IDEAS home Printed from https://ideas.repec.org/p/iik/wpaper/336.html
   My bibliography  Save this paper

Evaluating price fairness in hedonic and co-created categories

Author

Listed:
  • Praveen Sugathan

    (Indian Institute of Management Kozhikode)

Abstract

Since most of the consumer transaction are valued based on economic utility, prices and cost involved in transaction forms the important aspect of evaluating transactions. Price fairness literature evaluates the fairness of these transaction from the perspective of consumers. Most of the relevant research on price fairness are motivated by principle of dual entitlement (Kahneman et al 1986) which argues that in fairness perceptions are governed by the belief that firms are entitled to a reference profit and consumers are entitled to a reference price. Most of the literature on price fairness has been studying the fairness perceptions when status-quo is changed, for example increase in prices to take advantage surplus demand, or newly obtained monopoly power, or increase in costs. However, the literature has not looked in to price fairness perceptions related to the emerging categories of hedonic products or co-created products. Our research aims to contribute to such knowledge by explicating the price judgment mechanisms contextualized by theories related to these emerging categories.

Suggested Citation

  • Praveen Sugathan, 2019. "Evaluating price fairness in hedonic and co-created categories," Working papers 336, Indian Institute of Management Kozhikode.
  • Handle: RePEc:iik:wpaper:336
    as

    Download full text from publisher

    File URL: https://iimk.ac.in/websiteadmin/FacultyPublications/Working%20Papers/3097File%20For%20Upload.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Yunpeng Sun & Daniel W. Apley & Jeremy Staum, 2011. "Efficient Nested Simulation for Estimating the Variance of a Conditional Expectation," Operations Research, INFORMS, vol. 59(4), pages 998-1007, August.
    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. David J. Eckman & Shane G. Henderson & Sara Shashaani, 2023. "Diagnostic Tools for Evaluating and Comparing Simulation-Optimization Algorithms," INFORMS Journal on Computing, INFORMS, vol. 35(2), pages 350-367, March.
    2. Mingbin Ben Feng & Eunhye Song, 2020. "Optimal Nested Simulation Experiment Design via Likelihood Ratio Method," Papers 2008.13087, arXiv.org, revised Jul 2021.
    3. Mark Broadie & Yiping Du & Ciamac C. Moallemi, 2015. "Risk Estimation via Regression," Operations Research, INFORMS, vol. 63(5), pages 1077-1097, October.
    4. Mohammed Shahid Abdulla & L Ramprasath, 2019. "ANOVA with two timescale stochastic approximation for estimating Variance of Conditional Expectation," Working papers 337, Indian Institute of Management Kozhikode.
    5. Kamiński, Bogumił, 2015. "A method for the updating of stochastic kriging metamodels," European Journal of Operational Research, Elsevier, vol. 247(3), pages 859-866.
    6. Mark Broadie & Yiping Du & Ciamac C. Moallemi, 2011. "Efficient Risk Estimation via Nested Sequential Simulation," Management Science, INFORMS, vol. 57(6), pages 1172-1194, June.
    7. Liu, Xiaoyu & Yan, Xing & Zhang, Kun, 2024. "Kernel quantile estimators for nested simulation with application to portfolio value-at-risk measurement," European Journal of Operational Research, Elsevier, vol. 312(3), pages 1168-1177.
    8. Pedro Godinho, 2015. "Estimating State-Dependent Volatility of Investment Projects: A Simulation Approach," GEMF Working Papers 2015-02, GEMF, Faculty of Economics, University of Coimbra.
    9. Pedro Godinho, 2015. "Estimating State-Dependent Volatility of Investment Projects: A Simulation Approach," GEMF Working Papers 2015-02, GEMF, Faculty of Economics, University of Coimbra.
    10. Youngjun Choe & Henry Lam & Eunshin Byon, 2018. "Uncertainty Quantification of Stochastic Simulation for Black-box Computer Experiments," Methodology and Computing in Applied Probability, Springer, vol. 20(4), pages 1155-1172, December.
    11. Qiyun Pan & Eunshin Byon & Young Myoung Ko & Henry Lam, 2020. "Adaptive importance sampling for extreme quantile estimation with stochastic black box computer models," Naval Research Logistics (NRL), John Wiley & Sons, vol. 67(7), pages 524-547, October.
    12. Henry Lam, 2016. "Robust Sensitivity Analysis for Stochastic Systems," Mathematics of Operations Research, INFORMS, vol. 41(4), pages 1248-1275, November.
    13. Guangxin Jiang & L. Jeff Hong & Barry L. Nelson, 2020. "Online Risk Monitoring Using Offline Simulation," INFORMS Journal on Computing, INFORMS, vol. 32(2), pages 356-375, April.
    14. Wen Shi & Xi Chen, 2018. "Efficient budget allocation strategies for elementary effects method in stochastic simulation," Naval Research Logistics (NRL), John Wiley & Sons, vol. 65(3), pages 218-241, April.
    15. Wang, Tianxiang & Xu, Jie & Hu, Jian-Qiang & Chen, Chun-Hung, 2023. "Efficient estimation of a risk measure requiring two-stage simulation optimization," European Journal of Operational Research, Elsevier, vol. 305(3), pages 1355-1365.

    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:iik:wpaper:336. 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: Sudheesh Kumar (email available below). General contact details of provider: https://edirc.repec.org/data/iikmmin.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.