Consumers’ Interest in Alternative Food Delivery Systems:Results from a Consumer Survey in New Jersey

Ferdaus Hossain and Adesoji O. Adelaja

Changes in consumer demographic compositio~ information technology, labor force participatio~ and timedemands of the workplace have created demand as well as opportunities for the food retailing indust~ todeliver food using new alternative methods. Using a logit analysis, this study analyzes consumers’ interest inpatronizing four alternative food delivery mechanisms by examining the impacts of various socioeconomicand preference variables on consumers’ interest in using these services. Data for the study was obtained viasurveys conducted at various locations in New Jersey to gather information on consumers’ socioeconomicconditions and their interest in usiig four different methods of accessing food. Empirical results suggest thatyounger consumers, individuals with at least college education, and households having a larger food budgetare more likely to use these services. Interest in convenience contributes positively while concern overproduct quality, diversity, and prices negatively rdTect consumers’ interest in using one or more of theseservices. Gender, employment and marital statuses, and driving distance to nearest supermarket have effectson consumers’ interest level for some, but not all, of the alternative food delivery methods rudyzed.

Introduction

A paradigm shift is underway in food mar-

keting and distributio~ from traditional in-storeshopping toward alternative food delivery systems

(AFDSS). These alternative systems includeon-line shopping, telephone ordering, home-delivery services, and pick-up or drive-throughservices at supermarkets. Supermarket share oftotal food expenditure has been decreasing duelargely to the opportunity cost of shopping. On theother hand sales of fast food and home-deliveredfood have been increasing steadily. The shift to-ward alternative mechanisms for accessing food isa response to changing socioeconomic factors,rapid changes in Mormation technology, andchanges in consumers’ tastes and lifestyles, amongother things. For instance, many consumers todayfeel that they are time-starved as a consequence ofthe following factors: rising female labor-forceparticipation; more singleparent households;multiple job holdings; longer work hours; and in-creased job related stress (Kirschling and Linne-man, 1997). It is, therefore, no surprise that con-

The authors are, respectively, assistant professor and profes-sor, Department of Agricultural, Food and Resource Econom-ics, Cook College, Rutgers University. Adesoji Adelaja is alsodeanldirector of researck Cook College and the New JerseyAgricultural Experiment Station, and director, Food PolicyInstitute, Rutgers University, The research was partially sup-ported by the Food Policy Institute, Rutgers University.

venience is perhaps the most important factordriving consumers’ choice among alternativemeans of accessing food.

ht response to these changes, companies such asPeapo& Netgrocers, WebVq and HouseCaUs On-line now offix Internet-based ordering and deliveryservices. Others, such as Welsh Farm% offkr homedelivery of staples. Even supermarkets are now ex-panding their prepared food food com and homemeal-replacement activities and devoting more floorspace to these activities to meet growing demand forconvenient meal solutions. Although the use of theInternet as a vehicle for accessing food is recent phe-nomeno~ use of home delivery and mail order is notnew to American consumers. USDA historical dataon food expenditure using home delivery and mailorder dates back to 1954.1 The historical trend offood expenditure on home delivery and mail order ispresented in Figure 1. Compared to 1954, the vol-ume of sales through this method showed a decliningtrend until 1976. During the 1977 through 1987 pe-rio~ the trend reversed and returned to a level nearthat of 1954. Food sales via this method have regis-tered consistent and maiked increase since 1988:Total food expenditure on home delivery and mailorder increased from $3.38 billion in 1987 to $10.34billion in 1999. Such growth in sales using homedelivery and mail order is clearly reflective of con-sumers’ demand for convenience in accessing food.

] Data on food expenditure using home delivery and mail ordercan be accessed at <http:lhwnv.ers. usda.govhiefinglfood-mark/expend/data/history/homefood.htm>.

50 My 2000 Journal of Food Dis&ibution Research

0 I 1 ( r , ( I , , I , I , I , I , I 1 ) I , I I , I , $ I , I

1950 1955 1%0 1%5 1970 1975 19s0 19s5 1990 1995 2(XIO

Year

Figure 1. History of U.S. Food Sales Through Home Delivery and Mail Order.

Source: USDA (2000).

The above discussion suggests that food dis-tribution systems in the United States must findnew and innovative ways of delivering food toconsumers-such as home delivery, online order-ing and delivay, and mail order in an efficient andcost-effective manner. According to estimates bysupermarket operators, companies that do not of-fer home shopping services could be “frozen outof” 16.5 billion in annual sales (Kidding, Linne-mann, and Kochersperger, 1995). industry expertsbelieve that Internet shopping will reach 10 per-cent of food sales in 10 years (Kinsey, 1998). Ac-cording to another study, it is projected that 15–20million households will be using “consumer di-rect”z by the year 2007, with sales estimated at$85 billion (Orler and Friedma 1998). Homeshopping-for years an almost invisible compo-nent of the grocery business-is entering a newphase, and supermarkets that have always safely

2The emsumer Direet is a cooperative comprised of diverse com-pauies and grocery stores. It defines “wmsumer direct” as a “fidl-service ehaunel that helps consumers simplifjI their lives by pro-viding grcteries and related produets without goiug to a land-based store, usually aided by a personal computer or other auto-mated orderiug system” (Orler and FriedmaQ 1998).

ignored it could face severe bottom-line conse-quences if they do not give it proper attention(Kirschling, Linuemq and Kochersperger,1995). If supermarkets that are not involved inhome delivery lose 4 percent of their customers,they could lose 58 percent of operating profitsbefore taxes (Clowes, 1996).

Although home delivery and online foodshopping has increased in recent years and indus-try experts believe that the sector will continue toexperience signiilcant growth in the future, manyInternet retailers-both in food and non-food in-dustries-are finding that significant hurdles mustbe overcome in order to be successfid. Increas-ingly, retailers are failing in their quest to satis~the customers while remaining profitable at thesame time. Recent closures of E-commerce com-panies-like Cybershop, toy retailer Toysma@Internet fashion retailer Boo.com—and financialtroubles of pioneer online grocer Peapod highlightsome of the underlying problems in the expansionof the online grocery business. Traditional first-mover advantage did not assure success and prof-itability for Peapod. Among other things, highoperating cost, increasing competition from other

Hossain, Feralms and A&soji O. Adelaja Consumers’ Interest in Alternative Food Delivery Systems 51

online grocers, small profit margin, a pure Inter-net-based business model, and the costs of at-tracting customers are some of the challenges fac-ing the online grocery business. Considering thelosses incurred by Peapod (a $28.5 million loss onrevenue of $73.1 million in 1999), some industryexperts have expressed concern over the &tare ofthe online grocery business (Salkever, 2000~2000b). A recent article published in Internet Re-tailer quotes Alice Richter, of business consultingcompany KPMG Peat Marwic~ to suggest thatsurvival in this sector involves the continued tar-geting of high-income customers; the combinationof groceries with deliveries of other services, suchas dry cleaning and other errands (similar to whatStreamline has done in Orange County, Califor-nia); and the combination of online shopping withbrick-and-mortar stores. Other companies in thisindustry must learn from Peapod’s experience andstreamline their businesses in order to be success-ful in this emerging industry.

