在菲律宾的云存储消费者中使用机器学习合并方法进行实际使用评估
Ardvin Kester S Ong1, Gerlyn C Altes1, Josephine D German2
1School of Industrial Engineering and Engineering Management, Mapúa University, 658 Muralla St., Intramuros, Manila, 1002, Manila, Philippines.
Scientific reports
|November 23, 2024
概括
菲律宾人 菲律宾人
科学领域:
- 信息科学 信息科学 信息科学
- 计算机科学 计算机科学
- 技术采用 技术采用
背景情况:
- 云存储对于发达国家和发展中国家的数据管理至关重要.
- 包括菲律宾在内的发展中国家正在探索云存储,特别是免费服务.
- 了解用户的意图和实际使用云存储对于持续的采用和开发策略至关重要.
研究的目的:
- 分析影响菲律宾实际使用云存储的因素.
- 通过使用综合技术验收模型和价值框架,调查云存储采用的先例.
- 为开发云存储营销和实用性的有效策略提供见解.
主要方法:
- 用一个机器学习组合 (MLE) 来进行数据分析.
- 利用了616个有效的响应,并处理了33,264个数据集.
- 根据集成的扩展技术接受模型和价值框架,测量了实际的云存储使用情况.
主要成果:
- 机器学习组合实现了平均准确率为93%和90%.
- 影响实际云存储使用的关键因素包括自愿性,主观规范,感知效益,感知实用性和感知无处不在性.
- 个人和专业的使用都有助于采用,由一般的技术准备提供便利.
结论:
- 菲律宾的云存储采用受到用户看法和社会因素的影响.
- 为了持续使用云存储,需要加强技术基础设施.
- 综合框架可以应用于不同国家的其他技术公用事业.
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