Consumer Responses to Online Food Retailing

Michelle A. Morganosky and Brenda J. Cude

Consumer behavior in the context of online food retail channels is analyzed. The research is a follow-upto an earlier study conducted in early 1998 on consumer response to online food shopping. In the 1998study (N=243), a majority of the sample (51 percent) were "new" users of online food shopping (< 6months); 35 percent were "intermediate" users (1-6 months); and only 14 percent were "experienced"users (> 6 months). In contrast, the new user segment in the follow-up study (N=412) was 29 percent;the intermediate segment was 28 percent; and the experienced group was 43 percent. Demographicprofiles and shopping behaviors of respondents in the two studies are compared. Using cluster analysis,four distinct segments of online food shoppers are identified. Marketing strategy implications for onlineretailers and store retailers are discussed.

Background and Purpose

Predictions concerning demand for online foodshopping run the full gamut from best- to worst-casescenarios. The reality is that current online grocerysales ($200 million in 1999) are meager at best whencompared to annual supermarket volume ($400 bil-lion). However, online revenues are growing at a fasterrate than store revenues and are predicted to continueto outpace store revenues into the future (Radice,1999). Michael Sansolo, senior vice president of theFood Marketing Institute, predicts that existing storeretailers will be the key players in the future of onlinefood marketing (Mathews, 1999).

Some believe that either/or discussions aboutbrick-and-mortar versus online channel competition areinappropriate and that the most viable model for thefuture is some combination of both (Donegan, 2000).Others predict a bifurcation of the market where lowermargin, lower involvement goods are sold primarilythrough online channels and higher margin, in-storeexperience goods (for example, produce) are soldpredominately through store channels (Hickins, 2000).One forecast states that the greatest benefit of onlinegrocery shopping to consumers will be easy replen-ishment of staple items, such as dry goods, soaps,paper products, and other typical pantry items(Donegan, 2000). Peterson, Balasubramanian, andBronnenberg (1997) argue that all Internet-relatedmarketing activities take place in the context of mar-keting activities in conventional marketing channelsand should be considered in this context.

Michelle A. Morganosky is professor, Consumer and RetailMarketing, Department of Agricultural and Consumer Econom-ics, University of Illinois, Urbana, IL. Brenda J. Cude is profes-sor and head, Department of Housing and Consumer Economics,The University of Georgia, Athens, GA.

Which consumers are most likely to use anonline grocer? The Consumer Direct Cooperativeconducted a two-year study involving interviewswith more than 1,800 consumers nationwide andtracked the purchasing histories of 800 online shop-pers (Kutz, 1998). Their research identified fivemajor groups of potential online grocery shoppersbased on respondents' attitudes toward time, shop-ping, and technology. The group they termed"Shopping Avoiders" dislikes grocery shoppingwhile "Necessity Users" have limitations that makegoing to a store difficult. "New Technologists" areyoung and comfortable with technology while the"Time Starved" are less sensitive to price and willpay extra to free up time in their schedules. Thegroup termed "Responsibles" has available time andgets an enhanced sense of self-worth from shopping.The research indicated that the groups cut acrossincome and educational levels, age groups, andgeographic locations.

While online grocers vary somewhat in howthey describe their ideal customer, a frequent de-scription is the suburbanite with a higher income(Ingram, 1999; Kirsner, 1999; Lardner, 1998; Rans-dell, 1998). Research suggests, however, that thisdescription may be too narrow. Park et al. (1998)conducted focus group interviews with consumerswho had previous experience with home shoppingfor groceries. The researchers categorized homegrocery shoppers into two groups: hi-tech babyboomers and older/physically challenged consumers.Hi-tech baby boomers were interested in homeshopping for the convenience or the novelty andtypically used the computer to order items. In con-trast, the second group was composed of olderand/or physically challenged consumers who had

Introduction

Journal of Food Distribution Research

lower incomes and were more likely to live alone.They typically bought groceries via home orderingbecause of physical difficulty in going to the storeand tended to phone in orders when possible ratherthan ordering directly online.

Research by Hiser, Nayga, and Capps (1999)also confirms that consumers other than those insuburban dual-income households may be a viablemarket segment for online grocery shopping. Theysurveyed 390 consumers in four supermarkets inTexas. About one-third of the shoppers were famil-iar with online food shopping even though it was notavailable in the market area at the time of the survey.Logit analyses indicated that income, the number ofpeople living in the household, the presence ofchildren, and gender were not significant determi-nants of interest in using an online grocer; however,age and education were. People over age 50 wereless likely to consider using the service (compared topeople 18-29 years old) as were those with lesseducation.

