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Unpacking Innovation Incentives in Rural Tourism: A Simulation of Policy Impacts and Regional Heterogeneity

Fajian Liu et al.

Journal of Travel Research2026https://doi.org/10.1177/00472875251410562article
AJG 4ABDC A*
Weight
0.50

Abstract

Rural accommodation businesses are essential to rural tourism, where innovation is critical for maintaining competitiveness in a challenging market. This study developed a model of rural accommodation systems within an evolutionary economic geography framework, focusing on dynamic interactions among diverse agents. The model was implemented as a validated simulation through agent-based modeling to assess the impact of innovation incentive policies on rural accommodation practices. Findings demonstrated that innovation incentives enhance business performance, with effects varying across regions. This regional heterogeneity was attributed to the policy’s dual effects: fostering elite business clusters in high-demand areas and generating innovation spillovers in lower-demand regions. It also revealed that business performance was positively affected by entrepreneurial ability and market demand. By providing a novel perspective on the nonlinear dynamics of heterogeneous characteristics in tourism practices, this study advances the integration of tourism research and computational simulation.

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https://doi.org/https://doi.org/10.1177/00472875251410562

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@article{fajian2026,
  title        = {{Unpacking Innovation Incentives in Rural Tourism: A Simulation of Policy Impacts and Regional Heterogeneity}},
  author       = {Fajian Liu et al.},
  journal      = {Journal of Travel Research},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1177/00472875251410562},
}

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Unpacking Innovation Incentives in Rural Tourism: A Simulation of Policy Impacts and Regional Heterogeneity

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

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