kristof de wutf, gaby o(dekerken-schrocler, & dawn ...€¦ · kristof de wutf, gaby...

Kristof De Wutf, Gaby O(dekerken-Schrocler, & Dawn lacobucci

Investments in ConsumerRelationships: A Cross-Country and

Cross-Industry ExplorationThis research, investigating retailer-consumer relationships, has three distinct intended contributions: (1) It showsthat different relationship marketing tactics have a differential impact on consumer perceptions of a retailer's rela-tionship investment; (2) it demonstrates that perceived relationship investment affects relationship quality, ulti-mately leading to behavioral loyalty; and (3) it reveals that the effect of perceived relationship investment on rela-tionship quality Is contingent on a consumer's product category involvement and proneness to engage in retailrelationships. The authors empirically cross-validate the underlying conceptual model by studying six consumersamples in a three-country, transatlantic, comparative survey that investigates two industries.

In the current retail environment, relationship marketingtactics play a predominant role because of the increasedimportance consumers attach to relational properties of

their interactions with retailers (Crosby, Evans, and Cowles1990; Dorsch, Swanson. and Kelley 1998). In comparisonwith manufacturers, retailers have an advantage in buildingenduring relationships with consumers because they are in abetter position to detect consumer purchase patterns andapply this knowledge in a cost efficient way (Sweeney,Soutar, and Johnson 1999). Examples of relationship mar-keting practices in retailing are widespread. Ritz-Carlton iswell known for its personalized welcome and farewell ofguests, using the guest's natne when possible. Loyalty pro-grams initiated by airlines consist of not only rewarding themost valuable customers in the form of mileage prizes butalso showing recognition and providing special privileges.

Although academics recognize the importance ol" rela-tionship marketing practices (Berry 1995; Goft et al. 1997),etnpirieal evidence on the nature and extent of the impact ofrelationship marketing tactics on relationship quality isscarce (Gwinner, Gretnler, and Bitner 1998). Specifically,although relationship marketing has a strong theoreticalbase in industrial and channel marketing (e.g., Doney andCannon 1997). systematie research on relationship market-ing in a consumer environment is lacking (Bcalty et al.1996). Yet several authors agree with Dwyer. Schurr, and Oh(1987), who note that relational bonds create benefits inbusiness as well as in consumer environments (Christy.Oliver, and Penn 1996; Sheth and Parvatiyar 1995). In par-ticular, collecting information from the consumer's side ofthe retailer-consumer dyad is considered an Importantfuture research avenue (Gwinner, Gremler, and Bitner 1998;Sheth and Parvatiyar 1995).

Kristof De Wulf is Assistant Professor, VIerick Leuven Gent ManagementSchool and Faculty of Economics and Business Administration, GhentUniversity. Gaby OcJekerken-Schroder is Assistant Professor. Faculty ofEconomics and Business Administration, Maastricht University, Dawnlacobucci is Professor, University of Arizona.

With that in mind, our ohjectives are threefold. First, wewant to determine whether different relationship marketingtactics have a differential impact on consumer perceptionsof relationship investment hy the retailer' We consider thisimportant because retailers are often surrounded by uncer-tainty and incorrect beliefs ahout what matters to customers,which results in relationship marketing programs that areineffectively implemented. Given the observation that retail-ers largely make use of traditional, defensive strategies, it isespecially relevant to collect infortiiation on consumer per-ceptions of alternative, relationship-focused strategies(Beatty et al. 1996; Bolton 1998; Dorsch, Swanson, andKelley 1998; Sirohi. McLaughlin, and Wittink 1998). Yetfew efforts have been made to delineate different relation-ship marketing tactics (Christy, Oliver, and Pcnn 1996). Fur-thermore, hardly any systematic empirical investigation hasbeen published that examines the reactions of consumers torelational strategies (Gwinner, Gremler, and Bitner 1998).

Second, we want to provide empirical evidence for theimpact of perceived relationship investment on relationshipquality, and ultimately on behavioral loyalty. Based on thereciprocity principle, tbis effeet has been examined exten-sively in business markets (e.g., Anderson and Weitz 1992;Ganesan 1994; Huppertz, Arenson, and Evans 1978), but toour knttwiedge, it has not been included yet as a topic ofempirical investigation in consumer research.

Third, this research is one of the first empirical studiesdesigned to analyze whether the effect of perceived rela-

'In a first draft of the manuscript, we had originally called theconstruct "perceived relationship investment" by the label "cus-tomer retention orientation." This label, "customer retention orien-tation." originated from qualitative researcb in tbe form of con-sumer focus groups and was defined as a customer's overallperception of the extent to whieh a seller actively makes efforts thatare intended to contribute to tbe customer value of its regular cus-tomers. In response to one of the reviewers' concerns, we renamedthe construct "perceived relationship investment" to convey moreclearly tbe inbercnt meaning of our original construct and drawmore directly from the terms that are strongly established in exist-ing hteraturc.

Journal of MarketingVol. 65 (October 2001), 33-50 Investments in Consumer Relationships / 33

tionship investment on relationship quality is contingent onconsumer characteristics. Several authors stress that rela-tionship marketing practices are not considered effective inevery situation or context (Day 2(XK): Kalwani and Narayan-das 1995). Yet few empirical efforts have been made toassess the moderating role of consumer characteristics onrelationship nnarketing effectiveness (Beatty et al. 1996;Bendapudi and Berry 1997).

In addressing these issues, we hope to contribute to theaforementioned existing gaps in the relationship marketingresearch. Attempts to validate relationship marketing studiesacross settings are still exceptional (Geyskens et al. 1996),so we conduct a fairly comprehensive and rigorous test ofour research hypotheses by empirically eross-validating ourconceptual model in a multi-country and multi-industry con-text. Steenkamp and Baumgartner (1998) stress the need tovalidate models developed in one country, mostly the UnitedStates, in other countries as well.

Theoretical Background andHypotheses

Although an ail encompassing theory of relationship mar-keting is still lacking (Bagozzi 1995), the principle of reci-procity is considered a useful framework for investigatingexchange relationships (Huppertz, Arenson, and Evans1978). Reciprocity is identified as a key feature explainingthe duration and stability of exchange relationships (Larson1992). Moreover, it is often considered one of the mostrobust effects found in psychological literature (Moon2()(K)). Gouldner (I960, p. 168) states that the generalizednorm of reciprocity "evokes obligation toward others on thebasis of their past behavior." The principle of reciprocitystates that people should return good for good, in proportionto what they receive (Bagozzi 1995). According to the reci-procal action theory, actions taken by one party in anexchange relationship will be reciprocated in kind by theother party, because each parly anticipates the feelings ofguilt it would have if it violated the norm of reciprocity (Liand Dant 1997).

Reciprocity has regularly been used as a framework ofthought or a key variable of interest in research on channelrelationships. For example, reciprocity is apparent from thewillingness of a firm to give preference to a supplier that isalso a customer of the Urm's products (Bergen. Dutta, andWalker 1992). Compaq refused to sell directly becausedoing so would constitute competing with its own dealers.Compaq's dealers considered this refusal a sign of Com-paq's commitment to them, and the dealers reciprocated byproviding the brand greater support and shelf space (Day1990). In general, reciprocation of behavior will foster apositive atmosphere, remove barriers of risk, and enablechannel relationships to move forward (Smith and Barclay1997).

Bagozzi (1995) indicates that the phenomenon of reci-procity is also present in consunier-tlrm relationships, andhe stresses that further research on relationship marketingshould investigate the psychological manifestations of reci-procity and the way it functions in everyday consumerexchanges. Also, Huppertz, Arenson, and Evans (I97S) indi-

cate that the principle of reciprocity could be used for under-standing consumer behavior in general. Nevertheless, Moon(20(X)) recently has questioned whether the norm of reci-procity is compatible with the realities of consumerresearch, since engaging in a reciprocal interaction betweena consumer and a company would require a one-to-oneinteraction with every consumer. Given the recognizedimportance of the reciprocity principle in consumer rela-tionships and given our focus on relationship marketing tac-tics that are targeted at individual consumers, we regard theconcept of reciprocity as an appropriate framewt)rk ofthought for building our conceptual model as depicted inFigure I.

