DISRUPTION MANAGEMENT FOR SUPPLY CHAIN COORDINATION WITH EXPONENTIAL DEMAND FUNCTION

The coordination problem of a supply chain comprising one supplier and one retailer under market demand disruption is studied in this article. A novel exponential demand function is adopted, and the penalty cost is introduced explicitly to capture the deviation production cost caused by the market demand disruption. The optimal strategies are obtained for different disruption scale under the centralized mode. For the decentralized mode, it is proved that the supply chain can be fully coordinated by adjusting the price discount policy appropriately when disruption occurs. Furthermore, the authors point out that similar results can be established for more general demand functions that represent different market circumstances if certain assumptions are satisfied.

Supply Chain Coordination with Demand Disruptions under Convex Production Cost Function

This paper investigates the problem of how to handling demand disruptions ina one-supplier-one-retailer supply chain, where production cost is a convex function of productionquantity andprice-demand relationship is linear. Our results show that, ifdemand is disrupted, underthe new price-demand relationship, all-unit wholesale quantity discount policies combiningcapacitated linear pricingpolicies can also fully coordinate the supply chain.

The Strategic Analysis of Demand Forecast-Sharing in a Hybrid-Format Online Platform Supply Chain

This paper examines the optimal forecast-sharing strategy in a hybrid-format online platform supply chain where a supplier sells a product through agency format and reselling format provided by a platform retailer who possesses demand forecasts from two channels.Forecast asymmetry and co-opetitive relationship arise between the platform retailer and the supplier,which affect their operational decisions and the supply chain’s performance.To improve supply chain efficiency,we compare different forecast-sharing strategies(i.e.,no forecast sharing,sharing a single forecast,and sharing two forecasts),and analyze the effects of co-opetitive parameters on the optimal forecast-sharing strategy.Our analysis shows that forecast sharing is always beneficial to the supplier,and sharing two forecasts is more beneficial than sharing a single forecast.Whereas for the platform retailer and the whole supply chain,forecast sharing is beneficial only under certain conditions,depending on the co-opetitive parameters.The optimal forecast-sharing strategy is the result of a combination of the negative effect of double marginalization in reselling channel and the positive effect of responding pricing to demand uncertainty in agency channel.We illustrate the parameter regions of the platform retailer’s voluntary sharing,contract sharing,and no sharing,and also find that higher channel competition intensity,higher market share of agency channel,and higher commission rate can promote the platform retailer’s voluntary sharing.Our study extends the research scope of demand forecast-sharing and sheds light on the decision-making processes for managing a hybrid-format online platform supply chain.

AGENT-BASED WORKFLOW COORDINATION FOR SUPPLY CHAIN MANAGEMENT

To align customer demand with suppliers for reducing work in process and supply costs and increasing re sp onsiveness to customer requirements, a real time collaborative supply chain mana gement system is essential. A solution to the realization of supply chain manage ment capable of timely responding to customer requirements is proposed. Workflow automation is used to manage process interaction across enterprises; Agents can be automatically invoked by supply chain workflow process and are used to pro mote the flexibility and reconfigurability by providing the mechanism in support of distributed compution in an enterprises to meet the requirements of performa nce and business dynamics. An approach that supports agent based workflow proce ss in a supply chain is proposed. And the coordination mechanism between agents is also discussed.

Revenue-sharing contract to coordinate independent participants within the supply chain

To improve the performance of the supply chain with one supplier and multiple retailers under deterministic price-sensitive customer demand, an optimal strategy is proposed based on knowledge discovery. First the decentralized system in which the supplier and the retailers are independent, profit-maximizing participants with the supplier acting as a Stackelberg game leader is studied. Numerical examples illustrate the importance of the coordination. The conventional quantity discount mechanism needs to be modified to coordinate the supply chain, so a revenue-sharing contract is proposed to coordinate such supply chain. Lastly, a special decision under certain demand rates is studied. The pricing and replenishment policies can be decided sequentially, which yields much less loss comparing with optimal decision when the demand rates are sufficiently large.

