An empirical investigationof customer dependence

in interpersonal buyer-sellerrelationshipsKareem Abdul Waheed

Institute of Management Technology,Dubai International Academic City, Dubai, UAE, and

Sanjaya S. GaurAUT Business School, Auckland University of Technology,

Auckland, New Zealand

Abstract

Purpose – In the current highly competitive marketing environment, there are few situationsin which customers attempt to build and maintain relationships with marketers. In large-formatretail situations, customers maintain a non-personal association with the store and personalrelationships with salespersons. By contrast, many customers in developing countries such as Indiabuild and maintain long-term relationships directly with the small-scale retailers, who happen tobe the owners as well as the salespersons of the store. The purpose of this paper is to focuson customer dependence on the retailer, a rare phenomenon which is evident in rural areas of Indiaeven today.

Design/methodology/approach – The paper is based on an empirical study of a buyer-sellerrelationship between a farmer and a chemical fertilizer retailer, which is a common interpersonalbusiness constellation in India.

Findings – The paper identifies the determinants of customer dependence as customer perceivedmarket uncertainty, product importance and product familiarity. The paper also explains the positiveeffects of customer dependence on customer trust.

Originality/value – Traditionally, customer dependence is viewed as a structural constraint inrelationship outcomes. The effect of customer dependence on power, control and opportunistic behaviorin the buyer-seller relationship context is well researched. This paper applies an interpersonaltrust-development perspective and views customer dependence as a positive relationship construct andfills an apparent gap in research on customer dependence in the context of the interpersonal buyer-sellerrelationship.

Keywords India, Rural areas, Buyer-seller relationships, Customer dependence, Customer trust

Paper type Research paper

IntroductionIn the current highly competitive marketing environment, there are few situations inwhich customers attempt to build and maintain relationships with marketers.In large-format retail situations, customers maintain a non-personal association withthe store and personal relationships with salespersons. By contrast, many customers indeveloping countries like India build and maintain long-term relationships

The current issue and full text archive of this journal is available at

www.emeraldinsight.com/1355-5855.htm

The authors are grateful to Dr Brian Bloch for his comprehensive editing of the manuscript.

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Received 26 February 2011Accepted 18 August 2011

Asia Pacific Journal of Marketing andLogisticsVol. 24 No. 1, 2012pp. 102-124q Emerald Group Publishing Limited1355-5855DOI 10.1108/13555851211192722

directly with the small-scale retailers, who happen to be the owners as well as thesalespersons of the store.

The relationship marketing research extensively covers such variables as customerdependence, satisfaction, trust and loyalty, which play an important role in building andmaintaining long-term relationships (Anderson and Narus, 1990; Morgan and Hunt,1994; Andaleeb, 1995; Rajaobelina and Bergeron, 2009; Kassim and Abdullah, 2010).With regard to research in the retail domain, there is a focus on customer satisfaction,trust, loyalty and emotional attachment (Westbrook, 1981; Macintosh and Lockshin,1997; Reynolds and Beaty, 1999; Vlachos et al., 2010).

In this paper, we focus on customer dependence on the retailer, a rare phenomenonwhich is evident in rural areas of India even today. Dependence is an important initiatingvariable for buyer-seller relationship. Dependence has been studied in the marketingchannel and industrial buying literature (Andaleeb, 1995, 1996; Lusch and Brown, 1996;Gassenheimer et al., 1996, 1998; Joshi and Arnold, 1998) with an interorganizationalrelationship perspective. Retailing in India is still dominated by an interpersonal-basedbuyer-seller relationship. To the best of our knowledge, no study in the field hasresearched customer dependence from an interpersonal buyer-seller relationshipperspective. We attempt to identify the determinants of customer dependence and studythe effects on customer trust both through the literature and conceptual modeldevelopment. We conducted a survey to study customer dependence in the relationshipbetween a farmer and a chemical fertilizer retailer, which is an example of a typicalinterpersonal buyer-seller relationship in Indian context.

Literature reviewThe extant literature suggests that dependence of one party on another provides powerto the less dependent party (Anderson and Narus, 1984; Dwyer et al., 1987; Ganesan,1994). There is broader research on the negative aspects of dependence for long-termrelationships ( Johnson, 1999). The negative aspects of dependence are evident when thepowerful party tends to enforce a control mechanism then the dependent party tends tobehave opportunistically. This phenomenon ultimately discourages parties frommaintaining long-term relationships (Andaleeb, 1995, 1996; Monczka et al., 1995). It istherefore useful to understand coordinative behavior between buyer and seller subject toasymmetric dependence.

Emerson (1962) developed dependence theory in an interpersonal dependenceperspective. According to this theory, dependence is defined as the degree of dependenceof one individual on another as a multiplicative function of two factors: the value ofthe goal that the other individual mediates and the perceived availability of alternativeavenues for achieving the goal. In other words, the dependence of an individual on asource person is directly related to the rewards obtained from that source and inverselyrelated to the number of alternative sources of those rewards.

From an interorganizational perspective (Pfeffer and Salancik, 1978, p. 51),dependence is defined as “the product of importance of a given input or output to theorganization and the extent to which it is controlled by relatively few organizations”.Pfeffer and Salancik (1978) further describe dependency as a measure of the potency ofthe external organizations or groups in a given organizational environment, and of theextent to which organizations must be taken into account, perceived as important andconsidered in organizational decision making. The pressure on organizations to comply

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with external demands is especially significant when the level of dependency is high.Pfeffer and Salancik (1978) also mention three critical factors which determine thedependence of one organization on another:

(1) the extent to which the interest group has discretion over resource allocation and use;

(2) the extent to which they are limited by the availability of alternatives, or the extentof control over the resource by the interest group; and

(3) the essentiality of the resource, the extent to which the organizations require itfor continued operation and survival.

