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An analytical model that links customer-perceived value and competitive strategies

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  • Said Echchakoui

    (University of Quebec at Rimouski)

Abstract

Several authors developed predictive analytic models that link the value that represents customers to a firm (i.e., customer lifetime value) to several outcome variables, such as customer profitability, in relationship marketing. However, similar models that link the value that customers perceive and firm outcomes or customer responses are uncommon. To reduce this gap, we construct an analytic model that links customer-perceived value and a company’s competitive strategy, achieved through a multi-attribute model, analytic hierarchy processing, and a conceptualization of value that considers disparity between benefits and sacrifices. Operationalized in a context of industrial enterprise, the model predicts and orients a company’s competitive strategy and extends generic competitive strategies introduced in Bowman’s strategy clock mode by identifying when two strategies create competitive advantages.

Suggested Citation

  • Said Echchakoui, 2018. "An analytical model that links customer-perceived value and competitive strategies," Journal of Marketing Analytics, Palgrave Macmillan, vol. 6(4), pages 138-149, December.
  • Handle: RePEc:pal:jmarka:v:6:y:2018:i:4:d:10.1057_s41270-018-0043-9
    DOI: 10.1057/s41270-018-0043-9
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    References listed on IDEAS

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    Cited by:

    1. Adel Hatami-Marbini & Siavash Hekmat & Per J. Agrell, 2022. "A strategy-based framework for supplier selection: a grey PCA-DEA approach," Operational Research, Springer, vol. 22(1), pages 263-297, March.
    2. Zhenfang Zhang & Nan Zhang & Jiguang Wang, 2022. "The Influencing Factors on Impulse Buying Behavior of Consumers under the Mode of Hunger Marketing in Live Commerce," Sustainability, MDPI, vol. 14(4), pages 1-19, February.
    3. Kalle Nuortimo & Janne Harkonen, 2019. "Establishing an automated brand index based on opinion mining: analysis of printed and social media," Journal of Marketing Analytics, Palgrave Macmillan, vol. 7(3), pages 141-151, September.

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