657
20
16481
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Dublin Core
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Title
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Book Chapter
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Faculty Publications- Book Chapter
Dublin Core
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Blockchain application with specific reference to smart contracts in the insurance sector
Description
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The term blockchain was coined in 2008 by Satoshi Nakamoto. Initially, it was used for carrying out decentralised transactions to solve the problem of fake transactions. In the past few years, this was explored extensively for cryptocurrency only, but, over some time, its potential has been explored in many areas. The major reason for the growing interest in this particular technology is that it provides a secure, reliable, and trusted platform to perform digital activities. This is executed without the involvement of any third party. Once the data is entered into the nodes, it is impossible to tamper it. Though blockchain is costly, it provides better solutions to many research problems in real time. In recent times, researchers have explored blockchain in deep and used it in many applications such as building smart contracts, supply chain management, digital identity providers, voting systems, banking, and finance applications, P2P learning, and insurance sectors. Through this chapter, the readers will get a systematic and detailed study of blockchain in the insurance sector and smart contracts and its current applications in the insurance sector. This chapter will also provide a fair idea of blockchain technology in the insurance sector and additionally its usage in specific applications. In the end, a relevant set of further reading references will be provided. 2023 River Publishers. All rights reserved.
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Sharma V.; Ajmani P.; Iwendi C.
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The Application of Emerging Technology and Blockchain in the Insurance Industry, pp. 179-208.
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River Publishers
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2023-01-01
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<a href="" target="_blank" rel="noreferrer noopener"></a>
<br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85175665645&partnerID=40&md5=78256cd502aaa5a6dc98ae383940d761" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85175665645&partnerID=40&md5=78256cd502aaa5a6dc98ae383940d761</a>
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ISBN: 978-877004005-1; 978-877004006-8
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Online
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English
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Book chapter
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Sharma V., CHRIST, Delhi-NCR, India; Ajmani P., Vivekananda Institute of Professional Studies-TC, GGSIP University, India; Iwendi C., School of Creative Technologies, University of Bolton, United Kingdom
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Title
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Editorials
Editorial
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Title
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Preface
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[No abstract available]
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Sharma V.; Balusamy B.; Ferari G.; Ajmani P.
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Wireless Communication Technologies: Roles, Responsibilities, and Impact of IoT, 6G, and Blockchain Practices, pp. vii-viii.
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CRC Press
Date
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2024-01-01
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<a href="" target="_blank" rel="noreferrer noopener"></a>
<br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85194769476&partnerID=40&md5=43976dab3111c1cbaaf1bfe0fc2b8b9b" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85194769476&partnerID=40&md5=43976dab3111c1cbaaf1bfe0fc2b8b9b</a>
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ISBN: 978-104002620-5
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Online
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English
Type
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Editorial
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Sharma V., CHRIST (Deemed to be University), Delhi NCR Campus, India; Balusamy B., Shiv Nadar Institute of Eminence, Delhi-NCR Campus, India; Ferari G., University of Parma, Italy; Ajmani P., Vivekananda Institute of Professional Studies-TC, India
-
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Title
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Book
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Title
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Wireless Communication Technologies: Roles, Responsibilities, and Impact of IoT, 6G, and Blockchain Practices
Description
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This book introduces recent wireless technologies and their impact on recent trends, applications, and opportunities. It explores the latest 6G, IoT, and Blockchain techniques with AI and evolutionary applications, showing how digital integration can be used to serve society. It explores the most important aspects of modern technologies, providing insights into the newest 6G technology and practices; covering the roles, responsibilities, and impact of IoT, 6G, and Blockchain practices to sustain the world economy. This book highlights the roles, responsibilities, and impact of IoT, 6G, and Blockchain and its practices. By describing the implementation strategies for Blockchain, IoT, and 6G, this book focuses on technologies related to the advancement in wireless ad-hoc networks and the current sustainability practices used in IoT. It offers popular use cases and case studies related to 6G, IoT, and Blockchain to provide a better understanding and covers the global approach towards the convergence of 6G, IoT, and Blockchain along with recent applications and future potential. The book is a reference for those working with 6G, IoT, AI, and its related application areas. Students at both the UG and PG levels in various departments such as manufacturing, electronics, telecommunications, computer science, other engineering fields, and information technology will be interested in this book. It is ideally designed for use by technology development, academicians, data scientists, industry professionals, researchers, and students. 2024 selection and editorial matter, Vandana Sharma, Balamurugan Balusamy, Gianluigi Ferrari, and Prerna Ajmani.
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Sharma V.; Balusamy B.; Ferrari G.; Ajmani P.
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Wireless Communication Technologies: Roles, Responsibilities, and Impact of IoT, 6G, and Blockchain Practices, pp. 1-320.
