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Journal of Marketing Management, 2014Vol. 30, Nos. 7–8, 719–746, http://dx.doi.org/10.1080/0267257X.2013.839572

Money, mavens, time, and price search: Modellingthe joint creation of utilitarian and hedonic value ingrocery shopping

Alan Collins, Department of Food Business and Development,University College Cork, IrelandElla Kavanagh, Department of Economics, University College Cork,IrelandJames Cronin, Department of Marketing, Lancaster University, UKRichard George, Department of Food Marketing Haub School ofBusiness, Saint Joseph’s University, USA

Abstract This research deductively develops amodel of both in-store price searchand store deal proneness drawing on hedonic and utilitarian value creation.Based on a sample of 535 US grocery shoppers, the model reveals that in-storeprice search and store deal proneness share many of the same drivers, amongstthese, the value of time being the most important. The opportunity cost of timeengaged in price search is explained in terms of shoppers’ financial pressuresand role construction as price mavens. Price mavenism influences store dealproneness directly due to its capacity to yield the price information requiredto build and maintain a role identity, and indirectly through its effect on theopportunity cost of time engaged in price search. The primary implication of theresearch is that the relationship between time, search, and price mavenism maybe best explored by viewing price knowledge, the basis for identity maintenance,as a flow rather than a stock.

Keywords grocery; hedonic; utilitarian; maven; identity; price search

Introduction

Grocery shopping has arguably been conceptualised as one of the more high-frequency functionalistic marketplace activities in post-industrial society (Maher,Marks, & Grimm, 1997; Tauber, 1972). Often seen by consumers as a chore,it is characterised by high levels of mundanity, habitual, and scripted behaviourswhereby individuals are driven by necessity to patronise the market routinely for thepurposes of replenishing day-to-day household provisions (Aylott & Mitchell, 1999;Thomas & Garland, 2004). However, consumers being motivated by the mandatoryrepetitiveness of their practices often possess economic and other forms of incentive

© 2013 Westburn Publishers Ltd.

720 Journal of Marketing Management, Volume 30

to engage in search of lower prices, good deals, and promotions on their groceryshopping trips (Griffith, Leibtag, Leicester, & Nevo, 2009; McAlister, George, &Chien, 2009; Webster, 1965). This paper seeks to explain these search behavioursand reveal their underlying determinants.

Traditionally, the discussion on search behaviour has often occurred withinthe context of price sensitivity and consumer efficiency, drawing on classical andneoclassical economic theories, and views the behaviour as consistent with logical anddispassionate decision making (Becker, 1965; Stigler, 1961). This stream of literatureadopts a utilitarian perspective, assuming that the agent is rational and economising,where the value of time is evaluated primarily in terms of earnings foregone andthe wage rate (Deaton & Muellbauer, 1980). More recent work questions thisperspective, arguing that the wage rate overestimates the opportunity cost of timeengaged in search because some ‘utilitarian’ activities possess hedonic value creatingcomponents (Hibbert & Tagg, 2001; Marmorstein, Grewal, & Fishe, 1992; Urbany,Dickson, & Kalapurakal, 1996). This argument generally proposes that reasonsfor shopping extend beyond the provisioning domain (Miller, 1998) to includewider non-functionalistic value that is founded on experiential or tacitly understoodsocial benefits (Arnold & Reynolds, 2003; Megicks, Memery, & Williams, 2008).In addition to cost and time savings, elements of problem solving, feelings ofcompetence, and pleasure seeking derived from their grocery search behaviours,search can also be a means for consumers to construct and maintain their self andidentity, through choosing where to shop, identifying deals, and determining whichproducts to purchase (Campbell & Falk, 1997; Sandikci & Holt, 1998; Woodruffe-Burton & Wakenshaw, 2011). Thus, neoclassical thinking serves as the basis for anapproximation which may be more precisely attuned by considering other potentialsources of value.

In this paper, we extend the focus from the neo-classical utility maximisationproblem by drawing on concepts of identity production and value creation tocontribute to a more nuanced understanding of the motivations which drive groceryshopping behaviour characterised by search. We investigate the determinants of twoforms of external information search within the grocery market (Brown, 1988;Rose & Samouel, 2009). The first form, in-store price search, is concerned withthe extent to which the shopper compares and evaluates prices within a store. It ischaracterised by an examination of prices pre-purchase and an evaluation acrossbrands and products at the point of purchase. This form of search has a relativelylow opportunity cost of time when compared with the second form of price search,store deal proneness (SDP), defined as a shopping behaviour characterised by searchacross multiple stores for the purposes of purchasing products on special offer ortemporary price reductions.

The paper advances earlier research by specifying and modelling theinterdependencies between utilitarian and hedonic values. Furthermore, this paperdraws on recent developments in socio-economic theory which point to valuecreation through the process of socialised construction of image and the self throughthe engagement in particular rituals and practices (Cova & Dalli, 2009). This workincorporates these ideas by integrating the concept of the price maven (Lichtenstein,Ridgway, & Netemeyer, 1993) who, through the process of informationdissemination, builds identity. We will argue that price mavenism can partly explainthe extent of information search through its effect on the opportunity cost of timeengaged in search, but also directly through efficient price collection via in-store price

Collins et al. Money, Mavens, Time, and Price Search 721

comparison and across-store deal search. Price mavens’ self-constructed image willdepend on the value of their information which will in turn be related to the scopeof their information sources. By integrating the more mundane matter of householdfinances, we will show how utilitarian and hedonic motivations influence the valueof time which is shown to be the largest determinant of both forms of price search.

From a practitioner’s perspective, the relevance of the study rests with the notionthat the effect of search, particularly promotional search, can have a profoundeffect on shopper behaviour (Blattberg, Briesch, & Fox, 1995). In particular, searchactivities have been shown to influence the choice of store format (Bell, Ho, &Tang, 1998; Kumar & Leone, 1988; Tang, Bell, & Ho, 2001). Walters (1991)finds that promotional pricing has a significant effect on in-store and across-storesearch behaviour for both complementary and substitute products. In that regard,it is noteworthy that retailers invest substantial resources in providing price-relatedinformation and incentives to court shoppers while at the same time designingpolicies to reduce search behaviour (Lindsey-Mullikin & Petty, 2011; Srivastava &Lurie, 2001; Urbany, Bearden, & Weilbaker, 1988).

The structure of the paper is as follows. First, we situate the process of informationsearch within the household’s overall grocery shopping behaviours to develop thepoint that households can establish a myriad of shopping strategies to maximise theirexposure to retailers’ prices. The core concepts of utilitarian and hedonic value,price mavenism, and the opportunity cost of time are then addressed, followed bya consideration of the relationship between perceived quality and ‘trading down’ andthe consequences for price search. This is followed by the deductive developmentof a model of price information search by way of a series of hypotheses. The data-collection method will be outlined and the results of a confirmatory factor analysiswill be presented to justify our measures of the latent constructs used. The structuralmodel will be tested to find support for our hypothesised model and a discussion ofour results will follow.

