Causal Factors Influencing Logistics Performance in Tourism Businesses: A Supply Chain Collaboration Perspective

This study investigates the causal relationships among factors influencing logistics performance in tourism businesses, with a particular emphasis on supply chain collaboration, organizational trust, and commitment.A mixed-methods approach was employed, integrating quantitative data from 400 tourism entrepreneurs in China, collected via stratified random sampling, with qualitative insights from 15 purposively selected industry experts through in-depth interviews.Structural equation modeling (SEM) analysis revealed that supply chain collaboration, trust, and commitment exert significant direct effects on logistics performance, with the model demonstrating robust empirical fit ( = 25.86,df = 20, p = 0.17, GFI = 0.99, AGFI = 0.97, RMR = 0.0098).Qualitative findings highlighted the critical role of integrated collaboration among stakeholders, including local governments and suppliers, in enhancing service efficiency and responsiveness.The study proposes a comprehensive causal model that integrates these factors, offering actionable implications for tourism businesses to optimize logistics operations and for policymakers to foster sustainable tourism ecosystems.The model underscores the importance of trust-building and commitment as mediators in collaborative frameworks, providing a blueprint for improving operational efficiency in dynamic market environments.

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Publication Details

Journal
International Journal of Academic Research in Business and Social Sciences
Published
2025-05-17
DOI
https://doi.org/10.6007/ijarbss/v15-i5/25455
Primary Topic
Outsourcing and Supply Chain Management
Type
article
Field-Weighted Citation Impact
0.00
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article

Causal Factors Influencing Logistics Performance in Tourism Businesses: A Supply Chain Collaboration Perspective

Rudzi Munap, Zhi Zhou, Dr Yi Wang, Puteri Aina Megat Ameir Noordin
International Journal of Academic Research in Business and Social Sciences
Outsourcing and Supply Chain Management
article

Causal Factors Influencing Logistics Performance in Tourism Businesses: A Supply Chain Collaboration Perspective

Rudzi Munap, Zhi Zhou, Dr Yi Wang, Puteri Aina Megat Ameir Noordin
article en

Abstract

This study investigates the causal relationships among factors influencing logistics performance in tourism businesses, with a particular emphasis on supply chain collaboration, organizational trust, and commitment.A mixed-methods approach was employed, integrating quantitative data from 400 tourism entrepreneurs in China, collected via stratified random sampling, with qualitative insights from 15 purposively selected industry experts through in-depth interviews.Structural equation modeling (SEM) analysis revealed that supply chain collaboration, trust, and commitment exert significant direct effects on logistics performance, with the model demonstrating robust empirical fit ( = 25.86,df = 20, p = 0.17, GFI = 0.99, AGFI = 0.97, RMR = 0.0098).Qualitative findings highlighted the critical role of integrated collaboration among stakeholders, including local governments and suppliers, in enhancing service efficiency and responsiveness.The study proposes a comprehensive causal model that integrates these factors, offering actionable implications for tourism businesses to optimize logistics operations and for policymakers to foster sustainable tourism ecosystems.The model underscores the importance of trust-building and commitment as mediators in collaborative frameworks, providing a blueprint for improving operational efficiency in dynamic market environments.

International Journal of Academic Research in Business and Social SciencesVol. 15(5)
Decent work and economic growth
Openalex Percentile: Top 82%
Outsourcing and Supply Chain Management
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Causal Factors Influencing Logistics Performance in Tourism Businesses: A Supply Chain Collaboration Perspective — Rudzi Munap, Zhi Zhou, et al. · International Journal of Academic Research in Business and Social Sciences (2025) | TGRS Research Map | TGRS