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CRC Press
Date
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2024-01-01
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<a href="https://doi.org/10.1201/9781003389231" target="_blank" rel="noreferrer noopener">https://doi.org/10.1201/9781003389231</a>
<br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85194740535&doi=10.1201%2F9781003389231&partnerID=40&md5=186079ebc4826a75a490387992cfa8dc" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85194740535&doi=10.1201%2f9781003389231&partnerID=40&md5=186079ebc4826a75a490387992cfa8dc</a>
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ISBN: 978-104002620-5; 978-103248164-7
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Online
Language
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English
Type
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Book
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Sharma V., CHRIST (Deemed to be University), Delhi-NCR Campus, India, IEEE, United States, IEEE Consumer Technology Society, United States; Balusamy B., Delhi-NCR Campus, India; Ferrari G., Internet of Things (IoT) Laboratory, Department of Engineering and Architecture, India, things2i Ltd, Italy; Ajmani P., Vivekananda School of Information Technology, Vivekananda Institute of Professional Studies, India, Computer Society of India (CSI), India
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Title
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Book Chapter
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Faculty Publications- Book Chapter
Dublin Core
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Title
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Using Sentiment Analysis to Identify Consumers Emotions in the Hotel Industry
Description
An account of the resource
This research attempted to present a more comprehensive overview of online user-generated data by extending far beyond quantitative analysis. We gathered a distinctive and substantial database of online user ratings for the hotel industry from numerous websites over a significant amount of time. To gauge the quality of hotel service, we divided customer reviews into two categories using the sentiment analysis technique. The impact of those factors in influencing users overall evaluation and content creation behavior is then investigated. The findings imply that different aspects of user evaluations have considerably diverse effects on how users evaluate products and what motivates them to create content. 2025 by Apple Academic Press, Inc.
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Sharma V.; Kapse M.; Poulose J.; Mahajan V.
Source
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Sustainability in Marketing Practice: Strategies for Industry 4.0, pp. 99-114.
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Apple Academic Press
Date
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2024-01-01
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<a href="" target="_blank" rel="noreferrer noopener"></a>
<br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85199114515&partnerID=40&md5=be1e53c242470bd151b64288ae6d053e" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85199114515&partnerID=40&md5=be1e53c242470bd151b64288ae6d053e</a>
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ISBN: 978-100382892-1; 978-177491588-2
Format
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Online
Language
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English
Type
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Book chapter
Coverage
The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant
Sharma V., Symbiosis Center for Management and Human Resource Development, Symbiosis International University, Maharashtra, Pune, India; Kapse M., Symbiosis Center for Management and Human Resource Development, Symbiosis International University, Maharashtra, Pune, India; Poulose J., School of Business and Management, CHRIST (Deemed to be University), NCR, Delhi, India; Mahajan V., Symbiosis Center for Management and Human Resource Development, Symbiosis International University, Maharashtra, Pune, India
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Title
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Articles
Article
Faculty Publications -Articles
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Title
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Robotic dining delight unravelling the key factors driving customer satisfaction in service robot restaurants using PLS-SEM and ML
Subject
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machine learning; PLS-SEM; repeat experience; robotics; service restaurants; trust
Description
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In the past few years there has been a remarkable surge in demand for robot service restaurants. However, as both the technology and the concept of such restaurants are relatively new, there is a limited understanding of how consumers would react to this new change in the service industry. This study focuses on the key factors influencing customer satisfaction and their intention to repeat the experience by using two staged hybrid PLS-SEM and Machine Learning approaches. The finding confirms that perceived enjoyment, speed, and novelty influence customer satisfaction, whereas perceived usefulness has no influence. Additionally, the study uncovers that customer satisfaction and trust positively mediate the relationship and establish the link with repeat experience. The machine learning models (Artificial Neural Network, Support Vector Machines, Random Forest, K-Nearest Neighbors, Elastic Net) predict the intention to repeat the experience of the service robot with an overall model fit of around 57%. We also discussed several new and useful theoretical and practical implications for enhancing the customer experience during the visit to the restaurants. 2023 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.
Creator
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Sharma V.; Kapse M.; Poulose J.; Mahajan Y.
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Cogent Business and Management, Vol-10, No. 3
Publisher
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Cogent OA
Date
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2023-01-01
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<a href="https://doi.org/10.1080/23311975.2023.2281053" target="_blank" rel="noreferrer noopener">https://doi.org/10.1080/23311975.2023.2281053</a>
<br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85177233823&doi=10.1080%2F23311975.2023.2281053&partnerID=40&md5=91ded63fcd8a0e25ddf2aaec6426ad0e" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85177233823&doi=10.1080%2f23311975.2023.2281053&partnerID=40&md5=91ded63fcd8a0e25ddf2aaec6426ad0e</a>
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All Open Access; Gold Open Access; Green Open Access
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ISSN: 23311975
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Online
Language
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English
Type
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Article
Coverage
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Sharma V., Symbiosis Centre for Management and Human Resource Development (SCMHRD), Symbiosis International (Deemed University), Pune, India; Kapse M., Symbiosis Centre for Management and Human Resource Development (SCMHRD), Symbiosis International (Deemed University), Pune, India; Poulose J., School of Business and Management, CHRIST (Deemed to be University), Delhi-NCR, India; Mahajan Y., Symbiosis Centre for Management and Human Resource Development (SCMHRD), Symbiosis International (Deemed University), Pune, India
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Title
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Conference Papers
Conference Paper
Faculty Publications- Conference Papers
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Title
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Leveraging the Synergy of Edge Computing and IoT in Supply Chain Management
Subject
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Edge Computing; IoT; Supply Chain Management
Description
An account of the resource
This article investigates the possibilities of integrating edge computing and IoT in supply chain management, as well as the adoption of disruptive technologies such as blockchain integration, digital twins, robotics, and autonomous systems. Operational efficiency can be considerably enhanced by establishing a linked and intelligent supply chain ecosystem. The benefits of this technology include increased openness, efficiency, and resilience in supply chain processes. Among the benefits include real-time product tracking, environmental sustainability, enhanced production, and cost savings. The use of blockchain technology in a three-tiered Supply Chain Network (SCN) shows promise in terms of boosting supply chain transparency and security. The SCOR model is also discussed as a comprehensive framework for optimising supply chain processes. However, concerns such as data privacy, security, and employment displacement must be solved before firms can fully reap the benefits of new technologies. Overall, embracing these innovations has the potential to revolutionise supply chain management and create trust among stakeholders. 2023 IEEE.
