Knowledge diffusion trajectories in the Pythagorean fuzzy field based on main path analysis

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Liu Meng ◽  
Zhang Chonghui ◽  
Yu Chenhong ◽  
Ye Yujing
Keyword(s):  
Decision Making ◽  
Path Analysis ◽  
Fuzzy Sets ◽  
Fuzzy Theory ◽  
Fuzzy Decision Making ◽  
Content Type ◽  
The Past ◽  
Main Path ◽  
Main Path Analysis ◽  
Structure Of Knowledge

PurposeThe purpose of this article is to conduct a main path analysis of 627 articles on the theme of Pythagorean fuzzy sets (PFSs) in the Web of Science (WoS) from 2013 to 2020, to provide a conclusive and comprehensive analysis for researchers in this field, and to provide a study on preliminary understanding of PFSs.Design/methodology/approachThe research topic of Pythagorean fuzzy fields, through keyword extraction and describing the changes in characteristic themes over the past eight years, are firstly examined. Main path analysis, including local and global main paths and key route paths, is then used to reveal the most influential relationships between papers and to explore the trajectory and structure of knowledge transmission.FindingsThe application of Pythagorean fuzzy theory to the field of decision-making has been popular, and combinations of the traditional Pythagorean fuzzy decision-making method with other fuzzy sets have attracted widespread attention in recent years. In addition, over the past eight years, research interest has shifted to different types of PFSs, such as interval-valued PFSs.Research limitations/implicationsThis paper implicates to investigate the growth in certain trends in the literature and to explore the main paths of knowledge dissemination in the domain of PFSs in recent years.Originality/valueThis paper aims to identify the topics in which researchers are currently interested, to help scholars to keep abreast of the latest research on PFSs.

scholarly journals A Novel Analytic Framework of Technology Mining Using the Main Path Analysis and the Decision-Making Trial and Evaluation Laboratory-Based Analytic Network Process

Mathematics ◽  
2021 ◽  
Vol 9 (19) ◽  
pp. 2448
Author(s):  
Chi-Yo Huang ◽  
Liang-Chieh Wang ◽  
Ying-Ting Kuo ◽  
Wei-Ti Huang
Keyword(s):  
Decision Making ◽  
Research And Development ◽  
Path Analysis ◽  
Citation Network ◽  
Analytic Network Process ◽  
Analytic Framework ◽  
Main Path ◽  
Main Path Analysis ◽  
Network Process ◽  
Tech Mining

Tech mining is an analytical method of technology monitoring that can reveal technology trends in different industries. Patent databases are the major sources for information retrieval by tech mining methods. The majority of the commercially viable research and development results in the world can be found in patents. The time and cost of research and development can greatly be reduced if researchers properly analyze patents of prior arts. Appropriate analyses of patents also help firms avoid patent infringement while simultaneously developing new products or services. The main path analysis is a bibliometric method which can be used to derive the most dominant paths in a citation network of patents or academic works and has widely been adopted in tracing the development trajectory of a specific science or technology. Even though main path analysis can derive patent citation relationships and the weight associated with some specific arc of the citation network, the weights associated with patents and influence relationships among patents can hardly be derived based on methods of main path analysis. However, these influence relationships and weight can be crucial for defining research and development and patent aggregation strategies. Thus, the authors want to propose a novel analytic framework which consists of the Decision-Making Trial and Evaluation Laboratory (DEMATEL), the DEMATEL based Analytic Network Process (DANP) and the main path analysis. The proposed analytic framework can be used to derive the influence relationships and influence weights associated with the patents in a main path. Empirical cases based on the main path of a published work and the patent mining results of nanowire field effect transistors from the database of the United States Patent and Trademark Office will be used to demonstrate the feasibility of the proposed analytic framework. The analytic results of empirical research can be used as a basis for infringement evaluation, patent designing around and innovation.

