Psychological and environmental antecedentsof impulse buying tendency in the multichannel

shopping contextJihye Park

Hankuk University of Foreign Studies, Seoul, South Korea, and

Sharron J. LennonDepartment of Consumer and Textile Sciences, The Ohio State University, Columbus, Ohio, USA

AbstractPurpose – The purpose of this study is to examine the effect of psychological traits and shopping environmental factors on impulse buying tendencyvia television shopping programs and to reflect the inherent nature of the impulsive television shopping environment in the USA as well as thetraditional retail channel.Design/methodology/approach – A total of 154 questionnaires were returned from multichannel customers who purchased apparel from televisionshopping programs and traditional retail stores.Findings – Five causal relationships among impulse buying and interaction tendencies in both television and retail settings and TV shopping programbrowsing duration proposed in this study were confirmed through structural equation modeling.Research limitations/implications – This study adds valuable empirical findings to the literature on the distribution channel relationship byexamining buying behavior of multichannel customers as well as some theoretical implications for impulse buying-related theories.Originality/value – This study provides insights for customer impulse buying behavior in the multiple shopping environments.

Keywords Teleshopping, Buying behaviour, Consumer psychology, United States of America

Paper type Research paper

An executive summary for managers and executivereaders can be found at the end of this article.

T-commerce is a revolution in retailing. Television shoppingprograms, one of the major t-commerce, have become analternative shopping method for traditional retail storeshoppers. T-commerce, which is open 24 hours a day sevendays a week, may be considered as a convenient shoppingmethod since it is more accessible, compared to retail storesthat are only open during regular business hours. With othervarious benefits to customers such as saving time andtransportation cost for shopping trips, t-commerce hasexperienced a huge growth over time (Harden, 1996).Quality Value Convenience (QVC) and Home ShoppingNetwork (HSN) lead the t-commerce market in the USA.QVC leads with $4.4 billion in sales in 2002 (Gross, 2003).Moreover, the total sales revenue of QVC in 2002 exceededthat of other selling channels such as Bloomingdale’s Inc.($2.0 billion) and Amazon.com ($3.9 billion) (Gross, 2003).HSN also reported $2 billion in retail sales in 2002 byreaching more than 140 million households worldwide. HSNshipped 90,000 to 130,000 packages per day (HSN.com,2003). HSN also distributes the products via more than oneretail channel such as the internet and catalog (HSN

Company Profile, 2003). Although sales from television

shopping programs are increasing, many purchases are

returned. Yankelovich Partners, a market research firm,

speculates that television shoppers’ inability for physical

product inspection and experience may result in a higher

return rate, which is estimated between 20 percent and 40

percent. This could be an obstacle for television shopping.Shoppers who purchase products from television shopping

programs as well as traditional retail stores enjoy direct or

indirect interactions with the show hosts while watching

television shopping programs (Grant et al., 1991), which is

known to influence impulse purchase (e.g. Han et al., 1991).In fact, multichannel buyers who purchased products from

both a direct marketing channel and a traditional retail

channel reported that emotional connection to and

interactions with the brand or store are some important

aspects when they purchase products from each retail

channel. In addition, more than half of multichannel buyers

reported concerns about over-consumption and impulse

buying. The purchased products often have not been used

(Smith and Wood, 2003).Although there has been a strong need for empirical studies

examining individuals who use more than one channel or

medium (e.g. television shopping programs) for shopping

(Stone et al., 2002) and purchase products on impulse via

television shopping programs, research effort on those topics

was minimal. Therefore, the purpose of this study was to

examine the effect of psychological traits and shopping

environmental factors on impulse buying tendency via

television shopping programs and intended to reflect the

inherent nature of the impulsive television shopping

environment as well as the traditional retail channel.

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Journal of Consumer Marketing

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q Emerald Group Publishing Limited [ISSN 0736-3761]

[DOI 10.1108/07363760610654998]

56

Conceptual framework

Impulse buyingImpulse buying tendency is “the degree to which anindividual is likely to make unintended, immediate, andunreflective purchases (e.g. impulse purchases)” (Weun et al.,1998, p. 1124). According to Weinberg and Gottwald (1982),impulse buying occurs with emotional conflict betweenactually concluded and previously planned purchases. Rook(1987) mentioned that there are various psychologicalmotivations for impulse buying that people might experiencein shopping. A visual encounter with a product or apromotional incentive can motivate the sudden urge to buy.However, impulse buying behavior does not always comefrom direct visual encouragement. Sometimes, without anyreason or stimulation, people are suddenly motivated to shop(Rook, 1987). Among various product categories, apparel hasbeen a main target for impulse buying. According to Bellengerand Korgaonkar (1980), when consumers shop in a largedepartment store, 50 percent of impulse purchases were forapparel, where impulse purchases range from 27 percent to 62percent of the total sales.Impulse buying tendency has been conceptualized as a

personal trait (e.g. Dholakia, 2000; Murray, 1938) thatinfluences consistent responses to environmental stimuli(Kassarjian, 1971). Traits represent predispositionalattributes of personality that refers to a person’s uniquepsychological makeup. People tend to exhibit steady personaltraits and behave consistently across different situations.Impulsive individuals may have difficulty in restricting theirown behaviors and make frequent and consistent impulsepurchases in several different shopping contexts (Murray,1938). A theoretical model of impulse buying developed byBeatty and Ferrell (1998) presented impulse buying tendencyas a trait. The consumption impulse formation and enactment(CIFE) model developed by Dholakia (2000) also consideredthe impulse buying tendency as a personal trait thatcontributes to the formation of the consumption impulse.The impulse buying tendency as a consumer trait then, maybe positively related to the actual impulse buying. Rook andFisher (1995) also mentioned that consumers who rate highon the impulsivity trait buy things on impulse more frequentlythan do others.Impulse buying tendency as a personal trait can be even

