The customer consequences of returns in online retailing: An empirical analysis

Pressure continues to build on the operations management function to facilitate system and firm level benefits. In the online marketplace, one area of growing interest is that of product returns. Though commonly viewed as a cost center from an operations perspective, operations’ actions have the potential to strongly influence future customer buying behavior in several ways. Using an archival database of actual purchase and returns history provided by a moderately sized online retailer, this study examines the relationship between a customer's experience of product returns, and subsequent shopping behavior. Employing transaction cost, consumer risk, and procedural justice theories, we demonstrate that the returns management process, rather than being regarded as an afterthought to the production and deployment of goods, can significantly and positively influence repurchase behavior. Additionally, we provide evidence that certain customers should be considered for prioritization in the returns process. We suggest ways through which operations managers can take care in discharging their responsibilities in this area – to make returns processing more than simply a “necessary cost of doing business” rather, using it to their advantage in engendering repeat and increased purchase behavior.     

供应链采购与传统采购的比较分析

采购作业是企业运营管理工作中的重要一环，在采购环节所形成的成本是企业生产成本的重要组成部分，是企业降低成本的重要领域文章运用比较的方法．分析了供应链采购与传统采购的不同特点,指出供应链采购能改进与供应商的关系，减少传统采购中许多不增值的作业,是企业降低成本、增加效益的重要方法。     

考虑需求不确定的订单分配模型研究

从顾客需求不确定性出发,在考虑批量折扣的情况下,构建了一个基于成本、延迟交货数量、质量和交货提前期的具有模糊权重的多目标订单分配模型。在求解过程中,用隶属度函数表示决策者对各目标值的满意程度,用梯形模糊数来表示各指标的权重,然后将多目标规划问题转化为求全局满意度最优的单目标规划问题。最后通过一个数值算例说明了模型的求解过程。     

Planning horizons for master production scheduling

Production and operations planning in organizations quite often is a multi-level sequential process, involving aggregate planning, master production scheduling, and detailed operations planning and scheduling. To obtain good planning results, it is desirable to have a proper planning horizon for each level of planning. There have been a considerable number of studies dealing with planning horizons for aggregate planning or production smoothing problems. There are also many planning horizon studies for single-item lot sizing problems. No study has addressed the issues associated with the planning horizons for master production schedules (which is a multi-item lot sizing problem in nature), particularly with respect to the relationship to the aggregate plan.This study addresses the issue of planning horizons for companies employing a make-to-stock competitive strategy facing a seasonal demand for their products. We formulate the aggregate planning problem and the master scheduling problem as two separate mathematical programs to approximate the two-stage process that typically takes place in practice. Rolling planning horizons are used to approximate the periodic updates of the plans commonly done in practice. The models also incorporate resource requirements planning concepts to estimate loads on the critical work centers.The planning process is simulated as a single pass procedure where the results of aggregate planning are passed to the master production scheduling model once per month and the results of the master scheduling model (i.e., the portion of the master schedule actually implemented) are passed back to the aggregate planning model for the next planning session.The experimental results show that when the planner faces extreme cost structures such as high smoothing costs/high setup costs or low smoothing costs/low setup costs, the planning horizon effects are reduced to a minimum. Master schedule planning horizons need not be as long as aggregate planning horizons. Alternatively, non-extreme cost structures such as high smoothing costs/low setup costs and low smoothing costs/high setup costs should be handled with equal planning horizons for both aggregate planning and master scheduling.It is also found that the firm's cost structure has an impact on the appropriate planning horizon for both aggregate planning and master scheduling. Some cost conditions allow for smaller master schedule horizons. The best horizon choice seems to be equal planning horizons for both aggregate planning and master scheduling, even though the cost savings is slight in some cases.Finally, the proper length of the planning horizon for master scheduling is affected by the planning horizon of the aggregate plans.     

A multimodal,multicommodity, and multiperiod planning problem for coal distribution to poor families