The idea behind our mode! is consistent with the work ofBlau (1964), who recognizes that an investment of time,effort, and other irrecoverable resources in a relationshipcreates psychological ties that motivate parties to maintainthe relationship and sets an expectation of reciprocation. Weapply this principle in a consumer context, representingirrecoverable resources by the construct of perceived rela-tionship investment. The resulting constructs of relationsbipquality and behavioral loyalty, embtxiying consumers' reci-procation of a retailer's investments, reflect the extent towhich consumers want to maintain their relationship. This issimilar to Bagozzi's (1995) argument that consumersdemonstrate loyalty to certain sellers in reciprocation ofthese sellers" investments in the relationship. In addition,Kang and Ridgway (1996) argue that consumers feel oblig-ated to pay back the marketer's "friendliness." Moreover, todetect the extent to which relationship marketing tacticscontribute lo perceptions of relationship investment, weassess the relationship between four relationship marketingtactics (direct mail, preferential treatment, interpersonalcommunication, and tangible rewards) and perceived rela-tionship investment. Finally, we incorporate consumer rela-tionship proneness and product category involvement as

FIGURE 1Hypothesized Model

34 / Journal of Marketing, October 2001

moderators between perceived relationship investment andrelationship quality. In the seetions that follow, we dellneeach of the constructs and describe their expected effects.

Perceived Relationship InvestmentWhen a supplier makes a relationship investment of any kindon behalf of a customer, this customer ought to be favorablyimpressed (Hart and Johnson 1999). Investing time, effort,and other irrecoverable resources in a relationship createspsychological bonds that encourage customers to stay in thatrelationship and sets an expectation of reciprocation (Smithand Barclay 1997). Although the predominant approachregarding the construct of specific investment in a business-to-business or channel context has been to examine unrecov-erable investments in a specific A to-B relationship (e.g.,Anderson and Weitz 1992; Smith and Barclay 1997), weexamine investments that are unrecoverable only in the con-text of "one A to many B's," thai is. a retailer to its set of reg-ular customers rather than a retailer to one specific regularcustomer. The underlying rationale for this choice is that rela-tionship marketing tactics directed at consumers are mostoften pail of an overall relationship marketing strategy that isapplied similarly to all regular customers rather than devel-oped on a case-by-case basis as is common practice in busi-ness-to-business settings. Therefore, we define perceived rela-tionship investment as a consumer's perception uf the extentto which a retailer devotes resources, efforts, and attentionaimed at maintaining or enhaneing relationships with regularcustomers that do not have outside value and cannot be recov-ered if these relationships are terminated (Smith 1998).

We investigate the mediating role of perceived relation-ship investment, accounting for the connection betweenrelationship marketing tactics and relationship quality. Inline with our theoretical perspective of reciprocation, themeasurement items of relationship investment emphasize anaim for reciprocation by consumers that is based on reten-tion efforts made hy a retailer (e.g., "This store makesefforts to inerease regular customers' loyalty"). We positionrelationship marketing tactics applied by the retailer asantecedents of relationship investment to provide manager-ial guidelines as to what affects perceptions of relationshipinvestment. Relationship quality, ultimately influencingbehavioral loyalty, is positioned as a consequence of rela-tionship investment. A positive path between relationshipinvestment and relationship quality implies that the con-sumer reciprocates a retailer's actions.

Relationship Marketing Tactics

Few efforts have been made to define what relationship mar-keting tactics really are and how valuable consumers per-ceive them to be (Dorsch. Swanson. and Kelley 1998; Gwin-ner. Gremler. and Bitner I99S). Nevertheless, the successfulestablishment of commercial relationships is considered todepend largely on fine-tuning such tactics (Christy. Oliver,and Penn 1996; Dwyer. Schurr. and Oh 1987). In general,the literature distinguishes among three levels of relation-ship marketing (Berry 1995). A first level relies on pricingincentives to secure customer loyalty and is t)ften referred toas level one relationship marketing. It is considered theweakest level of relationship marketing because eompetitors

can easily imitate price. A second level of relationship mar-keting focuses on the s(x;ial aspects of a relationship, whichare exemplified by regularly communicating with con-sumers or referring to their names during encounters. Thesesocially inspired tactics are usually bundled into what iscalled level two relationship marketing. Level three rela-tionship marketing, offering structural solutions to customerproblems, is not investigated in this study. The reason forthis ehoice is that level three relationship marketing does notinvolve true relationship marketing tactics or skills, as Berry(1995, p. 241) argues: "At level three, the solution to the cus-tt)mer's problem is designed into the service-delivery systemrather than depending upon the relationship-building skills."Consequently, we distinguish among four types of relation-ship marketing tactics distributed across level one relation-ship marketing (tangible rewards) and level two relationshipmarketing (direct mail, preferential treatment, and interper-sonal communication).

Direct mail. We define direct mail as a consumer's per-ception of the extent to which a retailer keeps its regular cus-tomers informed through direct mail (e.g.. Anderson andNarus 1990; Dwyer, Schurr, and Oh 1987; Morgan and Hunt1994). In general, it is recognized that buyer-seller commu-nication increases tbe probability of discovering behaviorsthat generate rewards; enhances the prediction of behaviorof the other party and clarifies each other's roles (Doney andCannon 1997; Smith and Barclay 1997); leads to the dis-ct)very of similarities; and encourages feelings of trust, spe-cial status, and closeness (Anderson and Narus 1990). Byconveying interest in the customer, communication is oftenconsidered a necessary condition for the existence of a rela-tionship (Duncan and Moriarty 1998). In our study, we limitcommunication media to direct communication media,because mass media communication does not alkiw for tar-geting specific groups such as regular versus nonregularcustomers. Moreover, the underlying reason for liriiitingdirect communication media to direct mail is that in theresearch contexts investigated, other types of dircet mediacommunication are only occasionally used. As a result, weseek to establish that direct mail, as a way of communicat-ing with customers, should be a strong precursor for con-sumer perceptions of relationship investment. Therefore,

H|: A higher perceived level of direct mail leads to a higherperceived level of relationship inveslmenl.

Preferential treatment. We deline preferential treatmentas a consumer's perception of the extent lo which a retailertreats and serves its regular customers better than its non-regular customers (e.g., Gwinner, Gremler, and Bitner1998). For example, account holders at major shops aresometimes offered special shopping evenings or preferentialaccess to certain products for sale. Sheth and Parvatiyar(1995. p. 264) recognize that "implicit in the idea of rela-tionship marketing is et)nsumer focus and consumer selec-tivity—that is, all consumers do not need to be served in thesame way." O'Brien and Jones (1995) criticize companiesfor inadvertently treating all customers as equal; by not dif-ferentiating, companies waste resources in oversatisfyingless profitable customers while undersatisfying more valu-able, loyal customers. Peterson (1995) argues that distinc-

tnvestments in Consumer Relationships / 35

tive treatment enables a seller to address a person's basicbuman need to feel important. Thus, we expect to demon-strate tbat a stronger perception of preferential treatmentleads to a bigber perceived level of relationsbip investmentmade by tbe retailer. Accordingly,

Hy. A higher perceived level of preferential treatment leads toa higher perceived level of relationship investment.

Interpersonal communication. We define interpersonalcommunication as a consumer's perception of tbe extent towbicb a retailer interacts witb its regular customers in awarm and personal way (e.g., Metcalf, Frear, and Krishnan1992). Interpersonal communication differs from preferen-tial treatment in tbat tbe former refers to tbe personal toucbin communication between a store and its customers and thelatter empbasizes that regular customers receive a bigberservice level than nonregular customers. Tbe importance ofpersonal excbanges between consumers and retailers ininfluencing relationsbip outcomes sbould not be surprisinggiven tbat relationships are inherently social processes{Beatty et al. 1996). For example, almost five decades ago,Stone (1954) highlighted tbe importance of social excbangein recognizing tbe existence of sboppers who appreciate per-sonal contact in tbe store. Evans, Cbristiansen, and Gill(1996, p. 208) state tbat tbe social interaction afforded byshopping has been suggested to be "tbe prime motivator forsome consumers to visit retail establisbments." Examples ofsocial rclationsbip benefits are feelings of familiarity,friendsbip, and social support (Berry 1995); personal recog-nition and use of a customer's name (Howard, Gengler, andJain 1995); knowing tbe customer as a person; engaging infriendly conversations; and exhibiting personal warmth(Crosby, Evans, and Cowles 1990). This theorizing is sum-marized in tbe following bypotbesis:

Hi: A higher perceived level of interpersonal communica*tion leads to a higher perceived level of relationshipinvestment.

