清代常平仓法律探析

常平仓制度在清代已经比较成熟,从修建仓廒、确定储粮数额到仓库的日常管理都有明确的法律规定。其中筹集仓粮、严惩亏空等方面的法律相对稳定,而在额定存粮数目和存粜比例等方面的法律则随着形势变化不断做出调整。清前期常平仓在平抑粮价、救济灾民方面发挥着巨大作用,清中期常平仓开始亏空且问题日益严重,后期则彻底崩溃,相关法律规定也沦为一纸空文。     

城市仓储型物流企业区位选择——以嘉里大通物流广州分公司为例

城市仓储型物流企业区位选择是一个复杂问题，是内部因素和外部因素共同作用的结果。为提高选址的科学性与实用性，需要综合考虑地理位置、自然条件、交通、基础设施等多种因素。本文以嘉里大通物流有限公司广州分公司的仓库选址为例，从宏观和微观的不同尺度，以案例分析为主线，在梳理企业发展现状的基础上，通过宏观层面的仓库定位分析和微观层次的仓库选址分析，运用加权评分法，最终确定符合企业和市场需求的最佳仓库区位，旨在为相关仓储企业选址提供参考和借鉴。     

The market for (Ir)reproducible econometrics

Context: As the volume and complexity of research have increased, the amount of time spent on Institutional Review Board (IRB) review has decreased. The complexity of research has expanded, requiring increasingly specialized knowledge to review it. Dilemma: Under the current system, increasing numbers of research studies requiring expertise in ethics, new technologies or diverse study designs place a substantial burden upon local IRBs and often result in substantial variability among their reviews. This lack of uniformity in the review process creates uneven human subjects’ protection thus undermining the intent of the Common Rule. Objectives: To outline a scenario for expert centralized IRB review via implementation of a national virtual IRB review system overseen by the Office for Human Research Protections (OHRP). Conclusions: The complicated ethical issues and science involved in much of current research warrant an expert review panel. Centralized review would enable expert review specific to the research at hand, ensure consistency in human subjects protection, reduce the burden on local IRBs, and may reduce time spent obtaining approval. A centralized virtual system would allow IRB members to remain at their institutions while providing unprecedented expert review through currently available technology, and make information regarding monitoring and adverse event reporting available online in real-time.     

仓储型物流企业的核心竞争力探析

仓储型物流企业的核心竞争力主要体现在物流战略规划及企划能力、物流运营能力、改善创新能力、技术运用能力、资源整合能力、市场营销能力和高素质人才等多个方面。仓储型物流企业要在未来的竞争中取胜,必须全面提升各方面的能力与素质。     

关于代位权行使效果归属问题的探讨

债权人代位权行使效果归属有入库原则和直接受偿两种学说。代位权是一种实体性权利,它在我国的确立有其特殊的基础,其设立的目的并不在于保护所有债权人的一般债权。本文从代位权的行使范围、比较法学、诉讼经济、行使代位权可能产生的社会效果、对债务人处分权利的限制以及债权平等多个视角对两种学说进行考量,力证直接受偿原则优于入库原则。     

基于系统动力学的配送中心仓储系统研究

配送中心仓储系统的优化目标是使库存量尽量小而又能保证不会缺货。本文选用系统动力学方法时配送中心仓储系统进行深入分析，在进行系统边界分析与系统因果关系分析后，建立起配送中心面向三店铺配送的系统动力学流图与方程体系，并结合实例进行计算机仿真模拟。最后得出配送中心优化方向的相关结论——提高需求预测的准确性、减少供货延迟时间、增加库存调节时间及加强信息沟通机制。     

Ein Optimierungsansatz für ein fortlaufendes Datenqualitätsmanagement und seine praktische Anwendung bei Kundenkampagnen

