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<p>Digital economy developments have made consumers’ data become the core factor in promoting social productivity. We put forward the concept of “data factor endowment” and study the pattern changes of competition brought by value-added services based on data factor endowment on digital platforms. By setting up a duopoly competition model in the platform marketplace, we compare the equilibrium revenue of duopolistic manufacturers and the platform in three scenarios: (1) the platform provides no data-based value-added service (NN), (2) the platform provides exclusive data-based value-added service (YN), and (3) the platform provides non-differentiated data-based value-added service (YY). In equilibrium, four cases of optimal strategies space of the platform under different data factor endowment costs and market influence are derived. In addition, considering three types of costs of the data-based value-added services, we further confirm that the platform’s optimal revenue strategy space has strong robustness. Considering fairness constraints, we also propose a fixed fee for data-based value-added services to maintain the optimality of the non-differentiated value-added service (Scenario YY). Our results offer insights into the role of data factor endowment and how the platform sets the optimal value-added service strategies.</p>

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Platform value-added service strategy based on data factor endowment

  • 期刊论文

  • 发表日期：

    2025年4月21日

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  • Xudong Lin,
  • Shuilin Liu,
  • Guowei Dou,
  • Ruochen Zeng

摘要

Digital economy developments have made consumers’ data become the core factor in promoting social productivity. We put forward the concept of “data factor endowment” and study the pattern changes of competition brought by value-added services based on data factor endowment on digital platforms. By setting up a duopoly competition model in the platform marketplace, we compare the equilibrium revenue of duopolistic manufacturers and the platform in three scenarios: (1) the platform provides no data-based value-added service (NN), (2) the platform provides exclusive data-based value-added service (YN), and (3) the platform provides non-differentiated data-based value-added service (YY). In equilibrium, four cases of optimal strategies space of the platform under different data factor endowment costs and market influence are derived. In addition, considering three types of costs of the data-based value-added services, we further confirm that the platform’s optimal revenue strategy space has strong robustness. Considering fairness constraints, we also propose a fixed fee for data-based value-added services to maintain the optimality of the non-differentiated value-added service (Scenario YY). Our results offer insights into the role of data factor endowment and how the platform sets the optimal value-added service strategies.