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ChatGPT for tourism: applications, benefits and risks
2023 - Carvalho, Inês; Ivanov, Stanislav
Purpose: The rapid growth of artificial intelligence is disrupting various industries, including the tourism sector. This paper aims to outline the applications, benefits and risks of ChatGPT and large language models in general on tourism. It also aims to establish a research agenda for investigating the implications of these models in tourism. Design/methodology/approach: Drawing on the available literature on ChatGPT, large language models and artificial intelligence, the paper identifies areas of application of ChatGPT for several tourism stakeholders. Potential benefits and risks are then considered. Findings: ChatGPT and other similar models are likely to have a profound impact on several tourism processes. They will contribute to further streamline customer service in front-of-house operations and increase productivity and efficiency in back-of-house operations. Although negative consequences for human resources are expected, this technology mostly enhances tourism employees. Originality/value: To the best of the authors’ knowledge, this is one of the first studies that explore the potential implications of ChatGPT in tourism and hospitality.
Cultural Differences, Risk and Tourism: A Literature Review
2023 - Carvalho, Inês; Moraes, Michelle
Cultural differences are often important motivators for tourism, but they may also be associated with increased risk perceptions. Different cultures may also perceive risk differently. Despite the importance of this topic for tourism research, few studies have aimed to systematize literature on cultural differences, tourism and risk. Therefore, the main goal of the present chapter is to elaborate a bibliometric analysis of this literature, more specifically, to quantify its sources and clusters of co-citation and terms. To achieve this goal, the publications indexed in Web of Science with the terms cultural differences and tourism (242) are analysed using VOSviewer. A qualitative analysis of the studies which focus specifically on risk is also performed.
Socio-demographic correlates of energy concern and smart-home engagement: A MIMIC analysis from Guangdong, China
2026 - Cheng, Nankai; Casaca, Joaquim A.; Ayanoğlu, Hande; Gomes, Rute
Understanding the socio-demographic drivers of residential energy-saving behavior is critical for designing effective energy policies and technologies. This study applies a Multiple Indicators, Multiple Causes (MIMIC) model to examine how individual characteristics are associated with two latent constructs: energy concern and smart-home interest and usage. Using survey data collected from urban residents in Guangdong Province (N = 261), structural equation modeling was employed to assess both measurement and structural components of the model. The results show that income is positively associated with both energy concern and smart-home interest and usage, whereas being a bill payer is negatively related to both. Gender also plays a role, with females reporting higher energy concern. Other factors, such as age, education, and time spent at home, did not show significant effects. The model showed acceptable global fit indices; however, the reliability and convergent validity of the latent constructs were limited. Accordingly, the findings should be interpreted as exploratory associations observed within this sample and may serve as a basis for future research on segmentation in similar urban contexts.