IDEAS home Printed from https://ideas.repec.org/a/eee/jbrese/v112y2020icp248-253.html
   My bibliography  Save this article

Cognitive time as a service price determinant: Hidden dynamics and price collapse

Author

Listed:
  • von Schéele, Fabian
  • Haftor, Darek M.
  • Pashkevich, Natallia

Abstract

A novel service price equation is advanced to explain how prices in the services market depend on service workers’ cognitive time in relation to the actual clock time (physical time) that is contracted for a service. Cognitive time affects service revenues, costs, the targeted service profit, and budgeted service time. The equation shows how the cognitive time of service workers produces a hidden price-lever effect, in which the service price behavior becomes non-linear. A minor difference between the cognitive time and the physical time of a given service generates a significant change in the price level required to realize a targeted service profit. If the workload of a service worker is increased to a certain level, there is a potential service price collapse, implying that the service provider cannot reach the budgeted profit. This collapse condition further advances the emerging literature on behavioral pricing of services.

Suggested Citation

  • von Schéele, Fabian & Haftor, Darek M. & Pashkevich, Natallia, 2020. "Cognitive time as a service price determinant: Hidden dynamics and price collapse," Journal of Business Research, Elsevier, vol. 112(C), pages 248-253.
    • Handle: RePEc:eee:jbrese:v:112:y:2020:i:c:p:248-253
    DOI: 10.1016/j.jbusres.2019.10.056
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S014829631930640X
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.jbusres.2019.10.056?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Tom Fangyun Tan & Serguei Netessine, 2014. "When Does the Devil Make Work? An Empirical Study of the Impact of Workload on Worker Productivity," Management Science, INFORMS, vol. 60(6), pages 1574-1593, June.
    2. Franziska Völckner & Julian Hofmann, 2007. "The price-perceived quality relationship: A meta-analytic review and assessment of its determinants," Marketing Letters, Springer, vol. 18(3), pages 181-196, September.
    3. Williamson, Oliver, 2009. "The Theory of the Firm as Governance Structure: From Choice to Contract," Ekonomicheskaya Politika / Economic Policy, Russian Presidential Academy of National Economy and Public Administration, vol. 6, pages 111-134, December.
    4. Sinan Aral & Erik Brynjolfsson & Marshall Van Alstyne, 2012. "Information, Technology, and Information Worker Productivity," Information Systems Research, INFORMS, vol. 23(3-part-2), pages 849-867, September.
    5. Daniel Kahneman & Amos Tversky, 2013. "Prospect Theory: An Analysis of Decision Under Risk," World Scientific Book Chapters, in: Leonard C MacLean & William T Ziemba (ed.), HANDBOOK OF THE FUNDAMENTALS OF FINANCIAL DECISION MAKING Part I, chapter 6, pages 99-127, World Scientific Publishing Co. Pte. Ltd..
    6. von Schéele, Fabian & Haftor, Darek M., 2018. "Temporal workload in economic organizations: A hidden non-linear condition of economic efficiency," Journal of Business Research, Elsevier, vol. 88(C), pages 415-420.
    7. Wen-Chyuan Chiang & Jason C.H. Chen & Xiaojing Xu, 2007. "An overview of research on revenue management: current issues and future research," International Journal of Revenue Management, Inderscience Enterprises Ltd, vol. 1(1), pages 97-128.
    8. Richard H. Thaler & Eric J. Johnson, 1990. "Gambling with the House Money and Trying to Break Even: The Effects of Prior Outcomes on Risky Choice," Management Science, INFORMS, vol. 36(6), pages 643-660, June.
    9. von Schéele, Fabian & Haftor, Darek M. & Pashkevich, Natallia, 2019. "Cognitive time distortion as a hidden condition of worker productivity," Journal of Business Research, Elsevier, vol. 101(C), pages 591-596.
    10. Raphael Amit & Christoph Zott, 2001. "Value creation in E‐business," Strategic Management Journal, Wiley Blackwell, vol. 22(6‐7), pages 493-520, June.
    11. Gabriel Bitran & René Caldentey, 2003. "An Overview of Pricing Models for Revenue Management," Manufacturing & Service Operations Management, INFORMS, vol. 5(3), pages 203-229, August.
    12. Lillian L. Cheng & Kent B. Monroe, 2013. "An appraisal of behavioral price research (part 1): price as a physical stimulus," AMS Review, Springer;Academy of Marketing Science, vol. 3(3), pages 103-129, September.
    13. Martin, William C. & Ponder, Nicole & Lueg, Jason E., 2009. "Price fairness perceptions and customer loyalty in a retail context," Journal of Business Research, Elsevier, vol. 62(6), pages 588-593, June.
    14. Fabian von Schèele & Darek M. Haftor, 2014. "Cognitive Time Distortion on the Performance of Economic Organizations," Systems Research and Behavioral Science, Wiley Blackwell, vol. 31(1), pages 77-93, January.
    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. Qiao, Sen & Chen, Hsing Hung & Zhang, Rong Rong, 2021. "Examining the impact of factor price distortions and social welfare on innovation efficiency from the microdata of Chinese renewable energy industry," Renewable and Sustainable Energy Reviews, Elsevier, vol. 143(C).
    2. Pashkevich, Natallia & von Schéele, Fabian & Haftor, Darek M., 2023. "Accounting for cognitive time in activity-based costing: A technology for the management of digital economy," Technological Forecasting and Social Change, Elsevier, vol. 186(PB).

