Exploring the Sustainability of Swiss Online Shops: Preliminary Evidence from a Clustering Approach

Authors

Thomas Wozniak, Lucerne School of Business, Institute of Communication and Marketing, Lucerne, SwitzerlandFollow
Guang Lu, Lucerne School of Business, Institute of Communication and Marketing, Lucerne, SwitzerlandFollow
Dominik Georgi, Lucerne School of Business, Institute of Communication and Marketing, Lucerne, SwitzerlandFollow
Anja Janoschka, Lucerne School of Business, Institute of Communication and Marketing, Lucerne, SwitzerlandFollow
Antonia Steigerwald, Lucerne School of Business, Institute of Communication and Marketing, Lucerne, SwitzerlandFollow

Abstract

This paper proposes a framework for assessing the sustainability of online retailers. By adhering to the logic of the value chain, the framework captures all steps from procurement to shipping of products and handling product returns that typically occur in e-commerce. The framework is then applied to explore the sustainability of 227 Swiss online shops through a clustering approach. Core elements of the framework are dummified and condensed to 20 features using an autoencoder-based neural network. K-means clustering is used to identify three sustainability clusters that are visualised in the latent space. One-way ANOVA and chi-square analyses of the three-cluster solution indicate that the identified clusters are distinct across most elements of the proposed framework. These preliminary results hold a variety of future research avenues.

Recommended Citation

Wozniak, Thomas; Lu, Guang; Georgi, Dominik; Janoschka, Anja; and Steigerwald, Antonia, "Exploring the Sustainability of Swiss Online Shops: Preliminary Evidence from a Clustering Approach" (2021). BLED 2021 Proceedings. 20.
https://aisel.aisnet.org/bled2021/20