P.Y.L. Tu

11 papers receiving 510 citations

Peers

P.Y.L. Tu
Comparison fields: 5 of 57
  • Medical Laboratory Technology 48
  • Industrial and Manufacturing Engineering 160
  • Safety, Risk, Reliability and Quality 133
  • Management of Technology and Innovation 99
  • Management Information Systems 109
Replace Bhupesh Kumar Lad with:
Bhupesh Kumar Lad India
Marcus Bengtsson Sweden
Pulak Bandyopadhyay United States
Hossein Davari Ardakani United States
Velusamy Subramaniam Singapore
Ahmed Samet France
R.S. Lashkari Canada
Di Zhou China
Semra Tunalı Türkiye
P.Y.L. Tu relative to Bhupesh Kumar Lad India Bhupesh Kumar Lad's profile →
Citations per field
00.5×2×3.3×
Bhupesh Kumar Lad · 1×
Citations per year

Countries citing papers authored by P.Y.L. Tu

Since Specialization
Citations

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

Fields of papers citing papers by P.Y.L. Tu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by P.Y.L. Tu. 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 P.Y.L. Tu. The network helps show where P.Y.L. Tu may publish in the future.

Co-authors

The 8 scholars most cited alongside P.Y.L. Tu, 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 P.Y.L. Tu Line = papers co-authored together P.Y.L. Tu links everyone, so they are left out of the graph.

All Works

11 of 11 papers shown
#Work
1 2001333
2 200360
3 200134
4 199930
5 200121
6 200219
7 200018
8 200011
9 200711
10 20037
11 20024

About P.Y.L. Tu

P.Y.L. Tu is a scholar working on Management Information Systems, Computational Theory and Mathematics, Industrial and Manufacturing Engineering, Information Systems and Management of Technology and Innovation, having authored 11 papers that have together received 548 indexed citations. Recurring topics across this work include Business Process Modeling and Analysis (7 papers), Petri Nets in System Modeling (6 papers), Flexible and Reconfigurable Manufacturing Systems (5 papers), Collaboration in agile enterprises (2 papers), Service-Oriented Architecture and Web Services (2 papers), Scheduling and Optimization Algorithms (2 papers), Technology Assessment and Management (2 papers) and Quality Function Deployment in Product Design (1 paper). The work is most often cited by research in Medical Laboratory Technology (48 citations), Industrial and Manufacturing Engineering (160 citations), Safety, Risk, Reliability and Quality (133 citations), Management of Technology and Innovation (99 citations) and Management Information Systems (109 citations). P.Y.L. Tu has collaborated with scholars based in Hong Kong, New Zealand and Canada. Frequent co-authors include Richard C.M. Yam, Peter W. Tse, K.Y. Li, Richard Y.K. Fung, Ming J. Zuo, Zhibin Jiang, Jiafu Tang and Yizeng Chen. Their work appears in journals such as The International Journal of Advanced Manufacturing Technology, International Journal of Production Research, Computers & Industrial Engineering and Research in Engineering Design.

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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