Excellent progress has been made in our understanding of how firms may effectively design and manage their channels of distribution. For instance, there is an extensive literature looking at forward vertical integration decisions, bureaucratic structuring of distribution channels and distribution intensity (e.g., Anderson 1985; Dwyer and Welsh 1985; Fein and Anderson 1997; Frazier and Lassar 1996). We also have significantly improved our understanding of how manufacturers can develop strong, long-term relationships with their channel partners and of how these affect firm performance (e.g., Anderson and Weitz 1992; Heide and John 1992; Morgan and Hunt 1994; Palmatier et al. 2007a, b, 2008).

Recent developments point to new research opportunities. Today’s distribution channel systems are increasingly complex. Producers often serve end-user markets through multichannel systems where diverse channel types (e.g., telemarketing, sales force, and e-commerce operations) and/or diverse entities (e.g., the manufacturer and different independent firms) are involved in the performance of the main distribution functions. This complex network of channel players co-creates value within the channel system (Norman and Ramirez 1993, Vargo and Lusch 2008). We define value as the worth in monetary terms of the technical, economic, service, and social benefits a channel player derives from a given relationship (Anderson and Narus 1998). We thus conceive value as comprising both tangible (e.g., product and service benefits) and non-tangible benefits (e.g., satisfaction with a relationship). Firms need a comprehensive understanding of value creation with the channel system, of its dynamics, and of the role played by each party in this process. There is a promising opportunity to investigate how the design and management of these complex channel system structures create value at different levels, namely (1) at the individual network actor level (e.g., individual profits), (2) at the relationship level (e.g., intrinsic value derived from higher-quality relationships between the producer and the end-user), and (3) at the channel-system level, benefiting all network actors (e.g., channel-level innovation and system adaptability). Figure 1 illustrates our theoretical framework. Each side of the triangle represents a relationship between two different channel participants.

Fig. 1
figure 1

The channel value network

Full size image

In direct producer-to-customer distribution channels, the producer performs most distribution functions internally. The producer may utilize different channel types to create customer value. In indirect channels, channel partners serve an intermediary role in the flow of the primary offering from producer to end-users. Independent channels may themselves utilize multiple channel types to reach their customers. In many situations, multiple independent entities will be involved in the performance of distribution functions in a given producer’s territory. We argue that future research should incorporate a more complete view of the channel system comprising the three sides of the triangle, for the real strategy that reaches the end-user market emerges from the confluence of strategic elements implemented by the producer and channel partner(s).

1 Channel design and outcomes

In this section, we elaborate on how the design and management of multiple distribution channels impact value creation at different levels in the channel system. In Section 1.3, we take a more comprehensive view of the channel “triangle” and call for a better integration of the perspectives of all channel network actors, focusing particularly on the generation of customer (end-user) value.

1.1 Channel ownership

One of the most important channel design decisions is “what determines the structure of the channel triangle in Fig. 1,” i.e., when should a producer own its own channels, use independent channel entities exclusively, or use both? We start with the typical forward integration question (one or the other) and then discuss possible research opportunities looking at value creation within dual distribution systems (both channels simultaneously) and within channel systems where multiple independent channel entities are involved in the performance of distribution functions.

1.1.1 Direct or indirect channels

Transaction cost economists argue that channel structure should be based on an economizing logic (Williamson 1981; Anderson 1985) such that channel governance decisions should be based on the transaction costs in the channel. The default should be market based (i.e., independent channels), and integrated channels should only be used when transaction specific investments, performance evaluation difficulty, and environmental uncertainty are high. This logic has dominated channels research; might other models emerge?

An alternative logic, legitimacy, comes from the institutional literature in sociology (e.g., DiMaggio and Powell 1983). According to this logic, firms seek legitimacy, social fitness among their peer firms, and this search for legitimacy can lead industries to a similar structure. DiMaggio and Powell (1983) suggest that three forces drive this search for similarity, coercive, normative, and mimetic isomorphism. Coercive isomorphism arises from the existence of legal or extralegal rules that mandate a certain structure or process. Normative isomorphism occurs when firms base their decisions in the face of uncertainty on norms that can arise from, among other things, managers’ experience or training, and mimetic isomorphism occurs when firms seek to respond to uncertainty by copying legitimate firms in their industry. All three can lead an industry toward agreement as to the standard structure or processes. This logic can as readily apply to the choice of a standard channel structure as to the choice of any other organizational structure or process. More interesting is that mimetic isomorphism may be a heuristic for firms seeking to use an economizing logic. Which are the more legitimate firms? Those that seem economically successful, which suggests that mimicking them will in turn lead to economic success. Thus, “legitimate” firms’ choices will tend to be followed by firms seeking to be legitimate.