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Sharma V.; Mahanayak S.P.; Thapa T.; Mishra S.; Alkhayyat A.
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2023 10th IEEE Uttar Pradesh Section International Conference on Electrical, Electronics and Computer Engineering, UPCON 2023, pp. 1055-1062.
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Institute of Electrical and Electronics Engineers Inc.
Date
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2023-01-01
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<a href="https://doi.org/10.1109/UPCON59197.2023.10434623" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/UPCON59197.2023.10434623</a>
<br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85187387723&doi=10.1109%2FUPCON59197.2023.10434623&partnerID=40&md5=830d3085c3bdcbb48289cd31577391eb" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85187387723&doi=10.1109%2fUPCON59197.2023.10434623&partnerID=40&md5=830d3085c3bdcbb48289cd31577391eb</a>
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ISBN: 979-835038247-1
Format
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Online
Language
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English
Type
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Conference paper
Coverage
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Sharma V., Christ (Deemed to Be University), Delhi NCR, India; Mahanayak S.P., Kalinga Institute of Industrial Technology, Deemed to Be University, India; Thapa T., Kalinga Institute of Industrial Technology, Deemed to Be University, India; Mishra S., Kalinga Institute of Industrial Technology, Deemed to Be University, India; Alkhayyat A., College of Technical Engineering, The Islamic University, Najaf, Iraq
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Dublin Core
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Title
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Book Chapter
Book Chapter
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Dublin Core
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Title
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Green Supply Chain Management: Attaining Sustainable Competitive Advantage
Description
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[No abstract available]
Creator
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Sharma V.; Maheshkar C., Sr.; Poulose J.
Source
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Emerging Trends in Decision Sciences and Business Operations, pp. 235-260.
Publisher
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Taylor and Francis
Date
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2022-01-01
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<a href="https://doi.org/10.4324/9781003315568-13" target="_blank" rel="noreferrer noopener">https://doi.org/10.4324/9781003315568-13</a>
<br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85143954899&doi=10.4324%2F9781003315568-13&partnerID=40&md5=3284fabeb91f54dc756bfeafc47b0c45" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85143954899&doi=10.4324%2f9781003315568-13&partnerID=40&md5=3284fabeb91f54dc756bfeafc47b0c45</a>
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ISBN: 978-100064141-7; 978-103226919-1
Format
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Online
Language
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English
Type
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Book chapter
Coverage
The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant
Sharma V., CHRIST, India; Maheshkar C., Sr., University of Indore, India; Poulose J., CHRIST, India
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Title
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Book
Book
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Dublin Core
The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/.
Title
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Analytics Enabled Decision Making
Subject
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Big Data; Business Analytics; Decision Making; Industry 4.0; Pricing Analytics; Workforce Analytics
Description
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Analytics is changing the landscape of businesses across sectors globally. This has led to the stimulation of interest of scholars and practitioners worldwide in this domain. The emergence of big data, has fanned the usages of machine learning techniques and the acceptance of Analytics Enabled Decision Making. This book provides a holistic theoretical perspective combined with the application of such theories by drawing on the experiences of industry professionals and academicians from around the world. The book discusses several paradigms including pattern mining, clustering, classification, and data analysis to name a few. The main objective of this book is to offer insight into the process of decision-making that is accelerated and made more precise with the help of analytics. The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023.
Creator
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Sharma V.; Maheshkar C.; Poulose J.
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Analytics Enabled Decision Making, pp. 1-288.
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Springer Nature
Date
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2023-01-01
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<a href="https://doi.org/10.1007/978-981-19-9658-0" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-981-19-9658-0</a>
<br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85171506824&doi=10.1007%2F978-981-19-9658-0&partnerID=40&md5=7678a0888f68d54572bf84b977776f72" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85171506824&doi=10.1007%2f978-981-19-9658-0&partnerID=40&md5=7678a0888f68d54572bf84b977776f72</a>
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ISBN: 978-981199658-0; 978-981199657-3
Format
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Online
Language
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English
Type
The nature or genre of the resource
Book
Coverage
The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant
Sharma V., Symbiosis Centre for Management and Human Resource Development (SCMHRD), Symbiosis International (Deemed University), Maharashtra, Pune, India; Maheshkar C., East Nimar Education Society, Madhya Pradesh, Indore, India; Poulose J., CHRIST (Deemed to be University), Uttar Pradesh, Ghaziabad, India
-
Dublin Core
The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/.
Title
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Editorials
Editorial
Faculty Publications- Editorial
Dublin Core
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Title
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Preface
Description
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[No abstract available]
Creator
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Sharma V.; Maheshkar C.; Poulose J.
