Knowledge sharing behaviors ofindustrial salespeople

An integration of economic, socialpsychological, and sociological perspectives

Seigyoung AuhThunderbird School of Global Management, Glendale, Arizona, USA

Bulent MengucDepartment of Marketing, International Business, and Strategy,

Brock University, Ontario, Canada

Abstract

Purpose – This paper extends the sales literature by moving beyond salespeople’s role as knowledgegatherers to their role as knowledge sharers with personnel outside the sales unit. The aim is todevelop and test a conceptual model to establish how pay-for-performance (economic factor) affectsknowledge sharing behaviour under the contingency roles of coworker relationship quality (socialpsychological factor) and knowledge sharing norms (sociological factor).

Design/methodology/approach – Using the Dun & Bradstreet database, the authors collectedresponses from 374 salespeople in 51 Canadian industrial firms through an on-line survey. The authorsused hierarchical linear modeling (HLM) as multiple salespeople were nested within the organizationand the data were comprised of individual- and organizational-level constructs.

Findings – When there is misalignment between rewards and knowledge sharing behavior,motivational loss hampers knowledge sharing. However, when employees are provided with anenvironment that fosters high coworker relationship quality and consensual knowledge sharingnorms, the motivational loss resulting from the incongruence between pay-for-performance andknowledge sharing behavior is mitigated.

Research limitations/implications – Implications regarding how salespeople’s knowledgesharing contributes to relationship marketing along with practical ramifications for how salesmanagers can encourage knowledge sharing are discussed.

Originality/value – This study contributes to the sales literature (e.g. control, key accountmanagement, expanding role of sales) by testing a model that integrates different theoreticalperspectives to examine what types of control mechanisms and which combinations of these controlsaffect salespeople’s engagement in knowledge sharing behaviors.

Keywords Knowledge sharing behaviours, Pay-for-performance, Coworker relationship quality,Knowledge sharing norms, Knowledge sharing, Sales force, Canada, Interpersonal relations

Paper type Research paper

The role and job description of salespeople is changing from a transaction-basedshort-term focus to a relationship-based long term partnership emphasis (e.g. Davieset al., 2010; Flaherty and Pappas, 2009; Storbacka et al., 2009). Accordingly, knowledgeand relationship management capabilities have increasingly emerged as skill sets thatsalespeople need to possess to succeed in this newly competitive landscape (e.g. Arnettand Badrinarayanan, 2005). One key way that salespeople can contribute to thistransformation is to actively engage in knowledge sharing behaviors (KSBs hereafter)

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Received 8 April 2011Revised 1 September 2011

5 December 201113 December 2011

Accepted 21 December 2011

European Journal of MarketingVol. 47 No. 8, 2013

pp. 1333-1355q Emerald Group Publishing Limited

0309-0566DOI 10.1108/03090561311324354

with coworkers outside the sales unit. In fact, Flaherty and Pappas (2009, p. 806) positthat “salespeople are well-positioned to communicate strategic information generatedat the point of customer contact to key managers within the company. Verbeke et al.(2011) proposed that in today’s knowledge intensive economy, salespeople should takeon the role of “knowledge brokers” because salespeople are in a unique position toaccumulate and transfer knowledge with important stakeholders.

Despite existing research on salespeople as agents for knowledge accumulation(e.g. Liu and Comer, 2007), little empirical work has been conducted that examinessalespeople as knowledge disseminators (sharers) despite calls for research in the area(e.g. Arnett and Badrinarayanan, 2005). Consequently, our purpose is to address thisgap in the sales literature by examining different factors that motivate salespeople toengage in KSBs with people in functional areas outside of sales from an economic,social psychological, and social perspective, and using a multi-level modeling approachat the salesperson and organizational levels. To this end, we draw on organizationalcontrol theory, which is a meso-theory that captures economic, sociological, andsocio-psychological theories and models to explain how to motivate, govern, direct, andmaintain salesperson-organization and salesperson-coworker relationships.

In this study, KSBs pertain strictly to sharing customer-related knowledge, whichwill be discussed below. By coworkers outside the sales unit, we are referring topersonnel within the same organization who work in departments such as finance,product development, logistics, engineering, or R&D.

We posit three perspectives that can motivate KSBs. The first perspective isgrounded in economics. Reward systems that are aimed at influencing salespersons’KSBs through compensation are an example of an economic-based factor. The secondperspective is based on social psychology. An example of this perspective is coworkerrelationship quality, which is defined as the extent to which a salesperson perceives amutually beneficial and cooperative relationship with coworkers outside the sales unit.The third perspective is sociological. Knowledge sharing norms operate as an exampleof this perspective, where norms are defined as the informal, unwritten rules that aretypically initiated and adopted by group members to regulate and regularize theirKSBs (Feldman, 1984).

Although research into the role of interpersonal relationship qualities such as rapportand coworker collegiality (e.g. Lu et al., 2006), and knowledge sharing norms(e.g. Kankanhalli et al., 2005) exists, few studies have been conducted to ascertain theinfluence of rewards on KSBs, especially when the rewards are not directly tied to KSBs.Pay-for-performance, an individual incentive system in which a salesperson’s pay islinked to their sales volume (or quota), is a case in point (e.g. Joseph and Kalwani, 1998;Mallin and Pullins, 2009). KSBs are not usually part of formal compensation systems inthe majority of sales organizations, although exceptions do exist, including Fuji XeroxAustralia, which rewards salespeople for sharing knowledge (CEOforum.com.au, 2011).

Hence, the first goal of this study is to draw on the economics perspective andexamine the relationship between a formal reward system such as pay-for-performanceand KSBs, a relationship which has not been adequately addressed in the extantliterature.