Information search

Being able to identify, gather, recall, and assess market information regarding goods,prices, and so on deeply concerns the mutual configuration of knowledge and identityin such a way that it creates a sense of being a consumer (Mano & Elliott, 1997).In terms of price-related information, there is compelling evidence that shoppersexpend resources to obtain and process price information both across and withinstores (Putrevu & Lord, 2001; Urbany et al., 1996; Urbany, Dickson, & Sawyer,2000). Importantly, however, it has been well documented that shoppers have poorgrocery price knowledge and recall (Dickson & Sawyer, 1990; Kenning, Hartleb,& Schneider, 2011; Pechtl, 2008). Nevertheless, it is clear that price informationgathered helps determine the shopper’s reference price and influences the purchasedecision, and this results in conscious search processes for the ‘best deals’ (Briesch,Krishnamurthi, Mazumdar, & Raj, 1997; Monroe, 1973; Vanhuele & Drèze, 2002).Garretson and Burton (2003) equate price-conscious shopping with engagement inmarketplace monitoring and research. This involves an investment of significantamounts of time in activities such as checking flyers, cutting and collecting couponsfor competing retailers, in addition to transportation costs to visit stores (Bawa &Shoemaker, 1987; Dickson & Sawyer, 1990).


Janiszewski (1998) distinguishes between two types of search behaviour: goal-directed and exploratory search. In the current application, goal-directed searchfocuses on finding the deal and comparing prices across brands and stores. In-store price search and processing occurs when customers make decisions at thepoint of purchase (Mazumdar & Monroe, 1992). This can involve comparisonsof different combinations of price and other non-price decision variables used toevaluate competing brands and the relationship between price and perceived quality(Rao & Monroe, 1989; Richardson, Jain, & Dick, 1996; Völckner & Hofmann,2007). De Chernatony, Knox, and Chedgey (1992) argue that buying intentions areinfluenced more by relative prices rather than absolute prices which can be morereadily assessed at the point of sale. The extent of this price comparison behaviourdetermines search which can be extensive given the array of products facing theshopper.

The precise search and shopping strategies employed by households vary. Theorganisation of the shopping process itself can constitute a distinct form of searchactivity. In the grocery market, shopping missions have been classified according tomajor and fill-in trips, and both have been implicated with store deal proneness (Kahn& Schmittlein, 1992; Kollat & Willett, 1967). A third type of shopping trip, cherrypicking, is also recognised, where the shopper’s primary, or in extreme cases, solemotivation to visit a store is to purchase products on promotion or deal (Walters &Jamil, 2003).

Seminal work by Stigler (1961) focused on an evaluation of the economic costsversus economic benefits of search, proposing that search would continue as long atthe marginal benefits of search exceeded the costs. This work was advanced by Stiglerand Becker (1977) and by Ratchford (2001) who integrate the role of informationcapital as an output of the search process. More recently, the determinants ofprice search have been extended and categorised according to economic benefits,hedonic benefits, and economic costs (Ailawadi, Neslin, & Gedenk, 2001; Urbanyet al., 1996). Moving away from the original narrow economic focus has allowedattention to be paid to particular shopper characteristics and types, most notablyprice mavens (Berne, Mugica, Pedraja, & Rivera, 1999; Lichtenstein et al., 1993;Urbany et al., 1996). Importantly, however, before we introduce the theoreticalarchitecture supporting the concept of price maven, it is necessary to outline firstits association with hedonic value creation and furthermore how hedonic value canbe jointly produced with utilitarian value.

Utilitarian and hedonic shopping values

The central aspect of information search is the evaluative consequence of a shoppingexperience, that is, the value that is generated. Vargo and Lusch (2008) affirm that‘value is always uniquely and phenomenologically determined by the beneficiary’(2008, p. 7), suggesting value, as evaluation of an experience, can be defined byits ‘uniqueness’ and subjectivity. Specifically, value can have different meanings andcharacteristics depending on people, contexts, and activities. In terms of valueembedded in the shopping experience, Hirschman (1984) asserted that all shoppingendeavours involve the stimulation of thoughts and/or senses, and accordingly, theymay be viewed as a process that provides the individual with both cognitive andaffective benefits. This cognitive–affective dichotomy corresponds to ‘utilitarian’ and


‘hedonic’ shopping values. A consumer receives utilitarian shopping value whenhe or she obtains the needed product, and this value increases as the consumerobtains the product more effortlessly (Babin, Darden, & Griffin, 1994; Seo & Lee,2008). Utilitarian consumer behaviour is explained through task-related and self-oriented rational actions (Batra & Ahtola, 1990; Kempf, 1999; Urbany et al., 1996).Information search and the identification of price promotions and a comparison ofprices on-shelf should theoretically provide the consumer with benefits in the formof money savings and time effectiveness in acquiring required goods.

Compared to utilitarian value, hedonic shopping value is less easily quantified interms of rationalised benefits. Its value is perceived through the holistic emotionalsensations of fun, entertainment, and pleasure embedded in shopping behaviouras opposed to goal achievement (Hirschman & Holbrook, 1982). It includesexperiential feelings of adventure and discovery within a store and across stores.Shoppers find their experience interesting and engaging. It is not so much the endresult of purchasing a good deal but rather the excitement or intrinsic rewardsthat are felt throughout the discovery process. As Babin et al. (1994) reported,some shoppers just enjoy the practice of shopping around and seeking out deals.Further support is provided by Garretson and Burton (2003) who argue thatwhile retailers have attempted to reduce sharply the use of sales promotions inexchange for the development of consistent everyday low price (EDLP) initiatives,strong negative reactions from many consumers indicate they do not necessarilyfavour the reduction of sales promotion activities. Other authors suggest that ahigher-order source of hedonic value can also be generated from sales promotionsbecause the bargain may be a source of pride and accomplishment which can beshared with another person. Specifically, compared to shopping’s utilitarian aspects,hedonic values derived from shopping experiences that result in price savings includecompetence or a sense of accomplishment. Paying a low price for a particular itemmight lead a consumer to feel proud, smart, or knowledgeable (Holbrook, Chestnut,Oliva, & Greenleaf, 1984). Moving a little further conceptually, Schindler (1989)reports the excitement that is often experienced by consumers from encounteringa price promotion suggests that there is what he labels ‘an ego-expressive’ as wellas utilitarian aspect to a price. This ego-expressive aspect results in ‘smart shopperfeelings’ which transcend basic temporary feelings of hedonic satisfaction and may beparticularly relevant for the construction of their sense of self (Feick & Price, 1987;Guiltinan & Monroe, 1980; Kassarjian, 1981; Slama & Tashchian, 1985; Thorelli,Becker, & Engledow, 1975; Walsh, Gwinner, & Swanson, 2004). This brings us tothe concept of price mavenism which may be useful in elaborating consumers’ prideregarding their efficacy and communicable knowledge established during informationsearch.

Price mavenism

There is a widening acknowledgement that consumers go to markets to produce theiridentity – specifically aspects of their self-concepts (Cherrier & Murray, 2004; Fırat& Dholakia, 1998; Hogg & Michell, 1996). That is, being a ‘smart shopper’ is centralto their identities. There may also be the satisfaction of anticipating that the shoppingexpertise demonstrated by having found low prices can be used to help others getlow prices (Feick, Price, & Federouch, 1988). As a way of conceptualising this form


of identity construction and social fellowship, the market maven construct, firstintroduced by Feick and Price (1987), has attracted considerable scholarly interest.

