Deep transitions: a mixed methods study of the historical evolution of mass production

Kanger, Laur, Bone, Frédérique, Rotolo, Daniele, Steinmueller, W Edward and Schot, Johan (2022) Deep transitions: a mixed methods study of the historical evolution of mass production. Technological Forecasting and Social Change, 177. a121491 1-24. ISSN 0040-1625

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Industrial societies contain a range of socio-technical systems fulfilling functions such as the provision of energy, food, mobility, housing, healthcare, finance and communications. The recent Deep Transitions (DT) framework outlines a series of propositions on how the multi-system co-evolution over 250 years of these systems has contributed to several current social and ecological crises. Drawing on evolutionary institutionalism, the DT framework places a special emphasis on the concepts of ‘rules’ and ‘meta-rules’ as coordination mechanisms within and across socio-technical systems. In this paper, we employ a mixed-method approach to provide an empirical assessment of the propositions of the DT framework. We focus on the historical evolution of mass production from the 18th century to the present. Combining a qualitative narrative based on a synthesis of secondary historical literature with a quantitative text mining-based analysis of the corpus of Scientific American (1845–2019), we map the emergence and alignment of rules underpinning mass production. Our study concludes by reflecting on important methodological lessons for the application of text mining techniques to examine large-scale and long-term socio-technical dynamics.

Item Type: Article
Additional Information: Unmapped bibliographic data: DA - 2022/04/01/ [EPrints field already has value set] JO - Technological Forecasting and Social Change [Field not mapped to EPrints]
Keywords: Deep transitions, Socio-technical systems, Rules, Mass production, Mixed methods, Text mining, Historical sources
Schools and Departments: University of Sussex Business School > SPRU - Science Policy Research Unit
Subjects: H Social Sciences > H Social Sciences (General)
Depositing User: Daniele Rotolo
Date Deposited: 31 Jan 2022 08:52
Last Modified: 15 Feb 2022 10:15

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Project NameSussex Project NumberFunderFunder Ref
Deep TransitionsG2184BAILLIE GIFFORD & CO LTDJames Anderson