Frank H. Alpert, Michael A. Kamins, & John L Graham

An Examination of ResellerBuyer Attitudes Toward

Order of Brand EntryA national survey of 145 reseller buyers was used to study how brand entry order into new categoriesaffects reseller buyers' attitudes toward new items. The literature on pioneer brand advantage is extendedby finding empirical support for an advantage to pioneer brands with resellers. Also, an important dis-tinction is found between the first me-too follower brand and second or later me-too follower brands.Specifically, reseller buyers have a very favorable attitude toward pioneer brands, a less favorable butstill positive attitude toward first me-too follower brands, and an unfavorable attitude toward second orlater me-too follower brands. An adaptation of the multiattribute attitude model (that of "importance-likelihood") served as the psychological basis in an effort to explain how and why these attitudinal dif-ferences occurred. A causal model framework then was applied to the data to investigate the significantinterrelationships between brand order of entry and reseller buyer beliefs, attitudes, and behavior. Thetheoretical and managerial implications of entry order effects are discussed.

CONSIDERABLE research now supports pioneerbrand advantage (Carpenter and Nakamoto 1987,

1989; Lane 1980; Robinson 1988; Robinson andEomell 1985; Schmalensee 1982; Urban et al. 1986;White 1983). Pioneer brand advantage is a criticallyimportant marketing strategy topic because effectivemarketing strategy has been linked to achieving long-run consumer and competitive advantages (Cunninghamand Robertson 1983). However, research on pioneerbrand advantage has centered on the effects of pi-oneership on the manufacturer, competitors, or con-sumers—the impact on resellers has received vir-tually no attention.

Many theories have been proposed to explain the

Frank H. Alpert is Assistant Professor of Marketing, School of BusinessAdministration, University of Missouri-St. Louis. Michael A. Kamins isAssociate Professor of Marketing, School of Business Administration,University of Southern California. John L. Graham is Associate Profes-sor of Marketing, Graduate School of Management, University of Cali-fornia, Irvine, and Visiting Professor, Madrid Business School, Madrid,Spain. The authors thank Brian Harris of IRI/ABA, Inc. for his assistancein obtaining the data used in the study, as well as three anonymousJM reviewers who gave helpful comments.

advantage in market share gamered by the pioneer brand(which by definition is the first entrant into a newmarket). These theoretical explanations initially rangedfrom the establishment of entry barriers (Lane 1980)to the effects of switching costs (Schmalensee 1982).More recently, the pioneer brand has been hypothe-sized both to shape the individual's attribute prefer-ences toward the pioneer's configuration and, by vir-tue of its prototypicality for the product category, tobe more perceptually prominent than follower brands(Carpenter and Nakamoto 1989). Still another sourceof pioneer brand advantage may be reseller buyer at-titudes.

Reseller buying (buying by retailers or whole-salers) has grown considerably in importance in thelast decade (e.g., Feigner 1989; Rao and McLaughlin1989). In the past, large manufacturers such as Proc-ter & Gamble could be said to dominate supermarketchannels, but today the reverse is more likely to betrue. Several factors explain this reversal of channelpower (Feigner 1989): the consolidation of retail poweramong relatively few retailing companies, rapid retailexpansion during the 1980s, utilization of new infor-

Journal of MarketingVol. 56 (July 1992), 25-37 Examination of Reseller Buyer Attitudes / 25

mation technologies such as checkout scanners, andan unending stream of new product introductions andline extensions coming from manufacturers. The in-troduction of slotting allowances by resellers is a dra-matic outgrowth and indicator of this power reversal.Now manufacturers often must pay for new slots onthe shelves, if they can get them (Therrien 1989). Yet,despite these developments, the reseller buying liter-ature remains limited. Ettenson and Wagner (1986)have gone so far as to say that "there is no theory orconceptual framework specific to retail buying."

Nilsson and Host's (1987) review of the resellerbuying literature did find recognition that brand entryorder is one of many product characteristics that canmatter in the new product buying process. However,they conclude from their review that findings aboutthe impact of brand entry order on reseller buying are"so short and vague, that it is unclear which interre-lations are of importance" (p. 56). The goal of ourstudy is to fill this gap by examining the impact ofbrand entry order into new categories on reseller buyerattitude from a theoretical and empirical (survey-based)perspective. Specifically, we address two importantquestions:

1. Does it matter to reseller buyers whether a new brandis a pioneer or me-too follower (imitator)?

2. If entry order matters, why does it matter?

Answers to these questions will extend marketing'sunderstanding of two major topics—pioneer brandadvantage and reseller buying.

We define a "pioneer" as a new product that issignificantly different from any other product in thejudgment of a reseller buyer. This definition is largelyconsistent with other definitions of pioneers (the "firstentrant" into a market, Robinson and Fomell 1985;the first brand to create a new product category inconsumers' minds, Alpert 1987), except that it is aperceptual definition from the perspective of the re-seller buyer. We define a "me-too follower" as a newstockkeeping item that the reseller buyer perceives tobe about the same as a previously introduced item. Itmay have minor differences in price, features, or per-formance, but these differences are not sufficient toattract new customers who would not have bought thepioneer brand.

We delimit our study in three important ways. First,our research addresses a certain type of buying situ-ation, "new item" buying (Kotier 1991, p. 211), inwhich just one item is offered to and is under consid-eration by the reseller buyer. Second, we focus ex-clusively on new item buying early in the product lifecycle (i.e., the introductory and growth periods), be-cause for mature product categories it is obvious thatobtaining distribution represents a barrier to entry forme-too followers. Finally, we use a survey method

and rely on self-reports of reseller buyer beliefs andbuying outcomes.

An Importance-LikelihoodFramework for Reseller Buying

Past research on reseller buying decisions has tendedto rely on statistical analysis to find correlation rela-tionships between several independent variables—suchas expected profitability for the reseller, competitiveintensity among resellers, and manufacturer market-ing strategies—and the dependent variable of whethera new item is bought or rejected (Heeler, Kearney,and Mehaffey 1973; Nilsson and Host 1987; Rao andMcLaughlin 1989). No study to our knowledge hasattempted to gain an understanding of the reseller buy-ing process through a multidimensional attitudinalperspective as developed in psychology and consumerbehavior research.