Frooman (1999) describes resource essentiality as a function of two factors:

(1) the relative magnitude of exchange; and

(2) criticality.

The percentage of inputs to outputs accounted for by an exchange determines therelative magnitude of the exchange. Hence, one organization depends on another if alarge proportion of its inputs are supplied by the latter. The criticality of a resource has todo with whether an organization can exist without it. Therefore, for an organization to beeffective and increase its probability of survival and success, it has to deal withinfluences from external actors. An organization can undertake three types of action. Thefirst is to comply with such influence. The second response is to evade it, and the final isto alter external demands by modifying its relationships with external actors. Accordingto the theory, organizations take actions to reduce the risk caused by uncertainty ininterdependencies, by modifying their relationships with the external environment(Stern and Reve, 1980).

Resource dependence theory (RDT) has been applied in the marketing field, mostly inthe marketing channel literature, in order to understand the effects of dependencebetween the channel partners (Cronin et al., 1994; Gassenheimer and Ramsey, 1994;Andaleeb, 1996). RDT has also been applied in industrial buying situations (Biong andSelnes, 1995; Joshi and Arnold, 1998; Handfield and Bechtel, 2002). RDT has beenapplied both to marketing channels and industrial buying situations, in aninterorganizational perspective of dependence.

De Wulf (1999) questions the use of RDT in explaining long-term exchangerelationships resulting from coordinative behavior based on trust. Trust is a basiccomponent in any human interaction (Gambetta, 1988). In marketing, trust is studied ininterpersonal as well as interorganizational-based buyer-seller relationships in variouscontexts (Morgan and Hunt, 1994; Dwyer et al., 1987; Macintosh and Lockshin, 1997;Kennedy et al., 2001; Dagger and O’Brien, 2010). Customer dependence and trust areclosely related constructs (Andaleeb, 1995, 1996). There is a dearth of literature on thelink between customer dependence and trust. We attempt to apply an interpersonal trustdevelopment perspective (Lewicki and Bunker, 1996) to the effects of customerdependence in interpersonal buyer-seller relationships.

Several empirical studies identify a strong positive association between dependenceand commitment (Goodman and Dion, 2001; Gutierrez et al., 2004; Sriram et al., 1992;Iacobucci and Ostrom, 1996). Hence, the focus of the present study is on direct effectof dependence on trust. However, we do not consider the effect of dependence oncommitment, as this issue has already been studied comprehensively.

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Customer dependence in interpersonal buyer-seller relationshipsFigure 1 shows the proposed conceptual model of determinants of customer dependenceand both direct and indirect effects of customer dependence on customer trust ininterpersonal buyer-seller relationships. Customer-perceived product familiarity,product importance and supply uncertainty are expected to impact on customerdependence on the seller. Customer dependence should impact directly on customer trust.

Determinants of customer dependence and customer trustProduct familiarity. This concept refers to the degree of knowledge of a particularproduct or service (Alonso, 2000; Tuu and Ottar, 2009). Increased product knowledgeincreases the expertise of the customer (Alba and Hutchinson, 1987). Knowledgeablecustomers consider the purchase decision making less complex compared to lessknowledgeable (Dellaert and Stremersch, 2005). Product knowledge provides confidenceto the customers and it acts as a precursor for expert power (Chinomona and Pretorius,2011). There are numerous studies in distribution channel relationships area thatsuggest supplier’s expert power enables the supplier to infuse control mechanism in anon-coercive way and involve the customer to be non-coercively committed to therelationship and exhibit cooperative behavior (Harsini, 2001; Sahadev, 2005;Zhao et al., 2008; Lindblom et al., 2009). Because, customers perceive high risk whenthey lack product/service expertise, they tend to depend on a particular seller or serviceprovider (Bendapudi and Berry, 1997; Schultze, 2003). Also, as argued by Chakrabartyet al. (2010), highly dependent customers need the products/services of the sellingorganization and the knowledge and expertise of salespeople. Hence, the supplier’sexpert power necessitates the customer to depend on the supplier. When customers gainsuch an expert power which supplier possesses, they need not follow the controlmechanism of the supplier and be not dependent on the supplier. Furthermore, expertpower enables customers to switch easily between suppliers as their perceived switchingcosts is reduced, especially their procedural costs of switching (Burnham et al., 2003).

There are a couple of empirical findings that support our above argument. Selnes andHansen (2001) argued that the frequent use of self service (which is commonly used byinformed customers) by customers reduces the perceived utilitarian value of serviceperson and found that it reduces the social bonding between the customer and the serviceperson. Capraro et al. (2003) examined the relationship between level of knowledge aboutalternatives and defection in the context of actual health insurance choices and foundthat the level of objective and subjective knowledge about alternatives has a direct effecton likelihood of defection – above and beyond satisfaction level. Hence:

Figure 1.Conceptual model of

customer dependencefor rural traders

+

–

+

Productfamiliarity

Supplyuncertainty

Productimportance

+ Customertrust

Customerdependence

–

+

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H1a. The greater the level of customer product familiarity; the lower the level ofcustomer dependence on the retailer.

As mentioned in the above paragraph, product familiarity refers to the degree ofknowledge of a particular product or service (Alonso, 2000; Tuu and Ottar, 2009).Knowledge reduces perceived risk, improves the confidence and provides expert powerto the power holder (Reynolds and Beatty, 1999; Bendapudi and Berry, 1997;Schultze, 2003). Expert power reduces conflict and enhances the satisfaction betweenthe exchange partners (Lee, 2001). One party’s expert power leads the other party totrust the former. Extant literature in marketing channels also suggests that the supplierexpert power positively impacts customer trust (Harsini, 2001; Sahadev, 2005;Chinmona and Pretorius, 2011). In retailing context, Busch and Wilson (1976) conductedan experimental analysis of salesman expert and referent social power on customertrust in the salesman and found that the customers perceive both sources of power to betrustworthy. Also, they found that the expert power was more important than referentpower in affecting customer trust. When the customer acquires that expertise which thesalesman possesses, then the situation becomes different. Bell and Eisingerich (2007)argued that the customer investment expertise will reduce their loyalty to the financialservice provider (although they did not find empirical support for their argument).