In a recent study, Ward (2000) modeled con-sumer channel choice (online vs. store) and esti-mated the effects of various demographic variables.He found that, after controlling for demographicfactors, experience with online shopping increasedconsumer willingness to purchase online. He foundthat the likelihood of making an online purchaseincreased steadily with the amount of time that onehad been an Internet user. In addition, more experi-enced users were more proficient shoppers. Wardincluded 17 different product .categories in hisanalyses (including food and beverages) and foundconsistent results across product categories. Heconcluded that the number of consumers with accessto online shopping is increasing exponentially andthat experience influences online purchase behavior.

The purpose of the present study was toprovide a follow-up perspective on a study ofonline food shoppers conducted in 1998. Thisstudy was not a panel study (same subjects at twodifferent points in time) but a trend survey (a newsample was drawn at a second point in time tolearn what changes may have occurred). In theearlier study (Study 1: N=243), more than one-half (51 percent) of respondents were "new" users(buying food online for less than one month); 35percent were "intermediate" users (1-6 months);and 14 percent were "experienced" users (morethan six months' use). Our purpose in conductingthis follow-up study (Study 2: N=412) with cus-

tomers of the same online grocer was to answertwo research questions about consumer demandfor and response to online food shopping. First,we asked if consumer experience with online foodshopping was changing. That is, would the distri-bution of new, intermediate, and experiencedusers be different 18 months later? Second, assuggested by Ward's (2000) research, we askedhow experience with online grocery shoppingrelates to other consumer behaviors and demo-graphic characteristics. Third, we asked if it waspossible to segment the online grocery shoppersbased on demographic and behavioral variables.

Method

Data for the follow-up study were collected inAugust through November 1999 from 412 consum-ers who purchased groceries from Schnucks ExpressConnection, the Internet shopping service ofSchnucks Markets, a St. Louis-based chain of 92stores in Illinois, Missouri, and Indiana. SchnucksMarkets is privately owned and reported sales of $2billion in 1999 (Supermarket News, 2000). At thetime of data collection, Schnucks offered the servicein the St. Louis market area plus other markets inMissouri, Illinois, and Indiana. Schnucks ExpressConnection shoppers can choose to pick up theirorders or to have them delivered. The costs areabout $13 for same-day delivery, $10 for next-daydelivery, and $6 if the consumer picks up the order.A minimum order of $10 is required.

During the survey period, a shopper who com-pleted an order at the Schnucks Web site was invitedto click on a link to the researcher's site to answerquestions about online grocery shopping. Incentiveswere not offered to complete the survey. Once at thesite, shoppers were asked to respond to 29 ques-tions; 22 were closed-end questions, and seven wereopen-end questions. Only a subset of the data arereported in this paper. Responses to one open-endquestion-What specific grocery items would younot buy online?-are reported in this paper. The datafrom the closed-end questions reported in this papercame from questions asked of consumers regarding:

(1) length of time buying groceries online;

(2) whether groceries were usually delivered orpicked up;

(3) reasons for shopping online;

6 March 2001

Consumer Responses to Online Food Retailing 7

(4) most important reason to shop online;

(5) whether there were grocery items they wouldnot buy online;

(6) perception of time spent grocery shoppingonline versus in-store;

(7) where online grocery items were previouslybought;

(8) where most grocery items are currently bought;

(9) amount spent on most recent online grocery order;

(10) how most recent order compares to averageorder amount;

(11) frequency of ordering online for groceries;

(12) age;

(13) gender;

(14) education;

(15) number of children in household;

(16) number of adults in household;

(17) income; and

(18) zip code.

Including zip code information in the collecteddata served two purposes. First, it allowed the re-searchers to identify the market area in which therespondent lived. In addition, zip code informationand other demographic data could be compared toeliminate responses that matched perfectly and thuswere likely from the same household.

Results

We compiled a demographic profile of whowas grocery shopping online using the followingvariables: age, gender, education, market area,household size, and income. Comparative profilesfor respondents in Study 1 (April-June 1998) andStudy 2 (August-November 1999) are provided inTable 1. The demographic profiles were similar onmost variables across the two studies.

Table 1. Demographic Variables for Study 1 and Study 2 Participants.Study 1 Study 2

Variable Percent of total Percent of total Chi-SquareAge 1.53

34 or younger 33.8 30.335-44 34.6 37.645-54 22.5 21.155 or older 9.2 10.9

Gender 0.02Male 17.7 17.3Female 82.3 82.7

Educational Level 2.59b

High school education or less 8.0 10.2High school graduate w/ some college education 34.3 38.3College graduate 57.7 51.5

Income ($) 6.0229,999 or less 11.8 11.730,000-49,999 14.1 21.150,000-69,999 23.6 17.870,000 or more 50.5 49.4

Number of Adults 8.95 b

One 19.9 22.8Two 63.2 68.2Three or more 16.9 9.0

Number of Children 49.00 a

Zero 16.9 48.1One 27.3 14.3Two 35.7 20.6Three or more 20.1 17.0

Market Area 1.35St. Louis, Missouri area 57.1 50.0Other markets 42.9 50.0

p< .001.b p <.05.C p<.10.

