This podcast discusses an academic paper that investigates how digital transformation influences supply chain learning within the Australian food industry. Through a multi-case study, the authors explore how technologies like Internet-of-Things and big data shift the responsibility for knowledge creation from a single leading company to a collaborative network of suppliers and retailers. The findings suggest that while digitalisation democratises learning by making it more participatory, the shared knowledge tends to remain restricted to the food sector rather than being exchanged with other industries. Consequently, the researchers conclude that extensive digital adoption transitions the supply chain from a captive learning model to a more integrated consortium approach. Ultimately, this study provides strategic insights for organisations seeking to gain a competitive advantage through expedited, technology-driven learning..

Reference: Tortorella, G. L., Malik, M., Trianni, A., Pepper, M., Vassolo, R., Garcia, F., ... & Norena-Chavez, D. (2026). Supply Chain Learning in the Australian food industry: the impact of digital transformation. International Journal of Production Economics, 110074. https://doi.org/10.1016/j.ijpe.2026.110074

This podcast discusses a recent research article that explores the mechanisms behind green innovation within the Pakistani manufacturing sector using knowledge-based dynamic capabilities theory. The authors examine how green knowledge sharing fosters eco-friendly advancements by enhancing a firm's innovation capability and its capacity for knowledge creation. A significant finding reveals that while internal knowledge processes drive sustainability, customer involvement unexpectedly weakens the link between knowledge sharing and the development of new capabilities. The study employs a multimethod design, combining moderated-mediation analysis with necessary condition analysis to identify the essential factors for environmental progress. Ultimately, the source provides strategic guidance for managers on balancing internal expertise with external input to meet escalating environmental regulations.

Full article available at: https://onlinelibrary.wiley.com/share/author/AQBI3SHRRQGQZQQKVFNH?target=10.1002/bse.70721

This podcast synthesizes findings from a study on the relationship between organizations' perceptions of Artificial Intelligence (AI) and the nature of Supply Chain Learning (SCL). Based on an online survey of 206 top and middle managers from various industry sectors in Brazil, the research reveals that perceptions of AI's usefulness and its ease of use are critical determinants of how knowledge is created, shared, and driven across a supply chain.

The central conclusion is that different combinations of Perceived Usefulness (PU) and Perceived Ease of Use (PEOU) of AI correlate directly with four distinct types of SCL.

• When both PU and PEOU are low, a Captive SCL emerges, where a dominant focal company controls learning within a closed network.

• When PU is high but PEOU is low, a Selective SCL occurs, with a focal company leading learning across an open network of chosen partners.

• When PU is low but PEOU is high, a Consortium SCL prevails, driven by non-focal companies within a closed network.

• When both PU and PEOU are high, a Distributed SCL is fostered, characterized by democratized learning efforts led by diverse players across multiple supply chains.

These findings provide a strategic framework for managers, demonstrating that by prioritizing digitalization efforts and shaping perceptions of AI, they can actively influence the learning dynamics within their supply chains to enhance decision-making, problem-solving, and overall competitive advantage.

Source: Tortorella, G. L., Powell, D., Malik, M., Alfalla-Luque, R., Portioli-Staudacher, A., & Nascimento, D. (2025). Perceptions of AI adoption and their impact on supply chain learning. https://www.tandfonline.com/doi/full/10.1080/13675567.2025.2547202