If a customer trusts a trader solely regarding the task of the trader, it is considered asa low degree of trust (Kao, 1998). When the customer is familiar with the task that thetrader is performing for him, it is logical to conclude that the former need not trust thelater. There are divergent empirical findings on this issue. Coulter and Coulter (2003)found that customer knowledge/familiarity acted as a negative moderator on the impactof perceived service person “personality related” characteristics (e.g. empathy) oncustomer trust. A negative impact of product familiarity on trust was tested empiricallyin a developing country context by Andaleeb and Anwar (1996), who found anon-significant relationship. However, a research from a developed country by Kennedyet al. (2001) yielded a significant negative relationship between product familiarity andtrust in the salesperson, which suggests the need for further investigation. Hence:

H1b. Increased customer product familiarity is associated with lower levels ofcustomer trust in retailers.

Product importance. Bloch and Richins (1983, p. 71) define perceived product importanceas, “the extent to which a consumer links a product to salient, enduring orsituation-specific goals”. Product importance is derived from the product characteristics,consumer characteristics and purchase situation (Bloch and Richins, 1983). If the productis perceived to be important to customer goals, risk perceived by the customer will behigh (McQuiston, 1989). In such situations, customers always try to reduce the perceivedrisk, tending to acquire more information about the availability of alternatives. If thereare alternatives available, they would be in a more powerful and comfortable positionthan the suppliers. Otherwise, customers have to depend on the supplier. Customerdependence on the supplier is one way by which the customer attempts to reduceperceived risk (Pires and Stanton, 2005). Customers need to depend on the supplier whenthey perceive their product purchase decisions to be important. Hence:

H2a. The greater the perceived importance of the product, the greater the customerdependence on the retailer.

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Product importance is the perceived significance of the buying decision in terms of thesize of the purchase and/or the potential impact of the purchase on the buyer(Kool et al., 1997). Shepherd and Zacharakis (2003, p. 155) argued that “if the purchaseprice represents a significant amount of the buyer’s income and/or represents anemotional decision, then the importance placed on the product is high”. It also increasesthe expectations of the customers (Patterson et al., 1997). Conceptually, productimportance refers to the perceived consequences of making the wrong decision anddetermines the amount of time the buyer allocates to the purchase decision. The moreimportant the purchase, the greater the perceived risk of the purchase decision(McQuiston, 1989). Hence, as a risk reduction mechanism, customers increaseinformation acquisition behavior ( Jacoby et al., 1978) and improve informationexchanges, operational linkages (Lichtenthal and Tellefsen, 2001; Cannon and PerraultJr, 1999; Batt, 2000; Metcalf and Frear, 1993), interfirm cooperation and social exchanges(Lichtenthal and Tellefsen, 2001; Metcalf and Frear, 1993) with the supplier when theyperceive the product to be important for their business. When customers perceive thebuying decision of a product/service to be important, Patterson et al. (1997, p. 8) arguethat, “then to reduce dissonance (e.g. we chose the supplier who performed poorly),the customer will, all things being equal, tend to perceive the performance of the suppliermore positively”. Patterson et al. (1997) also empirically found that the perceived productimportance leads to higher perceptions of performance. It means that when there isgreater perceived product importance, customers tend to perceive positive about thesupplier by developing collaborative relationships (Cannon and Perrault Jr, 1999).

Furthermore, Cannon and Homburg (2001) found that the perceived productimportance increases their intention to expand purchases from the current supplier.Empirically, Batt (2000) found a positive relationship between the importance ofpurchasing seed and farmer trust in their potato seed suppliers. There are someempirical findings from another related concept to product importance namely, productinvolvement. When customers perceive certain products or services to be important,they place high purchase involvement on those products or services (Beatty et al., 1988;Mittal, 1989). Bloch and Richins (1983, p. 73) consider product involvement, “as themotivational state that results from the stimulus of product importance perceptions”.Kinard and Capella (2006, p. 361) found that high involvement consumers perceiverelational benefits from a service provider. In their research, the relational benefitsare categorized as confidence, social and special treatment. They also argued that “theconfidence benefits reduce anxiety levels associated with a service offering, increaseperceived trust in the provider, diminish the perception of risk, and enhance knowledgeof service expectations”. Similarly, Liang and Wang (2008) also found that a higher levelof product involvement leads to a higher level of trust and commitment. Hence:

H2b. Customer trust in retailers is positively associated with the perceivedimportance of the product.

Supply uncertainty. Uncertainty is defined as unanticipated change in the circumstancessurrounding an exchange (Noordewier et al., 1990; Jean et al., 2010) and is a basicrequirement for the successful relationship performance between buyer and seller(Ambrose et al., 2010). Uncertainty in the input market is concerned with the availabilityof adequate and stable input supplies and is a perception the customer holds beforemaking the purchase decision. Supply uncertainty can act as an exit barrier

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in relationships with suppliers, if there is perceived uncertainty about the availability ofalternative supplies and suppliers. If alternative suppliers are uncertain or unavailable,customers are normally motivated to continue established supplier relationships owingto difficulties in replacing existing suppliers in input markets. This exit barrier in thecustomer relationship with the supplier increases customer dependence on the supplier.

