Modelling category demand in retail chains

This paper is concerned with analysis of retail-chain data on the demand of frequently bought product categories. It is intended to extend the domain of demand analysis to chain-wide data that directly concern retail managers and researchers. The proposed model explores specific structural hypotheses for chain demand and provides a comprehensive framework that admits store heterogeneity, periodic sales variation, chain-wide sales shocks, and sales dynamics. The approach is illustrated in a case study using scanner data from 10 product categories and yields empirical, quantitative insights into the structure of category demand in retail chains. The model determines category elasticities with clear implications for the effectiveness of pricing policy at the retail level and provides a useful tool for applied demand analysis in the modern retail environment.     

Two-stage network constrained robust unit commitment problem

For a current deregulated power system, a large amount of operating reserve is often required to maintain the reliability of the power system using traditional approaches. In this paper, we propose a two-stage robust optimization model to address the network constrained unit commitment problem under uncertainty. In our approach, uncertain problem parameters are assumed to be within a given uncertainty set. We study cases with and without transmission capacity and ramp-rate limits (The latter case was described in Zhang and Guan (2009), for which the analysis part is included in Section 3 in this paper). We also analyze solution schemes to solve each problem that include an exact solution approach and an efficient heuristic approach that provides tight lower and upper bounds for the general network constrained robust unit commitment problem. The final computational experiments on an IEEE 118-bus system verify the effectiveness of our approaches, as compared to the nominal model without considering the uncertainty.     

A fractional programming approach for retail category price optimization

We present a new mixed-integer programming (MIP) approach to study certain retail category pricing problems that arise in practice. The motivation for this research arises from the need to design innovative analytic retail optimization techniques at Oracle Corporation to not only predict the empirical effect of price changes on the overall sales and revenue of a category, but also to prescribe optimal dynamic pricing recommendations across a category or demand group. A multinomial logit nonlinear optimization model is developed, which is recast as a discrete, nonlinear fractional program (DNFP). The DNFP model employs a bi-level, predictive modeling framework to manage the empirical effects of price elasticity and competition on sales and revenue, and to maximize the gross-margin of the demand group, while satisfying certain practical side-constraints. This model is then transformed by using the Reformulation–Linearization Technique in tandem with a sequential bound-tightening scheme to recover an MIP formulation having a relatively tight underlying linear programming relaxation, which can be effectively solved by any commercial optimization software package. We present sample computational results using randomly generated instances of DNFP having different constraint settings and price range restrictions that are representative of common business requirements, and analyze the empirical effects of certain key modeling parameters. Our results indicate that the proposed retail price optimization methodology can be effectively deployed within practical retail category management applications for solving DNFP instances that typically occur in practice.     

病人满意度影响因素的统计分析

本文在文献研究的基础上,选择了可能影响病人满意的27个指标,通过因子分析,把这27个指标综合成了5个因子,即医护人员技术与能力、医护人员的态度、医疗效果、花费、医疗环境和就医(辅助)过程5个方面;论文进一步对这5个方面构成的量表的可靠性作了验证;最后,应用多元回归技术分析了5个因子对病人满意度的影响程度,为医院提高病人满意度提供了科学的依据。     

Strategic interactions in service supply chain with horizontal competition

We analyze strategic interaction issues that arise in service supply chain, such as consulting, service outsourcing, and travel service. To capture strategic interactions in service supply chain, we study a case where there are two service vendors providing competing service products and selling them through a common Service Integrator. In particular, we derive and compare equilibrium solutions (e.g. service prices, wholesale prices, service volumes) for the service supply chain under three different scenarios. We then study the effect of key parameters in the model upon the equilibrium solution using sensitivity analysis, and discuss our results along with a numerical experiment. Finally, future research direction is pointed out.     

A resource allocation queueing fairness measure: properties and bounds

Fairness is an inherent and fundamental factor of queue service disciplines in a large variety of queueing applications, ranging from airport waiting lines to computer queueing systems. We study a newly proposed measure, a Resource Allocation Queueing Fairness Measure (RAQFM), first introduced in Raz, Levy, and Avi-Itzhak (Perform. Eval. Rev. 32(1):130–141, 2004). We analyze the properties of RAQFM and tie them to intuition, provide bounds for its values, and discuss briefly how it yields to analysis. This work was supported in part by the Israeli Ministry of Science and Technology, grant number 380-801, and by EURO-NGI network of excellence.     

Multi-echelon multi-company inventory planning with limited information exchange

Supply chain planning concepts from multi-echelon inventory theory are generally based on some form of centralised planning of supply chains. Those multi-echelon models that do consider decentralised planning, assume complete information and/or a specific single objective function. This paper investigates how multi-echelon inventory theory can accommodate a setting with decentralised decision makers (a supplier and a number of retail groups) without complete information. We present a coordination procedure that does not require the retail groups to exchange demand information, but does allow using opportunities for demand pooling between them. We illustrate our ideas by way of a quantitative analysis of a two-echelon divergent supply chain, with both cooperative and non cooperative retail groups. We conclude that coordination across a supply chain with decentralised control and limited centralised information is feasible by using available algorithms with satisfactory service level and cost performance.     

