集中连片特困地区扶贫产业发展的规模特征及其经济效率评价——以武陵山片区恩施自治州为例

[目的]在扶贫开发战略中成长起来的特色产业已经成为贫困地区经济发展和农民脱贫致富的支柱产业,特色产业的规模和经济效率直接决定着贫困地区脱贫致富能力。[方法]文章以茶叶、蔬菜代表武陵山片区湖北省恩施自治州扶贫产业,利用集中度指数、扩张弹性系数、单位面积的产值能力和产量能力以及单位产量的产值能力等指标进行扶贫产业发展的规模特征及其经济效率评价。[结果]“十一五”期间以来武陵山片区扶贫产业发展的产业地位逐渐提高、规模扩张优势显著、规模收益递增、投入规模扩张率高于产出规模扩张率、资源配置效率不断提高,比较经济效率差距持续扩大。[结论]扶贫产业亟待根据产业发展的生态化、集聚化和融合化等趋势,在规模扩张中强化特色产品的品质建设和效率优势品种生产专业化程度、提高生产技术水平以及完善产业化组织及其能力建设,提高扶贫产业的经济效率和致富能力。     

Factors influencing consumers' purchase decision-making in O2O business model: Evidence from consumers' overall evaluation

Online-to-offline (O2O) has become a rapidly growing e-commerce model worldwide, but the factors influencing consumers' purchase decision-making have not been examined well. After exploring the working mechanism of the O2O model, we extract eleven indexes of consumers' overall evaluation in the O2O model with Crawlzilla and R techniques. Social network analysis (SNA) is adopted to build social networks reflecting consumers' overall evaluation in the O2O model. Based on the modified social network and the extracted subgraph, this study (N = 768) reveals consumers' overall evaluation behavior patterns in the O2O model by calculating network density, central potential, edge betweenness. The results show that shoppers overall evaluate the eleven indexes, especially perceived product quality, online product price, promotion intensity, business reputation, and product brand, which reflects the significant associations between the indexes. Among all the eleven evaluation indexes, perceived product quality, online product price, and business reputation dominate consumers’ decision-making behavior. When making purchase decisions, consumers not only overall consider online product price, perceived product quality, and business reputation but also balance perceived product quality, business reputation, and promotion intensity. Finally, we make some suggestions on marketing strategy for e-commerce companies.     

Stochastic leader–follower DEA models for two-stage systems

Data envelopment analysis (DEA) is a non-parametric approach for measuring the relative efficiencies of peer decision making units (DMUs). In recent years, it has been widely used to evaluate two-stage systems under different organization mechanisms. This study modifies the conventional leader–follower DEA models for two-stage systems by considering the uncertainty of data. The dual deterministic linear models are first constructed from the stochastic CCR models under the assumption that all components of inputs, outputs, and intermediate products are related only with some basic stochastic factors, which follow continuous and symmetric distributions with nonnegative compact supports. The stochastic leader–follower DEA models are then developed for measuring the efficiencies of the two stages. The stochastic efficiency of the whole system can be uniquely decomposed into the product of the efficiencies of the two stages. Relationships between stochastic efficiencies from stochastic CCR and stochastic leader–follower DEA models are also discussed. An example of the commercial banks in China is considered using the proposed models under different risk levels.     

Auditors' Responses to Workload Imbalance and the Impact on Audit Quality*

Using detailed data for fieldwork hours and audit hours by rank from audit engagements in Korea, we examine whether audits conducted under workload imbalance, proxied by busy‐season audits, impair audit quality, and how auditors adjust staff assignments for busy‐season audits. We generally find that busy‐season audits are associated with lower audit quality, and that audit firms reduce the involvement of senior auditors during busy‐season audits. In addition, the greater the involvement of senior auditors and junior auditors, the lesser the deterioration in audit quality. Finally, although there is no increase in interim audits in response to workload imbalance during busy seasons, increasing interim audits can mitigate the negative impact of busy‐season audits on audit quality. Our results are relevant to auditors and regulators, who have expressed concerns about the adverse effects of workload imbalance on audit quality.     

混合型基金绩效评估及驱动因素分析——基于DEA-Tobit模型

将随机选出的混合型基金作为研究样本,采用DEA-Tobit二阶段模型进行研究.首先利用数据包络模型对样本进行绩效评估,在此基础上,利用Tobit模型研究相关指标对于基金绩效的影响机制.结果表明,基金本身所面临的风险收益因素以及基金经理团队稳定性对于基金绩效均具显著影响.最后结合实证结果就提升中国基金绩效提出相关的建议.     