Market mavenism is defined as a role identity characterised by possession ofgeneralised marketplace information, expertise, and influence over other consumers.As a role that can be adopted, the maven encourages enjoyment of shopping, theinitiation of discussions about shopping, and the desire to respond to requests forshopping information from other consumers (Feick & Price, 1987; Goodey & East,2008). Importantly, market mavenism as a role any consumer can adapt is thought tobe continuous in that it captures ‘market maven propensity’ rather than identifies‘mavens versus nonmavens’ (Feick & Price, 1987). In this sense, market mavenpropensity may be feasibly higher for one individual compared to another, and mayalso increase or decrease over the lifetime of a consumer, or fluctuate dependingon the market in which they are interacting. The grocery market, however, is aprincipal plateau for embodying the role of maven as grocery shopping, and foodprices are fertile ground for media comment and a common topic for discussionamong consumers.

Because of the wide-ranging salience of price information in the marketplace,Lichtenstein et al. (1993) developed a narrower perspective of the market mavenrole than Feick and Price (1987) by considering only price as consumers’ nexusof market knowledge, thus coining the construct ‘price maven’. Lichtenstein et al.(1993) define price mavenism as ‘the degree to which an individual is a source forprice information for many kinds of products and places to shop for the lowest prices,initiates discussions with consumers, and responds to requests from consumers formarketplace price information’ (p. 235). The price maven operates according toindividual propensity like its father concept. In order to manage consistency withthe focus of the present study, we consider price mavenism (i.e. consumers’ role asa source of low price information for other people) rather than the broader marketmavenism as a crucial construct in determining within and across-store informationsearch in the grocery market.

Measuring the opportunity cost of price search

An essential element of adopting the price maven role identity is a willingness toinvest effort to gather information for specific product purchases (Mano & Elliott,1997). In investigating price information search, various researchers have come torecognise that the ‘price’ shoppers pay can extend far beyond money to includeinvestments of time and effort (Babin & Darden, 1995; Batra & Ahtola, 1990; Bolton& Drew, 1991; Zeithaml, 1988). It is well recognised throughout the economics andmarketing literatures that the opportunity cost of the time taken up in searching willinfluence the extent to which individuals engage in search activities (Becker, 1965;Stigler, 1961; Urbany et al., 1996). According to Bryant (1990), the opportunity costof time may be defined as ‘the value of what was foregone in order for the individualto spend his or her time in the manner he or she did’ (p. 160). Economic theory positsthat individuals would spend additional time engaged in search as long as the benefitsof search exceed the marginal costs. The opportunity costs of search were usuallydominated in terms of currency and equated with the wage rate (Becker, 1965;Putrevu & Ratchford, 1997; Stigler, 1961). This measures the return forgone from anhour’s work in terms of the goods and services that could have been purchased with


that wage. However, research by Marmorstein et al. (1992) demonstrates that thewage rate overestimates the opportunity cost of time and that ‘the net opportunitycost of time equals the wage rate minus the utility that the shopper gets from . . .

shopping’ (p. 52). Further support for the overestimation caused by the use of thewage rate is provided by Okada and Hoch (2004) who find that spending time, oneof the chief elements of search, has a lower opportunity cost when compared tospending money.

Perceived quality and trading down

The purchase decision involves an evaluation of both prices and products.Consequently, one final consideration to take into account before model developmentis the relationship between price and perceived quality (Monroe, 1979; Rao &Monroe, 1989; Zeithaml, 1988). While the strength of the relationship will varyaccording to the availability of other informational cues (Zeithaml, 1988), pricehas been found to be positively linked to perceived quality (Dodds, Monroe, &Grewal, 1991). The apparent contradictory role of price as both an indicator ofproduct quality and monetary measure of sacrifice is well recognised (Scitovsky,1945). It results in a cognitive trade-off between perceptions of quality and sacrifice,with higher quality associated with an increased willingness to buy but offset bysacrifice which is associated with a lower incentive to purchase (Dodds et al., 1991).This trade-off between quality and price is faced by many shoppers who actively‘trade down’ to cheaper and lower perceived quality alternatives when circumstancesrequire. Reference to trading down may be found in the economics literature in thetaxonomic description of certain goods as inferior. These products are defined bytheir response to changes in income. When incomes falls, the demand for theseproducts increases, while when income increases, the demand for these productsfalls. The link between trading down and store brands is well established. Manystudies have found that shoppers perceive own brands to be inferior to nationalbrands (Bellizzi, Krueckeberg, Hamilton, & Martin, 1981); that the share in privatelabel is inversely related to disposable income (Hoch & Banerji, 1993) and theeconomic cycle (Lamey, Deleersnyder, Steenkamp, & Dekimpe, 2012); and that ownbrand consumers are willing to purchase lower quality when financial needs dictate(Geyskens, Gielens, & Gijsbrechts, 2010; Sivakumar & Raj, 1997).

Conceptual framework and model development

This section establishes a set of hypotheses which forms the overall model to betested. Broadly, the model adopts the view that in-store price search and store dealproneness are determined by motivations to derive both hedonic and utilitarianvalue. For the price maven, in addition to acquiring the everyday necessaries oflife, utilitarian motivators also include the need to obtain identity-creating priceinformation efficiently. While there is a wide body of literature that distinguishesbetween hedonic and utilitarian motivations, we will argue that the opportunitycost of time is influenced by both sets of motivations, creating direct and indirectrelationships between motivations and our two forms of price search.


Hypotheses

Some of the utilitarian benefits of engaging in store deal prone behaviour have beenestimated recently by Griffith et al. (2009). They estimated the financial benefits fromsmarter shopping and found that some UK households save up to 21% on annualgrocery expenditures by buying on promotion and stockpiling, with an average savingof 6.5% across all households.

Shoppers who seek deals are partially motivated by the economic benefits andthe need and desire to obtain price reductions and to maximise the purchasingpower of money (Ailawadi et al., 2001; Garretson & Burton, 2003). In times ofeconomic hardship and financial pressure, shoppers experience reduced consumptionopportunities; their incomes will only stretch so far. However, consumptionopportunities may be expanded because prices vary across brands, stores, and time.Prices also vary considerably among similar products which can act as suitablesubstitutes when needs be. Consequently, shoppers may derive significant savingsaccording to what they buy, where and when they buy it, and in the quantities theypurchase.

Real income is the measure of purchasing power. It is the amount of goods andservices that can be purchased with one’s nominal income. Shoppers with a preferredchoice set of products can, in the face of a fall in nominal income, engage in pricesearch both within and across stores and identify temporary lower promotional pricesfor their existing set of preferred products. In this manner, the shopper’s nominalincome can stretch further to purchase more of its preferred goods and services,thereby restoring some of the lost real income. However, grocery expenditure tendsto come from that part of net nominal income which remains after mortgages andrecurring bills are paid. While many researchers have explored the relationshipbetween income and search (Urbany et al., 1996), we propose using a measure offinancial pressure as a better indicator of the financial status of the shopper (Berneet al., 1999; Urbany et al., 1996). Consequently, the household has an incentive toengage in search activities as a direct result of financial pressures, and we propose:

H1: There is a direct and positive relationship between financial pressure and storedeal proneness.

H1a: There is a direct and positive relationship between financial pressure and in-store price search.