Source
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Analytics Enabled Decision Making, pp. vii-xi.
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Springer Nature
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2023-01-01
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<a href="" target="_blank" rel="noreferrer noopener"></a>
<br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85171516042&partnerID=40&md5=6f39fa6718c31005f66805dd49878fe7" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85171516042&partnerID=40&md5=6f39fa6718c31005f66805dd49878fe7</a>
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ISBN: 978-981199658-0; 978-981199657-3
Format
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Online
Language
A language of the resource
English
Type
The nature or genre of the resource
Editorial
Coverage
The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant
Sharma V., Symbiosis Centre for Management and Human Resource Development (SCMHRD), Symbiosis International (Deemed University), Maharashtra, Pune, India; Maheshkar C., East Nimar Education Society, Madhya Pradesh, Indore, India; Poulose J., CHRIST (Deemed to be University), Uttar Pradesh, Ghaziabad, India
-
Dublin Core
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Title
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Articles
Article
Faculty Publications -Articles
Dublin Core
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Title
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Women Entrepreneurs: A Study of Psychological Well-being and Empowerment in Indian Social Context
Subject
The topic of the resource
entrepreneurial behavior; entrepreneurship; psychological well-being; women empowerment; women entrepreneurs
Description
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Entrepreneurship is differentiated by decision-making ability, competition, economic gains, autonomy, and socioeconomic settings that provide a foundation for an individual to strive and run a venture in a highly competitive environment. In the present context, this study examines the relationship between empowerment and the psychological well-being of women entrepreneurs. This study attempted to analyze the various aspects of psychological well-being responsible for women's entrepreneurship. Exploratory design and regression analysis were used for the study. The study found that only purpose in life, personal growth and positive societal relations are significant psychological factors that influence women empowerment amongst women entrepreneurs in India. The results confirm a significant relationship between empowerment and the psychological well-being of women entrepreneurs in India. This research is apt in the present time as entrepreneurial ventures are considered to be the most critical factors that would help both urban and rural populations through the creation of jobs, rescue them from unemployment and poverty, and thereby have an impact on the development of skills, self-esteem, and self-sufficiency of women. 2023, Institute of Economic Sciences. All rights reserved.
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Sharma V.; Maheshkar C.; Poulose J.; Kapse M.; Mahajan Y.
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Journal Women's Entrepreneurship and Education, Vol-2023, No. 45750, pp. 95-121.
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Institute of Economic Sciences
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2023-01-01
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<a href="https://doi.org/10.28934/jwee23.34.pp95-121" target="_blank" rel="noreferrer noopener">https://doi.org/10.28934/jwee23.34.pp95-121</a>
<br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85179318717&doi=10.28934%2Fjwee23.34.pp95-121&partnerID=40&md5=1ace4e112504eb8650c5d8466de8a478" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85179318717&doi=10.28934%2fjwee23.34.pp95-121&partnerID=40&md5=1ace4e112504eb8650c5d8466de8a478</a>
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All Open Access; Gold Open Access
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ISSN: 18211283
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Online
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English
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Article
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Sharma V., Symbiosis International University, Symbiosis Center for Management Human Resource Development (SCMHRD) Symbiosis InfoTech, Campus Maharashtra, India; Maheshkar C., East Nimar Education Society, Madhya Pradesh, India; Poulose J., CHRIST (Deemed to be University), School of Business Management, Uttar Pradesh, India; Kapse M., Symbiosis International University, Symbiosis Center for Management Human Resource Development (SCMHRD) Symbiosis InfoTech, Campus Maharashtra, India; Mahajan Y., Symbiosis International University, Symbiosis Center for Management Human Resource Development (SCMHRD) Symbiosis InfoTech, Campus Maharashtra, India
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Articles
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Faculty Publications -Articles
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Trusted explainable AI based implementation for detection of neurodegenerative disorders (ND)
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Artificial intelligence (AI); Explainable AI (XAI); Neurodegenerative disorders (ND); Shapely additive explanations; Trust
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The potential of explainable artificial intelligence (XAI) in detection of neurodegenerative disorders (ND) holds great promise in the field of healthcare. These diseases interfere with the daily functioning and independence of a person. The current studies lack in highlighting the aspect of explainability in their predictions and the various algorithms cannot provide any plausible explanations for their predictions making it difficult for medical professionals to place trust in their findings. Thus, the proposed framework aims to bridge this gap by exploring the development of a trustworthy framework for XAI-based ND detection, focusing on key aspects that can significantly impact its effectiveness and acceptance. The framework makes use of Trust-based SHAP (SHapley Additive exPlanations) values in classification. By computing trust values, the framework ensures more reliable predictions and increases interpretability, instilling confidence in clinicians and patients. The results show that with the inclusion of the trust-driven framework, the accuracy of the algorithm increased from 93.33% in the normal circumstances to 98.21%, highlighting the efficacy of the framework as compared to the other works. This shows that a trustworthy framework for XAI-driven ND detection can reshape care by enabling early detection, personalized treatment plans and enhancing decision-making process. Bharati Vidyapeeth's Institute of Computer Applications and Management 2024.
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Sharma V.; Midhunchakkaravarthy D.