According to Williamson’s (1975) seminal work on transaction costs analysis (TCA)principle, if the input market is really uncertain, it increases transaction costs of thecustomers. These transaction costs normally happen in two ways namely, deterrence-and compliance-based transaction costs. The customer incurs deterrence-basedtransaction cost due to non-maintenance of relationship with the supplier whencustomer perceives the availability of input supplies and suppliers as uncertain. It meansthat the customer may not be able to continue its production in a smooth way and toavoid such a situation, the customer develops alternative transaction mechanism(increased opportunism) which also involves search cost. Also, customer might havedeveloped idiosyncratic investments (asset specificity) with the focal supplier’s inputand its processes ( Joshi and Stump, 1999). If customer moves out of the relationship,it leads to the loss of earlier investments specific to the relationship. In order to reducesuch cost, customers need to build and maintain long-term relationship with the supplier(Williamson, 1975). Building and maintaining long-term relationships (vertical relationsand reduced opportunism) also involves transaction cost which is nothingbut compliance-based transaction cost. Customers usually evaluate deterrence- andcompliance-based transaction costs. If customers opt for deterrence-based transactioncost, they do not depend on the focal suppliers as they do not mind the expenses infinding alternative supplier and loss of idiosyncratic investments when input marketis uncertain. However, if they opt for compliance-based transaction cost, it leads todependence on suppliers as this dependence is directly proportional to the levelof difficulty faced in gaining access to alternative sources of valued outcomes (Andersonand Narus, 1984, 1990). In practice, customer dependence is a prerequisite for attempts tobuild long-term relationships with suppliers.

There are controversial empirical findings on the effects of uncertainty on verticalrelations (Anderson and Schmittlein, 1984) as implied from Williamson’s framework,especially on interaction effects of asset specificity and uncertainty (Rindfleisch andHeide, 1996; David and Han, 2004). However, our research focuses on the main effect ofuncertainty on vertical relations. Rindfleisch and Heide (1996, p. 49) who critiqued TCAcontributions state that:

[. . .] these main effects suggest that the problem created by environmental uncertainty ishandled more efficiently by creating a governance structure that permits adaptation within anongoing relationship, rather than by switching to a new partner if changes need to be made.

We contend that the customer dependence on seller is one form of such “adaptation”mentioned above. Hence:

H3. The greater the level of supply uncertainty perceived by the customer, thegreater the customer dependence on the retailer.

Effect of customer dependence on customer trustResearchers such as Andaleeb (1995) on marketing channel relations, and Handfield andBechtel (2002) on industrial buyer – seller relations attempt to separate the effects

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of dependence from those of trust. Customer (economic) dependence (measured bysupplier assistance and revenue lost) is found to exert a significant positive effect oncustomer compliance (Gassenheimer and Calantone, 1994). Andaleeb (1995) questionsthe assumption of implicit trust in dependence-based relationships between the partiesand entails the possibility that the dependent party does not trust the other party.He examines how the behavioral intentions of channel members (such as the intention tocooperate, control and influence) are likely to be moderated by trust perceptions whendependence is high or low. The results indicate the important role of trust in explainingintentions to cooperate, control and influence in a buyer-seller dyad. Dependence wasalso found to influence intent to cooperate and willingness to adopt a strong stance,but had no effect on intentions to exert control.

A widely prevailing argument suggests that when the customer is dependent on thesupplier, the supplier can exploit its market power, and customers will be less able toobtain competitive price quotes to negotiate (Monczka et al., 1995). In addition, Handfieldand Bechtel (2002) argue that customers may trust a supplier when they have more thanone (multiple sourcing), but trust another supplier less, simply because they feelvulnerable, due to the fact that the supplier is the only source in the market for a uniqueproduct or service. This argument led Handfield and Bechtel (2002) to test the hypothesisthat increased levels of perceived customer dependence on the supplier have a negativeimpact on customer trust, which was however, not empirically supported in their study.

The interpersonal trust development perspective of Lewicki and Bunker (1996) isadopted in this paper in order to justify the hypothesis that customer dependence on thesupplier leads to customer trust. Lewicki and Bunker (1996) posit three stages of trustdevelopment in interpersonal relationships in a professional context: calculus-basedtrust (CBT), knowledge-based trust (KBT), and identification-based trust (IBT).According to them, interpersonal trust develops gradually as the parties move from onestage to another, evolving and changing over time. Trust is created as CBT develops;then, as the parties get to know one another better, the relationship may move on to theKBT stage. If only an arm’s length transaction is required, the relationship may notmove beyond CBT. A similar process is involved in the movement from KBT to IBT.

At the first stage of interpersonal trust development, CBT, interpersonal trust is an“ongoing, market-oriented, economic calculation whose value is derived by comparing theoutcomes resulting from creating and sustaining the relationship to the costsof maintaining or severing it” (Lewicki and Bunker, 1996, p. 145). We argue that bydefinition, both interpersonal dependence and CBT entail the same individualpsychological process, as both involve a comparison of the value of outcomes(Emerson, 1962). In other words, interpersonal dependence and CBT are one and the samething. Hence, as the relationship experience of dependence-based relations is positive, itwould lead to the next stages of trust development, KBT and the IBT. KBT relies uponinformation developed over time, as the parties get to know one another. Increasedinformation enhances the predictability of the other party, which contributes to thedevelopment of interpersonal trust (Shapiro et al., 1992). IBT is based on an understandingof the other’s needs and desires. Here, parties are confident that their interests will beprotected, and little or no monitoring of the other is required (Shapiro et al., 1992).

This contention is supported by Andaleeb (1995, p. 159), “with the initiation ofexchange, dependence relations are expected to result”. Dependence often establishesa need to build relationships. A recent study by Ferrer et al. (2010) found that

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the interdependency in inter-firm relationships have a significant positive influenceon the formation of both arm’s length and cooperative relationships. In theserelationships trust increases the merits of continuing them (Bradach and Eccles, 1989).Stevenson (1997) found a significant positive relationship between the extent ofexperience with a negotiation partner and the level of interpersonal trust, and a strongerpositive relationship between extent of experience and extent of relationship, when thequality of experience increases. We contend that even when the buyers are in dependentposition, the extent and quality of experience gained during the interactions could lead topositive effects on trust. Hence:

H4. The greater the customer dependence on the retailer, more the customer truststhe retailer.

