Journal of Engineering, Project, and Production Management, 2027, 17(1), 2026-227
Optimizing Rural Area Tourism Routes Using Structural Equation Modeling
Associate Professor, College of Culture and Tourism, Urumqi Vocational University, Urumqi, 830002, China, E-mail: liufenglian2025@163.com
Project Management
Received February 10, 2026; revised April 17, 2026; September 29, 2026; accepted October 6, 2026
Available online October 20, 2026
Abstract: With the advancement of the rural revitalization strategy, rural tourism has emerged as a significant growth point for regional economies. However, current tour routes predominantly rely on empirical planning, making it difficult to meet tourists' demands for personalized and immersive experiences. To enhance the rural tourism experience and improve tour efficiency, this study is based on 421 valid tourist questionnaires collected from typical rural areas in Shandong Province, China. The study first constructs an evaluation model for the importance of rural tourism resources. This model quantifies spatial characteristics of resources across multiple dimensions and calcu-lates node centrality using social network analysis. Subsequently, the study employs a structural equation model to analyze the impact of latent variables, such as personal attributes, on tourists' travel choices, thereby forming relevant mechanisms. A double-layer Nested Logit model is introduced, in which the upper layer selects activity chain types, and the lower layer selects travel modes, with parameters estimated via a phased approach. Finally, a dual-objective model integrating landscape service levels and travel time is constructed. This model takes node weights and mode shares as inputs and uses a genetic algorithm to find optimal solutions, yielding a generation model for rural landscape tour-route networks. The results indicate that travel preferences have the most direct impact on tourists' choices, with a path coefficient of 0.55, followed by transportation attributes and tourism activ-ity attributes. Significant behavioral differences are observed among different groups. For instance, the younger demographic prefers immersive activity chains, accounting for 42%, while family travelers rely heavily on public transportation, at 65%. Dual-objective optimization enhances the overall efficiency of the express-arterial-branch road network by 28%. This study couples the objective characteristics of resources with tourists' subjective behav-iors, providing a data-driven quantitative tool for rural tourism route planning.
Keywords: Rural tourism; structural equation modeling; genetic algorithm; nested logit; objective optimization.
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Citation: Liu, F. (2027). Optimizing Rural Area Tourism Routes Using Structural Equation Modeling. Journal of Engineering, Project, and Production Management, 17(1), 2026-227.
