Use of survival analysis to assess supply chain resilience

Motivation

Global supply chains are under increasing pressure - be it from geopolitical tensions, pandemics or natural disasters. In this context, the ability of supply chains to recover from disruptions (resilience) is becoming increasingly important. Survival analysis methods, originally used in medicine and reliability engineering, offer exciting approaches for analyzing downtimes and recovery times within supply chains. The aim of this thesis is to systematically investigate the potential of these methods in the context of supply chain resilience and to evaluate them on the basis of a use case.

Procedure of the bachelor thesis

1. Preliminary discussion (kick-off):
   Joint clarification of the objectives, structure and expectations of the thesis. Initial review of relevant literature.
2. Exposé (approx. 2-4 weeks):
   Preparation of a written exposé with research questions, methodology (in particular structure of the SLR) and timetable. Feedback discussion for finalization.
3. Registration:
   After a successful exposé, the thesis is formally registered with the examination office.
4. Implementation:
   • Part 1: Systematic literature review (SLR) on applications of survival analysis in supply chain and resilience contexts.
   • Part 2: Methodical comparison of suitable procedures (e.g. Kaplan-Meier, Cox regression) based on a defined use case
   • Part 3: Critical reflection and recommendations for science and practice.

Close supervision

We attach great importance to structured and closely supervised support. In addition to regular feedback meetings, we provide support with

• Method selection and literature review (SLR techniques),
• Structuring the analysis,
• implementation of data analysis methods (e.g. in Python or R).

Supervisor / contact person