James Derbyshire

866 total citations
33 papers, 588 citations indexed

About

James Derbyshire is a scholar working on Management Science and Operations Research, Economics and Econometrics and Management of Technology and Innovation. According to data from OpenAlex, James Derbyshire has authored 33 papers receiving a total of 588 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Management Science and Operations Research, 13 papers in Economics and Econometrics and 9 papers in Management of Technology and Innovation. Recurrent topics in James Derbyshire's work include Complex Systems and Decision Making (10 papers), Entrepreneurship Studies and Influences (8 papers) and Firm Innovation and Growth (8 papers). James Derbyshire is often cited by papers focused on Complex Systems and Decision Making (10 papers), Entrepreneurship Studies and Influences (8 papers) and Firm Innovation and Growth (8 papers). James Derbyshire collaborates with scholars based in United Kingdom, South Sudan and Portugal. James Derbyshire's co-authors include George Wright, Emanuele Giovannetti, Elizabeth Garnsey, Sevrin Waights, Ben Gardiner, Jamie Morgan, Céline Miani, Stijn Hoorens, Flavia Tsang and Katia Begall and has published in prestigious journals such as Ecological Economics, Technological Forecasting and Social Change and Technovation.

In The Last Decade

James Derbyshire

31 papers receiving 560 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
James Derbyshire United Kingdom 13 169 144 126 126 91 33 588
Scott Moss United Kingdom 12 201 1.2× 212 1.5× 120 1.0× 190 1.5× 62 0.7× 51 731
George Burt United Kingdom 9 218 1.3× 67 0.5× 227 1.8× 133 1.1× 73 0.8× 12 600
Efstathios Tapinos United Kingdom 12 138 0.8× 131 0.9× 298 2.4× 88 0.7× 43 0.5× 19 658
Jan Oliver Schwarz Germany 15 212 1.3× 69 0.5× 288 2.3× 123 1.0× 51 0.6× 34 633
Gill Ringland United States 7 210 1.2× 63 0.4× 153 1.2× 110 0.9× 96 1.1× 22 650
Rafael Popper France 10 152 0.9× 112 0.8× 137 1.1× 128 1.0× 122 1.3× 41 661
Darko Vuković Russia 20 107 0.6× 460 3.2× 124 1.0× 290 2.3× 52 0.6× 105 1.1k
Cristiano Cagnin Spain 10 121 0.7× 105 0.7× 118 0.9× 104 0.8× 118 1.3× 21 513
Peter Eckersley United Kingdom 17 64 0.4× 181 1.3× 113 0.9× 196 1.6× 169 1.9× 60 978
Philippe Durance France 8 106 0.6× 55 0.4× 101 0.8× 96 0.8× 54 0.6× 18 411

Countries citing papers authored by James Derbyshire

Since Specialization
Citations

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

Fields of papers citing papers by James Derbyshire

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of James Derbyshire

This figure shows the co-authorship network connecting the top 25 collaborators of James Derbyshire. A scholar is included among the top collaborators of James Derbyshire based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with James Derbyshire. James Derbyshire is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Derbyshire, James & Terje Aven. (2024). Out of sight but still in mind: Developing an expectation for surprises by formalizing unknowledge in a contemporary risk‐assessment framework. Risk Analysis. 45(6). 1199–1206. 2 indexed citations
2.
Derbyshire, James, Mandeep K. Dhami, Ian Belton, & Dilek Önkal. (2023). The value of experiments in futures and foresight science: A reply. Middlesex University Research Repository (Middlesex University Of London). 5(2).
3.
Derbyshire, James, Mandeep K. Dhami, Ian Belton, & Dilek Önkal. (2022). The value of experiments in futures and foresight science as illustrated by the case of scenario planning. Middlesex University Research Repository (Middlesex University Of London). 5(2). 4 indexed citations
4.
Derbyshire, James. (2021). Dominant narratives, uncertainty denial, negative capability, and conviction: A commentary on Fenton‐O'Creevy and Tuckett (2021). Middlesex University Research Repository (Middlesex University Of London). 4(3-4). 2 indexed citations
5.
Derbyshire, James. (2021). Increasing Preparedness for Extreme Events using Plausibility‐Based Scenario Planning: Lessons from COVID‐19. Risk Analysis. 42(1). 97–104. 6 indexed citations
6.
Derbyshire, James. (2020). History and scenario planning: A commentary on Schoemaker 2020. Middlesex University Research Repository (Middlesex University Of London). 2(3-4). 3 indexed citations
7.
8.
Derbyshire, James. (2019). Answers to questions on uncertainty in geography: Old lessons and new scenario tools. Environment and Planning A Economy and Space. 52(4). 710–727. 20 indexed citations
9.
Derbyshire, James. (2018). Use of scenario planning as a theory‐driven evaluation tool. Middlesex University Research Repository (Middlesex University Of London). 1(1). 7 indexed citations
10.
Derbyshire, James & Emanuele Giovannetti. (2017). Understanding the failure to understand New Product Development failures: Mitigating the uncertainty associated with innovating new products by combining scenario planning and forecasting. Technological Forecasting and Social Change. 125. 334–344. 24 indexed citations
11.
12.
Derbyshire, James. (2017). The siren call of probability: Dangers associated with using probability for consideration of the future. Futures. 88. 43–54. 27 indexed citations
13.
Derbyshire, James. (2016). Potential surprise theory as a theoretical foundation for scenario planning. Technological Forecasting and Social Change. 124. 77–87. 52 indexed citations
14.
Derbyshire, James & George Wright. (2016). Augmenting the intuitive logics scenario planning method for a more comprehensive analysis of causation. International Journal of Forecasting. 33(1). 254–266. 63 indexed citations
15.
Derbyshire, James & Elizabeth Garnsey. (2015). Are firm growth paths random? A further response regarding Gambler's Ruin Theory. Journal of Business Venturing Insights. 3. 9–11. 4 indexed citations
16.
Derbyshire, James, et al.. (2015). Small business survey: linking 2006 and 2007 waves to the IDBR. Middlesex University Research Repository (Middlesex University Of London). 1 indexed citations
17.
Tsang, Flavia, et al.. (2014). Use of childcare services in the EU Member States and progress towards the Barcelona targets. PUB – Publications at Bielefeld University (Bielefeld University). 12 indexed citations
18.
Derbyshire, James. (2014). The impact of ambidexterity on enterprise performance: Evidence from 15 countries and 14 sectors. Technovation. 34(10). 574–581. 59 indexed citations
19.
Mills, Melinda, Patrick Präg, Flavia Tsang, et al.. (2014). Use of childcare in the EU Member States and progress towards the Barcelona targets: Short Statistical Report No. 1. RAND Corporation eBooks. 25 indexed citations
20.
Derbyshire, James. (2010). Will Policies Designed to Encourage Links between European Clusters Weaken their Internal Dynamics?. Local Economy The Journal of the Local Economy Policy Unit. 25(4). 328–338. 1 indexed citations

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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