Responsive Pricing Newsvendor Networks with Discretionary Commonality

Discretionary commonality is a form of operational flexibility used in multi‐product manufacturing environments. Consider a case where a firm produces and sells two products. Without discretionary commonality, each product is made through a unique combination of input and production capacity. With discretionary commonality, one of the inputs could be used for producing both products, and one of the production capacities could be used to process different inputs for producing one of the products. In the latter case, the manager can decide, upon the realization of uncertainty, not only the quantities for different products (outputs) but also the means of transforming inputs into outputs. The objective of this study is to understand how the firm's value, its inventory levels for inputs and capacity levels for resources are affected by the demand characteristics and market conditions. In pursuing this research, we extend Van Mieghem and Rudi ( 2002 )'s newsvendor network model to allow for the modeling of product interdependence, demand functions, random shocks, and firm's ex post pricing decision. Applying the general framework to the network with discretionary commonality, we discover that inventory and capacity management can be quite different compared to a network where commonality is non‐discretionary. Among other results, we find that as the degree of product substitution increases, the relative need for discretionary commonality increases; as the market correlation increases, while the firm's value may increase for complementary products, the discretionary common input decreases but the dedicated input increases. Numerical study shows that discretionary flexibility and responsive pricing are strategic substitutes.     

On pricing and protection of complementary products

The business literature advises firms producing complementary products to sell the core product at a low price, but to price the complementary product at a higher premium. This strategy, however, is problematic if firms face competitors in the market for complementary products as well, as observed in recent years for instance in the market for printers/ink cartridges. Motivated by several measures the firms have taken in this market, the current paper analyzes whether firms are interested in protecting their complementary product from outside competition. We find that firms protect their products only if consumers underestimate the demand for the complementary product when deciding which core product to buy. Moreover, we investigate how the decision to protect the complementary product interacts with a firm’s pricing decision. We show that the price policy proposed in the business literature should only be applied, if consumers sufficiently underestimate their demand for the complementary product so that firms strongly protect these products from outside competition.     

Optimal pricing and production decisions in the presence of symmetrical and asymmetrical substitution

Firms may produce a variety of generally similar products or may practice “scientific pricing” or revenue management where the firm will offer similar or somewhat differentiated products in multiple market segments at different prices. Whenever generally similar products are available, the demand for the products is linked through the ability of the customer to substitute one product for another. One widely known type of demand substitution is referred to as inventory-driven substitution where a customer will substitute for a product that is out of stock by buying a similar product. A second type of substitution occurs as a response to price-differences when a customer substitutes a less expensive product for a similar higher priced product.     

Sourcing Decisions with Stochastic Supplier Reliability and Stochastic Demand

Supplier sourcing strategies are a crucial factor driving supply chain success. In this paper, we investigate the implications of uncertain supplier reliability on a firm's sourcing decisions in an environment with stochastic demand. In particular, we characterize specific conditions under which a firm should choose a single versus multiple supplier sourcing strategy. In an environment with both uncertain demand and supply, we characterize the total order quantity, the number of suppliers selected for order placement, and the allocation of the total order quantity among these selected suppliers. For deeper managerial insight, we also examine the sensitivity of the optimal sourcing decisions to interactions between uncertainties in product demand and supply reliability. We show that sourcing from a single supplier is an optimal strategy for environments characterized by high levels of demand uncertainty or high salvage values. A numerical analysis based on data obtained from an office products retailer further reinforces our analytical results. In addition, we also find that when minimal order quantities are imposed, there are situations where it is not optimal to place an order with the lowest cost supplier.     

