Sangjun Kim
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Sangjun Kim has a total of 3 co-authors. Here are the top co-authors by number of shared publications:
- Euiho Suh
Department of Industrial and Management Engineering, Pohang University of Science and Technology, Pohang, Republic of Korea
1 shared publication - Keedong Yoo
Division of Management, School of Economics and Commerce, Dankook University, Cheonan, Republic of Korea
1 shared publication - Kwangsup Shin
Graduate School of Logistics, Incheon National University, Incheon 22012, Republic of Korea
1 shared publication
Latest Publications
- Open Access
Comparative Analysis of Key Success Factors in S&OP: Focusing on Manufacturing and Retail Industry in South Korea
The global supply chain is facing unprecedented challenges due to pandemics, geopolitical tensions, volatile commodity prices, and rapid changes in consumer demand. The Sales and Operations Planning (S&OP) process can be an important solution by integrating supply and demand with business strategy and operational planning. However, previous studies have developed single frameworks or maturity models without considering industry-specific factors, overlooking the structural and operational characteristics of different industries that can have a significant impact on the approach and success factors of S&OP. Therefore, this study identifies and compares the key success factors of S&OP in the manufacturing and retail industries using the Analytic Hierarchy Process (AHP) technique. The results show clear differences in the prioritization of success factors between two industries. In the manufacturing industry, strategic support and leadership were evaluated as the most critical factor, while in the retail industry, operational processes were emphasized. In addition, the relative importance was concentrated on the top-ranked factor in the manufacturing industry, but the relative importance was distributed among several factors in the retail industry. This study provides valuable insights into the critical success factors for S&OP implementation in different industries and offers an understanding of how industry-specific characteristics influence the effectiveness of S&OP strategies.
Open AccessComparative Analysis of Key Success Factors in S&OP: Focusing on Manufacturing and Retail Industry in South Korea
The global supply chain is facing unprecedented challenges due to pandemics, geopolitical tensions, volatile commodity prices, and rapid changes in consumer demand. The Sales and Operations Planning (S&OP) process can be an important solution by integrating supply and demand with business strategy and operational planning. However, previous studies have developed single frameworks or maturity models without considering industry-specific factors, overlooking the structural and operational characteristics of different industries that can have a significant impact on the approach and success factors of S&OP. Therefore, this study identifies and compares the key success factors of S&OP in the manufacturing and retail industries using the Analytic Hierarchy Process (AHP) technique. The results show clear differences in the prioritization of success factors between two industries. In the manufacturing industry, strategic support and leadership were evaluated as the most critical factor, while in the retail industry, operational processes were emphasized. In addition, the relative importance was concentrated on the top-ranked factor in the manufacturing industry, but the relative importance was distributed among several factors in the retail industry. This study provides valuable insights into the critical success factors for S&OP implementation in different industries and offers an understanding of how industry-specific characteristics influence the effectiveness of S&OP strategies.
- 21 December 2006
- Published by Elsevier in Electronic Commerce Research and Applications
- Vol. 6 (2) , 146-158
A study of context inference for Web-based information systems
- 21 December 2006
- Published by Elsevier in Electronic Commerce Research and Applications
- Vol. 6 (2) , 146-158
A study of context inference for Web-based information systems