考虑销售努力和运输时间的农产品供应链弹性契约

目的 进一步实现农产品供应链数量弹性契约利润最大化。方法 在市场需求随机的条件下,考虑销售努力和运输时间为影响需求的关键变量,建立起由供应商和零售商组成的农产品供应链数量弹性契约模型。基于该模型引入奖励与惩罚策略,以实现农产品供应链弹性契约的一致性和有效性。结果 结合农产品特征,通过具体的模型优化方法和算例分析得出最优值以及各变量与最优销售努力水平、最优运输时间、最优订货量和整体农产品供应链利润之间的相关关系。结论 农产品供应链弹性契约能实现协调下的利润最大化,对农业经营主体企业开展农产品供应链弹性研究具有重要的理论和实践价值。     

价格随机条件下的应急双向期权数量弹性契约

旨在用期权应对批发价格波动的风险,用数量弹性契约来应对市场价格和市场需求随机波动带来的风险,探索双向期权数量弹性契约协调供应链的内在规律。将双向期权契约与数量弹性契约相融合,协调批发价、市场价格和市场需求均随机波动的供应链,寻找最优的供应链决策,并进行了算例仿真。研究结果表明：在批发价格波动时,采用双向期权弹性契约比采用基准数量弹性契约效果更好。双向期权弹性契约可以协调批发价格和市场价格均随机的供应链。     

不同主导力量下考虑公平偏好的旅游供应链定价策略

为了研究不同主导力量下决策者的公平偏好特征对旅游供应链定价策略的影响,建立了由一个景区和一个旅行社组成的旅游供应链Stackelberg主从博弈模型,在景区主导和旅行社主导两种供应链权势结构下,引入从属方的公平偏好特征,研究公平偏好信息对称与不对称情形下的定价策略,并进行对比分析。结果表明,景区主导情形下,旅行社公平偏好信息对称时,景区将采取降低门票批发价格行为,旅行社最优销售价格不变;旅行社公平偏好信息不对称时,景区最优门票价格不变,旅行社最优销售价格逐渐增大。旅行社主导情形下,无论景区公平偏好信息对称与否,景区最优门票批发价格逐渐增大,旅行社最优销售价格不变,但信息不对称下的景区最优门票价格小于信息对称情形。     

潜在市场需求不确定下的风险厌恶供应链决策

考虑新产品投入市场时潜在市场需求不确定下的供应链风险厌恶,构造了一个考虑制造商和零售商的效用函数,建立了基于广告费用、服务水平以及销售价格的最优短期决策模型,分析了需求风险和供应链成员风险容忍水平对供应链最优短期决策的影响,采用数值仿真分析了供应链最优长期决策。研究结果表明：最优广告费用分别是需求风险和风险容忍水平的单调递增和递减函数,最优销售价格和服务水平则因行业等因素不同与需求风险和风险容忍水平呈U型或倒U型关系;当市场环境变化时,销售价格和服务水平在不同市场条件下应做出不同调整,而广告费用调整与市场特征无关;从长期来看制造商可以达到效用最大化,而零售商效用只能次优。a     

电子商务环境下无缺陷退货政策

研究电子商务环境下包含一个制造商和一组顾客群的单周期供应链系统,建立了无质量缺陷的退货问题决策模型。分析顾客购买及退货的策略性决策的特点,确定了3种退货政策下,制造商的最优定价、最优供货量、最优退货价格及网络销售成本的临界值。比较分析3种退货政策的优劣及其对供应链绩效的影响。结果表明,当商品的采购/制造成本或残值较低时,零退货政策优于全额退货政策;而实行部分款额退货政策的供应链绩效优于全额退货政策。     

Impact of an emergency order opportunity on supply chain coordination

We consider a manufacturer-retailer supply chain in the pre-selling and selling seasons, whereby the manufacturer can offer the retailer an emergency order opportunity with a limited commitment quantity in addition to the regular order from the retailer before the selling season. Due to the short lead time for the emergency order, the manufacturer needs to prepare for it in the pre-selling season by producing more than the regular order or reserving its capacity for the responsive production. Through mathematically modelling and analyzing the supply chain, we found that, when the emergency order opportunity is provided, the manufacturer might be worse off, although the retailer is always better off. We derive the conditions whereby both the manufacturer and retailer can benefit from the emergency order, and the supply chain profit can be maximised. Further, we show that the supply chain can be coordinated by setting only the unit price and maximum commitment quantity for the emergency order. We also prove that Pareto improvement can be always achieved by setting the unit price for the regular order in addition to the unit price and maximum commitment quantity for the emergency order.     

