important addition to traditional ways ofpromoting product information and attracting non-store-basedtransactions by adopting multi-channel retail strategies. Multi-channel retail strategies provide the company with a competitiveedge as the firm operates two or more retail channels to distributeits products and/or services to the customers. In a multi-channelretail context, choosing a more efficient retail channel for shop-ping might be the greatest interest of the consumers. Multi-channel retailers usually generate greater revenues than singlechannel retail operators (DoubleClick, 2004). Retailers have rec-ognized that operating various formats of retail channels allowsthem to embrace a broader range of customers (Payne, 2004) aswell as to build more interactive consumer relationships throughoffering information, products and customer supports via two ormore corresponding channels (Rangaswamy and Van Bruggen,2005).

Today’s retail environment provides more options to consumersin collecting information and purchasing the merchandise not only

from one company who operates multi-channels but also from thevarious retail channels operated by different companies. This retailcontext provides customers with convenience and freedom todecide when, where and how to shop (Jensen et al., 2003; Gordon,2005). Consumers utilize some combination of various retail chan-nels (i.e. catalogues, the Internet and bricks-and-mortar stores) tosearch for product information and make product purchases. Theseshoppers are more involved with fashion, more fashion innovativeand Internet technology savvy (Goldsmith and Flynn, 2005). Theypurchase more frequently and spend more money than single ordual channel customers (Dholakia et al., 2005; Kumar andVenkatesan, 2005; Rangaswamy and Van Bruggen, 2005; Shankarand Winer, 2005). This fact is also confirmed by industry tradefindings (DoubleClick, 2004). Moreover, these multi-channelshoppers tend to be more satisfied with the retailer and stay loyalto the retailer in the long run (Freed, 2005).

As various retail channels are provided, consumers can choosedifferent retail formats compared with the single retail channelcontext, and they can easily and frequently use different channelsat different stages of their shopping. Consumers can gather infor-mation about products from non-store channels (the Internet, cata-logue and/or television), and decide to purchase products fromeither non-store or store-based retail channels. For instance, it maybe perceived that searching for product information on the Internet

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International Journal of Consumer Studies 32 (2008) 619–627 © The Authors

Journal compilation © 2008 Blackwell Publishing Ltd

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mailto:[email protected]

is much easier and faster than doing so at bricks-and-mortar stores(Balasubramanian et al., 2005; Van Baal and Dach, 2005). There-fore, customers can collect product information, such as the priceand style of the product, using the Internet and then they maymake a purchase at bricks-and-mortar stores (Jensen et al.,2003; Balasubramanian et al., 2005). In turn, they may returnthe products in stores or mail it back to the retailer upon theirconvenience.

The characteristics of both consumers and products play sig-nificant roles in the consumers’ channel choices and usage ofcertain channels or combinations of several channels (Dholakiaet al., 2005). Online shoppers are more inclined to shop acrossthe various channels (Kumar and Venkatesan, 2005), and multi-channel consumers exhibited strong loyalty to the retailers bymaking repeat purchases (Dholakia et al., 2005; Kumar and Ven-katesan, 2005). In addition, product characteristics are very criti-cal when choosing a retail channel. Consumers assign morevalue on store-based retailing for purchasing experiential prod-ucts (i.e. clothing), where consumers would need to examine theproduct in person before making purchases (Balasubramanianet al., 2005). Moreover, consumers find that bricks-and-mortarchannels are more useful to acquire items they need right awayas bricks-and-mortar channels yield a greater ‘possession value’and instant gratification of acquiring the product immediately(Noble et al., 2005). Pookulangara et al. (2003) found thatshopping benefits (i.e. convenience/variety, value/service, secu-rity and product assortment) and shopping costs significantlyinfluence the consumers’ channel choice behaviours and theirpurchase intentions using multi-channel retailing. They (Pooku-langara et al., 2003) also found that merchandise assortment isthe key to increase consumer product purchases using all threeretail channels including bricks-and-mortar, catalogues and theInternet.