Pricing surplus server capacity for mean waiting time sensitive customers

We consider a queueing model wherein the resource is shared by two different classes of customers, primary (existing) and secondary (new), under a service level based pricing contract. This contract between secondary class customers and resource manager specifies unit admission price and quality of service (QoS) offered. We assume that the secondary customers’ Poisson arrival rate depends linearly on unit price and service level offered while the server uses a delay dependent priority queue management scheme. We analyze the joint problem of optimal pricing and operation of the resource with the inclusion of secondary class customers, while continuing to offer a pre-specified QoS to primary class customers. Our analysis leads to an algorithm that finds, in closed form expressions, the optimal points of the resulting non-convex constrained optimization problem. We also study in detail the structure and the non-linear nature of these optimal pricing and operating decisions.     

Construction of ODE Curves

This paper deals with a construction problem of free-form curves from data constituted by some approximation points and a boundary value problem for an ordinary differential equation (ODE). The solution of this problem is called an ODE curve. We discretize the problem in a space of B-spline functions. Finally, we analyze a graphical example in order to illustrate the validity and effectiveness of our method.     

A unified framework for harmonic analysis of functions on directed graphs and changing data

We present a general framework for studying harmonic analysis of functions in the settings of various emerging problems in the theory of diffusion geometry. The starting point of the now classical diffusion geometry approach is the construction of a kernel whose discretization leads to an undirected graph structure on an unstructured data set. We study the question of constructing such kernels for directed graph structures, and argue that our construction is essentially the only way to do so using discretizations of kernels. We then use our previous theory to develop harmonic analysis based on the singular value decomposition of the resulting non-self-adjoint operators associated with the directed graph. Next, we consider the question of how functions defined on one space evolve to another space in the paradigm of changing data sets recently introduced by Coifman and Hirn. While the approach of Coifman and Hirn requires that the points on one space should be in a known one-to-one correspondence with the points on the other, our approach allows the identification of only a subset of landmark points. We introduce a new definition of distance between points on two spaces, construct localized kernels based on the two spaces and certain interaction parameters, and study the evolution of smoothness of a function on one space to its lifting to the other space via the landmarks. We develop novel mathematical tools that enable us to study these seemingly different problems in a unified manner.     

Manufacturer incentives to improve retail service levels

In this paper we provide a solution to the problem of how a manufacturer can provide an incentive to a separately-owned retailer to raise its service level above the level it would choose on its own. We analyze the effects the manufacturer's incentive has on the individual profits of the retailer and manufacturer, as well as their joint profits. Our work is an application of game theory in which we tackle the problem posed by separate ownership of the two firms and the resulting conflict over the gains from cooperation. We utilize a plausible model of service-sensitive demand, one which is relatively free of ad hoc assumptions. Our approach has the strength that it proposes a credible solution to the problem of manufacturer-retailer cooperation when profits are sensitive to retail service levels. Our results indicate that the optimal level of incentive for the manufacturer and the resulting shares of the manufacturer and retailer in increased profits are particularly sensitive to the underlying variability of demand and to the relative variability of additional demand induced by higher service levels.     

Tracking customer portfolio composition: A factor analysis approach

In this paper, we address the changing composition of a customer portfolio taking into account actions undertaken by the company to adapt its service offer to market conditions and/or technological innovations. We present a specific methodology to identify clusters of customers in different periods and then compare them over time. The classification process takes into account both qualitative and quantitative aspects of the consumption levels of the services or products offered by the company. The possibility of period‐to‐period variation in the customer portfolio and the service or product offer is also considered, in order to achieve a more realistic scenario. The core of the proposed methodology is related to the family of exploratory factorial and cluster techniques. The customers are classified by using a bicriterial clustering methodology based on ‘tandem’ analysis (multiple factor analysis+cluster analysis of the main factors). The bicriterial approach allows for a compromise between customers' consumption levels (a quantitative criterion) and their consumption/non‐consumption pattern (a qualitative criterion). The evolution of the customer portfolio composition is explored through multiple correspondence analysis. This technique allows visual comparison of the position of different clusters against time and the identification of key changes in customer consumption behavior. The methodology is tested on realistic customer portfolio scenarios for a major telecommunication company. We simulate various scenarios to show the strengths of our proposal. Copyright © 2009 John Wiley & Sons, Ltd.     

Cooperative location games based on the minimum diameter spanning Steiner subgraph problem

In this paper we introduce and analyze new classes of cooperative games related to facility location models. The players are the customers (demand points) in the location problem and the characteristic value of a coalition is the cost of serving its members. Specifically, the cost in our games is the service diameter of the coalition.We study the existence of core allocations for these games, focusing on network spaces, i.e., finite metric spaces induced by undirected graphs and positive edge lengths.     

