Authors: Aurifeille; Chris Medlin; Jacques-Marie
In business science, the studied objects are often groups ofpartners rather than independent firms. Extending classical segmentation to thesepolyads raises conceptual problems, principally: defining what should be consideredas common or specific at the partners? and at the segment levels. The generalapproaches consist either in merging partners characteristics and performances intoa single macro-object, thus loosing their specific contributions to each partner’sperformance, or in modelling partners? performance as if their models were independent.As a step to understanding, how partnership influences firms? performance,the dyadic (i.e. two partners?) case is studied. First, some theoretical issuesconcerning the degrees of individual and contributive interest in a dyadic populationare discussed. Next, partnership’s conceptualisation is based upon two modelsfor each firm: a ‘self-model? that reflects how the firm’s characteristics explain itsown performance, and a ?contributive-model? model that reflects how thesecharacteristics influence the partner’s performance. This allows definition of threerelationship modes: merging, teaming and sharing. Subsequently, dyad segmentationstrategies are discussed according to their capacity to reflect the modes of partnershipand a dyadic clusterwise regression method, based on a genetic algorithm,is presented. Finally, the method is illustrated empirically using actual data of businesspartners in the software market.
Journal: European Journal of Economic and Social Systems (15 – 3-16)
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Publish Year: 2001
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