IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i7p5708-d1106472.html
   My bibliography  Save this article

Research on Time to Market and Pricing of Platform Products in a Competitive Environment

Author

Listed:
  • Lei Zhou

    (School of Economics and Management, Hebei University of Science and Technology, Shijiazhuang 050018, China)

  • Yue Qi

    (School of Economics and Management, Hebei University of Science and Technology, Shijiazhuang 050018, China)

  • Xinshang You

    (School of Economics and Management, Hebei University of Science and Technology, Shijiazhuang 050018, China)

Abstract

Platforms are gradually becoming important business organization models, and platforms with bilateral market characteristics such as payment platforms and online shopping platforms are gradually penetrating people’s lives. Freemium content mostly exists in particular platforms such as online video platforms, etc. Platforms need to balance upstream and downstream markets when formulating strategies. This paper is the first to explore the time-to-market and pricing strategies of products in bilateral markets. By connecting upstream and downstream markets through cross-network externalities, we construct a system dynamics model of the problem, simulate the diffusion process of new product launches, and solve the problem of the optimal time to market and optimal pricing of the product. The simulation analyzes the effects of different parameters on the optimal time-to-market and pricing strategies, and comparing the diffusion in a unilateral market, we find that in a competitive market environment, the time-to-market and pricing of products are influenced by exogenous variables such as network externalities, and firms can promote their products more efficiently by changing the marketing mix strategy of platform product benefits and quality reputation. Meanwhile, the results obtained by considering bilateral markets when developing strategies for platform-based companies can lead to higher returns.

