旅游需求组合预测的理论研究和实证检验——基于贝叶斯理论的视角

Tourism demand forecasting is fundamental to making national tourism development policies and strategic plans, optimizing tourism market resource allocation, and developing strategic plans and decision for tourism enterprises. This project explores the influencing factors of inbound tourism demand and its forecasting practice from a new research perspective. It aims to establish a holistic theoretical and empirical analytical framework for forecasting tourism demand, which is capable of measuring the impact of various influencing factors on tourism demand, best utilizing the advantages of quantitative and qualitative forecasting methods, for the purpose of improving the forecast accuracy and robustness. The innovative contributions of the project lie in three aspects. First, it has been one of its first kind to propose a holistic theoretical framework that can measure the impact of all three types of influencing factors (economic factors, non-economic factors, and special events) on tourism demand. This has filled the research gap of the exiting tourism demand forecasting literature that can only taking one or two types of factors into consideration, which is expected to greatly reduce forecasting failure. Second, this project innovatively established Bayesian combined forecasting models that mathematically combine quantitative and qualitative forecasts, which is served to conduct empirical analysis that best reflect the utility of theoretical framework. Third, real tourism demand data will be used to verify the feasibility of the theoretical framework, the validity and reliability of the empirical models, and the practical value of this project’s research findings. Last but not least, this project provides forecasts for the inbound tourism markets in China over the next decade, with a view to providing recommendations and suggestions for decision-makers in making sound tourism plans, effective investment in various resources and coordinating the tourism demand and supply.

旅游需求预测在国家旅游战略规划和发展政策制定、旅游市场资源优化配置、旅游企业战略计划和决策制定等方面有着极为重要的作用。本项目从全新的视角研究入境游需求的内在影响机制及预测实践，建立旅游需求组合预测的理论和实证分析框架，量化整合定量和定性预测的信息，提高预测精度和稳健性。本项目的创新点和特色在于：（1）首次将经济因素，非经济因素和特殊事件纳入统一的分析框架考察对旅游需求的综合影响，以突破现有旅游预测模型未能同时测度这三者影响的局限，降低预测失灵的风险。（2）创新性地构建定量和定性预测相结合的贝叶斯旅游需求组合预测模型，探索建立与理论框架最为匹配的实证研究模型。（3）基于实际旅游数据来验证理论模型的可行性和实证模型的有效性，从而为项目成果提供实践价值依据。（4）为我国入境旅游市场提供未来十年的发展趋势，有助于合理规划旅游业发展方向和规模，有效配置和平衡旅游供给与需求间的协调关系提供决策依据。

本研究旨在填补基于高级计量经济模型和专家经验判断相结合的组合预测方法在旅游需求预测领域的研究空白，将德尔菲专家法、计量经济预测模型和在线旅游需求预测系统进行有机结合，首次对旅游需求的统计预测和专家调整后预测的精度和偏差进行评估，从业界和学界预测专家角度深层次挖掘其主观预测行为，并探析其背后成因。本研究的主要研究贡献，体现在以下五个方面：（1）利用计量模型生成统计预测，有助于为政府对旅游目的地入境旅游乃至旅游业的发展提供决策依据，为旅游目的地的旅游机构了解未来入境旅游市场的发展趋势、增长的模式以及主要客源市场的需求变动提供参考依据。（2）利用预测决策支持系统量化专家知识和经验，为旅游业界和学界专家提供一个在线对话交流平台。本研究所采用的在线德尔菲专家预测法可促进旅游学术界、政府机构旅游部门和旅游行业不同利益相关者的交流。（3）利用精度测量方法测度统计预测和专家调整预测，这是旅游预测文献中首次对专家调整预测的结果进行精度评价。（4）探讨预测误差的原因，此研究是国内外旅游预测文献中对统计预测和判断预测的误差产生原因探究的首次尝试。（5）为进一步改善现有旅游需求预测系统提供理论和实证支持，提供预测系统的有效性，从而提升预测效能。