The impact of supervisory monitoring on high-end retail sales productivity

Based on a two-stage analysis of a panel of data on 12 outlets of a high-end retailer for 24 months, we investigate how the level of supervisory monitoring affects retail sales productivity. In the first stage, we use Data Envelopment Analysis (DEA) to compute the relative productivity of retail outlets in using their labor and capital resources to generate store sales. In the second stage, we regress the logarithm of DEA scores on contextual variables to obtain consistent estimators of the impact of contextual variables on productivity (Banker and Natarajan in Operation Research 56:48–58, 2008). Contrary to agency theoretic prediction that supervisory monitoring leads to an increase in retail sales productivity, our empirical results indicate that the higher the level of supervisory monitoring, the lower is the retail sales productivity for high-end retail outlets.     

The Application of the Automatic Interaction Detector (A.I.D.) Programme and Multiple Regression Techniques to the Assessment of Store Performance and Site Selection

The paper begins with an examination of the gravity model approach to site selection and concludes that there are certain practical limitations which make it unsuitable for predicting the distribution of consumers' expenditure amongst individual outlets.It then describes how a combination of the Automatic Interaction Detector (A.I.D.) and multiple regression techniques can be used to provide criteria for judging the performance of a chain of retail outlets and assessing the potential of new sites. A feature of the approach is the measurement of approximately fifty factors which may influence turnover and the inclusion of attitudinal data, derived from a sample survey of shoppers, quantifying factors such as the appearance and image of a store. The method has been successfully applied to supermarkets, durable goods outlets, off-licences, chemists, building societies and car washes.     

Bicriterion Programs and Managerial Location Decisions: Application to the Banking Sector

In the design of a new urban retail network, the size of each office can be determined — once the number and the location of outlets have been fixed — by means of a location-allocation model. In order to carry out this task, two different solutions have been considered: the best solution in the opinion of the firm's managers and the solution obtained by maximizing the outlets' accessibility, based on a spatial interaction model. Our biobjective program bridges the gap between both solutions by enabling the generation of a finite set of non-inferior points, and constitutes, therefore, a valuable decision-support tool. The paper closes with a case study in the banking sector.     

Forecasting newspaper demand with censored regression

Newspaper circulation has to be determined at the level of the individual retail outlets for each of the editions to be sold through such outlets. Traditional forecasting methods provide no insight into the impact of the service level: defined as the probability that no out-of-stock will occur. The service level results in out-of-stock situations, causing missed sales and oversupply or returns. In our application management sets a policy aiming at a 97% service level. The forecasting system developed provides estimates for excess deliveries and for the expected shortages. The results compare favourably to the traditional moving average approach previously employed by the publisher. Censored regression is a natural approach to the newspaper problem. It provides information on key policy variables and it is relatively simple to integrate into the distribution policy, with only small adaptations to the existing forecasting and distribution policy.     

A multi-objective evolutionary algorithm for facility dispersion under conditions of spatial uncertainty

Avoiding concentration or saturation of activities is fundamental in many environmental and urban planning contexts. Examples include dispersing retail and restaurant outlets, sensitivity to impacts in forest utilization, spatial equity of waste disposal, ensuring public safety associated with noxious facilities, and strategic placement of military resources, among others. Dispersion models have been widely applied to ensure spatial separation between activities or facilities. However, existing approaches rely on deterministic approaches that ignore issues of spatial data uncertainty, which could lead to poor decision making. To address data uncertainty issues in dispersion modelling, a multi-objective approach that explicitly accounts for spatial uncertainty is proposed, enabling the impacts of uncertainty to be evaluated with statistical confidence. Owing to the integration of spatial uncertainty, this dispersion model is more complex and computationally challenging to solve. In this paper we develop a multi-objective evolutionary algorithm to address the computational challenges posed. The proposed heuristic incorporates problem-specific spatial knowledge to significantly enhance the capability of the evolutionary algorithm for solving this problem. Empirical results demonstrate the performance superiority of the developed approach in supporting facility and service planning.     

需求受价格影响的三层供应链协调模型

针对由一个制造商、一个批发商和一个零售商构成的三层供应链系统,在随机市场需求且需求受商品零售价格影响的情况下,研究了零售商如何定价和确定订货量.在此基础上给出了一个能使供应链系统达到完美协调的收益分享合约策略,最后给出了数值例子.     

Combined location-routing problems—a neural network approach

While in location planning it is often assumed that deliveries are made on a direct-trip basis, in fact deliveries, e.g., to the different supermarkets belonging to a specific chain or to retail outlets of any kind, usually are performed as round-trips. Therefore, it is often necessary to combine the two issues of locating a depot and of planning tours in one problem formulation.In this paper, a neural network approach based on a self-organizing map is proposed for solving such single-depot location-routing problems in the plane. The results derived by this approach are compared with those which can be found by different well-known heuristics, and it is shown that the self-organising map approach competes well with these concepts. Moreover, some modifications which rely on ideas from Tabu Search can be shown to be especially useful for increasing the number of feasible solutions found by the self-organising map approach. Finally, the implementation of the Weiszfeld procedure for a final improvement of the optimal depot location proves to be a useful device.     

