Corporate Diplomacy as a Management Decision

2018 ◽  
pp. 77-87
Author(s):  
Ioana Gutu ◽  
Maria Viorica Bedrule Grigoruță
Keyword(s):  
Management Decision

Centralization and Effectiveness of Reward Management in Multinational Enterprises

2018 ◽  
Vol 17 (2) ◽  
pp. 55-65 ◽  
Author(s):  
Michael Tekieli ◽  
Marion Festing ◽  
Xavier Baeten
Keyword(s):  
Decision Making ◽  
Social Identity Theory ◽  
Multinational Enterprises ◽  
Role Identity ◽  
Management Decision ◽  
Role Identities ◽  
Management Decision Making ◽  
New Perspective ◽  
Subsidiary Managers ◽  
The Relationship

Abstract. Based on responses from 158 reward managers located at the headquarters or subsidiaries of multinational enterprises, the present study examines the relationship between the centralization of reward management decision making and its perceived effectiveness in multinational enterprises. Our results show that headquarters managers perceive a centralized approach as being more effective, while for subsidiary managers this relationship is moderated by the manager’s role identity. Referring to social identity theory, the present study enriches the standardization versus localization debate through a new perspective focusing on psychological processes, thereby indicating the importance of in-group favoritism in headquarters and the influence of subsidiary managers’ role identities on reward management decision making.

Emergency management decision-making during severe weather

2006 ◽  
Author(s):  
Leigh A. Baumgart ◽  
Ellen J. Bass ◽  
Brenda Philips ◽  
Kevin Kloesel
Keyword(s):  
Decision Making ◽  
Emergency Management ◽  
Severe Weather ◽  
Management Decision ◽  
Management Decision Making

Providing additional education services for children: Challenges and solutions

2020 ◽  
Vol 18 (4) ◽  
pp. 675-687
Author(s):  
Yu.I. Brodovskaya ◽  
T.A. Smirnova
Keyword(s):  
Consumer Preferences ◽  
Methodological Approach ◽  
Management Decision ◽  
Public Authorities ◽  
Education Services ◽  
Supplementary Education ◽  
Management Decision Making ◽  
Additional Education ◽  
Sociological Studies ◽  
Municipal Level

Subject. This article considers the issues of provision of supplementary education services for children and methodological tools for the formation of educational environment. Objectives. The article aims to assess the level of development of the system of supplementary education of children in Krasnoyarsk and offer a methodological approach to improving the management decision-making procedure in the formation of a portfolio of supplementary education services at the municipal level. Methods. For the study, we used the methods of theoretical, empirical, and logistic analyses, and sociological studies. Results. The article offers concrete solutions to the lack of a methodological approach to providing supplementary education services, considering one of the micro-districts of Krasnoyarsk as a case in point. It also offers tools that can be used by public authorities to organize educational space at the municipal level. Conclusions. A unified methodological approach should be used to provide a system of supplementary education, taking into account financial means, as well as differentiation in the distribution of educational facilities throughout the area. The relevance of the set of supplementary education services and consumer preferences should be taken into account, as well.

Evaluation of an Integrated Traffic Flow Management Decision Making Approach

2010 ◽  
Vol 18 (4) ◽  
pp. 331-358 ◽  
Author(s):  
Shon Grabbe ◽  
Banavar Sridhar ◽  
Avijit Mukherjee
Keyword(s):  
Decision Making ◽  
Traffic Flow ◽  
Management Decision ◽  
Flow Management ◽  
Traffic Flow Management ◽  
Management Decision Making

MODELING A MANAGEMENT DECISION SUPPORT SYSTEM FOR THE ELIMINATION OF ROAD ACCIDENTS WITH DANGEROUS GOODS

2019 ◽  
Vol 84 ◽  
pp. 84-90
Author(s):  
V. V. Sinicyn ◽  
◽  
V. V. Tatarinov ◽  
Yu. V. Prus ◽  
A. A. Kirsanov ◽  
...  
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Management Decision ◽  
Road Accidents ◽  
Dangerous Goods ◽  
Management Decision Support

