Exploring dependency based probabilistic supply chain risk measures for prioritising interdependent risks and strategies

In this paper, we introduce an integrated supply chain risk management process that is grounded in the theoretical framework of Bayesian Belief Networks capturing interdependency between risks and risk mitigation strategies, and integrating all stages of the risk management process. The proposed process is unique in four different ways: instead of mapping the supply network, it makes use of Failure Modes and Effects Analysis to model the risk network which is feasible for modelling global supply chains; it is driven by new dependency based risk measures that can effectively capture the network wide impact of risks for prioritisation; it utilises the concept of Shapley value from the field of cooperative game theory to determine a fair allocation of resources to the critical risks identified; and the process helps in prioritising potential risk mitigation strategies (both preventive and reactive) subject to budget and resource constraints. We demonstrate its application through a simulation study

STRATEGI KOMUNIKASI DALAM MENCEGAH KERUSUHAN DI LEMBAGA PEMASYARAKATAN

In Indonesia, it is not uncommon to hear news about the Correctional Institutions riots. There have been recorded several cases of riots in 2020, for example Lembaga Pemasyarakatan Class I Cirebon, Lembaga Pemasyarakatan Class II A Manado, etc. Such riots were triggered by sensitivity due to friction between the Prison-Based Prisoners and Correctional Officers and among Correctional Prisoners. Therefore special attention is needed regarding this problem with prevention so that the prison environment remains conducive, one of which is the communication strategy. The purpose of this research is to find out how the communication strategy is in preventing riots in prisons. This research uses qualitative methods and data collection techniques of literature study. The results of the study found a strategy by utilizing daily interactions between inmates and officers as well as between inmates. The use of communication strategies can be one of the important efforts to prevent riots in prison. So that understanding of communication strategies needs to be considered by officers for a conducive prison environment

Risk matrix driven supply chain risk management: Adapting risk matrix based tools to modelling interdependent risks and risk appetite

There is a major research gap of developing a supply chain risk management process integrating the risk appetite of a decision maker and all stages of the risk management process within an interdependent network of systemic risks. We introduce an iterative process, namely risk matrix driven supply chain risk management, to bridge this gap. We make use of the recently introduced concept of utility indifference curves based risk matrix to capture the risk attitude of a decision maker. We also present algorithms for assessing and mitigating interdependent risks for risk-neutral and risk-averse/seeking decision makers and demonstrate the application of our proposed process through a simulation study. Utilising the method of cost-benefit analysis within an interdependent setting of interacting risks and risk mitigation strategies, we also propose a second approach that can help a decision maker to determine a set of Pareto-optimal risk mitigation strategies and select optimal solutions subject to the budget constraint and specific risk appetite

Supply chain risk network management : a Bayesian belief network and expected utility based approach for managing supply chain risks

The paper develops and operationalises a supply chain risk network management (SCRNM) process that captures interdependencies between risks, multiple (potentially conflicting) performance measures and risk mitigation strategies within a (risk) network setting. The process helps in prioritising risks and strategies specific to the decision maker's risk appetite. The process is demonstrated through a case study conducted in a global manufacturing supply chain involving semi-structured interviews and focus group sessions with experts in risk management. Theoretically grounded in the framework of Bayesian Belief Networks (BBNs) and Expected Utility Theory (EUT), the modelling approach has a number of distinctive characteristics. It utilises a top-down approach of Fault Tree Analysis (FTA). Performance measures are identified first and subsequently connected to risks. A 'probability conditional expected utility' matrix is introduced to reflect the propagation impact of interdependent risks on all performance measures identified. A 'weighted net evaluation of risk mitigation' method is proposed and the method of 'swing weights' is used to capture the tradeoff between the efficacy of strategies and the associated cost keeping in view the decision maker's risk appetite. The approach adapts and integrates techniques from safety and reliability engineering (FTA), decision making under uncertainty (EUT), and multi-criteria decision analysis (swing weights). The merits and challenges associated with the implementation of interdependency based frameworks are discussed. Propositions are presented to elucidate the significance of modelling interdependency between risks and strategies