Tangible rewards. We describe tangible rewards as aconsumer's perception of the extent to which a retailer offerstangible benefits sucb as pricing or gift incentives to its reg-ular customers in return for their loyalty. Babin, Dardcn, andGriffin (1994) refer to a duality of rewards for many humanbehaviors, the distinction between performing an act to "getsomething" versus doing so because "you love it." Manymarketers focus on the former, providing rewards that relyprimarily on pricing incentives and money savings to securecustomers' loyalty (Berry 1995; Peterson 1995). Similarly,our construct of tangible rewards implies tbat customersreceive something tangible in return for tbeir loyalty. Exam-ples of tangible rewards marketers provide as a means ofappreciating customers' patronage are frequent flyer miles,customer loyalty bonuses, free gifts, and personalized cents-otf coupons (Peterson 1995). Also, trying to earn points—onsucb things as hotel stays, movie tickets, and car wasbes—helps customers remain loyal, regardless of service enbance-ment or price promotions of competitors (Sharp and Sharp1997). Tberefore, we formulate the following:

H4: A higher perceived level of tangible rewards leads to ahigher perceived level of relationship invesEment.

Relationship QualityTbe choice of relationsbip quality as a relationsbip outcome inour study is consistent witb previous studies on relationshipmarketing (e.g., Kumar, Schcer, and Steenkamp 1995). Rela-tionsbip quality can be considered an overall assessment of tbestrength of a relationship (Garbarino and Jobnson 1999; Smith1998). Previous research conceptualizes relationship quality asa bigber-order construct consisting of several distinct, tbougbrelated, dimensions (e.g., Dorscb, Swanson, and Kelley 1998;Kumar, Scbeer, and Steenkamp 1995). Altbough tbere stillexists discussion on wbich dimensions make up relationshipquality, prior conceptualizations mainly emphasize tbe criticalimportance of relationsbip satisfaction, trust, and relationsbipcommitment as indicators of relationsbip quality. For example,Crosby, Evans, and Cowles (1990) and Dwyer, Schurr, and Ob(1987) consider relationsbip satisfaction and trust to be indica-tors of tbe bigber-order construct of relationsbip quality.Hennig-Tburau and Klce (1997), Leuthesser (1997), andDorscb, Swanson, and Kelley (1998) further argue to add rela-tionship commitment as a dimension of relationsbip quality.Therefore, we assume that a better-quality relationship isaccompanied by a greater satisfaction, trust, and commitment.We prefer the ab.stract relationship quality construct over itsmore specific dimensions because, even tbougb tbese variousforms of attitude may be conceptually distinct, consumers havedifficulty making fine distinctions between tbem and tend tolump them together (Crosby, Evans, and Cowles 1990). Next,we briefly elaborate on tbe dimensions of relationship quality.

Relationship satisfaction. Satisfaction with the relation-sbip is regarded as an important outcome of buyer-sellerrelationsbips (Smitb and Barclay 1997). We define relation-sbip satisfaction as a consumer's affective state resultingfrom an overall appraisal of bis or her relationsbip with aretailer (Anderson and Narus 1990). Tbus, we conceptualizerelationsbip satisfaction as an affective state (Smitb and Bar-clay 1997) in contrast witb more rational outcomes (Ander-son and Narus 1990). In addition, we view it as a cumulativeeffect over tbe course of a relationsbip compared witb satis-faction tbat is specific to eacb transaction (Anderson, For-nell, and Rust 1997).

Trust. Tbe development of trust is tbought to be an impor-tant result of investing in dyadic buyer-seller relationsbips(e.g., Gundlach, Achrol, and Mentzer 1995). Drawing on theexisting literature (e.g., Morgan and Hunt 1994), we definetrust as a consumer's confidence in a retailer's reliability andintegrity. Several scholars consider perceived trustworthinessand trusting bebaviors as two distinct, tbougb related, aspectsof trust. Wbereas trustworthiness refers to a belief or confi-dence, trusting bebaviors are related to tbe willingness toengage in risk-taking bebavior, reflecting a reliance on a part-ner (Smitb and Barclay 1997). Altbougb some scbolars mergeboth aspects into one definition of trust (e.g., Moorman,Despbande, and Zaltman 1993), otbers claim tbat trustwortbi-ness is a necessary and sufficient condition for trust to exist(e.g., Anderson and Narus 1990). In line witb tbe latter group,our definition encompasses only tbe notion of trustwortbiness.

Relationship commitment. Commitment is generallyregarded to be an important result of good relational inter-actions (Dwyer, Schurr, and Ob 1987). In our study, we


dcllnc relationship commitment as a consumer's enduringdesire to continue a relationship with a retailer accompaniedhy this consumer's willingness to make ctTorts al maintain-ing il (e.g., Morgan and Hunt 1994). Note that thederinitionimplies the presence and consistency over time of hoth thedesire to continue a relationship and the willingness to makeefforts directed at sustaining this relationship (Macintoshand Lockshin 1997). We believe that the desire for continu-ity is a necessary hut insulTicient condition for relationshipcommitment hecause. for example, it might be driven sim-ply hy hahitual cues or marketplace constraints. As a result,our measures of commitment incorporate hoth aspects.

The association hetween relationship investment andrelationship quality has rarely heen investigated empirically.A notahle exception is the strong support Crosby, Evans, andCowies (1990) find fora positive path from relational sellingbehavior to relationship quality. Furthermore. Wray. Palmer,and Bejt)u (1994) lind evidence for a positive relatit)nshipbetween a salesperson's customer orientation and relation-ship quality. Finally. Lagace. Dahlstrom, and Gassenheimcr(1991) (Ind a positive path from ethical salesperson behaviorto relationship quality. Although these constructs are notcompletely similar to our construct of relationship invest-ment, they provide an initial basis for our next hypothesis.

Stronger evidence can be lound for the impact of rela-tionship investment on the dimensions of relationship qual-ity. Relationship investment has heen shown to predict satis-faction in business marketing relationships {e.g., Andersonand Narus 1990; Ganesan 1994: Smith and Barclay 1997).Customers tend to be more satisfied with sellers who makedeliberate efforts toward them (Baker, Simpson, and Siguaw1999). Also, trust has been shown to be resulting from rela-tionship investment. For example, Ganesan (1994) tinds thatspccillc investments made by one partner result in increasedtrust. With respect to commitment, Dwyer. Schurr. and Ob(1987, p. 19) suggest that commitment is "'fueled by theongoing benefits accruing to each partner." In line with this.Bennett (1996) argues that the strength of customers" ct)m-mitment depends on their perceptions of efforts made by theseller. Furthermore, several authors bave empirically inves-tigated the relationsbip between relational performance, aconstruct that shows similarities to relationship investment,and relationship commitment (Anderson and Weitz 1992;Baker, Simpson, and Siguaw 1999; Morgan and Hunt 1994).Therefore, we suggest the following:

Hs: A higher perceived level of relationship investment leadsto a higher level of relationship quality.

Behavioral LoyaltyModels that theorize attitudinal as well as behavioral rela-tionship outcomes have strong precedence in relationshipstudies (e.g., BoUon 1998; Macintosh and LcKkshin 1997).Accordingly, we build on existing literature, which statesthat the effectiveness of relationship marketing tacticsshould also be evaluated in terms of the behavioral changesthey create {Sharp and Sharp 1997). As a result, we includedtbe construct of behavioral loyalty, defmed as a compositemeasure based on a consumer's purcbasing frequency andamount spent at a retailer compared wiih the amount spent

at other retailers from which the consumer buys. In otherwords, behavioral loyalty is measured as a unique combina-tion of behavioral indicators, concordant with suggestionsmade by Sirohi, McLaugblin. and Wittink (1998) andPritchard, Havitz, and Howard (1999).

