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Article analysis:

The article is written in an objective manner, providing a comprehensive overview of the risks associated with last mile delivery and proposing a framework for risk assessment. The authors provide evidence from literature reviews and interviews with experts in the field to support their claims, which adds credibility to the article. Furthermore, they use a Bayesian Belief Network (BBN) model to identify interdependencies between risks and rank them accordingly, which is an innovative approach that has not been explored before in this context.

However, there are some potential biases that should be noted when reading this article. Firstly, the authors do not explore any counterarguments or alternative approaches for risk assessment other than BBN models. Secondly, while they mention potential solutions such as drones or 3D printing for last mile delivery, they do not discuss any of the associated risks or challenges that come with these solutions. Finally, while they mention COVID-19 pandemic as an example of unexpected events that can disrupt supply chains worldwide, they do not discuss how it has impacted last mile deliveries specifically or what measures have been taken by logistics companies to mitigate its effects on deliveries.

In conclusion, this article provides a comprehensive overview of risks associated with last mile deliveries and proposes an innovative approach for assessing these risks using BBN models. However, it does not explore any counterarguments or alternative approaches for risk assessment nor does it discuss any of the associated risks or challenges that come with advanced solutions such as drones or 3D printing for last mile deliveries nor does it discuss how COVID-19 pandemic has impacted last mile deliveries specifically or what measures have been taken by logistics companies to mitigate its effects on deliveries.