We have discussed the contradictory role of price as both an indicator of productquality and a monetary measure of sacrifice (Scitovsky, 1945). According to Doddset al. (1991), this contradictory role results in a cognitive trade-off betweenperceptions of quality and sacrifice, with higher quality associated with an increasedwillingness to buy but offset by monetary sacrifice which is associated with a lowerincentive to purchase. We propose that the effect of financial hardship is to tip thebalance or trade-off towards sacrifice and that, for a given level of perceived quality,the monetary sacrifice assumes greater importance. To rebalance, the shopper tradesdown, achieving monetary savings at the expense of lower perceived quality.

Given the evidence that own brands and the economic cycle present on tradingdown in-store, it is plausible to adopt the view that shoppers can also trade downacross stores. While relationship between the demand for inferior goods and storechoice is not well established, it is apparent that the market share of discount stores,


and particularly limited line discounters, increases when household incomes fall(Collins, Kavanagh, & George, 2012). Shoppers who are more willing to trade downhave a wider product promotional choice set than those who remain loyal to theirpreferred products. In this regard, we differ from the views of Ailawadi et al. (2001)who suggest that quality consciousness should not influence in-store or out-of-storepromotion proneness. We suggest these shoppers have a greater incentive to engage insearch and store deal prone behaviours across a wider set of stores, and we postulate:

H2: There is a direct positive relationship between financial pressure and thewillingness to trade down.

H3: There is a positive relationship between willingness to trade down and storedeal proneness.

H3a: There is a positive relationship between willingness to trade down and in-storeprice search.

Utilitarian motivations would be expected to encourage the shopper to consider allthe resources available to enhance the efficiency of the shopping process and tomaximise the purchasing power of its nominal income. One such resource is storagespace (Ailawadi et al., 2001; Blattberg, Buesing, Peacock, & Sen, 1978) which, if usedefficiently, may yield additional savings through stockpiling for future consumption(Blattberg et al., 1995). The savings accrued from bulk buying, and consolidatingexpenditure also helps cover any additional transportation costs associated withvisiting a number of stores for their deals.

Following on, it may be useful to view the spatial configuration of the local retailinfrastructure as another resource. A well-developed retail infrastructure with plentyof competing fasciae, formats, promotional offers, and cycles provides the shopperwith further savings opportunities, thereby encouraging search. This is supportedby Brown (1988) who argues that more pre-purchase information search occurswhen retail outlets are clustered together. Alternatively, a poorly developed retailinfrastructure with few competing stores may be viewed as a constraint on store dealproneness.

This suggests:

H4: The availability of storage space will be positively related to store dealproneness.

H4a: The availability of storage space will be positively related to in-store pricesearch.

H5: The number of competing stores in the geographical area will be positivelyrelated to store deal proneness.

For the purposes at hand, we consider time as particularly valuable to the shopper andthe chief resource or cost being expended in the search process (Becker, 1965; Stigler,1961; Talukdar, Gauri, & Grewal, 2010). Stigler’s (1961) cost–benefit perspectivesuggests that an individual will engage in search as long as the anticipated marginalbenefits exceed the marginal costs or, to express it slightly differently, as long asit’s worth it. The cost of search can be measured by the opportunities foregone;the benefits that could have been enjoyed had time been used differently (e.g. hoursworked and the goods that could have been purchased with the nominal income


foregone or simply time spent engaged in leisure). Following the principle of marginalutility, as discretionary time becomes scarcer, the value of the marginal unit ofdiscretionary time increases. Time-poor individuals will have a higher opportunitycost of search because of competing alternative uses of scarce time. Consequently,these individuals are more likely to engage in less store deal prone and in-store pricesearch behaviours. This negative relationship between the opportunity cost of timeengaged in search and price search in the grocery market is well supported in theliterature (Fox & Hoch, 2005; Putrevu & Ratchford, 1997; Urbany et al., 1996).Thus, we also propose:

H6: There is a negative relationship between the opportunity cost of time engagedin search and store deal proneness;

H6a: There is a negative relationship between the opportunity cost of time engagedin search and in-store price search;

Financial pressure is frequently related to unemployment or underemployment wherethe individual is consuming enforced leisure. For these individuals with excessdiscretionary time, the opportunity cost of time spent searching for deals and betterprices will be lower. Another source of financial pressure, but affecting those inthe workplace, is falling real wages. As already discussed, there is a vast literaturethat equates the opportunity cost of time with the real wage rate (Bryant, 1990;Putrevu & Ratchford, 1997). The relationship between the opportunity cost of timeand financial pressure is negative because as real wages fall, and financial pressureincreases, the opportunity cost of search declines (Carlson & Gieseke, 1983; Gauri,Sudhir, & Talukdar, 2008). In this manner, we establish a negative relationshipbetween financial pressure and the opportunity cost of time spent looking for dealsand lower prices:

H7: There is a negative relationship between financial pressure and the opportunitycost of time engaged in search.

Earlier work, by focusing on the individual’s input to the shopping process, revealedthat the currency of search matters in determining the amount of search actuallyundertaken (Monga & Saini, 2009). On the benefit side of the equation, mavens,because of their expertise, will be particularly attuned to assessing promotional pricesand the value of savings on offer across different retailers. Consequently, we proposethat there will be a direct link between price mavenism and store deal proneness, asthe individual seeks to obtain savings to benefit his/her own household. Furthermore,acquiring price-related market information, the basis for the price maven’s perceivedexpertise, is an outcome of the search and purchase process. Ratchford (2001) arguesthat ‘consumers can be expected to engage in more search than otherwise if theircurrent activity creates either information capital or skill capital’ (p. 407) and thatthe value of the information obtained can exceed the value of product itself. Thisis also supported by Berne, Mugica, Pedraja, and Rivera (2001). Consequently, wesuggest that our two kinds of price search yield additional utilitarian value in theform of price information obtained for the purposes of identity creation.

H8: Price mavenism is positively related to store deal proneness.

H8: Price mavenism is positively related to in-store price search.


In addition to this direct relationship, we suggest that an indirect relationship alsoexists through the opportunity cost of search time. Marmorstein et al. (1992), intheir investigation of the value of time spent engaged in price comparison shopping,argued that the hedonic benefits associated with shopping needed to be consideredwhen estimating the opportunity cost of time. Shopping is more than just the physicalacquisition of goods and, by ignoring these hedonic aspects, the opportunity costof shopping time is overestimated when the wage is used as a proxy. For pricemavens, the hedonic benefits extend beyond the individualised gains of lower pricesand extend to the socialised self. As the shopper’s maven propensity increases, theopportunity cost of time allocated to search-related activities fall. This is consistentwith Marmorstein et al. (1992), where the additional utility resulting from theshopper’s maven tendencies need to be deducted from the wage to derive a correctestimate of the opportunity cost of time. Consequently, for a given wage rate, theopportunity cost of search will fall as price mavenism increases. Thus, we argue:

H9: There is a negative relationship between price mavenism and the opportunitycost of time spent engaged in price search.

The model

Based on the arguments established above, Figure 1 sets out the model to be tested.First, it proposes that store deal proneness (SDP) will be positively related to financialpressure (FP), available storage space (SS), the willingness to trade down for lowerprices (WTD), and price mavenism (PMAV). It will be negatively related to theopportunity cost of search time (OCTS). It also adopts the view that FP reduces theOCTS and increases the shopper’s WTD. The model stipulates that PMAV reducesOCTS. Finally, our model of SDP is situated within a given retail infrastructure whereit is viewed to be positively related to the number of competing stores. In addition,it proposes that in-store price search (ISPS) will be positively related to FP, WTD,OCTS, and PMAV.

