Has the web transformed experience goods into search goods?

Klein (Journal of Business Research 41(3): 195–203, 1998) posited that the Web can transform experience goods into search goods (ES shifts). We examine her proposition in three ways. First, we critically assess the background of her proposition in light of the Web evolution in the past decade. Second, we conduct a comparison of past studies that measured the extent of search, experience, and credence (SEC) characteristics of goods. Third, we report the results of an exploratory survey on a set of commonly purchased products to benchmark possible ES shifts against the past studies. Their results indicate that SEC classification changes do not seem significant.     

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.     

The perceptions towards mobile services: an empirical analysis of the role of use facilitators

The adoption patterns for new technology such as mobile services are essential to understand for developing them further. Hence, it is important to study how willing people are to try new mobile services and do variables, which facilitate the use of the services have an effect on the consumers’ perceptions of the services and their adoption readiness. This study analyses how the familiarity of mobile devices, the time the services are initially used and users’ technology skills affect the initial mobile service usage experience and the likelihood of continuous usage. The results show that the duration of the use does not effect consumers’ perceptions about mobile services, but familiarity of the device and user skills have an impact on the perceptions of the services.     

Agent based intelligent search framework for product information using ontology mapping

The Semantic Web and Web services provide many opportunities in various applications such as product search and comparison in electronic commerce. We implemented an intelligent meta-search and recommendation system for products through consideration of multiple attributes by using ontology mapping and Web services. Under the assumption that each shopping site offers product ontology and product search service with Web services, we proposed a meta-search framework to configure a customer’s search intent, make and dispatch proper queries to each shopping site, evaluate search results from shopping sites, and show the customer the relevant product list with associated rankings. Ontology mapping is used for generating proper queries for shopping sites that have different product categories. We also implemented our framework and performed empirical evaluation of our approach with two leading shopping sites in the world.     

智能Agent在比较购物中的应用

用智能Agent实现比较购物要解决海量信息搜索、根据用户偏好进行个性化筛选、用户偏好学习等问题。通过事先把主要电子商务网站的内容下载保存到本地数据库来实现快速搜索，通过关键向量信息过滤法可以实现筛选，通过样本学习和反馈学习可以获取用户偏好。以此实现用智能Agent来替用户比较、搜索合适的商品，从而大大提高在线购物的范围和效率，实现个性化的导购。     

Simulating Sequential Search Models with Genetic Algorithms: Analysis of Price Ceilings,Taxes, Advertising and Welfare

This paper studies advertising, price ceilings and taxes in a sequential search model with bilateral heterogeneities in production and search costs. We simulate equilibria using a genetic algorithm (GA) applied to over 100 market scenarios, each differing based on the number of firms, number of consumers, existence of price ceilings or taxes, costs of production, costs of advertising, consumers’ susceptibility to advertising and consumers’ search costs. We study the interaction of advertising and search and analyze the welfare effects of advertising, price ceilings and sales taxes. Despite advertising being uninformative, we find that firms charging lower prices tend to advertise more intensely and that price ceilings and advertising can improve welfare if search costs are high.     

Using Site Semantics to Analyze, Visualize, and Support Navigation

To satisfy potential customers of a Web site and to lead them to the goods offered by the site, one should support them in the course of navigation they have embarked on. This paper presents the tool STRATDYN, developed as an add-on module to the Web Usage Miner WUM. WUM not only discovers frequent sequences, but it also allows the inspection of the different paths through the site. STRATDYN extends these capabilities: It tests differences between navigation patterns, described by a number of measures of success and strategy, for statistical significance. This can help to single out the relevant differences between users' behaviors, and it can determine whether a change in the site's design has had the desired effect. STRATDYN also exploits the site's semantics in the classification of navigation behavior and in the visualization of results, displaying navigation patterns as alternative paths through a strategy space. This helps to understand the Web logs, and to communicate analysis results to non-experts. Two case studies investigate search in an online catalog and interaction with an electronic shopping agent in an online store. They show how the results of analysis can lead to proposals for improving a Web site. These highlight the importance of investigating measures not only of eventual success, but also of process, to help users navigate towards the site's offers.     

基于遗传算法的超市最短导购路径推荐

大型超市里商品数目的繁多、空间布局的复杂往往容易让消费者迷失在室内,花费大量时间进行商品搜寻。提出基于遗传算法的超市导购路径推荐方法,通过对超市的空间布局结构离散化建模,生成分别用节点和无向边表示商品区域和区域之间可行走路线的平面图;结合消费者的采购清单,根据商品所在的货架位置将商品与具体的区域做出匹配,用遗传算法优化生成一条联结超市入口、要采购的商品区域以及结账柜台的最短路线。Matlab的仿真结果显示,该方法简单、高效,能够快速为消费者推荐出最短路线,供其购物参考。     

Research interests: their dynamics,structures and applications in unifying search and reasoning

