Philip Tsang

16 papers receiving 343 citations

Peers

Philip Tsang
Comparison fields: 5 of 89
  • Catalysis 40
  • Management Science and Operations Research 68
  • Electronic, Optical and Magnetic Materials 62
  • Materials Chemistry 152
  • Marketing 28
Replace Shih‐Hsun Hsu with:
Shih‐Hsun Hsu Taiwan
Runyu Chen China
Jungwon Lee South Korea
Mohammad Iqbal Indonesia
Estefanía Argente Spain
Jiahui Li China
Wensi Li China
Rui Fan China
Rui Duan China
José Miguel Blanco Spain
Philip Tsang relative to Shih‐Hsun Hsu Taiwan Shih‐Hsun Hsu's profile →
Citations per field
00.5×10×13.3×
Shih‐Hsun Hsu · 1×
Citations per year

Countries citing papers authored by Philip Tsang

Since Specialization
Citations

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

Fields of papers citing papers by Philip Tsang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Philip Tsang. 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 Philip Tsang. The network helps show where Philip Tsang may publish in the future.

Co-authors

The 25 scholars most cited alongside Philip Tsang, 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 Philip Tsang Line = papers co-authored together Philip Tsang links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 2005154
2 200661
3 200536
4 200835
5 201025
6 201220
7 201013
8 20069
9 20073
10 20063
11 20142
12 20102
13 20112
14 20042
15
Preface to: Enhancing Learning Through Technology: Research on Emerging Technologies and Pedagogies
20081
16 20061
17 20210
18 20100
19 20210
20
Design of a WLAN experiment: a case study
20050

About Philip Tsang

Philip Tsang is a scholar working on Computer Networks and Communications, Management Science and Operations Research, Education, Signal Processing and Media Technology, having authored 20 papers that have together received 369 indexed citations. Recurring topics across this work include Online and Blended Learning (3 papers), Wireless Networks and Protocols (3 papers), Innovative Teaching and Learning Methods (2 papers), Stock Market Forecasting Methods (2 papers), Time Series Analysis and Forecasting (2 papers), Complex Systems and Time Series Analysis (2 papers), Wireless Communication Networks Research (1 paper) and Knowledge Management and Sharing (1 paper). The work is most often cited by research in Catalysis (40 citations), Management Science and Operations Research (68 citations), Electronic, Optical and Magnetic Materials (62 citations), Materials Chemistry (152 citations) and Marketing (28 citations). Philip Tsang has collaborated with scholars based in Hong Kong, United States and China. Frequent co-authors include Meilin Liu, Zhe Cheng, Shaowu Zha, Reggie Kwan, Kai S. Koong, Sheung‐On Choy, Felix T.S. Chan, Sin-Chun Ng, R.M. Fox and Jonathan Tsang. Their work appears in journals such as International Journal of Innovation and Learning, Engineering Applications of Artificial Intelligence, ˜The œHenry James review, Australasian Journal of Paramedicine and International Journal of Mobile Communications.

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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