Supply Chain Network Equilibrium with Revenue Sharing Contract under Demand Disruptions

Contract is a common and effective mechanism for supply chain coordination,which has been studied extensively in recent years.For a supply chain network model,contracts can be used to coordinate it because it is too ideal to obtain the network equilibrium state in practical market competition.In order to achieve equilibrium,we introduce revenue sharing contract into a supply chain network equilibrium model with random demand in this paper.Then,we investigate the influence on this network equilibrium state from demand disruptions caused by unexpected emergencies.When demand disruptions happen,the supply chain network equilibrium state will be broken and change to a new one,so the decision makers need to adjust the contract parameters to achieve the new coordinated state through bargaining.Finally,a numerical example with a sudden demand increase as a result of emergent event is provided for illustrative purposes.

Dynamic Analysis of Supply and Demand Coupling of Ecosystem Services in Loess Hilly Region:A Case Study of Lanzhou,China

The relationship between the supply and demand for ecosystem services(ESs)is a key issue for the rational allocation of natural resources and optimisation of sustainable development capacity.This paper investigateed the dynamic evolution features of supply and demand of four ESs in Lanzhou of China,namely,water supply,food supply,carbon fixation and soil retention services.The crosssectional data of 2005 and 2017 were used for calculating ESs value and its supply and demand through ArcGIS software,InVEST model,elastic coefficient model and coupling coordination model.Results showed that:1)from 2005 to 2017,the supply of water supply services increased,the demand of soil retention services decreased,and the supply and demand of food supply and carbon fixation services increased.The high-value areas of service supply were mainly distributed in the rocky mountain areas in the southeast and northwest with high vegetation coverage,while the high-value areas of demand were mainly distributed in the urban areas and surrounding areas with high population density.2)There were five different types of coupling relations.Water supply service was dominated by a negative coupling type D,which means that the decrease in demand for ESs has had a positive response on the supply of ESs.Negative coupling type C was the main type of food supply and carbon fixation services,which means that the increase in demand for ESs has had a negative response on the supply of ESs.All three services were supplemented by a positive coupling type A,which means that the increase in demand for ESs has had a positive response on the supply of ESs.Soil retention service generally exhibits a positive coupling type B,which means that the decrease in demand for ESs has had a negative response on the supply of ESs.3)Over the past 12 yr,the coordination degree of supply and demand of water supply,food supply and soil retention services decreased,and the coordination degree of carbon fixation service increased.Various types of ES had a low degree of coupling and coordination,showing different characteristics of temporal and spatial evolution.The areas with imbalanced ESs supply and demand were mainly distributed in urban areas dominated by construction land.The research results are valuable to the optimisation of urban and rural ecological environments and the sustainable development of territory space under the framework of ecological civilisation,including similar ecologically vulnerable areas in other developing countries.

Spatial matching and flow in supply and demand of water provision services: A case study in Xiangjiang River Basin

Global climate change and increased human consumption have aggravated the uneven spatiotemporal distribution of watershed water resources, affecting the water provision supply and demand state. However, this problem has often been ignored. The present study used the Xiangjiang River basin(XRB) as the study area, and the Integrated Valuation of Ecosystem Services and Trade-offs(InVEST) model, demand quantification model,supply–demand ratio, and water flow formula were applied to explore the spatial heterogeneity, flow, and equilibrium between water supply and demand. The results demonstrated significant spatial heterogeneity in the upstream, midstream, and downstream regions.The areas of water shortage were mainly located the downstream of the Changsha–Zhuzhou–Xiangtan urban agglomeration, and the Hengyang basin was the most scarcity area. Affected by terrain gradients and human needs, water flow varied from-16.33 × 10^(8) m^(3) to 13.69 × 10^(8) m^(3)from the upstream to the downstream area, which provided a possibility to reduce spatial heterogeneity. In the future, measures such as strengthening water resource system control,sponge city construction, and dynamic monitoring technology should be taken to balance the supply and demand of water in different river sections of the basin. This study can provide references for regulating water resources allocation in different reaches of the basin.

