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Ms. Zhongying Pan is the Vice President of United Family Hospital and Clinics Group, and the President of Beijing United Family Hospital and Clinics. She joined Beijing United Family Hospital and Clinics in 1996. In her fourteen years of career, she served as a project manager, administrative manager, interim general manager of Shanghai United Family Hospital, Acting President, and Vice President of strategic development system. As a practitioner, she is an expert in foreign-invested hospital management in China. Ms. Pan has in-depth experience in government relations, hospital operations, strategic business planning, local market expansion, and multicultural human resources management. In her career at Beijing United Family Hospital and Clinics, she was in charge of the approval of foreign-invested hospital opening, budgeting, supervision, project budget preparation, quality control, drug and medical equipment import, non-medical personnel management, and all aspects of recruitment and training. Ms. Pan has comprehensive understanding of China's health care system, policies and regulations. She has great knowledge of foreign hospital investment in China and deep insight into the current situation and development of China's healthcare market. Ms. Pan continues to pursue her PhD degree in Hospital Management from University of Alabama at Birmingham. She received her MBA in Healthcare Management at University of Colorado, MBA at Peking University, and BA in English Literature at the Xiangtan University. 简介:盘仲莹女士现担任和睦家医疗集团副总裁、北京和睦家医院院长职务。她于1996年正式加入和睦家医疗,在其十四年的职业生涯中,她历任项目经理,行政经理,总经理助理,上海和睦家医院代理院长,战略系统发展副总裁,具备丰富的外资医院管理经验。盘仲莹女士在政府关系到医院运营管理,在战略业务规划到地方市场拓展和在企业多元文化的塑造到人力资源的管理,拥有深入的实践经验。在和睦家的职业生涯中,她曾亲自负责外资医院的批准、筹建及项目的预算、监理, 项目预算控制到医疗设备、药品的进口以及非医疗人才的招聘到管理培训等各方面。盘仲莹女士全面了解中国的医疗体制、各项政策法规;深谙外资医院在华发展之道;洞悉中国医疗健康市场的现状与发展。她仍在不断学习中,在繁忙的工作之余,盘仲莹女士还在继续攻读美国阿拉巴马大学伯明翰分校医院管理博士学位。她于湘潭大学获得英语文学系学士学位,后取得北京大学工商管理硕士学位以及美国科罗拉多大学卫生保健专业工商管理硕士学位。

Disputes involved in public–private partnership (PPP) projects destroy the relationship between governments and private partners and generate huge losses. To multiply the chances of successfully preventing disputes, a holistic understanding of how a PPP dispute occurs is necessary. This paper contributes to the PPP dispute studies domain in (1) identifying various contributors that lead to the formation of PPP disputes at different levels, (2) proposing a fault tree (FT) framework of a PPP dispute, and (3) evaluating the likelihood of a PPP dispute and displaying the weakest part of a PPP project. First, three basic components that drive the development of PPP disputes are identified: project uncertainty, opportunistic behaviors, and contractual incompleteness. Second, scenario modeling of PPP disputes through fault tree analysis (FTA) depicts a more intelligible structure of PPP disputes. Furthermore, the fuzzy sets evaluation method was employed to compute the fuzzy occurrence likelihood of a PPP dispute. The results indicate that dispute is inevitable in PPP projects (with an occurrence likelihood of 0.9464). Additionally, opportunism is the dominant dispute inducer in PPPs. Our findings are expected to help PPP participants understand how various drivers contribute to the occurrence likelihood of PPP disputes where past data is inadequate. Then, more cost-efficient and appropriate preventive strategies can be developed based on the assessment to minimize the occurrence of PPP disputes.

Abstract. Liquefaction-induced hazards such as sand boils, ground cracks, settlement, and lateral spreading are responsible for considerable damage to engineering structures during major earthquakes. Presently, there is no effective empirical approach that can assess different liquefaction-induced hazards in one model. This is because of the uncertainties and complexity of the factors related to seismic liquefaction and liquefaction-induced hazards. In this study, Bayesian networks (BNs) are used to integrate multiple factors related to seismic liquefaction, sand boils, ground cracks, settlement, and lateral spreading into a model based on standard penetration test data. The constructed BN model can assess four different liquefaction-induced hazards together. In a case study, the BN method outperforms an artificial neural network and Ishihara and Yoshimine's simplified method in terms of accuracy, Brier score, recall, precision, and area under the curve (AUC) of the receiver operating characteristic (ROC). This demonstrates that the BN method is a good alternative tool for the risk assessment of liquefaction-induced hazards. Furthermore, the performance of the BN model in estimating liquefaction-induced hazards in Japan's 2011 Tōhoku earthquake confirms its correctness and reliability compared with the liquefaction potential index approach. The proposed BN model can also predict whether the soil becomes liquefied after an earthquake and can deduce the chain reaction process of liquefaction-induced hazards and perform backward reasoning. The assessment results from the proposed model provide informative guidelines for decision-makers to detect the damage state of a field following liquefaction.

Blockchain has been regarded as an emerging global phenomenon in the field of new technologies. However, the existing literature still lacks descriptions of the cooperation characteristics and innovation landscape of blockchain. This study uses the social network analysis method to compare the development of blockchain technology and technological collaboration in China and in the United States based on patent data. Our analyses suggest that the number of blockchain patent applications in China is increasing rapidly due to the Chinese Government developing consistent national strategies for blockchain technology. In all, both countries have notable agglomerations in a few geographical areas or cities. However, the university or enterprise block in the United States has broader and deeper cooperation, unlike the Chinese university or enterprise block, which is more inclined to cooperate within blocks and has more isolated blocks. Lastly, there are various patent attributes-influencing factors behind the importance of node cooperation. The results show that the degree of cooperation of cooperative inventors or important patents is greater in China's cooperation network, while in the United States, the influence of enterprises rather than universities or individuals is greater.

Blockchain has been regarded as an emerging global technological phenomenon. This study uses the patent analysis method to compare the development of blockchain technology in China and the USA. An overview of blockchain policies in China and the USA is presented. Our analyses suggest that policies related to the blockchain stimulate the number of blockchain patent applications and create regional innovation in China. The innovation capability of Chinese enterprises has been more affected by these policies than that of the USA, which is reflected in the fact that Chinese enterprises have become key players in China and actively carry out patent layout in the USA. Although the developmental trend of blockchain technology in China and the USA is almost identical, the USA attaches more importance to safety technology, whereas China pays more attention to the application technology based on the differences in policies.

This paper investigates a hybrid management policy of road tolls and tradable credits in mixed road networks with both public and private roads. In the public sub-network, a tradable credit scheme is applied to mitigate traffic congestion. In the private sub-network, tolls are collected by the private company, but the toll levels and toll locations are determined by the government. The purpose of toll charge is two-fold: on the one hand, the government uses it as a tool for mitigating congestion; on the other hand, a threshold of revenue should be guaranteed for the profitability of the private company. A bi-level programming model is formulated to minimize the total travel time in the network by taking into account the user equilibrium travel behaviour and the revenue requirement of private firms. To obtain a global optimum solution, the bi-level model is transformed into an equivalent single-level mixed integer linear program that can be easily solved with commercial software. Numerical examples are provided to demonstrate the effectiveness of the developed model and the efficiency of the proposed algorithm. It is shown that the mixed management schemes can achieve favourable targets, namely, joint implementation of road tolls and tradable credits can effectively mitigate traffic congestion and meanwhile maintain reasonable revenue for the private company.