Collaborate for what: a structural topic model analysis on CDP data

Abstract

[EN] The aim of this paper is to understand why firms engage with their suppliers to collaborate for sustainability. To this purpose, we use the Carbon Disclosure Project (CDP) Supply Chain dataset and apply the Structural Topic Model to 1) identify the topics discussed in an open-ended question related to climate-related supplier engagement and 2) estimate the differences in the discussion of such topics between CDP members and non-members, respectively focal firms and first-tier suppliers. The analysis highlights that the two most prevalent reasons firms engage with their suppliers relate to several aspects of the management of the supply chain, and the services and goods mobility efficiency. It is further noted how first-tier suppliers do not dispose of established capabilities and, therefore, are still in the course of improving their processes. On the contrary, focal firms have more structured capabilities so to manage supplier engagement for information collection. This study demonstrates how big data and machine learning methods can be applied to analyse unstructured textual data from traditional surveys.Salvatore, C.; Madonna, A.; Bianchi, A.; Boffelli, A.; Kalchschmidt, M. (2022). Collaborate for what: a structural topic model analysis on CDP data. En 4th International Conference on Advanced Research Methods and Analytics (CARMA 2022). Editorial Universitat Politècnica de València. 139-146. https://doi.org/10.4995/CARMA2022.2022.1507413914