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Supervisor: Dr. Mudassar Ali, Associate Professor

 

Developing Resilience in Pakistan’s Oil and Gas Supply Chains: Using Fuzzy Logic and Bayesian Belief Networks to Mitigate Terrorism-Induced Disruptions

 

Supervisor: Dr. Mudassar Ali, Associate Professor

Campus/School/Dept: Project Management and Supply Chain Management Department, Bahria Business School

RAC Approved Supervisor for Research Areas: Project Management

Supervisory Record

  • PhD Produced: 0
  • PhD Enrolled: 1
  • MS/MPhil Produced: 7
  • MS/MPhil Enrolled: 7

 

Topic Brief Description:

This study aims to analyze the risks of pipelines, infrastructure for storage, and logistical structures to deal with the critical challenges that terrorism presents to Pakistan’s oil and gas supply chains. The investigation will investigate innovative analytical methods and responsive leadership strategies to improve operational security by incorporating perspectives from project management and supply chain management. Data-driven approaches to risk reduction will be enabled by implementing advanced decision-support tools, such as Bayesian Belief Networks (BBNs) and fuzzy logic, to quantify uncertainty and evaluate the probability of disruptions. The study will also investigate the resilience of human and organizational systems, particularly emphasizing the importance of cross-stakeholder engagement and on-the-ground teams in maintaining continuity during crises. Using a combination of modeling simulations, stakeholder interviews, and case studies, this study will suggest strategic supply chain revamps that mitigate single points of breakdown, balance cost-security trade-offs, and facilitate proactive risk management. To guarantee Pakistan’s energy sector’s robustness toward geopolitical threats and its critical role in national economic strength, the findings aim to contribute to its sustainable development.

 

Research Objectives/Deliverables:

  1. Investigate the impact of terrorism on essential supply chain infrastructure, including pipelines, storage facilities, and logistical networks, and the potential consequences for the ongoing operation of oil and gas supply chains in Pakistan.
  2. Explore how effective decision-making processes and responsive leadership styles contribute to reducing the detrimental effects of terrorism on the oil and gas supply chain.
  3. Apply Bayesian belief networks and fuzzy logic to measure uncertainty and evaluate the risk of terrorism-related interruptions in oil and gas supply systems.
  4. Consider restructuring techniques for oil and gas supply networks that mitigate risks and enhance resilience against terrorism-related interruptions.

 

Deliverables

  1. In-depth analysis of the effects of terrorism on oil and gas supply networks in Pakistan, pinpointing critical weaknesses in logistics and infrastructure while evaluating the consequences for supply chain continuation.
  2. A paradigm for supply chain leadership emphasizing flexible decision-making and risk management measures to mitigate terrorism-related interruptions successfully.
  3. The creation of fuzzy logic models using Bayesian Belief Networks to assess and quantify risks related to terrorist interruptions in the oil and gas supply chain, aimed at practical uses for adaptive risk mitigation.
  4. A series of strategic proposals for reconfiguring oil and gas supply networks to enhance resilience, mitigate risks, and augment redundancy in response to terrorism challenges.

 

Research Questions: 

  1. How do delays caused by terrorism affect Pakistan’s oil and gas supply chains’ most vulnerable points, and how do they damage their capacity to continue operating?
  2. How can leadership methods in the supply chain be changed to better handle and minimize complications caused by terrorism in the oil and gas sector?
  3. How can fuzzy logic and Bayesian Belief Networks be utilized to determine the risk of oil and gas supply lines being disrupted by terrorists?
  4. How can effective modifications be made to oil and gas supply chains to make them more resilient, secure, and able to function even when terrorist risks exist?

 

Candidate’s Eligibility Profile:

  1. The applicant must have an MS/MPhil/Equivalent degree in project management/supply chain management with a CGPA > 3.0. Applicants must also have a strong background in data analytics techniques (Bayesian belief network, fuzzy logic, System Dynamics, Multi-Criteria Decision Analysis, and SEM), project management and supply chain management design/system thinking theories, and related fields.
  2. Experience with programming languages such as Python, SMART PLS, STATA, and SPSS is advantageous. Candidates should thrive in an international environment and have excellent communication skills to contribute actively to team research efforts.
  3. The candidate must be preferred based on SSCI (W-category) publication numbers and relevance to the proposed research topic.
  4. Proficiency in spoken and written English is essential. We value independence and responsibility while promoting teamwork and collaboration among colleagues.