IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v11y2023i13p2999-d1187432.html
   My bibliography  Save this article

Difference Game of Closed-Loop Supply Chain of Innovative Products with Discrete-Time Conditions

Author

Listed:
  • Lang Liu

    (School of Economics and Management, East China Jiaotong University, Nanchang 330013, China
    School of Business Administration, Guizhou University of Finance and Economics, Guiyang 550025, China)

  • Yutao Pu

    (School of Economics and Management, East China Jiaotong University, Nanchang 330013, China)

  • Zhenwei Liu

    (School of Economics and Management, East China Jiaotong University, Nanchang 330013, China)

  • Junjie Liu

    (School of Economics and Management, East China Jiaotong University, Nanchang 330013, China)

Abstract

This paper aims to explore the impact of the purchase regret of consumers on dynamic closed-loop supply chains (CLSCs) under discrete-time conditions. Durable products are mostly traded under discrete-time conditions, and consumers tend to have different purchase regret psychologies during the trading process of different types of durable products (innovative or remanufactured). In addition, different purchase regret psychologies can affect the dynamic decision-making behaviour of the nodal enterprises in the supply chain, thus affecting the dynamic decision-making optimization sequence of the supply chain and nodal enterprises. Based on the traditional Bass model, this paper introduces the factor of consumer purchase regret psychology into the Bass model and constructs a model of a CLSC led by the manufacturer and followed by the retailer and recycler on the premise of heterogeneous characteristics of new products and remanufactured products. The optimal control theory of discrete systems is used to obtain the optimal decision sequence for each participant in the CLSC, when there is consumer regret psychology in the market. Then, the effects of consumer purchase regret psychology on the members of the CLSC at each stage are analysed. Finally, the conclusions are verified by using a numerical analysis. Compared to previous studies, the results further revealed the following: when the market share of brand new products is below 50%, the wholesale and retail prices are positively related to the regret psychology; while when they are above 50%, the wholesale and retail prices are negatively related to the regret psychology; the product sales and the manufacturers and retailers’ profits are negatively related to the regret psychology; purchase regret psychology does not affect the recyclers’ profits. To mitigate the negative consequences of the purchase regret psychology, manufacturers and merchants should completely grasp the market, enhance product quality, such that the price plan for the product is fairer.

