Dipartimento di Ingegneria Gestionale

Measuring socio-economic impact of corporate strategic investments and policy decisions

About the project

The project aims to develop models and methodologies to measure and predict/forecast the socio-economic impact brought by diverse types of strategic investments made by corporations or public entities elaborating qualitative and quantitative approaches on several heterogeneous data sources. These approaches can be used both ex post, for measuring an organization’s results, and ex ante, for informing corporate strategic investments and policy decisions. In this field, the research group has supported large multinational companies (e.g. Eni, Terna), and public and private organizations (e.g. Consorzio Rilegno, Polis).

Principal Investigators: Marika Arena, Giovanni Azzone, Fabio Pammolli

Researcher team: Giovanni Azzone, Giovanni Bonaccorsi, Laura Dell’Agostino, Andrea Flori, Fabio Pammolli, Giulia Piantoni, Sara Ratti, Francesco Scotti, Valeria Urbano

Funders: Eni, Polis, Terna

Duration: 3 years


In the current economic context, the capacity of understanding the contribution of strategic investments to the socio-economic development has become crucial. Such evaluation is of interests of both large corporations and public actors and requires to consider different impact dimensions (economic, environmental, financial and social).

In order to evaluate this contribution, the research group has developed models and methodologies aimed to measure and predict/forecast the socio-economic impact generated by corporate strategic investments and policy decisions. These approaches rely on both qualitative and quantitative research instruments, depending on the objectives an organization aims to pursue with this analysis, the characteristics of the context where the analysis should be developed and data availability. The outcome of these approaches can be used both ex post, in order to measure the results, and ex ante, in order to forecast them and consequently support strategic decision-making processes.

These models have been developed, adapted and applied in different organizations, in both developed and developing countries. One key reference is provided by Eni. Over the last years, the research group has supported Eni to measure local content generated in different contexts (e.g. Italy, Ghana, Angola, Egypt …) by combining direct, indirect and induced effects, in connection to three domains: Economic impact, Employment impact, Human capital development. Further collaborations have been developed with both large companies (e.g. Terna), and other organizations. For instance, the research group has assessed the impact of the reuse and regeneration of post consumer wood for Consorzio Rilegno, and has started a collaboration with Polis for assessing the impact of regional policies through big data. The research group has adapted and customized the model to different settings in order to take into account the context characteristics and the specificities of the different environments.


Main publications or other impact results:

  • Arena, M., Azzone, G., Grecchi, M., & Piantoni, G. (2021). How can the waste management sector contribute to overcoming barriers to the circular economy?. Sustainable Development.
  • Pammolli, F., De Blasio, G. Nicita, A. (a cura di), Evidence-based Policy!. Ovvero perchè politiche pubbliche basate sull’evidenza empirica rendono migliore l’Italia. Il Mulino (2021).
  • Arena, M., Azzone, G., Piantoni, G. (2020). Shared value creation during decommissioning: a case study from the energy sector, Journal of Cleaner Production, Vol. 251
  • Azzone, G., Balducci, A., & Secchi, P. (2020). Infrastrutture e città. Innovazione, coesione sociale e digitalizzazione. Francesco Brioschi.
  • Azzone, G., & Caio, F. (2020). In un mare di dati. Quali dati per le politiche quali politiche per i dati. Mondadori Education spa.
  • Bonaccorsi, G., Pierri, F., Cinelli, M., Flori, A., Galeazzi, A., Porcelli, F., Schmidt AL., Valensise CM., Scala A., Quattrociocchi W., & Pammolli, F. (2020). Economic and social consequences of human mobility restrictions under COVID-19. Proceedings of the National Academy of Sciences, 117(27), 15530-15535.
  • Pammolli, F., Righetto, L., Abrignani, S., Pani, L., Pelicci, P. G., & Rabosio, E. (2020). The endless frontier? The recent increase of R&D productivity in pharmaceuticals. Journal of translational medicine, 18, 1-14.
  • Spelta, A., Flori, A., Pecora, N., Buldyrev, S., & Pammolli, F. (2020). A behavioral approach to instability pathways in financial markets. Nature Communications11(1), 1-9.
  • Spelta, A., Flori, A., Pierri, F., Bonaccorsi, G., & Pammolli, F. (2020). After the lockdown: simulating mobility, public health and economic recovery scenarios. Scientific Reports, 10(1), 1-13.
  • Righetto, L., Spelta, A., Rabosio, E., & Pammolli, F. (2019). Long-term correlations in short, non-stationary time series: An application to international R&D collaborations. Journal of Informetrics,13(2), 583-592.