Decision-Making Systems in Traditional and Network Organizations

Author(s):  
Jerzy Kisielnicki ◽  
Olga Sobolewska

Decision-making processes taking place in increasingly complex traditional and network organizations require the use of modern decision support systems. As a result of these solutions, decisions are made to support the development of the organization, its modernization, and thereby lead to increased competitiveness. The subject of the analysis of decision-making systems in organizations has been explored in a number of publications. This chapter addresses selected problems concerning the design and functioning of the decision-making system in traditional and network organizations. Particular attention was paid to the analysis of the decision-making process and the tools used to support this process. The results of research on evaluation of available solutions, especially in the field of information technology, in decision-making processes in network organizations were also presented.

Decision-making processes taking place in increasingly complex traditional and network organizations require the use of modern decision support systems. As a result of these solutions, decisions are made to support the development of the organization, its modernization, and thereby lead to increased competitiveness. The subject of the analysis of decision-making systems in organizations has been explored in a number of publications. This chapter addresses selected problems concerning the design and functioning of the decision-making system in traditional and network organizations. Particular attention was paid to the analysis of the decision-making process and the tools used to support this process. The results of research on evaluation of available solutions, especially in the field of information technology, in decision-making processes in network organizations were also presented.


2010 ◽  
pp. 135-143 ◽  
Author(s):  
Udo Richard Averweg

Decision support systems (DSS) deal with semi-structured problems. Such problems arise when managers in organisations are faced with decisions where some but not all aspects of a task or procedure are known. To solve these problems and use the results for decision-making requires judgement of the manager using the system. Typically such systems include models, data manipulation tools, and the ability to handle uncertainty and risk. These systems involve information and decision technology (Forgionne, 2003). Many organisations are turning to DSS to improve decision-making (Turban, McLean, & Wetherbe, 2004). This is a result of the conventional information systems (IS) not being sufficient to support an organisation’s critical response activities—especially those requiring fast and/or complex decision-making. In general, DSS are a broad category of IS (Power, 2003). A DSS is defined as “an interactive, flexible, and adaptable computer-based information system, specially developed for supporting the solution of a non-structured management problem for improved decision-making. It utilises data, it provides easy user interface, and it allows for the decision maker’s own insights” (Turban, 1995). There is a growing trend to provide managers with IS that can assist them in their most important task—making decisions. All levels of management can benefit from the use of DSS capabilities. The highest level of support is usually for middle and upper management (Sprague & Watson, 1996). The question of how a DSS supports decision-making processes will be described in this article. This article is organised as follows: The background to decisionmaking is introduced. The main focus (of this article) describes the development of the DSS field. Some future trends for the DSS field are then suggested. Thereafter a conclusion is given.


2009 ◽  
pp. 82-89
Author(s):  
John Wang ◽  
James Yao

Group decision support systems (GDSSs) which aim at increasing some of the benefits of collaboration and reducing the inherent losses are interactive information technology-based environments that support concerted and coordinated group efforts toward completion of joint tasks (Dennis, George, Jessup, Nunamaker, & Vogel, 1998). The term group support systems (GSSs) was coined at the start of the 1990’s to replace the term GDSS. The reason for this is that the role of collaborative computing was expanded to more than just supporting decision making (Patrick & Garrick, 2006). For the avoidance of any ambiguities, the latter term shall be used in the discussion throughout this paper


Author(s):  
Jan Kalina

The COVID-19 pandemic accelerated trends to digitalization and automation, which allow us to acquire massive datasets useful for managerial decision making. The expected increase of available data (including big data) will represent a potential for an increasing deployment of management decision support systems for more general and more complex tasks. Sophisticated decision support systems have been proposed already in the pre-pandemic times either to assist managers in specific decision-making processes or to perform the decision making fully automatically. Decision support systems are presented in this chapter as perspective artificial intelligence tools contributing to a deep transform of everyday management practices. Attention is paid here to their new development in the quickly transforming post-COVID-19 era and to their role under the post-pandemic conditions. As an original contribution, this chapter presents a vision of information-based management, which far exceed the rather limited pre-pandemic visions of evidence-based management focused primarily on critical thinking.


Author(s):  
Frédéric Adam ◽  
Jean-Charles Pomerol ◽  
Patrick Brézillon

In this article, a newspaper company which has implemented a computerised editorial system is studied in an attempt to understand the impact that groupware systems can have on the decision making processes of an organisation. First, the case study protocol is presented, and the findings of the case are described in detail. Conclusions are then presented which pertain both to this case and to the implementation of decision support systems that have a groupware dimension.