南京江北新区新型城镇化发展质量评价与提升路径

文章构建了由31项指标组成的新型城镇化综合发展质量评价指标体系,运用AHP层次分析法和熵值法,选择19个国家级新区中2018年经济总量排名前十的新区进行定量对比分析,并结合民生幸福建设群众满意度问卷调查分析,对南京江北新区新型城镇化发展质量进行综合评价。研究表明:(1)南京江北新区新型城镇化整体发展处于中上游水平,与发达新区相比存在一定差距,产业结构亟需优化;(2)发展增长方式、资源利用率、环境保护类指标明显落后;(3)科教文卫、居民生活等指标具有比较优势。文章最后提出新型城镇化提升路径为加快生态环境和公共服务建设,积极提升科教和生态示范效应,做大做强主导产业,促进城乡特色均衡发展和推进以人为核心的新型城镇化。     

Nowcasting South African gross domestic product using a suite of statistical models

Given lags in the release of data, a central bank must ‘nowcast’ current gross domestic product (GDP) using available quarterly or higher frequency data to understand the current state of economic activity. This paper uses various statistical modelling techniques to draw on a large number of series to nowcast South African GDP. We also show that GDP volatility has increased markedly over the last 5 years, making GDP forecasting more difficult. We show that all the models developed, as well as the Reserve Bank's official forecasts, have tended to overestimate GDP growth over this period. However, several of the statistical nowcasting models we present in this paper provide competitive nowcasts relative to the official Reserve Bank and market analysts' nowcasts.     

Japan's FDI drivers in a time of financial uncertainty. New evidence based on Bayesian Model Averaging

In this paper we analyse the determinants of Japanese outward FDI stock for the period 1996–2017. This period is especially relevant as it covers a process of increasing economic globalization and two financial crises. To this aim, we consider a large set of candidate variables based on the theory as well as on previous empirical analysis. Our sample includes a total of 27 host countries. We select the covariates using a data-driven methodology, the Bayesian Model Averaging (BMA) analysis. Moreover, we also analyse whether these determinants change depending on the degree of development (emerging vs developed) or the geographical areas (EU vs East Asia) of the countries considered. We find that Japan's FDI can be explained by a wide variety of variables, that include not only the typical gravitational ones but also institutional and macroeconomic variables, including those that measure financial development. Moreover, Japanese FDI can be explained by both horizontal and vertical FDI motives in the groups of countries analysed. However, in developed, and more precisely, EU countries, horizontal FDI strategies are predominant, whereas for East Asian and emerging countries, there is more evidence in favour of vertical FDI.     

An evaluation framework for developing green infrastructure by using a new hybrid multiple attribute decision-making model for promoting environmental sustainability

With the expansion of urbanization caused by the growth of population and industrial activities, the urban/city and suburban areas are facing a variety of environmental threats. Although more research and urban policy has advocated and practiced the development of green infrastructure (GI) to support urban sustainable environment, the evaluation framework for the development of GI for promoting environmental sustainability is still insufficient. Moreover, the Analytic Hierarchy Process (AHP) commonly applied in published literature, makes an unrealistic assumption of independent relationships among dimensions/criteria in decision making for satisfying the real-world problem. Therefore, the purpose of this study is to construct the evaluation framework, including four dimensions and related ten criteria, using a new hybrid-modified multiple attribute decision-making (MADM) model for developing and improving the GI for promoting environmental sustainability. This MADM model is combined with three different methodologies of MADM, including the Decision-Making Trial and Evaluation Laboratory (DEMATEL) for constructing the influential network relation map (INRM) to explore the complex influential inter-relationships and DEMATEL based on Analytic Network Process (DANP) for determining the influential weights with the VIse Kriterijumska Optimizacija I Kompromisno Resenje (VIKOR) for evaluating and presenting improvement strategies for six different GIs. The empirical study indicates that DEMATEL and DANP Results suggest that decision-makers should pay more attention to the improvement of Design (D₄) and Materials (D₂) in terms of dimensions when utilizing the GI to promote environmental sustainability. Because these dimensions are enhanced, Species (D₁) and Energy (D₃) will be improved in synchronization. From the perspective of criteria, five are key core criteria and need to be focused on first: increasing the green coverage rate (B₉), utilizing sustainable materials (B₄), using ecological engineering (B₈), shaping species biodiversity (B₁), and reducing energy consumption (B₅). Modified VIKOR reveals that “grass swales” are a comparatively better choice among six GIs for promoting environmental sustainability toward achieving the aspiration level. Therefore, this MADM model is beneficial to provide a more convincing assessment framework and improvement strategies for the development of GI for promoting environmental sustainability. As a result, these modified MADM models can be shown more conveniently and reasonably than traditional methods such as traditional AHP or ANP method.     

Return policy,No joke: An investigation into the impact of a retailer's return policy on consumers' decision making

This study investigates the important role of a retailer's return policy in consumers' decision making. Utilizing signaling theory and the Cue Diagnosticity framework, this study posits that return policy, as a cue from a retailer, interacts with other cues (product, price, and product quality) to reduce perceived purchase risk and increases store image and patronage intention. Employing factorial experiment design, the authors conduct two studies and find support for several hypotheses. Results show that consumers value return policies depending upon the situation. A lenient return policy drives down purchase risk and leads consumers to have positive store images and higher patronage intentions. Both theoretical and managerial implications of the findings are provided.