Exploring the knowledge development trajectories of the supply chain finance domain: a main path analysis

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Dejian Yu ◽  
Libo Sheng
Keyword(s):  
Supply Chain ◽  
Path Analysis ◽  
Trade Credit ◽  
Health Financing ◽  
Knowledge Diffusion ◽  
Financial Flows ◽  
Content Type ◽  
Supply Chain Finance ◽  
Main Path ◽  
Main Path Analysis

PurposeSupply chain finance (SCF), which is able to manage financial flows along the supply chains effectively, has received wide attention from all over the world. Faced with the increasing number of outputs, the purpose of this paper is to investigate the SCF development over the past decades effectively, including the hot topics, knowledge diffusion trajectories and structure.Design/methodology/approachThis paper adopts the keyword co-occurrence cluster and main path analysis (MPA) including four types of main paths, studying the historical development of SCF based on 2,233 papers retrieved from Web of Science during 1970–2019.FindingsThe results show that: (1) the research focuses on several aspects, including trade credit, supply chain management, procurement, health financing and sustainability, etc. and (2) trade credit financing has been the mainstream and the research focus has shifted from one-level trade credit to two-level trade credit. Recently, there is a trend to use game-theoretic models to find the best solutions for members in the supply chain.Originality/valueThis paper addresses the need to investigate the knowledge evolution in the SCF domain. It provides a framework to study the knowledge diffusion trajectories and structure, which helps scholars to handle thousands of papers effectively and deepen their understanding of the history, present and future trends of SCF development.

scholarly journals Current States and Future Trends in Safety Research of Construction Personnel: A Quantitative Analysis Based on Social Network Approach

2021 ◽  
Vol 18 (3) ◽  
pp. 883
Author(s):  
Xiangcheng Meng ◽  
Alan H. S. Chan
Keyword(s):  
Social Network ◽  
Path Analysis ◽  
Construction Industry ◽  
Occupational Safety ◽  
Future Trends ◽  
Network Approach ◽  
Main Path ◽  
Safety Research ◽  
Main Path Analysis ◽  
Social Network Approach

The construction industry is recognized as a high-risk industry given that safety accidents and personnel injuries frequently occur. This study provided a systematic and quantitative review of existing research achievements by conducting social network approach to identify current states and future trends for the occupational safety of construction personnel. A total of 250 peer-reviewed articles were collected to examine the research on safety issues of workers in construction industry. Social network approach was applied to analyze the interrelationship among authors, keywords, and citations of these articles using VOS viewer and CitNetExplorer. A knowledge structure map was drawn using main path analysis (MPA) towards the collected papers, which was implemented by Pajek. In line with the findings of social network analysis, five research groups, and six keyword themes were identified in accordance with the times of cooperation of researchers and correlation among keywords of the papers. Core papers were identified by using main path analysis for each research domain to represent the key process and backbone for the corresponding area. Based on the finding of the research, significant implications and insights in terms of current research status and further research trends were provided for the scholars, thus helping generate a targeted development plan for occupational safety in construction industry.

Multi-criteria decision making and pattern recognition based on similarity measures for Fermatean fuzzy sets

2021 ◽  
pp. 1-17
Author(s):  
Changlin Xu ◽  
Juhong Shen
Keyword(s):  
Decision Making ◽  
Pattern Recognition ◽  
Fuzzy Sets ◽  
Fuzzy Set ◽  
Medical Diagnosis ◽  
Intuitionistic Fuzzy Set ◽  
Similarity Measures ◽  
New Method ◽  
Fuzzy Decision Making ◽  
Multi Criteria Decision Making

 Higher-order fuzzy decision-making methods have become powerful tools to support decision-makers in solving their problems effectively by reflecting uncertainty in calculations better than crisp sets in the last 3 decades. Fermatean fuzzy set proposed by Senapati and Yager, which can easily process uncertain information in decision making, pattern recognition, medical diagnosis et al., is extension of intuitionistic fuzzy set and Pythagorean fuzzy set by relaxing the restraint conditions of the support for degrees and support against degrees. In this paper, we focus on the similarity measures of Fermatean fuzzy sets. The definitions of the Fermatean fuzzy sets similarity measures and its weighted similarity measures on discrete and continuous universes are given in turn. Then, the basic properties of the presented similarity measures are discussed. Afterward, a decision-making process under the Fermatean fuzzy environment based on TOPSIS method is established, and a new method based on the proposed Fermatean fuzzy sets similarity measures is designed to solve the problems of medical diagnosis. Ultimately, an interpretative multi-criteria decision making example and two medical diagnosis examples are provided to demonstrate the viability and effectiveness of the proposed method. Through comparing the different methods in the multi-criteria decision making and the medical diagnosis application, it is found that the new method is as efficient as the other methods. These results illustrate that the proposed method is practical in dealing with the decision making problems and medical diagnosis problems.

