Pricing and promotion strategies of an online shop based on customer segmentation and multiple objective decision making

The advent of the Internet and web technologies has enabled the prosperity of virtual stores, which greatly reduce customers’ search costs and retailers’ overhead. However, the furious competition between online shops makes it difficult for them to generate profits. This study attempts to establish pricing and promotion strategies for online shops to enhance their profitability. The pricing decision is based on the concept of customer relationship management, where a greater margin of price concession is given to customers who are more valuable to the shop. The process of our approach is: clustering customers into different classes based on their RFM data, computing and presenting the list prices of products to customers according to their classes, allowing customers to bargain over the price and offering conceded prices which are computed based on customer classes and a multi-objective decision making model, and finally providing promotion options to customers to reinforce their purchase inclination. The proposed approach is implemented at an online shop of a computer peripherals retailer. Transaction data before and after the implementation are collected and compared to assess the performance of the proposed approach.     

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.     

Online information privacy and price: A theoretical model and empirical tests

Information privacy has become an increasingly critical concern for many individuals, especially in the context of the increased collection, analysis, and visualization of personal information. Despite the importance of privacy in online transactions, most studies investigated the effects of privacy concerns on stated intentions. This study theoretically analyzes and empirically evaluates the link between privacy and price. In the proposed model, consumers are differentiated not only by their preferences for privacy but also by search costs. For simplicity, stores in the proposed model differ in terms of the price charged and the privacy protection level offered. As derived from the theoretical model and empirical validation, better privacy protection does not necessarily lead to the highest price, though it does allow stores to charge a premium price. Moreover, the price premium is higher if more consumers remain uninformed, indicating that uninformed consumers exert negative impacts on informed consumers.     

Quick response and omnichannel retail operations with the ship‐to‐store program

To better integrate online businesses with offline stores, fast‐fashion retailers roll out the “ship‐to‐store” (STS) initiative, which is an omnichannel fulfillment method that allows consumers to order online and have their parcels delivered to selected stores for pickup. To study the impact of STS on fast‐fashion operations, we consider four scenarios: multichannel retailing, multichannel retailing with quick response (QR), omnichannel retailing with STS, and omnichannel retailing with both STS and QR. Moreover, we investigate how STS influences the value of QR. The results show that although STS benefits firms in many situations, STS under a QR strategy can reduce a retailer's profits when inventory information disclosure due to STS dampens cross‐selling opportunities. Our findings also reveal that the implementation of STS may lower the value of QR when customers who encounter stockouts offline opt to purchase online directly rather than use STS.     

Using online pickup site inclusion policies to manage demand in retail/E-tail organizations

A major development in online retailing is the significant increase in the number of traditional “offline” retailers extending their brands online. Many of these retail/e-tail firms are attempting to leverage channel synergies by allowing customers to purchase products over the internet and then pick their orders up at one of the firm's local stores. This paper proposes that the firm presents only a subset of its stores to online customers as available pickup locations, rather than simply listing all local stores with inventory. By doing so, the firm can protect stores with critically low inventory levels and thereby reduce backorder costs. Specifically, we develop and evaluate a dynamic pickup site inclusion policy that incorporates real-time information to specify which of the firm's e-fulfillment locations should be presented at online checkout. Computational results indicate that managing in-store demand via such policies can decrease total cost (holding, backorder, and lost or redirected pickup sale costs) by as much as 18% over allowing customers to pick online orders up from any site with available inventory. The percentage of pickup sales and customers' sensitivity to travel are critical in determining the magnitude of the benefit.     

How does justice matter in online retailers’ reputation and purchase intentions: an empirical study of China

In recent years, online shopping has been proliferated around the world. Online retailers’ reputation and purchase intentions are critical for survival and profitability of any online store. Thus, this study proposes a research framework to examine the perceived justice effects on customers purchase intention and online retailers’ reputation. A confirmatory factor analysis was conducted to demonstrate the reliability and validity of the measurement model, and the structural equation modelling technique was used to test the research model. The hypothesised model was validated empirically using data collected from 383 online shopping customers in China. The results indicated that perceived procedural, distributive and interactional justice components were strong predictors of customers purchase intention and online retailers’ reputation while online retailers’ reputation had significant effects on purchase intentions. Finally, theoretical and managerial implications are also presented in the paper.     

Is paid search overrated? When bricks-and-mortar-only retailers should not use paid search

While bricks-and-mortar-only retailers do not offer online purchasing, they often take advantage of multi-channel management strategies to reach consumers in a pre-purchase phase. We investigate whether paid search can increase the sales of brick-and-mortar retailers who promote their offers via an informational website. Although a sizeable one third of all retailers still trade without an online-shop, previous work has been silent about the effects of paid search for them. We make use of a randomized field experiment and an end-to-end tracking mechanism to investigate the cross-channel behavior of individual consumers. Our empirical results suggest that, whilst paid search increases the number of potential customers through enhancing the reach of marketing initiatives, store sales are not increased. We conclude that customers who search online to buy offline primarily use paid search as a navigational shortcut to the retailer’s website. Consequently, bricks-and-mortar-only retailers seeking to increase store purchases should approach paid search with caution.     