MethodologySampleIn India, interpersonal buyer-seller relationships could be found in consumer-retailerrelationships where the retailer is the owner as well as the salesperson of the shop. In thisstudy, we considered the farmer (customer) and the rural-based chemical fertilizerretailer (seller) relationship. India is an agriculture-based country and it has 29 states.Every state has its due share in agriculture. Each state has a distinct language andculture. Farmers of Tamil Nadu state were selected for this study primarily due to thelead author’s familiarity with the language, customs, practices and geography of theregion. The study required the author to travel across selected villages in person andmeet the farmers for personal interviews.

The study was conducted with respect to farmers of Madurai, Pudukottai and Trichydistricts of Tamil Nadu state, India. These districts have a high per hectare chemicalfertilizer consumption. One taluk[1] from each of the above districts with high fertilizerconsumption was selected. Ten villages were selected randomly from each of the taluks.Lists of farmers were gathered from the Village Administrative Officer of the village inquestion. The lists from all 30 villages contained a population size of 3,119 farmers.A total sample size of 300 was planned to enable the statistical analysis required for thisstudy. The number of farmers from each village was specified in proportion to the totalnumber of farmers in the lists. The farmers were selected randomly from each village.If the selected farmer was not available, another was chosen randomly from the list, andso that the total number of farmers from each village was maintained as planned.

A questionnaire was prepared taking into account all the relevant measures anddemographics. The questionnaire was first translated into Tamil and then back translatedto English with the help of English and Tamil language translators (Brislin, 1980;McGorry, 2000). The earlier version of the English questionnaire was compared to theback-translated questionnaire and inconsistencies removed in consultation with thetranslators (Brislin, 1980; McGorry, 2000). The lead author of this article personally visitedall these villages and the questionnaire was filled by the lead author himself whileinterviewing the respondents. Due care was given to avoid response bias whileinterviewing the farmers as the interviews were conducted at the farmer’s home or in hisfarm. Either they were alone or with their family during the interview. We avoidedthe situation where other farmers were present during the interview as they could getinfluenced to provide socially acceptable responses. About 16 percent (48/300) of theselected farmers from the initial list were not available for the interviews in the village

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due to their travel commitments and they were replaced by other farmers randomlyselected from the complete farmer list of the respective village. Among the selectedfarmers for replacement 12.5 percent (5/48) were also not available and they were alsoreplaced by other farmers chosen from the farmer list and the total sample size of 300 wasmaintained.

All the farmers included in this survey had purchased fertilizer either from retailerslocated in their villages or in nearby villages or towns. The demographic characteristicsof respondents are shown in Table I. Approximately 97 percent of the respondents weremale. This is primarily due to the fact that the land holding pattern and farm managementpractices are still considered to be male activities in the rural areas of India. The age of therespondents is well distributed among all age groups. About 2 percent of the respondentshad no formal education at all and approximately only 50 percent of the respondents had

Frequency Percent

GenderMale 292 97.33Female 8 2.67AgeUnder 25 10 3.3325-30 30 10.0031-35 30 10.0036-40 44 14.6741-45 41 13.6746-50 32 10.6751-55 36 12.0056-60 23 7.6761-65 23 7.67Over 65 31 10.33EducationNo formal education 6 2.00Up to elementary school 49 16.33Up to high school 153 51.00Up to higher secondary school 45 15.00Up to college 47 15.67Marital statusMarried 274 91.33Unmarried 26 8.67Family sizeUnder five 59 19.67Five to nine 199 66.33Ten-13 38 12.6714 and above 4 1.33Annual incomea

Under Rs 35,000 148 49.33Rs 35,000-69,999 86 28.67Rs 70,000-1,04,999 45 15.00Rs 1,05,000-1,39,999 2 0.67Rs 1,40,000-1,74,999 7 2.33Rs 1,75,000 and above 12 4.00

Note: aOne American dollar ¼ 45.26 Indian rupees as on 26 February 2011

Table I.Characteristics of

respondents

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a high school education. In addition, 91 percent of the respondents were married, with66.33 percent living in a household comprising of five to nine members. Half therespondents had an annual income below Rs. 35,000 (approximately US$750).

Measurement scalesProduct familiarity. Most of the researchers conceptualized the construct expertise asone party’s perception of the other party’s expertise. For example, Chinomona andPretorius (2011) measured manufacturer’s perception of dealer’s expert power, Sahadev(2005) measured distributor’s perception of supplier expertise and Zhao et al. (2008)measured supplier’s perception of customer expert power. However, we conceptualizedproduct familiarity as customer’s perception about his or her own knowledge about theproduct which he or she intends to purchase from the retailer. Kennedy et al. (2001)measured buyers’ perception of their own knowledge about the product. Hence, buyerfamiliarity with the product was measured on a three-item, seven-point semanticdifferential scale from Kennedy et al. (2001). In their research, the scale yielded aCronbach a coefficient of 0.91. The scale was revised slightly to reflect the fertilizerpurchase situation.

Importance of the product. Cannon and Perrault Jr (1999) measured perceivedproduct importance in the context of manufacturing industry. Patterson et al. (1997)measured perceived product importance in the context of business to businessprofessional services. Batt (2000) measured farmer’s perceived product importance inseed potato purchases. We adapted Batt’s (2000) scale as it suited context of our study.This scale has two factors, namely supplier evaluation and economic consequences. Thefirst factor (supplier evaluation) suggested that farmers spend a considerable amount oftime making the purchase decision and that, despite the long-standing relationshipswhich often existed between seed suppliers and farmers, the farmers carefully evaluatedthe alternatives each time they purchased new seed. The supplier evaluation factoryielded a Cronbach a coefficient of 0.73. The second factor (economic consequences)dealt with the cost of purchasing the seed and the number of times the farmer chose tobuy the new seed from the supplier. This factor yielded a Cronbach’sa of 0.62. The scalewas revised to suit the study context.

