I already reviewed some articles by Denis Towill primarily because he does some interesting research on simulation and supply chains, but also because I like his clear style in his articles.
In one of his early papers (1992) he teamed up with Naim and Wikner and described state of the art strategies to fight the bullwhip effect or as it is called in the paper by its older name: Industrial Dynamics.
At the moment I am focussing more on the interviews I am conducting for my research, so I am not reading as much anymore. I therefore try to select articles which are both useful for my research and my blog.
I have read several articles by Mark Daskin (also reviewed another one here). So with him on the author list of today’s paper I think one can expect a clearcut research question, some kind of mathematical model, a fitting solution method and a definite answer to the underling problem. Well, let’s have a look!
In 2010 Lassar et al. did a grounded theory study (see here for more information on techniques for theory creation) on the question of what the determinants of strategic supply chain risk management might be?
This is another introductory article (book chapter) to supply chain risk management. I included it, since it is an early (2003) view on supply chain risk management from another perspective. Many other articles I reviewed up to now are following the “Cranfield School Approach” with (Christopher, Jüttner, …) and this one by Peter Kajüter (Münster University, Germany) shows a different approach developed in parallel.
Today I introduce you to the process of measuring agility in a supply chain. Agility is a major concept in the research of the last 10 years or so. I already have written some articles on this topic:
There are many definitions of agility. A supply chain can be defined as agile, when it is flexible and responds quickly to customer needs. Agility can also be seen as a measure to mitigate supply chain risks, building on this thought Dani and Ranganathan (2008) developed a model to mitigate risks using the concept of agility .
The quantification of supply chain planning is the next step in the field of supply chain optimization. After operational and logistical aspects have been modeled and optimized, margins for further improvement remain slim.
Based on this premise the paper I review today suggests and tests several alternative multilevel planning approaches to gain further supply chain improvements by optimizing the mid-term supply chain design.