Managing Supply Risk for Vertically Differentiated Co‐Products

The manufacturing complexity of many high‐tech products results in a substantial variation in the quality of the units produced. After manufacturing, the units are classified into vertically differentiated products. These products are typically obtained in uncontrollable fractions, leading to mismatches between their demand and supply. We focus on product stockouts due to the supply–demand mismatches. Existing literature suggests that when faced with product stockouts, firms should satisfy all unmet demand of a low‐end product by downgrading excess units of a high‐end product (downward substitution). However, this policy may be suboptimal if it is likely that low‐end customers will substitute with a higher quality product and pay the higher price (upward substitution). In this study, we investigate whether and how much downward substitution firms should perform. We also investigate whether and how much low‐end inventory firms should withhold to strategically divert some low‐end demand to the high‐end product. We first establish the existence of regions of co‐production technology and willingness of customers to substitute upward where firms adopt different substitution/withholding strategies. Then, we develop a managerial framework to determine the optimal selling strategy during the life cycle of technology products as profit margins shrink, manufacturing technology improves, and more capacity becomes available. Consistent trends exist for exogenous and endogenous prices.     

Multi‐Product Quality Competition: Impact of Resource Constraints

We study a multi‐product firm with limited capacity where the products are vertically (quality) differentiated and the customer base is heterogeneous in their valuation of quality. While the demand structure creates opportunities through proliferation, the firm should avoid cannibalization between its own products. Moreover, the oligopolistic market structure puts competitive pressure and limits the firm's market share. On the other hand, the firm has limited resources that cause a supply‐side fight for adequate and profitable production. We explicitly characterize the conditions where each force dominates. Our focus is on understanding how capacity constraints and competition affect a firm's product‐mix decisions. We find that considering capacity constraints could significantly change traditional insights (that ignore capacity) related to product‐line design and the role of competition therein. In particular, we show that when the resources are limited, the firm should offer only the product that has the highest margin per unit capacity. We find that this product could be the diametrically opposite product suggested by the existing literature. In addition, we show that for intermediate capacity levels, whereas the margin per unit capacity effect dominates in a less competitive market, proliferation and cannibalization effects dominate in a more competitive market.     

Inventory Planning for a Modular Product Family

This paper is motivated by observing that an increasing number of firms are offering modular products assembled with multiple option choices for the consumer. Starting with the PC offerings by Dell which allowed (and still allows) users to configure their product by choosing among multiple choices for each option, the current market place seems to have evolved to a make‐to‐stock scenario where Apple offers its IPAD series with multiple models each with a unique storage size, color, and wireless chip technology. The focus of our work is on determining the optimal stocking level of modular end‐products. Our analysis is based on a benchmark model with the aim of maximizing expected profit subject to an aggregate fill rate constraint as well as variant‐specific individual fill rates under a make‐to‐stock setting. To further assess the robustness of our finding, we consider the extensions of correlated market preferences over options, price‐dependent demand, and alternative probability distributions for characterizing uncertainty in market preferences or aggregate demand. Finally we also show how to extend the single period model into a multiple‐period setting. Through extensive computational analysis, we find that more precise estimates of market preferences for various modular options constitute extremely valuable information that goes beyond the usefulness of forecasts of aggregate market demand. From a practical perspective, this might be indicative of another classic marketing‐operations trade‐off. Offering more options for consumers would be preferred by marketing managers since this would reach more consumers and hence, enhance product sales. On the other hand, the ability to obtaining greater forecast accuracy would decline when the number of options increase. Hence, from an operational perspective, it would be preferred to limit option choices (so that better forecasts can be obtained) since this would lead to lower stocking costs and hence, higher profits.     

Joint Stocking and Product Offer Decisions Under the Multinomial Logit Model

This article studies a joint stocking and product offer problem. We have access to a number of products to satisfy the demand over a finite selling horizon. Given that customers choose among the set of offered products according to the multinomial logit model, we need to decide which sets of products to offer over the selling horizon and how many units of each product to stock so as to maximize the expected profit. We formulate the problem as a nonlinear program, where the decision variables correspond to the stocking quantity for each product and the duration of time that each set of products is offered. This nonlinear program is intractable due to its large number of decision variables and its nonseparable and nonconcave objective function. We use the structure of the multinomial logit model to formulate an equivalent nonlinear program, where the number of decision variables is manageable and the objective function is separable. Exploiting separability, we solve the equivalent nonlinear program through a dynamic program with a two dimensional and continuous state variable. As the solution of the dynamic program requires discretizing the state variable, we study other approximate solution methods. Our equivalent nonlinear program and approximate solution methods yield insights for good offer sets.     

