Idsse-M

2004

This paper reports the preliminary results of a project that is investigating the theoretic foundations of decision support systems (DSS). The project is principally motivated by a concern for the direction and relevance of DSS research. The main areas of research focus are the decision and judgement theoretic base of the discipline, the research strategies used in published articles, and

Decision Support Systems, 2008

This paper integrates a number of strands of a long-term project that is critically analysing the academic field of decision support systems (DSS). The project is based on the content analysis of 1093 DSS articles published in 14 major journals from 1990 to 2004. An examination of the findings of each part of the project yields eight key issues that the DSS field should address for it to continue to play an important part in information systems scholarship. These eight issues are: the relevance of DSS research, DSS research methods and paradigms, the judgement and decision-making theoretical foundations of DSS research, the role of the IT artifact in DSS research, the funding of DSS research, inertia and conservatism of DSS research agendas, DSS exposure in general "A" journals, and discipline coherence. The discussion of each issue is based on the data derived from the article content analysis. A number of suggestions are made for the improvement of DSS research. These relate to case study research, design science, professional relevance, industry funding, theoretical foundations, data warehousing, and business intelligence. The suggestions should help DSS researchers construct high quality research agendas that are relevant and rigorous.

Springer Handbook of Automation, 2002

Today, at the turn of the 21st century, many managers are using computers, business databases, and models to help make decisions. This is a positive change in behavior, and some evidence indicates the use of computers to support management decision making is entering a new and more sophisticated stage. The novelty of managers using computers is wearing off, and, more importantly, the capabilities of our support systems are beginning to match the expectations of managers. Decision Support Systems (DSS) are now both a business necessity and an opportunity to gain competitive advantage. This book tries to build on these positive changes and provide an updated exploration of computerized decision support systems. Decision Support Systems: Concepts and Resources for Managers is only one part of an innovative knowledge resource for people interested in learning more about DSS. It is an extension and integration of materials at DSSResources.COM. The idea is to develop a book that is strong on concepts and theory with timely and up-to-date application examples, integrated with Web-based materials. MISSION, AUDIENCE AND OBJECTIVES The mission of both the book and DSSResources.COM is to help people increase their knowledge of how to use information technologies and software to improve decision making. The primary target audience is managers interested in investigating innovative Decision Support Systems. My perspective at DSSResources.COM and in this book is both managerial and technical. In writing the chapters and collecting resources, my overriding concern has been to help people gain capabilities, knowledge, and skills that they can apply as they use and manage information systems and technologies. Some readers can apply the knowledge in this book to help build a DSS. Some xii Preface readers may want to read additional, specialized books and work as decision support analysts; some may be assigned to DSS project teams; and others may help in managing a DSS or in training DSS users. The primary focus of this book is helping people develop intellectual capabilities related to the design and development of DSS. The book also explores how DSS can support organization goals a nd how DSS impact organizations and managers. Throughout the book, DSS are defined broadly as interactive computer-based systems that help people use computer communications, data, documents, knowledge, and models to solve problems and make decisions. DSS are ancillary or auxiliary systems; they are not intended to replace skilled decision makers. This book examines the design, development, and implementation of systems that support management decision making. The focus is on technologybased systems. After completing Decision Support Systems: Concepts and Resources for Managers, readers should: • Have a more sophisticated understanding of how a DSS can help a company meet its objectives, including gaining a competitive advantage, increasing revenues and profits, decreasing expenses, providing better customer service, and improving decision making; • Be better informed consumers of DSS and information technology resources, especially for end-user development of DSS applications; • Know more about the Internet, the World Wide Web, its potential uses to support decision making, and its impact on decision behavior; • Have more capabilities related to DSS design and development; and, • Understand that Decision Support Systems are intended to support rather than replace decision makers. The emphasis throughout the book is on making sense of a rapidly changing computing applications area. Both descriptive and prescriptive ideas are linked to an expanded component-driven DSS framework. The focus is heavily oriented to practice and applications, but, when possible, empirical results and theory are referred to in an attempt to create a more enduring context for the conclusions. Also, every effort has been made to find examples that are current and understandable. In general, this is an "applications" book more than a "theory" book. It provides enough concrete detail to help people understand their experiences using DSS, and it has suggestions for people involved with DSS projects. Also, the book provides the knowledge and framework needed by people who want a general familiarity with current developments and with "what is possible." OVERVIEW OF THE CONTENTS Decision Support Systems: Concepts and Resources for Managers has 12 chapters. Chapter 1, titled "Supporting Business Decis ion Making," provides a rationale for studying about and understanding DSS and presents an expanded Preface xiii framework for categorizing DSS. Also, the chapter explains the differences between transaction processing systems and DSS. "Gaining Competitive Advantage with Decision Support Systems" is the focus of Chapter 2. After reviewing some technology trends that provide new opportunities for building DSS, the chapter discusses how DSS can create a competitive advantage. A few classic examples of DSS that provided companies with a competitive advantage are summarized in the chapter. Understanding business decision making and business decision processes is the key to building an effective DSS. Chapter 3, titled "Analyzing Business Decision Processes," explains fundamental concepts related to business decision making. Chapter 4, "Designing and Developing Decision Support Systems," is a pivotal chapter that changes the focus of the book to more technical issues. Once the topic of building and buying DSS is raised and discussed in Chapter 4, the next chapter addresses the topic of greatest importance to DSS success, the user interface. In Chapter 5, "Designing and Evaluating DSS User Interfaces," various types of user interfaces are briefly reviewed. The goal is to examine guidelines for DSS user interfaces. Chapter 6 is titled "Understanding DSS Architecture, Networking, and Security Issues," and it attempts to present a simplified introduction to extremely complex technical topics. The topics in this chapter are important for management-oriented and more technically savvy readers. Chapters 7 through 11 provide more details and examples related to the categories in the expanded DSS framework. Each chapter provides a survey of what is possible and an introduction to technical issues for making an innovative DSS a reality. Chapter 7 focuses on "Implementing Communications-Driven and Group Decision Support Systems;" Chapter 8 is titled "Building Data and Document-Driven Decision Support Systems;" Chapter 9, "Building Knowledge-Driven DSS and Mining Data," examines two related technologies, management expert systems and data mining. Chapter 10 discusses "Building Model-Driven Decision Support Systems;" Chapter 11, titled "Building Web-Based and Interorganizational Decision Support Systems," examines the latest developments in decision support. The concluding chapter of Decision Support Systems: Concepts and Resources for Managers is titled "Evaluating Decision Support System Projects." After reading the prior chapters, managers and aspiring managers may have some novel or interesting ideas for DSS. So, this chapter reviews and discusses tools and issues associated with evaluating proposed DSS projects. This book also includes a decision support readiness audit and a glossary of key decision support system terms.

