How can business decisions be made and tackled using economic theory, decision science methodology and computer modelling? Economic Analysis for Business and Strategic Decisions explains in a clear and layman-like format how you can apply these cutting-edge economic and financial concepts and tools to solving your real-life business problems. You will learn how to use this high-level economic thinking in making business and strategic decisions such as pricing strategies, yet still employing your regular computer software.
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This book presents introductory economics material using standard mathematical tools, including calculus. It is designed for a relatively sophisticated undergraduate who has not taken a basic university course in economics. The book can easily serve as an intermediate microeconomics text. The focus of this book is on the conceptual tools. Contents: 1) What is Economics? 2) Supply and Demand. 3) The US Economy. 4) Producer Theory. 5) Consumer Theory. 6) Market Imperfections. 7) Strategic Behavior.
This book provides a unified framework for business decision-making, by developing a logical and systematic approach to business problems. The book is split into three parts - The Nature of Decisions, The Decision Environment and Decision Areas, whilst each chapter concludes with a specific application of the principles and concepts outlined. The intended readership includes both undergraduate and postgraduate students of business, whilst its depth and range make it relevant to business studies and professional courses. Included in the book are a selection of undergraduate and postgraduate examination questions, together with notes on answers.
Widely acknowledged, this popular and detailed text is a comprehensive treatise on Managerial Economics both micro and macro-economic aspects. This text ensures a thorough understanding of core concepts before advancing to provide an expanded treatment of topics. It explains the economic environment and the impact on managerial decisions regarding price & output determination in different market structures followed by an account of the behaviour of individuals under conditions of uncertainty.
This introductory textbook presents research methods and data analysis tools in non-technical language. It explains the research process and the basics of qualitative and quantitative data analysis, including procedures and methods, analysis, interpretation, and applications using hands-on data examples in QDA Miner Lite and IBM SPSS Statistics software. The book is divided into four parts that address study and research design; data collection, qualitative methods and surveys; statistical methods, including hypothesis testing, regression, cluster and factor analysis; and reporting. The intended audience is business and social science students learning scientific research methods, however, given its business context, the book will be equally useful for decision-makers in businesses and organizations.
An introduction to the use of probability models for analyzing risk and economic decisions, using spreadsheets to represent and simulate uncertainty. This textbook offers an introduction to the use of probability models for analyzing risks and economic decisions. It takes a learn-by-doing approach, teaching the student to use spreadsheets to represent and simulate uncertainty and to analyze the effect of such uncertainty on an economic decision. Students in applied business and economics can more easily grasp difficult analytical methods with Excel spreadsheets. The book covers the basic ideas of probability, how to simulate random variables, and how to compute conditional probabilities via Monte Carlo simulation. The first four chapters use a large collection of probability distributions to simulate a range of problems involving worker efficiency, market entry, oil exploration, repeated investment, and subjective belief elicitation. The book then covers correlation and multivariate normal random variables; conditional expectation; optimization of decision variables, with discussions of the strategic value of information, decision trees, game theory, and adverse selection; risk sharing and finance; dynamic models of growth; dynamic models of arrivals; and model risk. New material in this second edition includes two new chapters on additional dynamic models and model risk; new sections in every chapter; many new end-of-chapter exercises; and coverage of such topics as simulation model workflow, models of probabilistic electoral forecasting, and real options. The book comes equipped with Simtools, an open-source, free software used througout the book, which allows students to conduct Monte Carlo simulations seamlessly in Excel.
There is a small and growing literature that explores the impact of digitization in a variety of contexts, but its economic consequences, surprisingly, remain poorly understood. This volume aims to set the agenda for research in the economics of digitization, with each chapter identifying a promising area of research. "Economics of Digitization "identifies urgent topics with research already underway that warrant further exploration from economists. In addition to the growing importance of digitization itself, digital technologies have some features that suggest that many well-studied economic models may not apply and, indeed, so many aspects of the digital economy throw normal economics in a loop. "Economics of Digitization" will be one of the first to focus on the economic implications of digitization and to bring together leading scholars in the economics of digitization to explore emerging research.