Lot Sizing for Optimal Collection and Use of Remanufacturable Returns over a Finite Life‐Cycle

Reverse supply chains process used product returns to recover value by re‐processing them via remanufacturing operations. When remanufacturing is feasible, the longer the return flows are delayed during the active (primary) market demand period of the product, the lower the value that can be recovered through these operations. In fact, in order to recover the highest value from remanufactured products, the collection rates, return timings, and reusability rates should be matched with the active market demand and supply. With these motivations, this paper is aimed at developing analytical models for the efficient use of returns in making production, inventory, and remanufacturing decisions during the active market. More specifically, we consider a stylistic setting where a collector collects used product returns and ships them to the manufacturer who, in turn, recovers value by remanufacturing and supplies products during the active market demand. Naturally, the manufacturer's production, inventory and remanufacturing decisions and costs are influenced by the timing and quantity of the collector's shipments of used product returns. Hence, we investigate the impact of the timing of returns on the profitability of the manufacturer‐collector pair by developing system‐wide cost optimization models. Analyzing the properties of the optimal shipment frequency, we observe that the fastest reverse supply chain may not always be the most efficient one.     

The Design and Introduction of Product Lines When Consumer Valuations are Uncertain

This article presents a model of the design and introduction of a product line when the firm is uncertain about consumer valuations for the products. We find that product line introduction strategy depends on this uncertainty. Specifically, under low levels of uncertainty the firm introduces both models during the first period; under higher levels of uncertainty, the firm prefers sequential introduction and delays design of the second product until the second period. Under intermediate levels of uncertainty the firm's first product should be of lower quality than one produced by a myopic firm that does not take product line effects into consideration. We find that when the firm introduces a product sequentially, the strategy might depend on realized demand. For example, if realized demand is high, the firm's second product should be a higher‐end model; if demand turns out to be low, the firm's second product should be a lower‐end model or replace the first product with a lower‐end model.     

Managing Interdependence: The Effects of Outsourcing Structure on the Performance of Complex Projects*

The outsourcing of complex activities has become a common organizational practice. Yet very little research has focused on the implications of how these activities are divided up among outsourcing partners. Drawing on structural contingency theory, we argue that: (1) because activities within stages of complex projects are highly interdependent, outsourcing structures where owner firms do not maintain high levels of dominance over the activities that are performed will pose control and coordination challenges, leading to poor project performance; (2) the adverse effects of poorly structured outsourcing arrangements will spill over to subsequent project stages when activities are interdependent across project stages; and (3) dividing activities among large numbers of contractors or distributing work evenly among contractors exacerbates coordination and control problems further contributing to poor project performance. Our empirical analysis of 323 capital facility construction projects supports our predictions. Overall, these results provide strong evidence that some outsourcing structures are more costly than others and that because of the nature of complex projects the detrimental effects of poorly structured outsourcing are often not completely observable at the time activities are completed. We discuss the implications of our findings for capital construction and for outsourcing more generally.     

心理因素、交易环境变化与结构性产品风险测度:一个研究综述

随着互联网金融的兴起，先前的交易环境已由线下交易为主逐步转变为基于线上平台的交易，金融产品市场呈现出与众不同的新特征。结构性产品繁荣发展的背后蕴藏着极大风险，风险测度与管理研究对结构性产品市场发展具有重要意义。研究表明，心理因素对投资者信念和预期产生重要影响，并且交易环境变化可以加剧投资者心理偏差，进而使其产生非理性的投资决策和行为。本文在梳理国内外有关结构性产品供需研究、心理偏差与投资者情绪等个体心理因素、交易环境变化以及风险测度理论与方法文献的基础上提出：面向互联网金融服务平台的结构性产品风险测度研究应将外部交易环境变化和内部心理偏差因素共同加以考虑，以有效地实现新环境下复杂金融产品市场的风险评估和管理。     