Fishbein and Ajzen's (1975) well-established mul-tiattribute attitude model serves as the foundation forthe attitude model we use. Fishbein and Ajzen iden-tify a consensus definition of attitude as "a learnedpredisposition to respond in a consistently favorableor unfavorable manner in respect to a given object"(p. 6). These attitudes are formed as the sum of theevaluations (good-bad) of relevant attributes times thelikelihood of occurrence of each attribute. We can usethis perspective to propose how entry order affects re-seller buying. First, reseller buyers are hypothesizedto have a more favorable attitude toward pioneers thantoward me-too followers. Then, according to the stan-dard cognition —> affect —> conation (also known asthink -^ feel -^ do) paradigm of high involvementbuying (cf., Engel, Blackwell, and Miniard 1986, p.115-116), reseller buyers are less likely to actuallybuy the me-too follower brand than to buy the pioneerbrand. Me-too follower áwadvantage can thus bedefined as the extent to which buyer attitude is lessfavorable toward me-too followers than toward pi-oneers. The multiattribute nature of the expectancy-value model then provides a basis for explaining whythe entry order effect occurs, through an examinationof buyers' beliefs and values. Therefore, our researchcenters on reseller buyer beliefs because those beliefsdrive the buying process.

We adapted Fishbein and Ajzen's (1975) attitudemodel to the context of grocery industry buying, theindustry in which our theory is tested. To do so, wemodified their model to an "importance-likelihood"model similar to that proposed by Bass and Talarzyk(1972). We measured attribute importance on a scaleof "not important" to "extremely important" and at-tribute likelihood on a scale of "not likely" to "ex-tremely likely." We then tested our adaptation of theFishbein and Ajzen attitude model in a causal model

26 / Journal of Marketing, July 1992

framework through the use of a PLS (partial leastsquares) approach that can examine the full cognition—> affect -» conation causal chain all at the same time.Hence, our study is unique in that it enables us tocompare fíndings on similar issues obtained throughthe use of vastly different methods.

Identification of Attributes

To operationalize the importance-likelihood model,attributes must be found that explain why buyers mighthold different attitudes toward pioneers and me-toofollowers. Note that we are looking for determinantattributes of these differences, not general attributesof reseller buying. Attributes used in our study weretherefore identified in two ways: (1) a review of theliterature and the authors' analysis of how entry ordershould affect reseller buying and (2) 10 exploratoryinterviews with retail and wholesale buyers in the LosAngeles area.

The exploratory interviews were extremely help-ful. At the beginning of the study we expected to clas-sify brand entry order into one of two categories, pi-oneer or me-too follower, but our exploratory interviewsand further analysis quickly convinced us that the cat-egory of "me-too follower" should be divided into ftrstme-too followers and second or later me-too follow-ers. As the names indicate, the first me-too followerin a product category is brought to the reseller buyersoonest after the pioneer. All me-too followers fromthen on are second or later me-too followers. In ourdiscussions of the disadvantages and advantages of me-too followers, we show that disadvantages of me-toofollower status accrue more to second or later me-toofollowers, whereas advantages of me-too follower sta-tus accrue more to fírst me-too followers. The ex-ploratory interviews also revealed several new rele-vant attributes, three of which pertain to how entryorder affects (1) "healthy" category competition, (2)"unhealthy" category competition, and (3) reseller de-pendence on brands in the category. We explain thesenew attributes more fully in a subsequent section.

A set of 10 relevant attributes was obtained fromour preliminary research. We believe this set is ascomprehensive as possible. Both the exploratory in-terviews and subsequent questionnaire pretests (alsowith reseller buyers) closed with a question askingwhether the buyers could think of any other relevantbeliefs, but no other beliefs were identifíed.

We organized the 10 attributes into a theoreticalframework and causal model that explains resellerbuying in the new item buying situation. Because re-seller buying serves the goal of maximizing profit perunit of shelf space, the various beliefs about entry or-der's effect should make sense in terms of their effecton that goal.

How Entry Order Matters

Our fírst hypothesis is designed to answer our fírstquestion: Does it matter to reseller buyers whether anew brand is a pioneer or me-too follower?

H|: Reseller buyer attitude (measured in both a global anda multiattribute format) should significantly differ to-ward pioneers, first me-too followers, and second orlater me-too followers. Specifically, reseller buyer at-titude should be most favorable toward pioneers, fol-lowed respectively by first me-too followers and thensecond or later me-too followers.

Why Entry Order Matters

If entry order matters, the next question is: Why doesentry order matter? Specifically, on what dimensionsdo reseller buyers have different preferences towardpioneer brands, fírst me-too followers, and second orlater me-too followers? An answer to this question re-quires an examination of each of the 10 separate at-tributes that make up our importance-likelihood mul-tiattribute attitudinal model.

Entry order effects fundamentally arise from thediffering interests of resellers and manufacturers. Re-sellers want maximum profítability from their shelfspace, whereas each manufacturer wants to sell its ownproducts. Therefore, to a large degree, resellers areconcemed with primary (total) demand whereas man-ufacturers are concemed with brand demand. Thesediffering interests confíict at times. Such conflict ismost evident over one of the main drawbacks of me-too followers—a new me-too follower may canni-balize sales from other brands that the reseller alreadycarries. The manufacturer may be delighted that itsbrand takes sales away from competitors. The re-seller, in contrast, can lose when substantial canni-balization occurs. Profítability per unit of shelf spacedevoted to a product category declines when a newitem is added but fails to generate new sales (i.e., branddemand for the new item is generated, but primarydemand remains about the same because of cannibal-ization).

For the purposes of our research, our task is topredict how entry order affects brand performance oneach attribute. For this particular attribute we predictreseller buyers will perceive that second or later me-too followers cannibalize more than fírst me-too fol-lowers. As more brands enter the product category,reseller buyers may perceive that an increasing pro-portion of the latest me-too follower's sales will haveto be taken directly from sales of previously enteredbrands.

The preceding analysis leads to the following hy-pothesis about the relative performance of the threeentry order categories on this attribute.

Examination of Reseller Buyer Attitudes / 27

H2a: Reseller buyers believe pioneers are least likely tocannibalize, followed by first me-too followers andthen by second or later me-too followers.