more intensive in television shopping context. Televisionshopping may be a built-in impulse situation becauseshoppers cannot predict what items will be sold beforewatching a television shopping program. Television shoppingchannels offer merchandise that consumers do not initiallyplan to buy, but may decide to do so during exposure to avariety of products (Stephens et al., 1996). In fact, Harden(1996) found that many television shoppers purchasedmerchandise on impulse. Sometimes, people may not beable to control themselves when spending money on shoppingfrom television shopping programs. Thus, both the inherentnature of the impulsive environment of television shoppingprograms and impulse buying tendency as a personal trait inthe retail setting may carry over to impulse buying in thetelevision shopping setting (e.g. Beatty and Ferrell, 1998;Murray, 1938). Based on the literature, it is reasonable toexpect that impulse buying tendency as a personal traitdeveloped in the traditional retail channel may increaseimpulse buying in television shopping settings. Therefore, thefollowing hypothesis is developed (see Figure 1).

H1. There is a positive relationship between impulsebuying tendency in the retail setting and impulsebuying tendency in the television setting.

Customer-salesperson interactionThe customer-salesperson interaction has been emphasized asan important element in marketing communications thataugment consumer buying in the traditional retail channel(e.g. Bagozzi, 1978; Davis and Silk, 1972; Weitz, 1981).Salespeople’s ability to inform and persuade through effectiveinteractions with customers influence customers’ purchases(Grewal and Sharma, 1991). Rook and Fisher (1995) foundthat impulse buying behavior is almost exclusively stimulusdriven. Impulsive buyers are likely to be open and flexible tosudden or unexpected buying ideas. Thus, impulsive buyersare likely to respond positively and immediately to buyingstimuli such as products, salespeople, or store environments.Increased exposure to stimuli also enhances the chance ofrecognizing product needs and leads consumers to processnew product information (Iyer, 1989).According to Stern (1962), impulse buying occurs when the

consumer is motivated by the suggestion to buy new productswithout previous knowledge about the product. Sometimes itoccurs when quality, function, and usefulness of the productare evaluated by a customer or a salesperson (Stern, 1962).Emotional reactions to a salesperson also can influencecustomer purchase intentions (Babin et al., 1995). Asalesperson often encourages or persuades customers topurchase more products in the store. Han et al. (1991) foundthat impulse buying was influenced by the amount ofinteractions with a salesperson in the store. Emotionalattraction to a desired product throughout interactions witha salesperson can stimulate buyers to accept sudden andunexpected buying ideas during shopping (Hoch andLoewenstein, 1991). Based on the literature, the followinghypothesis is developed (see Figure 1).H2. There is a positive relationship between interaction

with salespeople and impulse buying tendency in theretail setting.

Parasocial interactionGrant et al. (1991) defined parasocial interaction as a pseudo-intimate relationship between audiences and performers fromthe mass media including television, radio, and movies.Without actual interactions or communications, viewers oftendevelop the illusion of face-to-face interaction and pseudointeractive responses, when they feel a connection to a mediapersonality (e.g. television shopping show hosts).Viewers may perceive a sense of intimacy or friendship with

a media personality who uses various conversationaltechniques to attract and persuade the viewers. Forexample, the television shopping show hosts often askpersonal questions and try to find the similarities betweenviewers and hosts in order to create a strong friendlyrelationship (Stephens et al., 1996). The show hosts alsoprovide their e-mail addresses or extension numbers toencourage viewers to contact them again after the show(HSN, 2000).Parasocial interaction between viewers and television

personalities has been investigated by several researchers inrelation to the demographic and psychographic characteristics

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of viewers. Levy (1979) found that older viewers are more

likely to develop parasocial interactions through television.

Education has also been found to influence parasocial

interaction. Grant et al. (1991) found a negative relationship

between education and parasocial interaction. Education level

was negatively associated with dependency on television

shopping and as a result, it reduced parasocial interaction.

Similarly, Levy (1979) also found that less-educated viewers

tended to develop parasocial interactions.Parasocial interaction with a favorite television personality

is related to viewers’ loneliness (Rubin et al., 1985). Nordlund

(1978) suggested that the viewer’s loneliness may be often

caused by less social interaction and limitations of leisure

activity. People who feel lonely tend to interact with a

television personality more frequently than people who are

not lonely (Rubin et al., 1985). Similarly, Gregg (1971) found

that socially-isolated elderly viewers tend to be related

parasocially to personalities on specific television programs.

Parasocial interaction and interaction with salespeopleDesire to receive attention or to meet people to alleviate

loneliness may be important shopping motives (Tauber,

1972). Tauber (1972) found that people were likely to go

shopping when they needed attention or wanted to

communicate with others. People liked to chat with

salespeople in the store about their interests. This may be

even more true for elderly consumers who may have limited

social activities due to a lack of physical capability.According to Harden (1996), elderly consumers also may

watch more television shopping programs compared to

younger consumers to alleviate loneliness. The older ones

viewed television shopping as more advantageous than

younger people (Harden, 1996). In fact, Stanforth et al.(2000) found that shoppers who purchased apparel from

television shopping programs were likely to be older with an

average age of nearly 50, than those who did not purchase

apparel. As such they may have limited social interactions and

few leisure activities. They may have seen television shopping

as a form of entertainment and as a way of alleviating

loneliness. Television shoppers generally enjoyed listening to

the hosts and seeing what other consumers were buying.

