How can companies improve the environmental sustainability of their supply chains? A study by Laura Trinchera, a NEOMA researcher affiliated to the Area of Excellence AI, Data science and Business, and colleagues focuses on the positive effects of a data-driven culture in combination with adoption of artificial intelligence technologies.

The potential to convert huge amounts of data into new opportunities – that’s one of the key strategic advantages that data science can give manufacturing companies. When this expertise is combined with the capabilities of artificial intelligence (AI), then the revolution is likely to be even bigger. The gradual take-up of AI in various sectors over recent years – think technology, health, finance or industry – has helped the worldwide market explode. In 2022, the AI market was valued at around $ 140 billion; it is now expected to continue building on this success and climb above $ 1,700 billion by 2030.

Firms are already employing AI techniques on the ground in highly-diverse contexts, ranging from predictive maintenance to selecting suppliers. Companies across all sectors are now keen to leverage the muscle of these tools so they can optimise their supply chains. The aim is to strengthen their decision-making and boost their resilience for tackling operational hazards or to drive down their environmental impact. But how do a data-driven corporate culture and their capability to adopt new AI technologies influence the environmental performance of supply chains? In an attempt to answer this question, the NEOMA researcher and her colleagues collated data from supply chain managers in France and the USA.

AI-driven operational management

There are many different ways to fortify a supply chain’s environmental performance. For instance, a company can work on designing more environmentally-friendly sustainable products, optimise freight transport to cut back on greenhouse gas emissions, or reduce waste with better packaging and recycling.

As part of their work, the researchers looked at how the adoption of AI technologies influences these practices, focusing on how firms can use AI tools in flexible, reactive mode so they can adjust and improve their operations without interruption. This study builds on the findings of earlier research: the adoption of AI technologies really does help companies meet environmental challenges. In particular, the AI technologies make it easier to pre-empt fast-evolving changes external to the company. But the research outcomes take things a step further. This effect, argue the scientists, is directly linked to a company’s data-driven culture concerning the production and analysis of data regarding their supply chain.

 The catalytic effect of a data-driven culture

A data-driven culture is based on an organisational mindset that promotes the systematic use of data to make better decisions at different level of the organization.

The research shows that a culture that promotes the smart use of data is a key factor in advancing corporate sustainability. It has a mediation effect on the relationship between the adoption of AI technologies and environmental performance. It is now well established that data is the rocket fuel that powers AI. And yet the research also draws attention to a lesser known effect: the adoption of AI technologies can boost a data-driven culture by supplying firms with more powerful, more sophisticated tools.

National variations and management implications

The study suggests that the take-up and proactive use of AI-based technology may pay off for companies operating in supply chain management. It may have a hand not just in beefing up their operational efficiency, but also in consolidating their data-driven culture to leverage their sustainable environmental performance. It follows that a data-driven culture and the adoption of AI tools are so mutually reinforcing that they generate a momentum whose whole is greater than the sum of their parts. This is a significant finding at a time when new approaches, such as the generative AI behind ChatGPT, are being integrated into business logistics. They are introducing additional market opportunities and helping to identify risks. However, the way AI interacts with other tools derived from the industry of the future will give rise to new questions.

Last of all, the researchers observed that there was a slight difference in the extent of the impact of a data-driven culture from one country to the next. They suggest, therefore, that future research should examine the cultural factors influencing the connections among data utilisation, AI adoption, and environmental performance in the analysis of global supply chains.

Find out more

Samuel Fosso Wamba, Maciel M. Queiroz, Laura Trinchera, The role of artificial intelligence-enabled dynamic capability on environmental performance: The mediation effect of a data-driven culture in France and the USA, International Journal of Production Economics, Volume 268, 2024, https://doi.org/10.1016/j.ijpe.2023.109131