Hennig-Thurau and Klee (1997) argue that relationshipquality is an antecedent of repeat purchase behavior. Further-more, some empirical evidence has been found for relation-ships between dimensions of relationsbip quality and behav-ioral loyalty. With respect to satisfaction as a dimension ofrelationship quality, Bolton (1998) and Macintosh and Lock-shin (1997) find positive patbs from relationship satisfactionto hoth relationship duration and purchase intentions, whichcan be considered behavioral indicators of loyalty. Regardingtrust as a relationship quality dimension. Smith and Barclay(1997), for example, report a positive effect of trust on for-bearance from opportunism. Moorman. Despbandc, andZaitman (1993) suggest tbat customers who are committed toa relationship might have a greater propensity to act becauseof their need to remain consistent with their commitment.Morgan and Hunt (1994) find empirical support for the rela-tionship between a customer's commitment and acquies-cence, propensity to leave, and cooperation, all of which canhe regarded as behavioral outcomes of relationships. Derivedfrom these imdings, we investigate the following:

H : A higher level of relationship quality leads to a higherlevel of behavioral loyalty.

Factors Moderating the Effect of PerceivedRelationship InvestmentIn addition to testing for the effects we have described tbus far,this article also takes an initial step toward assessing the roleof moderators that iniluence the effectiveness of perceivedrelationship investment. An examination of sucb moderatorsenables marketers to understand when investing in relation-sbips is expected to be more effective or less effective. Not allconsumers search for more than the timely exchange of a prod-uct or service with a minimum t)f hassles, so making rest)urce-intensive relationship investments is considered neither appro-priate nor necessary for every consumer (Bendapudi and Berry1997: Christy, Oliver, and Penn 1996; Day 2(KX)). Given ourfocus on and general interest in the consumer, we investigatewhether tbe effects of perceived relationship investment arecontingent on either of two consumer cbaracteristics: productcategory involvement and consumer relationsbip proneness.

Product category involvement. In line wi lb Mittal

(1995), we define product category involvement as a con-sumer's enduring perceptions of the importance t>f the prod-uct category hased on the consumer's inherent needs, values,and interests. Researchers have suggested tbat people whoare highly involved with a product category reveal a ten-dency to be more loyal (Dick and Basu 1994; King and Ring1980). Tbey reason tbat a relationship can add value only forcustomers who are already interested in the product.Solomon and colleagues (1985) claim that in low-involve-ment situations, the treatment of customers as individualswt)uld probably not pay off, wbereas in high-involvementsituations, customers desire tnore personal treattiient. Gor-don, McKeage, and Fox (1998) state that involved buyers

Investments in Consumer Relationships / 37

are more likely to participate in marketing relationsbips andto derive value from these relationsbips. Sucb relationsbipsmay be perceived as invasive or annoying wben directed atconsumers with lower levels of involvement. Consequently,approaches by the seller, however well-intentioned, could beregarded by the customer as undesirable when the cus-tomer's involvement is low{Christy, Oliver, and Penn 1996).We expect the effects of perceived relationship investment tobe strengthened in the case of high levels of product cate-gory involvement:

Hy: A higher level ot" product category involvement strength-ens the impact of perceived relationship investment onrelationship quality.

Consumer relationship proneness. Gwinner. Gremler,and Bitner (1998) argue that relationship marketing successmay depend not only on its strategy or iniplemenlalion butalso on the preferences of the individual customer. Christy,Oliver, and Penn (1996) use the term "psychologically pre-disposed" to express the idea that some customers are intrin-sically inclined to engage in relationships. However, despitethe reeognized importance of customers' proneness toengage in relationships with sellers, no study has yet inves-tigated its impact on relationship effectiveness (Sheth andParvatiyar 199,'i). In this study, we define consumer rela-tionship proneness as a consumer's relatively stable andconscious tendency to engage in relationships with retailersof a particular product category. Several authors stress that abuyer's proneness to engage in relationships may varyacross groups of sellers (Bendapudi and Berry 1997;Christy. Oliver, and Penn 1996) (e.g., apparel stores versussupermarkets), so we postulate that consumer relationshipproneness must be defined within a particular product cate-gory. In addition, we emphasize consumers' conscious ten-dency to engage in relationships as opposed to a tendencybased more on inertia or eonvenience (e.g., Dick and Basu1994). From a seller's perspective, investing in relationshipswith buyers is not always considered a preferable strategy,beeause not all types of buyers are prone to engage in rela-tionships with sellers (Berry 1995; Crosby, Evans, andCowles 1990; Sheth and Parvatiyar 1995). We assume thatrelationship-prone consumers should reciprocate a retailer'sefforts more strongly, because by definition, relationship-prone consumers are most likely to develop relationships.Consequently, we test the following:

H : A higher level of consumer relationship pronenessstrengthens the impact of perceived relationship invest-ment on relationship quality.

MethodSetting

An externally valid, fuller understanding of consumer rela-tionships requires that the validity of conceptual modelsdeveloped in one setting be examined in other settings aswell. Our study is conducted in the food and apparel indus-tries, covering a wide variety of retailers, including discountstores, mass merchandisers, traditional department stores,and prestige stores. We consider these industries similar

with respeet to the competitiveness of their industry envi-ronment and lhe opportunities for consumers to switch.However, the industries differ on many other dimensions.For example, soeial features of a relationship might beexpected to be more important in an apparel context that ischaracterized by a high degree of personal contact andadvice. Conversely, economic features might play a moreimportant role in relationships between food retailers andconsumers who have a strong emphasis on discounts andanonymous self-service. In addition to studying variousindustries, in response to recent calls for cross-culturalresearch on relationships (lacobucci and Ostrom 1996). ourstudy is of a transatlantic nature; it includes respondents notonly from the United States but also from two highly devel-oped western European countries, tbe Netherlands and (theFlemish part oO Belgium. The selection of both Europeancountries was a matter of convenience. To the best of ourknowledge, this is the first study on consumer relationshipsthat compares survey data from three different countries.According to Hofstede's (1980) classification of countriesaccording to cultural dimensions (power distance, uncer-tainty avoidance, individualism, and masculinity), large-scale differences exist among these dimensions across thethree countries. The power distance scores for the UnitedStates, the Netherlands, and Belgium are, respectively, 40,38. and 65; uncertainty avoidance: 46, 53, and 94; individu-alism: 91, 80, and 75; and masculinity: 62, 14, and 54. Inaddition, significant variations in competitive conditions andlegal environments among the three countries are prevalent.In conclusion, the settings incorporated in our study differgreatly from one another, which should provide a fertileenvironment for conducting a true cross-validation.

Measure DevelopmentMeasures for some of the constructs we are examining wereavailable in the literature, ihough most were adapted to suil aretail environment. For the four relationship marketing tactics,relationship investment, and consumer relationship proneness,scales applicable to a retail context were not available and weredeveloped for the purpose of this study. First, focus groupswere used to examine how consumers described relationshipinvestment, relationship marketing tactics, and relationshipproneness. Four focus groups were organized in which partic-ipants were asked open-ended questions about their ownbehavior with respect to shopping for clothing. Then, directquestions were posed to acquire knowledge on relationshipinvestment, relationship marketing tactics, and relationshipproneness. Finally, projeetive techniques were used during theremainder of the discussions (i.e., depth descriptions, photo-sorts). Participants received a monetary incentive in return fortheir cooperation. The results were helpful in generating items.

Second, in an effort to enhance face validity, a group ofDutch and Belgian expert judges (four academies and threepractitioners) qualitatively tested an initial poo! of itemsintended to measure various relationship marketing tactics.Experts were provided with the definitions of the relationshipmarketing tactics and were asked to classify each item to themost appropriate tactic. Items that were improperly classifiedwere reformulated or deleted. Third, equivalence for all itemswas sought by conducting back-translation. A US-born


American citizen wbo was llucnt in Dutcb first translated tbeoriginal Dutcb version of the questionnaire into AmericanEnglish, and a native Dutcb speaker wbo was fluent in Amer-ican English then retranslated tbe questionnaire into Dutcb.The quality of the English translation was evaluated by amonolinguistic, U.S.-born American citizen on clarity andcomprehensiveness of tbe translated questionnaire. TbeDutcb questionnaire was used in tbe Dutch as well as in theBelgian sample (covering the Elemisb part of Belgium).