Our use of pay-for-performance, coworker relationship quality, and norms tomotivate salespeople’s KSBs is consistent with control theory. The sales literature haslong advocated that various forms of control (formal and informal) are an effective way

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to ensure that salespeople’s behavior is aligned with the objective of the salesorganization (e.g. Anderson and Oliver, 1987; Cravens et al., 1993). In essence, coworkerrelationship quality and norms can be considered forms of informal and socialexchange-based control, while pay-for-performance can be regarded as a form offormal and economic exchange-based control.

Consequently, our second goal is, by drawing on these three controls (one formaland two informal), to develop and test a model that examines how KSBs are motivatedby the interplay between formal and informal controls. In other words, we examinehow the economic perspective is moderated by the social psychological andsociological perspectives. Our examination of the interaction among the controlsaddresses Jaworski’s (1988, p. 36) comment and suggestion that “[i]t is also clear thatcontrols interact – often counterbalancing one another [. . .] An important contributionof future research would be to consider the interaction of different types of controls.”The importance of control combinations has been echoed by previous researchers(Cravens et al., 2004; Jaworski et al., 1993). We expect the interaction effects to clarifyhow the economic perspective and the social psychological and/or sociologicalperspectives either complement or substitute for one another in affecting KSBs.

In summary, the purpose of this study is to investigate the conditions under whichindividual pay-for-performance plans influence salespeople’s KSBs, especially whenthere is no formal assessment and recognition of KSBs. We make the case that normsand high salesperson relationship quality with coworkers outside the sales unit act asinformal control systems that form a strong social context to mitigate the motivationallosses that may result from a pay-for-performance plan. We develop a multilevel modelby considering pay-for-performance plan and coworker relationship quality asindividual-level antecedents and the strength of norms as an organization-levelantecedent to KSBs.

Our study addresses salespeople’s KSBs for firms that do not include KSBs in theirformal job description. When there is no link between a pay-for-performance plan andKSBs, the effectiveness of the pay-for-performance plan may be limited to onlymotivating sales performance, while KSBs will be largely determined by salespeople’sintrinsic motivation. As Osterloh and Frey (2000, p. 538) point out, under someconditions the use of a pay-for-performance plan may even undermine intrinsicmotivation (i.e. crowding-out effect) and result in motivational losses. That is,pay-for-performance may discourage salespeople from engaging in activities such asKSBs that are not part of and not linked to a formal reward system.

In the following sections, we first introduce this study’s conceptual framework andhypotheses. We detail our research method and the data analysis techniques employed,then we follow with a discussion of our major findings and their implications for theoryand practice.

Theoretical backgroundKnowledge sharing behaviorsAs boundary spanners, salespeople have wide access to various sources of knowledge,ranging from customers and competitors to suppliers (Alavi and Leidner, 2001). In thisstudy, we focus on customer-related knowledge. We refer to customer-relatedknowledge as salespeople’s organized, structured, and validated information,expertise, beliefs, and understanding of different types of customers (Li and

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Calantone, 1998). Consequently, we define knowledge sharing behaviors as actionsundertaken by salespeople to disseminate customer-related knowledge to coworkersoutside the sales unit (Ipe, 2003; Yi, 2009).

Drawing on Jaworski and Kohli’s (1993) concept of knowledge dissemination, weidentify salespeople’s KSBs with coworkers outside the sales unit as follows:

. engaging in ‘hall talk’ and discussing customers;

. sharing and explaining new customer developments through written documents(i.e. reports, formal e-mails);

. circulating documents that provide customer information when requested;

. sharing customer satisfaction data on a regular basis;

. participating in interdepartmental meetings to discuss customers’ current andfuture needs; and

. informing the entire organization when something important happens regardinga major customer.

For example, one area that has been receiving increasing attention in recent years is theinterface between sales and marketing. To date, a well-defined body of research existson information sharing and coordination between sales and marketing (e.g. Homburgand Jensen, 2005; Homburg et al., 2008). Homburg and Jensen (2005) suggest twomechanisms, boundary-reducing and boundary-bridging, that can facilitate thecoordination and integration between sales and marketing. Homburg et al. (2008)reveal a taxonomy of clusters of sales and marketing interfaces based on severalfactors, one of which is information sharing. On the other hand, Homburg and Jensen(2007) also show that thought world differences between marketing and sales canhamper the quality of cooperation between the two functions. For example, theyconfirm that differences in customer (vs product) orientation and differences in shortterm (vs long term) orientation negatively affect the quality of cooperation betweensales and marketing. We believe that such thought world differences can adverselyaffect inter-functional relationship quality and ultimately impede KSBs.

Despite the contribution of the role of sales automation tools and CRM technology toknowledge management (e.g. Rangarajan et al., 2005), knowledge sharing is notconfined to electronic media alone. Our position is that knowledge sharing should bebroader to include not only technology-based media (e.g. e-mails), but alsohuman-to-human interaction such as face-to-face conversations, departmentalmeetings, and informal hall talk (e.g. Huber, 2001). That is, our notion of knowledgesharing encompasses more avenues for sharing knowledge and is not restricted totechnology-based mechanisms.

Social exchange perspectiveWe take a multi-disciplinary approach by drawing on perspectives advanced ineconomics, social psychology, and sociology. Our approach is also in line with twoschools of thought frequently mentioned in the knowledge management literature(e.g. Davenport and Prusak, 1998). For example, sociology and social psychology viewknowledge sharing as a social exchange (e.g. Constant et al., 1994; Wasko and Faraj,2005). In other words, knowledge sharing is largely a voluntary behavior (e.g. Davenportand Prusak, 1998), which may not be forced, only motivated (e.g. Huber, 2001).

