Skip to Main Content
Article navigation
Purpose

This study aims to investigate how managerial practices influence artificial intelligence (AI) post-implementation success in Iran’s tourism and hospitality sector, with transactional and transformational leadership styles as moderators, to optimize AI adoption outcomes.

Design/methodology/approach

Grounded in Resource-Based View (RBV) and Upper Echelons Theory, data were collected from 218 Iranian tourism and hospitality firms using a survey. Hypotheses were tested via Partial Least Squares Structural Equation Modeling to analyze complex relationships.

Findings

Training and education, business process re-engineering (BPR) and system integration significantly enhance AI post-implementation success, which positively impacts financial performance. Transformational leadership positively moderates project management’s effect, whereas transactional leadership negatively moderates BPR’s impact. Project management shows no direct effect, highlighting contextual challenges.

Practical implications

Managers should prioritize training, BPR and system integration to maximize AI benefits. Transformational leadership fosters innovation in AI projects, whereas transactional leadership may hinder creative processes like BPR. Policymakers can support AI adoption through skill development and workforce stability programs.

Originality/value

This study uniquely integrates RBV and Upper Echelons Theory to examine AI post-implementation success, an underexplored phase, in Iran’s tourism sector. It identifies effective practices and leadership moderation role, offering a novel framework for AI optimization.

Licensed re-use rights only
You do not currently have access to this content.
Don't already have an account? Register

Purchased this content as a guest? Enter your email address to restore access.

Please enter valid email address.
Email address must be 94 characters or fewer.
Pay-Per-View Access
$39.00
Rental

or Create an Account

Close Modal
Close Modal