Artificial Intelligence, Data-Driven Learning, and the Decentralized Structure of Platform Ecosystems

Charting new courses to enter foreign markets: Conceptualization, theoretical framework, and research directions on non-traditional entry modes

“…In view of new technologies such as block chain, virtual office, and AI capabilities, future research may investigate the impact of technology on modes of governing international subsidiaries and external partners to improve the efficiency and effectiveness of existing governance mechanisms. At the same time, the information overload, emanating from the availability of big data about internal and external partners and customers/users across the globe, may undermine managerial capacity and may require novel approaches to international corporate governance (Clough & Wu, 2022 ; Raisch & Krakowski, 2021 ; Verbeke & Hutzschenreuter, 2020 ). Building on these ideas, future research could explore issues related to corporate governance in these new MNEs and between headquarters and networks of partners, investors, and complementors established through these non-traditional entry modes.…”

Data Network Effects: Key Conditions, Shared Data, and the Data Value Duality

“…In other words, the product improves over the consumption lifetime with more users adopting it. Clough and Wu (2020) suggest that the term "data network effects" is misleading, assuming that the two conditions stated above are typically not met. This view, however, overlooks the role of AI which is central to the activation of data network effects.…”

“…Second, another core characteristic of AI is the ability to efficiently scale data-driven learning and instantly release the resulting improvements to the product experience to affect the current value of the product for each user. While we explained these characteristics of AI in our original article (Gregory et al, 2020), we had not explicitly linked them to the key conditions for network effects, and we thank Clough and Wu (2020), Hagiu andWright (2020), andCennamo (2020) for triggering us to add this clarification to the debate.…”

An Eye for Artificial Intelligence: Insights Into the Governance of Artificial Intelligence and Vision for Future Research

“…Research suggests that with growing capacity to collect, process, and store data, businesses are likely to follow a trajectory of acquiring increasingly large data resources—both to improve their offerings and to gain competitive advantage with an overall shift from “exclusivity in technology to exclusivity in data” (Hartmann & Henkel, 2020, p. 359). As a result, some scholars have claimed that the time is ripe for firms to develop new business models (Clough & Wu, 2020; Gregory et al, 2020), highlighting that value creation in AI-based digital platforms relies heavily on network effects. By virtue of such network effects, user data (when processed using ML algorithms) help firms to build more efficient and innovative solutions for their customers (and themselves), which in turn attracts more customers to the platform, thereby bringing further business opportunities.…”