Computational and mathematical approaches to societal transitions

After an introduction of the theoretical framework and concepts of transition studies, this article gives an overview of how structural change in social systems has been studied from various disciplinary perspectives. This overview first leads to the conclusion that computational and mathematical approaches and their practical form, modeling, up till now, have been almost absent in the research and theorizing of structural change or transitions in social systems. Second, this review of the social science literature suggests numerous theoretical constructs relevant for transition modeling. Relevant concepts include the conceptualization of the micro-to-macro link, the importance of explaining both stability and change, quantitative and qualitative definitions of structural change, the use of dichotomies, synchronic and diachronic reasoning in explaining structural change, definitions of basic patterns of social change, the conceptualization of resistance to change and intentional and normative aspects of social change. This article employs these theoretical concepts to describe and discuss the models presented in this special issue in order to develop an understanding of what exactly entails a computational or mathematical approach to societal transitions

A system dynamics model of socio-technical regime transitions

Formal modelling of sociotechnical transitions has so far focused either on reproducing known historical case studies or on generic transition models that encompass some of the characteristics of the underlying processes. This article presents a model that captures the unfolding dynamics of an existing technological regime and the emerging niches as they compete and respond to landscape pressures. The theoretical basis is the “Multi-Level Perspective” (MLP) framework. The development of new technologies in niches is endogenous and stochastic. Model analysis can be seen as a test of the dynamic consistency of the MLP substitution pathway. Simulation results are consistent with what MLP theory suggests and raise relevant questions and insights for future modelling work on transition pathways and theory development

A (Computational) Social Science Perspective to Societal Transitions

This paper aims to illustrate how social sciences, sociology in particular, have theorized on societal transitions. The first section introduces some preliminary definitions. The assumption is that a societal transition is more than a social, economic or technological change. It is a large-scale and long-term macro process through which a given social system radically changes its structural basis, in terms of new socio-technical practices, governance rules, social and economic institutions, cultural frames, and patterns of social life. The second section provides an excursus on social science accounts on transitions. In particular, the attention has been given to Norbert Elias' famous study on the rise and fall of the court society in France, between 17th and 18th century and to Manuel Castells' recent analysis of the emergence of the network society. The third section discusses problems and challenges of standard approaches and suggests some building blocks of societal transition models, taken from complexity and social simulation literature. The concluding section suggests some way-forward measures towards a computational social science approach to societal transition

The impact of vulnerability and exposure to pervasive interprofessional incivility among medical staff on wellbeing

IntroductionTraditional methods for modelling human interactions within organisational contexts are often hindered by the complexity inherent within these systems. Building on new approaches to information modelling in the social sciences and drawing on the work of scholars in transdisciplinary fields, we proposed that a reliable model of human interaction as well as its emergent properties can be demonstrated using theories related to emergent information.MethodsWe demonstrated these dynamics through a test case related to data from a prevalence survey of incivility among medical staff. For each survey respondent we defined their vulnerability profile based upon a combination of their biographical characteristics, such as age, gender, and length of employment within a hospital and the hospital type (private or public). We modelled the interactions between the composite vulnerability profile of staff against their reports of their exposure to incivility and the consequent negative impact on their wellbeing.ResultsWe found that vulnerability profile appeared to be proportionally related to the extent to which they were exposed to rudeness in the workplace and to a negative impact on subjective wellbeing.DiscussionThis model can potentially be used to tailor resources to improve the wellbeing of hospital medical staff at increased risk of facing incivility, bullying and harassment at their workplaces

Social learning in innovation networks: how multisectoral collaborations shape discourses of sustainable agriculture

