Analysis of Risk Factors for Temperature-Controlled Warehouses

Abstract

This paper investigates risk factors associated with temperature-controlled warehouses with the aim of improving long-run performance of cold chains. A risk mitigation strategy is derived through Interpretive Structural Modelling (ISM) and a graphical hierarchy is presented to prioritize the impact levels of the risk factors. The paper also critically examines the contextual relationship between individual potential risk factors associated to temperature-controlled warehouses. The findings provide pathways to predict uncertainties that can lead to operational interruptions in temperature-controlled warehouses alongside expert opinions that lead to the development of risk mitigation strategies. Given its integrated approach considering identification, evaluation, analysis, and risk mitigation in temperature-controlled warehouses, we believe this paper helps to enrich both the practice and the literature. With the profound increase of significance in cold chains within the broader domain of supply chain management, this paper provides inspiration to more research in cold chains and temperature-controlled warehouses.

Assessment and risk mitigation on halal meat supply chain using fuzzy best-worst method (BWM) and risk mitigation number (RMN)

“…RMN is a new calculation concept introduced by Prakash et al (2017). The RMN method aims to find the right mitigation strategy to minimize the factors causing the emergence of risk (Sugathadasa et al , 2021). Several studies have used the RMN method to solve the problem of risk mitigation.…”

“…Other studies use RMN for risk mitigation, namely, the research conducted by Sugathadasa et al (2021), who perform risk identification using ISM while risk mitigation using RMN. In this study, it was found that there were 30 risks and 20 risk mitigations, which would then be identified with ISM and mitigated with RMN.…”

“…Therefore, risk mitigation measures are implemented to reduce the risk and minimize its potential impact. The determination of mitigation strategies should be designed to minimize the impact of risk factors that need to be followed up to control the industry’s consequences (Sugathadasa et al , 2021).…”

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“…Along with industry 4.0 and extended involvement of information and communication technologies, converting warehouses into smart environments has become a trend. Supply chains have more complex and dynamic systems in the present day [1]. Therefore, logistics systems play an important role in implying efficient coordination throughout the supply network.…”

Artificial Neural Network Based Demand Forecasting Integrated With Federal Funds Rate

“…Stockouts and overstocks are caused due to inaccuracy of demand forecasts which result in long-term customer dissatisfaction, customer loss, high inventory costs and waste of resources (Huang, Fildes, & Soopramanien, 2019;Yang, Goh, Xu, Zhang, & Akcan, 2015). Thus, accurate demand forecasting is crucial to take proactive measures in supply chain risk management (Perera, Thibbotuwawa, Rajasooriyar & Sugathadasa, 2016;Sugathadasa, Wakkumbura, Perera & Thibbotuwawa, 2021).…”