The role of data-driven services strategy in platform competition: A system performance perspective

PLOS ONE RESEARCH ARTICLE The role of data-driven services strategy in platform competition: A system performance perspective Qiang Hu ID1,2, Jiaping Xie ID1,3*, Guangsi Zhang1,3 1 College of Business, Shanghai University of Finance and Economics, Shanghai, China, 2 Shanghai University of Finance and Economics Zhejiang College, Jinhua, China, 3 School of Business Administration, Xinjiang University of Finance and Economics, Urumqi, China a1111111111 a1111111111 a1111111111 a1111111111 a1111111111 OPEN ACCESS Citation: Hu Q, Xie J, Zhang G (2023) The role of data-driven services strategy in platform competition: A system performance perspective. PLoS ONE 18(1): e0272547. https://doi.org/ 10.1371/journal.pone.0272547 Editor: Aurelio F. Bariviera, URV: Universitat Rovira i Virgili, SPAIN Received: May 10, 2022 Accepted: July 21, 2022 Published: January 26, 2023 Copyright: © 2023 Hu et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. * Abstract In the era of big data, data-driven services (DDS) have become critical competitive strategies for digital platform-based enterprises. This paper considers two operational modes of e-commerce platforms, which are self-operated and third-party modes, respectively, and they each lead a platform system. The Hotelling model is adopted to describe the competitive market of both platforms. We characterize their system performance functions. The optimization models are built using game theory to discuss the DDS and price decisions. We obtain the implementation conditions of DDS strategies for both platforms and the dominant situations of their respective DDS levels. We find that a platform adopting the price reduction strategy can improve the performance of its platform system while reducing the competitor’s system performance. From the system performance perspective, continuous improvement of the DDS level may appear “harming others may not benefit oneself”; that is, continuously improving the DDS level leads to a decrease in the competitor’s system performance but not necessarily an increase in its system performance. Further, consumer welfare within both platform systems shows the law of “as one falls then another rises”. As the big data industry matures, self-operated platforms would demonstrate the advantages of service level, profit, and system performance. In contrast, third-party platforms would have an advantage in consumer welfare. These conclusions have important implications for e-commerce platforms developing data-driven operations-based strategies. Data Availability Statement: All relevant data are within the manuscript and its Supporting Information files. Funding: This research was supported by the Major Project of National Social Science Foundation of China (No. 20&ZD060), the Key Project of National Social Science Foundation of China (No. 20AJY008), and the Development Foundation Project of Shanghai University of Finance and Economics Zhejiang College, China (No. 2018GR009; 2020GR004). The funders had no role in study design, data collection and 1. Introduction DDS (Data-driven services) refers to the services providers adopting big data technology to collect and analyze users’ data to provide higher quality services. In a way, the DDS level represents service providers’ big data analysis and application capabilities. As early as 2011, datadriven business analysis was identified as one of the four major technology trends in the IBM Tech Trends Survey [1]. The report “IDC FutureScape: Worldwide Digital Transformation 2021 Predictions” (Doc # US46880818) released by the International Data Corporation (IDC) PLOS ONE | https://doi.org/10.1371/journal.pone.0272547 January 26, 2023 1 / 21 PLOS ONE analysis, decision to publish, or preparation of the manuscript. Competing interests: The authors have declared that no competing interests exist. The role of data-driven services strategy in platform competition shows that by 2025, driven by the turbulent global environment, 75% of enterprise leaders would use digital platforms and ecosystem capabilities to adjust their value chains to adapt to new markets. With the help of big data analysis, enterprise managers can improve business decision-making and performance [2]. In China, leading e-commerce platforms have continued to invest in the field of big data technology in recent years, such as Alibaba and JD.com, which have become technologically innovative companies that provide high-tech services for consumers. E-commerce platforms have large amounts of demand-side data (including clickstreams, transactions, reviews, and other data). Compared with traditional offline retailers, ecommerce platforms have an advantage in collecting, storing, and analyzing abundant data. They can provide consumers with high-quality services in terms of intelligent customer service, accurate recommendation, platform UI design, return and exchange procedures, and selection of the logistics service provider. Therefore, implementing DDS strategies on e-commerce platforms can improve the consumers shopping experience and generate added value for consumers. A platform ecosystem is a collaborative system in which various cooperative entities use information technology to achieve open mesh contact under the platform’s leadership, which attracts participating enterprises (ecosystem complementors) to enter and jointly provide users with products and services [3]. The research on platform ecosystems has the characteristics of multidisciplinary integration, covering service management, information management and management science, and other fields. Among them, the governance decisions of platform owners and the strategic issues of platform complementors have attracted much attention [4]. In the value co-creation process of platform ecosystems, the coordination between platforms and participants (including users) is of great significance, rather than platforms only pursuing profit maximization. As the ecosystem leader, the platform needs to establish a collective identity for members within the ecosystem, co-supporting the provision of DDS that leads to benefits for the leader and the ecosystem complementors. Note that, in a third-party e-commerce platform ecosystem, the e-commerce platform, the merchant, and consumers are the key system members. Promoting the ecosystem’s value co-creation is the platform leader’s primary task [5]. These lead us to think about how e-commerce platforms implement DDS strategies to improve the performance of their platform systems, especially in a competitive environment. Moreover, there are different operational modes of e-commerce platforms in the market, and the typical ones are self-operated and third-party modes. Therefore, what are the differences in the implementation of DDS (...truncated)