Dam, Xuan Minh, Tan, Kim Lim, Agarwal, Manisha, and L. Eijdenberg, Emiel (2026) Algorithm and Ancestry: Multi-Level Insights into AI Implementation in Indigenous Tourism. In: Academy of Management Proceedings (2026) From: 2026 U.S. Academy of Management Annual Meeting, 31 July - 4 August 2026, Phliadelphia, PA, USA.

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Abstract

Adoption theories suggest that technological and organizational readiness drive AI use, yet in culturally grounded contexts, adoption often falters. This study explores how service providers in Vietnam’s Indigenous tourism interpret and implement AI. Based on 21 semi-structured interviews across frontline, managerial, and institutional roles, we apply the Technological-Organizational-People (TOP) and Technological-Organizational-Environment (TOE) frameworks to trace multi-level dynamics. Findings reveal that cultural alignment, the fit between AI applications and Indigenous value systems, is both a necessary condition for transforming readiness into legitimate use and a mediating mechanism linking policy and resources to daily practices. AI adoption unfolds through a translation process: frontline actors experiment and adapt, managers verify cultural compatibility, and institutional actors formalize cautious routines. Implementation weakens when technological-cultural misalignment and operational constraints persist. The study extends TOP and TOE by defining when readiness becomes effective and theorizes a multi-level implementation mechanism that legitimizes AI use. These insights guide the design and governance of AI that aligns with Indigenous values while enabling effective service delivery.

Item ID:	93135
Item Type:	Conference Item (Presentation)
ISSN:	2151-6561
Related URLs:	Publisher
Date Deposited:	25 Aug 2026 23:47
FoR Codes:	35 COMMERCE, MANAGEMENT, TOURISM AND SERVICES > 3508 Tourism > 350806 Tourist behaviour and visitor experience @ 100%
SEO Codes:	11 COMMERCIAL SERVICES AND TOURISM > 1104 Tourism services > 110402 Socio-cultural issues in tourism @ 100%
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