Despite recent developments in food retailingand huge growth potential for AFDSS, academic re-search has not fully explored the issue. Given thatfimdamental changes have been taking place in thefood retailing industry, it is extremely important tounderstand the evolution of this industry and toidenti& the factors that are driving the ongoingchanges. The present study contributes to a betterunderstanding of consumers’ attitudes toward andinterest in the AFDSS by identi&ing fhctors that de-termine consumers’ choice among alternative meth-ods of accessing food. Instead of focusing on onlineshopping via the Internet we model consumers’level of interest in four AFDSS: (1) home delivexy ofprepared meals; (2) home delivery of a iiill line ofgroceries; (3) drive-through pick-up; and (4) neigh-borhood truck delive~ of vegetables and meat prod-ucts. Some or all of these services could involve or-dering online or by telephone or fax.

Such an analysis is important to the food in-dustry in that it can guide the design of appropriateAFDSS for those consumer segments that are mostlikely to use them. The Consumer Direct Coopera-tive (CDC) identifies six potential consumergroups (Orler and Friedman, 1998):

(1) shopping avoiders—individuals who simplydislike going to grocery stores and wouldconsider any available alternative to avoidgrOCtXy shopping;

(2)

(3)

(4)

(5)

(6)

necessiy users+mlividuals who are limitedin their ability to go to the grocery stores;

new teclmologists~oung consumers veryftiliar with technology;

time-starved consumers-individuals willingto pay for services that will give them moretime to do other activities;

responsible consumers-those who feel thatit is their responsibility to do a good job ingrocery shopping; and

traditional shoppers-individuals who enjoygrocery shopping and avoid technology.

Of the above six consumer groups, all but the tra-ditional shoppers are likely users of the AFDSSanalyzed in this study.

With the growing population of educated,time-starved, technology-savvy customers, AFDSSare expected to grow steadily in the years to come.Thus, the objective of this study is to identifi thefactors that explain consumers’ interest level in thefour subject AFDSS and to quantitatively develop aprofile of the likely users of these food deliverymethods.

Methodology

A survey instrument was developed to gatherinformation on consumers’ sociodemographiccharacteristics, their shopping habits and priorities,and their interest in using the services. One sectionof the survey instmrnent focused on the socioeco-nomic characteristics of the respondents. Ques-tions in this section included age, gender, ethnic-ity, education, income, family size, employmentstatus and work habits, and home access to faxmachines, personal computers, and the Internet.Another section of the survey dealt with consum-ers’ shopping habits and priorities-such as fre-quency of shopping, distance traveled to grocerystores, average food budget, etc. Respondentswere also asked to rank, fi-om 1 (least important)to 5 (most important), the importance of variousconsiderations in choosing their food stores. Theseinclude selection and fi-eshness of products, lowprices, quality of service, convenience (that is,proximity to home or workplace), location(yroximity to other stores of interest), store ap-

52 JuJ32000 Journal of Food Distribution Research

pearance (that is, ambience), and wait in thecheckout line.

In another section of the survey, consumerswere asked to reveal their level of interest in thefour different AFDSS on a scale of 1 to 5, with 1representing no interest and 5 representing veryinterested.3 They also expressed their preferencesregarding preferred payment methods, frequencyand timing of home delivery, and interest in spe-cific commodities for home delivery service. Twogroups of customers were used to gather all rele-vant information. The f~st group of respondentswas selected at random at Kings Supermarket (invarious locations in New Jersey) and was invitedto complete the questionnaire. Specifically, con-sumers were surveyed at five different locations inNew Jersey. Each store was visited three times(twice during weekends and once during week-days) and at two different time periods (morningsand afternoons). A reasonable balance was main-tained with respect to the number of surveys com-pleted at each store and the time periods. The sec-ond set of questionnaires was mailed to customersof Parmalat-Welch Farm, a company that is well-known in the tri-state area as a supplier of icecream and other dairy and specialty dairy prod-ucts. Welch Farms currently offers home deliveryof specialty products in New Jersey. About 200customers of Kings Supermarket completed thesurvey, and about 500 more customers of WelchFarms were contacted by mail survey (350 werereturned). Of the completed/returned question-naires, about 400 were usable for analysis.

Model Specification

The objective of the study is to identifi thefactors that explain consumers; interest in t@DSsand to develop a profile of the likely users of theseservices. Specifically, a logit model is used to esti-mate the impacts of various socioeconomic andprefmence variables on the probabihty that a eon-snmer is highly interested in a particular alternative

3 Our study focuses only on measuring consumers’ interest inusing AFDSS; however, interest alone does not automaticallytranslate into actual use of these serviees. Costs associatedwith these services are also important determinants of growthin these services. Another of our ongoing studies addressesthe issue of how interest in these services changes when ques-tions about cost and other factors are included. As suck theresults of the study discussed in this paper should be inter-preted in proper context.

food deliv~ method. The logit model—a modelthat is commonly used in situations with a binarydependent variable-is selected because the asymp-totic characttistic of the model constrains the pr~dieted probabilities between O and 1. Since the datarepresent individ~ rather than group, observations,the standard choice of estimation method is themaximum likelihood (ML) method (Gujarati, 1992).Among the strengths of the ML estimator are con-sistent and asymptotically efficient parameter esti-mates (Pindyck and Rubinfel& 1997).

The empirical model assumes that the probabil-ity of observing a high interest level (in a particularAFDS), Pi, depends on a vector of independent va.ti-ables ~lj) associated with consumer i and variable j,and a vector of unknown parameters ~:

(1) Pi =FZi =F~i =l/[l+eXp– Zi],

where

F(Zi) = the value of logistic cumulative densityfunction associated with each possiblevalue of the underlying index ZI, and

pi= the probability that an individual revealshigh interest level in the particular alter-native food delivery metho& given theindependent variables Xis.

In the above equation, ~Xi is a linear combinationof the independent variables so that

where

Zi = unobserved index level or the log odds ofchoice for the ith observation;

i = observations;

P = parameters to be estimatd, and

&= random error or disturbance term.

The dependent variable Z, in equation (2) isthe logarithm of the probability that a particularchoice will be made. The estimated parameters ofequation (1) do not directly represent the marginaleffects of the independent variables on Pi. For a

Hossain, l’erahus and Adesoji 0. Adelaja Consumers’ Interest in Alternative Food Deliveiy Systems 53

continuous variable, the marginal effect on theprobability Pi that the dependent variable (y) takesthe value x = 1 is given by

(3) 6Pi /6kti =[~j exp-~i]/[l+exp- ~i]2.

