基于消费者隐性需求的营销模式研究策略

消费者隐性需求的相关理论和实践研究逐渐受到国内外学者的重视,这对于营销理论的再造和营销学的演进具有一定的理论价值。本文从营销范式的演进规律归纳得出,营销范式的转换归根结底源于隐性需求的开发。在此基础上,对传统营销模式及营销组合对隐性需求研究的普适性进行了检验,并探讨了基于隐性需求的4Vs营销模式及其现实意义。     

品牌质量差异、消费者产品涉入程度对品牌敏感的影响研究

品牌敏感是消费者品牌行为研究方面的一个新课题,它反映了消费者在购买决策过程中对品牌的重视程度.同一产品类别不同品牌之间的质量差异和消费者的产品涉入程度被认为是品牌敏感的两类主要解释变量.本文利用结构方程模型进行的实证分析表明,品牌质量差异和消费者产品涉入程度总体上对品牌敏感起正向影响作用,但该作用因产品类别而异,因产品质量和产品涉入程度的维度而异.     

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.     

Retailer's Response to Alternate Manufacturer's Incentives Under a Single‐Period,Price‐Dependent,Stochastic‐Demand Framework*

This article considers the joint development of the optimal pricing and ordering policies of a profit‐maximizing retailer, faced with (i) a manufacturer trade incentive in the form of a price discount for itself or a rebate directly to the end customer; (ii) a stochastic consumer demand dependent upon the magnitude of the selling price and of the trade incentive, that is contrasted with a riskless demand, which is the expected value of the stochastic demand; and (iii) a single‐period newsvendor‐type framework. Additional analysis includes the development of equal profit policies in either form of trade incentive, an assessment of the conditions under which a one‐dollar discount is more profitable than a one‐dollar rebate, and an evaluation of the impact upon the retailer‐expected profits of changes in either incentive or in the degree of demand uncertainty. A numerical example highlights the main features of the model. The analytical and numerical results clearly show that, as compared to the results for the riskless demand, dealing with uncertainty through a stochastic demand leads to (i) (lower) higher retail prices if additive (multiplicative) error, (ii) lower (higher) pass throughs if additive (multiplicative) error, (iii) higher claw backs in both error structures wherever applicable, and (iv) higher rebates to achieve equivalent profits in both error structures.     

产品涉入度、消费者从众与品牌承诺:品牌敏感的中介作用——以轿车消费市场为例

在高度竞争的市场环境下,提高消费者品牌承诺是企业获得长期竞争优势的有效方法。本文提出了产品涉入度、消费者从众及品牌敏感对品牌承诺的影响机制模型,并以轿车消费市场为例运用结构方程模型进行了实证研究。结果表明,产品涉入度和消费者从众对品牌承诺有正向显著影响,品牌敏感在产品涉入度、消费者从众和品牌承诺间起部分中介作用。     

On the Measurement of Perceived Consumer Risk

The role of perceived risk in consumer behavior has been studied extensively by academic researchers. This paper introduces a methodology for the measurement of the effects of product features, marketing mix components, and individual differences on perceived consumer risk based on theoretical foundations in the literature. A conjoint-type model based on paired comparison judgments is estimated to provide attribute weights. A modification of a stochastic multidimensional scaling-based vector model is then used to measure and summarize individual consumer differences with respect to the impact of brand attributes and marketing mix components on latent levels of perceived consumer risk. An illustration is provided using students’ risk perceptions of sports cars.     

消费者品牌忠诚对品牌商再制造市场策略的影响

独立再制造商IR的市场进入给品牌商带来了显著的竞争压力。品牌忠诚源于消费者对某个产品品牌的信任和特殊情感,在产品选择中具有明显的倾向性和排他性,进一步增加了品牌商市场策略的复杂性。针对这一现象,本文采用博弈论结合数值仿真研究了消费者具有品牌忠诚特性下的品牌商再制造市场策略问题。建立并求解了IR不进入且品牌商不再制造（n）、IR不进入且品牌商再制造（nR）、IR进入且品牌商不再制造（nr）、IR进入且品牌商再制造（nrR）四种市场模式,对模型结果进行了灵敏度分析,并探讨了各成员的模式偏好。研究表明：新产品价格、品牌再制品价格、一般再制品价格均与品牌忠诚度正相关;品牌忠诚度的提高一定增大品牌商的利润,但不一定会降低IR利润;当新产品制造成本较高时,品牌商的模式偏好始终为nR$\succ$nrR$\succ$n$\succ$nr,较低时模式偏好受到消费者品牌忠诚度的大小的影响;nr和nrR模式下,品牌忠诚度仅可能提高品牌消费者剩余,但会降低普通消费者剩余、总消费者剩余和社会总福利。     

