Role models and warning examples in industrial sustainability transformations
The project examines to what extent, how and why firms respond to changes in the behaviour of their peers. It studies influence in three types of networks, constituted by markets, employment patterns and personal networks.
Background
The project focuses on sustainability-related performances of industrial firms. A key data input to the research includes emerging Environmental Social and Corporate Governance (ESG) data that firms are increasingly reporting in addition to financal data. Such data is being assembled into ESG datasets. ESG data sets can be assessed, together with other data, in order to assess Role models and warning examples in industrial sustainability transformations.
Aims and objectives
The purpose of this project is to investigate the diffusion of sustainability-related management practices. We study patterns of adoption of strong sustainability management practices in a broad set of industries. Key questions are to what extent, how and why firms respond to changes in the behaviour of their peers.
Project plan
We adopt a mixed-methods study approach. Adopting a combination of econometric and machine learning techniques, we analyse of a very large dataset delineating ESG (environmental, social, governance) as well as financial indicators for more than 10 000 firms over a time period of five years. Insights from this analysis are cross-fertilized with results from an interview study employing a journey mapping technique.
The project examines influence in three types of networks, constituted by i) markets (firms are competitors in product markets), ii) employment patterns (firms are competitors on labour markets), and iii) personal networks (firms are linked by contemporaneous or recent engagements in competing firms by board members and CEOs). Furthermore, the project’s analysis also considers contingencies in the form of interactions between these three types of networks.
Together, the various analysis foreseen in the project are expected to provide an overview of how good practice in sustainability management is diffused between firms. The project will also provide new knowledge about key management practices in sustainability work of Swedish firms.
Applied interdisciplinarity
The project is designed to leverage opportunities for inter-department collaboration, with the Department of Industrial Economics and Management and the Department of Machine Design (existing staff + IRIS postdocs) in focus. Collaboration in this constellation allows for multi-method research.
KTH Collaborations
Industrial Economics and Management
Learning
Machine Design
Duration
September 2021– December 2023
Project participants