Once legitimacy logic has influenced the firm’s initial decision, path dependence (Argyres and Liebeskind 1999) reinforces that decision. Path dependence is the idea that once you are “there”, it is easier to stay “there” than it is to leave. Thus, whichever channel structure is adopted initially, path dependence supports that choice. This raises two questions, where do firms initially start and what keeps them there? Anderson et al. (2008) suggest that the starting point is generally an employee sales force for a number of organizational and personal reasons. First, the chief sales officer (CSO) takes this decision. The CSO is likely a sales professional who has emerged from the ranks of an employee selling organization. Thus, what he or she knows how to manage and what will yield her or him the most organizational influence is an employee sales organization. When these cognitive, affective, and professional preferences are compounded with an unwillingness of the larger organization to change the decision—perhaps because the CSO is the professional and the sales organization is distant and different (Churchill et al. 2000) and difficult to assess (Anderson and Oliver 1987)—this suggests that an employee sales force will generally be the choice. But what about the second question, what keeps path dependence working? Briefly, we suggest that changing is tougher with an employee sales force. Firing a complete arm of the organization would seem tougher and more embarrassing than firing an outside selling firm.

There is scope for much additional research in this domain:

  • Are institutional, organizational, and social factors empirically important?

  • Will path dependence really support the original decision, and if so, what factors will facilitate it?

  • Is mimetic isomorphism a heuristic for the economizing logic?

  • Perhaps more a propos in light of the focus of this section on multiple channels is the degree to which either logic, the economizing logic or the legitimacy logic, applies to structural issues such as whether to have multiple channels and, if so, which ones, and process issues such as how to monitor and control multiple channels if the firm chooses that option.

1.1.2 Direct and indirect channels

The simultaneous usage of manufacturer-owned and independent channels (dual distribution) is one type of multichannel system. Dual distribution represents an increasingly frequent phenomenon as suppliers expand the number of channels to serve different customer segments or to serve different needs of the same customers. However, we still know little about how manufacturers can effectively manage dual distribution systems and the resulting impact on producer, distribution-channel, end-user, and channel-system outcomes. While the literature suggests that potential competition between direct and indirect channels may have potential destructive effects on channel relationships (e.g., Frazier 1999; Sa Vinhas and Anderson 2005), there is little empirical evidence and research investigating possible moderators is particularly scarce. A recent study by Sa Vinhas et al. (2008) suggests that under certain circumstances, the usage of a manufacturer-owned operation in an independent channel’s territory can actually increase the level of satisfaction of the independent channel. The authors advance possible explanations for this counterintuitive effect. For instance, they argue that the manufacturer-owned channel performs certain demand generation functions that benefit all channels in that territory. Paradoxically, they also find that this positive effect on the satisfaction of independent channels is greater when the producer has better relationships with its own internal channels in a distributor’s territory. This study provides some additional insights on the outcomes of dual distribution systems. However, many questions remain unanswered:

  • Relationship satisfaction is only one of the relevant channel outcomes influencing value creation within the channel system. How does the usage and management of dual distribution systems impact channel-system outcomes such as the level of innovation in the channel and the overall value created within the channel system? How is market learning accomplished within a multiple channel system?

  • While recent studies provide a rationale for the coexistence of company owned and independent channels, the optimal mix of the two has not been adequately explored. There is a felt need to explore the optimal mix further and to explore exogenous factors impacting channel choice in a specific context (e.g., retail location quality, the firm’s brand strength, market turbulence, product complexity).

  • What are appropriate metrics to evaluate channel performance in a multiple channel context? When firms have a mixture of short-term and long-term goals, using multiple performance metrics is required to ensure that firms do not under invest in channels with primarily long-term advantages.

  • What is a good measure of channel conflict? Are different elements of conflict such as frequency of conflict and intensity of conflict (Webb and Hogan 2002) equally degenerative or is one worse than the other? What is the correspondence between conflict management mechanisms and the different elements of conflict? What collaborative components can be incorporated in the inherently competitive nature of vertical multichannel usage systems?