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From a social psychology perspective, interpersonal relationships that are based onrapport, trust, and mutual reciprocity motivate KSBs and alleviate the fear ofknowledge exploitation. Further, from a sociology perspective, KSBs may be viewedfrom the normative conformity hypothesis (Knoke, 1990). That is, salespeople areinherently motivated to share their knowledge not because they are driven by fear ofpunishment, but because they desire to do so (Knoke, 1990).

Economic exchange perspectiveThe economic perspective posited by agency theory and organizational control theoryapproaches knowledge as a currency of economic exchange (Bergen et al., 1992).Because both employers and salespeople pursue their self-interests in an economicexchange (Eisenhardt, 1985), goal incongruence between the two parties(i.e. salespersons’ reluctance to share) is likely to cause information asymmetry andknowledge shirking, especially when it is hard to monitor salespersons’ behavior(e.g. Ramaswami, 2002). In attempts to minimize (or avoid) the possibility thatsalespersons’ goals may not always converge with those of the organization, firmsimplement formal control mechanisms (Ouchi, 1980).

Agency theory has been widely used by previous researchers to investigate theconditions under which the implementation of formal control systems results in desiredoutcomes (e.g. Anderson and Oliver, 1987; Cravens et al., 1993). One of the mainassumptions of agency theory is that the principal (i.e. the firm) and agents(i.e. salespeople) have goals that are misaligned, in that the firm essentially pursuesefficiency and wealth maximization whereas salespeople are self-interested, rational,and risk-averse and, therefore, pursue utility maximization (e.g. Anderson and Oliver,1987).

Integrative perspectiveThe two perspectives explained above have historically been developed andmaintained without much consideration given to an integration of the two. In anattempt to examine the interplay between the two perspectives, we draw onorganizational control theory. A control system may be defined as “an organization’sset of procedures for monitoring, directing, evaluating, and compensating itsemployees” (Anderson and Oliver, 1987, p. 76). Organizational control theory positstwo types of control mechanisms: formal and informal. Formal control systems havetheir rationale embedded in economics-based theories and models such as agencytheory and transaction cost theory. Formal control systems are “written,management-initiated mechanisms that influence the probability that employees orgroups will behave in ways that support the stated [. . .] objectives” ( Jaworski, 1988,p. 26). A pay-for-performance plan, one type of formal control system that we use inthis study, is aimed at motivating salespeople to maximize their sales performance(e.g. Deckop et al., 1999, p. 421).

Conversely, informal control systems are predominantly based on such theories associal exchange, social capital, and social information processing that are embedded insociology and social psychology literatures. Informal control systems refer to“unwritten, typically worker-initiated mechanisms that influence the behavior ofindividuals or groups” ( Jaworski, 1988, p. 26). In this study, we focus on social andcultural forms of informal control systems. Social control refers to “the prevailing

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social perspectives and patterns of interpersonal interactions within subgroups in thefirm” (Jaworski, 1988, p. 27). We use coworker relationship quality to capture thestrength of salespeople’s social ties with their coworkers outside the sales unit. Weidentify knowledge sharing norms as one type of cultural control system (Jaworski,1988).

Model and hypothesesOur conceptual model, which illustrates the relationships between constructs at theindividual and organizational level, is shown in Figure 1.

Pay-for-performancePay for performance is defined as “a reward practice that links one’s pay increase toone’s performance” (Chiang and Birtch, 2010, p. 632). Pay for performance systemsmay be implemented at three levels: individual, team, and across work units/teams(Bartol and Srivastava, 2002). Bonuses and commissions are the most common tools ofincentives employed at the individual and team level, whereas profit sharing, gainsharing, and stock ownership are commonly implemented tools of pay-for-performancesystems across work units/teams (Bartol and Srivastava, 2002).

At the individual level, a salesperson’s pay increase may be linked to him/herattaining either customer satisfaction or sales volume, or both (Sharma and Sarel,1995). As Widmier (2002) reports, “customer satisfaction incentives motivatesalespeople to be customer-oriented by rewarding them for increasing thesatisfaction of their customers whereas sales-based incentives motivate salespeopleto increase sales volume” (p. 610). However, Sharma and Sarel’s (1995) study finds,quite interestingly, that salespersons’ customer-oriented behaviors (in the form ofcustomer service response) diminish under conditions of mixed incentive systemswhere customer satisfaction and sales volume incentives are employed in combination.They explain the reason for this finding by stating, “salespeople may be more aware of

Figure 1.Conceptual model andhypothesized relationships

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the activities that will lead to a specific amount of dollars and be uncertain about theactivities that will lead to a specific increase in customer satisfaction” (p. 27).

Direct effect. We propose that a pay-for-performance plan is related negatively tosalespersons’ engaging in KSBs. Kerr (1995) emphasizes the importance of designingcompensation systems very carefully to ensure that we are in fact rewarding thebehaviors we want. Having the compensation of salespeople tied to their in-roleperformance goals may fall short of motivating them to participate actively inknowledge sharing given that KSBs are not part of the formal job description. Thisfailure to motivate KSBs is largely identified as an agency problem that is manifestedin the form of knowledge shirking (or hoarding). Agency theory posits that the designof control systems realigns the goals of the firm and salespeople so that both partiesdesire the same outcome (Anderson and Oliver, 1987). Through a pay-for-performanceplan, the firm signals that salespeople must devote their knowledge, skills, time, andeffort to meet their sales targets (e.g. Joseph and Kalwani, 1998).

