In the technical-scientific field, many decisions are supported by measurements. However, it is essential to assign to measurement results their actual meaning to achieve a correct decision. This aspect is particularly important and formally required when operating in Quality Systems. Therefore, measures management must be rigorous and it can find a concrete support in the topics discussed in this volume, because of the attention to metrological part and the removal of unnecessary restrictions.

Measurement, Judgment, and Decision Making provides an excellent introduction to measurement, which is one of the most basic issues of the science of psychology and the key to science. Written by leading researchers, the book covers measurement, psychophysical scaling, multidimensional scaling, stimulus categorization, and behavioral decision making. Each chapter provides a useful handbook summary and unlocks the door for a scholar who desires entry to that field. Any psychologist who manipulates an independent variable that affects a psychological construct or who uses a numerical dependent variable to measure a psychological construct will want to study this book. Written by leading researchers in fields of measurement, psychophysical scaling, multidimensional scaling, stimulus categorization, and behavioral decision making Provides basic definitions and summaries of theories Presents summaries and citations to relevant literature Contains new developments, current controversies, and open questions Explains relationships among fields and historical links

The IT community has always struggled with questions concerning the value of an organization’s investment in software and hardware. It is the goal of value-based software engineering (VBSE) to develop models and measures of value which are of use for managers, developers and users as they make tradeoff decisions between, for example, quality and cost or functionality and schedule – such decisions must be economically feasible and comprehensible to the stakeholders with differing value perspectives. VBSE has its roots in work on software engineering economics, pioneered by Barry Boehm in the early 1980s. However, the emergence of a wider scope that defines VBSE is more recent. VBSE extends the merely technical ISO software engineering definition with elements not only from economics, but also from cognitive science, finance, management science, behavioral sciences, and decision sciences, giving rise to a truly multi-disciplinary framework. Biffl and his co-editors invited leading researchers and structured their contributions into three parts, following an introduction into the area by Boehm himself. They first detail the foundations of VBSE, followed by a presentation of state-of-the-art methods and techniques. The third part demonstrates the benefits of VBSE through concrete examples and case studies. This book deviates from the more anecdotal style of many management-oriented software engineering books and so appeals particularly to all readers who are interested in solid foundations for high-level aspects of software engineering decision making, i.e., to product or project managers driven by economics and to software engineering researchers and students.

-Identify your critical decisions. Focus on those that matter most to your company's performance. --

The research reported here deals with finding why people make some choices rather than others, why different people make different decisions in objectively similar situations. The book requires that its reader have some basic knowledge of statistical methods, and, since, it cuts across normally separate fields, it requires an adventuresome spirit. But, in return, the reader may expect to gain the use of a powerful tool that can be applied in his own practical projects and social science research.The message is on two levels. On one, the work is a practical handbook for application. On the other, it discusses some fundamental issues in the theory of decision-making and the social sciences.The book presents an application method for measuring assumptions realistic enough for use in management context. In a test-case study, the author uncovered startling diversity in the attributes investors use in picking stocks. More generally, such measures of assumptions are useful in managerial planning and control to aid in decision-making consistence, in learning to revise decision assumptions, and in designing information systems to support decision-making. They are also useful in improving joint decision-making and communication. Still other important applications are possible in consumer market research and in operations research modeling of decision processes. These applications are described with suggestive examples.To the management scientist the author seeks to show the benefits of extending explicitness beyond the traditional bounds of information systems into the realm of subjective decision assumptions. That is, subjective assumptions made explicit in a practical manner are employed as useful inputs to managerial information systems.Such measurement methods as reported here may also have widespread use in building social theory. Individual decision assumptions are key variables in microeconomics, in political science, in organization theory, and in the sociology of knowledge. Their measures play an analogous role in social science to that of thermometers in the development of thermodynamics.The material is developed as follows: First, the problem of discovering the assumptions which underlie decisions is sketched broadly. Alternative possible measurement approaches and theories are then described in logical order. An outline of the method for measuring assumptions is followed by the account of its use in a case study of stock market participants. It is this narrative that provides a practical handbook for the reader's use. A number of prototype applications are shown in some detail. The final chapters propose uses of the method for research in the social sciences and in accounting and the financial markets.