The impact of reverse logistics process coordination on third party relationship quality: A moderated mediation model for multichannel retailers in the fashion industry

Multichannel retailing is a widely adopted strategy in the fashion industry. Companies in this industry find it a source of competitive advantage to invest in reverse logistics infrastructure. However, limited empirical studies investigate the enablers of the relationship quality between the retailers and their reverse logistics service providers. This study quantifies the impact of reverse logistics process coordination between retailers and logistics service providers on relationship quality. Moreover, it tests the mediating role of reverse logistics service quality and the moderating role of conflict frequency in this relationship. Data were collected through a survey using a purposive sample of 241 retail store managers from the fashion retail industry of Pakistan. For this purpose, a self-administered questionnaire was developed using a five-point Likert Scale to gauge the responses. Conditional process analysis was used to evaluate the moderated mediation model. The findings showed a significant positive impact of reverse logistics process coordination on the relationship quality with a logistics service provider, a significant positive mediation effect of reverse logistics service quality, and a significant moderation effect of conflict frequency on the indirect relationship. However, conflict frequency, contrary to the hypothesis in the study, strengthened the indirect relationship. Furthermore, the moderation effect of conflict frequency on the direct relationship was insignificant. This study will help managers better understand the best practices leading to effective management of reverse logistics processes, particularly product returns.     

X频段高频谱纯度频率合成器设计

针对高灵敏度接收机对频率合成器的高技术指标要求，构建了一种融合了直接模拟、直接数字以及间接数字的频率合成技术方案，根据该方案，成功实现了频率合成器的工程研制。通过测试，频率合成器相位噪声达-112 dBc/Hz@5 kHz，杂散抑制优于-75 dBc，频率分辨率小于1 kHz，10 MHz跳频时间约为13 μs，满足了高灵敏度接收机对频率合成器的高技术指标要求，为高纯度频率合成器的实现提供了一条新途径。     

An explainable machine learning approach to improve take-off time predictions

Accurate aircraft trajectory predictions are necessary to compute exact traffic demand figures, which are crucial for an efficient and effective air traffic flow and capacity management. At present, the uncertainty of the take-off time is one of the major contributions to the loss of trajectory predictability. In the EUROCONTROL Maastricht Upper Area Control Centre, the predicted take-off time for each individual flight relies on the information received from the Enhanced Traffic Flow Management System. However, aircraft do not always take-off at the times reported by this system due to several factors, which effects and interactions are too complex to be expressed with hard-coded rules. Previous work proposed a machine learning model that, based on historical data, was able to predict the take-off time of individual flights from a set of input features that effectively captures some of these elements. The model demonstrated to reduce by 30% the take-off time prediction errors of the current system one hour before the time that flight is scheduled to depart from the parking position. This paper presents an extension of the model, which overcomes this look-ahead time constraint and allows to improve take-off time predictions as early as the initial flight plan is received. In addition, a subset of the original set of input features has been meticulously selected to facilitate the implementation of the solution in an operational air traffic flow and capacity management system, while minimising the loss of predictive power. Finally, the importance and interactions of the input features are thoroughly analysed with additive feature attribution methods.     

基于GM(1,1)模型的造纸业上市公司财务研究——以冠豪高新为例

财务风险是企业调整发展战略、提升管理水平的重要参考指标之一。财务风险预测模型的建立能够预测企业在中短期内的财务风险,为企业敲响警钟。以造纸业上市公司冠豪高新为例,选取近五年财务杠杆系数为风险指标,建立GM(1,1)风险预测模型,结果显示该公司短期内财务风险呈下降趋势,调查发现这主要得益于产品成本的降低以及营销策略的改变。     

黑龙江森工林区林业产业结构演变趋势及优势产业选择

采用灰色预测方法对黑龙江森工林区2018—2027年林业三次产业产值进行预测,并在此基础上利用动态偏离-份额分析方法对此阶段黑龙江森工林区的林业优势产业进行选择。结果表明:2019年黑龙江森工林区林业产业结构将演变为"三、一、二"模式;林业第一产业中的林木育种和育苗、经济林产品的种植和采集业可作为优势产业进行重点发展和管理。因此,提出优化黑龙江森工林区林业产业结构的相关建议:继续巩固发展林木育种和育苗、经济林产品的种植和采集这两个优势产业;推动加工制造业向深加工、精加工的方向转变;加强林业旅游与休闲服务业的竞争力。     

