电商平台信息披露策略研究

电商平台模式下，供应商决定产品价格将产品直接出售给消费者，并与平台企业共享收益。通常，消费者与产品供应商/平台企业在产品属性(匹配)信息上存在不对称性。本文基于博弈理论，研究电商平台(如：亚马逊、京东等)的产品信息披露策略，比较两种信息披露方式：“平台披露”与“供应商披露”。首先考虑由一个平台企业和一个供应商组成的垄断结构。研究表明，信息披露策略取决于产品属性(匹配)的相对重要性。同时，与平台披露相比，供应商更愿意披露全部产品信息。然后考虑一个平台企业和两个供应商组成的竞争结构。研究发现，与垄断结构不同，平台披露下，平台总是披露全部产品信息；而供应商披露下，信息披露策略取决于产品属性(匹配)信息的相对价值。此外，平台会偏好由供应商负责信息披露。     

基于混合定向方式的移动定向广告投放策略研究

以移动广告为研究背景,研究地理定向和消费者产品偏好定向相结合的混合定向方式下企业的定向广告投放策略,同时通过对比企业投放定向广告与大众广告,研究企业的广告策略选择问题。研究发现,企业运用定向广告策略应针对不同的消费者群体提供差异化较大的营销策略:对属于企业近距离范围且偏好企业产品的优势市场,企业应加大广告投放力度并实行高价;为了争取部分远端劣势市场的收益,企业应向其投放一定力度的广告并实行低价;对属于双方的竞争市场,企业应选择中等程度的广告和价格。同时,通过与企业投放大众广告相比较,发现竞争企业使用定向广告策略反而不如使用大众广告策略。     

社交网络情境下基于同侪影响的产品线规划研究

依托社交网络优化产品线是实现“匹配消费者需求带动产品设计-制造-营销全流程协调发展”的重要途径,尽管已经引起实业界的重点关注,相应的学术研究却十分匮乏。鉴于此,本文基于同侪影响理论与前景理论,结合社交网络情境下消费者的产品需求、偏好及决策,构建涵盖产品线营销层面和设计层面的双层规划模型;然后结合智能手机产品线实例,运用嵌套灰狼算法对该双层规划模型进行求解验证。本研究旨在提出社交网络与产品线规划之间耦合作用的联合优化框架,为面向社交网络的产品线规划提供理论依据。     

Optimal Pricing of Two Successive‐Generation Products with Trade‐in Options under Uncertainty

To entice consumers to purchase both current and next generation products, many manufacturers and retailers offer trade‐in programs that allow buyers of the first generation product to trade‐in the product and purchase the new generation product at a lower price. By considering the interactions between “forward‐looking” consumers and a firm when a trade‐in program is offered, we analyze a two‐period dynamic game to determine the optimal prices of two successive‐generation products in equilibrium, and examine the conditions under which trade‐in programs are beneficial to the firm. Our model incorporates market heterogeneity (valuation of the first generation product varies among the consumer population), product uncertainty (the incremental value of the new product is uncertain before its introduction), and consumers' forward‐looking behavior (consumers take future product valuation and prices into consideration when making purchasing decisions). With the trade‐in option, we show that consumers are willing to pay a price that is higher than their valuations of the current product. Furthermore, trade‐in programs are more beneficial to the firm when: (i) the durability of the current product is high; (ii) the market heterogeneity is low; or (iii) the uncertainty level (or the expected incremental value) of the new product is high. Finally, when the incremental value of the new product is more uncertain, consumers are more willing to purchase the current product because of the “option” value of the trade‐in programs and thus trade‐in programs can be more beneficial to the firm in this case.     