While salespeople are likely to respond to a pay-for-performance plan by devotingtheir time and effort to achieving greater levels of sales performance, the same planmay discourage them from engaging in KSBs (e.g. Huber, 2001). In turn, goalincongruence between the two parties (i.e. salespersons’ reluctance to share theirknowledge) is likely to cause information asymmetry and opportunistic tendencies inthe form of knowledge shirking, especially when monitoring a salesperson’s KSBs isdifficult (e.g. Bergen et al., 1992; Ramaswami, 2002). Knowledge sharing from therational utility/choice perspective involves the expectation that “people choose afterassessing the probable gains and losses in well-being (their own and others’) from a setof alternative actions” (Knoke, 1990, p. 31). Because participating in a social action isinherently self-interested behavior, it is most likely that a potential asymmetry of goalsmay result in salespeople’s reluctance to engage in KSBs (e.g. Knoke, 1990).

To further elaborate, as Jacobides and Croson (2001, p. 209) suggest, if the firm hasmultiple goals (e.g. satisfying sales quotas and sharing knowledge) for the salespeopleto achieve, only those objectives that are measured (i.e. meeting sales targets) andcompensated (i.e. a pay-for-performance plan) will be emphasized by salespeopleunless the objectives are perceived as perfect complements. As Jensen (1994, p. 43)states, “because people are, in the end, self-interested they will have conflicts ofinterests over at least some issues any time they attempt to engage in cooperativeendeavors.” Therefore, we hypothesize the following:

H1. Pay-for-performance is related negatively to knowledge sharing behaviors.

Coworker relationship qualityDirect effect. Coworker relationship quality is defined as the degree to which asalesperson perceives a mutually beneficial and cooperative relationship withcoworkers outside the sales unit. We identify the concept of coworker relationshipquality in terms of the strength of a salesperson’s relationship(s) with coworkersoutside the sales unit. In line with the existing literature on social networks, ourdefinition captures the characteristics of strong relationships between a salespersonand his/her coworkers based on closeness (i.e. I have very close working relationshipswith other employees outside the sales unit), mutuality (e.g. my interactions with otheremployees outside the sales unit can be defined as mutually beneficial), and

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frequent/regular contact (e.g. I regularly communicate with other employees outsidethe sales unit) (e.g. Smith et al., 2005).

Relationship quality that a salesperson has with coworkers outside the sales unitcan range from low to high (e.g. Seers et al., 1995). Low-quality relationships can becharacterized by social interactions that are mostly based on short-term andtransactional relationships, and due to a lack of affinity and trust, a limited exchange ofknowledge can be expected between a salesperson and his/her coworkers. Conversely,high-quality relationships are manifested in interpersonal relationships that are basedon social interactions that involve mutual trust, respect, emotional attachment,interpersonal reciprocity, and obligations (e.g. Janssen and Van Yperen, 2004).High-quality relationships with coworkers foster salespeople’s KSBs with otherindividuals through social (i.e. desire to reciprocate) and psychological (i.e. desire tomaintain balanced relationships) considerations (Reagans and McEvily, 2003).According to social exchange theory (Blau, 1964, p. 91), salespeople share theirknowledge because they “are motivated by the returns they are expected to bring [. . .]from others.” According to the norm of reciprocity (Gouldner, 1960), high-qualityrelationships also set the norm of reciprocity and play a central role in governing andmotivating the exchange of mutual benefits. In turn, salespeople are likely to go aboveand beyond their formally defined roles and reciprocate by engaging in KSBs whenrelationship quality is high. Therefore:

H2. Coworker relationship quality will be related positively to knowledge sharingbehaviors.

Moderating effect. When interpersonal ties are strong, salespeople are likely to be moremotivated to cooperate with members of their social group through knowledge sharing(Yilmaz and Hunt, 2001). We expect mutual trust, respect, emotional attachment, feltreciprocity, and obligations between salespeople and their coworkers (e.g. Coleman, 1988)to override the costs of knowledge sharing that result from an incongruent incentivesystem. Even when salespeople perceive no economic benefits to sharing their knowledge,the common goals, interests, and vision that members of the same social group share willhelp them see the value of knowledge sharing (Chiu et al., 2006; Tsai and Ghoshal, 1998).We predict that as interpersonal relationships intensify, salespeople will engage inbehaviors that are beyond their formal in-role expectations, such as KSBs. We expect thisto happen because high-quality relationships with coworkers can function as a buffer todampen motivational losses resulting from a misalignment between pay-for-performanceand KSBs. In other words, high-quality relationships with coworkers outside the salesunit act as an informal control (i.e. social) in governing salespeople’s behaviors andmotivating them to share their knowledge (e.g. Jaworski, 1988). Therefore:

H3. The negative relationship between pay-for-performance and knowledgesharing behaviors will be weaker under high-quality relationships withcoworkers.

Knowledge sharing normsWe define knowledge sharing norms as the informal, unwritten rules that are typicallyinitiated and adopted by group members to regulate and regularize their KSBs(Feldman, 1984; Fisher et al., 1997; Jaworski, 1988). Salespeople acquire norms through

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learning, imitation, and pressure to conform, and they internalize those norms andadhere to standards grounded in the value systems of the organization (Knoke, 1990).

Our focus is on organizational knowledge sharing norms and not knowledgesharing norms at the sales team level because, as mentioned before, KSBs involveinteractions with other functional members outside the sales unit. Further, ourconstruct of relationship quality refers to the quality of salespersons’ relationshipswith coworkers outside the sales unit. Thus, we focus on organization-wide norms ofknowledge sharing instead of team-level norms. Overall, our position is parallel to thatof Le Bon and Merunka (2006), who investigate salespeople’s contributions toknowledge management systems at the organizational level.

