Effects of Remanufacturable Product Design on Market Segmentation and the Environment

Despite documented benefits of remanufacturing, many manufacturers have yet to embrace the idea of tapping into remanufactured‐goods markets. In this article, we explore this dichotomy and analyze the effect of remanufacturable product design on market segmentation and product and trade‐in prices by studying a two‐stage profit‐maximization problem in which a price‐setting manufacturer can choose whether or not to open a remanufactured‐goods market for its product. Our results suggest that it is optimal for a manufacturer to design a remanufacturable product when the value‐added from remanufacturing is relatively high but product durability is relatively low and innovation is nominal. In addition, we find that entering a remanufactured‐goods market in and of itself does not necessarily translate into environmental friendliness. On the one hand, the optimal trade‐in program could result in low return and/or remanufacturing rates. On the other hand, a low price for remanufactured products could attract higher demand and thereby potentially result in more damage to the environment. Meanwhile, external restrictions imposed on total greenhouse gas emissions draw criticism in their own right because they risk stifling growth or reducing overall consumer welfare. Given these trade‐offs, we therefore develop and compare several measures of environmental efficiency and conclude that emissions per revenue can serve as the best proxy for emissions as a metric for measuring overall environmental stewardship.     

Design of Product Grading Procedures*

Consider a situation in which the items produced by a production process are sorted into two grades according to predetermined specifications and sold at two different prices. A loss is incurred by the producer when an item is classified into a grade and its quality does not meet the consumer's requirement of that grade. A loss in selling price is also incurred when an item is classified into a lower quality grade when it can meet the consumer's requirement of a higher grade. Consequently, the producer's profit is determined by sale prices and losses due to consumer dissatisfaction. The optimal grading specifications are determined to maximize the expected profit. Design of product grading procedures can be based on the performance variable of interest or a surrogate variable correlated with the performance variable. The practice of using correlated variables in product grading is common in industry. We develop product grading models for both the performance variable and a correlated variable.     

When to Offer Lower Quality or Remanufactured Versions of a Product

We investigate the profitability of adding a lower quality or remanufactured product to the product portfolio of a monopoly firm, both in single‐period and steady‐state settings. Consumer behavior is characterized by a deterministic utility function for the original product and a nonlinear relative utility function for the lower quality product. We find a threshold for the cost of the low‐quality product below which it is optimal to add it to the firm's portfolio, and show that while a cost advantage is necessary to make the lower quality offering profitable under linear or convex relative utility functions, market segmentation alone can justify the addition of the lower quality product under concave relative utility functions. In particular, we characterize (i) the new product cost under which it is optimal to offer a lower quality version of the product even if it is as costly to produce as the original product; and (ii) the weighted average of new and remanufactured product costs in the steady state under which it becomes cost effective to offer new products under the remanufactured label. Finally, we also identify the maximum possible profits from customer segmentation and the form of the relative utility function that achieves them. We discuss the implications for the common marketing practices of branding and generics.     

Optimizing Service Attributes: The Seller's Utility Problem*

Service designers predict market share and sales for their new designs by estimating consumer utilities. The service's technical features (for example, overnight parcel delivery), its price, and the nature of consumer interactions with the service delivery system influence those utilities. Price and the service's technical features are usually quite objective and readily ascertained by the consumer. However, consumer perceptions about their interactions with the service delivery system are usually far more subjective. Furthermore, service designers can only hope to influence those perceptions indirectly through their decisions about nonlinear processes such as employee recruiting, training, and scheduling policies. Like the service's technical features, these process choices affect quality perceptions, market share, revenues, costs, and profits. We propose a heuristic for the NP‐hard service design problem that integrates realistic service delivery cost models with conjoint analysis. The resulting seller's utility function links expected profits to the intensity of a service's influential attributes and also reveals an ideal setting or level for each service attribute. In tests with simulated service design problems, our proposed configurations compare quite favorably with the designs suggested by other normative service design heuristics.     

多产品竞争中企业产品线最优区域的选择

多产品厂商产品线延伸收缩的决策,不仅仅与自身的竞争实力有关,还与产品的市场特性有关。低端市场上的产品处于生命周期末期,厂商的市场空间不断缩小,市场竞争异常激烈。而新兴市场上的产品从成长期向成熟期过渡,技术不断成熟,消费群体稳步增长。拥有技术优势的厂商必然会收缩低端产品线,放弃低端市场,然后延伸高端产品线,进入新兴市场,从而提升自身的利润水平;由于低端市场上厂商的退出,市场竞争烈度的下降,低端市场在位企业的利润水平也会因此有所改善。     

A Structural Equation Model of New Product Design and Development*

This research uses structural equation modeling to analyze the effects of supplier assessment, Just‐In‐Time, and quality management strategies on new product design and development. A survey of senior managers who are members of the American Production and Inventory Control Society in the United States was used to test the relationships between the constructs in the model. In general, the survey results supported the proposed structural equation model. The data showed that supplier assessment and Just‐In‐Time strategies were correlated and affected the quality management strategy used, which in turn influenced the new product design and development strategy. The data also showed that the Just‐In‐Time strategy directly influenced the new product design and development strategy.     