    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. Pashkevich, Natallia & von Schéele, Fabian & Haftor, Darek M., 2023. "Accounting for cognitive time in activity-based costing: A technology for the management of digital economy," Technological Forecasting and Social Change, Elsevier, vol. 186(PB).
    2. Mohamed Es-Sanoun & Jude Gohou & Mounir Benboubker, 2023. "Testing of Herd Behavior In african Stock Markets During COVID-19 Pandemic [Essai de vérification du comportement mimétique dans les marchés boursiers africains au cours de la crise de covid-19]," Post-Print hal-04144289, HAL.
    3. Ispano, Alessandro & Schwardmann, Peter, 2017. "Cooperating over losses and competing over gains: A social dilemma experiment," Games and Economic Behavior, Elsevier, vol. 105(C), pages 329-348.
    4. Chorvat, Terrence, 2006. "Taxing utility," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 35(1), pages 1-16, February.
    5. Duncan Luce, R., 1997. "Associative joint receipts," Mathematical Social Sciences, Elsevier, vol. 34(1), pages 51-74, August.
    6. Elie Matta & Jean McGuire, 2008. "Too Risky to Hold? The Effect of Downside Risk, Accumulated Equity Wealth, and Firm Performance on CEO Equity Reduction," Organization Science, INFORMS, vol. 19(4), pages 567-580, August.
    7. Martin Kukuk & Stefan Winter, 2008. "An Alternative Explanation of the Favorite-Longshot Bias," Journal of Gambling Business and Economics, University of Buckingham Press, vol. 2(2), pages 79-96, September.
    8. Xue Dong He & Sang Hu & Jan Obłój & Xun Yu Zhou, 2017. "Technical Note—Path-Dependent and Randomized Strategies in Barberis’ Casino Gambling Model," Operations Research, INFORMS, vol. 65(1), pages 97-103, February.
    9. Einiö, Mikko & Kaustia, Markku & Puttonen, Vesa, 2008. "Price setting and the reluctance to realize losses in apartment markets," Journal of Economic Psychology, Elsevier, vol. 29(1), pages 19-34, February.
    10. Raymond H. Chan & Ephraim Clark & Xu Guo & Wing-Keung Wong, 2020. "New development on the third-order stochastic dominance for risk-averse and risk-seeking investors with application in risk management," Risk Management, Palgrave Macmillan, vol. 22(2), pages 108-132, June.
    11. Iñigo Iturbe-Ormaetxe & Giovanni Ponti & Josefa Tomás, 2016. "Myopic Loss Aversion under Ambiguity and Gender Effects," PLOS ONE, Public Library of Science, vol. 11(12), pages 1-11, December.
    12. Aloysius, John A., 2003. "Rational escalation of costs by playing a sequence of unfavorable gambles: the martingale," Journal of Economic Behavior & Organization, Elsevier, vol. 51(1), pages 111-129, May.
    13. Christoph Bühren & Thorben C. Kundt, 2013. "Worker or Shirker – Who Evades More Taxes? A Real Effort Experiment," MAGKS Papers on Economics 201326, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    14. White, Tiffany Barnett & Novak, Thomas P. & Hoffman, Donna L., 2014. "No Strings Attached: When Giving It Away Versus Making Them Pay Reduces Consumer Information Disclosure," Journal of Interactive Marketing, Elsevier, vol. 28(3), pages 184-195.
    15. Alex Imas & Sally Sadoff & Anya Samek, 2017. "Do People Anticipate Loss Aversion?," Management Science, INFORMS, vol. 63(5), pages 1271-1284, May.
    16. Massimiliano Caporin & Grégory M. Jannin & Francesco Lisi & Bertrand B. Maillet, 2014. "A Survey On The Four Families Of Performance Measures," Journal of Economic Surveys, Wiley Blackwell, vol. 28(5), pages 917-942, December.
    17. Andersen, Steffen & Harrison, Glenn W. & Lau, Morten Igel & Rutström, Elisabet E., 2014. "Dual criteria decisions," Journal of Economic Psychology, Elsevier, vol. 41(C), pages 101-113.
      • Andersen, Steffen & Harrison, Glenn W. & Lau, Morten Igel & Rutström, Elisabet, 2009. "Dual Criteria Decisions," Working Papers 02-2009, Copenhagen Business School, Department of Economics.
    18. Freudenreich, Hanna & Musshoff, Oliver & Wiercinski, Ben, 2017. "The Relationship between Farmers' Shock Experiences and their Uncertainty Preferences - Experimental Evidence from Mexico," GlobalFood Discussion Papers 256212, Georg-August-Universitaet Goettingen, GlobalFood, Department of Agricultural Economics and Rural Development.
    19. Yuri Levin & Jeff McGill & Mikhail Nediak, 2008. "Risk in Revenue Management and Dynamic Pricing," Operations Research, INFORMS, vol. 56(2), pages 326-343, April.
    20. Mohammad Reza Nikbakht & Mehrdad Sadr Ara, 2016. "A new experimental model for profit maximization," Journal of Economic and Financial Studies (JEFS), LAR Center Press, vol. 4(3), pages 45-52, June.

    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:eee:jbrese:v:112:y:2020:i:c:p:248-253. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/jbusres .

    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.