This paper aims to understand why firms engage with their suppliers to collaborate for sustainability. For 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 prominent reasons why firms engage with their suppliers relate to several aspects of the supply chain management, and the services and good transportation efficiency. It is further noted that first-tier suppliers do not possess established capabilities and, therefore, are still 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.

(2022). Collaborate for what: a structural topic model analysis on CDP data . Retrieved from https://hdl.handle.net/10446/234442

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

Madonna, Alice;Bianchi, Annamaria;Boffelli, Albachiara;Kalchschmidt, Matteo Giacomo Maria
2022-01-01

Abstract

This paper aims to understand why firms engage with their suppliers to collaborate for sustainability. For 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 prominent reasons why firms engage with their suppliers relate to several aspects of the supply chain management, and the services and good transportation efficiency. It is further noted that first-tier suppliers do not possess established capabilities and, therefore, are still 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, Camilla; Madonna, Alice; Bianchi, Annamaria; Boffelli, Albachiara; Kalchschmidt, Matteo Giacomo Maria
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10446/234442
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