Supply uncertainty. Ambrose et al. (2010) measured uncertainty by a four-item scalewhich was adapted from Gao et al. ’s (2005) scale in the context of supply chainrelationships. Batt (2000) measured uncertainty on a two-factor, five-item; stronglydisagree (1) to strongly agree (7) scale. The two factors were seed specifications and inputmarket uncertainty. The first factor of seed specifications was related to personalindecisiveness about the seed requirements. The second factor of input marketuncertainty had two items: price stability and supply stability. It is a two-item scale andyielded a Cronbach’s a of 0.89. We used Batt’s (2000) scale as it suited the context of ourstudy. We conceptualize supply uncertainty as unanticipated changes in the availabilityof an adequate and stable supply of inputs and hence used a single item related to thestability of supply. Previous researches also measured market uncertainty as a single-itemscale. For example, Anderson and Schmittlein (1984, p. 391) measured uncertainty asdifficulty of evaluating sales force performance in a single-item semantic differential scaleas, “It is very difficult to measure equitably the results of individual salespeople”.

Customer dependence. Dependence construct has been conceptualized in two ways,first, as a party’s perception of its own dependence on other party and second,

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the perception of other party’s dependence on them. Heide and John (1988)conceptualized distributors’ perception of their own dependence as potentialreplaceability of principal. Similarly, Andaleeb (1995, 1996) measured buyer’sperception of their own dependence on the seller. However, quite different from aboveauthors’ conceptualization, Carr et al. (2008) assessed customer’s perception of supplier’sdependence on them and Chakrabarty et al. (2010) measured customer dependence asperceived by salespersons.

We needed a scale to measure farmers’ perception of their own dependence onthe chemical fertilizer retailer. Very close to the context of our study, Batt (2000)measured farmer dependence on their potato seed suppliers which was developed fromthe following studies, Anderson and Narus (1990), Frazier et al. (1989), Heide andJohn (1988) and Ganesan (1994). Originally, the scale had three factors, namelyindependence, availability of alternatives and comparison of alternatives with six items,three items and one item, respectively. The reported Cronbach’sa for the factors such asindependence and availability of alternatives were 0.93 and 0.65, respectively. Thepresent study used Batt’s (2000) first factor namely, independence, which described howand despite the financial obligations between farmer and seed supplier, most farmerswere not unduly influenced by the demands imposed upon them by their seed supplier.The scale was revised to conform to the specific context of our study.

Customer trust. Morgan and Hunt (1994) measured retailers’ trust on their supplier.In an industrial purchasing context, Gao et al. (2005) assessed buyer trust andbuyer-perceived supplier trust adapted from previous studies (Doney and Cannon, 1997;Ganesan, 1994). In this study, Holden’s (1990) “sales trust” scale was used to assesscustomer trust in the retailer. Holden’s (1990) original scale, developed to assess trust inan industrial buyer-seller relationship has eight items and a reported Cronbach’s a of0.92. The same scale was also used by Kennedy et al. (2001) to assess trust in salespersonand has a reported Cronbach’s a of 0.97. The scale was again revised to conform to thepresent study.

Analysis and resultsMeasurement modelWe used AMOS 16.0 for the analysis. We first assessed the measurement model, followedby the structural model for the hypothesis testing, using the guidelines suggested byAnderson and Gerbing (1988). In this section, we first report the results of ourconfirmatory factor analysis (CFA) for all the measures in order to test their convergentvalidity. The product familiarity (three items) did not require any modification, as theirmeasurement model suggested a good fit with the data and reported significant factorloadings (product familiarity – x 2(1) ¼ 0.353, p ¼ 0.552, TLI ¼ 1.003, CFI ¼ 1,RMSEA ¼ 0.000; composite reliability: 0.905).

Other measures such as product importance, dependence and trust required somerefinement, due to weak factor loadings and poor fit indexes. We used a minimum cut offloading of 0.6 for all the measures. Following this procedure, we removed some of theitems for product importance, dependence and trust measures. The remaining itemsprovided a better fit and strong factor loadings as well (product importance –x 2(1) ¼ 0.208, p ¼ 0.649, TLI ¼ 1.007, CFI ¼ 1, RMSEA ¼ 0.0; trust – x 2 (1) ¼ 3.371,p ¼ 0.066, TLI ¼ 0.983, CFI ¼ 0.994, RMSEA ¼ 0.089; dependence – x 2 (1) ¼ 0.56,p ¼ 0.454, TLI ¼ 1.004, CFI ¼ 1, RMSEA ¼ 0.0). All these measures had a good

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composite reliability (product importance ¼ 0.729; trust ¼ 0.865; dependence ¼ 0.818).Table II summarizes the results of the CFA for all the individual measurement models.All the measurement scales related to the study are mentioned in the Appendix.

Once the convergent validity for all the measures had been established, we proceededto the next step of testing the discriminant validity with CFA among the relatedmeasures. The results are shown in Table III. The measurement models for all the pairshad a good fit with the data. Furthermore, we used a confidence interval test to check thecorrelation among the measures.