Zusammenfassung  Die Verbesserung der Datenqualit?t (DQ) wird in Wissenschaft und Praxis intensiv diskutiert. Ob die ergriffenen DQ-Ma?nahmen jedoch ?konomisch überhaupt gerechtfertigt sind und wann und in welchem optimalen Umfang investiert werden soll, wird oftmals nicht analysiert. Zur Untersuchung dieser Fragestellungen entwickeln die Autoren ein Optimierungsmodell, mit dem die Umf?nge und Zeitpunkte für Investitionen in ein fortlaufendes DQ-Management ermittelt werden k?nnen. Hierdurch lassen sich vier Investitionsszenarien mit allgemeinen Handlungsempfehlungen identifizieren. So ist bspw. bei ehemalig intensiven Kundenbeziehungen, die sich inzwischen verschlechtert haben (nur wenige Gesch?ftstransaktionen), zwar über mehrere Perioden zu investieren, jedoch bei einem sich nicht ver?ndernden, geringen Transaktionsanteil, in abnehmender H?he. Daneben l?sst sich u. a. zeigen, dass der Umfang der existierenden Kundendatenmenge und nicht, wie oftmals angeführt, ein schlechtes existierendes DQ-Niveau ma?geblich für die Entscheidung ist, ob überhaupt in DQ investiert werden soll. Anhand einer Fallstudie wird abschlie?end nicht nur die praktische Anwendbarkeit des Optimierungsmodells verdeutlicht, sondern es soll zudem aufgezeigt werden, wie sich für einen konkreten Sachverhalt detaillierte Empfehlungen hinsichtlich des DQM-Einsatzes ermitteln lassen.

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A model based approach for continuous data quality management and its implementation to improve customer campaigns

Summary  The improvement of data quality (DQ) currently finds a great deal of attention in science as well as in practice. Nevertheless there are two fundamental questions that are often ignored in the analysis: i) Are the DQ measures already implemented economically reasonable? ii) When and to what extent is investing into the improvement of DQ justifiable? For an in-depth understanding considering the design of DQ management the authors develop an optimization model which determines the optimal amount and point of time for consecutive DQ investments. Hence they distinguish between four scenarios and propose corresponding action recommendations. For example, a customer relationship with declining intensity up to the present (i. e. diminishing volume of business transactions) requires DQ investments over several future business periods- and at a decreasing investment rate in cases where the transaction volume continues to go down. Additionally it can be shown that in general the amount of available client data is a crucial factor for the decision whether it is reasonable to invest into DQ at all as opposed to a low quality level — which is often claimed. A concluding case study determines the practical applicability of the proposed optimization model.

     

A Performance Metric and Goal‐Setting Procedure for Deadline‐Oriented Processes

A performance metric and goal‐setting procedure is defined for an order fulfillment operation. In this operation, order requests arrive continuously, and filled orders are shipped at a specific time each day. The metric links the continuous operation of order fulfillment to the scheduled shipment times. To prescribe goals against the metric, a performance model is developed that incorporates the motivational effect of a goal. Goal‐Setting Theory is used to establish the performance goal and to show how to match arriving orders to deadlines based on their arrival times and expected processing times. Monte Carlo simulation on data from a large distribution center is used to demonstrate that setting these two parameters in the light of motivational research yields quite different results than doing so with an intuitive method. Moreover, a motivational goal leads to better operational performance; that is, correctly setting up the metric causes more customers to receive their orders sooner.     

Class‐Based Storage with a Finite Number of Items: Using More Classes is not Always Better

Class‐based storage is widely studied in the literature and applied in practice. It divides all stored items into a number of classes according to their turnover. A class of items with higher turnover is allocated to a region closer to the warehouse depot. In the literature, it has been shown that the use of more storage classes leads to a shorter travel time for storing and retrieving items. A basic assumption in this literature is that the required storage space for all items equals their average inventory level, which is valid only if an infinite number of items can be stored in each storage region. This study revisits class‐based storage by considering each storage space to contain only a finite number of items. We develop a travel time model and an algorithm that can be used for determining the optimal number and boundaries of storage classes in warehouses. Different from the conventional research, our findings illustrate that commonly a small number of classes is optimal. In addition, we find the travel time is fairly insensitive to the number of storage classes in a wide range around the optimum. This suggests that a manager can select a near‐optimal number of storage classes in an easy way and need not be worried about the impact of storage‐class reconfigurations. We validate our findings for various cases, including different ABC‐demand curves, space‐sharing factors, number of items, storage rack shapes, discrete storage locations, and stochastic item demand.     

基于系统动力学的配送中心仓储系统研究

配送中心仓储系统的优化目标是使库存量尽量小而又能保证不会缺货。本文选用系统动力学方法时配送中心仓储系统进行深入分析，在进行系统边界分析与系统因果关系分析后，建立起配送中心面向三店铺配送的系统动力学流图与方程体系，并结合实例进行计算机仿真模拟。最后得出配送中心优化方向的相关结论——提高需求预测的准确性、减少供货延迟时间、增加库存调节时间及加强信息沟通机制。