A second pure entry effect attribute, related tocannibalization, is that a me-too follower may not meetan unmet need. In exploratory interviews, resellerbuyers said they generally preferred pioneer brandsbecause a me-too follower "doesn't meet a need." Whatdo they mean by "need" ? Most consumers' need fora product is met if the reseller already carries an ad-equate brand of that product. Therefore, resellers wouldnot require me-too followers to satisfy their cus-tomers' needs. The more me-too followers, the lesslikely the last one is to have a chance to meet a stillunmet need for any reseller or any consumer. Hence,first me-too followers would be more likely to meetan unmet need than second or later me-too followers,though neither should be very likely to do so.'

Hîb: Reseller buyers believe pioneers are most likely tomeet an unmet need, then first me-too followers, andthen second or later me-too followers.

Me-too followers can create unhealthy competi-tion in a product category. The presence of many verysimilar brands may stimulate so much price compe-tition that each manufacturer's profits are drivendown—a basic finding in economics (see, e.g., Schererand Ross 1990, p. 277). Reseller buyers evaluatingprospects for total category sales from new categoriesmay find the degree of competition "excessive" be-cause new categories must generate sufficient profitto afford a continuing program of promotion to gen-erate awareness and trial and thus "grow the cate-gory" (a phrase many resellers use). Indeed, the needto generate product awareness and trial is a key pointof the product life cycle concept (e.g.. Kotier 1991,p. 365 or Day 1986, p. 90). However, when categoryprofits are divided among more brands and are draggeddown by price competition, sufficient promotion maybecome unaffordable. Unhealthy category competi-tion affects resellers because lower overall categorysales are divided over more brands and more shelfspace. The more brands already carried in a category,the more likely it is that competition will be severeand unhealthy. Hence, creating unhealthy competition

'Cannibalization is one unfavorable consequence of not meeting anunmet need, but another consequence is no sales at all (or very littlesales). Though some attributes in our study overlap other attributes,as in this case, it should not be unexpected that a model of resellerbuyer attitude results in a "fuzzy set" of attributes rather than a com-pletely mutually exclusive list. In any case, we believe there is nochoice but to accept these attributes and their overlap because (1) theyreflect reseller buyer thinking, not a researeher-constructed list (an"emic" not an "etic" list), and (2) these attributes make fine distinc-tions that would be lost if overlapping attributes were aggregated intoa reduced set that eliminates the overlap (as in dropping the unmetneed attribute because it overiaps with cannibalization).

is more a problem for second or later me-too follow-ers than for first me-too followers.

H2c: Reseller buyers believe second or later me-too fol-lowers are most likely to create unhealthy competi-tion in the category, then first me-too followers, andthen pioneers.

Though too many me-too followers may create un-healthy competition in a new product category, in somecases a me-too follower may stimulate healthy com-petition. When the pioneer is the only brand in thecategory, its manufacturer may choose to milk currentprofits from the category by keeping promotional ex-penditures low. Or, feeling no pressure at all, the pi-oneer's managers may simply be inattentive and pro-crastinate on marketing matters. If a me-too followerenters the category, however, fear of losing out maystimulate both competitors to focus on the categoryand increase their promotional expenditures. The en-suing battle of promotional expenditures may actually"grow the category," and primary and brand demandmay both increase. Healthy competition is more likelyto occur when just a few brands are competing in anew category; unhealthy competition is more likely tooccur when many brands are competing in a new cat-egory.

In terms of brand entry order, first me-too follow-ers are most likely to bring about healthy competition,whereas second or later me-too followers are least likelyto do so. Pioneers may stimulate some healthy com-petition with substitute product categories. Hence:

H2d: Reseller buyers believe first me-too followers are mostlikely to create healthy competition in the category,then pioneers, and then second or later me-too fol-lowers.

Adding a me-too follower may reduce the depen-dence of the reseller when just a single brand is car-ried. The first and only supplier has some degree ofmonopoly leverage over the reseller. Thus, the solesupplier can exert more pressure to raise the wholesaleprice to intermediaries and the retail price to con-sumers. Reseller buyers may feel they are protectingtheir company and their shoppers by preventing suchdependence by adding a second brand into the cate-gory. A first me-too follower is obviously more likelyto reduce dependence on a pioneer sole supplier thansecond or later me-too followers, as the latter arrivewhen several brands are already carried. Pioneers mayreduce dependence on the sole supplier of a substituteproduct category. Thus:

H2e: Reseller buyers believe first me-too followers are mostlikely to reduce reseller dependence on a sole sup-plier, then pioneers, and then second or later me-toofollowers.

When the manufacturer of a brand already carriedcannot provide sufficient product to meet growing de-

28 / Journal of Marketing, July 1992

mand, a me-too follower can meet that supply gap. Asupply gap, which always results in a stockout, is mostlikely in a high growth market. Resellers abhor stock-outs because their shoppers seeking the product willbe dissatisfied. A first me-too follower is most likelyto encounter the opportunity to meet a supply gap, asoccasionally the pioneer cannot produce enough to meetall of surging demand. Second or later me-too follow-ers are least likely to be needed to meet a supply gapas the several brands already carried should have suf-ficient total capacity to meet all but the most vora-cious demand. A pioneer may fill a supply gap in asubstitute product category. Formally, we posit that:

H2f: Reseller buyers believe first me-too followers are mostlikely to help resellers meet a supply gap, then pi-oneers, and then second or later me-too followers.

Pioneers may have greater sales potential than me-too followers. Extensive scholarly research has beendone on this issue. Robinson and Fomell (1985) foundevidence of market pioneer advantage in an econo-metric analysis of PIMS data. Urban et al. (1986) alsofound support for market pioneer advantage in a sta-tistical analysis of data gathered from experience witha test market model. Carpenter and Nakamoto (1989)found laboratory evidence supporting market pioneeradvantage. Whether or not reseller buyers are awareof this literature, they may come to the same basicconclusion through experience and observation. Re-seller buyers are also likely to conclude that secondor later me-too followers, arriving into crowded cat-egories already served by prior entries, are least likelyto have strong sales potential. Thus:

H2g: Reseller buyers believe pioneers are most likely toachieve high sales volume, followed by first me-toofollowers, and then second or later me-too followers.

