a multilevel framework - Springer Link

J. of the Acad. Mark. Sci. (2008) 36:278–291 DOI 10.1007/s11747-007-0055-z

Understanding the adoption of new brands through salespeople: a multilevel framework Jan Wieseke & Christian Homburg & Nick Lee

Received: 16 March 2007 / Accepted: 14 June 2007 / Published online: 7 July 2007 # Academy of Marketing Science 2007

Abstract So far there has been scant empirical attention paid to the role of the sales force in the adoption of new brands in the early implementation stages. We test a framework of internal (sales manager and salespeople) brand adoption using an empirical multilevel study. Our findings suggest that the construct of expected customer demand (ECD) plays an important role in sales force brand adoption. First, ECD directly influences salespeople’s and sales managers’ brand adoption. Second, ECD serves as a cross-level moderator of new brand adoption transmission. We find the influence of sales managers’ brand adoption on salespeople’s brand adoption to be stronger when salespeople’s ECD is lower. Keywords Brand adoption . Expected customer demand . Empirical . Multilevel Marketing innovations such as new brands are crucial to continuing firm success. In line with this, a large body of research has developed regarding the factors that can influence the adoption of new brands by customers. In particular, scholarly work has examined brand attributes such as quality, price and advertising, and their effects on

J. Wieseke : C. Homburg (*) Marketing Department, L 5,1, 68131 Mannheim, Germany e-mail: [email protected] N. Lee Marketing Group, Aston Business School, Birmingham, UK

the success of introductions (e.g., Chaudhuri 2002; Grewal et al. 1998; Hardesty et al. 2002; Smith and Park 1992; Sunde and Brodie 1993). Yet, despite the ever-increasing scholarly interest, marketing innovations such as new brands or products continue to face immense failure rates (Kaufman et al. 2006; Di Benedetto 1999). Although the existing literature in this area has provided valuable insights, it focuses almost exclusively on the customer as the unit of analysis. Research has largely neglected the study of internal customers and potential internal bottlenecks that can hinder innovation transmission (Atuahene-Gima 1997). This is despite the evident conceptual importance of internal stakeholders in the internal marketing literature (e.g., George 1990). For a number of reasons, one key bottleneck lies in the sales force. First, salespeople of all types span the boundary between the organization and the potentially-adopting customer (Schwepker and Good 2004; Weitz and Bradford 1999). Therefore, the sales force’s adoption of an innovative brand is likely to be critical to the adoption of an innovation by final customers (e.g., Di Benedetto 1999). This remains true even when taking into account recent developments in the selling function such as ‘customer relationship management’ (e.g., Tanner et al. 2005), ‘customer message management’ (e.g., Riesterer 2004), and ‘team selling’ (e.g., Jones et al. 2005). Despite the importance of these issues, salespeople’s direct contact with the customer ensures that they will remain a key influence on the ultimate market success of innovations. Second, it is commonly the case that sales and marketing are organized as distinct functional silos, often leading to each having separate goals (e.g., Homburg and Jensen 2007; Leigh and Marshall 2001; Matthyssens and Johnston 2006). For example, while marketing may have a more long-term perspective on the introduction of an innovation

