Integrated Order Scheduling and Packing

We consider an integrated production–distribution scheduling model in a make‐to‐order supply chain consisting of one supplier and one customer. The supplier receives a set of orders from the customer at the beginning of a planning horizon. The supplier needs to process all the orders at a single production line, pack the completed orders to form delivery batches, and deliver the batches to the customer. Each order has a weight, and the total weight of the orders packed in a batch must not exceed the capacity of the delivery batch. Each delivery batch incurs a fixed distribution cost. The problem is to find jointly a schedule for order processing and a way of packing completed orders to form delivery batches such that the total distribution cost (or equivalently, the number of delivery batches) is minimized subject to the constraint that a given customer service level is guaranteed. We consider two customer service constraints—meeting the given deadlines of the orders; or requiring the average delivery lead time of the orders to be within a given threshold. Several problems of the model with each of those constraints are considered. We clarify the complexity of each problem and develop fast heuristics for the NP‐hard problems and analyze their worst‐case performance bounds. Our computational results indicate that all the heuristics are capable of generating near optimal solutions quickly for the respective problems.     

物流服务供应链中基于期权契约的能力协调

不同于产品供应链,物流服务供应链作为能力链,其协调手段只能通过服务能力的调整与优化来实现。在Stackelberg主从博弈下提出一种基于期权契约的协调机制来研究集成商与分包商物流能力的订购与投资决策问题,并对协调机制效果及供应链期望额外利润的分配进行数值检验和结论分析。研究结果表明,所设计的期权契约可实现物流服务供应链完美协调,并提高双方的期望利润。而且,物流服务供应链实现协调时,期权契约参数--期权价格与期权执行价格之间存在负相关关系,而作为契约核心决策要素的期权价格必须在一个合理的范围内。     

Impacts of demand and supply factors on the capacity scheduling performance of logistics service supply chain with mass customisation service modes: an empirical study from China

This paper studies the influence of the demand–supply environment on the capacity scheduling performance of the logistics service supply chain. According to the key characteristics of the demand–supply environment, the cases of five Chinese companies were introduced and cross-analysed, then research hypotheses were developed. After receiving 154 valid questionnaires and testing our hypotheses, some key conclusions were obtained. From the aspect of demand, there is a positive correlation between the customised levels of demand and the scheduling cost of logistics service integrators but a negative correlation between the customised levels of demand and the scheduling flexibility; From the aspect of supply, a higher self-support ratio of logistics source and a higher sourcing integrity of logistics service integrators will lead to a higher scheduling cost and a lower scheduling flexibility; a whole-process performance evaluation is a moderator, which will positively improve the impact of the whole process scheduling performance.     

基于前景理论的LSSC服务质量管控策略的演化博弈分析

物流服务的完成质量依赖于物流服务供应链（LSSC）中集成商（LSI）与提供商（FLSP）的共同努力。本文基于决策者有限理性的假设，将前景理论与演化博弈相结合，分析物流服务供应链中服务质量管控活动，讨论提供商服务策略与集成商管控策略的博弈过程，通过仿真揭示损失规避系数、感知价值的敏感系数、竞争替代效应、责任分担比率对演化结果的影响。本文的创新与特色在于：一是借助前景理论中的价值函数与决策权重函数修正传统演化博弈中的支付矩阵，扩展了物流服务供应链中关于博弈者风险态度、损益感知价值等心理因素的讨论。二是通过考虑集成商间的竞争替代效应，丰富了现有文献中对集成商监管策略影响因素的探讨。研究结果表明：提升提供商对违约成本的感知价值、发挥集成商间的竞争替代效应是系统达到最优均衡点的有效途径；增强提供商与集成商对违约后果的认知程度、提高双方的风险意识能有效抑制服务违约行为；各核心要素对系统演化的影响方式不同，通过模型与仿真结果可解释由责任分担不当诱发的LSSC服务质量管控不利的问题。     