Thus, as women get older, they may seek interaction withsalespeople in the retail setting and develop parasocialinteractions with television personalities in the televisionsetting both as compensation for the lack of social interaction(Nordlund, 1978). Based on the literature, it is reasonable toexpect that interaction tendency in the retail setting may berelated to parasocial interactions with the show hosts intelevision setting. Thus, the following hypothesis is developed(see Figure 1).H3. There is a positive relationship between interaction

tendency with salespeople and parasocial interaction.

Parasocial interaction and impulse buying in television shoppingsettingsIntensive parasocial interaction may influence impulse buying.Stephens et al. (1996) found that conversational techniques ofthe host encourage and persuade viewers to form andmaintain parasocial interactions and to purchase items onimpulse. Viewers who make comments (e.g. “I bought severalitems. I’ve been watching QVC for three months and havefilled my house with QVC items.I have the Diamonique ring.I now wear rings because of QVC. Now, QVC is the onlything we watch!”) to hosts may be more likely to purchaseitems through television shopping programs on impulse.According to Stasi (1988), items on television shopping

programs are displayed in a serial fashion and draw attentionfrom viewers. At this point, the host on the television shoppingprogram may play an important role in displaying items andarousing interest from viewers. Viewers who develop strongrelationships with the hosts may be more likely to be persuadedby the host and purchase more products even though it is notinitially planned. Therefore, based on the literature, thefollowing hypothesis was developed (see Figure 1).H4. There is a positive relationship between parasocial

interaction and impulse buying tendency in thetelevision setting.

BrowsingBrowsing and parasocial interactionMedia exposure may accelerate developing parasocialinteraction. According to Nordlund (1978), among four

Figure 1 A proposed model for the impact of psychological and environmental factors on impulse buying in the multichannel context

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types of media such as magazines, television, radio, andnewspapers, more television exposure significantly increasedtelevision dependency and in turn, parasocial interaction.Similarly, Nordlund (1978) and Levy (1979) found that thereis a strong positive association between television exposureand parasocial interaction. This means that the more a personwatches television, the more the person tends to interact withtelevision personalities or vice versa.Rubin et al. (1985) found that parasocial interaction and

reliance on television when feeling lonely were positivelyrelated. People who rely on television are likely to haveparasocial relationships. With the ripple effect, if one hasparasocial interaction with many television hosts, oneprobably watches television more. In particular, olderpeople tend to be more exposed to television and have moreparasocial interaction (Miller, 1983). Miller (1983) alsofound a significant relationship between parasocial interactionand amount of television viewed among older people. Thissuggests that loneliness of older people may influence theamount of television exposure and in turn, increase parasocialinteraction.In the television setting, Grant et al. (1991) found a positive

relationship between the amount of browsing via televisionshopping program and parasocial interaction. The viewerswho watched more television shopping programs and browsedmore products tended to develop more intensive parasocialinteractions with television show hosts. Therefore, it isreasonable to expect that TV shopping program browsingduration may be positively related to parasocial interactionamong television apparel shoppers (see Figure 1).H5. There is a positive relationship between TV shopping

program browsing duration and parasocial interactionin the television setting.

Browsing and impulse buyingBrowsing may influence impulse buying. Han et al. (1991)described a simple process of impulse buying from browsing.People may walk down an aisle in the mall or store, browsemerchandise, and buy the products on impulse. Rook (1987)found that people feel sudden urges or mysterious forces topurchase products when they browse through merchandise ina store. This was likely to be stimulated by a visualconfrontation while browsing.Iyer (1989) argued that the amount of purchases made on

impulse is positively related to the amount of time spentbrowsing. If a shopper browses longer, she or he will havemore chance to be stimulated by a product increasing thelikelihood of impulse buying. Increased exposure to stimulialso enhances the chance of recognizing product needs andleads consumers to process new brand product information.In addition, during browsing, a shopper may feel morecomfortable choosing more products without time pressure.Bellenger et al. (1978) also indicated that browsing may leadto an immediate unplanned purchase. In fact, Jarboe andMcDaniel (1987) found a positive relationship betweenbrowsing and impulse buying in the retail setting. Shopperswho browsed longer, had more of a chance to be stimulatedby a product, increasing the likelihood of impulse buying.This can be applied to the television shopping setting. Ifshoppers browse longer (e.g. watch longer) on televisionshopping programs, they will have more of a chance to bestimulated by a product. As a result, longer browsing viatelevision shopping programs may increase the likelihood of

impulse buying. Therefore, it is reasonable to expect thatthere is a positive relationship between TV shopping programbrowsing duration and impulse buying among televisionshoppers. Based on the literature review, the followinghypothesis was developed (see Figure 1).H6. There is a positive relationship between TV shopping

program browsing duration and impulse buyingtendency in the television setting.

