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"Gilbert, G. Nigel"
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Agent-based land-use models: a review of applications
Agent-based modelling is an approach that has been receiving attention by the land use modelling community in recent years, mainly because it offers a way of incorporating the influence of human decision-making on land use in a mechanistic, formal, and spatially explicit way, taking into account social interaction, adaptation, and decision-making at different levels. Specific advantages of agent-based models include their ability to model individual decision-making entities and their interactions, to incorporate social processes and non-monetary influences on decision-making, and to dynamically link social and environmental processes. A number of such models are now beginning to appear--it is timely, therefore, to review the uses to which agent-based land use models have been put so far, and to discuss some of the relevant lessons learnt, also drawing on those from other areas of simulation modelling, in relation to future applications. In this paper, we review applications of agent-based land use models under the headings of (a) policy analysis and planning, (b) participatory modelling, (c) explaining spatial patterns of land use or settlement, (d) testing social science concepts and (e) explaining land use functions. The greatest use of such models so far has been by the research community as tools for organising knowledge from empirical studies, and for exploring theoretical aspects of particular systems. However, there is a need to demonstrate that such models are able to solve problems in the real world better than traditional modelling approaches. It is concluded that in terms of decision support, agent-based land-use models are probably more useful as research tools to develop an underlying knowledge base which can then be developed together with end-users into simple rules-of-thumb, rather than as operational decision support tools.
Journal Article
Simulation for the social scientist
What can computer simulation contribute to the social sciences?Which of the many approaches to simulation would be best for my social science project?How do I design, carry out and analyse the results from a computer simulation?.
eBook
Simulating innovation : computer-based tools for rethinking innovation
Christopher Watts and Nigel Gilbert explore the generation, diffusion and impact of innovations, which can now be studied using computer simulations. Agent-based simulation models can be used to explain the innovation that emerges from interactions among complex, adaptive, diverse networks of firms, people, technologies, practices and resources. This book provides a critical review of recent advances in agent-based modelling and other forms of the simulation of innovation. Elements explored include: diffusion of innovations, social networks, organisational learning, science models, adopting and adapting, and technological evolution and innovation networks. Many of the models featured in the book can be downloaded from the book's accompanying website. Bringing together simulation models from several innovation-related fields, this book will prove a fascinating read for academics and researchers in a wide range of disciplines, including: innovation studies, evolutionary economics, complexity science, organisation studies, social networks, and science and technology studies. Scholars and researchers in the areas of computer science, operational research and management science will also be interested in the uses of simulation models to improve the understanding of organisation.
Book
Joining Complexity Science and Social Simulation for Innovation Policy
This book explores how complexity science and social simulation can be used to improve and inform policy-making in both research and innovation. Beginning with an introduction to conceptual definitions of complexity science and social simulation, the book demonstrates the validity of the underlying integrated research framework used throughout. It is then divided into two parts, with the first investigating the effects and impacts of policy making on the structure, composition and outputs of research and innovation networks using the agent-based SKIN platform (Simulating Knowledge Dynamics in Innovation Networks, http://cress.soc.surrey.ac.uk/SKIN/). The second half of the book discusses a research initiative funded by the Irish government focusing on innovation policy simulation for economic recovery. This consists of empirical research on Irish research and innovation networks, and SKIN-based simulations of technology transfer issues and the commercialization of research in areas with high potential for innovation and economic growth. The book concludes with reflections on the maturity and utility of an approach combining complexity science and social simulation for research and innovation policy. Joining Complexity Science and Social Simulation for Innovation Policy will be of particular interest to scientists concerned with innovation and complex systems, including economists, sociologists, and complexity researchers, as well as students and practitioners, such as innovation policymakers and innovation business managers.
eBook
Referencing as Persuasion
Noting that although the analysis of citations has become a frequently used resource in recent empirical studies of science, little progress has been made towards understanding the reasons for the practice of citation, the paper explores the notion that references provide persuasive support for the results announced in the citing paper. It is argued that authors choose to cite articles they recognize to be authoritative in order to justify the validity, novelty and significance of their own work. In so doing, authors can be seen to be both demonstrating their allegiance to a particular section of the research community and contributing to the establishment of a consensus about the worth of the cited work. These ideas are applied to explain the findings of research on the quality of articles and on co-citation analysis, and is used to criticize studies which undertake a content analysis of citations.
Journal Article
INTEGRATING WOMEN INTO CLASS THEORY
A theoretical framework is proposed by which women as well as men may be included in class theory, and a methodology is suggested by which one aspect of women's class location, their relationship to the labour market, may be measured. It is argued that social class in a Weberian sense may be seen as comprising two distinct although related dimensions. Firstly, that based upon relationship to the labour market, measured at the level of the individual; and second, that represented by patterns of consumption (in terms of goods and services), measured at the level of the family. All those with a direct relationship to the labour market may be allocated to an occupational class position, irrespective of position within the family. Data from the General Household Survey are used to produce a preliminary occupational class schema for women which does not depend upon assumptions of skill or the manual/non-manual nature of the work.
Journal Article