The semantic Web revisited

The article included many scenarios in which intelligent agents and bots undertook tasks on behalf of their human or corporate owners. Of course, shopbots and auction bots abound on the Web, but these are essentially handcrafted for particular tasks: they have little ability to interact with heterogeneous data and information types. Because we haven't yet delivered large-scale, agent-based mediation, some commentators argue that the semantic Web has failed to deliver. We argue that agents can only flourish when standards are well established and that the Web standards for expressing shared meaning have progressed steadily over the past five years.     

搜索引擎的Web Robot技术与优化

针对目前如何使搜索引擎快速准确地从庞大的网页数据中获取所需资源的需求，文中对搜索引擎作了概述，重点阐述了搜索引擎的Web Robot搜索器的搜索策略、文档提取以及搜索优化措施，提出了改进搜索引擎的Web Rohot的方法，改进后的Web Robot能够更有效地发现和搜集信息。为搜索引擎进行信息搜集，高效、稳定的Web Rohot保证了为用户提供的网上信息的全面性和实时性。     

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.     

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.     

Der Einfluss von Such- und Empfehlungssystemen auf den Absatz im Electronic Commerce

The Internet and related technologies have vastly expanded the variety of products that can be profitably promoted and sold by online retailers. Furthermore, search and recommendation tools reduce consumers’ search costs in the Internet and enable them to extend their search from a few easily found best-selling products (blockbusters) to a large number of less frequently selling items (niches). As a result, Long Tail sales distribution patterns emerge that illustrate an increasing demand in niches. We show in this article how different classes of search and recommendation tools affect the distribution of sales across products, total sales, and consumer surplus. We hereby use an agent-based simulation which is calibrated based on real purchase data of a video-on-demand retailer. We find that a decrease in search costs through improved search technology can either shift demand from blockbusters to niches (search filters and recommendation systems) or from niches to blockbusters (charts and top lists). We break down demand changes into substitution and additional consumption and show that search and recommendation technologies can lead to substantial profit increases for retailers. We also illustrate that decreasing search costs through search and recommendation technologies always lead to an increase in consumer surplus, suggesting that retailers can use these technologies as competitive advantage.     

Price versus privacy: an experiment into the competitive advantage of collecting less personal information

In previous privacy studies, consumers have reported their unease with online retailers that collect a lot of personal data. Consumers claim they will switch to alternative providers or cancel transactions if data collection is deemed excessive. Therefore, privacy appears to be a competitive factor in electronic commerce. This paper describes a study which quantifies the degree to which privacy is a competitive advantage for online retailers. In an experiment, we offered 225 participants the option to purchase one DVD from one of two online stores. Throughout the study, one online shop asked for more invasive personal data—as confirmed by an exit-questionnaire. In the test treatment, the privacy-invasive store sold DVDs for one Euro less than the other, and in the control treatment, both stores sold DVDs for the same price. Across both treatments, 74 participants made a purchase and had the DVD they bought delivered. In our study we found that, when the price of DVDs was the same between both stores, the shop asking for less personal data did not amass the entire market. When consumers were offered a trade-off between price and privacy, the vast majority of customers chose to buy from the cheaper, more privacy-invasive, firm; this firm got both a larger market share and higher revenue. The cheaper shop generated strong dissatisfaction with their privacy practises; in contrast, consumers of the more expensive store displayed only weak dissatisfaction with price. We established the validity of our analysis by checking users made informed choices, and did not select one firm over the other due to hasty decision-making or ordering effects. We found no support for either a materialistic lifestyle nor the quest for immediate gratification as to why customers chose the cheaper but privacy-unfriendly store.     

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.     

基于移动代理的服务供应链构建仿真模型

在Internet环境中,客户可以通过移动代理的搜索,发现所需的产品和服务,并向服务提供者提出服务请求。服务提供者对客户的请求进行逐级的分解并响应,从而构建起一条由客户发起的服务供应链。传统的自顶向下和自底向上的供应链构建方法,都不太适合在Internet开放和分布式的环境下构建服务供应链。因此该文主要研究通过移动代理搜索的方法来构建服务供应链。首先用任务关系图描述了客户及服务提供者之间的服务关系,分析并比较了几种典型的服务提供者,提出了“桥式服务”的概念;接着在移动代理简单搜索策略的基础上,通过实验仿真研究了构建最优服务供应链的概率,以及服务提供者的类型和移动代理的数量变化,对这种概率的影响及趋势。     