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International Journal of Information Technology (Singapore)
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Springer Science and Business Media B.V.
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2024-01-01
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<a href="https://doi.org/10.1007/s41870-024-02254-6" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/s41870-024-02254-6</a>
<br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85212154627&doi=10.1007%2Fs41870-024-02254-6&partnerID=40&md5=5ed5a0616172b57ca114e6be7bec7e56" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85212154627&doi=10.1007%2fs41870-024-02254-6&partnerID=40&md5=5ed5a0616172b57ca114e6be7bec7e56</a>
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ISSN: 25112104
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Online
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English
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Article
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Sharma V., Department of Computer Science and Multimedia, Lincoln University College, Petaling Jaya, Malaysia, Christ University, Bengaluru, India; Midhunchakkaravarthy D., Department of Computer Science and Multimedia, Lincoln University College, Petaling Jaya, Malaysia
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Articles
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Local post-hoc interpretable machine learning model for prediction of dementia in young adults
Subject
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Artificial intelligence; Brain diseases; Classification model first; Convolutional neural network; Image segmentation techniques; U-net structure
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Dementia is still the prevailing brain disease with late diagnosis. There is a large increase in dementia disease among young adults. The major reason is over indulgence of young adults on social media resulting in denial of disease and delayed clinical diagnosis. Dementia is preventable and curable if diagnosed at an early stage, however, no attempts are being made to mitigate dementia in young adults. Today artificial intelligence (AI) based advanced technology with real-life consultations in clinical or remote setups are proved beneficial and is used to detect dementia. Most AI-based test is dependent on computer-aided diagnosis (CAD) tools and uses non-invasive imaging technology such as magnetic resonance imaging (MRI) data for disease diagnosis. In this paper, a local post-hoc interpretable machine learning (LPIML) model for prediction of dementia in young adults is proposed. The performance parameters are computed and compared based on accuracy, specificity, precision, F1 score and recall. The proposed work yields 98.87% training accuracy on original images and 99.31% training accuracy on morphologically enhanced images. The performance results are intrinsic and intuitive in learning the prediction results of individual case. The adoption of the proposed work will accelerate the diagnosis process in the era of digital healthcare. 2023 Institute of Advanced Engineering and Science. All rights reserved.
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Sharma V.; Midhunchakkaravarthy D.
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Indonesian Journal of Electrical Engineering and Computer Science, Vol-32, No. 3, pp. 1569-1579.
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Institute of Advanced Engineering and Science
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2023-01-01
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<a href="https://doi.org/10.11591/ijeecs.v32.i3.pp1569-1579" target="_blank" rel="noreferrer noopener">https://doi.org/10.11591/ijeecs.v32.i3.pp1569-1579</a>
<br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85178303803&doi=10.11591%2Fijeecs.v32.i3.pp1569-1579&partnerID=40&md5=d9bb3d9d67c60cc6ce18a61bd79e416e" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85178303803&doi=10.11591%2fijeecs.v32.i3.pp1569-1579&partnerID=40&md5=d9bb3d9d67c60cc6ce18a61bd79e416e</a>
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All Open Access; Gold Open Access
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ISSN: 25024752
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Online
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English
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Article
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Sharma V., Department of Computer Science and Multimedia, Lincoln University College, Petaling Jaya, Malaysia, Computer Science Department, CHRIST (Deemed to be University), Delhi-NCR Campus, India, Department of Computer Science and Multimedia, Lincoln University College Petaling Jaya, Selangor, Malaysia; Midhunchakkaravarthy D., Department of Computer Science and Multimedia, Lincoln University College, Petaling Jaya, Malaysia
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Conference Papers
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Title
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XGBoost Classification of XAI based LIME and SHAP for Detecting Dementia in Young Adults
Subject
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Dementia detection; Explainability; Explainable AI; LIME; SHAP
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As technology progresses on a fast pace, it is imperative that shall be used in the field of medicine for the early detection and diagnostics of dementia. Dementia affects humans by deteriorating the cognitive functions, and as such many algorithms have been used in the detection of the same but all these algorithms remain a black box to the medical fraternity which is still dubious about the nature and credibility of the prediction. To ease this issue, the use of explainable artificial intelligence has been proposed and implemented in this paper, which makes it easy to understand why and how the model is giving a particular output. In this paper the XGBoost classification algorithm has been used which give an accuracy of 93.33% and to understand these predictions, two separate algorithms namely Local Interpretable Model-agnostic Explanations (LIME) and Shapely Additive Explanations (SHAP) have been used. These algorithms are compared based on the type of explanation they provide for the same input and thus the weakness of LIME algorithm has been found out at certain intervals based on the clinically important features of the dataset. On the other hand, both the algorithms make it easy for medical practitioners to understand the dominating factors of a predicted output thereby helping to eliminate the black-box nature of dementia detection. 2023 IEEE.
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Sharma V.; Midhunchakkaravarthy D.
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2023 14th International Conference on Computing Communication and Networking Technologies, ICCCNT 2023
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Institute of Electrical and Electronics Engineers Inc.
