IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0221167.html

Reconstructing systematic persistent impacts of promotional marketing with empirical nonlinear dynamics

Author

Listed:
  • Ray Huffaker
  • Andrew Fearne

Abstract

An empirical question of long-standing interest is how price promotions affect a brand’s sale shares in the fast-moving consumer-goods market. We investigated this question with concurrent promotions and sales records of specialty beer brands pooled over Tesco stores in the UK. Most brands were continuously promoted, rendering infeasible a conventional approach of establishing impact against an off-promotion sales baseline, and arguing in favor of a dynamics approach. Moreover, promotion/sales records were volatile without easily-discernable regularity. Past work conventionally attributed volatility to the impact of exogenous random shocks on stable markets, and reasoned that promotions have only an ephemeral impact on sales shares in stationary mean-reverting stochastic markets, or a persistent freely-wandering impact in nonstationary markets. We applied new empirical methods from the applied sciences to uncover an overlooked alternative: ‘systematic persistence’ in which promotional impacts evolve systematically in an endogenously-unstable market governed by deterministic-nonlinear dynamics. We reconstructed real-world market dynamics from the Tesco dataset, and detected deterministic-nonlinear market dynamics. We used reconstructed market dynamics to identify a complex network of systematic interactions between promotions and sales shares among competing brands, and quantified/characterized the dynamics of these interactions. For the majority of weeks in the study, we found that: (1) A brand’s promotions drove down own sales shares (a possibility recognized in the literature), but ‘cannibalized’ sales shares of competing brands (perhaps explaining why brands were promoted despite a negative marginal impact on own sales shares); and (2) Competitive interactions between brands owned by the same multinational brewery differed from those with outside brands. In particular, brands owned by the same brewery enjoyed a ‘mutually-beneficial’ relationship in which an incremental increase in the sales share of one marginally increased the sales share of the other. Alternatively, the sales shares of brands owned by different breweries preyed on each other’s market shares.

Suggested Citation

  • Ray Huffaker & Andrew Fearne, 2019. "Reconstructing systematic persistent impacts of promotional marketing with empirical nonlinear dynamics," PLOS ONE, Public Library of Science, vol. 14(9), pages 1-28, September.
  • Handle: RePEc:plo:pone00:0221167
    DOI: 10.1371/journal.pone.0221167
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0221167
    Download Restriction: no

    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0221167&type=printable
    Download Restriction: no

    File URL: https://libkey.io/10.1371/journal.pone.0221167?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Gershon Feder, 1979. "Pesticides, Information, and Pest Management under Uncertainty," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 61(1), pages 97-103.
    2. Golyandina, Nina & Korobeynikov, Anton, 2014. "Basic Singular Spectrum Analysis and forecasting with R," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 934-954.
    3. Marnik G. Dekimpe & Dominique M. Hanssens, 1995. "The Persistence of Marketing Effects on Sales," Marketing Science, INFORMS, vol. 14(1), pages 1-21.
    4. Hassani, Hossein, 2007. "Singular Spectrum Analysis: Methodology and Comparison," MPRA Paper 4991, University Library of Munich, Germany.
    5. Harold Glenn A. Valera & Jim Lee, 2016. "Do rice prices follow a random walk? Evidence from Markov switching unit root tests for Asian markets," Agricultural Economics, International Association of Agricultural Economists, vol. 47(6), pages 683-695, November.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Ray Huffaker & Garry Griffith & Charles Dambui & Maurizio Canavari, 2021. "Empirical Detection and Quantification of Price Transmission in Endogenously Unstable Markets: The Case of the Global–Domestic Coffee Supply Chain in Papua New Guinea," Sustainability, MDPI, vol. 13(16), pages 1-18, August.
    2. Cole, Matthew T. & McCullough, Michael, 2023. "California beer price posting: An exploratory analysis of pricing along the supply chain," Journal of Wine Economics, Cambridge University Press, vol. 18(3), pages 205-225, August.
    3. Haydar Demirhan, 2020. "dLagM: An R package for distributed lag models and ARDL bounds testing," PLOS ONE, Public Library of Science, vol. 15(2), pages 1-23, February.
    4. Andrés Martínez & Alfonso Salafranca & Ana E. Sipols & Clara Simon Blas & Daniel Hengel, 2024. "Distributed lags using elastic-net regularization for market response models: focus on predictive and explanatory capacity," Journal of Marketing Analytics, Palgrave Macmillan, vol. 12(2), pages 417-435, June.