A fuzzy-based holistic approach for supply chain risk assessment and aggregation considering risk interdependencies

Producción CientíficaSupply chain risk management requires dealing with uncertainty, interrelations, and subjectivity inherent in the risk assessment process. This paper proposes a holistic approach for risk management that considers the impact on multiple performance objectives, the relation between risk agents, and the risk event interdependencies. An aggregated risk score is proposed to capture the cascading effects of common risk triggers and quantify the aggregated score by risk agent and objective. The approach also uses fuzzy logic to allow for the treatment of vague and ambiguity data as input parameters to the model from different domains and scales, according to knowledge and criteria nature. The integration of the balanced scorecard tool improves the analysis and prioritization of mitigation strategies in decision-making, both by risk agent and by strategic objective. A case study of a telecommunication company is presented to illustrate the applicability of the proposed approach

A framework for integrity assessment of multiscale energy infrastructures

The climate change phenomena represent a global issue that could significantly impact on world economic and social systems. During last decades, several international bodies and institutions (like the IPCC) developed scientific techniques to analyse the causes and effects of these phenomena, their evolution over time and possible future scenarios. According to these studies, in order to face climate change and air pollutant emissions issues several targets have been hypothesized and proposed. In particular, the ones related to the Paris Agreement (COP21) can be mentioned. These goals require, in the mid/long-term, significant changes in the structure of the energy systems at global level, aiming at achieving their substantial decarbonisation through the so-called “energy transition”. The implementation of this transition could be obtained by means of different pathways. In particular, two extreme options can be identified. On one side, a wide electrification of final uses, coupled with power generation from renewables and long-distance transmission through global interconnections. On the other, small-scale energy systems based on electricity, heat and gas produced by renewables sources, characterized by power generation from wind, solar photovoltaic and small hydro and with a relevant role played by storage systems. It can be expected that the future configuration of the global energy systems will be a mix of these extreme solutions. In every case, however, a crucial role will be played by the infrastructures for supplying, transmitting and distributing energy. For this reason, the integrity of these infrastructures – at all spatial levels (transnational gas and oil pipelines, maritime routes, power lines, district heating networks, etc.) – is a key factor for ensuring the long-term energy transition strategies. The integrity measures the capability of a given infrastructure to perform its function according to what is requested and to be properly managed from several points of view, including safety, environmental protection, maintainability, productivity, etc. Therefore, it is a concept more general than “security”, as it is multi-dimensional. Furthermore, the integrity is directly related to the development of infrastructures. The evolution of the current energy systems in the sense of the energy transition needs to plan the infrastructures architecture according to criteria that have to be not only technological, but also able to consider all the possible issues that can threat their integrity. In a long-term perspective, these issues should not be investigated through ex-post analyses, but they should be taken into account as much as possible in the design phase. Starting from this, the main goal of the doctoral project has been the identification of a multiscale approach for assessing the integrity of energy infrastructures. A two-dimensional scheme has been proposed, considering different spatial scales (energy corridors, transmission/distribution infrastructures, local networks) and kind of threats (natural, accidental, intentional) and assessing the impacts on the integrity dimensions (technological, geopolitical, environmental, economic) In particular, five case studies have been considered, covering all the considered spatial scales with respect to different integrity dimensions and threats. They focused on the geopolitical supply security, the resilience of distribution infrastructures, the effects of renewables penetration, the reliability of district heating networks and the impact of innovative vectors on the security. The obtained results showed that this multidimensional approach can be useful in defining guidelines for the integrity assessment and the development of energy infrastructure under a holistic perspective, in order to support the policy decision-making about strategical investments and their prioritization, planning, management, and identification and ranking of criticalities

Resilience-enhancing solution to mitigate risk for sustainable supply chain-an empirical study of elevator manufacturing