Tackling poverty has been one of the greatest global challenges and a prerequisite to sustainable development of countries. Countries implement nationally appropriate social protection systems and measures to address poverty. This paper addresses an aid system adopted by the government in Turkey where significant amounts of coal is distributed to poor families each year. The objective of the coal aid system is to complete the delivery of coal to poor families by the start of winter. However, an analysis of the data from previous years indicates that the distribution to many families cannot be completed on time. This results from the fact that planning is done manually and by trial-and-error as there is no system that can be used for distribution planning. This paper describes the planning problem encountered and develops a mathematical model to solve it. The proposed model is a multimodal, multicommodity, and multiperiod linear programming (LP) model. The model can be used to develop and update a distribution plan as well as to answer several what-if questions with regard to capacities, time constraints, and so forth. The model is solved using CPLEX for several problem instances obtained under different scenarios using data for the year 2012. The results show that at least 9% cost savings and about 40% decrease in distribution completion time can be achieved when the model is used. We analyze scenario results qualitatively and quantitatively and provide several insights to the decision makers. As a part of quantitative analysis, we develop regression models to predict optimal costs based on several factors. Our main contribution is to provide an efficient and effective tool to handle a large-scale real-world problem. The model has also helped to prove that the organization responsible for distribution planning may move from the current planning practice to an all-encompassing top-down approach.     

供应不确定下基于Supply-hub的供应商选择和库存协同决策

针对由供应商、Supply-hub和制造商组成的三级供应链的多产品供应商选择和库存协同问题,考虑供应商存在延迟交付风险、供应数量约束,以供应链运作成本最小为目标,构建整数规划模型。分析结果表明:在一定的条件下,总存在最优的供应商选择方案和库存策略;当供应商的延迟交付概率增加,供应链期望成本上涨;当供应商供应数量无限制时,减少最优订货批量可以弱化供应不确定性增加造成的影响;当供应商选择方案不变,订货提前期增加,供应链的运作成本以及最优订货批量不变;一种零部件提前期的变化不影响其他零部件的供应商选择和库存策略。     

BK医疗中国区配送中心分布优化研究

对生产型企业而言,物流成本是企业运转成本的一个非常重要的组成部分,我们希望和客户一起,通过分析物流成本的构成及其每个环节的发展和现状,在满足终端客户服务要求的前提下,通过科学、合理的物流管理方法,优化物流方案、以达到帮助企业有效降低物流成本。文中就对现合作客户BK医疗器械项目在中国区的物流配送中心运营现状进行分析,结合物流运输管理的相关知识,完成优化方案的构想和设计。     

食品经销商库存管理分析及对策研究

食品经销商本身没有自己的产品，它是厂家到终端和消费者直接见面的销售渠道链中的一个重要的环节，它的利润来源于所经销单位产品的价格差。在经销商的收益分析中，库存成本是除了产品本身成本之外的重要成本之一。而库存成本除了与商品库存数量有直接关系外，与商场、厂家和经销商的管理方式都有非常紧密的联系。     

A logistics model for emergency supply of critical items in the aftermath of a disaster

This paper proposes a logistics model for delivery of prioritized items in disaster relief operations. It considers multi-items, multi-vehicles, multi-periods, soft time windows, and a split delivery strategy scenario, and is formulated as a multi-objective integer programming model. To effectively solve this model we limit the number of available tours. Two heuristic approaches are introduced for this purpose. The first approach is based on a genetic algorithm, while the second approach is developed by decomposing the original problem. We compare these two approaches via a computational study. The multi-objective problem is converted to a single-objective problem by the weighted sum method. A case study is presented to illustrate the potential applicability of our model. Also, presented is a comparison of our model with that proposed in a recent paper by Balcik et al. [6]. The results show that our proposed model outperforms theirs in terms of delivering prioritized items over several time periods.     

Cost-aware request routing in multi-geography cloud data centres using software-defined networking

Current geographically distributed cloud data centres (CDCs) require gigantic energy and bandwidth costs to provide multiple cloud applications to users around the world. Previous studies only focus on energy cost minimisation in distributed CDCs. However, a CDC provider needs to deliver gigantic data between users and distributed CDCs through internet service providers (ISPs). Geographical diversity of bandwidth and energy costs brings a highly challenging problem of how to minimise the total cost of a CDC provider. With the recently emerging software-defined networking, we study the total cost minimisation problem for a CDC provider by exploiting geographical diversity of energy and bandwidth costs. We formulate the total cost minimisation problem as a mixed integer non-linear programming (MINLP). Then, we develop heuristic algorithms to solve the problem and to provide a cost-aware request routing for joint optimisation of the selection of ISPs and the number of servers in distributed CDCs. Besides, to tackle the dynamic workload in distributed CDCs, this article proposes a regression-based workload prediction method to obtain future incoming workload. Finally, this work evaluates the cost-aware request routing by trace-driven simulation and compares it with the existing approaches to demonstrate its effectiveness.     

