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印度健康保险用户群体。初始数据集共纳入269名参与者。研究设计了一份包含7个构念、共计25道题目的线上结构化问卷，用于验证所提出的研究假设；上述经过验证的构念均引自社会科学领域的多学科资料。此外，问卷还收集了受访者的人口统计学信息，以分析其人口特征。 本次数据采集采用多阶段分层随机抽样方法：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/中央直辖区，第二组则包含14个人均收入低于全国平均水平的邦/中央直辖区；随后，将上述群体进一步划分为农村、半城镇及城镇三类区域。我们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；同时从第二组的北方邦、比哈尔邦、贾坎德邦、奥里萨邦、拉贾斯坦邦及中央邦收集数据，以覆盖两组抽样群体。 本次调研共回收254份有效初始问卷，经审核剔除8份不合格问卷后，最终纳入后续分析的有效样本量为246份。