  • Given that business environments are dynamic and channel portfolios are characterized by inertia, what tools are available to ensure that firms do not mistakenly cling to outdated channel structures?

1.1.3 Multiple independent channel entities

In some situations, the manufacturer utilizes independent channels exclusively but multiple independent entities are involved in the performance of distribution functions. An important challenge in complex multichannel systems is access to channel- and market-level information (e.g., end-user demand and product inventories within the channel system). Better information flows allow channel players to better meet their customer’s needs and reduce inefficiencies in the channel system, thus increasing system-level value. A B2B channel network can be complex and have multiple tiers of indirect channel participants with products being bought and sold by a variety of industrial, retail, institutional, commercial, wholesale, or retail organizations before ultimately being sold to the consumer or user of the product. Because of the complexity of these channels, a manufacturer will rarely have complete visibility of the sales transaction occurring within its own distribution system nor will it typically know the identity of resellers farther down the chain.

Unlike consumer packaged goods, there is no readily available scanner data that can be purchased and analyzed. Furthermore, the sheer number of indirect channel participants makes it difficult to track and manage information about all transactions. To gain insight into their end markets, manufacturers increasingly collect point-of-sale data from their indirect channel partners. When a manufacturer begins collecting data on the channel’s activities, it can then establish new pay-for-performance compensation models for the indirect channel participants (e.g., Fein 2005). These fee-for-service payments are usually linked to various metrics that ensure a wholesaler is shipping to customer orders and not merely building stock. Some agreements also provide higher compensation to wholesalers who provide more accurate and complete reporting. Implementation of pay-for-performance systems becomes more complex when several channel members provide added-value services without taking title to the products. In these situations, it is harder to quantify and reward the channel players’ efforts.

These data-sharing agreements take place in a world of bounded rationality, potential opportunism, and shirking. Opportunism could derive from either party to a data-sharing relationship. For example, executives at a distributor may be reluctant to collect and share demand data because they are suspicious that manufacturers will attempt to bypass the wholesale distribution channel. These executives will also be wary of sharing data if they fear that the data will be misused or mishandled. On the other hand, manufacturers may wonder if wholesalers are providing complete and accurate data. There is significant scope for additional research in this domain:

  • How can firms devise compensation systems to encourage partner firms and individuals within those firms to share information and collaborate? How do these compensation systems influence value creation and distribution within the channel system? Research extending literature on team selling and team compensation to a network of channel participants from different firms would be valuable. When are fee-for-service compensation systems effective and how should they be implemented within complex channel systems?

  • How can downstream channel partners ensure that upstream partners and producers handle their end-user market data appropriately and securely? Who owns the “property rights” to channel- and customer-level information and how can these be specified and protected?

  • What are the system-level benefits of data sharing within a multichannel network? Does it lead to higher system adaptability and innovativeness? How can these benefits be quantified and divided among all the different channel participants? How can this division be monitored? How are information “prices” determined? Who will engage in monitoring activities? What are the channel strategy implications when channel partners allow producers greater access to their internal operations?

1.2 Multiple channel types

There is very limited research looking at how manufacturers should design and manage multiple channel types or ways of reaching the customer. We briefly elaborate on value creation within these channel systems. We also consider the possibility that different types of channels may play different roles in new product distribution contexts.

1.2.1 Different ways of reaching the customer

A different type of multichannel system is the usage of multiple channel types (e.g., retail outlets, sales agents, direct marketing channels). Only a few empirical studies such as Alba et al. (1997), Deleersnyder et al. (2002), Dutta et al. (1995), Geyskens et al. (2002), and Jindal et al. (2007) have explored this phenomenon. An interesting research question is how the channel variety decision, i.e., the number of different channel types, interacts with the channel intensity decision, i.e., the depth of presence in each channel or the number of channel entities in each channel distributing a manufacturer’s product. Existing literature has primarily explored intensity within a single route (e.g., Frazier and Lassar 1996). While the relationship between variety and intensity decisions has been conjectured in the literature (Frazier 1999), some studies suggest a complementary relationship while others argue for a supplementary relationship. What combinations of variety and intensity create—or destroy—value for channel system participants? What impact do these have on relationship, channel-system, and customer-level outcomes?

