Whether AI-based Chatbots Influence Destination Visit Intentions (original) (raw)
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Predicting the intentions to use chatbots for travel and tourism
Current Issues in Tourism, 2019
As with other businesses, tourist companies are taking advantage of modern technologies. Chatbots are a recent technology that hotels, travel agencies, and airline companies are adopting. Despite this industry-wide implementation, there is no evidence about the factors that explain why consumers are willing to interact with chatbots. This work proposes a model to explain chatbot usage intention. The model and its hypotheses were tested by structural equations with the PLS technique. The study was conducted on a sample of 476 individuals who had travelled on vacation in the previous 12 months. The study reveals that the intentions behind using chatbots are directly influenced by the following factors: the chatbots' expected performance, the habit of using chatbots, the hedonic component in using them, the predisposition to using self-service technologies, the social influences, and the fact that the chatbot behaves like a human. The inconvenience and problems related to communicating with the chatbot were found to have a negative influence. Lastly, the possibility that chatbots could replace jobs had a surprisingly positive influence, and not a negative one.
Chatbot recommender systems in tourism: A systematic review and a benefit-cost analysis
ACM Digital Library, 2023
This research is focused on the utilization of artificially intelligent (AI), customer service chatbots in travel, tourism and hospitality. Rigorous criteria were used to search, screen, extract and synthesize articles on conversational, automated systems. The results shed light on the most cited articles on the use of "chatbots" and "tourism" or "hospitality". The researchers scrutinize the extracted articles, synthesize the findings and outline the pros and cons of using these interactive technologies. This contribution implies that there is scope for tourism businesses to continue improving their online customer services in terms of their efficiency and responsiveness to consumers and prospects. For the time being, AI chatbots are still not in a position to replace human agents in all service interactions as they cannot resolve complex queries and complaints. However, works are in progress to improve their verbal, vocal and anthropomorphic capabilities to deliver a better consumer experience.
Current Issues in Tourism, 2023
The current research examined the link between the informativeness of tourist-chatbot interaction, destination image, and visit intention in two studies. In the first study, 111 participants were asked to interact with ChatGPT about a destination (i.e. Batumi) for 5–10 min. The conceptual model was analyzed using the Structural Equation Modelling framework. Findings suggested that the informativeness of touristchatbot interaction would increase destination image and visit intention. Destination image was also directly and positively related to visit intention. Specifically, destination image mediated the link between the informativeness of tourist-chat bot interaction and visit intention. A second study (N = 184) was conducted, in which the entire procedure was the same as the first study, to test the replicability of the current findings. Consequently, all results remained consistent with the first study. This is the first study to show the mediating role of destination image in the link between human-machine interaction and visit intention in tourism research. Thus, the findings would expand the current understanding regarding the role of human-machine interaction on attitude and behaviour.
The Evolution of Chatbots in Tourism: A Systematic Literature Review
2021
In the last decade, Information and Communication Technologies have revolutionized the tourism and hospitality sector. One of the latest innovations shaping new dynamics and fostering a remarkable behavioral change in the interaction between the service provider and the tourist is the employment of increasingly sophisticated chatbots. This work analyzes the most recent systems presented in the literature (since 2016) investigated via 12 research questions. The often appreciated quick evolution of such solutions is the primary outcome. However, such technological and financial fast-pace requires continuous investments, upskilling, and system innovation to tackle the eTourism challenges, which are shifting towards new dimensions.
Chatbot Adoption in Tourism Services: A Conceptual Exploration
Robots, Artificial Intelligence, and Service Automation in Travel, Tourism and Hospitality
To explore chatbots' online conversation processing Experimental Communication The realization that their conversational partners were not human beings did not affect participants. Additionally, chatbots can progress through different chat topics without getting stuck.
Journal of Tourism Futures
PurposeThe tourism and hospitality sectors are experiencing radical innovation boosted by the advancements in Information and Communication Technologies. Increasingly sophisticated chatbots are introducing novel approaches, re-shaping the dynamics among tourists and service providers, and fostering a remarkable behavioral change in the overall sector. Therefore, the objective of this paper is two-folded: (1) to highlight the academic and industrial standing points with respect to the current chatbots designed/deployed in the tourism sector and (2) to develop a proof-of-concept embodying the most prominent opportunities in the tourism sector.Design/methodology/approachThis work elaborates on the outcomes of a Systematic Literature Review (SLR) and a Focus Group (FG) composed of experts from the tourism industry. Moreover, it presents a proof-of-concept relying on the outcomes obtained from both SLR and FG. Eventually, the proof-of-concept has been tested with experts and practitioner...