Researchers noted that multi-channel retailers need more infor-mation on their target market profiles and shopping behaviours,which will significantly impact their business performance(Rangaswamy and Van Bruggen, 2005; Neslin et al., 2006).Empirical research on multi-channel shoppers’ information searchand purchase behaviour using various retail channels is verylimited and there is much to be explained.

Although the benefits of the multi-channels have been acknowl-edged by scholars and market researchers, the applications of itsmarketing practice exist in various formats. It can be used by thenational brands to increase market penetration and can be adoptedby local retailers, with their distinctive characteristics comparedwith the national retailers. However, there has been little researchabout consumers’ cross-shopping behaviours in the various chan-nels available in the current retail context. Further work is particu-larly needed to examine consumers’ perceptions and usage ofvarious retail channels, which would be beneficial in the potentialmulti-channel context in the future. The purpose of this study is toexplain the consumer information search and purchase behavioursin using various retail channels. The roles were investigated ofperceived retail usefulness for product information search andsatisfaction with previous purchases of apparel products to explainconsumers’ actual product information search and actual purchasebehaviours in five different retail settings – Internet shopping,catalogue shopping, television shopping, local retail shopping andnon-local retail shopping.

Literature review

Influences of perceived retail usefulness onconsumer behaviour

Perceived usefulness originates from the technology acceptancemodel (TAM) (Davis et al., 1989). Perceived usefulness of tech-nology and perceived ease of use of technology are two majorantecedents explaining the individual’s adoption of informationtechnology for job purposes (Davis et al., 1989). Perceived use-fulness is defined as ‘the degree to which a person believes thatusing a particular system would enhance his or her job perfor-mance’ in TAM (Davis et al., 1989, p. 320). As one of the con-structs of TAM, it has been one of the critical antecedents ofpredicting the consumers’ intentions to use the information tech-nology field. Researchers have successfully applied this concept,perceived usefulness, in a web site use setting (Teo et al., 1999;Moon and Kim, 2001) and online shopping (Lin and Lu, 2000;Childers et al., 2001; Chen et al., 2002b; Koufaris, 2002; O’Cassand Fenech, 2003; Chen and Tan, 2004; Vijayasarathy, 2004; Leeet al., 2006).

The Internet helps consumers to search for products/servicesand product/retailer information easily, anywhere and any time(Chen et al., 2002a). Perceived usefulness of a multi-channelretailer would increase when an Internet retail site offers in-depthinformation about product attributes (e.g. price, brand, quality,materials) as well as customer services (Chen et al., 2002a;Ratchford et al., 2003). The product and service information pro-vided by the Internet retailer would affect consumers’ perceivedusefulness of the retailer, thereby making their browsing and shop-ping experiences more enjoyable and convenient.

Researchers found that perceived usefulness has a significantimpact on consumers’ intentions to make purchases from theonline retailer as well (Gefen and Straub, 1997; Chen et al.,2002a; Koufaris, 2002; O’Cass and Fenech, 2003; Chen and Tan,2004; Vijayasarathy, 2004; Lee et al., 2006). The perceivedusefulness of the online retailer was the primary determinant ofconsumers’ attitudes towards using the retailer and behaviourintentions towards the retailer (Chen et al., 2002a; Koufaris,2002; Lee et al., 2006). Vijayasarathy (2004) investigated adultconsumers’ intentions to use online shopping and found that per-ceived usefulness positively influenced both attitudes towardsthe online retailer and intentions to use the online retailer. Otherresearchers also supported the significant effects of perceivedusefulness on attitudes and behavioural intentions towards onlineshopping and discussed its usefulness in online shopping (Gefenand Straub, 1997; Childers et al., 2001; O’Cass and Fenech,2003; Lee et al., 2006). Likewise, using other non-store-basedretailers, consumers can explore a variety of brands and products,which may not be available locally and/or regionally, and alsocompare the product attributes (i.e. prices, styles, merchandiseassortment and/or trends) across retail channels in the multi-channel retailing environment.