Designing two-echelon supply networks

A modern distribution network design model needs to deal with the trade-offs between a variety of factors, including (1) location and associated (fixed) operating cost of distribution centers (DCs), (2) total transportation costs, and (3) storage holding and replenishment costs at DCs and retail outlets. In addition, network design models should account for factors such as (4) stockouts, by setting appropriate levels of safety stocks, or (5) capacity concerns, which may affect operating costs in the form of congestion costs. The difficulty of making such trade-offs is compounded by the fact that even finding the optimal two-echelon inventory policy in a fixed and uncapacitated distribution network is already a hard problem. In this paper, we propose a generic modeling framework to address these issues that continues and extends a recent stream of research aimed at integrating insights from modern inventory theory into the supply chain network design domain. Our approach is flexible and general enough to incorporate a variety of important side constraints into the problem.     

Estimating the Effect of Variety on Sales

The short-term relationship between the sales of consumer durables by a chain of retail outlets and the amount of variety is determined by two different methods. One method uses the sales lost because of non-availability and the other uses sales assistants' subjective estimates of the probability of selling purchasers an alternative brand if the one bought was unavailable. The two techniques are compared and the implications of the results for inventory policies are indicated.     

深圳蔬菜安全风险评估与抽样检验方案设计

运用模糊数学模型和食品安全指数IFS模型进行安全风险评估,对深圳市新鲜蔬菜批发市场、农贸市场、超市及零售店等常规渠道与其他输入渠道进行模糊评价,得出食品安全风险等级,构建了蔬菜安全风险评估层次结构模型,评估出深圳市新鲜蔬菜安全风险较高。对已有的抽样方案进行改进,设计了两套深圳市新鲜蔬菜抽样检验方案,分别适用于深圳市所有的蔬菜交易市场和销售蔬菜的超市、零售店以及蔬菜产地、蔬菜加工厂的样本抽取及实验室试样的制备。     

The use of simple calibrations of individual locations in making transshipment decisions in a multi-location inventory network

Demands occur at each location in a network of stock-holding retail outlets. Should a location run out of stock between successive replenishments, then subsequent demands may be met either by transshipping from another location in the network or by an emergency supply from a central depot. We deploy an approximate stochastic dynamic programming approach to develop a class of interpretable and implementable heuristics for making transshipment decisions (whether and from where to transship) which make use of simple calibrations of the candidate locations. The calibration for a location depends upon its current stock, the time to its next replenishment and the identity of the location needing stock. A numerical investigation shows strong performance of the proposed policies in comparison with standard industry practice (complete pooling, no pooling) and a recently proposed heuristic. It points to the possibility of substantial cost savings over current practice.     

Supply chain scheduling: Just-in-time environment

We study the benefits of coordinated decision making in a supply chain consisting of a manufacturer, a distributor, and several retailers. The distributor bundles finished goods produced by the manufacturer and delivers them to the retailers to meet their demands. The distributor is responsible for managing finished goods inventory. An optimal production schedule of the manufacturer, if imposed on the distributor, may result in an increased inventory holding cost for the distributor. On the other hand, an optimal distribution schedule of the distributor, if imposed on the manufacturer, may result in an increased production cost for the manufacturer. In this paper we develop mathematical models for individual optimization goals of the two partners and compare the results of these models with the results obtained for a joint optimization model at the system level. We investigate the computational complexities of these scheduling problems. The experimental results indicate that substantial cost savings can be achieved at the system level by joint optimization. We also study conflict and cooperation issues in the supply chain. The cost of conflict of a supply chain partner is a measure of the amount by which the unconstrained optimal cost increases when a decision is to be made under the scheduling constraint imposed by the other partner. We quantify these conflicts and show that the cost of conflicts are significant. We also show that a cooperative decision will generate a positive surplus in the system which can be shared by the two partners to make cooperation and coordination strategy more attractive.     

带批次和临时库存的越库配送车辆路径问题研究

从零售业供应链整合入手,构建供应商、配送中心和零售点构成的协同配送网络,研究带批次和临时库存的越库配送车辆路径问题.将越库过程分为取货、分拣和配货三个阶段,考虑配送中心分拣能力,分批次设置车辆协同到达配送中心的服务时刻,据此建立以最小化车辆运输成本、临时库存成本和固定成本为目标的数学模型.考虑问题特征,设计一种混合变邻域搜索粒子群算法求解,并将结果进行横纵向比较.结果表明,所提算法有效且可靠,能够为带批次和临时库存的越库配送问题提供解决方案.     

Strategic design of competing supply chain networks for inelastic demand

A model for designing the network of a new entrant supply chain under inelastic demand and in the presence of pre-existing competing chains is proposed. These supply chains provide an identical product for a market area. The model considers the location of distribution centres and retail outlets on a discrete set of potential locations. The assumptions of the model are: (1) static competition between the new and pre-existing chains and (2) a probabilistic customer behaviour based on an attraction function depending on both the location and the quality of the retailers. This model also incorporates the impact of the facilities’ location decisions on the operational inventory and shipment decisions. The resulting model is formulated as a mixed integer non-linear programme (MINLP). To solve the MINLP it is transformed to a linear one. We illustrate the model, discuss the results of a real-world case, and investigate the effectiveness of the proposed algorithm using randomly generated examples.     