Structural modelThe full structural and measurement model analysis was performed to test the fit of ourproposed theoretical model with the data. The results are provided in Table IV. Fitindexes such as the x 2 fit index, TFI, CLI and RMSEA suggested a good fit with the data(x 2(50) ¼ 68.148, p ¼ 0.045, TLI ¼ 0.984, CFI ¼ 0.988, RMSEA ¼ 0.035). Overall, thetheoretical model was found to have a satisfactory fit with the data. We now turn ourattention to the hypothesis testing, Table IV the results of which are presented inTable IV. The results indicate that customer dependence is influenced positively

Construct /items Std. Reg. Coeff. x 2 p dF TLI CFI RMSEA Comp. reliability

Product familiarity 0.353 0.552 1 1.003 1 0 0.905pf1 0.915pf2 0.817pf3 0.881

Dependence 0.56 0.454 1 1.004 1 0 0.818de1 0.818de2 0.744de3 0.76

Trust 3.371 0.066 1 0.983 0.994 0.089 0.865tr1 0.795tr2 0.859tr3 0.82

Product importance 0.208 0.649 1 1.007 1 0 0.729pi1 0.761pi2 0.754

Table II.CFA resultsfor all the measures

95% confidenceinterval

Correlations between Estimate SE Lower Upper x2 p dF TLI CFI RMSEA

DE $ PF 20.125 0.195 20.515 0.265 3.928 0.864 8 1.01 1 0DE $ PI 20.014 0.144 20.302 0.274 17.357 0.004 5 0.94 0.97 0.091DE $ TR 0.112 0.189 20.266 0.49 15.302 0.054 8 0.98 0.99 0.055TR $ PI 0.556 0.155 0.246 0.866 1.794 0.877 5 1.01 1 0TR $ PF 20.032 0.18 20.392 0.328 10.589 0.226 8 1 1 0.033PF $ PI 20.008 0.139 20.286 0.27 1.862 0.868 5 1.01 1 0

Notes: TR, trust; PF, product familiarity; DE, dependence; PI, product importance

Table III.Assessment ofdiscriminant validityamong selected pairsof constructs

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by supply uncertainty (standardized coefficient ¼ 0.277; critical ratio ¼ 4.459) with ap-value less than 0.01 and negatively influenced by product familiarity (standardizedcoefficient ¼ 20.133; critical ratio ¼ 22.066) with a p-value less than 0.05.Furthermore, product importance was found to have a significant positive associationwith customer trust (standardized coefficient ¼ 0.559; critical ratio ¼ 7.447) with ap-value less than 0.01. The main contention of our study, that of customer dependence(standardized coefficient ¼ 0.120; critical ratio ¼ 1.898) was found to have significantpositive association with trust, with a p-value of 0.058.

General discussion and implicationsThere is well-documented research suggesting the importance of customer dependencefor long-term buyer-seller relationships. However, the limited research in the marketingdomain has considered the phenomenon of customer dependence in the marketplace.Our study conceptualized and empirically tested the determinants of customerdependence and its effects on customer trust.

Customer perceptions of supply uncertainty were empirically established as animportant determinant of customer dependence in buyer-seller relationships,specifically in the interpersonal relationship context. When customers perceive highsupply uncertainty, they attempt to adapt within an ongoing relationship (Rindfleischand Heide, 1996) which leads to their dependence on the retailers. Primarily, this findingconforms to the implications of Williamson’s TCA framework. Some researchers haveshown contradicting results of the impact of uncertainty on vertical integration orrelations (Harrison and Kelly, 2010; Leonidou et al., 2006). However, our result of thepositive impact of supply uncertainty on customer dependence could be one of thereasons for the previous research finding on buyer and seller cooperation duringuncertainty (Eriksson and Sharma, 2003).

Perceived product familiarity was found to have no impact on customer trust.We expected a negative impact of product familiarity on customer trust. Previousresearch on this issue also showed contradicting results. Kennedy et al. (2001) found

Path Hypo-thesesStandardized

estimatesCritical

ratio p-value

Product familiarity ! customerdependence H1a 20.133 22.066 0.039Product familiarity ! customer trust H1b 20.014 20.244 0.807Product importance ! customerdependence H2a 20.052 20.731 0.465Product importance ! customer trust H2b 0.559 7.447 0.000Supply uncertainty ! customerdependence H3 0.277 4.459 0.000Customer dependence ! customer trust H4 0.120 1.898 0.058x 2 68.148DF 50P 0.045TLI 0.984CFI 0.988RMSEA 0.035

Table IV.Summary of results for

the structural model

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a significant negative relationship while Andaleeb and Anwar (1996) found therelationship to be non-significant. However, we found that the perceived productfamiliarity to significantly reduce customer dependence on the seller. Retailers have beenprovided with information and training related to the products and their functionality bythe manufacturers which improves their product knowledge and gives expert power overtheir customers. Customers also look for such expertise from sellers to make an informedpurchase decision which consequently leads them to cooperate and be committed to therelationship with the sellers (Sahadev, 2005; Zhao et al., 2008). In contrast, whencustomers improve their familiarity with the product and possess such expert power(expertise), they do not depend on the sellers. This finding is important to the marketersand implies them to understand customer familiarity status. This could be performed bythe seller by knowing customer status in the “customer buying task continuum”(Hanson, 1979). According to the “buying task continuum”, in “new task buying”’customer lacks knowledge about the product, familiarity increases in “modified rebuy”and customer gets a great deal of experience and information in “straight rebuy” (Parkand Lessig, 1977; Hanson, 1979). This would possibly help the retailers to understandcustomer dependence level which could be used in their sales strategy formulation.

More product familiarity leads to lack of dependence on the retailer which meanscustomer would switch from one particular retailer to another when they are highlyfamiliar with the product. This does not mean that the retailers should not educate thecustomers about the product. It is always better for marketers to educate customers onthe functionality of their product as it improves customer satisfaction (Soderlund, 2002).Soderlund (2002, p. 861) found that “when service performance was high,high-familiarity customers expressed a higher level of satisfaction and behavioralintentions than did less familiar customers”. Furthermore, theoretically, our findingconforms with previous researches which were conducted on the similar lines by Selnesand Hansen (2001) and Capraro et al. (2003) and possibly provides the missing link intheir research as to why self-service reduces social bonding (Selnes and Hansen, 2001)and why knowledge about alternatives increases defection (Capraro et al., 2003).

