The antecedents of tourists’ gaming spend: does the brand prestige matter?

This study endeavors to empirically analyse the influential effect among brand prestige, service quality, casino visitor satisfaction and spend. Data from 304 tourists who had travelled to Macau and had participated in gambling activities were used and structural equation modelling and multi-group analysis were employed in hypotheses testing. The findings demonstrated that both brand prestige and perceived service quality are determinants of satisfaction and gaming spend, and that brand prestige also affects service quality positively. Furthermore, past experience moderates the service quality and visitors’ satisfaction relationship, also service quality and visitors’ gaming spend relationship.     

中国北方大规模生猪养殖技术效率研究

[目的]通过对我国北方地区大规模生猪养殖技术效率进行测度,以期发现影响其技术效率增长的主要因素,为我国现阶段生猪养殖业战略性区划调整"南猪北进"工作提供实践指导和理论支持。[方法]根据随机前沿分析方法 (SFA)基本原理,运用对数型柯布—道格拉斯生产函数及我国北方大规模生猪养殖数据构建中国北方大规模生猪养殖随机前沿分析模型,对我国北方大规模生猪养殖技术效率进行测度并据此提出相关建议。[结果]北方地区大规模生猪养殖技术效率值纵向上来看整体在不断下降,而从地域上来看内蒙古自治区和东北地区技术效率值较高,北京与西北地区技术效率值较低。[结论]内蒙古自治区与东北地区适宜作为大规模生猪养殖承载地,与国家政策具有一致性;华北地区与西北地区大规模生猪养殖技术效率测度值较低,存在较大改进空间;针对该现状提出构建经济效益与环境保护并重的规模生态生猪养殖体系。     

大豆大杂粉碎及重杂灭活工艺改造

随着国家对环保的重视,改变进口大豆大杂(豆荚、豆杆)焚烧处理的传统做法尤为重要,采用风选、粉碎等手段,区分处理轻重杂,杂质分别采用生产线高温高压和蒸汽湿热灭活法进行处理后,可充当纤维类物质掺入到成品豆粕中。根治环境污染的同时降低厂内安全风险,充分利用进口大豆秸秆类纤维物质,减少大豆损耗,以较小的投入实现经济效益和环境保护。     

应对新冠疫情冲击的货币政策国际协调*

新冠疫情冲击了世界经济增长和金融市场稳定。很多国家推出极度宽松货币政策应对危机。从经典货币政策国际协调的博弈理论来看，应对本次疫情冲击的各国货币政策协调性不足，“以邻为壑”的非合作均衡效果明显。为数不多的货币政策协调也存在执行力不足、深度与广度不够、新兴市场国家话语权低等问题。在世界经济紧密联系、货币政策溢出效应加强的背景下，为了应对疫情冲击，国际组织需要创设协议和合作剩余分配机制，寻找货币政策刺激效果和防止国际资产泡沫之间的平衡，加强政策沟通和信息共享，提高新兴市场国家话语权，建设有效的应对危机的货币政策国际协调机制。中国应在“一带一路”倡议的框架下建立长期货币政策协调机制，在现有的IMF和G20等平台上发挥发达国家与新兴市场国家之间的协调桥梁作用，通过持续开展央行间技术性合作等措施参与和推进协调进程。     

经济政策不确定性、区域经济复杂度与企业创新行为

构建包含宏观经济政策不确定性指标、区域经济复杂度和上市公司特征变量“宏观-区域-企业”的实证面板数据，在理论分析经济政策不确定性对企业创新行为作用机理的基础上，以区域经济复杂度为视角，对经济政策不确定性与企业创新行为作用机制进行再检验。研究发现：经济政策不确定性对企业创新存在正向激励综合效应，同时，区域经济复杂度不仅能够促进企业创新行为，而且能够强化经济政策不确定性对企业创新行为的影响即抑制负向作用而强化正向作用。考虑内生性，通过替换核心变量检验稳健性以保证研究结论可靠，并且，研究企业特征发现，高科技企业和非高科技企业存在差异。     

基于熵权Topsis的淮河生态经济带水资源承载力评价

[目的]评价发展规划驱动下的水资源承载力特征,为区域发展提供科学依据。[方法]以淮河生态经济带为对象,采用熵权重的Topsis评价方法,分析淮河生态经济带水资源承载力的区域差异及其影响因素。[结果] 2015年不同市县水资源承载力综合得分介于0. 305 8～0. 698 8之间,其中盐城市最高,桐柏县最低;境内江苏、安徽、河南3省的水资源承载力分别为0. 585 2、0. 478 2、0. 524 9。[结论](1)淮河生态经济带水资源承载力具有在淮河干流上、下游承载力高,但中游偏低的空间分布特征。(2)水资源系统层面,水资源总量是承载力高低的供给侧决定性因素,是水资源承载力高低的重要基础。(3)社会系统中,用水量与用水结构是提升和优化水资源承载力的调控性因素。(4)城镇化发展与人口增加是水资源承载力高低的胁迫性因素,而经济发展水平是水资源承载力调控的重要保证。     

CEO hometown identity and firm green innovation

Drawn on the upper echelons theory, this study investigates how chief executive officer (CEO) hometown identity drives firm green innovation. We propose that CEO hometown identity has a positive impact on a firm's green innovation performance. Furthermore, we explore the moderating role of managerial discretion determined by organizational and environmental factors (i.e., institutional ownership and market complexity). We propose that institutional ownership negatively moderates the positive relationship between CEO hometown identity and green innovation, but market complexity plays a positive moderating role. Using Chinese publicly listed firms from 2002 to 2016 in heavily polluting industries, our findings support these hypotheses. Our research contributes to the upper echelons theory and corporate social responsibility literature and has substantial practical implications.     

Evaluation of the green technology innovation efficiency of China's manufacturing industries: DEA window analysis with ideal window width

Data Envelopment Analysis (DEA) window analysis with ideal window width is applied to evaluate the green technology innovation efficiency of 28 manufacturing industries in China during 2006–2014. The obtained results are compared with those calculated using the traditional DEA model, and convergence analysis of the efficiency is conducted. Five years is the obtained ideal window width and DEA window analysis with ideal window produces results closer to reality for China's manufacturing industry. The overall efficiency of the green technology innovation in the manufacturing sector is low following a wave-shaped curve – first decreasing, then increasing and decreasing again, with large inter-industrial differences. There are 8 high-, 14 medium- and 6 low-efficiency industries. A convergence trend in the green technology innovation efficiency within the 28 manufacturing industries exists, implying a catch-up effect between them.