D
Daekook Kang
Researcher at Inje University
Publications - 51
Citations - 814
Daekook Kang is an academic researcher from Inje University. The author has contributed to research in topics: Computer science & Multiple-criteria decision analysis. The author has an hindex of 8, co-authored 34 publications receiving 474 citations. Previous affiliations of Daekook Kang include Seoul National University & Samsung SDS.
Papers
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Journal ArticleDOI
Review-based measurement of customer satisfaction in mobile service: Sentiment analysis and VIKOR approach
Daekook Kang,Yongtae Park +1 more
TL;DR: A new framework for measurement of customer satisfaction for mobile services by combining VIKOR (in Serbian: ViseKriterijumsa Optimizacija I Kompromisno Resenje) and sentiment analysis is developed, which believes that the proposed customer-review-based approach not only saves time and effort in measuring customer satisfaction, but also captures the real voices of customers.
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Technology roadmapping for technology-based product-service integration: A case study
TL;DR: In this paper, the concept and typology of technological interface in product-service integration is suggested and based on the technological interface, a generic structure of product service integrated roadmap is developed.
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Evaluation of e-commerce websites using fuzzy hierarchical TOPSIS based on E-S-QUAL
TL;DR: The empirical case study of B2C e-commerce provides the researchers and practitioners to understand in a better way the evaluation process from a practical point of view and the comparison results with other MCDM methods further verify the robustness of the proposed approach.
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A novel assessment of bio-medical waste disposal methods using integrating weighting approach and hesitant fuzzy MOOSRA
Samayan Narayanamoorthy,Veerappan Annapoorani,Daekook Kang,Dumitru Baleanu,Jeonghwan Jeon,Joseph Varghese Kureethara,L. Ramya +6 more
TL;DR: A new methodology of hesitant fuzzy weight finding technique is proposed, named as Hesitant Fuzzy Subjective and Objective Weight Integrated Approach (HF-SOWIA) and a new hesitant fuzzy rank finding methodology, it is named as Helpshift Multi-Objective Optimization on the basis of Simple Ratio Analysis ( HF-MOOSRA).
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The customisation framework for roadmapping product-service integration
TL;DR: A customisation framework for product-service roadmapping according to the technological interface involved is suggested, and practical guidance in its implementation is provided.