Automation and artificial intelligence in hospitality and tourism

Jabeen, Fauzia; Zaidi, Sameera Al; Dhaheri, Maryam Hamad Al

doi:10.1108/tr-09-2019-0360

Cited by 65 publications

(48 citation statements)

References 68 publications

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“…Those tourists who intend to communicate with staff are forced to experience these smart devices, and the one-to-one service ends up being replaced by mass customised STT services. This matches Jabeen et al's (2021) research results that indicate further innovation of STTs should pay more attention to strengthening human knowledge of STTs. It will be important to make STTs for museums more available and customised to develop this part of service.…”

Section: Practical Implicationssupporting

confidence: 90%

Smart tourism technologies towards memorable experiences for museum visitors

Yang

Zhang²

2022

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Purpose This study aims to investigate the perception of smart tourism technologies (STTs) in creating museum tourism experiences and assess visitors’ intentions to test the impact, the extent and role that STTs play in museum service. Design/methodology/approach The investigation was conducted through an online and on-site survey; data were collected in four different museums with 365 museum tourists in four countries. SmartPLS (version 3.3.3) was used to access the measurement and structural model based on path modelling and bootstrapping. Findings STTs have a positive impact on creating a memorable tourism experience for museum visitors and are beneficial to revisit intention and positive recommendations. The impact is stronger than traditional services such as museum setting and staff service. STTs can be considered an independent new service to museums rather than complementing existing services. STTs negatively affect tourism’s experience at the communication stage. Originality/value Previous studies have noted the growing attention to the museum visitor experience, but the combined impact of new elements, such as STTs, remains an unexplored area. This study addressed the research gap through an empirical investigation and offers guidelines to test museum visitors’ acceptance and fitness for the services provided by STTs. In addition, this study presents a new point of view on the roles that STTs take in museum service, which can be useful for further investigations.

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Section: Practical Implicationssupporting

confidence: 90%

Smart tourism technologies towards memorable experiences for museum visitors

Yang

Zhang²

2022

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“…Likewise, consumers perceive that the excessive use of technology, particularly at the frontend, may result in a loss of empathetic listening skills from the HATS employees (Prentice et al , 2020). AIR is also being perceived as a threat to jobs and human staff, particularly unskilled or semi-skilled staff perceives technology as their replacements (Jabeen et al , 2021). Customers perceive the usage of AIR in HATS as a marketing gimmick and service automation or getting served by robots makes the service consumption fancier and costly (Tung and Au, 2018; Hou et al , 2021).…”

Section: Discussionmentioning

confidence: 99%

“…Ivanov et al (2019) scouted “robot,” “robot manufacturer,” “human,” “education, training, and research,” “external environment,” “servicescape” and “travel/tourism/hospitality company” as main themes. The second group of scholarly articles (Jabeen et al , 2021) discussed the benefits and the problems employees and institutions are witnessing due to automation and AIR. The third line of studies centered on empirical investigations regarding AIR adoption among consumers.…”

Section: Literature Reviewmentioning

confidence: 99%

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Consumers’ adoption of artificial intelligence and robotics in hospitality and tourism sector: literature review and future research agenda