基于品类管理和需求外生模型的医药电商网页空间优化策略

网页空间优化对电子商务企业的绩效有着显著影响。本文结合医药品的特性，利用需求外生模型从品类管理的角度研究医药电商的网页空间优化问题，即有限网页空间内的内容优化与内容布局优化。考虑存在商品缺货以及蚕食效应的情况下，本文首先基于需求外生模型使用极大似然估计法估计了商品市场份额与商品替代率，然后提出最大市场份额指标并构建了一个加权最大市场份额最大化的整数规划模型来优化医药电商网页的内容与内容布局。通过对中国知名医药电商1药网2015年8月1日到10月31日的乙肝类抗病毒药物专栏的销售数据进行实证分析，结果表明，本模型优化的推送内容和布局顺序可以有效提高1药网各药品专栏最高至27.21%的销量，乙肝其他抗病药物专栏可以提高8.06%。研究表明，本文提出的基于最大市场份额最大化的优化模型能有效决策网页空间优化来提高医药电商的销量与市场占有率。     

考虑网络退货和渠道成本时全渠道BOPS定价与服务决策

随着线上线下融合的全渠道零售的兴起，越来越多的品牌商开始为顾客提供线上购买线下取货BOPS （Buy Online and Pickup in Store）的购物选择。本文考虑网络退货和渠道成本，基于网络渠道、实体渠道和BOPS渠道下的消费者效用函数构建品牌商开设BOPS渠道前后的利润模型，分析BOPS模式对品牌商需求分布和盈利能力的影响，研究定价和服务的最优决策。结果表明：（1）当网络退货率和BOPS渠道不便利程度之间满足特定关系时，开设BOPS渠道可使品牌商总需求增加、网络渠道和实体渠道的需求减少；（2）当网络退货率达到一定阈值或BOPS渠道很便利时，开设BOPS渠道可使品牌商总利润增加；（3）当网络退货率很低而网络渠道购物成本较高时，开设BOPS渠道可使品牌商获利更大；（4）在交通便利之处增设具有体验服务的顾客自提门店，不论网络渠道购物成本和网络退货率高低，甚至适当提升商品定价也可使品牌商有利可图。本研究可为品牌商实施BOPS全渠道战略提供一定的管理见解。     

品牌和单品忠诚对在线消费者选择行为的影响研究

不同消费者对于不同品牌特性有不同的偏好和忠诚度,如果不考虑不同类型的偏好,不在消费者品牌选择模型中引入消费者的品牌忠诚或单品忠诚行为,将不能很好地刻画消费者购买行为的异质性和动态性,难以提高模型的解释力度。文章通过构建动态多项Logit离散选择模型,研究和鉴别在线渠道每一个消费者品牌忠诚因子和单品忠诚因子。研究发现,在线环境下消费者在可乐产品的选择上,不同的忠诚特性对在线消费者品牌选择的影响强度是不同的,其中单品忠诚对在线消费者品牌选择的影响最为显著,这不仅刻画了消费者购买概率的异质性,而且提高了模型的解释力度;不同的属性虽然会对在线消费者的品牌选择行为产生影响,但这种影响并不是孤立存在的,而是会受到其他属性或忠诚变量的影响而产生相应变化。     

营销伦理对品牌重生影响的实证研究

本文构建了非营销伦理行为、品脾资产衰减和品牌重生难度三个变量之间的结构方程模型,利用来自教育培训业的数据进行了实证研究。结果发现,非利他主义营销行为和非社会公正营销行为直接影响品牌重生难度;利己主义营销行为对品牌衰减影响显著,并对品牌重生难度产生间接影响;非经典效用营销行为对品牌资产衰减和品牌重生难度都产生了直接影响,并对品牌重生难度产生间接效应;品牌资产衰减对品牌重生难度存在显著的直接影响。消费者从不同视角感知到的企业非营销伦理行为越严重,企业品牌重生的可能性就越小。     