Pioneer brands can increase excitement aboutshopping. Something new coming out that piquesconsumers' interest can make them look forward togoing shopping. Groceries are necessities rather thanluxuries for most shoppers, so resellers face a difficulttask to generate enthusiasm about going grocery shop-ping. A constant flow of interesting new items helps.Me-too followers, being defined as about the same aspreviously introduced items, are unlikely to add muchexcitement, especially second or later me-too follow-ers. Hence:

H2h: Reseller buyers believe pioneers are most likely toincrease consumer excitement about shopping, thenfirst me-too followers, and then second or later me-too followers.

From talking with reseller buyers, we know howimportant they consider a manufacturer's marketingsupport expenditures to be. Pioneer brands must teachthe target market about an unfamiliar new product. To

do so may require more resources than me-too fol-lowers' promotion goal of brand awareness in whatmay already be at least a somewhat familiar productcategory. Second or later me-too followers, facingdimmer prospects than first me-too followers, are leastlikely to receive substantial marketing support in-vestment from their manufacturers. Therefore:

H2¡: Reseller buyers believe pioneers are most likely tohave substantial marketing support expenditures, thenfirst me-too followers, and then second or later me-too followers.

The sales potential of me-too followers can be es-timated to some degree from earlier sales of similarbrands, such as the pioneer. However, there is greateruncertainty about the sales potential of a particular pi-oneer because it is one of a kind. Resellers may ex-pect pioneers to be bigger sellers than me-too follow-ers (H2g), but variance may be higher for pioneersbecause many will not capture the public's fancy. Thus,pioneers are at a potential disadvantage.

H2j: Reseller buyers believe pioneers are most likely tohave high sales uncertainty, then first me-too follow-ers, and then second or later me-too followers.

MethodBecause our interest is in reseller buyers' attitudes to-ward pioneer and me-too follower brands, an appro-priate empirical method should in some way ask re-seller buyers about these issues. Therefore, we choseto survey reseller buyers in a confirmatory fashion.

Sample Size and Subjects

With response rate always at issue for "cold call" sur-veys, we relied on a database of food industry buyersfrom the president of IRI/ABA, whose company is amajor supplier of shelf-space planning software to su-permarkets. The database consists of food industrybuyers who have participated in the Quaker Oats Buy-ing Skills Seminar that he runs. This approach had theadvantage of a cover letter from the president of IRI/ABA introducing and endorsing the survey and thusestablishing a personal and industry-insider connec-tion with respondents. Buyers in the database repre-sent many different companies, both large and small,across the country.

Two hundred and eighty-three questionnaires weremailed in the summer of 1989. Three envelopes wereretumed as undeliverable and an attempt to verify cor-rectness of all nonrespondents' addresses showed that40 buyers no longer worked for the same company.Hence, we had an effective mailing list of 240. A totalof 139 responses were received between the initial andfollowup mailings for an overall response rate of57.9%. Six completed questionnaires from pretesting

Examination of Reseller Buyer Attitudes / 2 9

were also available, for a total of 145 observations.^The Armstrong and Overton (1977) test for nonres-ponse bias found no evidence suggesting that respon-dents might differ from nonrespondents.

QuestionnaireBecause of the reseller buyer's time limitations, a ma-jor constraint in constructing the questionnaire waslength. We kept the final version of the questionnaireto four pages and gave careful consideration to thequestions that could be included.

A central premise of our research design is thatdemand artifacts will not substantially distort re-sponses. As a check, the subjects given pretest ques-tionnaires were asked about the likelihood that re-spondents would try to please the researchers byanswering in the way they believed the researcherswanted. All those pretested reported that they defi-nitely believed other respondents would give honestanswers. They also felt the questionnaire addressedmany issues, so the researchers' agenda was not de-tectable.

Results

Our first hypothesis attempts to answer the questionof whether it matters to reseller buyers whether anew brand is a pioneer or me-too follower. We mea-sured the key attitude construct in two distinct ways,through single-item and multiple-item measures (thelatter provided by the importance-likelihood model),thus allowing for convergent validity in our findingsand a deeper understanding of the underlying com-ponents used in the formation of attitude. The surveyquestionnaire asked reseller buyers the following globalattitude question (similar to that of Smith and Swinyard1983) for each entry order category: "My overall at-titude toward carrying [pioneers, first me-too follow-ers, second or later me-too followers] in our stores atthis time is . . . (extremely negative = — 3 to ex-tremely positive = +3)." The first three rows of Table1 show mean overall attitude responses and t-statisticsfor each entry order category; the last three rows showthe mean differences and t-statistics between each pairof those three means. Similarly, Table 2 shows atti-tude and attitude differences derived from the mul-tiattribute model.

A one-way repeated-measures analysis of varianceapplied across brand types revealed a significant dif-ference across brands for both global attitude and

'The main result of pretesting was to make the questionnaire shorter,so the remaining questions were the same as on the final question-naire. No difference was detected when we compared findings withand without the pretest responses. Therefore, the pretest responseswere included in the analysis.

attitude calculated through the multiattribute model(F = 282.10, p < .0001 for global attitude; F = 179.23,p < .0001 for multiattribute attitude). Univariate t-tests reject in every case the null hypothesis that at-titude toward pioneers, first me-too followers, andsecond or later me-too followers really equals zero andtherefore is neutral (shown in the first three lines ofTable 1 and Table 2). Finally, paired-comparison t-tests reject in every case the null hypothesis of no sta-tistically discernible difference between each pair ofthose means (shown in the last three lines of Tables1 and 2). These results strongly support Hp

Besides being statistically significant, these resultsappear to be "policy significant" because differencesin attitude seem large in relation to the 7-point scaleon which they were measured. Furthermore, thesefindings demonstrating me-too follower disadvantageare important because, according to our survey, morethan two-thirds of new items are me-too followers.^

An important issue is whether reseller buyers' dif-ferent overall global attitudes toward pioneers, firstme-too followers, and second or later me-too follow-ers can be linked to the importance-likelihood mul-tiattribute model and relevant attributes. As a criterionvalidity test for expectancy-value models, differencesin attitudes from the single-item measures (discussedpreviously) were correlated with differences in atti-tudes calculated by the importance-likelihood model.The first three rows of Table 3 show that differencesin attitude between brand entry order classificationsare indeed correlated when measured in an overall ascompared to an importance-likelihood approach. Testresults clearly reject in every case the null hypothesisof no correlation, supporting the use of the impor-tance-likelihood model with the study's attribute set.Ajzen and Fishbein (1980, p. 99) suggest that for in-terpreting multiattribute attitude model criterion valid-ity correlation tests, "correlations around .30 have beenconsidered satisfactory." By this standard, the cor-relations in Table 3 are all acceptable, though the low-est correlation (.27 for the pioneer vs. me-too fol-lower comparison) would preferably have beenstronger.

