基于景观适宜性的山地公园植物景观 评价研究——以贵阳黔灵山公园为例

以贵阳市黔灵山公园为研究对象，选取24个植物景观单元。以生态适宜、景观适宜、社会适宜为准则层，建立山地公园植物景观景观适宜性评价体系。运用主成分分析确定评价指标权重，克服以往植物景观评价赋权重的主观性，建立山地公园植物景观景观适宜性评价模型，得到不同植物景观的景观适宜性指数。结果表明：黔灵山公园在适宜范围内的植物景观有10个，占评价单元总数的41.6%，适宜性较差的有14个，乔灌比(数量)在1:11.2~1.7:1之间的植物群落景观适宜性较好。根据评价结果，提出了3点山地公园植物景观营建策略，以期为山地公园植物景观评价及营建提供理论指导。     

Assessment of OECD Better Life Index by incorporating public opinion

Well-being has a multidimensional nature as it depends on multifaceted factors such as material conditions and quality of life. The Organization for Economic Co-operation and Development (OECD) has developed the Better Life Index (BLI) as part of the OECD Better Life initiative to facilitate the better understanding of what drives well-being of people. The BLI is a three-level hierarchical composite indicator that covers several socio-economic aspects. In this paper, considering the entire hierarchical structure of the index, we introduce a bottom-up procedure for the aggregation of the components at each level. We formulate the assessment of BLI as a multiple objective programming (MOP) problem that facilitates the implementation of different concepts to derive different aggregation schemes. We incorporate the data from previous years into the normalization process of the indicators, to take into account the discrepancy on their observed values and smooth their deviations across the years. Also, we consider the public opinion about well-being that is captured from the worldwide responses in the web platform of OECD BLI. We incorporate the public opinion into the assessment models in the form of weight restrictions. In this way, we reduce the effect of compensation that might be imposed by the adopted modelling approach. We apply our methodology to the data of 38 countries (35 OECD and 3 non-OECD economies) for the year 2017. Our findings illustrate that the public opinion in the form of weight restrictions can effectively drive the optimization process and depict the collective preferences to the BLI scores.     

Dynamic efficiency evaluation of Italian judicial system using DEA based Malmquist productivity indexes

The aim of this study is the empirical analysis of the Italian judicial system, measuring its efficiency and productivity. For this purpose, in details, the Data Envelopment Analysis (DEA) and Malmquist indexes were used, since they are recognized by the current literature as successful techniques to evaluate the performance of decision making units, namely the courts of law in our field of application.The statistical data on the administration of justice in Italy, as reported in Dossier n. 11 May 2013, Senate Research Services, Research Office on Institutional Issues, Justice and Culture, XVII legislature, shows that the efficiency crisis of justice in Italy began in the 1970s of the last century, aggravating during the ‘80s, and reaching its most critical moment during the 1990s. Several studies emphasize the relevance of the effects of inefficiency upon the judicial system on the credit and financial markets.The present analysis, using data that covers a wide time span and is disaggregated at district level, has set the goal of measuring the efficiency of the individual Italian judicial offices while assessing the progress of productivity in its components, by the means of technological progress and scale efficiency. The efficiency analysis that was carried out transcends the aspect of judicial taxation, considering how the passage of time has impacted on judicial efficiency.Considering the judges and judicial administration employed, in the new, pending and finished cases during the years ranging from 2011 to 2016, the results highlighted a distinct heterogeneity among courts, depending on their geographical location. The five-year period that was considered, included the years in which the judicial geographical distribution reform entered into force, so to better comprehend how this complex reform influenced the recovery of efficiency of the judicial offices. Furthermore, by breaking down the index into change in efficiency and change in technology, this work offers a further glimpse into judiciary organization. The application of combined DEA method and Malmquist indexes for evaluating court efficiency in a large time frame showed very interesting and useful results, relevant for judicial administration.     

新时代中国城市土地集约利用若干问题的再认识

研究目的：基于中国城市土地集约利用研究现状，面向新时代要求，重新审视与厘清城市土地集约利用理论认知、评价标准、影响机制和优化调控等基本问题，为中国土地集约利用的理论完善和实践创新提供支撑。研究方法：理论分析法和推理演绎法。研究结果：（1）城市土地集约利用在理论认知上应由“三个阶段”转向“三个时期”；（2）城市土地利用集约度的评价标准应由静态指标转向动态耦合；（3）城市土地集约利用的影响机制研究应由封闭区域转向关联传导；（4）城市土地集约利用优化调控策略应由极限集约转向最优集约。研究结论：进入新时代，城市土地集约利用理论上可实现“不增地，多增效”甚至“地减量，效增加”，未来相关研究应重点关注存量和减量规划中建设用地与经济发展之间关系的变化特征，以及国土空间规划与土地利用计划管理改革下新的城市土地集约利用问题。国家相关规程中的集约评价标准须结合区域发展阶段进行“匹配性”修正，政策制定要考虑区域间的“关联性”和“传导性”进行精准化设计，治理方案应按照最优集约度的“动态性”进行差异化调控。     