Method

SampleA total of 1,500 individuals who experienced purchasingproducts via television shopping channels as well as intraditional retail channels were randomly selected from apurchased national database in the USA. Questionnaires weresent to these individuals through US first class mail.Following Dillman (2000), three weeks after the firstmailing replacement questionnaires were sent only to non-respondents (n ¼ 1; 388) with nearly the same appearance asthe original mailout. Finally, from the returned questionnaires(n ¼ 357) with 23.8 percent of response rate, only about43 percent of respondents (n ¼ 154) used multiple channels(t-commerce/traditional retailer) for apparel shopping,whereas about 57 percent used traditional retail channels forapparel shopping. Thus, only multichannel apparel shoppers(n ¼ 154) were selected for analysis. The similar groupcomposition (apparel purchasers vs non-apparel purchasers)in the television shopper population was found in Stanforthet al. (2000) who found that about 56 percent of televisionshoppers purchased apparel from television shoppingprograms and indicated that apparel purchasers fromtelevision shopping programs may not account for the wholepopulation of television shoppers. Therefore, although theultimate return rate of multichannel apparel customers was10.3 percent after excluding non-apparel purchasers, sinceour interest was specific to apparel purchasers not the totalpopulation of television shoppers, we believe that this groupcan still represent apparel purchasers from television shoppingprograms and traditional retail channels.

InstrumentA mail questionnaire included a one-page cover letter withinformation about researchers and academic institutions,purpose and significance of this research, anonymity ofrespondent identity, and return deadline. Incentives were notprovided and response was purely voluntary. To identifymultichannel customers who purchased apparel productsfrom television shopping channels as well as traditional retailchannels, two questions of “Have you purchased clothingfrom television shopping programs” and “Have you everpurchased clothing in retail stores including non-grocerystores (e.g., K-mart, Wal-mart, etc)” were elicited. Peoplewho circled “yes” for both questions were defined asmultichannel customers in this study. For the responseformat of the variables, impulse buying tendency, parasocialinteraction, and interaction tendency with salespeople wererated on a 1 (strongly disagree) to 5 (strongly agree) Likertscale. In order to measure impulse buying tendency inmultiple shopping channel settings, 15 items developed byHan et al.’s (1991) were revised to reflect each setting. Hanet al. (1991) classified five sub-dimensions for capturingvarious types of apparel impulse buying:

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(1) Planned impulse buying (e.g. I decide what to buy after Iwatch a television shopping program).

(2) Reminder impulse buying (e.g. When I see a product Ihad looked for before, I buy it even though I watch atelevision shopping program for other items).

(3) Suggestion impulse buying (e.g. If I see a product with anew style, I buy it while I watch a television shoppingprogram).

(4) Pure impulse buying (e.g. I buy anything I suddenly feelcompelled to buy).

(5) Planned buying (e.g. I plan carefully what to buy before Iwatch a television shopping programs).

The last dimension was reversed to direct toward impulsebuying condition. The reported reliability was 0.89 (Han et al.,1991). Parasocial interaction with the TV shopping showhosts were measured by seven items for parasocial interactiondeveloped by Levy (1979). The items from the original scalewere slightly modified to reflect TV shopping settings. Inorder to measure interaction tendency with salespeople in thetraditional retail setting, seven parasocial interaction items(Levy, 1979) were modified and revised to be appropriate tosocial interaction with salespeople in the retail setting. Insteadof using a social interaction tendency scale, the modifieditems from parasocial interaction were used to be consistentacross two different settings. TV shopping program browsingduration was measured by asking the number of days ashopper watched television shopping programs in an averageweek.In addition to personal checks as a payment method,

television shopping channels allow customers to use majorcredit cards such as Visa, MasterCard, or American Expressthrough a toll-free number that may stimulate impulsepurchases. Thus, five items about credit card usage and theamount of money spent were developed by the researcher andused to provide additional information regarding purchasingbehavior for multichannel customers. Demographicinformation such as age, sex, race, and marital status waselicited from the subjects in the last part of a questionnaire.All questionnaire items were carefully pretested for readabilityand understanding. Five graduate students reviewed thequestionnaire and suggested for wording and format of thequestionnaire.

Results

Preliminary analysisDemographicsThe mean age of respondents (n ¼ 152) was about 57 years,with a range of 30 to 84 years. More than 70 percent of therespondents were over 45 years old. Around 80 percent of therespondents were women. Most respondents were CaucasianAmericans (92.3 percent). Other respondents were NativeAmerican (7.5 percent), African American (4.6 percent),Hispanic American (1.4 percent), Asian/Asian American (0.9percent), and other (3.2 percent). About 69 percent ofrespondents were married, whereas 30.1 percent were singleor equivalent such as widowed or divorced (see Table I). Thedemographics were compared with television shopperrespondents from Lee et al. (2000) who reported 33.4percent of response rate in order to examine the difference inmultichannel shoppers and the typical television shopperprofile. Demographics were similar in average age, ethnicbackground, and marital status. The average age was 56 yearsold. About 75 percent respondents were 50 or older.

