IDEAS home Printed from https://ideas.repec.org/a/vrs/ecobur/v9y2023i2p115-132n6.html
   My bibliography  Save this article

Pricing and data science: The tale of two accidentally parallel transitions

Author

Listed:
  • Wallusch Jacek

    (1 Instytut Kliometrii i Badań nad Transformacją, ul. Nałęczowska 85, 60-472, Poznań, Poland)

Abstract

Accidentally parallel at the beginning, the transition to value-based pricing and transition to pricing data science have blended harmoniously, changing the pricing landscape. Using the marketing capability approach, I show that the introduction of pricing data science is costly and requires higher management support. Despite its cost, algorithmic price optimisation allows one to react swiftly to changes in demand. The optimisation process is applied to inherently non-linear, multimodal, and right-skewed pricing data. Presenting the interactions between new computational techniques and value-data pricing, I concentrate on altered perceptions of price elasticity, value-driver estimations, and contract opportunity analysis.

Suggested Citation

  • Wallusch Jacek, 2023. "Pricing and data science: The tale of two accidentally parallel transitions," Economics and Business Review, Sciendo, vol. 9(2), pages 115-132, April.
    • Handle: RePEc:vrs:ecobur:v:9:y:2023:i:2:p:115-132:n:6
    DOI: 10.18559/ebr.2023.2.739
    as

