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基于服务营销混合元素的游客满意度预测建模,使用机器学习技术

Md Nazmul Hoque¹, Sumiya Nur Jannat², Yasin Arafat²

¹Department of Marketing, Comilla University, Comilla, Bangladesh, cou.ac.bd.

TheScientificWorldJournal

|January 12, 2026

概括

这项研究表明,定价和位置显著影响了孟加拉国考克斯巴扎尔的游客满意度和忠诚度. 有效的营销组合策略对于增强整体旅游体验和推动重复访问至关重要.

科学领域:

旅游市场营销旅游市场营销
服务营销服务营销
行为经济学是一种行为经济学.

背景情况:

游客满意度和忠诚度是目的地成功的关键指标.
了解服务营销组合的影响对于旅游业发展至关重要.
考克斯巴扎尔是一个受欢迎的旅游目的地,需要战略营销洞察力.

研究的目的:

调查服务营销组合对考克斯巴扎尔游客满意度和忠诚度的影响.
确定最有影响力的营销组合元素来增强旅游体验.
开发一个强大的预测模型,以满足游客的需求.

主要方法:

使用调查从500名受访者收集数据.
统计分析包括克伦巴赫的α,变量通胀因子 (VIF) 和主要成分分析 (PCA).
机器学习模型 (XGBoost) 用于预测分析,通过交叉验证,灵敏度和学习曲线评估进行验证.

主要成果:

XGBoost模型显示了高的预测准确性 (R平方=0.74,MSE=0.10).
汇总的价格和位置变量是最重要的预测因素 (68.20%).
克伦巴赫的α值超过了0.70,证实了构造可靠性;VIF低于1.05,表明没有多线性.

结论:

定价和位置策略对于提高考克斯巴扎尔的游客满意度和忠诚度至关重要.
这项研究证实了XGBoost模型在旅游营销研究中的有效性.
调查结果为政策制定者和旅游业利益相关者提供了可行的建议,以优化营销努力并增强旅游旅程.

关键词:

考克斯巴扎尔 (Cox's Bazar) 是一个古老的城市.在XGBoost中使用.重要的特征重要的特征重要的特征机器学习是机器学习.多对线性多对线性.服务营销组合服务营销组合游客的满意度游客的满意度

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