Estrategia para la consolidación del sector logístico en el marco de un mercado digital AgradecimientosAgradecerle primero a Dios, por sus infinitas bondades y poner en mi camino grandes oportunidades, retos y personas que me acompañan en este camino que es la vida.A mi familia: Mis padres, Nelson y Damaris, por su amor incondicional, su ejemplo de vida y apoyarme en cada proyecto que emprendo; a mi novia, Ángela, por su amor, compañía, paciencia y llenarme de ánimos para seguir adelante cuando no doy más; a mis hermanos, Luis Fernando y Carmen Lizeth, por su amor y confianza; a mis sobrinos Daniel Santiago y Lizeth Daniela, por enseñarme a luchar por mis sueños porque siempre habrá alguien que me preguntará si me gusta lo que hago; a mis abuelas, Toribia y Clara, por su amor y oraciones; y a todos los demás por ser un apoyo incondicional.Al profesor Juan Pablo Castrellón Torres, mi director y amigo, por creer incondicionalmente en mí y enseñarme que en este camino que a veces es complicado siempre hay espacio para una risa.A los miembros del grupo de investigación

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Taking government environmental regulation and consumer’s green preference into a unified analytical framework, this study constructed a differential game model. With the joint effect of supplier and manufacturer green innovation efforts on the dynamic change of the product’s green level, it compared and analyzed the long-term dynamic equilibrium strategies of green innovation cooperation in a supply chain under decentralized and centralized decision-making situations. Accordingly, a scientific and reasonable profit-distribution contract was then proposed. On this basis, it further carried out a numerical simulation analysis on the dual-driving effects of the government and market. The results showed that the scientific and reasonable profit-distribution contract under the centralized decision-making situation, which was designed by using the Rubinstein bargaining game model, could effectively ensure that the supply chain members’ sharing profits would realize "Dual Pareto Improvements." With the increase of the environmental regulation’s intensity, the product’s green level kept rising and tended to be stable. However, the overall equilibrium profit of the supply chain was characterized by "U" fluctuation, which first descended and then ascended. In addition, the product’s green level, the green innovation investment and equilibrium (distributed) profits of supply chain members, and the overall profits of supply chain all increased with the consumers’ green preference.

The length of waiting time has become an important indicator of the efficiency of medical services and the quality of medical care. Lengthy waiting times for patients will inevitably affect their mood and reduce satisfaction. For patients who are in urgent need of hospitalization, delayed admission often leads to exacerbation of the patient’s condition and may threaten the patient’s life. We gathered patients’ information about outpatient visits and hospital admissions in the Nephrology Department of a large tertiary hospital in western China from January 1st, 2014, to December 31st, 2016, and we used big data-enabled analysis methods, including univariate analysis and multivariate linear regression models, to explore the factors affecting waiting time. We found that gender ( P = 0.048 ), the day of issuing the admission card (Saturday, P = 0.028 ), the applied period for admission ( P < 0.001 ), and the registration interval ( P < 0.001 ) were positive influencing factors of patients’ waiting time. Disease type (after kidney transplantation, P < 0.001 ), number of diagnoses ( P = 0.037 ), and the day of issuing the admission card (Sunday, P = 0.001 ) were negative factors. A linear regression model built using these data performed well in the identification of factors affecting the waiting time of patients in the Nephrology Department. These results can be extended to other departments and could be valuable for improving patient satisfaction and hospital service quality by identifying the factors affecting waiting time.