1.2.2 Different channels performing different roles

An important outcome in a multichannel network is the extent to which the system as a whole facilitates the introduction of new products. New products may create value for the producer and channel partners by increasing margins, while simultaneously providing end-user value by improving product performance. The literature provides ample evidence of intermediaries’ difficulty in deciding whether or not to carry a product; for example, retailers find decisions regarding newly introduced consumer products particularly challenging. The channel partner not only must consider whether the product is suitable for its end-users but also must consider how its adopt versus non-adopt decision may impact its relationship with the producer. Channel partners’ decisions regarding new product acceptance are particularly difficult in multichannel systems with the presence of direct producer-to-end-user channels or interchannel competition among different types of channel partners and configurations of indirect channels. Potential research questions include:

  • How does distribution coverage arise? Sales and distribution coverage of multiple brands of a new consumer durable in competing channel types could be analyzed. Previous research has established that some channel types may act as “market-makers” such that increases in coverage increase durable sales, whereas others may act as “market-takers”, increasing coverage in response to sales increases. A third possibility is that some intermediaries may engage in both roles simultaneously, such as in fast-moving consumer goods categories (Bronnenberg et al. 2000).

  • What is the role of all-under-one-roof value stores (hypermarkets such as Tesco or Wal-Mart Supercenter) in new product distribution? This channel type has seen explosive growth in recent years but does not fit current taxonomies. All-under-one-roof value stores include both a supermarket and a large general merchandise offering. These characteristics make hypermarkets both habitual stores (meriting regular trips for consumables) and destination stores (meriting special visits for uncommon purchases, such as durables). Future research could explore the possibility that this combination gives hypermarkets unusual properties that may influence coverage decisions within other types of channels and the resulting sales in these channels.

  • Can some types of channels act as “scouts” and others as “troops” when increasing (or decreasing) coverage of a new product? Troop channels imitate scout channel decisions—an effect that has been shown among stores within a channel (Jones and Mason 1990), but not between entire channel types.

1.3 Customer management and multiple channels

We now argue that there is an enormous potential to integrate this channel design literature with the emerging literature on customer relationship management (CRM), thus taking a more comprehensive view of the channel network “triangle” and incorporating the perspective of all channel actors.

1.3.1 The motivation to link customer management and channel design

There is a rich history in interorganizational research of studying an issue from the firm or dyad perspective and translating the insights into channel design. This research is valuable, but has not taken the multichannel customer perspective. In contrast, a developing field within the CRM arena takes the multichannel customer perspective. This is called “multichannel customer management” (Neslin et al. 2006). This area examines customer acquisition and retention in a multichannel context. However, this stream has paid less attention to the links between customers and channel design and coordination. Hence, we see an opportunity to integrate traditional channel design research and multichannel customer management, in the realms of both customer acquisition and customer retention/development.

1.3.2 Customer acquisition

A key finding in multichannel customer management research is that the value of an acquired customer depends on the channel through which the customer is acquired. Verhoef and Donkers (2005) found that customer retention and cross-buying rates differed depending on acquisition channel. Villanueva et al. (2008) found that customers acquired through the firm’s marketing activities performed better in the short run, but word-of-mouth-acquired customers performed better in the long run.

To link these findings to channel design, we need to understand how acquisition channel characteristics relate to subsequent customer performance. A recent study by Banerjee et al. (2008) addresses these issues by linking governance theory (Dutta et al. 1995; Anderson 1985) to the goals which a firm seeks to achieve through acquiring channels. The authors find support for their contention that firms use a mixture of company owned and independent channels because they seek to simultaneously achieve quantity (volume of customers acquired) and quality (revenues/customer) goals by utilizing the appropriate customer acquisition channels. This study provides further evidence linking acquiring channels to customer performance and provides a substantive link between the characteristics of acquiring channels and long-term and short-term customer level outcomes.

In summary, we are beginning to understand the role that channels play in customer acquisition. More work is needed, however, especially building on Banerjee et al. (2008) that examines the role of channel characteristics. This in turn would provide more guidance for channel design.

