IDEAS home Printed from https://ideas.repec.org/p/vnm/wpaper/167.html
   My bibliography  Save this paper

Leading advertisers efficiency evaluated by data envelopment analysis

Author

Listed:
  • Andrea Ellero

    (Department of Applied Mathematics, University of Venice)

  • Stefania Funari

    (Department of Applied Mathematics, University of Venice)

  • Elena Moretti

    (Department of Applied Mathematics, University of Venice)

Abstract

In this paper we analyze the problem of measuring the advertising efficiency of the Leading US Advertisers during the period 2001-2006. We use the DEA (Data Envelopment Analysis) approach that enables to evaluate the relative efficiency in case of multiple inputs and outputs. In particular, the classical CCR-DEA model is first implemented in each year considered; a windows analysis approach is then used in order to better capture the dynamics of efficiency. Finally, the effect on efficiency of advertising spending over time, is captured by Adstock as an additional variable of the DEA model. The dynamics of Adstock is described by a finite difference equation.

Suggested Citation

  • Andrea Ellero & Stefania Funari & Elena Moretti, 2008. "Leading advertisers efficiency evaluated by data envelopment analysis," Working Papers 167, Department of Applied Mathematics, Università Ca' Foscari Venezia.
    • Handle: RePEc:vnm:wpaper:167
    as