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2023-01-01
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<a href="https://doi.org/10.1109/ICCCNT56998.2023.10307791" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ICCCNT56998.2023.10307791</a>
<br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85179852160&doi=10.1109%2FICCCNT56998.2023.10307791&partnerID=40&md5=87b2e4358280e9b3e71695349818292c" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85179852160&doi=10.1109%2fICCCNT56998.2023.10307791&partnerID=40&md5=87b2e4358280e9b3e71695349818292c</a>
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ISBN: 979-835033509-5
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Online
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English
Type
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Conference paper
Coverage
The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant
Sharma V., Lincoln University College, Department of Computer Science and Multimedia, Kuala Lumpur, Malaysia, Christ (Deemed to Be University), Delhi-NCR, India; Midhunchakkaravarthy D., Lincoln University College, Department of Computer Science and Multimedia, Kuala Lumpur, Malaysia
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The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/.
Title
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Conference Papers
Conference Paper
Faculty Publications- Conference Papers
Dublin Core
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Title
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SVM Based AutoEncoder for Detecting Dementia in Young Adults
Subject
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Dementia detection; Explainability; Explainable AI; LIME; SHAP
Description
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Dementia's impact on cognitive function necessitates timely diagnosis for effective intervention. Understanding the need for timely detection, the proposed work integrates SVM's decision boundary determination and autoencoder's noise reduction capabilities. The proposed work advances in dementia detection in young adult. Results indicate promising performance, with the model achieving high accuracy around 85.33%. The ROC curve illustrates a balanced trade-off between sensitivity and specificity, while the precision-recall curve highlights effective classification. Importantly, the model surpasses existing literature, underscoring its practical utility. While acknowledging limitations, such as parameter fine-tuning, this study lays the groundwork for refining and expanding this innovative methodology. In summary, this research contributes to the urgent field of early dementia detection, potentially transforming patient care and intervention strategies. 2023 IEEE.
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Sharma V.; Midhunchakkaravarthy D.
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Proceedings of International Conference on Contemporary Computing and Informatics, IC3I 2023, pp. 2516-2520.
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Institute of Electrical and Electronics Engineers Inc.
Date
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2023-01-01
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<a href="https://doi.org/10.1109/IC3I59117.2023.10397637" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/IC3I59117.2023.10397637</a>
<br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85185228697&doi=10.1109%2FIC3I59117.2023.10397637&partnerID=40&md5=fc8237056dcaca28249653a946f70b77" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85185228697&doi=10.1109%2fIC3I59117.2023.10397637&partnerID=40&md5=fc8237056dcaca28249653a946f70b77</a>
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ISBN: 979-835030448-0
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Online
Language
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English
Type
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Conference paper
Coverage
The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant
Sharma V., Lincoln University College, Department of Computer Science and Multimedia, Kuala Lumpur, Malaysia, CHRIST (Deemed to Be University), Delhi-NCR, India; Midhunchakkaravarthy D., Lincoln University College, Department of Computer Science and Multimedia, Kuala Lumpur, Malaysia
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Articles
Article
Faculty Publications -Articles
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A comprehensive examination of factors influencing intention to continue usage of health and fitness apps: a two-stage hybrid SEM-ML analysis
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Cognitive Psychology; Consumer Behaviour; Health and fitness applications; heath valuation; hedonic motivation; machine learning algorithms; Management of Technology & Innovation; Marketing; Production, Operations & Information Management; smart PLS-SEM; utilitarian motivation
Description
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This research developed a theoretical framework based on the uses and gratification theory to investigate the intention to continue usage of Health and Fitness Apps (HFAs). In addition, this study explored how health valuation moderates the relationship between determinants and users intention to continue usage. A total of 447 HFA users data was collected from Delhi NCR, India through a purposive sampling technique. Partial least square-structure equation modeling was used to test the role of potential predictors influencing users behavioral intention to continue. The machine learning algorithms were employed to identify the features of importance. The results revealed that system quality, networkability, recordability, and task technology fit have a positive influence on hedonic motivation and utilitarian motivation. While information quality influences hedonic motivation but does not affect utilitarian motivation. Health valuation positively moderates the relationship between information quality, system quality, and networkability to intention to continue usage. We also observed that hedonic motivation emerged as a key predictor of users intention to continue usage of HFAs. The results would possibly offer useful recommendations for HFA developers, marketers, and health policymakers. The quality of fitness apps should be the primary concern of app developers. Furthermore, gamification can be incorporated into HFAs as it may influence the users hedonic motivations. The research contributes by developing a uses and gratification theory tailored for the HFAs. Additionally, this research incorporates hedonic and utilitarian motivation as mediating variables and health valuation as a moderator. 2024 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.
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Sharma V.; Payal R.; Dutta K.; Poulose J.; Kapse M.
