Data Comparative Analysis of Player Satisfaction and Continuance Willingness Between Players of Mobile of Multiplayer Online Battle Arena

This dataset supports a quantitative study examining the effects of Community Interaction (CIN), Gaming Experience (GEX), Social Value (SOV), and Entertainment Value (ENT) on Player Satisfaction (SAT) and Continuance Willingness (CWI) among mobile Multiplayer Online Battle Arena (MOBA) game players in Indonesia. The conceptual model was tested using Partial Least Squares Structural Equation Modeling (PLS-SEM) and extended with Multi-Group Analysis (MGA) to compare two distinct player segments: Mobile Legends: Bang Bang (ML) and League of Legends: Wild Rift (LoLWR). The dataset consists of (1) raw survey responses from 60 respondents collected via online questionnaire, and (2) six SmartPLS 4 output files containing full structural model results, bootstrapping statistics, and MGA comparisons. The data is intended to support replication, secondary analysis, and methodological review of the PLS-SEM and MGA procedures reported in the associated publication.本数据集支持一项定量研究，该研究以印度尼西亚移动多人在线战术竞技游戏（Multiplayer Online Battle Arena, MOBA）玩家为研究对象，探讨社区互动（Community Interaction, CIN）、游戏体验（Gaming Experience, GEX）、社会价值（Social Value, SOV）与娱乐价值（Entertainment Value, ENT）对玩家满意度（Player Satisfaction, SAT）及持续意愿（Continuance Willingness, CWI）的影响。本研究的概念模型通过偏最小二乘结构方程模型（Partial Least Squares Structural Equation Modeling, PLS-SEM）进行检验，并通过多群组分析（Multi-Group Analysis, MGA）对比两个细分玩家群体：无尽对决（Mobile Legends: Bang Bang, ML）与英雄联盟手游（League of Legends: Wild Rift, LoLWR）玩家。 本数据集包含两部分内容：(1) 通过在线问卷收集的60份受访者原始调研数据；(2) 6份SmartPLS 4输出文件，涵盖完整结构模型结果、自助法统计量及多群组分析对比结果。本数据集旨在支持相关研究论文中报告的偏最小二乘结构方程模型与多群组分析方法的复现、二次分析及方法学检视。