scholarly journals Application of Simulation Modelling Means in Management Decisions-making within the Security and Defence Sector

2021 ◽  
Vol 5 (4) ◽  
pp. 521-532
Author(s):  
Artem Bratko ◽  
Viktor Bereziuk ◽  
Artem Shevchenko ◽  
Yaroslav Kubetsky ◽  
Valentyn Didyk ◽  
...  
Keyword(s):  
Large Scale ◽  
Simulation Modelling ◽  
Practical Implementation ◽  
Systematic Analysis ◽  
Technical Requirements ◽  
Complex Simulation ◽  
Complex Models ◽  
Effective Decision ◽  
Defence Sector ◽  
Effective Decision Making

Problems and modern tendencies in the field of creating complex models of combat operations are considered. The systematic analysis of existing models of combat operations is carried out and their conformity to modern conditions and development of military art is defined. Features of combat operations models development when using means of simulation modelling are exposed with the use of a method of mathematical simulation. The structure of the complex simulation modelling of actions of forces is formed. The composition of standard models of components of the security and defence sector is determined and the sphere of their application is outlined, which allows controlling the unit in different situations at the stage of choosing decisions at different levels of management. The main directions of the development of modelling complexes and systems are determined. The practical implementation of these approaches, along with the implementation of the principles of cost-effectiveness of models, their coordinated development, system compatibility of models for different purposes and large-scale use of proven commercial decisions will create a cluster of combat operations models, which is a real tool for effective decision-making on troops management and allows laying down technical requirements for the development of a modern complex of simulation modelling. Doi: 10.28991/esj-2021-01294 Full Text: PDF

Affordances of Data Science in Agriculture, Manufacturing, and Education

Web Services ◽  
2019 ◽  
pp. 953-978
Author(s):  
Krishnan Umachandran ◽  
Debra Sharon Ferdinand-James
Keyword(s):  
Big Data ◽  
Large Scale ◽  
Data Science ◽  
Data Generation ◽  
Large Scale Data ◽  
Big Data Applications ◽  
Effective Decision ◽  
Effective Decision Making ◽  
Text Images ◽  
Scale Data

Continued technological advancements of the 21st Century afford massive data generation in sectors of our economy to include the domains of agriculture, manufacturing, and education. However, harnessing such large-scale data, using modern technologies for effective decision-making appears to be an evolving science that requires knowledge of Big Data management and analytics. Big data in agriculture, manufacturing, and education are varied such as voluminous text, images, and graphs. Applying Big data science techniques (e.g., functional algorithms) for extracting intelligence data affords decision markers quick response to productivity, market resilience, and student enrollment challenges in today's unpredictable markets. This chapter serves to employ data science for potential solutions to Big Data applications in the sectors of agriculture, manufacturing and education to a lesser extent, using modern technological tools such as Hadoop, Hive, Sqoop, and MongoDB.

Affordances of Data Science in Agriculture, Manufacturing, and Education

2017 ◽  
pp. 14-40 ◽  
Author(s):  
Krishnan Umachandran ◽  
Debra Sharon Ferdinand-James
Keyword(s):  
Big Data ◽  
Large Scale ◽  
Data Science ◽  
Data Generation ◽  
Large Scale Data ◽  
Big Data Applications ◽  
Effective Decision ◽  
Effective Decision Making ◽  
Text Images ◽  
Scale Data

Continued technological advancements of the 21st Century afford massive data generation in sectors of our economy to include the domains of agriculture, manufacturing, and education. However, harnessing such large-scale data, using modern technologies for effective decision-making appears to be an evolving science that requires knowledge of Big Data management and analytics. Big data in agriculture, manufacturing, and education are varied such as voluminous text, images, and graphs. Applying Big data science techniques (e.g., functional algorithms) for extracting intelligence data affords decision markers quick response to productivity, market resilience, and student enrollment challenges in today's unpredictable markets. This chapter serves to employ data science for potential solutions to Big Data applications in the sectors of agriculture, manufacturing and education to a lesser extent, using modern technological tools such as Hadoop, Hive, Sqoop, and MongoDB.

scholarly journals Specifics of business processes of petrochemical enterprises in the context of digitalization of the economy

2021 ◽  
pp. 64-72
Author(s):  
E. A. Dolonina ◽  
M. V. Shinkevich
Keyword(s):  
Industry 4.0 ◽  
Large Scale ◽  
Business Processes ◽  
New Technologies ◽  
Value Stream ◽  
Industrial Enterprises ◽  
Digital Production ◽  
Effective Decision ◽  
Effective Decision Making ◽  
Structured Approach

Digital transformation is more focused on the management aspects of digitalization. It is associated with a large-scale process of implementing digital technologies and corresponding organizational changes. The article reveals the features of designing business processes of petrochemical enterprises in the context of the transition to the digital economy and the introduction of new technologies in the production process. The paper identifies the main technologies of Industry 4.0 used in the chemical and petrochemical industries. The study analyses the key technologies and drivers of the development of traditional and digital production, as well as the barriers to their implementation. The author summarizes the key principles on which Industry 4.0 should be based in order to support effective decision-making in the industry. The paper notes that the design of business processes is determined by the production technology. In the direction of improving business processes, there is a need for wider use of decision support systems based on artificial intelligence and expert systems. The authors developed a model for the implementation of production processes that takes into account the design features of business processes of industrial enterprises in the conditions of digitalization of the economy. The distinctive feature of the presented model is the combination of the life cycle and the value stream with a structured approach to defining the components of Industry 4.0. 