Most scientific publication information, which may reflects scientists’ research interests, is publicly available on the Web. Understanding the characteristics of research interests from previous publications may help to provide better services for scientists in the Web age. In this paper, we introduce some parameters to track the evolution process of research interests, we analyze their structural and dynamic characteristics. According to the observed characteristics of research interests, under the framework of unifying search and reasoning (ReaSearch), we propose interests-based unification of search and reasoning (I-ReaSearch). Under the proposed I-ReaSearch method, we illustrate how research interests can be used to improve literature search on the Web. According to the relationship between an author’s own interests and his/her co-authors interests, social group interests are also used to refine the literature search process. Evaluation from both the user satisfaction and the scalability point of view show that the proposed I-ReaSearch method provides a user centered and practical way to problem solving on the Web. The efforts provide some hints and various methods to support personalized search, and can be considered as a step forward user centric knowledge retrieval on the Web. From the standpoint of the Active Media Technology (AMT) on the Wisdom Web, in this paper, the study on the characteristics of research interests is based on complex networks and human dynamics, which can be considered as an effort towards utilizing information physics to discover and explain the phenomena related to research interests of scientists. The application of research interests aims at providing scientific researchers best means and best ends in an active way for literature search on the Web.     

Comparison of product bundling strategies on different online shopping behaviors

Bundling is a very popular sales-promotion tool, in which a critical issue is to decide what products should be sold together in order to improve sales. Traditionally, this decision is based on the order data collected from the points of sale. However, Internet marketing now allows marketers to efficiently collect not only order data but also browsing and shopping-cart data, which provide marketers with information on the consumers’ decision-making processes, rather than only the final shopping decisions. The present study aimed to determine the value of this newly available information by comparing the performance of decision-making on product bundling based on three types of data on online shopping behaviors. The results from a field experiment reveal that significantly better decisions are made on the bundling of products when browsing and shopping-cart data are integrated than when only order data or browsing data are used.     

An examination of the celebrity endorsements and online customer reviews influence female consumers’ shopping behavior

The goal of this study is to compare the influence of celebrity endorsements to online customer reviews on female shopping behavior. Based on AIDMA and AISAS models, we design an experiment to investigate consumer responses to search good and experience good respectively. The results revealed that search good (shoes) endorsed by a celebrity in an advertisement evoked significantly more attention, desire, and action from the consumer than did an online customer review. We also found that online customer reviews emerged higher than the celebrity endorsement on the scale of participants’ memory, search and share attitudes toward the experience good (toner). Implications for marketers as well as suggestions for future research are discussed.     

Next-generation agent-enabled comparison shopping

Agents are the catalysts for commerce on the Web today. For example, comparison-shopping agents mediate the interactions between buyers and sellers in order to yield more efficient markets. However, today's shopping agents are price-dominated, unreflective of the nature of seller/buyer differentiation or the changing course of differentiation over time. This paper aims to tackle this dilemma and advances shopping agents into a stage where both kinds of differentiation are taken into account for enhanced understanding of the realities. We call them next-generation shopping agents. These agents can leverage the interactive power of the Web for more accurate understanding of buyer's preferences. This paper then presents an architecture of the next-generation shopping agents. This architecture is composed of a Product/Merchant Information Collector, a Buyer Behavior Extractor, a User Profile Manager and an Online Learning Personalized-Ranking Module. We have implemented a system following the core of the architecture and collected preliminary evaluation results. The results show this system is quite promising in overcoming the reality challenges of comparison shopping.     

Transaction models for Web accessibility

The Web has evolved into a dominant digital medium for conducting many types of online transactions such as shopping, paying bills, making travel plans, etc. Such transactions typically involve a number of steps spanning several Web pages. For sighted users these steps are relatively straightforward to do with graphical Web browsers. But they pose tremendous challenges for visually impaired individuals. This is because screen readers, the dominant assistive technology used by visually impaired users, function by speaking out the screen’s content serially. Consequently, using them for conducting transactions can cause considerable information overload. But usually one needs to browse only a small fragment of a Web page to do a step of a transaction (e.g., choosing an item from a search results list). Based on this observation this paper presents a model-directed transaction framework to identify, extract and aurally render only the “relevant” page fragments in each step of a transaction. The framework uses a process model to encode the state of the transaction and a concept model to identify the page fragments relevant for the transaction in that state. We also present algorithms to mine such models from click stream data generated by transactions and experimental evidence of the practical effectiveness of our models in improving user experience when conducting online transactions with non-visual modalities.     

Consumer's decision to shop online: The moderating role of positive informational social influence

While much of the current literature tends to focus on the direct effect of social influence on consumer online shopping behavior, our study drew heavily on social influence theory and argued for an alternative theory focusing on the moderating role of social influence. In particular, we explored how positive messages in online discussion forums may affect consumers’ decisions to shop online. We used a laboratory experiment in which the treatment group was required to read positive messages about online shopping experience in an online discussion forum. Positive social influence was found to reinforce the relationship between beliefs about and attitude toward online shopping, as well as the relationship between attitude and intention to shop. We believe our alternative theory provides new insight into the complex processes through which social influence is brought to bear on consumers’ online shopping decisions. Implications of our work are discussed.     

