Please use this identifier to cite or link to this item: https://rfos.fon.bg.ac.rs/handle/123456789/2929
Title: Navigating the landscape: Unveiling the reflection of AI in the sharing economy through bibliometric-based approach
Authors: Uskoković, Veljko
Maričić, Milica
Dacić-Pilčević, Aleksandra
Jeremić, Veljko 
Contributors: Dlačić, Jasmina
Maradin, Dario
Keywords: artificial intelligence;sharing economy;bibliometric analysis
Issue Date: 23-Dec-2024
Publisher: SVEUČILIŠTE U RIJECI EKONOMSKI FAKULTET UNIVERSITY OF RIJEKA FACULTY OF ECONOMICS AND BUSINESS
Abstract: Recent scholarly attention has surged in integrating artificial intelligence (AI) across various scientific domains, prompting a closer examination of AI’s pervasive influence on economic paradigms like the sharing economy (SE). This study delves into the multifaceted intersections of AI within the SE, employing a bibliometric-based analytical framework. By establishing a terminological grounding in AI, the study surveys a broad spectrum of AI applications in the SE, culminating in a bibliometric analysis that identifies emerging themes and trends. Analysing literature metadata from the Web of Science database over the past eight years, the focus is on citation topics within the SE. In-depth analyses, facilitated by the Bibliometrix R package, are applied to a curated selection of papers. The
findings reveal key insights, such as how AI-driven text analytics significantly enhance customer satisfaction through user-generated reviews. Additionally, AI plays a crucial role in promoting energy-efficient behaviour in smart accommodations, while algorithmic oversight is increasingly integrated into digital labour platforms to balance automation with human dignity. Furthermore, AI optimizes resource allocation and improves matching algorithms on online labour platforms, thereby boosting platform efficiency. The study suggests future research avenues, advocating for broader exploration of AI’s role in digital economic models and greater governmental involvement
URI: https://rfos.fon.bg.ac.rs/handle/123456789/2929
ISSN: 1331-8004
Appears in Collections:Radovi istraživača / Researchers’ publications

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