The value of information for price dependent demand

Predicting demand and determining optimal pricing are essential components of operations management. It is often useful to think in terms of the price elasticity of demand when reasoning about the demand curve. Firms wishing to invest in demand prediction and information gathering should reason about the relationship between the expected value of perfect information (EVPI) on demand and demand elasticity. Should firms pay more/less for information on demand if elasticity is high/low? Furthermore, when considering different product prices, correlation may exist between demand at different prices. Should firms pay more/less for information if the correlation between demand at different prices is high or low? This paper derives analytic and numeric results to answer these questions. We start with the assumption that demand is uncertain and follows a uniformly distributed band around a deterministic demand curve where the upper and lower bounds of the demand distribution vary with price. This formulation enables a closed form expression for EVPI that provides a useful benchmark. We find nuanced behavior of EVPI that depends on both the elasticity and the initial price preference. The EVPI approaches zero as elasticity increases (decreases) for a firm that initially prefers the low (high) price. Numerical results using the truncated normal and beta distributions relax assumptions about the uniform distribution and show EVPI is similar when the distribution variances are similar. Finally, we relax the assumption of perfect information and show the expected value of imperfect information (EVOI) follows similar patterns as EVPI with respect to demand elasticity.     

Some Aspects of the Distributional Properties of the Expected Value of Perfect Information (EVPI)

In this paper we examine the Expected Value of Perfect Information (EVPI), with respect to the underlying probability distribution. By the method of optimal control theory we show that for any given second and third moments the underlying distribution that maximizes the EVPI is a 2-spike distribution. We find that shifting the distribution mean from zero will decrease the associated EVPI. The EVPI is further analyzed when the underlying distribution is symmetric, centred at zero.     

Multistage stochastic convex programs: Duality and its implications

In this paper, we study alternative primal and dual formulations of multistage stochastic convex programs (SP). The alternative dual problems which can be traced to the alternative primal representations, lead to stochastic analogs of standard deterministic constructs such as conjugate functions and Lagrangians. One of the by-products of this approach is that the development does not depend on dynamic programming (DP) type recursive arguments, and is therefore applicable to problems in which the objective function is non-separable (in the DP sense). Moreover, the treatment allows us to handle both continuous and discrete random variables with equal ease. We also investigate properties of the expected value of perfect information (EVPI) within the context of SP, and the connection between EVPI and nonanticipativity of optimal multipliers. Our study reveals that there exist optimal multipliers that are nonanticipative if, and only if, the EVPI is zero. Finally, we provide interpretations of the retroactive nature of the dual multipliers. This work was supported by NSF grant DMII-9414680.     

Sequential Importance Sampling Algorithms for Dynamic Stochastic Programming

This paper gives a comprehensive treatment of EVPI-based sequential importance sampling algorithms for dynamic (multistage) stochastic programming problems. Both theory and computational algorithms are discussed. Under general assumptions it is shown that both an expected value of perfect information (EVPI) process and the corresponding marginal EVPI process (the supremum norm of the conditional expectation of its generalized derivative) are nonanticipative nonnegative supermartingales. These processes are used as importance criteria in the class of sampling algorithms treated in the paper. When their values are negligible at a node of the current sample problem scenario tree, scenarios descending from the node are replaced by a single scenario at the next iteration. On the other hand, high values lead to increasing the number of scenarios descending from the node. Both the small sample and asymptotic properties of the sample problem estimates arising from the algorithms are established, and the former are evaluated numerically in the context of a financial planning problem. Finally, current and future research is described. Bibliography: 49 titles. __________ Published in Zapiski Nauchnykh Seminarov POMI, Vol. 312, 2004, pp. 94–129.     

A differential game model of the marketing-operations interface

In the development of their dynamic strategies, the marketing and operations functions within a firm have differing objectives, and conflict between the two functions is common. The strategic interdependence involving marketing and operations decisions is modeled as a noncooperative differential game. Demand is assumed to be a function of price and advertising goodwill, and marketing controls price and advertising to maximize its discounted stream of revenue net of advertising costs. Backlogging is allowed, and operations controls production to minimize its discounted stream of production and backlog costs. A feedback Nash equilibrium is derived for the game, which allows a solution of the system of differential equations for goodwill and backlog, and is analyzed to study the nature of the dynamic strategies for price, advertising, and production.     

On stochastic programming ii: dynamic problems under risk ∗

This paper surveys recent work on dynamic stochastic programming problems and their applications. New results are included on the measurability and interpretation-in terms of the expected value of perfect information (EVPI)-of the dual multiplier processes corresponding to these problems. A final section reports preliminary computational experiments with algorithms for 2-stage problems     

Supply chain optimization of petroleum organization under uncertainty in market demands and prices

A multi-period stochastic planning model has been developed and implemented for a supply chain network of a petroleum organization operating in an oil producing country under uncertain market conditions. The proposed supply chain network consists of all activities related to crude oil production, processing and distribution. Uncertainties were introduced in market demands and prices. A deterministic optimization model was first developed and tested. The impact of uncertainty on the supply chain was studied by performing a sensitivity analysis in which ±20% deviations were introduced in market demands and prices of different commodities. A stochastic formulation was then proposed, which is based on the two-stage problem with finite number of realizations. The proposed stochastic programming approach proved to be quite effective in developing resilient production plans in light of high degree of uncertainty in market conditions. The anticipated production plans have a considerably lower expected value of perfect information (EVPI). The main conclusion of this study is that for an oil producing country with oil processing capabilities, the impact of economic uncertainties may be tolerated by an appropriate balance between crude exports and processing capacities.     

