A New Approach to the Computer Support of Strategic Decision Making in Enterprises by Means of a New Class of Understanding Based Management Support Systems

2007 ◽  
Author(s):  
Ryszard Tadeusiewicz ◽  
Marek Ogiela ◽  
Lidia Ogiela
Keyword(s):  
Decision Making ◽  
Support Systems ◽  
Computer Support ◽  
Strategic Decision ◽  
Strategic Decision Making ◽  
Management Support ◽  
New Approach ◽  
New Class ◽  
Management Support Systems

Understanding Based Managing Support Systems

2010 ◽  
pp. 91-102
Author(s):  
Lidia Ogiela ◽  
Ryszard Tadeusiewicz ◽  
Marek R. Ogiela
Keyword(s):  
Decision Making ◽  
Information Systems ◽  
Semantic Analysis ◽  
Support Systems ◽  
Expert Knowledge ◽  
Management Support ◽  
Economic Data ◽  
Economic Information ◽  
Management Support Systems ◽  
Intelligent Information

This publication presents cognitive systems designed for analysing economic data. Such systems have been created as the next step in the development of classical DSS systems (Decision Support Systems), which are currently the most widespread tools providing computer support for economic decision-making. The increasing complexity of decision-making processes in business combined with increasing demands that managers put on IT tools supporting management cause DSS systems to evolve into intelligent information systems. This publication defines a new category of systems - UBMSS (Understanding Based Management Support Systems) which conduct in-depth analyses of data using on an apparatus for linguistic and meaning-based interpretation and reasoning. This type of interpretation and reasoning is inherent in the human way of perceiving the world. This is why the authors of this publication have striven to perfect the scope and depth of computer interpretation of economic information based on human processes of cognitive data analysis. As a result, they have created UBMSS systems for the automatic analysis and interpretation of economic data. The essence of the proposed approach to the cognitive analysis of economic data is the use of the apparatus for the linguistic description of data and for semantic analysis. This type of analysis is based on expectations generated automatically by a system which collects resources of expert knowledge, taking into account the information which can significantly characterise the analysed data. In this publication, the processes of classical data description and analysis are extended to include cognitive processes as well as reasoning and forecasting mechanisms. As a result of the analyses shown, we will present a new class of UBMSS cognitive economic information systems which automatically perform a semantic analysis of business data.

The Evaluation of Decision-Making Support Systems' Functionality

2011 ◽  
pp. 329-338 ◽  
Author(s):  
Giusseppi Forgionne ◽  
Stephen Russell
Keyword(s):  
Decision Making ◽  
Support System ◽  
Support Systems ◽  
Field Studies ◽  
Integrated System ◽  
Management Support ◽  
Individual System ◽  
Management Support Systems ◽  
Independent Effects ◽  
Decision Making Support

Contemporary decision-making support systems (DMSSs) are large systems that vary in nature, combining functionality from two or more classically defined support systems, often blurring the lines of their definitions. For example, in practical implementations, it is rare to find a decision support system (DSS) without executive information system (EIS) capabilities or an expert system (ES) without a recommender system capability. Decision-making support system has become an umbrella term spanning a broad range of systems and functional support capabilities (Alter, 2004). Various information systems have been proposed to support the decision-making process. Among others, there are DSSs, ESs, and management support systems (MSSs). Studies have been conducted to evaluate the decision effectiveness of each proposed system (Brown, 2005; Jean-Charles & Frédéric, 2003; Kanungo, Sharma, & Jain, 2001; Rajiv & Sarv, 2004). Case studies, field studies, and laboratory experiments have been the evaluation vehicles of choice (Fjermestad & Hiltz, 2001; James, Ramakrishnan, & Kustim, 2002; Kaplan, 2000). While for the most part each study has examined the decision effectiveness of an individual system, it has done so by examining the system as a whole using outcome- or user-related measures to quantify success and effectiveness (Etezadi-Amoli & Farhoomand, 1996; Holsapple & Sena, 2005; Jain, Ramamurthy, & Sundaram, 2006). When a study has included two or more systems, individual system effects typically have not been isolated. For example, Nemati, Steiger, Lyer, and Herschel (2002) presented an integrated system with both DSS and AI (artificial intelligence) functionality, but they did not explicitly test for the independent effects of the DSS and AI capabilities on the decision-making outcome and process. This article extends the previous work by examining the separate impacts of different DMSSs on decision effectiveness.