Parliamentarism and the Legislative Branch

2017 ◽  
Author(s):  
András Sajó ◽  
Renáta Uitz
Keyword(s):  
Decision Making ◽  
Political Parties ◽  
Legislative Branch ◽  
Effective Decision ◽  
The Law ◽  
Internal Operations ◽  
Effective Decision Making ◽  
The Relationship ◽  
Law Making

This chapter examines the relationship between parliamentarism and the legislative branch. It explores the evolution of the legislative branch, leading to disillusionment with the rationalized law-making factory, a venture run by political parties beyond the reach of constitutional rules. The rise of democratically bred party rule is positioned between the forces favouring free debate versus effective decision-making in the legislature. The chapter analyses the institutional make-up and internal operations of the legislature, the role of the opposition in the legislative assembly, and explores the benefits of bicameralism for boosting the powers of the legislative branch. Finally, it looks at the law-making process and its outsourcing via delegating legislative powers to the executive.

scholarly journals Corporate Social Responsibility (CSR): motivations and challenges of a Multinational Enterprise (MNE) subsidiary’s engagement with host communities in Ghana

2021 ◽  
Vol 6 (1) ◽  
Author(s):  
Lyon Salia Awuah ◽  
Kwame Oduro Amoako ◽  
Stephen Yeboah ◽  
Emmanuel Opoku Marfo ◽  
Peter Ansu-Mensah
Keyword(s):  
Stakeholder Engagement ◽  
Multinational Enterprise ◽  
Cost Savings ◽  
Community Members ◽  
Mining Sector ◽  
High Expectations ◽  
Effective Decision ◽  
Effective Decision Making ◽  
Internal Stakeholders ◽  
Corporate Social

AbstractThis paper aims to explore the motivations and challenges of engaging host communities in CSR practices within the context of Newmont Ahafo Mines (NAM), a subsidiary of a Multinational Mining Enterprise (MNE) operating in Ghana’s mining sector. This paper draws insights from stakeholder theory and interviews conducted with internal stakeholders (management and employees) and stakeholders in host communities (traditional rulers and community members). The findings indicate that effective decision-making, gaining legitimacy, cost savings, management of risks, and accountability are some of the perceived motivations of NAM’s stakeholder engagement in CSR. Nonetheless, the most critical challenges to NAM in improving stakeholder engagement in CSR practices are the lack of community members’ support in CSR projects, communities’ high expectations of NAM on development projects and over-dependency on NAM on the part of host communities. Therefore, it is reasonable for MNEs in emerging economies to attune engagement practices to the host community’s context. This will enable CSR practices and policies to fully exploit the latent benefits of CSR in the mining sector.

scholarly journals Reflections on the Importance of Cost of Illness Analysis in Rare Diseases: A Proposal

2021 ◽  
Vol 18 (3) ◽  
pp. 1101
Author(s):  
Patrizio Armeni ◽  
Marianna Cavazza ◽  
Entela Xoxi ◽  
Domenica Taruscio ◽  
Yllka Kodra
Keyword(s):  
Rare Diseases ◽  
Cost Of Illness ◽  
Fragile X ◽  
Direct Costs ◽  
Medicinal Products ◽  
Novel Treatments ◽  
Decision Making Processes ◽  
Effective Decision ◽  
Cross Country ◽  
Effective Decision Making

In the field of rare diseases (RDs), the evidence standard is often lower than that required by health technology assessment (HTA) and payer authorities. In this commentary, we propose that appropriate economic evaluation for rare disease treatments should be initially informed by cost-of-illness (COI) studies conducted using a societal perspective. Such an approach contributes to improving countries’ understanding of RDs in their entirety as societal and not merely clinical, or product-specific issues. In order to exemplify how the disease burden’s distribution has changed over the last fifteen years, key COI studies for Hemophilia, Fragile X Syndrome, Cystic Fibrosis, and Juvenile Idiopathic Arthritis are examined. Evidence shows that, besides methodological variability and cross-country differences, the disease burden’s share represented by direct costs generally grows over time as novel treatments become available. Hence, to support effective decision-making processes, it seems necessary to assess the re-allocation of the burden produced by new medicinal products, and this approach requires identifying cost drivers through COI studies with robust design and standardized methodology.

DISAST-CIR: Disastrous Incidents Systematic Analysis Through Components, Interactions and Results: Application to a Large-Scale Train Accident

2009 ◽  
Vol 37 (1) ◽  
pp. 46-50 ◽  
Author(s):  
Adi Leiba ◽  
Dagan Schwartz ◽  
Talor Eran ◽  
Amir Blumenfeld ◽  
Daniel Laor ◽  
...  
Keyword(s):  
Large Scale ◽  
Systematic Analysis
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