在工业4.0中预测产品信息传播以实现可持续的质量管理:改进的巴斯模型方法
Zhongya Han1, Xiangtang Chen2, Kepao Miao1
1School of Economics and Management, Wenzhou University of Technology, Wenzhou, 325035, China.
Scientific reports
|July 17, 2025
概括
预测产品信息的受欢迎程度是工业4.0的关键. 一个增强的Bass模型,考虑到用户差异和兴趣衰退,比数字营销的经典模型提高了预测准确度.
科学领域:
- 信息科学 信息科学 信息科学
- 营销科学 营销科学
- 计算社会科学 计算社会科学
背景情况:
- 工业4.0需要准确的产品信息,用于营销优化和可持续增长.
- 经典的Bass模型虽然有用,但无法解释用户的异质决策和数字环境中的时间兴趣衰退.
研究的目的:
- 提出一个增强的Bass模型,解决传统模型在数字环境中的局限性.
- 将双相扩散框架和利息衰减机制纳入巴斯模型.
主要方法:
- 开发了一种增强的Bass模型,整合了双相扩散框架和放松恒定影响系数.
- 通过使用来自微博平台的电影预告片传播数据验证了模型.
主要成果:
- 增强的Bass模型在预测信息受欢迎程度方面明显优于经典的Bass模型及其变体 (功率函数,指数函数).
- 发现,对信息传播的内部和外部影响随着时间的推移而衰退.
- 社会压力被确定为塑造内部扩散的一个因素.
结论:
- 增强的Bass模型为预测数字环境中的信息受欢迎程度提供了更准确的方法.
- 研究结果为数据驱动的传播模型和数字营销效率提供了宝贵的见解.
- 未来的研究应该探索该模型在各种产品类别和社交媒体平台上的适用性.
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