战略与复杂双重维度下商业生态系统形成机理研究

基于战略和复杂双重维度，剖析阿里巴巴商业生态系统形成逻辑。结果发现：较强的战略控制力有利于强化平台商业模式，催生跨行业多样化平台，继而推进生态内信息化不断深入发展；随后，商业生态系统积蓄丰富的共享数据资源，打开资源交易和创造边界，提升生态主体能力的同时重塑生态系统属性；有着更强复杂应配力的生态主体不断探索商业模式创新，生态内外的创新扩散催化商业生态系统竞争，进一步强化复杂应配力。在核心企业战略控制力和生态主体复杂应配力的双重作用下，商业生态系统呈现前生态状态、生态内卷、生态扩散和生态共生4种不同状态。     

刑事涉财产执行中的案外人权益救济——以案外人权益救济程序的当事人构造为视角

刑事涉财产执行程序因采取移送执行模式而被误认为不存在申请执行人，使得刑事涉财产执行程序及其衍生的案外人权益救济程序过分依赖执行法院的职权主义。在刑事附带民事诉讼裁判、追缴或责令退赔违法所得并返还被害人判项、责令被免予刑事处罚的被告人赔偿被害人损失判项的执行程序中，案外人权益救济程序原则上应以被害人为申请执行人，并参照适用民事强制执行程序中的案外人权益救济制度。其他刑事涉财产执行程序应以检察机关为申请执行人。除非出现被执行人逃避执行或者案外人对执行标的提出排除执行请求等特殊情形，作为申请执行人的检察机关通常无须现实参加执行程序。     

Debt Overhang and Deleveraging in the US Household Sector: Gauging the Impact on Consumption

Using a novel data set for the U.S. states, this paper examines whether household debt and the protracted debt deleveraging help explain the dismal performance of U.S. consumption since 2007 in the aftermath of the housing bubble. By separating the concepts of deleveraging and debt overhang—a flow and a stock effect—we find that excessive indebtedness exerted a meaningful drag on consumption over and beyond wealth and income effects. The overall effect, however, is modest—‐around one sixth of the slowdown in consumption between 2000–06 and 2007–12—and mostly driven by states with particularly large imbalances in their household sector. This might be indicative of non‐linearities, whereby indebtedness begins to bite only when misalignments from sustainable debt dynamics become excessive.     

Employee workplace spirituality and pro-environmental behavior in the hotel industry

Pro-environmental behaviors in the workplace are less investigated than those in the public and private spheres. With this in mind, and through the values framework of workplace spirituality (WPS), synthesizing the theories of connectedness and organizational citizenship, the current study proposed a theoretical model to gauge the influence of WPS, a relatively new area of inquiry in organizational research and a neglected field in tourism and hospitality, on hotel employees’ organizational citizenship behavior for the environment (OCBE). In this framework, the emerging concept of connectedness to nature (CNS) – a strong cognitive and affective predictor of pro-environmental behavior – was depicted as a mediator, and the construct of environmental awareness (EA) was deemed a moderator. The intended model received support through empirical testing, and results confirmed that WPS is significantly associated with employees’ OCBE, and CNS indirectly affects the relationship between WPS and OCBE, while EA functions as a booster. The theoretical and practical implications of the study were discussed, and a series of contributory managerial implications were described accordingly.     

面源污染视角下江西省耕地利用效率研究

[目的]在面源污染视角下考察耕地利用效率,可以为推动耕地可持续利用提供理论和参考依据。[方法]文章基于2000—2014年我国13个粮食主产省(区)耕地投入产出的面板数据,运用SBM方向性距离函数将耕地面源污染因素纳入到传统的效率分析框架,从省际比较的维度对江西省耕地利用效率进行了测度与分析。[结果]考虑面源污染因素对耕地利用效率测算产生了一定的影响;江西省耕地利用效率值呈现阶段性特征,耕地利用效率排名比较稳定,近年来排名有上升趋势;江西省耕地利用绩效一般,且与最佳实践者存在较大的差距。[结论]忽视面源污染因素的耕地利用效率评估是失真和不符合实际的,宜将面源污染因素纳入到耕地利用效率的测度框架,以此来更科学地量化评估耕地利用绩效;设计和完善相关政策,以有效控制耕地面源污染;加强与先进省(区)的交流与合作,学习其农业可持续耕作技术与管理经验,进一步推动江西省耕地产出与资源、环境协调发展。     

