What is he best known for?
The fields of study he is best known for:
- Management
- Marketing
- Artificial intelligence
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.
His most cited work include:
- Green as the new Lean: how to use Lean practices as a catalyst to greening your supply chain (365 citations)
- Market demand, green product innovation, and firm performance: evidence from Vietnam motorcycle industry (237 citations)
- Harvesting big data to enhance supply chain innovation capabilities: An analytic infrastructure based on deduction graph (210 citations)
What are the main themes of his work throughout his whole career to date?
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.
He most often published in these fields:
- Supply chain (25.58%)
- Process management (21.51%)
- Knowledge management (16.28%)
What were the highlights of his more recent work (between 2018-2021)?
- Supply chain (25.58%)
- Industrial organization (15.70%)
- Context (6.98%)
In recent papers he was focusing on the following fields of study:
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.
Between 2018 and 2021, his most popular works were:
- Loyalty toward online food delivery service: the role of e-service quality and food quality (47 citations)
- Developing a fuzzy green supplier selection model using six sigma quality indices (42 citations)
- A framework for food supply chain digitalization: lessons from Thailand (26 citations)
In his most recent research, the most cited papers focused on:
- Management
- Marketing
- Artificial intelligence
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.
