D. Daniel Sheu

440 citations
30 papers · 316 · h-index 11

Impact in

Papers in

D. Daniel Sheu

26 papers receiving 298 citations

Peers

D. Daniel Sheu
Comparison fields: 5 of 64
  • Management of Technology and Innovation 113
  • Industrial and Manufacturing Engineering 106
  • Safety, Risk, Reliability and Quality 70
  • Medical Laboratory Technology 7
  • Management Information Systems 38
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John Terninko United States
Samuel Bassetto Canada
Ellen Domb United Kingdom
Michel Tollenaere France
Jaeil Park South Korea
Éric Blanco France
Dag Bergsjö Sweden
Jelena Milisavljevic-Syed United Kingdom
Jürgen Bode China
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Citations per year

Countries citing papers authored by D. Daniel Sheu

Since Specialization
Citations

This map shows the geographic impact of D. Daniel Sheu'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 D. Daniel Sheu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites D. Daniel Sheu more than expected).

Fields of papers citing papers by D. Daniel Sheu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by D. Daniel Sheu. 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 D. Daniel Sheu. The network helps show where D. Daniel Sheu may publish in the future.

Co-authors

The 9 scholars most cited alongside D. Daniel Sheu, 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 D. Daniel Sheu Line = papers co-authored together D. Daniel Sheu links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 30 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201064
2 202038
3 201330
4 200624
5 200618
6 200616
7 201815
8 201015
9 202014
10 200313
11 201611
12 20159
13 20087
14 20177
15 20076
16 20195
17 19924
18 20064
19 20113
20 20213

About D. Daniel Sheu

D. Daniel Sheu is a scholar working on Industrial and Manufacturing Engineering, Safety, Risk, Reliability and Quality, Mechanical Engineering, Information Systems and Electrical and Electronic Engineering, having authored 30 papers that have together received 316 indexed citations. Recurring topics across this work include Manufacturing Process and Optimization (12 papers), Scheduling and Optimization Algorithms (5 papers), Technology Assessment and Management (5 papers), Design Education and Practice (4 papers), Industrial Vision Systems and Defect Detection (4 papers), Advanced Manufacturing and Logistics Optimization (3 papers), Advanced Machining and Optimization Techniques (3 papers) and Reliability and Maintenance Optimization (2 papers). The work is most often cited by research in Management of Technology and Innovation (113 citations), Industrial and Manufacturing Engineering (106 citations), Safety, Risk, Reliability and Quality (70 citations), Medical Laboratory Technology (7 citations) and Management Information Systems (38 citations). D. Daniel Sheu has collaborated with scholars based in Taiwan, United States and China. Frequent co-authors include Ming‐Chuan Chiu, Chia‐Hung Chen, Usharani Hareesh Govindarajan, Darrell Mann, Alan H. Bond, Chia-Lin Ho, Liangxing Shi, Helena V. G. Navas and Virgílio António Cruz Machado. Their work appears in journals such as Computers & Industrial Engineering, Journal of Intelligent Manufacturing, International Journal of Production Economics, Journal of Manufacturing Systems and IEEE Transactions on Semiconductor Manufacturing.

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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