|Coordinatore del Gruppo|
|Corrado Lo Storto - Professore di ingegneria economico-gestionale (ING-IND/35)|
|Settore ERC del Gruppo|
|SH1_3, SH1_6, SH1_9|
|Componenti del Gruppo|
|Gabriella Ferruzzi - Ph.D. Post-doc Researcher
Benedetta Capano - Ph.D. Student
The research team aims at conducting and supporting high quality research in the field of market and business analytics. Analytics can help both policy-makers and managers concerned with capturing and understanding information in order to make swift political and business decisions, and finally improve efficiency and productivity. Economic models relative to products, processes and infrastructure assets are specified and estimated for analyzing complex business and market problems and quantifying the effects of context, technology and regulatory environment changes.
Research on analytics is using several approaches, quantitative methods and tools that provide descriptive analytics (scorecards, clustering, basic statistics), prescriptive analytics (Data Envelopment Analysis, optimization, simulation), and predictive analytics (econometric modeling, statistical and machine learning techniques) to derive actionable insights and outcomes from available data. Scholars of the team undertake collaborative research and pursue consulting opportunities with a range of people in academia, business and government.
Research is focused on the following two major streams:
Infrastructure planning and economics
Infrastructure is a critical asset for countries in all stages of development, a key pillar of international competitiveness and economic growth. According to the McKinsey Global Institute (MGI), the estimated amount of infrastructure investment between 2013 and 2030 is about USD 57 trillion, while the adoption of best practices in planning, delivering, and managing infrastructure assets might increase the productivity of infrastructure investment achieving savings of about USD 1 trillion a year, that is to say 40%. Thus, improving project selection and optimizing infrastructure portfolios, streamlining delivery, boosting asset utilization, sound planning, assuring adequate governance, and implementing the proper procurement model are major concerns of local and national governments. Research in this stream is mainly focused on the following topics:
- optimal bidding under uncertainty in liberalized energy markets;
- economic models for the integration of disseminated energy sources into distribution networks;
- efficient and effective business models to implement smart and micro-grids;
- public utilities, service supply contracts and concessionaires operational performance (water supply and air transport industries);
- business models and economical performance of infrastructure assets (airport, gas, water supply, and renewable energy infrastructure industries);
- Benchmarking and competitiveness (products, processes, and assets).
The benchmarking practice has recently become a common practice, both in the public and private sector. As the public sector organizations are facing an increasing pressure to improve service quality on the one side, and, in the same time, to reduce costs on the other side, benchmarking has become one important practice that may successfully support them in their effort to increase the value for money delivered to citizens, identifying performance gaps, developing and implementing action plans in order to improve performance in terms of cost efficiency and customer satisfaction. In the private sector, technical or product benchmarking practice can be a valuable means that might assist manufacturing companies to improve their innovative performance identifying trajectories for improving products and make them more competitive and appealing in the market. One of the key benchmarking technique used by the team is Data Envelopment Analysis (DEA). Research in this stream focuses on these topics:
- benchmarking models of public utilities (water supply, gas, renewable energy, and transportation industries);
- technical benchmarking of high technology products (i.e., websites, automobiles, airplanes);
- non-parametric ranking and selection methods to prioritize competitive alternatives;
- operational efficiency and effectiveness measurement of public utility infrastructure assets