Perceived product importance was found to have no impact on customer dependence,but it does exert a significant impact on customer trust. This finding implies that thecustomers are comfortable in being positive about the retailers and they expect higherperceptions of performance when they perceive the product to be important andconsequently manifest trust on the retailers rather than feel dependent on them(Patterson et al., 1997; Cannon and Perrault Jr, 1999). Theoretically, this findingcompliments similar researches conducted earlier (Batt, 2000; Liang and Wang, 2008).

Our main contention on the effect of customer dependence on customer trust was wellsupported ( p-value ¼ 0.058). Basically, this result emphasizes the relevance ofinterpersonal trust development perspective (Lewicki and Bunker, 1996) ininterpersonal-based buyer-seller relationships. We view the development of CBT as aprocess that leads the customer dependence. The possible subsequent interactionsbetween the buyer and seller add to mutual knowledge and positive experiences, whichmay lead to information symmetry. Such symmetry between the buyer and seller willevolve when the customer develops IBT in the seller. Such trust between buyer and sellerleads to joint goals, cooperative behavior, collective decision-making and collectiveefforts. Hence, this process negates the negative consequences of customer dependencein buyer-seller relationships.

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Morgan and Hunt (1994, p. 33) in their seminal article on “commitment-trust theory ofrelationship marketing” acknowledged the importance of power and resultingdependence for deriving partner’s compliance and suggested extending their modelby including power as one variable that leads to “sick relationships”. They contendedthat continuing exercise of power and resulting dependence destroys trust andcommitment and results in relationship failures. This made researchers to viewdependence as having negative consequences in relationship marketing that results in“sick relationships” and motivated them to focus only on “healthy relationships”(Morgan and Hunt, 1994, p. 33) based constructs. Consequently, researchers neglecteddependence construct in the researches of relationship marketing except in a few(Cronin et al., 1994; Gassenheimer and Ramsey, 1994; Andaleeb, 1996). In contrast to thewidespread belief, we found that dependence did not yield negative consequences and infact improves customer trust which would further build “healthy relationships”.

Also, Morgan and Hunt (1994) in their original model found that the manufacturer’sless opportunistic behavior enhances retailer trust and in their extended modelhypothesized that the manufacturer’s power reduces retailer trust. Basically, theyconceptualized customer trust from the perspective of the perceived behavior aboutpartners (manufacturer/supplier/seller). However, we conceptualized customer trustfrom customer perspective, that is, how customer trust develops when customers feelthey are dependent. Future research could also focus on how customer trust developswhen customers perceive lack of power from their side and when they have lessopportunistic behavioral tendencies.

We derive several implications from this finding. Apart from providing high-qualityproducts and services and satisfying the customers (Kennedy et al., 2001), improvingcommunication and inculcating shared values (Morgan and Hunt, 1994) to developcustomer trust, the marketers should also look at building dependence negating itsnegative consequences as it eventually enhances trust. Marketers can nurturedependence mechanisms towards the goals of trust-based, long lasting relationships byproviding ongoing streams of suitable products, facilitating upgrades from one productto another or investing in capital, people, lasting assets and basic business procedures( Jackson, 1985). Further, this result could be applied to the case of inter-firm alliances.Both the alliance partners should invest in men, machine and money which wouldincrease mutual dependence and that would finally lead the alliance to a mutualtrust-based long-term success.

Even though, our study is greatly limited in scope as it was conducted in smallvillages of the Indian market, it implies that future research in relationship marketingshould basically change its mindset on dependence construct considering its positiveconsequence on trust development. Also, the future research should look into thecomparison of our findings with other cultures and contexts.

Note

1. A taluk is the main revenue, administrative and planning unit in the district.

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Appendix. Measurement scales after back translation (statements followed by (–)indicate reverse scoring)Product familiarity – seven-point semantic differential scale

. How familiar or unfamiliar were you with the chemical fertilizers you purchased, beforefirst visiting the current retailer’s shop? (completely familiar to completely unfamiliar) (– )

. How informed or uninformed were you about chemical fertilizers, prior to first visiting thecurrent retailer? (fully informed to not at all informed) (– )

. How knowledgeable or unknowledgeable were you about chemical fertilizers before firstvisiting the current retailer? (knew all to knew nothing at all) (– )

Supply uncertainty – seven-point scale: strongly disagree to strongly agreeThe supply of fertilizer is highly unstable.

Product importance – seven-point scale: strongly disagree to strongly agree. I buy fertilizer from my retailer at least once a year.. Fertilizer is the most significant component of my total production costs.

Customer dependence – seven-point scale: strongly disagree to strongly agree. My retailer decides what fertilizers I should use.. My retailer controls all the information pertaining to decision making in our relationship.. My retailer has all decision making power in our relationship.

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Customer trust – seven-point scale: strongly disagree to strongly agree. My retailer would not lie even if he could gain by doing so.. My retailer always maintains his principle of honesty and integrity even though his

business is not doing particularly well.. My retailer can be trusted.

About the authorsKareem Abdul Waheed is an Associate Professor of Marketing at the Institute of ManagementTechnology, Dubai, UAE. His research interests include buyer-seller relationship, societalmarketing and corporate social responsibility. He has published research articles in MeasuringBusiness Excellence, Supply Chain Management: An International Journal and CorporateEnvironmental Strategy: International Journal Corporate Sustainability. Kareem Abdul Waheedis the corresponding author and can be contacted at: waheed@imtdubai.ac.ae

Sanjaya S. Gaur is an Associate Professor of Sales & Marketing at AUT Business School,Auckland University of Technology, New Zealand. His research interests include buyer-sellerrelationships, relationship selling behaviour, small group buying behaviour, TBSS adoptionbehaviour, market orientation and its impact on firms in emerging economies. His research hasappeared in Asian Journal of Marketing, Asia Pacific Journal of Marketing and Logistics andCorporate Environmental Strategy: International Journal Corporate Sustainability.

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