Due to the increasing occurrence of disruptive events caused by both human and also natural disasters, supply chain risk management has become an emerging research field in recent years, aiming to protect supply chains from various disruptions and deliver sustainable and long-term benefits to stakeholders across the value chain. Implementing optimum designed risk-oriented supply chain management can provide a privileged position for various businesses to extend their global reach. In addition, using a proactive supply chain risk management system, enterprises can predict their potential risk factors in their supply chains, and achieve the best early warning time, which leads to higher firms' performance. However, relatively little is known about sustainable risks in food supply chains. In order to manage the ever-growing challenges of food supply chains effectively, a deeper insight regarding the complex food systems is required. Supply chain risk management embraces broad strategies to address, identify, evaluate, monitor, and control unpredictable risks or events with direct and indirect effect, mostly negative, on food supply chain processes. To fill this gap, in this paper we have critically discussed the related supply chain risk management literature. Finally, we propose a number of significant directions for future research.
Abstract. Recently, we have witnessed son many natural catastrophies such as earthquakes in Japan, severe floods in the UK, US and many other parts of the world. In addition businesses have been losing tens of billions of dollars because there have been various natural and man-made disasters. However, the Disaster Management System (DMS) and system that have been put in place have proven important means of reducing the risk of damages to businesses, in particular. The DMS can minimize and in some cases, eliminates the risks through technical, management or operational solutions (risk management effort). However, it is virtually impossible to eliminate all risks. Information technology systems, for example, are vulnerable to a variety of disruptions (e.g. short-term power outage, disk drive failure) from a variety of sources such as natural disasters to terrorist actions. In many cases, critical resources may reside outside the organizations control (such as telecommunications or electric power), and the organization may be unable to ensure their availability. This study proposes a model for Disaster Management System as an Element of Risk Management using the PESTLE framework. Thus, an effective Disaster Management System in the form of contingency planning, execution and testing are essential to mitigate the risk of system and service availability. We have developed a global model for Disaster recover planning and management based on the PESTLE framework which can be customized and applied to a variety of disasters prone systems such natural, emergency, IT/Network/Security, Data recovery, and incident-response systems. The main aspect of this model has been currently used and evaluated.
Due to the dynamic nature of the food supply chain system, food supply management could suffer because of, and be interrupted by, unforeseen events. Considering the perishable nature of fresh food products and their short life cycle, fresh food companies feel immense pressure to adopt an efficient and proactive risk management system. The risk management aspects within the food supply chains have been addressed in several studies. However, only a few studies focus on the complex interactions between the various types of risks impacting food supply chain functionality and dynamic feedback effects, which can generate a reliable risk management system. This paper strives to contribute to this evident research gap by adopting a system dynamics modelling approach to generate a systemic risk management model. The system dynamics model serves as the basis for the simulation of risk index values and can be explored in future work to further analyse the dynamic risk’s effect on the food supply chain system’s behaviour. According to a literature review of published research from 2017 to 2021, nine different risks across the food supply chain were identified as a subsection of the major risk categories: macro-level and operational risks. Following this stage, two of the risk groups identified first were integrated with a developed system dynamics model to conduct this research and to evaluate the interaction between the risks and the functionality of the three main dairy supply chain processes: production, logistics, and retailing. The key findings drawn from this paper can be beneficial for enhancing managerial discernment regarding the critical role of system dynamics models for analysing various types of risks across the food supply chain process and improving its efficiency.
As the application of computer technology continues to proliferate and diversify, vehicles are becoming increasingly intelligent and it is expected that in the near future they will be equipped with radio interfaces for short range communications. This will enable the formation of vehicular networks, commonly referred to as VANETs, an instance of mobile ad hoc networks with vehicles as mobile nodes. Vehicular networks are receiving a lot of attention due to the wide variety of services they can provide and are likely to be deployed commercially in coming years. Security is a fundamental issue because such networks will provide the necessary infrastructure for various applications that can help improve the safety of road traffic. Effective security of vehicular ad hoc network is an ill-defined problem as most existing security mechanisms available for VANET do not combine efficiency, security and traceability. They tend to score well in one or two qualities, but not all three because of the potential contradictions between some of their attributes. In this paper, we give an overview of VANETs and the security challenges related to their deployment. We identify and analyse current security limitations, then an effort is made to show that efficiency, security and traceability are the key qualities to consider while implementing an effective security mechanism. Therefore the most suitable way to achieve this goal is by identifying the intersection point connecting their attributes.
This paper aims to critically examine the potential barriers to the implementation and adoption of Robotic Process Automation (RPA) in the beef supply chain. The beef supply chain has been challenging due to its complex processes, activities, and management. The beef industry has relied heavily on the human workforce in the past; however, RPA adoption allows automating tasks that are repetitive and strenuous in nature to enhance beef quality, safety and security. There are considerable potential barriers to RPA adoption as organisations have not focused on trying to eliminate them due to various reasons. Previous studies lack knowledge related to potential barriers to RPA adoption, so this creates a research gap and requires attention. Statistical data and information are extracted using secondary data relevant to RPA adoption in the beef supply chain. A business process model is formed which uses values or variables using existing statistical data and information. Simulation of the process model is carried out using Simul8 software and analyses of different scenarios help in choosing the best approach for RPA adoption. Results have identified the potential barriers in RPA adoption through the simulation process thus ensuring RPA performs with more potential. Analysis of ‘what-if’ scenarios allows organizational and employee-level improvements along with enhancing RPA’s accuracy. The process model is a generic model for use in real-life scenarios and can be modified by organisations according to their own business needs and requirements. The study contributes in theoretical and practical aspects as it allows decision-makers and managers to adopt RPA in a robust manner and adds to scientific knowledge by identification of potential barriers to RPA adoption.
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