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Handbook of Marketing Decision Models pp 527–559Cite as

Marketing Engineering: Models that Connect with Practice

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Part of the book series: International Series in Operations Research & Management Science ((ISOR,volume 121))

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Notes

  1. 1.

    Wierenga and van Bruggen (2000) define MMSS as “Any device combining (1) information technology, (2) analytic capabilities, (3) marketing data and (4) marketing knowledge made available to one or more marketing decision makers to improve the quality of marketing management.” This definition represents a “systems” view of decision support for the entire marketing function, whereas marketing engineering is focused more specifically on the analysis methods and processes (i.e., those that have a strong analytic component). MMSS and MDSS also incorporate non-analytic processes (e.g., analogizing and creativity enhancement), as well as aspects of the systems architecture, an issue beyond the scope of ME as we define it.

  2. 2.

    The reluctance of decision makers to use decision models even when those models can improve performance is not restricted to marketing.. For example, DSSs significantly improve a doctor’s clinical performance in prescribing decisions (Hunt et al. 1998), yet medical professionals are largely unwilling to use such DSSs (Sintchenko et al. 2004; Lapointe and Rivard 2006),

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Authors and Affiliations

  1. Pennsylvania State University, USA

    Gary L. Lilien

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  1. Gary L. Lilien
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  2. Arvind Rangaswamy
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Correspondence to Gary L. Lilien .

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Editors and Affiliations

  1. Erasmus University, Rotterdam, The Netherlands

    Berend Wierenga (Prof) (Prof)

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Lilien, G.L., Rangaswamy, A. (2008). Marketing Engineering: Models that Connect with Practice. In: Wierenga, B. (eds) Handbook of Marketing Decision Models. International Series in Operations Research & Management Science, vol 121. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-78213-3_16

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