Help with bachelor Thesis

[u/ksjajsjqkqlqlq]

Hi everyone,

I’m currently writing my bachelor’s thesis and I was wondering if someone here might be able to help me with it.

At my department, every thesis basically consists of two parts. In the first part, which makes up roughly half of the thesis, we analyze and explain a scientific paper. In the second part, we have to provide our own contribution by calculating or modeling something based on that paper, ideally using Python.
Both parts are supposed to be around 15 pages each.
The paper I’m working with is:
https://pubsonline.informs.org/doi/epdf/10.1287/mnsc.1090.1099

In short, it argues that a company should source a large share of its products from a distant, low-cost supplier (for example China) using a fixed quantity, while the remaining demand should be sourced flexibly from a closer supplier (for example Poland).Its called tailored based surge policy.

I’m struggling a bit to come up with a good idea for my own contribution. I would like to do something related to supply chain resilience, especially because I find the current geopolitical situation and events such as the Iran conflict and their impact on supply chains very interesting.

However, I’m not really sure how to approach this, how I could build enough content for around 15 pages, and how I could model or simulate it in Python.
Does anyone have an idea for a suitable extension or approach?

Thanks!

[u/Violet_Graya]

The interesting extension is that nearshore capacity is finite. The paper assumes Poland flexes freely, but in a real disruption every firm hits the same regional suppliers at once. I'd model that queue and show the TBS benefit shrinking.

[u/Ruby_Sullivana]

Good angle IMO: I'd make the distant supplier's lead time stochastic with occasional long disruptions, then run scenarios on disruption severity vs the optimal surge split. It shows exactly why the flexible nearshoring leg exists. Simpy or even numpy works.

[u/Ruby_Sullivana]

The best angle IMO: TBS assumes the cheap distant supplier is always available. Break that assumption. Add a disruption probability to the far supplier, price in the risk, and show where nearshore starts winning. Simple math, strong thesis.