A framework for evaluating remote diagnostics investment decisions for semiconductor equipment suppliers

With advances in information technology, service activities for expensive equipment used in semiconductor manufacturing can be performed from a remote location. This capability is called remote diagnostics (RD). Currently, there are intense development efforts in the semiconductor industry for implementing RD in wafer fabrication facilities to reduce maintenance and capital costs and improve productivity. In this paper, we develop a queueing-location model to analyze the capacity and location problem of after sales service providers, considering the effects of RD technology. Our model optimizes the location, capacity and the type of service centers while taking congestion effects into consideration. We solve this model using a simulation optimization approach in which we use a genetic algorithm to search the solution space. We demonstrate how our methodology can be used in strategic investment planning regarding the adoption of RD technology and service center siting through a realistic case study.     

A Degenerate Isoperimetric Problem and Traveling Waves to a Bistable Hamiltonian System

We analyze a nonstandard isoperimetric problem in the plane associated with a metric having degenerate conformal factor at two points. Under certain assumptions on the conformal factor, we establish the existence of curves of least length under a constraint associated with enclosed euclidean area. As a motivation for and application of this isoperimetric problem, we identify these isoperimetric curves, appropriately parametrized, as traveling wave solutions to a bistable Hamiltonian system of PDEs. We also determine the existence of a maximal propagation speed for these traveling waves through an explicit upper bound depending on the conformal factor.© 2015 Wiley Periodicals, Inc.     

Pointwise convergence to shock waves for viscous conservation laws

We are interested in the pointwise behavior of the perturbations of shock waves for viscous conservation laws. It is shown that, besides a translation of the shock waves and of linear and nonlinear diffusion waves of heat and Burgers equations, a perturbation also gives rise to algebraically decaying terms, which measure the coupling of waves of different characteristic families. Our technique is a combination of time-asymptotic expansion, construction of approximate Green functions, and analysis of nonlinear wave interactions. The pointwise estimates yield optimal L_p convergence of the perturbation to the shock and diffusion waves, 1 ≤ p ≤ ∞. The new approach of obtaining pointwise estimates based on the Green functions for the linearized system and the analysis of nonlinear wave interactions is also useful for studying the stability of waves of distinct types and nonclassical shocks. These are being explored elsewhere. © 1997 John Wiley & Sons, Inc.     

A co-opetitive framework for the hub location problems in transportation networks

In this paper, we present the first model of co-opetition for a Hub Location Problem between two logistics service provider (LSPs) companies where the mother company is the owner of infrastructure. The LSPs would like to cooperate with each other by establishing joint edges with limited capacities connecting their service networks. Such services are in form of pendulum services (a direct service between two points) between nodes of different networks. Additional market can be generated as a result of joining the two networks. At the same time, a competition is taking place between the two operators to increase their share from the additional market generated. In order to solve this problem, we propose a matheuristic approach combining a local search algorithm and a Lagrangian relaxation-based approach. In our matheuristic algorithm, the neighbourhood solutions are evaluated using a Lagrangian relaxation-based approach. Numerical results of applying the proposed algorithm on a real case study of the problem are presented.     

Modeling first bid in retail secondary market online auctions: A Bayesian approach

We propose a Bayesian framework to model bid placement time in retail secondary market online business‐to‐business auctions. In doing so, we propose a Bayesian beta regression model to predict the first bidder and time to first bid, and a dynamic probit model to analyze participation. In our development, we consider both auction‐specific and bidder‐specific explanatory variables. While we primarily focus on the predictive performance of the models, we also discuss how auction features and bidders' heterogeneity could affect the bid timings, as well as auction participation. We illustrate the implementation of our models by applying to actual auction data and discuss additional insights provided by the Bayesian approach, which can benefit auctioneers.     

The impact of digital channel distribution on the experience goods industry

We explore the impact of a digital channel for experience goods on the profitability and behavior of players in the supply chain and on piracy. We consider a firm which can sell an experience good in physical form, in digitized form, or both. We analyze different pricing schemes – price for whole album on the retail channel and linear and nonlinear pricing for songs on the digital channel. Consumers are divided into a retail-captive segment whose consumers are limited to the retail channel and a hybrid segment whose consumers have access to both retail and digital channels.     

基于乘积季节模型的社会消费品零售总额分析

社会消费品零售总额是反映人们消费水平的重要度量指标,也是国民经济体系中的一个重要评价指标.因此,分析研究社会消费品零售总额发展趋势对于转型期的中国经济高质量发展具有重要意义.基于乘积季节模型对2001年至2020年的社会消费品零售总额数据进行时间序列分析,经过差分、单位根检验、模型识别与拟合等过程,确定最终模型为ARIMA(1,1,1)(1,1,0)12,结果表明,社会消费品零售总额数据具有明显的线性趋势和季节性特征,并进一步得出其波峰和波谷到达的时间,另外,该模型对社会消费品零售总额有非常好的拟合效果,且有较高的预测精度.