Einally, 12 graduate students in marketing researcb (4 ineach country) were instructed to pretest a questionnaire thatincluded all constructs on a total sample of 60 consumersthrough personal in-home interviews. Items measuring thevarious constructs were mixed in the questionnaire to reducebalo effects. To ensure tbat respondents were distributedacross age, sex, and country, students were assigned to par-ticular combinations of quota criteria and were allowed toselect respondents wbo matched tbese criteria (e.g., friends,family, neighbors). They asked respondents to complete thequestionnaire and then describe the meaning of eacb ques-tion, explain tbeir answers, and state any problems tbeyencountered wbile answering questions. Small revisions totbe U.S. and Dutcb/Belgian version of tbe questionnairewere made on basis of tbe protest.

Final MeasuresFinal attempts at measure purification were conducted on asample (n = 371) drawn to resemble tbe eventual multi-coun-try, multi-industry sample. We factored tbe items to investigatewbether they correctly measured tbeir intended constructs.Tlieoretically, it was likely tbat tbe latent constructs would becorrelated, so we applied an oblique rotation. We oniy retaineditems tbat minimally loaded .65 on tbe proper latent factor andmaximally loaded .30 on tbe otbers to enbance tbe distinctive-ness of the intended constructs. The resulting measurementappeared to be clean across scales, countries, and industries.The Appendix contains all (.seven point Likert) scales, orga-nized by construct. Moreover, Table 1 provides an overview ofconstruct means, standard deviations, and correlations.

Witb respect to relationsbip satisfaction, trust, and rela-tionsbip commitment, we first factor-analyzed these multi-item scales for each construct separately; across all samples,a single factor emerged in each case. As Cronbacb's alpbavalues ranged between .70 and .93, reliability was uniformlybigb in all samples fi)r all tbree constructs. Tben we assessedtbe second order factor model with the first order factors(relationship satisfaction, trust, and relationsbip commit-ment) tbat originated from tbe bighcr-order factor relation-ship quality.- These measurement results were acceptable ineach sample (comparative fit index [CEI] and nonnonned fitindex [NNFI] ranged from .93 to .97 for CFl and from .89to .96 for NNFI). All first-order and second-order factorloadings were signitlcant, demonstrating convergent valid-ity. Tbis provided us witb enougb confidence to calculateaverages for relationsbip satisfaction, trust, and relationsbipcommitment based on tbe tbree items of eacb construct and

-On request, the authors can report the detailed results on thefactor analysis, reliability scores, and the second-order factormtxlel.

use tbese averages as indicators of tbe construct relationsbipquality (see Crosby, Evans, and Cowles 1990; FosdakoffandMackenzie 1994).

SamplesInformation was collected from real consumers as opposed tostudent samples. Mall intercept personal interviews wereadministered in tbe United States (food: n = 231, apparel: n =230), tbe Netberlands (food: n = 337, apparel: n = 338), andBelgium (food: n = 289, apparel: n = 302). Samples weredrawn from sbopping mall visitors to obtain variance in age(18 to 25 years, 26 to 40 years, 41 to 55 years, and 55 yearsand over), sex, and allocated share of wallet for tbe storereported on (0%-20%, 2\%^()%, 41%-60%, 6l%-80%,and 819^-100%). We also sougbt even coverage over inter-viewing time of day and interviewing day of week to reducepossible shopping pattern biases. Across our samples, an aver-age of 37% of the visitors who were approached participated.

ProcedureParticipants were first asked wbetber they bad ever made apurchase in the particular product category. If so, they wereasked to indicate the names of five stores at which they usu-ally bought food or apparel. Next, respondents indicatedtheir approximate share of wallet for each store listed (mea-sured on a continuous scale from 0% to 100%) and theextent to wbicb they believed they were regular customers ofeacb store (measured on a scale from I to 7). Finally, theinterviewers selected a specific store to focus on for tberemaining questions on tbe basis of tbe reported sbare ofwallet figures. Care was taken tbat respondents reportinglow, medium, and higb levels of sbare of wallet were repre-sented in eacb sample. By definition, a relationship is ofextended duration and composed of multiple interactions, somany of the ct)sts and benefits from buyer-seller relation-sbips cannot be assessed a priori (Dwyer, Scburr, and Ob1987; Parasuraman 1997). Gwinner, Gremler, and Bitner(1998) stale tbat tbougb customers may receive relationshipbenefits and believe tbat tbese benefits are important, theymay not always be aware ot these benefits" existence in theearly stages of a relationsbip and may not bave assessedtbeir value yet. Therefore, only tb<isc stores were includedfor wbicb respondents indicated at least a 4 on tbe 7-pointscale tbat measured "being a regular customer of the store."To enbance interrater reliability, tbe cover letter attacbed totbe questionnaire explained the term "regular customer" torespondents as "a customer who regularly buys clotbes/foodin a store and not simply visits tbe store to look around."

ResultsExamination of Data PoolingTo decide wbetber we needed to estimate separate mtxlelsfor eacb sample, we investigated tbe possibility of poolingdata across countries and/or industries by means of severalmultigroup LISREL analyses. To assess pooling of industrysamples, we evaluated two nested models for eacb country:{I) a model in wbich all structural patbs were set equalacross tbe two industry samples (equal model) and (2) amode! in wbicb all structural patbs were set free across tbe

Investments in Consumer Relationsbips / 39

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TABLE 2Overall Model Fits

Fit Statistics

X^(177)

GFIAGFIRMSEASRMRNNFICFi

United States

428.442.42

.85

.80

.079

.073

.93

.94

Food

Netherlands

458.132.59

.88

.84

.072

.072

.90

.92

Belgium

355.492.01

.89

.86

.061

.061

.94

.95

United States

457.212.58

.83

.78

.087

.073

.92

.93

Apparel

Netherlands

390.732.21

.90

.87

.058

.054

.95

.95

Belgium

373.512.11

.89

.86

.060

.060

.93,94

Notes: GFI = goodness-of-fit index, AGFI - adjusted goodness-of-fit index.

two industry samples (free mtKlel). We followed the sameprocedure to assess pooling of country samples. Withrcspeci to pooling across industries, the free model in theDutch sample obtained a significantly better fil than theequal model, which indicates that not all of the paths wereequal across apparel and food. With respect to poolingacross countries, the differences between the equal and freemodels were statistically significant for four of six countrycomparisons. Therefore, we decided not to pool the dalaacross countries or industries.

Overall Model EvaluationIn Table 2, we report the values of the fit statistics. The chi-squares are all significant (p < .O,*!; Bollen 1989), a fmdingnot unusual with large sample sizes (Doney and Cannon1997). The ratios of chl square to degrees of freedom (d.f.)are between 2.01 and 2.59, all within the acceptable rangeof 2 to 5 {Marsh and Hovecar 1985). The values for CFI,NNFI. root mean square error of approximation (RMSEA),and standardized ro(>t mean residual (SRMR) are accept-ahly close to the standards suggested by Hu and Bentler(19W): .95 for CFI and NNFI, .06 for RMSEA. and .08 forSRMR. Given that these batteries of overall goodness-of-fitindices were accurate and that the model was developed ontheoretical bases, and given the high level of consistencyacross samples, no respecifications of the model weremade. This enables us to proceed in evaluating the mea-surement and structural models.

Measurement Model EvaluationIn Table 3, we report [he results of the measurement models.We assessed the quality of our measurement efforts byinvestigating unidimensionality, convergent validity, relia-bility, discriminant validity, and metric equivalence. Evi-dence for the unidimensionality of each construct includedappropriate items thai loaded at least .65 on their respectivehypothesized component and loaded no larger than .30 onother components in a factor analysis. In addition, the over-all goodness of fit supports unidimensionalily (Steenkampand van Trijp 1991). Convergent validity was supported byall loadings being significant (/? < .01) and nearly all R-exceeding .50 (Hildebrandt 1987). We assessed reliabilityjointly for all items of a construct by computing lhe com-posite reliability and average variance extracted (Baumgart-nerand Homburg 1996; Sleenkamp and van Trijp 1991). For

a construct to possess good reliability, composite reliabilitysht)uld be between .60 and .80, and the average varianceextracted should at least be .50 (Bago/.zi and Yi 1988). Allscales demonstrate good reliabilities.