Mass Customization and Guardrails: “You Can Not Be All Things to All People”

A mass customization strategy enables a firm to match its product designs to unique consumer tastes. In a classic horizontal product‐differentiation framework, a consumer's utility is a decreasing function of the distance between their ideal taste and the taste defined by the most closely aligned product the firm offers. A consumer thus considers the taste mismatch associated with their purchased product, but otherwise the positioning of the firm's product portfolio (or, “brand image”) is immaterial. In contrast, self‐congruency theory suggests that consumers assess how well both the purchased product and its overall brand image match with their ideal taste. Therefore, we incorporate within the consumer utility function both product‐specific and brand‐level components. Mass customization has the potential to improve taste alignment with regard to a specific purchased product, but at the risk of increasing brand dilution. Absent brand dilution concerns, a firm will optimally serve all consumers’ ideal tastes at a single price. In contrast, by endogenizing dilution costs within the consumer utility model, we prove that a mass‐customizing firm optimally uses differential pricing. Moreover, we show that the firm offers reduced prices to consumers with extreme tastes (to stimulate consumer “travel”), with a higher and fixed price being offered to those consumers having more central (mainstream) tastes. Given that a continuous spectrum of prices will likely not be practical in application, we also consider the more pragmatic approach of augmenting the uniformly priced mass customization range with preset (non‐customized) outlying designs, which serve customers at the taste extremes. We prove this practical approach performs close to optimal.     

Modeling whether,what and how much to buy the right way: an empirical analysis with implications for model building

Whether, what and how much to buy are central decisions in consumer goods markets. Marketing research commonly uses a sequential approach where quantity decision is conditional on purchase incidence and brand choice (e.g., Ailawadi et al. in J Mark Res 44:450–467, 2007). This approach assumes separability between decisions and suffers from selectivity bias. The bias can be overcome by explicitly controlling for it (e.g., Zhang et al. in Rev Mark Sci 3(1), 2005) or by using one unifying utility function, a method considered “state of the art in analyzing purchase behavior in a single product category” (e.g., Song and Chintagunta in J Mark Res 44(4):595–612, 2007). However, this latter method puts restrictive assumptions on the influence of prices on choices, which may affect managerial implications derived from the model results. This study investigates the effect of selectivity bias by comparing the sequential approach—with and without explicitly controlling for endogeneity bias—to the unifying utility function approach. Based on household panel data from three categories, we illustrate the extent to which managerial implications from these frameworks differ. We show that the superiority of one framework versus the other depends on the specific category and its characteristics. The managerial implications of using the “wrong” framework are demonstrated by conducting two simulation studies; these show that price elasticities substantially deviate across frameworks.     

Management of school locations allowing for free school choice

Nearly without exception, we find in literature (school) location models with exogenously given demand. Indeed, we know from a large number of empirical studies that this assumption is unrealistic. Therefore, we propose a discrete location model for school network planning with free school choice that is based on simulated utility values for a large average sample. The objective is to maximize the standardized expected utility of all students taking into account capacity constraints and a given budget for the school network. The utility values of each student for the schools are derived from a random utility model (RUM). The proposed approach is general in terms of the RUM used. Moreover, we do not have to make assumptions about the functional form of the demand function. Our approach, which combines econometric and mathematical methods, is a linear 0–1 program although we consider endogenous demand by a highly non-linear function. The proposed program enables practicing managers to consider student demand adequately within their decision making. By a numerical investigation we show that this approach enables us to solve instances of real size optimally – or at least close to optimality – within few minutes using GAMS/Cplex.     

