Decision Support Systems and Megaputer (2nd Edition)

Book Description
Packed with essential information, this valuable volume helps future business management professionals learn to make and support managerial decisions, providing a thorough understanding of the support aspect of DSS. Written from a cognitive processes and decision-making perspective, it concentrates on issues that emphasize managerial applications and the implication of decision support technology on those issues. The volume examines data warehouses, intelligent software agents and DSS system development, as well as an introduction to decision support systems, decision in the organization, modeling decision processes, group decision support and groupware technologies, executive information systems, expert systems and artificial intelligence, knowledge engineering and acquisition, and data mining and data visualization. For Data Warehouse Administrators, CIO and Directors of Information Systems.

From the Back Cover
Students will... Learn Data warehousing, data mining and visualization, and intelligent agent technology. Practice With the end-of-chapter material, the Companion Website at www.prenhall.com/marakas, and Megaputer Intelligence, Inc.'s©, PolyAnalyst™ and TextAnalyst™ data mining and visualization software applications. The Megaputer software suite represents the leading edge in data mining and visualization applications and is being distributed exclusively with this textbook. Real-world data sets are used in both the tutorials and for many of the Megaputer exercises included at the end of relevant chapters. Students will use the Megaputer software in conjunction with exercises from this text to associate, classify, predict, and acquire knowledge from numerical and structured data. Apply The expertise gained from Marakas's Decision Support Systems in the 21st Century, Second Edition, and the Megaputer software as they enter the workforce to make informed managerial decisions with knowledge extracted from data mining and warehousing technologies. New to the Second Edition Three completely new chapters covering topics related to intelligent software agents, DSS system development, and building data warehouses. State-of-the-art DSS design and implementation coverage giving this edition a greater technical focus than its first edition.

About the Author
George M. Marakas is an associate professor of information systems and the BAT Faculty Fellow in Global IT Strategy at the Kelley School of Business at Indiana University in Bloomington. His teaching expertise includes systems analysis and design, technology-assisted decision making, managing IS resources, behavioral IS research methods, and data visualization and decision support. In addition, Marakas is an active researcher in the area of systems analysis methods, data mining and visualization, creativity enhancement, conceptual data modeling, and computer self-efficacy. Marakas received his doctorate in information systems from Florida International University in Miami and his MBA from Colorado State University. Prior to his academic career, he enjoyed a highly successful career in the banking and real estate industries. His corporate experience includes senior management positions with Continental Illinois National Bank and the FDIC. In addition, Marakas served as president and CEO for CMC Group, Inc., a major RTC management contractor in Miami, for 3 years. During his tenure at the University of Maryland and now at Indiana University, Marakas distinguished himself both through leis research and in the classroom. He received numerous national teaching awards, and his research has appeared in the top journals in his field. Beyond his academic endeavors, Marakas is also an active consultant and serves as an advisor to a number of organizations including the Central Intelligence Agency, the Department of the Treasury, the Department of Defense, British-American Tobacco, Xavier University, Citibank Asia-Pacific, Nokia Corporation, Eli Lilly Corporation, and United Information Systems, among many others. His consulting activities are concentrated primarily on e-commerce strategy, workflow reengineering, CASE tool integration, and global IT strategy formation. He is a Novell Certified Network Engineer and has been involved in the corporate beta testing program for Microsoft Corporation since 1990. Marakas is also an active member of a number of professional IS organizations, an avid golfer, a PADI-certified divemaster, and a member of Pi Kappa Alpha fraternity.

Excerpt. © Reprinted by permission. All rights reserved.