Methodology

Data collection

Following much of the existing research in the area, direct self-reported measureswere used for all the dependent and independent variables. The data were collectedin the Philadelphia MSA, the fifth largest MSA in the country, representingPennsylvania, New Jersey, Delaware, and Maryland states using an externalmarketing company. This company was requested to build a random sample of500 respondents from their shopper database subject to the condition that 30% ofrespondents were male, that the respondent was the individual responsible for thehousehold’s primary shopping, and that the respondent had completed a groceryshop within the previous four weeks. The sample size was determined by cost. Eachqualifying respondent completed a 10-minute online survey. To encourage responses,a $5 reward was given for each completed questionnaire. Invitations were sent outin batches, and the number of qualifying responses exceeded the 500 sample-size


Figure 1 A model of store deal proneness and in-store price search.

StorageSpace

WillingnessTo TradeDown

In-StorePrice Search

ISPS

Number ofCompetingStores

Store DealProneness

SDP

SS

WTD

H2+

H7–

H9–

H6a–

H6–

H8+

H8a+

H1a+

H1+

H3a+

H3+

H4+

H4a+

H5+

MavenismPMAV

OpportunityCost of TimeEngaged in Search

OCTS

FinancialPressure

FP

Table 1 Sample characteristics (N = 535).Income band % of sample Age group % of sample<$25,000 4.4 18−24 6.3$25,000−$34,999 5.6 25−34 21.5$35,000−$49,999 11.7 35−44 20.7$50,000−$74,999 20.9 45−54 18.9$75,000−$100,000 15.9 55−64 23.3>$100,000 25.7 65−74 7.6Decline to answer 15.7 ≥75 1.7Total 100.0 100.0

requirement. The additional observations are included in the analysis. Some sampledetails are provided in Tables 1 and 2.

Measurement model

The indicators used for each latent construct in the model are presented in Table 3.Items were chosen directly or modified from earlier works (Ailawadi et al., 2001;


Table 2 Primary grocery store (N = 535).Retailer % of sample Retailer % of sampleShoprite 29.4 Target 2.0Giant 17.8 BJ s 1.3Acme 14.4 Costco 1.3Wegmans 5.0 Aldi 1.1Genuardis 4.6 Sam s .9Walmart 3.5 The Fresh Grocer .7Pathmark 3.1 Save-a-Lot .6SuperFresh 3.1 IGA .2Trader Joe’s 3.0 Others 5.4Whole Foods 2.4 Total 100.0

Lichtenstein et al., 1993; Urbany et al., 1996). A five-point Likert scale anchoredby 1 = ‘strongly disagree’ to 5 = ‘strongly agree’ was used. One construct, theopportunity cost of time spent engaged in price search, employs a subset of items usedby Lichtenstein et al. (1993) to measure price consciousness. We suggest that giventhe definition of the opportunity cost adopted earlier, the current use is appropriate,as face validity supports the view that the items capture the essence of the decisionto engage in search considering the alternative opportunities that would be forgoneif search were to be carried out. A maximum likelihood confirmatory factor analysiswas carried out using AMOS v18 to test the measurement model. All exogenousvariables were permitted to correlate. The overall model fit measures, chi-square(χ2) = 234.84, degrees of freedom (df) = 131, p = .000, goodness of fit index(GFI) = .96, adjusted goodness of fit index (AGFI) = .94, comparative fit index(CFI) = .97, the Tucker–Lewis index (TLI) = .97, and the root mean square errorof approximation (RMSEA) = .039 are provided. The chi-square indicates that thereis a significant difference between the sample covariance matrix and the restrictedcovariance matrix. However, this is common where sample sizes are large, andhence we rely on the remaining measures which support an acceptable model fit(Byrne, 2001). All standardised factor loadings demonstrate statistical significance(p < .01) on their corresponding construct.

Convergent validity was assessed by examining the size and significance of thefactor loadings and their associated critical values (Table 3), as well as inspecting theaverage variances extracted (AVE) for each construct (Table 4), all of which meetthe .50 threshold (Hair, Anderson, Thatham, & Black, 1995). All items significantlyand positively loaded on their corresponding construct, demonstrating adequateconvergent validity. Reliability is demonstrated through the use of Cronbach’s alphascores (Table 3) with all constructs meeting the desired .70 threshold (Nunally, 1981).Discriminant validity is supported by the fact that the average variance extractedexceeds the squared correlation coefficient for each pair of latent factors (Fornell& Larcker, 1981). Consequently, the measures of the constructs used in our modelachieve satisfactory reliability and convergent and discriminant validity.

To identify the number of proximate stores, respondents were asked to identifythe different store banners that they could visit within a 20-minute drive time. Whilethe Competition Commission (2008) in the United Kingdom specified a 10-minute


Table 3 Confirmatory factor results.

Constructs Standardised factor loadingOpportunity cost of time engaged in price search (α = .81) (Lichtenstein et al., 1993)Opc1 The time it takes searching for lower prices is not worth it .730∗∗∗

Opc2 The money saved on searching for cheaper food is not worth it .815∗∗∗

Opc3 Looking for lower prices takes too much time .775a

Price mavenism (α = .75) (Ailawadi et al., 2001)Pmav1 I enjoy giving people shopping tips .714∗∗∗

Pmav2 I’ll advise others on where to get the best value .931a

Pmav3 I find visiting food retailers interesting .486∗∗∗

Willingness to trade-down (α = .71) (Ailawadi et al., 2001)Pqu1 I’d prefer better prices rather than quality .697a

Pqu2 I’d sacrifice some quality for lower prices .790∗∗∗

Household financial pressure (α = .88) (Urbany et al., 1996)HF1 Money is tight so I have to reduce my bills .819∗∗∗

HF2 Household finances are such that I am trying to save on my bills .860∗∗∗

HF3 My household budget is usually tight .854a

Store deal proneness (α = .75) (Putrevu & Ratchford, 1997)Sdp1 I check newspapers and flyers for the best deals .658∗∗∗

Sdp2 I shop in a number of food retailers for their deals .666∗∗∗

Sdp3 I shop around to pick up the best deals .785a

In-store price search (α = .78) (Putrevu & Ratchford, 1997)Pcom1 I compare prices on the shelf before deciding which product to buy .692∗∗∗

Pcom2 Before buying a product, I usually check its price .748a

Pcom3 I compare prices between brands .795∗∗∗

Storage space (α = .84) (Ailawadi et al., 2001)Str1 I have plenty of storage space at home .821∗∗∗

Str2 I have room at home to stock extra grocery products .878a

Note. α = Cronbach’s alpha; aCritical value not estimated as loading set to 1. ∗∗∗p= .001. χ2 = 234.846,df = 131, p = .000, GFI = .96, AGFI = .94, CFI = .97, TLI = .97, RMSEA = .039.

drive time in determining the spatial extent of a local market, anecdotal evidencefrom the United States suggested that a longer drive time would be appropriate. Theindependent variable was the sum of banners within a 20-minute drive time.

