Towards the realisation of an integratated decision support environment for organisational decision making

Traditional decision support systems are based on the paradigm of a single decision maker working at a stand‐alone computer or terminal who has a specific decision to make with a specific goal in mind. Organizational decision support systems aim to support decision makers at all levels of an organization (from executive, middle management managers to operators), who have a variety of decisions to make, with different priorities, often in a distributed and dynamic environment. Such systems need to be designed and developed with extra functionality to meet the challenges such as collaborative working. This paper proposes an Integrated Decision Support Environment (IDSE) for organizational decision making. The IDSE distinguishes itself from traditional decision support systems in that it can flexibly configure and re‐configure its functions to support various decision applications. IDSE is an open software platform which allows its users to define their own decision processes and choose their own exiting decision tools to be integrated into the platform. The IDSE is designed and developed based on distributed client/server networking, with a multi‐tier integration framework for consistent information exchange and sharing, seamless process co‐ordination and synchronisation, and quick access to packaged and legacy systems. The prototype of the IDSE demonstrates good performance in agile response to fast changing decision situations

Enterprise Systems for Organizational Decision Support: A Research Agenda

In recent years, most major organizations have implemented enterprise systems from such vendors as SAP, Oracle, Peoplesoft, Baan, and J. D. Edwards. Historically, the emphasis of these systems has been on enhancing transaction-oriented business processes. Using the integrated, enterprise-wide knowledge store within enterprise systems for decision support is garnering an increased attention from enterprise system vendors and from third party software developers. Despite the recent interest in decision support from enterprise system practitioners, little research exists that connects enterprise systems to the field of decision support systems. This paper outlines the foundations of this connection along with an agenda to advance this line of research

Requirements of knowledge sharing for group decision support system

Group decision support systems (GDSS) have evolved from applications designed primarily to support decision making for groups. Indeed, it is generally accepted that improvements of group support systems is a longstanding interest to organizational researchers, containing solid practical as well as scientific significance. Within this practice, there is increasing challenge to improve the exchange of knowledge among group members in order to enhance GDSS capability of knowledge sharing. Therefore, the paper investigates the current GDSS situation and analyzing the requirements of knowledge sharing (KS) to enhance GDSS. It is hoped that these findings will aid to provide GDSS systems with the solid capability of knowledge sharing

AN ARCHITECTURE FOR ORGANIZATION-WIDE DECISION SUPPORT SYSTEMS

An architecture was developed from a synthesis of concepts derived from the literature and field observations to identify and integrate the total decision support (DSS) function in organizations. Four distinct types of decision support systems were identified (corporate planning systems; functional decision support systems; executive information systems; and local decision support systems) and were integrated within a framework that incorporated organizational level, system formality, and decision making mode. The architecture is used as a cohesive framework for discussing research and management issues for organization-wide DSS

Organizational Decision Support Systems

This paper presents a notion for developing Organizational Decision Support Systems (ODSS). The lens used is to see ODSS as a specialization of Social Decision Support Systems (SDSS) and a generalization of Group Decision Support Systems (GDSS). A unit decision process can be raised by any person in a organizational whole, the organization itself or some sub-organization. The decision process can use a given formalism coherent with the idea that as the contributions from people in the decision process expands, so does the space of available perceptions (P), the space of available actions (A), strategies (S), and options (O), the space of available criteria (C) of valuation of options (V), leading to decision. Atomic decision processes link in the global decision process of the organization. Potential benefits, shortcomings and needed technologies are indicated as well as prospects of development.Fundação para a Ciência e a Tecnologia (FCT

A Survey of the Application of Machine Learning in Decision Support Systems

Machine learning is a useful technology for decision support systems and assumes greater importance in research and practice. Whilst much of the work focuses technical implementations and the adaption of machine learning algorithms to application domains, the factors of machine learning design affecting the usefulness of decision support are still understudied. To enhance the understanding of machine learning and its use in decision support systems, we report the results of our content analysis of design-oriented research published between 1994 and 2013 in major Information Systems outlets. The findings suggest that the usefulness of machine learning for supporting decision-makers is dependent on the task, the phase of decision-making, and the applied technologies. We also report about the advantages and limitations of prior research, the applied evaluation methods and implications for future decision support research. Our findings suggest that future decision support research should shed more light on organizational and people-related evaluation criteria

