Daecheol Kim

750 citations
39 papers · 566 · h-index 12

Impact in

Papers in

Daecheol Kim

34 papers receiving 533 citations

Peers

Daecheol Kim
Comparison fields: 5 of 107
  • Industrial and Manufacturing Engineering 124
  • Management Science and Operations Research 95
  • Marketing 69
  • Management Information Systems 49
  • Tourism, Leisure and Hospitality Management 7
Replace María Teresa Ballestar with:
María Teresa Ballestar Spain
Steven Thompson United States
Albérico Travassos Rosário Portugal
Darek Haftor Sweden
Adele Parmentola Italy
Dimitrios Gounopoulos United Kingdom
Johan Sandberg Sweden
Min‐Jae Lee South Korea
Jakub Horák Czechia
Daniel Nylén Sweden
Daecheol Kim relative to María Teresa Ballestar Spain María Teresa Ballestar's profile →
Citations per field
00.5×9.5×
María Teresa Ballestar · 1×
Citations per year

Countries citing papers authored by Daecheol Kim

Since Specialization
Citations

This map shows the geographic impact of Daecheol Kim's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Daecheol Kim with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daecheol Kim more than expected).

Fields of papers citing papers by Daecheol Kim

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daecheol Kim. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Daecheol Kim. The network helps show where Daecheol Kim may publish in the future.

Co-authors

The 25 scholars most cited alongside Daecheol Kim, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Daecheol Kim Line = papers co-authored together Daecheol Kim links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 39 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200983
2 202076
3 200357
4 201738
5 201738
6 201736
7 201735
8 201835
9 200929
10 200017
11 201916
12 201511
13 200410
14 200210
15 20149
16 20189
17 20147
18 20227
19 20185
20 20195

About Daecheol Kim

Daecheol Kim is a scholar working on Management Science and Operations Research, Economics and Econometrics, Industrial and Manufacturing Engineering, Molecular Biology and Strategy and Management, having authored 39 papers that have together received 566 indexed citations. Recurring topics across this work include Efficiency Analysis Using DEA (14 papers), Scheduling and Optimization Algorithms (5 papers), Diverse Topics in Contemporary Research (4 papers), Customer Service Quality and Loyalty (3 papers), Advanced Manufacturing and Logistics Optimization (3 papers), Technology Adoption and User Behaviour (3 papers), Firm Innovation and Growth (3 papers) and Multi-Criteria Decision Making (2 papers). The work is most often cited by research in Industrial and Manufacturing Engineering (124 citations), Management Science and Operations Research (95 citations), Marketing (69 citations), Management Information Systems (49 citations) and Tourism, Leisure and Hospitality Management (7 citations). Daecheol Kim has collaborated with scholars based in South Korea, United States and Taiwan. Frequent co-authors include José A. Ventura, JinHyo Joseph Yun, Min-Ren Yan, Hyuk-Chan Kwon, Sung-Hyun Kim, Sung Yong Oh, Ki‐Jae Park, Mee-Sook Roh, Hyojin Kim and Hongjo Choi. Their work appears in journals such as Sustainability, Journal of Open Innovation Technology Market and Complexity, Electronics, The International Journal of Advanced Manufacturing Technology and BMB Reports.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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