We face decisions every day. The really good news about making decisions is that most of the ones encountered in our daily lives are both routine and relatively clear-cut. What clothes to wear, what to have for breakfast, what movie to watch on television, or what food to buy at the grocery are all typical of the day-to-day decisions that confront us. The bad news is that, although important, these decisions do not resemble the type that we must face in the course of pursuing our chosen occupation. We will not get paid for being able to decide what to wear to work. As managers, we establish our worth with our organizations by being able to cope with decisions such as whether to invest in an emerging technology that could create significant competitive advantage for the firm, or how we can best deploy the limited human resources available for a given project, or what mix of products is best for the current and future market conditions. In other words, the really important decisions are often difficult to make and require both a great deal of information and an increased level of decision support, which brings us to what this book is all about: making and supporting managerial decisions. CONCEPT AND PURPOSE This text provides a foundation for teaching the subject of decision support systems (DSSs) from a cognitive processes and decision-making perspective. The contents emphasize managerial applications and the implication of decision support technologies on those issues. Gorry and Scott Morton (1989) are often credited for the classic definition of a DSS: Decision support systems couple the intellectual resources of individuals with the capabilities of the computer to improve the quality of decisions. They comprise a computer-based support system for management decision makers who deal with semi-structured problems. (p. 60) I find it somewhat counterintuitive that the definition of the subject is written from a user's perspective, yet the texts available to teach the subject to students in business schools tend to be written from a designer's perspective. In response, this text places strong emphasis on helping the student thoroughly understand the "support" aspect of a DSS. The content focuses on a distinctly "real-world" orientation that emphasizes application and implementation over design and development in all topic areas. The manager of tomorrow does not need to understand DSS design, which is the domain of the computer scientist and the systems analyst. Rather, the skills necessary relate to the effective and strategic application of decision support technologies to advance the quality of problem identification and the associated solutions. Taking a multidisciplinary user/manager approach, this text looks at decisions and technologies necessary to support those decisions in the twenty-first century. The coverage of decision making and cognitive processes includes such topics as models of decision making, biases and heuristics, creativity enhancement, decision strategies, simulation, and discovery. This book reflects an incorporation of the best components of the leading texts on decision support while additionally providing coverage of topics not previously broached (most notably, data visualization and mining). In short, this book was motivated by my belief in the need to integrate our knowledge of decision making with the application of decision support technology! Application and understanding of use are, and will continue to be, more important to our managers of today and tomorrow than design. WHO SHOULD USE THIS BOOK This book is directed to business school students who aspire to a career in management with a firm that is a significant user of technology or is a member of a technology-driven industry—in others words, all students in business school. The primary course targets for this text are upper-level undergraduate or graduate DSS electives. These types of courses ire regularly offered at 4-year universities as well as many community colleges. Ideally, students should have completed an introductory MIS program and possibly a semester of systems analysis and design before moving on to a focus on DSSs. In addition, the further students are in their business curriculum, the more relevant the decision-making perspective of the text becomes. In addition to being directed to students, many of the chapters in this text offer a good reference for practitioners in the course of their daily decision-making activities. ELEMENTS OF PEDAGOGY The text makes appropriate use of many traditional pedagogical features commonly found in top business school curricula. The writing style is intended to strike a useful balance between a professional and conversational approach. The text uses graphics and examples of each concept introduced extensively throughout. Each chapter contains an introductory minicase highlighting the concepts introduced in that chapter. The end-of-chapter structure contains a summary of the key concepts introduced, review questions and problems, and additional support readings. A brief description of each of the pedagogical features of the text is listed here. Chapter Learning Objectives A statement of learning objectives for each chapter is presented in both performance and behavioral terms. In other words, the objectives state what the student should be capable of doing and understanding as a result of reading the chapter. Chapter Minicase The minicases are all derived from actual situations and were selected to allow the student a point of reference for the material about to be presented in the chapter. In addition, each minicase makes specific reference to each of the key players in the scenario so that additional investigation using a variety of research tools could be conducted by either an individual student or a student team to further explore the situation presented. Figures and Tables Clear, carefully designed figures and tables can aid in the student's understanding of the material. Wherever possible, the diagrams contained in each chapter are not only referenced in the body of the text but are positioned in such a way that they serve as a repeated visual reference for the textual discussion. Narrative Vignettes To further the explanation of some of the concepts associated with the process of making a decision, the technique of narrative vignette is employed. Here, a situation using a fictitious cast of characters is presented to allow the student not only to see how the particular technique under discussion is applied but also to relate it to a set of circumstances or a context in which it might be considered relevant or applicable. Data Mining and Data Visualization Exercises New to this edition is the bundling of Megaputer's PolyAnalyst and TextAnalyst software. Tutorials found on the supplied CD focus on the component algorithms contained within the applications. Several chapters of the text incorporate exercises that use actual large-scale data sets supplied by Megaputer specifically for this text. In working through these exercises, students receive hands-on