The increasing complexity of modern day society has led to the emergence of a specific type of sustainability problems known as complex problems. These types of problems can be characterised by their cognitive complexity and inherent insecurity, their normative complexity that allows for completely different interpretations rooted in different worldviews and finally the occurrence of a conflict of interests between different actors. Sustainable agriculture is the case in point. The Dutch countryside is standing on the threshold of a major transition. Rural development in The Netherlands nowadays involves far more than just restructuring agricultural production. The linear innovation perspective where new knowledge was discovered at universities and subsequently transferred to farmers by means of government sponsored extension services has given way to a new perspective on innovation. This perspective takes a relational view on innovation in which knowledge and innovations are co-created together with stakeholders and it emphasises the importance of experimentation and social learning involving a multisectoral network of actors from science, businesses, government agencies and nongovernmental organisations. The aim of these collaborative innovation networks is to contribute to the transition to sustainable agriculture, a radical and structural change of the agricultural system as a whole. This thesis focuses on these innovation networks in the context of sustainable agriculture. Its aim is to explore some of the underlying social mechanisms at play in these collaborative networks. Network perspectives have been used extensively to model the linear diffusion of knowledge from universities to farmers and between farmers themselves. However, bottom-up innovation projects with stakeholders do not only require knowledge transfer, but also need to change the organisational structures, laws and institutions governing the sector. This thesis consists of two main parts. The first part of this thesis addresses the content of the concept of sustainable agriculture. It conceptualises innovation as a social learning process in which participants forge new relationships to enhance information flows and learn from each other. The results can thus be divided into ‘outputs’ and ‘outcomes’. Outputs are the plans, scenarios, computer models and indicators that form the physical results of a collaborative process. The outcomes are formed by the building of trust and the development of a new discourse, a new shared language with which to communicate with each other. Using discourse analysis and Q-methodology the existing rurality discourses in the Netherlands were compared to the discourses that were present in the number of innovation projects dealing with sustainable agriculture. Results show that discourses of sustainable agriculture are a natural continuation of existing rurality discourses. The use of technology and the agricultural production function of rural landscapes are among the two most contested elements within the discourses. They are either anti-technological focusing on a multi-functional use of the countryside, or technophile with a strong sense of entitlement of agrarian production in the countryside. Both these extremes are limiting the possibilities for innovative projects to become successful. This thesis defines the concept of Metropolitan Agriculture as a form of sustainable agriculture that combines a technological approach of agriculture on the one hand with a multifunctional use of the countryside. The second part of the thesis elaborates a new network perspective that links three network functions in innovation systems to individual skills of knowledge creation, institutional entrepreneurship and innovation brokerage. These functions are necessary for the up- and outscaling of a local innovation. Social Network Analysis was used to study the distribution of these three functions over the participants of a collaborative innovation network. Results showed that these three functions are concentrated in three small core-groups and that these core-groups only displayed a very limited overlap. To what extent people are capable to perform one of these three functions depends for a large part on the type of organisation they work for. Finally, this thesis presents a new mapping technique to investigate and explain the network dynamics of a collaborative innovation network. Using this technique a longitudinal two-mode affiliation network was constructed over a period of 16 years. The analysis of the network dynamics shows how the structural characteristics of size, composition, connectedness and centralisation of a collaborative network change and how these changes are the result of the social relations between actors at the project level as they choose their partners to cooperate with and enter a process of social learning. This thesis therefore shows how the macro-level network dynamics can be explained by micro-level niche processes. It shows how the ideas in the niche change over time with new actors entering the network and other ones leaving after a certain period. The two parts of the thesis together explain how collaboration processes at the niche level can only gradually change societal discourses. In order to ‘sell’ a new idea it has to be embedded within familiar discourse elements. At the same time, these ideas play an important role in finding new partners to collaborate with and expand the existing innovation network. </p

Transition Experiments: Exploring societal changes towards sustainability

This PhD thesis presents the outcome of exploratory research on how transition experiments can be used as instruments to further sustainable development. A transition experiment is a specific type of innovation project that is aimed at exploring radically new ways to meet societal needs, such as the need for energy, mobility and health care. Transition experiments are a key instrument of the governance approach Transition Management (TM), which has recently been developed and applied to influence and direct transitions towards sustainability. This book presents a conceptual framework for analysing and managing transition experiments and their potential contribution to sustainability transitions. Central concepts in this framework are the mechanisms deepening (learning in a specific context), broadening (linking and repeating in different contexts) and scaling-up (embedding in established ways of thinking, doing and organising). The framework was developed in interaction with practitioners in three Dutch sustainability programmes: Learning for Sustainable Development, Transumo (TRANsition to SUstainable MObility) and the Transition Programme in Long-term Care. The practice-oriented concepts and examples that are described in this book could provide researchers, policy makers, programme managers and project leaders with a new way of looking at the role of innovation projects in transitions to sustainable development