Grey assessment and prediction of the financial agglomeration degree in central five cities

2014 ◽  
Vol 4 (1) ◽  
pp. 95-103 ◽  
Author(s):  
Li Li ◽  
Guo-hui Hu
Keyword(s):  
Decision Making ◽  
Scientific Development ◽  
Fuzzy Decision Making ◽  
Grey Prediction ◽  
Fuzzy Decision ◽  
Content Type ◽  
Multiple Dimension ◽  
The Government ◽  
Development Tendency ◽  
Decision Making Model

Purpose – At present, financial agglomeration tendency in domestic and foreign countries is increasingly evident. Therefore, from a comparative perspective, this paper aims to assess and predict the financial agglomeration degree in central five cities. Design/methodology/approach – According to the diversity of evaluating indexes and the uncertainty of financial agglomeration, this paper constructs a set of indexes of evaluating the financial agglomeration degree, comprehensively evaluates the financial agglomeration degree of the five cities – Wuhan, Changsha, Zhengzhou, Nanchang and Hefei – in China's middle region from 2001 to 2010 by using the multiple dimension grey fuzzy decision-making model, and predicts their development tendency by using the GM (1, 1, β) model. Findings – The results show that the multiple dimension grey fuzzy decision-making pattern cannot only be used to determine the weights of evaluating indexes, but also get the fuzzy partition and ranking order of the financial agglomeration in central five cities. The grey prediction results can objectively reflect the development tendency of the financial agglomeration in central five cities. Practical implications – From the results, it is necessary for any competitive city to clarify their relative strengths and weaknesses in order for the accurate location and scientific development, and it also provides a reference for the government decision-making. Originality/value – The paper succeeds in using the multiple dimension grey fuzzy decision-making model to measure the financial agglomeration degree of the five central cities and the grey prediction model to predict future trends.

Selection of resilient suppliers in manufacturing industries post-COVID-19: implications for economic and social sustainability in emerging economies

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Abhijit Majumdar ◽  
Jeevaraj S ◽  
Mathiyazhagan Kaliyan ◽  
Rohit Agrawal
Keyword(s):  
Decision Making ◽  
Incomplete Information ◽  
Emerging Economies ◽  
Supplier Selection ◽  
Fuzzy Decision Making ◽  
Ideal Solution ◽  
Fuzzy Decision ◽  
Content Type ◽  
Intuitionistic Fuzzy ◽  
Selection Of

PurposeSelection of resilient suppliers has attracted the attention of researchers in the past one decade. The devastating effect of COVID-19 in emerging economies has provided great impetus to the selection of resilient suppliers. Under volatile and uncertain business scenarios, supplier selection is often done under imprecise and incomplete information, making the traditional decision-making methods ineffective. The purpose of this paper is to demonstrate the application of a fuzzy decision-making method for resilient supplier selection.Design/methodology/approachA group of three decision makers was considered for evaluating various alternatives (suppliers) based on their performance under different primary, sustainability and resilience criteria. Experts' opinion about each criterion and alternative was captured in linguistic terms and was modelled using fuzzy numbers. Then, an algorithm for solving resilient supplier selection problem based on the trapezoidal intuitionistic fuzzy technique for order preference by similarity to ideal solution (TrIFTOPSIS) was introduced and demonstrated through a case study.FindingsA closeness coefficient was used to rank the suppliers based on their distances from intuitionistic fuzzy positive-ideal solution and intuitionistic fuzzy negative-ideal solution. Finally, the proposed fuzzy decision making model was applied to a real problem of supplier selection in the clothing industry.Originality/valueThe presented TrIFTOPSIS model provides an effective route to prioritise and select resilient suppliers under imprecise and incomplete information. This is the first application of intuitionistic fuzzy multi-criteria decision-making for resilient supplier selection.

