团队科学创造力的提升需重视团队成就目标导向——被调节的中介效应

基于创造力成分等多维理论，构建以团队反馈寻求行为为中介变量，团队凝聚力为调节变量的被调节的中介效应模型，以期深入解释创新团队成就目标导向如何影响其团队科学创造力。基于129个理工科大学生科技创新团队数据，研究结果表明，团队学习目标导向和团队表现目标导向分别与团队科学创造力有显著的正向和负向关系；团队反馈寻求行为在团队成就目标导向与团队科学创造力间起部分中介作用；团队凝聚力负向调节团队反馈寻求行为与团队科学创造力间的关系，并弱化了团队成就目标导向通过团队反馈寻求行为对团队科学创造力的间接影响。结论对提高科技创新团队科学创造力有一定指导价值。     

基于AHP-TOPSIS模型的京津冀家政服务人力资源供给质量评价研究

依托已有的研究成果构建了家政服务人力资源供给质量评价指标体系,利用AHP-TOPSIS模型对京津冀家政服务人力资源供给质量进行了评价和排名,并使用障碍度模型分析了员工制、准员工制、培训学校、中介制四种类型家政机构人力资源供给质量的关键制约因素,在此基础上,给出了不同类型家政机构人力资源供给质量改善的针对性建议,为家政服务人力资源供给质量的改善提供参考依据。     

Are you really doing good things in your boss's eyes? Interactive effects of employee innovative work behavior and leader–member exchange on supervisory performance ratings

Organizations increasingly depend on employee efforts to innovate. However, the quality of relationships between leaders and employees may affect the recognition that employees receive for their innovative work behaviors. Drawing from a social cognition perspective, we tested a model in which leader–member exchange (LMX) moderates the impact of employee innovative work behavior on supervisory ratings of employee performance. Results from two multisource studies combining self, colleague, and supervisor ratings consistently showed that employees receive more favorable performance ratings by engaging in innovative work behavior when they have high‐quality LMX relationships. Moreover, we found that this interactive relationship was mediated by leader perceptions of innovative employee efforts, providing support for a moderated mediation model. Implications for the literatures on performance appraisal, LMX, and innovation are discussed.     

Close relationship with the supervisor may impede employee creativity by suppressing vertical task conflict

Leader‐member exchange as a form of supportive leadership is expected to foster employee creativity. However, empirical evidence suggested this relationship is complex. This study attempts to address this complexity by proposing and testing a curvilinear mechanism, which attenuates the overall positive effect of LMX on creativity by transmitting a curvilinear indirect effect via vertical task conflict. Results drawn from a sample of 276 supervisor–subordinate dyads provided support for the hypothesized curvilinear indirect effect. Specifically, LMX was found to negatively influence employee creativity by suppressing vertical task conflict for subordinates in high‐quality LMX relationships, while the indirect effect was not significant for subordinates in low‐quality LMX relationships.     

The Moderating Effects of Status-Consumption Motive and Age in the Relationship between CSR Advertising Appeal Type and Purchase Intentions

The primary purpose of this study was to examine factors that influence the effectiveness of benefit appeal types (i.e., help-other vs. help-self) in Corporate Social Responsibility advertising. To that end, we designed and administered a between-subjects experiment where participants viewed one of the two CSR advertisements crafted with help-self and help-other benefit appeals. Results provided evidence supporting the moderating effects of status-consumption motives and age on purchasing intentions. Additional analysis suggested consumers younger than 48 years old were more likely to be persuaded by a help-other ad appeal when they didn't have strong desires for status consumption. Results were discussed in light of the self-concept theory and value-expressive framework in CSR advertising.     

自来水供应系统水质风险耦合致因分析

以城市自来水水质事故致因为研究视角,首先识别供水水质风险因素,并从单、双及多因素角度分析供水水质风险因素间的耦合关系,再借助N-K模型对2008—2017年全国所发生的362起城市重大供水水质风险耦合度进行度量。结果表明:城市自来水供应动态系统中,水质风险率随着参与耦合的风险因素的增多而增加;管理因素风险是水质风险的内因,风险管控是规避水质风险的关键;环境因素风险对水质事故的发生起推动作用。     

The influencing factors of satisfaction and lending intention in online lending investment: an empirical study based on the Chinese market

This paper develops a platform‐based influencing factors model which considers value perception, risk prevention measure, non‐default experience, trust and incentive gap, to better examine the impact of platforms on investors’ satisfaction and lending intention based on the Chinese market. The results reveal that the first four factors positively influence the satisfaction of the investors, while the incentive gap has a negative impact, and there is a positive association between investors’ satisfaction and lending intention. Some specific features of China’s online lending market are identified, which provides valuable insights for online lending platforms and the government.     