However, if the independent variables are alsoqualitative or discrete in nature as is the case formost of the independent variables used in themodel, dpi /aij does not exist. In such cases, the

marginal effect of a discrete independent variableis obtained by evaluating Pi at alternative values ofXti. Marginal effects of such variables are deter-mined as:

(4) @i /&ij ‘~i:X~ ‘l-~i:Xij ‘O.

In empirical analysis, the following model isused to predict the probability that an individualwould reveal high interest in using one of the al-ternative food delivery methods:

Interest = f10+ @ntoth + /32fdbgt2

+ ~fdbgt3 + fl’Dis + ##cl

+ &Frsh + /37Pr + AQIW

+ flgConv+~lOAppr + fll~Wait

+ f12Fsz + ~1~Alt35+ &A35 -45

+ &Gndr + &Mar + flTEmp

+~1gIlt50+~1~150–100 + f120College

+ f121Grad+ AZPrmshop + 6,

where

Interest = 1 if the consumer reveals a high inter-est level in the particular alternativefood delivery method and Ootherwise;

Intoth = level of interest in receiving other fooditems via the deiivexy service (this vari-able is excluded from models for homedelivay of fidl grocay line and drive-through pick-up servic@4;

(5)

4 Home delivery of full groce~ line includes all items, andtherefore, interest in home delivery of other items (that is,variable Moth) is not included as an explanatory variable.Similarly, drive-through pick-up service does not involvehome delivery, and consequently, interest in home delivery ofspeeific items is not relevant for this model.

Fdbgtl =

Fdbgt2 =

Fdbgt3 =

Dis =

Sel =

Frsh =

pr=

Qlty =

Conv =

Appr =

wait=

Fsz =

Alt35 =

A35-45 =

Agt45 =

1 if the household spends less than $200per month on fbod and Ootherw@

1 if the household spends between$200 and $400 per month on foodand Ootherwise;

1 if the household spends morethan $400 per month on food andO otherwise;

Average driving distance to the usualgroce~ shopping site;

1 if the respondent assigns high im-portance to the selection of products inchoosing a food store and Ootherwise;

1 if the consumer attaches high impor-tance to the freshness of products inchoosing a food store and Ootherwise;

1 if the consumer attaches high impor-tance to low prices of products inchoosing a food store and Ootherwise;

1 if the consumer attaches high impor-tance to the quality of service inchoosing a food store and Ootherwise;

1 if the consumer attaches high impor-tance to the convenience of location inchoosing a food store and Ootherwise;

1 if the consumer attaches high impor-tance to the store appearance inchoostig a food store and Ootherwise;

1 if the consumer attaches high im-portance to the wait at the checkoutline in choosing a food store and Ootherwise;

number of members in the fhmily;

1 if the individual respondent is lessthan 35 years of age and Ootherwise;

1 if the individual respondent is be-tween 35 and 45 years of age and Ootherwise;

1 if the individual respondent is above45 years of age and Ootherwise;

54 July 2000 Jbumal of Food Distribution Research

(=j@ .

Mm.

Emp =

Ilt50 =

150-100 =

Igt100 =

School =

College =

@~.

Prmshop =

1 if the individual respondent is fe-male and Ootherwise;

1 if the individual respondent is mar-ried and Ootherwise;

1 if the individual respondent is em-ployed and O otherwise;

1 if the (annual) income is less than$50,000 and Ootherwise;

1 if the (annual) income is between$50,000 and $100,000 and O oth-erwise;

1 if the (annual) income is above$100,000 and Ootherwise;

1 if the respondent holds a highschool diploma or less and O oth-erwise;

1 if the respondent holds an associateor a four-year college diploma and Ootherwise;

1 if the respondent holds a graduatedegree (M.S. or Ph. D.) and O other-wise; and

1 if the respondent is the primaryshopper for household and O other-wise.

Data Description and Summary Statistics

The dependent variable is the level of inter-est in each of the four alternative models. Asdescribed earlier, consumers were asked to ex-press their interest on a scale of 1 (implying notinterested) to 5 (indicating very interested). Onthe basis of survey responses, a binary depend-ent variable, lnteresl, was created as follows:The variable Merest was assigned a value of 1if the level of interest was 4 or 5 and O if theinterest level was 3 or below. Approximately 53percent of the responses fell into the category 1,and the remaining 47 percent fell into categoryO; however, when asked about their interestlevel in using the four alternative delivery sys-tems for specific products, there were noticeabledifferences in response. The distribution of re-

spondents’ interest level for different productcategories and delivery mechanisms is summar-ized in Table 1.

More than 50 percent of respondents ex-pressed high interest in obtaining milk and otherdairy products, irrespective of the deliverymechanism. Similarly, more than one-half of therespondents indicated high interest in receivingfresh produce in cases of three of the four deliv-ery methods, with home delivery of preparedmeals being the exception. In the contexts ofhome delivery of full grocery line and drive-through pick-up service, more than 50 percentof the surveyed individuals expressed high in-terest level in obtaining canned goods, soda andother drinks, dry goods, and frozen food. Morethan one-half of the survey participants revealedhigh interest in seafood in the contexts of homedelivery of prepared meals and neighborhoodtruck-delivery service, High interest in obtainingmeat and poultry products via neighborhoodtruck delivery method was expressed by morethan one-half of the respondents; the same istrue about prepared meals via drive-throughpick-up service. High interest in newspaper de-livery was expressed by less than one-half of thesurvey participants, irrespective of the deliverymethod used. This may be due to the fact thathouseholds already have the option of newspa-per delivery and, hence, may not see the par-ticular value of receiving this item through anyof the four delivery mechanisms outlined in thesurvey.

The independent variables in the model in-cluded demographic and other economic variables,which are dummy or indicator variables in mostcases. Descriptive statistics on the explanatoryvariables used in the analysis are presented in Ta-ble 2. The following are specific variables in-cluded in the model:

. Intoth: This variable represents consumers’ in-terest in obtaining various individual items to bedelivered along with home delivexy of preparedmeals or neighborhood truck delivery of vegeta-bles and meat products. Included among theseitems are products such as so@ newspapers andmagazines, milk and staples, sedoo~ etc. Con-sumers’ stated levels of interest (on a scale of 1to 5) for each of these items are added to com-pute the variable Intoih.

Hossain, Ferahus and Adesoji O. Adelaja Consumers’ Interest in Aitemative Food Delivery Systems 55

Table 1. Distribution of Stated Interest Level in Alternative Food Delivery Systems by Product Type.

