Supply chains in the presence of store brands

Increased competition from store brands is forcing manufacturers to re-evaluate their strategies in regard to pricing and contracting with trade intermediaries. We analyze a supply chain in which a retailer accepts (with the appropriate contractual agreements) a national brand for resale and then determines whether to introduce a store brand, how to price the store brand, and what quantities of the product(s) to order. We show that when the national brand’s cost per unit quality (CPUQ) is larger than the store brand’s CPUQ, then the retailer seeks to introduce the store brand (SB) and the national brand (NB) manufacturer/supplier is unable to deter him from doing so. We find that the efficiency loss in the decentralized supply chain becomes smaller when a store brand is introduced. Recognizing the inadequacy of standard contracts in coordinating this supply chain, we propose a simple minimum order quantity contract that can coordinate this supply chain.     

A model of consumer choice for national <Emphasis Type="Italic">vs</Emphasis> private label brands

Most consumer choice theory is built around the study of manufacturer brands but in recent years there has been a dramatic rise in the share of private label brands. This empirical study suggests that models of consumer choice need to recognise an asymmetry in competition when both manufacturer and retailer private label brands are available. A nested logit model is introduced which demonstrates asymmetric cross-brand substitutability in this type of market and leads to important implications for strategic brand management.     

National and store brand advertising strategies

As the propensity of premium store brands (SBs) increases, retailers must consider different ways to drive sales besides promotional strategies. With this in mind, we consider a national brand (NB) and a (premium) SB co-existing in a market. Each brand has to decide the amount to invest in advertising its product and the prices to charge its customers, which can be determined separately or in unison. When either advertising expenditures or pricing decisions are set, each brand must keep in mind that the advertising efforts and revenue may spillover between the two brands, customers who intend to purchase the NB may end up purchasing the SB and vice versa. We derive an analytical model of the situations described and characterize equilibrium advertising decisions. We find that the characteristics of a premium SB may depend on which marketing/promoting instrument (advertising or pricing) is the primary method for driving demand; and in some situations an NB may be better off to not advertise at all and instead let the premium SB carry out all of the advertising.     

Sell through a local retailer or operate your own store? Channel structure and risk analysis

Either a company store or a local retailer can be used to establish a sales channel. For high-value products with an existing competing brand, this choice represents a crucial decision a brand-named manufacturer must make for a new market. Under the burden of high operating costs, a weak local retailer may find it difficult to sustain and using it may hurt the manufacturer’s chance to successfully establish the channel. We consider a chain-to-chain competition model comprising two manufacturers and two retailers, in which one retailer may be unable to continue its operation because of high financing costs. We identify a threshold policy for the manufacturers to select the channel structure. Interestingly, we find that channel integration is not always better. Without the consideration of contract termination risk, the manufacturer will bear the operating expenses when its opportunity cost is low or the retailer’s financing cost is sufficiently high. In equilibrium, the manufacturers will choose either (decentralized, decentralized) or (integrated, integrated) channel structure. However, when the termination risk is considered, the equilibrium channel structure would be more likely (integrated, integrated) or (integrated, decentralized).     

Drawing inferences from logit models for panel data

Logit models have been widely used in marketing to predict brand choice and to make inference about the impact of marketing mix variables on these choices. Most researchers have followed the pioneering example of Guadagni and Little, building choice models and drawing inference conditional on the assumption that the logit model is the correct specification for household purchase behaviour. To the extent that logit models fail to adequately describe household purchase behaviour, statistical inferences from them may be flawed. More importantly, marketing decisions based on these models may be incorrect. This research applies White's robust inference method to logit brand choice models. The method does not impose the restrictive assumption that the assumed logit model specification be true. A sandwich estimator of the covariance ‘corrected’ for possible mis‐specification is the basis for inference about logit model parameters. An important feature of this method is that it yields correct standard errors for the marketing mix parameter estimates even if the assumed logit model specification is not correct. Empirical examples include using household panel data sets from three different product categories to estimate logit models of brand choice. The standard errors obtained using traditional methods are compared with those obtained by White's robust method. The findings illustrate that incorrectly assuming the logit model to be true typically yields standard errors which are biased downward by 10–40 per cent. Conditions under which the bias is particularly severe are explored. Under these conditions, the robust approach is recommended. Copyright © 2000 John Wiley & Sons, Ltd.     

