Scopus: Could AI technologies be harnessed to break down barriers to inclusivity for women entrepreneurship in tourism?
Program
KU Authors
KU-Authors
Co-Authors
Advisor
Date
Language
Type
Journal Title
Journal ISSN
Volume Title
Abstract
Despite growing scholarly attention to artificial intelligence (AI) and gender-related challenges in tourism research, a void exists in how the responsible AI could be harnessed to enhance women's inclusivity in tourism entrepreneurship. Drawing on Rawls’ theory of justice, this study aims to fill this glaring gap by exploring whether and how AI could contribute to fostering a more equitable, inclusive and ethically responsible entrepreneurial ecosystem for women, help break down existing barriers, and thus, support women's entrepreneurial endeavors in the tourism sector. Based on qualitative data collected from semi-structured interviews and focus group discussions with elite informants, the study highlights significant positive externalities of AI technologies adoption, beyond the generally recognized benefits in customer engagement and personalized offerings, efficiency, and overall performance, to help female entrepreneurs in particular deal with work-life balance predicaments, unanimously considered the most significant barrier to inclusivity. The findings also emphasize how responsible AI design, adoption and governance can help deal with prevalent ethical concerns of AI in tourism, namely, bias, lack of transparency, fairness and privacy, the absence of a human-centered approach, and accountability. The latter two, alongside gender biases, emerge as the ‘most sensitive ethical parameters’ for women's inclusivity in tourism entrepreneurship. By integrating Rawls’ perspective the study offers a novel analytical lens for understanding how responsible AI can foster a more just and equitable entrepreneurial ecosystem for women in tourism, and for evaluating attendant strategies contributing to sustainable and inclusive growth. Important theoretical contributions and actionable managerial implications flow from the findings.
Description
Source:
Publisher:
Elsevier Ltd
