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Empirically Analysing the Factors Influencing the Organization's Adoption of an AI-Based Chatbot for Air Ticket Reservation

Year: 2025

Type: article

Abstract: The aviation industry is experiencing a rapid digital transformation driven by globalization, technological advancements, and evolving customer expectations.Among these technologies, AI-based chatbots have emerged as a powerful tool to streamline operations, enhance customer service, and support internal business functions.However, their adoption in air ticket reservation services is still in its early stages.This study aims to provide innovative insights into understanding the factors that determine the adoption of AI-based chatbots for air ticket reservations from the organization's perspective.The study introduces two new constructs, diversity and sensibility, and conceptually integrates the "Technology Organization Environment" theory and the "Diffusion of Innovation" theory.Data from 154 respondents were modeled using PLS-SEM, suitable for models with many variables and small sample sizes.The finding reveals that the organization's technical capability is a key factor influencing the adoption.Diversity, referring to the chatbot's multifunctionality, promotes broader acceptance.Moreover, the impact of sensibility on adoption intention posits that a user-friendly design of the chatbot that enhances the "look" and provides a sense of human touch significantly increases the adoption intention.The relative advantage of AI-based chatbots on adoption illustrates that among all other ticket reservation channels, they prove to be the most efficient and profitable.Also, the complexity and government involvement were identified as relevant predictors of adoption.This study provides valuable insights for organizations and stakeholders and offers both theoretical and practical implications.The study concludes with limitations and proposes directions for future research.

Source: International Journal of Transport Development and Integration

DOI: 10.18280/ijtdi.090304

Authors: Sudati Kumari, Totakura Bangar Raju, Shweta Agarwal

Institutions: University of Petroleum and Energy Studies, Indian Maritime University

Language: English

Topic: Technology Adoption and User Behaviour

Subfield: Information Systems and Management

Field: Decision Sciences

Domain: Social Sciences

SDG: Industry, innovation and infrastructure

Open Access status: gold

Estimated APC paid: $950