基于时间的易变质品整合补货发货模型

近年来,VMI被越来越多的企业采用,它使企业效率和效益得到提高,因此,VMI便成为了企业库存控制的重点。文中分析了VMI环境下整合补货发货策略,并考虑产品变质率服从威布尔分布因素,以总成本最低建立了需求服从Possion分布的整合补货发货模型,确定了补货周期和最佳库存水平,并分析各个参变量对模型总成本的影响。     

Optimal maintenance center inventories for fault-tolerant repairable systems

In many military and commercial contexts, complex equipment which is expected to perform very reliably is often designed to be fault-tolerant, that is, able to function although some of the parts have failed. A popular fault-tolerant design is the m-out-of-n system, where there are n identical parts, at least m of which must be functional for machine operation. Complex equipment of this type often undergoes scheduled maintenance overhauls at regular intervals during which all failed components are replaced. Failure to have replacements on hand for failed parts requires emergency measures at premium cost. When repairable parts are highly reliable and expensive, both holding and shortage costs are high. A reasonable objective is to choose initial spares inventory to minimize the sum of holding costs and expected shortage costs.We first develop a model to determine the optimal repairable parts inventory for a maintenance center servicing machines containing a single m-out-of-n system. The model is then extended to handle a related problem, finding optimal maintenance center inventories for machines containing several m-out-of-n systems of different parts, minimizing total expected costs subject to a constraint on total inventory investment.We assume that there is a fleet of machines, which experience identical workloads. There is a cycle time of T days between overhauls for an individual machine. A machine arrives at the maintenance center for overhaul each day. At the overhaul, all failed parts are removed and sent to a repair shop, from which they eventually return to the maintenance center to be used again as spares. The total number of spares undergoing repair and on hand is a constant. There are no backorders; if the number on-hand spares is insufficient to meet demand at an overhaul, a shortage penalty is assessed which depends on the number and type of spares required.While computing holding costs is straightforward, computing expected shortage costs is more complex. Expected shortage costs are dependent upon several factors, including component failure rates, the values of m and n, part repair rates, and the initial number of spares on hand. We assume that the system of interest is well specified, so that the parameters of the model are known except for the number of initial spares of each type, which are the decision variables. We model the on-hand inventory of each type of part as a Markov chain with the number of spares on hand at the end of each day as the states, under the assumptions that failure rates are constant and repair times follow independent exponential distributions. We then calculate the steady-state probabilities of stockout of various numbers of spares, as a function of the initial spares inventory. The expected shortage costs for a given type of spare may then be calculated by finding the product of the penalty cost for lacking p spares and the probability of lacking p spares and summing over all possible p values.Solutions to the problem of finding optimal initial inventory level for a machine containing a single m-out-of-n system may be found easily by enumeration. Solutions to the constrained problem where the machine contains several independent m-out-of-n systems, may be found by dynamic programming. Sensitivity analysis of costs to changes in the inventory investment constraint is clear, and computational effort is reasonable. A simple example is included to illustrate the solution method for both problems.     

Green logistics in food distribution – a case study

Environmental impacts, such as Green House gas emissions, have been introduced to supply chain management as an additional parameter to traditional key performance indicators such as cost, lead-time and on-time delivery. This paper analyses a case example from the food industry on how CO₂ emissions are structured in a value chain. The focus of the analysis covers food factory order-picking operations, transportation, warehousing and distribution aspects. The paper aims to demonstrate greening and CO₂ saving potential areas of development for thermo-controlled food logistics. The results show the energy-saving potential of several supply chain processes giving examples of distribution logistic online-temperature controlling possibilities. Greening decisions in supply chain design in the food industry are considered.     

基于顾客价值的大学生电脑市场细分研究——以济南为例

基于顾客价值视角,应用在济南部分高校的调查数据,对大学生电脑市场进行市场细分研究。结论表明:影响大学生购买决策的6个价值因子按其重要度依次为性价比、售后服务、购物体验、产品形象、信息沟通和废弃处理;整个市场可划分为时尚型用户、慎重型用户、服务型用户和实用型用户四个细分市场,并且它们在各价值因子上都有较好的解释。这些结果对于电脑厂商进行目标市场选择和市场定位,实施差异化营销,具有重要的参考价值。     

一种考虑供应商转换成本的多期供应商选择模型

为解决供应链中多期多种产品的供应商选择问题,对现有的供应商选择模型进行了改进,综合考虑供应商供应能力、交货提前期等限制,以及供应商转换成本、交易成本和批量库存成本对供应商选择方案的影响,建立了混合整数规划模型,以确定每个时期每种产品的最优供应商选择方案及供应量,并通过实际算例验证了模型的有效性。     