Non-response bias testBecause this study relied on voluntary responses without anyincentives, response rate for apparel purchasers in multiplechannels may be low (10.3 percent). Thus, generalization ofour findings should be cautious. In order to examine if therewere differences in demographics between early respondents(the first 25 percent of respondents) and late respondents (thelast 25 percent of respondents), the non-response bias testwas conducted by the procedures suggested by Armstrong

Table I Demographics of respondents

Multichannel

shoppers

f Percentage

Age (n5152)Under 25 0 0

25 to 34 1 0.7

35 to 44 19 12.5

45 to 54 53 34.9

55 to 64 48 31.6

65 to 74 27 17.8

75 and over 75 4 2.6

Total 152 100

Sex (n5152)Female 142 93

Male 10 6.7

Total 152 100

Ethnic background (n5151)African American 8 5.3

Caucasian American 131 86.8

Hispanic American 1 0.7

Native American 8 5.3

Asian/Asian American 1 0.7

Other 2 1.3

Total 151 100

Education (n5150)Some high school 7 4.7

High school graduate 35 23.3

Some college 69 46

College graduate 13 8.7

Some graduate school 10 6.7

Graduate degree 16 10.7

Total 150 100

Income level (n5152)Prefer not to answer 36 23.7

Less than $25,000 19 12.5

$25,000 to $34,999 20 13.2

$35,000 to $49,999 28 18.4

$50,000 to $74,999 30 19.7

$75,000 to $99,999 9 5.9

Over $100,000 10 6.6

Total 152 100

Marital status (n5151)Married 97 64.2

Single or equivalent (Widowed, divorced, etc.) 52 34.4

Other 2 1.3

Total 151 100

Note: Different n s are due to missing information

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and Overton (1977). The two groups did not differ ondemographic characteristics; for age, tð47Þ ¼ 20:86,p ¼ 0:57; for ethnic background, x2ð4Þ ¼ 2:28, p ¼ 0:69;and for marital status, x2ð1Þ ¼ 2:28, p ¼ 0:13. Theseindicated that late respondents are similar in demographiccharacteristics to early respondents. Therefore, we believethat there are few differences between our respondents andnon-respondents.

Factor analysisConstruct validity for impulse buying tendency and parasocialinteraction in the television setting and impulse buyingtendency and interaction tendency with salespeople in theretail setting was assessed using factor analysis (Cronbach andMeehl, 1955). Exploratory factor analyses were conducted todetermine whether multiple indicators for each variablecomprised one factor dimension. Factor loadings above 0.55(Nunnally, 1967) and not higher than 0.30 on other factors(Kline, 1998) were considered evidence for construct validity.Impulse buying tendency in both settings were generated asmore than one factor. Thus, the first factor including threeitems that explains most variance (24 percent in the televisionsetting, 28 percent in the retail setting) was chosen for thefurther analysis. Other constructs were generated as a singlefactor. Then, the multiple items for each construct weresummed to create a research variable (see Table II).

ReliabilitiesUsing reliability analysis (i.e. Cronbach’s alpha), reliabilitiesfor impulse buying tendency scale was 0.80 in the televisionsetting and 0.87 in the retail setting. Reliability for parasocialinteraction in the television setting was 0.85. Reliability forinteraction tendency with salespeople in the retail setting was0.89 (see Table II). Cronbach’s alpha scores assessing internalconsistency of measures were above 0.80, indicating goodreliabilities of measures (see Table II).

Path analysisBecause our main interest is to examine casual relationsamong variables with a single observed measure (e.g.browsing duration), path analysis was conducted by amaximum-likelihood estimation procedure using AMOS 4.0(Analysis of Moment Structures). The conceptual modelconsists of two exogenous variables (interaction tendency withsalespeople and TV shopping program browsing duration)and three endogenous variables (parasocial interaction,impulse buying tendency in the retail setting, and impulsebuying tendency in the television setting). To assess model fit,a chi-square statistic, goodness-of-fit index (GFI), adjustedgoodness-of-fit index (AGFI), normed fit index (NFI),relative fit index (RFI) and root mean square error ofapproximation (RMSEA) were used. As an indicator of goodmodel fit to the data, Kline’s (1998) criteria were adopted(e.g. GFI $ 0.95, AGFI $ 0.90, NFI $ 0.90, RFI $ 0.90,and RMSEA # 0.08).The results of causal model analysis revealed a chi-square of

3.261 (p ¼ 0:515) with 1 degree of freedom. The other fitindices were GFI ¼ 0:99, AGFI ¼ 0:97, NFI ¼ 0:98,RFI ¼ 0:94, and RMSEA ¼ 0:00 which indicated theproposed model fit the data well. Figure 2 provides squaredmultiple correlations (R2) for each endogenous construct aswell as path coefficients and t-values for each statisticallysignificant path. In addition, descriptives (e.g. means,standard deviations) and correlations among constructmeasures for the model are shown in Table III.

All hypotheses except one (H6) were statistically supported.The proposed positive relationship between impulse buyingtendency in the retail setting and impulse buying tendency inthe television setting (H1) was supported (b2* ¼ 0:51,t ¼ 8:37, p , 0:001). H2, predicting a positive effect ofinteraction with salespeople on impulse buying tendency inthe retail setting, was supported (b1* ¼ 0:11, t ¼ 2:85,p , 0:01). H3, predicting a positive relationship betweeninteraction with salespeople and parasocial interaction withtelevision shopping program hosts, was supported(b3* ¼ 0:52, t ¼ 7:41, p , 0:001). H4, predicting a positiverelationship between parasocial interaction and impulsebuying tendency in the television setting, was supported(b4* ¼ 0:10, t ¼ 3:33, p , 0:001). Finally, a proposedpositive relationship between exposure to televisionshopping programs and parasocial interaction was alsosupported (b5* ¼ 0:75, t ¼ 4:63, p , 0:001). However, theproposed positive relationship between TV shopping programbrowsing duration and impulse buying tendency in thetelevision setting (H6) was not supported (b6* ¼ 0:00,t ¼ 20:05) (see Figure 2).To further examine the effects of interaction with

