ABSTRACT
We investigate how tracking the running times of durable medical equipment connected to the Internet of Things (IoT) can be used to estimate the demand for MRO products and consumable supplies (MRO & CS) and lessen the Bullwhip Effect in healthcare supply chains (HSCs). By analyzing a unique data set consisting of orders for medical supplies in a multi-echelon HSC spanning 12 quarters (3 years), using two-stage econometric modeling and counterfactual analysis methods, we find that the sharing of these usage and consumption signals significantly improves forecast accuracy, lowers order size, and reduces the bullwhip effects of MRO & CS. We find that the supply chain benefits of tracking equipment running time are amplified by the scope of the relational exchanges between supply chain partners. We analyze the two dominant IoT networking paradigms—Edge and cloud IoT—and find that the benefits of signal sharing are significantly higher under the Edge IoT network. We also find that the tracking of medical equipment has second-order effects that extend to products whose consumption is correlated with the tracked products. Our research makes important theoretical contributions to the HSC and technology management literatures and provides valuable insights into how emergent technologies can be used to address the distinctive challenges of healthcare supply chains.