This perceived usefulness can also be applied to bricks-and-mortar retail setting. Consumers could extend their informationsearch from the non-store-based retailers to the store-basedretailers by integrating the appropriate information from differentchannels. At the local retail stores, consumers can physicallyexamine apparel products by touching and/or trying them on at

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the retail stores. It may provide more opportunities for the con-sumer to gather information limited to non-store-based retailersabout how a product fits and looks on the individual. Noble et al.(2005) found that consumers perceive the bricks-and-mortarretailers as more advantageous than catalogues and Internetchannels because consumers can purchase and possess theproduct immediately at physical stores. When consumers per-ceive a certain retail channel as useful for information search,they are more likely to search for product information and, inturn, purchase a product from that retail channel. Therefore, wehypothesize:

H1: Perceived usefulness of a retail channel for informationsearch for apparel products will positively influence the fre-quency of information search via the retail channel [(a) Inter-net; (b) catalogues; (c) television; (d) local retail stores; and(e) non-local retail stores].H2: Perceived usefulness of a retail channel for informationsearch for apparel products will positively affect the fre-quency of product purchase via the retail channel [(a) Inter-net; (b) catalogues; (c) television; (d) local retail stores; and(e) non-local retail stores].

Influence of product information search onpurchase behaviour

In the economics of information theory, Stigler (1961) argued thatthe more information the consumer has, the better decision she/hewill make. However, the consumer does not search for the infor-mation indefinitely because of the costs of searching for theinformation. Therefore, when marginal benefits derived frominformation search equal marginal costs derived from the infor-mation, the consumer will stop searching for more information(Stigler, 1961). Klein’s (1998) economics of information searchmodel addressed that consumer would choose the least costly wayfor searching and purchasing the goods and services. Searchingand purchasing within one retail channel may be perceived as lesscostly than searching and purchasing in the multiple channels(Klein, 1998). If the retailer offers the product at the right price atthe time the consumer is searching for it, then the customer maychoose a single channel to reduce shopping cost rather than chooseto use multiple channels for gathering information and purchasingproducts. The findings of Ratchford et al. (2003) are in line withKlein’s proposition in the economics of information search model.Ratchford et al. (2003) found that purchase intentions via theInternet increased as a function of the amount of online searchintention for product information. Researchers provided moreempirical support on this positive relationship between the infor-mation search behaviour and purchase behaviour using the Inter-net (Lohse et al., 2000; Rowley, 2000; Swinyard and Smith,2003). For example, Rowley (2000) suggested that frequent Inter-net browsing for information search eventually lead to frequentInternet purchases. Patwardhan and Yang (2003) found that con-sumers’ Internet dependency (i.e. frequent use of the Internet forinformation search and communication purposes) was a signifi-cant predictor of actual online purchasing. The positive relation-ship between information search intention via the Internet andpurchase intention from online stores was also found for apparelproducts (Shim et al., 2001; Watchravesringkan and Shim, 2003;Kim and Park, 2005).

Research showed that there is a positive relationship betweenthe amount of exposure to the media/retailer and purchase inten-tion via that media/retailer. In the television shopping context,Grant et al. (1991) found that consumers who were exposed moreto television shopping programmes tended to purchase more itemsthan the ones who were exposed less to the programmes. Park andLennon (2004) also showed that consumers who watched televi-sion shopping programmes more often and longer purchased moreoften and impulsively spent more money on apparel products viatelevision shopping channels. In the bricks-and-mortar retailsetting, numerous studies found that length of browsing in thepleasant retail environment was positively associated with shop-per’s purchase intentions (Morris and Boone, 1998; Martin et al.,2005), impulse purchases (Park et al., 1989; Morin and Chebat,2005) and money spending (Chebat and Michon, 2003). Based onthe literature, it is reasonable to expect that people who frequentlysearch for product information via a certain retail channel (i.e.Internet, catalogue, television, local or non-local retailer) arelikely to purchase more frequently via the retail channel, as com-pared with people who less frequently search (or do not search) forproduct information via the retail channel. Thus, we propose:

H3: The frequency of apparel product information search viaa retail channel will positively influence the frequency ofapparel purchase via the retail channel [(a) Internet; (b)catalogues; (c) television; (d) local retail stores; and (e)non-local retail stores].

