Transportation is vital for access to health care, especially in rural areas, where travel distances are great and access to alternative modes such as transit is less prevalent. This study estimated the impacts of transportation and travel distance on the utilization of health care services for older adults in rural and small urban areas. With data collected from a survey, a model was developed on the basis of the Health Behavior Model, which considered transportation and distance as factors that could enable or impede health care utilization. A random sample of individuals age 60 years and older living in the rural Upper Great Plains states of Montana, North Dakota, South Dakota, and Wyoming were surveyed by mail. Responses were received from 543 individuals (20% response rate). Probit models were used to estimate trip frequency and the likelihood that an individual would miss or would delay a health care trip. Distance and transportation variables were not found to influence significantly the total number of routine or chronic care trips made overall, while emergency care visits were affected by the availability of transportation options. Additional results showed that those who could not drive made more trips if someone in the household could drive and that distance and access to transportation affected the difficulty reported in making trips and the likelihood of missing or delaying a trip. The greatest problems for people using public transportation for health care trips were inconvenient schedules, the need to match transit and medical schedules, and infrequent service.

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Sustainability is key factor for transforming traditional supply chain networks into modern ones. This study, for the first time, considers the impacts of the backup suppliers and lateral transshipment/resupply simultaneously on designing a Sustainable Closed-Loop Supply Chain Network (SCLSCN) to decrease the shortage that may occur during the transmission of produced goods in the network. In this manner, the fuzzy multi-objective mixed-integer linear programming model is proposed to design an efficient SCLSCN resiliently. Moreover, the concept of circular economy has been studied in this paper to reduce environmental effects. This study aims to optimize total and environmental costs, including energy consumption and pollution emissions, while increasing job opportunities. A demand uncertainty component is considered to represent reality more closely. Due to the importance of demand, this parameter is estimated using the Fuzzy Inference System (FIS) as an input into the proposed mathematical model. Then, the fuzzy robust optimization approach is applied in a fuzzy set’s environment. The model is tackled by a Multi-Choice Goal Programming Approach with Utility Function (MCGP-UF) to be solved in a timely manner, and the equivalent auxiliary crisp model is employed to convert the multi-objective function to a single objective. The proposed model is tested on the case study of the tire industry in terms of costs, environmental impacts, and social effects. The result confirmed that considering the concept of lateral resupply and backup supplier could considerably decrease the total costs and reduce shortages on the designed SCLSCN. Finally, sensitivity analysis on some crucial parameters is conducted, and future research directions are discussed.