The Evaluation of Decision-Making Support Systems' Functionality

2011 ◽  
pp. 149-160
Author(s):  
Giusseppi Forgionne ◽  
Stephen Russell
Keyword(s):  
Decision Making ◽  
Support System ◽  
Support Systems ◽  
Field Studies ◽  
Integrated System ◽  
Management Support ◽  
Individual System ◽  
Management Support Systems ◽  
Independent Effects ◽  
Decision Making Support

Contemporary decision-making support systems (DMSSs) are large systems that vary in nature, combining functionality from two or more classically defined support systems, often blurring the lines of their definitions. For example, in practical implementations, it is rare to find a decision support system (DSS) without executive information system (EIS) capabilities or an expert system (ES) without a recommender system capability. Decision-making support system has become an umbrella term spanning a broad range of systems and functional support capabilities (Alter, 2004). Various information systems have been proposed to support the decision-making process. Among others, there are DSSs, ESs, and management support systems (MSSs). Studies have been conducted to evaluate the decision effectiveness of each proposed system (Brown, 2005; Jean-Charles & Frédéric, 2003; Kanungo, Sharma, & Jain, 2001; Rajiv & Sarv, 2004). Case studies, field studies, and laboratory experiments have been the evaluation vehicles of choice (Fjermestad & Hiltz, 2001; James, Ramakrishnan, & Kustim, 2002; Kaplan, 2000). While for the most part each study has examined the decision effectiveness of an individual system, it has done so by examining the system as a whole using outcome- or user-related measures to quantify success and effectiveness (Etezadi-Amoli & Farhoomand, 1996; Holsapple & Sena, 2005; Jain, Ramamurthy, & Sundaram, 2006). When a study has included two or more systems, individual system effects typically have not been isolated. For example, Nemati, Steiger, Lyer, and Herschel (2002) presented an integrated system with both DSS and AI (artificial intelligence) functionality, but they did not explicitly test for the independent effects of the DSS and AI capabilities on the decision-making outcome and process. This article extends the previous work by examining the separate impacts of different DMSSs on decision effectiveness.

Using DSS for Crisis Management

2011 ◽  
pp. 292-304
Author(s):  
Sherif Kamel
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Public Sector ◽  
Crisis Management ◽  
Socioeconomic Development ◽  
Support Systems ◽  
Management Support ◽  
The Public ◽  
Management Support Systems ◽  
The Government

This case focuses on the use of crisis management support systems in Egypt in leveraging the decision-making process in the government and the public sector for socioeconomic development. It describes the experience of the Egyptian public sector in socioeconomic decision-making and the related emergence of an information-based support organization for the government “Information and Decision Support Center”. The case reflects on the type of decision-making and the crisis management mode of operation at the top policy level and the needs and requirements in terms of resources and infrastructure to support the decision-making process. The case addresses the basics and concepts of crisis management support systems in the context of a developing country, Egypt, stemming from the experience of the Information and Decision Support Center from 1985 to date, the growing implications of the information and communication technology evolution and the lessons learned in responding to crisis management situations in supporting decision and strategic issues at the government and the public sector. The essence of the case is to address the use of advanced information systems in responding to socioeconomic development needs. The case demonstrates the use of management and decision support systems in a crisis mode that has had a number of successes over the last decade that implied concrete results within the developmental process that Egypt, a developing country, is realizing.

scholarly journals Usage of the Agent-Service Approach for the Development of Intelligent Decision Support Systems in the Energy Sector

2020 ◽  
Vol 18 (3) ◽  
pp. 5-18
Author(s):  
Vladimir R. Kuzmin ◽  
Yury A. Zagorulko
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Decision Support Systems ◽  
Support Systems ◽  
Energy Sector ◽  
Strategic Decision ◽  
Strategic Decision Making ◽  
Intelligent Decision ◽  
Intelligent Decision Support Systems ◽  
Intelligent Decision Support

Recently, the concept of intelligent energy systems becomes more popular in Russia. In order to implement such systems, it is required both development and usage of modern information technologies to manage technological infrastructure, and upgrade of this infrastructure. In turn, infrastructure upgrade requires a strategic decision-making for energy sector development. To provide a high quality of such decisions, intellectualization of the process of making them is required. This article deals with usage of agent-service approach for development of intelligent decision support systems (IDSS). Concepts of agent and multiagent system are being considered. Detailed description of agentservice approach and architecture of a typical IDSS, used in this approach, is provided. Also, article considers usage of agent-service approach for development of IDSS “Situation polygon” (for strategic decision-making support in energy sector) and web-oriented information-analytical system WIS (for impact assessment of the energy sector on geoecology). In the future, we plan to add additional functionality in these systems, in particular, to provide in the “Situation polygon” an automatic setting of the values of connections in cognitive maps based on the values of connections in the ontology, and to add in WIS the possibility of calculating the trajectory of the transfer of harmful substances.