As the complexity of supply chains increases, the enhancement of resilience for mitigating sustainable disruption risks in supply chains is an important issue. Quality function deployment (QFD) has been successfully applied in many domains to solve multicriteria decision-making (MCDM) problems. However, research on developing two houses of quality to connect sustainable supply chain disruption risks, resilience capacities, and resilience-enhancing features in elevator manufacturing supply chains by using the MCDM approach is lacking. This study aims to develop a framework for exploring useful decision-making by integrating the MCDM approach and QFD. By applying the framework, supply chain resilience can be improved by identifying the major sustainable risks and the key resilience to mitigate these risks. Important managerial insights and practical implications are obtained from the framework implementation in a case study of the elevator manufacturing industry. To strengthen resilience and thus mitigate key risks, the most urgent tasks are to connect the working site and the backstage to enhance product development and design and to share real-time job information. When these features are strengthened, agility, capacity, and visibility can be improved. Finally, unexpected events lead to changes in supplier delivery dates, and factors such as typhoon and lack of critical capacities/skilled employees with the greatest impact can be alleviated. This framework will provide an effective and pragmatic approach for constructing sustainable supply chain risk resilience in the elevator manufacturing industry.</p

Evaluating network criticality of interdependent infrastructure systems: applications for electrical power distribution and rail transport

Critical infrastructure provides essential services of economic and social value. However, the pressures of demand growth, congestion, capacity constraints and hazards such as extreme weather increase the need for infrastructure resilience. The increasingly interdependent nature of infrastructure also heightens the risk of cascading failure between connected systems. Infrastructure companies must meet the twin-challenge of day-to-day operations and long-term planning with increasingly constrained budgets and resources. With a need for an effective process of resource allocation, this thesis presents a network criticality assessment methodology for prioritising locations across interdependent infrastructure systems, using metrics of the expected consequence of an asset failure for operational service performance. Existing literature is focused mainly upon simulating the vulnerability of national-scale infrastructure, with assumptions of both system dynamics and dependencies for simplicity. This thesis takes a data-driven and evidence-based approach, using historical performance databases to inherently capture system behaviour, whilst network diagrams are used to directly identify asset dependencies. Network criticality assessments are produced for three applications of increasing complexity from (i) electricity distribution, to (ii) railway transport, to (iii) electrified railway dependencies on external power supplies, using case studies of contrasting infrastructure management regions. This thesis demonstrates how network criticality assessments can add value to subjective tacit knowledge and high-level priorities both within and between infrastructure systems. The spatial distribution of criticality is highlighted, whilst the key contribution of the research is the identification of high-resolution single points of failure and their spatial correlation across systems, particularly within urban areas. Service-level metrics also have a broad applicability for a range of functions, including incident response, maintenance and long-term investment. The role of network criticality within a holistic and systemic decision-making process is explored, for risk assessment and resilience interventions. The limitations of the research, regarding sample-size caveats and the definition of system boundaries within performance databases, lead to recommendations on cross-system fault reporting and the improvement of information systems

Project complexity and risk management (ProCRiM) : towards modelling project complexity driven risk paths in construction projects

Project complexity has been extensively explored in the literature because of its contribution towards the failure of major projects in terms of cost and time overruns. Focusing on the interface of Project Complexity and Interdependency Model ling of Project Risks, we propose a new process that aids capturing interdependency between project complexity, complexity induced risks and project objectives. The proposed modelling approach is grounded in the theoretical framework of Expected Utility Theory and Bayesian Belief Networks. We consider the decision problem of identifying critical risks and selecting optimal risk mitigation strategies at the commencement stage of a project, taking into account the utility function of the decision maker with regard to the importance of project objectives and holistic interaction between project complexity and risk. The proposed process is supported by empirical research that was conducted in the construction industry in order to explore the current practices of managing project compl exity and the associated risks. The experts interviewed acknowledged the contribution of the proposed process to the understanding of complex dynamics between project complexity attributes and risks. Application of the proposed process is illustrated through a simulation study