{"title":"使用基于球线性二方位建模方法评估虚拟商业应用的 Metaverse","authors":"Ghazala Bilquise, Khaled Shaalan, Manar AlKhatib","doi":"10.1155/2024/4571959","DOIUrl":null,"url":null,"abstract":"<p>The rise of the metaverse has ignited a surge of interest among researchers and decision-makers, seeking to develop effective virtual commerce (v-commerce) applications that cater to business demands and customer preferences. v-commerce, an emerging concept, redefines the future of shopping experiences and customer-product interactions. While businesses are actively exploring the potential of immersive technologies to deliver captivating and engaging shopping experiences, there remains a lack of consensus on what constitutes an ideal v-commerce experience and how to identify optimal v-commerce stores effectively. Considering this, benchmarking v-commerce applications for the metaverse is crucial for its development. This endeavor falls within the realm of multiple-criteria decision-making, given various critical issues such as the multitude of design attributes, uncertainty regarding their relative importance, and data variability. This study proposes an innovative approach that extends the fuzzy-weighted zero-inconsistency (FWZIC) method with spherical linear Diophantine fuzzy sets (FSs) (SLDFSs) to determine the weights of v-commerce attributes. The obtained weights are integrated with the ranking alternatives by trace median index (RATMI) method to select the optimal v-commerce application for the metaverse. Criterion weighting results reveal that “ease of navigation” and “recommendation agents” are the most significant criteria in assessing v-commerce solutions. Based on these results, 24 v-commerce solutions were evaluated. Additionally, sensitivity analysis and comparative evaluation were used to assess the robustness and validity of the proposed framework. This research provides essential insights for decision-makers and practitioners to facilitate business growth, consumer satisfaction, and further research in this domain.</p>","PeriodicalId":36408,"journal":{"name":"Human Behavior and Emerging Technologies","volume":null,"pages":null},"PeriodicalIF":4.3000,"publicationDate":"2024-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/2024/4571959","citationCount":"0","resultStr":"{\"title\":\"Evaluation of Virtual Commerce Applications for the Metaverse Using Spherical Linear Diophantine-Based Modeling Approach\",\"authors\":\"Ghazala Bilquise, Khaled Shaalan, Manar AlKhatib\",\"doi\":\"10.1155/2024/4571959\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>The rise of the metaverse has ignited a surge of interest among researchers and decision-makers, seeking to develop effective virtual commerce (v-commerce) applications that cater to business demands and customer preferences. v-commerce, an emerging concept, redefines the future of shopping experiences and customer-product interactions. While businesses are actively exploring the potential of immersive technologies to deliver captivating and engaging shopping experiences, there remains a lack of consensus on what constitutes an ideal v-commerce experience and how to identify optimal v-commerce stores effectively. Considering this, benchmarking v-commerce applications for the metaverse is crucial for its development. This endeavor falls within the realm of multiple-criteria decision-making, given various critical issues such as the multitude of design attributes, uncertainty regarding their relative importance, and data variability. This study proposes an innovative approach that extends the fuzzy-weighted zero-inconsistency (FWZIC) method with spherical linear Diophantine fuzzy sets (FSs) (SLDFSs) to determine the weights of v-commerce attributes. The obtained weights are integrated with the ranking alternatives by trace median index (RATMI) method to select the optimal v-commerce application for the metaverse. Criterion weighting results reveal that “ease of navigation” and “recommendation agents” are the most significant criteria in assessing v-commerce solutions. Based on these results, 24 v-commerce solutions were evaluated. Additionally, sensitivity analysis and comparative evaluation were used to assess the robustness and validity of the proposed framework. This research provides essential insights for decision-makers and practitioners to facilitate business growth, consumer satisfaction, and further research in this domain.</p>\",\"PeriodicalId\":36408,\"journal\":{\"name\":\"Human Behavior and Emerging Technologies\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":4.3000,\"publicationDate\":\"2024-08-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://onlinelibrary.wiley.com/doi/epdf/10.1155/2024/4571959\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Human Behavior and Emerging Technologies\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1155/2024/4571959\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"PSYCHOLOGY, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Human Behavior and Emerging Technologies","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1155/2024/4571959","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"PSYCHOLOGY, MULTIDISCIPLINARY","Score":null,"Total":0}
Evaluation of Virtual Commerce Applications for the Metaverse Using Spherical Linear Diophantine-Based Modeling Approach
The rise of the metaverse has ignited a surge of interest among researchers and decision-makers, seeking to develop effective virtual commerce (v-commerce) applications that cater to business demands and customer preferences. v-commerce, an emerging concept, redefines the future of shopping experiences and customer-product interactions. While businesses are actively exploring the potential of immersive technologies to deliver captivating and engaging shopping experiences, there remains a lack of consensus on what constitutes an ideal v-commerce experience and how to identify optimal v-commerce stores effectively. Considering this, benchmarking v-commerce applications for the metaverse is crucial for its development. This endeavor falls within the realm of multiple-criteria decision-making, given various critical issues such as the multitude of design attributes, uncertainty regarding their relative importance, and data variability. This study proposes an innovative approach that extends the fuzzy-weighted zero-inconsistency (FWZIC) method with spherical linear Diophantine fuzzy sets (FSs) (SLDFSs) to determine the weights of v-commerce attributes. The obtained weights are integrated with the ranking alternatives by trace median index (RATMI) method to select the optimal v-commerce application for the metaverse. Criterion weighting results reveal that “ease of navigation” and “recommendation agents” are the most significant criteria in assessing v-commerce solutions. Based on these results, 24 v-commerce solutions were evaluated. Additionally, sensitivity analysis and comparative evaluation were used to assess the robustness and validity of the proposed framework. This research provides essential insights for decision-makers and practitioners to facilitate business growth, consumer satisfaction, and further research in this domain.
期刊介绍:
Human Behavior and Emerging Technologies is an interdisciplinary journal dedicated to publishing high-impact research that enhances understanding of the complex interactions between diverse human behavior and emerging digital technologies.