The willingness to invest in Internet of Things (IoT) and Big Data Analytics (BDA) seems not to depend on supply nor demand of technological innovations. The required sensing and communication technologies have already matured and became affordable for most organizations. Businesses on the other hand require more operational data to address the dynamic and stochastic nature of supply chains. So why should we wait for the actual implementation of tracking and monitoring devices within the supply chain itself? This paper provides an objective overview of state-of-the-art IoT developments in today’s supply chain and logistics research. The main aim is to find examples of academic literature that explain how organizations can incorporate real-time data of physically operating objects into their decision making. A systematic literature review is conducted to gain insight into the IoT’s analytical capabilities, resulting into a list of 79 cross-disciplinary publications. Most researchers integrate the newly developed measuring devices with more traditional ICT infrastructures to either visualize the current way of operating, or to better predict the system’s future state. The resulting health/condition monitoring systems seem to benefit production environments in terms of dependability and quality, while logistics operations are becoming more flexible and faster due to the stronger emphasis on prescriptive analytics (e.g., association and clustering). Further research should extend the IoT’s perception layer with more context-aware devices to promote autonomous decision making, invest in wireless communication networks to stimulate distributed data processing, bridge the gap in between predictive and prescriptive analytics by enriching the spectrum of pattern recognition models used, and validate the benefits of the monitoring systems developed.

投资于物联网（IoT）和大数据分析（BDA）的意愿似乎并不取决于技术创新的供求关系。所需的传感和通信技术已经成熟，并且对于大多数组织来说已经可以负担得起。另一方面，企业需要更多的运营数据来解决供应链的动态和随机性。那么，为什么我们要等待供应链本身中跟踪和监视设备的实际实施呢？本文客观地概述了当今供应链和物流研究中最新的物联网发展。主要目的是找到可以解释组织如何将物理操作对象的实时数据纳入其决策的学术文献示例。进行了系统的文献综述，以深入了解物联网的分析能力，从而形成了79个跨学科出版物的列表。大多数研究人员将新开发的测量设备与更传统的ICT基础设施集成在一起，以可视化当前的操作方式，或更好地预测系统的未来状态。由此产生的健康/状况监视系统似乎在可靠性和质量方面使生产环境受益，而由于更加强调规范性分析（例如关联和聚类），物流操作变得更加灵活和快捷。进一步的研究应使用更多上下文感知设备扩展IoT的感知层，以促进自主决策，