A Computational Study of Replicated Clustering with an Application to Market Segmentation*

In most commercial applications of k-means clustering, researchers choose one set of kseed points to start the partitioning process; often, the initial set of seeds is chosen randomly. Using Monte Carlo simulation, we show that significant benefits are associated with replicated starting configurations that incorporate seed selection procedures based on a hierarchical clustering of sample points drawn from the original data matrix. A real-world application of the approach is then presented.     

A UNIFIED APPROACH TO THE PRICE-BREAK ECONOMIC ORDER QUANTITY (EOQ) PROBLEM*

In many developing countries where supply is limited, a premium rather than a discounted price is paid for buying in larger amounts. In order for management science/operations research solutions to be relevant to developing economies, such realities need to be explicitly recognized and any decisions evaluated from that perspective. To illustrate this point, a typical inventory-purchasing problem is solved. In the process, formulae are developed that introduce simultaneous price and quantity sensitivity into the inventory equation. A systematic procedure is suggested to locate the optimal order quantity for a given schedule of discounts or premiums.     

A Dynamic Model of Product Quality and Pricing Decisions on Sales Response

This paper presents a dynamic model that examines the influence of price and customer perception of product quality on the sales rate of a firm producing durable goods. The sales rate of the firm is modeled as a function of its price, average product life, perceived quality, and market potential. Specifically, the model considers: (1) the process by which perceived quality is determined by including the effects of the average life of a product and quality weighted units in the market; (2) the time delay in the influence of actual quality on perceived quality; (3) the process by which demand (i.e., potential sales) is converted to realized sales due to the effects of price and perceived quality; and (4) the saturation effect and associated non-linearity in the demand function. The model presented is a reformulation and extension of the model originally proposed by Bass [2]. The validity of the model is tested using historical data on For Mustang.     

我国制造型企业市场导向和创新导向对新产品绩效影响的实证研究

本研究基于我国227家制造型企业的问卷调查数据,实证考察了市场导向和创新导向对新产品开发绩效的影响,以及创新导向和环境变动在市场导向和新产品绩效关系中的调节作用。结果显示:(1)本研究的概念模型整体拟合度优于西方常用模型;(2)市场导向和创新导向对制造型企业新产品开发绩效的影响显著为正,且均高于以前文献研究的一般水平;(3)创新导向和技术变化对于市场导向和新产品绩效的关系起到正向调节作用;(4)市场变化和竞争强度的调节作用不显著。研究结果对于制造型企业改善产品创新绩效具有重要的启示意义。     

对市场导向、顾客资产导向与新产品开发绩效之间关系的探索性研究——基于中国背景的调节效应模型

当前,市场导向的收益和顾客资产的重要性已经得到了广泛的认同。然而,一方面有关市场导向的认识尚未达成共识,另一方面有关顾客资产的认识也出现了新的误区,而且尚未有文献对新产品开发绩效的复杂影响进行过系统的实证研究。本文旨在开发测量顾客资产导向的有效量表,并通过区分反应型市场导向和先动型市场导向,运用中国企业的实证数据揭示它们对新产品开发绩效的差异性影响,并检验了顾客资产导向对两种不同市场导向与新品绩效之间关系的调节作用,从而引导学者和企业家对市场导向和顾客资产导向的作用形成更为科学的认识。结果发现,顾客资产导向对新产品开发绩效的直接影响并不显著,但却可以对先动型市场导向与新产品开发绩效之间的关系产生积极的调节作用。     

Incorporating Price and Replacement Purchases in New Product Diffusion Models for Consumer Durables*

The article presents theoretical and empirical research findings which incorporate price and replacement purchases in new product diffusion models. On the theoretical side, this paper characterizes, qualitatively, optimum pricing policies for new products. Possible entry of rivals is not considered, but repeat sales, cost learning dynamics and discounting of future profit streams are allowed. Theoretical research findings suggest that the inclusion of repeat purchases in the diffusion model significantly changes the derived optimal pricing policy even if replacements were not price dependent. On the empirical side, alternative first purchase and repeat purchase models have been estimated and compared using nonlinear procedures. The diffusion data analyzed is related to nine consumer durables. Empirical research findings suggest that, for the considered product categories, diffusion is basically an imitative process, price can affect first and replacement purchases, and unit production cost is a decreasing function of cumulative first purchases. Managerial implications of the research findings are also discussed.     

Two Stochastic Multidimensional Choice Models for Marketing Research

Two recently developed probabilistic multidimensional models for analyzing pairwise choice data are introduced, discussed in terms of their differential properties, and extended in several ways. The first one, the wandering vector model, was originally suggested by Carroll [12] and extended by De Soete and Carroll [30]. The second model, called the wandering ideal point model, is a more recently proposed [32] unfolding analog of the wandering vector model. A general maximum likelihood estimation method for fitting the various models described is mentioned, as well as a statistical test for assessing the goodness of fit. Finally, an application of the models is provided concerning consumer choice for some 14 brands of over-the-counter analgesics to illustrate how such models can be gainfully utilized for marketing decision making concerning product positioning.     