A Model for Partial Product Complementarity and Strategic Production Decisions under Demand Uncertainty

This paper considers a general industrial setting where multiple manufacturers each produce a different product and sell it to the markets. These products are partially complementary in the sense that there is a common demand stream that requests all these products as complementary sets and there are streams of individual demands each requesting only one of the products. All demands are uncertain and may follow any general, joint distributions. Facing demand uncertainties, the manufacturers each choose a production quantity for its product with an objective to maximize its own expected profit. We formulate the problem as a non‐cooperative game to study the strategic interactions of such firms and their implications to supply chain performance. We show that such a game may have numerous equilibria. Among all the possible equilibria, however, we prove that there always exists a unique one that maximizes each and every manufacturer's profit, and we derive an explicit solution for this Pareto‐optimal equilibrium point. We further study the optimal solution for a centralized system and compare it with the decentralized solution. Managerial insights are drawn as to how system parameters and control mechanisms affect firms' decisions and performance.     

融合内容分析和关联分析的短生命周期体验品需求特征模式挖掘方法研究

挖掘特定产品的需求模式无法从整体掌握该类产品的市场特征;短生命周期体验品因缺乏历史销售数据,并且销售总量波动性极大,尤其需要从整体掌握销售总量与产品属性间关系的需求特征规律,但又难以挖掘,亟待提出适用于该类产品的需求特征模式挖掘方法。基于按销售总量分区后各区的需求特征的规律性,提出了一种按销售总量分区、以已有产品介绍集和销售总量为源信息、适用于新产品开发前使用、融合内容分析和关联分析的短生命周期体验品需求特征模式挖掘方法。该方法包括基于内容分析法的产品属性挖掘方法和基于关联分析的产品属性关系模式挖掘方法。前者可以得到较全面的产品属性;后者能够构建不同销售总量区间内产品集的属性关系模式,得到各区间的产品属性关系网,获得高销售总量区间具备,但中、低区间不具备的属性关系模式,从而获得需求特征模式。通过不断更新产品介绍集和销售总量并迭代挖掘,该方法能够动态挖掘需求特征模式。最后利用2013至2016年国产犯罪和爱情类电影数据验证了该方法的可行性,并得到了这两类电影的产品属性及近年的需求特征模式,可用于指导这两类电影的创作。     

Assortment optimisation problem: A distribution-free approach

Assortment optimisation is a critical decision that is regularly made by retailers. The decision involves a trade-off between offering a larger assortment of products but smaller inventories of each product and offering a smaller number of varieties with more inventory of each product. We propose a robust, distribution-free formulation of the assortment optimisation problem such that the assortment and inventory levels can be jointly optimised without making specific assumptions on the demand distributions of each product. We take a max-min approach to the problem that provides a guaranteed lower bound to the expected profit when only the mean and variance of the demand distribution are known. We propose and test three heuristic algorithms that provide solutions in O(nlog (n)) time and identify two cases where one of the heuristics is guaranteed to return optimal policies. Through numerical studies, we demonstrate that one of the heuristics performs extremely well, with an average optimality gap of 0.07% when simulated under varying conditions. We perform a sensitivity analysis of product and store demand attributes on the performance of the heuristic. Finally, we extend the problem by including maximum cardinality constraints on the assortment size and perform numerical studies to test the performance of the heuristics.     