Suggested Citation

  • Lang Liu & Yutao Pu & Zhenwei Liu & Junjie Liu, 2023. "Difference Game of Closed-Loop Supply Chain of Innovative Products with Discrete-Time Conditions," Mathematics, MDPI, vol. 11(13), pages 1-20, July.
  • Handle: RePEc:gam:jmathe:v:11:y:2023:i:13:p:2999-:d:1187432
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/11/13/2999/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2227-7390/11/13/2999/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Javad Nasiry & Ioana Popescu, 2012. "Advance Selling When Consumers Regret," Management Science, INFORMS, vol. 58(6), pages 1160-1177, June.
    2. He, Qidong & Wang, Nengmin & Yang, Zhen & He, Zhengwen & Jiang, Bin, 2019. "Competitive collection under channel inconvenience in closed-loop supply chain," European Journal of Operational Research, Elsevier, vol. 275(1), pages 155-166.
    3. Pietro Giovanni, 2014. "Environmental collaboration in a closed-loop supply chain with a reverse revenue sharing contract," Annals of Operations Research, Springer, vol. 220(1), pages 135-157, September.
    4. De Giovanni, Pietro & Reddy, Puduru V. & Zaccour, Georges, 2016. "Incentive strategies for an optimal recovery program in a closed-loop supply chain," European Journal of Operational Research, Elsevier, vol. 249(2), pages 605-617.
    5. Frank M. Bass, 1969. "A New Product Growth for Model Consumer Durables," Management Science, INFORMS, vol. 15(5), pages 215-227, January.
    6. Davvetas, Vasileios & Diamantopoulos, Adamantios, 2017. "“Regretting your brand-self?” The moderating role of consumer-brand identification on consumer responses to purchase regret," Journal of Business Research, Elsevier, vol. 80(C), pages 218-227.
    7. Surendra Vikram Singh Padiyar & Vandana & Shiv Raj Singh & Dipti Singh & Mitali Sarkar & Bikash Koli Dey & Biswajit Sarkar, 2022. "Three-Echelon Supply Chain Management with Deteriorated Products under the Effect of Inflation," Mathematics, MDPI, vol. 11(1), pages 1-19, December.
    8. Yuchun Zhang & Yanan Wang & Bharosh Kumar Yadav & Alireza Goli, 2022. "Application of Circular Economy and Uncertainty Planning in Analyzing the Sustainable Closed-Loop Supply Chain Network Design," Mathematical Problems in Engineering, Hindawi, vol. 2022, pages 1-16, February.
    9. Bruce Robinson & Chet Lakhani, 1975. "Dynamic Price Models for New-Product Planning," Management Science, INFORMS, vol. 21(10), pages 1113-1122, June.
    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. Lang Liu & Lulu Wang & Taisheng Huang & Jinhui Pang, 2022. "The Differential Game of a Closed-Loop Supply Chain with Manufacturer Competition Considering Goodwill," Mathematics, MDPI, vol. 10(11), pages 1-18, May.
    2. Régis Chenavaz & Corina Paraschiv & Gabriel Turinici, 2017. "Dynamic Pricing of New Products in Competitive Markets: A Mean-Field Game Approach," Working Papers hal-01592958, HAL.
    3. Day Yang Liu & Wen Chun Tsai & Pei Leen Liu & Chung Yi Fang, 2021. "Determinants of sales revenue in innovation diffusion effects of Taiwan sports lottery during the FIFA World Cup 2018," International Journal of Research in Business and Social Science (2147-4478), Center for the Strategic Studies in Business and Finance, vol. 10(4), pages 43-58, June.
    4. Frank M. Bass, 2004. "Comments on "A New Product Growth for Model Consumer Durables The Bass Model"," Management Science, INFORMS, vol. 50(12_supple), pages 1833-1840, December.
    5. Zhang, Abraham & Wang, Jason X. & Farooque, Muhammad & Wang, Yulan & Choi, Tsan-Ming, 2021. "Multi-dimensional circular supply chain management: A comparative review of the state-of-the-art practices and research," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 155(C).
    6. Haitao Chen & Zhaohui Dong & Gendao Li, 2020. "Government Reward-Penalty Mechanism in Dual-Channel Closed-Loop Supply Chain," Sustainability, MDPI, vol. 12(20), pages 1-15, October.
    7. Kim, Namwoon & Srivastava, Rajendra K., 2007. "Modeling cross-price effects on inter-category dynamics: The case of three computing platforms," Omega, Elsevier, vol. 35(3), pages 290-301, June.
    8. Darghouth, M.N. & Ait-kadi, D. & Chelbi, A., 2017. "Joint optimization of design, warranty and price for products sold with maintenance service contracts," Reliability Engineering and System Safety, Elsevier, vol. 165(C), pages 197-208.
    9. Ruiz-Conde, Enar & Wieringa, Jaap E. & Leeflang, Peter S.H., 2014. "Competitive diffusion of new prescription drugs: The role of pharmaceutical marketing investment," Technological Forecasting and Social Change, Elsevier, vol. 88(C), pages 49-63.
    10. Wagner A. Kamakura & Siva K. Balasubramanian, 1987. "Long‐term forecasting with innovation diffusion models: The impact of replacement purchases," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 6(1), pages 1-19.
    11. Peters, Kay & Albers, Sönke & Kumar, V., 2008. "Is there more to international Diffusion than Culture? An investigation on the Role of Marketing and Industry Variables," EconStor Preprints 27678, ZBW - Leibniz Information Centre for Economics.
    12. Orbach Yair & Fruchter Gila E., 2010. "A Utility-Based Diffusion Model Applied to the Digital Camera Case," Review of Marketing Science, De Gruyter, vol. 8(1), pages 1-28, June.
    13. Michael Krapp & Johannes B. Kraus, 2019. "Coordination contracts for reverse supply chains: a state-of-the-art review," Journal of Business Economics, Springer, vol. 89(7), pages 747-792, September.
    14. Krishnamoorthy, Anand & Prasad, Ashutosh & Sethi, Suresh P., 2010. "Optimal pricing and advertising in a durable-good duopoly," European Journal of Operational Research, Elsevier, vol. 200(2), pages 486-497, January.
    15. Zhu, Xiaoyan & Jiao, Can & Yuan, Tao, 2019. "Optimal decisions on product reliability, sales and promotion under nonrenewable warranties," Reliability Engineering and System Safety, Elsevier, vol. 192(C).
    16. Herbert Dawid & Reinhold Decker & Thomas Hermann & Hermann Jahnke & Wilhelm Klat & Rolf König & Christian Stummer, 2017. "Management science in the era of smart consumer products: challenges and research perspectives," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 25(1), pages 203-230, March.
    17. Xu, Mei & Xie, Pu & Xie, Bai-Chen, 2020. "Study of China's optimal solar photovoltaic power development path to 2050," Resources Policy, Elsevier, vol. 65(C).
    18. Wei-yu Kevin Chiang, 2012. "Supply Chain Dynamics and Channel Efficiency in Durable Product Pricing and Distribution," Manufacturing & Service Operations Management, INFORMS, vol. 14(2), pages 327-343, April.
    19. Velickovic, Stevan & Radojicic, Valentina & Bakmaz, Bojan, 2016. "The effect of service rollout on demand forecasting: The application of modified Bass model to the step growing markets," Technological Forecasting and Social Change, Elsevier, vol. 107(C), pages 130-140.
    20. M Günther & C Stummer & L M Wakolbinger & M Wildpaner, 2011. "An agent-based simulation approach for the new product diffusion of a novel biomass fuel," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(1), pages 12-20, January.

    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:gam:jmathe:v:11:y:2023:i:13:p:2999-:d:1187432. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.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.