These hypotheses address the issue of why entry ordermatters by examining entry order differences amongbrands on each of the attributes. Table 4 summarizesthe measurement and analysis for Hj^ through H2J. Letus examine the first row to show how Table 4 is in-terpreted. To the general question, "How importantis it for a new item to . . .," respondents gave for theattribute "contribute incremental sales; not cannibal-

'Reseller buyers in our survey reported that pioneers, first me-toofollowers, and second or later me-too followers made up respectively13%, 23%, and 46% of new items.

30 / Journal of Marketing, July 1992

TABLE 1Attitude Toward Entry Order Categories Measured by Single-Item Overall Measure

ProbtBrand Type n Mean t Hp: Mean = 0PioneersFirst me-too followersSecond or later me-too followers(Pioneers-first me-too followers)(First me-too-second or later followers)(Pioneers-second or later followers)

144144144144144144

2.221.13-.841.091.973.06

25.4313.75-6.71

9.9417.4618.84

< .0001< .0001< .0001< .0001< .0001< .0001

TABLE 2Attitude Toward Entry Order Categories Calculated From Importance-Likelihood ModeP

Prob tBrand Type n Mean t Hp: Mean = 0

PioneersFirst me-too followersSecond or later me-too followers(Pioneers-first me-too followers)(First me-too-second or later followers)(Pioneers-second or later followers)

'Attitude calculated in the standard way as the sum of the Importance-weighted likelihood beliefs. Note that sample sizes are slightlysmaller than in Table 1 because importance-likelihood model calculations require that all 10 importance ratings and all 10 re-spective likelihood beliefs be filled in by respondents, and in a few cases values were missing.

TABLE 3Correlation of Single-Item Measured Attitude Versus Importance-Likelihood Model Calculated Attitude

129133133129133129

35128916863

121183

35.4834.0316.337.27

16.3114.52

< .0001< .0001< .0001< .0001< .0001< .0001

Brand Type

(Pioneers-first me-too followers)(First me-too-second or later followers)(Pioneers-second or later followers)

SingleItemMean

1.091.973.06

Importance-Likelihood

ModelMean

63121183

Cor-relation

.27

.44

.41

ProbHp: r = 0

.0017< .0001< .0001

n

129133129

ize" an average importance rating of 8.6 (in column1 on a scale of 0 = not important to 10 = extremelyimportant). Similarly, to the general question, "Howlikely is each type of new item to . . .," respondentsreported for the same attribute an average likelihoodof 8.6 (on a scale of 0 = not likely to 10 = extremelylikely) for pioneer brands (column 2), 6.1 for first me-too followers (column 3), and 3.8 for second or laterme-too followers (column 4). Column 5 presents thedifference in likelihoods for the pioneer versus the firstme-too follower (8.6 — 6.1 = 2.5), whereas columns6 and 7 show the respective differences for the firstversus second me-too follower comparison (6.1 — 3.8= 2.3) and then the pioneer versus second me-too fol-lower comparison (8.6 — 3.8 = 4.8). According tothe importance-likelihood model, when each of theserespective differences is multiplied by the importancescore for the attribute (i.e., 8.6 for not cannibalizing),the results are attitudinal impact scores (as presentedin columns 8, 9, and 10).

Because there are 30 attitudinal component dif-ferences in columns 8 through 10 to be tested, a mul-

tiple comparison procedure is necessary to identifywhich differences are statistically significant. We chosethe Tukey-Kramer method because it is superior toother multiple comparison procedures when all pair-wise comparisons for the set of means are of interest(Neter, Wasserman, and Kuttner 1988, p. 584). Wereport these test results in Table 4 (columns 8-10),using a 5% experimentwise error rate. Asterisks bythe numbers in columns 8 through 10 indicate that thedifferences are significant, thus supporting H2a.

Table 4 shows that the largest impact contributingto reseller buyers' less favorable opinion of me-toofollowers arises from me-too followers' much lowerability to meet an unmet need, contribute incrementalsales, and generate excitement about going shopping,as well as their lower potential to achieve high vol-ume—four of the most important criteria for new items.Second or later me-too followers in particular per-formed dramatically worse than pioneers on thesequalities, as expected. First me-too followers also werepoor on these attributes, being rated less likely to bringabout the desired consequences than pioneers, but still.

Examination of Reseller Buyer Attitudes / 31

TABLE 4Attribute Analysis With Hypothesis Test Results^

HypothesisNumber

2a

2b

Measures'*

Contribute incrementalsales; not cannibalize

Meet an unmeet need; pro-vide a unique advantage toconsumers

Importance*̂1

8.6

8.4

Likelihood"

P

8.6

9.1

1

6.1

5.7

2

3.8

2.8

LikelihoodDifferences

P_1 i_2 p-2

2.5 2.3 4.8

3.4 2.9 6.3

Impact on AttitudeDifference, WithTukey-KramerTest Results

1» 1« 1«{P-) 11-2) IP-2)

21.5* 19.8* 41.3*

28.6* 24.4* 53.0*

2c

2d

2e

2f

2g

2h

2i

2j

Lead to unhealthy, excessivecompetition that slows thesales growth of close substi-tutes we already carry (e.g.,"drain the category") 6.3

Lead to healthy competitionthat speeds sales growth ofclose substitutes we alreadycarry (e.g., "build the cate-gory") 6.9

Keep us from becoming de-pendent on our sole supplierof a similar item 5.2

Meet a current or predictedsupply gap from shortagesof a similar item we alreadycarry 6.4

