K. M. Clayton

Bio: K. M. Clayton is an academic researcher. The author has an hindex of 1, co-authored 1 publications receiving 2185 citations.

Deconstructing clusters: chaotic concept or policy panacea?

Abstract: Over the past decade, there has been growing interest in local industrial agglomeration and specialization, not only by economic geographers but also by economists and by policy-makers. Of the many ideas and concepts to have emerged from this new-found focus, Michael Porter's work on ‘clusters’ has proved by far the most influential. His ‘cluster theory’ has become the standard concept in the field, and policy-makers the world over have seized upon Porter's cluster model as a tool for promoting national, regional, and local competitiveness, innovation and growth. But the mere popularity of a construct is by no means a guarantee of its profundity. Seductive though the cluster concept is, there is much about it that is problematic, and the rush to employ ‘cluster ideas’ has run ahead of many fundamental conceptual, theoretical and empirical questions. Our aim is to deconstruct the cluster concept in order to reveal and highlight these issues. Our concerns relate to the definition of the cluster concept, its theorization, its empirics, the claims made for its benefits and advantages, and its use in policy-making. Whilst we do not wish to debunk the cluster idea outright, we do argue for a much more cautious and circumspect use of the notion, especially within a policy context: the cluster concept should carry a public policy health warning.

Multi-Agent Systems for the Simulation of Land-Use and Land-Cover Change: A Review

Abstract: This paper presents an overview of multi-agent system models of land-use/cover change (MAS/LUCC models). This special class of LUCC models combines a cellular landscape model with agent-based representations of decisionmaking, integrating the two components through specification of interdependencies and feedbacks between agents and their environment. The authors review alternative LUCC modeling techniques and discuss the ways in which MAS/LUCC models may overcome some important limitations of existing techniques. We briefly review ongoing MAS/LUCC modeling efforts in four research areas. We discuss the potential strengths of MAS/LUCC models and suggest that these strengths guide researchers in assessing the appropriate choice of model for their particular research question. We find that MAS/LUCC models are particularly well suited for representing complex spatial interactions under heterogeneous conditions and for modeling decentralized, autonomous decision making. We discuss a range of possible roles for MAS/LUCC models, from abstract models designed to derive stylized hypotheses to empirically detailed simulation models appropriate for scenario and policy analysis. We also discuss the challenge of validation and verification for MAS/LUCC models. Finally, we outline important challenges and open research questions in this new field. We conclude that, while significant challenges exist, these models offer a promising new tool for researchers whose goal is to create fine-scale models of LUCC phenomena that focus on human-environment interactions.

Towards a Politics of Mobility

Abstract: This paper proposes an approach to mobility that takes both historical mobilities and forms of immobility seriously. It is argued that is important for the development of a politics of mobility. To...

Explaining Fixed Effects: Random Effects modelling of Time-Series Cross-Sectional and Panel Data

Abstract: This article challenges Fixed Effects (FE) modelling as the ‘default’ for time-series-cross-sectional and panel data. Understanding different within- and between-effects is crucial when choosing modelling strategies. The downside of Random Effects (RE) modelling – correlated lower-level covariates and higher-level residuals – is omitted-variable bias, solvable with Mundlak’s (1978a) formulation. Consequently, RE can provide everything FE promises and more, as confirmed by Monte-Carlo simulations, which additionally show problems with Plumper and Troeger’s FE Vector Decomposition method when data are unbalanced. As well as incorporating time-invariant variables, RE models are readily extendable, with random coefficients, cross-level interactions, and complex variance functions. We argue not simply for technical solutions to endogeneity, but the substantive importance of context/heterogeneity, modelled using RE. The implications extend beyond political science, to all multilevel datasets. However, omitted variables could still bias estimated higher-level variable effects; as with any model, care is required in interpretation.

Theorizing Sociospatial Relations

Abstract: This essay seeks to reframe recent debates on sociospatial theory through the introduction of an approach that can grasp the inherently polymorphic, multidimensional character of sociospatial relations. As previous advocates of a scalar turn, we now question the privileging, in any form, of a single dimension of sociospatial processes, scalar or otherwise. We consider several recent sophisti- cated 'turns' within critical social science; explore their methodological limitations; and highlight several important strands of sociospatial theory that seek to transcend the latter. On this basis, we argue for a more systematic recognition of polymorphythe organization of sociospatial relations in multiple formswithin sociospatial theory. Specifically, we suggest that territories (T), places (P), scales (S), and networks (N) must be viewed as mutually constitutive and relationally intertwined dimensions of sociospatial relations. We present this proposition as an extension of recent contribu- tions to the spatialization of the strategic-relational approach (SRA), and we explore some of its methodological implications. We conclude by briefly illustrating the applicability of the 'TPSN framework' to several realms of inquiry into sociospatial processes under contemporary capitalism.