Consumer preference analysis: A data-driven multiple criteria approach integrating online information

Multiple criteria approaches can assist the product manager to know the consumer preferences in the context of e-commerce. Consumer preference analysis explains what aspects of a product affect and how they affect a consumer’s purchasing decision. This issue plays an important role in e-commerce platforms from its relevance in marketing decisions such as advertisements, recommendations and promotions. In this regard, we propose a data-driven multiple criteria decision aiding (MCDA) approach to integrate online information, such as explicit (e.g., reviews and ratings) and implicit (e.g., clicks and purchases) feedback from consumers. However, MCDA approaches present a critical challenge that even an experienced product manager could find it difficult to pre-define the criteria on which a product is evaluated. To address this issue, our proposed approach first utilizes text-mining techniques to assist the product manager identify the criteria, and then determines and collects the relative importance of the criteria and their values. Given the criteria information, we use a sampling process to provide two indices, the consumer preference index and rank acceptability index. The first index helps in prioritizing the pairwise comparisons of products, while the second one helps in deriving a default ranking list for first-time-registered consumers. We record the products viewed by consumers and generate their preference information in the form of pairwise comparisons for analyses within an aggregation-disaggregation paradigm. We also provide a representative value function to help the product manager gain insight into the preferences. Finally, we describe how a real-world application including the product manager and consumers exploits the proposed approach on an e-commerce platform to take a large step toward aiding more realistic and data-driven multiple criteria decision making.     

The Competitive Impact of Targeted Television Advertisements Using DVR Technology

Digital video recorders (DVRs) are an emerging technology that is fundamentally changing the competitive landscape in industries that advertise on television. Perhaps the most familiar impact of DVR technology is that it enables consumers to avoid advertisements (ads) by fast forwarding through them. However, this “zipping” of ads is only one aspect of the impact of DVR technology. DVRs also collect a wealth of information at the consumer level that can be used by firms to target their ads more effectively. We examine how this targeting capability moderates the impact of ad avoidance in a competitive setting. Insights are provided on how best to manage this emerging technology in terms of the key managerial decisions of product pricing and advertising efforts, as well as its impact on profits in a competitive (duopoly) marketplace.     

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.     

The Impact of Geographic Proximity on What to Buy,How to Buy,and Where to Buy: Evidence from High‐Tech Durable Goods Market*

Social contagion effects due to geographical proximity refer to the social effects wherein the behavior of an individual varies with the behavior of other individuals who are geographically close. Although the influence of such effects on consumer choices has been established in several contexts, much of the extant studies have focused on its effect on consumers’ decision of whether to buy a new product or adopt a new innovation. There has been no systematic examination of the influence of geographic proximity on other aspects of consumers’ product buying process such as what to buy (i.e., brand choice), how to buy (i.e., the channel), and where to buy (i.e., retailers). Such effects can matter significantly in high‐technology and durable goods markets and therefore, it is critical to understand the scope of these on consumers’ choice of retailers and channel as well. Drawing on literatures from word of mouth effects, ecommerce, and consumers’ perception of risk in their purchase process, we develop a set of hypotheses on the effect of geographic proximity on consumers’ choices of what to buy, how to buy, and where to buy. Leveraging a microlevel dataset of purchases of personal computers, we develop brand‐, retailer‐, and channel‐related measures of proximity effects at the individual consumer level and estimate a joint disaggregate model of the three choices that make up a product purchase process to test these hypotheses. Our results indicate a significant contagion effect on each of the three choices. Furthermore, we find evidence of a greater effect of geographic proximity on inexperienced consumers—those who are new to the product category. Our results thus help develop a holistic understanding of the influence of social contagion effects on consumers’ decision making.     

Consumer Awareness, Understanding and Usage of Unit Pricing

The debate continues over whether prescribed quantities or unit pricing offers the best method to enable consumers to make value-for-money comparisons. In theory, the 'informed' consumer should benefit from being given unit-price information to identify optimum purchases; in practice, however, it would appear that many consumers do not use the data. Although unit pricing can reduce the level of confusion caused by large product ranges and large numbers of unique size–price combinations, results of a survey of over 1000 people showed that: 31% of the sample did not understand how unit pricing was meant to help them compare products; 35% could not be bothered to look at unit prices and 28% stated that unit pricing was too difficult to use. Those least likely to look at unit prices are women, the least educated and consumers aged 18–34. The research investigated why consumers do not use unit-price information and found: some consumers do not possess the cognitive ability to process the information and feel unit pricing is too complicated to use; some products are not comparable, which makes unit prices misleading; many shops do not provide unit-price information; unit-price information was felt unnecessary when evaluating products with few or no alternative sizes or brands; unit-price comparisons take too much time; consumers use simpler strategies for getting value for money, e.g. volume discount heuristic, own brands, special offers, x% free, reward points, etc. The paper explores policy and retailer implications for unit pricing and examines recommendations for government.     