考虑消费者效用与保鲜的生鲜农产品EOQ模型

针对生鲜农产品新鲜度随时间减小的特点,构造受生鲜农产品新鲜度和零售价格影响的消费者时变效用函数,分析了消费者在不同时刻够买生鲜农产品的效用和数量的变化,并基于此建立了消费者偏好影响需求的生鲜农产品EOQ模型;以提高消费者效用为目的,分析了两种不同保鲜情形下零售商的最优订货决策和最优保鲜投入。研究发现,零售商的最优保鲜投入并不能使消费者效用最大化,满足消费者对生鲜农产品新鲜度的要求必须依靠政府的宏观调控。     

消费者效用测度与产业需求函数

把概率解释为Ramsey的信念度,商品效用便可赋予von Neumann-Morgenstern效用性质从而得到测度;按二元价值结构的消费偏好特性建立新的需求模型,可导出在严格意义上用于产业分析的非线性需求函数,为解释现代产业组织及竞争行为提供科学依据。     

Enhancing corporate social responsibility: Contract design under information asymmetry

We consider a two-stage supply chain in which a contract manufacturer (CM) sells products through a brand name retailer. The contract manufacturer can invest in corporate social responsibility (CSR) activities to improve customer perception about the firm and increase demand, while the retailer can influence the demand by exerting marketing efforts. We design optimal contracts for such a supply chain, which faces information asymmetry. The wholesale price contract was developed as the base model to derive insight into the value of information sharing. We examine the impact of CSR cost on CSR commitment and profits. We find that CM׳s CSR cost impacts the CM׳s and the retailer׳s profits differently. Under certain conditions, the CM׳s profit will increase with cost, while that of the retailer is uncertain. We also propose two-part tariff contracts for both the symmetric and asymmetric cases with the aim of maximizing the retailer׳s profit and improving CM׳s commitment to CSR. Finally, numerical experiments are conducted to illustrate and validate the proposed models and provide managerial insights.     

Retail category management: State-of-the-art review of quantitative research and software applications in assortment and shelf space management

Retail requires efficient decision support to manage increasing product proliferation and various consumer choice effects with limited shelf space. Our goal is to identify, describe and compare decision support systems for category planning. This research analyzes quantitative models and software applications in assortment and shelf space management and contributes to a more integrated modeling approach. There are difficulties commonly involved in the use of commercial software and the implementation and transfer of scientific models. Scientific decision models either focus on space-dependent demand or substitution effects, whereas software applications use simplistic rules of thumb. We show that retail assortment planning models neglect space-elastic demand and largely also ignore constraints of limited shelf space. Shelf space management streams on the other hand, mostly omit substitution effects between products when products are delisted orout-of-stock, which is the focus of consumer choice models in assortment planning. Also, the problem sizes of the models are often not relevant for realistic category sizes. Addressing these issues, this paper provides a state-of-the-art overview and research framework for integrated assortment and shelf space planning.     

Comparing reactive Kanban and reactive CONWIP

This paper compares a reactive Kanban system to a reactive CONWIP system under conditions of unstable changes in demand using simulation experiments. After an introduction, a model of the JIT ordering systems, the Kanban and the CONWIP systems, is constructed. In order to obtain the fundamental information for developing a control rule of buffer size, the performance of the two types of the JIT ordering systems is analysed under various stable-demand conditions by simulation experiments. Based on the results, the reactive JIT ordering systems are proposed, and the performance of the proposed systems is investigated. The results showed that both of the proposed systems can react to unstable changes in demand and maintain the mean waiting time of demand at less than the required level. In the reactive Kanban system, the total of the mean work-in-process inventories becomes much less than that in the traditional Kanban system without controlling buffer size. However, in the reactive CONWIP system, the total of the mean work-in-process inventories becomes much more than or nearly equal to that in the traditional CONWIP system without controlling buffer size under the strongly correlated or the weakly correlated processing times, respectively. Based on the results, it can be claimed that, in the proposed systems, the reactive Kanban system is more effective to react to unstable changes in demand than the reactive CONWIP system.     

Modelling multibrand consumption

In this article a model for the multibrand consumption of fast moving non-durable consumer goods is presented. The model is derived by the mixing of a multinomial distribution (representing the brand consumption probabilities of an individual household) with the continuous multivariate Beta (Dirichlet) distribution (which allows for differences between households). The core of the analysis involves the use of complete bivariate tables. The model is shown to provide an adequate representation of a set of consumption data and to satisfactorily estimate the various brand market shares.