Jun Du

74 papers receiving 2.4k citations

Jun Du's Hit Papers

Modelling the innovation value chain 2008 · 505 citations
5050+6+13Years since publication100200300400500

Peers

Jun Du
Comparison fields: 5 of 95
  • Strategy and Management 1k
  • Management of Technology and Innovation 329
  • Economics and Econometrics 635
  • Accounting 276
  • General Economics, Econometrics and Finance 152
Replace Nile W. Hatch with:
Nile W. Hatch United States
Lucia Piscitello Italy
Nicoletta Corrocher Italy
Jarunee Wonglimpiyarat Thailand
Luigi Marengo B Italy
Dilek Çetindamar Türkiye
Martin Woerter Switzerland
Fernando F. Suárez United States
Kazuyuki Motohashi Japan
Aija Elina Leiponen United States
Jun Du relative to Nile W. Hatch United States Nile W. Hatch's profile →
Citations per field
00.5×1.5×2.2×
Nile W. Hatch · 1×
Citations per year

Countries citing papers authored by Jun Du

Since Specialization
Citations

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

Fields of papers citing papers by Jun Du

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 84 papers — load more, or switch the sort, to bring in the rest.

#Work
1
The innovation value chain
Hit paper breakdown →
2006519
2
Modelling the innovation value chain
Hit paper breakdown →
2008505
3 2015131
4 200897
5 201489
6 201687
7 201082
8 201382
9 201080
10 200760
11 201360
12 201556
13 201747
14 201742
15 201435
16 200734
17 201234
18 201631
19 201028
20 202028

About Jun Du

Jun Du is a scholar working on General Economics, Econometrics and Finance, Strategy and Management, Accounting, Economics and Econometrics and Artificial Intelligence, having authored 84 papers that have together received 2.6k indexed citations. Recurring topics across this work include Global trade and economics (12 papers), Machine Learning and Algorithms (11 papers), International Business and FDI (10 papers), Firm Innovation and Growth (9 papers), Corporate Finance and Governance (9 papers), Banking stability, regulation, efficiency (4 papers), Regional Economics and Spatial Analysis (4 papers) and China's Socioeconomic Reforms and Governance (4 papers). The work is most often cited by research in Strategy and Management (1k citations), Management of Technology and Innovation (329 citations), Economics and Econometrics (635 citations), Accounting (276 citations) and General Economics, Econometrics and Finance (152 citations). Jun Du has collaborated with scholars based in United Kingdom, China and Canada. Frequent co-authors include James H. Love, Stephen Roper, Sourafel Girma, Tomasz Marek Mickiewicz, Charles X. Ling, Yama Temouri, Zhi‐Hua Zhou, Bach Nguyen, Michele Bernini and Alessandra Guariglia. Their work appears in journals such as Regional Studies, World Economy, Small Business Economics, IEEE Transactions on Knowledge and Data Engineering and Journal of International Business Studies.

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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