This paper is motivated by a concern in China’s current medical practice in which patients can bypass the primary care and seek secondary care directly. We employ a queueing approach to examine two settings, i.e. the gatekeeping and non-gatekeeping settings, in a service system consisting of two types of service provider — one with basic skills (C-H), e.g. community hospital, and the other with advanced skills (AAA-H), e.g. specialist hospital. Customers are heterogeneous with respect to service requirement. The C-H can only serve customers with a complexity level of service requirement lower than the cure threshold, while the AAA-H can serve all customers. We aim to analyze the social planner’s capacity decision for the C-H in both settings and assess the relative merit of each setting with respect to total social welfare, i.e. the sum of customer benefits net of customer delay costs and service providers’ operating costs. Our findings show that when the C-H’s capacity is exogenous, the gatekeeper setting is preferable if the capacity of the C-H is in the intermediate range because customers’ self-selection behavior gives rise to negative externality. When the C-H’s capacity is optimized by the social planner, the non-gatekeeping setting is preferable if the capacity of the AAA-H is large or the cure threshold is high, because customers’ self-selection behavior as well as the investment in the C-H’s capacity can result in a better distribution of demand among the two service providers. The gatekeeping setting is preferable if the cure threshold is low because it is economical for the social planner to invest in a large capacity in the C-H to serve all customers. We also show numerically the conditions under which the two settings can achieve the first-best solution.

Many original equipment manufacturers (OEMs) carry out collecting operations by themselves or a third party. Most of the existing research papers in the literature consider the collecting mode selection problem from an economic perspective. However, in practice, the firm’s collecting decisions can be affected by the carbon policies at present. This paper aims to bridge the gap in research on remanufacturing supply chain by taking the effects of cap-and-trade regulation into consideration. Stackelberg models are established to study the quantity and price decisions under different collecting modes. We find that the OEM reaps more profits in the OEM collecting mode than the third-party collecting mode when collection cost is large. Otherwise, the third party has lower collection cost, and the third-party collecting mode may make the OEM more profitable. From an environmental perspective, with high collection cost, the third party collecting mode can reduce the carbon emissions unless the cost of new products and the emissions intensity are small. In addition, when the collection cost is low but the quantity of remanufacturing products is restricted by that of new products, the third party collecting mode may increase the carbon emissions. In addition, the implementation of cap-and-trade regulation can always reduce carbon emissions, and it may increase the OEM’s profits if consumers preference for remanufactured products is small.

In recent years, China’s dry ports have entered into a period of rapid development, especially driven by the Belt and Road initiative (BRI). This initiative not only provides valuable opportunities, but also intensifies fierce competition between ports. In order to earn more profits and maintain an advantageous position, dry ports generally tend to rely on seaports to increase competitiveness and attract more goods, and seaports are also willing to cooperate with dry ports to expand their business. As a large coastal province in China, Shandong Province has good maritime resources. Because of the fierce competition among seaports inside and outside Shandong Province, port operators should make good use of the opportunity offered by BRI to make connections with the inland cities through the dry port-seaport logistics network and enhance the competitiveness. In order to take an active part in the process of the BRI, forming a dry port-seaport logistics network is a win-win strategy for Shandong province. The research first analyzes the impact of the Belt and Road initiative on ports of Shandong and its development, then uses complex network theory and TOPSIS method to select dry port candidate cities from BRI’s important transportation nodes. After considering economic benefits, carbon emissions and construction costs, a multi-objective optimization model is established with a construction cost preference coefficient. Then the NSGA-II algorithm is used to solve the realistic problem. The study finds that when the construction cost increases, the transportation cost and carbon emission cost will decrease, which indicates that the dry port-seaport logistics network established under the BRI can reduce the cost of logistics transportation and environmental pollution.

Cataract is a very common eye disease and the most significant cause of blindness. In consideration of its burden on society, the focus was put on testing the risk factors of cataract and building robust machine learning models in which these factors can be utilized to predict the risk of cataract. The data used herein was collected by a Chinese physical examination center located in Shanghai. It contains more than 120,000 examinees and about 500 physical examination metrics. Firstly, association rules were adopted to filter 39 abnormalities which are more likely to incur the risk of cataract, and the significance of these abnormalities was tested with univariate analysis and multivariate analysis. The test results indicate that age, diabetes, refractive error, retinal arteriosclerosis, thyroid nodules, and incomplete mammary gland degeneration significantly increase the possibility of cataract. Various machine learning models were compared in terms of their performance in predicting the risk of cataract based on these six factors, among which the logistic regression model and the decision-tree based ensemble methods outperform others. The test set AUC of these models can reach 0.84.

The bullwhip effect is widely found in business and exerts adverse effects on business activities. To investigate the influence of the bullwhip effect on firms’ performance and their responses, this study proposed an environment-behavior-performance analysis framework and offered a new perspective for studying the bullwhip effect. Using data collected from 1,734 listed manufacturers in China from 2002 to 2017, we adopted regression models to test the proposed model and conducted a series of robustness tests. We find that the bullwhip effect is positively related to operating risk, inventory, and cash holdings, and the moderate levels of inventory and cash are negatively associated with operating risk. Specifically, inventory and cash play different roles and work together to alleviate operating risk induced by the bullwhip effect. However, excess resource holdings are positively associated with operating risk. Therefore, firms with different levels of resources should hold suitable levels of inventory, cash, or both as contingent responses to the bullwhip effect.

In a credence goods market, a consumer (he) is unaware of his true need, which can be either intense or minor. An expert (she) designs a menu that either charges a uniform price to both services, termed pooling pricing, or varies charges according to service types, termed differential pricing. Learning the menu offered by the expert and anticipating her behavior in serving consumers, a consumer weighs the expected utility of service provision against the cost incurred in transportation to decide whether to visit the expert, termed entry decision. Upon arrival of a consumer, the expert discerns his true need and recommends a service along with the associated charge. Under the liability assumption, the expert provides a service to satisfy the consumer’s need. However, the consumer is unable to discern the nature of the service actually provided. This can induce the expert who adopts differential pricing to recommend intense service to a consumer with minor need, termed overcharging. We investigate the effects of consumers’ entry decision on the expert’s optimal pricing strategy and the occurrence of overcharging, and study the robustness of the main results to practical features.