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.     

产品责任、企业社会责任偏好与供应链中的质量-数量协调

在产品质量和产品数量（订货量）内生化的情形下，同时实现其质量和数量的协调将成为供应链管理的一个重要问题。进一步，在产品低质量对消费者造成伤害的情形下，制造商将面临着产品责任（表征制造商对消费者产品伤害的补偿），从而导致"产品责任如何影响供应链中的质量-数量协调"这一问题。最后，如果核心企业具有对消费者的企业社会责任（CSR）偏好，则这种CSR偏好又如何影响供应链中的质量-数量协调？针对这三个问题，首先，利用批发价合同构建了一个由上游制造商和下游零售商组成的两级供应链运作博弈模型；其次考察了制造商产品责任、CSR偏好程度和质量改进效率对其产品质量决策、批发价合同和相应的供应链节点企业利润的影响；最后，研究了供应链质量-数量协调问题。结果表明：（1）产品责任不影响产品质量、订货量、供应链节点企业经济利润和消费者剩余，但制造商批发价随产品责任的增加而增加；（2）随着CSR偏好程度的增加，产品质量、订货量、零售商经济利润、供应链系统经济利润和消费者剩余随之增加，而制造商经济利润随之减小；（3）质量改进效率的提高，有利于产品质量、订货量、零售商经济利润、供应链系统经济利润和消费者剩余的增加；（4）一个由数量折扣契约和质量改进成本分担契约共同构成的协调机制，可以有效的实现供应链系统的协调，其中，产品责任将促使数量折扣契约中产品批发价的增加和质量改进成本分担比例的减小，而CSR偏好程度的增加将促使数量折扣契约中产品批发价的减小，但不影响质量改进成本分担比例。     

Browse‐and‐Switch: Retail‐Online Competition under Value Uncertainty

Although online shopping is becoming popular, consumers who are unsure about whether to buy a product may find it advantageous to visit a brick‐and‐mortar retail store to first examine the product before purchasing it. But, after browsing at the store, consumers have the option of switching to an e‐tailer to purchase the item at a cheaper price rather than buying at the store. Recent business press refers to this browse‐and‐switch behavior as “showrooming,” and attributes to it the declining profits of brick‐and‐mortar retailers. To study the effect of the browse‐and‐switch option on retail and online pricing strategies and profits, we analyze a stylized economic model that incorporates uncertainty in consumers' valuation of the product, captures the heterogeneity among consumers in their inclination to purchase online, and permits product returns. We consider various equilibrium scenarios for different combinations of consumer shopping behaviors, characterize the parameter ranges for each scenario, and demonstrate that browse‐and‐switch behavior can indeed occur under equilibrium. Our analysis further shows that the option for consumers to browse‐and‐switch intensifies competition, reducing the profits for both firms.     

本土品牌逆袭与消费者偏好逆转的纵向扎根研究

  如今的中国市场,诸多行业本土品牌崛起甚至逆袭,消费者对全球品牌与本土品牌的偏好相应逆转。已有研究较为全面地揭示了全球品牌和本土品牌偏好的驱动因素,但本土品牌逆袭过程中全球品牌与本土品牌偏好的驱动因素是否相同、本土品牌逆袭与消费者偏好逆转的互动影响路径是怎样的,对这些问题缺乏探讨。         在梳理相关研究的基础上,以手机行业为研究对象,采用扎根理论的研究方法,通过对网络讨论数据的初始编码、聚焦编码和理论编码,首先研究全球品牌与本土品牌偏好的驱动因素的异同,然后结合对讨论数据的纵向统计结果,研究本土品牌逆袭过程中品牌逆袭与消费者偏好逆转的互动影响路径。         研究结果表明,本土品牌逆袭中,全球品牌与本土品牌偏好的驱动因素模型具有相似的结构,功能价值和社会价值的测量受个人因素调节而影响消费者偏好,但测量功能价值或社会价值的具体因素在全球品牌与本土品牌中存在差异。品牌逆袭有助于提升综合国力、促进消费者成熟,进而驱动消费者偏好逆转;消费者偏好逆转则通过反馈路径帮助品牌进一步逆袭。具体的,消费者对产品特质更加重视,全球品牌的原产国效应和符号价值表现力减弱,本土品牌的口碑效应和符号价值表现力增强,同时消费者的民族主义增强而爱国绑架感减弱,这些因素通过感知价值带来消费者偏好逆转。综合而言,本土品牌逆袭和消费者偏好逆转是互动提升的关系。         研究结果丰富了全球品牌和本土品牌的相关研究,为全球品牌和本土品牌的建设提供了实践启示。产品特质是影响消费者偏好的主要因素,并对其他驱动因素有支撑作用。所以全球品牌和本土品牌都要重视产品的创新和研发,还要根据各驱动因素的变化调整其营销策略。     

