Neil M. Kay

1.7k citations
51 papers · 812 · h-index 17

Impact in

Papers in

    • Business Strategy and Innovation 9
    • Innovation and Knowledge Management 6
    • Digital Platforms and Economics 3
    • Economic Theory and Institutions 7
    • Economic theories and models 4
    • Economic Growth and Productivity 3

Neil M. Kay

48 papers receiving 684 citations

Peers

Neil M. Kay
Comparison fields: 5 of 76
  • Strategy and Management 427
  • Business and International Management 31
  • Accounting 134
  • Economics and Econometrics 310
  • Management of Technology and Innovation 78
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Citations per year

Countries citing papers authored by Neil M. Kay

Since Specialization
Citations

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

Fields of papers citing papers by Neil M. Kay

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Neil M. Kay. 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 Neil M. Kay. The network helps show where Neil M. Kay may publish in the future.

Co-authors

The 13 scholars most cited alongside Neil M. Kay, 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 Neil M. Kay Line = papers co-authored together Neil M. Kay links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 51 papers — load more, or switch the sort, to bring in the rest.

#Work
1 198892
2 199874
3 198454
4 197953
5 201849
6 198243
7 199238
8 201035
9 198633
10
The Emergent Firm: Knowledge, Ignorance and Surprise in Economic Organisation
198427
11 201326
12 198425
13 201725
14
The Innovating Firm: A Behavioural Theory of Corporate R & D
197923
15 200020
16 199918
17 198517
18 199913
19
The Scottish Parliament and the Barnett Formula
199811
20 200810

About Neil M. Kay

Neil M. Kay is a scholar working on Strategy and Management, Economics and Econometrics, Political Science and International Relations, Management Information Systems and Accounting, having authored 51 papers that have together received 812 indexed citations. Recurring topics across this work include Business Strategy and Innovation (9 papers), Economic Theory and Institutions (7 papers), Innovation and Knowledge Management (6 papers), Economic theories and models (4 papers), Corporate Finance and Governance (4 papers), Digital Platforms and Economics (3 papers), Economic Growth and Productivity (3 papers) and Complex Systems and Decision Making (2 papers). The work is most often cited by research in Strategy and Management (427 citations), Business and International Management (31 citations), Accounting (134 citations), Economics and Econometrics (310 citations) and Management of Technology and Innovation (78 citations). Neil M. Kay has collaborated with scholars based in United Kingdom, United States and Malaysia. Frequent co-authors include Julia Porter Liebeskind, Craig S. Galbraith, Sohvi Leih, David J. Teece, Peter E. Earl, Beverly Wagner, Adamantios Diamantopoulos, Neil Fligstein, David J. Teece and Harvie Ramsay. Their work appears in journals such as Industrial and Corporate Change, JCMS Journal of Common Market Studies, Managerial and Decision Economics, Research Policy and International Journal of the Economics of Business.

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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