AIRA Chatbot for Travel: Case Study of AirAsia

Kasinathan, Vinothini; Wahab, Mohd Helmy Abd; Idrus, Syed Zulkarnain Syed; Yuen, Kho Zhi

doi:10.1088/1742-6596/1529/2/022101

Cited by 12 publications

(8 citation statements)

References 7 publications

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“…Other examples are direct Figure 3 (a) AIRA responding to user's input. (b) Chatbot interface for AIRA from Kasinathan et al (2020) connections between the smart hotel rooms' amenities/services and the CB (exposing the same level of configuration); Buhalis and Yen (2020) implementation of emotions-based mechanisms to develop proactive CB; Buhalis and Yen (2020) (increasingly leveraging on AI and ML) realized trainable/trained CB to learn users' behavioral styles to be mirrored. Moreover, CB might behave according to specific styles, possibly identifying given brands (Hu et al, 2018), increase the possibly heterogeneous data-sources (e.g.…”

Section: Slr Resultsmentioning

confidence: 99%

Leveraging inter-tourists interactions via chatbots to bridge academia, tourism industries and future societies

Calvaresi

Kineber

Calbimonte

et al. 2021

JTF

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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 practitioners of the tourism sector.FindingsAmong the findings elicited by this paper, we can mention the quick evolution of chatbot-based solutions, the need for continuous investments, upskilling, system innovation to tackle the eTourism challenges and the shift toward new dimensions (i.e. tourist-to-tourist-to-chatbot and personalized multi-stakeholder systems). In particular, we focus on the need for chatbot-based activity and thematic aggregation for next-generation tourists and service providers.Originality/valueBoth academic- and industrial-centered findings have been structured and discussed to foster the practitioners' future research. Moreover, the proof-of-concept presented in the paper is the first of its kind, which raised considerable interest from both technical and business-planning perspectives.

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Section: Slr Resultsmentioning

confidence: 99%

Leveraging inter-tourists interactions via chatbots to bridge academia, tourism industries and future societies

Calvaresi

Kineber

Calbimonte

et al. 2021

JTF

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“…Table III presents publicly existing platforms in the selected articles to implement chatbots. The other research works done in [35], [36],[37], [38] develop chatbots using programming languages based on C# in Verbot 5.0, on Snatchbot, Microsoft Visual Studio linked to Google Translate API and the Twilio platform, respectively, as well as some libraries in python are used, such as ChatterBot and chatterbot_corpus.…”

Section: B Conducting the Reviewmentioning

confidence: 99%

“…Classical Arabic [73], [60], [72] Education English [117], [86], [90], [108], [118],[1 07], [45], [112], [109], [122] Classical and MSA Arabic [50], [51] MSA Arabic [54], [58], [57], [55], [52], [53], [ 67], [66], [110], [63], [65] Arabic dialects: Saudi Arabic dialect and Jordanian [77], [78] Healthcare English [41], [44], [47], [70], [49], [71], [ 119] MSA Arabic [74], [111] Arabic Dialects: Egyptian [100] Tourism and airline English [35], [43] MSA Arabic [59], [75], [46], [113], [115] Business and customer service English [87], [69], [121],…”

Section: Religionmentioning

confidence: 99%

English and Arabic Chatbots: A Systematic Literature Review

Alsheddi¹,

Alhenaki²

2022

IJACSA

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In recent years, the availability of chatbot applications has increased substantially with the advancement of artificial intelligence techniques, and research efforts have been active in the English language, which presents state-of-the-art solutions. However, despite the popularity of the Arabic language, its research community is still in an immature stage. Therefore, the main objective of this systematic literature review is studying state-of-the-art researchfor both the English and Arabic languagesto answer the proposed research questions regarding the development approaches, application domains, evaluation metrics, and development challenges of chatbot applications. The findings show that researchers have devoted more attention to the education domain using retrieval-based approaches while the generation-based approach has grown in popularity recently for providing new responses tasks. Whereas the hybrid approach for ranking multi-possible responses of combining both previous approaches shows a performance improvement. Besides, most metrics used to evaluate chatbot performance are human-based, followed by bilingual evaluation understudy and accuracy metrics. However, defining a common framework for evaluating chatbots remains a challenge. Finally, the open problems and future directions are highlighted to help in developing chatbots with minimal human interference to simulate natural conversations.

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“…In general, chatbot interfaces are just composed of the chat showing the messages exchanged and the keyboard or the interaction menu prizing simplicity and efficiency. Nevertheless, a few applications opted for dedicating an important portion of the screen/window to the profile picture (i.e., a cartoonized icon of a flight assistant [23]).…”

Section: Srq7: Services Realizedmentioning

confidence: 99%

The Evolution of Chatbots in Tourism: A Systematic Literature Review

Calvaresi

Kineber

Calbimonte

et al. 2021

Information and Communication Technologies in Tourism 2021

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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.

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AIRA Chatbot for Travel: Case Study of AirAsia

Cited by 12 publications

References 7 publications

Leveraging inter-tourists interactions via chatbots to bridge academia, tourism industries and future societies

Leveraging inter-tourists interactions via chatbots to bridge academia, tourism industries and future societies

English and Arabic Chatbots: A Systematic Literature Review

The Evolution of Chatbots in Tourism: A Systematic Literature Review

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