We tested discriminant validity by means of several sub-sequent prtJcedures. First, as a basic test of discriminantvalidity, we checked whether correlations among the latentconstructs were significantly less than I. In all samples, con-struct correlations indeed met this criterion. Second, we com-pared a series of nested confirmatory factor models in whichcorrelations between latent constructs were constrained to I(each of tbe 21 off-diagonal elements was constrained andthe model reestimated in turn), and indeed chi-square differ-ences were significant for all model comparisons (^ < .01) inall samples, again in support of discriminant validity. Third,we performed a stronger test for discriminant validity pro-vided by Fornell and Larcker (1981). This test suggests thata scale possesses discriminant validity if the average varianceextracted by the underlying construct is larger than the sharedvariance (i.e. the squared intercorrelation) with other latentconstructs. On the basis of this most restrictive test, we foundstrong evidence for discriminant validity between each pos-sible pair ol latent constructs in all samples (i.e.. all pairs ofseven factors in all three countries in both industries). Onlytwo exceptions were found. In the U.S. food sample, thesquared intercorrekition between preferential treatment andtangible rewards (.79) was larger than the shared varianceextracted by both constructs (.76 and .69, respectively). In theDutch apparel sample, the .squared intercorrelation betweenrelationship investment and relationship quality (.67) waslarger than the shared variance extracted by relationship qual-ity (.63). However, given that neither problem occured in theother five sainples, we do not consider tbis a major problem.

Finally, to crt)ss-nationally investigate the interrelation-ships between ctmstructs in a nomological net, Steenkampand Baumgartner (1998) indicate that lull or partial metricinvariance must be satisfied because the scale intervals of thelatent constructs must be comparable across countries. Weassessed metric invariance by comparing two nested modelsfor each construct separately in terms of the difference inchi-square relative to degrees of freedom, RMSEA, NNFI,and CFI.^ En the first model (base model), all error variances

'On request, the authors can report the detailed results on thetests fiir lull or partial metric invari;ince.


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and all factor loadings were allowed to be free across sam-ples. (One marker item was selected, and the same markeritem was used in each sample.) Only the factor variance ofthe latent construct was constrained to be equal across sam-ples. (We measured each latent construct on basis of threeindicators, so at least one parameter should be fixed acrosssamples to generate a nonsaturated model.) In the secondmodel (equal loadings model), we additionally constrainedthe remaining two factor loadings (apart from the markeritem) to be equal across the six samples. While metric invari-ance is "a reasonable ideal..,, a condition to be striven for,not one expected to be fully realized" (Horn 1991, p. 125),our measurement model supported full metric invariance forthree of seven constructs incorporated. For constructs notrevealing full metric invariance (direct mail, interpersonalcommunication, tangible rewards, and relationship commit-ment), we sequentially relaxed constraints on parameters totest for partial metric invariance. Partial metric invariancewas supported for all remaining constructs.

In summary, the measurement models are clean, withevidence for unidimensionality, convergent validity, reliabil-ity, discriminant validity, and metric invarianee, whichenabled us to proceed to the structural model evaluation.

Structural Model Evaluation

Table 4 indicates that in each sample, all significant rela-tionships between latent constructs are in the hypothesizeddirection, which provides initial evidence for our conceptualmodel and supports the nomological validity of the con-

structs. An important fmding is that the relationship betweenperceived relationship investment and relationship qualityand the positive path from relationship quality to behavioralloyalty are confirmed across all samples. This result pro-vides strong empirical evidence for the cross-validation ofthis part of our conceptual model, which is especially note-worthy given that the countries examined differ consider-ably on demographic, economic, and cultural dimensions.Consequently, there was strong and uniform support for H5and H5.

In examining H1-H4, which explicate the associationsbetween relationship marketing tactics and perceived rela-tionship investment, only in the United States is there a con-sistent pattern of effects across the two industries. In addi-tion, only for preferential treatment in the food industry andfor interpersonal communication in the apparel industry isthere a consistent pattern of effects across the three coun-tries. Apart from these effects, the data provided mixed evi-dence. Specifically, direct mail had a positive impact on per-ceived relationship investment (H|) in three of fourEuropean samples as opposed to the U.S. samples, in whichno significant paths were detected. Preferential treatmentrevealed a nonsignificant relationship with perceived rela-tionship investment (H2) in all samples except for the Bel-gian apparel sample. Interpersonal communication had thestrongest impact on perceived relationship investment (Hi),being cross-validated in all samples except for the Belgianfot)d sample. Finally, the data support a positive path fromtangible rewards to perceived relationship investment (H4)

TABLE 4Structural Models

HypothesizedPath

Hi: Direct mail -*perceived relationshipInvestment (+)

H2: Preferential treatment -»perceived relationshipinvestment (+)

H3: Interpersonal communication —*perceived relationshipinvestment (+)

H4: Tangible rewards -*perceived relationshipinvestment (+)

H5: Perceived relationship investmentrelationship quality (+)

HQ. Relationship quality ->behavioral loyalty (+)

UnitedStates

.09(.09)

-.10(.16)

.74"(.12)

.02(.18)

-> .68"(-08). 4 1 "

(.07)

Estimate (Standard Error)

Food

Nether-lands

.08(08)

.04(.10)

.19"(.08)

.24"(09)

.72"(.08). 2 1 "

(.06)

Squared Multiple Correlations for Structural Equations

Perceived relationship investmentRelationship qualityBebavioral loyalty

.44

.46

.17

.18

.52

.04

Belgium

.16"(.07)

.08(.09)

.08(.08)

.47"(.10)

. 6 1 "(.08).40"

(.07)

.41

.37

.16

UnitedStates

.22(.14)

-.11(.12)

.42"(.11)

.18(.20)

.76"(.08).46"

(.08)

.44

.58

.21

Apparel

Nether-lands

.27"(.06)

.09(.07)

.40"(.06)

.18"(.08)

.82"(08).36"

(.07)

.55

.68

.13

Belgium

.28"(.07)

.15'(.07)

.16*(.08)

.12(.09)

.48"(.07).33"

(.07)

.31

.23

.11'p < .05 (one-sided)."p< .01 (one-sided).


FIGURE 2Rival Model

in three of four European samples but do not provide evi-dence lor ihis path in ihe U.S. samples.

We now turn to two model modifiealions: First, we test arival structural model to enhance our confidence in the focalmodel further, and second, we introduce (he potential mod-erators of product category involvement and consumer rela-tionship proneness, in accordance with our prior theorizing.

A Rival Mode!

[t is generally agreed that researchers should compare rivalmodels and not jusl test the performance of a proposedmodel (Bagoz/.i and Yi 1988). In discussing the construct ofperceived relationship Investment previously, we provided atheoretical basis for positioning perceived relationshipinvestment as a mediating variable. Because our parsimo-nious hypoihesized mode! allows no direct paths frotn any ofthe four relationship marketing tactics to relationship qual-ity or to behavioral loyalty, it implies a central nomologicalstatus for relationship investment. A nonparsimonious rivalmodel w(iuld hypothesi/.e only direct paths from each of theprecursors to the outcomes relationship quality and behav-ioral loyalty. This model makes relationship investmentnomologically similar to the four relationship marketing tac-tics. The tested rival model (see Figure 2) therefore permitsno indirect effects, implying that reiationship investment isnot allowed to mediate any of the relationships.