基于Logit离散选择模型的品类优化问题综述

品类优化问题(Assortment Optimization Problem)是收益管理的经典问题.它研究零售商在满足运营约束的前提下,应如何从给定产品集合中选择一个子集提供给消费者,以最大化预期收益.该问题的核心在于如何准确地刻画消费者在面对细分产品时的选择行为、建立相应的优化模型并设计高效率的求解算法.基于Logit离散选择模型的品类优化问题:首先,介绍了基于Multinomial Logit模型的品类优化问题.然后介绍了两个更复杂的变种:第一个是基于两层以及多层Nested Logit模型的品类优化问题,这类问题可合理刻画细分产品之间的"替代效应";第二个是基于Mixtures of Multinomial Logits模型的品类优化问题,这类问题可充分考虑消费者群体的异质性.随后,介绍了数据驱动的品类优化问题的相关进展.最后,指出该问题未来可能的若干研究方向.     

Network revenue management with inventory-sensitive bid prices and customer choice

We develop an approximate dynamic programming approach to network revenue management models with customer choice that approximates the value function of the Markov decision process with a non-linear function which is separable across resource inventory levels. This approximation can exhibit significantly improved accuracy compared to currently available methods. It further allows for arbitrary aggregation of inventory units and thereby reduction of computational workload, yields upper bounds on the optimal expected revenue that are provably at least as tight as those obtained from previous approaches. Computational experiments for the multinomial logit choice model with distinct consideration sets show that policies derived from our approach can outperform some recently proposed alternatives, and we demonstrate how aggregation can be used to balance solution quality and runtime.     

Optimal inventory management for a retail chain with diverse store demands

Item demands at individual retail stores in a chain often differ significantly, due to local economic conditions, cultural and demographic differences and variations in store format. Accounting for these variations appropriately in inventory management can significantly improve retailers’ profits. For example, it is shown that having greater differences across the mean store demands leads to a higher expected profit, for a given inventory and total mean demand. If more than one inventory shipment per season is possible, the analysis becomes dynamic by including updated demand forecasts for each store and re-optimizing store inventory policies in midseason. In this paper, we formulate a dynamic stochastic optimization model that determines the total order size and the optimal inventory allocation across nonidentical stores in each period. A generalized Bayesian inference model is used for demands that are partially correlated across the stores and time periods. We also derive a normal approximation for the excess inventory from the previous period, which allows the dynamic programming formulation to be easily solved. We analyze the tradeoffs between obtaining information and profitability, e.g., stocking more stores in period 1 provides more demand information for period 2, but does not necessarily lead to higher total profit. Numerical analyses compare the expected profits of alternative supply chain strategies, as well as the sensitivity to different distributions of demand across the stores. This leads to novel strategic insights that arise from adopting inventory policies that vary by store type.     

Measuring the effects of new brand introduction on inter-brand strategic interaction

This paper empirically investigates the effects of a new brand introduction on the market structure of a product market, i.e., the nature of competition among existing brands. The model is based on the discrete choice multinomial logit model in which the household-specific brand intercepts are decomposed into brand locations in attribute space and households' importance weights for these attributes. The formulation also incorporates the effects of marketing variables on brand choice behavior. The relative proximity of brands in the attribute space provides a measure of the intensity of competitive rivalry among brands. A new brand introduction results in an additional location in this space. Three consequences of the introduction are investigated. (i) Impact on brand locations of extant brands. (ii) Change in the importance weights assigned by households to the attributes. (iii) Effects on households' sensitivities to marketing activities. As some or all of the above could change, these three effects result in eight combinations that need to be studied. The general model is one in which all three components are allowed to change and this nests the remaining seven specifications. The specification that is most consistent with the data can, therefore, be isolated via a statistical test of nested hypotheses. Identifying the consequences of the introduction for market structure has implications for managerial action. An empirical application of the model to household scanner panel data using liquid laundry detergents is provided.     

Price competition and store competition: Store brands vs. national brand

This paper studies pricing strategies in a market channel composed of one national brand manufacturer and two retailers who, each, carry their own store brand and a national brand products. The model accounts for product competition between store brands and the national brand products, as well as for store competition between retailers.     

A greedy algorithm for the two-level nested logit model

We consider the assortment optimization problem under the classical two-level nested logit model. We establish a necessary and sufficient condition for the optimal assortment and develop a simple and fast greedy algorithm that iteratively removes at most one product from each nest to compute an optimal solution.     

Dynamic sequencing and cut consolidation for the parallel hybrid-cut nested L-shaped method

The nested L-shaped method is used to solve two- and multi-stage linear stochastic programs with recourse, which can have integer variables on the first stage. In this paper we present and evaluate a cut consolidation technique and a dynamic sequencing protocol to accelerate the solution process. Furthermore, we present a parallelized implementation of the algorithm, which is developed within the COIN-OR framework. We show on a test set of 51 two-stage and 42 multi-stage problems, that both of the developed techniques lead to significant speed ups in computation time.     

