The book contains the Proceedings of the 2010 Conference of the Italian Systems Society. Papers deal with the interdisciplinary study of processes of changing related to a wide variety of specific disciplinary aspects. Classical attempts to deal with them, based on generalising approaches used to study the movement of bodies and environmental influence, have included ineffective reductionistic simplifications. Indeed changing also relates, for instance, to processes of acquisition and varying properties such as for software; growing and aging biological systems; learning/cognitive systems; and socio-economic systems growing and developing through innovations. Some approaches to modelling such processes are based on considering changes in structure, e.g., phase-transitions. Other approaches are based on considering (1) periodic changes in structure as for processes of self-organisation; (2) non-periodic but coherent changes in structure, as for processes of emergence; (3) the quantum level of description. Papers in the book study the problem considering its transdisciplinary nature, i.e., systemic properties studied per se and not within specific disciplinary contexts. The aim of these studies is to outline a transdisciplinary theory of change in systemic properties. Such a theory should have simultaneous, corresponding and eventually hierarchical disciplinary aspects as expected for a general theory of emergence. Within this transdisciplinary context, specific disciplinary research activities and results are assumed to be mutually represented as within a philosophical and conceptual framework based on the theoretical centrality of the observer and conceptual non-separability of context and observer, related to logically open systems and Quantum Entanglement. Contributions deal with such issues in interdisciplinary ways considering theoretical aspects and applications from Physics, Cognitive Science, Biology, Artificial Intelligence, Economics, Architecture, Philosophy, Music and Social Systems.

With the advent of electronic databases, information technologies, and the Internet, organizations now more than ever have easy access to all the knowledge they need to conduct their affairs. Identifying the useful information in all that data, however, can pose a challenge. Knowledge Discovery, Transfer, and Management in the Information Age brings together the latest empirical research in knowledge management practices and information retrieval strategies to assist organizations in effectively and efficiently utilizing the data at their disposal. Academics, managers, researchers, and professionals within the field of knowledge management will make use of this book to increase their understanding of best practices in the manipulation of information resources.

In the aftermath of both ongoing globalisation (with both widening and deepening effects on countries, regions and cities) and structural changes resulting from the 2008 economic recession, regions and cities in our world are confronted with a different arena of players, performances and institutions. The challenges are formidable and numerous. Many regions and cities seem to resort to their indigenous strength, without much regard to other players in the field. This has enormous consequences for the competitive behaviour and profile of regional and urban actors but has at the same time deep impacts on the distribution of wealth, income and employment over and within countries, regions and cities. There is indeed much evidence that disparities among regions and in cities are increasing in this new force field. This special issue of REGION makes a solid scientific attempt (i) to map out the spatial consequences of recent transitions in growth trajectories of countries or regions, and (ii) to trace policy strategies and design effective policy information, to cope adequately with these new challenges. The present special issue does so by highlighting the new force field of regional and urban dynamics from three angles in the context of spatial quality and inequality. These will be briefly sketched below.

Within the field of psychology there is a proliferation of paradigms, theories, models, and dimensions without an underlying conceptual framework or theory. This conclusion has been reached by representatives of many different psychological specialties. In response to this inconsistency this book presents a hierarchical framework about important theoretical issues that are present in psychological thinking. These issues concern definitions of three major theoretical concepts in theory and practice: (a) paradigms, (b) theories, and (c) models. It focuses on defining, comparing, and contrasting these three conceptual terms. This framework clarifies differences among paradigms, theories, and models, terms which have become increasingly confused in the psychological literature. Paradigms are usually confused with theories or with models while theories are confused with models. Examples of misuses of these terms suggest the need for a hierarchical structure that views paradigms as conceptual constructions overseeing a variety of psychological theories and verifiable models.

Since the publication of the first edition in 1982, the goal of Simulation Modeling and Analysis has always been to provide a comprehensive, state-of-the-art, and technically correct treatment of all important aspects of a simulation study. The book strives to make this material understandable by the use of intuition and numerous figures, examples, and problems. It is equally well suited for use in university courses, simulation practice, and self study. The book is widely regarded as the “bible” of simulation and now has more than 100,000 copies in print. The book can serve as the primary text for a variety of courses; for example: • A first course in simulation at the junior, senior, or beginning-graduate-student level in engineering, manufacturing, business, or computer science (Chaps. 1 through 4, and parts of Chaps. 5 through 9). At the end of such a course, the students will be prepared to carry out complete and effective simulation studies, and to take advanced simulation courses. • A second course in simulation for graduate students in any of the above disciplines (most of Chaps. 5 through 12). After completing this course, the student should be familiar with the more advanced methodological issues involved in a simulation study, and should be prepared to understand and conduct simulation research. • An introduction to simulation as part of a general course in operations research or management science (part of Chaps. 1, 3, 5, 6, and 9).