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Management Procedures: The Soft Side of IAQ Success
Published in H.E. Burroughs, Shirley J. Hansen, Managing Indoor Air Quality, 2020
H.E. Burroughs, Shirley J. Hansen
The advantages of a proactive program include providing occupants a comfortable productive environment; enhancing management/employee relations or management/tenant relations; improving building operations and maintenance; and providing an increasingly important selling point for marketing property.
Tracking and Trending Performance
Published in Frances Alston, Brian K. Perkins, Strategic Environmental Performance, 2020
Frances Alston, Brian K. Perkins
Proactivity: Stay on top of how work is performed and refrain from waiting until something fails or goes wrong before improving them. Being proactive demonstrates that there is a plan and propensity to improve.
Federated machine learning for privacy preserving, collective supply chain risk prediction
Published in International Journal of Production Research, 2023
Ge Zheng, Lingxuan Kong, Alexandra Brintrup
The field of supply chain risk management (SCRM) studies risk management techniques that aim to reduce risk exposure in supply chains. Proactive strategies are mainly targeted at risk mitigation and include actions such as increased safety stock, multi-sourcing, information sharing, collaboration, and contingent rerouting. Most of these studies mainly focus on trade offs between enhanced resilience and the costs of adding redundancies or flexibility in supply sources or in-house production. Reactive strategies are deployed after a disruption occurs, and include strategies such as dynamic pricing to counter demand, supply chain reconfiguration, operational rerouting (Ghadge, Dani, and Kalawsky 2012). However, a priori prediction of risk in supply chains remains an unsolved problem that has received little attention.
Proactive management in the context of construction supply chains
Published in Production Planning & Control, 2020
Spearman correlation is used in this research to examine the correlation between each proactive management indicator and problem avoidance/minimization and the correlation between each proactive management indicator and continuous improvement. Table 3 shows a positive correlation of problem avoidance/minimization with each proactive management indicator and a positive correlation of continuous improvement with each proactive management indicator. All the correlations shown in Table 3 are significant at the 0.01 level. The findings provide strong evidence to demonstrate the real effect of proactive management. Hypotheses 3 and 4 are supported. As a result, proactive management proves to be a significant contributor to both problem avoidance/minimization and continuous improvement. Clearly, the findings in this research reveal the critical role of proactive management in ensuring the success of construction projects and supply chains. They explain why proactive management is more and more adopted in today’s construction practice. They also support the necessity of replacing reactive management with proactive management.
Cloud platforms for remote monitoring system: a comparative case study
Published in Production Planning & Control, 2020
Yuqiuge Hao, Petri Helo, Angappa Gunasekaran
At the early stage of remote monitoring, the data collection mainly relies on manual activities, such as barcode scanning or on-site downloading and then it is brought back for analysis (Guo et al. 2015). This results in incomplete and lagged data. Since business requirements have trended towards constant surveillance and rapid detection of changes, continuous data collection is now critical. Remote monitoring is entering a new era with the development of wireless sensing devices (Grubic 2012) and other Internet technologies (Wang, Peter and Lee 2006). When the data is accessed in real-time, it adequately achieves continuous remote monitoring and provides early warning information to enable proactive operations. The users can concentrate on data analysis rather than data collection. This is crucial to decision-makers so that they can find trends based on previous data and respond appropriately before an actual error happens.