INFORMATICA ECONOMICA

JOURNAL

 

CONTENTS

Vol. 24 No. 4/2020

Issue Topic: Cooperative Decision-Making: Consensus Building vs Crowdsourcing–based Decisions


A Crowdsourcing Effort about Mobilizing Students to Forward Thinking of Their Studies
Jan W. OWSIŃSKI, Cristian CIUREA, Florin Gheorghe FILIP 5
The paper presents some preliminary research results, obtained within the framework of the project “Multiparticipant cooperative decision-making: consensus building vs. crowdsourcing-based decisions”, concerning the introduction to a crowdsourcing effort meant to mobilize students to forward thinking of their studies. A study was conducted by Bucharest University of Economic Studies and by Warsaw School of Information Technology under the auspices of the Polish Academy of Sciences and relevant data were collected using a questionnaire delivered to Romanian and Polish students. The results were interpreted in order to extract relevant information about expected nature of work after graduating, based on gender, nationality and university. Crowdsourcing solutions are presented in order to reveal their advantages applicable in collaborative environments.
Keywords: Decision-Making, Collaborative, Crowdsourcing, Multi-Participant, Online Education.

A Computational Approach to Economic Inequality, Happiness and Human Development
Irina GEORGESCU, Jani KINNUNEN, Armenia ANDRONICEANU, Ane-Mari ANDRONICEANU 16
In this paper, we study the connections of categorical levels of Human Development Index (HDI), GDP per capita, World Happiness Index, the Gini indexes of Income and Wealth inequalities together with poverty rate for 98 world countries. By clustering analysis, we identify four groups of countries with similar features. K-means clustering algorithm is applied to obtain four clusters of sizes 21-26 countries by explaining 68.3% of the total variation in data. The analysis reveals significant differences between the clusters, while also factors with largest differences within the clusters. Secondly, multinomial logistic regression (MLR) is applied in predicting the HDI categories of the full sample of 98 world countries for year 2018. The MLR model can capture also nonlinear relationship. The logistic regression model achieved 91.8% overall accuracy. The results of our research together from earlier literature is followed by suggestions for the future research.
Keywords: Human Development Index, Economic inequality, Happiness Index, Poverty rate.

An Approach for Information Security Risk Assessment in Cloud Environments
Livia Maria BRUMĂ 29
Cloud technology has revolutionized the way computational resources are accessed, offering benefits that have led to widespread adoption. The risk of losing important data is one of the reasons why some organizations do not adopt the migration to a public cloud or adopt the par-tial migration of information that is not critical. The process of risk assessment should be done since the initial stage of a project and become a continuous process. It is an essential process that help management structure to take strategic decision about security mechanisms needed to be implemented to avoid information leaks and about the costs and impact of unexpected events. This paper presents the process of information security risk assessment as well as the importance of knowledge of the associated risks. The paper also proposes a model for deter-mining risk of data security according to their importance for the organization, which provides an overview of vulnerabilities and their real impact on assets. Furthermore, the proposed mod-el helps organizations to choose the right methods to ensure the optimal level of security, in line with operational requirements and critical information.
Keywords: Cloud computing, Risk assessment, Information security, Security assessment, CVSS metrics.

Cloud Computing in Supply Chain Management and Economic, Environmental and Social Impact Analysis
Elena PUICĂ 41
Information and communication technology (ICT) has gained influence in supply chain management (SCM) in recent years. Supply chain management acts on operational processes, divergent and consolidated information flows and interaction processes with a variety of business partners. Considering all the well-known problems of these central information systems, the question arises whether cloud-based information systems are a better alternative to establish technological support for supply chain management and whether the effects from an economic, social and economic point of view. and environmental results have a positive impact. The aim of this research is to provide a better understanding of the overlap of supply chain management and cloud technology from an economic, environmental and social perspective.
Keywords: Cloud Computing, SCM, Economic environment, Social impact

Word Cloud and Sentiment Analysis of Amazon Earphones Reviews with R Programming Language
Ahmed Imran KABIR, Koushik AHMED, Ridoan KARIM 55
The internet has opened a very wide range of ways for exchanging information or data. The development of internet influenced our daily lives to share our opinion on internet. We can share our opinions in social media like twitter, Facebook, LinkedIn or micro blogging site. We can give reviews about any product or we can share what things we are expecting. The sharing of information in internet makes internet a rich resource. Large organization or any type of business who want to do business in a customer centric way needs to know what peoples are thinking. To know that, we can use online resources but to analyze all the data in a short time is not easy if we try to figure out everyone is thought one by one. Sentiment analysis and word cloud in text mining is introduced to eradicate this problem. It helps to know what peoples are thinking and helps to develop the client experience and helps to take decision in a customer centric way. The project on word cloud and sentiment analysis of amazon earphones reviews is basically done to know the process which we can used in our practical life to know the people’s attitude, opinions, reviews, sentiment towards something from unstructured big data from online resources.
Keywords: Word Cloud, Sentiment Analysis, Big Data Analysis, R Programming Language

Semantic Web Applications: Current Trends in Datasets, Tools and Technologies’ Development for Linked Open Data
Sabina-Cristiana NECULA 72
We report a survey on the actual state of the art about semantic web and its applications. Semantic Web plays a major role in integrating data, especially open data, publicly available on the Internet. We reviewed scientifically research papers, study cases, web sites and specialty books in order to discuss the main applicative areas, especially in the field of governmental use, the main technologies and the architectures involved. Both quantitative and qualitative analyses were carried out on the data, which related to 1460 ontologies belonging to Linked Open Data Cloud. The second analysis was on the content of scientific articles belonging to Clarivate Analytics, Scopus and Google Scholar databases. We identified and analyzed 84941 articles written on the subject of ontology, from which computer science is represented by 36264 articles. The results of our research proved that semantic web technologies are an important tool for describing and integrating data and an important component in the data layer of any intelligent application. This study contributed to the mainstream of the research literature by presenting the applicative areas of semantic web and semantic web applications’ development tools, architectures, and methodology.
Keywords: Semantic web, Linked Open Data, Resource Description Framework, SPARQL Protocol and RDF Query Language

The 20th International Conference on Informatics in Economy, IE 2021 85

Publishing Guide for Authors 86

INFOREC Association 88




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