我国大麦价格波动特征及其影响因素分析

[目的]大麦价格剧烈波动会直接影响大麦种植户的生产积极性和大麦产业的平稳发展,研究大麦价格波动特征及其影响因素,有助于提升大麦产业链相关主体识别和应对市场风险的能力,促进大麦产业的健康发展。[方法]文章先采用HP滤波法和ARCH类模型分析了2011年4月至2017年2月我国大麦价格波动特征,然后采用脉冲响应函数分析了我国大麦价格波动影响因素。[结果]我国大麦价格波动存在明显的季节性和周期性,样本期内总体上呈现逐渐下降趋势;我国大麦价格具有显著的波动集聚性,我国大麦价格具有显著的不对称性;在该文选择的影响因素中,大麦进口量和国际大麦价格是影响我国大麦价格波动的主要因素。[结论]该文提出必须保障并提高国内大麦合理产能、完善大麦价格监测预警体系、加强国内大麦进口企业整合和推动大麦进口来源多元化的政策建议。     

基于遥感蒸散数据的农田灌溉水平评价和设施建设分区研究

[目的]利用遥感蒸散数据快速评价农田年度灌溉水平,及时获取基本农田建设成效,为农田灌溉设施分区建设提供参考。[方法]以黑龙江省海伦市为研究区,MOD16蒸散产品为数据源,计算有效灌溉量、灌溉需水量和作物缺水指数,分别对研究区2013年的旱地和水田灌溉水平进行评价,并将评价结果与农田水利设施作用分值图进行叠加分析,在此基础上进行基本农田灌溉设施建设分区。[结果]2013年海伦市耕地灌溉水平整体较高,区域间建设水平差别较大,可划分为4个级别。其中1级和2级灌溉水平的地块面积比例可达78.06%,地域分布上看,北部、西部、中部乡镇灌溉水平较高,东南部乡镇灌溉水平相对较低。叠加得出8种组合类型,分为设施修建型、设施提升型和设施维护型3种分区类型。[结论]研究为高标准农田建设提供了更详细的农田灌溉水平评价方法和更具差别化的农田灌溉设施建设策略。     

Do Boards of Directors Influence Corporate Sustainable Development? An Attention‐Based Analysis

Following the attention‐based view of the firm (ABV), boards of directors’ link to corporate sustainable development (CSD) could be dependent upon certain attention structures: valuation of environmental stimuli, rules of the game and the players. Studying a sample of large Australian firms, the findings indicate that the proposed attention‐directing structures do appear to be linked to CSD in a manner consistent with the ABV. Specifically, creating awareness through scanning efforts links boards to CSD. Stakeholder debate, as a boardroom rule, is also significantly associated with CSD. Furthermore, as a so‐called ‘player’ on the board, women directors have a moderating effect on the relationships between environmental scanning, stakeholder debate and CSD. The findings are discussed along with limitations and directions for future research. Copyright © 2018 John Wiley & Sons, Ltd and ERP Environment     

衡水市农户土地资源转出意愿的影响因素与行政干预

[目的]通过了解河北省衡水市农户土地转出的意愿状况,分析影响农户土地资源转出意愿的关键因素,并制定正确的战略决策,为构建农地适度规模化经营奠定理论基础,促进衡水市农民的现代化发展。[方法]文章结合调研情况,对样本区农户土地使用权流转行为进行了统计描述和分析研究,并运用Logistic模型对农户土地使用权转出意愿的影响因素进行了分析,找到了影响衡水市土地流转的关键性因素。[结果]研究表明,户主年龄、从事职业和文化程度、农户家庭非农收入以及农户家庭兼业人数等与农户土地转出意愿呈显著正相关关系,显著性数值分别为0. 018、0. 000、0. 010、0. 000、0. 028,而农户家庭农用机械数量则与农户土地转出意愿呈显著负相关关系,显著性数值为0. 033。此外农户社会保障程度和农户对政府土地流转的相关政策了解程度等因素也影响着农户土地流转的意愿。[结论]影响农户土地转出意愿的显著性因素包括家庭非农收入、户主年龄和职业;另外,户主的年龄、职业、文化程度、非农收入、家庭兼业人数和农用机械数量均是影响农户土地转出意愿的重要内容。     

Big data driven cycle time parallel prediction for production planning in wafer manufacturing

Cycle time forecasting (CTF) is one of the most crucial issues for production planning to keep high delivery reliability in semiconductor wafer fabrication systems (SWFS). This paper proposes a novel data-intensive cycle time (CT) prediction system with parallel computing to rapidly forecast the CT of wafer lots with large datasets. First, a density peak based radial basis function network (DP-RBFN) is designed to forecast the CT with the diverse and agglomerative CT data. Second, the network learning method based on a clustering technique is proposed to determine the density peak. Third, a parallel computing approach for network training is proposed in order to speed up the training process with large scaled CT data. Finally, an experiment with respect to SWFS is presented, which demonstrates that the proposed CTF system can not only speed up the training process of the model but also outperform the radial basis function network, the back-propagation-network and multivariate regression methodology based CTF methods in terms of the mean absolute deviation and standard deviation.