Domain-Independent Decision Aids for Managerial Decision Making

An examination of the literature on managerial decision making provides insights for improving the design of Declslon Support Systems. Frequently, these systems are designed using one dominant decision making model; some ignore them altogether. This paper incorporates conflicting decision making constructs into an overall framework for designing Decision Support System and discusses the evolution of Decision Support Systems within this framework. This framework is then used to examine advances in decision support research. Perceived useful ness and appl icabillty of decision support tool s demonstrate the trend toward domai n- independent General Decision Support Systems. Domain-independent systems are those which can be adapted to many different problem areas, usually by the addition or del etion of pertinent data and models. We conclude with an evaluation of the advances that artificial intelligence techniques can bring to decision support system research. The major purpose of this paper is to identify aspects of managerial decision support where techniques of artificial intelligence may provide useful contributions. In addition, a framework is devel oped for positioning and eval uating current research efforts on AI-based Decision Support Systems (DSS) vis-a-vis other approaches identified in the literature. The paper is organized as follows: The first section presents a brief review of the organizational and individual decision making literature relevant to the design and evaluation of DSS. The next section outlines the evolution of DSS design phil osophy over the last two decades with a view toward identifying major contributions made to managerial decision making. Finally, the third section examines recent advances made in AI-based DSS

Decision support systems and its role in developing the universities strategic management: Islamic university in Gaza as a case study

This paper aims to identify the decision support systems and their role on the strategic management development in the Universities- Case Study: Islamic University of Gaza. The descriptive approach was used where a questionnaire was developed and distributed to a stratified random sample. (230) questionnaires were distributed and (204) were returned with response rate (88.7%). The most important findings of the study: The presence of a statistically significant positive correlation between the decision support systems and strategic management in the Islamic University in Gaza, and this shows that there is a role for decision support systems in strategic management development. The senior management is convinced of the importance of strategic management of the organization, and this conviction paid to clearly understand the process of the development of strategic management and thus led to a commitment to this process to improve its performance. There is an impact on the strategic management of the capabilities available for the use of decision support systems, and the type of decision support systems used, while there is little effect of top management support for the use of decision support systems. Also, the results showed that there were no statistically significant differences between the averages of the respondents answers attributed to personal data. The research also concluded a series of recommendations: The Islamic University of Gaza need to develop its infrastructure of decision support systems when it develops the strategic management. It should increase its interest in organizational potential through the necessity of a separate unit for decision support systems. As well as increased interest in the physical and technical capabilities available to decision support systems through continuity in keeping pace with technological means and techniques, continued support of senior management in the organization of strategic management for its positive role on decision support systems, that senior management will continue in the organization in creating a culture of strategic management, and it should encourage employees to participate in the strategic management process

Intelligent Decision Making Using Evolutionary System for Optimizing Product-Mix Model

The development and deployment of managerial decision support system represents an emerging trend in the business and organizational field in which the increased application of Decision Support Systems (DSS) can be compiling by Intelligent Systems (IS). Decision Support Systems (DSS) are a specific class of computerized information system that supports business and organizational decision-making activities. A properly designed DSS is an interactive software-based system intended to help decision makers compile useful information from raw data, documents, personal knowledge, and/or business models to identify and solve problems and make decisions. Competitive business pressures and a desire to leverage existing information technology investments have led many firms to explore the benefits of evolutionary system data management solutions such as Particle Swarm Optimization (PSO) and Genetic Algorithm (GA). This study proposes a new model for product mix problem based on evolutionary system for optimizing constraint values as well as objective function. The formulations of the objective function for the minimization problem. This technology is designed to help businesses to finding multi objective functions

Decision Support Systems for Inquiring Organizations

For many years, organizations have been faced with increasing amounts of information but have not been able to adequately use that information in a way that allows for organizational growth. The ability of an organization to learn is likely to be the only competitive advantage left in an economy where technology can be a significant leveling factor. Integrating decision support systems and inquiring systems will produce support for a learning organization that is capable of complex problem formulation and solution. There are many similarities between inquiring systems and decision support systems. This paper suggests that decision support will be enhanced by integrating the theory of decision support in a comprehensive inquiring system that is capable of adapting to changes in the business environment. Development of such a system will ensure that decisionmakers and managers can focus on the task of guiding an organization to its ultimate success rather than expending energy sorting through information to make accurate and timely decisions