Pub Date : 2022-07-15DOI: 10.1142/s0219622022500353
Shubham Sachan, A. Barve, Aditya Kamat, S. Shanker
{"title":"Assessing the Barriers Towards the Glocalization of India's Mobile Industry: An IVIFs-DEMATEL with Choquet Integral Method","authors":"Shubham Sachan, A. Barve, Aditya Kamat, S. Shanker","doi":"10.1142/s0219622022500353","DOIUrl":"https://doi.org/10.1142/s0219622022500353","url":null,"abstract":"","PeriodicalId":13527,"journal":{"name":"Int. J. Inf. Technol. Decis. Mak.","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82484096","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-07-15DOI: 10.1142/s0219622022500341
M. Nilashi, Sarminah Samad, Abdullah M. Alghamdi, Muhammed Yousoof Ismail, O. Alghamdi, Syed Salman Mehmood, Saidatulakmal Mohd, W. Zogaan, Ashwaq Alhargan
{"title":"A New Method for Analysis of Customers' Online Review in Medical Tourism Using Fuzzy Logic and Text Mining Approaches","authors":"M. Nilashi, Sarminah Samad, Abdullah M. Alghamdi, Muhammed Yousoof Ismail, O. Alghamdi, Syed Salman Mehmood, Saidatulakmal Mohd, W. Zogaan, Ashwaq Alhargan","doi":"10.1142/s0219622022500341","DOIUrl":"https://doi.org/10.1142/s0219622022500341","url":null,"abstract":"","PeriodicalId":13527,"journal":{"name":"Int. J. Inf. Technol. Decis. Mak.","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83880332","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-07-15DOI: 10.1142/s0219622022500390
Mona Jami Pour, Fatemeh Abbasi, B. Sohrabi
{"title":"Toward a Maturity Model for Big Data Analytics: A Roadmap for Complex Data Processing","authors":"Mona Jami Pour, Fatemeh Abbasi, B. Sohrabi","doi":"10.1142/s0219622022500390","DOIUrl":"https://doi.org/10.1142/s0219622022500390","url":null,"abstract":"","PeriodicalId":13527,"journal":{"name":"Int. J. Inf. Technol. Decis. Mak.","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86238429","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-06-17DOI: 10.1142/s0219622022300038
Kai Xiong, Yucheng Dong, Zhaoxia Guo, F. Chiclana, E. Herrera-Viedma
: This study aims to present a multiattribute decision making and clustering method to explore the ranking, classifications and evolution mechanisms of the research fronts in the Web of Science Essential Science Indicators (ESI) database. First, bibliometrics are used to reveal the characteristics of the 57 ESI research fronts with more than 40 ESI highly cited papers (ESI-HCPs). Second, the 8 representative indicators are discovered to get answers to the following two questions: (i) who publishes ESI-HCPs to form a research front? and (ii) where citations to these ESI-HCPs come from in a research front? Next, we investigate the ranking and clusters among the 57 ESI research fronts and uncover the evolution process of the research fronts in different clusters based on these representative indicators. We also compare the performances of different countries in these research fronts, and find that the USA and China are the leading countries in most research fronts. However, the two countries behave differently at different levels with regard to the rankings, the classifications and the evolution.
本研究旨在提出一种多属性决策聚类方法，探讨Web of Science Essential Science Indicators (ESI)数据库中研究前沿的排序、分类及其演化机制。首先，采用文献计量学方法对57个ESI研究前沿的40多篇ESI高被引论文(ESI- hcps)进行特征分析。其次，发现8个具有代表性的指标，得到以下两个问题的答案:(i)谁出版ESI-HCPs以形成研究前沿?(ii)这些esi - hcp在研究前沿的引用来自哪里?接下来，我们对57个ESI研究前沿的排名和集群进行了研究，并基于这些代表性指标揭示了不同集群中研究前沿的演变过程。我们还比较了不同国家在这些研究领域的表现，发现美国和中国在大多数研究领域处于领先地位。然而，在排名、分类和演变方面，两国在不同层次上的表现不同。
{"title":"Exploring the Ranking, Classifications and Evolution Mechanisms of Research Fronts: A Method Based on Multiattribute Decision Making and Clustering","authors":"Kai Xiong, Yucheng Dong, Zhaoxia Guo, F. Chiclana, E. Herrera-Viedma","doi":"10.1142/s0219622022300038","DOIUrl":"https://doi.org/10.1142/s0219622022300038","url":null,"abstract":": This study aims to present a multiattribute decision making and clustering method to explore the ranking, classifications and evolution mechanisms of the research fronts in the Web of Science Essential Science Indicators (ESI) database. First, bibliometrics are used to reveal the characteristics of the 57 ESI research fronts with more than 40 ESI highly cited papers (ESI-HCPs). Second, the 8 representative indicators are discovered to get answers to the following two questions: (i) who publishes ESI-HCPs to form a research front? and (ii) where citations to these ESI-HCPs come from in a research front? Next, we investigate the ranking and clusters among the 57 ESI research fronts and uncover the evolution process of the research fronts in different clusters based on these representative indicators. We also compare the performances of different countries in these research fronts, and find that the USA and China are the leading countries in most research fronts. However, the two countries behave differently at different levels with regard to the rankings, the classifications and the evolution.","PeriodicalId":13527,"journal":{"name":"Int. J. Inf. Technol. Decis. Mak.","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76471289","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-06-17DOI: 10.1142/s0219622022500328
O. Yanmaz, Cigdem Kadaifci, E. Bozdag
{"title":"A New Approach to Correspondence Analysis Based on Interval-Valued Hesitant Fuzzy Sets","authors":"O. Yanmaz, Cigdem Kadaifci, E. Bozdag","doi":"10.1142/s0219622022500328","DOIUrl":"https://doi.org/10.1142/s0219622022500328","url":null,"abstract":"","PeriodicalId":13527,"journal":{"name":"Int. J. Inf. Technol. Decis. Mak.","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90916239","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-06-17DOI: 10.1142/s0219622022500316