Results

AMOS v18 was used to estimate the structural model for both SDP and ISPS.The results are provided in Figure 2 which also shows the hypothesised signs. Allexogenous variables were permitted to correlate. The results of the analysis arepresented and show each hypothesis, its expected sign, the estimated coefficientvalue, and the significance level. The chi-square = 287.5, df = 151, p < .01,


Table 4 Discriminant validity.

Variance extracted,Cronbach’s alpha(diagonal) andsquaredcorrelations R2 Average

VarianceConstruct FP PM OCTS WTD SS SDP ISPS ExtractedFinancial pressure .879 .05 .07 .10 .01 .10 .17 .71Price mavenism .75 .10 .04 .03 .35 .14 .54Opportunity cost ofsearch

.81 .01 .00 .43 .24 .59

Willingness to tradedown

.71 .00 .16 .09 .55

Storage space .84 .21 .00 .73Store dealproneness

.750 .24 .50

In-store pricesearch

.784 .56

GFI = .95, AGFI = .93, CFI = .97, TLI = .96, and RMSEA = .041, indicating agood level of fit. The squared multiple correlations indicate that the independentvariables explained 68% of the variation in SDP and 39% in the case of ISPS. Thiscompares well with other studies in the area (Ailawadi et al., 2001).

Figure 2 Results of the structural model.

StorageSpace

WillingnessTo TradeDown

SS

WTD

H2 +, (β = .323***)

H3+ , (β = .278***)

H1a +, (β = .220***)

H6a –, (β = .366***)

H8 +, (

β = .355***

)

H8a +, (β = .173***)

H1+, (β = .022, p.638)

H6 –, (β = –.5

06***)

H4 +, (β = .116, p.008)

H5 +, (β = .095, p.012)

H3a+, (β = .164, p.002)

H4a +, (β = .037, p.427)H7 –, (β = –.206***)

H9 –, (β = –.274***)

FinancialPressure

FP

OpportunityCost of TimeEngaged in Search OCTS

PriceMavenismPMAV

Chi-square (χ2) = 287.9, df. = 151, p<.01,Gfi = .95 AGFi = .93 CFI = .97, TLI = .97 RMSEA = .041*** significant at the .001 level

Number ofCompetingStores

Store DealProneness

SDP

In-StorePrice Search

ISPS


Table 5 Total, direct, and indirect (standardised) effects.

Store deal proneness In-store price searchTotaleffect

Directeffect

Indirecteffect

Totaleffect

Directeffect

Indirecteffect

FP→ SDP .216 .022 .194 FP→ ISPS .349 .220 .129PMAV→ SDP .494 .355 .139 PMAV→ ISPS .273 .173 .100OCTS→ SDP −.506 −.506 N/A OCTS→ ISPS −.366 −.366 N/AWTD→ SDP .278 .278 N/A WTD→ISPS .164 .164 N/APMAV→ OCTS −.274 −.274 N/A PMAV→ OCTS −.274 −.274 N/AFP→ OCTS −.206 −.206 N/A FP→OCTS −.206 −.206 N/AFP→WTD .323 .323 N/A FP→WTD .323 .323 N/AStorage→ SDP .116 .116 N/ANo. Stores→SDP

.095 .095 N/A

An examination of the coefficient values and significance levels provides clearsupport for the overall model with all coefficient signs showing the correct direction.All but two of the hypotheses are accepted. The first is H1, which concerns therelationship between FP and SDP. Surprisingly, no evidence is found to supportthis relationship. It is noteworthy, however, that H1a, the corresponding hypothesisrelating to ISPS, is supported. Second, there is no support for H4a, the relationshipbetween SS and ISPS.

Regarding SDP, the coefficient values for storage space (β = .116) and the numberof competing stores (β = .095), while significant, appear small. Each causal pathwas removed from the model, in turn resulting in poorer models with significantchanges in model fit at the .01 level (�χ2 = 7.76, df = 1 in the case of storage, and�χ2 = 6.0, df = 1 in the case of the number of competing stores). Consequently,both these variables and causal paths are retained.

An examination of the modification indices indicated that the model’s fit wouldbe improved if a casual path between price mavenism and the willingness to tradedown was incorporated (χ2 = 281.6, df = 151, �χ2 = 6.9, df = 1). However, givenour specific definition of price mavenism, there is little theoretical rationale for thisinclusion, so it is not integrated into the model.

To assist further analysis, Table 5 presents the total, direct, and indirect effectsbetween our independent and dependent variables.

Considering the results for SDP, we can see that the perceived OCTS has the largesttotal and direct effect (β = −.506) on our dependent variable. As anticipated, andconsistent with existing theory, its coefficient sign shows that falling opportunity costof time spent searching for lower prices increases shoppers’ propensity to search andvisit multiple stores for deals.

We can also see that shoppers’ PMAV tendencies have a very substantial total effecton SDP (β = .494) and that a considerable portion of this effect is mediated indirectlythrough OCTS. Returning to Figure 2, we can observe that both our hypothesiseddeterminants of OCTS, PMAV (β = −.274) and FP (β = −.204), are found to beboth negative and significant. It is noteworthy that price mavenism has the largerimpact on OCTS. We shall return to this later.


Given earlier research (Ailawadi et al., 2001), it is somewhat surprising thatthe direct effect of FP on SDP is not found to be significant. However, ourfindings show that it has an important positive indirect effect (β = .194) throughboth OCTS and WTD. FP’s direct effects on OCTS (β = –.206) and WTD(β = .320) are both significant at the .001 level. The evidence that FP increasesshoppers’ WTD (β = .323) and that WTD is strongly implicated as a determinantof SDP (β = .278) has important implications for both branded manufacturers andretailers alike. It points to the causal path between FP and SDP that can lead to bothbusinesses suffering; trading down leads to a reduction in the manufacturer’s marketshare while store switching affects the retailer. This is an important extension to thebody of work investigating price and deal search as the phenomenon of trading downhas not been implicated or considered directly.

Moving our attention to ISPS, we see that all the proposed hypotheses areaccepted. FP has the second largest total effect on ISPS (β = .349) among all theindependent variables considered. Compared with SDP, we find that the direct andpositive relationship between FP and ISPS is significant and has the expected positivesign (β = .220). This is consistent with the work of Ailawadi et al. (2001) who founda positive relationship between financial constraints and in-store promotion usage.However, expanding beyond this research, we see that FP also has an indirect effecton ISPS (β = .129) via OCTS and WTD. Similar to SDP, we find that OCTS has thelargest total and direct effect on ISPS (β = −.366).

Table 5 enables us to compare the strength of the relationships between ourindependent variables and our two aspects of price search, SDP and ISPS. Taking FPfirst, we can see that its total effect is considerably stronger on ISPS (β = .349) thanon SDP (β = .216). Table 5 also shows a very strong direct effect between FP and ISPS(β = .228), while for SDP, no such effect is supported. This is somewhat surprising.However, we saw that the OCTS has a much larger effect on SDP than ISPS. Thus,it may be that financial pressure needs to reach a certain level before substantialsearch costs involved in multiple store visits are willingly incurred. This suggests thatshoppers’ first response to financial pressure is to search and compare prices in theirusual store rather than actively search across stores. Alternatively, other factors suchas access to or the cost of transport, which might be reasonably expected to be relatedto financial pressure but excluded from the model, might be involved and explain thenon-significant finding.