Geospatial Decision Support Systems

2020 ◽  
pp. 163-177
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Information Systems ◽  
Decision Support Systems ◽  
Support Systems ◽  
Development Planning ◽  
Strategic Decision ◽  
Strategic Decision Making ◽  
Interactive Decision Support

The chapter is on the geospatial decision support systems. Challenges arise when simple GIS is used to support complex problems encountered at higher level, strategic decision-making, and long-term development planning. In this case, SDI can be more valuable. The chapter presents the perspective of information systems for decision support taking into account the following: the levels of decisions and the process of decision making. Trends on the tools and framework for interactive decision support systems are discussed focusing on geospatial decision support systems based on GIS and SDI.

scholarly journals QuantumIS: A Qualia Consciousness Awareness and Information Theory Quale Approach to Reducing Strategic Decision-Making Entropy

Entropy ◽  
2019 ◽  
Vol 21 (2) ◽  
pp. 125 ◽  
Author(s):  
James A. Rodger
Keyword(s):  
Decision Making ◽  
Information Theory ◽  
Information System ◽  
Competitive Advantage ◽  
Strategic Decision ◽  
Strategic Decision Making ◽  
Top Management ◽  
Theory Approach ◽  
Management Support ◽  
Top Management Support

This paper investigates the underlying driving force in strategic decision-making. From a conceptual standpoint, few studies empirically studied the decision-maker’s intrinsic state composed of entropy and uncertainty. This study examines a mutual information theory approach integrated into a state of qualia complexity that minimizes exclusion and maximizes the interactions of the information system and its dynamic environment via logical metonymy, illusion, and epigenetics.; The article questions whether decision-makers at all levels of the organization are responding from the consciousness of an objective quale from a more subjective qualia awareness in the narrow-sense perspective of individual instances of their conscious experience. To quantify this research question, we explore several hypotheses revolving around strategic information system decisions. In this research, we posit that the eigenvalues of factor analysis along with the reduction in the uncertainty coefficients of the qualia entropy will be balanced by the quale enthalpy of our information theory structural equation model of trust, flexibility, expertise, top management support, and competitive advantage performance. We operationalize the integration of the aforementioned top management support, information systems competencies, and competitive advantage performance concepts into the qualia consciousness awareness and information theory quale framework.

Using DSS for Crisis Management

2011 ◽  
pp. 292-304 ◽  
Author(s):  
Sherif Kamel
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Public Sector ◽  
Crisis Management ◽  
Socioeconomic Development ◽  
Support Systems ◽  
Management Support ◽  
The Public ◽  
Management Support Systems ◽  
The Government

This case focuses on the use of crisis management support systems in Egypt in leveraging the decision-making process in the government and the public sector for socioeconomic development. It describes the experience of the Egyptian public sector in socioeconomic decision-making and the related emergence of an information-based support organization for the government Information and Decision Support Center. The case reflects on the type of decision-making and the crisis management mode of operation at the top policy level and the needs and requirements in terms of resources and infrastructure to support the decision-making process. The case addresses the basics and concepts of crisis management support systems in the context of a developing country, Egypt, stemming from the experience of the Information and Decision Support Center from 1985 to date, the growing implications of the information and communication technology evolution and the lessons learned in responding to crisis management situations in supporting decision and strategic issues at the government and the public sector. The essence of the case is to address the use of advanced information systems in responding to socioeconomic development needs. The case demonstrates the use of management and decision support systems in a crisis mode that has had a number of successes over the last decade that implied concrete results within the developmental process that Egypt, a developing country, is realizing.

DSS for Strategic Decision Making

2011 ◽  
pp. 230-246 ◽  
Author(s):  
Sherif Kamel
Keyword(s):  
Decision Making ◽  
Information Technology ◽  
Decision Support ◽  
Decision Support Systems ◽  
Support Systems ◽  
Strategic Decision ◽  
Strategic Decision Making ◽  
Changing Environments ◽  
Socio Economic Development ◽  
Egyptian Government

This chapter describes and analyzes the experience of the Egyptian government in spreading the awareness of information technology and its use in managing socio-economic development through building multiple information handling and decision support systems in messy, turbulent and changing environments. The successes over the past 10 years in developing, implementing and sustaining state-of-the-art decision support systems for central governmental decision making holds many lessons for the implementation of sophisticated systems under conditions of extreme difficulty.

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