In-store consumer behavior: How mobile recommendation agents influence usage intentions,product purchases,and store preferences

Product information given in purchase situations influences purchase behavior. In online purchase situations, the use of recommendation agents increases the value of product information as information becomes adaptive and thus more relevant to consumers’ information needs. Correspondingly, mobile recommendation agents (MRAs) may also increase the value of product information in bricks-and-mortar stores. In this sense, product information is not only adaptive but can also be requested at any place such as in front of products consumers are interested in. Because unprecedented, we investigate the use of a MRA that is virtually bound to a physical product via an RFID-enabled mobile device and provides product information. Based on Theory of Planned Behavior, Innovation Diffusion Theory, and Technology Acceptance Model, we develop a model to better understand the impact of MRAs on usage intentions, product purchases and store preferences of consumers. This model is then tested in a lab experiment (n = 47). Among high usability scores, results indicate that perceived usefulness of a MRA influences product purchases, predicts usage intentions and store preferences of consumers. Thus, new business models for retail stores can be considered in which MRAs satisfy both the information needs of consumers and the communication needs of retailers.     

Enticing online consumers: an extended technology acceptance perspective

The business-to-consumer aspect of electronic commerce (EC) is the most visible business use of the World Wide Web (WWW). A virtual store allows companies to provide product information and offer direct sales to their customers through an electronic channel. The fundamental problem motivating this study is that: in order for a virtual store to compete effectively with both physical stores and other online retailers, there is an urgent need to understand the factors that entice consumers to use it. This research attempted to provide both theoretical and empirical analyses to explain consumers’ use of a virtual store and its antecedents.By applying the technology acceptance model (TAM) and innovation diffusion theory (IDT), this research took an extended perspective to examine consumer behavior in the virtual store context. The data from a survey of online consumers was used empirically to test the proposed research model. Confirmatory factor analysis (CFA) was performed to examine the reliability and validity of the measurement model, and the structural equation modeling (SEM) technique was used to evaluate the causal model. The implication of the work to both researchers and practitioners is discussed.     

Which is more important in Internet shopping,perceived price or trust?

Price and trust are considered to be two important factors that influence customer purchasing decisions in Internet shopping. This paper examines the relative influence they have on online purchasing decisions for both potential and repeat customers. The knowledge of their relative impacts and changes in their relative roles over customer transaction experience is useful in developing customized sales strategies to target different groups of customers. The results of this study revealed that perceived trust exerted a stronger effect than perceived price on purchase intentions for both potential and repeat customers of an online store. The results also revealed that perceived price exerted a stronger influence on purchase decisions of repeat customers as compared to that of potential customers. Perceived trust exerted a stronger influence on purchase decisions of potential customers as compared to that of repeat customers.     

Selling luxury fashion to conspicuous consumers in the presence of discount sensitivity behavior

In the luxury fashion industry, with the possibility of stockout, conspicuous consumers may purchase products at the full price rather than wait for any potential discount. However, in the presence of a possible future discount, conspicuous consumers may also feel regret to purchase at the full price if they find that the product is still available at the markdown price. Considering the possible stockout and future discount, in this paper, we evaluate the firm's pricing and production decisions on conspicuous consumers in the presence of discount sensitivity behavior. We build up an analytical model and consider that the customer purchasing utility decreases with discount sensitivity if she/he purchases at the full price. The firm can create scarcity in the market by reducing inventory to induce customers to purchase early. If the fraction of the customers with discount sensitivity is lower than a certain level, the firm should intentionally produce a large amount of products. Moreover, we find that product design enhancement can effectively weaken the negative effects of customer discount sensitivity on the quantity decisions. More managerial insights are discussed.     

Re-examining the influence of trust on online repeat purchase intention: The moderating role of habit and its antecedents

Customer loyalty or repeat purchasing is critical for the survival and success of any store. By focusing on online stores, this study investigates the moderating role of habit on the relationship between trust and repeat purchase intention. Prior research on online behavior continuance models perceives usefulness, trust, satisfaction, and perceived value as the major determinants of continued usage or loyalty, overlooking the important role of habit. We define habit in the context of online shopping as the extent to which buyers tend to shop online automatically without thinking. Building on recent research on the continued usage of IS and repeat purchasing, we develop a model suggesting that habit acts as a moderator between trust and repeat purchase intention, while familiarity, value and satisfaction are the three antecedents of habit. Data collected from 454 customers of the Yahoo!Kimo shopping mall provide strong support for the research model. The results indicate that a higher level of habit reduces the effect of trust on repeat purchase intention. The data also show that value, satisfaction, and familiarity are important to habit formation and thus relevant within the context of online repeat purchasing. The implications for theory and practice and suggestions for future research are also discussed.     

