工程供应链风险源的识别与控制策略研究

工程项目的复杂性造成了工程风险的普遍性,风险管理是工程管理的主要内容。本文针对传统的工程风险管理与控制的不足,基于工程供应链的视角,立足于工程生命周期角度重新审视了工程风险。从系统的观点出发,工程供应链是一个复杂系统,可划分为供应商管理、供应链运作管理、"制造商"管理三个子系统,系统或子系统在系统内生因素和外生因素的干扰下会产生中断和延迟两种风险结果,因此共形成六种工程供应链风险组合。本文在建立了多维度风险识别框架的基础上,从上述六方面识别了工程供应链风险的来源,并提出了应对策略。     

Relevance of functional flexibility for heterogeneous sales response models: A comparison of parametric and semi-nonparametric models

So far studies estimating sales response functions on the basis of store-specific data either consider heterogeneity or functional flexibility. That is why in this contribution a model is developed possessing both these features. It is a multilayer perceptron with store-specific coefficients which follows a hierarchical Bayesian framework. An appropriate Markov Chain Monte Carlo estimation technique is introduced capable to satisfy theoretical constraints (e.g. sign constraints on elasticities). The empirical study refers to a data base consisting of weekly observations of sales and prices for nine leading brands of a packaged consumer good category. The data were acquired in 81 stores over a time span of at least 61 weeks. The multilayer perceptron is compared to a strict parametric multiplicative model and turns out to be clearly superior in terms of posterior model probability. This result indicates the benefits of using a flexible model even if heterogeneity is dealt with. Estimated sales curves and elasticities demonstrate that both models differ with regard to implications on price response.     

Time traps in supply chains: Is optimal still good enough?

Operations Researchers support Supply Chain Management and Supply Chain Planning by developing adequate mathematical optimization models and providing suitable solution procedures. In this paper we discuss what adequate could mean. Therefore, we may ask several questions concerning “optimality” in Supply Chain Planning under causal and temporal uncertainty: What is an optimal solution? When is it optimal? For how long is it optimal? How should the design of a supply chain be changed when conditions and requirements ask for new structures? In particular, we discuss new approaches to Supply Chain Planning in order to give an optimal transformation from an initial solution over multiple periods to a desired one rather than just specifying an optimal snapshot solution. Time and uncertainty are the factors triggering the whole discussion. In particular, several flaws often found when dealing with these factors result in so-called “time traps”. We look at the impact of recent technological developments like the Internet of Things or Industry 4.0 on operational supply chain planning and control, and we show how online optimization can help to cope with real-time challenges. Moreover, we re-coin the concept of risk in the realm of Supply Chain Planning. Here the question is how to measure supply chain specific risks and how to incorporate them “adequately” into mathematical models.     

Impact of replenishment rules with endogenous lead times on supply chain performance

This text summarizes the PhD thesis of Robert Boute, obtained at the Katholieke Universiteit Leuven (Belgium) under supervision of Marc Lambrecht. This doctoral dissertation in the field of Supply Chain Management demonstrates that significant cost reductions can be obtained for both the retailer and the manufacturer when they align their replenishment policy. Such a collaboration strategy goes far beyond “information sharing”. In this summary, we present the research model, the general outline of the thesis and the methodology used. The PhD thesis, written in English, is available from the author upon request.      

Railway scheduling reduces the expected project makespan over roadrunner scheduling in a multi-mode project scheduling environment

The Critical Chain Scheduling and Buffer Management (CC/BM) methodology, proposed by Goldratt (Critical chain, 1997), introduced the concepts of feeding buffers, project buffers and resource buffers as well as the roadrunner mentality. This last concept, in which activities are started as soon as possible, was introduced in order to speed up projects by taking advantage of predecessors finishing early. Later on, the railway scheduling concept of never starting activities earlier than planned was introduced as a way to increase the stability of the project, typically at the cost of an increase in the expected project makespan. In this paper, we will indicate a realistic situation in which railway scheduling improves both the stability and the expected project makespan over roadrunner scheduling.     

Strategic simulation models as a new methodological approach: an application to information technologies integration,lean/just-in-time and lead-time

Central European Journal of Operations Research - Hypothesis contrast using statistical models with Structural Equations is a technique widely used in Supply Chain Management research. However,...     

Estimating market shares in each market segment using the information entropy concept

Sales data of a certain product for the various competitors are usually available at the aggregate level. However these data give no clue to the heterogeneities in the sales pattern across different market segments. Heterogeneities are caused by different purchasing behavior in each market segment; as a purchaser in a segment will be attracted to the attributes of the product most important to that segment. This concept can be formalized via a simple attraction model that utilizes an elasticity measure for each quality or price attribute [G.S. Carpenter, L.G. Cooper, D.M. Hanssens, D.F. Midgley, Modeling asymmetric competition, Marketing Science 7 (4) (1998) 393–412]. Assessment of these elasticities is not difficult since customer response – in each market segment – to perception of quality and price is tracked by most firms [J. Ross, D. Georgoff, A survey of productive and quality issues in manufacturing. The state of the industry, Industrial Management 3 (5) (1991) 22–25]. This paper attempts to formulate a generic framework based on the information entropy concept that utilizes such an attraction model to estimate competitors’ sales in each market segment.     

