Probabilistic modeling represents a subject spanning many branches of mathematics, economics, and computer science to connect pure mathematics with applied sciences. Operational research also relies on this connection to enable the improvement of business functions and decision making. Analyzing Risk through Probabilistic Modeling in Operations Research is an authoritative reference publication discussing the various challenges in management and decision science. Featuring exhaustive coverage on a range of topics within operational research including, but not limited to, decision analysis, data mining, process modeling, probabilistic interpolation and extrapolation, and optimization methods, this book is an essential reference source for decision makers, academicians, researchers, advanced-level students, technology developers, and government officials interested in the implementation of probabilistic modeling in various business applications.

This book is intended for systems analysts, designers, developers, users, experts, as well as those involved in quality, risk, safety and security management, and, of course, scientists and students. The various sets of original and traditional probabilistic models and interesting results of their applications to the research of different systems are presented. The models are understandable and applicable for solving system engineering problems: to optimize system requirements, compare different processes, rationale technical decisions, carry out tests, adjust technological parameters, and predict and analyze quality and risks. The engineering decisions, scientifically proven by the proposed models and software tools, can provide purposeful, essential improvement of quality and mitigation of risks, and reduce the expense of operating systems. Models, methods, and software tools can also be used in education for system analysis and mathematical modeling on specializations, for example "systems engineering," "operations research," "enterprise management," "project management," "risk management," "quality of systems," "safety and security," "smart systems," "system of systems," etc.

A graduate level textbook on probabilistic risk analysis, aimed at statisticians, operations researchers and engineers.

The integration of recent technological advances into modern business processes has allowed for greater efficiency and productivity. However, while such improvements are immensely beneficial, the modeling and coordination of these activities offers a unique set of challenges that must be addressed. Business Architectures for Risk Assessment and Strategic Planning: Emerging Research and Opportunities is a pivotal reference source for the latest research findings on the utilization of business models and value propositions in modern enterprises. Featuring extensive coverage on relevant areas such as management information systems, business planning, and value analysis, this publication is an ideal resource for information system practitioners, universities and colleges, business managers, and advanced-level students seeking the latest research on achievements in this field.

Globalization, accelerated by information technologies, has increased the speed of business transactions and has reduced the distances between international businesses. This growth has transformed the realm of foreign investment in countries around the world, calling for a methodological approach to planning feasible capital investment proposals in general and foreign direct investment projects. Planning and Analyzing Foreign Direct Investment Projects: Emerging Research and Opportunities is a pivotal reference source that provides a systems approach to investment projects in a globalized and open society. While highlighting topics such as consumer analysis, competitive strategy, and market analysis, this publication explores the profitability and feasibility of international investments, as well as the risks and resources associated with strategic project planning. This book is ideally designed for business managers, entrepreneurs, researchers, academicians, graduate students, policymakers, investors, and project managers seeking current research on planning, analyzing, and evaluating investment projects.

Probabilistic modeling represents a subject arising in many branches of mathematics, economics, and computer science. Such modeling connects pure mathematics with applied sciences. Similarly, data analyzing and statistics are situated on the border between pure mathematics and applied sciences. Therefore, when probabilistic modeling meets statistics, it is a very interesting occasion that has gained much research recently. With the increase of these technologies in life and work, it has become somewhat essential in the workplace to have planning, timetabling, scheduling, decision making, optimization, simulation, data analysis, and risk analysis and process modeling. However, there are still many difficulties and challenges that arrive in these sectors during the process of planning or decision making. There continues to be the need for more research on the impact of such probabilistic modeling with other approaches. Analyzing Data Through Probabilistic Modeling in Statistics is an essential reference source that builds on the available literature in the field of probabilistic modeling, statistics, operational research, planning and scheduling, data extrapolation in decision making, probabilistic interpolation and extrapolation in simulation, stochastic processes, and decision analysis. This text will provide the resources necessary for economics and management sciences and for mathematics and computer sciences. This book is ideal for interested technology developers, decision makers, mathematicians, statisticians and practitioners, stakeholders, researchers, academicians, and students looking to further their research exposure to pertinent topics in operations research and probabilistic modeling.