    Download full text from publisher

    File URL: https://doi.org/10.18559/ebr.2023.2.739
    Download Restriction: no
    File URL: https://libkey.io/10.18559/ebr.2023.2.739?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. Patrick Lünnemann & Thomas Y. Mathä, 2010. "Rigidities and inflation persistence of services and regulated prices," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 31(2-3), pages 193-208.
    2. Shantanu Dutta & Mark J. Zbaracki & Mark Bergen, 2003. "Pricing process as a capability: a resource‐based perspective," Strategic Management Journal, Wiley Blackwell, vol. 24(7), pages 615-630, July.
    3. Mark Bils & Peter J. Klenow, 2004. "Some Evidence on the Importance of Sticky Prices," Journal of Political Economy, University of Chicago Press, vol. 112(5), pages 947-985, October.
    4. Andreas Hinterhuber & Todd C. Snelgrove & Bo-Inge Stensson, 2021. "Value first, then price: the new paradigm of B2B buying and selling," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 20(4), pages 403-409, August.
    5. Raja, Jawwad Z. & Frandsen, Thomas & Kowalkowski, Christian & Jarmatz, Martin, 2020. "Learning to discover value: Value-based pricing and selling capabilities for services and solutions," Journal of Business Research, Elsevier, vol. 114(C), pages 142-159.
    6. Florian Steinbrenner & Jana Turčínková, 2021. "The Value-Based Pricing Determination Matrix for Pricing Method Selection," Central European Business Review, Prague University of Economics and Business, vol. 2021(4), pages 99-123.
    7. Coenen, Gunter & Levin, Andrew T. & Christoffel, Kai, 2007. "Identifying the influences of nominal and real rigidities in aggregate price-setting behavior," Journal of Monetary Economics, Elsevier, vol. 54(8), pages 2439-2466, November.
    8. Anton Korinek, 2023. "Language Models and Cognitive Automation for Economic Research," NBER Working Papers 30957, National Bureau of Economic Research, Inc.
    9. Andreas Hinterhuber & Stephan M. Liozu, 2018. "Thoughts: premium pricing in B2C and B2B," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 17(4), pages 301-305, August.
    10. van Giffen, Benjamin & Herhausen, Dennis & Fahse, Tobias, 2022. "Overcoming the pitfalls and perils of algorithms: A classification of machine learning biases and mitigation methods," Journal of Business Research, Elsevier, vol. 144(C), pages 93-106.
    11. repec:onb:oenbwp:y::i:101:b:1 is not listed on IDEAS
    12. Christen, Tatjana & Hess, Manuel & Grichnik, Dietmar & Wincent, Joakim, 2022. "Value-based pricing in digital platforms: A machine learning approach to signaling beyond core product attributes in cross-platform settings," Journal of Business Research, Elsevier, vol. 152(C), pages 82-92.
    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. Jacek Wallusch, 2012. "How frequently do consumer prices change in transition countries?," Applied Economics Letters, Taylor & Francis Journals, vol. 19(10), pages 921-928, July.
    2. Henri Kuokkanen & Jean-Pierre Van der Rest, 2022. "Game—Gimme a Better Price! A Negotiation Role Play on B2B Pricing in Hotel Revenue Management," INFORMS Transactions on Education, INFORMS, vol. 23(1), pages 46-55, September.
    3. Juillard, Michael & Kamenik, Ondra & Kumhof, Michael & Laxton, Douglas, 2008. "Optimal price setting and inflation inertia in a rational expectations model," Journal of Economic Dynamics and Control, Elsevier, vol. 32(8), pages 2584-2621, August.
    4. Jouchi Nakajima & Nao Sudo & Takayuki Tsuruga, 2010. "How well do the sticky price models explain the disaggregated price responses to aggregate technology and monetary policy shocks?," IMES Discussion Paper Series 10-E-22, Institute for Monetary and Economic Studies, Bank of Japan.
    5. Bratsiotis, George J. & Robinson, Wayne A., 2016. "Unit Total Costs: An Alternative Marginal Cost Proxy for Inflation Dynamics," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 20(7), pages 1826-1849.
    6. Luca Guerrieri & Christopher Gust & J. David López-Salido, 2010. "International Competition and Inflation: A New Keynesian Perspective," American Economic Journal: Macroeconomics, American Economic Association, vol. 2(4), pages 247-280, October.
    7. Dixon, Huw & Kara, Engin, 2006. "Understanding inflation persistence: a comparison of different models," Working Paper Series 672, European Central Bank.
    8. Emmanuel Dhyne & Luis J. Alvarez & Herve Le Bihan & Giovanni Veronese & Daniel Dias & Johannes Hoffmann & Nicole Jonker & Patrick Lunnemann & Fabio Rumler & Jouko Vilmunen, 2006. "Price Changes in the Euro Area and the United States: Some Facts from Individual Consumer Price Data," Journal of Economic Perspectives, American Economic Association, vol. 20(2), pages 171-192, Spring.
    9. Levin, Andrew T. & López-Salido, José David & Yun, Tack, 2007. "Strategic Complementarities and Optimal Monetary Policy," Kiel Working Papers 1355, Kiel Institute for the World Economy (IfW Kiel).
    10. Huw David Dixon & Kun Tian, 2017. "What We can Learn About the Behaviour of Firms from the Average Monthly Frequency of Price-Changes: An Application to the UK CPI Data," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 79(6), pages 907-932, December.
    11. Engin Kara & Huw Dixon, 2005. "Persistence and Nominal Inertia in a Generalized Taylor Economy: How Longer Contracts Dominate Shorter Contracts," Computing in Economics and Finance 2005 87, Society for Computational Economics.
    12. Dixon, Huw David, 2009. "A unified framework for understanding and comparing dynamic wage and price setting models," Cardiff Economics Working Papers E2009/20, Cardiff University, Cardiff Business School, Economics Section.
    13. Fang Yao, 2009. "Real and Nominal Rigidities in Price Setting: A Bayesian Analysis Using Aggregate Data," SFB 649 Discussion Papers SFB649DP2009-057, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    14. Gregory de Walque & Frank Smets & Rafael Wouters, 2006. "Firm-Specific Production Factors in a DSGE Model with Taylor Price Setting," International Journal of Central Banking, International Journal of Central Banking, vol. 2(3), September.
    15. John V. Colias & Stella Park & Elizabeth Horn, 2021. "Optimizing B2B product offers with machine learning, mixed logit, and nonlinear programming," Journal of Marketing Analytics, Palgrave Macmillan, vol. 9(3), pages 157-172, September.
    16. Chen, Haipeng (Allan) & Levy, Daniel & Ray, Sourav & Bergen, Mark, 2008. "Asymmetric Price Adjustment in the Small," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 55(4), pages 728-737.
    17. Fang Yao, 2010. "Can the New Keynesian Phillips Curve Explain Inflation Gap Persistence?," SFB 649 Discussion Papers SFB649DP2010-030, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    18. David Altig & Lawrence Christiano & Martin Eichenbaum & Jesper Linde, 2011. "Firm-Specific Capital, Nominal Rigidities and the Business Cycle," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 14(2), pages 225-247, April.
    19. Andrew T. Levin & Alexei Onatski & John Williams & Noah M. Williams, 2006. "Monetary Policy under Uncertainty in Micro-Founded Macroeconometric Models," NBER Chapters, in: NBER Macroeconomics Annual 2005, Volume 20, pages 229-312, National Bureau of Economic Research, Inc.
    20. Fauzia SOHAIL* & Ambreen FATIMA**, 2018. "PRICE SETTING BEHAVIOUR IN PAKISTAN: Stylized Facts from Micro SPI Dataset," Pakistan Journal of Applied Economics, Applied Economics Research Centre, vol. 28(2), pages 253-286.

    More about this item

    Keywords

    pricing; value-based pricing; machine learning; data science;
    All these keywords.

    JEL classification:

    • L11 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Production, Pricing, and Market Structure; Size Distribution of Firms
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • M31 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - Marketing

    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:vrs:ecobur:v:9:y:2023:i:2:p:115-132:n:6. 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: Peter Golla (email available below). General contact details of provider: https://www.sciendo.com .

    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.