salespeople and browsing duration in the television settingon impulse buying tendency in the retail setting andparasocial interaction and impulse buying in the televisionsetting, the decomposition of indirect, direct, and total effectsof exogenous variables on endogenous variables wasconducted (see Table IV). All exogenous variables exceptbrowsing duration in the television setting had significant totaleffects on each dependent variable. Impulse buying tendencyin the retail setting was the strongest variable explainingimpulse buying tendency via television shopping programs.Parasocial interaction was then, the second strongest variableexplaining impulse buying tendency in the television setting.The R2s of impulse buying tendency in the retail setting,parasocial interaction, and impulse buying tendency in thetelevision setting were 0.05, 0.35, and 0.39, respectively. LowR2 of impulse buying tendency in the retail setting was found,which indicates only small amount of impulse buyingtendency in the retail setting can be explained byinteractions with salespeople. This implies that impulsebuying tendency in retail setting can be predicted by otherconditions (e.g. store environment, mood, promotion) thathave been studied in the past research. However, our maininterest of this study was to examine the psychological traitstransmitted from retail settings rather than marketing stimuliin the retail environment.

Discussion and implications

Out of six, five causal relationships proposed in this studywere confirmed through structural equation modeling. Theresults showed that the proposed model for impulse buyingand interaction tendencies in multichannel settings generallyfit the data. Multichannel shoppers who had moreinteractions with salespeople purchased more products onimpulse in the retail setting and in turn, purchased productson impulse in the television setting. In addition, customerswho had interactions with salespeople in the retail setting hadgreater parasocial interaction with the hosts via televisionshopping programs and in turn, purchased more products onimpulse in the television setting. Focusing on the televisionsetting, parasocial interaction mediated the relationshipbetween TV shopping program browsing duration and

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Table II Factor analysis results for constructs

Variables Factor itemsFactorloadings Eigenvalue

Percent ofvariance a

Impulse buying tendency inthe television setting

If I see clothing in a new style, I buy it from televisionshopping programs 0.738 3.57 23.79 0.80When I see a garment with a new feature via televisionshopping programs, I buy it to try it out 0.708I like to buy new clothing from television shoppingprograms which has just come out 0.632

Parasocial interaction in the The hosts are almost like friends I see everyday 0.764 3.70 52.80 0.85television setting I like hearing the voices of the hosts in my house 0.825

When the host shows how s/he feels about the product,it helps me make up my mind about the product 0.696I like to compare my feelings for the product with whatthe host has to say about it 0.708When the hosts joke around with one another, it makesthe program even more enjoyable 0.808I feel sorry for the hosts when they make mistakes 0.617Television shopping programs show you what people inthe media are really like 0.642

Impulse buying tendency If I see clothing in a new style, I buy it 0.706 4.14 27.57 0.87in the retail setting When I see a garment with a new feature, I buy it to try it

out 0.757I like to buy new clothing which has just come out 0.663

Interaction tendency with Salespeople are almost like friends I see everyday 0.813 4.27 60.96 0.89salespeople in retail setting I like hearing the voices of salespeople in retail stores 0.838

When the salesperson shows how s/he feels about theproduct, it helps me make up my mind about the product 0.866I like to compare my feeling for the product with whatthe salesperson has to say about it 0.813When the salespeople joke around with one another, itmakes shopping even more enjoyable 0.786I feel sorry for the salespeople when they make mistakes 0.548The salesperson shows you what products are really like 0.757

Figure 2 A final model for the impact of psychological and environmental factors on impulse buying in the multichannel context

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impulse buying from television shopping programs. This

implies that people who are more exposed to television

shopping programs are likely to have greater parasocial

interactions with the show hosts and in turn, purchase more

products on impulse via television shopping programs. These

findings supported the past literature (e.g. Babin et al., 1995;

Grant et al., 1991; Stephens et al., 1996).We expected a positive relationship between TV shopping

program browsing duration and impulse buying tendency in

the television setting. However, there was no direct

relationship between the amount of time television shopping

programs were watched and impulse buying among

multichannel shoppers. This is not consistent with the

previous findings (e.g. Jarboe and McDaniel, 1987) that

browsing via television shopping programs positively

influences impulse buying. In these data, browsing via

television only affected impulse buying from television

indirectly. It is possible that personal traits such as

parasocial interaction and impulse buying tendency have

strong and direct influence on impulse buying tendency in

television setting. Personal traits may be consistent across

different shopping contexts. Once a person develops personal

traits relevant to shopping in the traditional shopping context,

it will Based on the sequential relationship from browsing

intention via parasocial interaction to impulse buying

tendency via television shopping programs, parasocial

interaction seems to possibly mediate between browsing

duration and impulse buying tendency. Shopper who develop

parasocial interaction from watching more television shopping

programs may purchase more products on impulse.This study adds valuable empirical findings to the literature

on the distribution channel relationships by examining buying

behavior of multichannel customers who shop both via

television shopping programs as well as at the traditional retail

channels. The results revealed that customer-salesperson

interaction and impulse buying tendency in the retail setting

influenced parasocial interaction and impulse buying

tendency in the television setting. This implies that each

buying setting is not separate; rather multiple buying

environments may interact and influence each other.

