Governing science as a complex adaptive system

Research policy is a complex matter. Copying best practices in research policy, as identified by benchmarking studies, is popular amongst policy makers but fails because of ‘knowledge asymmetries’. Research fields exhibit distinct knowledge dynamics that respond differently to governance interventions. Extending the idea of search regimes, this paper aims at providing a policy model for different knowledge dynamics by elaborating the notion of knowledge production as a complex adaptive system. Complex regimes emerge from three interacting sources of variance. In our conceptualisation, researchers are the nodes that carry the science system. Research can be considered as geographically situated practices with site specific skills, equipments and tools. The emergent science level refers to the formal communication activities of the knowledge published in journals and books, and announced in conferences. The contextual dynamics refer to the ways in which knowledge production provides resources for social and economic development. This conceptualization allows us to disaggregate knowledge dynamics both in horizontal (field related) and vertical (level related) dimensions by articulating the three different dynamics and their path dependencies (in research, science and society) in co-evolution with each other to produce distinct search regimes in each field. The implication for research governance is that generic measures can sometimes be helpful but there is clear need for disaggregated measures targeting field specific search regimes. Governing knowledge production through disaggregated measures means targeting in a distinct way not only different fields, but also, and more importantly, the interactions between local research practices, emergent scientific landscapes, and the field’s relationship to its societal context. If all three “levels” are aligned, there is a stable regime.search regime, research and innovation governance, complex adaptive system

Emerging Search Regimes: Measuring Co-evolutions among Research, Science, and Society

Scientometric data is used to investigate empirically the emergence of search regimes in Biotechnology, Genomics, and Nanotechnology. Complex regimes can emerge when three independent sources of variance interact. In our model, researchers can be considered as the nodes that carry the science system. Research is geographically situated with site-specific skills, tacit knowledge and infrastructures. Second, the emergent science level refers to the formal communication of codified knowledge published in journals. Third, the socio-economic dynamics indicate the ways in which knowledge production relates to society. Although Biotechnology, Genomics, and Nanotechnology can all be characterised by rapid growth and divergent dynamics, the regimes differ in terms of self-organization among these three sources of variance. The scope of opportunities for researchers to contribute within the constraints of the existing body of knowledge are different in each field. Furthermore, the relevance of the context of application contributes to the knowledge dynamics to various degrees

Actor-relational planning in deprived areas : challenges and opportunities in luchtbal Antwerpen, Belgium

In this article we report and discuss our experience with actor relational approaches in the regeneration of a post war housing estate in Luchtbal, Antwerp, Belgium. Actor relational approaches are informed by post-structuralist ideas of space, complexity theory and actor network theory. Although ARA itself is not new, the application of ARA to deprived area’s such as Luchtbal is novel. We report how the approach has been elaborated, its process and outcome. We conclude with our evaluation from an insider’s perspective

South American Expert Roundtable : increasing adaptive governance capacity for coping with unintended side effects of digital transformation

This paper presents the main messages of a South American expert roundtable (ERT) on the unintended side effects (unseens) of digital transformation. The input of the ERT comprised 39 propositions from 20 experts representing 11 different perspectives. The two-day ERT discussed the main drivers and challenges as well as vulnerabilities or unseens and provided suggestions for: (i) the mechanisms underlying major unseens; (ii) understanding possible ways in which rebound effects of digital transformation may become the subject of overarching research in three main categories of impact: development factors, society, and individuals; and (iii) a set of potential action domains for transdisciplinary follow-up processes, including a case study in Brazil. A content analysis of the propositions and related mechanisms provided insights in the genesis of unseens by identifying 15 interrelated causal mechanisms related to critical issues/concerns. Additionally, a cluster analysis (CLA) was applied to structure the challenges and critical developments in South America. The discussion elaborated the genesis, dynamics, and impacts of (groups of) unseens such as the digital divide (that affects most countries that are not included in the development of digital business, management, production, etc. tools) or the challenge of restructuring small- and medium-sized enterprises (whose service is digitally substituted by digital devices). We identify specific issues and effects (for most South American countries) such as lack of governmental structure, challenging geographical structures (e.g., inclusion in high-performance transmission power), or the digital readiness of (wide parts) of society. One scientific contribution of the paper is related to the presented methodology that provides insights into the phenomena, the causal chains underlying “wanted/positive” and “unwanted/negative” effects, and the processes and mechanisms of societal changes caused by digitalization

The forgotten legacy: oil heritage sites in Iran

During the rapid process of deindustrialization in Iran, the term ‘industrial heritage’ has recently emerged as a new subject into public realm. In order to integrate the methodologies for the protection and adaptive reuse strategies, the ‘industrial heritage’ itself needs to be divided into various categories. UNESCO has begun inscribing increasing numbers of local industrial legacies such as railway, mines, factories, assembly plants, agricultural production and manufacturing production in its World Heritage List. However, in the process of their adaptive reuse the question of heritage meanings arises. Over the past century in Iran, powerful corporate and governmental actors have created a broad range of oil imaginaries that changed over time and in line with local cultures. Starting from 1920s and after the nationalization of oil industry in Iran, oil cities such as Abadan and Masjid Suleiman saw massive expansion to house labors and oil-industry specialists who had arrived from the United States, Europe, India, and the Persian Gulf states. This research aims to clarify how the oil industry, in close collaboration with national governments, has materially shaped the oil cities through oil-specific architecture like company headquarters, gas stations, retail and infrastructure buildings. The current legacy of oil industry continues to reshape the industry, society and politics as well. This research uses a critical and analytical problem-based approach to examine the current policies that build a new image and identity through adaptive reuse strategies to promote sustainable local development in Iran’s industrial heritage

Understanding Governance Dynamics: The Governing System of Spatial Data Infrastructures

The importance and influence of spatial data has risen in all kinds of governmental and non-governmental processes, giving spatial data infrastructures (SDIs) a key role in spatial data sharing and dissemination. SDIs are nowadays challenged by new technologies and user demands. Proper SDI governance seems essential, but it is unclear to what extent current SDI governing systems are fully equipped to deal with the dynamics and complexity of SDIs. This research proposes a governing system framework for analysing the governing system of SDIs, adapted from the concepts of Kooiman. This framework is applied to two Dutch SDI cases: the Risk Map and the New Map of the Netherlands. With the help of the framework, the strong and weak aspects of the governing system of SDIs become more apparent and insights emerge on which interactions, images, instruments, actions and structures enable or constrain SDI governance. By observing changes in governing systems over time, SDI governance dynamics become visible. The governing system framework brings a new perspective to SDIs and SDI theory and is a potentially useful analytical tool for SDI governors