1.3.3 Customer retention and development

To understand the issues regarding customer retention and development, we must first understand the customer (end-user) decision process in a multichannel environment. Customer channel decisions occur in the search, purchase, and after-sales phases, where the customer can choose to use one or several channels, for a given firm or across firms. Horizontal multichannel usage entails using different channels for different phases of the decision process, e.g., one can search on the Internet but purchase from a VAR. Vertical multichannel usage means using different channels for the same phase of the decision process, e.g., one can purchase from sales reps, the Internet, mail order, or a VAR. Vertical multichannel usage may increase customer satisfaction but cause vertical channel conflict, as described in previous sections. We focus below on horizontal channel usage.

Search-to-purchase horizontal multichannel usage

Customers use different channels for search and purchase (Verhoef et al. 2007). Verhoef et al. propose that three factors influence this “research shopping”. First, the customer may find channel A more attractive for search than channel B; channel B may be more attractive for purchase. Second, the search channel may have ineffective “lock-in”. It may be too easy for the customer just to gather information through that channel and make the purchase elsewhere. Third, the search and purchase channels may be synergistic in that searching on channel A enhances channel B’s effectiveness as a purchase channel. Verhoef et al. found that Internet-to-retail-store was the most common form of search-to-purchase horizontal multichannel usage and that all three determinants came into play: The Internet excelled in search convenience but was deficient regarding privacy, product inspection ability, service, and keeping the customer. Finally, there was some channel synergy between Internet and store.

Future research questions regarding search-to-purchase horizontal multichannel usage include:

  • To what extent does this phenomenon, already quantified in B2C settings, apply to B2B settings? Given a B2B customer’s decision process complexity, it is possible that they follow different horizontal multichannel usage patterns.

  • How should the firm divvy up the “credit” for the sale between the search channel and the purchase channel?, i.e., how much credit should channel A get if it was crucial for search but the purchase was made in channel B? How can each channel’s contribution be determined? This has implications for management compensation.

  • Should firms embrace or avoid search-to-purchase multichannel usage? The concern is the firm can lose customers along the way, i.e., an IT director wishing to purchase laptops for employees can search Dell’s website, gather useful information, and then go to a value-added reseller and buy HPs.

  • If the firm decides to embrace search-to-purchase multichannel usage, how should channels be designed to make this mutually beneficial for the firm and the customer?

Purchase-to-after-sales horizontal multichannel usage

The after-sales stage is critical for business customers. This is because postpurchase challenges faced by customers often have negative, long-term relationship and performance consequences for suppliers. For instance, IT implementation projects are notoriously disaster-prone, with ultimate failure rates approaching 50% to 80% by some estimates (Zhen 2005). This has made successful technology “assimilation” by customers as important as product adoption for technology companies (Cusumano 2004). Many firms engage in alliances with third-party service providers to assist with service provision to customers in the postpurchase phase. However, under certain conditions, these alliances may not be efficient or effective. Moreover, since both goods and services dominant companies are posited to benefit from adopting a “service-dominant” logic (Vargo and Lusch 2008), which dimensions of a service-oriented strategy (Homburg et al. 2003) most impact customer specific outcomes?

Recent research by deLeon and Chatterjee (2008) addresses some of these questions. A test of their conceptual model in the context of business intelligence systems finds that it is not the scope of services provided, but rather the services mindset on the part of vendors that plays the dominant role in building positive customer relationships. They conclude that horizontal multichannel usage by customers with third party provision of service elements such as system installation, training, integration, or other services do not hamper customer-level outcomes (e.g., satisfaction).

However, effective management of alliances within a channel network is critical. Future research could address the following research questions:

  • How can producers manage channel conflict within the channel network? What type of compensation systems and control mechanisms maximize value creation at the network level?

  • When should producers internalize after-sales service versus using a network of independent service providers? How does this decision impact customer and channel-system outcomes?

2 Conclusion

In this paper, we identify several research opportunities in the channel design and management domain. In particular, we call for a more complete view of the channel value network and of how channel systems create value for the participants. Channels of distribution should be seen as value constellations or value networks. Customers are important actors in this network, both as value creators and as value appropriators. This emphasis will likely require new conceptual tools, theories, and approaches and/or methods. In particular, a more complete view of the channel system will increase the complexity of data collection. The need to account for relationships and outcomes at different levels of analysis will likely require more complex theories or the integration of theories at different levels of analysis. A clear definition of the unit of analysis becomes even more critical. Evolving from “traditional” manufacturer → distributor → customer distribution systems to value creation within multichannel marketing offers great opportunities for future research. We elaborate further on some empirical challenges below.

