Leadership mindsets: Why new managers fail and what to do about it

It is not a secret that many leadership development programs are not producing intended results, and the majority of first-time managers are ineffective. Even though organizations prioritize leadership development, most companies recognize that their programs need improvement in selecting and developing first-time managers. Perhaps it is time to reconsider the assumptions that these programs are based on. First, while organizations tend to promote high-performing individual contributors, the mindsets of an effective individual contributor do not translate to effective leadership mindsets. Second, leadership development programs generally assume that new managers can change behavior by focusing on skill development. These programs fail to identify, name, and address the underlying mindsets that influence individual action. In this article, I highlight research on leadership and leadership mindsets that can replace the flawed assumptions of underperforming leadership selection and training programs. Building on leadership mindset research, I make recommendations to help organizations better select and train new managers.     

南方丘陵区新增耕地质量空间特征研究*——以江西省宜春市为例

［目的］粮食安全的根本是在耕地，关键在于耕地质量。目前新增耕地主要源于土地开发项目、城乡建设用地增减挂钩土地复垦项目等，这些新增耕地需要对其开展耕地质量等别评定工作，了解新增耕地的质量状况，分析其空间特征，这对落实国家耕地保护制度、开展农村土地整治工作等具有重要作用。［方法］文章以南方典型丘陵区域——江西省宜春市作为研究区域，在新增耕地质量评价的基础上，运用地统计学、景观生态学、Arcgis空间分析技术和典型相关分析方法，研究宜春市新增耕地质量的空间特征，掌握耕地质量等别的分布规律，了解耕地质量的影响因素，为制定合理的耕地资源利用与保护政策提供依据。［结果］（1）Moran′s I值结果表明宜春市2014年新增耕地利用质量在空间分布上的空间自相关性最强，而耕地自然质量空间自相关性最弱。（2）景观破碎度指数结果表明优、高等别的新增耕地质量破碎度大于中、低等别的； 多样性指数结果表明新增耕地质量多样性指数比较大； 优势度指数结果表明新增耕地质量等别优势度指数比较小，与多样性指数结果相呼应； 均匀度指数结果表明，新增耕地质量等别均匀度指数相差不大，新增耕地质量等别比较均匀。（3）质心结果表明2013—2014年间宜春市新增耕地质量的格局整体上是向西南方向变化。［结论］宜春市新增耕地质量不高； 新增耕地的利用水平差异性较小，自然本底状况差异较大； 新增耕地质量等别类型多，各质量等别类型耕地均有增加，耕地质量参差不齐，较高等地的新增耕地相对低等地而言更破碎化； 新增耕地的开发格局向着西南方向移动； 该研究为南方丘陵区的新增耕地保护提供了一定的参考依据。     

绿色物流视角下生活垃圾回收处理研究文献综述

近些年来,我国众多城市都出现了"垃圾围城"的现象,垃圾回收处理也成为了社会广泛关注的热点,但是众多学者对相关理论的研究成果并没有被系统性的总结。文章将在绿色物流视角下,对生活垃圾回收处理的相关研究进行全面梳理,从居民垃圾分类意识、垃圾回收处理服务网络构建、垃圾回收站点及中转站的选址等三个方面进行综述,最后进行述评和研究展望。     

基于模糊多属性群决策的维护方式选择研究

维护方式选择是维护管理中的重要工作之一,合理的维护方式既能达到保障设备的稳定运行,又能同时兼顾其它各个方面的要求。由于对维护方式的评价涉及多个部门、人员和属性,有些指标只是一个模糊的概念,因而采用模糊多属性群决策的方法对维护方式进行优先抉择。本文结合A公司的设备维护方式选择问题,尝试使用模糊多属性群决策折衷算法求解最佳的维护方式。     

市域(郊)铁路车辆选型方案探讨

随着城镇化进程的加快和城市经济辐射能力的增强,以特大城市中心城为核心的都市圈逐渐形成,都市圈内的经济联系更加紧密,都市圈核心区与外围的出行需求迅速增长,市域(郊)铁路的概念被引进,选择符合市域(郊)铁路特点的车辆类型是设计的重点。     

险资股权投资的结构性改革研究*——基于险资投资的倒U型效应分析

保险资金作为重要的机构投资者能否发挥促进公司绩效提升的作用在已有研究和监管政策制定上都存在较大争议。本文以2005-2017年A股上市公司为研究样本，发现险资持股比例对上市公司绩效以及估值影响存在显著的倒U型曲线效应，相应机制研究表明险资持股通过显著影响两类代理成本的渠道发挥治理作用。在适度持股比例以下，险资增持能够降低被投资公司管理费用率和其他应收款占比，并提高资产周转率，从而降低两类代理成本；持股超过一定比例反而造成两类代理成本上升。险资持股比例变化对保险机构调研次数的影响则从公司治理参与角度印证了以上结论。对倒U型曲线效应的深入分析既有助于深化对机构投资者影响公司绩效的多重效应和机制的认识，同时为在金融机构层面落实金融供给侧结构性改革、增强险资服务实体经济能力提供参考。     

Online adaptive lasso estimation in vector autoregressive models for high dimensional wind power forecasting

Wind power forecasts with lead times of up to a few hours are essential to the optimal and economical operation of power systems and markets. Vector autoregression (VAR) is a framework that has been shown to be well suited to predicting for several wind farms simultaneously by considering the spatio-temporal dependencies in their time series. Lasso penalisation yields sparse models and can avoid overfitting the large numbers of coefficients in higher dimensional settings. However, estimation in VAR models usually does not account for changes in the spatio-temporal wind power dynamics that are related to factors such as seasons or wind farm setup changes, for example. This paper tackles this problem by proposing a time-adaptive lasso estimator and an efficient coordinate descent algorithm for updating the VAR model parameters recursively online. The approach shows good abilities to track changes in the multivariate time series dynamics on simulated data. Furthermore, in two case studies it shows clearly better predictive performances than the non-adaptive lasso VAR and univariate autoregression.     

Are You a Chocolate Lover? An Investigation of the Repurchase Behavior of Chocolate Consumers

This study aimed to understand the factors affecting repurchase behavior of chocolate brands and, consequently, customer retention and acquisition. The study adopted a qualitative, inductive approach using in-depth interviews with 31 Australian consumers. The factors identified in the extant literature as antecedents of customers’ repurchase intention in the chocolate industry, including brand recognition, sales promotion, product price value, variety, taste, texture, size, packaging, and customer satisfaction, were confirmed. The results also indicated that functional value, product selection value, self-gratification value, socialization value, and transactional value were also considered during the consumer decision-making process. Implications for practitioners are provided.     

Classification of intraday S&P500 returns with a Random Forest

Stock markets can be interpreted to a certain extent as prediction markets, since they can incorporate and represent the different opinions of investors who disagree on the implications of the available information on past and expected events and trade on their beliefs in order to achieve profits. Many forecast models have been developed for predicting the future state of stock markets, with the aim of using this knowledge in a trading strategy. This paper interprets the classification of the S&P500 open-to-close returns as a four-class problem. We compare four trading strategies based on a random forest classifier to a buy-and-hold strategy. The results show that predicting the classes with higher absolute returns, ‘strong positive’ and ‘strong negative’, contributed the most to the trading strategies on average. This finding can help shed light on the way in which using additional event outcomes for the classification beyond a simple upward or downward movement can potentially improve a trading strategy.