Direct effect. Knowledge sharing norms vary in strength (Feldman, 1984). Strongnorms indicate group-level consensus (Coleman, 1990) so that knowledge sharing isperceived to be crucial for the survival (or proper functioning) of the organization(Knoke, 1990). Unlike weak norms, strong norms have certain advantages. First, strongnorms set certain rewards (punishments) for conformity (deviance), whereas weaknorms allow a wide latitude of acceptable behaviors (Fisher et al., 1997). Second, normsbecome a social justification mechanism so that salespersons’ conformity to norms isrewarded and deviance is punished (i.e. social isolation, lack of support) (Feldman,1984). In other words, social norms legitimize the informal authority to reward (punish)those who comply with (deviate from) desirable behaviors. Third, when norms arestrong, they help salespeople learn their role expectations and increase thepredictability of their KSBs (Feldman, 1984). When salespeople perceive thatknowledge sharing is required, expected, and supported, they are likely to look foropportunities to share their knowledge and promote KSBs (cf. Fisher et al., 1997). Thisalso means that a common understanding of reciprocity is set (e.g. Coleman, 1988),which in turn diminishes salespeople’s fear of knowledge exploitation and perceivedloss of knowledge power. Hence:

H4. Strength of knowledge sharing norms is related positively to knowledgesharing behaviors.

Moderating effect. We assert that strong norm consensus positively moderates thepay-for-performance – KSBs relationship (i.e. two-way interaction).

Mischel’s (1973) situational strength theory provides the theoretical rationale forhow individual behaviors are formed and shaped under the influence of strong versusweak norm consensus. A strong norm consensus on knowledge sharing leadsindividuals to interpret particular behaviors in the same way, induces uniformexpectancies regarding the most appropriate behaviors, and provides social incentivesfor that behavioral response (Mischel, 1973). In other words, strong norm consensusacts as an informal mechanism (i.e. cultural control) in governing salespeople’sbehaviors and motivating them to share their knowledge (e.g. Jaworski, 1988).Therefore, even when salespeople are not rewarded explicitly for their time and effortin knowledge sharing, strong norm consensus may constrain their knowledgeshirking.

Conversely, a weak norm consensus does not generate uniform expectanciesconcerning knowledge sharing, does not offer sufficient social incentives for itsperformance, and/or fails to provide the learning conditions required for the successfulconstruction of behavior. Individual differences can determine which behavioral

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actions to take when the situation is ambiguously structured, such that salespeople arenot guided by clear expectations about the behaviors most likely to be appropriate(normative or otherwise) in a given situation (Mischel, 1973). In other words, sincenormative expectations about knowledge sharing are not well defined, salespeoplehave more discretion in knowledge shirking. Therefore:

H5. The negative relationship between pay-for-performance and knowledgesharing behaviors will be weaker when knowledge sharing norms arestronger.

Research methodSample and procedureSince the purpose of this study is to investigate salespersons’ KSBs, the unit of analysisis salespeople. We collected data from industrial salespeople employed at largeCanadian organizations using an online survey method. We compiled a list of 200organizations, which we randomly choose from the Dun & Bradstreet database. Thelist included organizations that operate in various sectors such as electronics andcomputer parts, IT and software development, biotechnology, manufacturingequipment, etc.

Since the database also provided the names and addresses of top managers (i.e. CEO,chief sales executive, chief marketing managers), we sent them a formal invitation toparticipate in our survey. The invitation informed managers about the purpose of oursurvey and the sample design, and explained that we were interested in salespersons’KSBs in organizations that do not use monetary incentives tailored specificallytowards KSBs. The managers of 51 organizations that fit with our sample designagreed to participate in our survey. In our second contact with the managers, weprovided them with a URL address that housed the salesperson survey and asked themto inform their salespeople. Salespeople who wished to participate were instructed togo to a sign-up page on the survey’s URL. After two waves of reminders sent tosalespeople by managers, we obtained useable responses from 374 salespeople. Sincethe maximum number of responses we could receive from salespeople would be 1,438,the response rate was 26 percent.

We tested for nonresponse bias by comparing the early and late respondents interms of demographics and actual responses to key model variables. For each variable,a t-test revealed no significant differences, which indicates that early respondents didnot differ from late respondents. Of the salespeople, 82 percent were males and theaverage age was 45.6 years. 50 percent of the salespeople had higher education(i.e. undergraduate and above), and 70.6 percent had their degree in business (70.6percent). The average company tenure and previous experience in sales were 8.9 yearsand 14.3 years, respectively. Regarding the 51 organizations, the average firm size was768 full-time employees and the distribution of industries in which that competed wasas follows: electronics and computer parts (15), IT and software development (12),biotechnology (11), manufacturing equipment (9), others (4).

MeasuresTable I reports the measures and the respective scale items.

We measured salespersons’ knowledge sharing behaviors with an eight-item,five-point Likert scale (1-not at all; 5-to a great extent). At the time we prepared our

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questionnaire, there was no established scale to measure KSBs in the sales context. Theavailable scales outside the sales context (i.e. IS) were largely limited to employees’attitudes and intentions to share their knowledge electronically (i.e. Bock et al., 2005;Kankanhalli et al., 2005; Wasko and Faraj, 2005). Keeping those studies in mind, weadapted Jaworski and Kohli’s (1993) scale of intra-organizational knowledgedissemination to capture salespersons’ KSBs through different channels(i.e. interdepartmental meetings; hall talks with coworkers; circulating documentsand customer satisfaction data).

