Relationship Learning with Key Customers
Fred Selnes and James Sallis, 1999 [99-103]
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Many companies emphasize learning in their relationships with key customers in order to enhance their ability to deliver value. By sharing information about needs, preferences, products, systems, and competencies—and by developing systems for interpreting and integrating the information into organizational memory—the parties to a learning relationship can improve their competitive positions.
In this study, authors Selnes and Sallis develop a deeper understanding of learning processes in industrial customer-supplier relationships. In particular, they focus on how an organization can strengthen its learning capabilities in targeted customer relationships.
Through a synthesis of the marketing and organizational literature, as well as interviews with both sides of 13 buyer-seller pairs, they define a construct of relationship learning and propose a conceptual model that includes antecedents and consequences of relationship learning.
Selnes and Sallis develop the following propositions:
- External competition motivates relationship learning. As markets are opened up via cross-border trade agreements such as WTO, EU, and NAFTA, and through improving communication and transportation technologies, companies are under increasing pressure to develop their learning capabilities. All the countries in the sample were experimenting with different types of learning arrangements, from loosely coupled sales agreements to tightly governed contracts.
- External shock motivates relationship learning. In the farmed salmon industry, for example, the British "mad cow disease" crisis drastically increased consumer awareness of food sources, and prompted several producers and retailers to implement systems to trace lots of salmon back to specific farms and hatcheries.
- Increasing technological complexity motivates relationship learning. Some producers in the farmed salmon industry, for example, are relying on technological advances in smoking and filleting to increase product consistency and reduce waste; this is contingent on consistency and quality through the value chain, from fish farms through retailers.
- Transaction complexity and relationship complexity increase the motivation for relationship learning. As complexity increases, so do the number and seriousness of problems; thus customers and suppliers are motivated to increase learning to solve problems. An example of high transaction complexity is the purchase of a computer system involving mainframes, PCs, printers, and software delivered on short-term notice to be operative in a few days.
- Moderating the influence of these forces are two variables: relationship learning strategy (which defines learning objectives and the major mechanisms for how the learning process will be approached) and level of trust between the customer and supplier.
- Relationship learning has a positive effect on relationship efficiency and relationship effectiveness. In the field interviews, most respondents highlighted better understanding of customer needs as the most important effect of relationship learning. In the long run, high-learning relationships are likely to foster products and services that provide more value and are superior in solving problems for their users.
An organization can strengthen its learning capability in targeted customer relationships. When implementing a relationship learning strategy, managers must first define the objectives and major mechanisms for how the learning process will be approached. Next, they must develop mechanisms that facilitate the learning process through information sharing, joint interpretation, and integration into relationship memory. It is important that these elements are addressed simultaneously. Without a balanced approach, the potential for enhancing relationship learning is limited. As relationship learning relies on mutuality, it is important to ensure the willingness of the other party to cooperate.
Fred Selnes is Professor of Marketing and James Sallis is a doctoral fellow, both at the Norwegian School of Management BI.
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1999 Working Paper Series
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