浅谈价值工程在地下管线探测项目设计方案评价中的应用

价值工程作为一种将功能与成本、技术与经济相结合而进行技术经济评价的方法,又称为价值分析。本文通过结合地下管线探测项目的具体实例,探讨了在具体的施工过程中,为了在降低工程成本的同时能够有效的保证施工工程的质量和进度,如何采用价值工程的方法选择以及优化施工组织设计的方案。实践证明,在施工项目中应用价值工程的方法不仅能够完善施工方案,还能有效确保施工进度并且能够有效提高利润,最重要的是还能够很好的保证施工质量。     

交叉中值模型在物流设施选址中的应用研究

城镇化目前已经成为扩大改革开放的一项重要举措,但随着而来的就是相关基础服务设施不完善,严重影响了新城镇广大居民的生活质量和水平。因此,对于新建城镇相关物流服务设施的选址问题就变得尤为重要,交叉中值模型则是一个城镇区域内单一设施连续点选址的非常适合的方法。     

视频业务识别方法综述

视频用户体验的质量要求给网络传输带来了巨大挑战，未来的虚拟现实/增强现实(Virtual Reality/Augmented Reality，VR/AR) 视频业务则对交互时延提出了更高要求。视频业务识别是网络运营商及视频业务提供商对视频进行优先网络资源分配和自适应速率控制的基本前提。综述了业务识别领域的一般研究方法及其对视频业务的具体应用。首先，总结了每种业务识别方法的工作原理，对比了这些方法应用于视频业务时的优缺点及在准确率和召回率指标上的识别性能;然后，特别介绍了可以提升识别准确率和计算性能的特征选择算法;最后，阐述并分析了高吞吐量网络分类速度不够、无成熟视频业务识别平台和样本分布不均衡等视频业务识别面临的挑战，并针对现有业务识别方法存在的问题，给出了引入移动边缘计算、基于端口的方法串联其他识别方法等可能的解决方案。     

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.     

Early Experience and Later Outcomes of Education: Schooling Transition Evidence from Indonesia

This paper investigates the effect of early school experience on later educational attainment. Using the Indonesia Family Life Survey (IFLS), we find that students who repeat a grade at primary school are less likely to progress to junior high school. We also find that grade retention is associated with lower rates of transition from junior high school to senior high school. The relationship persists across years and samples. Meanwhile, the age of students when starting school and the hours they spend there have limited effects on whether they continue their schooling. We also observe that the effects of parental education and household income on the transition of students from primary school to junior high school are weakening. Given the long-term impact of grade retention, policymakers should be cautious when recommending it for underachieving children and should look for alternatives.     

宗地规模、城市类型与土地出让溢价——基于70个大中城市住宅用地出让数据的实证分析

研究目的:确定住宅用地出让溢价率水平与宗地规模之间的关系,比较不同规模和区位城市中这一关系的差异。研究方法:理论分析,面板数据分析。研究结果:总体上宗地规模对土地溢价率的影响呈现"倒U"型变化关系,不同规模和区位城市中这一关系有差异。人口介于500万～1 000万之间的特大城市中土地溢价水平受宗地规模的影响较为强烈,东部和中部城市中宗地规模大小对土地溢价水平影响显著,西部城市不显著。研究结论:地方政府在总量既定条件下调整宗地投放规模可在一定程度上调控土地溢价率。     

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.     

Making the next move: When does the newness of experience matter in overseas sequential entries of multinational companies?

Traditional internationalization models suggest multinational companies (MNCs) can exploit their accumulative experience to facilitate their sequential entries. However, experience may depreciate over time. Thus, obtaining benefits from prior experience for MNCs is based on two critical premises, i.e., interpreting and applying experience correctly. We argue that there is a need to study the newness dimension of experiential learning. In doing so, we aim to explore to what extent the newness of experience matters in overseas sequential entries for MNCs. Moreover, we expect that the benefits from recent experience in guiding sequential entries are contingent on the extent of context similarity between the most recent entry location and sequential entry location and the outcome expectancy of focal entry. With a sample of 112 Chinese listed firms and 410 observations during the period of 2000–2012, we find that else being equal, the newness of experience of MNCs is positively associated with sequential entry and such a relationship is positively moderated both by context similarity in institutional environment and the outcome expectancy of the focal entry. We also compare the effects of the newness of different types of experience and find that the newness of the most recent experience has a larger influence on sequential entry than location-specific experience and general experience.     

Optimal contracting with altruism and reciprocity

Motivated by the recent experimental evidence on altruistic behavior, we study a simple principal–agent model where each player cares about other players' utility, and may reciprocate their attitude towards him. We show that, relative to the selfish benchmark, efficiency improves when players are altruistic. Nevertheless, in contrast to what may be expected, an increase in the degree of the agent's altruism as well as a more reciprocal behavior by players has ambiguous effects on efficiency. We also consider the effects of the presence of spiteful players and discuss how monetary transfers between players depend on their degrees of altruism and spitefulness.