Price-aware matrix factorization model for personalized recommendations

Recommendation methods aim to assist consumers in their decision-making process to find products that they are quite likely interested in. Current recommendation methods generally use online consumer reviews or ratings to predict consumers’ preferences for products. In e-commerce transactions, price plays a significant role in consumers’ purchase decisions. And each consumer's preference for product prices is specific. In this paper, we propose a novel price-aware recommendation method based on the matrix factorization model which fully considers the effect of price. We distill the price preferences of consumers from ratings and discover consumers’ real preferences for products. We further calculate the price sensitivities of consumers, not only considering the difference in price preference between a consumer and others but also focusing on the consumers’ price preferences in a specific price range. The final predicted ratings are calculated by adding the term of price effect into the matrix factorization framework. The results show that the proposed method has achieved high accuracy and performed better than several existing methods in both rating prediction and Top-N recommendation. And the products we recommend for consumers are more in line with their price preferences. Moreover, we find that, to some extent, the proposed method can solve the long-tail product recommendation problem with the consideration of the price effect.     

Pricing strategies in online book industry: a comparative study

In this paper, we examine pricing strategies in the U.S. online book industry over two time periods, with an aim to understand whether and how the driving factors of price dispersion change over time. Our empirical results show that dispersion in prices has remained substantial over the period of 2001–2006, but the driving factors of these variations in price have evolved. In 2001 online book retailers generally engaged in obfuscation, frustrating consumer search by manipulating shipping options. As documented by prior literature and revealed in our 2001 data, higher prices charged by retailers were positively related with longer shipping time. This strategy has been abandoned, as shown by our results of a 2006 sample. Online retailers are now competing to ship items quicker than rivals and to pass fewer or no shipping costs on to consumers. The impact of trust assurance seals (e.g., seals of online security and privacy) on price has materialized over the period of 2001–2006. This is because as more consumers become security conscious, the effects of assurance seals on the price becomes better recognized. Moreover, although retailers are roughly clustered into three cohorts, they strategize prices across different product items within each cohort.     

Enhancing the impact of online hotel reviews through the use of emoticons

Online consumer reviews (OCRs) have received increasing scrutiny in recent years. The present study focuses on the effect of OCRs on consumers’ perceptions and attitudes, when pictorial representation of consumer emotions is used in online hotel reviews. A 2?×?2 experimental study is designed to examine the effect of two independent variables: review valence (positive vs. negative) and emoticons use (no emoticons vs. emoticons). Research findings show that positive OCRs result in more positive attitude and higher booking intention. Interestingly, the presence of emoticons in negative reviews strengthens the review credibility and usefulness, but attenuates consumers’ attitude towards the hotel and their booking intention. Managerial implications and research opportunities are discussed.     

Incentive mechanisms,fairness and participation in online group-buying auctions

The main idea of an online group-buying auction is to recruit enough people to generate a sufficient volume of orders to create the basis for a lower transaction price. Typically, the larger the number of orders, the more consumers will wish to participate. This is because the final auction price is likely to be lower than it would be otherwise. This positive feedback is a demand externalities phenomenon. Nevertheless, there also is a phenomenon of inertia that often occurs at the beginning of online group-buying auctions. Due to the small number of orders that occur in the beginning of an online group-buying auction, many potential participants are inclined to wait until the auction price for the sale item falls to an acceptable level. This only comes through the participation of more people in the auction. As a result, consumers will tend to wait for one another to join the auction. Thus, the startup inertia must be overcome before the number of orders will increase. We explore three incentive mechanisms to address this problem: sequence-based, time-based and quantity-based incentives. We conducted a series of experiments using an online group-buying auction experimental test bed deployed on the Internet to develop deeper insights into how these incentives work in the context of bakery cookie sales. Using theory to represent a variety of decision-making perspectives that can be applied in the online group-buying auction context, we explore whether the different incentive mechanisms cause consumers to perceive a lack of price fairness and procedural fairness in an auction’s operations. Our results suggest that consumers view participation discounts as creating the basis for perceptions of greater price fairness in online group-buying auctions. Compared with other incentive mechanisms, a sequence-based incentive mechanism gives consumers a sense of less procedural fairness. Finally, perceptions of fairness tend to have a positive association with price satisfaction and purchase intention.     

