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1 – 4 of 4Integrating the Chat Generative Pre-Trained Transformer-type (ChatGPT-type) model with government services has great development prospects. Applying this model improves service…
Abstract
Purpose
Integrating the Chat Generative Pre-Trained Transformer-type (ChatGPT-type) model with government services has great development prospects. Applying this model improves service efficiency but has certain risks, thus having a dual impact on the public. For a responsible and democratic government, it is necessary to fully understand the factors influencing public acceptance and their causal relationships to truly encourage the public to accept and use government ChatGPT-type services.
Design/methodology/approach
This study used the Latent Dirichlet allocation (LDA) model to analyze comment texts and summarize 15 factors that affect public acceptance. Multiple-related matrices were established using the grey decision-making trial and evaluation laboratory (grey-DEMATEL) method to reveal causal relationships among factors. From the two opposite extraction rules of result priority and cause priority, the authors obtained an antagonistic topological model with comprehensive influence values using the total adversarial interpretive structure model (TAISM).
Findings
Fifteen factors were categorized in terms of cause and effect, and the antagonistic topological model with comprehensive influence values was also analyzed. The analysis showed that perceived risk, trust and meeting demand were the three most critical factors of public acceptance. Meanwhile, perceived risk and trust directly affected public acceptance and were affected by other factors. Supervision and accountability had the highest driving power and acted as the causal factor to influence other factors.
Originality/value
This study identified the factors affecting public acceptance of integrating the ChatGPT-type model with government services. It analyzed the relationship between the factors to provide a reference for decision-makers. This study introduced TAISM to form the LDA-grey-DEMATEL-TAISM method to provide an analytical paradigm for studying similar influencing factors.
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Muhammad Saleem Sumbal and Quratulain Amber
Generative AI and more specifically ChatGPT has brought a revolution in the lives of people by providing them with required knowledge that it has learnt from an exponentially…
Abstract
Purpose
Generative AI and more specifically ChatGPT has brought a revolution in the lives of people by providing them with required knowledge that it has learnt from an exponentially large knowledge base. In this viewpoint, we are initiating the debate and offer the first step towards Generative AI based knowledge management systems in organizations.
Design/methodology/approach
This study is a viewpoint and develops a conceptual foundation using existing literature on how ChatGPT can enhance the KM capability based on Nonaka’s SECI model. It further supports the concept by collecting data from a public sector univesity in Hong Kong to strenghten our argument of ChatGPT mediated knowledge management system.
Findings
We posit that all four processes, that is Socialization, Externalization, Combination and Internalization can significantly improve when integrated with ChatGPT. ChatGPT users are, in general, satisfied with the use of ChatGPT being capable of facilitating knowledge generation and flow in organizations.
Research limitations/implications
The study provides a conceptual foundation to further the knowledge on how ChatGPT can be integrated within organizations to enhance the knowledge management capability of organizations. Further, it develops an understanding on how managers and executives can use ChatGPT for effective knowledge management through improving the four processes of Nonaka’s SECI model.
Originality/value
This is one of the earliest studies on the linkage of knowledge management with ChatGPT and lays a foundation for ChatGPT mediated knowledge management system in organizations.
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They build on last year’s rules on ‘deep synthesis’ (or ‘deepfake’) content and long-established rules on online content management. While Chinese tech majors such as Baidu and…
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DOI: 10.1108/OXAN-DB278369
ISSN: 2633-304X
Keywords
Geographic
Topical
Yogesh K. Dwivedi, Neeraj Pandey, Wendy Currie and Adrian Micu
The hospitality and tourism sector has witnessed phenomenal growth in customer numbers during the postpandemic times. This growth has been accompanied by the use of technologies…
Abstract
Purpose
The hospitality and tourism sector has witnessed phenomenal growth in customer numbers during the postpandemic times. This growth has been accompanied by the use of technologies in customer interface and backend activities, including the adoption of self-serving technologies. This study aims to analyze the existing practices and challenges and establish a research agenda for the implementation of generative artificial intelligence (AI) (such as ChatGPT) and similar tools in the hospitality and tourism industry.
Design/methodology/approach
This study analyzes the existing literature and practices. This study draws upon these practices to outline a novel research agenda for scholars and practitioners working in this domain.
Findings
The integration of generative AI technologies, such as ChatGPT, will have a transformational impact on the hospitality and tourism industry. This study highlights the potential challenges of implementing such technologies from the perspectives of companies, customers and regulators.
Research limitations/implications
This study serves as a reference material for those who are planning to use generative AI tools like ChatGPT in their hospitality and tourism businesses. This study also highlights potential pitfalls that ChatGPT-enabled systems may encounter during service delivery processes.
Originality/value
This study is a pioneering work that assesses the applications of ChatGPT in the hospitality and tourism industry. This study highlights the potential and challenges in implementing ChatGPT within the hospitality and tourism industry.
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