Cite Article
Cite Article
MLA
Yeh, Jen-Yin, and Yu-Ting Wang. "A Prediction Model for Electric Vehicle Sales Using Machine Learning Approaches." JGIM vol.31, no.1 2023: pp.1-21. http://doi.org/10.4018/JGIM.327277
APA
Yeh, J. & Wang, Y. (2023). A Prediction Model for Electric Vehicle Sales Using Machine Learning Approaches. Journal of Global Information Management (JGIM), 31 (1), 1-21. http://doi.org/10.4018/JGIM.327277
Chicago
Yeh, Jen-Yin, and Yu-Ting Wang. "A Prediction Model for Electric Vehicle Sales Using Machine Learning Approaches," Journal of Global Information Management (JGIM) 31, no.1: 1-21. http://doi.org/10.4018/JGIM.327277
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Journal of Global Information Management (JGIM) The Journal of Global Information Management (JGIM) provides a forum for researchers and practitioners to share leading-edge knowledge in the global information resource management area. Playing a pivotal role in the discussion of the organizational applications and managerial implications of information resource management technologies, JGIM’s contributors include a growing list of 2,400+ industry-leading experts, making the scope and breadth of the research diverse as it provides solutions to concepts like reengineering, rightsizing, network organizations, and the virtual corporation.
As stated by John Naisbitt, in his book Global Paradox , "the bigger the world economy, the more powerful its smaller players." While the world is becoming more interconnected, international strategic alliances are increasing due to the reality that no single company and/or country can be a successful player in this new global game. As such, big international companies are deconstructing themselves and creating new structures to survive in the new world order. JGIM is highly indexed, with prestigious placements such as Web of Science® - Social Sciences Citation Index®, Scopus®, Compendex®, INSPEC®, and more, placing it well within that global communicative space.
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