Supply chain coordination mechanisms under asymmetric information with retailer cost disruptions

A two-level supply chain model involving one supplier and one retailer with linear demand is developed, and supply chain coordination mechanisms under asymmetric information （the retailer＇ s cost structure is asymmetric information） are proposed by employing game theory in two scenarios： coordination mechanisms under asymmetric information in a regular scenario （without disruption）; and coordination mechanisms under asymmetric information in an irregular scenario （ with retailer cost disruptions）. It is optimal for the supply chain to maintain the original production plan and to guarantee a steadily running system if variations of retailer costs are sufficiently low and do not exceed an upper bound. This shows that the original production plan has certain robustness under disruptions. Decisions must be re-made if a retailer＇ s cost change is greater and exceeds an upper bound. Impacts of retailer cost disruptions on the order quantity, the retail price, the wholesale price and each party＇ s as well as the system＇ s expected profits are investigated through numerical analyses.

Optimal pricing and production decisions in a supply chain with e-marketplace

The concept of the e-marketplace is introduced.Considering a supply chain with a single manufacturer who sells a single item in an e-marketplace,an analytical model for the use of the e-marketplace in a supply chain is provided.Assuming the market demand is stochastic and price-dependent,the conditions under which the manufacturer and the e-marketplace owner share the market in equilibrium is developed.The existence and uniqueness of the optimal selling price,quantity and transaction percentage are proved.An integrated supply chain is put forward,and then the efficiency of supply chain coordination is studied by comparing the integrated supply chain with the decentralized supply chain.To gain further insights on the theoretical models,extensive simulations are then carried out.

SUPPLY CHAIN DISRUPTION MANAGEMENT WITH MULTIPLE COMPETING RETAILERS

As for the supply chain consisting of a manufacturer and multiple competing retailers, the disruption management decision is considered for the demand disruption that both the investment sensitivity coefficient and the investment-elasticity are changed simultaneously. Meanwhile, the corresponding solutions are given for different cases of the disruption, and the characteristics of the solutions are analyzed. The production plan is proved to he robustness under certain conditions, and the production plan of the coordination strategy is investigated for the disruption with appropriate contractual arrangement, i. e. , a subside rate schedule. Mutual restraints exist between the changed investment sensitivity coefficient and the investment-elasticity when the coordination mecha- nism is used. And the more the number of the retailers in the system, the more the subside provided by the suppler on the coordinaton strategy.

The effect of supply disruption in a two-layer supply chain with one retailer and two suppliers with promotional effort under random demand

This paper considers a closed-loop supply chain comprising one retailer and two suppliers.It assumes one supplier as the main supplier and another as the backup.The coordination issue of the supply chain has been discussed in this work.The main supplier’s yield is considered subject to disruption.The demand considered here is stochastic.We aim to calculate the supplier’s optimum production quantity.Similarly,the retailer’s optimal ordering quantity is found out.Additionally,in the centralized supply chain model,we want to maximize the expected profit under certain restriction.Numerical illustrations are discussed to the benefit some characteristic insights over the supply chain model.

Supply chain decisions and coordination in the presence of an imperfect spot market

This study considers a supply chain consisting of a commodity supplier and a final product manufacturer with uncertain demand.In addition to purchasing from the supplier through a forward contract,the manufacturer can adjust their inventory by trading the commodity in an online spot market after observing the actual demand.However,the spot market is imperfect in that transactions cannot be certainly realized and come with additional transaction costs.Furthermore,the spot price is volatile such that overly relying on the spot market is unwise.To investigate how the spot market affects the decisions and coordination in a supply chain,we develop a game-theoretical model incorporating spot trading.We derive the optimal ordering decision in a centralized supply chain,as well as the supplier's and manufacturer's equilibrium pricing and ordering decisions in a decentralized supply chain.The impact of the imperfect spot market on the optimal decisions and profits is analyzed.This study also demonstrates how the supply chain can be coordinated in the presence of an imperfect spot market.Finally,a numerical analysis is performed to examine the analytical results.Our results indicate that the spot market can generally improve the performance of the centralized supply chain and benefit the manufacturer in the decentralized one.However,it can be detrimental to the supplier.The supply chain can be coordinated by a revenue-sharing contract,and both parties'profits can be improved.Our findings suggest that the manufacturer could take advantage of the spot market,and the supplier should attempt to integrate or coordinate the supply chain to share the benefits of spot trading.