Optimal pricing of online products based on customer anchoring-adjustment psychology

Online product pricing is an important factor that affects the purchase of customers and the earnings of e-commerce platform enterprises. It has an increasingly prominent influence on consumers’ purchasing decisions. To study the influence of customers’ anchoring psychology and product pricing on customers’ purchasing behaviors, this paper proposes a pricing model that considers online consumers to be anchored by the product price and sales. The cognitive bias of online consumers is described by a utility function based on an anchoring-adjustment heuristic, and consumer choice behavior and an online product pricing strategy are studied with a multinomial logit model. Then, it studies the influence of the anchoring point and anchoring degree on optimal pricing, sales and profit. In particular, when consumers are anchored only by sales of goods, the optimal solution is monotonic with respect to the anchoring degree. However, when consumers are anchored by both price and sales, both factors affect consumer behaviors and produce more complex results. This paper provides a flexible pricing mechanism for platform enterprises, and it can provide a theoretical basis and decision support for dynamic pricing of platform enterprises based on historical consumption data.     

Pricing strategies for tied digital contents and devices

Media companies are increasingly offering digital content to consumers. Many of these companies are tying digital content with their proprietary digital devices. In this study, we develop a consumer demand model for digital device and digital content based on a constant elasticity demand function. In modeling consumer valuation of the digital device, we take consumer surplus on digital content into account. We further derive equilibrium prices for digital devices based on an oligopoly competition model with horizontal product differentiation. We analyze the equilibrium prices and how prices affect firm profits. We find product differentiation and the level of product substitutability affect prices. We also find that content price plays a significant role in affecting the price of the digital device. Content price can either increase or decrease the tied digital device price depending on the profit margin and demand elasticity of the digital content. We further analyze how content and device prices affect their respective profits and the overall profit of the firm. We extend our model to vertical product differentiation and find vertical product differentiation and the level of product quality affect prices.     

需求依赖于产品价格和消费者时间偏好的定价与订货决策

研究产品的市场需求依赖于价格和消费者时间偏好情形下的供应链及其成员的最优定价与订货问题. 利用时间偏好因子刻画消费者的时间偏好, 利用产品市场需求关于零售价格的弹性指数反映消费者的价格敏感程度, 建立存在强势零售商、强势供应商和供需双方势力均衡3 种渠道权力结构下的定价与订货模型. 数值结果表明, 在3 种渠道权力结构下, 消费者的时间偏好和产品市场需求关于零售价格的弹性指数是供应链主导者最优定价、订货量和期望利润的单调减函数, 将其纳入定价与订货决策的影响因素予以考量能够增加供应链主导者的最大期望利润.

     

基于最小购买模式的多产品定价方法

通过与顾客的在线交互,电子商务网站能够获得消费者反馈的有关参考数据。这些有效的数据结合完善的分析工具可使企业通过价格的优化来增加效益。基于这些有效数据研究了多产品定价问题,其中,给定消费者有关产品的参考数据(包括预算和定购产品列表),通过设定一个企业多个产品的价格,极大化企业的总收益;提出了基于最小购买模式的多产品定价问题模型,设计了针对该模型的遗传算法。仿真实例证明了该模型的有效性。     

Product type and consumers’ perception of online consumer reviews

Consumers hesitate to buy experience products online because it is hard to get enough information about experience products via the Internet. Online consumer reviews may change that, as they offer consumers indirect experiences about dominant attributes of experience products, transforming them into search products. When consumers are exposed to an online consumer review, it should be noted that there are different kinds of review sources. This study investigates the effects of review source and product type on consumers’ perception of a review. The result of the online experiment suggests that product type can moderate consumers’ perceived credibility of a review from different review sources, and the major findings are: (1) consumers are more influenced by a review for an experience product than for a search product when the review comes from consumer-developed review sites, and (2) a review from an online community is perceived to be the most credible for consumers seeking information about an experience product. The findings provide managerial implications for marketers as to how they can better manage online consumer reviews.     

Examining the Gramm–Leach–Bliley Act's opt-out method for protecting consumer data privacy rights on the Internet

This article involves examining the Gramm–Leach–Bliley Act's (GLBA) opt-out method in concern with protecting consumer data privacy rights online. Its purpose is to show that further regulatory measures are necessary at the federal level in order to provide better protection for consumers. To lay a foundation, it provides a background on the development of consumer data privacy rights and the collection and dissemination of personal data online and continues by exploring the practices of online merchants, credit card companies, and electronic banking in relation to the treatment of consumers’ data online. Through addressing state, federal, and self-regulatory evolvements, this article makes it apparent that the GLBA, the primary federal law protecting consumers from financial institutions use of consumer data, is insufficient and a revised legal approach for protecting consumer data online is required that is more in line with the progressive approach by the European Union and its opt-in method.     