价格随机条件下看涨期权折扣契约的应急供应链协调研究

在突发事件造成市场需求与市场价格均随机波动的条件下,将期权与数量折扣契约融合,形成一种新的期权折扣契约,并用看涨期权折扣契约模型来协调供应链。通过海塞矩阵判断得知供应链存在最优决策,并进行算例分析。结果表明：当突发事件引起市场需求增加时,看涨期权折扣契约和数量折扣契约均能有效地提升供应链收益,且看涨期权折扣契约提升的幅度更大;当突发事件引起市场需求缩小时,2种契约均不能扭转整个供应链收益大幅下降的局面,且看涨期权折扣契约下降的幅度更大。为获取超额利润,决策者必须充分获取市场信息并对市场需求进行准确的预测才能使新的契约机制更有效。在新的前提条件下,看涨期权折扣契约模型能有效地协调供应链并提高整个供应链系统的绩效。该契约实现了风险共担和收益双赢,在一定程度上提升了供应链的柔性。     

The impact of consumer price forecasting behaviour on the bullwhip effect

As prices fluctuate over time, a strategic consumer may buy more in advance to reduce his or her future needs in anticipation of higher prices in the future, or may choose to postpone a purchase in anticipation of lower prices in the future. We investigate the bullwhip effect from a consumer price forecasting behavioural perspective in the context of a simple two-level supply chain composed of a supplier and a retailer. We consider two different forms for the demand function – linear and iso-elastic demand functions, both depending on the prices in multiple periods. Assuming that the retailer employs an order-up-to inventory policy with exponential smoothing forecasting technology, we derive analytical expressions for the bullwhip effect under the two demand functions, and extend the results to the multiple-retailer case. We find that consumer forecasting behaviour can reduce the bullwhip effect, most significantly when the consumer sensitivity to price changes is medium (approximately 0.5) for both the demand forms. In addition, for iso-elastic demand, the mitigation of the bullwhip effect induced by consumer price forecasting behaviour becomes more significant as the product price sensitivity coefficient and standard deviation of the price decrease. These findings are applicable to the development of managerial strategies by supply chain members that are conducive to bullwhip effect reduction through customer behaviour.     

Reducing the effects of demand uncertainty in single-newsvendor multi-retailer supply chains

Due to fierce competition in today’s global market, businesses are forced to provide customers with high service levels. Typically, vendors produce or order sufficient quantities at the beginning of a selling season to ensure reasonable service levels for the whole season. However, due to the probabilistic nature of demand, high service levels at the beginning of a selling season does not guarantee appropriate service levels during the course of consuming the item. Thus, revision of service levels during a selling season is important and ignoring such revision may lead to serious consequences for businesses like profit loss due to cancelled orders and reduction of the market share of the company. In this paper, we propose a model for a newsvendor supply chain with single vendor and multiple retailers where the vendor has two-ordering opportunities. At the beginning of a selling season, the retailer orders from a vendor a quantity such that a predetermined service level is achieved. At the second-ordering instant, the retailer learns more about the demand pattern and uses the new available demand data to update the coming demand using Bayesian approach. Based on the updated demand, the retailer evaluates the new service level for the remaining portion of the selling season. If this service level is lower than a specific value, a second batch is ordered. We develop the model for general demand distribution and determine the optimal quantities at the beginning of the selling season and at the second-ordering opportunity.     

Delphi study on supply chain flexibility

The flexibility literature is dominated by research on manufacturing flexibility. More recently, supply chain flexibility has been recognized as an important flexibility construct for meeting customer demand. An Internet-based Delphi study involving a group of expert practitioners is used to enumerate the characteristics, and the importance of those characteristics, in making a supply chain flexible. Expert opinion is one method for gathering information that can be used to develop a model of supply chain flexibility and provide a framework for future research.     