Potentially achieve high vol-ume 8.3

Generate consumer excite-ment about going shopping 7.0

Come with substantial man-ufacturer's consumer mar-keting expenditures (ads,promotion, etc.) 7.9

Leave me with high uncer-tainty about sales potential 7.1

3.1 4.1 5.1 -1.0 -1.0 -2.0 -7.6* -6.9* -13.9*

5.8 6.6 4.9 - .8 1.7 .9 -5.7* 11.7* 6.3*

4.3 5.9 4.6 -1.6 1.3 - . 3 - 8 . 3 * 10.8* -1 .7**

4.8 5.4 4.0 - .6 1.4 .8 -4.2« 9.0* 4.8*

8.0 6.0 4.0 2.0 2.0 4.0 15.8* 16.6* 32.4*

7.5 4.9 2.8 2.6 2.1 4.7 15.2* 14.7* 32.9*

8.2 7.4 6.0 .8 1.4 2.2 5.6* 10.3* 16.6*

5.7 4.6 4.9 1.1 - .3 .8 7.i ' - 2 . 1 * * 5.0**

'I = importance, P = pioneer likelihood, 1 = first me-too likelihood, 2 = second or later me-too likelihood.''Attribute definitions as presented to reseller buyers in the questionnaire. Emphasis added.'Scale: not important = 0 to extremely important =10."Scale: not likely = 0 to extremely likely = 10.'Borderline. Sign right direction. Tukey-Kramer CI at p = .05: -9.1 to 2.4. One-sided t-test p = .014.'Borderline. Sign right direction. Tukey-Kramer CI at p = .05: -.054 to 11.62. One-sided t-test p = .0006.*Tukey-Kramer method simultaneous tests of attitude difference impacts reject null hypothesis of mean difference equal zero

statistically significant at p = .05.**Not statistically significant.

as predicted, were much more likely to bring themabout than second or later me-too followers. The greatimportance of these four criteria, combined with largedifferences in likelihood of achieving them, contrib-utes to their substantial impact on attitude differences.These results (Table 4) strongly support H2a, H2b, Hzg,and H2h- Clearcut support for H2c, H2d, and H2Í is alsoevident in Table 4.

The remaining three hypotheses (H2e, H2f, and H2j)

all have one or more nonsupporting or borderline find-ings.'' Though one prediction (the least important) forH2e is not supported, the main prediction is sup-ported—first me-too followers are found to be most

"The p = .05 cutoff is arbitrary, and all borderline results were nearthat cutoff. Note that the Tukey-Kramer test is a somewhat conser-vative test for our research design in that it is limited to two-sidedtests when one-sided tests would be more suitable for the directionalpredictions in the attribute hypotheses.

32 / Journal of Marketing, July 1992

likely to reduce reseller dependence. H2f receives lim-ited support in that pioneers were only marginally lesslikely to meet a supply gap than first me-too follow-ers. Finally, H2J is not supported. No significant dif-ferences between brand entry order conditions are ob-served in terms of sales uncertainty.

In sum, 25 of 30 attitude component differencepredictions are statistically supported, and seven of 10hypotheses in the subset of H2 are entirely supported.Hence, the pattem of results from the Tukey-Kramertest provides strong support for our proposed expla-nation for reseller buyers' different attitudes towardpioneers, first me-too followers, and second or laterme-too followers.

Because H| and H2 involve attitude, for complete-ness we believed it was important to straightforwardlyquery reseller buyers about behavioral consequences.We asked them whether "some me-too followers arerejected primarily because they are me-too followers"(strongly disagree = — 3 to strongly agree = +3).Seventy-three percent of respondents agreed, with amean response of 1.14, which is significantly greaterthan zero (t = 7.92, p < .0001).

Buyers were also asked to generalize about actualbuying outcomes over the course of a year as an in-dicator (though still self-reported) of actual buyer be-havior. When asked, "Approximately what percent ofeach brand type did you accept?", buyers reported that64% of pioneers were accepted, 47% of first me-toofollowers were accepted, and only 27% of second orlater me-too followers were accepted (all three per-centages statistically discernible from each other at p< .0001). Thus me-too followers' attitude disadvan-tage (refiected by support of the prior attitudinal hy-potheses) seems to have the expected behavioral con-sequences. Furthermore, the critical elements forimproving attitude-behavior correspondence—target,action, context, and time (Ajzen and Fishbein 1977)—are consistent between reseller buyer attitude towardbuying each entry order type and the actual buying ofeach entry order type. We conclude that though it isnot the only way to examine reseller buying, our studydemonstrates how a multiattribute attitude model canbe useful in reseller buying research.

A Causal Model Approacbto tbe Data

Though the preceding discussion presents implicit linksbetween brand entry order, reseller beliefs, reseller at-titude, and reseller buying behavior, an explicit testof the interrelationships between these constructs isextremely important from both theoretical and man-agerial perspectives. To accomplish this objective, weexamined the data by a structural equation analysisapproach—partial least squares (PLS).

The hypothesized model in Figure 1 presents acausal ordering whereby brand order of entry affectsreseller beliefs, which then infiuence attitude, whichfinally affects behavior, all in a direct sequence. Forthis model, we treated entry order as an ordinal vari-able and measured the constructs of belief, attitude,and behavior as previously noted, with two excep-tions. First, we used only global attitude (as measuredin Table 1, first three rows) because the multiattributemeasure of attitude is mathematically confounded withbeliefs. Second, we combined the data from the 10separate beliefs to form the latent construct "beliefs"by using a formative indicator approach as describedby Fornell and Bookstein (1982, p. 441-442). Theydiscuss the appropriateness of formative indicators:

Unobserved constructs can be viewed either as un-derlying factors or as indices produced by the ob-servable variables. That is, the observed indicatorscan be treated as reflective or formative. Reflectiveindicators are typical of classical test theory and fac-tor analysis models; they are invoked in an attemptto account for observed variances or covariances.Formative indicators, in contrast, are not designed toaccount for observed variables; they are used to min-imize residuals in the structural relationship. Decid-ing how unobservables and data should be related in-volves three major considerations: study objective,theory, and empirical contingencies.