J. of the Acad. Mark. Sci. (2008) 36:278–291

that may not be successful immediately, the sales force may be more concerned with short-term targets and quotas (Rouziès et al. 2005). Salespeople may thus prefer to focus on existing products that are proven sellers, leading to suboptimal effort towards the innovation. The sales force’s relevance to the success of an innovation can aptly be summarized by a quote from Atuahene-Gima (1997, p. 498): “Some firms take sales force commitment to any new product as a given, seemingly adopting the attitude, ‘If we build it, they will sell’. However, management has no guarantee of salespeople’s commitment to a new product. For various reasons, salespeople may fail to sell a new product, or they may engage in dysfunctional behavior during the selling process—for example, misrepresenting the product’s benefits to gain short-term sales.” An interesting question in this context is whether, and under what conditions, a sales manager’s brand adoption affects the brand adoption of subordinate salespeople. Our research addresses this issue. We will develop a multilevel framework (multilevel, since it models constructs at two levels: that of the salesperson and the sales manager) that distinguishes two major forces driving salespeople’s brand adoption. First, we argue that brand adoption is driven by the salesperson’s observations regarding the extent to which his or her immediate manager adopts the brand. Second, we propose that salespeople put themselves in the place of potential customers, and build a judgment of expected customer demand (ECD) for the new brand. This ECD in turn should be mainly triggered by the different brand attributes—such as price–performance relation and quality— that are visible to the sales force. Moreover, we propose ECD to influence the transfer of brand adoption between sales managers and salespeople as a cross-level moderator. Here the assumption is that sales manager’s brand adoption exerts a stronger cross-level influence on salespeople’s brand adoption, if salespeople’s ECD is low. Addressing these issues is salient to marketing researchers and practitioners alike. Academically, this research is relevant to gain insight into the key intra-firm success factors for new brand implementation. This extends existing knowledge on new brand success that has heretofore been mainly concerned with the customer level. For practitioners our research provides a way of understanding how sales managers can impact on salespeople’s innovation adoption, and the circumstances that may effect this influence. For example, knowing when sales managers have only a limited influence on salespeople’s adoption would prevent significant managerial mistakes regarding resource allocation during new brand implementation. An important feature of our study is that it will use data collected at both levels of interest, i.e. from salespeople and the sales manager responsible for them. In fact, existing

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literature examining the cross-level influence of sales managers on salespeople’s adoption has utilized data solely from salespeople (e.g., Hultink and Atuahene-Gima 2000). Unfortunately, this approach runs the risk of both common method bias (Homburg and Stock 2004; Netemeyer et al. 1997), and informant bias resulting from the hierarchical position of the subjects. Instead, questions such as the ones we have raised above are best examined with separate data collection on each level of interest, and the use of specific statistical analysis procedures (Raudenbush and Bryk 2002). In the next section, we will derive a multilevel model including explicit hypotheses on sales force brand adoption at both the sales manager and salesperson level. Subsequently, we will present a large-scale multilevel study to test our hypotheses. After reporting the results, we will discuss the theoretical and managerial implications of our findings.

Theoretical foundation and hypotheses Figure 1 depicts our multilevel model of the consequences and predictors of salespeople’s and sales managers’ brand adoption. As stated above, we depict two main sources that should influence salespeople’s brand adoption: (1) the brand adoption of their superordinate sales managers, and (2) how strongly salespeople expect the customer demand for the new brand to be, which is triggered by the salesperson’s perceptions and evaluations of the attributes of the brand. A key assumption of our model is a crosslevel interaction effect between salespeople’s ECD, and the Level 2: Sales managers

evaluation of brand attributes a b c d

Expected Customer Demand (ECD)

Brand adoption

Expected Customer Demand (ECD)

Brand adoption

e

Level 1: Salespeople

evaluation of brand attributes a b c d e

Figure 1 Multilevel framework of predictors of salespeople’s brand adoption.

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brand adoption of their sales managers. Here, we propose that the cross-level influence of sales managers’ brand adoption on sales people’s brand adoption is stronger if the salespeople’s ECD is low. Finally, assuming sales managers are influential on salespeople’s brand adoption, we are also interested in factors that have an influence on sales managers’ brand adoption. Similar to the salesperson level, we expect the strength of sales managers’ ECD for the new brand (again determined by their perceptions of brand attributes) to be influential on sales managers’ brand adoption. Intralevel influences on brand adoption For our intralevel models on salespeople’s and sales managers’ brand adoption, we take the left part of the model (which deals with the evaluation of brand attributes and their influence on ECD) as given. Because these relationships appear straightforward and do not represent a central notion of this paper (indeed, conceptual and empirical evidence for their existence is clear in prior research), we provide only a short explanation of the basic principles behind them, without deriving hypotheses in detail. The influence of brand attribute evaluations on ECD The influences on potential customers’ brand adoption are commonly examined in the literature (e.g., Smith and Park 1992; Sunde and Brodie 1993). More specifically, prior empirical research has generally found a number of brand attributes to be linked to new product success, such as price–performance congruence (Henard and Szymanski 2001), quality perceptions (e.g., Cronin et al. 2000), brand image factors such as image fit with parent brand (e.g., Czellar 2003), differentiation (e.g., Agres and Dubitsky 1996), and advertising (Chaudhuri 2002). All things remaining equal, salespeople who believe that a new brand has many positive attributes should believe that potential customers would also perceive the attributes of the new brand as favorable, leading to a high ECD. The influence of ECD on brand adoption In our model we propose that salespeople’s brand adoption is influenced by their ECD. We argue that salespeople often evaluate a brand from a customer’s point of view. Thus, ECD is defined here as a sales force member’s perceptions of the likely customer demand for the new brand. This idea is related to Schatzel and Calantone’s (2006) construct of market anticipation which deals with the receptiveness for a firm’s new product, as well as curiosity and interest concerning the new offering on a broader market level.


