How Groupware Systems Can Change How an Organisation Makes Decisions

Study Protocol ◽

Support Systems ◽

Decision Making Processes ◽

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.

The optimization model of the logging machinery usage in forestry practice

Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis ◽

10.11118/actaun200957060105 ◽

2009 ◽

Vol 57 (6) ◽

pp. 105-112 ◽

Cited By ~ 1

Author(s):

Jitka Janová ◽

M. Lindnerová

Keyword(s):

Decision Making ◽

Czech Republic ◽

Decision Support ◽

Optimization Model ◽

Support Systems ◽

Decision Problems ◽

Optimization Models ◽

Ongoing Research ◽

The decision support systems commonly used in industry and economy managerial practice for optimizing the processes are based on algoritmization of the typical decision problems. In Czech forestry business, there is a lack of developed decision support systems, which could be easily used in daily practice. This stems from the fact, that the application of optimization methods is less successful in forestry decision making than in industry or economy due to inherent complexity of the forestry decision problems. There is worldwide ongoing research on optimization models applicable in forestry decision making, but the results are not globally applicable and moreover the cost of possibly arising software tools are indispensable. Especially small and medium forestry companies in Czech Republic can not afford such additional costs, although the results of optimization could positively influence not only the business itself but also the impact of forestry business on the environment. Hence there is a need for user friendly optimization models for forestry decision making in the area of Czech Republic, which could be easily solved in commonly available software, and whose results would be both, realistic and easily applicable in the daily decision making.The aim of this paper is to develop the optimization model for the machinery use planning in Czech logging firm in such a way, that the results can be obtained using MS EXCEL. The goal is to identify the integer number of particular machines which should be outsourced for the next period, when the total cost minimization is required. The linear programming model is designed covering the typical restrictions on available machinery and total volume of trees to be cut and transported. The model offers additional result in the form of optimal employment of particular machines. The solution procedure is described in detail and the results obtained are discussed with respect to its applicability in practical forestry decision making. The possibility of extension of suggested model by including additional requirements is mentioned and the example for the wood manipulation requirement is shown.

Decision Support Systems and Decision-Making Processes

Business Information Systems ◽

10.4018/978-1-61520-969-9.ch010 ◽

2010 ◽

pp. 135-143 ◽

Cited By ~ 1

Author(s):

Udo Richard Averweg

Keyword(s):

Decision Making ◽

Decision Support ◽

Support Systems ◽

Management Problem ◽

Upper Management ◽

Structured Problems ◽

Decision Making Processes ◽

Complex Decision Making ◽

Computer Based

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.

Handbook of Research on Entrepreneurship, Innovation, Sustainability, and ICTs in the Post-COVID-19 Era - Advances in Business Strategy and Competitive Advantage ◽

Managerial Decision Support in the Post-COVID-19 Era

10.4018/978-1-7998-6776-0.ch011 ◽

2021 ◽

pp. 225-241

Author(s):

Jan Kalina

Keyword(s):

Decision Making ◽

Decision Support ◽

Management Practices ◽

Support Systems ◽

Management Decision ◽

Managerial Decision ◽

Massive Datasets ◽

New Development ◽

Decision Making Processes

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.

Decision Support Systems and Decision-Making Processes

Encyclopedia of Decision Making and Decision Support Technologies ◽

10.4018/978-1-59904-843-7.ch025 ◽

2010 ◽

pp. 218-224 ◽

Cited By ~ 2

Author(s):

Udo Richard Averweg

Keyword(s):

Decision Making ◽

Decision Support ◽

Support Systems ◽

Management Problem ◽

Upper Management ◽

Structured Problems ◽

Decision Making Processes ◽

Complex Decision Making ◽

Computer Based

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.