Dual Objective Segmentation to Improve Targetability: An Evolutionary Algorithm Approach**

Cluster‐based segmentation usually involves two sets of variables: (i) the needs‐based variables (referred to as the bases variables), which are used in developing the original segments to identify the value, and (ii) the classification or background variables, which are used to profile or target the customers. The managers’ goal is to utilize these two sets of variables in the most efficient manner. Pragmatic managerial interests recognize the underlying need to start shifting from methodologies that obtain highly precise value‐based segments but may be of limited practical use as they provide less targetable segments. Consequently, the imperative is to shift toward newer segmentation approaches that provide greater focus on targetable segments while maintaining homogeneity. This requires dual objective segmentation, which is a combinatorially difficult problem. Hence, we propose and examine a new evolutionary methodology based on genetic algorithms to address this problem. We show, based on a large‐scale Monte Carlo simulation and a case study, that the proposed approach consistently outperforms the existing methods for a wide variety of problem instances. We are able to obtain statistically significant and managerially important improvements in targetability with little diminution in the identifiability of value‐based segments. Moreover, the proposed methodology provides a set of good solutions, unlike existing methodologies that provide a single solution. We also show how these good solutions can be used to plot an efficient Pareto frontier. Finally, we present useful insights that would help managers in implementing the proposed solution approach effectively.     

A Goal Programming Model for Effective Segment Determination: A Comment and Application

This note presents a model for the effective market segment determination problem. The integer goal programming model was developed for a nonprofit health care organization. The approach is an alternative application of a model presented by McClure and Wells [7]. The model includes input from the organization's clients as well as the organization's decision makers. A distinctive element is the simultaneous development of market segments and the consideration of management, institutional, and resource constraints. The purpose of the model was to aid the decision makers in determining if effective market segments exist which can be reached with information and educational materials concerning infant nutrition and breastfeeding. The model was tested and found to be effective in helping the decision makers segment their clients.     

A Model for Determining Retail Product Category Assortment and Shelf Space Allocation

We develop a category management model to aid retailers in the space constrained decisions of which products to stock (assortment) and how much shelf space to allocate to those products. The model is formulated as a constrained optimization problem with two basic decision variables: assortment and allocation of space to the items in the assortment. The non-linearities in the objective function and the zero-one decision variables disallow a closed form solution. We develop a heuristic solution procedure based on simulated annealing and test it on a problem with a known optimum. We also apply the technique to a larger problem without a known optimum. Finally, the solution found by simulated annealing is compared against a solution produced using a shelf allocation rule based on share of sales.     

On the Creation of Acceptable Conjoint Analysis Experimental Designs

Conjoint analysis studies typically utilize orthogonal fractional factorial experimental designs to construct a set of hypothetical stimuli. Occasionally, these designs include environmentally correlated attributes that can lead to stimulus profiles that are not representative of the subject's environment. To date, no one has proposed a remedy well-grounded in statistical theory. This note presents a new methodology utilizing combinatorial optimization procedures for creating modified fractional factorial designs that are as “orthogonal” as possible, which do not contain nonrepresentative stimulus profiles.     

A Note on ‘An Approximate Solution to Deterministic Systems’

In a recent paper, Moeeni and Chang (1990) presented an efficient heuristic solution method to solve a specific case of a deterministic kanban system. In this paper, we first provide a simple numerical example to show that the kanban system formulation proposed by Moeeni and Chang can result in infeasible solutions. We then present a modified formulation and show its feasibility. We discuss the implications of the corrected formulation and finally present conclusions and future research directions.     

The Role of Existing Knowledge in New Product Innovativeness and Performance

The purpose of this study is to provide a more thorough assessment of the link between existing knowledge and organizational performance than currently exists in the literature. We identify factors and processes influential in the management of existing knowledge within the areas of learning culture, knowledge building, and organizational performance. Through structural equation modeling, a more thorough examination is given of the role existing knowledge plays in new product performance and innovativeness. In completing this task, we provide insight into the subprocesses of knowledge building by evaluating the influence of shared interpretation and two aspects of information acquisition—efficiency and degree of innovativeness of newly acquired information—on new product development (NPD) outcomes. Included in the examination of these processes are organizational culture and structure characteristics believed to influence knowledge management success.     

Multiproduct,Multicriteria Model for Supplier Selection with Product Life‐Cycle Considerations

In industrial purchasing contexts firms often procure a set of products from the same suppliers to benefit from economies of scale and scope. These products are often at different stages of their respective product life cycles (PLCs). Firms consider multiple criteria in purchasing such products, and the relative importance of these criteria varies depending on the PLC stage of a given product. Therefore, a firm should select suppliers and choose sourcing arrangements such that product requirements across multiple criteria are satisfied over time. The extant models in sourcing literature for evaluating and selecting suppliers for a portfolio of products have not considered this important and practical issue faced by firms. This article proposes a mathematical model that effectively addresses this issue and contributes to the sourcing literature by demonstrating an approach for optimally selecting suppliers and supplier bids given the relative importance of multiple criteria across multiple products over their PLC. The application of the model on a hypothetical data set illustrates the strategic and tactical significance of such considerations.