A combined forecasting method for intermittent demand using the automotive aftermarket data

Intermittent demand forecasting is an important challenge in the process of smart supply chain transformation,and accurate demand forecasting can reduce costs and increase efficiency for enterprises.This study proposes an intermittent demand combination forecasting method based on internal and external data,builds intermittent demand feature engineering from the perspective of machine learning,predicts the occurrence of demand by classification model,and predicts non-zero demand quantity by regression model.Based on the strategy selection on the inventory side and the stocking needs on the replenishment side,this study focuses on the optimization of the classification problem,incorporates the internal and external data of the enterprise,and proposes two combination forecasting optimization methods on the basis of the best classification threshold searching and transfer learning,respectively.Based on the real data of auto after-sales business,these methods are evaluated and validated in multiple dimensions.Compared with other intermittent forecasting methods,the models proposed in this study have been improved significantly in terms of classification accuracy and forecasting precision,which validates the potential of combined forecasting framework for intermittent demand and provides an empirical study of the framework in industry practice.The results show that this research can further provide accurate upstream inputs for smart inventory and guarantee intelligent supply chain decision-making in terms of accuracy and efficiency.

THE DEMAND DISRUPTION MANAGEMENT PROBLEM FOR A SUPPLY CHAIN SYSTEM WITH NONLINEAR DEMAND FUNCTIONS

This paper addresses the problem of handling the uncertainty of demand in a one-supplier-one-retailer supply chain system. Demand variation often makes the real production different from what is originally planned, causing a deviation cost from the production plan. Assume the market demand is sensitive to the retail price in a nonlinear form, we show how to effectively handle the demand uncertainty in a supply chain, both for the case of centralized-decision-making system and the case of decentralized-decision-making system with perfect coordination.

Research on two-part revenue-sharing contract under demand disruption

Assuming that the realized demand is determined by the inventory level,a two-part revenue sharing contract of one supplier and one retailer is analyzed under the circumstance of demand disruption(the disruption cost occurs at the supplier).Based on the centralized optimization,the profits of the two members are maximized in sequential optimization though a two-part revenue-sharing contract.The result shows that when the demand disruption occurs,if the degree of disruption is within some range,the ordering and manufacturing plans need not be changed,while only the revenue sharing fraction for the retailer should be diminished;if not,both the plan and the revenue sharing fraction should be changed for the possible coordination of the supply chain.Finally,numerical illustrations of the contract for various scenarios are given.

Properties of Nash Equilibrium Retail Prices in Contract Model with a Supplier, Multiple Retailers and Price-Dependent Demand

Recently, price contract models between suppliers and retailers, with stochastic demand have been analyzed based on well-known newsvendor problems. In Bernstein and Federgruen [6], they have analyzed a contract model with single supplier and multiples retailers and price dependent demand, where retailers compete on retail prices. Each retailer decides a number of products he procures from the supplier and his retail price to maximize his own profit. This is achieved after giving the wholesale and buy-back prices, which are determined by the supplier as the supplier’s profit is maximized. Bernstein and Federgruen have proved that the retail prices become a unique Nash equilibrium solution under weak conditions on the price dependent distribution of demand. The authors, however, have not mentioned the numerical values and proprieties on these retail prices, the number of products and their individual and overall profits. In this paper, we analyze the model numerically. We first indicate some numerical problems with respect to theorem of Nash equilibrium solutions, which Bernstein and Federgruen proved, and we show their modified results. Then, we compute numerically Nash equilibrium prices, optimal wholesale and buy-back prices for the supplier’s and retailers’ profits, and supply chain optimal retailers’ prices. We also discuss properties on relation between these values and the demand distribution.