Established buying tendency from one channel may

influence purchasing from another channel. Impulse buying

tendency may be consistent across different buying channels.

This suggests support for an impulsive buying trait.In addition, some theoretical implications can be generated

for impulse buying. In the past, impulse buying tendency was

examined within a limited buying setting (e.g. traditional

retail channels). However, reflecting new retailing and buying

trends, impulse buying tendency as a personal trait in one

shopping setting can be seen to influence buying behavior in

other shopping settings such as televisions, catalogs, and the

internet. Thus, impulse buying tendency as both cause and

Table IV Decomposition of direct, indirect, and total effects for the proposed model

Dependent variable

Independent variable Total effects Indirect effects Direct effects

IBT in the television settingInteraction with salespeople 0.11* 0.11* –

IBT in the retail setting 0.51** – 0.51**Parasocial interaction 0.10* – 0.10*TV shopping program browsing duration 0.07 0.07 –

R2 0.39

Parasocial interactionInteraction with salespeople 0.52** – 0.52**TV shopping program browsing duration 0.75** – 0.75**R2 0.35

IBT in the retail settingInteraction with salespeople 0.11* – 0.11*R2 0.05

Notes: * p , 0:01; ** p , 0:001; Standardized path estimates are reported

Table III Correlation matrix of model constructs

Correlations

Model constructs (n5 144) Mean SD IS TVBD PI IBT/RS IBT/TS

Interaction with salespeople 13.15 5.49 1.00

TV shopping program browsing duration 3.56 2.39 0.028 1.00

Parasocial interaction 15.69 5.79 0.507* 0.325* 1.00

Impulse buying tendency in the retail setting 5.59 2.58 0.232* 0.078 0.159 1.00

Impulse buying tendency in the television setting 5.88 2.41 0.162 0.118 0.318* 0.585* 1.00

Notes: * p , 0:01; IS – Interaction with salespeople; TSBD – TV shopping program browsing duration; PI – Parasocial interaction; IBT/RS – Impulse buyingtendency in the retail setting; IBT/TS – Impulse buying tendency in the television setting

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effect needs to be considered and tested in multiple shoppingenvironments for external validity for impulse buying-relatedtheories (e.g. Dholakia, 2000). In addition, Impulse buyingtendency (M ¼ 5:88) in the television setting was slightlyhigher than that in the retail setting (M ¼ 5:59). This impliesthat the inherent nature of impulsive condition in televisionshopping settings can intensify impulse buying tendency.Although consistent impulse buying tendency was found intwo different settings, certain shopping contexts can possiblystrengthen or weaken the degree of impulse buying tendencyas a personal trait. Thus, in future research, impulse buyingtendency can be examined in other multiple combined buyingsettings (e.g. traditional channel – catalog – internet). Eventhough the internet is considered as more plannedenvironment compared to catalogs and televisions, impulsebuying tendency as a personal trait in traditional channelsmay positively influence buying behavior in the internet.Customers who are likely to interact with salespeople in the

store may have greater potential for building parasocialrelationships with the show hosts when they watch televisionshopping programs. Interaction tendencies in both settingsmay then positively influence impulse buying in the televisionsetting. Thus, interaction tendency seems to be consistentacross different buying channels. Similar to impulse buyingtendency, it is also possible that interaction tendency may beanother personal trait affecting buying behavior. Customerswho enjoy interactions with the salesperson in the traditionalchannel may also like to build an interactive relationship andincrease communications with the show host in the televisionsetting.This study also contributes to knowledge about customer

relationship marketing (CRM) for t-commerce. Multichannelcustomers who shop via television shopping programs as wellas at retail stores may be willing to interact with salespeopleeither for entertainment or to alleviate loneliness. Thus,developing a close relationship between customers andsalespeople in both television and retail settings may bebeneficial to generate sales for t-commerce. If direct (physicalinteraction in the retail setting) or indirect (parasocialinteraction in the television setting) positive customer-salesperson relationships are built, customers may purchasemore. T-commerce marketers may encourage show hosts toapproach the viewers (potential buyers) through friendly andentertaining comments that can evoke emotional responsesfor purchasing. This also may create a synergy effect that leadsto more parasocial interactions with the host and in turn,increase the amount of purchases. In addition, directcommunications over the phone during the show may behelpful to facilitate more interactions. Constant reminders ofasking shoppers to stay tuned on the shopping channels mayincrease the amount of browsing via television shoppingprograms. However, t-commerce marketers should be awareof negative consequences of impulse purchases such as creditcard debt or non-use of product purchased. Merchandisersshould select guaranteed quality of merchandise and vendorsto reduce negative consequences of impulse purchases fortelevision shoppers. Easy process of returns may minimizereturning effort and help customers to return products backto the distribution center. Special instructions formerchandise return can be announced and emphasized bythe show hosts.This study has some limitations. Beyond low response rate,

some responses may not fully reflect actual shopper behavior.Respondents may rely on their memories to recall their past

shopping experience, but often recall inaccurate information.This may even more true for older respondents. Thus,browsing duration may be possibly inaccurate in the processwhere respondents might need to mentally generalize oraverage their viewing time.In addition, because multichannel shoppers were selected

without temporal limitation, store patronage difference in twoshopping contexts was not captured. Some respondents shopmore often from television shopping programs, whereasothers shop more frequently at traditional retail stores. Forexample, about 20 percent of respondents did not spendmoney for apparel last month in the retail stores. Althoughthey reported that they have shopped at the traditional retailstores, they may not shop often. The similar observation canapply to television shopping context.

