Evaluation of Medicine Reverse Logistics Practices in Hospitals

Logistics performance: critical factors in the implementation of end-of-life management practices in the pharmaceutical care process

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. The purpose of this study is to evaluate the effect that critical factors play in the adoption of end-of-life management practices for medication and its influence on logistics performance. Literature provided some critical factors: management factor, collaboration factor, information technology factor, infrastructure factor, politics factor, financial and economic factor, end-of-life management practices, and logistics performance factor. A sample of 67 professionals from the public pharmaceutical care process answered a structured questionnaire. The collected data was analyzed using partial least square-structural equation modeling. The theoretical structural test confirmed eleven out of the fifteen hypotheses considered. The results have indicated that end-of-life management practices exert a direct influence on logistics performance. The analysis confirmed a direct effect of the information technology factor on end-of-life management practices, but not a moderation effect. Findings have contributed to the literature by providing deeper insights into the relationship between end-of-life management practices for medicines and logistics performance. Moreover, it supports health managers' decision-making in the pharmaceutical care process improvement and engagement with solid waste management policies.

Dynamic Uncertainty Study of Multi-Center Location and Route Optimization for Medicine Logistics Company

Multi-center location of pharmaceutical logistics is the focus of pharmaceutical logistics research, and the dynamic uncertainty of pharmaceutical logistics multi-center location is a difficult point of research. In order to reduce the risk and cost of multi-enterprise, multi-category, large-volume, high-efficiency, and nationwide centralized medicine distribution, this study explores the best solution for planning medicine delivery for the medicine logistics. In this paper, based on the idea of big data, comprehensive consideration is given to uncertainties in center location, medicine type, medicine chemical characteristics, cost of medicine quality control (refrigeration and monitoring costs), delivery timeliness, and other factors. On this basis, a multi-center location- and route-optimization model for a medicine logistics company under dynamic uncertainty is constructed. The accuracy of the algorithm is improved by hybridizing the fuzzy C-means algorithm, sequential quadratic programming algorithm, and variable neighborhood search algorithm to combine the advantages of each. Finally, the model and the algorithm are verified through multi-enterprise, multi-category, high-volume, high-efficiency, and nationwide centralized medicine distribution cases, and various combinations of the three algorithms and several rival algorithms are compared and analyzed. Compared with rival algorithms, this hybrid algorithm has higher accuracy in solving multi-center location path optimization problem under the dynamic uncertainty in pharmaceutical logistics.

An integrated fuzzy sustainable supplier evaluation and selection framework for green supply chains in reverse logistics

Green supply chain management considers the environmental effects of all activities related to the supply chain, from obtaining raw materials to the final delivery of finished goods. Selecting the right supplier is a critical decision in green supply chain management. We propose a fuzzy green supplier selection model for sustainable supply chains in reverse logistics. We define a novel hierarchical fuzzy best-worst method (HFBWM) to determine the importance weights of the green criteria and sub-criteria selected. The fuzzy extension of Shannon's entropy, a more complex evaluation method, is also used to determine the criteria weights, providing a reference comparison benchmark. Several hybrid models integrating both weighting techniques with fuzzy versions of complex proportional assessment (COPRAS), multi-objective optimization by ratio analysis plus the full multiplicative form (MULTIMOORA), and the technique for order of preference by similarity to ideal solution (TOPSIS) are designed to rank the suppliers based on their ability to recycle in reverse logistics. We aggregate these methods' ranking results through a consensus ranking model and illustrate the capacity of relatively simple methods such as fuzzy COPRAS and fuzzy MOORA to provide robust rankings highly correlated with those delivered by more complex techniques such as fuzzy MULTIMOORA. We also find that the ranking results obtained by these hybrid models are more consistent when HFBWM determines the weights. A case study in the asphalt manufacturing industry is presented to demonstrate the proposed methods' applicability and efficacy.

The Impact of Consequences Awareness of Public Environment on Medicine Return Behavior: A Moderated Chain Mediation Model

With global aging trends and prosperity in the medicine market, the number of unused or expired household unused or expired medicines is increasing. Medicines which are discarded improperly result in serious pollution. From the perspective of behavioral science, the main contribution of this paper is the construction of a chain mediation model to analyze the influence mechanism between consequences awareness of the public environment and proper return behavior of unused or expired medicines. The model explores the moderating effect of personal health awareness with through observation of to the mediating effect of personal norms and return intention. Using a sample size of 366 residents from China, the proposed hypotheses are empirically tested. The results show: firstly, the direct effect of residents’ consequences awareness of public environmental awareness on the proper medicine return behavior is not significant; secondly, return intention plays a mediating role in the positive effect of consequences awareness of the public environment on proper return behavior; thirdly, personal norms and return intention play a chain mediating role in the positive impact of consequences awareness of the public environment on proper return behavior; and lastly, personal health awareness moderates the chain mediation path by strengthening the positive effect of return intention on proper return behavior.