Suggested Citation

  • Lei Zhou & Yue Qi & Xinshang You, 2023. "Research on Time to Market and Pricing of Platform Products in a Competitive Environment," Sustainability, MDPI, vol. 15(7), pages 1-19, March.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:7:p:5708-:d:1106472
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/7/5708/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/15/7/5708/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Zijun (June) Shi & Kaifu Zhang & Kannan Srinivasan, 2019. "Freemium as an Optimal Strategy for Market Dominant Firms," Marketing Science, INFORMS, vol. 38(1), pages 150-169, January.
    2. John A. Norton & Frank M. Bass, 1987. "A Diffusion Theory Model of Adoption and Substitution for Successive Generations of High-Technology Products," Management Science, INFORMS, vol. 33(9), pages 1069-1086, September.
    3. Yanan Ji & Yi Li & Wenzhi Tang, 2022. "Service Investment and Pricing Strategies in E-Commerce Platforms With Seller Competition," International Journal of Information Systems and Supply Chain Management (IJISSCM), IGI Global, vol. 15(1), pages 1-21, January.
    4. Mark Armstrong, 2006. "Competition in two‐sided markets," RAND Journal of Economics, RAND Corporation, vol. 37(3), pages 668-691, September.
    5. Trichy V. Krishnan & Dipak C. Jain, 2006. "Optimal Dynamic Advertising Policy for New Products," Management Science, INFORMS, vol. 52(12), pages 1957-1969, December.
    6. Jean‐Charles Rochet & Jean Tirole, 2006. "Two‐sided markets: a progress report," RAND Journal of Economics, RAND Corporation, vol. 37(3), pages 645-667, September.
    7. Frank M. Bass, 1969. "A New Product Growth for Model Consumer Durables," Management Science, INFORMS, vol. 15(5), pages 215-227, January.
    8. Lee, Hakyeon & Kim, Sang Gook & Park, Hyun-woo & Kang, Pilsung, 2014. "Pre-launch new product demand forecasting using the Bass model: A statistical and machine learning-based approach," Technological Forecasting and Social Change, Elsevier, vol. 86(C), pages 49-64.
    9. Hao Li & Qing Xiao & Ting Peng, 2023. "Optimal Pricing Strategy of New Products and Remanufactured Products Considering Consumers’ Switching Purchase Behavior," Sustainability, MDPI, vol. 15(6), pages 1-26, March.
    10. Wu, Cheng-Han & Lai, Jing-Yi, 2019. "Dynamic pricing and competitive time-to-market strategy of new product launch under a multistage duopoly," European Journal of Operational Research, Elsevier, vol. 277(1), pages 138-152.
    11. Kang Li & Jingwei Zhang & Lunchuan Zhang, 2021. "Optimal Software Feature-Limited Freemium Model Design: A New Consumer Learning Theoretical Framework," Mathematics, MDPI, vol. 9(9), pages 1-24, April.
    12. Katarzyna Kreczmańska-Gigol & Tomasz Gigol, 2022. "The Impact of Consumers’ Green Skepticism on the Purchase of Energy-Efficient and Environmentally Friendly Products," Energies, MDPI, vol. 15(6), pages 1-12, March.
    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. Liu, Xueying & Madlener, Reinhard, 2019. "Get Ready for Take-Off: A Two-Stage Model of Aircraft Market Diffusion," FCN Working Papers 15/2019, E.ON Energy Research Center, Future Energy Consumer Needs and Behavior (FCN).
    2. Singhal, Shakshi & Anand, Adarsh & Singh, Ompal, 2020. "Studying dynamic market size-based adoption modeling & product diffusion under stochastic environment," Technological Forecasting and Social Change, Elsevier, vol. 161(C).
    3. Rong, Ke & Sun, Hui & Li, Dun & Zhou, Di, 2021. "Matching as Service Provision of Sharing Economy Platforms: An Information Processing Perspective," Technological Forecasting and Social Change, Elsevier, vol. 171(C).
    4. Alexei Parakhonyak & Nick Vikander, 2019. "Optimal Sales Schemes for Network Goods," Management Science, INFORMS, vol. 65(2), pages 819-841, February.
    5. Ghobadi, Somayeh Najafi- & Bagherinejad, Jafar & Taleizadeh, Ata Allah, 2021. "A two-generation new product model by considering forward-looking customers: Dynamic pricing and advertising optimization," Journal of Retailing and Consumer Services, Elsevier, vol. 63(C).
    6. Zhengrui Jiang & Dipak C. Jain, 2012. "A Generalized Norton-Bass Model for Multigeneration Diffusion," Management Science, INFORMS, vol. 58(10), pages 1887-1897, October.
    7. Zhen Lian & Garrett van Ryzin, 2021. "Optimal Growth in Two-Sided Markets," Management Science, INFORMS, vol. 67(11), pages 6862-6879, November.
    8. Zhu, Weijun & Xie, Jiaping & Xia, Yu & Wei, Lihong & Liang, Ling, 2023. "Getting more third-party participants on board: Optimal pricing and investment decisions in competitive platform ecosystems," European Journal of Operational Research, Elsevier, vol. 307(1), pages 177-192.
    9. Giovanni Modanese, 2023. "The Network Bass Model with Behavioral Compartments," Stats, MDPI, vol. 6(2), pages 1-13, March.
    10. Fan, Zhi-Ping & Che, Yu-Jie & Chen, Zhen-Yu, 2017. "Product sales forecasting using online reviews and historical sales data: A method combining the Bass model and sentiment analysis," Journal of Business Research, Elsevier, vol. 74(C), pages 90-100.
    11. Geng, Yang & Zhang, Yulin, 2020. "Platform launch in two-sided markets and users’ expectations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 558(C).
    12. Chuan Zhang & Yu-Xin Tian & Ling-Wei Fan, 2020. "Improving the Bass model’s predictive power through online reviews, search traffic and macroeconomic data," Annals of Operations Research, Springer, vol. 295(2), pages 881-922, December.
    13. Stoneman, Paul, 2011. "Soft Innovation: Economics, Product Aesthetics, and the Creative Industries," OUP Catalogue, Oxford University Press, number 9780199697021.
    14. Lim, Hyungsoo & Jun, Duk Bin & Hamoudia, Mohsen, 2019. "A choice-based diffusion model for multi-generation and multi-country data," Technological Forecasting and Social Change, Elsevier, vol. 147(C), pages 163-173.
    15. Cambier, Adrien & Chardy, Matthieu & Figueiredo, Rosa & Ouorou, Adam & Poss, Michael, 2022. "Optimizing subscriber migrations for a telecommunication operator in uncertain context," European Journal of Operational Research, Elsevier, vol. 298(1), pages 308-321.
    16. Hui Zhang & Kai Luo & Guanqun Ni, 2022. "The effects of price subsidy and fairness concern on pricing and benefits of take-away supply chain," Journal of Combinatorial Optimization, Springer, vol. 43(5), pages 1106-1124, July.
    17. Amelio, Andrea & Giardino-Karlinger, Liliane & Valletti, Tommaso, 2020. "Exclusionary pricing in two-sided markets," International Journal of Industrial Organization, Elsevier, vol. 73(C).
    18. Shigeno, Hidenori & Matsuzaki, Taisuke & Ueki, Yasushi & Tsuji, Masatsugu, 2023. "The Effect of the Covid-19 Pandemic on the Innovation Process of Small and Medium-sized Regional Firms," 32nd European Regional ITS Conference, Madrid 2023: Realising the digital decade in the European Union – Easier said than done? 278018, International Telecommunications Society (ITS).
    19. Sohn, So Young & Lim, Michael, 2008. "The effect of forecasting and information sharing in SCM for multi-generation products," European Journal of Operational Research, Elsevier, vol. 186(1), pages 276-287, April.
    20. 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.

    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:jsusta:v:15:y:2023:i:7:p:5708-:d:1106472. 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.