Dynamic Consumer Profiling and Tiered Pricing Using Software Agents

Shopbots or software agents that enable comparison shopping of items from different online sellers have become popular for quick and easy shopping among online buyers. Rapid searches and price comparison by shopbots have motivated sellers to use software agents called pricebots to adjust their prices dynamically so that they can maintain a competitive edge in the market. Existing pricebots charge the same price for an item from all of their customers. Online consumers differ in their purchasing preferences and, therefore, a seller's profit can be increased by charging two different prices for the same good from price-insensitive and price-sensitive consumers. In this paper, we present an algorithm that partitions the buyer population into different segments depending on the buyers' purchase criteria and then charges a different price for each segment. Simulation results of our tiered pricing algorithm indicate that sellers' profits are improved by charging different prices to buyers with different purchase criteria. Price wars between sellers that cause regular price fluctuations in the market, are also prevented when all the sellers in the market use a tiered pricing strategy.     

Is that deal worth my money? The effect of relative and referent thinking on starting price under different promotion programs using hotel coupons in online auctions

Developments in information technology have made shopping at home much easier and have created a so-called “Otaku economy” that is an increasing focus for tourism and hotel business managers. A related development is the increase in the popularity and value of online auction channels. Scholars thus argue that it is important to examine what factors influence consumers’ bidding behavior in this new context. One issue is what initial bidding price and a promotion program must offer to attract customers to join an auction when they will be using a complex online auction mechanism. This study used a 2 × 2 between-subjects design and the principles of relative and referent thinking to examine the influence of the starting price (whether the starting price deviates from the reference price) and the promotion program (price vs. non-price) on consumers’ online bidding for hotel coupons. The results of the analysis indicate the following. First, starting price is positively related to end price. Second, the relative thinking effect holds when the actual price is the same as the sellers’ reference price (i.e., when the starting price is higher). In this context, consumers prefer price promotion programs, and hence, their willingness to pay through bidding will increase. Finally, the referent thinking effect holds when the actual price deviates from the seller’s reference price (i.e., when the starting price is low). In this context, consumers prefer non-price promotion programs, and their willingness to pay through bidding will increase. The academic and managerial implications of this research are discussed in the conclusion.     

Price competition in e-tailing under service and recognition differentiation

The Internet has significantly increased the bargaining power of consumers. Many online shopping search engines allow consumers to find most retailers that sell a specific product, compare product prices, and review detailed store ratings. With competition just a click away, online retailers have little control over where consumers would shop. Offering the lowest price alone does not always guarantee that consumers will come and buy at your site. Other non-price attributes, such as service quality and a merchant’s brand recognition, also play important roles in helping online retailers to build competitive advantages. In this paper, we present a model of price competition that assumes e-tailers can mainly differentiate themselves by providing different levels of service and by establishing a different online recognition. Closed-form equilibrium solutions are obtained for the different scenarios that may arise in this model. Based on such solutions, we give managerial insights on how e-tailers should position themselves when parameters such as service cost, service levels, and recognition are varied.     

Consumer informedness and diverse consumer purchasing behaviors: Traditional mass-market,trading down,and trading out into the long tail

As truly informed consumers are increasingly able to find exactly what they want and willing to pay premium prices to obtain products with perfect fit for them, companies have responded with new product portfolio strategies and new pricing strategies, based on the concepts of resonance marketing and hyperdifferentiation. This is not just consumers’ pursuit of products that are better, but rather better for them. It is not trading up, but rather trading out. In this paper we offer a more complete explanation of changes in consumer behavior, based on consumers’ new-found informedness, and an understanding of consumers’ pursuit of products that truly meet their individual wants and needs, cravings and longings.This paper also contributes to a deeper understanding of how online reviews are linked to sales. Recent empirical studies suggest that consumers use information in different ways in different shopping experiences, and that consumers’ purchasing behavior varies across different online shopping experiences; consequently, the best predictors of the success of different online products will therefore vary depending on what consumers are buying and why and how they are buying it.     