However, while Schatzel and Calantone’s (2006) construct focuses on the firm level, we consider ECD at the sales force level. The proposed linkage between salespeople’s brand adoption and their expectations of the level of customer demand (i.e. ECD) can be drawn from Vroom’s (1964) Expectancy Theory. In this model expectancy is defined as “a momentary belief concerning the likelihood that a particular act will be followed by a particular outcome” (Vroom 1964, p. 17). In our context, expectancy refers to the likelihood that the selling effort for the new brand results in the purchase of the innovative brand by customers. In the case of high ECD the salespeople’s expectancy of selling the brand successfully to customers— if they try—should lead to an increased brand adoption. In other words, they will have a higher motivation to adopt a new brand if they expect a high customer demand. Empirical evidence supports this view, because expectancy has been found to be strongly related to subsequent attitudes, behavior, and intentions (e.g., Van Eerde 1998). Thus, we hypothesize H1: Salespeople’s brand adoption towards a new brand is positively associated with their ECD for the brand. Previous literature has not examined influences on the brand adoption of sales managers specifically. However, we expect these influences to be largely analogous to those for salespeople. Specifically, internal marketing efforts should influence sales managers’ brand adoption in similar ways compared to how they influence salespeople. After all, sales managers are tasked with ensuring their sales team achieves certain targets, and higher levels of relevant brand attributes should mean sales managers expect any new brand to experience high customer demand, that in turn influences their own performance. Thus, analogous to the salesperson level, we assume: H2: Sales managers’ brand adoption is positively associated with their ECD for the brand. Cross-level influences on brand adoption: the influence of the sales manager on salespeople’s brand adoption Contemporary research has conceptually and empirically supported the notion that sales managers have a decisive effect on salespeople’s behavior (e.g., Russ et al. 1996; Wotruba and Rochford 1995). Accordingly, a number of behavior modification and control strategies have been discussed in the sales literature (e.g., Cadogan and Simintiras 1994; Scott et al. 1986). Even considering the major changes to the sales force’s role since the turn of the century, the sales manager remains one of the key influences on whether or not salespeople behave appropriately and effectively in their roles (Fang et al. 2005; Schwepker and Good 2004).


