考虑线上线下零售商竞争的制造商双渠道定价策略

根据现有的不同电商销售平台模式,将制造商双渠道销售模式划分为自营模式、平台模式和混合模式.分析在制造商主导的双渠道供应链中,3种不同渠道模式下价格竞争系数和佣金比例系数对其他经济变量的影响,以及制造商的最优定价决策与渠道选择问题.通过模型和数值分析发现,在平台模式和混合模式中,当制造商保证佣金比例系数在一定范围内,制造商利润随佣金比例系数的增加而减少,传统零售商、网络零售商和供应链总利润随佣金比例系数的增加而增加.在3种渠道模式中,混合模式对传统零售商和制造商利润增加更有利,平台模式对网络零售商和供应链总利润增加更有利.     

主制造商供应商协同合作最优定价决策博弈与混沌分析

基于主制造商供应商的协同合作模式和利益追求,建立了主制造商供应商的价格博弈模型,考虑主制造商供应商的合作共生关系,引入共生系数,研究利益分配下的供应链定价问题.应用复杂系统理论分析了系统的稳定性与混沌状态,通过数值模拟,发现了供应商的价格调整速度影响供应链系统的稳定,共生系数影响主制造商和供应商的利益.由此,供应链企业通过选择合适的控制系数,可使系统维持在稳定状态下,这一研究结果对复杂产品主制造商供应商的价格决策有很好的借鉴作用.     

零售商定价/订货决策下竞争/互补制造商采用RFID的策略研究

以一个零售商主导的两级供应链为研究对象,构建两个生产竞争性或互补性产品的制造商是否采用无线射频识别技术(radio frequency identification,RFID)时链上成员的收益模型,分析求解出各种情景下零售商定价/订货决策时制造商的最优批发价和RFID标签成本分摊系数,以及零售商的最优零售价/订货量,进...     

公平偏好行为下考虑质量和营销努力的定价策略

研究零售商公平偏好下考虑质量和营销努力的联合决策问题.首先考虑制造商Stackelberg的情形,研究发现, 零售价格、批发价格、质量努力水平、营销努力水平以及制造商利润均随零售商嫉妒偏好系数的增大而递减,但是零售商利润关于其嫉妒偏好系数的变化不大;然后,考虑零售商Stackelberg的情形,研究发现,批发价格、质量努力水平、营销努力水平以及制造商利润均随零售商的同情偏好系数的增大而递增,零售商利润则随其同情偏好系数的增大而递减;最后进行算例分析,并给出一些管理学的意义.     

考虑市场细分的闭环供应链生产与定价策略

基于市场细分建立闭环供应链模型,分析了决策变量随外生变量的变化规律,并比较了闭环供应链与不回收再制造情形的决策.结果表明:新制造和再制造产品的批发价随回购价的增加而增加,随回收价的增加而减少,零售价随回收价和回收努力程度的增加而增加;产品总量随消费者偏好系数的增加而增加,随再制造成本、回收努力程度及回收价的增加而减少;闭环供应链的新制造产品批发价和零售价均比不回收再制造时高;消费者偏好系数高于临界值时,回收再制造对于闭环供应链有利.     

制造商竞争与合作下双渠道供应链联合减排的微分博弈分析

以两个制造商与一个零售商组成的双渠道供应链为研究对象,分析制造商竞争与合作模型下供应链的最优均衡策略,并探讨系统关键参数对供应链各成员利润的影响.研究发现,只有当减排效率差异水平满足一定条件时,两制造商才会同时选择合作,且合作模型下制造商的利润总和增大,而减排努力、广告分担率、广告努力和零售商的利润减小.随着传统渠道市场占有率、减排竞争和广告竞争的增大,竞争模型下零售商的利润增大,而合作模型下的利润与广告竞争无关;制造商的利润变化取决于减排效率、网络渠道和传统渠道的边际利润.     

制造商竞争下创新投资对零售商信息分享策略的影响

研究在由两个竞争制造商和一个共同零售商组成的二级供应链中,制造商创新投资对零售商信息分享策略的影响.首先构建3种信息分享策略(不分享、部分分享和均分享)下的博弈模型,并对比分析得出零售商最优信息分享策略及不同策略下制造商/供应链利润大小关系;然后,探讨竞争制造商创新投资效率不等和存在横向溢出效应情形下零售商的信息分享策略.研究结果表明:当制造商投资效率相等时,若投资效率较低,则零售商没有动机分享预测信息;若竞争强度较小且投资效率较高,或者竞争强度较大且投资效率适中,则零售商总是倾向于均分享策略;若竞争强度较大且投资效率较高,则零售商选择部分分享策略.当制造商投资效率不等时,零售商更愿意与投资效率较高的制造商分享信息.此外,横向溢出效应更能激励零售商分享信息.     