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About the authors

Jihye Park is an assistant professor at Hankuk University ofForeign Studies. Her research focuses on multichannelretailing including the internet and mobile and technologyuse in retail management. Jihye Park is the correspondingauthor and can be contacted at: jihyepark@hufs.ac.krSharron J. Lennon is a professor at the Ohio State

University. Her research focuses on the internet and televisionshopping for apparel and customer service (in-store oronline).

Executive summary and implications formanagers and executives

This summary has been provided to allow managers and executivesa rapid appreciation of the content of this article. Those with aparticular interest in the topic covered may then read the article intoto to take advantage of the more comprehensive description of theresearch undertaken and its results to get the full benefits of thematerial present.

Research has shown that a significant number of purchasesare made on impulse. Visual contact with a product canprompt impulse buying, as can promotions or sales. On otheroccasions, there are no apparent stimuli when impulse buyingoccurs. Evidence suggests that clothing is particularly proneto be purchased on impulse and studies have revealed that up

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to 50 percent of impulse buying in a large department store islikely to involve clothing.Based on suggestions that impulse buying might occur as

the result of a personality trait, Park and Lennon carried out astudy to determine the motivation for and extent of impulsebuying across various shopping environments. The authorsfocused specifically on the growing phenomenon of tcommerce, whereby consumers purchase from televisionshopping channels that are open round the clock, seven days aweek. The study was carried out in the USA and the 154respondents selected to submit completed questionnaires hadall purchased clothing in different shopping contexts. Therespondents had a mean age of 57, with more than 70 percentbeing over 45. Around 80 percent were female and the vastmajority Caucasian American.

Some issues to considerThe study analyzed different factors that potentiallyencouraged impulse buying in one or both settings.

Impulse buying in a retail settingThe hypothesis here was that such a tendency would alsoinspire the consumer to purchase on impulse from a televisionshopping channel.

Interaction with salespeopleResearch has suggested that some shoppers are motivated tovisit retail outlets because it presents an opportunity to meetpeople. As a result of interaction with salespeople, theemotional bond that is formed paves the way for thesalesperson to exert influence on the consumer. Thisinfluence often results in the consumer making purchasesthat were not originally intended.

Parasocial interactionThe theory here is that consumers will form a similarattachment to the TV shopping channel host, despite the factthat no genuine interaction takes place. Instead, this perceivedintimacy might develop because of the host asking questionson air and inviting viewers to contact by telephone or email. Itis believed that older viewers who are lonely and lack mobilitywatch more shopping TV programs and are thus especiallyprone to developing parasocial relations. The extent of theserelations increases in line with the duration of TV shopping.The authors hypothesized that this in turn enhances theprospect that impulse buying will occur. Researchers alsosuggest that less educated people have a greater tendencytowards developing parasocial relations.

BrowsingPrevious research had suggested that browsing encouragesimpulse buying in a retail environment. The shopper is able toinspect merchandise and the temptation to purchase increasesalong with the duration that browsing takes place. Park andLennon speculated that the concept could also be applied tothe TV setting.

The study revealed that many TV shoppers purchased onimpulse. It was also discovered that the above factors in themain influenced impulse buying. The exception to this wasbrowsing in a TV setting, a finding that proved contrary toprevious results. Impulse buying in a retail context moststrongly influenced similar behavior in its TV counterpart.The second most influential factor was parasocial interaction.This may be particularly significant given that evidencesuggests the average age of consumers purchasing clothingfrom a TV shopping channel is around 50. Consumers’ desireto interact with salespeople/TV presenters also invites theconclusion that this will prevail within other shoppingcontexts.

ImplicationsEvidence that impulsive buying tendencies span differentsettings adds weight to the theory that an impulsive charactertrait exists. It also indicates that shopping contexts interactand influence consumer behavior within each other.Therefore, different settings should not be regarded inisolation. However, that impulse buying tendency was foundto be slightly higher in the TV context perhaps implies thatdifferent environments may reinforce or weaken the tendencyto purchase on impulse. The authors suggest that researchshould be carried out into impulse buying as a cause andeffect in other shopping contexts such as catalogues and theinternet before any wider conclusions can be drawn.The study confirms that retail salespeople and TV shopping

presenters who build close relations with the consumer areable to influence purchase decisions by prompting impulsebuying. Park and Lennon suggest that the TV presentershould aim to entice the consumer by making friendlyremarks, encouraging the viewer to stay tuned and providingcontact details. But the authors also point out the negativeconsequences of impulse buying such as credit card debt orproducts not being used after purchase. It is thereforeimperative that marketers behave responsibly, part of whichinvolves ensuring that procedures for the smooth return ofunwanted goods are in place. Since statistics demonstrate thatthe inability to inspect products purchased from a televisionshopping channel has resulted in a return rate of between 20and 40 percent, this is clearly importantSurvey participants were asked to recall past shopping

experiences. The authors point out that some inaccuraciesmay have resulted because older respondents had to rely onmemory to calculate their average shopping or viewing time.They also suggest that the amount of time spent andpurchases made in the respective shopping contexts could besignificant, although this factor was not analyzed in the study.

(A precis of the article “Psychological and environmentalantecedents of impulse buying tendency in the multichannelshopping context”. Supplied by Marketing Consultants forEmerald.)

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