近年来,中国人口结构转变速度加快,老龄化趋势明显,“银发族”对文化娱乐和社交活动的需求剧增,下午茶行业作为可以满足该需求的新兴领域,展现出了老龄化为社会带来的消费新潜力,为发展银发经济提供了新机遇。基于此,本文以上海市为例,...近年来,中国人口结构转变速度加快,老龄化趋势明显,“银发族”对文化娱乐和社交活动的需求剧增,下午茶行业作为可以满足该需求的新兴领域,展现出了老龄化为社会带来的消费新潜力,为发展银发经济提供了新机遇。基于此,本文以上海市为例,对“沪上银发”下午茶的市场背景、影响因素及对策建议进行研究。运用因子分析法与系统聚类分析对整体受访者进行特征划分;接着利用二元Logistic回归模型分析影响其消费行为的因素。最后,提出相关对策建议,为行业发展提供参考。In recent years, China's demographic transition has accelerated. The aging trend is obvious, and the demand of the “silver ethnic groups” for cultural entertainment and social activities has increased dramatically. As an emerging field that can satisfy this demand, the low tea industry has demonstrated the new consumption potential brought by aging to the society, and provided new opportunities for the development of the silver economy. Based on this, this paper takes Shanghai as an example to study the market background, influencing factors and countermeasure suggestions of “Shanghai silver” low tea. Factor analysis and systematic cluster analysis are used to classify the characteristics of the whole respondents;then, binary Logistic regression models are used to analyze the factors affecting their consumption behaviors. Finally, relevant countermeasure suggestions are put forward to provide reference for the development of the industry.展开更多
文摘近年来,中国人口结构转变速度加快,老龄化趋势明显,“银发族”对文化娱乐和社交活动的需求剧增,下午茶行业作为可以满足该需求的新兴领域,展现出了老龄化为社会带来的消费新潜力,为发展银发经济提供了新机遇。基于此,本文以上海市为例,对“沪上银发”下午茶的市场背景、影响因素及对策建议进行研究。运用因子分析法与系统聚类分析对整体受访者进行特征划分;接着利用二元Logistic回归模型分析影响其消费行为的因素。最后,提出相关对策建议,为行业发展提供参考。In recent years, China's demographic transition has accelerated. The aging trend is obvious, and the demand of the “silver ethnic groups” for cultural entertainment and social activities has increased dramatically. As an emerging field that can satisfy this demand, the low tea industry has demonstrated the new consumption potential brought by aging to the society, and provided new opportunities for the development of the silver economy. Based on this, this paper takes Shanghai as an example to study the market background, influencing factors and countermeasure suggestions of “Shanghai silver” low tea. Factor analysis and systematic cluster analysis are used to classify the characteristics of the whole respondents;then, binary Logistic regression models are used to analyze the factors affecting their consumption behaviors. Finally, relevant countermeasure suggestions are put forward to provide reference for the development of the industry.