Influence of satisfaction with previouspurchases on purchase frequency

The role of customer satisfaction in predicting loyalty intentiontowards the retailer or product is well noted in the literature.Consumers who are satisfied with the retailer make product pur-chases more frequently and repeatedly from the same retailer(Fornell, 1992; Anderson and Sullivan, 1993; Anderson et al.,1994; Zeithaml et al., 1996; Miller et al., 1998). Repeated pur-chase from the same retailer is one of the indicators of store loyaltybehaviour. When consumers are loyal to the retailer, they revisitthe retailer, repurchase products/services from the retailer andrecommend the product/retailer to their friends and/or family (Zei-thaml et al., 1996; Bolton et al., 2000). This positive relationshipbetween customer satisfaction and behavioural intentions has beenconfirmed in the traditional retail setting (Jones and Reynolds,2006), Internet retailing (Srinivasan et al., 2002; Shankar et al.,2003; Yen and Gwinner, 2003; Bansal et al., 2004; Balabaniset al., 2006), catalogue shopping (Shim and Bickle, 1993) andtelevision shopping (Ray and Walker, 2004). Using a sample of145 multi-channel firms including apparel retailers, Bansal et al.(2004) found that overall satisfaction with an Internet retailerenhanced customer behavioural intentions (e.g. likelihood ofrepurchase) and actual browsing behaviours towards the retailer.Balabanis et al. (2006) also found that e-store satisfaction is posi-tively related to e-store loyalty regarding various products includ-ing clothing, health and beauty products, books and music CDs.This positive linkage between satisfaction and loyalty behaviourwas also found in a multi-channel retail environment (Wallaceet al., 2004). Therefore, we propose:

H4: The satisfaction with the apparel purchase from thatretail channel will positively influence the frequency of

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apparel purchases via the retail channel [(a) Internet; (b)catalogues; (c) television; (d) local retail stores; and (e) non-local retail stores].Based on the literature review and hypotheses, we developed a

conceptual model for this study (See Fig. 1).

Methods

Instrument development

A self-administered paper-based questionnaire was developedbased on the previous literature and study objectives. The ques-tionnaire consisted of five separate sets of questions: (1) perceivedusefulness of various retail channels for apparel product informa-tion search; (2) frequencies of apparel product information searchvia the different retail channels; (3) frequencies of apparel productpurchase via the multiple retail channels; (4) satisfaction with theprevious purchase for apparel product via various retail channels;and (5) demographics.

To tap the perceived usefulness of various retail channels forapparel product information search, four facets of the productinformation category were developed – price, promotion, style/trends and merchandise availability – on a five-point Likert-typescale ranging from Very Useless (1) to Very Useful (5). To createthe perceived usefulness of various retail channels for apparelproduct information search variable, four items for each retailchannel were summated and averaged for further statistic analy-ses. To measure the information search frequencies for apparelproducts using multiple retail channels, researchers developedquestions asking how often participants use the retail shoppingchannels for searching for apparel product information via fivechannels – the Internet, catalogues, television, local retail storeand non-local retail store – on a five-point Likert-type scale: Oncea month (1), every other week (2), every week (3), twice a week (4)and everyday (5).

Researchers also created five questions asking how often par-ticipants use the five different retail channels for apparel productpurchases for their own use on a five-point Likert-type scaleranging from Never (1) to Very Often (5). Satisfaction with previ-ous apparel purchases via various retail channels was measured byfive items, which were developed by the researchers as well. Theitems were measured using a five-point Likert-type scale ranging

from Very Dissatisfied (1) to Very Satisfied (5). Finally, respon-dents were asked about their age, gender and ethnicity.

