Strategic use of digital technologies in logistics systems: pathways to superior product operational performance in product lines
Esteban Lafuente, Juan Carlos Leiva, Ronald Mora-Esquivel, Yancy VaillantPurpose
The study evaluates how the implementation of artificial intelligence (AI)-enabled strategies (i.e. augmentation and automation) in product logistics influences product operational performance. We also explore if the positive impact of such strategies amplifies in products whose processes are characterized by high levels of operational flexibility and adaptiveness.
Design/methodology/approach
The study's empirical exercise uses multi-level regression models on a unique sample that includes information for 139 distinct product lines generated by Costa Rican firms for 2024.
Findings
The core findings of the study show that both augmentation- and automation-based AI strategies contribute to product operational performance. It was also found that an augmentation AI strategy leads to superior operational performance in products whose processes have developed adaptability capacities that facilitate rapid product reconfigurations.
Research limitations/implications
We highlight the strategic implications of different AI implementation logics at the product level and how they interact with operations' adaptive capabilities to improve coordination between product's managers and customers.
Practical implications
The results provide actionable insights into how to configure AI technologies to support customization across product lines. By highlighting the significance of digital technologies for product logistics, the study establishes critical pathways to strategize digital technologies' implementation processes.
Originality/value
This study focuses on the strategic implementation of AI technologies at the product level, where critical logistical tasks such as configuration, customization and delivery occur. By focusing on the product as unit of analysis, the study offers a unique perspective to explore the potential of AI strategies, which might differ significantly in terms of their alignment with product-specific processes and operational goals.