The Triple Bottom Line (TBL) concept emphasizes that business success should not be measured solely by financial performance. It includes social and environmental impacts alongside profit. Additionally, dynamic capabilities help firms adapt to rapid environmental changes and enhance sustainability performance. Previous studies have shown that TBL initiatives can also improve sustainability performance. However, no research has investigated how dynamic abilities and TBL initiatives jointly impact B2B firms’ sustainability performance in the post-COVID-19 period. This study aims to examine the implications of dynamic capabilities on TBL performance, particularly from a B2B marketing perspective. By developing and validating a conceptual research model, it contributes to the literature related to dynamic capability view, TBL, and sustainability.
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Robotic warehouses have transformed logistics, prioritizing speed and efficiency. However, traditional static priority systems often leave low-priority customers facing excessive delays, raising concerns about fairness. This research, based on Invia, a robotic warehouse company, proposes a dynamic priority allocation model to balance efficiency and fairness. By adjusting order priorities over time, this approach ensures that both high-priority and long-waiting low-priority orders receive timely fulfillment. Through stochastic modeling and simulations, we demonstrate that dynamic prioritization reduces delays compared to static and first-come, first-served (FCFS) models. Case studies in e-commerce and healthcare logistics illustrate the broader impact of fairness in automation. As industries increasingly rely on AI-driven decision-making, the balance between efficiency and equity becomes critical. This research challenges the assumption that robotic warehouses should optimize for speed alone and advocates for a future where fairness plays a central role in automated commerce.
- Recherche
- Logistique et Supply Chain, Transformation Digitale