MorPganosky, M.A., and B. J Cude

Journal of Food Distribution Research

The majority of respondents in both studieswere younger than 45 years of age (68 percent),female (82 percent vs. 83 percent), and had somecollege education or a college degree (92 percent vs.90 percent). Many reported an annual income of$70,000 or more (51 percent vs. 49 percent), while12 percent in both studies had an annual incomebelow $30,000. In most households, there were twoadults (63 percent vs. 68 percent) in both studies.One-half or more of the respondents in both studieslived in the St. Louis, Missouri market area (57percent vs. 50 percent).

Demographic Characteristics

Many of the respondents in both studiesmatched the description of online grocery shopperstypically provided by online grocers-suburbaniteswith incomes higher than $75,000 (Ingram, 1999;Kirsner, 1999; Lardner, 1998; Ransdell, 1998).However, chi-square analyses indicated a significantrelationship between being in Study 1 vs. Study 2and three demographic variables. Study 1 respon-dents were somewhat better educated than Study 2respondents; 58 percent were college graduates,versus 52 percent in Study 2. There were moresingle-adult households in Study 2 than there werein Study 1. Chi-square analyses also indicated asignificant relationship between being in Study 1 vs.Study 2 and in the number of children in the house-hold. Almost one-half (48 percent) of respondents inStudy 2 had no children, compared to 17 percent inStudy 1. However, 37 percent of he respondents inStudy 1 did not answer this question. The format ofthe question was changed for Study 2, and all re-spondents answered it. If the question design inStudy 1 led households without children to leavethat answer blank, the proportion of respondents inStudy 1 without children would have been verysimilar to the proportion in Study 2 (46 percent vs.48 percent, respectively).

Shopping Behavior Results

While the overall demographic profile of onlineshoppers was not substantially different 18 monthsafter the first study, notable shifts were observed invarious shopping behaviors (Table 2). First, respon-dents had more experience with online groceryshopping. Fourteen percent of Study 1 respondentssaid that they had been buying groceries online formore than six months; 35 percent for between one

and six months; and a majority (51 percent) for lessthan one month. However, in Study 2, 43 percent ofthe respondents had more than six months' experi-ence buying groceries online, a difference of 29percent. Furthermore, compared to Study 1, farfewer of the online shoppers in Study 2 were newonline grocery shoppers [22 percent fewer in Study2 (29 percent) than in Study 1 (51 percent)]. Most(90) of the 120 new users in Study 2 indicated thatthe order they placed at the time they responded tothe survey was their first online grocery purchase.

Among the rest of the Study 2 sample, 22percent said that they grocery shopped online oncea week; 36 percent, every two weeks; 27 percent,every four weeks; and 15 percent, every six to eightweeks. The median order amount in Study 2 was$115, and the mean was $134. (We did not ask thisquestion in Study 1.) Excluding first-time orderers,two-thirds of the respondents said that the dollaramount listed was typical of an average order.

Respondents in Study 2 continued to favordelivery (79 percent) over pick up (19 percent), andthis was the only shopping behavior for which wedid not detect a statistically significant differencebetween studies. There were notable differencesbetween Study 1 and Study 2 respondents in theirwillingness to buy all or most of their groceriesonline. A majority of Study 2 respondents (62 per-cent) said that they now buy all or most of theirgroceries online, compared to 19 percent of respon-dents in Study 1. These differences may be indica-tive of some movement away from a complementarymodel of channel choice (purchasing online and inretail stores).

Among Study 2 respondents who continued tobuy most of their groceries in a retail store, 71percent said that they bought most of their groceriesat Schnucks stores; 10 percent said other supermar-kets; and 19 percent reported that they bought mostof their groceries elsewhere, including combinationsof more than one type of retail store. Study 2 re-spondents were also asked where they previouslybought the groceries they now buy online. Sixty-twopercent said that the online items were previouslypurchased at the retailer's stores; 30 percent at othersupermarkets; 3 percent at supercenters; 2 percent atlimited line discount stores; and 1 percent at ware-house clubs.