基于顾客不公平规避的服务定价研究

设计合理的服务机制和定价策略对于企业运营至关重要。由于顾客异质性（等待时间成本不同）企业通常对顾客进行分类服务,然而分类服务会引发顾客的不公平心理,并带来负效用,从而引起顾客流动与转移,进而影响企业收益与社会成本。本文针对垄断型服务系统中,顾客不公平规避心理（用参数α表示）对于企业优化目标的影响进行分析,在此基础之上,研究企业是否对顾客采取分类服务以及如何合理定价。结果表明,当顾客不公平规避偏好心理较弱时,从社会成本最小化和企业收益最大化的角度都应该对顾客进行分类服务并收取优先服务费用。当顾客不公规避心理较强时,从企业收益最大化的角度应仅保留优先权顾客并收取优先服务费用,从社会成本最小化的角度则应取消优先服务费用仅保留普通顾客。最后,通过数值模拟和理论分析对上述结论进行验证。     

Interpretive structural modeling-based framework for mass customisation enablers: an Indian footwear case

Abstract

In the epoch of open economy and with the emergence of availability of individualised products over the Internet, Indian manufacturing industries are facing an enormous pressure to become more flexible and responsive, to accomplish customer’s varied and increasing demands. Mass customisation (MC) is about developing a customised product on demand for a particular customer after reception of a real order and producing it with the similar operational efficiency as one would anticipate from a mass-produced product. MC takes into account the merits of both the earlier systems of production, i.e. mass production and craft production. The craft production satisfies the personalised demands of customers and the mass production produces a limited variety of products at lower cost. Industries in developing countries such as India confront pressure from several perspectives to adopt MC. This study has been presented in the context of Indian manufacturing industries, and particularly for footwear industries to examine the enablers of MC. Achieving MC, however, require certain enabling technologies and processes in place. Several such enablers have been identified from the research literature. The objective of this study it to key out significantly important enablers for MC using interpretive structural modelling (ISM), and develop a hierarchy of these enablers for the Indian footwear units. ISM results show that modularity-based practices, digital manufacturing practices and supply chain integration are the most important MC enablers. Enhanced flexibility and responsiveness in the footwear production system can be achieved through modular and reconfigurable production system.     

Supply chain scheduling optimisation in mass customisation based on dynamic profit preference and application case study

Traditionally, the ‘postponement strategy’ is a better way to solve the contradiction between ‘scale production effect’ and ‘customised demand level’ in mass customisation (MC). In higher customisation situation, the conflict between the role of postponement and the higher level of customised demand must be outstanding. When MC operates in supply chain, the excellent flexible characters of the supply chain system will create better conditions to solve the conflict from a new perspective, but the operating combination of MC and the supply chain with uncertain characters will lead to various complicated contradictions and bottlenecks. In this article, we discuss the supply chain scheduling optimisation in MC based on dynamic profit preference to solve these contradictions and bottlenecks, establish a special optimisation model to implement the scheduling. We make a computational industrial case study to illustrate the method application and show the benefits of solving the key contradiction in MC by the supply chain scheduling.     

Impact of customer loyalty and service operations on customer behaviour and firm performance: empirical evidence from UK retail sector

Abstract

Retail networks are striving to achieve competitive advantage by increasing value through loyalty and efficiency with a focus on service operations. As sales promotions have become an integral part of the retail supply chain planning, customer behavioural aspects based on loyalty and service operations have been challenged greatly. Subsequently, management capabilities, such as planning and timely replenishment, have become complicated tasks for many retail store managers. This study develops a model integrating retail network value and efficiencies with customer behaviour and performance. We validate the model using survey data from prominent U.K. retail store customers. Our data analysis shows that both loyalty and service operation attributes have positive significant impact on customer behaviour, while the service operation mediates the relationship between loyalty and customer behaviour. This result gives a new outlook to build managerial capability based on customer loyalty and service operations. Our results specifically show that the service operation attributes will indirectly influence the customers’ buying behaviour even in the presence of loyalty attribute such as promotion schemes. This result sends a strong signal to retail supply chain managers to offer customised promotions considering local community rather than having uniform sales promotion nationwide.     

