This book deals with the theoretical, methodological, and empirical implications of bounded rationality in the operation of institutions. It focuses on decisions made under uncertainty, and presents a reliable strategy of knowledge acquisition for the design and implementation of decision-support systems. Based on the distinction between the inner and outer environment of decisions, the book explores both the cognitive mechanisms at work when actors decide, and the institutional mechanisms existing among and within organizations that make decisions fairly predictable. While a great deal of work has been done on how organizations act as patterns of events for (boundedly) rational decisions, less effort has been devoted to study under which circumstances organizations cease to act as such reliable mechanisms. Through an empirical strategy on open-ended response data from a survey among junior judges, the work pursues two main goals. The first one is to explore the limits of “institutional rationality” of the Spanish lower courts on-call service, an optimal scenario to observe decision-making under uncertainty. The second aim is to achieve a better understanding of the kind of uncertainty under which inexperienced decision-makers work. This entails exploring the demands imposed by problems and the knowledge needed to deal with them, making this book also a study on expertise achievement in institutional environments. This book combines standard multivariate statistical methods with machine learning techniques such as multidimensional scaling and topic models, treating text as data. Doing so, the book contributes to the collaboration between empirical social scientific approaches and the community of scientists that provide the set of tools and methods to make sense of the fastest growing resource of our time: data.

Frequently (and often inappropriately) decision making in the work environment has been analyzed and modeled in terms of isolated decisions made by one person. In reality, decision making is a continuous, interpersonal process usually involving several ``decision makers'' aiming at dynamic and cooperative control of the state of affairs at work. Based on original contributions from researchers and research teams, this book provides an urgently needed cognitive approach to models of distributed decision making, exploring the basis for design of decision support systems in various complex, collective, modern work environments. It identifies the state of the art of modeling distributed decision making and the problems imposed by modern high-tech systems. A also formulates promising research avenues.

Work motivation can be defined as the level of energy, commitment, and creativity that a company's workers bring to their roles. It is a multidimensional construct influenced by intrinsic and extrinsic factors, as well as contextual elements within the workplace. Theories of work motivation provide frameworks through which organizations can understand not only why employees are motivated but how they can enhance motivation levels to achieve organizational goals.

This collection reflects emerging research on the cognitive dimensions of business models and business model innovation. Numerous scholars have over the past decade point to the promise of cognition theories to clarify business models. This collection takes stock and provide examples of new developments.

This work explores the difficulties of solving contemporary environmental problems within existing global institutions. It questions guidelines set out in recent influential policy reports, and suggests new agendas for sustainability, industrial ecology, and institutional reform. Including case studies from the USA, Europe and China, this book investigates a wide range of environmental problems presently confronting experts worldwide.