Thus, it appears that there is a reasonably largetransfer of online sales from the retailer's stores tothe retailer's online channel. For this retailer, online

8 March 2001

Consumer Responses to Online Food Retailing 9

Table 2. Shopping Behavior Variables for Study 1

VariableExperience with online grocery shopping

Less than one monthOne to six monthsMore than six months

Usually have groceries delivered or pick up orderDeliveredPick upPick up as often as have delivered

Buy groceries only or mostly onlineNoYes

Most important reason to shop onlineConvenience/timePhysical constraintsHate grocery shopping/hate grocery storesBuying for a businessCan avoid impulse buyingDo not like standing in lineOther

Grocery items will not buy onlineNothingMeats and/or produceItems cannot buy because are not offeredPerishablesOtherDon't know

Perception of time spent online vs. in-storeA lot lessLessSame or more

p <.001.b p <.05.p<.10.

and Study 2 Participants.Study 1 Study 2

Percent of total Percent of total

51.234.714.1

75.421.7

2.9

80.719.3

73.614.95.0L.5

1.20.82.1

48.430.2

4.43.99.93.3

30.821.747.5

29.227.543.3

79.218.52.3

37.762.3

53.318.313.00.83.33.08.5

79.415.10.50.54.50.0

52.628.519.0

items are picked directly from stores and then deliv-ered to customers. Sales generated by online ordersare added to those of the store from which they werepicked. Under such an arrangement, store managerslikely view online sales as augmenting store volumerather than detracting from it or at least holding onto store business that might go elsewhere. As notedabove, 30 percent of Study 2 respondents said thatthey previously bought their online purchases atsupermarkets other than Schnucks. This likely indi-cates a transfer of sales from competing store retail-ers into the retailer's online channel. Thus, the onlinechannel may provide a way to "protect" existingstore sales and to attract customers from competingstores.

Chi-square analyses also indicated a significantrelationship between Study 1 vs. Study 2 and the

primary reason for grocery shopping online. Whilea majority of Study 2 respondents (53 percent) citedconvenience as the most important reason for buyinggroceries online, the proportion was substantiallyless than that in Study 1 (74 percent). However, ahigher proportion (53 percent) of Study 2 respon-dents said that, by moving their grocery shoppingonline, they were spending a lot less time groceryshopping (31 percent in Study 1). This likely reflectsthe greater experience of Study 2 respondents withonline grocery shopping. "Hating" grocery shoppingand grocery stores was cited more often in Study 2(13 percent) than in Study 1 (5 percent) as the pri-mary reason for grocery shopping online. In addi-tion, physical constraint issues-such as disabilitiesthat made driving, shopping, and carrying groceriesdifficult or impossible-were somewhat more likely

Chi-Square62.60a

1.28

111.03a

80.44a

74.42a

107.01a

- -.... I I I~ II I I . . . . . II I

I

Morganosky, M.A., and B. J Cude

Journal of Food Distribution Research

to be cited as the primary reason for online groceryshopping in Study 2 (18 percent) than they were inStudy 1 (15 percent).

A far higher proportion of Study 2 respondentswas willing to buy any grocery item online. A ma-jority of Study 2 respondents (79 percent) said thatthey were willing to buy any grocery item online,compared to 48 percent in Study 1. All productcategories appeared to gain in consumer acceptabil-ity. For example, nearly one-third of the respondentsin Study 1 listed meat or produce as items that theywould not purchase online. In Study 2, this propor-tion dropped to 15 percent and may indicate expan-sion of the consumer's "consideration set"(Lehmann and Pan, 1994; Nedugade, 1990; Shockeret al., 1991) for products purchased online.

Relationships Between Demographicsand Shopping Behaviors

Relationships between variables within eachstudy were analyzed and are reported in Table 3.The overall pattern of relationship between variableswas fairly similar for each study. A number ofdemographic variables were significantly related tothe most important reason for shopping online.

Compared to those who cited physical constraintsas most important, those that shopped online for otherreasons, including convenience, tended to have higherincomes, were younger, and lived in households withlarger numbers of adults and children. Of those whoshopped online for reasons other than physical con-straints, 56 percent (Study 1) and 55 percent (Study 2)reported annual incomes of $70,000 or more, com-pared to 18 percent (Study 1) and 23 percent (Study 2)of those who shopped online due to physical con-straints. Of those who shopped online primarily due tophysical constraints, 20 percent (Study 1) and 32percent (Study 2) were aged 55 or over, compared with5 percent (Study 1) and 6 percent (Study 2) of thosewho shopped online for other reasons. Those whoshopped online for reasons other than physical con-straints were more likely to say that online shoppingsaved time than were those for whom physical con-straints were the primary reason for grocery shoppingonline. Education was also significantly related to themost important reason for shopping online but only inStudy 2. In Study 2, 29 percent of those who shoppedonline due to physical constraints said that they werehigh school graduates with some college, compared to41 percent of those who shopped online for otherreasons.