Level of Interest of Respondents5 4 3 2 1

Delivery Method Home Delivery of Full Line of Groce~

----------------------------------------percent-----------------------------------------

Prepared Meals 38.3 10.8 19.5 6.1 25.3Fresh Produce 48.2 16.8 12.4 2.9 19.7Canned Goods 50.5 11.4 15.0 2.9 20.1Meat and Poultry 39.1 11.5 18,3 5,7 25.4Milk 72.7 8.4 10.5 0.7 7.6Dairy Products 62.0 10.9 12.7 2.2 12.3Soda & Drinks 49.8 14.1 12.3 4.8 19.0Dry Goods 50.5 12.8 16,1 3,3 17.2Newspaper 34.0 5.4 8.9 1.9 49.8Frozen Food 44.6 16.4 15.0 5.0 18.9Seafood 38.2 2.2 19.1 4.5 36.0

Delive~A4ethod Home Deliveiy of Prepared Meals

Prepared Meals — . — — —

Fresh Produce 35.5 13.2 18.9 7.5 24,9Canned Goods 20.1 5.6 12.9 10.8 50.6Meat and Poultry 28.2 13.5 18.9 5.4 34.0Milk 74.7 4.5 9.8 0.0 10.9Dairy Products 60,8 9,4 13.2 3.0 13.6Soda & Drinks 27.7 12.5 18.4 5.9 35.5Dry Goods 23.3 8.0 21.7 8,4 38.6Newspaper 27.1 7.3 9.3 5.3 51.0Frozen Food 22.1 12,6 19.8 7.1 38.3Seafood 58.8 5.9 13.2 2.9 19.1

Delivery Method Drive- l%rough Pick-Up Service

Prepared Meals 41.6 15.6 15.6 2.5 24.7Fresh Produce 41.2 17.9 12.0 6.9 22.0Camed Goods 43.8 15.2 12,4 4.9 23.7Meat and Poultry 31.5 12.6 19.2 7.3 29.4Milk 62.7 8.4 10.8 1.7 16.4Dairy Products 59.4 13.4 12.0 2.1 13.1Soda & Drinks 52.1 20.4 9.6 3.9 13.9Dry Goods 43.3 17,3 13.0 4.2 22.2Newspaper 36.5 7,4 10.7 3,0 42.4Frozen Food 38.0 15.5 11.6 6.7 28.2Seafood 41,9 5,8 8.1 7.0 37.2

Delivery Method Neighborhood Tmck Delive~

Prepared Meals 35,4 10,3 15.7 5.8 32.7Fresh Produce 59.9 15.5 15.5 2.6 6.5Canned Goods 24.5 6.4 22.3 8.2 38.6Meat and Poultry 44.9 15.3 19.5 2.1 18.2Milk 64.3 9.0 13.1 0.5 13.1Dairy Products 55,9 11.3 17,1 3.6 12.2Soda & Drinks 29.1 10.5 16.8 7.7 35.9Dry Goods 29.3 6.3 21.6 6.3 36.5Newspaper 25.5 2.4 9,0 3.3 59.9Frozen Food 33.8 10.8 22.1 3.6 29.7Seafood 64,3 0.0 21.4 0.0 14.3

56 h“ 2000 .Joumal of Food Disfribufion Research

Table 2. Descriptive Statistics of Variables.a-..stanaarci

Variable Description of VariableIntoth

Fdbgtl*

Fdbgt2

Fdbgt3

Dis

Sel

Frsh

Pr

Qlty

Appr

Conv

wait

Fsz

Alt35

A35-45

Agt45 *

Mar

Gndr

Emp

Ilt50

150-100

Igt100*

School*

College

Grad

Prmshop

Level of interest in receiving other items via home delivery

1 = (monthly) food budget less than $200; O= otherwise

1 = food budget between $200 to $400; O= otherwise

1 = food budget greater than $400; O= otherwise

Average driving d&-mce to commonly used supermarket

1 = product selection is highly important in choosing a place toshop; O= otherwise1 = product freshness is highly important in choosing a place toshop; O= otherwise1 = low produet prices are highly important in choosing a place toshop; O= otherwise1 = service quality is highly important in choosing a place to shop; O= otherwise1 = store appearance is highly important in choosing a place to shop;O= otherwise

1 = convenience of location (near home/work) is highly important inchoosing a place to shop; O= otherwise1 = wait in checkout line is highly important in choosing a place toshap; O = otherwiseNumber of people in the household

1 = age below35 years; O = otherwise

1 = age between35 and 45 years; O = otherwise

1 = age greater than 5 years; O = otherwise

1 = married; O = otherwise

1 = female; O otherwise

1 = employed; O = otherwise

1 = income below $3 5,000; O = otherwise

1 = income between $50,000 and $100,000; O = otherwise

1 = income greater than $1 00,000; O = otherwise

1 = education up to high school; O= otherwise

1 = associate or four-year college degree; O= otherwise

1 = graduate degree; O = otherwise

1 = primary shoppeq O = otherwise

Mean Deviation28.54 14.14

0.33

0.44

0.23

4.27

0.77

0.85

0.58

0.78

0.66

0.67

0.64

3.68

0,25

0.41

0.34

0.81

0.79

0.67

0.16

0.40

0.44

0.27

0.49

0.24

0.87

0.47

0.500.424.38

0.42

0.35

0.49

0.41

0.47

0.47

0.48

1.22

0,44

0.49

0.47

0.39

0.4

0,47

0.26

0.49

0.50

0.44

0.50

0.43

0.34

‘An asterisk denotes that the variable was dropped during esdmation to avoid the dummy variable trap. The variable lntoth wasused for the home delivery of prepamxlmeals and neighborhood truck delivery (of vegetables and meat products) medels only.

Hossain, Ferdhus and Adesoji O. Adeiaja Consumers’ Interest in Alternative Food Delive~ Systems 57

● Food Budget: This variable denotes averagehousehold food expenditure per month. Therespondents are categorized into three groupsaccording to the size of their food budget, andthree dummy variables are defined to repre-sent these groups as follows: (1) less than$200 (Fdbgtl); (2) between $200 and $400(Fdbgt2); and (3) more than $4oO (F’dbgt3).Thirty-three percent of the respondents belongto group 1; 44 percent belong to group 2; andthe remaining 23 percent belong to group 3.No a priori assumption is made regarding thelikely effect of the food budget on consumers’level of interest in using the AFDSS.

. Age: Three age groups are identified as fol-lows: (1) less than 35 years (,41135); (2) be-tween 35 and 45 years (A35–45); and (3)more than 45 years (Agt45). Twenty-five per-cent of the respondents belong to category 1;41 percent belong to category 2; and the re-maining 34 percent belong to category 3.

. Gender The dummy variable Gndr is as-signed a value of 1 if the respondent is femaleand O otherwise. Seventy-nine percent of therespondents are female while the remaining 21percent are male. No a priori assumption ismade regarding the effect of gender on the de-pendent variable.

. Education: Three different levels of educa-tion are identified, and accordingly, threedummy variables are defined as: (1) highschool diploma or less (Schoo~; (2) associ-ate degree and four-year college degree(College); and (3) graduate degree (Grad).Twenty-seven percent of the respondents

have education up to a high school diploma;49 percent hold an associate or four-yearcollege degree; and 24 percent hold a gradu-ate degree. A priori, it is expected that con-sumers with higher education are likely tobe more interested in using one or more ofthe AFDSS.

. Employment: The dummy variable Emp is

assigned a value of 1 if the respondent is em-ployed and O otherwise. A priori, it is ex-pected that employed consumers are morelikely to use one or more of the AFDSS.