The Decision Hedgehog

Encyclopedia of Decision Making and Decision Support Technologies ◽

10.4018/978-1-59904-843-7.ch017 ◽

2011 ◽

pp. 148-154

Author(s):

Patrick Humphreys

Keyword(s):

Decision Making ◽

Decision Support ◽

Group Decision ◽

Support Systems ◽

Group Decision Support ◽

Group Decision Support Systems ◽

Decision Systems ◽

Perceived Need ◽

The discourses established as the foundations of group decision support systems (GDSS) have been called into question not only in the interests of advancing the academic GDSS field (Bannon, 1997), but also out of the perceived need to plug gaps that sophisticated GDSS systems throw up in practice (Huber, 1981; Humphreys & Brezillon, 2002; Humphreys & Jones, 2006; Stabell, 1987). The limitations of rational perspectives of “decision- making as choice” have been raised (Carlsson, 2002; Cyert & March, 1992; Nappelbaum, 1997). The challenges relate to failures of implementation, the rise of unintended outcomes, the impact of cultures of fear and failure within organisations (Humphreys & Nappelbaum, 1997), and problems associated with externalisation of decision systems designers who “play God” by designing from outside the game for those who are inside (Humphreys, 1989).

Communication and Decision Support Systems

International Journal of Safety and Security Engineering ◽

10.18280/ijsse.110413 ◽

2021 ◽

Vol 11 (4) ◽

pp. 397-407

Author(s):

Luigi Palestini

Keyword(s):

Decision Making ◽

Decision Support ◽

Communication Systems ◽

New Technologies ◽

Support Systems ◽

Just In Time ◽

Strategic Decisions ◽

Voice Data ◽

In emergencies, assessment and communication activities are particularly important for the support of the top decision-making bodies, to evaluate “just in time” the best actions to be taken. The multiple problems to be solved require specific skills in different areas. Upon the occurrence of a calamity, the authorities must answer questions such as “is a given place safe from the threat (e.g., an oncoming flood)?”, that’s why today knowledge of tools that can support decision-making is increasingly necessary: the so-called Decision Support Systems (DSS), software that allow users to improve situation assessment, helping all those who must make strategic decisions. Hand in hand with the growing interest in DSS there is an increasing use of communication systems based on IT. First responders know that to face an emergency everything must be prepared and planned, also communication. In fact, DSS and voice/data transmission systems are often integrated into a single system, as proposed by the European projects FIRE IN and IN PREP, because managing information is crucial for carrying out rescue activities in the best possible way. This work describes the impact of new technologies on rescue and emergency management in Italy and Europe, highlighting the challenges associated with their use.

Understanding Decision-Making in Data Warehousing and Related Decision Support Systems

Business Intelligence in the Digital Economy ◽

10.4018/978-1-59140-206-0.ch012 ◽

2011 ◽

pp. 228-250

Author(s):

John D. Wells ◽

Traci J. Hess

Keyword(s):

Decision Making ◽

Decision Support ◽

Financial Services ◽

Support Systems ◽

Data Warehousing ◽

Performance Model ◽

Customer Relationship ◽

Decision Performance

Many businesses have made or are making significant investments in data warehouses that reportedly support a myriad of decision support systems (DSS). Due to the newness of data warehousing and related DSS (DW-DSS), the nature of the decision support provided to DW-DSS users and the related impact on decision performance have not been investigated in an applied setting. An explanatory case study was undertaken at a financial services organization that implemented a particular type of DW-DSS, a Customer Relationship Management (CRM) system. The DSS-decision performance model has provided some theoretical guidance for this exploration. The case study results show that the decision-making support provided by these systems is limited and that an extended version of the DSS-decision performance model may better describe the factors that influence individual decision-making performance.

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

International Business & Economics Research Journal (IBER) ◽

10.19030/iber.v3i4.3679 ◽

2011 ◽

Vol 3 (4) ◽

Author(s):

Mehdi Beheshtian Ardakani ◽

Mohsen Modarres ◽

Ahmad Ispahani

Keyword(s):

Decision Making ◽

Information Technology ◽

Decision Support ◽

Information Systems ◽

Emerging Economies ◽

Support Systems ◽

Strategic Decision ◽

Top Executives ◽

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.

Decision Support Systems in Agriculture, Food and the Environment - Advances in Environmental Engineering and Green Technologies ◽

The Role of Decision Support Systems (DSS) in Planning For Improved Water Quality in Coastal Lakes

10.4018/978-1-61520-881-4.ch003 ◽

2011 ◽

pp. 47-73 ◽

Cited By ~ 1

Author(s):

R. A. Kelly ◽

W. S. Merritt

Keyword(s):

Decision Making ◽

Decision Support ◽

Support Systems ◽

Juvenile Fish ◽

Ease Of Use ◽

Coastal Lakes ◽

Management Actions ◽

Trade Offs ◽

Decision Making Processes

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.