Information Systems Success Measurement presents a comprehensive review of the foundations, the trends, and the future challenges of IS success measurement in order to improve research and practice in terms of the measurement and evaluation of information systems. Information Systems Success Measurement explores the foundations and trends in the definition and measurement of information systems success. Starting with an introduction that examines how the concept of "effective" or "successful" information systems has progressed as information technology and its use has changed over the past 60 years. The authors introduce the DeLone and McLean Information Systems Success Model as an organizing framework for this monograph. Section 2 identifies five eras of information systems and for each of these eras the authors consider the types of information systems used in firms, the stakeholders impacted by these systems, the relevant research about information systems evaluation, and the measurement of IS success in practice during each of these periods. Section 3 discusses the foundational research on IS success measurement. Based on the evolution of the field's understanding of IS success, important trends in IS success measurement is highlighted in Section 4. Section 5 examines the future of IS success research. Section 6 reviews empirical findings related to success factors, which influence IS success. Section 7 explores how managers can improve the methods they use to measure and track IS success. Finally, the authors offer concluding remarks in Section 8.

Information Systems Success Measurement focuses on insights and developments related to system success, including comparisons of system success instruments, validation of system success measures, and new and improved measures of systems success. It presents a wide range of important areas within the information systems success research agenda. This book will provide researchers and professionals with a comprehensive reference for understanding and measuring systems success in modern organizations throughout the world.

"This book explores new approaches which may better effectively identify, explain, and improve IS assessment in organizations"--Provided by publisher.

Currently, there is neither a commonly-accepted definition of information systems (IS) quality nor a convergence of perspectives on quality approaches. The IS community has focused on the various contributions of people, delivery processes, development philosophies and methods. Measuring Information Systems Delivery Quality represents a spotlight on IS quality that represents the efforts of authors from several countries across the globe. Despite this diversity, this book reflects the common position that improving objective knowledge of potentially quality-enhancing methods is far more likely to assist the production of high-quality software than experimentation with each new gadget. Measuring Information Systems Delivery Quality provides thoughtful analysis and explains some of the contradictions and apparent paradoxes of the many IS quality perspectives. It offers prescriptions, grounded in research findings, syntheses of relevant, up-to-date literature, and leading IS quality practices to assist the assimilation, measurement, and management of IS quality in order to increase the odds of producing higher quality systems.

Performance improvement thought leader Dean Spitzer explains why performance measurement should be less about calculations and analysis and more about the crucial social factors that determine how well the measurements get used. Transforming Performance Measurement presents a breakthrough approach that will not only significantly reduce those dysfunctions, but also promote alignment with business strategy, maximize cross-enterprise integration, and help everyone to work collaboratively to drive value throughout your organization. Spitzer’s "socialization of measurement" process focuses on learning and improvement from measurement, and on the importance of asking such questions as: How well do our measures reflect our business model? How successfully are they driving our strategy? What should we be measuring and not measuring? Are the right people having the right measurement discussions? Performance measurement is a dynamic process that calls for an awareness of the balance necessary between seemingly disparate ideas: the technical and the social aspects of performance measurement. This book gives you assessment tools to gauge where you are now and a roadmap for moving, with little or no disruption, to a more "transformational" and mature measurement system. The book also provides 34 TMAPs, Transformational Measurement Action Plans, which suggest both well-accepted and "emergent" measures (in areas such as marketing, human resources, customer service, knowledge management, productivity, information technology, research and development, costing, and more) that you can use right away. Transforming Performance Measurement tells you not only what to measure, but how to do it -- and in what context -- to make a truly transformational difference in your enterprise.

The overall mission of this book is to provide a comprehensive understanding and coverage of the various theories and models used in IS research. Specifically, it aims to focus on the following key objectives: To describe the various theories and models applicable to studying IS/IT management issues. To outline and describe, for each of the various theories and models, independent and dependent constructs, reference discipline/originating area, originating author(s), seminal articles, level of analysis (i.e. firm, individual, industry) and links with other theories. To provide a critical review/meta-analysis of IS/IT management articles that have used a particular theory/model. To discuss how a theory can be used to better understand how information systems can be effectively deployed in today’s digital world. This book contributes to our understanding of a number of theories and models. The theoretical contribution of this book is that it analyzes and synthesizes the relevant literature in order to enhance knowledge of IS theories and models from various perspectives. To cater to the information needs of a diverse spectrum of readers, this book is structured into two volumes, with each volume further broken down into two sections. The first section of Volume 1 presents detailed descriptions of a set of theories centered around the IS lifecycle, including the Success Model, Technology Acceptance Model, User Resistance Theories, and four others. The second section of Volume 1 contains strategic and economic theories, including a Resource-Based View, Theory of Slack Resources, Portfolio Theory, Discrepancy Theory Models, and eleven others. The first section of Volume 2 concerns socio-psychological theories. These include Personal Construct Theory, Psychological Ownership, Transactive Memory, Language-Action Approach, and nine others. The second section of Volume 2 deals with methodological theories, including Critical Realism, Grounded Theory, Narrative Inquiry, Work System Method, and four others. Together, these theories provide a rich tapestry of knowledge around the use of theory in IS research. Since most of these theories are from contributing disciplines, they provide a window into the world of external thought leadership.

Developed by the authors, generalized structured component analysis is an alternative to two longstanding approaches to structural equation modeling: covariance structure analysis and partial least squares path modeling. Generalized structured component analysis allows researchers to evaluate the adequacy of a model as a whole, compare a model to alternative specifications, and conduct complex analyses in a straightforward manner. Generalized Structured Component Analysis: A Component-Based Approach to Structural Equation Modeling provides a detailed account of this novel statistical methodology and its various extensions. The authors present the theoretical underpinnings of generalized structured component analysis and demonstrate how it can be applied to various empirical examples. The book enables quantitative methodologists, applied researchers, and practitioners to grasp the basic concepts behind this new approach and apply it to their own research. The book emphasizes conceptual discussions throughout while relegating more technical intricacies to the chapter appendices. Most chapters compare generalized structured component analysis to partial least squares path modeling to show how the two component-based approaches differ when addressing an identical issue. The authors also offer a free, online software program (GeSCA) and an Excel-based software program (XLSTAT) for implementing the basic features of generalized structured component analysis.