Adverse effect of social media on generation Z user's behavior: Government information support as a moderating variable

Social media emerged as a primary source of information among young users, but its severe effect on mental state due to information overload, still an area of concern for the researchers. Generation Z users' addiction to the mobile phone/gadgets is increasing with a rise in social media and consequently their behavioral outcomes have transformed completely. Nowadays behavioral issues including stress, fatigue, ‘fear of missing out’ and ‘phubbing’, anxiety etc. rising each day but the relationship among these issues and information overload is less examined. The social media users are unable to filter the trustworthy information due to its enormous size and thus role of information support from government becomes essential. The current study extends the S-O-R theory exploring relationship between the stimulus of enormous information on the responses generated among the Generation Z such as social media fatigue, ‘fear of missing out’, ‘phubbing’ and anxiety. The findings from a sample of 319 users belonging to Generation Z suggest that social media platforms need to understand user's compulsive usage that is resulting into fatigue and consequently anxiety. The role of government information support on reducing fatigue and anxiety is found to be positive. The relationship between ‘fear of missing out’, ‘phubbing’ and anxiety is found significant and shows presence of partial mediation. The study offers significant theoretical and practical implications. It is significant for the service providers and social media platforms to advance interfaces with minimum fatigue for the users and offers information support to the users to reduce stress caused by information load.     

数字经济时代会计变革及对策

随着数字经济时代的来临，以人工智能技术为代表的现代信息技术越来越多地应用到会计工作中，会计工作将进入数字会计时代，向共享会计、管理会计、智能会计发展。为了适应数字经济带来的变化，会计机构要成为企业的“数据中心”，发挥管理和服务职能。会计人员要积极学习现代信息技术和管理知识，实现由核算型向管理型转型。     

实现2035年发展目标的潜在增长率*

党的十九届五中全会提出了到2035年人均GDP达到中等发达国家水平的远景目标，因此测算和回答能否和如何如期实现该目标，对于我国实现第二个百年奋斗目标和坚持“四个自信”具有重要的意义。为此，本文根据跨越和陷入“中等收入陷阱”经济体的发展经验，对2021—2035年我国潜在增长率变化进行了测算。一是参照跨越和陷入“中等收入陷阱”经济体在我国相同发展阶段时各主要生产要素的变化，模拟设定我国未来各主要生产要素的增长率；二是通过运用附加人力资本的增长核算模型测算基准、乐观和悲观三种不同情境下未来我国经济的潜在增长率，验证我国2035年发展目标实现的可能性；三是依据主要要素对潜在增长率的贡献度，提出我国如期实现2035年发展目标的相应政策建议。     

Deep learning for modeling the collection rate for third-party buyers

This study evaluates a wide range of machine learning techniques such as deep learning, boosting, and support vector regression to predict the collection rate of more than 65,000 defaulted consumer credits from the telecommunications sector that were bought by a German third-party company. Weighted performance measures were defined based on the value of exposure at default for comparing collection rate models. The approach proposed in this paper is useful for a third-party company in managing the risk of a portfolio of defaulted credit that it purchases. The main finding is that one of the machine learning models we investigate, the deep learning model, performs significantly better out-of-sample than all other methods that can be used by an acquirer of defaulted credits based on weighted-performance measures. By using unweighted performance measures, deep learning and boosting perform similarly. Moreover, we find that using a training set with a larger proportion of the dataset does not improve prediction accuracy significantly when deep learning is used. The general conclusion is that deep learning is a potentially performance-enhancing tool for credit risk management.     

Determinants of China's bilateral trade balance in global value chains

This paper identifies the determinants of China's bilateral trade balance using a new measure based on international input–output data, the so-called ‘trade in value-added’ (TiVA), which can prevent double counting in the estimation of bilateral trade balance. Our results show that using a measure based on gross exports, rather than TiVA, causes relatively large overestimation of the impact of the RMB exchange rate on China's bilateral trade balance. This overestimation is mainly because that the increasing production of exports may require increasing intermediate imports as a consequence of international fragmentation of production in global value chains. In addition, our results also show that the impact of FDI inflows on China's bilateral trade balances depends on the position and role of China and its trading partners in GVCs.     

信息传播培养理论视域下的农户亲环境行为研究——对甘肃省19个县（区）542农户的调研分析

大众传播媒介及农业信息服务网络通过环保信息传播可在潜移默化中培养农户的亲环境价值观，进而影响农户的亲环境行为。基于信息传播培养理论，整合计划行为理论和“信念—价值—规范”理论构建亲环境行为理论模型，并采用甘肃省19个县（区）542户样本农户的调研数据进行验证，结果显示：环保信息的有效传播可以潜移默化地强化农户的亲环境价值观，农户的亲环境价值观、行为态度、主观规范、知觉行为控制及责任归属均对其亲环境行为有显著的正向预测作用，农户经营规模和专业化水平对其亲环境行为也有显著正向影响。应提高农户生产经营的规模化和专业化程度，加强对农户亲环境价值观及主体责任认知、亲环境行为知识和技能等方面的教育和培训，并充分发挥农村干部、党员、能人等的带头示范作用，以有效促进农户亲环境行为。     

基于GIS和RS的蓄滞洪区和谐发展的技术路线

应用遥感与地理信息系统技术构建基于GIS模型的蓄滞洪区空间数据库,对蓄滞洪区内的基础地理数据进行存储、管理,并对空间数据进行可视化和空间分析等操作;运用RS技术对蓄滞洪区内的土地利用、生态环境变化等情况进行动态监测,建立蓄滞洪区发展指标体系;探求蓄滞洪区的和谐发展模式,为蓄滞洪区的可持续发展提供科学依据。     

Herding behaviour and the declining value relevance of accounting information: evidence from an emerging stock market

This article sheds light on the underlying mechanisms behind the changes in the value relevance of accounting information in the Karachi Stock Exchange (KSE) during the 1999–2010 period. We find that neither changes in earnings quality nor the earnings lack of timeliness hypothesis can explain the decline in the value relevance of accounting information in the KSE. Based on the stylized facts associated with the growth of the KSE and the broader economics literature, we argue that the reduction in the explanatory power of accounting information vis-à-vis stock returns was caused by herding behaviour. Empirical estimates from state-space model of herding behaviour confirm the existence of herding, and we find that the value relevance of accounting information is significantly lower in periods characterized by herding behaviour. This article is also amongst the first attempts to empirically demonstrate that an expansionary monetary policy and increases in foreign portfolio investment lead to increased levels of herding.     

中国土地信息学30年发展研究

研究目的:明确土地信息学核心研究内容和学科地位,系统总结1980—2017年中国土地信息学研究的重要进展,划分土地信息学发展的主要阶段及各个阶段重要成果,指出土地信息学未来研究的方向和重点。研究方法:理论归纳法和文献计量法。研究结果:土地信息学是以权籍为核心、土地信息为对象,研究土地信息获取、分析、处理、存储与表达的理论、方法与技术的一门学科,服务于土地调查、评价、规划、利用、整治和保护等信息共享与决策支持。中国土地信息学发展可划分为起步阶段(1980—1995年)、关键技术应用阶段(1996—2006年)与稳步加速发展阶段(2007—2017年)三个阶段。研究结论:未来土地信息学应树立大权籍观,围绕权籍信息采集、管理、分析、表达、安全、标准等问题,研究快速、高效、精准的多元土地信息获取技术;研究土地信息的标准化、安全组织、数据交换和共享管理机制和技术;开展土地信息数据的深度挖掘分析、综合表达、集成应用技术,以及大数据、云计算、人工智能在土地信息学中的应用技术等。