Variations in prices within a store may provide the shopper with some scopefor substituting similar quality brands and products when promotional cycles onbranded products are sufficiently frequent to avoid store switching. However, therecomes a point where further savings can be realised only through trading down. Theevidence indicates that the willingness to trade down to lower-quality goods for lowerprices has a substantially bigger effect on SDP (β = .278) than on ISPS (β = .164).This result is somewhat surprising but may be due to the extent of the quality andprice differentials that exist across stores. Observations that support this include therapid growth in the sales of limited line discounters, which tend to emphasise ownbrand products, where same-brand substitution across stores is not feasible (Collinset al., 2012). Another explanation may lie in perceived psychosocial risks where theshopper may fear negative status evaluation due to the visibility of their productchoice in their normal store (Semeijn, van Riel, & Ambrosini, 2004).

The most prominent feature to emerge from the results is that the OCTS has thelargest total and direct effects on both SDP (β = −.506) and ISPS (β = −.366).


This is arguably the most important contribution of the paper, as it extends earlierwork by Putrevu and Ratchford (1997), where the opportunity cost of time is viewedas exogenous, and work by Ailwadi et al. (2001), who argue that time pressureis a function of demographics. Given the size of the coefficients, it is clear thatunderstanding the value of time and how shoppers create value, both utilitarian andhedonic, from time is critical to our understanding of price search behaviours. Moreinsight into the time–search relationship may be gained by exploring the determinantsof OCTS itself.

Our analysis finds that PMAV (β = .274) and FP (β = −.206) affect OCTS andthat, of these, PMAV has the larger effect. That PMAV has a direct effect on OCTS isunsurprising and is well supported in the literature (Babin et al., 1994; Marmorsteinet al., 1992; Urbany et al., 1996). However, that it has a larger effect on OCTS thanFP, a measure of financial stress, is provoking, given the large body of work that usesthe wage rate as the measure of the cost of time. To address this, we turn to Okada andHoch (2004) who suggest that there is ambiguity in the value of time and that ‘peoplehave a much easier time wasting time than wasting money’ (p. 314). We suggestthat one must extend beyond a consideration of the financial payoffs of spendingtime to identify properly the additional utilitarian and hedonic values generated thathelp explain this specific finding. We suggest that for shoppers with higher maventendencies, shopping is a form of joint production; goods are acquired, shoppingis enjoyed and the experience consumed, while at the same time information isaccumulated which provides the basis for the creation and maintenance of theirsocialised selves.

We can see that PMAV’s total effect is much greater on SDP (β = .494) than ISPS(β = .283). In particular, its direct effect on SDP (β = .355) is almost twice that onISPS (β = .173). This may be explained by the fact that price mavens extract value,over and above the consumption-related use value associated with lower prices andcheaper goods, through the acquisition of information capital (Ratchford, 2001).The value of this information is subject to scope; being knowledgeable about pricesin many stores is more valuable than being knowledgeable about prices in one store.This supports the unexpected findings of Urbany et al. (1996) and questioned byPutrevu and Ratchford (1997). Following Ratchford (2001), we suggest that ongoingprice search across stores provides information capital critical to maintain reputationand identity capital as a price maven.

Returning to FP, we see that it reduces OCTS. We argued earlier that this might bedue to unemployment, where the shopper is taking enforced leisure and where thevalue of the last hour of leisure is low and is more willingly sacrificed for lower-pricedgoods found through search. Alternatively, the household may experience a fall inreal income (e.g. through pay cuts or increased taxes). This causes the return frommarket work to fall (in terms of goods) relative to household production of whichsearch may be just one element (Bryant, 1990; Ratchford, 2001). Consequently, ineither case, ISPS and SDP increase as OCTS declines in an attempt to regain some ofthe lost real income through lower-priced products.

Finally, we can see that the local retail infrastructure is also implicated in SDP.As the number of competing stores increase, shoppers exploit their access to awider choice set of promotional deals on different promotional cycles to better theirhouseholds’ welfare. Similarly, the findings also support the availability of SS as adeterminant of SDP. This fits with earlier studies (Ailawadi et al., 2001; Blattberget al., 1978) which linked promotional stockpiling with storage space and shows how


the effective use and management of a household resource can encourage a particularshopping behaviour.

Theoretical contributions

Time as a resource has been implicated in many aspects of search behaviour(Ratchford, 2001; Stigler & Becker 1977; Urbany et al., 1996). This study, by linkingtime to identity formation, has found it to be the more important determinant ofprice search behaviours. Price mavens have particularly low opportunity costs oftime engaged in search because of the value being placed on the breadth of priceinformation in terms of across-store scope. This suggests price mavenism is related toreconnaissance, discovery, or breaking new ground for harvesting and disseminatinginformation. It is thereby possible to interpret the role of price maven as tantamountto ‘role of scout’ whereby reconnoitre and research is valued. On the one hand,this theoretical advancement is important, as it largely clashes with the neoclassicalnotion that, given time constraints, a consumer might limit the number of storespatronised or time spent searching for alternatives (Lastovicka & Gardner, 1979).On the other hand, we find some consistency with underlying neoclassical thought,as our results indicate that mavens are willing to engage in more search becauseof the marginal benefits in terms of identity construction. They see value in priceinformation that others do not. Also, the benefits of the marginal unit of informationare higher when that information comes from another store. In this manner, hedonicand utilitarian values converge and blur, a point that needs to borne in mind whenexploring this kind of time-consuming behaviour. Particularly, the pursuit of hedonicvalue consumes time, a resource that is limited and to be utilised efficiently. It isarguable that grocery shopping, as a market-based endeavour, is one of the fewareas of activity that combines both the unavoidable necessitation of daily life andthe capacity to create an aspect of oneself through the appropriate negotiation andallocation of time.

A follow-on contribution is that when observing this convergence of mundanitywith the possibility of role-identity creation, the time commitment is considerable.Expanding on Ratchford’s (2001) argument linking human capital and search, oneview of search is that the agent ‘will direct their consumption and search activities inways that maximise the impact of their accumulated expertise’ (p. 409). Regardingprice mavens, identity expertise is a function of their price knowledge which hasa limited shelf life; prices and promotions change rapidly according to retailerdetermined cycles (Berne et al., 2001). As a form of knowledge capital and the basisfor constructing identity, grocery prices are not an immutable resource and cannotbe stored and built upon over time like, for example, knowledge of product heritage,the most atmospheric places to shop, or awareness of consumer rights and ethicalpractices of the retailer. For the maven, price knowledge must be seen as a flow ratherthan a stock of accumulated knowledge that demands continuous time investmentsto maintain one’s constructed reputation. In this regard, the price maven differs fromthe broader generic market maven concept, where accumulated knowledge can berecycled and reused as an indicator of one’s market competence and savvy. Ourfindings also harbour theoretical implications for the literature on self and identitycreation as we draw attention to the ongoing commitments that need to be made for


maintaining identity. In that regard, it points to the practical importance of identityresources being considered as either stocks or flows.

