A Web Based Modular Environment for Assisting Health Policy Making Utilizing Big Data Analytics

2018 ◽  
Author(s):  
Konstantinos Moutselos ◽  
Dimosthenis Kyriazis ◽  
Ilias Maglogiannis
Keyword(s):  
Big Data ◽  
Health Policy ◽  
Policy Making ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Web Based

An experimental investigation of the impact of using big data analytics on customers’ performance measurement

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Marwa Rabe Mohamed Elkmash ◽  
Magdy Gamal Abdel-Kader ◽  
Bassant Badr El Din
Keyword(s):  
Big Data ◽  
Performance Measurement ◽  
Data Analytics ◽  
Positive Impact ◽  
Big Data Analytics ◽  
Unstructured Data ◽  
Future Research ◽  
Web Based ◽  
Content Type ◽  
The Impact

Purpose This study aims to investigate and explore the impact of big data analytics (BDA) as a mechanism that could develop the ability to measure customers’ performance. To accomplish the research aim, the theoretical discussion was developed through the combination of the diffusion of innovation theory with the technology acceptance model (TAM) that is less developed for the research field of this study. Design/methodology/approach Empirical data was obtained using Web-based quasi-experiments with 104 Egyptian accounting professionals. Further, the Wilcoxon signed-rank test and the chi-square goodness-of-fit test were used to analyze data. Findings The empirical results indicate that measuring customers’ performance based on BDA increase the organizations’ ability to analyze the customers’ unstructured data, decrease the cost of customers’ unstructured data analysis, increase the ability to handle the customers’ problems quickly, minimize the time spent to analyze the customers’ data and obtaining the customers’ performance reports and control managers’ bias when they measure customer satisfaction. The study findings supported the accounting professionals’ acceptance of BDA through the TAM elements: the intention to use (R), perceived usefulness (U) and the perceived ease of use (E). Research limitations/implications This study has several limitations that could be addressed in future research. First, this study focuses on customers’ performance measurement (CPM) only and ignores other performance measurements such as employees’ performance measurement and financial performance measurement. Future research can examine these areas. Second, this study conducts a Web-based experiment with Master of Business Administration students as a study’s participants, researchers could conduct a laboratory experiment and report if there are differences. Third, owing to the novelty of the topic, there was a lack of theoretical evidence in developing the study’s hypotheses. Practical implications This study succeeds to provide the much-needed empirical evidence for BDA positive impact in improving CPM efficiency through the proposed framework (i.e. CPM and BDA framework). Furthermore, this study contributes to the improvement of the performance measurement process, thus, the decision-making process with meaningful and proper insights through the capability of collecting and analyzing the customers’ unstructured data. On a practical level, the company could eventually use this study’s results and the new insights to make better decisions and develop its policies. Originality/value This study holds significance as it provides the much-needed empirical evidence for BDA positive impact in improving CPM efficiency. The study findings will contribute to the enhancement of the performance measurement process through the ability of gathering and analyzing the customers’ unstructured data.

Big Data Analytics on the Characteristic Equilibrium of Collective Opinions in Social Networks

Big Data ◽  
2016 ◽  
pp. 1403-1420 ◽  
Author(s):  
Yingxu Wang ◽  
Victor J. Wiebe
Keyword(s):  
Social Networks ◽  
Big Data ◽  
Computational Intelligence ◽  
Data Analytics ◽  
Collective Intelligence ◽  
Big Data Analytics ◽  
Fuzzy Data ◽  
Web Based ◽  
Data Engineering ◽  
Computational Sociology

Big data are products of human collective intelligence that are exponentially increasing in all facets of quantity, complexity, semantics, distribution, and processing costs in computer science, cognitive informatics, web-based computing, cloud computing, and computational intelligence. This paper presents fundamental big data analysis and mining technologies in the domain of social networks as a typical paradigm of big data engineering. A key principle of computational sociology known as the characteristic opinion equilibrium is revealed in social networks and electoral systems. A set of numerical and fuzzy models for collective opinion analyses is formally presented. Fuzzy data mining methodologies are rigorously described for collective opinion elicitation and benchmarking in order to enhance the conventional counting and statistical methodologies for big data analytics.