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Cogent Business and Management, Vol-11, No. 1
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Cogent OA
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2024-01-01
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<a href="https://doi.org/10.1080/23311975.2024.2391124" target="_blank" rel="noreferrer noopener">https://doi.org/10.1080/23311975.2024.2391124</a>
<br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85201943728&doi=10.1080%2F23311975.2024.2391124&partnerID=40&md5=ad7fe200b3ed970825bd7d792c5686bb" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85201943728&doi=10.1080%2f23311975.2024.2391124&partnerID=40&md5=ad7fe200b3ed970825bd7d792c5686bb</a>
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All Open Access; Gold Open Access
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ISSN: 23311975
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Online
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English
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Article
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Sharma V., Symbiosis Centre for Management and Human Resource Development (SCMHRD), Symbiosis International (Deemed University), Pune, India; Payal R., Institute of Management Technology, Ghaziabad, India; Dutta K., School of Entrepreneurship, Rishihood University, Delhi-NCR, India; Poulose J., School of Business and Management, CHRIST (Deemed to be University), Delhi-NCR, India; Kapse M., Symbiosis Centre for Management and Human Resource Development (SCMHRD), Symbiosis International (Deemed University), Pune, India
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Articles
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Prioritizing the Essentials: The MBA Aspirants Dilemma
Subject
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Chi-Square; Correlation; Exploratory Data Analysis; One-way ANOVA; Regression and Random Forest; t-test; Welch Test
Description
An account of the resource
Objective decision-making while choosing an appropriate college for a Master in Business Administration (MBA) is only half-done. It is critical that the student be able to find the best placement at the end of the course by acquiring the most critical skills/specializations affecting placements and involves data-driven decision-making based on past placement trends. Viti and Vania have done their preliminary selection, of ABC College for their MBA course, based on the colleges credence quality. However, they are trying to understand the key success factors (KSFs) affecting placements at ABC to focus their next two years on getting most placement-ready. Having been provided with the placement details of the outgoing batch, they are looking to analyze the data to discover the most critical parameters affecting placements. NeilsonJournals Publishing 2023.
Creator
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Sharma V.; Poulose J.; Kapse M.; Sanjeev M.A.; Mahajan Y.
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Journal of Organizational Behavior Education, Vol-16, pp. 121-126.
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NeilsonJournals Publishing
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2023-01-01
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<a href="" target="_blank" rel="noreferrer noopener"></a>
<br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85193909851&partnerID=40&md5=922a8633ae7a072e64d0dc046406901c" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85193909851&partnerID=40&md5=922a8633ae7a072e64d0dc046406901c</a>
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ISSN: 16497627
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Online
Language
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English
Type
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Article
Coverage
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Sharma V., Symbiosis Centre for Management and Human Resource Development (SCMHRD), Symbiosis International (Deemed University), Pune, India; Poulose J., School of Business and Management, CHRIST (Deemed to be University) Delhi-NCR, India; Kapse M., Symbiosis Centre for Management and Human Resource Development (SCMHRD), Symbiosis International (Deemed University), Pune, India; Sanjeev M.A., Symbiosis Centre for Management and Human Resource Development (SCMHRD), Symbiosis International (Deemed University), Pune, India; Mahajan Y., Symbiosis Centre for Management and Human Resource Development (SCMHRD), Symbiosis International (Deemed University), Pune, India
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Book Chapter
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Analytics Enabled Decision Making Tracing the Journey from Data to Decisions
Subject
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Analytics; Business analytics; Data science; Data-based decision making; Decision making; Model building
Description
An account of the resource
In the current business environment, which is greatly dynamic and competitive, business organizations are continually striving for expanding their competence and financial performance through improving almost every facet of their business--product/service quality, customer satisfaction, customer retention, productivity, line filling strategies, and others. In this sense, success and failure of organizations depend on the extent of precision of their decisions. Organizations are engaged with data to extract insights, identify trends and make decisions at different levels; and also, many of them learn how to utilize the power of data. Analytics can enable them to derive conclusions, make predictions, and ascertain actionable insights in a contextual and time-bound manner. It helps to examine data from multiple perspectives and gives visualizations by using different frameworks and platforms such as IBM Watson, Tableau, and R. The chapter presents the role of analytics in decision-making processes and assess the effectiveness of decisions upon their implementation, so the corrective measures can also be inserted. As decision making is a continuous business process, analytics accelerates it and gives organizations a pace to keep updated with changing business scenarios. Thus, this chapter presented a decision-making framework exhibiting how decision-making functions as an ongoing process. Different contexts and cases have been used to establish the relevance of each step of the framework. The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023.
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Sharma V.; Poulose J.; Maheshkar C.
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Analytics Enabled Decision Making, pp. 1-22.
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Springer Nature
Date
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2023-01-01
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<a href="https://doi.org/10.1007/978-981-19-9658-0_1" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-981-19-9658-0_1</a>
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ISBN: 978-981199658-0; 978-981199657-3
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Online
Language
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English
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Book chapter
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The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant
Sharma V., Symbiosis Centre for Management and Human Resource Development (SCMHRD), Symbiosis International (Deemed University), Pune, India; Poulose J., East Nimar Society for Education, Khandwa, India; Maheshkar C., School of Business and Management, CHRIST (Deemed to Be University), Delhi NCR, India
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Book Chapter
Book Chapter
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Title
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Detection of breast cancer in mammography images using intelligent models
Description
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Amongst the several cancer types, incidence of breast cancer is the highest in women. Breast cancer can be diagnosed and treated effectively through various screening methods and computer-aided detection systems (CADs). However, conventional computer-aided diagnosis (CAD) programs for detecting potential cancers on mammograms are lacking diagnostic accuracy and require upgradation. The advances in machine learning, particularly with the use of deep (multi-layered) convolutional neural networks, have allowed artificial intelligence to create a transformation in CAD that has improved models' prediction quality. The outline of this chapter includes a structured method for predicting presenting breast cancer stages, identification, segmentation and classification of lesions, and breast density assessment using the current technological models which includes artificial intelligence, deep learning, and machine learning. 2024, IGI Global. All rights reserved.