General discussion and managerial implications

Griffith et al. (2009) found that some households save more than 21% of theirgrocery shopping bill through smarter shopping. Understanding when to buy, whereto buy, and how much to buy can ease the financial pressure on households and enablethem to enjoy a substantially wider consumption bundle than those that display lessexpertise in the shopping process. To underpin their competitiveness, retailers seekto shape shoppers’ price perceptions and obfuscate unflattering price differentialswith competing stores (Lindsey-Mullikin & Petty, 2011; Srivastava & Lurie, 2001;Urbany et al., 1988). However, mavens and particularly price mavens have much ofthe information required for smart shopping and, given their propensity to search,purchase, and publicise, represent a significant threat to many retailers in theirattempt to maintain loyalty and margins.

Price mavens seek self-confirmation through the process of information diffusionthrough word of mouth (Goodey & East, 2008). The mundane, routine, and frequentnature of grocery shopping and the proportion of household expenditure accountedfor by these products provide the price maven with an incentivised and ubiquitousaudience. Given their reputational investments in identity, it is likely that the level ofbelievability associated with the maven’s information may serve as either an effectivecounter or endorser of retailers’ advertising claims (Devlin, Ennew, McKechnie, &Smith, 2013). Furthermore, given simple, inexpensive, and readily available diffusiontechnologies such as texting, the potential for price mavens to play an increasing rolein determining the effectiveness of grocers’ price and promotional strategies mayrequire greater consideration.

The evidence suggests that in response to financial pressure, the primary effectis that shoppers will engage in more search for lower prices in-store which mayultimately have an effect on shoppers’ perception of value. Where the valueproposition offered by the store is weak and financial pressure leads to trading down,the larger effect is to encourage search across stores and deal proneness. This may beto the advantage of discounters who sell a range of brands atypical to the shopper’smore mainstream stores. Similar to Berne et al. (2001), we suggest that to counterthis, the risk of trading down may be averted if the promotional cycle on preferredbrands is sufficiently timely to encourage customers to postpone purchases ratherthan switch stores. It may be that promotions on leading brands reduce both cross-store and brand-switching behaviours by reducing perceived sacrifice and increasingperceived value. On a more positive note for the retailer, while the in-store pricesearch response to the willingness to trade down is lower than across store dealproneness, it may still offer greater opportunity to communicate the benefits of switchand save programmes that are frequently employed to encourage more own brandpurchases. The corollary of this, however, is that in times of increasing financialpressure, retailers perceived as lower quality such as discounters should promotedeals to encourage trial and increase customer traffic.

The weak effect of the retail infrastructure on SDP, while significant, suggests thathaving more competing stores in an area by itself does not really have a serious


effect on store switching for deals. Price comparisons both in and across stores aremuch more related to household and individual factors and changing circumstances.This points to a certain amount of shopper inertia when times are good. Forpolicymakers, this suggests that the benefits of establishing and maintaining a healthylevel of competition in local markets might only be seen when economic conditionsdeteriorate.

Conclusions, limitations, and directions for further research

The chief limitation with this research is that while it permitted a more detailedinvestigation of the interdependencies that exist among many of the factorsimplicated in the determination of our two forms of search, by focusing on justone aspect of mavenism, it may have omitted other relevant factors. Specifically, itmay be that the willingness to trade down might be influenced by expert productand market knowledge which might increase product and promotional choice sets.The modification indices pointed to a relationship between price mavenism andwillingness to trade down, but no theoretical rationale existed for this relationship.Second, the literature on own brands indicates that these products are in someway inferior to manufacturer brands and are normally sold at a discount. In thatregard, it would be interesting to see if this model could be adapted to explain own-brand purchases given the ubiquity of switch-and-save campaigns where retailersencourage substitution of own brands for brand leaders through direct pricecomparisons. Finally, while the model explained a very substantial amount of thevariation in store deal proneness (68%), it fared less well in terms of in-storeprice search (39%). Store-specific factors including atmospherics, layout, and theuse of point of sale are likely to be implicated but were beyond the scope ofthis work. Similarly, the nature of the shopping mission such as major or fill-inshopping trips might also influence in-store price search (Kahn & Schmittlein, 1992)and merits further investigation. In particular, the opportunity cost of time spentengaged in price search may be expected to vary considerably between the differentforms of shopping trip. Our model, using a generalised measure of opportunitycost of time spent engaged in search, was not able to separate out this potentialeffect.

This research developed a model of both in-store price search and promotionalprice search across stores based on a conceptual framework focused on hedonicand utilitarian motivations. The model shows that in-store price search and storedeal proneness share many of the same drivers, and amongst these, the value oftime is the most important. The main contribution has been the uncovering of theinterdependencies that exist between the variables that explain our focal behaviours.Central to the model is that the opportunity cost of time is endogenous and isexplained in terms of economic pressures and price mavenism. Price mavenism isfound to have a larger effect on the opportunity cost of time when comparedwith financial stresses. It also influences store deal proneness directly due to therequirement to collect identity-building information to maintain maven status andindirectly through its effect on the opportunity cost of time. The model also explicitlyincorporates shoppers’ willingness to trade down which has a substantial effect onpromotional search across stores.


Acknowledgements

The authors would like to acknowledge the contributions made by the editor and anonymousreviewers during the preparation of this paper.

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About the authors

Alan Collins is a senior lecturer in the Department of Food Business & Development atUniversity College Cork, Ireland, where he lectures in retail marketing, food economics,and supply-chain management. Having spent a number of years in industry in the marketingservices and buying functions with a major British retailer, he returned to academia at UCCand completed his doctoral studies at the University of Stirling. He has published on retailer–manufacturer relationships in the food industry, retail branding, and below-cost legislation ingrocery retailing. More recently, he has turned his attention to consumer behaviour, focusingon grocery shopping behaviour.

Corresponding author: Alan Collins, Senior Lecturer, Department of Food Business andDevelopment, University College Cork, Cork, Ireland.

T 353-21-4902066E [email protected]

Ella Kavanagh is a lecturer in the Department of Economics at University CollegeCork, Ireland. She completed her PhD at the University of Strathclyde. She lectures inmacroeconomics and monetary economics at undergraduate and postgraduate level. She hasbeen the Chair of the Graduate Studies Committee in the Department of Economics since1994, and is currently the Academic Director of Economics within the BA degree. Her currentresearch interests are in the areas of monetary economics, financial instability, pricing, andprice-search behaviours.

T 353-21-4902571E [email protected]

James Cronin (BA, H.Dip, MBS Food Marketing) is a lecturer in the Department of Marketingat the University of Lancaster, UK. He completed his doctoral studies at University CollegeCork, investigating the role of food within neo-tribal communities of consumption. Hisresearch interests are in the areas of transformative consumer research, consumer culture

mailto:[email protected]



doi:10.1108/07363760410525678


http://dx.doi.org/10.1016/S0148-2963(01)00201-6

http://dx.doi.org/10.1016/S0148-2963(01)00201-6


doi:10.1108/02634501111102760

doi:10.1108/02634501111102760




theory, anthropology of food, consumer resistance, gender, ethnography, and collectivebehaviour.

T + 44 1524 510663E [email protected]

Richard George is a well-recognised and highly respected expert in the areas of food marketing,brand strategy, business ethics, and customer service. Recently, he was one of 19 professorsnationwide named as their favourite undergraduate business professor, and he was profiledby Business Week in a feature titled ‘Class Acts’. He has authored or co-authored 10 books ontopics such as strategy, customer service, focus groups, and trends. His latest books are WinningCustomer Rules and Winning Marketing Strategy: The Rules.

T 01 610 660 1608E [email protected]



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