scholarly journals Managerial Decision Support Making in Economic Systems Based on Cognitive Modeling

2018 ◽  
Vol 7 (4.3) ◽  
pp. 588
Author(s):  
L. Filipkovska ◽  
O. Matviienko
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Cognitive Modeling ◽  
Management Strategies ◽  
External Environment ◽  
Analytical Models ◽  
Economic Systems ◽  
Managerial Decision ◽  
Intelligent Decision Making ◽  
Managerial Decisions

The research is devoted to the search for the technologies to support managerial decisions in the transport industry economic systems. The problems of the complex economic systems modelling have been identified. Cognitive modelling is considered as a tool of supporting intelligent decision making in economic systems. The modelling is based on methods of pattern recognition theory. The results of the scientific research are presented with structural-analytical models of decision support systems. Such models represent the knowledge processing to formulate recommendations for making managerial decisions. Knowledge based on the experience of managing a production situation should be stored in the knowledge base of the information decision making support system. Cognitive modeling will make it possible to study the problems that arise in unstable, weakly structured dynamic economic systems, taking into account changes of the external environment and the object of management itself, systematizing and verifying the expert's perception of the management object and its external environment, forecasting the values of economic system factors and generating optimal management strategies.  

scholarly journals Managerial Decision Making on the Development of Intellectual Capital of an Enterprise

2020 ◽  
Vol 22 (1) ◽  
pp. 36-43
Author(s):  
Oleksandr Litvinov ◽  
Keyword(s):  
Decision Making ◽  
Intellectual Capital ◽  
External Environment ◽  
Managerial Decision ◽  
Managerial Decision Making ◽  
Industrial Enterprises ◽  
Managerial Decisions ◽  
Management Measures ◽  
Third Stage ◽  
Capital Development

Introduction. Despite the crucial importance of intangible components in the activities of modern enterprises there is an increasing the urgency of the problem of development of methodical tools for making managerial decisions aimed at the development of intellectual capital. Herewith managerial decision-making procedure should include task setting, intellectual capital diagnostics, and formation of a set of possible and optimal management measures. Purpose. The article is devoted to the technology of managerial decision making on the development of intellectual capital, taking into account the requirements of their economic efficiency, and paretooptimality. Practical approbation of the proposed procedure on the example of domestic industrial enterprises is a separate task of the article. Results. The results of a comprehensive analysis of the internal and external environment of the enterprise, the analysis of the efficiency of intellectual capital reproduction were taken into account. The author`s technology of managerial decision-making on the development of intellectual capital development includes 6 stages. The first stage forms target marks and budget constraints that determine direction of managerial decisions for each of the components of intellectual capital. In the third stage a number of possible management decisions is formed, which is then checked for paretooptimality. In the fifth stage, optimal managerial decisions are selected in terms of investment intensity of increasing in the level of intellectual capital development. At the last stage, the degree of achieving management targets is checked, than, if necessary, changes are made. Conclusions. Developed technology provides consideration of the peculiarities of the internal and external environment, targets and investment opportunities of an enterprise, and also allows paretooptimal and effective managerial decision making.

Managerial Decision Support in the Post-COVID-19 Era

2021 ◽  
pp. 225-241
Author(s):  
Jan Kalina
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Decision Support Systems ◽  
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.

From Decision Making to Decision Support

2019 ◽  
Author(s):  
Frederic Adam ◽  
Ciara Heavin
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Operations Research ◽  
Human Cognition ◽  
Support Needs ◽  
Managerial Decision ◽  
Full Diversity ◽  
History Of ◽  
Research Questions ◽  
Considerable Depth

In such a complex and well-researched domain as decision support systems (DSS), with a long history of authors making insightful contributions since the 1960’s, it is critical for researchers, especially those less experienced, to have a broad knowledge of the seminal work that has been carried out by prior generations of researchers. This can serve to avoid proposing research questions which have been considered many times before, without having consideration for the answers which have been put forward by previous scholars, thereby reinventing the wheel or “rediscovering” findings about the life of organizations that have been presented long before. The study of human and managerial decision-making is also characterized by considerable depth and seminal research going back to the beginning of the 20th century, across a variety of fields of research including psychology, social psychology, sociology or indeed operations research. Inasmuch as decision-making and decision support are inextricably linked, it is essential for researchers in DSS to be very familiar with both stream of research in their full diversity so they are able to understand both what activity is being supported and how to analyze requirements for developing decision support artefacts. In addition, whilst the area of decision support has sometimes been characterized by technology-based hype, it is critical to recognize that only a clear focus on the thinking and actions of managers can provide decisive directions for research on their decision support needs. In this article, we consider first the characteristics of human cognition, before concentrating on the decision-making needs of managers and the lessons that can be derived for the development of DSS.