跳频信号的归一化多普勒频差最大似然估计

针对双站定位涉及的跳频信号多普勒频差估计问题，提出了归一化的频差最大似然估计算法，利用两个定位站接收到的跳频脉冲串信号，构建一个关于基准跳频频率多普勒频差的似然函数，通过网格搜索得到使似然函数最大的多普勒频差估计，既解决了跳频信号在不同跳频频率上多普勒频差不一致的问题，又充分利用在不同频率的脉冲串信号提高了多普勒频差估计精度。通过仿真对算法的性能进行了评估，结果表明，与基于子空间的算法比较，在脉冲数达到240个时，所提算法执行效率提升30%以上。     

Are REITs more resilient than non-REITs? Evidence from natural experiments

REITs draw attention from investors around the world, yet our understanding of the various risks associated with such securities is limited. Using the introduction of Arrowhead, a low-latency high-frequency trading platform, to the Tokyo Stock Exchange and the financial crisis of 2008 as natural experiments, we compare the resilience of REITs and equities in terms of liquidity and volatility. The results indicate that the introduction of Arrowhead improved the quality of the Japanese REIT market but also increased the probability of flash crashes. We also find that although the financial crisis significantly deteriorated overall equity market quality, the Japanese REIT market was resilient. Finally, using a difference-in-differences regression model, we show that the higher transparency and better price discovery of REITs, compared to non-REITS, protected them from the negative effects of the financial crisis and the introduction of Arrowhead. Overall, our analysis shows that REITs are more resilient than non-REITs.     

Market impact: a systematic study of the high frequency options market

This paper deals with a fundamental subject that has seldom been addressed in recent years, that of market impact in the options market. Our analysis is based on a proprietary database of metaorders—large orders that are split into smaller pieces before being sent to the market—on one of the main Asian markets. In line with our previous work on the equity market [Said, E., Bel Hadj Ayed, A., Husson, A. and Abergel, F., Market impact: A systematic study of limit orders. Mark. Microstruct. Liq., 2018, 3(3&4), 1850008.], we propose an algorithmic approach to identify metaorders, based on some implied volatility parameters, the at the money forward volatility and at the money forward skew. In both cases, we obtain results similar to the now well-understood equity market: Square-Root Law, Fair Pricing Condition and Market Impact Dynamics.     

基于深度学习的跳频信号识别

针对跳频信号分选存在人工提取参数特征具有复杂性的问题，提出了一种基于深度学习的识别方法。首先对跳频信号进行短时傅里叶变换，得到二维的时频矩阵；接着提取信号的轮廓特征，构造三维矩阵作等高线图，并对等高线图进行预处理；最后把预处理后的等高线图输入到卷积神经网络中进行训练、测试，进而实现分类识别。仿真结果表明，在不需要复杂的人工提取参数特征的基础上，在分选率为100〖WT《Times New Roman》〗%〖WTBZ〗时，所提方法经裁剪处理下的信噪比为-15 dB，比支持向量机和传统K-Means聚类算法都低10 dB。实测数据的算法验证表明，所提方法能够将大疆精灵4Pro、hm无人机、司马航模X8HW以及大疆悟2这四类无人机正确分类。     

一种嵌入式软件无线电频谱监测系统

为了降低研发成本，提高频谱系统的灵活性和缩短研制周期，提出了一种基于软件无线电的嵌入式频谱监测系统。首先研究了系统硬件平台组成和特点，在此基础上设计了一种灵活的软件定义系统架构；然后考虑到硬件平台自身性能的限制，重点研究了频率偏移校正、频谱扫描策略等关键技术，分别提出了基于GSM信号和温度传感器的频偏校正方法和基于相关性的扫频策略；最后通过具体实验，对系统性能进行验证与评估，结果表明所提出的频偏校正方法能够将绝对平均频偏控制在1.749×10-6以内，所设计的基于相关性的扫频策略对时变信号的频谱监测效果最好。