基于消费者显著性偏好的双边平台转换成本和定价策略研究

针对消费者对转换成本和价格属性具有显著性偏好的实际情况，基于显著性理论对垄断双边平台企业的转换成本和定价策略问题进行了研究。研究发现：1)在显著性偏好非对称型市场上，对价格敏感的一方收取的价格最低，对高转换成本的一方收取的价格最高，而在显著性偏好对称型市场上，平台的最优价格位于非对称型市场之间，但是对价格敏感型市场收取的价格低于转换成本敏感型市场的价格。2)在高转换成本的市场，平台利润最低；低转换成本市场平台利润最高，而混合型情况的最优利润位于这两者之间。该研究结论说明平台企业应该采取措施来降低用户加入平台的转换成本，从而增加利润，这与现实的案例研究结论相吻合。     

Digitalisierung und Konvergenz von Online- und Offline-Welt

The increasing diffusion of mobile phones with internet access (Smartphones) enables more and more consumers to use the mobile internet. In addition, there is a continuing integration of location-based services (LBS). By means of Global Positioning Systems or WiFi-triangulation LBS provide context-aware information to consumers. This leads to a convergence of online and offline worlds. The usage of LBS delivers additional information to consumers (e.g. alternative offers or detailed product information). Therefore LBS do have an influence on consumer behavior. Particularly during the search process, information about prices or geographic distances, that are relevant for the purchase, are of importance. This study analyzes the relevance of location-based internet search empirically. Search costs are estimated on an individual level in a choice-based conjoint analysis using two different products. As a result, location-based internet search is considered to be very relevant for search and influential on consumer behavior. The study shows different consumers preferences and different search costs depending on the product. To conclude the study, the implications are discussed. The major contribution of this study is that it shows that offline and online search do have a mutual impact on each other. Furthermore, search costs are measured in a mobile context.     

The Interplay between Information Acquisition and Quality Disclosure

This study investigates the interactions between a manufacturer's information acquisition and quality disclosure strategies in a supply chain setting in which the manufacturer privately knows his product quality but is uncertain about consumer preferences. We argue that the manufacturer should treat his information acquisition and quality disclosure decisions as an integrated process because these decisions can significantly influence a retailer's rational inferences about product quality and can have conflicting effects on his own profitability. Although information acquisition helps a manufacturer subsequently craft better pricing and quality disclosure strategies, it also leaks certain product information to the retailer, thus helping the retailer better estimate product quality. Therefore, in equilibrium, a manufacturer may choose not to acquire any consumer information, even when such acquisition is costless. Moreover, we find that this adverse effect of acquisition is highly dependent on the cost of disclosure and consumers’ preference differentiation. Increased consumer preference differentiation may have a non‐monotonic relationship with the manufacturer's profit, and information acquisition can become detrimental to the manufacturer once the disclosure cost is sufficiently high.     

