Integration of decision support systems to improve decision support performance

Decision support system (DSS) is a well-established research and development area. Traditional isolated, stand-alone DSS has been recently facing new challenges. In order to improve the performance of DSS to meet the challenges, research has been actively carried out to develop integrated decision support systems (IDSS). This paper reviews the current research efforts with regard to the development of IDSS. The focus of the paper is on the integration aspect for IDSS through multiple perspectives, and the technologies that support this integration. More than 100 papers and software systems are discussed. Current research efforts and the development status of IDSS are explained, compared and classified. In addition, future trends and challenges in integration are outlined. The paper concludes that by addressing integration, better support will be provided to decision makers, with the expectation of both better decisions and improved decision making processes

A Look Toward the Future: Decision Support Systems Research is Alive and Well

This commentary examines the historical importance of decision support to the information systems (IS) field from the viewpoint of four researchers whose work spans the several decades of decision support systems (DSS) research. Given this unique “generational” vantage point, we present the changes in and impact of DSS research as well as future considerations for decision support in the IS field. We argue that the DSS area has remained vital as technology has evolved and our understanding of decision-making processes has deepened. DSS work over the last several years has contributed both breadth and depth to decision-making research; the challenge now is to make sense of it all by placing it in an understandable context and by applying our analysis to the relevant issues looming in the future. One major outcome of this commentary is the identification of future trends in DSS research and what the users of these new DSS outlets can learn from the past. Trends include the increasing impact of social and mobile computing on DSS research, as well as knowledge management DSS and negotiation support systems that shift the focus to delivering more customer-centric and marketplace support

Business intelligence as the support of decision-making processes in e-commerce systems environment

The present state of world economy urges managers to look for new methods, which can help to start the economic growth. To achieve this goal, managers use standard as well as new procedures. The fundamental prerequisite of the efficient decision-making processes are actual and right information. Managers need to monitor past information and current actual information to generate trends of future development based on it. Managers always should define strictly what do they want to know, how do they want to see it and for what purpose do they want to use it. Only in this case they can get right information applicable to efficient decision-making. Generally, managers´ decisions should lead to make the customers´ decision-making process easier. More frequently than ever, companies use e-commerce systems for the support of their business activities. In connection with the present state and future development, cross-border online shopping growth can be expected. To support this, companies will need much better systems providing the managers adequate and sufficient information. This type of information, which is usually multidimensional, can be provided by the Business Intelligence (BI) technologies. Besides special BI systems, some of BI technologies are obtained in quite a few of ERP (Enterprise Resource Planning) systems. One of the crucial questions is whether should companies and firms buy or develop special BI software, or whether they can use BI tools contained in some ERP systems. In respect of this, there is a question if the modern ERP systems can provide the managers sufficient possibilities relating to ad-hoc reporting, static and dynamic reports and OLAP analyses. A one of the main goals of this article is to show and verify Business Intelligence tools of Microsoft Dynamics NAV for the support of decision-making in terms of the cross-border online purchasing. Pursuant to above-mentioned, in this article authors deal with problems relating to managers´ decision-making, customers´ decision-making and a support of its using the BI tools contained in ERP system Microsoft Dynamics NAV. A great deal of this article is aimed at area of multidimensional data which are the source data of e-commerce systems.Business Intelligence, decision-making, e-commerce system, cross-border online purchasing, multi-dimensional data, reporting, data visualization

Appropriate Information Technology In Emerging Economies: An Application For Strategic Decision-Making In Manufacturing Industries

Competing in global marketplace has pressured managers respond to shifting market trends by increasing product quality, business process reengineering, and decreasing time to market for new products.  Within emerging economies top executives have realized that adoption of appropriate information technologies such a decision support systems (DSS) and group decision support systems (GDSS) have led to changes in the existing organizational structure and communication mechanisms.  This paper explores the advantages and constraints of DSS and GDSS in formulating manufacturing strategies in emergent economies.  We argued that to fit appropriate information technology to organizational design top executive would benefit from strategic information systems planning process.  This process enables top executives to invest in appropriate information system that fits their structural arrangements and organizational culture.  Moreover, we explored the impact of DSS and GDSS on executive decision-making capabilities.  We also explored the methodology for implementation of appropriate information systems in manufacturing firms in emergent economies

Determining prerogative by factors of significance, logical or programming controller

Advances in information technology design computer systems and networks helped to deepen the study of the processes that can lead to loss of integrity, confidentiality or availability of information or even its destruction. Information technology protect the confidentiality of information in computer systems and networks for the present time by following directions - SDN (software-defined networking) and ACI (Application Centric Infrastructure). Given the trends of information technology and approaches to problem-solving information security important task is to determine the appropriate direction through the use of a decision support system to further improve the selected information technology. Using decision support system conducted experimental verification of analytical model that allows you to answer about the merits of one or another system chosen key measurements and metrics, identify the strengths and weaknesses of the systems that will allow for further development and open up new opportunities

Determining prerogative by factors of significance, logical or programming controller

Advances in information technology design computer systems and networks helped to deepen the study of the processes that can lead to loss of integrity, confidentiality or availability of information or even its destruction. Information technology protect the confidentiality of information in computer systems and networks for the present time by following directions - SDN (software-defined networking) and ACI (Application Centric Infrastructure). Given the trends of information technology and approaches to problem-solving information security important task is to determine the appropriate direction through the use of a decision support system to further improve the selected information technology. Using decision support system conducted experimental verification of analytical model that allows you to answer about the merits of one or another system chosen key measurements and metrics, identify the strengths and weaknesses of the systems that will allow for further development and open up new opportunities

Artificial Intelligence, Decision Making, and the Knowledge Creation Process

The continued evolution of artificial intelligence (AI) presents new opportunities for businesses to improve performance through better decision making. Prior literature has emphasized the relationship between AI and decision making as structures contributing to improved decision quality. This paper proposes that knowledge is a critical construct in the decision-making process and that it is the combined interactions of AI, decision making, and knowledge management within decision support systems and processes that contribute to improved decision quality. This paper outlines research trends that have occurred over the years and where the conversations regarding AI, decision making, and knowledge converge. Proposed in this paper is a research framework to classify AI capabilities in the knowledge creation process to further our understanding of these critical linkages