Analytics and Operations

Data defines the modern era. From customer spending patterns to supply chains, modern businesses must be able to gather and interpret the information available and translate it into business strategy.

Our faculty’s research encompasses the fields of data analytics and operational research. The common thread is how information can be used to extract a competitive advantage.

From devising original models capturing information in large datasets, to decision-making across all aspects of business operation, our research aims to leverage technical advances to bring practical insights.

Econometric Modelling and Forecasting

Econometric models are statistical models designed for use in economics, finance, marketing and elsewhere in the social sciences.

Research in this area involves developing new models and methods capable of capturing the rich information in today’s big datasets.

Examples of such research at MBS include models for the more accurate forecasting of downside risk in the macroeconomy, estimating the time-varying risk premia of thousands of assets during financial crises, methods for detecting jumps in the volatility of asset prices, and the modelling of inter-regional trade in the Australian electricity market.

Researchers: Tomohiro Ando, Worapree (Ole) Maneesoonthorn, Michael Smith

Revenue Management

Revenue management (RM) is a business practice to maximise profits by selling products to the right customer, at the right price, and at the right time.

It has been a very powerful managerial tool in exploiting the potential of increased revenues in many industries. Examples of such research at MBS involve developing models and methods to characterise optimal policies on pricing, resource allocation, and product assortments, as well as finding efficient algorithms to estimate and solve these models.

Researchers: Yalçın Akçay, Gerardo Berbeglia

Bayesian Analysis and Modelling

Bayesian methods and models are crucial tools for fully utilising the information in complex data.

They are a key component of the rapid advance in data science, including in business analytics. Researchers at MBS and FBE are at the forefront of research in this area.

They have developed new Bayesian models for macroeconomics, microeconomics, financial time series, marketing and business forecasting. They have also made major contributions to new Bayesian methodology suitable for extracting information from big data.

Researchers: Liana Jacobi, Worapree (Ole) Maneesoonthorn, Michael Smith; Yong Song,Tomasz Wozniak