Data collection procedure

The researchers contacted course instructors to ask their permis-sion to recruit potential participants for the study. The studentswere then informed of the study’s objectives and were asked tovolunteer for this study. Students who voluntarily participated inthis survey received extra credits for the course. Students whodecided not to participate in the present study had the alternativesto receive extra credit from the course instructor.

Description of sample

A total of 176 college students from a Midwestern university in theUS provided usable responses to the survey. The average age of theparticipants was 20.47 and most of them (96.1%) were between 18and 24 years old. The majority of the respondents were female(94.5%) and White or European Americans (86.6%). There werefew Asian Americans (6.1%) and Black or African Americans(2.2%) among the participants. The sample of the study waslimited to college students; however, this demographic group isappropriate to investigate their usage of various retail channels ascollege students are one of the major purchasers of apparel prod-ucts using multi-channels (Ray and Walker, 2004).

Results

Perceived retail usefulness and the frequencyof product information search

Hypotheses 1a through 1e proposed the positive relationshipbetween perceived retail usefulness of apparel product informa-tion search and the frequency of product information search viathe retail channel. Simple regression analyses were used to assessthe relationship between perceived retail usefulness for apparelproduct information search and frequency of product informationsearch via the retail channel among our sample for all five chan-nels (H1a–e). As hypothesized, perceived retail usefulness forsearching for apparel product information had a significant andpositive impact on the frequencies of apparel product information

Figure 1 A proposed model predicting con-sumer search and purchase behaviours ofapparel products in a multi-channel retailenvironment.

Perceivedusefulness of

productinformation search

Frequency of product

information search

Frequency of product purchases

Satisfaction with previous product

purchases

H1H3

H2

H4




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search via the Internet (H1a: F1177 = 56.68, P = 0.000,beta = 0.493, t = 7.53), catalogues (H1b: F1177 = 34.65, P = 0.000,beta = 0.405, t = 5.89), television (H1c: F1177 = 39.32, P =0.000, beta = 0.426, t = 6.27), local stores (H1d: F1177 = 10.44,P = 0.001, beta = 0.236, t = 3.23) and non-local stores (H1e:F1177 = 13.72, P = 0.000, beta = 0.268, t = 3.71). Thus, collegeconsumers who perceived a retail channel as useful for apparelinformation search were more likely to search for apparel productinformation via that retail channel. Perceived retail usefulness forapparel information search accounted for 5.6–24% of the variancein the apparel information search frequency using the retailchannel (Internet = 24%; catalogue = 16.4%; television = 18.2%;local stores = 5.6%; non-local stores = 7.2%). Therefore, hypo-theses 1a through 1e were statistically supported.

Perceived retail usefulness and the frequencyof product purchases

Hypotheses 2a through 2e proposed the positive influence of per-ceived retail usefulness of product search on the frequency ofproduct purchases. Multiple regression analyses were used to testhypotheses 2a through 2e. As hypothesized, consumers’ percep-tion of retail usefulness of product information search had a sig-nificant and positive impact on their frequency of apparelpurchases via the Internet (H2a: beta = 0.192, t = 2.88, P = 0.004),catalogues (H2b: beta = 0.19, t = 2.81, P = 0.005), local stores(H2d: beta = 0.20, t = 2.88) and non-local stores (H2e:beta = 0.20, t = 3.10, P = 0.002). However, this positive relation-ship between perceived retail usefulness of product search andfrequency of product purchases did not receive a statistical supportfor television shopping context (H2c: beta = 0.06, t = 0.80,P = 0.424). Thus, hypotheses 2 received statistical support for allretail channels except television.

Frequencies of product information search andproduct purchases

Hypotheses 3a through 3e examined the relationships between thefrequency of product information search and frequency of productpurchases via a retail channel. A significant and positive relation-ship in all five retail channels was expected. Multiple regressionanalysis results showed that this relationship was strongly positivefor the Internet (H3a: beta = 0.21, t = 3.78, P = 0.000), catalogues(H3b: beta = 0.19, t = 2.97, P = 0.003), television (H3c:beta = 0.20, t = 2.90, P = 0.004) and non-local stores (H3e:

beta = 0.18, t = 3.10, P = 0.002). However, the positive relation-ship between frequency of product information search and fre-quency of product purchase did not hold for local stores (H3d:beta = 0.09, t = 1.48, P = 0.142). Therefore, hypothesis 3 waspartially supported.