The Challenges of Scanner Data

Data capture at point of sale, using laser scanning technology, is now commonplace in retail outlets in developed economies. The volume of data collected is enormous (a single UK grocery superstore carries over 15 000 different lines, each with a unique 13 digit barcode and will sell 600 000 items per week). It has been recognized that, where point of sale data can be translated into meaningful information, there is scope for efficiency savings and exploitable competitive advantage. In UK grocery retailing the uses of scanner data have concentrated on operational aspects such as improved ordering systems and staff scheduling. There have, however, been many recent studies, predominantly in the USA, which have examined, using scanner data, the relationship between marketing variables (price, display, advertising, coupons, and other promotions) and customer purchasing behaviour. This paper presents an overview of these studies and identifies the opportunities for operational researchers to further the understanding of such relationships through modelling and data handling.     

Product allocation to different types of distribution center in retail logistics networks

We consider the problem of assigning stockkeeping units to distribution centers (DCs) belonging to different DC types of a retail network, e.g., central, regional, and local DCs. The problem is motivated by the real situation of a retail company and solved by an MIP solution approach. The MIP model reflects the interdependencies between inbound transportation, outbound transportation and instore logistics as well as capital tied up in inventories and differences in picking costs between the warehouses. A novel solution approach is developed and applied to a real-life case of a leading European grocery retail chain. The application of the new approach results in cost savings of 6% of total operational costs compared to the present assignment. These savings amount to several million euros per year. In-depth analyses of the results and sensitivity analyses provide insights into the solution structure and the major related issues.     

Launching new products through exclusive sales channels

When launching a new product, a manufacturer usually sells it through competing retailers under non-exclusive arrangements. Recently, many new products (cellphones, electronics, toys, etc.) are sold through a single sales channel via an exclusive arrangement. In this paper we present two separate models that examine these two arrangements. Each model is based on a Stackelberg game in which the manufacturer acts as the leader by setting the wholesale price and the retailers act as the followers by choosing their retail prices. For each model, we solve the Stackelberg game by determining the manufacturer’s optimal wholesale price and each retailer’s optimal retail price in equilibrium. Then we examine the conditions under which the manufacturer should sell the new product through an exclusive retailer. In addition, we examine the impact of postponing the wholesale price decision and the impact of demand uncertainty on the manufacturer’s optimal profit under both arrangements.     

基于经销商再制造的闭环供应链政府补贴策略及效果分析

针对制造商负责再制造设计,经销商负责再制造的闭环供应链系统,建立政府无补贴、补贴经销商再制造和补贴制造商再制造设计3种策略下的Stackelberg博弈模型,分析不同补贴策略对供应链成员企业决策的影响。同时,应用数值仿真方法研究相同补贴支出下两种补贴策略的优劣。结果表明:相对于无补贴策略,两种补贴策略均会降低再制品和新产品的销售价格,提高再制品销售量,提升再制造设计水平,并且在再制品需求量小于新产品需求量时均会降低新产品销售量,在再制品和新产品的需求量相等时均会提高新产品销售量;另外,在相同的补贴支出下,当新产品需求量大于再制品需求量时,补贴经销商更能降低两种产品的销售价格和新产品的销售量,提高再制品销售量和制造商与经销商的利润,补贴制造商则更能提升再制造设计水平。     

技术许可下信息分享和政府补贴对闭环供应链的影响分析——基于经销商再制造模式

研究了信息分享对制造商许可经销商从事再制造模式下闭环供应链的影响。分别建立了无信息分享和信息分享下经销商再制造和制造商再制造两种模式下的闭环供应链模型并分析了政府补贴对废旧产品回收量和渠道成员决策的影响。研究发现,当经销商对制造商进行信息分享时,经销商的利润减少,而制造商的利润增加。渠道领导者制造商总是能从再制造活动中抽取利润,在经销商再制造模式下,制造商通过收取许可费分享再制造的利润;在制造商再制造模式下,制造商设定适当的批发价格及回收价格协调正向流和逆向流,从而实现利润最大化。同时表明了政府补贴的刺激会显著地提高废旧产品的回收量。     

A supply chain network equilibrium model with random demands

In this paper, we develop a supply chain network model consisting of manufacturers and retailers in which the demands associated with the retail outlets are random. We model the optimizing behavior of the various decision-makers, derive the equilibrium conditions, and establish the finite-dimensional variational inequality formulation. We provide qualitative properties of the equilibrium pattern in terms of existence and uniqueness results and also establish conditions under which the proposed computational procedure is guaranteed to converge. Finally, we illustrate the model through several numerical examples for which the equilibrium prices and product shipments are computed. This is the first supply chain network equilibrium model with random demands for which modeling, qualitative analysis, and computational results have been obtained.