Could game theory help us understand risk in contracting?
3 min read
- Risk management
- New Zealand
The ITA has a goal of exploring new approaches that may provide fresh perspectives and unpick some of the issues facing the building and construction industry.
Over the summer break, four university students were engaged by the ITA to see whether maths and data science techniques could unlock new insights into contracting and risk.
Specifically, the interns worked on two projects – Optimal Contracting which looked at spreading risk in the industry, and Contracting Networks which looked at connectivity and failure in contracting networks.
Through their work they came up with some interesting new approaches which may have value down the track.
Collaborative contracting model proposed
For his study of optimal contracting, Jack Skerman explored whether game theory could help provide a perspective on collaborative contracting versus conventional contracting. He asserted that “a collaborative contracting model has the potential to transform the risk landscape of the construction industry”.
Under this type of model, a project owner pledges to share the benefits they receive from an exceptional performance by non-owner participants, for example subcontractors. The non-owner then has a financial motivation to align their incentives with the project owner and act in the best interest of all parties.
Jack said using this collaborative contracting approach could, in theory, deliver a big increase in long-term payoff for the project owners. For example, using the theoretical model, based on a project owner completing 500 projects, the increase in financial yield for the owner would be approximately 6 percent more than using a conventional contracting model. Subcontractors would share the increase in revenue.
Analysing contracting networks
The topic of Contracting Networks, and the related issue of cascading failure, was tackled by Rebecca Cui, Jackie Excell and Ella Laing. They explored whether relationships, networks and connectivity between companies could provide insights into the cascading of failure across the network.
They analysed connectivity between companies using information gleaned from news data and developed a simulation calculation of the cascading effect of failure using real data supplied by the University of Auckland’s property department.
Te Pūnaha Matatini director Professor Shaun Hendy said the team looked at the industry using a network approach.
“This was in much the same way as we analysed the All Blacks a few years ago. How does the performance of one player in the industry affect all the others? Are there industry players which, if they fail, can cause a cascade of failure across the industry?
“It’s early days yet, but this approach might allow us to design new types of contracting arrangements that can make the industry more resilient and more productive in the long run."
ITA programme leader Karla Falloon says both these projects have generated ideas for future work.
“We will continue to explore how different methods and capabilities could be brought to some of the gnarly issues in the industry.
“Maybe they will help uncover some insights into the complexities that exist in the construction industry that we haven’t fully understood before.”
Introducing the researchers
The four students were part of the summer internship programme at Te Pūnaha Matatini, a Centre of Research Excellence at The University of Auckland. They brought a range of skills to the projects including maths, data science, engineering and commerce.
Being able to extract and analyse information from the data was a key component of both projects. All the students enjoyed applying their theoretical knowledge to practical real-life issues in the construction industry.
Jack Skerman has completed a Bachelor of Science in maths and is now doing honours. He hopes to continue his studies overseas.
Rebecca Cui has a Bachelor of Commerce and is currently completing a Masters in Data Science. She is interested in visualisations and will be looking for a job which combines strategy and data analysis.
Jackie Excell has a Bachelor of Chemical Engineering and is part-way through a Masters in Data Science. She sees lots of possibilities for jobs related to machine learning or artificial intelligence.
Ella Laing has a Bachelor of Engineering and a Masters in Data Science. She is keen to work in a field related to data analysis.