云南省农业科技创新资源配置效率及影响因素研究

[目的]为及时了解云南省农业科技创新的最新动态,充分合理地开发云南省农业科技资源,文章对2002—2016年云南省的农业科技创新资源配置进行研究。[方法]首先分析各个单项指标15年内的变化趋势,分析其对资源配置的影响和作用。再运用DEA模型分析法,将2002—2016年的每个年份作为一个决策单元进行处理,对云南省农业科技创新资源配置效率进行分析。[结果] 2002—2016年云南省农业科技创新资源配置的综合效率为0. 984,并且呈现出不稳定的波动,在2004和2009—2012年出现了配置效率降低的情况。总体来看,资源配置的综合效率大体上是接近于1的水平。处于DEA有效的年份为2002—2003年,2005—2008及2013—2016,属于规模报酬不变的阶段; 2004年属于弱DEA有效阶段,规模报酬则处于上升阶段;处于非DEA有效的有2004年、2009—2012年。[结论]云南省农业科技创新资源的配置效率整体水平处于较高的状态,综合效率值总体上接近于1。有个别年份出现了较小范围的波动,可能与总播种面积的变化有关。综合来看,云南省农业科技创新资源在技术投入、人力资源和农业资金投入逐年的增加,使资源配置效率能够保持在较高的水平,并在出现下降后迅速恢复。     

农产品直播效果影响因素分析

随着互联网技术、网络技术等与农产品深度融合,新一轮农产品销售模式孕育兴起.农产品直播销售为各行业带来巨大的商机,农产品直播已经成了农民的"新农具",各大直播平台都开展了各种直播活动.在前人研究的基础上,结合直播实践,通过因子分析法分析农产品直播效果的影响因素,以期改善农产品直播效果,促进农产品销售.     

员工企业社会责任感知影响人力资源管理效能？—基于领导行为的协同中介

通过对贵州、广东和福建3个省80家企业1148名员工进行调研,基于员工对企业社会责任、领导行为感知对人力资源管理效能带来积极影响为研究问题构建了一个中介模型。企业社会责任在组织微观层面的内涵越来越得到企业的重视,实现了员工的企业社会责任由产出需求转向投资视角,成为企业满足员工工作需要和工作资源的参照标准体系,有利于提升企业人力资源管理效能。本文研究发现:企业社会责任分别从企业经济责任、法律责任、伦理责任和自行裁量责任影响人力资源管理效能;变革型领导和交易型领导对企业社会责任和人力资源管理效能具有协同中介作用。研究结论对于企业社会责任、领导行为和人力资源管理三者匹配具有重要的理论和现实意义。     

基于CE模型的河南省耕地生态补偿额度研究

[目的]基于生态补偿利益主体的需求和支付意愿,充分考虑区域经济发展状态,测算具有弹性的生态补偿标准,确保生态补偿机制顺利运行。[方法]以河南省457份实地调查问卷为基础,采用选择实验法,建立由4个属性水平、7个选择集组成的生态价值属性集,测算受访对象生态补偿的支付意愿。[结果]城乡居民对于耕地资源景观与生态环境关注度最高,其次是耕地质量和耕地面积;农民和市民对于耕地生态价值属性满足的支付意愿存在显著差异性,农民支付意愿为2 060.55元/hm~2,市民支付意愿为3 396.15元/hm~2,两者相差近1 335.60元/hm~2,收入水平、环保意识是影响受访对象生态补偿支付意愿的最直接因素,但两者均认为耕地面积不变、耕地质量改善和耕地景观生态环境改善为最优选择。[结论]补偿额度应充分考虑相关利益主体的支付能力和意愿,将农民的支付意愿作为生态补偿下限,市民的支付意愿作为生态补偿上限,可建立具有一定弹性的生态补偿机制。     

Economic impacts of smallholder farmers’ adoption of drought-tolerant maize varieties

Drought and high temperatures are major threats to sustainable food production and consequently the livelihoods of the majority of Africans who depend on fragile agricultural systems. As a response to these threats, climate-smart agricultural technologies, such as drought-tolerant maize (DTM) varieties, have been developed and promoted on the continent. It is well-known that the adoption of improved technologies generally impacts positively on the wellbeing of adopters. Nevertheless, the magnitude of the impact of any technology or intervention is always an empirical question. Therefore, this study sought to determine the factors that influence the adoption of DTM and subsequently estimate how yield, commercialization intensity, and farm income are affected by adoption. To establish causation, we relied on observations from 200 farm households in the Northern Region of Ghana and estimated an instrumental variable regression. Consistent with findings reported in the literature, we found that DTM adoption is primarily driven by access to seed, extension service, labor availability, and location of farm households. In addition, we found that DTM adoption positively impacts on yield and commercialization intensity. The magnitude of impact is not trivial. For example, the yield of farm households increased by more than 150% (936 kg/ha) following DTM adoption. These results imply that policy-makers and development practitioners must support research and promotion of climate-smart agriculture to improve adoption and welfare indicators, such as yield and commercialization.     