消费者视角下中小企业社群动态定制仿真建模及其管理策略研究

移动互联时代下，基于在线社群的聚合力和社群经济效益的社群定制模式，如何有效解决大部分中小定制企业普遍面临的定制顾客少、销售转换率低及总体利润低等问题，是定制企业界目前亟待解决的重要问题之一。针对此，首先，本文对社群定制模式和一般在线定制模式进行定性分析，阐明两种定制模式的实现路径和特征，对其差异性进行归纳。然后，从消费者行为角度出发，结合定制模式的实现路径和差异性，分别建立多Agent仿真模型，分析两种定制模式下定制销售转化率、购买人数、消费者满意度和企业利润的差异，从而验证社群定制模式的有效性。最后，进一步研究不同企业和市场特征对社群定制与一般在线定制模式定制效果的影响，并探讨社群特征对社群定制效果的影响，为企业有效的定制选择及社群定制实现提供相应的管理策略。     

基于顾客公平偏好的服务机制与定价研究

由于顾客异质性（单位时间等待成本不同），服务提供商通常对顾客采取分类服务策略，然而分类服务会引起服务系统中不同类型顾客之间等待时间和服务价值的差异性，从而给顾客带来心理上的不公平感，进而引起顾客在服务系统中的流动和转移，进一步影响企业收益和社会福利。本文针对非抢占M/M/1服务系统顾客分类情形为背景，由两种顾客之间期望等待时间的不同和公平偏好参数相结合构建普通顾客的公平心理效用模型，以垄断型服务系统为背景，分别从企业收益、社会福利与顾客效用三个视角进行分析。研究表明，服务提供商应对顾客采取可观测型的分类服务机制来获得最大收益；从社会福利视角，服务提供商应对顾客采取不可观测型的分类服务机制；从顾客效用视角，服务提供商应取消顾客分类服务，仅保留普通顾客。最后同现有结论进行比较分析，并进行拓展研究。本文研究对服务提供商采取合理的服务机制及相应的服务定价具有重要参考价值和指导意义。     

OPTIMAL RENEGING DECISIONS IN A G/M/1 QUEUE

This paper is an analysis of the optimal reneging decision of a customer who joins a G/M/1 queue, having imperfect information about the queue. It is assumed that a customer receives a constant, known reward upon completion of service and incurs a cost proportional to the time spent in the queueing system. It is also assumed that a customer revises his estimated remaining waiting time in the system based on his initial estimate and observations of service time. Thus, a customer will renege when his estimated cost of remaining in the system exceeds his reward. The probability of a customer reneging during any given service is determined. Finally, it is shown how this probability varies with the parameters of the customer.     

On the fair optimization of cost and customer service level in a supply chain under disruption risks

This paper presents a new decision-making problem of a fair optimization with respect to the two equally important conflicting objective functions: cost and customer service level, in the presence of supply chain disruption risks. Given a set of customer orders for products, the decision maker needs to select suppliers of parts required to complete the orders, allocate the demand for parts among the selected suppliers, and schedule the orders over the planning horizon, to equitably optimize expected cost and expected customer service level. The supplies of parts are subject to independent random local and regional disruptions. The fair decision-making aims at achieving the normalized expected cost and customer service level values as much close to each other as possible. The obtained combinatorial stochastic optimization problem is formulated as a stochastic mixed integer program with the ordered weighted averaging aggregation of the two conflicting objective functions. Numerical examples and computational results, in particular comparison with the weighted-sum aggregation of the two objective functions are presented and some managerial insights are reported. The findings indicate that for the minimum cost objective the cheapest supplier is usually selected, and for the maximum service level objective a subset of most reliable and most expensive suppliers is usually chosen, whereas the equitably efficient supply portfolio usually combines the most reliable and the cheapest suppliers. While the minimum cost objective function leads to the largest expected unfulfilled demand and the expected production schedule for the maximum service level follows the customer demand with the smallest expected unfulfilled demand, the equitably efficient solution ensures a reasonable value of expected unfulfilled demand.     

