Publications for Duncan Robertson
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Journal Articles
Pagel, C,
Robertson, D, Yates, C (2024)
Principles for ensuring foresight approaches lead to more effective policy making for emergency preparedness,
BMJ: British Medical Journal, 387, e078647, ISSN: 1759-2151. DOI:
10.1136/bmj-2023-078647.
Gilbert, N, Chattoe-Brown, E, Watts, C,
Robertson, D (2022)
Why we need more data before the next pandemic,
Sociologica, 15(3), pp.125-143, ISSN: 0038-027X. DOI:
10.6092/issn.1971-8853/13221.
Hadley, L, Challenor, P, Dent, C, Isham, V, Mollison, D,
Robertson, D, Swallow, B, Webb, CR (2021)
Challenges on the interaction of models and policy for pandemic control,
Epidemics, 37, 100499, ISSN: 1755-4365. DOI:
10.1016/j.epidem.2021.100499.
Currie, CSM, Fowler, JW, Kotiadis, K, Monks, T, Onggo, BS,
Robertson, D, Tako, A (2020)
How simulation modelling can help reduce the impact of COVID-19,
Journal of Simulation, 14(2), pp.83-97, ISSN: 1747-7778. DOI:
10.1080/17477778.2020.1751570.
Robertson, D (2018)
Spatial transmission models: A taxonomy and framework,
Risk Analysis, 39(1), pp.225-243, ISSN: 0272-4332. DOI:
10.1111/risa.13142.
Robertson, DA (2017) Review of Agent-Based Modeling and Simulation (Taylor, S, Ed.),
The Journal of Artificial Societies and Social Simulation, 20(1), ISSN: 1460-7425.
Arvitrida, NI, Tako, A,
Robertson, D, Robinson, S (2017)
Duration of collaboration from a market perspective: An agent-based modeling approach,
OPERATIONS AND SUPPLY CHAIN MANAGEMENT, 10(3), pp.149-159, ISSN: 1979-3561.
Collet, F,
Robertson, DA, Lup, D (2014)
When does brokerage matter? Citation impact of research teams in an emerging academic field,
Strategic Organization, 12(3), pp.157-179, ISSN: 1476-1270. DOI:
10.1177/1476127014530124.
Vertes, PE, Nicol, RM, Chapman, SC, Watkins, NW,
Robertson, D, Bullmore, ET (2011)
Topological isomorphisms of human brain and financial market networks,
Frontiers in Systems Neuroscience, 5, pp.75-75, ISSN: 1662-5137. DOI:
10.3389/fnsys.2011.00075.
Conferences
Callaghan, H, Tako, A, Jackson, L, Dunnett, S (2021)
Developing a discrete event simulation model using multiple data sources. In
SW21 The OR Society Simulation Workshop; Proceedings of SW21 The OR Society Simulation Workshop, Online Conference. DOI:
10.36819/sw21.021.
Robertson, DA (2021)
Agent-based models: A tutorial. In
, Operational Research Society 10th Simulation Workshop, SW 2021 - Proceedings, pp.83-86, DOI:
10.36819/SW21.008.
Robertson, DA (2017) Agent-based models: A tutorial. In
, Proceedings of the Operational Research Society Simulation Workshop 2018, SW 2018, pp.43-46.
Robertson, DA and White, L (2016) An Agent-Based Model of Teams under External Shocks. In
EURO 2016 - 28th European Conference on Operational Research, Poznan, Poland.
Robertson, D and Franco, LA (2016)
An agent-based model of knowledge transferral: Exploring the need for closure and cognition. In
OR Society: 8th Simulation Workshop (SW16), Stratford.
Robertson, D and White, L (2016)
An agent-based model of teams under external shocks. In
Group Decision & Negotiation (INFORMS), Seattle, WA.
Arvitrida, N, Robinson, S, Tako, A,
Robertson, D (2016)
An agent-based model of supply chain collaboration: Investigating manufacturer loyalty. In
Proceedings of the Operational Research Society Simulation Workshop 2016 (SW16), Stratford, Worcestershire, pp.35-44.
Robertson, DA and Franco, LA (2015) An Agent-Based Model of Knowledge Transferral: Exploring the Need for Closure & Cognition. In
EURO 2015: 27th European Conference on Operational Research, Glasgow, UK.
Arvitrida, N, Robinson, S, Tako, A,
Robertson, D (2015)
An agent-based model of competition and collaboration in supply chains. In
, Loughborough.
Robertson, D and Franco, LA (2015)
An agent-based model of knowledge transferal. In
Group Decision & Negotiation (INFORMS), Warsaw, Poland,ISBN: 9788373789852.
Books
Robertson, DA and Caldart, AA (2009) The Dynamics of Strategy Mastering Strategic Landscapes of the Firm, Oxford University Press, USA.
Other
Robertson, D (2019)
Agent-based strategizing, Strategic management is a system of continual disequilibrium, with firms in a continual struggle for competitive advantage and relative fitness. Models that are dynamic in nature are required if we are to really understand the complex notion of sustainable competitive advantage. And new tools are required to tackle challenges of how firms should compete in environments characterized by both exogeneous shocks and intense endogenous competition. A rich history of alternative dynamic models exist in other social and natural sciences, some of which have been incorporated into the strategic management literature, notably the NK series of models. Yet there is a whole history of models from systems models, organizational ecology,
and general fitness landscape models that can be converted to agent-based models and used for the study of strategic management. Agent-based modelling of firms’ strategies offers an alternative analytical approach, where individual firm or component parts of a firm are modelled, each with their own strategy. Where traditional models can assume homogeneity of actors, agent-based models simulate each firm individually. This allows experimentation of strategic moves, which is particularly important where reactions to strategic moves are non-trivial. This Element introduces agent-based models and their use within management, reviews the influential NK suite of models, and offers an agenda for the development of agent-based models in strategic management. DOI:
10.1017/9781108767835.
Robertson, DA (2017)
Agent-Based Modeling and Simulation (OR Essentials).