Supply chain, Supply chain management, Knowledge management, Quality and Supply chain risk management are his primary areas of study. His studies deal with areas such as Fuzzy set, Risk analysis, Operations management and Acronym as well as Supply chain. His work deals with themes such as New product development, Knowledge value chain and Data management, Digital firm, which intersect with Supply chain management.
His Knowledge management research is multidisciplinary, incorporating perspectives in Lean project management, Lean practices and Big data. His Quality research is within the category of Marketing. Kim Hua Tan has researched Supply chain risk management in several fields, including Environmental resource management, Qualitative property and Scale.
Kim Hua Tan spends much of his time researching Supply chain, Process management, Knowledge management, Process and Industrial organization. His research integrates issues of Quality, Production and Risk analysis in his study of Supply chain. In his research on the topic of Production, Big data is strongly related with Operations research.
Kim Hua Tan interconnects Operations management, Manufacturing engineering, Strategic management, Lean project management and Performance measurement in the investigation of issues within Process management. His Process research focuses on Management science and how it connects with Visualization and Decision support system. His Industrial organization research is multidisciplinary, incorporating elements of Context, Marketing, Innovation management and Emerging markets.
Kim Hua Tan mainly focuses on Supply chain, Industrial organization, Context, Quality and Process. His research in Supply chain is mostly concerned with Supply chain management. His work deals with themes such as Comparative case and Analytic hierarchy process, which intersect with Supply chain management.
His research investigates the connection between Industrial organization and topics such as Big data that intersect with problems in Competence. Kim Hua Tan combines subjects such as Reliability engineering, Product, Fuzzy logic and Contract farming with his study of Quality. His work in Process addresses issues such as Risk analysis, which are connected to fields such as Association rule learning and Innovation process.
The scientist’s investigation covers issues in Process, New product development, Quality, Industrial organization and Big data. As a part of the same scientific study, Kim Hua Tan usually deals with the Process, concentrating on Risk analysis and frequently concerns with Production and Innovation process. His work in New product development tackles topics such as Knowledge management which are related to areas like Qualitative property and Scale.
Quality is the subject of his research, which falls under Marketing. In Industrial organization, he works on issues like Industry 4.0, which are connected to Product lifecycle and Context. His Big data study incorporates themes from Supply chain and Decision support system.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
Green as the new Lean: how to use Lean practices as a catalyst to greening your supply chain
Christina Maria Dües;Kim Hua Tan;Ming Lim.
Journal of Cleaner Production (2013)
Market demand, green product innovation, and firm performance: evidence from Vietnam motorcycle industry
Ru-Jen Lin;Kim-Hua Tan;Yong Geng.
Journal of Cleaner Production (2013)
Harvesting big data to enhance supply chain innovation capabilities: An analytic infrastructure based on deduction graph
Kim Hua Tan;YuanZhu Zhan;Guojun Ji;Fei Ye.
International Journal of Production Economics (2015)
Toward sustainability: using big data to explore the decisive attributes of supply chain risks and uncertainties
Kuo-Jui Wu;Ching-Jong Liao;Ming-Lang Tseng;Ming K. Lim.
Journal of Cleaner Production (2017)
Knowledge management in sustainable supply chain management: Improving performance through an interpretive structural modelling approach
Ming K. Lim;Ming Lang Tseng;Kim Hua Tan;Tat Dat Bui.
Journal of Cleaner Production (2017)
Managing product quality risk and visibility in multi-layer supply chain
Ying Kei Tse;Kim Hua Tan.
International Journal of Production Economics (2012)
Managing product quality risk in a multi-tier global supply chain
Ying Kei Tse;Kim Hua Tan.
International Journal of Production Research (2011)
Leveraging the supply chain flexibility of third party logistics - Hybrid knowledge-based system approach
K. L. Choy;Harry K. H. Chow;K. H. Tan;Chi-Kin Chan.
Expert Systems With Applications (2008)
Strategy visualisation: knowing, understanding, and formulating
Ken Platts;Kim Hua Tan.
Management Decision (2004)
Green and lean sustainable development path in China: Guanxi, practices and performance
Yuanzhu Zhan;Kim Hua Tan;Guojun Ji;Leanne Chung.
Resources Conservation and Recycling (2018)
Asian University
University of Cambridge
De La Salle University
Deakin University
Shanghai Jiao Tong University
Hong Kong Polytechnic University
Anhui University of Finance and Economics
University of Warwick
University of Nottingham Ningbo China
University of Guelph
Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking d-index is inferred from publications deemed to belong to the considered discipline.
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