A new assessment of economic integration in East Asia: Application of an industry-specific G-PPP model

It is well known that intra-industry trade and cross-border production networks have promoted economic growth and regional integration in East Asia. However, regional supply and production chains may have been formed differently across industries, reflecting different degrees and a different scope of regional economic linkages at an industry level. This paper makes a threefold contribution. First, to assess industry-level differences, this study adopts the generalized purchasing power parity (G-PPP) model using industry-specific producer prices. Second, the momentum threshold autoregressive (M-TAR) model is employed to allow for possible nonlinearity arising from the dynamic nature of regional economic growth and development. Third, the Granger causality test is also conducted to assess whether regional economies have autonomously integrated. The empirical results reveal that economic integration has progressed more autonomously in the electrical industry, as well as in the transportation equipment industry, as China and the ASEAN countries have become the final destination markets for finished products in these two industries.     

Microfinance and social capital formation- a social network analysis approach

The microcredit program has emerged as an important poverty alleviation strategy over the last three decades, and several studies have examined its economic impacts on the community well-being. However, far too little attention has been paid to the effects of micro credits on community social connection and solidarity. This paper aims to examine the application of Social Network Analysis (SNA) to explore the impact of the rural microcredit fund on community social capitals. In doing so, the data on interactions of four rural development groups' members before and after the microcredit project implementation were collected using participatory workshops in Neyzar village of Qom province in Iran. The data were analyzed by Ucinet software, and the socio-graphs were produced by the NetDraw application. The results show that, more people have been involved in the social interactions after the project implementation and there was statistically significant increase in density and decrease in centralization of cooperation network. Furthermore, there were no important distinctions in centrality of people with various educational levels before and after the project implementation. Overall, it can be concluded that, the microfinance initiative considerably promotes the community social capital and participation in the rural development activities. Moreover, the SNA techniques are applicable as an impact assessment tool to investigate changes in community social capital.     

Comparative study of deep learning models for analyzing online restaurant reviews in the era of the COVID-19 pandemic

Online reviews remain important during the COVID-19 pandemic as they help customers make safe dining decisions. To help restaurants better understand customers’ needs and sustain their business under current circumstance, this study extracts restaurant features that are cared for by customers in current circumstance. This study also introduces deep learning methods to examine customers’ opinions about restaurant features and to detect reviews with mismatched ratings. By analyzing 112,412 restaurant reviews posted during January-June 2020 on Yelp.com, four frequently mentioned restaurant features (e.g., service, food, place, and experience) along with their associated sentiment scores were identified. Findings also show that deep learning algorithms (i.e., Bidirectional LSTM and Simple Embedding + Average Pooling) outperform traditional machine learning algorithms in sentiment classification and review rating prediction. This study strengthens the extant literature by empirically analyzing restaurant reviews posted during the COVID-19 pandemic and discovering suitable deep learning algorithms for different text mining tasks.     

The mechanism of credit risk contagion among internet P2P lending platforms based on a SEIR model with time-lag

The credit risk contagion of Internet peer-to-peer (P2P) lending platforms is an important part of Internet financial risk management and supervision. This study analyzes the contagion path of credit risk in Internet P2P lending. Based on complex network theory and the theory of infectious disease dynamics, the characteristics of Internet P2P lending development are combined to construct a SEIR model of credit risk transmission among Internet P2P lending platforms with time lag, and the robustness of the model is analyzed and proven. The influence of platform correlations, the susceptible immune rate, the platform elimination rate, contagion latency, the saturation coefficient, and the susceptibility input rate on credit risk contagion behavior among Internet P2P lending platforms is analyzed, using the equilibrium point and threshold value. The impact of each variable is analyzed by simulation. Corresponding countermeasures and suggestions are proposed to prevent and control credit risk contagion among these platforms.     

Perceived hygiene attributes in the hotel industry: customer retention amid the COVID-19 crisis

The COVID-19 pandemic has caused a crisis in the hotel industry worldwide, but few studies have suggested methods to retain customers. This study proposes hygiene management as a means to minimize the indirect damage from COVID-19 to the hotel industry. It identifies perceived hygiene attributes and explores their influence on hotel image, word of mouth, and revisit intentions. This study identifies and validates three types of perceived hygiene attributes through qualitative and quantitative methods. It uses structural equation modeling to validate hypotheses and concludes that there are significant relationships of influence between the proposed variables. This study provides important and meaningful insights into hotel image and customer behavior through perceived hygiene attributes.     

