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Academic ResearchMarch 10, 2026International Journal of Hospitality Management

Centralization or diversification? Artificial intelligence application and supply chain configuration in hospitality enterprises

This study shows that AI adoption in hospitality significantly promotes supply chain diversification by improving productivity and cost efficiency. Risks influence how firms use AI to adjust supply chains, suggesting tailored strategies for different hospitality sectors and risk environments.

Authors

Xin Liu, Yan Huang, Rui Qi, Lu Zhang, Abdulaziz Alshalfan

Article content

What the paper studied

This research analyzed how artificial intelligence (AI) adoption affects supply chain configuration in hospitality enterprises. Using data from 144 hospitality-related companies listed on China's A-share market between 2001 and 2023, the study explored whether AI leads to more centralized or diversified supply chains. It also examined the mechanisms behind this effect and how different types of risks influence firms' supply chain decisions.

Key findings

  • AI application significantly reduces supply chain concentration, encouraging diversification.
  • The diversification effect is driven by AI improving labor productivity, total factor productivity, and cost efficiency.
  • Firms facing higher opportunistic risks are more likely to use AI to diversify their supply chains, enhancing resilience.
  • Systemic risks, such as financial crises or public health emergencies, also affect how AI influences supply chain strategies.

Why it matters for hospitality

Supply chain management in hospitality has traditionally struggled with slow market responses and high operational risks, partly due to poor data sharing across supply chain partners. This study highlights AI's potential to break down these barriers by enabling better data flow and collaboration between upstream suppliers and downstream operators. By diversifying supply chains, hospitality businesses can reduce dependency on single suppliers or channels, improving flexibility and resilience. Understanding how risk environments shape AI adoption helps managers and policymakers tailor strategies to maximize benefits.

Practical takeaways

  • Hotels can use AI-driven demand forecasting to optimize procurement of room amenities and food & beverage supplies, reducing waste and reliance on dominant online travel agencies.
  • Restaurants benefit from AI inventory systems that predict reorder points and automate ordering, allowing them to diversify suppliers between local producers and large distributors.
  • Tourism operators and attractions can leverage AI for real-time coordination with transport and local vendors, adjusting operations based on seasonality or events.
  • Small and medium-sized enterprises should adopt scalable, cloud-based AI solutions gradually, supported by partnerships and government training programs.
  • Governments can facilitate AI-driven supply chain diversification by establishing shared data platforms, standardizing data formats, and incentivizing collaboration across the hospitality supply chain.
  • Risk-sensitive policies are essential: firms in high-opportunism environments may need risk-sharing grants or tax incentives to encourage AI adoption, while those in stable markets benefit from training and demonstration projects.
  • After systemic shocks like financial crises, governments should prioritize digital innovation support to accelerate AI-driven diversification; after public health crises, focus on operational stabilization before expanding technology investments.

Overall, AI offers hospitality enterprises a powerful tool to reconfigure supply chains toward greater diversification, efficiency, and resilience. Strategic adoption tailored to risk contexts and supported by collaborative data sharing can enhance competitive advantage and operational stability in a rapidly evolving industry.

Tags

Artificial IntelligenceSupply Chain ManagementHospitality IndustryDigital TransformationRisk Management

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