The role of chatterbots in enhancing tourism: a case study of Penang tourism spots
IAES International Journal of Artificial Intelligence (IJ-AI), 2020
Chatterbots have been widely used as a tool for conversational booking assistance mainly for hotels such as the Expedia. This paper extends the use of chatterbot beyond booking by presenting the proof of concept of a chatterbot expert system called the VIZARD. The proposed VIZARD is developed using an expert system shell called verbot. The core of Vertbot 5 is the natural language processing (NLP) engine based on pattern matching. The core Verbot 5 engine is responsible for finding matches to a given user input string and firing the appropriate rule. The findings from the user acceptance test concluded that majority of the respondents agreed that the VIZARD expert system stands at an unbiased state while being more aligned on supporting the usefulness of the system.
Buhalis, D., and Cheng, E., 2020, Exploring the Use of Chatbots in Hotels: Technology Providers’ Perspective Exploring the Use of Chatbots in Hotels: Technology Providers’ Perspective. In: Neidhardt J., Wörndl W. (eds) Information and Communication Technologies in Tourism 2020. Springer, Cham. pp.231-242 https://doi.org/10.1007/978-3-030-36737-4\_26 Virtual assistants, also known as chatbot technology is getting more prominent and is applied widely in many industries. The use of chatbots, advantages, disadvantages, and future implication should be further understood; particularly from a technology provider' perspective. Previous studies, specialised in the hospitality context, focused solely on user's perspective. They have widely neglected the expert's point of view, which creates a gap in literature on the understanding of chatbot implications. The purpose of this study is to explore the use of chatbots in hotels by conducting semi-structured interviews with industry experts (technology providers). This study explores the use of chatbots and the key value the offer through interviews with chatbot experts. The findings show that the use of chatbots receive positive feedback and the benefits of chatbots outweigh the challenges. This will lead to further deployment of chatbot in the industry and the need to develop their abilities in order to achieve their full potential.
Tércio Pereira, P. Limberger, F. Minasi S. M. Buhalis, D., (2023): New Insights into Consumers’ Intention to Continue Using Chatbots in the Tourism Context, Journal of Quality Assurance in Hospitality & Tourism, https://doi.org/10.1080/1528008X.2022.2136817 Several industries recognize the potential of Artificial Intelligence to complete tasks. However, there is limited research on chatbots, and a gap in the research on what factors contribute to consumers' intention to continue using them. This research aims to analyze the relationship of the TAM and ISS dimensions, continuing to use satisfaction and brand attachment as mediators, and using the need for interaction with the employee as a moderating dimension. The results indicated that the role of brand attachment increases the model's explanatory power, and the need for interaction with the employee positively favors the relationship between brand attachment and satisfaction.
