The University of Michigan's Survey Research Center developed a tool to quantify how people feel towards the state of the economy. Dr. George Katona, a psychologist and professor at the University of Michigan developed the Index of Consumer Sentiment (ICS) in the 1940s. As decades of data were collected on aggregate consumer sentiment through the 50s and 60s, a discovery was made. The ICS seemed to indirectly predict the direction of the economy by accurately anticipating aggregate purchasing versus saving decisions. The index is even used today by the U.S. Government to measure consumer confidence and has been noted to give investors an unfair advantage if they have this information before others. The literature shows many researchers attempting to measure the index's predictive ability on consumer expenses, but little to none have conducted an in depth analysis on identifying which variables, experiences, and individual characteristics influence the ICS. This dissertation takes on a systems perspective to recognize that the economy is one large societal system; whereby, all members of society along all levels on the socioeconomic strata are interconnected and are in conflict with their needs and values. A 45-question survey was distributed to a national sample of 535 participants. Participants from all states in the U.S. (except North Dakota), and including Puerto Rico were captured in the sample population. The survey identifies each participant's economic literacy, income levels, gender identities, political and religious affiliations, participant and parent's level of education, marital status, household size, employment status, news network preference, trust in the government, willingness to commit a crime in bad financial times, and personal experiences with foreclosure, bankruptcy and layoffs, among other variables. This quantitative methods research utilizes Spearman's rho correlation coefficient to identify the variables that are most statistically significant in influencing the ICS. The data show strong statistical significance among certain variables and the ICS (such as discretionary income, trust in the government, and news network preference), which further grounds the fact that consumers are easily conditioned and influenced by their environment.

Le changement des comportements individuels s'est récemment imposé comme un objectif majeur pour l'action publique, qui mobilise dans cette optique de nouveaux savoirs de gouvernement : les sciences comportementales. Ces savoirs sont employés de manière explicite et croissante dans la politique énergétique du Japon pour réduire la consommation d’énergie des ménages, dans un contexte marqué par l’accident nucléaire de Fukushima et la libéralisation des marchés de l’énergie. Cette thèse examine les facteurs explicatifs et les modalités concrètes de cette transformation significative dans un domaine jusque-là dominé par une approche techno-économique prêtant peu attention aux comportements. Notre analyse associe des perspectives théoriques et méthodologiques issues de la sociologie de l'action publique et des études sur les transferts de politiques publiques pour retracer la genèse et la mise en œuvre de deux expérimentations : celle des réseaux électriques « intelligents » dans les Smart Communities et celle des nudges et des Home Energy Reports de l’entreprise étasunienne Opower. La conduite d’environ quatre-vingt entretiens semi-directifs et l’examen de nombreuses sources écrites ont mis en évidence la place centrale des circulations transnationales dans l’élaboration et la conduite de ces programmes et plus généralement de la politique énergétique de l’archipel.Nous défendons la thèse que la mobilisation des sciences comportementales dans la politique énergétique japonaise résulte d’une multiplicité de facteurs qui questionne l’opposition entre des changements de nature soit endogène soit exogène, et la distinction entre facteurs domestiques et facteurs extranationaux. Le recours à ces savoirs de gouvernement s’explique en effet par la capacité d’un petit groupe d’acteurs programmatiques japonais à introduire dans la politique énergétique des sciences et des instruments originaires de l’étranger, en réponse à des enjeux spécifiques au Japon. Notre analyse microsociologique des stratégies de ces acteurs invite à une endogénéisation de l’explication du changement intégrant les facteurs exogènes et les dynamiques extranationales. La mobilisation des sciences comportementales dans la politique nippone résulte indissociablement de l’essor de ces savoirs dans la recherche et l’action publique aux États-Unis et en Europe, des stratégies d’acteurs transnationaux, étasuniens et japonais, et de la prégnance des enjeux climatiques et énergétiques sur l’archipel. Nous suggérons par ailleurs que les États-Unis sont au cœur de la circulation des sciences comportementales dans le domaine de l’énergie, et que le recours à ces savoirs dans l’action publique s’explique par, outre leur succès académique, leur dimension « pratique » et « consensuelle ». / In recent years, changing individual behaviours has become a key issue for public policy, which has been mobilising new bodies of knowledge, namely behavioural sciences. These are explicitly and increasingly used in Japan’s energy policy in order to lower household energy consumption, in the context of both the Fukushima nuclear disaster and the liberalisation of the energy markets. My dissertation investigates the explanatory factors and the implementation of this significant change in a policy domain which was so far marked by a techno-economic approach paying little attention to behavioural issues. Drawing on theoretical and methodological perspectives from public policy analysis and policy transfer studies, I analyse the genesis and the implementation of two large-scale programs: first, the smart grid social experiments named Smart Communities; second, the Opower’s Home Energy Reports pilot study. Building on about eighty semi-structured interviews and on a wide variety of written sources, I emphasise the major role played by transnational circulations in the design and the implementation of these programs, and more broadly in Japan’s energy policy.I argue that the mobilisation of behavioural sciences in Japan’s energy policy results from manifolds factors which question the opposition between the endogenous and exogenous nature of policy change, as well as the distinction between domestic and extranational factors. Indeed, the use of this body of knowledge can be explained by the strategies of a few stakeholders who achieved to introduce new policy ideas and tools coming from abroad, in response to issues faced by the Japanese Government. Through a micro-sociological analysis of their strategies, I suggest to endogenize the explanation of policy change while integrating exogenous factors and extranational dynamics. The mobilisation of behavioural sciences in Japan’s energy policy results inseparably from the expansion of this body of knowledge in academia and in public policy in the US and in Europe; from the strategies of transnational, Japanese and American stakeholders; and from the stringency of climate and energy problems in Japan. The US plays a central role in the transnational circulation of behavioural sciences in the energy field, which can be explained by the “practical” and “consensual” dimension of these sciences.