Empirical challenges and opportunities

An important challenge when analyzing complex channel systems comprising multiple channel types and entities is the need to consider possible multilevel effects. Whether direct or indirect channels are used and regardless of the types of channel partners involved in those indirect channels, issues concerning multilevel relationships between channel participants should be considered. In reality, any B2B relationship is comprised of a complex web of cross-firm linkages at three distinct levels of analysis—the interfirm, interpersonal, and person-to-firm levels. For example, researchers studying the relationship between a manufacturer and business end-user may examine the selling firm–buyer firm relationship, cross-firm interpersonal relationships between salesperson and buyer and/or person–firm relationships such as between an individual buyer and the selling firm as a collective entity. Even in consumer markets, the consumer may have relationships with the selling firm or with an individual salesperson or service provider within that selling firm.

Consideration of concurrent multilevel relationships is important, for failure to account for cross-level effects can lead to overestimation or underestimation of effects between constructs at the same relationship level. For example, the research of Palmatier et al. (2007a, b) suggests that effects of a buyer’s loyalty to the selling firm on the seller’s financial outcomes can be overestimated if salesperson-owned loyalty is not explicitly modeled. The relative impact of these two types of loyalty will vary greatly depending on the context and the specifics of a focal relationship, but unless salesperson-owned loyalty is assessed, one cannot be certain how much of this ambiguous “loyalty to the firm” is truly vested in the buyer’s relationship with the salesperson. On the other hand, Palmatier et al. (2008) demonstrate that focusing solely on the buyer’s relationship with the salesperson can underestimate the effects of that selling firm’s relationship marketing. The findings of these and other research studies which incorporate variables at more than one relationship level (e.g., Doney and Cannon 1997; Fang et al. (2008); Iacobucci and Ostrom 1996; Sirdeshmukh et al. 2002) indicate that researchers should consider what, if any, cross-level effects may be relevant for their specific constructs of interest and research context.

While these multilevel effects exist in any B2B relationship, they are likely to be more complex and diverse in multichannel settings. Multichannel systems typically involve a complex web of B2B relationships among the producer, its multiple channels, and the end-user organization, as well as among the individuals within each of these organizations. For instance, people within an end-user organization frequently interact with a sales team comprising people from different organizations within the channel network. It is important to account for these multilevel relationships when assessing the effectiveness of the relationship marketing efforts of the different players in the channel system.

The existence of simultaneous relationships within the B2B interaction implies that survey researchers should strive to focus respondents and especially informants very clearly at the desired level of analysis—even when the study focuses only on a single level. However, if constructs at multiple levels are studied within a single survey, the importance of clarity and consistency in item development and survey design are particularly critical. Empirical modelers who use secondary data should also consider how their models may be biased by the omission of relevant interpersonal and person–firm variables. Efforts to theoretically identify, measure, and integrate such variables when appropriate appear to offer the potential to enrich the generalizability of B2B models.

Investigations of B2B relationships could also be enriched by judicious use of experimental research. Researchers have been unable to peek into the black box of relationship development due to method constraints. Although they have emphasized statistical solutions and causal modeling techniques to identify the “average causal effects” (e.g., Diamantopoulos and Siguaw 2000), experiments offer the opportunity to determine causal direction in a more definitive manner than survey or secondary methods.

Experiments can be particularly useful when retrospective methods cannot disentangle the effects of focal independent variables or when an independent variable itself may be impacted by the outcome over time. For example, Scheer and Stern (1992) used experimental research to examine whether attitudes are impacted more by the type of influence exercised or by the outcomes the firm receives from compliance with that influence. When one receives favorable outcomes from compliance with another’s influence, the self-serving bias argues that the influenced party will retrospectively adjust its recollection about the nature of that influence and the party’s original willingness to pursue that ultimately successful course of action. If this ex post facto adjustment occurs, retrospective methods are unlikely to be able to capture the original attitudinal effects of influence type or to disentangle them from the effects of the resulting outcomes of compliance. However, a key challenge in conducting experiments in B2B research is that it is difficult to capture the richness of the relational environment in an experimental setting. Wang et al. (2008) propose that experimental case research can cope with this problem, where they employ rich business contexts and two design stages to study the trust building process.