可列集合套

[1]中给出模糊集的分解定理与表现定理，指出可利用集合套H＝{H（λ）|λ∈[0,1]}刻化模糊集。本文定义可列集合套H＝{H（a）|a∈Q}，Q是（0，1）的可列稠密子集。相应地给出新的分解定理与表现定理。指出可利用可列集合套刻化的模糊集。     

Two-stage discrete choice models for scanner panel data: An assessment of process and assumptions

Discrete choice models such as the multinomial logit assume that consumers choose from the full set of alternatives available to them. However, because (i) consumers may not be able to recall or recognize available brands, (ii) consumers may not have the cognitive capacity or mental energy to process information pertaining to all available brands, or (iii) careful consideration of all available brands might be suboptimal from an economic standpoint given the cost of information search, consumers tend to make choices from a relatively small subset of the available brands. This study assesses the process assumptions of existing two-stage models for scanner panel data and their consistency with the actual processes believed to be used by consumers in forming choice sets. After reviewing what is known from two-stage models in scanner data applications, we highlight issues in need of research.     

Robust assortment optimization using worst-case CVaR under the multinomial logit model

We consider robust assortment optimization problems with partial distributional information of parameters in the multinomial logit choice model. The objective is to find an assortment that maximizes a revenue target using a distributionally robust chance constraint, which can be approximated by the worst-case Conditional Value-at-Risk. We show that our problems are equivalent to robust assortment optimization problems over special uncertainty sets of parameters, implying the optimality of revenue-ordered assortments under certain conditions.     

On the topology of nested set complexes

Nested set complexes appear as the combinatorial core of De Concini-Procesi arrangement models. We show that nested set complexes are homotopy equivalent to the order complexes of the underlying meet-semilattices without their minimal elements. For atomic semilattices, we consider the realization of nested set complexes by simplicial fans proposed by the first author and Yuzvinsky and we strengthen our previous result showing that in this case nested set complexes in fact are homeomorphic to the mentioned order complexes.

     

The role of store brand positioning for appropriating supply chain profit under shelf space allocation

We consider a retailer’s decision of developing a store brand (SB) version of a national brand (NB) and the role that its positioning strategy plays in appropriating the supply chain profit. Since the business of the retailer can be regarded as selling to NB manufacturers the shelf space at its disposal, we formulate a game-theoretical model of a single-retailer, single-manufacturer supply chain, where the retailer can decide whether to launch its own SB product and sells scarce shelf-space to a competing NB in a consumer good category. As a result, the most likely equilibrium outcome is that the available selling amount of each brand is constrained by the shelf-space available for its products and both brands coexist in the category. In this paper, we conceptualize the SB positioning that involves both product quality and product features. Our analysis shows that when the NB cross-price effect is not too large, the retailer should position its SB’s quality closer to the NB, more emphasize its SB’s differences in features facing a weaker NB, and less emphasize its SB’s differences in features facing a stronger NB. Our results stress the importance of SB positioning under the shelf-space allocation, in order to maximize the retailer’s value appropriation across the supply chain.     

Price optimization under the extended nested logit model

We examine multi-product price optimization of the extended nested logit (ENL) model proposed by Kovach and Tserenjigmid, including the nested logit, increasing linear nested stochastic, and two-stage nested attraction models as special cases. The well-known constant adjusted markup and adjusted nest-level markup properties are extended to ENL. In addition, we present sufficient conditions under which the objective function is unimodal. We also provide the upper and lower bounds of the optimal adjusted nest-level markup when preconditions are not met.     

Pricing policies under direct vs. indirect channel competition and national vs. store brand competition

This paper analyzes channel pricing in multiple distribution channels under competition between a national brand (NB) and a store brand (SB), where an NB can be distributed both through a direct channel (e-channel) and an indirect channel (local stores) but an SB can be distributed only through an indirect channel. We first explore cross-brand and cross-channel pricing policies. Formulating the problem as a Nash pricing game, we reach two findings: (1) brand loyalty building is profitable for both an NB and an SB; and (2) marketing decisions are more restrictive for an NB channel than they are for the SB channel. We next assess supply chain coordination and reach two findings: (1) wholesale price change does not coordinate the supply chain and (2) an appropriate combination of markup and markdown prices can achieve both supply chain coordination and a win–win outcome for each channel.     

A PTAS for capacitated sum-of-ratios optimization

Motivated by an application in assortment planning under the nested logit choice model, we develop a polynomial-time approximation scheme for the sum-of-ratios optimization problem with a capacity constraint and a fixed number of product groups.