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postgraduate thesis: The impact of human-machine coexistence on employee performance in labor-intensive industries : evidence from an online real estate platform

TitleThe impact of human-machine coexistence on employee performance in labor-intensive industries : evidence from an online real estate platform
Authors
Issue Date2025
PublisherThe University of Hong Kong (Pokfulam, Hong Kong)
Citation
Zhao, T. [趙彤陽]. (2025). The impact of human-machine coexistence on employee performance in labor-intensive industries : evidence from an online real estate platform. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR.
AbstractAs artificial intelligence (AI) applications proliferate across industries, they introduce significant changes to operational processes and customer interactions. Across sectors ranging from healthcare to finance, AI tools enhance operational efficiency, enable personalized experiences, and transform service delivery methods. In the real estate sector, where timely and accurate information exchange is essential, AI technologies, particularly AI-generated videos and AI-driven chatbots, have gained increasing prominence. This dissertation examines the influence of these AI applications on agent performance within an online real estate platform and investigates the underlying mechanisms from both consumer and agent perspectives. The research comprises two primary studies. The first study examines the impact of AI-generated videos on consumer engagement. The findings indicate that these videos reduce the probability of consumers initiating conversations with sales agents, particularly for less desirable property listings. Furthermore, AI videos encourage consumers to provide contact information more readily, with this effect being more pronounced for attractive properties. The comprehensive information integration in AI videos affects sales agents' online service provision, resulting in decreased online presence and slower response times. This creates a disconnect between consumers' desire for immediate interaction and agents' perception of AI videos as service substitutes. The second study evaluates the direct and indirect effects of an AI-driven chatbot on sales agents' consumer interactions. The chatbot implementation improves overall agent performance through increased consumer-initiated chats, higher response rates, and conversion rates comparable to human agents. However, the study also reveals a negative indirect effect: agents who frequently utilize the chatbot experience diminished chat volumes and lower conversion rates. This adverse outcome stems from self-selection bias among consistent chatbot users. Through a comprehensive analysis of these studies, we gain a deeper understanding of the multifaceted roles that artificial intelligence tools play in revolutionizing the way consumers and real estate agents interact. These studies collectively highlight the transformative potential of AI, demonstrating how it can reshape the dynamics of the real estate sector. The insights derived from these research endeavors underscore the significance of strategically deploying AI technologies within the industry. By doing so, it is possible to achieve a delicate balance between leveraging the benefits of automation and artificial intelligence, on one hand, and preserving the irreplaceable value of personalized, high-quality service on the other. The strategic implementation of AI solutions not only enhances consumer engagement but also boosts agent efficiency, leading to a more streamlined and effective real estate transaction process.
DegreeDoctor of Business Administration
SubjectArtificial intelligence - Economic aspects
Real estate business - Data processing
Real estate agents - Effect of technological innovations on
Dept/ProgramBusiness Administration
Persistent Identifierhttp://hdl.handle.net/10722/368501

 

DC FieldValueLanguage
dc.contributor.authorZhao, Tongyang-
dc.contributor.author趙彤陽-
dc.date.accessioned2026-01-12T01:21:02Z-
dc.date.available2026-01-12T01:21:02Z-
dc.date.issued2025-
dc.identifier.citationZhao, T. [趙彤陽]. (2025). The impact of human-machine coexistence on employee performance in labor-intensive industries : evidence from an online real estate platform. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR.-
dc.identifier.urihttp://hdl.handle.net/10722/368501-
dc.description.abstractAs artificial intelligence (AI) applications proliferate across industries, they introduce significant changes to operational processes and customer interactions. Across sectors ranging from healthcare to finance, AI tools enhance operational efficiency, enable personalized experiences, and transform service delivery methods. In the real estate sector, where timely and accurate information exchange is essential, AI technologies, particularly AI-generated videos and AI-driven chatbots, have gained increasing prominence. This dissertation examines the influence of these AI applications on agent performance within an online real estate platform and investigates the underlying mechanisms from both consumer and agent perspectives. The research comprises two primary studies. The first study examines the impact of AI-generated videos on consumer engagement. The findings indicate that these videos reduce the probability of consumers initiating conversations with sales agents, particularly for less desirable property listings. Furthermore, AI videos encourage consumers to provide contact information more readily, with this effect being more pronounced for attractive properties. The comprehensive information integration in AI videos affects sales agents' online service provision, resulting in decreased online presence and slower response times. This creates a disconnect between consumers' desire for immediate interaction and agents' perception of AI videos as service substitutes. The second study evaluates the direct and indirect effects of an AI-driven chatbot on sales agents' consumer interactions. The chatbot implementation improves overall agent performance through increased consumer-initiated chats, higher response rates, and conversion rates comparable to human agents. However, the study also reveals a negative indirect effect: agents who frequently utilize the chatbot experience diminished chat volumes and lower conversion rates. This adverse outcome stems from self-selection bias among consistent chatbot users. Through a comprehensive analysis of these studies, we gain a deeper understanding of the multifaceted roles that artificial intelligence tools play in revolutionizing the way consumers and real estate agents interact. These studies collectively highlight the transformative potential of AI, demonstrating how it can reshape the dynamics of the real estate sector. The insights derived from these research endeavors underscore the significance of strategically deploying AI technologies within the industry. By doing so, it is possible to achieve a delicate balance between leveraging the benefits of automation and artificial intelligence, on one hand, and preserving the irreplaceable value of personalized, high-quality service on the other. The strategic implementation of AI solutions not only enhances consumer engagement but also boosts agent efficiency, leading to a more streamlined and effective real estate transaction process. -
dc.languageeng-
dc.publisherThe University of Hong Kong (Pokfulam, Hong Kong)-
dc.relation.ispartofHKU Theses Online (HKUTO)-
dc.rightsThe author retains all proprietary rights, (such as patent rights) and the right to use in future works.-
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.-
dc.subject.lcshArtificial intelligence - Economic aspects-
dc.subject.lcshReal estate business - Data processing-
dc.subject.lcshReal estate agents - Effect of technological innovations on-
dc.titleThe impact of human-machine coexistence on employee performance in labor-intensive industries : evidence from an online real estate platform-
dc.typePG_Thesis-
dc.description.thesisnameDoctor of Business Administration-
dc.description.thesislevelDoctoral-
dc.description.thesisdisciplineBusiness Administration-
dc.description.naturepublished_or_final_version-
dc.date.hkucongregation2025-
dc.identifier.mmsid991045141653503414-

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