On the basis of Morgan and Hunt (1994), we comparedour hypothesized model with the rival model on the follow-ing criteria:"* overall fit, parsimony, percentage of eithermodel's parameters that were statistically signitlcant, andR-s for the endogenous constructs. With respect lo overalltu, the average CFI of the rival model was slightly higherthan that of the hypothesized mode! (.947 versus .938), andthe rival model's mean ratio of chi-square to degrees of Iree-dom was slightly lower than that of the hypothesized model(2.24 versus 2.32). Note, however, that to achieve this slightincrease in lu, we needed to estimate four additional paths

••On request, the authors can report Ihe detailed results on therival model.

in the rival model, which reduced the rival model's parsi-mony and partially offset the incremental improvemeni infit. in addition, on!y 47% of the paths in the rival modelwere significant as opposed to 67% in the hypothesizedmodel, which suggested that the additional paths were notmeaningful theoretically or empirically. Finally, the averageexplained variance of relationship quality was .56 in therival mode! as opposed to .47 in the hypothesized model.This is not surprising because in addition to relationshipinvestment, as a precursor of relationship quality, four extraantecedents were modeled to explain relationship quality inthe rival model. In contrast, the average explained varianceof behavioral loyalty was only .12 in the riva! mode! asopposed to .14 in the hypothesized mode!. This means thatthe explanatory power of relationship quality as a singleantecedent of behavioral !oya!ty is stronger than the com-bined explanatory power of the four re!ationsbip marketingtactics p!us re!atit)nship investment.

On the basis of these findings, we beheve that the exer-cise of fitting a rival model has strengthened the support wefound for the meaningfulness and robustness of our hypoth-esized model. In addition to the conceptual support foundfor positioning perceived relationship investment as a medi-ating variable in the hypothesized model, the rival modelempirically demonstrates its added value. Neglecting themediating role of this construct reduces its parsitnony andresults in a lower percentage of significant path coefficients.

Moderating Influences

We tested tnoderating effects through muttigroup analyses,splitting the samples into subsamples according to whetherconsumers scored high or low on the moderating variablesto ensure within-group homogeneity and between groupheterogeneity. The subgroup method is a commonly pre-ferred technique for detecting mt>derating effects (Stone andHollenheck 1989). For each moderator. Table 5 displays theresults for 12 separate structural model estimations in termsof chi-square and degrees of freedom.

Moderatinfi influence of product category involvement.Considering prt)duct category involvement as a moderator.


TABLE 5Moderating Influences

Food Apparel

Moderator: ProductCategory Involvetnent

d.f.

d.f.

UnitedStates

405742.07

404735.97

6.10*

Nether-lands

405782.86

404782.84

.02

Belgium

405674.91

404674.88

.03

UnitedStates

405794.60

404781.45

13.15**

Nether-lands

405758.81

404754.51

4.30'

Belgium

405653.99

404653.60

.39

Equal model

H7: Perceived relationship investmentrelationship quality: free

Moderator: ConsumerRelationship Proneness

Equal model d.f.

y Perceived relationship investment -» d.f.relationship quality: free X

405844.85

404833.58

11.27**

405690.03

404689.92

.11

405664.47

404656.50

7.97**

405855.85

404851.17

4.68'

405770.40

404769.42

.98

405741.29

404741.18

.11

*p < .05 (one-sided)."p< .01 (one-sided).

in the equal models, we set all paths ofthe structural modelequal across high- and low-product category involvementsuhsamples. In the free models, we constrained all paths tobe equal across high- and low-product category involve-ment suhsamples, except for the link that was potentiallyaffected by the moderator variable. Differences in chi-square values between models determine whether productcategory involvement acts as a moderating variable; that is,a significant decrease in chi-square from the equal model toa model in which one relationship is set free implies that themoderator variable has a significant infiuence on that rela-tionship. Table 5 reveals that the level of product categoryinvolvement significantly moderates the impact of perceivedrelationship investment on relationship quality in three sam-ples (U.S. food, U.S. apparel, and Dutch apparel). For rela-tionships that were moderated, the within-group path coeffi-cients were consistently lower in the low-involvement thanthe high-involvement subsample. The following differencesin path coefficients were found for the link from perceivedrelationship investment to relationship quality: U.S. food+.19. U.S. apparel +.23, and Dutch apparel +.09. In conclu-sion, for some industry-country combinations, our data sug-gest that investing in a relationship generates a higher pay-off in terms of increased relationship quality whencustomers are more involved with the product category.These findings tentatively support H7.

Moderating influence of consumer relationship prone-ness. We used the same procedure to assess the moderatingimpact of consumer relationship proneness. The resultsshow that consumer relationship proneness significantlymoderates the impact of perceived relationship investmenton relationship quality in three samples (U.S. food, U.S.apparel, and Belgian food). For relationships that were mod-erated, within-group path coefficients were consistentlylower in the low-relationship proneness than the high-relationship proneness subsample. The following differ-

ences in path coefficients were found for the link from per-ceived relationship investment to relationship quality: U.S.food +.30, U.S. apparel +.15, and Belgian food +.30. Thesefindings suggest that the impact of perceived relationshipinvestment may he stronger when customers are more proneto engage in relationships with sellers. These results providepreliminary support for Hg.

Discussion and ImplicationsThe deveiopment and sustainability of loyalty is increasinglydifficult to achieve and is still surrounded with ambiguityregarding its underlying determinants, so we believe that ourresearch makes a significant contribution to relationship mar-keting theory in three different ways. First, our model con-tributes to the existing literature by specifying how retailerscan guide consumer perceptions of relationship investmentby applying four different relationship marketing tactics.Prior studies have rarely investigated the role of such tacticsin shaping consumer relationships. Second, our study demon-strates why retailers benefit from investing in consumer rela-tionships by assessing the impact of perceived relationshipinvestment on relationship quality and ultimately on behav-ioral loyalty. Third, this study is a first attempt to provideinsights into the role of contingency factors in determiningrelationship quality by emphasizing the moderating impact ofa newly introduced construct, consumer relationship prone-ness, and prt>duct category involvement. We tested these threeresearch questions comprehensively and rigorously by repli-cating the study across three countries and two industries.

With respect to our first research question, relationshipmarketing tactics were found to play a differential yet con-sistently positive role in affecting perceived relationshipinvestment. Today's retailers increasingly offer comparablemerchandise, copy competitors" price promotions, sharecommon distribution systems, and treat customers well in


terms of services offered, so there are increased opportuni-ties for directing greater attention to developing and imple-menting relationship marketing tactics. With respect to thedirect mail tactic, we found mixed evidence for its positiveeffect on perceived relationship investment. Most strikingly,no empirical support was found for positive effects of directmail in the United States. A likely explanation for this find-ing is that the longer tradition of sending direct mail to reg-ular customers in affluent U.S. markets has worn out itseffect on perceived relationship investment. Whereas in theUnited Stales, direct marketing expenditures constituted57.8% of total advertising expenditures in 1997(DMAAVEFA 1998), these percentages were significantlylower in the Netherlands and Belgium during the sameperiod: 47.4% and 38.9%, respectively (FEDMA 1998).This is illustrated by the difference across countries in thenumber of direct mail pieces received per capita. The aver-age number of U.S. direct mail pieces received over the past50 years has risen from approximately 145 pieces per yearto more than 700 per year (James and Li 1993). In 1997,Dutch consumers received an average of only B1.7 pieces ofaddressed direct mail, and Belgian consumers found anaverage of 110.1 pieces of addressed mail in their mailbox(FEDMA 1998).

Interpersonal communication proved to be a dominantdeterminant of perceived relationship investment, beingreplicated in five out of six samples, an observation that issensible given that relationships are inherently social. Itdemonstrates the crucial role of retail employees who are indirect contact with customers. Retailers capable of trainingand motivating their employees to show warm and personalfeelings tov ard customers can reap the resulting benefits interms of improved perceptions of relationship investment.Also, when hiring store personnel, store management needsto focus on candidates' social abilities that facilitate socialinteractions with target consumers (Weitz and Bradford1999). Tbis is especially important, because the emergenceof automated retailing has gradually reduced opporluniliesfor social interaction in the store. Retailers should investi-gate whether ct)nsuniers are willing to trade off the loss ofsocial contact for the benefits of automation.

