Guissepi Forgionne’s research while affiliated with University of Maryland, Baltimore County and other places

This chapter describes and illustrates IDSSE-M, a methodology for designing and building intelligent decision support systems. IDSSE-M follows a prototype-based evolutive approach on four main phases: project initiation, system design, system building and evaluation, and user’s definitive acceptance. IDSSE-M is theoretically founded in Saxena’s Decision Support Engineering Methodology, and Turban and Aronson’s DSS Building Paradigm. Although IDSSE-M has been only used in academic settings, the complexity of the implementations has been high, and based on realistic organizational cases, with satisfactory results. Main benefit of IDSSE-M is providing a systematic software engineering oriented process for new developers of intelligent DMSS.

Making organizational decisions is a critical and central activity to successful operations of profit and nonprofit-based organizations (Huber, 1990; Simon, 1997). Organizational paradigm evolution from the paternalistic/political and accountability/bureaucratic organizational paradigms toward process-oriented and decisional views (Huber & McDaniel, 1986) has also fostered the organizational relevance of such processes. Some studies suggest that decision-making ineffectiveness is the main cause for top executive firings in large corporations (Rowe & Davis, 1996). Others state the need to find possible solutions/decisions to the new critical and complex world problems (such as pollution, poverty or corruption) (McCosh & Correa-Perez, 2006) and make better strategic business managerial decisions (Savolein & Liu, 1995). Consequently, how to do so becomes a relevant research stream for academicians and has strong practical implications for decision-makers. Purchase this chapter to continue reading all 11 pages >

Decision support systems (DSSs) have been researched extensively over the years with the purpose of aiding the decision maker (DM) in an increasingly complex and rapidly changing environment (Sprague & Watson, 1996; Turban & Aronson, 1998). Newer intelligent systems, enabled by the advent of the Internet combined with artificial-intelligence (AI) techniques, have extended the reach of DSSs to assist with decisions in real time with multiple informaftion flows and dynamic data across geographical boundaries. All of these systems can be grouped under the broad classification of decision-making support systems (DMSS) and aim to improve human decision making. A DMSS in combination with the human DM can produce better decisions by, for example (Holsapple & Whinston, 1996), supplementing the DM’s abilities; aiding one or more of Simon’s (1997) phases of intelligence, design, and choice in decision making; facilitating problem solving; assisting with unstructured or semistructured problems (Keen & Scott Morton, 1978); providing expert guidance; and managing knowledge. Yet, the specific contribution of a DMSS toward improving decisions remains difficult to quantify. Purchase this chapter to continue reading all 10 pages >

Abstract Information Systems (IS) discipline has been critiqued for being a fragmented discipline, and with little accumulative tradition. Consequently, several research frameworks have been proposed since the 1970s (Mason and Mitroff 1973; Ives, Hamilton and Davis 1980; Nolan and Wheterbe, 1980; Alter 2003) to help to organize, define and delimit such objects of study. However, despite the benefits reported to guide IS research to focus on the adequate objects of study, a formal systemic analysis of them reveals that these frameworks are still incomplete and have systemic inconsistencies. Then, this paper, based in the premise of the development of a more updated and comprehensive framework is required, reports a new one. Its completeness,regarding previous frameworks,is discussed as well as its potential utilization. Keywords:Theory of Systems, IS Research Frameworks, Cybernetics Approach. Context of the Research Problem and Related Works Information Systems (IS) discipline has been critiqued for being a fragmented,discipline

Decision-making Support Systems (DMSS) are computer-based systems that support individual or organisational decision-making processes. Recent advances in information technology and artificial intelligence are enhancing these systems and giving rise to intelligent-DMSS. Intelligent Decision-making Support Systems: Foundations, Applications and Challenges is the first book to provide integrated coverage of the technical aspects of intelligent Decision-Making Support Systems together with discussion of their application and evaluation in organisational structures. The book brings together up-to-date information on the theory and application of i-DMSS. Readers will learn about the foundations, architectures, methods and strategies for successfully designing, developing, implementing, and evaluating intelligent Decision-making Support Systems. Intelligent Decision-making Support Systems: Foundations, Applications and Challenges will be of value to researchers in AI and management studies interested in the latest thinking in decision-making, as well practising managers and consultants who are involved with putting advanced information technologies into practice in organisations.

The information systems (IS) field has been recognized as a scientific discipline since the 80’s, as indicated by: (i) the existence of an intellectual community related with doctoral programs and research centers around the world that generates scientific knowledge and solves practical problems using standard scientific procedures accepted and regulated by this community, and (ii) the diffusion of scientific knowledge related with IS through research outlets and research conferences under a rigorous peer- based review process. Nonetheless, the discipline of information systems has been critiqued by: (i) the lack of formal theories (Farhoomand, 1987, p.55); (ii) the scarce utilization of deductive and formal (e.g., logical-mathematical) research models and methods (idem, p.55); and (iii) the lack of a formal and standard set of fundamental core well-defined concepts associated with the central object of study in this discipline (Alter, 2001, p.3; Banville & Landry, 1989, p.56; Wand & Weber; 1990, p.1282). Consequently, a common-sense language based on informal, conflicting and ambiguous concepts is used as the communicational system in this discipline (Banville & Landry, 1989), and this approach hinders the development of a cumulative research tradition and delays the maturation of the field (Farhoomand, 1987; Wand & Weber, 1990).