Review of classification studies for machine learning in the development of intelligent management decision support systems

2020 ◽  
Vol 89 ◽  
pp. 20-29
Author(s):  
Sh. K. Kadiev ◽  
◽  
R. Sh. Khabibulin ◽  
P. P. Godlevskiy ◽  
V. L. Semikov ◽  
...  
Keyword(s):  
Machine Learning ◽  
Decision Support ◽  
Mathematical Models ◽  
Decision Support Systems ◽  
Support Systems ◽  
Management Decision ◽  
Classification Methods ◽  
Advantages And Disadvantages ◽  
Intelligent Management ◽  
Management Decision Support

Introduction. An overview of research in the field of classification as a method of machine learning is given. Articles containing mathematical models and algorithms for classification were selected. The use of classification in intelligent management decision support systems in various subject areas is also relevant. Goal and objectives. The purpose of the study is to analyze papers on the classification as a machine learning method. To achieve the objective, it is necessary to solve the following tasks: 1) to identify the most used classification methods in machine learning; 2) to highlight the advantages and disadvantages of each of the selected methods; 3) to analyze the possibility of using classification methods in intelligent systems to support management decisions to solve issues of forecasting, prevention and elimination of emergencies. Methods. To obtain the results, general scientific and special methods of scientific knowledge were used - analysis, synthesis, generalization, as well as the classification method. Results and discussion thereof. According to the results of the analysis, studies with a mathematical formulation and the availability of software developments were identified. The issues of classification in the implementation of machine learning in the development of intelligent decision support systems are considered. Conclusion. The analysis revealed that enough algorithms were used to perform the classification while sorting the acquired knowledge within the subject area. The implementation of an accurate classification is one of the fundamental problems in the development of management decision support systems, including for fire and emergency prevention and response. Timely and effective decision by officials of operational shifts for the disaster management is also relevant. Key words: decision support, analysis, classification, machine learning, algorithm, mathematical models.

EXPERT MANAGEMENT SYSTEMS OF AGROTECHNOLOGIES IN CLOUD INFORMATION TECHNOLOGY

1970 ◽  
pp. 12-17
Author(s):  
I. М. Mikhaylenko ◽  
V. N. Timoshin
Keyword(s):  
Decision Making ◽  
Pattern Recognition ◽  
Information System ◽  
Knowledge Base ◽  
Information Technologies ◽  
Agricultural Sector ◽  
Perennial Grasses ◽  
Management Decision ◽  
Agricultural Technologies ◽  
Automation Systems

The transition to "intellectual" agriculture is the main vector of modernization of the agricultural sector of the economy. It is based on integrated automation and robotization of production, the use of automated decision-making systems. This is inevitably accompanied by a significant increase in data flow from sensors, monitoring systems, meteorological stations, drones, satellites and other external systems. Farm management has the opportunity to use various online applications for accurate recommendations and making various kinds of management decisions. In this regard, the most effective use of cloud information technologies, allowing implementing the most complex information and technical level of automation systems for management of agricultural technologies. The purpose of this work is to test the approach to creating expert management decision support systems (DSS) through the knowledge base (KB), formed in the cloud information system. For this, we consider an example of constructing a DSS for choosing the optimal date for preparing forage from perennial grasses. A complete theoretical and algorithmic database of the analytical DSS implemented in the data processing center of the cloud information system is given. On its basis, a KB is formed for a variety of different decision-making conditions. This knowledge base is transmitted to the local DSS. To make decisions about the optimal dates for the preparation of the local DSS, two variants of algorithms are used. The first option is based on management models, and the second uses the pattern recognition method. The approbation of the algorithms was carried out according to the BZ from 50 cases. According to the results of testing, the method of pattern recognition proved to be more accurate, which provides a more flexible adjustment of the situation on the local DSS to a similar situation in the KB. The considered technique can be extended to other crops.

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