An Analysis of Big Data Analytics

2021 ◽  
pp. 203-230
Author(s):  
Vijander Singh ◽  
Amit Kumar Bairwa ◽  
Deepak Sinwar
Keyword(s):  
Big Data ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Past Century ◽  
Data Generation ◽  
Microsoft Excel ◽  
Web Based ◽  
The Past ◽  
Digital World ◽  
World Information

In the development of the advanced world, information has been created each second in numerous regions like astronomy, social locales, medical fields, transportation, web-based business, logical research, horticulture, video, and sound download. As per an overview, in 60 seconds, 600+ new clients on YouTube and 7 billion queries are executed on Google. In this way, we can say that the immense measure of organized, unstructured, and semi-organized information are produced each second around the cyber world, which should be managed efficiently. Big data conveys properties such as unpredictability, 'V' factor, multivariable information, and it must be put away, recovered, and dispersed. Logical arranged data may work as information in the field of digital world. In the past century, the sources of data as to size were very limited and could be managed using pen and paper. The next generation of data generation tools include Microsoft Excel, Access, and database tools like SQL, MySQL, and DB2.

Agile Big Data Analytics for Web-Based Systems: An Architecture-Centric Approach

2016 ◽  
Vol 2 (3) ◽  
pp. 234-248 ◽  
Author(s):  
Hong-Mei Chen ◽  
Rick Kazman ◽  
Serge Haziyev
Keyword(s):  
Big Data ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Web Based

scholarly journals Big data analytics of sustainable ecotourism development in Bromo Tengger Semeru National Park

2021 ◽  
Vol 5 (1) ◽  
pp. 35-48
Author(s):  
Joshi Maharani Wibowo ◽  
Sri Muljaningsih ◽  
Dias Satria
Keyword(s):  
Sustainable Development ◽  
Big Data ◽  
Protected Area ◽  
Policy Making ◽  
Data Analytics ◽  
National Park ◽  
Big Data Analytics ◽  
Sustainable Livelihoods ◽  
Qualitative Approach ◽  
Environmental Aspects

Bromo Tengger Semeru National Park (BTSNP) are designated as the 10 new Bali of Indonesia. As a protected area, BTSNP has unique ecotourism characteristics that distinguish it from other ecotourism destinations. This study seeks to examine the appropriateness of BTSNP sustainable development-based ecotourism through the Sustainable Livelihoods Approach (SLA) approach. This study used TripAdvisor reviews related to BTSNP in 2019 as the main data. The data were analyzed using a qualitative approach. The results of this study revealed the extent to which the process of developing BTSNP ecotourism on the basis of sustainable development as observed from economic, tourism, socio-cultural, and environmental aspects. The results of this study are expected to be considerations for policy-making to develop tourism that pays attention to the environment by not imposing BTSNP boundaries as protected areas for conservation.

Big Data Analytics on the Characteristic Equilibrium of Collective Opinions in Social Networks

2014 ◽  
Vol 8 (3) ◽  
pp. 29-44 ◽  
Author(s):  
Yingxu Wang ◽  
Victor J. Wiebe
Keyword(s):  
Social Networks ◽  
Big Data ◽  
Data Analytics ◽  
Collective Intelligence ◽  
Big Data Analytics ◽  
Fuzzy Data ◽  
Web Based ◽  
Fuzzy Models ◽  
Data Engineering ◽  
Computational Sociology

Big data are products of human collective intelligence that are exponentially increasing in all facets of quantity, complexity, semantics, distribution, and processing costs in computer science, cognitive informatics, web-based computing, cloud computing, and computational intelligence. This paper presents fundamental big data analysis and mining technologies in the domain of social networks as a typical paradigm of big data engineering. A key principle of computational sociology known as the characteristic opinion equilibrium is revealed in social networks and electoral systems. A set of numerical and fuzzy models for collective opinion analyses is formally presented. Fuzzy data mining methodologies are rigorously described for collective opinion elicitation and benchmarking in order to enhance the conventional counting and statistical methodologies for big data analytics.

A New Web-Based Big Data Analytics for Dynamic Public Opinion Mapping in Digital Networks on Contested Biotechnology Fields

2020 ◽  
Vol 24 (1) ◽  
pp. 29-42 ◽  
Author(s):  
Virginie Tournay ◽  
Mathieu Jacomy ◽  
Andra Necula ◽  
Annette Leibing ◽  
Alessandro Blasimme
Keyword(s):  
Big Data ◽  
Public Opinion ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Digital Networks ◽  
Web Based
Sign in / Sign up

Export Citation Format

Share Document