Satisfaction with previous product purchasesand frequency of product purchases

Hypotheses 4a through 4e examined positive relationshipsbetween consumer’s satisfaction with product purchase from aretail channel and the frequency of product purchase from thatretail channel. Multiple regression analyses results revealed thatconsumers’ satisfaction level with their product purchases had asignificant and positive impact on the frequency of apparel pur-chases from the Internet (H4a: beta = 0.50, t = 7.64, P = 0.000),catalogues (H4b: beta = 0.46, t = 7.11, P = 0.000), television(H4c: beta = 0.44, t = 6.14, P = 0.000), local stores (H4d:beta = 0.45, t = 6.41, P = 0.000) and non-local stores (H4e:beta = 0.50, t = 7.97, P = 0.000). Therefore, hypothesis 4 was sup-ported for all five retail channels.

Independent variables (perceived retail usefulness for apparelproduct information search, the frequency of information searchvia the retail channel and satisfaction with previous purchase viathe retail channel) explained moderate to substantial amount ofvariance in the frequency of purchase via all five retail channels(See Tables 1a–e). These three independent variables accountedfor 61% of variance in the frequency of purchase via the Internet,45% of variance in the frequency of purchase via the catalogue,33% of variance in the frequency of purchase via the television,38% of variance in the frequency of purchase via the local storesand 49% of variance in the frequency of purchase via the non-localstores.

DiscussionThe proposed model in the present study was supported in all fivevarious retail channels. The data illustrated that, for all five retailchannels (i.e. the Internet, catalogues, television, local retail storesand non-local retail stores), a consumer’s perception of how usefula retail channel is for product information search positively influ-enced his/her apparel search behaviour using that retail channel(H1). These findings parallel previous studies. It was found thatperceived usefulness of the online retailer was one of the mostimportant factors influencing consumers’ purchase intentions

Table 1 Multiple regression analysis resultsfor the Internet

Frequency of purchase viathe Internet beta t-value P-value F-value R2 Adjusted R2

Perceived Internet usefulness forapparel product informationsearch

0.192 2.88 0.004 90.0 0.78 0.61

Frequency of the productinformation search via theInternet

0.211 3.78 0.000

Satisfaction with previous purchasevia the Internet

0.504 7.64 0.000




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towards the retailer (e.g. Chen et al., 2002a; Koufaris, 2002). Theresults of the present study especially show that non-store-basedretail channels (i.e. the internet, catalogues and television) havestronger paths from perceived usefulness for the product search tofrequency of product search of that retail channel, as comparedwith the brick-and-mortar stores (i.e. local and non-local retailstores). In addition, variance of the frequency of product informa-tion search indicated the strong explanation of the non-store-based

channels vs. store-based channels. This finding indicates that therespondents of the study used all five different channels for theirapparel information search; however, college students perceivedthe Internet, catalogues and television more useful retail channelsfor information search. In turn, this led to their frequent searchbehaviour for apparel products using non-store-based retail chan-nels compared with store-based retail channels (local and non-local stores).