●

●

●

●

●

●

●

Income: Three different (annual) income lev-els are identifie~ and accordingly, threedummy variables are defined as follows: (1)less than $50,000 (11150);(2) between $50,000and $100,000 (150–1 00); and (3) more than$100,000 (lgt100). Sixteen percent of the re-spondents have income below $50,000; 40percent have income between $50,000 and$100,00; and the remaining 44 percent haveincome greater than $100,000. It is generallyexpected that consumers with higher incomesare likely to be more interested in using one ormore of the services.

Family Size: Family size is defined as thenumber of members in the family.

Marital Status: A dummy variable Mar is de-fined by assigning a value of 1 if the respon-dent is married and O otherwise. Eighty-onepercent of the respondents are married.

Distance: The variable Dis represents the dis-tance (in miles) of the respondent’s home andthe supermarket where S/he usually goes forgrocery shopping. It is expected that thelonger the driving distance, the more likelythat the individual will have high interest inusing the AFDSS.

Product Selection: The dummy variable Sel isassigned a value of 1 if the consumer rankedthe importance of product selection as 4 or 5and O otheryise. A priori, the effect of thisvariable on the dependent variable could beeither positive or negative.

Product Freshness: The dummy variable Frshis assigned a value of 1 if the respondentranked the importance of product freshness as4 or 5 and O otherwise. No assumption ismade on the likely impact of this variable onthe dependent variable.

Low Prices: The dummy variable Pr is as-

signed a value of 1 if the consumer ranked theimportance of low prices as 4 or 5 and O oth-erwise. It is expected that those attaching highimportance to low prices are less likely to beinterested in the AFDSS since these servicesare expected to be associated with some costs.

58 Ju& 2000 Journal of Food Distribution Research

● Service Quality The dummy variable Ser is

assigned a value of 1 if the consumer rankedthe importance of service quality as 4 or 5 andO otherwise. No assumption is made about thedirection of the impact of this variable on thedependent variable.

● Convenience: The dummy variable Conv is

assigned a value of 1 if the consumer rankedthe importance of convenience (that is, prox-imity to home or workplace) as 4 or 5 and Ootherwise. It is expected that those attachinghigh importance to convenience are likely tobe interested in the AFDSS.

. Appearance: The dummy variabIe Appr isassigned a value of 1 if the consumer rankedthe importance of store appearance (ambiencefactor) as 4 or 5 and O otherwise. No assumpt-ion is made about the likely impact of thisvariable.

. Waiting The dummy variable Wait is assigneda value of 1 if the consumer ranked the im-portance of the wait in the checkout line as 4or 5 and O otherwise. It is expected that thoseattaching high importance to the wait in thecheckout line are more likely to be interestedin using the AFDSS.

In addition to the variables describedabove, we found in our sample that, among themarried couples, 69 percent of respondents bothheld jobs. Only 31 percent of these householdshad one spouse working. Sixteen percent of allrespondents were single but working full-time,and only 3 percent of all survey participantswere retired. On the average (over all respon-dents), individuals worked 4.77 days a week,and the average workday was 10.3 hours.Among all respondents, 5.3 percent reportedfood shopping once a month; 11.3 percent re-ported a hi-weekly food shopping pattern; and35.8 percent of the households shopped for foodonly once a week. About 36.4 percent of therespondents reported food shopping 2 to 3 daysa week while 10.59 percent reported shoppingmore than three times a week. About 79 percentof the survey participants reported having a per-sonal computer at home; 68 percent reportedhaving Internet access; and 49 percent of thehouseholds reported having a fax machine.

Initially, during the estimation stage, vari-ables such as the following were included as ex-ploratory variables: location of the store (that is,proximity to other stores); ethnic origin of the re-spondent; home access to fhx machine, personalcomputers, and the Inteme~ frequency of shop-ping; and whether one spouse worked outside thehome. However, these variables were found to bestatistically insignificant in all models and, conse-quently, were dropped from the final analysis.

A significant portion of survey participantsare patrons of Parmalat-Welsh Farm Companyand use the company’s home delivery service forice cream and specialty dairy products. So, it wasreasonable to expect that consumers with priorexperience with home delivery of food itemswould respond differently than those withoutsimilar prior experience. Therefore, we initiallyestimated the model with data from the two sepa-rate groups; however, we did not fid meaningfiddifferences in the results from the two estimatedmodels. Also, sample sizes were rather small. Wethen decided to pool the two samples, estimatingthe model that included a dummy variable to ac-count for the potential effects of prior exposure tohome delivery system on our model estimates andresults. The coefficient of the dummy variable wasfound to be statistically insignificant. A likelihoodratio test led us to the same conclusion, therefore,the dummy variable was excluded in the estima-tion of the final model.

Model Estimation, Results, and Discussion

The logistic model was estimate~ using theeconometric software L.ZA4DEP, to explain andpredict consumers’ levels of interest in using thefour AFDSS. The estimated model coefficients, theassociated t-ratios, and the marginal impacts of thevariables on the dependent variable are reported inTables 3 through 6. These tables also report theestimated log likelihood fimctions of the unre-stricted and restricted (that is, all slope coefficientsare O) models, McFadden’s R2, and predictionsuccess.

Home Delive~ of Prepared Meals

Results of model estimation for home deliv-ery of prepared meals are reported in Table 3. Co-efficients of food budgets higher than $400; inter-est in the home delivery of other items; age

Hossain, Fer&us andAdesoji O. Adelaja Consumers’ Interest in Alternative Food Delivery Systems 59

Table 3. Home Delivery of Prepared Meals.’

MarginalVariable Coefficient t-ratio EffectConstant -2,57 -3.18Fdbgt2 0.399 1.30Fdbgt3 * 0.898 2.32 0,2::Intoth* 0.089 7.24 0.020Dis -0.033 -1.08 naSel 0.351 0.74Frsh* -1.360 -2.33 -0.3:;Pr -0.114 -0.47Qlty* 1.198 2.58 0.2:Conv* 0.835 2.78 0.186Appr* -0.772 -2.26 -0.172wait* 0,831 2.46 0.185FSZ* -0.344 -2.90 -0.077Alt35** 0.618 1.82 0.137A35-45 0.148 0.47 naGndr 0.048Mar* *

0.14-0,634 -1.72 -0.1:

Emp 0.347 1.23 naIlt50 0.032 0.07 na150-100 0.023 0.08 naCollege 0.304 0.98Grad* 0.833 2.16 0.1::Prmshop -0,285 -0.63 na

LL -200.44“Restricted LL -268.50Chi-Square (22) 136.13No. of Obs 405McFadden’s R* 0.21

PredictedActual o 1 TOTALo 216 36 2521 57 96 153Total 273 132 405

‘ LL denotes the log likelihood fhnction. Single and double asterisks denote that the variable is significant at the 5’7. and 10’7.level, respectively, Marginal effects are calculated only for variables that are statistically significant. na denotes that the variableis statistically insignificant, and consequently, marginal effect is not calculated. Marginal effects are calculated at mean valuesof the explanatory variables Molh, Dis, and Fsz.