    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. Xingmin Zhang & Zhiyong Li & Yiming Zhao & Lan Wang, 2025. "Carbon trading and COVID-19: a hybrid machine learning approach for international carbon price forecasting," Annals of Operations Research, Springer, vol. 345(2), pages 1267-1295, February.
    2. Mahdi Kalantari & Hossein Hassani, 2019. "Automatic Grouping in Singular Spectrum Analysis," Forecasting, MDPI, vol. 1(1), pages 1-16, October.
    3. Telesca, Luciano & Laib, Mohamed & Guignard, Fabian & Mauree, Dasaraden & Kanevski, Mikhail, 2019. "Linearity versus non-linearity in high frequency multilevel wind time series measured in urban areas," Chaos, Solitons & Fractals, Elsevier, vol. 120(C), pages 234-244.
    4. Huffaker, R. & Canavari, M. & Muñoz-Carpena, R., 2018. "Distinguishing between endogenous and exogenous price volatility in food security assessment: An empirical nonlinear dynamics approach," Agricultural Systems, Elsevier, vol. 160(C), pages 98-109.
    5. Winita Sulandari & Yudho Yudhanto & Paulo Canas Rodrigues, 2022. "The Use of Singular Spectrum Analysis and K-Means Clustering-Based Bootstrap to Improve Multistep Ahead Load Forecasting," Energies, MDPI, vol. 15(16), pages 1-22, August.
    6. Tang, Wenjin & Bu, Hui & Ji, Yuqiong & Li, Zhongfei, 2024. "Market uncertainty and information content in complex seasonality of prices," Pacific-Basin Finance Journal, Elsevier, vol. 86(C).
    7. Jones, Randall E. & Cacho, Oscar J., 2000. "A Dynamic Optimisation Model of Weed Control," 2000 Conference (44th), January 23-25, 2000, Sydney, Australia 123685, Australian Agricultural and Resource Economics Society.
    8. Serra, Teresa & Zilberman, David & Goodwin, Barry K. & Featherstone, Allen M., 2005. "Effects of Decoupling on the Average and the Variability of Output," 2005 International Congress, August 23-27, 2005, Copenhagen, Denmark 24601, European Association of Agricultural Economists.
    9. Yuyang Gao & Chao Qu & Kequan Zhang, 2016. "A Hybrid Method Based on Singular Spectrum Analysis, Firefly Algorithm, and BP Neural Network for Short-Term Wind Speed Forecasting," Energies, MDPI, vol. 9(10), pages 1-28, September.
    10. Lichtenberg, Erik & Zilberman, David & Archibald, Sandra O., 1990. "Economics and Pesticides," Working Papers 197750, University of Maryland, Department of Agricultural and Resource Economics.
    11. David J. Pannell, 1991. "Pests and pesticides, risk and risk aversion," Agricultural Economics, International Association of Agricultural Economists, vol. 5(4), pages 361-383, August.
    12. van de Gucht, Linda M. & Dekimpe, Marnik G. & Kwok, Chuck C. Y., 1996. "Persistence in foreign exchange rates," Journal of International Money and Finance, Elsevier, vol. 15(2), pages 191-220, April.
    13. Donya Rahmani & Saeed Heravi & Hossein Hassani & Mansi Ghodsi, 2016. "Forecasting time series with structural breaks with Singular Spectrum Analysis, using a general form of recurrent formula," Papers 1605.02188, arXiv.org.
    14. Carpentier, A. & Reboud, X., 2018. "Why farmers consider pesticides the ultimate in crop protection: economic and behavioral insights," 2018 Conference, July 28-August 2, 2018, Vancouver, British Columbia 277528, International Association of Agricultural Economists.
    15. Aman Kalteh, 2016. "Improving Forecasting Accuracy of Streamflow Time Series Using Least Squares Support Vector Machine Coupled with Data-Preprocessing Techniques," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(2), pages 747-766, January.
    16. 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.
    17. Tristan Le Cotty & Elodie Maître d’Hôtel & Raphael Soubeyran & Julie Subervie, 2018. "Linking Risk Aversion, Time Preference and Fertiliser Use in Burkina Faso," Journal of Development Studies, Taylor & Francis Journals, vol. 54(11), pages 1991-2006, November.
    18. Pan, Rui & Liu, Tongshen & Huang, Wei & Wang, Yuxin & Yang, Duo & Chen, Jie, 2023. "State of health estimation for lithium-ion batteries based on two-stage features extraction and gradient boosting decision tree," Energy, Elsevier, vol. 285(C).
    19. Harold Glenn A. Valera & Mark J. Holmes & Valerien O. Pede & Jean Balié, 2023. "How convergent are rice export prices in the international market?," Agricultural Economics, International Association of Agricultural Economists, vol. 54(1), pages 127-141, January.
    20. Yura Kim & Taeyeon Kim & Hye-Jeong Nam, 2021. "Marketing Investments and Corporate Social Responsibility," Sustainability, MDPI, vol. 13(9), pages 1-12, April.

    More about this item

    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:plo:pone00:0221167. 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: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    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.