Preferential treatment revealed a nonsignificant retation-sbip with perceived relationship investment in all samplesexcept one, and this contradicts the common opinion thatregular buyers should be treated and served differently thannonregular buyers should. A potential explanation for thisfinding might be that customers do not appreciate beingopenly favored above other customers. If this is true, itwould hold important implications for retailers, because itemphasizes that efforts directed at customers should bemade delicately to avoid putting customers in an uncomfort-able position. Alternatively, perhaps preferential treatment issimply not as powerful as the other antecedents of perceivedrelationship investment, and in the presence of the other tac-tics, preferential treatment is less valued by tbe consumer.

Finally, mixed evidence was detected for the positiveeffects of tangible rewards on perceived relationship invest-ment. Again, this was true in the U.S. samples in which nosignificant paths were found. In U.S. markets, the longer tra-dition of providing customers with tangible rewards for their

loyalty might decrease the impact of such offers. The naturalappeal of tangible rewards can be assumed to decrease ifmore sellers start offering them. As tangible rewards becomewidespread, their absence may disappoint consumers,whereas their presence would not necessarily boost cus-tomer retention. Competitors can easily imitate tangiblerewards such as frequent flyer programs, customer loyaltybonuses, and free gifts. Perhaps such "wear-out" effectshave simply occurred less in the European markets.

A second key research objective of tbis study was to assessthe effect of perceived relationship investment on relationshipquality and ultimately behavioral loyalty. We expected per-ceived relationship investment to play an important role indetermining relationship quality, which was confirmed in allsix samples. The path from relationship quality to behavioralloyalty was also demonstrated across samples. These resultssupport the findings of Bagozzi (1995) and Kang and Ridg-way (1996), who argue that consumers feel obligated to reci-procate a retailer's investments in the retailer-consumer rela-tionship by increasing their loyalty to this retailer. This findingimplies that it pays off for retailers to invest in consumer rela-tionships, because it results in increased loyalty.

Finally, we found initial support for our third researchquestion. We collected empirical evidence for what previ-ously have been only assumptions suggesting that customercharacteristics ean influence the effectiveness of relation-ship marketing investments (e.g., Ganesan 1994). Theresults show that consumer relationship proneness repeat-edly acts as a moderator of the effectiveness of perceivedrelationship investment, perhaps operating as a heightenedsensitivity to a seller's efforts directed at buyers (see Dwyer,Schurr, and Oh 1987). In addition, product categoryinvolvement moderated the effecl of perceived relationshipinvestment in some cases. Paths that are significantly mod-erated suggest that consumers with a lower degree of prod-uct category involvement are less influenced by a retailer'sinvestment in the relationship (e.g., consistent with Solomonet al. 1985). Leuthesser (1997) points out that a buyer'sstake in a relationship with a seller tends to be higher wilhgreater involvement in the product category. Our data thenmight be reasonably interpreted as higber stakes in a rela-tionship, which cause consumers to appreciate a retailer'sinvestments more strongly.

These observations emphasize that retailers should notlose sight of the importance of consumer-related factors inshaping relationship quality. No matter how much trouble theretailer goes to in order to increase relationship quality, theeffects of those efforts and resources can be tempered orstrengtbened by the consumer's level of relationship prone-ness and product category involvement. Consequently, re-tailers should not only invest more in consumer relationshipsbut also pay equal attention to finding consumers who aremost receptive to such investments. In addition to the moretraditional criteria of product-market segmentation such asmarket size, market growth, and expected market share, seg-menting consumers according to levels of consumer relation-ship proneness or product category involvement could affectexpected share of market and share of customer. For exam-ple, a practical approach toward accomplishing this objectivemight be to add a few questions to the registration form of a


store's customer loyally card that measure consumer rela-tionship proneness and product category involvement.

Limitations and Directions for Further ResearchSome limitations might be related to collecting our data andinterpreting our results. A first limitation might be the omis-sion of important variables. For example, additional tangibleelements in the retail mix, such as pricing and promotion,product quality and assortment, and service quality, could beadded as antecedents of relationship investment. This is evi-denced by the fact that the percentage of explained varianceof perceived relationship investment could still be improved.Relationship marketing theory not only should have eyes fortypical relationship marketing constructs but also couldexamine the value of existing instruments such asSERVQUAL in affecting relationships. Although theSHRVQUAL measures (Parasuratnan. ZeithamI, and BerryI9SS) can be applied to a broad spectrum of contexts, noprevious research of which we are aware has examined theireffects on the relationship outcomes examined in this study.Moreover, it is likely thai the relative importance of product.service, and relationship marketing tactics in determiningrelationship investment varies according to the length of arelationship. We could assume that the longer a relationshipexists, the stronger is the relative impact of relationship mar-keting tactics on perceived relationship investment com-pared with product and service tactics. Consequently, itcould be fruitful to compare research models incorporatingall these components across buyer segments that exhibit dif-ferent levels of relationship length.

Second, this study focused on consumer-specific moder-ators of perceived relationship investment, but a challengingresearch avenue would be to assess the role of other contin-gency factors. For example, it might be interesting to studythe differences between large store chains and small, inde-pendent neighborhood stores. It could be argued that smallstores would demonstrate more relationship friendly charac-teristics than large store chains, given that the degree ofsocial exchange and the possibilities for interpersonal com-munication are generally greater in smaller stores. Whereaslarger store chains generally operate on the basis of anony-mous self-service, the survival of small, independent storesis often dependent on personal service and knowledge ofconsumer preferences. A third potential shortcoming in thestudy is common method bias. We used one questionnaire tomeasure all constructs included, so perhaps the strength ofthe relationships among these constructs may be somewhatintlated. A fourth potential limitation is related lo the mea-surement of behavioral loyalty. The irue meaning of behav-ioral loyalty may be only partially captured given that itsmeasure was based on self-reports. Database inlbrmationcould be used as input for measuring actual purchasingbehavior. The confidence in our results could be strength-ened with access to behavioral data on customer purchasehistories that are nol subject to potential recall loss. It wouldthen be possible to examine longer strings of purchases andperhaps to incorporate contextual information. These recog-nized shortcomings could inspire researchers to define theirI'uturc research agendas.

APPENDIXSummary of Measures

Construct Measures

Direct mail

Preferentialtreatment

Interpersonalcommunication

Tangible rewards

Perceived relationshipinvestment

Relationship qualityRelationship

satisfaction

Trust

This store often sends mailings to regular customers.Tbis store keeps regular customers informed tbrougb mailings.This store often informs regular customers through brochures.

This store makes greater efforts for regular customers than for nonregular customers.This store offers better service to regular customers than to nonregular customers.This store does more for regular customers than for nonregular customers.

This store takes the time to personally get to know regular customers.This store often holds personal conversations with regular customers.Tbis store often inquires about the personal welfare of regular customers.

This store rewards regular customers for their patronage.This store offers regular customers something extra because tfiey keep buying there.Tbis store offers discounts to regular customers for their patronage.

This store makes efforts to increase regular customers' loyalty.This store makes various efforts to improve its tie with regular customers.This store really cares about keeping regular customers.

As a regular customer, I have a high-quality relationship with this store.I am happy with the efforts this store is making towards regular customers like me.I am satisfied with the relationship I have with this store.

This store gives me a feeling of trust.I have trust in tbis store.This store gives me a trustworthy impression.


APPENDIXContinued

Construct Measures

Relationship I am willing 'lo go the extra mile" to remain a customer of this store,commitment I feel loyal towards this store.

Even if this store would be more difficult to reach, I would still keep buying there.

What percentage of your total expenditures for clothing do you spend in this store?Of the 10 times you select a store to buy clothes at, how many times do you select this store?How often do you buy clothes in this store compared to other stores where you buy clothes?

Generally, I am someone who finds it important what clothes he or she buys.Generally, I am someone who is interested in the kind of clothing he or she buys.Generally, I am someone for whom it means a lot what clothes be or she buys.

Generally, I am someone who likes to be a regular customer of an apparel store.Generally, I am someone who wants to be a steady customer of the same apparel store.Generally, I am someone who is willing to "to go the extra mile" to buy at the same apparel store.

Notes: The items formulated in the Appendix were based on the apparei samples. In the food samples, the term "apparel store" was replacedby "supermarket." All are seven-point scales with "strongly disagree" and "strongly agree" as the anchors.

Behavioral loyalty

Product categoryinvolvement

Consumer relationshipproneness

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