If the study is intended to account for observablevariances, reflective indicators are most suitable. Ifthe objective is explanation of abstract or "unob-served" variance, formative indicators would givegreater explanatory power . . . when constructs areconceived as explanatory combinations of indicators(such as "population change" or "marketing mix")which are determined by a combination of variables,their indicators should be formative.

We selected PLS, rather than the more common LIS-REL approach, because it allows the use of formativeindicators to model the beliefs construct.

To construct the causal model, we decomposed theresponses of each of the 145 respondents into threeseparate cases (i.e., pioneer, first me-too follower, andsecond or later me-too follower), yielding a usablesample size of 378. This analysis approach allows fordirect testing of the hypothesized model in Figure 1,with the entry order construct operationalized as anordinal variable (1 = pioneer, 2 = first me-too fol-lower, 3 = second or later me-too follower). Statis-

FIGURE 1A Model of the Effects of Entry Order on Beliefs,

Attitudes, and Behavior

Examination of Reseller Buyer Attitudes / 33

tical significance of the parameters was determined byusing a maximum likelihood estimation technique(Jöreskog and Sörbom 1981), with the PLS latentvariable correlation matrix as input, to calculate thet-value for each parameter estimate. The significancelevels would present some evidence that the relation-ships are present, in fact, as opposed to the altemativehypothesis that they are the result of a spurious ar-rangement (Fomell and Robinson 1983).

The causal model also enables us to assess the rel-ative importance of each of the 10 product beliefs,which is of both theoretical and practical import. First,we asked each respondent to rate the importance di-rectly on the questionnaire. Next, we used the loadingpattem matrices from the PLS analysis to provide adifferent perspective on the importance of the variousattributes. We then compared these two different es-timates for further assessment of convergent validitybetween the two methods.

Hypothesized ModelTable 5 is the correlation matrix used for input for thePLS analysis. Results are reported in Table 6. Thedata fit the hypothesized model well. All parameterestimates are large and statistically significant. Find-ings reveal that entry order strongly infiuences buy-ers' beliefs about the brands (gamman = - . 82 , p <.05) and the beliefs strongly infiuence overall attitudetoward the brand (beta2i = .76, p < .05). Overallattitude has a substantial infiuence on the decision tostock the product (beta32 = .47, p < .05). In this model,entry order alone explains 67% of the variance in be-liefs about the product. The beliefs modeled here ex-plain 58% of the variance in overall attitude towardthe brands. Finally, 22% of the variance in the stock-

ing decision is explained by the buyers' overall atti-tude toward the brand.

Full ModelA more comprehensive model includes direct rela-tionships among all the latent constructs (i.e., gamma2i,gamma3,, beta3i). Testing of the model (see Table 6)indicates that entry order has substantial direct effectson overall attitude (gamma2i = - .30 , p < .05) andbehavior (gamma3, = - . 27 , p < .05), increasing thevariance explained by the latent constructs, eta2 (at-titude) by 3% and eta3 (behavior) by 4%. An effectof beliefs on behavior (beta3i = .05, p < .05) is alsoevident.

Importance of Separate Belief ComponentsAs suggested by the information in Table 7, the im-portance of the various product beliefs varies sub-stantially. When directly rated by buyers through oursurvey (see column 1), "does not cannibalize" ratedhighest at 8.6, followed by "meeting an unmet need"(8.4), "achieving high volume" (8.3), and "marketingexpenditures" (7.9). Among the analytically derivedimportance ratings (from the PLS loading pattem ma-trices included as column 2), the four most importantare "meet an unmet need" with a coefficient of .98,"generates consumer excitement" (.80), "does notcannibalize" (.76), and "achieving high volume" (.72).

Spearman's rank order correlation was appliedacross all 10 belief components to compare statisti-cally the importance of product beliefs derived fromour survey (column 1) with those analytically derivedthrough the absolute value of PLS loading pattems(column 2). The result was a rank correlation of rs =.709 which, through the use of a one-tailed t-test

TABLE 5Descriptive Statistics and Correlation Matrix of Study Variables

(n = 378)

Entry OrderBeliefs

1.2.3.

A

Not cannibalizeUnmet needUnhealthycompetitionUaoltk\/

Mean

6.185.87

4.19

S.D.

3.163.15

3.20

1.00

-.616-.806

.297

1.00.696

-.208

1

1.00

-.277 1.00 <

competition5. Dependent6. Supply gap7. Volume8. Excitement9. Marketing

support10. Uncertainty

AttitudeBehavior

6.71 2.94 -.124 .212 .181 .323 1.004.91 3.16 .041 .121 .059 .251 .568 1.00 ,4.71 3.14 -.085 .193 .193 .193 .213 .527, .642 1.005.96 2.75 -.579 .688 .624 -.021 .326 .151 .311 1.005.13 3.05 -.637 .678 .697 -.041 .241 .104 .322 .693 1.00

7.24 2.42 -.337 .386 .437 .125 .382 .333 2.75 .395 .372 1.00 ,5.14 3.01 -.084 .112 .142 .340 .165 .176 .143 .102 .066 .273

.785 1.75 -.723 .585 .742 -.219 .231 .108 .193 .562 .624 .38947.35 32.65 -.482 .348 .446 -.113 .071 -.038 .106 .332 .293 .205

1.00.039 1.00

-.004 .471 1.00

34 / Journal of Marketing, July 1992

TABLE 6Relationships Among Entry Order, Beliefs,

Attitude, and Behavior (n = 378)

Parameter

T i l

T2I

T3I

ß21ß32ß31R^ for TillR^ for TI2R^ for Ti3Model's RMS

Hypothesized Model-.82*

——.76*.47*—.67.58.22.52

Full Model-.82*-.30*-.27*

.51*

.24*

.05*

.67

.61

.26

.52

*p < .05.

(Rickmers and Todd 1967), is significant at p < .02,indicating that despite some differences the two mea-sures of importance lead to basically the same result.

The fact that factor loadings (derived from PLS)significantly match results on belief importance de-rived from our survey lends validity to our findingsbecause similar results were obtained by substantiallydifferent methods. This finding suggests that the fac-tors the buyers "say" are important do indeed influ-ence their decisions.

