Perspectives on Multiple Category Choice

Marketing Letters 8:3 (1997): 297–305© 1997 Kluwer Academic Publishers, Manufactured in The Netherlands

Perspectives on Multiple Category Choice

GARY J. RUSSELLCollege of Business Administration, 108 Pappajohn Business Administration Building, The University of Iowa,Iowa City, IA 52242-1000

DAVID BELLUCLA

ANAND BODAPATINorthwestern University

CHRISTINA L. BROWNNYU

JOENGWEN CHIANGHong Kong University of Science and Technology

GARY GAETHUniversity of Iowa

SUNIL GUPTAColumbia University

PUNEET MANCHANDAColumbia University

Abstract

Multiple category choice is a decision process in which an individual selects a number of goods, all of whichare nonsubstitutable with respect to consumption. Choices can be made either simultaneously or sequentially.The key feature of multiple category choice is the treatment of the choices as interrelated because each item inthe final collection of goods contributes to the achievement of a common behavioral goal. We discuss current andpotential applications of psychology, economics and consumer choice theory in developing models of multiplecategory choice.

Key words: multiple category choice, product bundles, market basket models

Introduction

In many settings, consumer choice involves the selection of a collection of goods. Forexample, consumers may choose a basket of items in a grocery store setting, a portfolioof securities at a brokerage firm, or a predefined set of concert tickets from a performing

Kluwer Journal@ats-ss11/data11/kluwer/journals/mark/v8n3art5 COMPOSED: 07/29/97 10:29 am. PG.POS. 1 SESSION: 7

arts organization. The way consumers go about constructing and evaluating such collec-tions of goods is of considerable interest. In particular, researchers wish to know whenconsumer behavior theories based upon single-item choice fail to predict behavior ad-equately in a situation involving multiple choices.

The purpose of this review is to highlight current and potential contributions of psy-chology, economics, and consumer choice theory in developing a theory of multiplecategory choice. We begin by defining multiple category choice as a multiple item selec-tion task in which both consumption complementarity and substitution enter into thedecision process. We then examine two distinct research streams (bundle valuation andmarket basket analysis) which explore why multiple category choices are interrelated andhow this choice dependence may be modeled. We conclude with an agenda for futurework.

Defining multiple category choice

Because many choice problems deal with the selection of several items (either sequen-tially or simultaneously), the number of items selected during the choice process does notprovide a clear definition of multiple category choice. Even a single category choice task(e.g., choosing a brand of coffee) can be viewed as the selection of a multiple item set(e.g., all coffee brands purchased during a one year period) by appropriately redefining thescope of the decision. Because of this ambiguity, a richer conceptual framework is neededto draw attention to the distinguishing characteristics of multiple category choice.

We define a category as a set of items, each of which are substitutes relative to aconsumer’s consumption utility (cf. Simmons 1974). Because a consumer may elect notto make a choice from some category, we also assume that each category includes a nullalternative which corresponds to non-choice. To separate categories, however, we requirethat any two items from different categories be either complements or independent, againviewed relative to consumption utility. Using this terminology, we define a multiplecategory choice problem as the selection of a collection of category choices for a given setof category alternatives.

The key feature of multiple category choice is that elements of the collection are notsubstitutes. In many settings, the consumer is confronted with a “pick any” situation andmay elect to include alternatives from only a subset of the available categories. Thisflexibility in tailoring the bundle stands in sharp contrast to a single category choice taskrequiring the consumer to pick one (non-null) item from a set of given alternatives. Insome choice situations (such as pure bundle selection), the consumer is not allowedcomplete freedom to tailor the final set of category alternatives. For example, in choosingoptions for a new automobile, consumers may only be able to obtain a given set of optionsby purchasing a larger bundle of options defined by the manufacturer. Nevertheless, wedefine such tasks as multiple category choice because the items in the selected bundleretain the property of being nonsubstitutable with respect to demand.

Our definition also implies that choices in one category alter the utility of choices inother categories. For example, a selection of a type of cake mix and a type of cake frosting

298 GARY J. RUSSELL ET AL.


in a grocery retail setting is multiple category choice. Because utility of cake consumptiondepends upon an appropriate match between cake mix and frosting, the utility associatedwith one part of the bundle (cake mix) may be affected by the utility of another part of thebundle (frosting). Notice that the timing of the selections is unimportant. Suppose theconsumer already has frosting in the pantry at home. If the selection of cake mix on thenext purchase occasion is influenced by the attributes of the frosting, then we wouldregard this decision task as multiple category choice. In this instance, the bundle isconstructed sequentially (over two shopping trips), but interactions in the utilities of thebundle items are still present.