2000

Integrated Decision-Making Support Systems (IDMSS), are specialized Computer Based Information Systems designed to support all phases of the DecisionMaking Process. Full integration of stand-alone components was proposed in the early 90 s and, despite substantial reported benefits above less integrated systems, few of the fully integrated systems have been implemented in practice. We believe that this “implementation paradox” is caused by the lack of a process-oriented perspective to guide the implementation of IDMSS. This tutorial has the goal of offering such a process-oriented approach.

Concepts, Methodologies, Tools, and Applications

Since their creation in the early 1960's, decision support systems (DSSs) have evolved over the past 4 decades and continue to do so today. Although DSSs have grown substantially since its inception, improvements still need to be made. New technology has emerged and will continue to do so and, consequently, DSSs need to keep pace with it. Also, knowledge needs to play a bigger role in the form of decision making. We first discuss design and analysis methods/techniques/issues related to DSSs. Then, the three possible ways to enhance DSSs will be explored.

Systemic Practice and Action Research, 1992

A study of the DSS implementation area reveals an increased emphasis on methodologies for DSS development. As the DSS field matures, a larger number of methodological options are becoming available to the DSS developer. Existing methodologies have adopted various methods for performing the important task of DSS requirements analysis and specification. In envisaging a hierarchy of requirements analysis methods, a method for improved requirements analysis is proposed to remedy observed deficiencies within it. This method is based on a view of generic types of inquiries or solicitations made by the DSS user during decision-making. This formalism constitutes the basis of a proposed DSS development methodology that offers several benefits to DSS development. The intended benefits include a sharper and more focused requirements analysis to improve the DSS development process. This paper describes the model and methodology, alongside details of a real-world example of their use in developing a Marketing Decision Support System (MKDSS) for the support of marketing decision-making.

2014

Http Dx Doi Org 10 1080 02827581 2013 837950, 2014

Decision support systems (DSSs) are important in decision-making environments with conflicting interests. Many DSSs developed have not been used in practice. Experts argue that these tools do not respond to real user needs and that the inclusion of stakeholders in the development process is the solution. However, it is not clear which features of participatory development of DSSs result in improved uptake and better outcomes. A review of papers, reporting on case studies where DSSs and other decision tools (information systems, software and scenario tools) were developed with elements of participation, was carried out. The cases were analysed according to a framework created as part of this research; it includes criteria to evaluate the development process and the outcomes. Relevant aspects to consider in the participatory development processes include establishing clear objectives, timing and location of the process; keeping discussions on track; favouring participation and interaction of individuals and groups; and challenging creative thinking of the tool and future scenarios. The case studies that address these issues show better outcomes; however, there is a large degree of uncertainty concerning them because developers have typically neither asked participants about their perceptions of the processes and resultant tools nor have they monitored the use and legacy of the tools over the long term.

2016

Despite a well-established research tradition, the field of Decision Support Systems (DSS) suffers from a lack of practitioner relevance. DSS researchers have comprehended the emergence of Design Science Research (DSR) for the issue as it provides support to improve the behavioral aspect of design. However, conceptualizations for DSR as the common approach to conducting DSS research have not been materialized to address the relevance issues. In the paper extending an existing conceptualization, we introduce a new DSR view for DSS development. The view incorporates design dimensions related to DSS design, such as professional value, interaction, intentions, practices, and problem-solving. We developed the DSR view from an action design research approach conducted through a well-defined framework for developing a generic DSS solution. The view represents the importance of practitioner’s centric DSR to better address practitioner’s relevance issues in DSS design.

Journal of Information Technology, 2005

This paper critically analyses the nature and state of decision support systems (DSS) research. To provide context for the analysis, a history of DSS is presented which focuses on the evolution of a number of sub-groupings of research and practice: personal DSS, group support systems, negotiation support systems, intelligent DSS, knowledge management-based DSS, executive information systems/business intelligence, and data warehousing. To understand the state of DSS research an empirical investigation of published DSS research is presented. This investigation is based on the detailed analysis of 1,020 DSS articles published in 14 major journals from 1990 to 2003. The analysis found that DSS publication has been falling steadily since its peak in 1994 and the current publication rate is at early 1990s levels. Other findings include that personal DSS and group support systems dominate research activity and data warehousing is the least published type of DSS. The journal DSS is the majo...