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http://dspace.aiub.edu:8080/jspui/handle/123456789/772
Title: | Prospects of No-Code and Low-Code Artificial Intelligence Technologies |
Authors: | Mehzabul Hoque Nahid |
Keywords: | SEO |
Issue Date: | Mar-2022 |
Publisher: | American International University-Bangladesh (AIUB) |
Abstract: | The aim of this study is to conduct a thematic analysis in order to investigate and characterize the evolution of business process automation in the tourist and hospitality industries enabled by artificial intelligence. As adoption of AI technologies in the tourism industry is still in its infancy, it is critical to have a conceptual framework for understanding the processes, opportunities, and constraints in a structured manner. Online databases such as news articles, blogs, google scholar and research databases are used to gather data for qualitative desktop research. Qualitative analysis was then performed by grouping literatures into distinct themes and examining the conceptual or empirical links between those topics and AI-in business operations. The study then incorporated the results of the thematic analysis to provide recommendations for further research. According to the literature assessment, five distinct themes are revealed. There is a dearth of research on how tourism businesses can extract value through the use of AI-powered technologies to automate repetitive, multistep business transactions such as chatbots, frictionless booking processes, augmented reality, smart baggage handling, flight forecasting, prediction analysis, hyperdynamic pricing, data analytics to uncover valuable insights, robots and voice assistants, dynamic price tracking, smart translations, voice assistant, facia. The purpose of this study is to contribute to the filtering of the digital transformation literature through a thematic review and careful classification of various themes, to clarify the complex relationship between organisational digital transformations, and to identify critical blind spots in tourism and hospitality businesses. |
URI: | http://dspace.aiub.edu:8080/jspui/handle/123456789/772 |
Appears in Collections: | Publications From FBA : Conference |
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