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Sharma V.; Rawat Y.; Surve G.; Rai R.H.
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Green AI-Powered Intelligent Systems for Disease Prognosis, pp. 241-260.
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IGI Global
Date
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2024-01-01
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<a href="https://doi.org/10.4018/979-8-3693-1243-8.ch013" target="_blank" rel="noreferrer noopener">https://doi.org/10.4018/979-8-3693-1243-8.ch013</a>
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ISBN: 979-836931244-5; 979-836931243-8
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Online
Language
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English
Type
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Book chapter
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Sharma V., Christ University, India; Rawat Y., Institute for Technology and Management, Mumbai, India; Surve G., Institute for Technology and Management, Mumbai, India; Rai R.H., Delhi Pharmaceutical Sciences and Research University, India
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Articles
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Assessing stimulusorganism responses in impulse buying among young consumers on online platforms using a hybrid BWM-ISM approach
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Bestworst method; Interpretive structural modeling; Online impulse buying behavior; Stimulusorganismresponse framework; Young consumers
Description
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With the advent of online buying habits, this study employs three stages (identify, rank, and decode relationships) approach to investigate the enablers of online impulse buying behavior (OIBB) among young consumers. First, literature review in the backdrop of stimulusorganismresponse (SOR) framework was used to identify and experts opinions were used to validate 21 enablers of OIBB. Next, hybrid multi-criteria decision-making approaches, namely the bestworst method (BWM) was used to assign weights and rank; and interpretive structural modeling (ISM) to decide mutual relationship among the top ranked enablers. Results indicate that promotion, product variety, and product quality are the top ranked enablers of OIBB among young consumers. The study develops a hierarchical model to simplify complex relationships among key enablers, clarifying impulse buying through the first-time use of the BWM-ISM approach in OIBB research. This enables marketers and e-commerce sellers to better prioritize critical enablers of OIBB. This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply 2024.
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Sharma V.; Saharan A.; Gupta H.; Drave V.A.; Singh P.
Source
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Journal of Marketing Analytics
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Palgrave Macmillan
Date
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2024-01-01
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<a href="https://doi.org/10.1057/s41270-024-00366-3" target="_blank" rel="noreferrer noopener">https://doi.org/10.1057/s41270-024-00366-3</a>
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ISSN: 20503318
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Online
Language
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English
Type
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Article
Coverage
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Sharma V., School of Business and Management, Christ University, Bengaluru, India; Saharan A., Jindal Global Business School, O.P. Jindal Global University, Sonipat-Narela Road, Near Jagdishpur Village, Sonipat, 131001, India; Gupta H., Department of Management Studies, Indian Institute of Technology, Indian School of Mines, Dhanbad, India; Drave V.A., Jindal Global Business School, O.P. Jindal Global University, Sonipat-Narela Road, Near Jagdishpur Village, Sonipat, 131001, India; Singh P., School of Business and Economics, State University of New York at Plattsburgh, 101 Broad Street, Plattsburgh, 12901, NY, United States
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Conference Papers
Conference Paper
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QSAR Approach for Drug Discovery Targeting the Glucagon Receptor Using Machine Learning
Subject
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Computational modeling; Drug Discovery; Glucagon receptor; Ligand efficiency; Machine Learning; QSAR
Description
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Metabolic disorders like type 2 diabetes are increasing day by day so the study focusing drug discovery of glucagon receptor has become important.One of the method to study the binding strength between chemical compounds is Quantitative Structure-Activity Relationship (QSAR) which is discussed in this paper.We gathered a curated dataset of glucagon receptor ligands from the ChEMBL bio activity dataset and studied the physical and chemical properties of the molecules using factors like molecular weight and logarithm of the partition coefficient.Then Random forest regression model was applied for prediction of the binding strength of ligands. The efficiency information of ligand was extracted which contributed to study of the molecular features concerning the activity of glucagon receptor in a much easier manner. These findings highlight the potential of QSAR in elucidating the key determinants of ligated-receptor interactions and guiding the rational design of novel glucagon receptor modulators. The integration of computational approaches with experimental validation holds promise for accelerating the development of effective therapies for metabolic disorders, addressing unmet clinical needs in this field. 2023 IEEE.
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Sharma V.; Sarkar O.; Mishra S.; Sinha S.
Source
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2023 10th IEEE Uttar Pradesh Section International Conference on Electrical, Electronics and Computer Engineering, UPCON 2023, pp. 702-706.
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Institute of Electrical and Electronics Engineers Inc.
Date
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2023-01-01
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<a href="https://doi.org/10.1109/UPCON59197.2023.10434543" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/UPCON59197.2023.10434543</a>
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ISBN: 979-835038247-1
Format
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Online
Language
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English
Type
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Conference paper
Coverage
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Sharma V., Christ (Deemed to Be University), Delhi NCR, India; Sarkar O., Kalinga Institute of Industrial Technology, Deemed to Be University, India; Mishra S., Kalinga Institute of Industrial Technology, Deemed to Be University, India; Sinha S., Kalinga Institute of Industrial Technology, Deemed to Be University, India