While much previous sales research has explored how formal control systems put in place at an organizational level influence salespeople’s behavior (e.g., Oliver and Anderson 1994; Piercy et al. 2006), Leigh and Marshall (2001) argue that leadership is of particular importance in contemporary selling organizations. Rather than explicit controls and other management structures, leadership research suggests that managers’ actual new brand adoption should have a direct impact on the new brand adoption of subordinates, through the mechanisms of social learning (e.g., Bandura 1977) and social norm effects (Ajzen and Madden 1986). Therefore, we use Social Learning Theory and the Theory of Planned Behavior to justify the proposed influence of sales managers’ brand adoption on salespeople’s brand adoption. Social Learning Theory suggests that individuals learn by observing the behavior of others (Luthans and Kreitner 1985). Thus, salespeople should tend to follow the example of their sales manager in performing behaviors related to adopting (or not) a new brand. Sales managers’ adoption of a new brand also implies that they expect similar behavior from their salespeople. Salespeople are likely to be cognizant of the rewards available from their sales manager if they behave as expected, and likewise the sanctions implied if they do not. Since managers have the hierarchical power to punish or reward subordinates, subordinates are likely to act in conformity with managers (e.g., Cadogan and Simintiras 1994). Additionally, it is also possible to draw inference directly from the Theory of Planned Behavior (Ajzen and Madden 1986). In particular the cross-level influence of sales managers on salespeople’s brand adoption can be explained with the ‘subjective norm’ construct within the Theory of Planned Behavior. A subjective norm represents an individual’s perception of whether significant others will welcome or reject a given behavior (Ajzen 1985). These subjective norms have been found to directly relate to individual attitudes and behavioral intentions (e.g., Ajzen and Madden 1986). Furthermore, subjective norms have been found to be more influential when they relate to a salient person or group (Terry and Hogg 1996) such as a sales manager. Drawing from this, salespeople will utilize their evaluations of sales managers’ new brand adoption as a subjective norm in forming their own new brand adoption. This leads to the following hypothesis: H3: The brand adoption of sales managers is positively associated with the brand adoption of salespeople. In addition to the cross-level main effect, a cross-level interaction effect is also hypothesized. Specifically, while we propose that both a salesperson’s ECD and the superordinates’ brand adoption influence salespeople’s brand adoption, we also expect the influence of sales managers’ brand adoption on salespeople’s brand adoption to be

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strongest when salespeople’s ECD is low. In such cases, sales managers are likely to play a far more important role in the brand adoption of salespeople. When salespeople are not already confident in the future success of the innovation, they might perceive their manager as more knowledgeable and experienced in the market. Therefore, a higher level of brand adoption by the sales manager may go some way towards convincing salespeople that adopting the new brand is still a good idea even though the salespeople themselves are insecure concerning the demand in the market. In line with this reasoning, it is proposed in selfefficacy theory that significant others have the potential to motivate behavior, if someone has a low level of expectancy (Bandura 1997). Conversely, if salespeople are confident that a new brand is likely to be a big market success, this will supersede the possible influence of the sales manager. In such cases, salespeople will wish to adopt that brand irrespective of their sales manager’s brand adoption, since salespeople will expect the brand to make a large contribution to their success and corresponding remuneration. Further, if salespeople’s ECD for a new product is high, then a higher brand adoption by the sales manager is unlikely to be able to do much more to increase the adoption of salespeople. Of course, the brand adoption of salespeople is lowest if the brand is neither supported by superordinate management, nor expected to be a market success due to a low ECD. Thus, we hypothesize: H4: The relation between sales managers’ brand adoption and a salesperson’s brand adoption should be stronger when the salespersons’ ECD is low. Control variables In addition to the predictors in our multilevel framework, other factors are possibly influential on salespeople’s brand adoption. Thus, we included a number of control variables in our empirical analyses in order to test the robustness of our proposed relationships while controlling for important extraneous influences. A first important variable to control for can be found in sales force rewards as an integral part of control systems (Fang et al. 2005). Control is considered to gain importance in times of increasing requirements for salespeople, for example through increasing customer demands, increasing complexity of the sales role, and adoption of innovative products or sales systems (Brown et al. 2005). According to the aforementioned expectancy theory (Vroom 1964) a link from new brand sales to valuable rewards would have a motivational effect. This effect is based on the perceived instrumentality of brand sales in order to receive rewards. Second, we control for market competitiveness, because one can assume that higher competitive pressure may

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influence salespeople to be more open towards innovative brands, in order to retain their competitive advantage and differentiate from competitors (e.g., Jelinek et al. 2006). Furthermore, as suggested by previous research in sales force innovation adoption (e.g., Speier and Venkatesh 2002), we control for salespeople’s age and gender. This is of potential importance, because sales manager of different age and gender groups might display different brand attitudes and employ different management approaches (e.g., Piercy et al. 2006). Finally, we included the length of the relationship between a salesperson and their respective sales manager as a control variable.