Joint supplier selection and scheduling of customer orders under disruption risks: Single vs. dual sourcing

This paper presents a stochastic mixed integer programming approach to integrated supplier selection and customer order scheduling in the presence of supply chain disruption risks, for a single or dual sourcing strategy. The suppliers are assumed to be located in two different geographical regions: in the producer's region (domestic suppliers) and outside the producer's region (foreign suppliers). The supplies are subject to independent random local disruptions that are uniquely associated with a particular supplier and to random semi-global (regional) disruptions that may result in disruption of all suppliers in the same geographical region simultaneously. The domestic suppliers are relatively reliable but more expensive, while the foreign suppliers offer competitive prices, however material flows from these suppliers are more exposed to unexpected disruptions. Given a set of customer orders for products, the decision maker needs to decide which single supplier or which two different suppliers, one from each region, to select for purchasing parts required to complete the customer orders and how to schedule the orders over the planning horizon, to mitigate the impact of disruption risks. The problem objective is either to minimize total cost or to maximize customer service level. The obtained combinatorial stochastic optimization problem will be formulated as a mixed integer program with conditional value-at-risk as a risk measure. The risk-neutral and risk-averse solutions that optimize, respectively average and worst-case performance of a supply chain are compared for a single and dual sourcing strategy and for the two different objective functions. Numerical examples and computational results are presented and some managerial insights on the choice between the two sourcing strategies are reported.     

顾客可能取消订单的MTO企业订单定价策略

研究了顾客下订单后可能取消订单的按订单生产型企业的定价策略。顾客到达后向企业询问订单报价,如果价格合适,顾客将下订单,否则选择离开。引入了顾客接受概率模型,以最大化订单期望利润为目标,得出了订单最优定价和最大期望利润。通过分析最优定价和最大期望利润对于各参数的敏感性得出:最优定价是系统积压订单数的增函数,是订单取消概率和取消订单赔偿比例的减函数;而最大期望利润是系统积压订单数的减函数,是取消订单赔偿比例的增函数。通过数值分析发现,在顾客确实可能取消订单的背景下,如果决策者在对订单进行定价时不考虑这一可能性,将会减小企业获得的最大期望利润。     

基于顾客心理期望等待时间的服务策略研究

顾客在排队系统获取服务时，会存在心理上的期望等待时间，该期望会影响顾客在排队系统中的行为变化和流动，从而影响企业收益。本文以传统的M/M/1排队系统为背景，基于顾客存在期望等待时间的前提下，以企业收益最大化为优化目标进行研究。首先，对相应基础理论和模型假设进行介绍；其次，对顾客存在心理期望等待时间情形提出三种新的策略：重新定价、通过折扣对顾客期望值进行调整、提高服务率；然后，分别对上述三种策略进行优化分析，并同现有结果进行比较；研究表明：三种策略都比维持原有定价带来更大收益；当折扣力度较小时或顾客对费用感知强于时间感知时，折扣策略优于重新定价策略；当折扣力度较大或顾客对时间感知强于费用感知时，重新定价策略优于折扣策略；最后，通过对最优结果分析提出相应管理启示。本文的研究对于顾客存在心理期望等待时间的服务定价具有重要的指导意义和实际应用价值。     

Adjusting MRP for dynamic differentiation of identical items for process customisation

In the make-to-order (MTO) environment, different customer orders often require similar products that share identical basic features but require different customisation processes. To achieve efficiency, these products are often manufactured in a group at the initial stages. A significant issue then emerges as to how to differentiate identical items at the intermediate stages so that they can be dispatched to different kinds of work centres for process customisation. This article adjusts the current material requirements planning (MRP) approach for the MTO mode. A yield-allocating approach is then proposed for adjusting the material demand plans according to real-time process quality information. An approach for dynamically differentiating identical customised items at intermediate stages is then presented. How to implement the proposed methodology in a computer-based environment is also briefly introduced. A case study demonstrates that the proposed methodology can fulfil the dynamical differentiation task and can result in more reasonable differentiation decisions than the traditional MRP approach.     

