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"This book examines related research in decision, management, and other behavioral sciences in order to exchange and collaborate on information among business, industry, and government, providing innovative theories and practices in operations research"--

In this paper, we sketch the main developments of the program in Econometrics & Management Science at Erasmus University Rotterdam in the past 50 years, discuss its current status and point out the main challenges for the future.

We propose that random variation should be considered one of the most important explanatory mechanisms in the management sciences. There are good theoretical reasons to expect that chance events strongly impact organizational behavior and outcomes. We argue that models built on random variation can provide parsimonious explanations of several important empirical regularities in strategic management and organizational behavior. The reason is that random variation in a structured system can give rise to systematic patterns at the macro level. Here, we define the concept of a chance explanation; describe the theoretical mechanisms by which random variation generates patterns at the macro level; outline how key empirical regularities in management can be explained by chance models; and discuss the implications of chance models for theoretical integration, empirical testing, and management practice.

Evolution has long been a biological process "borrowed" by management sciences to define structural and procedural development in organizations. The theory of Darwinian Evolution in biology has existed for a long time and still (with modification) remains the main theory in life sciences. However in biotechnology new concepts have risen. In parallel, organization sciences have been evolving the concept of evolution on different levels of the organization, discussing the evolution of organization during their life cycle, the evolution of populations of organizations, sectors, etc. Directed evolution in biology creates new organisms that can produce molecules with attributes better fitting industrial use, from naturally occurring organisms, allowing new organisms to function in non‐biological environments and perform processes they never needed to perform in a natural environment. We will show that by translating the concept from biology into organization sciences, we can develop the techniques for the evolution of new organizational structures and fitting routines, that would fit new emerging environments, where we seek the best adapted routines and structures for performance. We will adopt the concept of directly evolving a structure fitting for pre‐designed purposes by using bio‐technology methods, and will try and bridge the gap in organization sciences between the current development of the evolutionary theory and the advance made in biology. At the end discusses opportunities for research (the European Framework Program, national programs), together with a proposed general plan of action. The theory and the techniques descried can lead to further research and active experimentation.

Defines common ground at the interface of strategy and management science and unites the topics with an original approach vital for strategy students, researchers and managers Strategic Analytics: Integrating Management Science and Strategy combines strategy content with strategy process through the lenses of management science, masterfully defining the common ground that unites both fields. Each chapter starts with the perspective of a certain strategy problem, such as competition, but continues with an explanation of the strategy process using management science tools such as simulation. Facilitating the process of strategic decision making through the lens of management science, the author integrates topics that are usually in conflict for MBAs: strategy and quantitative methods. Strategic Analytics features multiple international real-life case studies and examples, business issues for further research and theory review questions and exercises at the end of each chapter. Strategic Analytics starts by introducing readers to strategic management. It then goes on to cover: managerial capabilities for a complex world; politics, economy, society, technology, and environment; external environments known as exogenous factors (PESTE) and endogenous factors (industry); industry dynamics; industry evolution; competitive advantage; dynamic resource management; organisational design; performance measurement system; the life cycle of organisations from start-ups; maturity for maintaining profitability and growth; and finally, regeneration.' -Developed from the author's own Strategy Analytics course at Warwick Business School, personal experience as consultant, and in consultation with other leading scholars -Uses management science to facilitate the process of strategic decision making -Chapters structured with chapter objectives, summaries, short case studies, tables, student exercises, references and management science models -Accompanied by a supporting website Aimed at both academics and practitioners, Strategic Analytics is an ideal text for postgraduates and advanced undergraduate students of business and management.