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Regeln für die Allokation eines Marketing-Budgets auf Produkte oder Marktsegmente

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  • Sönke Albers

    (Christian-Albrechts-Universität zu Kiel)

Abstract

Summary The problem of optimally allocating a scarce resource with impact on sales across products or market segments has been addressed in the marketing literature by statistically estimating the response functions and applying a nonlinear optimization algorithm. In contrast, managers typically use simple but nonoptimal allocation rules such as budgets proportional to past or planned sales. Here, a new and easy to implement rule is derived from the property that in the optimum the product of profit contribution and the respective elasticity should be equal across products and segments. The goodness of traditional rules as well as the new one is investigated with the help of a computer simulation experiment. The results show that the new rule is superior, provides very good solutions already in the first application, near-optimal solutions after a few consecutive applications and converges to the optimum.

Suggested Citation

  • Sönke Albers, 1998. "Regeln für die Allokation eines Marketing-Budgets auf Produkte oder Marktsegmente," Schmalenbach Journal of Business Research, Springer, vol. 50(3), pages 211-235, March.
  • Handle: RePEc:spr:sjobre:v:50:y:1998:i:3:d:10.1007_bf03371503
    DOI: 10.1007/BF03371503
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    Cited by:

    1. Wolfgang Polasek, 2011. "Marketing Response Models for Shrinking Beer Sales in Germany," Working Paper series 50_11, Rimini Centre for Economic Analysis.
    2. Cathérine Grisar & Matthias Meyer, 2016. "Use of simulation in controlling research: a systematic literature review for German-speaking countries," Management Review Quarterly, Springer, vol. 66(2), pages 117-157, April.
    3. Marc Fischer & Sönke Albers & Nils Wagner & Monika Frie, 2011. "Practice Prize Winner --Dynamic Marketing Budget Allocation Across Countries, Products, and Marketing Activities," Marketing Science, INFORMS, vol. 30(4), pages 568-585, July.
    4. Hans Buhl & Martin Gneiser & Julia Heidemann, 2009. "Ein modelltheoretischer Ansatz zur Planung von Investitionen in Kundenbeziehungen," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 20(2), pages 175-195, October.
    5. Albers, Sönke, 1998. "Optimale Allokation von Hochschul-Budgets," Manuskripte aus den Instituten für Betriebswirtschaftslehre der Universität Kiel 473, Christian-Albrechts-Universität zu Kiel, Institut für Betriebswirtschaftslehre.
    6. Manfred Krafft & Sönke Albers, 2000. "Ansätze zur Segmentierung von Kunden — Wie geeignet sind herkömmliche Konzepte?," Schmalenbach Journal of Business Research, Springer, vol. 52(6), pages 515-536, September.
    7. Christian-Albrechts-Universität zu Kiel, Institut für Betriebswirtschaftslehre (Ed.), 1999. "Jahresbericht 1998," Manuskripte aus den Instituten für Betriebswirtschaftslehre der Universität Kiel 495, Christian-Albrechts-Universität zu Kiel, Institut für Betriebswirtschaftslehre.
    8. Gahler, Daniel & Hruschka, Harald, 2016. "Resource Allocation Heuristics for Unknown Sales Response Functions with Additive Disturbances," University of Regensburg Working Papers in Business, Economics and Management Information Systems 488, University of Regensburg, Department of Economics.
    9. Uwe Götze & Constanze Linke, 2008. "Interne Unternehmensrechnung als Instrument des marktorientierten Zielkostenmanagements – ausgewählte Probleme und Lösungsansätze," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 19(1), pages 107-132, May.
    10. Bernd W. Wirtz & Torsten Olderog & Joachim Schwarz, 2003. "Strategische Erfolgsfaktoren in der Internetökonomie," Schmalenbach Journal of Business Research, Springer, vol. 55(1), pages 60-77, February.

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