With the exception of education in Study 2,demographic variables were not significantly relatedto willingness to buy any grocery item online ineither study. Respondents in Study 2 who restrictedtheir online choices to only some grocery items weresomewhat more likely to be college graduates (64percent) than were those who said that they wouldbuy any food or grocery item online (49 percent).Furthermore, in Study 2, there was a marginallysignificant relationship between willingness to buyany grocery item online and the respondent's per-ception of time spent grocery shopping. Fifty-fivepercent of respondents who were willing to buy anygrocery item online said that they spent a lot lesstime grocery shopping since moving their purchasesonline, compared to 46 percent of those who re-stricted their online choices.

With the exception of education in Study 2,demographic variables were not significantly relatedto perception of time spent shopping online versusin a retail store. Respondents in Study 2 who thoughtshopping online took less time tended to be bettereducated. In both studies, those who thought shop-ping online took less time were more likely to citereasons other than physical constraints as their mostimportant reason for shopping online and were morelikely to state that they buy all or most of theirgroceries online. Furthermore, in Study 2, those whothought online shopping took less time were morelikely to be experienced users (> 6 months).

In both studies, age was related to experiencewith online grocery shopping. New users (< 1month) tended to be somewhat younger than moreexperienced users (> 6 months). In Study 2, percep-tion of time spent shopping online versus in the storewas significantly related to experience with onlinegrocery shopping. Among those using the onlineservice less than one month, only 38 percent saidthat shopping online took a lot less time than in-store shopping, compared to 58 percent of thosewith more than six months' experience.

Segmentation of Online Food Shoppers

Cluster analysis was used to classify onlinefood shoppers from Study 2 into segments, usingdemographic variables (age, gender, education,income, number of adults in household, and numberof children in household) and shopping variables(where most groceries bought, reason to shop online,willingness to buy all items online, perception oftime spent shopping, and experience level). As a

10 March 2001

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Morganosky, M.A., andB.J. Cude Consumer Responses to Online Food Retailing 11

Journal of Food Distribution Research

result of cluster analysis, a four-cluster solutionemerged. Mean scores and standard deviations fordemographic and shopping behavior variables byclusters are presented in Table 4.

The four-cluster solution was validated usingdiscriminant analysis, ANOVA, and a scatter plot ofclusters. The result of disciminant analysis showed that97 percent of respondents were correctly classified (Table5). Finally, a scatter plot of the clusters provided evidencethat the dusters occupied distinct positions when graphi-cally arranged. Thus, we found support for segmentingthis group of online food shoppers.

Cluster 1: Physically Constrained Shoppers (16%)

Consumers in this cluster were primarily moti-vated to use the online channel for grocery purchasesdue to physical constraints that hindered their abilityto shop, drive, or cany groceries. In contrast, the threeother clusters were primarily motivated by conven-ience and time savings factors. An inspection of thequalitative comments provided by respondents re-vealed that physical constraints were minor to majorin nature and interfered with completion of the gro-cery shopping task. Some typical comments made byrespondents follow:

problem, and I love shopping this way. Iplan on continuing. "

"My husband and 1 are both physically un-able to walk long distances or to carry heavyobjects. This is a real life saverfor us. "

"I hurt my back! They deliver the grocer-ies to my kitchen counter. This is a tre-mendous help. Also, I have a sickpersonin the home and can't leave. "

As might be deduced from these comments,Physically Constrained Shoppers tended to be olderthan shoppers in the other three clusters. In addition,household income was lower than among FemaleInvolved Shoppers (Cluster Two) or Female Conven-ience Shoppers (Cluster Four). There were fewerchildren in the households of Physically ConstrainedShoppers than there were in Female Involved Shopperor Female Convenience Shopper households. Physi-cally Constrained Shoppers included both male andfemale respondents, in contrast to Cluster Two andCluster Four (which were exclusively female) andCluster Three (which was exclusively male).

Cluster 2: Female Involved Shoppers (55%)"I recently had surgery and it is very difficultcarrying groceries up twoflights ofstairs."

"My husband has arthritis, and I havebackproblems; the online shopping takescare of the heavy and pantry items. "

"It is hard for me to stand and walk along time, especially in big stores andlong lines of waiting to get checked out. "

"l am not able to walkwell and cannot carryand make trips to carry into apartment."