Contracting Costs and Information Asymmetry Reduction in Cross‐Border M&A

This paper explores the contracting costs of conducting mergers and acquisitions (M&A), creates a theoretical model of the information asymmetry involved, and shows how buying firms employ several mechanisms to reduce such asymmetry. Extending prior literature, the paper examines these costs in both domestic and cross‐border settings using a sample of over 3000 M&A deals. I consider both the fees paid and the time required in the bargaining phase to be contracting costs, and model them simultaneously to help explicate their endogenous relationship. The results show that buyers in cross‐border deals are more likely to employ mechanisms to affect information asymmetry, while the employment of these mechanisms affects contracting costs. The results help to explain why cross‐border M&A are more costly yet more quickly executed. Finally, modelling the use and effects of the mechanisms is sufficient to explain the contracting cost differences between domestic and cross‐border M&A.     

Vehicle flow formulation for two-echelon time-constrained vehicle routing problem

Two-echelon routing problems, including variants such as the two-echelon vehicle routing problem (2E-VRP) and the two-echelon location routing problem (2E-LRP), involve assignment and location decisions. However, the two-echelon time-constrained vehicle routing problem (2E-TVRP) that caters to from-linehaul-to-delivery practices does not involve assignment decisions. This routing problem variant for networks with two echelons has not yet attracted enough research interest. Localized or long-distance services suffer from the lack of the assignment decisions between satellites and customers. Therefore, the 2E-TVRP, rather than using assignment decisions, adopts time constraints to decide the routes on each of the two interacting echelons: large-capacity vehicles transport cargoes among satellites on the first echelon, and small-capacity vehicles deliver cargoes from satellites to customers on the second echelon. This study introduces a mixed integer linear programming model for the 2E-TVRP and proposes a heuristic algorithm that incorporates the savings algorithm followed by a variable neighborhood search phase. Illustrative examples are used to test the mathematical formulation and the heuristic and a case study is used to demonstrate that the heuristic can effectively solve realistic-size instances of the 2E-TVRP.     

基于时间约束的单产品共同配送研究

随着物流业的调整发展．提高物流效率、降低物流成本逐渐成为关注的焦点。有着发达物流业的国家,如德国、美国等的实践已经证实,采用共同配送这一先进的配送模式,将能够改善在物流效率、物流成本方面所凸现的问题。在我国,共同配送体系还不完善,加之客户对于配送时间的要求也越来越高．满足客户时间要求的集约化、协同化配送就成为亟待解决的问题。文章针对这一问题,将“软时间窗”和“硬时间窗”同时引入到共同配送中,建立模型并通过算例分析对理论研究进行了实证。     

A socio-economic optimization model for blood supply chain network design during the COVID-19 pandemic: An interactive possibilistic programming approach for a real case study

In uncertain circumstances like the COVID-19 pandemic, designing an efficient Blood Supply Chain Network (BSCN) is crucial. This study tries to optimally configure a multi-echelon BSCN under uncertainty of demand, capacity, and blood disposal rates. The supply chain comprises blood donors, collection facilities, blood banks, regional hospitals, and consumption points. A novel bi-objective Mixed-Integer Linear Programming (MILP) model is suggested to formulate the problem which aims to minimize network costs and maximize job opportunities while considering the adverse effects of the pandemic. Interactive possibilistic programming is then utilized to optimally treat the problem with respect to the special conditions of the pandemic. In contrast to previous studies, we incorporated socio-economic factors and COVID-19 impact into the BSCN design. To validate the developed methodology, a real case study of a Blood Supply Chain (BSC) is analyzed, along with sensitivity analyses of the main parameters. According to the obtained results, the suggested approach can simultaneously handle the bi-objectiveness and uncertainty of the model while finding the optimal number of facilities to satisfy the uncertain demand, blood flow between supply chain echelons, network cost, and the number of jobs created.     

Why Do Landlords Include Utilities in Rent? Evidence from the 2000 Housing Discrimination Study (HDS) and the 2002 American Housing Survey (AHS)

This study assesses the decision to include utilities in the rent and the effect of this decision on rents. We utilize individual house-level data from the 2000 Housing Discrimination Study (HDS) and 2002 American Housing Survey (AHS), and determine that the cost of meter installation is not the only reason that utility costs are included in rent. We find evidence that landlords include utilities in the rent to attract more customers. Additionally, our findings demonstrate that utility inclusion behavior differs significantly between old and new building owners. For the hedonic rent estimation, we find that the decision to include the cost of utilities in the rent raises rent.