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。     

海南城乡居民消费水平差异性分析和预测

从1985-2018年海南城乡居民收入、消费数据出发，分别建立消费关于收入、消费差距关于收入差距的自回归模型，结果表明农村居民当期消费更易受近期收入和消费水平的影响，具有不稳定性。再利用GM(1,1)模型预测城乡居民收入差距，结合自回归模型，完成未来10年海南城乡消费差距的预测：收入差距和消费差距将呈直线递增趋势，收入差距的增幅高于消费差距增幅。缩小海南城乡居民消费差距的根本途径在于缩小收入差距，应因地制宜，切实提高农民收入水平。     

决策可靠性分析及在SAR图像目标识别中的应用

决策融合是提高合成孔径雷达（Synthetic Aperture Radar,SAR）目标识别性能的重要手段，然而，可靠性较弱的决策往往会导致最终决策融合的效果变差。将可靠性分析引入基于决策融合的SAR目标识别方法中，分别计算各个决策的可靠性系数并选取可靠性的决策参与最终的决策融合。为了验证方法的有效性，分别将提出的可靠性分析应用于多特征决策融合以及多分类器决策融合并基于MSTAR（Moving and Stationary Target Acquisition and Recognition）数据集进行了目标识别实验。在基于主成分分析、线性鉴别分析和非负矩阵分解三种特征进行多特征决策融合的条件下，所提方法和直接进行决策融合的方法的识别率分别为97.47%和96.50%。在基于K近邻、支持向量机和稀疏表示分类器的多分类器决策融合中，所提方法和直接进行决策融合的方法的识别率分别为97.10%和96.28%。实验结果充分证明了所提方法的有效性。     

Measuring industrial upgrading: applying factor analysis in a global value chain framework

ABSTRACT

A key question for promoting international competition is how to improve the position of countries and industries in global value chains (GVCs). The first step is to properly measure industrial upgrading in GVCs. This is not a trivial issue because upgrading has not been defined unambiguously. Several authors have used different (and sometimes related) measures, all of which indicate certain aspects of upgrading. Rather than trying to find the single, ultimate measure of upgrading, we propose a different approach. We examine the multidimensionality of industrial upgrading, using eight indicators in factor analysis. Four of the eight indicators adopt the GVC perspective and include, for example, the growth of the share in value-added exports. We provide three quantitative dimensions of industrial upgrading: process upgrading, product upgrading, and skill upgrading. With these dimensions, we compare and analyze the upgrading of different countries and industries using the World Input–Output Database.     

江苏省农田保护经济补偿政策绩效评价与空间差异研究

［目的］分析评价江苏省现有农田保护经济补偿政策绩效与空间差异对建立完善长效的农业生态补偿机制和推动我国农业生态环境的可持续发展具有重要意义。［方法］以江苏省为研究区域，运用熵权-TOPSIS法，选取2010—2017年全省及苏北、苏中、苏南三个区域内11个指标，计算江苏省及三大区域农田保护经济补偿政策综合绩效值与经济、生态和社会效益单项绩效值，进行比较分析。［结果］（1）江苏省农田保护经济补偿政策在2010—2017年8年综合绩效值由0189波动增长到0841，效果初现且具有较强推广价值。（2）经济效益绩效值以年均257%的增长率由0增长到1，效果最为显著，社会效益次之，生态效益自2013年后为绩效值中最低值，与前两项最大差距在05左右，反映出环境改善、农田质量提高效应远低于农户创收、社会公平效应，政策拟合度不高。（3）江苏省农田保护经济补偿政策效果存在空间差异，综合来看政策效果表现为苏南>苏中>苏北，苏南凭借经济优势在2016年和2017年的综合绩效值上比苏中苏北高出01、在经济与社会绩效值以002的差距领先且生态绩效值没有下降拐点，具有长效可持续性。［结论］现阶段农田保护经济补偿政策效果依赖地方政府经济实力，尚未形成良性长效机制，需从制度体系、环境经济手段、差别化补偿措施、农业补贴结构和宣传等5方面着手，推进农田保护经济补偿政策更好地服务生态环境。