“互联网$+$”环境下考虑消费者行为的资源回收策略

在“互联网$+$回收”环境下,考虑人们对传统回收渠道以及网络回收渠道的态度,建立基于不同消费者行为的回收模型,研究传统回收商、网络回收商和再制造商对再生资源的回收策略.研究结果表明:在竞争回收时,网络消费者比例和普通消费者对网络回收渠道的接受程度同时影响定价决策,且网络消费者比例越高回收价格越低,普通消费者对网络回收渠道的接受程度越高回收价格越低;在联盟回收时,回收价格不受网络消费者比例和普通消费者接受程度的影响,回收商收益增加,但再制造商的收益受损.再制造商为了减少损失,可以设计收益分配机制与回收商进行合作,增加供应链收益.根据模型分析,认为联盟回收是最佳回收方式,政府应整合上下游企业,推动“互联网$+$回收”平台化、规模化发展.     

基于消费者时间偏好和决策者风险偏好的定价与订货策略*

在供应链管理过程中, 消费者时间偏好和决策者风险偏好是影响产品定价与订货决策的两个重要因素。本文以累积前景理论为框架, 将消费者时间偏好与价格依赖等影响产品市场需求的因素和决策者风险偏好与参考依赖等影响决策的因素共同纳入模型考量范围, 建立了基于消费者的时间偏好和决策者风险偏好的定价与订货模型。研究表明：随着消费者时间偏好的增大, 产品的最优定价和订货量都将减少;随着决策者心理参考点的增大, 产品的最优定价降低,最优订货量增加;随着决策者损失规避程度的增大, 产品最优定价增加, 而最优订货量减少。考虑消费者时间偏好和决策者的风险偏好的定价与订货模型能够提高供应链中决策者的最大累积前景效用。     

考虑成员企业风险态度的制造商资金约束闭环供应链定价与回收决策

针对制造商资金约束的闭环供应链,考虑制造商、零售商和回收商面对市场需求不确定性表现出不同的风险态度,研究闭环供应链如何确定其最优定价与回收决策.首先,依据均值-方差法给出制造商、零售商、回收商和闭环供应链的效用函数;然后,基于博弈论的思想分别确定集中式决策下闭环供应链的最优策略和效用,以及分散式决策下制造商、零售商和回...     

Markup pricing strategies between a dominant retailer and competitive manufacturers

Markup pricing contracts have been widely employed in many industries. Under such contracts, a retailer charges a retail margin over the wholesale price levied by the supplier to guarantee her financial prudence. In a setting where two competitive manufacturers sell substitutable products through a common dominant retailer, we investigate and compare performance of two different markup arrangements, namely, percentage and dollar, under the deterministic and stochastic demand situations, respectively. We find that, no matter what the demand characteristic is, when the retailer switches from dollar to percentage markup, the retailer makes a higher profit while the manufacturers suffer, because the switching forces manufacturers charge lower wholesale prices and thus leads to lower retail prices. Moreover, under the deterministic demand situation, the switching brings about a larger order quantity and a higher channel profit. Under the stochastic demand situation, however, the effect of the switching on order quantity and channel profit depends on manufacturer differentiation and retailer efficiency: order quantity (channel profit) becomes smaller (lower), as manufacturer differentiation becomes weaker or retailer efficiency becomes higher. And, the demand uncertainty intensifies the effect.     

Location equilibria for a continuous competitive facility location problem under delivered pricing

The problem of finding location equilibria of a location-price game where firms first select their locations and then set delivered prices in order to maximise their profits is investigated. Assuming that firms set the equilibrium prices in the second stage, the game can be reduced to a location game for which a global minimiser of the social cost is a location equilibrium, provided that the demand is completely inelastic and the marginal production cost is constant. When the set of feasible locations is a region of the plane the minimisation of the social cost becomes a hard-to-solve global optimisation problem. We propose an exact interval branch-and-bound algorithm suitable for small and medium size problems and an alternating Weiszfeld-like heuristic for larger instances. The latter approach is based on a new iterative formula for which the validity of the descent property is proved. The proposed heuristic performs extremely well against the exact method when tested on small to medium size instances while requiring a tiny fraction of its computational time.     

Bilevel competitive facility location and pricing problems

We propose new models for competitive facility location and pricing as bilevel Boolean linear programming problems. We obtain results that characterize the complexity of the problem where a monopolist’s profit on each of the markets is defined with a monotone nonincreasing function of the servicing cost. For this problem, we also propose two approximate algorithms based on the ideas of alternating heuristics and local search. We give results of a computational experiment that show a possibility for fast computation of approximate solutions.     

