Identifying volunteer groups based on motivational patterns using latent class analysis

Engineering notes

Key topics: autonomous driving, control. See the paper for implementation details and experimental results.

Chinese explanation / 中文解读

中文解读待补充：本站会优先为端到端自动驾驶、BEV感知、3D目标检测、轨迹预测、路径规划、LiDAR感知等高价值论文补充中文说明。

Original abstract

Background Volunteers dedicate their time and effort to enhancing communities, supporting social causes, and fostering social cohesion. Self-Determination Theory suggests that volunteer motivation may vary along a continuum of internalization from controlled to autonomous motivation. However, there is limited understanding of whether motivational profiles reflect qualitatively distinct types or primarily differ in intensity. This study seeks to identify fundamental motivational groupings among volunteers and to analyse the sociodemographic factors associated with these profiles using data from a cross-national survey. Methods Data from 2,605 respondents in the World Values Survey (1982–2022) were analysed using 14 indicators of volunteer motivation. Two to six classes were fitted using Latent Class Analysis (LCA). Multinomial logistic regression subsequently examined associations between class membership and sociodemographic characteristics. Results A three-class model was identified, characterized primarily by varying degrees of motivational intensity: low (31.2%), moderate (32.1%), and high (36.7%) motivation. Classes showed parallel response patterns across altruistic, moral, social, religious, and self-oriented motivations, suggesting quantitative rather than qualitative differences. Older adults (35–54 years: OR = 0.62; 55 + years: OR = 0.59) and women (OR = 0.67) were less likely to belong to the low-motivation group, while higher education (OR = 1.44) was associated with greater likelihood of low motivation. Conclusion Volunteer motivations differ primarily in intensity rather than type, suggesting a continuum of motivational engagement rather than distinct volunteer profiles. Volunteer policies should acknowledge individual differences in motivational strength and provide opportunities designed to foster deeper and more sustained engagement. Considering sociodemographic and cultural differences can help ensure volunteering initiatives are inclusive, sustainable, and effective across diverse global settings.

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