Policy lessons from spatiotemporal enrollment patterns of payment for ecosystem service programs in Argentina

Payment for ecosystem services schemes (PES) are lauded as a market-based solution to curtail deforestation and restore degraded ecosystems. However, PES programs often fail to conserve sites under strong long-term deforestation pressures. Underperformance, in part, is likely due to adverse selection. Spatial adverse selection occurs when landowners are more likely to enroll parcels with low deforestation pressure than parcels with high deforestation pressure. Temporal adverse selection arises when parcels are enrolled for short time periods. In both cases, financial resources are allocated without having a sizeable impact on long-term land use change. Improving program performance to overcome these shortcomings requires understanding attributes of landowners and their parcels across large scales to identify spatial and temporal enrollment patterns that drive adverse selection. In this paper, we examine these patterns in Argentina’s PES program in Chaco forest, a global deforestation hotspot. Our study area covers 252,319 km². Results from multinomial logistic regression models showed that large parcels of enrolled land and parcels owned by absentee landowners exhibit greater evidence of spatiotemporal adverse selection than smaller parcels or parcels owned by local landowners. Furthermore, parcels managed under land use plans for conservation and restoration are more likely to be associated with adverse selection than parcels managed for financial returns such as harvest of non-timber forest products, silviculture, and silvopasture. However, prior to recommending that PES programs focus on land uses with higher potential earnings, a greater understanding is needed of the degree to which these land uses meet ecological and biodiversity goals of PES programs. We suggest that increased spatial targeting of enrollment, along with enrollment of local landowners and further incentives for land uses that support conservation and restoration, could promote long-term conservation of forest lands.     

Probabilistic wind forecasting up to three months ahead using ensemble predictions for geopotential height

We develop a method for forecasting the distribution of the daily surface wind speed at timescales from 15-days to 3-months in France. On such long-term timescales, ensemble predictions of the surface wind speed have poor performance, however, the wind speed distribution may be related to the large-scale circulation of the atmosphere, for which the ensemble forecasts have better skill. The information from the large-scale circulation, represented by the 500 hPa geopotential height, is summarized into a single index by first running a PCA and then a polynomial regression. We estimate, over 20 years of daily data, the conditional probability density of the wind speed at a specific location given the index. We then use the ECMWF seasonal forecast ensemble to predict the index for horizons from 15-days to 3-months. These predictions are plugged into the conditional density to obtain a distributional forecast of surface wind. These probabilistic forecasts remain sharper than the climatology up to 1-month forecast horizon. Using a statistical postprocessing method to recalibrate the ensemble leads to further improvement of our probabilistic forecast, which then remains calibrated and sharper than the climatology up to 3-months horizon, particularly in the north of France in winter and fall.     

The effects of slack resource of R&D professionals on firm performance: evidence from traditional manufacturing firms in an emerging economy

Abstract

As an important component of organizational human resource slack (HR slack), the slack of research-and-development (R&D) professionals has been studied by several authors. However, it remains unclear whether and how this small component of general HR slack, i.e. the slack of research-and-development professionals (RHR slack), may affect overall firm performance in an emerging economy without much R&D tradition or pro-R&D institutions. Based on two organizational theories, i.e. institutional theory and the resource-based view of the firm (RBV), we propose competing hypotheses on the relationship between RHR slack and firms’ accounting performance. We also examine whether the relationship between RHR slack and firm performance should be linear or curvilinear. Finally, we also test the relationship between RHR slack and other dimensions of firm performance. Several interesting findings have been obtained. For instance, neither the perspective based on institutional theory nor that based on RBV can fully predict all types of RHR slack-performance relationships, be these relationships linear or curvilinear.     

Can environmentally oriented CEOs and environmentally friendly suppliers boost the growth of small firms?

The core question addressed in the natural resource‐based view (NRBV) of the firm is how to develop and exploit resources beneficial for both the natural environment and firm performance. Due to the resource constraints and increased competition facing small manufacturing firms, achieving this is a challenge for such companies. Building on the NRBV and resource orchestration literatures, we examine the relationship between green purchasing capabilities (GPCs), CEO's environmental orientation (EO), and firm growth. Results from 304 Swedish small manufacturing firms indicate a significant relationship between GPC and growth, and this relationship is positively moderated by the EO of the CEO.     

医疗卫生资源、新型冠状病毒肺炎死亡率与资源优化配置

新冠肺炎疫情发生后，湖北省一直是疫情的重灾区与抗疫的焦点地区，患者死亡率远远高于全国平均水平。本文构建纳入医疗资源条件的新冠肺炎传播的SIER模型进行机制分析和模拟研究，发现改善卫生资源条件会降低疫情的死亡率。针对湖北省疫情数据，使用最小二乘方法进行实证研究后发现,无论是增加医院或者卫生系统内的床位数，还是增加医护人员数，均可显著地降低疫情死亡率。进一步通过时变效应和断点回归模型考察重大突发公共卫生事件一级响应政策效应和外援医疗团队效应，实证结果也佐证了上述推断。结合研究结论和湖北省防疫经验，本文提出先整合医院内部医疗资源，打破医院内部各科室之间分割，再整合地区内医疗卫生系统的资源，同时实施医疗系统外部资源三管齐下的医疗资源配置建议措施，以期为国内外疫情防控贡献中国智慧。