基于属性重要度的产品定制程度测量模型及定制策略

定制程度的高低反映了制造商对顾客个性化需求响应的程度。运用组合分析法建立基于效用的顾客属性定制偏好测量模型和基于属性重要度的产品定制程度测量模型;以笔记本电脑装配定制为研究对象,运用K-means聚类将样本分成5个不同的属性偏好群体,测量个体与5个属性偏好群体满意度,比较分析多样化生产方式与定制化生产方式下顾客满意度的差异,建立不同偏好群体定制程度与顾客满意度之间的回归模型。研究表明,按照定制属性重要度从大到小依次进行定制生产比细分市场的多样化生产能更有效地提高顾客满意度。     

基于在线客户评论的客户细分研究

针对基于在线客户评论数据进行客户细分分析的问题,设计了二阶段客户细分分析框架.在客户偏好建模阶段,设计了同义属性识别方法和属性偏好换算方法,基于产品属性树结构,构建粒度统一的客户偏好向量;在客户聚类阶段,设计了包含最优聚类数识别的聚类流程,基于模糊C均值聚类方法,对客户进行聚类.     

基于消费行为的市场细分模型构建与验证——以移动通信行业为例

针对客户偏好和客户需求开展市场营销活动是每一个移动运营商最为关注的问题.为此,分析了移动通信行业现行的以人口统计变量和ARPU值为划分维度的市场细分方法,并在此基础上提出了以消费行为作为划分维度的市场细分模型,该模型将客户按照"当前价值"、"发展性"和"忠诚度"3个维度进行细分,并从数据库中分别提取相应的变量对各个维度进行有效测量.同时采用了K-means聚类算法和相关的数据挖掘和统计方法对模型进行了验证,进一步确定了模型的实用价值.     

基于利益偏好的大学生手机市场细分实证研究

论文从利益细分的角度,对大学生购买手机时追求的利益进行市场的细分研究。首先通过定性研究,选取反映大学生手机决策中利益偏好的测量变量;然后采用利益偏好量表进行调查,对有关数据进行因子分析和聚类分析,得到具有利益偏好的五个细分市场;再对这五个细分市场的人口统计变量进行分析,刻画出了各个子市场的特征,从而揭示出基于利益偏好形成的细分市场与大学生群体特征的潜在关系。     

利益细分变量研究与消费者市场细分

在当今激烈的市场竞争环境中,市场细分理论对企业市场营销活动的指导作用已为越来越多的企业所认同,并引起市场营销研究人员的关注。本文从市场细分变量入手,通过对市场细分变量的四大类型和消费者市场细分组合的多样性进行分析,并以针对国内牙膏市场上主要品牌所进行的利益细分调研为例,论述了进行利益细分研究对市场营销的指导意义。     

基于蚁群智能的客户群偏好分析方法

采用蚁群智能的数据挖掘方法,根据客户对产品属性的偏好评分,对客户进行有效的分类.将客户偏好作为n维空间中的一个点,运用基于蚁群智能的聚类方法,根据预先设定的群体相似系数和拾起或放下概率进行聚类分析,在空间中采用递归算法,以获得不同偏好特征的客户群体模式.     

对中国饮料市场利益细分的探索性研究

本文从市场细分理论入手,分析了市场细分变量的四大种类、对消费者市场的意义以及组合的多样性;通过对我国饮料市场上主要品牌进行利益细分调研,论述了进行利益细分研究对市场营销的价值和利益细分是建立细分市场的必要前提。     

市场细分新范式:基于两类不同产品的实证研究

本文根据描述变量对行为变量影响的本质原因和有关学者提出的模型,提炼出主要由客观需要、目标价值观、信号价值观和消费资源构成的关键描述变量,认为如果关键描述变量对人口统计因素等基本描述变量与行为变量之间的关系具有中介作用,就可对其进行直接测量和细分,以用于解释和预测行为变量,由此可解决营销者不知如何在复杂的描述变量中选择最有用的变量进行市场细分的困惑,降低市场分析和决策成本.为了验证关键描述变量是否具有中介作用、以及新的市场细分范式是否容易操作,本研究选择了私家车和笔记本电脑两种产品进行了实证研究.研究结果表明,关键描述变量具有中介作用,新的市场细分范式具有可操作性.     

