The Selection of Industry 4.0 Technologies Through Bayesian Networks: An Operational Perspective
研究了工业4.0技术如何影响运营绩效，并利用贝叶斯网络和机器学习帮助制造企业根据运营目标选择技术组合。
Many manufacturing firms today are considering whether to adopt one or more technologies associated with the Industry 4.0 vision. Yet, neither academic nor practitioner literature provide much guidance about these technology choices. This article aims at understanding how Industry 4.0 (I4.0) technologies can impact operational performance and at discovering possible synergies among I4.0 technologies. More specifically, the research seeks to analyze the full network of relationships between I4.0 technologies and operational performance, assess the impact of single technologies on performance, construct portfolios of technologies depending on the firms’ operational targets, and identify possible operational improvements to achieve by adjusting a portfolio of I4.0 technologies. To pursue these research goals, we use a Bayesian network and machine-learning algorithms to drive firms’ investment decisions based on I4.0 technologies. The analysis has been conducted on a sample of 289 Italian manufacturing firms and companies that provide services directly related to manufacturing activities. Our findings provide managerial insights and intuitions to improve operational performance by either adopting single I4.0 technologies or creating an ad hoc portfolio of technologies.