Bundle valuation

A straightforward way of building a model of multiple category choice is to assume thatthe consumer chooses all items simultaneously. The consumer’s decision process thentakes place in two stages: an evaluation of the utility of each available bundle of categorychoices followed by the selection of the most attractive bundle. Because selection isassumed to correspond to the bundle with maximum utility, the focus in this approach isunderstanding the process of bundle valuation.

This perspective is related to the classical economic theory of product bundling, thepractice of selling two or more nonsubstitutable items together at a single, combined price(Adams and Yellen 1976). The economic theory of bundling is developed from the pro-ducer’s perspective and demonstrates how different bundling strategies can affect thefirm’s profitability (Schmalensee 1984, Guiltinan 1987, Nagle 1987). In this normativetheory, consumers are assumed to view a bundle as a holistic entity whose valuation doesnot depend on the choice context.

An illustration of the normative perspective is provided by the balance model of Far-quhar and Rao (1976). Consumers assemble a bundle of products sharing a set of commoncharacteristics by trading off the maximization of the level of certain attributes with themaximization of the within-bundle variance on other attributes. Although the utilities ofdifferent parts of the bundle are clearly interrelated (i.e., the utility of adding one item tothe bundle depends upon the attributes of the items already in the bundle), the consumeralways assigns the same value to a given bundle—regardless of the specific context of thechoice setting.

An important stream of research in behavioral decision making questions this assump-tion. Yadav and Monroe (1993) use Kahneman and Tversky’s (1979) Prospect Theory toargue that consumer evaluation of a bundle depends upon how consumers frame thechoice problem—in particular, whether the bundle is viewed from the perspective ofsegregation or integration of multiple gains (i.e., multiple items in the bundle). In theirexperiment, Yadav and Monroe (1993) show that bundle transaction value is a combina-tion of perceived savings on the bundle integrated with perceived savings offered on theindividual items, as opposed to the segregated savings on the sum of the bundle items.

A more process oriented approach is based upon Information Integration Theory(Anderson 1981, 1982). Gaeth et al. (1991) show that consumers integrate information

PERSPECTIVES ON MULTIPLE CATEGORY CHOICE 299


about the products in a bundle through an averaging process and provide evidence forinteractions among the products in the bundle. That is, evaluation of a bundle can beinfluenced more by the impact of a less-expensive tie-in product than would be predictedby its monetary value alone. Recent work by Gaeth et al. (1996) provides evidence for thesub-addivity of bundle items. That is, the judgment of a bundle’s monetary worth isviewed by consumers as less than the sum of the individual product worths.

Bundle valuation can also be affected by discretion, the amount of freedom the con-sumer is allowed in selecting bundle components. Experimental work supports the notionthat the bundle is evaluated more highly when the consumer plays a role in bundlecreation (Drumwright 1992, Gaeth et al. 1996). Again, this violates the standard economicassumption that choice context plays no role in the bundle valuation process.

Market basket analysis

Market basket analysis is a generic term for models which predict the choice of a bundle(or basket) of multiple items during a single shopping occasion. Because work in this areais informed by economic theory, consumer choice theory, and statistical demand theory,market basket models do not yet incorporate insights from the psychological literature.However, all models assume that market basket construction involves interdependentchoices and offer explanations for why these dependencies exist.

Economic theory

Economic theory provides a foundation which links market basket construction to long-run consumption goals (Chiang 1996). Within each discrete time period (say a month),assume that the household must decide which bundle of items (drawn from variousproduct categories) should be consumed. Further, assume that the frequency of purchaseaffects both the transaction cost of the shopping trip and the satisfaction of productconsumption. For example, buying coffee in smaller quantity may force more trips to thestore, but yield better taste (i.e., fresher coffee).

Using these assumptions and Becker’s (1971) notion that household time constraintsaffect household consumption decisions, Chiang (1996) argues that consumers maximizea joint utility function defined over product quantity, shopping frequency, and leisure time.That is, the consumer uses a global utility function to develop a market basket purchasestrategy: when to go shopping and what to include in the market basket at each shoppingoccasion. Accordingly, the choice of items placed in a market basket reflect long-runconsumption goals, short-run environmental influences (e.g., prices), and tradeoffs overthe use of time.

