The Most Competitive Airline Routes in the World

I am using airline data to construct a network of competition in the airline industry.  As part of this, I am listing the routes that are the most competitive – not necessarily the ones that have the most flights, but the ones that have the most competitors.

And here they are

Map generated from

HKG-ICN  Hong Kong – Incheon, Seoul (South Korea)

Not shown: EastarJet

TPE-NRT  Taipei (Taiwan) – Narita, Tokyo (Japan)

Not shown: Vanilla Air, Tiger Air, Scoot, Transasia

SIN-CGK   Singapore – Jakarta (Indonesia)

Not shown: Indonesian Air Asia, Scoot, JetStar Asia

SIN-DPS   Singapore – Denpasar, Bali (Indonesia)

Not shown: Qantas, Qatar, Indonesia Air Asia, Scoot (nb JetStar and JetStar Asia are different airlines)

Please note that these data are a few years old, are preliminary and not completely accurate, and airlines come and go on such competitive routes.

Two Funded PhD Studentships in Agent-Based Modelling at Loughborough University School of Business and Economics

I am looking for high quality, numerate, candidates to fill these exciting PhD studentships with me as a (co-) supervisor at Loughborough’s School of Business and Economics.

The first is modelling dynamic responses to dynamic threats; the second is using analytics in traditional industries.  Please see the links below for further details and how to apply.  Note that for further information, you will need to click on the blue links below.

Modelling Dynamic Responses to Dynamic Threats (with Professor Gilberto Montibeller)

One of the most challenging issues for policy makers dealing with bio-security threats is their dynamic nature: diseases may spread quickly and deadly among vulnerable populations and pandemics may cause many casualties.

Finding the appropriate response to threats is a major challenge.  Whilst models exist for understanding of the dynamics of the threats themselves, responses can be largely ad-hoc or ‘firefighting’.  The aim of this research is to produce robust responses for dynamic threats.

The research will build up as follows, from low to high complexity: static responses to static threats; static responses to dynamic threats; dynamic responses to static threats; and dynamic responses to dynamic threats.

We will use a variety of methods to define the best response: cellular automata, network analysis, spatial modelling, agent-based modelling, and the generation of dynamic fitness landscapes.

This PhD studentship is most suitable for candidates with a background in a quantitative discipline such as management science, operations research, engineering, physics and other natural sciences.

Business Analytics for Public Services and Regulated Industries: New Techniques for Analytics-Driven Decision Making in Traditional Industries (with Dr Maria Neiswand and Professor David Saal)

The rise of business analytics has given rise to enormous opportunities within the private sector, but these benefits have yet to be fully realized in public services and regulated industries such as energy, water, and transportation networks. Conversely, governments are mandating collection of data by installing smart metering devices. This gives rise to the need for innovative ways of thinking in industries that are still largely based on traditional economic thinking involving conventional assumptions on optimization and behaviour.

As an example, the energy sector is characterised by strongly defined market structures with incumbents and an ultimate need for energy network security, which not only prevents the quick adoption of technical changes but also translates into regulatory outcomes, such as price caps.

This exciting PhD opportunity will integrate theoretical and empirical approaches and spans two strengths of Loughborough’s School of Business and Economics: microeconomics and particularly rigorous analysis of the determinants of productivity and performance (including cost modelling) and management science (including simulation and network analysis).

We are therefore seeking a student with a quantitative background (whether in economics, management science, engineering, physics or other natural sciences). A willingness to learn new techniques such as, cost modelling, performance measurement, agent-based modelling and network analysis is desired.


Building the Multiplex: An Agent-Based Model of Formal and Informal Network Relations

EURO Conference 2016 PoznanThis presentation from the EURO 2016 conference in Poznan, Poland, and from the GDN conference in Bellingham, WA, USA, joint work with Leroy White of Warwick Business School, shows how combining formal and informal organizational networks enables decisions to flow more freely around organizations, but at a cost, leading to an optimal size of informal organizational networks.  If organizations can control these, this leads to implications for optimal information flows in companies.

When does Brokerage Matter? Citation Impact of Research Teams in an Emerging Academic Field

StrategicOrganizationThis paper with François Collet of ESADE and Daniela Lup of the LSE analyzes the emergence of the strategic management filed showing the benefits of network brokerage are stronger during the early phase of development and diminish over time.

Through exposure to heterogeneous sources of knowledge, actors who broker between unconnected contacts are more likely to generate valuable output. We contribute to the theory of social capital of brokerage by considering the impact of field maturity. Using longitudinal data from the field of strategic management we find that the benefits of network brokerage are stronger during the early stages of field development and diminish as the field matures. The results of our study call for further research on the interplay between network structures and processes of field emergence.


Topological Isomorphisms of Human Brain and Financial Market Networks

FrontSystNeuroThis paper, published with colleagues from Warwick University and Cambridge University: Petra Vertes, Ruth Nicol, Sandra Chapman, Nicholas Watkins, and Edward Bullmore was the result of inter-disciplinary work funded by the EPSRC – the Engineering and Physical Sciences Research Council (Grant number EP/H02395X/1).  We investigated the similarities in the network structure financial markets and brain networks.

Although metaphorical and conceptual connections between the human brain and the financial markets have often been drawn, rigorous physical or mathematical underpinnings of this analogy remain largely unexplored. Here, we apply a statistical and graph theoretic approach to the study of two datasets – the time series of 90 stocks from the New York stock exchange over a 3-year period, and the fMRI-derived time series acquired from 90 brain regions over the course of a 10-min-long functional MRI scan of resting brain function in healthy volunteers. Despite the many obvious substantive differences between these two datasets, graphical analysis demonstrated striking commonalities in terms of global network topological properties.