Transfer pricing in a dynamic marketing-operations interface

A transfer price mechanism is proposed to coordinate the strategies of the marketing and operations functional areas operating in a dynamic interface environment in a decentralized firm. Marketing and operations are strategic decision-makers in a differential game, in which marketing has price and advertising and operations has production as control variables, and advertising goodwill and production backlog are state variables. A constant transfer price is entered into the objective functionals for marketing and operations, and subgame perfect feedback strategies are derived for price, advertising, and production as functions of the state variables. The feedback strategies allow a solution for the dynamic system involving goodwill and backlog, and the total payoff to the firm, the sum of the payoffs to marketing and operations, is determined as a function of the transfer price. Finally, for certain parameter conditions an interior maximum of the payoff function is achieved, and the optimal transfer price is identified.     

基于模糊AHP建构休闲农业营销绩效评价模式之研究

目的是以台湾地区休闲农场为研究对象,首先以德尔菲法,结合许多专家意见来建立休闲农业在营销评价指针项目,并以平衡计分卡观点,建构休闲农业绩效评估因素,接着利用模糊层级分析法分析出休闲农场在营销服务方面相关因素及权重比,并推导各因素构面重要性及大小顺序,提供业者作为一有效经营参考指标.研究结果显示:休闲农业营销绩效评价指标有3项一级指标(主构面),14项二级指标(次构面).在一级评价指标当中,依序为游客满意度(0.564)、游客贡献度(0.247)、休闲农场对游客吸引力(0.189).在对应于一级指标中,各二级指针最重要项目分别为:年度游客量(0.086)、服务满意度(0.116)、年净利润(0.154).而依两层级串联后权重值×100得知,14项指标中最重要的前三项分别为:游客对休闲农场人员服务满意度(6.543)、整体环境满意度(4.738)、餐饮满意度(5.584).     

Integrating operations and marketing decisions using delayed differentiation of products and guaranteed delivery time under stochastic demand

In this research, we integrate the issues related to operations and marketing strategy of firms characterized by large product variety, short lead times, and demand variability in an assemble-to-order environment. The operations decisions are the inventory level of components and semi-finished goods, and configuration of semi-finished goods. The marketing decisions are the products price and a lead time guarantee which is uniform for all products. We develop an integrated mathematical model that captures trade-offs related to inventory of semi-finished goods, inventory of components, outsourcing costs, and customer demand based on guaranteed lead time and price.The mathematical model is a two-stage, stochastic, integer, and non-linear programming problem. In the first stage, prior to demand realization, the operation and marketing decisions are determined. In the second stage, inventory is allocated to meet the demand. The objective is to maximize the expected profit per-unit time. The computational results on the test problems provide managerial insights for firms faced with the conflicting needs of offering: (i) low prices, (ii) guaranteed and short lead time, and (iii) a large product variety by leveraging operations decisions.     

The Organization and Improvement of Market Forecasting

Quantitative forecasting techniques are not much used in organizations. Instead, organizations rely on the judgement of managers working close to the product market. Increasingly however, developments at the interface between marketing and operations require more accurate forecasting. Quantitative marketing models have that potential. Drawing on theories from the ‘diffusion of innovation’ literature and results on ‘the barriers to effective implementation’, this paper first considers those factors that should be included in any complete evaluation of market forecasting. Using this framework and based on detailed survey work in a multi-divisional organization, the paper then describes how this company produces its market forecasts, and the perceptions of its managers as to inadequacies in the procedures. Reasons are proposed as to why quantitative forecasting techniques are not effectively used. The paper concludes with a discussion of the causes behind the organization's mismanagement of their forecasting activity and how these activities might best be improved.     

Vendor Management Inventory with consignment contracts and the benefits of cooperative advertising

Most of the cooperative advertising literature has focused on studying the effects of such programs considering marketing variables. This paper integrates production and inventory management with pricing and advertising considerations to assess the effects of cooperative advertising programs in bilateral monopolies. We consider a supply chain where a Vendor Managed Inventory (VMI) along with a consignment contract is implemented to coordinate the chain. We develop and solve a differential model for two games. The first one is a benchmark scenario where no cooperative advertising is offered, while the manufacturer offers the cooperative program in the second game. The main results show that cooperative advertising programs, usually considered as successful marketing initiatives, can be very difficult to implement in a supply chain undertaking a VMI policy with a consignment contract, in which operations and marketing interface is taken into account. A cooperative program mainly hurts the manufacturer’s profits, and can be profit-Pareto-improving only in a few cases. Although the retailer is generally willing to receive a support from the manufacturer, she can opt for a non-cooperative program when the largest part of the supply chain profits goes to the manufacturer. We developed several special cases to strengthen our findings.     