Predictive data analytics for contract renewals: a decision support tool for managerial decision-making

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Serhat Simsek ◽  
Abdullah Albizri ◽  
Marina Johnson ◽  
Tyler Custis ◽  
Stephan Weikert
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Organizational Performance ◽  
Predictive Analytics ◽  
Design Science ◽  
Decision Support Tool ◽  
Managerial Decision ◽  
Managerial Decision Making ◽  
Content Type ◽  
Support Tool

PurposePredictive analytics and artificial intelligence are perceived as significant drivers to improve organizational performance and managerial decision-making. Hiring employees and contract renewals are instances of managerial decision-making problems that can incur high financial costs and long-term impacts on organizational performance. The primary goal of this study is to identify the Major League Baseball (MLB) free agents who are likely to receive a contract.Design/methodology/approachThis study used the design science research paradigm and the cognitive analytics management (CAM) theory to develop the research framework. A dataset on MLB's free agents between 2013 and 2017 was collected. A decision support tool was built using artificial neural networks.FindingsThere are clear links between a player's statistical performance and the decision of the player to sign a new offered contract. “Age,” “Wins above Replacement” and “the team on which a player last played” are the most significant factors in determining if a player signs a new contract.Originality/valueThis paper applied analytical modeling to personnel decision-making using the design science paradigm and guided by CAM as the kernel theory. The study employed machine learning techniques, producing a model that predicts the probability of free agents signing a new contract. Also, a web-based tool was developed to help decision-makers in baseball front offices so they can determine which available free agents to offer contracts.

scholarly journals Strategies for making management decisions in information and analytical activity

2021 ◽  
pp. 26-30
Author(s):  
Olha Danylyuk ◽  
Lyudmyla Petryshyn
Keyword(s):  
Decision Making ◽  
Management System ◽  
Management Decisions ◽  
Managerial Decision ◽  
Significant Information ◽  
Managerial Decision Making ◽  
Managerial Decisions ◽  
Regional Management ◽  
Analytical Research ◽  
Principles Of Design

The aim of the study is to substantiate and analyze the strategy of managerial decision-making in information and analytical activities, to specify the main aspects of analytics for decision-making.Strategies for making managerial decisions in information and analytical activities are substantiated. The relevance of the use of information-analytical research is determined. The main aspects of analytics for decision making are analyzed, as well as the ranging of classes according to the degree of intelligence and complexity of tasks is taken into account. The peculiarities of completeness and reliability of information for information-analytical research are revealed. It is determined, that information analytics is a component of management.The regional management analytics is analyzed, as a result of which it is proposed the scheme of regional management with the use of information and analytical support is offered. The basic principles of design are offered. It is proved, that the management system requires modern analytical support, performed according to the requirements of science, the latest methodologies, including information and analytical activities. Problems and negative sides in the process of information-analytical activity in the system of regional management are determined. It is noted, that information and analytical support helps to achieve the best results, and the effectiveness of activities in any field depends on the management system. The obtained research results will allow will improve planning, organization and coordination of managerial decision-making and will help to form a significant information capital for making relevant management decisions at all hierarchical levels of management

scholarly journals Key sur(VIR)val factors in water supply companies: some lessons from Poland

2020 ◽  
Author(s):  
Paweł Chudziński ◽  
Szymon Cyfert ◽  
Wojciech Dyduch ◽  
Maciej Zastempowski
Keyword(s):  
Decision Making ◽  
Water Supply ◽  
Economic Crisis ◽  
Office Work ◽  
Key Factors ◽  
Managerial Decision ◽  
Home Office ◽  
Managerial Decision Making ◽  
Managerial Decisions ◽  
Made In

