Exploring DeepSeek Adoption Through UTAUT2: A Comparative Study of India, Pakistan, and Bangladesh

The dataset you're referring to is structured to analyze AI adoption using the <b>UTAUT2 model</b>, specifically within the context of DeepSeek adoption in <b>India, Pakistan, and Bangladesh</b>.<b>Data Overview:</b><b>Scope:</b> The study covers South Asian countries to provide comparative insights into adoption behavior.<b>Sample Size:</b> Includes responses from <b>Bangladesh</b>, along with India and Pakistan, ensuring a balanced perspective.<b>Variables:</b> Constructs from UTAUT2—such as <b>performance expectancy, effort expectancy, social influence</b>, and the newly introduced <b>Geopolitical Concern</b>—are assessed.<b>Analysis Methodology:</b> <b>Structural Equation Modeling (SEM-PLS)</b> is used to test the proposed hypotheses and validate the extended model.

本数据集旨在依托<b>统一技术接受与使用理论2（UTAUT2）模型</b>，针对<b>印度、巴基斯坦与孟加拉国</b>境内的DeepSeek应用采纳场景，开展人工智能技术采纳行为的相关分析。
<b>数据概览：</b>
<b>研究范围：</b>本研究覆盖南亚多国，旨在为技术采纳行为提供具有对比性的研究洞察。
<b>样本规模：</b>研究纳入<b>孟加拉国</b>、印度与巴基斯坦三地的有效调研反馈，以保障分析视角的平衡性。
<b>变量维度：</b>本研究对统一技术接受与使用理论2（UTAUT2）的核心构念进行测评，涵盖<b>绩效期望（performance expectancy）、努力期望（effort expectancy）、社会影响（social influence）</b>，以及新增引入的<b>地缘政治关切（Geopolitical Concern）</b>。
<b>分析方法：</b>本研究采用<b>偏最小二乘结构方程模型（SEM-PLS）</b>，对预设研究假设进行检验，并验证拓展后的理论模型。