Publications by authors named "Istefani Carisio de Paula"

The management of healthcare waste and end-of-life medication coming from different sources are primary challenges faced by public health leaders. Several factors may be considered critical and inhibitive to reverse logistics within the context of waste management processes. If those factors are not addressed, they may become obstacles to reverse logistics implementation.

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End-of-use and end-of-life medicines waste management has been a challenge for public and private managers in different countries. Reverse logistics is a waste management strategy whose application to public pharmaceutical care processes faces legal restrictions and incertitude. Nevertheless, reverse logistics of end-of-use and end-of-life medicines may be both a saving and an environmental strategy in developing countries that manage health under limited resources.

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There is an increasing interest in product recovery, closed-loop supply chains, and reverse logistics (RL) for mitigating environmental impairment. Although RL is becoming a mandatory policy in developed countries, it is still in an embryonic stage in some industrial sectors of emerging economies. The purpose of this study is twofold: (1) identify the critical factors to the successful implementation of RL in the Brazilian pharmaceutical care process (PCP) and (2) determine the cause-and-effect relationships among them.

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Business models have being designed, worldwide, to create sustainability competencies and in particular to incorporate reverse logistics, but Brazilian executives have not yet fully adhered to Law 12,305 on solid waste and reverse logistics. What would be the Brazilian executives' perception about reverse logistics competency and the support provided by a collaborative and IT competency? The objective of the paper is to investigate the effects of collaboration and IT competency in developing reverse logistics competency, as a strategy, and its consequences in economic and environmental performance. A survey was performed with 320 Brazilian supply chain executives and analyzed using Structural Equation Modeling.

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