Author(s):  
Udo Richard Averweg

Decision support systems (DSS) deal with semi-structured problems. Such problems arise when managers in organisations are faced with decisions where some but not all aspects of a task or procedure are known. To solve these problems and use the results for decision-making requires judgement of the manager using the system. Typically such systems include models, data manipulation tools, and the ability to handle uncertainty and risk. These systems involve information and decision technology (Forgionne, 2003). Many organisations are turning to DSS to improve decision-making (Turban, McLean, & Wetherbe, 2004). This is a result of the conventional information systems (IS) not being sufficient to support an organisation’s critical response activities—especially those requiring fast and/or complex decision-making. In general, DSS are a broad category of IS (Power, 2003). A DSS is defined as “an interactive, flexible, and adaptable computer-based information system, specially developed for supporting the solution of a non-structured management problem for improved decision-making. It utilises data, it provides easy user interface, and it allows for the decision maker’s own insights” (Turban, 1995). There is a growing trend to provide managers with IS that can assist them in their most important task—making decisions. All levels of management can benefit from the use of DSS capabilities. The highest level of support is usually for middle and upper management (Sprague & Watson, 1996). The question of how a DSS supports decision-making processes will be described in this article. This article is organised as follows: The background to decisionmaking is introduced. The main focus (of this article) describes the development of the DSS field. Some future trends for the DSS field are then suggested. Thereafter a conclusion is given.


2008 ◽  
pp. 397-407
Author(s):  
Alexander Anisimov

This chapter is dedicated to the major managerial, organizational and technological aspects of development of data warehouses in a global information environment, when different external sources of information are available and potentially may have value for decision support and managerial analysis. It summarizes the major benefits that become available for businesses if they decide to integrate information from external sources into their data warehouses. It also introduces the overall organizational framework of development of data warehouses that are based upon the information from different external sources. Furthermore the author hopes that understanding of the framework introduced will not only inform practitioners (both information technology (IT) specialists and managers in different spheres of business) of new possible approaches to design of decision support systems but also assist in the improvement of approaches to decision-making procedures.


Author(s):  
John Wang ◽  
James Yao

Group decision support systems (GDSSs) which aim at increasing some of the benefits of collaboration and reducing the inherent losses are interactive information technology-based environments that support concerted and coordinated group efforts toward completion of joint tasks (Dennis, George, Jessup, Nunamaker, & Vogel, 1998). The term group support systems (GSSs) was coined at the start of the 1990’s to replace the term GDSS. The reason for this is that the role of collaborative computing was expanded to more than just supporting decision making (Patrick & Garrick, 2006). For the avoidance of any ambiguities, the latter term shall be used in the discussion throughout this paper.


Author(s):  
Mehdi Beheshtian Ardakani ◽  
Mohsen Modarres ◽  
Ahmad Ispahani

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.


Author(s):  
R. A. Kelly ◽  
W. S. Merritt

Coastal lakes are ecosystems which provide significant environmental, social and economic values. They are a key habitat for many aquatic species, particularly for juvenile fish and aquatic invertebrates. They are a focus for human activity, including recreation, tourism, and many forms of industry and production such as oyster and commercial fisheries. More and more the foreshore areas of lakes are seen as a desirable place to live, with urban development a key pressure on lake systems. However current development, use and management of these systems mean that these values are already under threat. Environmental managers, urban planners and other decision makers need to make complex decisions about patterns of current and future use of these systems which allow for the trade-offs associated with various activities to be effectively taken into account. Decision support systems (DSS) are seen to have a role to play in supporting these activities.When developed properly, DSS can support decision making processes by providing users with a tool that shows the relationships between drivers of a system and outcomes. Environmental outcomes (e.g. estuary health) are controlled by often complex biophysical, ecological, economic and/or social drivers and processes. In this context a DSS should address uncertainty in data, knowledge and predictions, and allow users to explore the sensitivity of outcomes to controllable drivers (e.g. management actions), uncontrollable drivers (e.g. climate variability) and uncertainty. The DSS development and adoption process also needs to be flexible to a changing decision making environment. Ultimately the success of any DSS will depend not only on its technical capacity, including the robustness of any science underlying it, or the ease of use of any interface but also on the circumstances into which it arrives: the time and money allowed for training, capacity building, incorporation of stakeholder comments and development of trust between DSS developers, scientists and the community; the way in which the DSS is embedded in the decision making process; and the ‘politics’ and constantly changing face of the decision making environment.This chapter will discuss issues regarding the development of a DSS under typical planning timeframes where there are limited resources (time and budgetary) and where current and future management issues may not be certain and/or may change over the planning timeframe. The chapter largely draws on experiences gained during the development and application of the CAPER DSS in the Great Lakes, NSW Australia.


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