As stated earlier, our focus is on pay-for-performance plans implemented at theindividual salesperson level through which a salesperson’s total compensation ispartially tied to a combination of bonuses and commissions awarded for achievingstated sales quota/volume. Hence, we asked salespeople to indicate what percentage of

Measures and items Loading t-value

Knowledge sharing norms (a ¼ 0.87; CR ¼ 0.89; AVE ¼ 0.61)In this organization, . . . Everyone believes that sharing knowledge is important 0.72 –There is a tradition of interpersonal knowledge sharing 0.86 12.61Knowledge sharing between employees is not encouraged (r) 0.76 11.10Our supervisors expect us to share our knowledge 0.68 9.63Employees do not care about sharing knowledge with one another (r) b –Knowledge sharing among employees is not the norm (r) 0.86 12.60

Coworker relationship quality (a ¼ 0.90; CR ¼ 0.92; AVE ¼ 0.66)I have very close working relationships with other employees outside the salesunit 0.89 –I regularly communicate with other employees outside the sales unit 0.85 12.58I do not have much interaction with other employees outside the sales unit 0.80 12.17My interactions with other employees outside the sales unit can be defined asmutually beneficial 0.86 12.63Maintaining good relationships with other employees outside the sales unit isimportant to me 0.70 10.01My relationships with other employees outside the sales unit can be described ascooperative rather than competitive 0.77 11.34

Knowledge sharing behaviors (a ¼ 0.90; CR ¼ 0.92; AVE ¼ 0.59)When I have learned something new about customers, I share it with otheremployees 0.78 –When I find out something important about customers, I explain it to otheremployees through written documents (e.g. reports, formal emails, etc.) 0.79 11.90I engage in a lot of informal “hall talk” with other employees about customers 0.59 7.09I participate in interdepartmental meetings to discuss customers’ current andfuture needs 0.70 10.12I spend time discussing customers with employees in other departments 0.84 12.42I circulate documents that provide information regarding customers 0.80 12.03When something important happens to a major customer, I let the entireorganization know about it within a short period of time 0.84 12.40I share data regarding customer satisfaction with all levels of this organizationon regular basis 0.76 11.09

Notes: t-values higher than 2.0 are significant at p , 0.05; (a) – item was fixed to 1 to set the scale;(b) – deleted item; (r) – reverse scored item

Table I.CFA results

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their total salary is accounted for by incentives (bonus and commission) resulting fromachieving sales quota/volume. This operationalization is consistent with previousstudies in the marketing literature (e.g. John and Weitz, 1989; Mallin and Pullins, 2009).

We measured the quality of coworker relationships with coworkers outside the salesunit with a six-item, five-point scale (1-strongly disagree; 5-strongly agree). Weborrowed the scale items from previously published research in the marketingliterature and adapted them to the context of our study (e.g. Ganesan et al., 2005;Rindfleisch and Moorman, 2001). For example, the original scale item “maintaining along-term relationship with this organization is important to us” was adapted to read“maintaining good relationships with other employees outside the sales unit isimportant to me.”

We measured salespersons’ perception of knowledge sharing norms with afive-item, five-point Likert scale (1-strongly disagree; 5-strongly agree). We adaptedFisher et al.’s (1997) scale to the context of our study. To eliminate common methodbias, we excluded a focal employee’s response on the scale items and aggregated allother salespersons’ responses to operationalize norms at the organization level. Wecomputed the rwg, ICC(1) and ICC(2) values to test whether the aggregation wasstatistically appropriate ( James et al., 1984). Since these values were all above therecommended values reported in the literature (rwg ¼ 0.90, ICC(1) ¼ 0.27,ICC(2) ¼ 0.73), the aggregation was justified (Schneider et al., 1998).

We computed the strength of norms for every organization as follows. First, wecalculated the standard deviation value for each item in the scale of knowledge sharingnorms as perceived by all other salespeople but the focal salesperson. Second, weadded the standard deviation value of the items to reach an average deviation score.Third, since the average deviation score indicates organization-wide disagreement (ordissensus) on the strength of norms, we multiplied it by 21 so that a high scorerepresents high agreement (or consensus) on the strength of norms (Bliese andHalverson, 1998).

Control variables. We included age, educational background (business versus other),firm tenure, and career tenure as salesperson-level control variables to avoid modelmisspecification. We also controlled for firm size and industry type. We grouped thefirms into five categories (1 – electronics and computer parts, 2 – IT and softwaredevelopment, 3 – biotechnology, 4 – manufacturing equipment, 5 – others) and thenentered four industry types into the model as dummy variables by omitting thecategory of “others”.

Analysis and resultsMeasurement validity and reliabilityWe tested the reliability and validity of our constructs by performing a confirmatoryfactor analysis (CFA) (Gerbing and Anderson, 1988). We deleted one item in the scale ofknowledge sharing norms due to low factor loading. The revised measurement modelprovides an acceptable fit (x2(df ¼ 149) ¼ 342.7, GFI ¼ 0.90; TLI ¼ 0.91; CFI ¼ 0.92;RMSEA ¼ 0.07).

As Table I reports, all factor loadings were statistically significant (Gerbing andAnderson, 1988) and the average variance extracted (AVE) values were higher than0.50 (Bagozzi and Yi, 1988). These findings support the convergent validity of theconstructs. We also confirmed the discriminant validity of the constructs because the

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square of the intercorrelations between two constructs was less than the AVEestimates of the same constructs (Fornell and Larcker, 1981). Table II reports thedescriptive statistics and intercorrelations for the variables.

Testing for common method biasWe followed Podsakoff et al.’s (2003) recommendation to check for common method bias.As they suggest, allowing the common method factor to correlate with other variablesmakes it possible to examine the potential increase in model fit. The chi-square differencebetween the model with a common method factor and our measurement model was notstatistically significant (Dx2 ¼ 47.7, Ddf ¼ 20, ns). Further, 14 percent of the totalvariance was explained by the common method factor, which is much less than themedian of method variance (25 percent) reported by Williams et al. (1989).

Also, from a conceptual point-of-view, there is minimal threat of common methodbias since we operationalize knowledge sharing norms at a different level(i.e. organizational) than other constructs (individual). In addition,pay-for-performance was measured using an objective measure. As stated earlier,we computed the mean level of norms and the strength (or within-organizationagreement) of the norms by excluding a focal salesperson’s own response.

