Operation and Supply Chain Management
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Browsing Operation and Supply Chain Management by Author "Qazi, Abroon"
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Item Impact assessment of country risk on logistics performance using a Bayesian Belief Network model(Emerald Group Holdings Ltd., 2023-05-05) Qazi, Abroon; Simsekler, Mecit Can Emre; Formaneck, StevenPurpose: This paper aims to assess the impact of different drivers of country risk, including business environment, corruption, economic, environmental, financial, health and safety and political risks, on the country-level logistics performance. Design/methodology/approach: This study utilizes three datasets published by reputed international organizations, including the World Bank Group, AM Best and Global Risk Profile, to explore interactions among country risk drivers and the Logistics Performance Index (LPI) in a network setting. The LPI, published by the World Bank Group, is a composite measure of the country-level logistics performance. Using the three datasets, a Bayesian Belief Network (BBN) model is developed to investigate the relative importance of country risk drivers that influence logistics performance. Findings: The results indicate a moderate to a strong correlation among individual risks and between individual risks and the LPI score. The financial risk significantly varies relative to the extreme states of the LPI score, whereas corruption risk and political risk are the most critical factors influencing the LPI score relative to their resilience and vulnerability potential, respectively. Originality/value: This study has made two unique contributions to the literature on logistics performance assessment. First, to the best of the authors’ knowledge, this is the first study to establish associations between country risk drivers and country-level logistics performance in a probabilistic network setting. Second, a new BBN-based process has been proposed for logistics performance assessment and operationalized to help researchers and practitioners establish the relative importance of risk drivers influencing logistics performance. The key feature of the proposed process is adapting the BBN methodology to logistics performance assessment through the lens of risk analysis. © 2021, Emerald Publishing Limited.Item Prioritizing risks in sustainable construction projects using a risk matrix-based Monte Carlo Simulation approach(Elsevier Ltd, 2021-02) Qazi, Abroon; Shamayleh, Abdulrahim; El-Sayegh, Sameh; Formaneck, StevenSustainability-related risks and risk management frameworks have been introduced in the literature to help project managers identify and manage critical risks influencing project sustainability. Theoretically grounded in the framework of Monte Carlo Simulation, this paper introduces and operationalizes a new process for prioritizing sustainability-related project risks using risk matrix data. Sustainability-related construction project risks have never been assessed relative to different confidence levels across the risk matrix-based exposure zones. The application of the proposed process on construction projects completed in the United Arab Emirates reveals that the conventional risk prioritization scheme undermines the importance of tail risks (unexpected events), whereas such risks are captured in the proposed process. In contrast to the most critical risks identified using the conventional scheme such as shortage of client's funding, insufficient or incorrect sustainable design operation, and design changes, the proposed process prioritizes risks such as poor productivity of labor and equipment in sustainable construction, unreasonable tight schedule for sustainable construction, and poor scope definition of sustainable construction. The proposed process is generalizable to prioritizing risks influencing sustainability in international construction projects and beneficial for enhancing project sustainability as there is a huge uncertainty associated with sustainability-related risks. © 2020 The Author(s)Item Supply chain risk network value at risk assessment using Bayesian belief networks and Monte Carlo simulation(Springer, 2023-03) Qazi, Abroon; Simsekler, Mecit Can Emre; Formaneck, Steven