ABSTRACT

This paper is interested in the application of ‘digital innovation’ modes in an extended geographical economy setting, namely automotive industry process innovation. It is clear that challenging, complex and combinatory or ‘crossover’ knowledge issues arise periodically as competing system processes rise and fall in popularity with rivalrous automakers. This involves achieving the image if not the reality as ‘digital twins’ of prescience in marketing, monitoring and maintenance. These are all central elements of ‘surveillance capitalism’ facilitated by big data analytics, artificial intelligence and machine learning. Such combinations are envisioned and to varying degrees implemented in what Industry 4.0 advocates call the ‘smart factory’, but its critics call the ‘lights out’ or ‘dark factory’. This is because of its potentially full automation and absence of humans. Brief conclusions follow.

摘要

本文感兴趣的是“数字创新”模式在扩展地理经济环境中的应用，即汽车行业流程创新。很明显，随着相互竞争的系统流程在相互竞争的汽车制造商中的流行度上升和下降，挑战性、复杂和组合或“交叉”知识问题会周期性地出现。这涉及在营销、监控和维护方面实现作为先见之明的“数字双胞胎”的形象，如果不是现实的话。这些都是大数据分析、人工智能和机器学习推动的“监视资本主义”的核心要素。在工业 4.0 倡导者所说的“智能工厂”中设想并在不同程度上实施了这种组合，但其批评者称之为“熄灯工厂”或“黑暗工厂”。这是因为它可能完全自动化并且没有人类。简要结论如下。