"My arthritis is bad enough that walking andcarrying wear me out after a very short time.By using the computer, I still have control my-selfinstead of depending on myfamily. "

"I am in a wheelchair and cannot driveor carry groceries. "

"I have been in and out ofhospitals the lastyear. I loved the convenience of shoppingthis way and am somewhat healthier now;however, walking and bending are still a

This exclusively female cluster differed from thePhysically Constrained Cluster in several ways. Com-pared to Physically Constrained Shoppers, FemaleInvolved Shoppers were younger, had higher incomes,and had more children in the household. Female In-volved Shoppers were fairly similar to Female Con-venience Shoppers (Cluster Four); however, theydiffered in one important way. Female Involved Shop-pers were less willing to buy all grocery items online(especially meat and produce) than were Female Con-venience Shoppers. It appears likely that many of theFemale Involved Shoppers will continue to patronizeboth store and online channels because they wantpersonal involvement in selecting some grocery items.Some typical comments follow:

"I usually make one trip to the store forproduce and sometimes meat. I like to seethe fruits and veggies so I know how ripe or

fresh they are. Meats are easier to see too. "

"I don't like to buy my produce online.It 's just a personal thing and I want fruitthat looks a certain way."

12 March 2001

Consumer Responses to Online Food Retailing 13

Table 4. Cluster Means and Standard Deviations.Cluster 1 Cluster 2

Age 2.77 2.02(1.06) (.82)

Gender

Education

Income

Adults in household

Children in household

Buy groceries only ormostly online

Most important reasonto shop online

Willing to buy allgrocery items online

Perception of time spentonline vs. in-store

Experience with onlinegrocery shopping

1.15(.36)

2.38(.75)

2.42(1.11)

1.85(.70)

.44(.85)

1.33(.47)

1.00(.00)

1.83(.38)

1.98(.83)

2.35(.74)

1.00(.00)

2.41(.67)

3.12(1.07)

1.88(.50)

1.23(1.14)

1.37(.51)

1.99(.02)

1.96(1.9)

1.59(.78)

2.16(.85)

Cluster 31.89

(1.03)

2.00(.00)

2.51(.63)

3.00(1.00)

1.78(.64)

.67(1.07)

1.38(.58)

1.98(.15)

1.82(.39)

1.62(.72)

1.91(.87)

Cluster 41.69(.74)

1.00(.00)

2.57(.54)

3.57(.71)

F Value14.75a

591.87a

1.09

11.08a

2.08(.34)

1.33(1.09)

1.33(.47)

1.98(.14)

1.02(.14)

10.06 a

.21

1,549.3 a

165.54a

1.63(.73)

2.20(.82)

2.25°

ap< .001.bp <.05.Cp<.10.

Table 5. Classification Matrix for Four-Group Discriminant Analysis.aPredicted Group Membership

Actual Group # of cases Cluster 1 Cluster 2 Cluster 3 Cluster 4

Cluster 1 52 52 0 0 0100.0% 0.0% 0.0% 0.0%

Cluster 2 179 1 171 0 7.6% 95.5% 0.0% 3.9%

Cluster 3 45 1 0 44 02.2% 0.0% 97.8% 0.0%

Cluster 4 47 0 0 0 470.0% 0.0% 0.0% 100.0%

aPercent of grouped cases correctly classified: 97.2%.

I

Morganosky, M~A., andBJJ Cude

Journal of Food Distribution Research

"I am afraid that I will not get quality(fresh fruit andproduce) merchandise. "

"I'd rather look at it (meats) and pick itout myself. Most of the time Ifeel that wayabout produce as well. "

"I am very particular and would prefer tosee these items (produce and meat) beforepurchasing."

"I don't like to buy produce (online). Ihave in the past, and the shopper's qual-ity standard did not match mine. "

Cluster 3: Male Convenience Shoppers (14%)

This exclusively male cluster was motivatedto shop online by convenience (similar to FemaleInvolved Shoppers and Female ConvenienceShoppers). In addition, Male Convenience Shop-pers were younger than Physically ConstrainedShoppers (Cluster One); however, Male Conven-ience Shoppers were less likely to have childrenliving in the household than were either FemaleInvolved Shoppers or Female Convenience Shop-pers. Male Convenience Shoppers deviate fromthe stereotypical image of the online segment asbusy suburban families. Some typical commentsfollow:

"Grocery shopping is a necessary evil.Doing it online, I can still get it done onmy schedule, not based on when the storeis less busy. "

"Much more convenient (online shop-ping) and much less hassle, and the de-liver charge is reasonable, consideringthat I would spend at least $10 more atthe grocery anyway if were there 'with'the actual items."

"My free time is more valuable to methan the $10 delivery charge."

"I am going to school and working andI can do my shopping at odd hours."

