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Acknowledging the importance of both lean thinking (LT) and Industry 4.0 (I4.0) for successful business performance and organisational success, the present study investigates the critical success factors (CSFs) for the concurrent implementation of both approaches, a field not yet significantly explored.

The study conducts two systematic literature reviews (SLRs), one on LT and the other one on I4.0 to map out the CSFs for the effective implementation of each approach. These CSFs are subsequently prioritised with the use of a Delphi Study. Finally, from the set of the common CSFs recognised through the two approaches, a more condensed list is put forward as the first step towards achieving a successful synergy between LT and I4.0.

The study’s findings suggest the most important CSFs and determine their definition in the context of a concurrent implementation of LT and I4.0. This can provide managers and practitioners with the awareness of crucial factors, enabling them to take the necessary steps for planning and implementing both approaches.

A concise set of CSFs for the concurrent implementation of both LT and I4.0 has been identified, which can be viewed as a starting point for providing top executives and managers with useful insights into enhanced business efficiency and performance. This study furthermore contributes to the overall body of knowledge on LT and I4.0.

The scholarly literature that explores a common set of CSFs for the concurrent implementation of LT and I4.0 is limited. This gap significantly enhances the importance of the present research, contributing to a better understanding amongst both academics and practitioners of the key supporting factors for the integration of the two approaches.

Being clear and specific on what moderating and/or mediating variables are included and what effects are observed in academic research helps the reader to better understand the academic research context and results. But in terms of managerial relevance, it is also important to do this in a way that it provides descriptive, goal and operational relevance to decision makers in practice, depending on the type of intended research. This article wants to provide “a question-based step-by-step guide” on how to make the analysis of moderating/mediating variables and their observed effects more managerially relevant.

Based on a critical review of the literature, important criteria of managerial relevance are confronted with important aspects of theory building with respect to mediating and moderating effects, leading to best-practice insights and recommendations. Moreover, exemplary articles are used to illustrate these findings.

The insights and step-by-step recommendations assist the academic researcher in making choices when analyzing moderators and mediators, by not only taking a theoretical perspective, but also a managerial (relevance) perspective. Adding moderators/mediators may for instance challenge the “core logic of managerial practice” (in terms of thinking and decision making), even if it does not change the “core logic of a theory” as such. In the other direction, academics (and their theory) may be challenged by practitioners, in the way they define moderators/mediators and their levels. The steps in this article relate to aspects such as measurability, controllability and role of moderators and mediators in managerial problem and decision contexts. In case of multiple moderating and/or mediating variables, the decision architecture for managers becomes more complex, especially when the effects are countervailing/opposite. Multiple studies in this article illustrate that in that case, making optimal decisions becomes a “balancing” act for managers/decision makers and may even challenge their common beliefs (e.g. linear thinking).

The guidelines on managerial relevance of moderating and/or mediating variables and their effects can be used by academic researchers and editors of academic journals, pursuing not only academic rigor, but also managerial relevance. Besides being a guide for managerially relevant output, it also helps in determining for which questions in the research process, input from practitioners or at least insights from practice (e.g. through sources such as business magazines and portals) may be needed. The guidelines may also be used for teaching purposes, complementing more theoretical articles that mainly focus on methodological/statistical issues of moderating/mediating variables and their effects.

The COVID-19 pandemic dramatically affected the fire service: stay-at-home orders and potential exposure hazards disrupted standard fire service operations and incident patterns. The ability to predict incident volume during such disruptions is crucial for dynamic and efficient staff allocation planning. This work proposes a model to quantify the relationship between the increase in “residential mobility” (i.e. time spent at home) due to COVID-19 and fire and emergency medical services (EMS) call volume at the onset of the pandemic (February – May 2020). Understanding this relationship is beneficial should mobility disruptions of this scale occur again.

The analysis was run on 56 fire departments that subscribe to the National Fire Operations Reporting System (NFORS). This platform enables fire departments to report and visualize operational data. The model consists of a Bayesian hierarchical model. Text comments reported by first responders were also analyzed to provide additional context for the types of incidents that drive the model’s results.

Overall, a 1% increase in residential mobility (i.e. time spent at home) was associated with a 1.43% and 0.46% drop in EMS and fire call volume, respectively. Around 89% and 21% of departments had a significant decrease in EMS and fire call volume, respectively, as time spent at home increased.

A few papers have investigated the impact of COVID-19 on fire incidents in a few locations, but none have covered an extensive number of fire departments. Additionally, no studies have investigated the relationship between mobility and fire department call volumes.