The aim of this study is to provide investors, policymakers and others with information on how greenhouse gas (GHG) emissions and green innovation affect corporate financial performance. Although reporting by corporate venture capital (CVC) firms on GHG emissions as well as their green innovation has increased significantly, especially in the last two decades, little is known about how these two factors affect financial performance. To fill this gap, this article investigates the relationships between environmental performance, green innovation, and financial performance in CVC investments in the US over an 18-year period between 2002 and 2019.

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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.
YUAN Zhe - EMLV |
- Research
- Digital Transformation, Logistics and Supply Chain