Coordination via cost and revenue sharing in manufacturer-retailer channels

The problem of establishing efficiency in a manufacturer-retailer channel (channel coordination) is extensively discussed in the industrial economics, the marketing and the operations research literature. However, studies considering consumer demand to be simultaneously affected by price and non-price variables are scarce. One subset of models investigates efficient contracts with non-linear tariffs, but requires mechanisms which are rarely observed in managerial practice. The other subset analyses channel efficiency effects of alternative royalty payments, but omits to design an efficient contract. We contribute to this literature by investigating a contract of royalty payments that is sufficient for channel coordination. Based on the analysis of the underlying vertical externalities, we show that channel coordination requires cost and revenue sharing via a revenue sharing rate and marketing effort participation rates on both manufacturer and retailer level. Some surprising findings are highlighted: there exists a continuum of efficient contracts. Efficiency requires a retailer’s participation of at least 50% in the manufacturer’s cost of marketing effort. Moreover, the elimination of double marginalisation is not necessary for channel coordination. Manufacturer and retailer can choose an efficient contract via bargaining over the wholesale price. The main challenge for managers will be to create acceptance of new types of royalty payments based on a trustful manufacturer-retailer relationship. We also discuss the cases of the Apple iPhone market launch and of innovative restaurant franchising to further illustrate and underline the relevance of our results.     

On the product line selection problem under attraction choice models of consumer behavior

Product line design (PLD) involves important decisions at the interface of operations and marketing that are very costly to implement and change, and, simultaneously, determinant for market success. To evaluate the financial performance of a product line, a number of mathematical programming approaches have been proposed. Problem formulations are typically mixed or pure integer non-linear optimization models that are intractable for exact solution - in particular when empirically supported consumer choice models are incorporated.     

Forecasting and operational research: a review

From its foundation, operational research (OR) has made many substantial contributions to practical forecasting in organizations. Equally, researchers in other disciplines have influenced forecasting practice. Since the last survey articles in JORS, forecasting has developed as a discipline with its own journals. While the effect of this increased specialization has been a narrowing of the scope of OR's interest in forecasting, research from an OR perspective remains vigorous. OR has been more receptive than other disciplines to the specialist research published in the forecasting journals, capitalizing on some of their key findings. In this paper, we identify the particular topics of OR interest over the past 25 years. After a brief summary of the current research in forecasting methods, we examine those topic areas that have grabbed the attention of OR researchers: computationally intensive methods and applications in operations and marketing. Applications in operations have proved particularly important, including the management of inventories and the effects of sharing forecast information across the supply chain. The second area of application is marketing, including customer relationship management using data mining and computer-intensive methods. The paper concludes by arguing that the unique contribution that OR can continue to make to forecasting is through developing models that link the effectiveness of new forecasting methods to the organizational context in which the models will be applied. The benefits of examining the system rather than its separate components are likely to be substantial.     

A survey of personalized treatment models for pricing strategies in insurance

We consider a model for price calculations based on three components: a fair premium; price loadings reflecting general expenses and solvency requirements; and profit. The first two components are typically evaluated on a yearly basis, while the third is viewed from a longer perspective. When considering the value of customers over a period of several years, and examining policy renewals and cross-selling in relation to price adjustments, many insurers may prefer to reduce their short-term benefits so as to focus on their most profitable customers and the long-term value. We show how models of personalized treatment learning can be used to select the policy holders that should be targeted in a company’s marketing strategies. An empirical application of the causal conditional inference tree method illustrates how best to implement a personalized cross-sell marketing campaign in this framework.     

A Single-period Stochastic Inventory Model Under the Influence of Marketing Policies

A single-period stochastic inventory model is developed under different marketing policies using the concepts of fixed prices and fixed mark-up of prices where discounts are offered on bulk purchases. In the mathematical model shortages are allowed, and it is assumed that any unit unsold at the end of the period has no economic value. The model yields simple solutions for some particular demand distributions. It is illustrated with a suitable example.     

信息经济时代的客户知识模型

客户知识由客户界定，沟通渠道，客户需求，客户行为以及客户赢利价值五个层次组成。其中每个知识层次都是包含该层次具体内容的客户知识子集。客户知识的掌握是一个过程，它从了解客户的基本信息以实现对客户进行界定开始，到识别客户对企业的赢利价值这一客户知识的核心。客户知识是制定“以客户为中心”的整合营销行动计划的基础。     

Generalized Farkas' theorem and optimization of infinitely constrained problems

This note is concerned with the generalization of Farkas' theorem of the alternative and its application to derive the necessary optimality conditions for min-max problems with satisfaction conditions. Farkas' theorem is generalized to a system of linear inequalities with max operations. The problems studied require a solution at which the worst objective value attains its minimum over a set of solutions fulfilling satisfaction conditions. The satisfaction conditions claim that plural performance criteria should be kept below the permissible level, whatever disturbances may happen or whatever opponents' decisions may be taken. We present a generalized Farkas' theorem in order to derive the necessary optimality conditions for the problems of this class.