A reinforcement learning approach to competitive ordering and pricing problem

This study analyses simultaneous ordering and pricing decisions for retailers working in a multi‐retailer competitive environment for an infinite horizon. Retailers compete for the same market where the market demand is uncertain. The customer selects the winning agent (retailer) in each term on the basis of random utility maximization, which depends primarily on retailer price and random error. The complexity of the problem is increased by competitiveness, necessity for simultaneous decisions and uncertainty in the nature of increases, and is not conducive to examination using standard analytical methods. Therefore, we model the problem using reinforcement learning (RL), which is founded on stochastic dynamic programming and agent‐based simulations. We analyse the effects of competitiveness and performance of RL on three different scenarios: a monopolistic case where one retailer employing a RL agent maximizes its profit, a duopolistic case where one retailer employs RL and another utilizes adaptive pricing and ordering policies, and a duopolistic case where both retailers employ RL.     

Acquisition and pricing strategies in hybrid manufacturing-remanufacturing systems

There are two typical cases of acquisition and remanufacturing in a closed-loop supply chain: The third party remanufacturer (3PR) and the original equipment manufacturer (OEM) separately acquire and remanufacture used products. The used products have different qualities, and they can be classified for acquisition in reality. In this paper, under the grading acquisition mode, we compare the acquisition strategies of used products and the pricing strategies of new products and remanufactured products in different manufacturing-remanufacturing systems. Then we further study the impact of the timing of remanufacturing on the profit and the environment. From an environmental perspective, the 3PR is willing to acquire and remanufacture used products at the best grade, whereas the OEM may choose more grades. The latter can reduce environmental impact. From an economic perspective, as long as the total cost of acquiring and remanufacturing used products does not exceed the threshold, remanufacturing can bring more profit for the OEM than only selling new products. Moreover, when consumers’ preference for remanufactured products is relatively high, and the total cost of acquisition and remanufacturing does not exceed the threshold, the OEM can engage in remanufacturing business before the new products exit from the market.     

Leading strategies in competitive on-line prediction

We start from a simple asymptotic result for the problem of on-line regression with the quadratic loss function: the class of continuous limited-memory prediction strategies admits a “leading prediction strategy”, which not only asymptotically performs at least as well as any continuous limited-memory strategy, but also satisfies the property that the excess loss of any continuous limited-memory strategy is determined by how closely it imitates the leading strategy. More specifically, for any class of prediction strategies constituting a reproducing kernel Hilbert space, we construct a leading strategy, in the sense that the loss of any prediction strategy whose norm is not too large is determined by how closely it imitates the leading strategy. This result is extended to the loss functions given by Bregman divergences and by strictly proper scoring rules.     

IT strategies: beyond competitive advantage

During the 1980s, we saw considerable energy being expended in the search for the Holy Grail of competitive advantage from information technology (IT). There were many academic papers published on the topic and consultants grew rich from their efforts to persuade companies to invest in strategic information systems. The topic itself rose to become one of the top two information systems management issues identified by IT directors and senior IT executives in the USA, and many organizations sought to replicate the success stories of American and United Airlines, Thomson Holidays, Frito-Lay, Otis Elevators, Mrs Field's Cookies and all the other celebrated cases that have entered the information systems mythology.In the cold light of the 1990s, however, much of this mythology has begun to pale. Were the success stories as real as they were first reported? Where is the sustainable advantage from IT? And if the stories were indeed real, to what extent were they planned or merely serendipitous?This editorial reflects on some of the more recent evidence available and raises some key points for debate in this important aspect of information systems management. It attempts to answer the question: What comes after competitive advantage? in terms of the on-going development of the topic ‘IT strategy’.     

BOPS渠道下制造商优惠券投放决策和零售商增值服务策略演化研究

为了合力开通BOPS渠道,制造商进行优惠券促销,零售商决定是否提供增值服务,构建单次Bertrand- Stackelberg博弈模型和单种群零售商对称性演化博弈模型,以此分析一般均衡结果和零售商群体的演化稳定策略.可以发现:不同策略组合下的双寡头零售商具备“囚徒困境”的博弈特征,制造商能够以批发定价和优惠券面值双重调控零售商的定价行为和服务策略选择;提供增值服务是零售商群体存在的唯一演化稳定策略,参数的变动影响演化稳定区域的大小;在引入价格偏好特征的拓展模型中,零售商群体只会达成混合策略演化均衡,且群体中选择提供增值服务策略的零售商数量始终只占较小比例.     

Internal pricing strategies design and simulation in virtual enterprise formation

A virtual enterprise (VE) is an organization intended to cope with the rapidly changing manufacturing environment. Organization building is important in virtual domains because it has largely been affecting the success of VEs. However, the process of forming a VE is based on self-determination by the participants. This paper adopts a bargaining model under a scenario of incomplete information to formalize the formation process, considers the characteristics of the VE formation process, presents the pricing strategies for the corresponding bargaining, and verifies the correctness and validity of the pricing strategies using computer simulation. This paper breaks through the relative research that compares the formation process with partner selection from the core enterprise’s perspective and also provides the basis for the intelligent information platform of VE, whose key part is pricing software.