Table 2 Multiple regression analysis results forcatalogues

Frequency of purchase viacatalogues beta t-value P-value F-value R2 Adjusted R2

Perceived catalogue usefulness forapparel product informationsearch

0.187 2.81 0.005 47.59 0.67 0.45

Frequency of the productinformation search via catalogues

0.186 2.97 0.003

Satisfaction with previous purchasevia catalogues

0.460 7.11 0.000

Table 3 Multiple regression analysis results fortelevision

Frequency of purchase viatelevision beta t-value P-value F-value R2 Adjusted R2

Perceived television usefulness forapparel product informationsearch

0.059 0.80 0.424 29.15 0.58 0.33

Frequency of the productinformation search via television

0.201 2.90 0.004

Satisfaction with previous purchasevia television

0.438 6.14 0.000

Table 4 Multiple regression analysis results forlocal stores

Frequency of purchase via localstores beta t-value P-value F-value R2 Adjusted R2

Perceived local stores usefulnessfor apparel product informationsearch

0.201 2.88 0.004 35.71 0.62 0.38

Frequency of the productinformation search via localstores

0.092 1.48 0.142

Satisfaction with previous purchasevia local stores

0.453 6.41 0.000

Table 5 Multiple regression analysis results fornon-local stores

Frequency of purchase vianon-local stores beta t-value p-value F-value R2 Adjusted R2

Perceived non-local storeusefulness for apparel productinformation search

0.198 3.11 0.002 55.19 0.70 0.49

Frequency of the productinformation search via non-localstores

0.176 2.90 0.000

Satisfaction with previous purchasevia non-local stores

0.504 6.14 0.000




624

The findings of this study illustrate that the consumers’ percep-tion of retail usefulness for apparel product information searchhave a significant and positive impact on their frequencies ofapparel product purchases via all retail channels, except television(H2). According to previous research (Lennon et al., 2003; Parkand Lennon, 2004), television shoppers are generally middle-agedconsumers and females who have higher motivations for shoppingfrom television than younger consumers and males. Our respon-dents, who were college students, might have looked for upcomingstyle and trend information on television; however, they did notpurchase the apparel items from television shopping because theyspent more time browsing websites or stores for apparel products.In addition, because mature females are the main target customersof television shopping, the product assortment of television shop-ping networks may be more geared towards that consumersegment, rather than college-aged female consumers. This mightbe another reason why the respondents of the present study did notpurchase much via television shopping for apparel products.

It was found that consumers’ frequencies of information searchfor apparel products via a retail channel had a significant influenceon their frequencies of apparel product purchases via that retailchannel (H3) for all retail channels except local retail stores.Possible explanations for this finding are: first, the geographicallocation of our respondents. The present study was conducted in asmall Midwest town in the US. Because the participants in thisstudy reside in a rural area, what they look for in terms of styles,design and even brands may not be found in the local apparelretailers. This may explain why the consumers’ frequency ofproduct information search at the local retailer did not signifi-cantly influence their frequency of apparel purchase at the localretailers. Second, the characteristics and channel usage of oursample may explain why they searched the local stores for apparelproduct information but did not shop there. According to Lee andKim (2008), college-aged consumers are likely to be multi-channel shoppers. The majority of their sample shopped via cata-logues (84.0%) and the Internet (76.7%), while some shopped viathe television (38.6%) (Lee & Kim, 2008). Consumers in ourstudy are also college-aged consumers and they may use localretail stores for product information search activities and trial ofthe actual garments. Then, they may turn to non-store-based retailchannels (i.e. Internet, catalogues) for product purchases as thesenon-store-based retailers offer wider assortments in terms ofstyles, colours and sizes. For example, American Eagle, Old Navyand Victoria’s Secret offer online exclusive items and wider sizeranges. Also, a number of pure e-tailers selling name brand clothessuch as ShopBop.com and eLuxury.com periodically offer freeshipping promotions to customers. These pure e-tailers also do notcollect tax on the purchases, which comes to customers as majorbenefits of non-store-based shopping (Kim and Damhorst, submit-ted). The findings of this present study illustrated that for all fiveretail channels, consumers’ satisfaction level with previousproduct purchases from a retail channel also significantly influ-enced their apparel purchase behaviour using that retail channel(H4). This finding extends the previous research of effects ofsatisfaction on patronage behaviours for apparel products in tra-ditional retail (i.e. Miller et al., 1998) and non-store-based retailsetting (i.e. Shim and Bickle, 1993; Kim and Damhorst, submit-ted) into a multi-channel retail context. For all five retail channelstested, consumers who are more satisfied with their previous

apparel purchases from a retail channel more frequently purchasedthe products from that particular retailer. In addition, R2 of thefrequency of product purchase for all five retail channels indicatedthat our proposed model provided strong explanations for both thenon-store-based channels and store-based channels. The findingsrevealed that all three predictor variables, especially perceivedretail usefulness and satisfaction with previous purchases, clearlyexplained consumer apparel purchase behaviour in five differentretail channels.