客户细分方法研究综述

本文研究以客户为导向的各种细分方法.首先简要描述了各种细分方法在细分维度、细分依据以及与细分目标的关联性这三个方面所表现出来的特点,同时比较了它们之间的差异;其次以维度和细分技术为主要内容对四种主要的细分方法进行了详细的叙述:人口统计细分、生活方式细分侧重维度内涵的变迁,而行为细分和利益细分则侧重细分技术的发展,尤其是利益细分;最后在结束语部分指出了现有细分方法的不足和发展方向.     

考虑质量水平的产品更新策略研究

将质量水平作为关键因子引入到更新产品设计的最优决策问题。通过界定质量水平、质量效用、顾客质量偏好及产品更新率的内涵，构建了新旧产品同时存于市场的竞争模型和旧产品退出市场的非竞争模型，求解得到了质量效用、质量水平改进量和顾客质量偏好的关系，确定了更新产品最佳质量水平的取值。通过数值分析，验证与分析了最佳质量水平与质量效用的关系，给出了新旧产品价格与质量优势区间，为企业的产品更新决策提供了科学依据。     

Evaluating Consumer Preferences for Existing Multiattribute Products: A Non-Metric Approach

A model evaluating consumer preferences for multiattribute products is derived. The model possesses the following features: (1) the method works for existing products; (2) the input data require only overall product rankings and attribute rankings; (3) the distribution of part worths (utility) for particular attributes is derived and used to judge the trade-offs among different attributes; (4) the procedure can be implemented with existing software; and (5) the attributes do not need to be quantifiable.     

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.     

考虑市场细分的零售商自主以旧换新策略研究

在越来越多企业开始自主推行以旧换新业务的背景下,本文从供应链的视角出发,构建考虑市场细分和消费者效用的策略模型,研究零售商自主以旧换新策略选择及相应的供应链决策问题,着重分析市场细分和旧产品折旧程度对策略选择、决策和供应链效率的影响.研究发现:零售商的策略选择除了受产品制造成本影响外,还依赖于外部客户比例和旧产品折旧程度;当老客户占比和旧产品折旧度处于某区域时,自主以旧换新策略优于无以旧换新策略;在某些情况下,制造商的期望策略与零售商的最优策略相悖;供应链效率受客户比例和旧产品折旧度影响.此外,当老客户占比或旧产品折旧度高于某阈值时,老客户对主体的利润贡献大于新客户.本文的研究结论对企业在供应链环境下推行以旧换新政策有一定的理论指导意义.     

Design of the Reverse Channel for Remanufacturing: Must Profit‐Maximization Harm the Environment?

A key attribute of a remanufacturing strategy is the division of labor in the reverse channel, especially whether remanufacturing is performed in‐house or outsourced. We investigate this decision for a retailer who accepts returns of a remanufacturable product. Our formulation considers the cost structures of the two strategies, uncertainty in the input quality of the collected/returned used products, consumer willingness‐to‐pay for remanufactured product, the extent to which the remanufactured product cannibalizes demand for a new product, and the power structure in the channel. For the profit‐maximizing retailer, the differentials in variable remanufacturing costs drive strategy choice, and higher fixed costs of in‐house remanufacturing favors outsourcing. The variable remanufacturing costs and the balance of power in the prospective outsourced reverse channel are the key drivers of environmental impact, as measured by the retailer's propensity to remanufacture. While profitability and environmental goals often conflict, they align under certain conditions. These include (a) the third party has less bargaining power; or (b) the fixed cost for in‐house remanufacturing is relatively high. All else equal, when remanufacturing is outsourced, the environment fares better if the third party has leadership power. We generalize to the cases when remanufacturing achieves a quality level less than “good‐as‐new" and when used items have non‐zero salvage value. Analysis of these extensions illuminates how relative power in the reverse channel drives the firms’ preferences, as well as the end customers’ consumption experience.     

