Forecasting for social good

Rostami-Tabar, Bahman ORCID: https://orcid.org/0000-0002-3730-0045, Ali, Mohammad M., Hong, Tao, Hyndman, Rob J., Porter, Michael D. and Syntetos, Aris ORCID: https://orcid.org/0000-0003-4639-0756 2022. Forecasting for social good. International Journal of Forecasting 38 (3) , pp. 1245-1257. 10.1016/j.ijforecast.2021.02.010

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Abstract

Forecasting plays a critical role in the development of organisational business strategies. Despite a considerable body of research in the area of forecasting, the focus has largely been on the financial and economic outcomes of the forecasting process as opposed to societal benefits. Our motivation in this study is to promote the latter, with a view to using the forecasting process to advance social and environmental objectives such as equality, social justice and sustainability. We refer to such forecasting practices as Forecasting for Social Good (FSG) where the benefits to society and the environment take precedence over economic and financial outcomes. We conceptualise FSG and discuss its scope and boundaries in the context of the "Doughnut theory". We present some key attributes that qualify a forecasting process as FSG: it is concerned with a real problem, it is focused on advancing social and environmental goals and prioritises these over conventional measures of economic success, and it has a broad societal impact. We also position FSG in the wider literature on forecasting and social good practices. We propose an FSG maturity framework as the means to engage academics and practitioners with research in this area. Finally, we highlight that FSG: (i) cannot be distilled to a prescriptive set of guidelines, (ii) is scalable, and (iii) has the potential to make significant contributions to advancing social objectives.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Business (Including Economics)
Publisher:	Elsevier
ISSN:	0169-2070
Date of First Compliant Deposit:	23 March 2021
Date of Acceptance:	10 February 2021
Last Modified:	08 May 2023 06:29
URI:	https://orca.cardiff.ac.uk/id/eprint/140015

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