    Download full text from publisher

    File URL: http://virgo.unive.it/wpideas/storage/2008wp167.pdf
    File Function: First version, 2008
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Luo, Xueming & Donthu, Naveen, 2005. "Assessing advertising media spending inefficiencies in generating sales," Journal of Business Research, Elsevier, vol. 58(1), pages 28-36, January.
    2. Ray,Subhash C., 2012. "Data Envelopment Analysis," Cambridge Books, Cambridge University Press, number 9781107405264, January.
    3. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    4. Cook, Wade D. & Seiford, Larry M., 2009. "Data envelopment analysis (DEA) - Thirty years on," European Journal of Operational Research, Elsevier, vol. 192(1), pages 1-17, January.
    5. Mahajan, Jayashree, 1991. "A data envelopment analytic model for assessing the relative efficiency of the selling function," European Journal of Operational Research, Elsevier, vol. 53(2), pages 189-205, July.
    6. Fare, Rolf & Grosskopf, Shawna & Seldon, Barry J. & Tremblay, Victor J., 2004. "Advertising efficiency and the choice of media mix: a case of beer," International Journal of Industrial Organization, Elsevier, vol. 22(4), pages 503-522, April.
    7. William W. Cooper & Lawrence M. Seiford & Kaoru Tone, 2006. "Introduction to Data Envelopment Analysis and Its Uses," Springer Books, Springer, number 978-0-387-29122-2, October.
    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. Martin Eling, 2006. "Performance measurement of hedge funds using data envelopment analysis," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 20(4), pages 442-471, December.
    2. Yang, Guo-liang & Fukuyama, Hirofumi & Chen, Kun, 2019. "Investigating the regional sustainable performance of the Chinese real estate industry: A slack-based DEA approach," Omega, Elsevier, vol. 84(C), pages 141-159.
    3. Matthias Staat & Maik Hammerschmidt, 2004. "A Super Efficiency Model for Product Evaluation," Microeconomics 0402011, University Library of Munich, Germany.
    4. Adel Hatami-Marbini & Madjid Tavana & Kobra Gholami & Zahra Ghelej Beigi, 2015. "A Bounded Data Envelopment Analysis Model in a Fuzzy Environment with an Application to Safety in the Semiconductor Industry," Journal of Optimization Theory and Applications, Springer, vol. 164(2), pages 679-701, February.
    5. Chen, Chien-Ming & van Dalen, Jan, 2010. "Measuring dynamic efficiency: Theories and an integrated methodology," European Journal of Operational Research, Elsevier, vol. 203(3), pages 749-760, June.
    6. Petridis, Konstantinos & Malesios, Chrisovalantis & Arabatzis, Garyfallos & Thanassoulis, Emmanuel, 2013. "Efficiency analysis of forestry journals: Suggestions for improving journals’ quality," Journal of Informetrics, Elsevier, vol. 7(2), pages 505-521.
    7. Ströhl, Florian & Borsch, Erik & Souren, Rainer, 2018. "Integration von Gewichtsrestriktionen in das DEA-Modell nach Charnes, Cooper und Rhodes: Exemplarische Optionen und Auswirkungen," Ilmenauer Schriften zur Betriebswirtschaftslehre, Technische Universität Ilmenau, Institut für Betriebswirtschaftslehre, volume 3, number 32018, September.
    8. Walter Briec & Kristiaan Kerstens & Ignace Van de Woestyne, 2022. "Nonconvexity in Production and Cost Functions: An Exploratory and Selective Review," Springer Books, in: Subhash C. Ray & Robert G. Chambers & Subal C. Kumbhakar (ed.), Handbook of Production Economics, chapter 18, pages 721-754, Springer.
    9. Sarmento, Joaquim Miranda & Renneboog, Luc & Verga-Matos, Pedro, 2017. "Measuring highway efficiency : A DEA approach and the Malquist index," Other publications TiSEM 23264815-321e-45a3-83ee-9, Tilburg University, School of Economics and Management.
    10. Mehmet APAN & İhsan ALP & Ahmet ÖZTEL, 2019. "Determination of the Efficiencies of Textile Firms Listed in Borsa İstanbul by Using DEA-Window Analysis," Sosyoekonomi Journal, Sosyoekonomi Society, issue 27(42).
    11. Marco Marto & João Lourenço Marques & Mara Madaleno, 2022. "An Evaluation of the Efficiency of Tertiary Education in the Explanation of the Performance of GDP per Capita Applying Data Envelopment Analysis (DEA)," Sustainability, MDPI, vol. 14(23), pages 1-20, November.
    12. Zurano-Cervelló, Patricia & Pozo, Carlos & Mateo-Sanz, Josep María & Jiménez, Laureano & Guillén-Gosálbez, Gonzalo, 2019. "Sustainability efficiency assessment of the electricity mix of the 28 EU member countries combining data envelopment analysis and optimized projections," Energy Policy, Elsevier, vol. 134(C).
    13. Chia-Nan Wang & Hoang-Phu Nguyen & Cheng-Wen Chang, 2021. "Environmental Efficiency Evaluation in the Top Asian Economies: An Application of DEA," Mathematics, MDPI, vol. 9(8), pages 1-19, April.
    14. Rashidi, Kamran & Cullinane, Kevin, 2019. "Evaluating the sustainability of national logistics performance using Data Envelopment Analysis," Transport Policy, Elsevier, vol. 74(C), pages 35-46.
    15. Stepan Zemtsov & Maxim Kotsemir, 2019. "An assessment of regional innovation system efficiency in Russia: the application of the DEA approach," Scientometrics, Springer;Akadémiai Kiadó, vol. 120(2), pages 375-404, August.
    16. Petr PRŮŠA & Stefan JOVČIĆ & Josef SAMSON & Zuzana KOZUBÍKOVÁ & Aleš KOZUBÍK, 2020. "Using A Non-Parametric Technique To Evaluate The Efficiency Of A Logistics Company," Transport Problems, Silesian University of Technology, Faculty of Transport, vol. 15(1), pages 153-161, March.
    17. Meng, Fanyi & Su, Bin & Thomson, Elspeth & Zhou, Dequn & Zhou, P., 2016. "Measuring China’s regional energy and carbon emission efficiency with DEA models: A survey," Applied Energy, Elsevier, vol. 183(C), pages 1-21.
    18. Yang, Guo-liang & Yang, Jian-Bo & Xu, Dong-Ling & Khoveyni, Mohammad, 2017. "A three-stage hybrid approach for weight assignment in MADM," Omega, Elsevier, vol. 71(C), pages 93-105.
    19. Wanfang Shen & Guoliang Yang & Zhongbao Zhou & Wenbin Liu, 2019. "DEA models with Russell measures," Annals of Operations Research, Springer, vol. 278(1), pages 337-359, July.
    20. Trigo Gamarra, Lucinda, 2007. "Single- versus multi-channel distribution strategies in the German life insurance market: A cost and profit efficiency analysis," Thuenen-Series of Applied Economic Theory 81, University of Rostock, Institute of Economics.

    More about this item

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • M37 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - Advertising

    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:vnm:wpaper:167. 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: Daria Arkhipova (email available below). General contact details of provider: https://edirc.repec.org/data/dmvenit.html .

    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.