Abstract This paper presents the outcomes of research on managerial decisions that were made as a first reaction to the economic crisis caused by the SARS-Cov-19 virus (the coronacrisis). The research was carried out among 116 companies from the water supply sector operating in Poland that includes water supply and sewage. The results indicate which elements were perceived by managers as key factors for survival and further functioning. It is clear that the most frequent managerial decisions made were reducing investments and sending employees for home office work, as well as prolonging the payment deadlines. Interestingly, investment reductions were accompanied by sustaining the R&D expenses, as the researched organisations desired to stay competitive and innovative right after the crisis. Only a few of the water supply companies decided to make workers redundant, as the majority declared the intent to protect the workforce, e.g. by sending employees on leave. The research has also shown that the companies approached the coronacrisis rather methodologically and systematically, which indicates a good level of managerial decision-making under pressure, overall enterprise preparedness for crisis situations, as well as staff involvement. Based on our research, we offer some recommendations concerning how the water supply sector organisations can prepare for similar crises in the future. Our research indicates that the decisions made had the following goals in mind: protecting workforce and sustaining cash flow, as well as securing competitive position after the crisis. Our research also focuses on the necessary decisions to be made in water supply companies before the next crises.

Improving Intelligent Decision Making in Urban Planning

2021 ◽  
Vol 8 (3) ◽  
pp. 40-58
Author(s):  
Abderrazak Khediri ◽  
Mohamed Ridda Laouar ◽  
Sean B. Eom
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Urban Planning ◽  
Agglomerative Clustering ◽  
New Techniques ◽  
Intelligent Decision Support System ◽  
Intelligent Decision Making ◽  
Intelligent Decision ◽  
Urban Issues ◽  
Intelligent Decision Support

Generally, decision making in urban planning has progressively become difficult due to the uncertain, convoluted, and multi-criteria nature of urban issues. Even though there has been a growing interest to this domain, traditional decision support systems are no longer able to effectively support the decision process. This paper aims to elaborate an intelligent decision support system (IDSS) that provides relevant assistance to urban planners in urban projects. This research addresses the use of new techniques that contribute to intelligent decision making: machine learning classifiers, naïve Bayes classifier, and agglomerative clustering. Finally, a prototype is being developed to concretize the proposition.

An Intelligent Support System Integrating Data Mining and Online Analytical Processing

2011 ◽  
pp. 141-156
Author(s):  
Rahul Singh ◽  
Richard T. Redmond ◽  
Victoria Yoon
Keyword(s):  
Data Mining ◽  
Decision Making ◽  
Decision Support ◽  
Decision Makers ◽  
Online Analytical Processing ◽  
Intelligent Decision Making ◽  
Course Of Action ◽  
Intelligent Decision ◽  
Analytical Processing ◽  
Intelligent Decision Support

Intelligent decision support requires flexible, knowledge-driven analysis of data to solve complex decision problems faced by contemporary decision makers. Recently, online analytical processing (OLAP) and data mining have received much attention from researchers and practitioner alike, as components of an intelligent decision support environment. Little that has been done in developing models to integrate the capabilities of data mining and online analytical processing to provide a systematic model for intelligent decision making that allows users to examine multiple views of the data that are generated using knowledge about the environment and the decision problem domain. This paper presents an integrated model in which data mining and online analytical processing complement each other to support intelligent decision making for data rich environments. The integrated approach models system behaviors that are of interest to decision makers; predicts the occurrence of such behaviors; provides support to explain the occurrence of such behaviors and supports decision making to identify a course of action to manage these behaviors.

Tools for solving management tasks in economic systems of the «organization» type

2021 ◽  
pp. 82-96
Author(s):  
B. Gerasimov
Keyword(s):  
Decision Making ◽  
Empirical Research ◽  
Scientific Literature ◽  
Economic Systems ◽  
Managerial Decision ◽  
Managerial Decision Making ◽  
Professional Management

There is a need to research and determine the composition and content of tools that form and ensure the implementation of professional management tasks. Scientific literature and empirical research have allowed us to choose as such tools methods of performing procedures, methods of managerial decision-making and management elements. The use of these tools for the design of technologies for solving professional management tasks will improve the quality and efficiency of the studied, designed and operated processes and their parts in organizations.

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