生成式人工智能用户中辍行为影响因素与关联路径研究

• 作者： 郭海玲 ¹ 刘仲山 ¹ 卫金金 ¹ 魏悦华 ¹
• 作者单位：
  1.  河北大学 管理学院
• 通讯作者： 刘仲山 
• 提交时间：2024-10-22

摘要: [目的/意义]本文旨在探究生成式人工智能用户中辍行为的影响因素及其结构关系，为解释和改善生成式人工智能当前服务状态、保障生成式人工智能健康可持续发展提供理论借鉴和现实指导。[方法/过程]综合运用文献调研、半结构化访谈进行影响因素识别，利用解释结构模型、交叉影响矩阵相乘法对生成式人工智能用户中辍行为的影响因素进行关系梳理。[结果/结论]最终得出政策法规、产业支撑能力、信息内容质量等7项生成式人工智能用户中辍行为的关键影响因素，并从信息环境、信息人、信息、信息技术维度出发，为多元信息生态主体提出靶向性的生成式人工智能用户中辍行为消解对策。

Abstract: Abstract:[Purpose/Significance] This paper aims to investigate the factors influencing dropout behavior among users of generative artificial intelligence and analyze their structural relationships. The objective is to provide theoretical references and practical guidance for understanding and improving the current service status of generative artificial intelligence, thereby ensuring its healthy and sustainable development.[Methods/Process] A combination of literature research and semi-structured interviews was employed to identify the influential factors. An explanatory structure model along with cross-influence matrix multiplication was utilized to elucidate the relationship between these factors affecting dropout behavior in generative artificial intelligence users.[Results/Conclusion] Ultimately, seven key influencing factors contributing to dropout behavior in generative artificial intelligence users are identified, including policies and regulations, industrial support capabilities, as well as information content quality. Targeted measures addressing user dropout resolution are proposed from various dimensions such as information environment, information personnel, information technology, aiming at multiple subjects within the information ecosystem.

• 来自： 刘仲山
• 分类： 信息资源管理 >> 情报学
• 引用： PSSXiv:202411.00172 (或此版本 PSSXiv:202411.00172V1)
  DOI:10.12451/202411.00172
  CSTR:32012.36.PSSXiv.202411.00172
• 推荐引用方式： 郭海玲,刘仲山,卫金金,魏悦华.生成式人工智能用户中辍行为影响因素与关联路径研究.哲学社会科学预印本平台:https://zsyyb.cn/abs/202411.00172.[PSSXiv:202411.00172V1] (点此复制)