"I don't enjoy grocery shopping. Thestores are usually crowded The aisles arepacked with too many products and ad-vertisements. Generally, the check out is

most stressful. Internet shopping is veryconvenient."

"I am unable to get to the store duringthe week; andfor the cost, I am able to letsomeone else shop for an hour and bringit to me!"

"I don't like shopping, so doing my shop-ping online eliminates the problem. "

"Online shopping gives me time to do thethings I really enjoy. "

Cluster 4: Female Convenience Shoppers (15%)

These shoppers were fairly similar to FemaleInvolved Shoppers except that they were youngerand household incomes were somewhat higher. Animportant distinguishing difference between the twoclusters was that Female Convenience Shopperswere more willing to buy all grocery items online(including meat and produce) than were FemaleInvolved Shoppers. Female Convenience Shoppersmay be less particular about their purchases andhave less need to be involved in their selection.Since they are younger, they may also be lessknowledgeable about product selection and thusmore willing to trust expert pickers. While thiscluster was not the largest in terms of numbers, it isan important group from a marketing perspective.

On average, this group had the highest incomeand the greatest number of children and adults in thehousehold of any of the clusters. Many had youngerchildren and were time-constrained. Some typicalcomments follow:

"We have young children and both work. I don'twant to spend our valuable time together at a gro-cery store."

"I workfull-time; my husband travels; I have chil-dren; my schedule is very busy. I love shopping onthe Internet because I can also do the laundry andwatch TV or a movie all at the same time withoutleaving the house."

"My 2 year-old doesn 't want to stay in the cart, andit is hard to concentrate and watch him. If do havea sitter, I have other things Iprefer to do. "

"I can spend the quality time at home with the kids,rather than spending the hour with them shopping."

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Consumer Responses to Online Food Retailing 15

Discussion and Implications

Before discussing the results, limitations shouldbe acknowledged. A non-probability sample for aspecific Internet grocery shopping service was used.Therefore, generalizations to other audiences maynot be appropriate. In addition, the online grocerwas affiliated with a supermarket that is well-knownin the communities it serves and has local stores inthose communities. Thus, the results may not be asapplicable for warehouse-based online grocers asthey are for store-based online grocers.

The distribution of new, intermediate, andexperienced users did change in the 18-month inter-val between studies. In fact, the change was dra-matic-14 percent of respondents in Study 1 wereexperienced online grocery shoppers, compared to43 percent in Study 2. However, comparison of theresults from the two studies suggests a relativelystable demographic profile of online grocery shop-pers. Compared to the general population, onlineshoppers in both of the studies were better educated,had relative higher incomes, and tended to besomewhat younger. They were also predominantlyfemale. The majority of respondents in both studieslived in households with children.

While there were far more experienced usersparticipating in Study 2, the number of new users ineach study was nearly identical (124 vs. 120). Froma marketing perspective, this suggests the possibilitythat the online channel is able to attract a sizablenumber of new users and retain a portion of theseusers over time. While we have no specific data onconsumers who tried online shopping and returnedto in-store shopping, the data suggest that this par-ticular online food retailer has found a way to moveat least a portion of in-store shoppers from non-use,to first-time use, to regular online use. (We realizethat most retailers would not typically equate "morethan six months" with "regular use" status. However,the online channel has been available to consumersfor a relatively short period of time.)

Compared to those with less experience, moreexperienced online grocery shoppers (> 6 months)were disproportionately more likely to say that theynow spend a lot less time grocery shopping. Fur-thermore, those that reported dividends from timesavings were disproportionately more likely to saythat they buy most or all of their groceries onlineand were more willing to buy any type of groceryitem online. Perhaps one or both of these behaviors

is necessary to realize time savings in online groceryshopping. For more experienced online groceryshoppers, the choice set appears to be simultane-ously narrowing at one level (online channel) andbroadening at another (product types). This changesuggests exclusiveness in relation to channel choiceand inclusiveness in relation to the product choice.

From the marketer's perspective, this likelyrepresents a highly attractive picture of consumerdemand; consumers shop more exclusively with aretailer but are willing to buy a wider range or set ofgoods from that particular retailer.

It is not possible for us to clearly specifywhether the "perception of time spent" variable is anantecedent or consequent variable. That is, does theconsumer's belief that online grocery shoppingsaves time influence their willingness to buy gro-ceries online and to buy all grocery items online?

Or, is it more likely that the consumer's per-ception of time savings changes with experience, ass/he becomes more willing to buy various itemsonline and to use the online channel for most gro-cery purchases? We suggest that the influence islikely in both directions. As consumers becomemore experienced users of this new marketing chan-nel, they may indeed improve their efficiency andreduce the overall time spent to complete the shop-ping task. Consumers who become online groceryshoppers because of anticipated time savings may bemore likely than other consumers to believe thatshopping online saves time.