Conclusions and implicationsThis present study shows a holistic view of the multi-channelcontext in terms of the information search and product purchasebehaviours for apparel products. To our knowledge, this has notbeen done before with a same population of the consumer group.

The proposed model in this study worked in various differentchannel environments; therefore, the present study empiricallyrevealed that college-aged consumers could be strong multi-channel shoppers and this consumer segment would be appropri-ate for the multi-channels retailers to target.

While there has been much research effort paid to consumersearch and purchase intentions using non-store-based retail chan-nels (i.e. Johnson et al., 2003; Kim et al., 2003; Watchravesring-kan and Shim, 2003; Kim and Damhorst, submitted), few studieshave examined consumer’s actual search behaviour or purchasebehaviour for apparel products in a multi-channel retailing contextwith a focus on small communities and local stores in smallcommunities. The current study has provided understanding ofcollege-aged consumers’ search and purchase behaviours forapparel products, which complements the previous findings basedon consumers residing in the US metropolitan cities (Watchraves-ringkan and Shim, 2003).

The present study provides managerial implications for theapparel industry. As the Internet matures as a retail channel, multi-channel retailing becomes one of the major retailing strategies forthe apparel retailing industry. College students would be the sig-nificant market segmentation for the multi-channels retailers. Amajority of college-aged consumers have multi-channel shoppingexperiences; they choose a retail channel for product informationsearch and product purchases upon their shopping orientations andbenefits sought from the retail channel (Lee & Kim, 2008). Theproposed model in the present study works in all five differentchannels, and the findings of this study suggest that consumersutilize the various retail channels to search for product informationand, in turn, to make product purchases via the channel of theirchoice. Therefore, the apparel retail industry needs to understandthis younger consumer market’s characteristics and its channelusages to enhance their multi-channel retail strategies.

In this study, consumers satisfied with their previous apparelpurchases via a certain retail channel shopped more frequentlyfrom the retail channel for apparel products. Customer satisfactionwith a purchase stems from three factors, such as consumer per-ceptions of merchandise quality, customer service quality andvalue attributes of a retailer (Lee and Kim, 2008). This suggeststhat the apparel retailing industry needs to ensure all three aspectsof their product/service offerings to the customers in order to havetheir customers satisfied. Especially, when it comes to multi-channel retailers, they should provide cohesive and consistent




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customer services throughout their various retail channels toassure the consumer’s convenience of shopping. Consumer satis-faction is the key to build and maintain customer loyalty to theretailer (i.e. Anderson et al., 1994; Zeithaml et al., 1996). There-fore, the apparel retailing industry should carefully examine itscapability of serving its customers using multi-channels andimplement the multi-channel strategy to keep its customersdelighted and loyal to the retailer.

There were some limitations of the present study. The data forthis study were limited to college-aged consumers. Hence, find-ings of this study cannot be generalized to other consumer seg-ments. Future studies focusing on multi-channel retailing maycollect more representative data with diverse demographic back-grounds to draw conclusions applicable to general consumers.This study focused on the apparel product category as it is one ofthe most sold products over the Internet (US Department of Com-merce, 2003, 2005); however, future research may study otherproduct categories using this model. Consumers actively searchfor gift information and buy gifts over the Internet because it savestime and it is easy to ship the gift to the receiver (Hollenbeck et al.,2006). It would be beneficial to investigate the consumer decision-making mechanism regarding gift-searching and purchasing in amulti-channel retailing context, as well as the synergetic impact ofmulti-channel retailing on their channel choice behaviours forgift-searching and buying.

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