基于模糊评价模型的物流管理专业实践教学体系研究

考虑物流管理专业实践教学的特性,从实践环节、创新与创业、管理机制、教学团队等方面构建了实践教学指标体系,并运用模糊综合评价法进行评价分析。研究结论表明,毕业实习、毕业论文、学科竞赛、创新与创业项目对物流管理专业实践教学的影响较大。     

基于平衡计分卡的银行系寿险公司绩效评价研究

随着金融混业经营趋势不断加强，2009年起中国的银行开始入股保险公司，且以建立寿险公司为主。为了能全面评价银行入股保险公司后的运营绩效，通过构建平衡计分卡模型，从各项评价指标和总绩效角度将银行系寿险公司与传统寿险公司进行比较，发现在三年的时间里，银行系寿险公司发展迅速，且综合绩效较好，相对于传统的中小型寿险公司，具有明显的优势和发展潜力，但与大型的寿险公司相比仍有一定的差距。     

基于K-S检验与距离相关分析的网络借贷信用评价指标体系构建

网络借贷作为一种新型互联网金融模式,提升了金融资源使用效率,缓解了小企业融资难的困局。构建合理的网络借贷信用评价指标体系,从而对网络借贷的潜在风险及时甄别与预防,对互联网金融健康持续发展意义重大。本文根据K-S检验与距离相关分析相结合,筛选对借款客户违约状态甄别能力强的指标,建立了网络借贷信用评价指标体系,通过P2P网络借贷(peer to peer lending,个人对个人借贷)平台LendingClub交易数据进行实证研究,结果表明:不仅借款金额、借款利率等借款标的特征对借贷者违约具有显著相关性,借款者年龄等个人特征、借款者年收入等财务特征以及借款者违约次数等信用特征均对借贷者违约风险产生显著影响。投资者在出借资金时,往往青睐于已婚、年龄适中、具有一定工作经历、历史违约次数较少的借款人。因此,风险监管部门应构建网络借贷违约风险评估模型,对P2P平台进行风险监测,同时建立关键信息共享机制,融合多源数据,明确审查范围,实现P2P网络借贷行业健康有序发展。     

敦煌种业财务绩效评价研究

选择以农业上市公司敦煌种业为研究对象,以企业2014—2019年的报表数据为基础,采用功效系数法并以国务院国资委所编写的《企业绩效评价标准值》中国有企业绩效评价体系作为参考,构建对农业企业的财务指标评价体系,对敦煌种业2014-2019年企业财务指标的表现进行纵向分析,选择同行业中营业收入水平较高的北大荒进行横向对比,通过对比发现敦煌种业的问题主要体现在盈利能力和资产质量方面,对此提出了改进措施及建议。     

首旅酒店EVA业绩评价研究

EVA业绩评价法立足于为股东创造更多财富的经营目标,有助于企业更加客观地判断经营现状和调整经营策略,近年来被越来越多的企业选择采用。本文以首旅酒店为例,探讨EVA模型在旅游业中的具体应用,分析EVA模型相较于传统的业绩评价指标的优点,并提出具体的实施建议。     

Green multi-tier supply chain management: An enabler investigation

Stakeholder pressure, from actors including regulators, consumers and non-governmental organizations, has made organizations more responsible for poor environmental performance of their direct and sub-suppliers. Thus, green multi-tier supplier management (GMSM) has become an emergent topic. Yet it is still unclear how to enable GMSM practices effectively, i.e. how to enable sub-suppliers' environmental performance improvement. To help address the gap in the literature, this paper aims to identify enablers for sub-suppliers' environmental performance improvement, and it further applies a Decision-Making Trial and Evaluation Laboratory (DEMATEL)-based case study method to evaluate inter-relationships among these enablers and improve the focal company's GMSM practices, by using action research (AR) method principles. The data analysis and discussion with a follow-up evaluation after two years provided insights for the successful implementation of GMSM. The results show that top managers’ support from the organizations is a prominent and necessary foundational enabler. An interesting observation is that close proximity of supply chain members is regarded as a very prominent enabler. Evaluation and feedback on these enablers two years later found that the enabler mapping was beneficial, allowing them to address the most influential enablers, and thus the GMSM practices of the focal company has been highly improved. This paper concludes with directions for further research.