Optimal reservation pricing strategy for a fashion supply chain with forecast update and asymmetric cost information

We address the reservation pricing problem for a two-echelon fashion supply chain in which the downstream manufacturer with private information on its operations cost (low or high type) reserves the capacity for a critical component from the upstream supplier before placing the final order. We consider the case when the demand forecast is partially updated. We find that a novel menu of reservation contracts containing the unit reservation fee with reservation quantity and final order could induce the manufacturer to reveal its operations cost information truthfully. We also show that the supplier should require less capacity reservation and charge a lower unit reservation fee if it has asymmetric information about the manufacturer’s operations cost. Finally, we analyse the effects of forecast update, and our results indicate that: (i) the supplier benefits from forecast update because the optimal reservation pricing strategy is designed to reveal the true information and meanwhile induce a higher capacity reservation; and (ii) a greater amount of forecast update decreases the supply chain deficit and increases the supplier’s agency cost.     

Compound Poisson demand with price-dependent intensity for fast moving items: price optimisation and parameters estimation

We consider a single-period single-item inventory system. The demand is a compound Poisson process with price-dependent intensity and continuous batch size distribution. The intensity of the customers’ arrivals is sufficiently high to use a diffusion approximation of the demand process. Equations for retail price maximising of an expected profit with the optimal order quantity are obtained and an approximate solution is proposed. Numerical results illustrating the percentage of the increase in profit for linear price-intensity dependence are given. An approximate distribution of the selling time of a large order is obtained. Demand parameters estimation procedures based on two censored samples – the observed selling durations and demands – are discussed.     

信息不对称下多供应商与单零售商的退货策略

研究由多个提供互补组件的供应商和一个组装商组成的报童型供应链中,零售商将需求信息私有化时,供应商如何制定克服信息不对称的退货策略,使得零售商订货量和信息对称情况下供应链最优订货量相等。假设需求分高需求和低需求两种状态,供应商在需求状态未知的情况下给出针对不同需求状态的两个子契约,使得零售商按照实际需求状态而确定相应订货量。首先分析集权型供应链中整个供应链的最优订货量,再分析分权型供应链中零售商的订货决策,进一步分析信息不对称情况下供应商间的博弈及批发价和回收价契约参数的确定方法。通过算例,说明激励零售商按照真实需求状态选择子契约的合理性,供应商制定的退货策略可以克服信息不对称。     

基于供应链金融的银行决策分析

根据需求模型,建立了包含银行在内的供应链决策模型,研究分散决策模型下的收益问题,分别得到供应链各个参与者的期望收益,并通过数值仿真,得到银行在供应链中产生的影响。从供应链金融的角度出发,研究零售商订购量、制造商批发价格、银行利率的关系。并利用Stackelberg博弈的理论,以银行为主导者,制造商和零售商为跟随者,求出均衡最优解。研究发现当市场需求较小时,三者收益函数趋势一致;当市场需求较大时,银行利率对零售商订购量没有影响并且银行的收益最后逐渐平稳达到一个固定值。     

Pricing and ordering decisions in a supply chain with imperfect quality items and inspection under buyback of defective items

In this article, the economic production and inventory model in a three-layer supply chain including one distributor, one manufacturer and one retailer for a single-product and general demand functions under three scenarios is developed. We assume that during the production process, both healthy and defective items are generated. As the first scenario, we develop the first model, in which the defective items are not reworked and all considered as scrape, while in the second model, we assume that the defective items are reworked and are sold as perfect item. In the second scenario, we assume that defective item can be sold with lower price than the selling price. Moreover, raw materials with imperfect quality are sent back from a distributor to outside supplier under a lower price. Determining the order quantity of the distributor and the selling prices of the distributor and the manufacturer as well as the retailer was the goal of this article such that the total profit of each member is maximised. In order to solve the models, the Stackelberg approach is employed between the members, and the concavity of the profit functions is proved using several theorems. Then, closed form solutions are derived for the decision variables and a solution algorithm is proposed to determine the optimal solutions. Finally, a numerical example is presented to illustrate the applicability of the model.     