Hypotheses testsSince our dataset consisted of multiple salesperson responses from every organization(i.e. nested data), we tested our hypotheses using the Hierarchical Linear Modeling(HLM 6) technique (e.g. Raudenbusch et al., 2004). The results of a null model (i.e. withno variables) indicated a significant between-organization variance in salespersons’KSBs (ICC [1] ¼ 0.27; x2[50] ¼ 156.9, p , 0.001). Hence, multilevel modeling was anappropriate technique.

Table III reports the results. We found that pay-for-performance plan (g ¼ 20.12,p , 0.05) was related negatively to KSBs, and coworker relationship quality (g ¼ 0.33,p , 0.001) was related positively to KSBs. These findings support H1 and H2.

We found that the interaction effect of pay-for-performance and coworkerrelationship quality is positive and statistically significant (g ¼ 0.39, p , 0.01). Wefurther tested the simple slopes for salespeople with a higher (one standard deviationhigher) and a lower (one standard deviation lower) level of coworker relationshipquality. Pay-for-performance was not related to KSBs for salespeople with a lowerquality of coworker relationships (b ¼ 20.01, ns), whereas pay-for-performance wasrelated positively to KSBs for salespeople with a higher quality of coworkerrelationships (b ¼ 0.45, p , 0.01). H3 was, therefore, supported (see Figure 2). Normstrength was not significantly related to KSBs. Hence, H4 was not supported.

We found that the interaction effect of pay-for-performance and norm strength ispositive and statistically significant (g ¼ 0.56, p , 0.01). Pay-for-performance waspositively related to KSBs under strong norms (b ¼ 0.62, p , 0.01), whereas therelationship was not statistically significant when norms were weak (b ¼ 20.01, ns).Hence, H5 was supported (see Figure 3).

Of the control variables, age was related negatively to KSBs (g ¼ 20.04, p , 0.05),whereas career tenure was related positively to KSBs (g ¼ 0.04, p , 0.01). We alsofound that firm size and industry type were not related to KSBs.

Knowledgesharing

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1345

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Table II.Descriptive statistics andintercorrelations

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Finally, a significant between-organization interaction might lead to a spuriouscross-level interaction (Hofmann et al., 2003). Therefore, we tested H5 by adding theorganization level of pay-for-performance as well as its product term with norm strengthas predictors of the intercept. Since the cross-level interaction remained significant, thesignificant cross-level interaction reported in Table III was not spurious.

Discussion and implicationsDespite the critical role that salespeople have in this knowledge dissemination process,our understanding of factors that promote and impede salespeople’s engagement inKSBs is still limited. The key goal of this study was to fill this void in the literature.

Our study contributes to key account management, the expanding role of sales(i.e. relationship management and knowledge sharing), and sales force controlliterature. There is widespread consensus that the field of sales is moving beyond

Model 1b Model 2a

Variables B t-value B t-value

Intercept 3.04 42.79 * * * 2.80 35.20 * * *

Level 1Age 20.05 22.13 * 20.04 22.03 *

Education 0.06 1.20 0.07 1.89Firm tenure 0.01 0.64 0.01 0.79Career tenure 0.05 3.21 * * 0.04 3.11 * *

Pay-for-performance 20.13 22.42 * * 20.12 22.19 *

Coworker relationship quality 0.27 3.81 * * * 0.33 4.10 * * *

Level 2Firm size 0.02 1.00 0.03 1.05Industry 1e (electronics and computer parts) 0.01 0.66 0.03 1.01Industry 2 (IT and software development) 0.03 1.01 0.01 0.69Industry 3 (Biotechnology) 20.01 20.70 0.01 0.71Industry 4 (Manufacturing equipment) 0.02 0.99 0.01 0.70Knowledge sharing norms 0.40 2.68 * * 0.38 2.39 *

Norm strength 0.06 1.02 20.04 20.70

InteractionsPay-for-performance £ Strength ofknowledge sharing norms 0.56 3.21 * *

Pay-for-performance £ Coworkerrelationship quality 0.39 2.43 * *

Model deviance (df ) 629.4 * * * (16) 609.1 * * * (18)DDeviance (Ddf ) 161.7 * * * (13)c 20.3 * * (2)d

R 2within-group 0.29 0.32

R 2between-group 0.58 0.69

Total R 2 0.37 0.42

Notes: Entries are final estimations of fixed effects with robust standard errors; aLevel l variables aregroup mean centered, Level 2 variables are grand mean centered (Hofmann and Gavin, 1998); bBothLevel 1 and Level 2 variables are grand mean centered (Hofmann and Gavin, 1998); cDecrease indeviance is computed in comparison to null model; dDecrease in deviance is computed in comparisonto Model 1; eOmitted category is all others; Total R 2=R 2

within-group £ (1-ICC1)+R 2between-groups £ ICC1

(Hirst et al., 2009); *p , 0.05; * *p , 0.01; * * *p , 0.001 (two-tailed test)Table III.

HLM results

Knowledgesharing

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being a function (i.e. an isolated activity) and an operative posture to being a process(i.e. an integrated cross-functional activity) and a strategic approach that increasinglyrelies on team selling and key account management to engage in long-term relationalexchanges (e.g. Storbacka et al., 2009). Over time, the role and accountability of thesalesperson has changed from that of “order taker” to “relationship builder,” whichrequires skills, knowledge, and assets that facilitate value creation with customers. Inthis respect, sharing customer information with coworkers outside of sales is animportant step in improving relationships with key accounts.

Our results suggest that different combinations of controls can motivate KSBs.Specifically, even when formal controls such as economic incentives are misalignedwith the goal of salespeople, other informal controls such as norms or relationshipquality with coworkers can mitigate the negative relationship between salespeople’sbehavior and economic incentives. This finding is also consistent with the fact thatconsumers and salespeople alike are driven not only by economic utility/satisfaction,but also by social and psychological utility/satisfaction (e.g. Geyskens and Steenkamp,

Figure 2.The moderating effect ofcoworker relationshipquality

Figure 3.The moderating effect ofnorm strength

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2000). More broadly, our results are in line with Granovetter’s (1985) embeddednesstheory in that decisions are a joint product of economic and social relations.