Discussion of the Model's Findings

The results of the PLS causal model suggest that entryorder directly affects beliefs, and thereby indirectlyaffects attitude and the stocking decision (i.e., the causalchain, entry order -^ beliefs —> attitude —» behavior).Entry order also is found to directly affect attitude,possibly suggesting that our list of beliefs is not com-

plete and/or that entry order affects behavior througha mechanism other than the belief-attitude (cognitive)model. However, our list of beliefs does perform wellby explaining 58% (more than half) of the variancein overall attitude in the hypothesized model.

Obviously, more work needs to be done to de-velop a more comprehensive model (i.e., to explaina greater percentage of the variance in the stockingdecision). Clearly, our study and causal model couldbe extended to a consideration of moderating influ-ences on brand entry order, which also affect the re-seller's stocking decision. For example, 85% of thereseller buyers we surveyed agreed that they wouldchange their minds and accept a me-too follower brandthat they would not otherwise accept if it came witha strong brand name extension. Other moderating in-fluences on brand adoption—such as the amount ofbusiness done with the supplier and the effect of a"pull" promotional strategy on the part of a large sup-plier—could be modeled in more comprehensive studiesin the future.

ConclusionA national survey of 145 reseller buyers was used tostudy how brand entry order into new categories af-fects reseller buyers' attitudes toward new items. Thesurvey documents that reseller buyers have a muchmore favorable attitude toward pioneer brands than to-ward me-too follower brands (Hj). Key causes for whythis difference occurs are found to be the lower like-lihood of me-too followers, especially second or laterme-too followers, to bring about consequences fromnew items that are important to reseller buyers: in par-

TABLE 7Comparison of Buyer-Related Significance With Analytically Derived Significance of Product Beliefs

Analytically Derived PLSLoading Pattern

Beliefs Rated Directly by Subjects CoefficientsContribute incremental sales; not cannibalizeMeet an unmet need; provide a unique advantage to

consumersLead to unhealttiy, excessive competition that slows

the sales growth of close substitutes we alreadycarry (e.g., "drain the category")

Lead to healthy competition that speeds sales growthof close substitutes we already carry (e.g., "buildthe category")

Keep us from becoming dependent on our solesupplier of a similar item

Meet a current or predicted supply gap fromshortages of a similar item we already carry

Potentially achieve high volumeGenerate consumer excitement about going shoppingCome with substantial manufacturer's consumer

marketing expenditures (ads, promotion, etc.)Leave me with high uncertainty about sales potential

8.68.4

6.3

6.9

5.2

6.4

8.37.07.9

7.1

.76

.98

-.33

.22

.04

.17

.72

.80

.46

.08

Examination of Reseller Buyer AttKudes / 35

ticular, meeting an unmet need, contributing incre-mental sales, generating excitement about going shop-ping, and having potential to achieve high volume (H2).In sum, eight of 11 hypotheses are clearly supported.Moreover, the results of our causal model are consis-tent with what direct questioning revealed. That is,entry order directly affects beliefs and thereby affectsattitude, and so me-too follower brands are less likelyto be stocked.

Two limitations of our study must be kept in mind.First, the hypotheses were tested only on the groceryindustry, which may limit their generalizability. Sec-ond, all data are self-reported. Future research cancorroborate our results from self-report data with a di-rect statistical test of our hypotheses using actual buy-ing data.

Keeping these limitations in mind, let us now con-sider the most important implications of our results formarketing theory. Our main finding is that resellerpreference for pioneer brands should be includedamong the sources of pioneer brand advantage. Therole of resellers has been underemphasized in the past,as the literature on pioneer brand advantage rarelymentions resellers. Until now, reseller buyer attitudein favor of pioneer brands has not been demonstratedempirically.

In addition, a tripartite entry order classificationthat distinguishes between first me-too followers andsecond or later me-too followers is found to be sig-nificant. Reseller buyers have a more favorable atti-tude tov/aid first me-too followers than toward secondor later me-too followers. Of special note is the find-ing that first me-too followers have unique advan-tages, such as being more likely to generate healthycompetition, prevent a possible supply gap, and re-duce dependence on the sole supplier of a product.These findings suggest that it may be inaccurate tolump all me-too follower brands together when ana-lyzing entry order effects.

Furthermore, one sometimes hears that the effi-cacy of the marketing concept has yet to be actuallyproven (Narver and Slater 1990). Our study suggeststhat brands neglecting the marketing concept's ad-monition to find and satisfy an unserved need will windup facing me-too follower disadvantages with resellerbuyers. Reseller buyers are not only serving their own

interests, but also are providing the valuable serviceof screening out new items that probably would notinterest consumers.

As a practical matter, managers of me-too fol-lower items have several options for gaining reselleracceptance of their product. First, an attempt can bemade to break out of me-too status by varying productcharacteristics or product positioning such that keybenefits sought by reseller buyers—meeting an unmetneed, not cannibalizing, generating excitement aboutshopping, and providing potential to be a relativelybig seller—are perceived by reseller buyers as morelikely to be delivered. One less costly approach, whichrequires great creativity, is to put together a "sellingangle." For example, during exploratory interviewsone sales manager reported success with an extra at-tractive joint promotion for a new me-too item andseveral established items of the same product family.A deal like this is a win-win opportunity, because forthe manufacturer the resource commitment is one timeonly and the financial expenditure is allocated to con-sumer promotion instead of slotting allowance. Forthe reseller, established brands with proven customerattractiveness went on deal. As noted, however, someestablished manufacturers can disregard such strategicand tactical adjustments by virtue of powerful brandname extensions that can overcome me-too followerdisadvantage.

To research on reseller buying, our study contrib-utes a multiattribute attitude model that isolates andmeasures key beliefs that explain how brand entry or-der affects reseller buying. In addition, our results showthat a multiattribute model is a useful and valid toolfor studying reseller buying, and that it can dovetailwell with a causal model approach.

In sum, reseller buyer preference for pioneer itemsover me-too follower items is a major consideration.The study of reseller buyer attitudes toward brand en-try enriches both our understanding of reseller buying,at a time when reseller buying is becoming an evermore important factor in marketing, and our under-standing of pioneer brand advantage. In £in increas-ingly competitive economy, pioneer brand advantageis a source of long-term sustainable competitive ad-vantage for companies. It is also a source of increasedconsumer welfare through the emphasis on product in-novation.

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