Goel

Kaushik

Pillai³

et al. 2022

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Purpose The purpose of this study, a current systematic literature review, is to synthesize the extant literature on consumers’ adoption of artificial intelligence and robotics (AIR) in the context of the hospitality and tourism sector (HATS) to gain a comprehensive understanding of it. This study also outlines insights for academia, practitioners, AI marketers, developers, designers and policymakers. Design/methodology/approach This study used a content analysis approach to conduct a systematic literature review for the period of 10 years (2011–2020) of the various published studies themed around consumer’s adoption of AIR in HATS. Findings The synthesis draws upon various factors affecting the adoption of AIR, such as individual factors, service factors, technical and performance factors, social and cultural factors and infrastructural factors. Additionally, the authors identified four major barriers, namely, psychological, social, financial, technical and functional that hinder the consumer’s adoption of artificial intelligence and robots in the hospitality and tourism industry. Originality/value To the best of the author’s/authors’ knowledge, this study is a first attempt to synthesize the factors that drive consumers’ adoption of artificial intelligence and robots in the hospitality and tourism industry. The present work also advances the tourism and consumer behavior literature by offering an integrated antecedent-outcome framework. Visual abstract Figure 2 The objective of the current systematic literature review is to synthesize the extant literature on consumer’s adoption of artificial intelligence and robotics (AIR) in the context of the hospitality and tourism sector (HATS) to gain a comprehensive understanding of it. For that purpose, authors conducted content analysis of extant literature on consumer’s adoption of AIR in HATS from 2011 to 2020. Authors presented an integrated antecedent outcome framework of the factors that drive consumer’s adoption of artificial intelligence and robots in the hospitality and tourism industry.

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“…lifts, lighting, heating, ventilation and air conditioning) to collect Big Data which, in combination with historical data from databases and external real-time data, empower hotels to create tailored services and boost guest satisfaction and loyalty (Buhalis and Leung, 2018). Some examples of IoT devices in hotels include security alarms, beacons, thermostats, light switches, smart TVs, electric blinds, mobile app-driven smart room keys, smart mirrors, customisable walls and VAs (Buhalis and Leung, 2018; Car et al , 2019; Fischbach, 2019; Nadkarni et al , 2020; Jabeen et al , 2022).…”

Section: Introductionmentioning

confidence: 99%

Voice assistants in hospitality: using artificial intelligence for customer service

Buhalis

Moldavska

2021

JHTT

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Purpose Voice assistants (VAs) empower human–computer interactions by recognising human speech and implementing commands pronounced by users. This paper aims to investigate VA-enabled interactions between hotels and guests in the hospitality context. The research positions VAs within the artificial intelligence (AI)-enabled Internet of Things (IoT) context, disrupting old practices and processes. Smart hospitality uses VAs to support effortless value cocreation for guests cost-effectively. The research examines consumer perceptions and expectations of hospitality VAs and explores VA capabilities through expert technology providers. Design/methodology/approach This empirical paper investigates the current use and future implications of VAs for hotel environments. It uses qualitative, semi-structured in-depth interviews with 7 expert hospitality VA technology providers and 21 hotel guests who have VA experience. The research adopts a demand and supply approach, addressing the VAs in hospitality holistically. Findings The findings illustrate the requirements from both end-users’ sides, hotels and guests, exploring VA advantages and challenges. The analysis demonstrates that VAs increasingly become digital assistants. VA technology helps hotels to improve customer service, expand operational capability and reduce costs. Although in its infancy, VA technology has made progress towards optimising hotel operations and upgrading customer service. The study proposes a speech-enabled interactions model. Research limitations/implications This research stimulates the transformation of hospitality services by using VAs and the development of smart hospitality and tourism ecosystems. The study can benefit from further research with hotel managers, to reflect hoteliers’ points of view and investigate their perception of VAs. Further research can also explore different aspects of consumer–VA interaction in different contexts. Practical implications The paper makes a significant contribution to hospitality management and human–computer interaction best practices. It supports technology providers to reconsider how to develop suitable technology solutions towards improving their strategic competitiveness. It also explains how to use VAs cost-effectively and profitably while adding value to travellers’ experience. Originality/value VA studies are often focussed on the technology in private households, rather than in commercial or hotel spaces. This paper contributes to the emerging literature on AI and IoT in smart hospitality and explores the acceptance and operationalisation of VAs. The research contributes to the conceptualisation of VA-enabled hotel services and explores positive and negative features, as well as future prospects.

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Automation and artificial intelligence in hospitality and tourism

Cited by 65 publications

References 68 publications

Smart tourism technologies towards memorable experiences for museum visitors

Smart tourism technologies towards memorable experiences for museum visitors

Consumers’ adoption of artificial intelligence and robotics in hospitality and tourism sector: literature review and future research agenda

Voice assistants in hospitality: using artificial intelligence for customer service

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