Large group two-stage risk emergency decision-making method based on big data analysis of social media

2019 ◽  
Vol 36 (3) ◽  
pp. 2645-2659 ◽  
Author(s):  
Xuan-hua Xu ◽  
Xin Yang ◽  
Xiaohong Chen ◽  
Bingsheng Liu
Keyword(s):  
Decision Making ◽  
Social Media ◽  
Big Data ◽  
Data Analysis ◽  
Big Data Analysis ◽  
Two Stage ◽  
Large Group ◽  
Emergency Decision Making ◽  
Emergency Decision

Application of Statistical Analysis Tools and Concepts to Big Data and Predictive Analytics to New Product Development

2020 ◽  
Vol 3 (1) ◽  
pp. 17-35
Author(s):  
Brian J. Galli
Keyword(s):  
Decision Making ◽  
Big Data ◽  
Data Analysis ◽  
Product Development ◽  
Competitive Advantage ◽  
New Product Development ◽  
New Product ◽  
Big Data Analysis ◽  
Life Cycles ◽  
The Impact

In today's fiercely competitive environment, most companies face the pressure of shorter product life cycles. Therefore, if companies want to maintain a competitive advantage in the market, they need to keep innovating and developing new products. If not, then they will face difficulties in developing and expanding markets and may go out of business. New product development is the key content of enterprise research and development, and it is also one of the strategic cores for enterprise survival and development. The success of new product development plays a decisive role both in the development of the company and in maintaining a competitive advantage in the industry. Since the beginning of the 21st century, with the continuous innovation and development of Internet technology, the era of big data has arrived. In the era of big data, enterprises' decision-making for new product development no longer solely relies on the experience of decision-makers; it is based on the results of big data analysis for more accurate and effective decisions. In this thesis, the case analysis is mainly carried out with Company A as an example. Also, it mainly introduces the decision made by Company A in the actual operation of new product development, which is based on the results of big data analysis from decision-making to decision-making innovation. The choice of decision-making is described in detail. Through the introduction of the case, the impact of big data on the decision-making process for new product development was explored. In the era of big data, it provides a new theoretical approach to new product development decision-making.

scholarly journals A Novel Linguistic Z-Number QUALIFLEX Method and Its Application to Large Group Emergency Decision Making

2020 ◽  
Vol 2020 ◽  
pp. 1-12 ◽  
Author(s):  
Xue-Feng Ding ◽  
Li-Xia Zhu ◽  
Mei-Shun Lu ◽  
Qi Wang ◽  
Yi-Qi Feng
Keyword(s):  
Decision Making ◽  
Group Decision ◽  
Real Life ◽  
Decision Makers ◽  
Decision Matrix ◽  
Large Group ◽  
Emergency Event ◽  
Emergency Decision Making ◽  
Emergency Decision ◽  
Alternative Solutions

After an unconventional emergency event occurs, a reasonable and effective emergency decision should be made within a short time period. In the emergency decision making process, decision makers’ opinions are often uncertain and imprecise, and determining the optimal solution to respond to an emergency event is a complex group decision making problem. In this study, a novel large group emergency decision making method, called the linguistic Z-QUALIFLEX method, is developed by extending the QUALIFLEX method using linguistic Z-numbers. The evaluations of decision makers on the alternative solutions are first expressed as linguistic Z-numbers, and the group decision matrix is then constructed by aggregating the evaluations of all subgroups. The QUALIFLEX method is used to rank the alternative solutions for the unconventional emergency event. Besides, a real-life example of emergency decision making is presented, and a comparison with existing methods is performed to validate the effectiveness and practicability of the proposed method. The results show that the proposed linguistic Z-QUALIFLEX can accurately express the evaluations of the decision makers and obtain a more reasonable ranking result of solutions for emergency decision making.

scholarly journals AI-powered Energy Internet Towards Carbon Neutrality: Challenges and Opportunities

2021 ◽  
Author(s):  
Chaojie Li
Keyword(s):  
Decision Making ◽  
Big Data ◽  
Data Analysis ◽  
Energy Supply ◽  
Big Data Analysis ◽  
Energy Industry ◽  
Energy Internet ◽  
Carbon Neutrality ◽  
Intelligent Decision Making ◽  
Intelligent Decision

From self-driving vehicles, voice recognition based virtual digital assistants, smart thermostats to recommendation systems, Artificial Intelligence (AI) is becoming a crucial part of the carbon neutral society that has drawn considerable interest from energy supply firms, startups, technology developers, financial institutions, national governments and the academic community. The emergence of AI initiates numerous opportunities to transform energy industry to AI-powered smart system which can revolutionize traditional approaches of creativity thinking, strategical operation, and solution seeking, especially for accelerating carbon neutrality of our society. This survey provides a comprehensive overview of fundamental principles that underpin applications of big data analysis in Energy Internet (EI), such as smart energy supply and consumption, smart health and Fintech. Next, we focus on intelligent decision-making for the energy industry and inform the state-of-the-art by thoroughly reviewing the literature. Subsequently, cybersecurity issues for AI system related to EI are discussed with recent advancements from vulnerability analysis of AI system to differential privacy and to blockchain based security technology. To our knowledge, this is one of the first academic, peer-reviewed works to provide a systematic review of AI applications for EI research and initiatives in terms of big data analysis, intelligent decision-making and AI related cybersecurity These initiatives were systematically classified into different groups according to the field of application, methodology and contribution Afterwards, potential challenges, limitations for existing research and opportunities for future directions are discussed, ranging from emerging explainable AI, to localized multi-energy marketplaces, self-driving electric vehicle charging and e-mobility. This paper can help us understand how to build smart cities and critical infrastructure for a climate-changed world towards the UN’s sustainable development goals.

scholarly journals BIG DATA ANALYSIS FOR INNOVATION DEVELOPMENT DECISION MAKING IN ENERGY SECTOR

2020 ◽  
Author(s):  
А.В. Михеев
Keyword(s):  
Decision Making ◽  
Big Data ◽  
Data Analysis ◽  
Semantic Analysis ◽  
Big Data Analysis ◽  
Energy Sector ◽  
Innovative Development ◽  
Innovation Development ◽  
Bibliometric Review ◽  
Scopus Database

В статье рассматриваются возможности применения методов анализа больших данных для принятия решений по инновационному развитию в энергетике. Выполнен библиометрический обзор научных исследований по использованию анализа больших данных для задач в сфере энергетики на основе публикаций международной базы Scopus за 2010-2020 гг. Приведены содержательные задачи мониторинга, прогнозирования и оценки перспективности технологических решений в энергетике на основе семантического анализа больших данных. The article discusses the feasibility and possible applications of big data analysis for making decisions on innovative development in the energy sector. A bibliometric review of scientific research on the use of big data analysis for problems in the energy sector was carried out based on publications of Scopus database for 2010-2020. The substantive tasks of monitoring, forecasting and evaluating the prospects of technological solutions in the energy sector based on semantic analysis of big data are presented.

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