experience with actual data mining and data visualization applications. Key Concepts Immediately following each chapter summary is an outline of the key concepts presented in the chapter in order of their appearance. This section can aid the student in reviewing the material contained in the chapter in preparation for class discussion or examination. Questions for Review Each chapter contains a list of 10 to 20 questions intended to support student retention and understanding of the material contained in the chapter. Each question is phrased in such a manner that a detailed and precise answer can be readily found in the chapter. Sample responses to each question are available in the instructor sections of the World Wide Web (WWW) site for the text. Further Discussion Several questions at the end of each chapter expand upon the material presented to allow the student to engage in a richer thought process and discussion than would occur using the review questions. Each of the discussion questions can be used to engage students in an open class discussion, and many of them can be easily expanded into individual or team miniprojects. Companion Web Site The companion Web site for this text is located at www.prenhall.com/marakas. This extensive resource contains direct links to DSS-related Internet sites. To further enhance the learning process, the links are organized in the same manner as the text and are categorized according to their direct relevance to a particular section within each chapter. As such, each section of each chapter can be expanded as necessary by using the Internet resources associated with that section to allow for exploration or greater focus on a particular subject. NEW IN THE SECOND EDITION Several significant changes have been made in this second edition of the text. Most notable is the inclusion of three completely new chapters covering topics related to intelligent software agents, DSS system development, and building data warehouses. In addition, many of the chapters from the first edition were revised to reflect the state-of-the-art in DSS design and implementation. The second major change to this new edition is the inclusion of Megaputer's PolyAnalyst and TextAnalyst data mining and visualization software applications. This software suite represents the leading edge in data mining and visualization applications and is being distributed exclusively with this textbook. To purchase a commercial version of this software would cost more than $10,000. The version included with the text is fully enabled but has a time element built into it such that the software will only be available for use by students during the semester in which they are studying with this text. Included with the Megaputer applications is access to several actual data sets to be used in both the tutorials for the application and for many of the Megaputer exercises included at the end of relevant chapters. IMPORTANT NOTE: The software bundled with this text is intended for use only in conjunction with adoption or purchase of this text. Following the installation and registration process, the software will be fully functional for a period of 6 months from the date of the installation. The software cannot be copied to another machine or reinstalled without purchasing an additional software license. NOTE TO THE INSTRUCTOR Companion Web Site (www.prenhall.com/marakas) The instructor-accessible sections of the Web site contain a number of useful support elements and materials. PowerPoint slide files intended for use in preparing class lectures are provided for each chapter. The review questions found in the text are also posted online so students can conveniently e-mail their answers directly to their professors. In addition, several data sets and sample software packages are either stored or linked to in the instructor section of the site. These resources can be used to create projects of any length or complexity as well as in-class demonstrations of actual DSS-related software applications. Access to the instructor section of the Web site requires a valid user ID and password to enter. You simply need to register yourself as the instructor of the course by going to the Web site and completing the initial instructor registration process. Upon completion of the process, your registration request will be forwarded to your sales representative for validation. If you have any problem with your authorization, please contact your Prentice Hall sales representative. INSTRUCTOR'S RESOURCE CD-ROM The Instructor's Manual, Test Item File, and PowerPoint slides are conveniently found on the Instructor's Resource CD-ROM. The Instructor's Manual and PowerPoint slides are also available for download from the secure faculty section of the Marakas Web site. MEGAPUTER POLYANALYST AND TEXTANALYST SOFTWARE Also note that the Megaputer software bundled with this text is designed to be installed on one machine only and, upon completion of the installation and registration process, will operate for a period of 6 months from the date of installation. Sample copies of the software for review can be obtained from your Prentice Hall representative. CHAPTER DESCRIPTIONS Chapter 1—Introduction to Decision Support Systems The first chapter introduces the concept of a DSS and explains each of the commonly associated component elements. Also included is a brief history of the evolution of the DSS to the present day. Additionally, the chapter includes a discussion of the various types and categories of DSSs that are currently available and in use. Chapter 2—Decisions and Decision Makers This chapter focuses attention on the decision makers and positions them as an integral part of the DSS environment. Issues such as decision styles, effectiveness of decisions, and the types of support that can be provided by a DSS are discussed. We also focus on the concept of a decision and the process by which it is made. Basic decision theory is introduced and related issues including bounded rationality, biases and heuristics, and fundamental cognitive processes are discussed. In addition, the student is introduced to the concepts of effectiveness and efficiency with a discussion that focuses on comparing and contrasting these often confusing characteristics of a decision. Chapter 3—Decisions in the Organization The third chapter focuses on the organization. Because it is in this environment and context that most managerial decisions will be made, it is important to understand the basic concept of an organization and to explore many of its facets including culture, power and politics, and the types of "organizational level" decisions that might be encountered. Chapter 4—Modeling Decision Processes The various common techniques employed in the modeling of decision processes are presented along with several examples of common decision model structures. Also in this chapter is a discussion of probability and methods for forecasting probabilistic events that may be associated with a complex managerial decision. Chapter 5—Group Decision Support and Groupware