Applications of sequential set partitioning: a set of technical information systems problems

Many problems that appear in different contexts are conceptually similar and so are amenable to solution by a common technique. Three such technical Information Systems (IS) problems are: (1) segmentation of computer programs; (2) attribute discretization for decision tree induction; and (3) design of hash tables in database systems. In this paper we show how each of these seemingly different problems can be formulated as a sequential (set) partitioning problem, and solved using a parametric linear programming (LP) procedure. This approach provides optimal solutions unlike previous solution approaches which were either greedy heuristics or limited to solving only a specific problem situation. Given the likelihood that other applications of the sequential partitioning problem exist in IS, the material presented here could be useful to other researchers in formulating the problem at an appropriate level of abstraction so that available optimal solution approaches can be identified. In addition to providing a common solution method, parametric LP frees the user from having to make premature decisions regarding the number of groups for the partition, and this decision can be delayed post solution.     

Market segmentation: A multiple criteria approach combining preference analysis and segmentation decision

We propose a new multiple criteria decision aiding approach for market segmentation that integrates preference analysis and segmentation decision within a unified framework. The approach employs an additive value function as the preference model and requires consumers to provide pairwise comparisons of some products as the preference information. To analyze each consumer’s preferences, the approach applies the disaggregation paradigm and the stochastic multicriteria acceptability analysis to derive a set of value functions according to the preference information provided by each consumer. Then, each consumer’s preferences can be represented by the distribution of possible rankings of products and associated support degrees by applying the derived value functions. On the basis of preference analysis, a new metric is proposed to measure the similarity between preferences of different consumers, and a hierarchical clustering algorithm is developed to perform market segmentation. To help firms serve consumers from different segments with targeted marketing policies and appropriate products, the approach proposes to work out a representative value function and the univocal ranking of products for each consumer so that products that rank in the front of the list can be presented to her/him. Finally, an illustrative example of a market segmentation problem details the application of the proposed approach.     

Distribution of Aggregate Utility Using Stochastic Elements of Additive Multiattribute Utility Models

Conventionally, elements of a multiattribute utility model characterizing a decision maker's preferences, such as attribute weights and attribute utilities, are treated as deterministic, which may be unrealistic because assessment of such elements can be imprecise and erroneous, or differ among a group of individuals. Moreover, attempting to make precise assessments can be time consuming and cognitively demanding. We propose to treat such elements as stochastic variables to account for inconsistency and imprecision in such assessments. Under these assumptions, we develop procedures for computing the probability distribution of aggregate utility for an additive multiattribute utility function (MAUF), based on the Edgeworth expansion. When the distributions of aggregate utility for all alternatives in a decision problem are known, stochastic dominance can then be invoked to filter inferior alternatives. We show that, under certain mild conditions, the aggregate utility distribution approaches normality as the number of attributes increases. Thus, only a few terms from the Edgeworth expansion with a standard normal density as the base function will be sufficient for approximating an aggregate utility distribution in practice. Moreover, the more symmetric the attribute utility distributions, the fewer the attributes to achieve normality. The Edgeworth expansion thus can provide a basis for a computationally viable approach for representing an aggregate utility distribution with imprecisely specified attribute weights and utilities assessments (or differing weights and utilities across individuals). Practical guidelines for using the Edgeworth approximation are given. The proposed methodology is illustrated using a vendor selection problem.     

Strategic implications of consumer food safety preferences

This study examines the tradeoffs consumers are willing to make relative to food safety attributes and other product attributes, such as quality and price, and develops implications for both the government and private sector firms. Conjoint analysis was used to elicit consumers’ preferences for fresh Red Delicious apples. The attributes studied include price, product quality as depicted by the level of defects, a variable representing the level of pesticide usage and the associated cancer risk, and a variable representing different levels of government inspection.The results indicated that most consumers have a strong preference for increased food safety. Government policy options that are explored include stricter production standards, improved regulatory monitoring, and government-defined labels. Private industry options that are examined include grower labels, retailer labels, and third party labels.