Best Practice in Managing HTTP-Based Client Sessions

Most organizations now have substantial investments in their online Internet presences. For major financial institutions and retailers, the Internet provides both a cost effective means of presenting their offerings to customers, and a method of delivering a personalised 24/7 presence. In almost all cases, the preferred method of delivering these services is over common HTTP. Due to limitations within the protocol, there is no in-built facility to identify or track a particular customer (or session) uniquely within an application. Thus the connection between the customer’s Web browser and the organisation's Web service is commonly referred to as being “stateless”. Because of this, organizations have been forced to adopt custom methods of managing client sessions if they wish to maintain state.An important aspect of correctly managing state information through session IDs relates directly to authentication processes. While it is possible to insist that a client using an organization's Web application provide authentication information for each “restricted” page or data submission, it would soon become tedious and untenable. Thus session IDs are not only used to follow clients throughout the Web application, they are also used to identify each unique, authenticated user — thereby indirectly regulating access to site content or information.     

Understanding multi-channel research shoppers: an analysis of Internet and physical channels

The purpose of this study is to analyze how channel characteristics influence the channel attitudes of multi-channel research shoppers. In addition, the study also considers consumers’ complex shopping behaviors that involve using one channel for search and another for purchase simultaneously. Survey data were collected from 191 consumers with recent (i.e., in the last 3 months) multi-channel experiences. Qualified respondents had either searched in physical retail stores and purchased on the Internet or searched on the Internet and subsequently purchased in physical retail stores. The research hypotheses were examined using multiple regression analysis. The results show that customer perceptions of channel characteristics drive channel choice attitudes. Importantly, we find the significance of channel characteristics varies between the Internet and the physical channel. The research findings deepen our understanding of shopping behaviors in the multi-channel context. Practitioners may use the findings to manage the characteristics of the complementary channels while also designing marketing programs to create positive consumer attitudes toward search and purchase.     

Assessing Web-enabled call center technologies

E-commerce's explosive growth has seen corporate Web sites mature from electronic versions of glossy brochures to full-service storefronts. To support this new environment, companies are providing real-time customer service to their Web customers. Despite this tremendous e-commerce growth, many people remain reluctant to complete a Web transaction without first talking to a live agent. Corporations are linking their Web sites to call centers where pools of trained agents can assist Web shoppers that need help in real time. To provide Web visitors with instant customer service, retailers are adding a talk-to-agent button on Web pages. When a visitor presses the button, the Web site will present the caller with several options for actuary talking to an agent. These options include e-mail, text chat, agent callback, and Internet telephony. There are two main technology alternatives that a call center can implement for Web integration. The first technology enables a traditional call center that has circuit-switched-based systems to support talk-to-agent alternatives. The second technology is the implementation of an all-IP call center infrastructure. Mitretek's Call Center Lab has assessed several products     

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.     

Tuning up the search engine

Advances in Internet search engine technology may not help you blast Klingons into outer space, but they should help you find them more quickly on the Web. The whole arena for Internet searching has become rather interesting. Search engines appear poised to make some serious breakthroughs in relevancy ranging and personalization that promise to increase the accuracy and reliability of search. On the ether hand, data suggests that users are becoming increasingly disenchanted with search engines that don't actually search the Web, but rather search records of the Web sites their robots have visited. Some online merchants (Victoria's Secret, for example) don't even enable keyword searches on their sites. The Web's increasingly dynamic nature complicates searching. New pages created on the fly using personalization information, and even static content, with dynamically inserted sidebars, navigation bars, advertising and commentary, can present a rapidly changing picture for any robot to discover. And as indexes grow larger, search system performance becomes a significant problem     

Internet channel entry: retail coverage and entry cost advantage

In this research we study how existing market coverage affects the outcome of the Internet channel entry game between an existing retailer and a new entrant. A market is not covered when some consumers with low reservation prices are priced out by existing retailers and do not purchase. In a model with multiple existing retailers and a potential new entrant, we demonstrate that when entry costs are equal, one of the existing retailers enters the Internet channel first. However, if the market is covered by existing retailers before entry, then because of the threat of Internet channel entry by the potential new entrant, retailer entry cannibalizes existing retail profits—cannibalizing at a loss. In addition, if a potential new entrant has a slight advantage in Internet channel entry costs and the market is not covered by existing retailers, then the new entrant enters the Internet channel first. If the market is covered by existing retailers, then the new entrant must have a larger Internet channel entry cost advantage to be first to enter the Internet channel.

