乡村森林旅游项目规划中哲学元素运用的个案分析——以宜春市月都花溪谷项目为例

以江西省宜春市"月都花溪谷"乡村森林旅游项目规划中哲学元素的应用为个案,结合哲学理论进行分析。结果表明:乡村森林旅游项目规划应有哲学的自觉,根据项目所在地自然和人文资源禀赋,因地制宜地吸收哲学元素,从而打破乡村森林旅游项目同质化和见物不见人的困局,赋予乡村森林旅游项目以特色和灵魂。因此,提出突破森林旅游项目规划中一元化的经济思维定势、以哲学思维唤起人学意义、因地制宜激发内生式哲学文化活性等启发性建议。     

中国集体林产权制度改革回顾与展望

采用历史产权制度研究方法,利用详实的历史数据与信息,系统地分析改革开放以来中国集体林产权制度改革每个重要时期的改革内容与进程以及集体林地林木流转制度演化历程,发现改革开放四十年中国集体林所有权和家庭经营的基因没有变,变的是集体林地承包经营权的实现形式;指出集体林产权制度变迁道路中的困惑;提出未来集体林产权制度的选择路径。     

生态文明建设背景财政扶持、林权改革对林业生产效率的影响

基于2000—2016年中国省际面板数据,利用DEA-Malmquist指数法对中国林业生产效率的区域差异和时序变化进行研究,运用面板Tobit模型检验财政扶持对林业生产效率的影响并验证林权改革对二者关系的调节作用。研究发现:在生态文明建设背景下,林业生产效率存在显著的区域差异;技术进步对于全要素生产率的提升起到重要推进作用;财政扶持与林权改革均对林业生产效率产生了正向影响,但林权改革并没有对财政扶持与林业生产效率的关系产生积极调节作用。因此,各省份应当通过加大政府扶持力度、优化投资方式、深化集体林权制度改革等措施促进林业生产效率提升。     

互联网金融规制与市场有效性改善*——来自中国网络借贷行业的证据

中国的互联网金融经历了一个先创新发展后监管规制的过程，本文通过对网络借贷行业的实证研究，分析监管规则的出台实施对新型互联网融资市场有效性的影响。实证结果表明，网络借贷平台资金的银行存管、持有ICP证等强制性规定缓解了投资者、平台企业与借款人之间的信息不对称，对克服早期平台间通过竞相承诺高回报率来吸引投资者导致的“柠檬市场”问题、对解决网贷市场上缺乏平台风险性高低有效信号的问题都起到了正向作用，有助于互联网融资市场的有效性提高。     

区域森林公园生态效率实证分析——以华东地区为例

采用Malmquist-Luenberger指数法对华东地区森林公园生态效率值进行测定的结果表明:从时序范围看,2011—2016年华东地区森林公园生态效率的均值为1. 006,但从2015年起进入下滑态势,说明华东地区森林公园的生态效率已经达到有效水平,但在扩大森林公园规模的同时忽视了对环境的有效保护以及资源的合理配置;从空间差异角度看,只有浙江与安徽两省的森林公园生态效率值未达到有效水平(分别为0. 851和0. 871),其余各省(市)的森林公园生态效率值均大于1,说明区域内存在一定的差异性;技术进步指数下降是制约MalmquistLuenberger指数提升的主要原因。由此可见,加大技术投入,促成交流合作机制,形成特有的竞争优势等,对提高区域森林公园生态效率是十分重要的。     

Drivers of eWOM engagement on social media for luxury consumers: Analysis,implications, and future research directions

The rapid industrialization and growth across the world have fostered the consumption of luxury fashion brands. Electronic word-of- mouth on social media (eWOM) is fast becoming an effective and germane strategy to engage luxury consumers through posting pictures, sharing reviews, and communicating information on platforms like Facebook, Instagram, and TikTok. Extant research has not examined the antecedents and drivers that lead to eWOM behavior. We leverage self-congruity theory and through its focal lens, our study addresses this research gap through a survey conducted with 453 consumers in Mexico, Latin America's fastest growing market. Our results indicate that need for status, susceptibility to normative influence, and luxury brand involvement, moderated by authentic pride and social media influencers lead to eWOM behavior on social media. We also demonstrate that luxury brand involvement and susceptibility to normative influence mediate the relationship between need for status and eWOM behavior on social media. The study provides important implications to managers and researchers by suggesting long-term actionable strategies for growth that can help luxury firms develop a sustainable competitive advantage over rivals and competitors.     

Twenty-Five Years after the Fall of the Berlin Wall: An Empirical Revisit of West German Consumers' Attitudes Toward Products and Brands from Former East Germany

More than 25 years after the German reunification, data show that products/brands from the eastern regions of Germany (“Neue Länder”) still do not have significant shares in the country's western part (“Alte Länder”). To analyze potential reasons for this phenomenon, our current study replicates a previous study that investigated selected attitudes of Alte Länder consumers toward products/brands from the Neue Länder. It is shown that factors such as consumer ethnocentrism, product judgment, willingness to buy, and economic animosity continue to influence consumer behavior and as such our study offers potential explanation for the failure of Neue Länder products/brands in the western regions of Germany.     

刑事涉财产执行中的案外人权益救济——以案外人权益救济程序的当事人构造为视角

刑事涉财产执行程序因采取移送执行模式而被误认为不存在申请执行人，使得刑事涉财产执行程序及其衍生的案外人权益救济程序过分依赖执行法院的职权主义。在刑事附带民事诉讼裁判、追缴或责令退赔违法所得并返还被害人判项、责令被免予刑事处罚的被告人赔偿被害人损失判项的执行程序中，案外人权益救济程序原则上应以被害人为申请执行人，并参照适用民事强制执行程序中的案外人权益救济制度。其他刑事涉财产执行程序应以检察机关为申请执行人。除非出现被执行人逃避执行或者案外人对执行标的提出排除执行请求等特殊情形，作为申请执行人的检察机关通常无须现实参加执行程序。     

Machine learning for financial transaction classification across companies using character-level word embeddings of text fields

An important initial step in accounting is mapping financial transfers to the corresponding accounts. We devised machine-learning-based systems that automate this process. They use word embeddings with character-level features to process transaction texts. When considering 473 companies independently, our approach achieved an average top-1 accuracy of 80.50%, outperforming baselines that exclude the transaction texts or rely on a lexical bag-of-words text representation. We extended the approach to generalizes across companies and even across different corporate sectors. After standardization of the account structures and careful feature engineering, a single classifier trained on 44 companies from 28 sectors achieved a test accuracy of more than 80%. When trained on 43 companies and tested on the remaining one, the system achieved an average performance of 64.62%. This rate increased to nearly 70% when considering only the largest sector.