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

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  • Albers, Sönke

Abstract

In der Literatur hat man das im Marketing bedeutende Problem der Verteilung einer knappen Ressource, von der eine Umsatzwirkung ausgeht, auf Produkte oder Marktsegmente dadurch zu lösen versucht, daß man die Parameter vorher spezifizierter Umsatzreaktionsfunktionen statistisch schätzt und dann das Optimum mit geeigneten Algorithmen bestimmt. Im Gegensatz dazu findet man in der Praxis vorwiegend einfache Allokationsregeln, z.B. Budgetverteilung proportional zum bisherigen oder geplanten Umsatz, deren Güte allerdings fraglich ist. In diesem Beitrag wird aus der Optimalitätsbedingung ohne Unterstellung spezifischer Funktionstypen eine Regel abgeleitet, nach der im Optimum die Deckungsbeiträge multipliziert mit den jeweiligen Elastizitäten gleich sein müssen. Mit Hilfe eines computergestützten Simulationsexperimentes ist für unterschiedliche Datensituationen die Güte der verschiedenen heuristischen Allokationsregeln untersucht worden. Die Ergebnisse zeigen, daß die hier vorgeschlagene und leicht implementierbare Allokationsregel bereits bei einmaliger Anwendung zu sehr guten Ergebnissen und nach wenigen Perioden zu fast-optimalen Lösungen führt sowie zum Optimum konvergiert. Alle anderen Allokationsregeln sind deutlich unterlegen und weisen keine Konvergenzeigenschaft auf. Abschließend wird gezeigt, wie die Regel modifiziert werden muß, wenn man die Prämissen voneinander unabhängiger Allokationseinheiten sowie statischer, symmetrischer und deterministischer Reaktionsfunktionen aufhebt.

Suggested Citation

  • Albers, Sönke, 1996. "Regeln für die Allokation eines Marketing-Budgets auf Produkte oder Marktsegmente," Manuskripte aus den Instituten für Betriebswirtschaftslehre der Universität Kiel 413, Christian-Albrechts-Universität zu Kiel, Institut für Betriebswirtschaftslehre.
    • Handle: RePEc:zbw:cauman:413
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    References listed on IDEAS

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    1. Pradeep K. Chintagunta, 1993. "Investigating the Sensitivity of Equilibrium Profits to Advertising Dynamics and Competitive Effects," Management Science, INFORMS, vol. 39(9), pages 1146-1162, September.
    2. Dennis H. Gensch & Ulf Peter Welam, 1973. "An Optimum Budget Allocation Model for Dynamic, Interacting Market Segments," Management Science, INFORMS, vol. 20(2), pages 179-190, October.
    3. Hanan Luss & Shiv K. Gupta, 1975. "Technical Note—Allocation of Effort Resources among Competing Activities," Operations Research, INFORMS, vol. 23(2), pages 360-366, April.
    4. Duncan M. Holthausen, Jr. & Gert Assmus, 1982. "Advertising Budget Allocation under Uncertainty," Management Science, INFORMS, vol. 28(5), pages 487-499, May.
    5. Peter Doyle & John Saunders, 1990. "Multiproduct Advertising Budgeting," Marketing Science, INFORMS, vol. 9(2), pages 97-113.
    6. Leonard M. Lodish & Ellen Curtis & Michael Ness & M. Kerry Simpson, 1988. "Sales Force Sizing and Deployment Using a Decision Calculus Model at Syntex Laboratories," Interfaces, INFORMS, vol. 18(1), pages 5-20, February.
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    1. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. Wolfgang Polasek, 2011. "Marketing Response Models for Shrinking Beer Sales in Germany," Working Paper series 50_11, Rimini Centre for Economic Analysis.
    7. 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.
    8. 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.
    9. 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.
    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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