S. Bennani, S. Ebersold, M. Hamlaoui, B. Coulette, M. Nassar
{"title":"A Group Decision-Making Approach for Global Consistency of Heterogeneous Models","authors":"S. Bennani, S. Ebersold, M. Hamlaoui, B. Coulette, M. Nassar","doi":"10.1142/s0219622022500316","DOIUrl":"https://doi.org/10.1142/s0219622022500316","url":null,"abstract":"","PeriodicalId":13527,"journal":{"name":"Int. J. Inf. Technol. Decis. Mak.","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89464682","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-05-31DOI: 10.1142/s0219622022500201
Koji Kashihara
It is desirable to prevent traffic accidents by focusing on elderly people’s brain characteristics. The attention level during driving depends on the amount of information-processing resources. This study first aimed at investigating the effects of the change in attention levels on the electroencephalogram (EEG) waves during the graded working memory tasks for a traffic situation. With the increase in memory loads, reaction times were delayed in the elderly than the young group. The difficult tasks activated the induced [Formula: see text] and [Formula: see text] powers in the frontal midline area primarily in the elderly, during the selective task for a target. The elderly could retain the attention level because of the activated slow EEG responses, regardless of the task performance, although the increased [Formula: see text] wave may reflect drowsiness. Because the assistance system based on drivers’ brain signals can prevent car accidents, this study also aimed at evaluating the analytical method to automatically discriminate the different attentional tasks from the EEG signals. Compared with [Formula: see text]-nearest neighbors and artificial neural networks, support vector machines more accurately classified attention levels (i.e., task difficulty) during working memory tasks reflecting a change in the induced [Formula: see text] and [Formula: see text] waves. This result can be related to a brain-computer interface system to judge the task difficulty during driving and alert a driver to danger. The experimental tasks for this study were limited because they involved simulations only in which participants recognized guided boards and removed irrelevant information. Real-time judgments should be investigated using EEG data to improve systems that can alert drivers to oncoming dangers.
{"title":"Automatic Discrimination of Task Difficulty Predicted by Frontal EEG Activity During Working Memory Tasks in Young and Elderly Drivers","authors":"Koji Kashihara","doi":"10.1142/s0219622022500201","DOIUrl":"https://doi.org/10.1142/s0219622022500201","url":null,"abstract":"It is desirable to prevent traffic accidents by focusing on elderly people’s brain characteristics. The attention level during driving depends on the amount of information-processing resources. This study first aimed at investigating the effects of the change in attention levels on the electroencephalogram (EEG) waves during the graded working memory tasks for a traffic situation. With the increase in memory loads, reaction times were delayed in the elderly than the young group. The difficult tasks activated the induced [Formula: see text] and [Formula: see text] powers in the frontal midline area primarily in the elderly, during the selective task for a target. The elderly could retain the attention level because of the activated slow EEG responses, regardless of the task performance, although the increased [Formula: see text] wave may reflect drowsiness. Because the assistance system based on drivers’ brain signals can prevent car accidents, this study also aimed at evaluating the analytical method to automatically discriminate the different attentional tasks from the EEG signals. Compared with [Formula: see text]-nearest neighbors and artificial neural networks, support vector machines more accurately classified attention levels (i.e., task difficulty) during working memory tasks reflecting a change in the induced [Formula: see text] and [Formula: see text] waves. This result can be related to a brain-computer interface system to judge the task difficulty during driving and alert a driver to danger. The experimental tasks for this study were limited because they involved simulations only in which participants recognized guided boards and removed irrelevant information. Real-time judgments should be investigated using EEG data to improve systems that can alert drivers to oncoming dangers.","PeriodicalId":13527,"journal":{"name":"Int. J. Inf. Technol. Decis. Mak.","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85240778","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-05-26DOI: 10.1142/s0219622022500298
Zeshui Xu, Zijing Ge, Xinxin Wang, Gang Kou
{"title":"A Look at the Focus on Big Data for Information Technology and Decision Making During 1994 to 2020","authors":"Zeshui Xu, Zijing Ge, Xinxin Wang, Gang Kou","doi":"10.1142/s0219622022500298","DOIUrl":"https://doi.org/10.1142/s0219622022500298","url":null,"abstract":"","PeriodicalId":13527,"journal":{"name":"Int. J. Inf. Technol. Decis. Mak.","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80107620","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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