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Transition Regions: Green Innovation and Economic Development

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Cooperation, Clusters, and Knowledge Transfer

Part of the book series: Advances in Spatial Science ((ADVSPATIAL))

Abstract

This chapter has three main aims. The first of these is to discuss and critique the main spatial and non-spatial theories that address methods by which societies may transition from a hydrocarbon to a post-hydrocarbon technological regime. It is argued that the first approach, which combines urban regime theory of politics with ecological modernisation theory, is ultimately contradictory and rooted in an inadequate “sustainability” discourse. The second approach is more interesting, not least because it adopts an evolutionary rather than a conflict perspective, it visualises the problem as “climate change” rather than “sustainability” and it conceptualises change beyond the level of mere technological regimes of a Schumpeterian kind. It allows the strategist to progress from the potential of building a “green” market niche that includes the urban governance stimulus but is not limited by it. Then it facilitates thinking about how such niches may coalesce to form an intervening “green” technological paradigm Schumpeter-style. Finally, it opens out a co-evolutionary process by which all social, political and economic sub-systems become synchronised long term into a post-hydrocarbon socio-technical landscape of a kind that would mitigate anthropogenic global warming. Its weakness is a lack of spatial sensibility regarding how this process would work, an underdeveloped notion of the role of governance in niche, regime and landscape co-evolution, and an inadequate appreciation of how innovation operates in facilitating these processes. To overcome this we propose the theoretical and practical concept of Transition Regions.

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Notes

  1. 1.

    Regulation theory analyses capitalist economic development in terms of a relationship between two key sub-systems. The first is the “regime of (capital) accumulation” and the second is the “mode of (capitalist) regulation”. It is also a theory of transition, albeit Marxist in inspiration, which was utilised particularly penetratively in analysing the 1980s transition in the predominant way of organising factory production. This had been based on Fordist mass production means, involving repetitive work and a strict division of labour producing standardised goods for mass consumption markets under a Keynesian welfare state mode of state regulation. A transition period denoted neo-Fordism with intense automation was a prelude to post-Fordism, which was a transition to a more flexibly specialised, even customised mode of production, with outsourcing to supply chains under a neoliberal or so-called “Schumpeterian workfare state” mode of regulation. It captured the way in which the Reagan–Thatcher “small state” ideologies synchronised with western capitalism’s crisis of productivity and competitiveness arising from Asian rivals, notably the Japanese “lean production” model in an ideological context focused on ending the Cold War by the “creative destruction” of the Soviet bloc. Interestingly, lack of innovation was seen by many observers as a key factor in the demise of the Soviet model (Lipietz 1987; Halliday 1990; Cooke 1990; Amin 1994; Jessop 1995; Peck 2000).

  2. 2.

    The endogeneity problem is common to social sciences and economics, particularly in econometrics where it, for the moment, casts doubt on much econometric analysis that utilises secondary data not designed to tackle precisely the focus of the research problem being tackled. For example, in innovation studies, it is too tedious to begin listing the innumerable published papers that profess to “explain” the distribution of, for example, “regional innovation systems” by conducting sophisticated technical analyses of regionalised research and development (R&D) or patent data, which a moment’s thought will bring realisation that they are not measures of innovation in any significant way. Innovation is defined by the neo-Schumpeterian school as, in simple terms, “the commercialisation of new knowledge (or sometimes ‘new combinations of knowledge’)” (see, e.g. Edquist 1997). Thus, such indicators not only mis-measure their object of interest but they also reveal that places with concentrations of such research and patenting activity are indeed the “innovation” capitals. However, a moment’s further reflection reveals that in most countries, most R&D is conducted in the capital city because a governments pay for a large share of it and historic path dependence analysis shows many such research institutes were set up by governments in the capital city for reasons to do with easy access to important research intelligence. Private businesses often followed suit for similar reasons of knowledge access or access to skilled labour pools. Hence endogeneity is built into the statistical patterns being “explained” even if only “the geography of research” were the object of interest. Accordingly, nothing of significant interest is explained at all, but especially nothing regarding innovation, by such metrics. The endogeneity problem in more historical economic accounts such as that of David (1985) is that they seem to offer little opportunity for new combinations or novelties by which evolution may occur. In other words that kind of path dependence has a “locked-in” endogeneity pathway. As will be shown, “green innovation” presents a particularly clear opposite to this viewpoint.

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Cooke, P. (2013). Transition Regions: Green Innovation and Economic Development. In: Ferreira, J., Raposo, M., Rutten, R., Varga, A. (eds) Cooperation, Clusters, and Knowledge Transfer. Advances in Spatial Science. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33194-7_6

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  • DOI: https://doi.org/10.1007/978-3-642-33194-7_6

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