60 July 2000 Jinmnal of Food Dis&ibution Research

Table 4. Home Delivery of FuIJ Grocery Line.a

MarginalVariable Coefficient t-ratio EffectConstant 0.407 0.56Fdbgt2* 0.862 2.95 0.215Fdbgt3 * 1.058 2.93 0.264Dis -0.004 -0.14 naSel** -0.565 -1,83Frsh**

-0.141-0.660 -1.95 -0.165

Pr* -0.603 -2.31 -0.150Qlty** 0.666 1.84Conv*

0.1660.618 2.15 0.154

Appr* -0.723 -2.49 -0.180wait* 0.860 2.91 0.215FSZ* -0.376 -3.43 -0.094Alt35* 0.627 1.99 0.156A35-45 0.372 1.28 MGndr 0.347 0.99 naMar 0.152 0.42 naEmp* 0.567 2.18 0.141Ilt50 0.016 0.04 m150-100 0.247 0.88 naCoUege -0.089 -0.31Grad**

na0.724 1.94 0.181

Prmshoo* -0.922 -2.1O* -0.230

LL -219.64Restricted LL -273.43Chi-Square (21) 107.57No. of Obs 395McFadden’s R2 0.15

Predicted

Actual o 1 TOTAL

o 154 52 2061 59 130 189Total 213 182 395

a LL denotes the log likelihood function. Single and double asterisks denote that the variable is significant at the 5% and 10%level, respectively. Marginal effects are calculated only for variables that are statistically significant. na denotes that the variable isstatistically insignificant, and consequently, marginal effect is not calculated. Marginal effects are calculated at mean values of theexplanatory variables lntoth, Dis, and l?sz.

Hossain, Feroixus and Adesoji O. Adelaja Consumers’ Interest in Alternative Food De[iveqv Systems 61

Table 5. Drive-Through Pick-up Service.a

MarginalVariable Coefficient t-ratio Effectconstant -2.255 -3.18Fdbgt2* 0.743 2.76 0.185Fdbgt3 * 0.709 2.11 0.176Dis* 0.101 3.09 0.025Sel* -0.798 -2.15 -0.198Frsh “ 0,158 0.32Pr* -0.737 -3.00 -0.::3Qlty 0,452 1.21Conv* 0.784 2.99 0, ;;5Appr* -0.620 -2.13 -0.154Wait* 0.927 3.47 0.231FSZ* 0.381 3.63 0.095Alt35 0.209 0.68 naA35-45 -0.125 -0.46 naGndr 0,016 0.05Mar** -0.595 -1.73 -0.::8Emp* 0.637 2.49 0.158Ilt50 0.007 0.02 na150-100 0.207 0.77 naCollege 0,238 0.87 naGrad* * 0.728 2.07 0.181Prmshop -0.465 -1.18 na

LL -235.23Restricted LL -285.63Chi-Square (21) 100.79No. of Obs 413McFadden’s R2 0.13

Predicted

Actual o 1 TOTAL

o 131 64 1951 59 159 218Total 190 223 413

=LL denotes the log likelihood function. Single and double asterisks denote that the variable is significant at the 5% and 10’%level, respectively. Marginal effects are calculated only for variables that are statistically significant. na denotes that the variable isstatistically insignificant, and consequently, marginal effect is not calculated. Marginal effects are calculated at meau values of theexplanatory variables Intoth, W, andFsz.

62 Jzdy 2000 Journal of Food Distribution Research

Table 6. Neighborhood Truck Delivery of Vegetable and Meat Products.’

MarginalVariable Coefficient t-ratio EffeetConstant -5.96 -5.57Intoth* 0.095 8.07 0.019Fdbgt2 0.038 0.11 naFdbgt3 0.637 1.53Dis* 0.111 2.93 0.03Sel* 1.74 3.16 0.350Frsh -0.801 -1.29 naPr -0.306 -1.14 naQlty -0.099 -0.23Conv* 0.910 2.53 0.1::Appr* -1.000 -3.11 -0.201Wait -0.437 -1.55 naFsz -0.187 -1.55Alt35** -0.559 -1.75 -0.1::A35-45 -0.130 -0.39Gndr* 1.389 3.03 0.2%Mar 0.632 1.44 naEmp 0.423 1.35Ilt50* * 0.886 1.85 0.1%150-100 0.218 0.63College** 0.625 1.81 0,1:Grad 0.340 0.76 naPrmshop 0.322 0.63 na

LL -168.04Restricted LL -252.83Chi-Square (22) 169.59No. of Obs 393McFadden’s R2 0.30

Predicted

Actual o 1 TOTAL

o 229 29 2581 47 88 135

Total 276 117 393

a LL denotes the log likelihood function. Single and double asterisks denote that the variable is significant at the s~o and 10’7. level,respectively. Marginal effects are calculated only for variables that are statistically significant. na denotes that the variable is statisti-cally insignificant and consequently, marginal eff~t is not calculated. Marginal effeets are calculated at mean values of the ex-planatory variables Intoth, Dis, and Fsz.

Hossain, Ferdzus and Adesoji O. Adelaja Consumers’ Interest in Alternative Food Deiivery Systems 63

less than 35 years and education level beyondfour-year college; family size; and marital statushave statistically significant (at 10 percent orlower level) effects on consumers’ interest in usingthis particular service. Similarly, high importanceof product fkeshness, service quality, convenienceof locatiou store appearance, and wait in thecheckout line till have statistically significant ef-fects. On the other han~ effkcts of distance, foodbudgets between $200 and $400, age group be-tween 35 and 45 years, education with an associateor a four-year college degree, importance of prod-uct selection and low prices, income leve~ emp-loyment status, and respondent as primary shop-per are found to be statistically insignificant.

The estimated marginal effects of the inde-pendent variables included in the model suggestthat those who attach high importance to servicequality, convenience of location, and wait in thecheckout line are 26.6, 18.6, and 18.5 percent,respectively, more likely to have high interest inhome delivery service for prepared meals.Households with food budgets higher than $400are 20 percent more likely to be interested inthis service compared to those spending lessthan $200 per month on food. Individuals belowthe age of35 years are 13.7 percent more likely(compared to those above 45 years of age), andthose with graduate education are 18.5 percentmore likely (compared to those with educationof high school diploma or less) to have high in-terest in this particular food delivery system.Although statistically significant, interest in thehome delivery of other products has only asmall marginal effect on the dependent variable.On the other hand, those attaching high impor-tance to product fleshness and store appearanceare 30.2 and 17.2 percent, respectively, lesslikely to have high interest in the service. Also,larger households and married individuals are7.7 and 14.1 percen\ respectively, less likely tohave high interest in this particular method offood delivery.

