04724nam a22006015i 4500 978-3-031-55615-9 DE-He213 20251030112011.0 cr nn 008mamaa 240425s2024 sz | s |||| 0|eng d 9783031556159 978-3-031-55615-9 10.1007/978-3-031-55615-9 doi HF54.5-54.56 KJQ bicssc UF bicssc BUS083000 bisacsh KJQ thema UF thema Role of Explainable Artificial Intelligence in E-Commerce [electronic resource] / edited by Loveleen Gaur, Ajith Abraham. 1st ed. 2024. Cham : Springer Nature Switzerland : Imprint: Springer, 2024. VIII, 135 p. 19 illus., 15 illus. in color. online resource. text txt rdacontent computer c rdamedia online resource cr rdacarrier text file PDF rda Studies in Computational Intelligence, 1860-9503 ; 1094 1. Introduction to XAI in E-Commerce -- 2. Explainable Artificial Intelligence (XAI) for Managing Customer Needs in E-Commerce: a Systematic Review -- 3. Decoding the Recommender System: A Comprehensive Guide to Explainable AI in E-commerce -- 4. The AI Revolution in E-Commerce: Personalization and Predictive Analytics -- 5. Impact of Artificial Intelligence on Purchase Intention: A bibliometric analysis -- 6. Chatbot-XAI – The New Age Artificial Intelligence Communication tool for E-Commerce -- 7. Demystifying Applications of Explainable Artificial Intelligence (XAI) in e-Commerce -- 8. From Algorithms to Ethics: XAI's Impact on E-Commerce. The technological boom has provided consumers with endless choices, removing the hindrance of time and place. Understanding the dynamic and competitive business environment, marketers know they need to reinforce indestructible customer experience with the support of algorithmic configurations to minimize human intrusion. World Wide Web (WWW) and online marketing have changed the way of conducting business; with artificial intelligence (AI), business houses can furnish a customized experience to fulfil the perceived expectation of the customer. Artificial intelligence bridges the gap between business and prospective clients, provides enormous amounts of information, prompts grievance redressal system, and further complements the client’s preference. The opportunities online marketing offers with the blend of artificial intelligence tools like chatbots, recommenders, virtual assistance, and interactive voice recognition create improved brand awareness, better customer relationship marketing, and personalized product modification. Explainable AI provides the subsequent arena of human–machine collaboration, which will complement and support marketers and people so that they can make better, faster, and more accurate decisions. According to PwC’s report on Explainable AI(XAI), AI will have $15.7 trillion of opportunity by 2030. However, as AI tools become more advanced, more computations are done in a “black box” that humans can hardly comprehend. But the rise of AI in business for actionable insights also poses the following questions: How can marketers know and trust the reasoning behind why an AI system is making recommendations for action? What are the root causes and steering factors? Thus, transparency, trust, and a good understanding of expected business outcomes are increasingly demanded. Business information services. Artificial intelligence. 58441 Engineering Data processing. Computational intelligence. 64052 IT in Business. Artificial Intelligence. 58441 Data Engineering. 66059 Computational Intelligence. 64052 Gaur, Loveleen. editor. edt http://id.loc.gov/vocabulary/relators/edt 74849 Abraham, Ajith. editor. edt http://id.loc.gov/vocabulary/relators/edt 74850 SpringerLink (Online service) Springer Nature eBook Printed edition: 9783031556142 Printed edition: 9783031556166 Printed edition: 9783031556173 Studies in Computational Intelligence, 1860-9503 ; 1094 68854 https://doi.org/10.1007/978-3-031-55615-9 ZDB-2-ENG ZDB-2-SXE 59382 59382