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Enhancing Logistics Management Education for Non-STEM Students in the AI Era: Evaluating the Role of Industry Experts in Logistics Education

In: AI, Society and Digital Transformation

Author

Listed:
  • Toshikuni Sato

    (Meiji University, School of Commerce)

  • Kazuo Kikuchi

    (Meiji University, School of Commerce)

  • Ippei Machida

    (Meiji University, School of Commerce)

Abstract

The worldwide shortage of logistics workers has emerged as a pressing issue. Especially in Japan, which has not accepted large numbers of immigrants, the implementation of the 2024 Working Style Reform Act, coupled with the country’s acute aging population, is anticipated to cause significant disruptions to logistics services, creating a complex and challenging environment for the Japanese logistics industry. In response to escalating labor shortages, several Japanese logistics companies are increasingly leveraging information and digital technologies. Global trends also indicate the increasing adoption of AI and digital transformation within the logistics sector. Given this context, logistics education and research are relatively straightforward to develop with engineering students due to their technical background; however, this study focuses on the educational needs of Non-STEM students to expand the talent pool capable of contributing to the industry. This study introduced a lecture series featuring industry experts and investigated its educational impact on students’ attitudes towards logistics knowledge and employment. The results indicate that the lectures deepened the students’ logistics knowledge; however, a notable gap exists between students’ interest in logistics and their motivation to work in the logistics industry.

Suggested Citation

  • Toshikuni Sato & Kazuo Kikuchi & Ippei Machida, 2026. "Enhancing Logistics Management Education for Non-STEM Students in the AI Era: Evaluating the Role of Industry Experts in Logistics Education," Lecture Notes in Operations Research, in: Xiaolei Xie & Kejia Hu & Guiping Hu & Weiwei Chen & Robin Qiu (ed.), AI, Society and Digital Transformation, pages 197-209, Springer.
  • Handle: RePEc:spr:lnopch:978-3-032-13116-4_16
    DOI: 10.1007/978-3-032-13116-4_16
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