We now discuss the three key contributions of our study in greater detail. First,Arnett and Badrinarayanan (2005) argue that knowledge management competence isan important dimension of a customer-needs-driven CRM strategy. Our findingscontribute empirically to this area by taking an integrative approach to KSBs.

Second, our findings indicate that when there is misalignment between rewards andsalespeople’s performance, KSBs suffer (Deckop et al., 1999). Our results are consistentwith agency theory and transaction cost economics in that goal incongruence betweentwo parties leads to salesperson behaviors that diverge from the interests of theorganization. When KSBs are not part of the formal compensation package,salespeople will feel less incentive to engage in KSBs. KSBs can be taxing and mayrequire the expenditure of extra resources; thus, salespeople may be unwilling toperform them unless they are compensated for doing so.

Third, the negative relationship between pay-for-performance and KSBs can bereversed when salespeople have high quality relationships with coworkers outside thesales unit and when there is consensus on norms. This finding, in essence, illustratesthat even when a formal control (i.e. pay-for-performance) is ineffective in motivatingthe desired behavior (i.e. KSBs), informal controls, when used effectively, can mitigatethe negative effects caused by a misalignment between pay-for-performance and KSBs.Hence, it is important to select the appropriate “bundle” of controls that can collectivelymotivate the desired behaviors. When salespeople have interpersonal relationshipswith coworkers outside the sales unit that are based on trust, rapport, and mutualreciprocity, their role seems to broaden so that behaviors such as KSBs, which wouldmostly be undertaken when economic rewards are provided, may be relaxed. That is,more extra-role behavior may be included in the net of job descriptions as relationshipquality is enhanced.

Contrary to expectations, the strength of norms was not related to KSBs. Recall thatthe strength of norms we used in our study was at the organizational level and not atthe sales team level per se. The broader consensus of norms at the organizational levelmay have had fewer binding effects on how salespeople should behave to comply withfirms’ expectations regarding KSBs. Consensus on more specific and focused normsmay be more powerful in regulating expected salesperson behaviors.

Managerial implicationsSome firms such as Ernst & Young and Xerox use individual rewards contingent onthe extent of knowledge that employees contribute to knowledge repositories (Hansenet al., 1999; Huber, 2001). However, these firms are the exceptions rather than the rule.The majority of firms are slow and hesitant to embrace this idea, especially in a salescontext. Our study contributes to the CRM literature by explicating how salesmanagers in firms where KSBs are not part of the formal job description can stillmotivate salespeople to engage in KSBs through the use of norms and coworkerrelationship quality.

The following can be points to consider if sales managers desire to motivate theirsalespeople to engage in KSBs. First, provide reward incentives that are aligned withknowledge sharing. The most effective reward would be tangible compensations suchas monetary incentives that are tied to promotions or sales performance. However,

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even if such tangible compensation is infeasible, it is important to recognize andpromote awareness that individuals who go to great lengths to share knowledge areperceived as experts by coworkers and management. Second, if reward systems are notyet formally established, the presence of high relationship quality with coworkersoutside the sales unit and the installation of a strong norm that is shared bysalespeople can compensate for the motivational loss that results from not linkingrewards to KSBs.

Future research and limitationsOur study is not without limitations; however, these provide directions for futureresearch. First, since we employed a convenience sample, future researchers shouldcollect data from salespeople employed at a larger set of companies. Second, futurestudies examining KSBs could consider collecting KSBs not only from salespeople, butalso from direct recipients of such knowledge.

Third, salespersons’ engagement in knowledge sharing with coworkers outside thesales unit helps organizations implement market orientation systems and structure(i.e. knowledge dissemination and responsiveness). Hence, the scale that we developed,which is based on Jaworski and Kohli’s (1993) scale of market orientation, seems quiterelevant. However, our scale measures salesperson’s KSBs with coworkers outside thesales unit in general as opposed to with coworkers in specific departments such asmarketing, manufacturing, finance, etc. This may be considered a limitation of ourscale and consequently of our study. Hence, we suggest that future researchers whowish to refine and/or redevelop the scale for salespeople’s KSBs review the literature oncross-functional relationships, especially those involving marketing and sales(Dewsnap and Jobber, 2000; Guenzi and Troilo, 2007).

Fourth, since there is no established scale to measure specifically the extent ofsalespersons’ relationship quality with their coworkers, we have adapted a scalepreviously used in the marketing literature (e.g. Ganesan et al., 2005). Futureresearchers may develop a more refined scale that will tap into coworker relationshipquality within the sales context. Fifth, all of the firms in our sample did not formallyreward salespeople for engaging in KSBs. Future studies should have a mix of firmsthat do and do not directly reward KSBs and examine whether relationship quality andnorms play equally important moderating roles in the KSB process. Sixth, our findingsdo not provide insight into the return on KSBs from a financial perspective. To thisend, linking KSBs to salespeople’s contribution to profitability and sales could beinformative. Seventh, we focus on two moderators that reversed the negative impact ofpay-for-performance on KSBs. However, other organizational design/structural factors(e.g. task or goal interdependence) and psychological elements may play a role andshould be considered in future studies. Eighth, the pay-for-performance measure wasconfined to bonuses and commissions based on meeting or exceeding salesquota/volume. Other incentives such as customer satisfaction scores or number ofcustomer complaints could be included.

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Corresponding authorSeigyoung Auh can be contacted at: seigyoung.auh@thunderbird.edu

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