A number of implications follow from this framework. First, demand for differentproduct categories can be linked either because of true consumption complementarity orbecause of the convenience of buying items during the same shopping trip. In fact,consumption complementarity may not manifest itself as coincidence in the market bas-



ket. Because products are used at different rates, it is possible for consumption comple-ments to be rarely be found in the same market basket. For example, pumpkin pie andwhipped topping (which are combined to prepare a dessert) may rarely appear in the samemarket basket because the household can use the same whipped topping over severaldessert occasions.

Second, the general formulation implies that a key component of market basket modelsis the prediction of when shopping trips occur. With a few notable exceptions (e.g., Gupta1988, Bucklin and Gupta 1992), most single category choice models take the purchaseevent as given and concentrate only upon brand choice. In contrast, depending uponcurrent levels of inventory and the promotional environment of the retailers, market basketcomposition (in terms of product categories) will fluctuate (e.g., empty (non-purchase)baskets, smaller “fill-in” baskets and larger “stock-up” baskets). These fluctuations, how-ever, are planned in the sense that they take into account the interdependencies in itemutilities implied by the household’s long-run consumption goals.

Consumer choice theory

Recent research in choice theory emphasizes store choice as an explanation of interde-pendence in multiple choices. Bodapati (1996) relates feature advertising to store trafficeffects using a nested logit framework. The model assumes that consumers choose aretailer by anticipating the cost of obtaining a likely basket of goods. Once the retailer isselected, the basket is formed by a series of nested models predicting category incidence,brand choice and purchase quantity. Managerially, the model implies that category coin-cidence in a market basket is both due to household patterns of preference across productcategories and to the store traffic effects of feature advertising.

Bell and Lattin (1996) develop a model which relates store choice to the pricingstrategy of a store across multiple product categories. Similar to Bodapati (1996), thismodel assumes that the consumer anticipates the likely market basket and chooses thestore accordingly. Although category demands are not explicitly linked, category inci-dence probability increases when the total expenditure for the trip rises. Accordingly, aconsumer who decides to make a major shopping trip (i.e., allocate a larger dollar ex-penditure to the basket) will tend to have more items in the market basket.

Both models offer only implicit ways of linking demand across product categories.Explicit ways of relating purchase probabilities across products have been proposed byHarlam and Lodish (1995) (for items within one category) and by Erdem (1995) (foritems across different categories). In each case, a consumer’s consumption experiencewith one product affects the choice probabilities of another product sharing a commonattribute such as brand name. These models are similar in spirit to the Chiang’s (1996)assumption that interdependence in choice is caused by long-run behavioral factors.



Correlational models

Russell and Rao (1996) provide a conceptualization of market basket selection as con-current Poisson time series processes in purchase volumes for all possible categorieswithin the basket. The time varying Poisson mean of each category is assumed to be afunction of retail marketing activity within and outside the target category. An alternativeapproach has been proposed by Manchanda and Gupta (1996). This work examines bothcategory incidence and brand choice for pairs of categories by incorporating both substi-tution and complementarity effects in a random utility maximization framework. Bothstudies attempt to detect the choice dependency which defines multiple category choice,but do not offer a behavioral explanation as to the source of this dependency.

Research directions

Multiple category choice is the extension of single category choice to allow for theacquisition of a collection of nonsubstitutable products. Clearly, the most distinctiveelement of multiple category choice is dependence in the choice process across categories.The work facing marketing scholars is identifying situations in which choices will bedependent and specifying the nature of the dependence.

Research scope

A central question is when a multiple category choice model is necessary. In general, amultiple category choice process will be employed whenever consumers view a singlechoice in the context of a larger choice task (Brown 1996). Accordingly, a major issue inmultiple category choice research is the identification of global utility functions which tietogether individual choices. Examples of such global evaluations include quality associa-tions due to common brand names (Erdem 1995), long-run consumption needs (Chiang1996), true product complementarity (Ratneshwar et al. 1995), and the desirability of highvariance in product attributes due to uncertain future consumption needs (Simonson1990).

