The impact of AI-aided service delivery on post-purchase behaviour of health insurance consumers' during COVID-19

Data collected from health insurance users in India during COVID 19. Its primary data set had 269 participants. An online structured questionnaire has been prepared with seven constructs, comprising 25 questions to test the proposed hypothesis. These verified constructs are adopted from multi-disciplinary sources in social sciences. Besides this, demographic information from the respondent has been asked to understand their demographic characteristics. Data was collected using a multi-stage stratified random sampling procedure. For this purpose, Indian states and union territories (UTs) have been divided into two groups based on their per capita income. The first group consists of 19 states/UTs with per capita income higher than the national average, while the second group consists of 14 states/UTs with per capita income lower than the national average. This population has further been divided into rural, semi-urban, and urban areas. We randomly selected samples from states/UTs such as Maharashtra, Karnataka, Delhi, Chandigarh, Uttarakhand, and Punjab from the first group. Data were also collected from Uttar Pradesh, Bihar, Jharkhand, Odisha, Rajasthan, and Madhya Pradesh to represent the second group. We received a total of 254 responses; after scrutiny, 8 were discarded, and only 246 were used for further analysis.

本数据集采集自新冠疫情期间的印度健康保险用户。初始数据集共纳入269名参与者。研究人员编制了包含7个构念、共计25个问题的线上结构化问卷，以验证所提出的研究假设。上述经过验证的构念引自社会科学领域的多学科研究成果。此外，问卷还收集了受访者的人口统计学信息，以便了解其人口统计学特征。数据采集采用多阶段分层随机抽样方法，研究人员首先依据人均收入水平，将印度各邦及中央直辖区（Union Territories，UTs）划分为两组：第一组包含19个人均收入高于全国平均水平的邦/UTs，第二组包含14个人均收入低于全国平均水平的邦/UTs，随后将各组区域进一步划分为农村、半城镇及城镇三类区域。研究人员从第一组中随机选取马哈拉施特拉邦、卡纳塔克邦、德里、昌迪加尔、北阿坎德邦及旁遮普邦开展样本采集，同时从第二组中选取北方邦、比哈尔邦、贾坎德邦、奥里萨邦、拉贾斯坦邦及中央邦进行数据收集。本次研究共回收254份问卷，经审核筛查剔除8份不合格样本，最终纳入246份问卷用于后续分析。