Crowdsourcing-based semantic relation recognition for natural language questions over RDF data

ABSTRACT

Natural language query systems over RDF data need to rely on the semantic relations in query. First, we propose the new crowdsourcing model that used to produce semantic relations dataset. The model not only inherits completeness of the iterative model and accuracy of the parallel model, but also saves human resources. Second, we mine the rules of semantic relation recognition from the correlations between dependency structures and semantic relations. Third, we propose an algorithm of semantic relation recognition for natural language query over RDF data, and experiments demonstrate that it can recognize more semantic relations than existing methods.     

Why will Trump lose the trade war?

ABSTRACT

The escalating U.S.–China trade conflicts have increasingly shadowed the outlook of the world economy. The Trump administration aims to achieve its strategic goals including reducing current account deficits, promoting the U.S. manufacturing sector, and curbing Chinese high-tech industries by waging the trade war against China. This paper argues that the current account deficits and the declining manufacturing sector in the U.S. are mainly driven by its internal structural factors, such as low saving rates, high labor costs, and rising service sector, rather than by the import competition from China. Moreover, the trade war further deteriorates the U.S. current account deficits and erode its comparative advantage, and it forces China to invest more in technological innovation and human capital, and thus promote its progress in high-tech industries. Thus, the U.S. will not be able to achieve its strategical goals and eventually lose the trade war.     

基于冠层光谱和BP神经网络的水稻叶片氮素浓度估算模型

[目的]快速、准确地诊断水稻叶片氮素营养状况,为水稻氮肥精准管理提供依据。[方法]以江西省农科院8种不同施肥处理的晚稻为研究对象,于主要生育期同步测定了水稻冠层光谱反射率及叶片全氮浓度(Leaf Nitrogen Concentration,LNC),系统分析了原始光谱反射率、一阶微分光谱、"三边"参数以及由350～1 350nm两两波段组合的差值(SD (Rλ1,Rλ2))、比值(SR (Rλ1,Rλ2))及归一化(ND(Rλ1,Rλ2))光谱指数与水稻LNC的相关关系,筛选出敏感参数,并以之为自变量构建了水稻LNC的传统预测模型,另外构建不同指标个数的多元线性与BP神经网络模型,并对模型进行验证。[结果](1)水稻LNC与一阶微分光谱在751nm处的相关性最高(r=0. 822);(2)"三边"参数中的红边面积SDr与LNC的相关性较高(r=0. 687);(3) 750nm附近的红边波段与近红外波段差值组合、550nm附近的绿光波段与近红外波段的比值及归一化差值组合与水稻LNC的相关性较高,以SD (R752,R751)、SR (R534,R1 350)和ND (R534,R1 349)表现最好,相关系数分别为0. 827、-0. 790和0. 788;(4)传统回归模型中以SD(R752,R751)构建的一元线性模型最佳(RC2=0. 665、RV2=0. 750、RMSEV=0. 4%、RPD=2. 034);(5)利用5个指标((R'751、SDr、SD (R752,R751)、SR (R534,R1 350)、ND (R534,R1 349))经逐步回归筛选出的2个指标SD ((R752,R751)和SR (R534,R1 350))构建预测水稻氮素的BP神经网络模型,预测效果最佳,其验证参数值分别为R2=0. 859、RMSEV=0. 302%和RPD=2. 669。[结论]基于单指标构建的传统线性模型计算过程简单但精度略低,而基于2个指标(SD (R752,R751)、SR (R534,R1 350))构建的BP神经网络模型预测精度高于该2指标构建的多元线性模型,表明在指标适合的情况下,BP神经网络对氮素具有较好的预测能力,是一种快速准确估算水稻叶片全氮浓度的方法。