成渝城市群与珠三角城市群创新潜力比较及影响因素分析

城市群区域创新一体化对促进区域内部资源优化整合,带动周边城市创新发展具有重大意义。使用随机前沿知识生产模型研究了成渝城市群及珠三角城市群创新潜力,并采用一步法的创新非效率模型分析了影响创新潜力的主要因素。结果表明,随着创新阻力的减少,成渝城市群及珠三角城市群的创新效率在不断提升,且差距逐渐缩小;相比于珠三角城市群,成渝城市群拥有更大的创新潜力。同时,城市群内部各城市之间创新效率差异明显。为进一步提高各城市群的创新效率,应进一步转变经济发展方式,扩大开放,加强政府对创新的扶持力度,优化创新环境,提高工业集聚水平。     

宁波外商直接投资的业绩指数和潜力指数分析

随着经济全球一体化的推进,外商直接投资(FDI)对开放性区域经济增长的贡献日益增大。本文首先以外商直接投资业绩指数为依据,对宁波市利用外商直接投资进行纵向的时序分析,然后根据长三角16个城市2003年的外商直接投资业绩指数与潜力指数排序,通过横向的比较,分析当前宁波市在利用外资方面的优势与不足。对宁波市利用外商直接投资的业绩与未来吸引外资的潜力进行了评价。     

中国潜在产出与产出缺口的估算

本文在分析比较了潜在产出的三种估算方法的基础上 ,估算出我国1 978— 2 0 0 2年间的潜在产出、产出缺口和潜在增长率。结果表明 :(1 ) 1 978— 2 0 0 2年间我国的产出缺口出现了波动水平正负交替的古典周期情形 ;(2 ) 1 995年以前 ,产出缺口波动比较剧烈而且频繁 ,1 996年特别是 1 999年以后 ,产出缺口变化较为平缓 ;(3 )从 1 999年开始 ,我国产出缺口扩大的势头明显趋缓 ,但在 2 0 0 2年出现了一些反转迹象 ,这表明 1 998年开始实施的积极财政政策在遏制经济下滑、治理经济衰退方面起到了重要作用 ;(4)根据以消除趋势法和生产函数法估算的潜在产出 ,我们可以推断 1 978— 2 0 0 2年间的平均潜在产出增长率     

关联方交易会计规范的不足及完善

我国关联方交易会计规范存在的不足主要有:(1)对关联方关系范围的界定过于狭窄,完全忽视了隐性的关联方关系;(2)对关联方交易性质的界定有失偏颇,过于强调关联方交易的危害;(3)对关联方交易具体形式的变化估计不足,会计规范无法达到预期效果。我们应结合关联方交易发展的新趋势,从完善关联方交易立法、制定关联方交易准则、完善监管规范体系和强化内部约束机制等方面来规范我国公司的关联方交易行为。     

人工智能潜在替代风险与员工职业能力发展:基于员工不安全感视角

随着智能科技的蓬勃发展,"人工智能+"在有助于生产和生活的同时,也为员工的职业发展带来了挑战。本文采用机器学习算法计算我国各类职业潜在替代风险,在此基础上深入探讨了潜在替代风险对员工不安全感与职业能力发展的影响。基于13158条职业数据和808份调查问卷的分析,研究发现:我国职业面临着较强的人工智能潜在替代问题的威胁,潜在替代风险高中低的比例分别是52.80%、25.72%和21.48%;潜在替代风险最低的职业大类是企业、事业单位负责人,最高的是生产、运输设备操作人员及有关人员。进一步地,人工智能潜在替代风险在质量性不安全感与职业能力发展间起负向调节作用,当潜在替代风险高时,质量性不安全感对职业能力发展的正向影响作用更小,当潜在替代风险低时,质量性不安全感对职业能力发展的正向影响作用更大。人工智能潜在替代风险对数量性不安全感与职业能力发展的U型关系起正向调节作用,当潜在替代风险高时,数量性不安全感对职业能力发展的U型效应更强,当人工智能潜在替代风险低时,员工数量性不安全感对职业能力发展的U型效应更低。本研究丰富了人工智能领域与职业能力发展的实证研究,为新时代人才培养和技能转型提供建议。     

A dissection of Indian growth using a DSGE filter

In order to build a strong and sustainable recovery post the COVID-19 pandemic, we need to draw important observations from the growth experience of the past. In this context, this paper uses a dynamic stochastic general equilibrium (DSGE) model that takes into account persistent growth rate shocks to decompose the Indian GDP into potential output and output gap. Apart from analysing the trajectory of potential output-output gap, it also examines their underlying drivers. The results suggest that a combined deceleration in neutral and investment-specific technology growth post 2016, brought down the potential growth to around 6 per cent in 2020Q1. The output gap also witnessed a persistent decline since 2018Q1, primarily due to weak demand and a rise in investment adjustment costs reflecting heightened stress in the investment and financial sectors. A forecasting exercise is also undertaken which shows that the estimates of output gap from the model possess competing inflation forecasting ability compared to HP filtered output gap.     

Detection of potential customers’ empathy behavior towards customers' reviews

The aim of the current study is to identify potential customers' empathy behavior and their behavioral reactions based on appraisal and stimulus–organism–response (SOR) theories to customers' reviews of financial services firms using lexicon-based unsupervised learning techniques. After filtering, we obtained 30263 reviews from the Yelp dataset of financial service companies. We examined the connections between several sorts of emotional dimensions and different types of behavioral reactions of potential consumers using lexicon-based unsupervised machine learning methods. Our findings show that the various types of customer sentiment have a significant impact on potential customers' emotional experiences on social media platforms, prompting them to behave differently. Furthermore, potential consumers' reactions to the customers' reviews varied according to their seven emotional aspects. The study is the first to examine the impact of potential customers' empathetic behavioral reactions on customers' evaluations using lexicon-based unsupervised learning techniques.