Pricing and lot-sizing decisions in a two-echelon system with transportation costs

We consider a single-buyer single-supplier system. The market demand is sensitive to the selling price set by the buyer. Both the buyer and the supplier operate with unit product costs, inventory holding costs, and order placement costs. In addition, the buyer is responsible for the freight cost. We formulate a model for determining the optimal lot-sizing and pricing decisions. Existing models for the problem do not consider the transportation costs with price sensitive market demand, and determine the optimal decisions through an exhaustive search. We propose an approximate solution procedure, and report the computational results on the effectiveness of the proposed procedure.     

Value chain management for commodities: a case study from the chemical industry

We present a planning model for chemical commodities related to an industry case. Commodities are standard chemicals characterized by sales and supply volatility in volume and value. Increasing and volatile prices of crude oil-dependent raw materials require coordination of sales and supply decisions by volume and value throughout the value chain to ensure profitability. Contract and spot demand differentiation with volatile and uncertain spot prices, spot sales quantity flexibility, spot sales price–quantity functions and variable raw material consumption rates in production are problem specifics to be considered. Existing chemical industry planning models are limited to production and distribution decisions to minimize costs or makespan. Demand-oriented models focus on uncertainty in demand quantities not in prices. We develop an integrated model to optimize profit by coordinating sales quantity, price and supply decisions throughout the value chain. A two-phase optimization approach supports robust planning ensuring minimum profitability even in case of worst-case spot sales price scenarios. Model evaluations with industry case data demonstrate the impact of elasticities, variable raw material consumption rates and price uncertainties on planned profit and volumes.     

随机需求下零售商主导供应链的订单决策分析

已有关于供应链中订单决策问题的研究大都是从制造商主导交货期的角度来研究订单价格和交货期,但在"集群"环境下和市场随机需求下,零售商拥有购买决策权,主导订单时间。通过引入制造商声明策略,研究了在随机市场需求下和市场不确定性与观察时间相关联下,制造商—零售商之间的订单决策问题。建立了不同策略下的零售商订单决策模型,分析了制造商声明策略对零售商订单决策的影响,推导了制造商最佳利润率的求解算法。研究表明:制造商的不加班策略对自身始终是最有利,但最优利润率受市场不确定影响;零售商的订单决策受制造商声明策略和订单价格的影响。最后,通过算例给出制造商的最佳利润率以及市场不确定性对双方收益的影响。     

基于差异化物流服务的供应链决策与数量折扣协调

针对一个具有差异化物流服务的供应链,设计了基于数量折扣合同的协调策略以优化供应链定价决策,提高供应链及链上各方企业的利润。首先基于效用函数分析了消费者选择行为,并由此获得每种配送服务的需求函数。然后基于Stackelberg博弈模型求解了分散决策下的供应链均衡策略并与集中决策情形进行对比,发现分散决策下过高的产品销售定价及过低的快速配送附加运费导致消费者效用减少并使供应链总利润降低25%。为了达到集中决策下的最优绩效,基于物流企业视角提出数量折扣定价合同并对相关参数进行设计,发现促使供应链达到协调的数量折扣合同有无数多个,且在一定范围内这些合同能够实现双方企业利润的改善。最后基于数值分析模拟了部分数量折扣合同,并分析了零售企业还价能力对双方利润的影响。     

Optimal collection and remanufacturing decisions in reverse supply chains with collector’s imperfect sorting

We consider a reverse supply chain comprising two independent companies: the collector and the remanufacturer. The collector is responsible for sorting the collected used products and then transporting the ‘remanufacturable’ items to the remanufacturer. As sorting is not perfectly accurate, the misclassification errors affect the optimal decisions in the reverse supply chain. We focus on the optimal collection quantity for the collector and the optimal order quantity for the remanufacturer using game theory under both deterministic and uncertain demand. We characterise the optimal solution and show that under certain conditions, the remanufacturer should allow the collector to transport more ‘remanufacturables’ than the order quantity. We then examine the case where both the collector and the remanufacturer belong to a single company with centralised decision-making and compare the optimal collection quantities under both structures of the reverse supply chain.