Group Selling,Product Durability,and Consumer Behavior

Firms producing complementary goods often strategically form groups and jointly sell their products to better coordinate their decisions. For consumer durables, decisions about such collaboration might be complicated due to two factors. Because of their durability and presence of used goods markets, such products engender “future” price competition between new and used goods. On the other hand, consumers of such products might be forward‐looking and patient, both of which affect their purchasing behavior. In this study, we study how the above product and consumer characteristics interact to affect the group selling decisions of complementary firms. We do so through a two‐period model consisting of a value chain with two upstream manufacturers and a downstream retailer. When consumers are relatively impatient and reluctant to wait to buy later, group selling by manufacturers will take place only when the end product is relatively perishable, that is, product durability is low. However, if consumers are patient, that is, willing to wait, collaboration happens only when the end product is quite durable; for relatively perishable products the manufacturers sell their products separately. We also comment on how our results are affected by factors like manufacturers directly selling to end consumers or there being multiple opportunities to decide whether or not to use group selling strategy.     

The Dark Side of Information and Market Efficiency in E‐Markets*

Price dispersion reflects the differences in prices for identical products. While in physical markets such dispersion is prevalent due to high search costs, many researchers argue that search costs and price dispersion will be much lower in electronic markets (e‐markets). Empirical evidence does not support this contention, and researchers have studied search costs, market factors, and service‐quality factors to explain this dispersion. Previous research has largely assumed that more information is better. By ignoring the dark side of information, we argue that only a partial understanding of price dispersion is possible. In this article, information overload and equivocality are studied as two dark attributes of information that lead sellers to different pricing decisions in e‐markets. Hypotheses relating these attributes to price dispersion are supported through analysis of 161 product markets. This work opens up new avenues in the study of e‐markets and discusses the implications of these findings for research and practice on consumer and seller decisions.     

Demand Growth in Services: A Discrete Choice Analysis of Customer Preferences and Online Selling

The selling of perishable services (e.g., hotel rooms, airline seats, and rental cars) online is increasingly popular with both retailers and consumers. Among the innovative approaches to online sales is opaque selling. First popularized by Priceline.com's name‐your‐own‐price model, opaque selling hides some attributes of the service (notably, brand and specific location) until after the purchase decision, in exchange for a discounted price. This means that a branded “product” is being sold as somewhat of a commodity, but the brand “name” is protected by the opaque model. The attraction of this model for retailers is that they are presumably able to increase their revenue stream, albeit at a lower rate, by selling rooms that otherwise would remain in inventory. In this article, we outline the development and analysis of an online choice survey to understand consumer preferences among three types of online distribution channels: regular full information sales channels, and opaque sales channels with or without consumer bidding. A Multinomial Logit model is employed to analyze the data and measure the consumer trade‐offs between price and other attributes of the product. We use the estimated model to calculate the incremental demand and revenue created by using an opaque channel simultaneously with regular full information channels. On balance, we find that correctly priced opaque channels can add to hotels revenue streams without undue cannibalization of regular room sales.     

网店信息呈现的框架效应对消费者购买决策的影响研究

目前有关在线消费者购买意愿的研究，绝大多数是基于实验统计的方法，分析影响消费者购买决策的因素，网店信息呈现的框架形式往往仅作为其中的关键因素被一些研究提及并加以验证。但是，"形态各异"的信息到底如何影响消费者心理进而影响到他们的决策？商家如何从消费者心理的微观层面来设计信息呈现策略，从而增强其购买意愿？目前关于此的研究尚不多见。本研究从前景理论的决策参考点视角，以价格因素为例，一方面，通过情境实验，验证了价格信息的不同呈现框架对于消费者购买意愿的影响作用；另一方面，在利用情境实验界定了消费者心理价格参考点的基础上，通过决策模型的构建和计算，从微观层面分析了不同价格信息呈现框架下，消费者购买选择大相径庭的原因。研究结果表明：（1）在风险框架下，相对于用不确定的语言来描述商品价格信息，确定性语言描述会使消费者的心理价格参考点和购买意愿更高。（2）在属性框架下，相对于用负面的语言来描述商品信息，正面的语言描述更能提高消费者的心理价格参考点和购买意愿。（3）在目标框架下，相对于强调购买行为可能给消费者带来的收益，强调不购买该商品可能给消费者带来的损失更有助于消费者的心理价格参考点和购买意愿的提高。基于上述研究结果，作者围绕网店如何有效的呈现信息提出了管理建议，并讨论了本研究的理论意义与应用价值。