Research method In the present section we present a field study that was designed to test the hypotheses derived above. The context of the study is a large travel agency franchise system that introduced a new travel brand. We chose a franchise context as it can be seen as a typical sales organizational structure, incorporating decentralized sales units/stores, where different brand implementation bottlenecks exist. Also, travel agencies are an ideal context for our study, as typically they exhibit both a close sales manager–salesperson interaction and a close salesperson–customer interaction. Under the studied new brand a portfolio of leisure travel brands was offered. The main focus was on city travel, long distance travel, and adventure travel. These offerings were organized and conducted by the travel agency franchise organization. Thus, from the travel agency organization’s perspective, the aim of the brand implementation was to extend its business activities. Instead of merely selling tourism offerings to end customers, and thus being a mediator between tourism providers and end customers, the travel agency organization aimed at acting as a tour operator itself. The idea for a travel agency brand to implement its own range of travel offerings was innovative to the firm as well as to the industry. As with most innovations in this particular market, a brand extension strategy was used, by designing the new brand with a clear connection to an existing brand (in this case the franchise brand itself). Data collection and sample Data for the study was collected in two phases. First, a qualitative study was conducted with 5 sales managers, 5 salespeople, and 104 potential customers. The aim of this study was to gain additional grounding in the field, as well as to clarify concepts and appropriate construct measurements. Following this, quantitative data was collected via a postal survey of sales managers and salespeople. In order to do so, 288 travel agency franchises were contacted by


telephone and asked to participate, of which 258 agreed to do so. The average franchise consisted of one sales manager and around 3–4 salespeople. Questionnaires were sent to 258 sales managers and 976 sales employees, and returned by 156 sales managers (a 60.5% response rate) and 391 sales employees (a 40.1% response rate). Of the sales managers, 49% were female, the mean age was 41 years (SD =10.6 years). Of the sales employees, 87% were female, and the mean age was 29.8 years (SD=9.1 years). Nonresponse bias was assessed using Armstrong and Overton’s (1977) time–trend extrapolation. No differences between early and late responders were detected on any of the constructs of interest or demographic variables within the two samples. In order to test the cross-level hypotheses regarding the sales manager–salesperson interface, the data sets were matched. For these purposes, only data from travel agencies who returned responses at both the sales manager and salesperson level were included. The resulting data set contained data from 112 sales managers, matched to 310 salespeople. This sample size is considered to be sufficient for multilevel regression analysis where generally macrolevel (in this case the sales managers) sample sizes should be 50 or more. Micro-level sample size (in this case the amount of salespeople per sales manager) is a comparatively minor issue when macro-level sample size is large (Hox and Maas 2002). Measure development and assessment All scales were drawn from previous research except for the novel construct of ECD. The scale development approach for ECD included four steps drawn from relevant literature (e.g., Anderson and Gerbing 1982; DeVellis 1991). First, the construct was specified through a review of the relevant literature in marketing. The second phase dealt with the construct operationalization. In a series of interviews with five marketing scholars, a pool of three potential scale items was generated. Third, the scale items were pre-tested with sales managers and salespeople in order to clarify and improve the items. This pretest was conducted during the aforementioned qualitative study, and resulted in minor modifications to the wording of the scale items in order to improve their clarity. For example, we changed the item “I believe that potential customers will like the brand” to “I believe the potential customer demand for brand X is strong”. Fourth as we will detail below, we tested the psychometric quality (e.g., convergent and discriminant validity) of the scale on the basis of the large-scale quantitative survey data. The final scale items resulting from this process, as well as the items of all other measures used in this study, are presented in the Appendix together with Cronbach’s alpha,


composite reliability, factor loadings, and item reliabilities for all scales. All scales had a sufficient reliability at both levels (Cronbach’s alpha and composite reliabilities between .60 and .96). Furthermore, with few exceptions, item reliabilities are above the recommended value of .40 (Bagozzi and Baumgartner 1994). The variance extracted was above .40 for each construct, giving evidence for convergent validity. Also, for each level we conducted confirmatory factor analysis (CFA) using AMOS 5.0 to assess convergent and discriminant validity of our construct operationalizations. The overall results for each model were: sales manager level χ2 (289)=333.17 (p