基于不同TPL权力的电商供应链决策研究

第三方物流企业受到政府补贴的大力扶持,物流服务显著提升,对消费者网购产生积极影响,逐渐享有供应链话语权。通过分析物流服务供应商的物流成本结构,分别考虑物流投资与物流成本函数,从第三方物流供应链权力视角构建三种电商供应链物流外包权力结构场景(物流服务商主导模式、物流服务商次主导模式和物流服务商跟随模式),综合研究第三方物流企业权力对电商物流外包供应链决策的影响。结果表明,当物流服务商权力越小时,物流服务水平、市场规模、制造商利润和网络零售商利润越大。而不同权力结构下的批发价格、零售价格、物流服务商利润关系受到物流投资系数和物流配送费用的共同影响。当满足条件时,物流服务商跟随模式使得供应链实现帕累托最优。不同第三方物流企业处于不同权力地位时,供应链利润均随物流配送费用的增加、物流投资系数的增加,物流成本系数的减小而增加。据此对不同的物流补贴政策效果进行分析,并为政策制定者和供应链主体提供参考性意见。     

How Long Should a Customer Wait for Service?

A major concern for service managers is the determination of how long a customer should wait to be served. Services, due to the customer's direct interaction with the process, must face a trade-off between minimizing the cost of having a customer wait and the cost of providing good service. A total cost model is presented for determining how long a customer should wait when these two conflicting cost components are considered. An integral part of this model includes a measure of customer satisfaction with waiting time which is used to develop a waiting cost function. The model is then applied to a major fast food chain, using data collected at several locations. Analysis of the data reveals that the “ideal” waiting time for this firm is significantly less than the current corporate waiting time policy. Thus, as indicated by the model, a corporate policy change is recommended to provide much faster service. The adoption of such a policy would result in increased labor costs, and would simultaneously increase the firm's overall profits. Although appearing contradictory, increases in current labor costs and long-term profits are both possible when management takes the long-range perspective suggested in this paper.     

成本信息不对称下的应用服务外包菜单式合约

客户企业实施应用服务外包时,面临着成本信息不对称所带来的风险。针对该问题,以客户企业期望收入最大化为目标,在应用服务提供商(Application Service Provider, ASP)所拥有的成本效率参数及努力水平不可观测下研究客户企业如何通过服务外包菜单式合约的设计激励ASP付出最优的努力水平,并显示出真实的成本信息。研究表明,收益共享系数是成本效率参数、风险规避度、产出方差的减函数;客户企业向ASP支付的期望服务报酬除了补偿保留效用与服务生产成本还将额外支付风险成本、信息租金;风险成本随风险规避度、产出方差递增,随成本效率参数递减;信息租金随风险规避度、产出方差、成本效率参数递减。     

考虑自取服务和门到门服务的电动汽车物流网络优化策略研究

在环境意识增长与政府政策支持的有利条件下,电动汽车在物流领域得以快速发展。为提高物流服务的效率,降低企业运营成本,文中研究了考虑顾客服务策略的电动物流汽车服务设施选址与配送路径问题。采取顾客自行取货与配送人员送货上门相结合的多样化服务策略,使得服务站点的建设成本、顾客点配送路径成本以及服务站点补货路径成本之和最小。建立了整数规划数学模型,允许配送车辆在服务过程中前往服务站点接受充电服务。其次,提出了基于改进节约算法和禁忌算法的混合启发式算法MCWSA-TS。随后,在小规模算例将CPLEX运算结果与MCWSA-TS进行对比,证明了算法的有效性。最后,采用多组算例探讨了顾客取货半径对运营成本的影响,并对分离配送策略与联合配送策略进行对比分析。实验结果表明,多样化服务策略有助于企业满足顾客取货时间和取货方式的个性化需求。同时,兼顾运营成本与顾客满意度,促进电动汽车参与的物流服务快速发展。