Retail store scheduling for profit

In spite of its tremendous economic significance, the problem of sales staff schedule optimization for retail stores has received relatively scant attention. Current approaches typically attempt to minimize payroll costs by closely fitting a staffing curve derived from exogenous sales forecasts, oblivious to the ability of additional staff to (sometimes) positively impact sales. In contrast, this paper frames the retail scheduling problem in terms of operating profit maximization, explicitly recognizing the dual role of sales employees as sources of revenues as well as generators of operating costs. We introduce a flexible stochastic model of retail store sales, estimated from store-specific historical data, that can account for the impact of all known sales drivers, including the number of scheduled staff, and provide an accurate sales forecast at a high intra-day resolution. We also present solution techniques based on mixed-integer (MIP) and constraint programming (CP) to efficiently solve the complex mixed integer non-linear scheduling (MINLP) problem with a profit-maximization objective. The proposed approach allows solving full weekly schedules to optimality, or near-optimality with a very small gap. On a case-study with a medium-sized retail chain, this integrated forecasting–scheduling methodology yields significant projected net profit increases on the order of 2–3% compared to baseline schedules.     

Inventory routing problems: a logistical overview

This paper presents an overview of Supply Chain Management while focussing on the area of Inventory Routing. We aim to provide the state-of-the-art in this area while highlighting the usefulness of the models in practice as well as their limitations. We have classified the papers based on the planning horizon employed in the models namely single period, multiperiod and infinite horizon models that are then complemented by those with stochastic demand patterns. Future research avenues that we believe to be of interest to the OR/MS community are also presented.     

Performance evaluation of purchasing and supply management using value chain DEA approach

Purchasing and Supply Management (PSM) today is increasingly becoming more important to senior management due to its potential to strategically influence both operational performance as well as financial performance outcomes. However the cross-functional nature of many PSM activities has led to inadequate data collection and performance measurement resulting in weak performance evaluation methodologies and mixed results. We address this gap in the current study, firstly by using an external assessment survey methodology that complements the internal perceptional measures of PSM performance, to collect data for a sample of over 120 firms across the globe with more than 3 billion US dollar turnover, representing seven industry sectors. Next, we develop a comprehensive performance measurement framework using the classical and two-stage Value Chain Data Envelopment Analysis models, which make use of multiple PSM measures at various stages and provide a single efficiency measure that estimates the all-round performance of a PSM function and its contribution to the long term corporate performance in each of these seven industry sectors. The relevance of this measurement methodology is demonstrated through an in-depth analysis of the distribution of efficiencies within and across industry sectors and through the estimation of target PSM performance levels.     

Setting Commission Rates for the Control of the Salesperson's Client-prospect Effort Allocation

The literature on setting optimal commission rates for decentralized controls over salespeople's time allocations has used the sales of various product lines as the relevant selling activities. When the time allocation is between calls to prospects versus customers, the problem should account for specific aspects, such as: (1) the conversion pattern of prospects for the various product lines; (2) the attrition rate in the sales force; (3) the salespeople's attitudes toward delayed income. These variables recognize that several calls over some period of time are typically needed for converting prospects, and that salespeople will be able to cash commissions only at the conversion time and provided they are still in charge of the same accounts. Using a simple Markovian structure, this paper shows that under typical conditions, commissions on sales to prospects during the conversion period should always be larger than commissions on sales to customers. Managerial implications and implementation issues are discussed.     

Langevin type limiting processes for adaptive MCMC

Adaptive Markov Chain Monte Carlo (AMCMC) is a class of MCMC algorithms where the proposal distribution changes at every iteration of the chain. In this case it is important to verify that such a Markov Chain indeed has a stationary distribution. In this paper we discuss a diffusion approximation to a discrete time AMCMC. This diffusion approximation is different when compared to the diffusion approximation as in Gelman et al. [5] where the state space increases in dimension to ∞. In our approach the time parameter is sped up in such a way that the limiting process (as the mesh size goes to 0) approaches to a non-trivial diffusion process.     

Dynamic Nonlinear Modelization of Operational Supply Chain Systems

Supply Chain Management (SCM) is an important activity in all producing facilities and in many organizations to enable vendors, manufacturers and suppliers to interact gainfully and plan optimally their flow of goods and services. To realize this, a dynamic modelling approach for characterizing supply chain activities is opportune, so as to plan efficiently the set of activities over a distributed network in a formal and scientific way. The dynamical system will result so complex that it is not generally possible to specify the functional forms and the parameters of interest, relating outputs to inputs, states and stochastic terms by experiential specification methods. Thus the algorithm that will presented is Data Driven, determining simultaneously the functional forms, the parameters and the optimal control policy from the data available for the supply chain. The aim of this paper is to present this methodology, by considering dynamical aspects of the system, the presence of nonlinear relationships and unbiased estimation procedures to quantify these relations, leading to a nonlinear and stochastic dynamical system representation of the SCM problem. Moreover, the convergence of the algorithm will be proved and the satisfaction of the required statistical conditions demonstrated. Thus SCM problems may be formulated as formal scientific procedures, with well defined algorithms and a precise calculation sequence to determine the best alternative to enact. A “Certainty equivalent principle” will be indicated to ensure that the effects of the inevitable uncertainties will not lead to indeterminate results, allowing the formulation of demonstrably asymptotically optimal management plans.     