The likelihood ratio test of overall modelsignificance (that is, all coefficients except theintercept are simultaneously O) yields a test sta-tistic of 136.13, which is higher than the 95 per-cent critical value of Chi-square distributionwith appropriated degrees of freedom that sug-gest that the model has significant explanatorypower. Estimated McFadden’s R2 is 0.21. The

estimated model correctly predicts 317 of 405sample observations, with a prediction successrate of 78 percent.

Home Delive~ of Full Grocery Line

Estimation results for the home delivery offull groce~ line model are reported in Table 4,showing that coefficients of food budgets between$200 and $400 and that fkrnily size, age below 35years, employment status, and graduate educationfor budgets above $400 are statistically significantat 10 percent or lower level. Similarly, importanceof product selection and product freshness, lowprices, service quality, convenience of location,store appearance, wait in checkout line, and re-spondent as primary shopper have significant ef-fects on the consumers’ interest in using thismodel of food delivery. On the other hand, agebetween 35 and 45 years, gender, marital status,income level, associate or college degree leveleducatio~ and distance seem to have insignificanteffects on consumers’ interest level in this service.

The estimated marginal effects suggest thatconsumers with age below 35 years are 15.6 per-cent more likely (compared to those above 45years), and those with graduate education are 18.1percent more likely (compared to those with highschool diploma or less) to be interested in homedelivery of full grocery line. Similarly, householdswith food budget between $200 and $400 andabove $400 are 21.5 and 26.4 percent, respec-tively, more likely to be interested in this service(compared to those with food budget below$200). Employed individuals are 14.1 percentmore likely while the primary shopper in thehousehold is 23 percent less likely to be interestedin this model of food delivery. Similarly, thoseattaching high importance to service quality, con-venience of locatio~ and wait in checkout line are16.6, 15.4, and 21.5 percent, respectively, morelikely to have high interest in this service. On theother hand, those attaching high importance toproduct selectio~ product freshness, and lowprices are 14.1, 16.5, and 15 percent, respectively,less likely to be interested in using this service.Similarly, those attaching high priority to storeappearance and those with larger family size are18 and 9.4 percent, respectively, less likely to beinterested in using this food delivery method.

Likelihood ratio tests of the null hypothesis thatall slope coefficients are simultaneously Oyield a test

64 July 2000 Journal of Food Distribution Research

statistic of 107.57, which clearly exceeds the 95 per-cent critical value of the Chi-square distribution withappropriate degrees of fi-eedom. Estimated McFad-den’s R2 is 0.15.The model correctly predicts 290 of395 observations, with a prediction success rate of73.4 percent.

Drive-Through Pick-Up Service

The results for the drive-though pick-upmodel are reported in Table 5. Results show thatcoefficients of two food budgets, distance, familysize, marital and employment statuses, and gradu-ate education are statistically significant at 10 per-cent or lower level. Simiiarly, concern about theselectiom low prices, convenience of locatio~store appearance, and wait in the checkout line areimportant determinants of consumers’ level ofinterest in using this particular service. On theother han~ importance of product freshness,service quality, education with two-year or four-year college degree, age distributio~ gender, in-come level, and respondent as primary shopperhave statistically insignificant effects on consum-ers’ (high) interest in using this service.

The estimated marginal effkcts indicate thathouseholds with food budget between $200 and$400 and above $400 are 18.5 and 17.6 percent,respectively, more likely to be interested in thedrive-through pick-up service compared to thosewith food budget below $200. Individuals withgraduate degree and those with larger family sizeare 18.1 and 9.5 percent, respectively, more likelyto have high interest in this mode of accessingfood. Similarly, consumers attaching high impor-tance to convenience and the wait at the checkoutline are 19.5 and 23.1 percent, respectively, morelikely to be interested in this service. Although thecoefficient of distance is statistically significant,its marginal effect on consumers’ interest level isvery low. On the other han~ consumer concernover selection of products, low prices, and appear-ance of the store are 19.8, 18.3, and 15.4 percent,respectively, less likely to be interested in usingthe drive-through service. ALso, married individu-als are 14.8 percent less likely to use this model offood delivery compared to those who are single(that is, never married, separated, or widowed).

Estimated likelihood ratio statistic for overallmodel significance is 100.79, which is clearlyhigher than the 95 percent critical value of the Chi-Square distribution with appropriate degrees of

freedom. McFadden’s R2 for this model is 0.13.The model correctly predicts 290 of413 observa-tions, implying a prediction success rate of 70.2percent.

Neighborhood Truck Deliveq

of Vegetables and Meat Products

Model estimation results for neighborhoodtruck delive~ of vegetables and meat products arepresented in Table 6. Results show that coeffi-cients of interest in other products, distance, agebelow 35 years, gender, income below $50,000,and education level with an associate or four-yearcollege degree are statistically significant. Simi-larly, importance of product selectiom conven-ience of location (of food store), and store appear-ance have coefficients that are statistically signifi-cant. On the other han~ coefficients of differentfood budgets, employment and marital statuses,income between $50,000 and $100,000, age be-tween 35 and 45 years, family size, graduate edu-catio~ primary shopper status, importance ofproduct tieshness, low prices, and wait in thecheckout line are statistically insignificant.

Estimated marginal effects suggest that fe-males are 27.9 percent more likely to have highinterest in the neighborhood truck delivery service.Individuals with (annual) income below $50,000are 17.9 more likely (compared to those with in-come above $100,000), and those with an associ-ate or four-year college degree are 12.6 percentmore likely (compared to those with a high schooldiploma or less) to be interested in using this fooddelivery method. Similarly, those attaching highimportance to product selection and convenienceof location are 35 and 18.3 percent, respectively,more likely to have high interest in this service.Although interests in other products and distancehave coefficients that are statistically significant,their marginal effects are very low. On the otherhan~ those attaching high importance to store ap-pearance and individuals below 35 years of ageare 20.1 and 11.3 percent, respectively, less likelyto be interested in using this particular model offood delivery.

Estimated likelihood ratio statistic for overallmodel significance is 169.59, which clearly ex-ceeds the 95 percent critical value of the Chi-Square distribution with appropriate degrees offreedom, implying significant model explanatorypower. Estimated McFadden’s R2 for the model is

Hossain, Femkws and Adesoji O. Adelaja Consumers’ Interest in Alternative Food Delivery Systems 65

0.30.The model correctly predicted 317 of 393observations, yielding a prediction success rate of80.7 percent.

Discussion

Empirical results of this study suggest that con-sumers’ attitudes, prefwences, and priorities withrespect to quality of food items and convenience ofobtaining them are important determinants of theirinterest level an~ consequently, their likelihood ofusing alternative methods of accessing food. Forexample, consumers attaching high importance tolow prices of products are significantly less likely tobe interested in three of the four AFDSS analyzed inthis study. Similarly, consumer concerns over qualityand diversity of products, such as freshness and selection of products and store appearance (ambience),generally have negative effects on consumers’ inter-est in using the AFDSS. On the other han~ conven-ience fwors generally have positive impacts on cOn-sumer interest in using the AFDSS. For instance,consumers attaching high importance to factors suchas distance, convenience of locatio~ service quality,and wait in the checkout line are statistically morelikely to be interested in using one or more of theAFDSS. This suggests that companies, in their at-tempts to reach their customers via alternative fooddelivay methods, need to address not only the con-venience issue, but also the issues of quality and di-versity of products and competitive prices.