Opinion Evolution Model for Online Reviews from the Perspective of Value Co-creation

Opinions from online reviews reflect consumers’ value perception toward products and services. However, the evolution mechanism of online opinions in the process of value co-creation resulting from an interaction between heterogeneous consumers and merchants remains unclear. In this context, we propose an opinion evolution model based on the advanced Hegselmann–Krause model from the value co-creation perspective to explore the online opinions in a merchant–consumer interaction process. Simulation results show that the heterogeneity of consumers, merchants’ review display methods, and investment behaviors have an impact on online opinions and merchants’ profits. Radical and active consumers are less likely satisfied with merchants’ products or services; whereas balanced, robust, and conservative consumers are more likely satisfied. In addition, the review volume displayed per page has an impact on online opinions and merchants’ profits but becomes invalid when a certain threshold is exceeded. The brand effect can significantly increase online opinions and merchants’ profits only when such an effect exceeds a certain threshold. Furthermore, findings indicate that merchants should not only be concerned about short-term investment in initial products/services quality but also on the long-term investment in the brand effect. They should also avoid the idea of getting once-and-for-all or free-riding.     

Does Accessibility Affect Retail Prices and Competition? An Empirical Application

This paper attempts to link the concepts of accessibility and the firm’s conduct in the regional retail market in Spain. We use a database that includes sale price, service station location, level of traffic and type of road. We show that accessibility has two main effects on final prices. The accessibility of own-brand gas stations increased their prices while the accessibility of rival gas stations causes price reductions. If we include the value of time, then no rational consumer should travel further than his nearest petrol station in search of lower prices. Finally, our paper shows that service stations can establish a dominant position if consumers do not have access to other retailers within a 17-min radius.     

Source effect of advertised reference price influences on transaction value in online shopping environments

Prior studies examine whether or not using advertised reference price (ARP) increases consumers’ perceived gain from the purchase decision. However, few studies address whether or not the ARP should involve an online or offline source. Present study thus investigates the influence of the APR source on consumer perceived value. Empirical results indicate that consumers would perceive higher transaction value when an online seller adopts another online retailer’s sale price as ARP than when the online seller uses an offline competitor’s sale price as the ARP.     

基于多摇臂赌博机的产品定价算法

针对在线零售商在不完全需求信息下的单产品定价问题,提出了一种基于多摇臂赌博机的产品定价算法。为了提升多摇臂赌博机算法在定价问题中的效果,该算法利用了需求曲线的单调性,并加入了消费者偏好识别。对消费者的保留价格进行分析得到消费者购买概率,将在线零售商的定价问题建模为多摇臂赌博机模型,给出了相应的定价算法并进行了理论分析,最后通过仿真实验比较了相关算法的定价效果。仿真结果表明该算法提高了在线零售商的收益。     

Consumers rule: How consumer reviews influence perceived trustworthiness of online stores

Two studies examined the impact of online store reviews on consumer trust in online stores. Based on the warranting principle, it was proposed that consumer reviews are a more important cue for judging the trustworthiness of an online store than the overall reputation of the store (Experiment 1) or assurance seals (Experiment 2). The role of dispositional trust was also examined. In both experiments, consumer reviews turned out as the strongest predictor of trustworthiness judgments. Store reputation had no significant effect. In Experiment 1, there was a main effect of dispositional trust on perceived trustworthiness. In Experiment 2, dispositional trust moderated the effects of reviews and assurance seals. High trusters were more influenced by the reviews of other consumers; and only high trusters tended to be influenced by assurance seals. The results show that consumer reviews play an important role in consumer decision making, indicating that online consumer communities indeed empower consumers.     

Gender differences in consumers’ perception of online consumer reviews

Since the early days of the Internet, gender gap has existed in using the Internet, and it is particularly evident for online shopping. Females perceive higher level of risk for online shopping, and as a result, they tend to hesitate to make purchase online. Online consumer reviews can effectively mitigate such perceived risk by females and thereby attract them to buy online. This study investigates the effect of online consumer reviews on consumer’s purchase intention. In particular, we examine whether there are gender differences in responding to online consumer reviews. The results show that the effect of online consumer reviews on purchase intention is stronger for females than males. The negativity effect, that consumers are influenced by a negative review more than by a positive review, is also found to be more evident for females. These findings have practical implications for online sellers to guide them to effectively use online consumer reviews to engage females in online shopping.