Bridging the Gap: Fine-Tuning Artificial Intelligence (AI) Chatbots for Tourism
MTCON'24 Proceedings, 2024
Generative pre-trained transformers (GPTs) are subsets of large language models (LLMs) that are designed to understand, generate and interact with human language (ChatGPT). GPTs are trained with vast amounts of data in order to answer queries in a human-like manner. As a member of the broader GPT family, OpenAIs ChatGPT is regarded as a game changer artificial intelligence (AI) chatbot because it allowed public to access LLMs complex world in a user-friendly way (Dai et al., 2023). Users of ChatGPT can easily handle queries such as domain-specific questions, content generation, statistical analyses, language-based corrections (Ali, 2024), thus, it provides useful tools for customer services in diverse businesses (Nah et al., 2023). ChatGPT has promising opportunities for tourism & travel industry in terms of dealing with guest services, automating specific tasks, facilitating more dynamic social media, increasing the efficiency of the staff, fostering marketing activities, enhancing travel-related decision making, therefore tailoring a better guest experience (Carvalho & Ivanov, 2023; Wong et al., 2023). AI chatbots have also raised the interest of tourism & hospitality academia due to their potential benefits (Cai et al., 2022; Rather, 2024; Tosun et al., 2024; Gursoy et al., 2023; Pillai and Sivathanu, 2020; Wong et al., 2023). Despite the advancements in natural language processing (NLP), chatbots still struggle with some conversational abilities while interacting with its users (Hosseini, 2020). There could be problematic issues such as (1) generation of non-sensical or misleading content by the chatbot which is called hallucination, (2) insufficiency or lowquality of training data, (3) difficulties regarding the update of real- time data (Nah et al., 2023; Gursoy et al., 2023). In addition to these, GPT-4, which is the most advanced and recent language model of ChatGPT has a data cut-off date of April 2023 (ChatGPT), which indicates that the language model has been trained at the very latest at that time. For these reasons, Hsu et al. (2024) called for a tourismspecific generative AI concept according to the industry needs. They advise that LLMs could be trained specifically with domain-specific, trustful tourism data. Because these LLMs are pre-trained models, fine-tuning them with up-to-date data might be useful and beneficial (Hsu et al., 2024; Dai et al., 2023; Brown et al., 2020). Fine-tuning allows users to feed their language model periodically to keep it up-todate and train them with context specific data. By doing so, pre-trained LLMs will act more accurately for tourism-specific contexts in which ChatGPT exhibits deficient or false responses. One of the most attractive tourism-specific contexts that requires domain-specific data could be regarded as enotourism (wine tourism), which is progressively growing in Türkiye. Türkiye stands as fifth in grape production worldwide, processing 4.2 million tons of grapes (in 2022), thereby reaching a level of 62.2 billion liters of total wine production yearly (in 2022) (OIV, 2022a: 5,7; https://www.oiv.int/what-we-do/data-discovery-report?oiv). Historically, Anatolias organized wine production could be dated back to 4000 BC (McGovern et al., 2017; Gürsoy, 2021: 15). Therefore, grape cultivation and wine production was always an important cultural heritage aspect of Anatolia, which makes Türkiye to be able to produce unique types of wine-grapes nowadays. This leads to the research question of this study. Although there is sufficient information about recognised Anatolian wine-grapes such as Boğazkere, Öküzgözü, and Çalkarası, relatively lesser-known and indigenous grapes that are grown in specific local-regions often lack comprehensive and accurate information. Preliminary search revealed that this information lacks in both online search engines and ChatGPTs (and other AI Chatbots) latest versions. ChatGPT provides erroneous and misleading results about indigenous grapes, thus requires a proper fine-tuning with reliable data. This researchs objective is to develop a fine-tuned AI chatbot to answer users and potential tourists queries. Proper fine-tuning was aimed to train the chatbot, so the necessary text-data to be trained was decided. Mardin and Şırnak regions located in southeastern Turkiye host unique grape types that are known as Syriac (or Assyrian) wine- 129 grapes. Data about these indigenous wine-grapes (called Mazrona and Kerküş)-which are being used to produce the famous Syriac wine (a unique cultural heritage value for Turkiyes enotourism), was obtained. Then these steps were followed, respectively: - An assistant API was generated from openAIs platform - In order to fine‐tune the data, openAIs guidelines were followed (https://platform.openai.com/docs/guides/fine‐ tuning) - For assistant preference, OpenAIs recommendation was compiled (gpt‐3.5‐turbo‐0125) - Appropriate fine‐tuning data was obtained from a licensed local (Syriac/Mardin) tourist guide - json, jsonl, docx, pdf and txt types of data were used during testing process - Code interpreter and retrieval options were tested separately As a result of the fine-tuning process, the txt document type was found to be the most effective training data for chatbot. It gave the most human-like and appropriate answers regarding the specific Syriac wine-grape queries. The trained assistants’ responses were superior to base (untrained) ChatGPT 3.5/4. Besides, base ChatGPT displays misleading or deficient answers to questions, and were prone to hallucination. Consequently, while AI chatbots are powerful tools for tourism, their effectiveness is limited regarding local heritage, culture or custom-specific queries, unless they have been specifically trained by tourism professionals (Hsu et al., 2024; Wong et al., 2023). The tourism and travel industry has many diverse subsets to be trained, offering unique fine-tuning opportunities. Therefore, the context of this research should be extended to niche domains of tourism such as local cuisines, cultural routes, alternative types of tourism and historical & archeological heritage.