Among the sociodemographic variables,younger customers (that is, those below the age of35 years) are more likely to use the alternativechannels for accessing food, except the neighbor-hood truck delivery method in which these indi-viduals are less likely to be interested. The limitedinterest by this group in neighborhood truck deliv-ery may relate largely to delivery time. Resultssuggest that no significant difference in interest inthe AFDSS among individuals in age group 35 to45 years compared to those above 45 years. Gen-der difference matters only in the case of neigh-borhood truck delivery method (where females aremore interested than male customers) while mari-tal status matters for home delivery of preparedmeals and drive-through pick-up service, the effect

being negative in both cases. Family size hasmixed impacts: Larger households are less likelyto use home delivery service for either the pre-pared meals or fidl groce~ line whereas they aremore likely to use drive-through pick-up service.

Individuals with higher education beyond highschool are more likely to use one or more of theseshopping methods, although graduate-level educa-tion seems to matter more than college-level edu-cation. Households with food budget (monthly)above $200 seem to have high interest in usingone of these services.

Results also indicate that income differencesdo not have significant impacts for the sampleused in this study. However, it may be noted thatrespondents in the survey came from relativelyaffluent segments of the society (about one-half ofthe individuals participating in the survey had an-nual income above $100,000), and income differ-ences at those income levels may not be importantfor food consumption and for accessing decisions.The results of this study, therefore, must be inter-preted in proper context.

It is difficult to compare the results of thisstudy with those of other studies since academicresearch is yet to fully explore the issue of con-sumers’ willingness to use alternative mechanismsto access food. In analyzing consumers’ attitudestoward a particular product or service, researchershave used alternative scaling methods in measur-ing consumers’ attitudes and perceptions. For ex-ample, Hinson, Harrison, and Andrews (1998) usea dichotomous response (yes/no) method in ana-lyzing consumers’ attitudes toward food irradia-tion. Underhill and Figuero (1996) use a five-pointscale in analyzing consumers’ perceptions of non-conventionally grown produce, while Kreider,Gempesaw, and Bacon (1993) use a seven-pointscale to study consumers’ perceptions of fish andseafood products. Other researchers have usedeven wider scale in measuring consumers’ interestand perceptions about various products. As is ap-parent, the subject matter of most of these studiesis quite different from that of ours; therefore, us-ing a different scale, it is difficult to compare ourresults to their results. However, our results maybe compared with at least two previous studiesfocusing on consumers’ willingness to use alterna-tive mechanisms to access food. These two studiesby White (1996), and Hiser, Nayg% and Capps(1999) both focus exclusively on consumers’willingness to use online shopping.

In Hiser, Nayg& and Capps’ (1999) study,which uses a dichotomous response (yes/no), 34percent of the respondents were willing to useonline shopping services, and 53 percent of the

66 July2000 Jmmai of Food Distribution Research

respondents revealed high interest in at least oneof the four alternative food delivery mecha-nisms. A higher percentage of our respondentsrevealed high interest level than did the respon-dents in Hiser, Nayga, and Capps’ (1999) study.This finding may be due to the fact that our de-livery options are not exclusively Internet-based.In addition, average education and income levelsin our sample are higher than those in the otherstudy, and there are significant differences inlife patterns between the samples in these twostudies. Despite these differences in characteris-tics of the two samples, our results are consis-tent with some of the findings of Hiser et al. Forinstance, our findings-that younger consumersand those with college- level education or higherare more likely to have high interest inAFDSs—are similar to the findings of Hiser,Nayg~ and Capps. Similarly, consistent with theabove-mentioned study, we find that consumerswho attach high importance to convenience andquality of services are more likely, whereasthose concerned with product quality and pricesare less likely, to use one or more of the alter-native methods of accessing food.

White (1996) uses a three-level responsesystem (very/somewhat unlikely, neither likelyor unlikely, and somewhat/very likely) to meas-ure consumers’ interest in online shopping forspecialty food and drinks (specifically, on threeitems—coffee, sals~ and drinks). He found thatabout 68 percent of the survey participants werevery/somewhat unlikely to use online shopping,11 percent were neither likely nor unlikely touse the service, and 21 percent responded assomewhative~ unlikely. However, about 58percent of survey participants indicated willing-ness to use online shopping within the next sixmonths to buy food items from at least onecompany. About 19 percent of the respondentsexpressed willingness to buy coffee online,while 29 percent and 13 percent indicated theirwillingness to use online shopping to purchasesa.lsa and seafood, respectively. The percentageof respondents in that study who expressedwillingness to use online shopping is lower thanthe percentages in Hiser, Nayg~ and Capps’(1999) study and in the current study. In contrastto Hiser, Nayga and Capps’ study and our study,

White (1996) finds younger people to beless likely to use online shopping for food.

Hiser, Nayga, and Capps’ study and our studysuggest that younger individuals are more likelyto use such alternative channels to access food.Such differences could be due to the fact thatthe data for the White (1996) study was col-lected in 1996, almost two years before the datawas collected for Hiser, Nayga, and Capps’(1999) study and three years prior to our datacollection. Since consumers’ interest in altern-ative means of food shopping has heightened inrecent years, it is not surprising that a higherpercentage of respondents are willing to use on-line and other alternative methods of food shop-ping in our sample.

Conclusion

As technology, demographics, and consum-ers’ attitudes and priorities continue to change inour society, food delivery systems must respondto these changes in order to better serve custom-ers. In order to remain competitive, companiesengaged in the business of food delivery mustbe innovative in the ways that they can reachcustomers and better serve their needs. The re-sults of this study suggest that there is consider-able interest among consumers in AFDSS, asindicated by the percentage of respondents whorevealed a high interest in one or more of thefour different food delivery mechanisms ana-lyzed in this study. However, convenience has tobe combined with quality of products and serv-ices, and competitive pricing.

Finally, because of the small sample size,care must be taken in interpreting and gener-alizing the results of the study in a broadercontext. Nevertheless, the empirical findingsare useful in identi~ing potential target con-sumers who are likely to use alternative fooddelivery methods. Results of the study help toidentifi consumers’ concerns and to allowbusinesses to preemptively address these con-cerns, to improve planning and management,and to provide better customer service. Thestudy does not address the questions of con-sumers’ willingness to pay for these servicesor the cost effectiveness of the alternativefood delivery mechanisms that are analyzed inthis study. Future research in the area shouldaddress these and similar issues.

Hossain, Ferahus and Adesoji O. Adekxja Consumers’ interest in Alternative Food Delivery Systems 67

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