Achieving sustainability requires major changes in several areas in which society makes use of technology to meet human needs and while doing so influences the environment, such as agriculture, mobility, power production and water management. The awareness of a need for radical changes is accompanied by an increasing recognition of the interconnectedness of technological, socio-cultural and environmental elements and processes. This has led to an increasing amount of research on system innovations. System innovations refer to changes to a "structurally different" system involving radical changes in the technological and socio-cultural domains and are often contrasted to incremental (technological) change. System innovations involve many actors and many factors, and developments at multiple levels interact. Control over such processes is distributed, they are laden with uncertainty and they exhibit sometimes surprising and unexpected behaviour due to non-linear dynamics and emergent properties involved. Our current understanding of system innovations is limited and the need for an enhanced understanding has clearly been recognized. Computer simulation models seem a promising tool to that end as they already proved to be useful to enhance the understanding of complex systems in many fields like complex chemistry, ecosystems and physics. However, system innovations are mostly processes in social systems. In the social sciences, the application of formal simulation models has a far shorter history and the availability of formalized (and widely accepted) theories and generalizations is low compared to the natural sciences. It is thus not clear-cut which role computer simulation models can play with respect to system innovations. This thesis fathoms the potential of computer simulation models for enhancing our understanding of system innovations and takes some first steps towards fruitful application of models. A theoretical and methodological discussion outlines how models can in principle contribute to an understanding of social macro-processes through facilitating a causal reconstruction of processes that account for the respective observed phenomenon. The view adopted regarding the representation of the social world thereby is that of reciprocity of agency and structure. Compared to the sociological literature the perspective is extended beyond comprising actors and institutions but encompasses also other entities, especially technological artefacts. The thesis then relates the current state of empirical and conceptual work in the field of transition research (the terms "transition" and "system innovation" are used interchangeably) to insights from modelling of complex systems. The intrinsic characteristics of system innovations and the knowledge base available to study them are explicated and implicated challenges and opportunities for model application are discussed. This is complemented by a review of the few existing models of system innovations. The thesis further develops a specification of the regime concept. A regime refers to a dominant structure which originates incremental change but resists system innovations. The concept of "regime" is at the heart of the multi-level perspective, the most widely used framework of transition research, but it is yet only loosely defined. The absence of shared definitions, concept specifications and operationalizations of key concepts of transition research is a major obstacle for defining (and especially for comparing) models. In this thesis, five defining characteristics of regimes are developed and a method to structure and graphically represent knowledge about a regime is introduced. Furthermore, theoretical and conceptual work has been complemented by hands-on experience to make methodological and theoretical deliberations tangible. An agent-based model has been developed which addresses the transition from rainfed to irrigated agriculture in the Upper Guadiana, Spain. The purpose of the model is to bridge a gap in the explanation for the observed process. Case specific literature provides information on driving forces (technological development, changes in regulations) and consequences (amount of irrigation). The model focuses on the farmers which "translate" driving forces into practices of irrigation and water use. It studies the effect of weights farmers attach to a list of priorities. The main findings are that interactions of factors have to be considered and that it is important to acknowledge heterogeneity of farm types to understand empirically observed land-use changes. Based on the outlined work, different possibilities to model system innovations have been abstracted and discussed with respect to their advantages and limitations: a) functional subsystems, b) interacting structures (niches, regimes and landscape) as suggested by the multi-level perspective and c) micro-level entities (actors, technological artefacts, institutions, etc.). None of these representations is superior to the other ones per se but each features certain advantages and drawbacks. The model purpose is a necessary guideline to choose an appropriate representation and to distinguish those parts and aspects of a system which need to be captured from negligible ones. The main findings of this thesis can be summarized as follows: System innovations feature several characteristics which put model-based approaches to this topic on the most challenging edge of the broader endeavour of understanding and modelling social systems. Those are the significance of emergent decay and re-creation of structure during system innovations; the vast scope of system innovations involving several types of subsystems (consumption, production, governance, and nature); the intertwinement of system innovations with their governance – a field which is hardly accessible to modelling; the complexity of the topic; and the unpredictability of innovations. Still, it is concluded that models can be useful as thinking tools. In any case, given the complexity of the topic and the underdeveloped knowledge base, adhering to transparency is essential. In a field as vast and complex as system innovations this requires either very strong simplifications or restricting a model's scope to some parts or aspects of an overall process. This thesis proposes to make use of existing building blocks of understanding of an intermediate level of complexity – e.g. timing and kind of multi-level interactions - to define abstractions and model scope. The challenge to identify, specify, understand and relate conceptual building blocks, to identify the contexts and situations in which each of them becomes relevant and to explicate their role in the overall system innovation could be an agenda for transition modelling for the coming years. Modelling system innovations will remain a huge challenge in the near future. However, this thesis fathoms that models can be valuable tools contributing to the enhancement of the knowledge base of the field; little by little adding to answers of the "big questions". The specific role(s) models of system innovations can play in this endeavour needs to be further explored and discussed.