Dawn of the Internet appliance

Internet technologies have fundamentally changed the way machines can gather, store and share information. Devices can now transmit important information and instructions via the Internet. Now the standardization of Internet protocols and competition among Internet service providers (ISPs) have driven down the price of Internet connectivity, so vendors are beginning to incorporate it into a wide range of devices. Developers can now put Internet connectivity into a variety of devices, including factory machinery, VCRs and hand-held appliances. In addition, low-cost communications technologies, such as wireless, promise to let users connect these devices inexpensively to intranets. Moreover, because Web browsers are so common, developers can provide sophisticated low-cost interfaces by supporting Web servers in their products. It is easy for developers to create such applications because they are so familiar with Internet tools     

The Effectiveness of Low Price Matching in Mitigating the Competitive Pressure of Low Friction Electronic Markets

The conventional wisdom is that Internet commerce substantially reduces the transaction costs for comparison shopping, which in turn intensifies price competition. However, the technology of the Internet marketplace offers retailers tools with the potential to blunt some of this competition. This paper explores the competitive impact of an electronic low price matching policy when firms can track customer search behavior. Using controlled laboratory techniques, we find that through the use of low price matching sellers are able to dampen some of the intense competition spawned when a large proportion of consumers comparison shop.     

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.     

Perceptions of Customer Service,Information Privacy,and Product Quality From Semiotic Design Features in an Online Web Store

The rise of the World Wide Web for electronic commerce has led to a proliferation of companies selling products online. The global nature of the Internet allows customers to browse the products of companies with which they are wholly unfamiliar. However, concerns about customer service, information privacy, and product quality discourage purchasing from unknown companies. In this article, the effects of semiotic Web design features on expectations of these performance criteria in a purchase situation are investigated. Specifically, the presence and prominence of links to customer service and a site privacy policy, and the existence of product ratings and customer testimonials, were tested to measure their effects on customer perceptions and expectations. Results indicate that some design features have a strong semiotic effect on customer expectations. Prominent links to customer service and a site privacy policy significantly increased expectations of customer service and privacy protection. The presence of product ratings increased perceptions of product quality. All 3 design features led to increased likelihood of purchase. Furthermore, participants were not aware of these effects and reported not considering product ratings in their decisions. Implications of these results on Web site design and consumer behavior are discussed.     

Sensors + agents + networks = aware agents

Software agents are being deployed in increasing numbers to help users find and manage information, particularly in open environments such as the Internet. For the most part, they operate independently and are typically designed to be aware only of their users and the environment in which they perform their tasks. Thus, they fail to take advantage of each other's abilities or results. For example, a shopping agent might periodically access several online databases to find the best price for a music CD and then purchase it if the price falls below its user's threshold. Other agents might be tracking prices for the same CD, duplicating each other's work. Similarly, if your agent and an agent for the person in the next cubicle are both browsing the same Web site, two identical data streams arrive on your LAN, using twice the bandwidth actually needed. To be more effective, agents must be aware of each other; therefore, they must acquire models of each other. One way to do this is by exchanging messages. A second form of awareness involves the state of the agent's own environment, including characteristics of the computer on which it is executing and its network connection. A third involves self awareness: knowing its name, age, ontology, goals, areas of expertise and ignorance, and reasoning abilities. Finally, the agent should be aware of its physical environment. The article explains how software agents can develop awareness     

Customer-adapted coupon targeting using feature selection

The management of coupon promotions is an important issue for marketing managers since it still is the major promotion medium. However, the distribution of coupons does not go without problems. Although manufacturers and retailers are investing heavily in the attempt to convince as many customers as possible, overall coupon redemption rate is low.

This study improves the strategy of retailers and manufacturers concerning their target selection since both parties often end up in a battle for customers. Two separate models are built: one model makes predictions concerning redemption behavior of coupons that are distributed by the retailer while another model does the same for coupons handed out by manufacturers. By means of the feature-selection technique ‘Relief-F’ the dimensionality of the models is reduced, since it searches for the variables that are relevant for predicting the outcome. In this way, redundant variables are not used in the model-building process. The model is evaluated on real-life data provided by a retailer in Fast Moving Consumer Goods (FMCG).

The contributions of this study for retailers as well as manufacturers are three-fold. First, the possibility to classify customers concerning their coupon usage is shown. In addition, it is demonstrated that retailers and manufacturers can stay clear of each other in their marketing campaigns. Finally, the feature-selection technique Relief-F proves to facilitate and optimize the performance of the models.