The power of a thumbs-up: Will e-commerce switch to social commerce?

By taking advantage of social networking capabilities, social commerce provides features that encourage customers to share their personal experiences. The popularity of online social networks has driven the purchase decisions of buyers on social commerce sites, but few studies have explored why consumers switch between e-commerce (product-centered) and social (social-centered) commerce sites. In applying the push–pull–mooring model, the objective of this study was to gain an understanding of specifically how push, pull, and mooring factors shape their switching intentions. The findings revealed that push effect, in terms of low transaction efficiency, drives customers away from e-commerce sites, whereas the pull effects, including social presence, social support, social benefit, and self-presentation, attract customers to social commerce sites. Moreover, mooring effects, including conformity and personal experience, strengthened consumers’ behavior in switching between e-commerce and social commerce sites. Besides, conformity was also found to moderate the influences of social presence, social support, social benefit, and efficiency on switching intention, whereas personal experience moderated the effects of social benefit, self-presentation, and efficiency on switching intention. Such an understanding assists online retailers in understanding online shoppers’ switching behaviors, and thus turning social interactions into profits and sales.     

Keep your bots to yourself [software law]

There are now a variety of Web bots or spiders available to scour the Web to automatically gather information. Bots, sometimes called agents when they are instructed to perform particular searches, are useful in performing the time-consuming and repetitive searches required to gather comparison data or to find an elusive item. In some cases, agents can not only find information but can make a purchase or take another action based on the data they collect. Although bots are great for consumers, some Internet retailers hate them. Just as a brick and mortar store wants potential customers to walk in the door, Web retailers want potential customers to personally view their sites. Once there, consumers might purchase the initial products they were seeking and then see advertisements or buy accessories, upgrades, or unrelated additional items as well. Because bots can reduce or eliminate these possibilities, some Internet retailers are trying to stop them. It's one thing to be upset about bots, spiders, agents, and data miners, but it is quite another to put an end to the practice. It should come as no surprise that federal and state laws in the US do not expressly mention bots. Those seeking to challenge their use must resort to a variety of more generic laws, none of which fit very well     

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。     

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.     

传统企业成功转型——“杭州祜康”O2O模式

O2O是指线上线下电子商务,把线上的消费者带到现实商店中:在线支付线下商品、服务,再到线下享受服务。同时,把线下商店的消息推送给互联网用户,从而将他们转换为自己的线下客户。杭州祐康采用的就是通过线上下单,由公司旗下的社区便利店等方式实现配送等业务的O2O模式。     

Communication Privacy Management in Electronic Commerce

This study applies Petronio's Communication Privacy Management theory (CPM) to understand the tension between information disclosure and privacy within e-commerce relationships. It proposes that consumers manage their privacy concerns through decisions to reveal or conceal information about themselves in interactions with online retailers. The study investigates the degree to which privacy management strategies identified by CPM theory to regulate privacy and disclosure within interpersonal relationships, including withholding and falsifying information, as well as seeking information seeking from a relational partner, operate in the computer-mediated context of e-commerce relational transactions. Findings suggest that online consumers do erect boundaries around personal information and form rules to decide when to reveal information that are consistent with CPM theory. Overall, this study provides knowledge about privacy in online commercial transactions, serves as a basis for more directed theory construction in this arena, and has important practical and policy implications.     

“Bid more,pay less” – overbidding and the Bidder’s curse in teleshopping auctions

This paper provides a theoretical and empirical analysis of the multi-unit Dutch teleshopping auctions of 1–2–3.tv. There are two channels for sales transactions: Customers either bid in the teleshopping auctions or purchase in the online shop for a simultaneously available fixed price. Our theoretical analysis indicates that profit-maximizing customers do not overbid the fixed price, since they risk experiencing the Bidder’s Curse: Buying at a uniform auction price that is higher than the fixed price. Our data set includes nearly 700,000 recorded bids. We find that customers overbid in 26% of all bids, but the Bidder’s Curse only occurs in 5% of all auctions. Offline-bidders (telephone calls) overbid both by larger amounts and more often than do online-bidders (website or app), and, on average, the most frequent customers do not experience learning effects.     

基于多渠道供应链博弈的线上价格策略

对一个开辟线上直销渠道的制造商和一个双渠道零售商组成的供应链系统，考虑线下渠道促销努力及消费者搭便车行为，在零售商主导的Stackelberg博弈下，就线上价格是否一致，研究了各渠道的定价策略。结果表明：当制造商线上渠道基本市场份额较大时，对制造商和零售商来说，线上价格不一致是最优策略。当制造商线上渠道基本市场份额较小时，双方都倾向拥有线上价格的决定权；并且当制造商承担部分促销成本时，零售商能接受制造商决定线上价格。