Adoption of AI-based chatbots for hospitality and tourism

被引:312
|
作者
Pillai, Rajasshrie [1 ]
Sivathanu, Brijesh [2 ]
机构
[1] Pune Inst Business Management, Dept Management, Pune, Maharashtra, India
[2] Sri Balaji Univ, Dept Management, Pune, Maharashtra, India
关键词
AI-based chatbots; Anthropomorphism; Mixed method; Perceived trust; Perceived intelligence; PLS-SEM; TAM; WORD-OF-MOUTH; TECHNOLOGY ACCEPTANCE; PERCEIVED SAFETY; USER ACCEPTANCE; SOCIAL MEDIA; BIG DATA; SERVICE; ROBOT; TRUST; DETERMINANTS;
D O I
10.1108/IJCHM-04-2020-0259
中图分类号
F [经济];
学科分类号
02 ;
摘要
Purpose This study aims to investigate the customers' behavioral intention and actual usage (AUE) of artificial intelligence (AI)-powered chatbots for hospitality and tourism in India by extending the technology adoption model (TAM) with context-specific variables. Design/methodology/approach To understand the customers' behavioral intention and AUE of AI-powered chatbots for tourism, the mixed-method design was used whereby qualitative and quantitative techniques were combined. A total of 36 senior managers and executives from the travel agencies were interviewed and the analysis of interview data was done using NVivo 8.0 software. A total of 1,480 customers were surveyed and the partial least squares structural equation modeling technique was used for data analysis. Findings As per the results, the predictors of chatbot adoption intention (AIN) are perceived ease of use, perceived usefulness, perceived trust (PTR), perceived intelligence (PNT) and anthropomorphism (ANM). Technological anxiety (TXN) does not influence the chatbot AIN. Stickiness to traditional human travel agents negatively moderates the relation of AIN and AUE of chatbots in tourism and provides deeper insights into manager's commitment to providing travel planning services using AI-based chatbots. Practical implications This research presents unique practical insights to the practitioners, managers and executives in the tourism industry, system designers and developers of AI-based chatbot technologies to understand the antecedents of chatbot adoption by travelers. TXN is a vital concern for the customers; so, designers and developers should ensure that chatbots are easily accessible, have a user-friendly interface, be more human-like and communicate in various native languages with the customers. Originality/value This study contributes theoretically by extending the TAM to provide better explanatory power with human-robot interaction context-specific constructs - PTR, PNT, ANM and TXN - to examine the customers' chatbot AIN. This is the first step in the direction to empirically test and validate a theoretical model for chatbots' adoption and usage, which is a disruptive technology in the hospitality and tourism sector in an emerging economy such as India.
引用
收藏
页码:3199 / 3226
页数:28
相关论文
共 50 条
  • [1] AI-Generated Future: What Awaits Tourism and Hospitality with AI-Based Deep Learning Technologies?
    Collins, Ayse
    Ali, Seyid Amjad
    Yilmaz, Semih
    [J]. INFORMATION AND COMMUNICATION TECHNOLOGIES IN TOURISM 2024, ENTER 2024, 2024, : 35 - 39
  • [2] (Why) Do We Trust AI?: A Case of AI-based Health Chatbots
    Prakash, Ashish Viswanath
    Das, Saini
    [J]. AUSTRALASIAN JOURNAL OF INFORMATION SYSTEMS, 2024, 28
  • [3] (Why) Do We Trust AI?: A Case of AI-based Health Chatbots
    Prakash, Ashish Viswanath
    Das, Saini
    [J]. AUSTRALASIAN JOURNAL OF INFORMATION SYSTEMS, 2024, 28
  • [4] AI-based chatbots in customer service and their effects on user compliance
    Adam, Martin
    Wessel, Michael
    Benlian, Alexander
    [J]. ELECTRONIC MARKETS, 2021, 31 (02) : 427 - 445
  • [5] AI-based chatbots in customer service and their effects on user compliance
    Martin Adam
    Michael Wessel
    Alexander Benlian
    [J]. Electronic Markets, 2021, 31 : 427 - 445
  • [6] Determinants and consequences of trust in AI-based customer service chatbots
    Prakash, Ashish Viswanath
    Joshi, Arun
    Nim, Shubhi
    Das, Saini
    [J]. SERVICE INDUSTRIES JOURNAL, 2023, 43 (9-10): : 642 - 675
  • [7] Conversational AI chatbots as counselors for hospitality employees
    Wang, Yao-Chin
    Chi, Oscar Hengxuan
    Saito, Hiroaki
    Lu, Yue
    [J]. INTERNATIONAL JOURNAL OF HOSPITALITY MANAGEMENT, 2024, 122
  • [8] Ai-based counterfactual reasoning for tourism research
    Xia, Haiyang
    Muskat, Birgit
    Li, Gang
    Prayag, Girish
    [J]. ANNALS OF TOURISM RESEARCH, 2023, 101
  • [9] Modeling users' satisfaction and visit intention using AI-based chatbots
    Orden-Mejia, Miguel
    Carvache-Franco, Mauricio
    Huertas, Assumpcio
    Carvache-Franco, Orly
    Carvache-Franco, Wilmer
    [J]. PLOS ONE, 2023, 18 (09):
  • [10] AI-based chatbots in conversational commerce and their effects on product and price perceptions
    Justina Sidlauskiene
    Yannick Joye
    Vilte Auruskeviciene
    [J]. Electronic Markets, 2023, 33