Barriers to implementing digitalization in the Indian construction industry

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Avirag Bajpai ◽  
Subhas C. Misra
Keyword(s):  
Decision Making ◽  
Construction Industry ◽  
Research Paper ◽  
Fuzzy Decision Making ◽  
Top Management ◽  
Research Approach ◽  
Extensive Literature ◽  
Total Quality ◽  
Fuzzy Dematel ◽  
Content Type

PurposeThis research paper aims to analyze the critical barriers to implementing digitalization in the Indian construction industry as Indian construction companies are lagging in the implementation of digital technologies in the work environment.Design/methodology/approachIn this research paper, a qualitative research approach is adopted, and multiple detailed interviews are conducted with industry and academic experts. Further, multi-criteria decision-making (MCDM) techniques are used to finalize the prioritization among various alternatives. The fuzzy-decision-making trial and evaluation laboratory (Fuzzy-DEMATEL) and interpretive structural modeling (ISM) techniques are employed to find the exact relationship among the identified alternatives.FindingsThis study identifies 14 critical barriers from an extensive literature review and multiple interviews with industry professionals, and further driving and critical barriers are identified.Research limitations/implicationsIn this research paper, an exploratory study with a limited number of respondents from a large Indian construction company is carried out. Further, a detailed longitudinal analysis can be done to assess the subjectivity of the participants with more advanced statistical tools. However, this research discusses several points pertaining to the implementation of digitalization in the construction industry. The research further identifies the critical barriers to digitalization in the Indian construction industry.Practical implicationsThe finding of the study has two-pronged implications. First, it provides a road-map to the construction industry by highlighting the engagement of top management as the key focus area for successful digitalization. Second, the finding also shows similarity of the digitalization process to the adoption of process improvement techniques like lean and total quality management (TQM), wherein the top management plays a crucial role in ushering in the implementation of a disruptive change.Originality/valueThe research is unique in two ways. First, this is one of the very few attempts to understand digitalization in the Indian context. Second, the research also demonstrates that the combination of fuzzy DEMATEL and ISM techniques can be successfully employed in the emerging field of construction digitalization research.

Lean in higher education

2019 ◽  
Vol 27 (1) ◽  
pp. 82-102 ◽  
Author(s):  
Yigit Kazancoglu ◽  
Yesim Deniz Ozkan-Ozen
Keyword(s):  
Higher Education ◽  
Decision Making ◽  
Business School ◽  
Stage Structure ◽  
Fuzzy Decision Making ◽  
Multi Criteria Decision Making ◽  
Stage Model ◽  
Content Type ◽  
Road Map ◽  
Multi Stage

PurposeThis research aims to investigate and define the eight wastes of lean philosophy in higher education institutions (HEIs) by proposing a multi-stage model.Design/methodology/approachThe authors have used a specific multi-criteria decision-making method, fuzzy decision-making trial and evaluation laboratory, to investigate the cause–effect relationships and importance order between criteria for wastes in HEIs. In total, 22 criteria were categorized under eight wastes of lean. The study was implemented in a business school with the participation of faculty members from different departments.FindingsThe results showed that the most important wastes in the business school selected were repeated tasks, unnecessary bureaucracy, errors because of misunderstanding/communication problems, excessive number of academic units and creation of an excessive amount of information. Another important result was that all the sub-wastes of talent were in the causes group, while motion and transportation wastes were in the effect group.Practical implicationsA road map to guide lean transformation for HEIs is proposed with a multi-stage model and potential areas for improvement in HEIs were presented.Originality/valueThis study proposes a multi-stage structure by applying multi-criteria decision-making to HEIs, focussing on wastes from a lean perspective.

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