A genetic algorithm for optimal operating parameters of VMI system in a two-echelon supply chain

This paper deals with the operational issues of a two-echelon single vendor–multiple buyers supply chain (TSVMBSC) model under vendor managed inventory (VMI) mode of operation. The operational parameters to the above model are: sales quantity and sales price that determine the channel profit of the supply chain, and contract price between the vendor and the buyer, which depends upon the understanding between the partners on their revenue sharing. In order to find out the optimal sales quantity for each buyer in TSVMBSC problem, a mathematical model is formulated. Optimal sales price and acceptable contract price at different revenue share are subsequently derived with the optimal sales quantity. A genetic algorithm (GA) based heuristic is proposed to solve this TSVMBSC problem, which belongs to nonlinear integer programming problem (NIP). The proposed methodology is evaluated for its solution quality. Furthermore, the robustness of the model with its parameters, which fluctuate frequently and are sensitive to operational features, is analysed.     

Cointegration analysis of brand and category sales: Stationarity and long‐run equilibrium in market shares

The present study uses modern time series methodology to understand long‐run equilibrium in markets and provides additional evidence of the frequent existence of stationary market shares for frequently purchased consumer products. Dekimpe and Hanssens, Marketing Science 1995; 14(2):G109–121 using a database of over 400 prior studies, found that 78 per cent of the market share series they studied were stationary, but that 68 per cent of the sales series were evolving. Our findings reconcile these results. A major contribution of this paper is its demonstration that the prior empirical evidence that a majority of sales series is in evolution is consistent with stationary market shares, if brand sales and category sales are cointegrated. To the extent that competitive activities have an effect on market share, an implication of our findings is that these activities may, in general, only have a temporary effect on market share. Finally, we distinguish, from a strategic perspective, between sales and share response at the primary‐demand level (category sales), selective‐demand level (brand sales) and relative‐position level (market share) and identify strategic scenarios depending upon their stable/evolving nature. Copyright © 2000 John Wiley & Sons, Ltd.     

The Impact of Risk Attitude on the Optimal Compensation Plan in a Multi-product Situation

This paper examines the role of uncertainty and risk in determining the optimal commission rates a company should choose for each product of a salesman's product line. We assume that sales for each product are a stochastic function of the time (sales effort) allocated to that product. When sales are assumed to be deterministic, we achieve optimality when each product's commission is the same fraction of its gross margin. However, we determine here that when sales are stochastic this may no longer be true. Optimality conditions require explicit consideration of the utility function of the salesman and the moments of the sales response function.     

The value of virtual pooling in dual sales channel supply chains

Recently the most significant growth in online retailing has been attributed to traditional offline retailers extending their brands online. Unfortunately, there is little research addressing the value of better information in retail/e-tail organizations. To fill this gap, this paper examines how investing in the continuous monitoring of online demands and inventory positions can provide economic benefit for companies that handle both in-store and online sales. Specifically, we develop and evaluate two dynamic assignment policies that incorporate real time information to specify which of a firm’s e-fulfillment locations will handle each of its Internet sales. Computational results indicate that investing in dynamic assignment capability can reduce system cost (holding, backorder, and transportation) by as much as 8.2% over the optimal static policy. The percentage of sales occurring online plays a critical role in determining the magnitude of the benefit.     

对复合函数求导定理证明的评论与研究

本文指出了一些广泛使用的教科书对复合函数求导定理的证明是不严格，并创造性地举例阐明存在这样的复合函数f(u)，它对自变量u可导，而对中间变量u=g(x)不可导。本文也给出了该定理的一个严格证明，同时揭示了复合函数求导法则的表达形式与其内容并不完全一致。     

QUOPLAN: A System for Optimizing Sales Quota-Bonus Plans

This paper describes an IBM-PC menu-driven and user-friendly procedure which can help sales management in setting up optimal quota-bonus plans. For a given sales force, the resulting quotabonus plan maximizes the firm's current profits subject to (1) keeping every individual sales-force member at least at his/her current level of satisfaction (or eventually, increasing this level), and (2) being consistent and harmonious across sales representatives. The QUOPLAN system is composed of two submodels. The first submodel is used by salespersons for eliciting their own utility functions, and is essentially based upon the principles of conjoint analysis. The second submodel is used by management for reconciling all the individuals' judgements and the company's objectives into a consistent quota-bonus plan.