IDEAS home Printed from https://ideas.repec.org/p/cte/wbrepe/wb090868.html
   My bibliography  Save this paper

Optimal risk in marketing resource allocation

Author

Listed:
  • Vidal-Sanz, Jose M.
  • Balbás, Alejandro
  • Esteban-Bravo, Mercedes

Abstract

Marketing resource allocation is increasingly based on the optimization of expected returns on investment. If the investment is implemented in a large number of repetitive and relatively independent simple decisions, it is an acceptable method, but risk must be considered otherwise. The Markowitz classical mean-deviation approach to value marketing activities is of limited use when the probability distributions of the returns are asymmetric (a common case in marketing). In this paper we consider a unifying treatment for optimal marketing resource allocation and valuation of marketing investments in risky markets where returns can be asymmetric, using coherent risk measures recently developed in finance. We propose a set of first order conditions for the solution, and present a numerical algorithm for the computation of the optimal plan. We use this approach to design optimal advertisement investments in sales response management

Suggested Citation

  • Vidal-Sanz, Jose M. & Balbás, Alejandro & Esteban-Bravo, Mercedes, 2009. "Optimal risk in marketing resource allocation," DEE - Working Papers. Business Economics. WB wb090868, Universidad Carlos III de Madrid. Departamento de Economía de la Empresa.
  • Handle: RePEc:cte:wbrepe:wb090868
    as

    Download full text from publisher

    File URL: https://e-archivo.uc3m.es/rest/api/core/bitstreams/4ffdc422-6768-4558-80ea-74636cbf5c7e/content
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Leeflang, P.S.H. & Wittink, Dick R., 2000. "Building models for marketing decisions: past, present and future," Research Report 00F20, University of Groningen, Research Institute SOM (Systems, Organisations and Management).
    2. repec:dgr:rugsom:00f20 is not listed on IDEAS
    3. Martin Natter & Thomas Reutterer & Andreas Mild & Alfred Taudes, 2007. "—An Assortmentwide Decision-Support System for Dynamic Pricing and Promotion Planning in DIY Retailing," Marketing Science, INFORMS, vol. 26(4), pages 576-583, 07-08.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Gary L. Lilien & John H. Roberts & Venkatesh Shankar, 2013. "Effective Marketing Science Applications: Insights from the ISMS-MSI Practice Prize Finalist Papers and Projects," Marketing Science, INFORMS, vol. 32(2), pages 229-245, March.
    2. Risselada, Hans & Verhoef, Peter C. & Bijmolt, Tammo H.A., 2010. "Staying Power of Churn Prediction Models," Journal of Interactive Marketing, Elsevier, vol. 24(3), pages 198-208.
    3. Wiesel, Thorsten & Skiera, Bernd & Villanueva, Julian, 2011. "Customer Lifetime Value and Customer Equity Models Using Company-reported Summary Data," Journal of Interactive Marketing, Elsevier, vol. 25(1), pages 20-22.
    4. De Bruyn, Arnaud & Viswanathan, Vijay & Beh, Yean Shan & Brock, Jürgen Kai-Uwe & von Wangenheim, Florian, 2020. "Artificial Intelligence and Marketing: Pitfalls and Opportunities," Journal of Interactive Marketing, Elsevier, vol. 51(C), pages 91-105.
    5. Marusia Ivanova, 2007. "Genesis and Evolution of Market Share Predictive Models," Economic Studies journal, Bulgarian Academy of Sciences - Economic Research Institute, issue 2, pages 117-148.
    6. Horváth, Csilla & Wieringa, Jaap E., 2003. "Combining time series and cross sectional data for the analysis of dynamic marketing systems," Research Report 03F13, University of Groningen, Research Institute SOM (Systems, Organisations and Management).
    7. Schulz, Petra & Shehu, Edlira & Clement, Michel, 2019. "When consumers can return digital products: Influence of firm- and consumer-induced communication on the returns and profitability of news articles," International Journal of Research in Marketing, Elsevier, vol. 36(3), pages 454-470.
    8. Sibdari, Soheil & Pyke, David F., 2010. "A competitive dynamic pricing model when demand is interdependent over time," European Journal of Operational Research, Elsevier, vol. 207(1), pages 330-338, November.
    9. B. P. S. Murthi & Sumit Sarkar, 2003. "The Role of the Management Sciences in Research on Personalization," Management Science, INFORMS, vol. 49(10), pages 1344-1362, October.
    10. Kris Johnson Ferreira & Bin Hong Alex Lee & David Simchi-Levi, 2016. "Analytics for an Online Retailer: Demand Forecasting and Price Optimization," Manufacturing & Service Operations Management, INFORMS, vol. 18(1), pages 69-88, February.
    11. Yang, Yang & Cao, Yang & Yang, Li-Ting (Grace), 2017. "Product diversification and property performance in the urban lodging market: The relationship and its moderators," Tourism Management, Elsevier, vol. 59(C), pages 363-375.
    12. Agarwal, Manoj K. & Ma, Zecong & Park, Chang Hee & Zheng, Yilong, 2022. "The impact of a manufacturer’s financial liquidity on its market strategies and pricing and promotion decisions in retail grocery markets," Journal of Business Research, Elsevier, vol. 142(C), pages 844-857.
    13. Ullah, Subhan & Attah-Boakye, Rexford & Adams, Kweku & Zaefarian, Ghasem, 2022. "Assessing the influence of celebrity and government endorsements on bitcoin’s price volatility," Journal of Business Research, Elsevier, vol. 145(C), pages 228-239.
    14. G Baltas, 2005. "Modelling category demand in retail chains," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 56(11), pages 1258-1264, November.
    15. Melvin Woodley, 2021. "Decoupling the individual effects of multiple marketing channels with state space models," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 20(3), pages 248-255, June.
    16. Fildes, Robert & Ma, Shaohui & Kolassa, Stephan, 2019. "Retail forecasting: research and practice," MPRA Paper 89356, University Library of Munich, Germany.
    17. Thomas Niemand & Sascha Kraus & Sophia Mather & Antonio C. Cuenca-Ballester, 2020. "Multilevel marketing: optimizing marketing effectiveness for high-involvement goods in the automotive industry," International Entrepreneurship and Management Journal, Springer, vol. 16(4), pages 1367-1392, December.
    18. van Diepen, Merel & Donkers, Bas & Franses, Philip Hans, 2009. "Does irritation induced by charitable direct mailings reduce donations?," International Journal of Research in Marketing, Elsevier, vol. 26(3), pages 180-188.
    19. Pauwels, Koen & Neslin, Scott A., 2015. "Building With Bricks and Mortar: The Revenue Impact of Opening Physical Stores in a Multichannel Environment," Journal of Retailing, Elsevier, vol. 91(2), pages 182-197.
    20. Nagengast, Liane & Evanschitzky, Heiner & Blut, Markus & Rudolph, Thomas, 2014. "New Insights in the Moderating Effect of Switching Costs on the Satisfaction–Repurchase Behavior Link," Journal of Retailing, Elsevier, vol. 90(3), pages 408-427.

    More about this item

    Keywords

    Resource allocation;

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:cte:wbrepe:wb090868. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Ana Poveda (email available below). General contact details of provider: http://www.business.uc3m.es/es/index .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.