Research on the topic of clusters and industrial districts is very extensive. However, most of it has focused more on understanding the past than on trying to map out the future. The aim of this book is to fill this gap by identifying and discussing the main research topics that populate the current scientific debate and highlight the emergent lines of research that will constitute the future research agenda. It does so by drawing on the debate started with the "rethinking clusters" workshops, which in a short time have become a rich place for discussion among cluster scholars around the world. Rethinking Clusters: Towards a New Research Agenda for Cluster Research collects contributions from authoritative colleagues, who cover a number of relevant and timely issues, such as the territorial roots of radical innovation processes, new ways of understanding and measuring the role of place in economic development, path renewal, internationalization and entrepreneurship. The final section is devoted to the critical analysis of policies that support smart specialization. The chapters in this book were originally published as a special issue of the journal European Planning Studies.

This volume discusses how different geographical spaces can enhance or hinder the capacity of a variety of organizational settings to achieve economic value creation in the pursuit of sustainable regional development. In order to provide the most comprehensive picture of new sources of value creation for sustainable transitions, the book collects contributions that tackle this issue from a variety of perspectives, and adopts a systemic approach where macro, meso and micro-levels of analysis are intertwined in three sections. This multidisciplinary and interdisciplinary approach comes from scholars operating in the fields of planning, economic geography, social entrepreneurship and organizational management. The first section of the book adopts a macro-level approach linking sustainability to the regional development theme, and addresses how organizations work between different social interests to produce outcomes not previously realized. The second section of the book focuses on the spatial dimensions of sustainable development, with particular clusters, industrial districts and regions considered as relevant units of analysis (meso-level analysis). The third section of the book is dedicated to a micro-level approach, illustrating how to drive social entrepreneurship activities, which are based upon sustainable business models centered in the creation of a shared value. The book is geared towards scholars working on sustainable development issues intersecting the disciplines of regional studies, economic geography and management, and will appeal to geographers and researchers in economic development, business innovation, and sustainability transitions.

Clusters and Sustainable Regional Development conceptualises the role of organised clusters in the transition towards sustainability. It introduces a novel perspective on these clusters, viewing them as deliberate collective actors within their environments that can become the driving force for transformation in their regions or nations. The book draws upon the meta-organisational perspective in cluster studies, in contrast to traditional approaches. This view suggests that clusters are not merely territories or geographical areas, but organised entities. As such, they are defined as territorially anchored groups of independent organisations engaging in joint decision-making, pursuing system-level goals and capable of purposive collective action. This text introduces a new set of ideas and questions at the intersection of economic geography, regional and cluster studies, organisation and management, policy and governance research. It will appeal to researchers from these diverse fields seeking to further develop the meta-organisational view of clusters as well as conceptualise their role in sustainability transitions. This book will also be a useful guide for policymakers who have an interest in the dynamics of economic development and the transition towards sustainability.

Addressing the role of regional clusters in the context of ongoing globalization, this timely book investigates the two seemingly competing trends of globalization and localization from both quantitative and qualitative perspectives. International case studies offer pioneering insights into the internationalization process of regional clusters and the effect of this on regional as well as firm performance.

Transition economies, such as the countries in Southeast Europe, face an expeditious institutional transition from a centrally planned to a market economy. The state withdraws from its monitoring function, which results in institutional voids that affect the economy in general and small and medium sized enterprises (SMEs) in specific. With a qualitative case study approach Tine Schrammel develops a scheme to detect institutional voids as one source of competitive disadvantages of SMEs in transition economies. In a second step she demonstrates that specific cluster services bridge institutional voids and improve the competitive position of SMEs in environments of institutional voids. The findings add to the understanding of institutional voids and to the role of clusters in transition economies.

"This book provides theoretical frameworks and empirical research findings to assist managers, academics and consultants gain a thorough understanding of intellectual capital and social capital as a base for improving their tasks"--Provided by publisher.

Statistical Rethinking: A Bayesian Course with Examples in R and Stan builds readers’ knowledge of and confidence in statistical modeling. Reflecting the need for even minor programming in today’s model-based statistics, the book pushes readers to perform step-by-step calculations that are usually automated. This unique computational approach ensures that readers understand enough of the details to make reasonable choices and interpretations in their own modeling work. The text presents generalized linear multilevel models from a Bayesian perspective, relying on a simple logical interpretation of Bayesian probability and maximum entropy. It covers from the basics of regression to multilevel models. The author also discusses measurement error, missing data, and Gaussian process models for spatial and network autocorrelation. By using complete R code examples throughout, this book provides a practical foundation for performing statistical inference. Designed for both PhD students and seasoned professionals in the natural and social sciences, it prepares them for more advanced or specialized statistical modeling. Web Resource The book is accompanied by an R package (rethinking) that is available on the author’s website and GitHub. The two core functions (map and map2stan) of this package allow a variety of statistical models to be constructed from standard model formulas.