Technologies This chapter begins a series of chapters that each focuses on a particular aspect of decision support technologies. We begin with a thorough exploration of the process of group decision making and conclude with identification and explanation of various types of multiparticipant decision-making (MDM) technologies. Chapter 6—Executive Information Systems Continuing the focus on specific DSS technologies, this chapter looks at the domain of the executive and the application of DSS technology to the development and application of an executive information system (EIS). Coverage includes a definition of EIS technology, a brief history of its evolution, and the unique characteristics of executive-level decisions and decision makers, as well as issues related to the successful introduction of an EIS into an organizational environment. Chapter 7—Expert Systems and Artificial Intelligence A brief overview of the concept of expertise begins this chapter. A thorough discussion of the elements of artificial intelligence and expert systems follows. The chapter concludes with a look at the issues associated with designing, building, and evaluating an expert system. Appended to Chapter 7 is a chronological synopsis of expert system technologies. Chapter 8—Knowledge Engineering and Acquisition Chapter 8 extends the discussion of expert systems by focusing on the concept of knowledge and the methods by which it is acquired and codified in an expert system's knowledge base. Chapter 9—Machines That Can Learn The newest members of the world of artificial intelligence and decision support systems are the focus of this chapter. The concepts of fuzzy logic and linguistic ambiguity are introduced in detail as a precursor to a discussion of artificial neural networks and genetic algorithms. Appended to Chapter 9 is an overview of a popular software application within this realm. Following this, a mathematical derivation of the most popular artificial neural network learning algorithm is provided. Chapter 10—The Data Warehouse This chapter and the next introduce the hottest topics in decision support systems today: the data warehouse and data mining. Chapter 10 thoroughly covers the basic concepts of data warehousing and discusses several commercial data warehousing products. Chapter 11—Data Mining and Data Visualization Extending the concepts introduced in Chapter 10, this chapter looks at the realm of data mining and complex pattern extraction. The concept of online analytical processing (OLAP) and its variations are introduced. In addition, the chapter contains a discussion of the techniques used to mine data, their current limitations, and their application in data visualization contexts. New to this edition is the inclusion of several examples and student problem sets that make use of the bundled PolyAnalyst and TextAnalyst software application from Megaputer. Although optional on the part of the instructor, these exercises and tutorials provide a rich, interactive learning environment for students to actually experience data mining and data visualization techniques using real data sets from real-world problem settings. This book is the only DSS text available that includes a real commercially available data mining and data visualization software package and integrates it into the content and pedagogy. Chapter 12—Designing and Building the Data Warehouse Chapter 12, also new to this edition, delves deeper into the processes, procedures, tools, and techniques commonly found in conjunction with the development of an organizational data warehouse. This material allows students to better understand the unique challenges associated with this new and powerful approach to data storage. Chapter 13—The Systems Perspective of a DSS Still another new addition to this text, Chapter 13 presents a variety of issues associated with the predevelopment activities of a modern DSS. In this chapter, we explore the concept of a systems perspective, the DSS information system architecture, and the role of the Internet in DSS design. In keeping with the needs of our adopters, this chapter brings a greater balance between the design and development aspects of a modern DSS and the processes associated with managerial application of the software. Chapter 14—Designing and Building Decision Support Systems The topic of decision support, even in its most applied sense, would not be complete without a discussion of the strategies and tools necessary to bring the system to life. This chapter is the first of a two-part focus on the issues associated with the design and development of a modern DSS. Chapter 15—Implementing and Integrating Decision Support Systems Chapter 15 concludes our focus on DSS development issues by looking at the activities necessary to effectively implement, integrate, and evaluate an organizational DSS. Chapter 16—Creative Decision Making and Problem Solving As we begin to close our in-depth focus on decision making and problem solving, it becomes necessary to include a discussion of one of the most elusive yet critical elements to successful managerial decision making: creativity. This chapter, greatly expanded from the first edition, looks at the concept of creativity and the various methods of enhancing it. Following it is a discussion of a related topic, intelligent agents. Chapter 17—Intelligent Software Agents, Bots, Delegation, and Agency Also in this edition, we greatly expanded our coverage and discussion of the new world of delegation and the role that it will play in the DSS of tomorrow. A thorough overview of the various types of intelligent software agents, their design, construction, and applications is presented. It is the only currently available DSS text to present this material at this level of detail. Chapter 18—Decision Support in the Twenty-First Century This capstone chapter looks at the DSS of tomorrow. By reviewing where we have been to date, the chapter guides us into a brief glimpse of what the future holds for DSSs, expert systems and artificial intelligence, and executive information systems.


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Packed with essential information, this valuable volume helps future business management professionals learn to make and support managerial decisions, providing a thorough understanding of the support aspect of DSS. Written from a cognitive processes and decision-making perspective, it concentrates on issues that emphasize managerial applications and the implication of decision support technology on those issues. The volume examines data warehouses, intelligent software agents and DSS system development, as well as an introduction to decision support systems, decision in the organization, modeling decision processes, group decision support and groupware technologies, executive information systems, expert systems and artificial intelligence, knowledge engineering and acquisition, and data mining and data visualization. For Data Warehouse Administrators, CIO and Directors of Information Systems.


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