Before global goals are posited in any application, researchers need to show that amultiple category choice model will yield improved predictive power relative to classicalsingle category choice models. Clearly, the selection of a bundle of categories can alwaysbe represented as a number of single category choices if we willing to assume that choicesin individual categories are independent. Relative to this benchmark, a researcher candemonstrate the existence of a multiple category choice process by using statistical pro-cedures to exhibit the presence of inter-category correlations in category choices. Thisdemonstration must be carried with individual choice data to avoid the appearance ofspurious correlations due to heterogeneity in utility parameters across consumers. Recentwork in statistics (Fahrmeir and Tutz 1994, section 3.5) gives specific methodologicalguidelines for implementing this type of analysis.



Modeling strategy

Depending upon the context of the choice problem, a researcher can view a multiplecategory choice problem as either one collective choice (analogous to pure bundle selec-tion) or a series of choices in a specified order. Viewing the collection of choices as asingle entity allows multiple category choice to be modeled as simple choice problem inwhich the consumer makes one selection over the universe of possible category bundles.Although this modeling strategy is conceptually straightforward, specification issues arecomplex. The researcher must posit a theory of bundle evaluation explaining the expectedutility interactions in cross-category attributes (e.g., the balance model of Farquhar andRao (1976)) and a realistic choice rule taking into account the varying degree of similarityof different pairs of bundles (e.g., a general covariance probit model (Daganzo 1980)).Moreover, in some settings (such as retail market basket selection), the large number ofpossible bundles will render this approach impractical.

A more flexible approach is the decomposition of the bundle into individual categorychoices made in a prescribed order. Using this modeling strategy, the consumer is stillassumed to combine attributes across products to produce global goals. However, thesequential nature of choice allows the consumer to evaluate the utility of the currentchoice relative to a cumulative variable representing the composite utility of the bundle ofprevious choices. Because the utility of the final bundle of choices is dependent upon thesequence chosen, sequential models are consistent with notion that choice context impactsbundle valuation. The advantage of the sequential approach is that the sequence informa-tion itself may allow both the utility specification and the choice rule to be comparativelysimple. For example, the Harlam and Lodish (1995) model assumes that utility dependsupon an attribute comparison (current item versus previously chosen items) while choicefollows a simple logit model.

The principal disadvantage of the approach is that sequence information may not beavailable, except in special settings (e.g., acquisition of financial instruments (Kamakuraet al. 1991)). It is possible to continue to use the sequential approach without knowingsequential information by assuming either a specified sequence rule (e.g., sequence isbased on intrinsic item preference (Harlam and Lodish, 1995)) or by assuming simulta-neous choices conditioned upon a single decision (such as the total amount to be spent onthe entire bundle (Bell and Lattin, 1996)). However, the quality of the behavioral insightsfrom the modeling effort will depend critically upon the realism of the assumed sequence.For this reason, researchers engaged in primary data collection should record the timingof decisions—not just the composition of the final bundle.

Research opportunities

Multiple category choice is a challenging research problem because it breaks away fromthe classical choice paradigm of selecting one item from a set of alternatives. Instead, thedecision maker is faced with multiple decisions, all of which may be contributing towarda global goal. The resulting behavior is complex because it involves both substitution



across alternatives within each category and mutual dependence (e.g., complementarity)in choices across categories.

The state of the art in multiple category choice modeling is best regarded as a loosely-connected collection of models designed for particular applications. Although furtherwork is needed to improve the technical aspects of model construction (e.g., global utility,decision sequence and choice rule), there is a strong need to develop an integrative theorywhich explains the role of context in choice behavior. In a certain sense, all choicedecisions—even single category choice decisions—are made in the context of previouschoices. It is not clear, however, when context is important enough to the consumer tocreate a bundle of mutually dependent choices. Research focused on this key issue,perhaps drawing upon theories in economics (e.g., long-run consumption utility) or psy-chology (e.g., framing effects), is apt to make the strongest lasting contribution towardsthe development of a theory of multiple category choice.1

Note

1. This paper is based upon the discussions of the Session on Preferences for Collections of Items of the ThirdInternational Choice Symposium, June 1996. Comments should be addressed to Prof. Gary Russell, Collegeof Business Administration, 108 Pappajohn Business Adm. Building, University of Iowa, Iowa City, IA52242.

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Perspectives on Multiple Category Choice