Pricing and Replenishment of Competing Perishable Product Variants under Dynamic Demand Substitution

I consider pricing and ordering decisions faced by a retailer selling a perishable product with a two‐period shelf life over an infinite horizon. In the first period, the product is “new”; in the next, it becomes “old.” The new product is perceived by customers to have a higher quality than the old product. Every period, the retailer makes three decisions: prices for the new and old products and how much new product to order. I first show, with some simple cases, that demand uncertainty can make the sale of the old product profitable. I then consider a more realistic case with dynamic demand substitution among customers. I recognize that the retailer's decisions may be constant or may vary across different periods, under different contexts. For instance, varying the price of the new product can sometimes be difficult due to the negative impact it generates among customers. I find that (i) the benefit obtained from selling the old product with constant decisions is much higher than the benefit from allowing all the decisions to vary; (ii) the former benefit increases with a higher procurement cost, a higher quality of the new product, and higher demand volatility; however, the latter benefit is non‐monotone in these parameters; (iii) most of the latter benefit can be obtained by just changing the order quantity; and (iv) as the inventory of the old product increases, when all the decisions vary, the optimal price of the new product may increase or decrease.     

Bundling of Vertically Differentiated Products in a Supply Chain*

We consider a supply chain consisting of a single manufacturer and a single retailer. The manufacturer produces a basic and a premium product. If desired, a bundle of the two products might also be produced at a unit bundling cost. We allow either the manufacturer or the retailer to produce the bundle from the component products. All products, however, must be sold exclusively through the retailer. Using game theoretic models, we compare and contrast the equilibrium outcomes under retailer bundling and manufacturer bundling scenarios. We show that under manufacturer bundling, the manufacturer never offers the full product line composed of the basic product, the premium product, and the bundle, at equilibrium; while the same does not hold under retailer bundling. We show that total supply chain profit under retailer bundling weakly dominates that under manufacturer bundling and characterize the region in the parameter space where this domination is strict. We explore an extension where there is a capacity constraint in producing one or both of the component products and characterize the equilibrium outcomes. We show that unlike the infinite capacity case, offering the full product line is an equilibrium outcome under manufacturer bundling when the capacity of the premium good is limited.     

DEMAND FULFILLMENT RATES IN AN ASSEMBLETO- ORDER SYSTEM WITH MULTIPLE PRODUCTS AND DEPENDENT DEMANDS

This paper presents a model for evaluating product fulfillment rates in an assemble-to-order system with a two-level bill-of-material structure (products and components). Inventories are kept at the component level and are used to support service levels to product demands; each component is managed under a periodically reviewed, decentralized order-up-to policy. Product demands are correlated in a given period but are independent across periods. We develop the demand fulfillment rate for each product when demands are filled based on a first-come-first-served discipline with limited priorities for different products within a period. We show that the fulfillment rate can be expressed as a multivariate normal probability when the product demands follow a multivariate normal distribution. We then use a numerical example to discuss computational issues and bounds associated with the evaluation of the demand fulfillment rates. Finally, we consider a model for minimizing the total inventory investment subject to given product demand fulfillment rates.     

多资产的股票挂钩保本型理财产品定价研究

结构性理财产品定价的核心问题是收益函数的确定,定价技术难点在于资产相关性的处理.应用Cholesky分解方法,先解决资产间的相关性问题,然后针对多资产保本型股票挂钩结构性产品收益函数特点,利用蒙特卡罗方法对其进行定价.最后以深圳商业银行盈丰理财0706号为例,介绍该方法的应用.结果表明,该产品定价偏高,产品实际收益率偏低.     

Cost Allocation in Manufacturing–Remanufacturing Operations

For firms remanufacturing their products, the total life‐cycle costs and revenues from new and remanufactured products determine their profitability. In many firms, manufacturing/sales and remanufacturing/remarketing operations are carried out in different divisions. Each division is responsible for only part of the product's life cycle. Practices regarding transfer pricing across divisions vary significantly among companies, affecting the life‐cycle profit performance of the product. In this research, we identify characteristics of transfer prices that achieve the firm‐wide optimal solution. To this end, we consider a manufacturer who also undertakes remanufacturing operations and we focus on price (quantity) decisions. We determine that a cost allocation mechanism that allocates a portion of the initial production cost to each of the two stages of the product life cycle should be used. We also conclude that cost allocation should be implemented as a fixed cost allocation, where charges to the remanufacturing division should be determined independently of the actual quantity of units remanufactured.