A Study on an Extensive Hierarchical Model for Demand Forecasting of Automobile Components

Demand forecasting and big data analytics in supply chain management are gaining interest.This is attributed to the wide range of big data analytics in supply chain management,in addition to demand forecasting,and behavioral analysis.In this article,we studied the application of big data analytics forecasting in supply chain demand forecasting in the automotive parts industry to propose classifications of these applications,identify gaps,and provide ideas for future research.Algorithms will then be classified and then applied in supply chain management such as neural networks,k-nearest neighbors,time series forecasting,clustering,regression analysis,support vector regression and support vector machines.An extensive hierarchical model for short-term auto parts demand assess-ment was employed to avoid the shortcomings of the earlier models and to close the gap that regarded mainly a single time series.The concept of extensive relevance assessment was proposed,and subsequently methods to reflect the relevance of automotive demand factors were discussed.Using a wide range of skills,the factors and co-factors are expressed in the form of a correlation characteristic matrix to ensure the degree of influence of each factor on the demand for automotive components.Then,it is compared with the existing data and predicted the short-term historical data.The result proved the predictive error is less than 6%,which supports the validity of the prediction method.This research offers the basis for the macroeconomic regulation of the government and the production of auto parts manufacturers.

Determination of Effectiveness of Energy Management System in Buildings

Building Energy Management Systems(BEMS)are computer-based systems that aid in managing,controlling,and monitoring the building technical services and energy consumption by equipment used in the building.The effectiveness of BEMS is dependent upon numerous factors,among which the operational characteristics of the building and the BEMS control parameters also play an essential role.This research develops a user-driven simulation tool where users can input the building parameters and BEMS controls to determine the effectiveness of their BEMS.The simulation tool gives the user the flexibility to understand the potential energy savings by employing specific BEMS control and help in making intelligent decisions.The simulation is developed using Visual Basic Application(VBA)in Microsoft Excel,based on discrete-event Monte Carlo Simulation(MCS).The simulation works by initially calculating the energy required for space cooling and heating based on current building parameters input by the user in the model.Further,during the second simulation,the user selects all the BEMS controls and improved building envelope to determine the energy required for space cooling and heating during that case.The model compares the energy consumption from the first simulation and the second simulation.Then the simulation model will provide the rating of the effectiveness of BEMS on a continuous scale of 1 to 5(1 being poor effectiveness and 5 being excellent effectiveness of BEMS).This work is intended to facilitate building owner/energy managers to analyze the building energy performance concerning the efficacy of their energy management system.

数字经济重塑经济循环模式:理论逻辑与推进路径

畅通经济循环是构建新发展格局的关键任务,而供需协同是构建高水平经济循环的关键环节。传统经济循环模式面临结构失衡导致循环动力不足、投资效益低下导致循环路径不畅的现实约束,因而不可持续。随着中国经济进入新发展阶段,数字经济成为推动供需协同、重塑经济循环模式的重要抓手。数据要素的内嵌性与数字技术赋能的广泛性,使得数字经济呈现高渗透性、高融合性、高创新性等特征,能够有效统筹供需两端,推动供需协同。数字经济通过赋能扩大内需和优化供给,推动实现经济循环规模的合理增长;通过重塑技术进步机制和收入增长机制,推动实现经济循环质量的有效提升;通过推动经济循环的中心从生产转向消费、正向激励从投资扩张转向消费升级,形成良性经济循环。为了加快数字经济重塑经济循环模式的进程,需要推动数据要素市场化,筑牢广泛赋能基础;加快数实深度融合,拓展经济增长空间;加强数字经济与技术创新有效互动,提高自主创新能力;促进数字经济与共同富裕有机结合,优化收入分配格局。