How attributions of coproduction motives shape customer relationships over time

Pascal Güntürkün (), Till Haumann (), Laura Marie Edinger-Schons () and Jan Wieseke ()
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Pascal Güntürkün: Vienna University of Economics and Business
Till Haumann: South Westphalia University of Applied Sciences
Laura Marie Edinger-Schons: University of Hamburg
Jan Wieseke: Ruhr-University of Bochum

Journal of the Academy of Marketing Science, 2023, vol. 51, issue 5, No 3, 990-1018

Abstract: Abstract Despite the proliferation of coproduction concepts in various B2C contexts, knowledge on how coproduction shapes customer relationships is still surprisingly limited, as prior studies find mixed results and are bound to a short-term perspective. The present study addresses these limitations by providing first insights into the underlying psychological processes that explain differences in the short- and long-term relationship consequences of positive and negative coproduction perceptions. Drawing from the multiple inference model, this research shows how customers’ ambivalent attributions of a firm’s coproduction motives (i.e., firm-serving and customer-serving) affect customer satisfaction, willingness to pay, and spending behavior over time. The results of a latent growth analysis based on a longitudinal field study (n1 = 12,662; six waves) show that coproduction can harm customer relationships in the long-run, as the detrimental effects of firm-serving motive attributions are temporally more persistent than the favorable but ephemeral effects of customer-serving motive attributions. An additional experiment (n2 = 931) and field study (n3 = 360) confirm the generalizability of the key findings and provide new managerial insights into how firm-specific characteristics of a coproduction concept (i.e., coproduction intensity, design freedom, monetary savings) influence customer attributions different coproduction motives and thereby shape customer relationships over time.

Keywords: Customer participation; Coproduction; Inferred firm motives; Longitudinal design; Latent growth modeling (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s11747-022-00910-6

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