Teleshopping or going shopping? An information acquisition perspective

Abstract

Shopping is the acquisition of information that precedes the purchase of goods and services for household or individual consumption. New telecommunications technologies enable individuals to shop and purchase without leaving the home. Teleshopping options put the individual in a choice situation between home-based shopping and store shopping. This involves a trade-off between the costs (in terms of time and money) and benefits of making a trip or of communicating with vendors. Teleshopping serves as a useful case study for examining the demand for videotex-based services and some psychological factors involved in their adoption. Two major factors associated with the benefits of shopping appear to affect that choice. First, the direct experience of multi-sensory stimulation of store or shopping-mall environments is superior in terms of information quality and quantity to that obtained through teleshopping for many products. Thus, teleshopping may not reduce the uncertainty involved in purchasing decision to the extent possible in store shopping and, therefore, may not be a satisfactory substitute. Second, the recreational and psychological gratification (or costs) that many people experience in store shopping activity but which do not exist in teleshopping may affect the adoption of teleshopping. The relative importance of these factors varies across product or service type and individual shopper's preferences.     

A web DSS approach to building an intelligent internet shopping mall by integrating virtual reality and avatar

This paper is concerned with designing and implementing the Internet shopping mall by using a virtual reality-driven avatar and web decision support system (Web DSS). Traditionally, the Internet shopping mall has been designed based on the combination of several hyperlinks, images, and texts. However, this sort of approach results in a lower performance because possible customers cannot make accurate shopping decisions. To overcome these kinds of pitfalls facing the current Internet shopping malls, we propose using a combination of virtual reality and Web DSS. The main virtues of our proposed approach to designing the Internet shopping mall are as follows: First, the virtual reality technique is emerging as one of the alternatives that guarantee a sense of reality for the customers' part and facilitating the complex process of shopping decision makings. Especially, the avatar, which is an artificially designed man working on the Internet, can make the Internet shopping-related decision making processes easier. Second, the Web DSS approach can provide an effective decision support mechanism for customers. Especially, we design a set of intelligent agents for the proposed Web DSS. Experimental results with an illustrative example showed that our proposed approach can yield a new Internet shopping mall paradigm with which customers can benefit from a high level of decision support functions.     

Automating user reviews using ontologies: an agent-based approach

The Web is becoming a global market place, where the same services and products are offered by different providers. When obtaining a service, consumers have to select one provider among many alternatives to receive a service or buy a product. In real life, when obtaining a service, many consumers depend on the user reviews. User reviews—presumably written by other consumers—provide details on the consumers’ experiences and thus are more informative than ratings. The down side is that such user reviews are written in natural language, making it extremely difficult to be interpreted by computers. Therefore, current technologies do not allow automation of user reviews and require too much human effort for tasks such as writing and reading reviews for the providers, aggregating existing information, and finally choosing among the possible candidates. In this paper, we represent consumers’ reviews as machine processable structures using ontologies and develop a layered multiagent framework to enable consumers to find satisfactory service providers for their needs automatically. The framework can still function successfully when consumers evolve their language and when deceptive reviewers enter the system. We show the flexibility of the framework by employing different algorithms for various tasks and evaluate them for different circumstances.     

Effects of collaborative online shopping on shopping experience through social and relational perspectives

Collaborative online shopping refers to an activity in which a consumer shops at an eCommerce website with remotely located shopping partners such as friends or family. Although collaborative online shopping has increased with the pervasiveness of social networking, few studies have examined how to enhance this type of shopping experience. This study examines two potential design components, embodiment and media richness, that could enhance shoppers’ experiences. Based on theories of co-presence and flow, we examined whether the implementation of these two features could increase co-presence, flow, and the intention to use a collaborative online shopping website.     

Disentangling utilitarian and hedonic consumption behavior in online shopping: An expectation disconfirmation perspective

Increasingly, researchers have come to acknowledge that consumption activities entail both utilitarian and hedonic components. Whereas utilitarian consumption accentuates the achievement of predetermined outcomes typical of cognitive consumer behavior, its hedonic counterpart relates to affective consumer behavior in dealing with the emotive and multisensory aspects of the shopping experience. Consequently, while utilitarian consumption activities appeal to the rationality of customers in inducing their intellectual buy-in of the shopping experience, customers’ corresponding emotional buy-in can only be attained through the presence of hedonic consumption activities. The same can be said for online shopping. Because the online shopping environment is characterized by the existence of an IT-enabled web interface that acts as the focal point of contact between customers and vendors, its design should embed utilitarian and hedonic elements to create a holistic shopping experience. Building on Expectation Disconfirmation Theory (EDT), this study advances a research model that not only delineates between customers’ utilitarian and hedonic expectations for online shopping but also highlights how these expectations can be best served through functional and esthetic performance, respectively. Furthermore, we introduce online shopping experience (i.e., transactional frequency) as a moderator affecting not only how customers form utilitarian and hedonic expectations but also how they evaluate the functional and esthetic performances of e-commerce sites. The model is then empirically validated via an online survey questionnaire administered on a sample of 303 respondents. Theoretical contributions and pragmatic implications to be gleaned from our research model and its subsequent empirical validation are discussed.