Ronaldo Parente , Ke Rong , Xinwei Shi , Zhengyao Kang , Di Zhou
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引用次数: 0
Abstract
The prevalence of platform-based multinational corporations (PMNCs) has been increasing, and these businesses are encountering several growing challenges. These challenges include the dynamics and diversification of the global Regulatory context (R), the evolution of platform Ecosystems as innovative organization forms (E), the emergence of Artificial intelligence technologies as a new capability (A), and the introduction of Data as a novel resource (D). A ‘READ’ framework is proposed to guide the research of PMNCs based on four dimensions. This framework aims to enhance comprehension of the challenges faced by PMNCs within the global context and to offer direction for future research endeavors.
期刊介绍：
Long Range Planning (LRP) is an internationally renowned journal specializing in the field of strategic management. Since its establishment in 1968, the journal has consistently published original research, garnering a strong reputation among academics. LRP actively encourages the submission of articles that involve empirical research and theoretical perspectives, including studies that provide critical assessments and analysis of the current state of knowledge in crucial strategic areas. The primary user base of LRP primarily comprises individuals from academic backgrounds, with the journal playing a dual role within this community. Firstly, it serves as a platform for the dissemination of research findings among academic researchers. Secondly, it serves as a channel for the transmission of ideas that can be effectively utilized in educational settings. The articles published in LRP cater to a diverse audience, including practicing managers and students in professional programs. While some articles may focus on practical applications, others may primarily target academic researchers. LRP adopts an inclusive approach to empirical research, accepting studies that draw on various methodologies such as primary survey data, archival data, case studies, and recognized approaches to data collection.
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