In fact, online shoppers may exhibit what Kahnand McAlister (1997) referred to as a "confirmationbias;" that is, a tendency to see that which confirmswhat one believes. For example, if consumers per-ceive an online delivery charge as an added "cost,"they may be more likely to perceive a time-savings"benefit" to offset that cost. Thus, perceptions oftime-saving efficiencies (whether accurate or not)may be viewed as influencing other consumer be-haviors (for example, willingness to buy most itemsonline) as well as being influenced by these vari-ables. Furthermore, if we think of online deliverycharges as "fixed" costs, these become proportion-ately less as the consumer's purchase total per orderincreases.

It is our view that time perceptions, motiva-tions, experience levels, willingness to buy fromalternative channels of distribution, and productitem choice sets likely interact in various combi-nations for different consumer segments. Indeed,

Morganosky, M.A., and B.J. Cude

Journal of Food Distribution Research

we found preliminary evidence for the segmenta-tion of online grocery shoppers based on motiva-tion, gender, willingness to buy all grocery itemsonline, number of children in the household, andtime savings perceptions. According to Schiffmanand Kanuk (2000), segmentation of consumermarkets is most effective when the segments areidentifiable, stable or growing, reachable, andsufficient in size. Our view is that the first threecriteria for effective segmentation of the onlinegrocery market likely can be met; however, suffi-ciency in terms of size is still unknown.

Managerial Impiications

Peterson, Balasubramanian, and Bronnenberg(1997) predicted that use of the Internet would notlikely contribute to increased consumer spendingoverall. Instead, as suggested by Hagel and Eisen-man (1994), E-commerce would likely result in aredistribution of existing revenues among channelsor among members within a channel. In our studywe found some support for this proposition. Sixty-two percent of respondents in the follow-up studysaid that the groceries they now buy online werepreviously bought at that particular retailer's stores.

Their online purchases likely represent a redistri-bution of revenues into the online channel from thestore channel. Perhaps even more surprising is that 30percent of respondents said that their online purchaseswere previously bought at competing brick-and-mortarsupermarkets, representing what appears to be a redis-tribution of revenues between retailers.

Park et al. (1998) suggested that, if home shop-ping becomes "mainstream," it could have a nega-tive effect on supermarket sales. We suggest thathome shopping does not have to become "main-stream" to have an impact, given the highly com-petitive nature of the U.S. market and the notori-ously low profit margins within the food retailingindustry.

Within such a context, the hybrid model (pick-ing online orders out of existing stores) may beintuitively appealing to store retailers consideringentry into retailing. The hybrid model is a fairly lowcost method for testing the market (at least whencompared with warehouse building). The hybridmodel may also allow early entry into the onlinemarket with subsequent first mover advantages. Inaddition, if the store retailer's positioning in existingmarkets is positive, unique, or service-driven, suchpositioning may transfer into the online arena.

However, picking from stores is generallyconsidered a more expensive approach than pickingfrom warehouses (especially when compared withefficiencies that can be achieved through state-of-the-art automated warehouses). Therefore, the hy-brid model may be an appropriate strategy in testingand introduction stages, but its long-term feasibilityfrom a cost perspective is questionable.

In general, what consumers want from onlineretailers is similar to what they want from storeretailers-convenience, quality, service, reasonableprices, and selection. The retailer's "offer" in theonline setting in many ways resembles the parame-ters of the in-store "offer." However, online foodretailing typically includes picking and deliveryservice considerations. How well retailers managethe unique aspects of online retailing factors maywell determine their ultimate success or failure.

Limitations and Directionsfor Future Research

Our paper was limited to an examination ofconsumer response to and demand for online foodretailing in the context of one type of online businessmodel (hybrid model with in-store picking). However,there are various other business models-including thecentral distribution model, mini-distribution centers inexisting supermarkets, and dual systems in which in-store fulfillment is used for fresh products and dedi-cated warehouses are used for slower moving items ornon-perishables. Research in the context of thesedifferent business models is suggested Analysis of thecosts and benefits of various models from the con-sumer's and retailer's perspective is encouragedWhich online strategy is most profitable for retailers?Which is most value-enhancing for consumers? Dodifferent consumer segments see the online service asadding value? Our research suggests that they do.Ultimately, consumers buy from those marketers thatthey believe offer the highest delivered value-thedifferential between total benefits and total costs of themarketing offer.

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Morganosky, M.A., and B.J. Cude