Online Interactive Consumer Decisions Aids (ICDAs) 互动消费者决策辅助工具（ICDAS）
According to Alba et al. (1997) study the tools of interactive consumer decisions aids available for implementing device interactivity in an electronic commerce environment have to provide customers with unexampled opportunities to set and compare product offerings (Alba et al. 1997, p.38). 据Alba等人1997的研究，有助于实现设备在电子商务环境下的互动的互动消费决策辅助工具，为客户提供设置和比较的产品的无可比拟的机会（ALBA等，1997年，第38页）。Such functions are especially valuable given that online shops cannot provide real contact with products, they do not have the opportunity to offer the consumer face to face advise with a salesperson, and may offer a vast range of products because their shelf space is virtually infinite这些功能在以下情况下特别有价值：网上商店不能提供产品的真正接触，他们不会有机会作为销售人员向消费者提供面对面建议，但是因为他们的货架空间几乎是无限的，他们可能提供了广阔的产品; it is a lack of physical constraints about product display (Haubl and Trifts, 2000). 它缺乏关于产品展示的物理限制。
A crucial issue about decision-making in the electronic environment is that it is often unable to help inpiduals evaluate all available choices (Beach, 1993) 关于电子环境中的决策的一个关键问题是，它常常无法帮助个人对所有可供选择的商品进行评估. Therefore, a normal sorting of interactive shopping agents is depending on whether a tool is created to help a customer determine where or what to buy. These two assignments may be described as product breaking and merchant brokering (Guttman et al., 1998). The primarily two step of purchase decision making process may expand as follows: firstly the consumer screens a vast range of products and gives them an in-depth evaluation, and secondly she or he examines the latter in more depth, implements comparisons across commodity on important attributes, and makes their purchase decision (Haubl and Trifts, 2000). According to Haubl and Trifts (2000) given these two different assignments to be implemented in the purchase decision making processes, interactive tools help to consumers in the abovementioned two aspects seem especially valuable; they are primary screening of available products to decide which ones are worth evaluating further. Furthermore, in an article by Murray and Haubl (2008), interactive decision aids are a technology designed to help consumers make better purchase decisions. The role of an interactive customer decision aid will be introduced in the following order:互动客户决策辅助工具的作用将按以下顺序进行介绍：
(1)Clerk - help consumers to search for products.
(2)Advisor – apply consumers’ actions to make product recommendations.
(3)Banker – provide banking information to help consumers to finish transactions.
(4)Tutor – help consumers to form their preferences.
However, this research will be focuses on the two decision aids: Recommendation Agent and Comparison Matrix, each of them are designed to support customers implementing purchase decision.
Recommendation Agent (RA) 推荐代理
The capability of recommendation agent as Haubl and Trifts once stated:推荐代理的能力正如Haubl和Trifts曾经说过的：
“To allow consumers to efficiently screen the (potentially very large) sets of alternatives available in an online shopping environment” (Haubl and Trifts, 2000). 让消费者能够在网上购物环境有效地筛选（可能非常大）的替代品 “（Haubl Trifts，2000年）。
Nowadays there is a trend to apply a recommendation agent in order to help consumers online shopping be more successful. If consumers effectively implement recommendation agents, then it can increase both customer loyalty and the overall sales volume.
A typical recommendation agent is used in response to the problem of information overload to the consumer (Haubl and Murray, 2003). Thus, Recommendation agents are a kind of system that filters information for the user’s needs. They try to understand the consumers’ interests (Haubl and Murray, 2003). Furthermore and more important, their main function is to apply different methods of filtering the vast amount of information to fit in with the user’s needs and to reduce the cost of searching. According to Rensnick and Varian (1997) that recommendation agent was born to solve the problem of information overload. Nevertheless, a relationship between the one with the problem and the problem solver sometimes does not real exist in the electronic shopping environment. However, what we need to note is that a recommendation agent includes the process of filter information; the main point is to recommend proper information in order to attract users.
Thus, in this information age, recommendation agents are broadly applied on e-commerce, education, and organization knowledge management (Spiekermann, 2001). It provides a kind of mass customization that is rapidly growing throughout the World Wide Web. However this research focuses on the e-commerce area. For a website, a good choice of the correct intelligent tools can affect its survival, a useful product recommendation system is progressively known by online stores as a means to sell more products. On the other hand, websites that do not adapt the correct tools will see a poor purchase rate and experience less traffic as consumers are more likely to keep coming back to online stores that are adapting recommendation system (Castagnos et. al, 2009). For instance, Yahoo!, Alta Vista, and Amazon all use a recommendation tool to suggest relevant documents according to any keywords the customer has supplied or even from past purchases they have made. Furthermore, it is hard to estimate when consumers will visit the website, and it is also hard to hire employees to set up an employees’ working timetable. Thus, in order to advance a website’s efficiency and to reduce customers supply problems, Amazon applied a recommendation agent function aimed to marketing products or give customers purchase recommendation as well as to replace some of their workers. For instance, the sort of recommendations may include music, books, movies, or even restaurants according to other similar consumers’ tastes in terms of their likes and dislikes (Birukov et al., 2004).
To sum up, “A recommendation agent is a tool for screening alternatives” (Haubl and Murray, 2003).
Comparison Matrix (CM) 比较矩阵
Haubl and Trifts (2000) suggest “A comparison matrix is designed to help with in-depth comparisons among selected alternatives.” Haubl和Trifts在2000年提出“设计比较矩阵是来帮助在各种可选择的替代品之间进行深入地比较。”The business domains of the Wide Web World have been growing at a very rapid pace (Vallamsetty, 2003); it provides consumers another way to shop online. In the meanwhile, business information comparison websites have been created. These kinds of websites collect a lot of online stores’ information, which provides consumers with a series of alternatives. It is not only a decrease in the product size but also an increase in the quality of customers’ consideration set (Haubl and Murray, 2003). For instance, lastminute.com and pricescan.com employed a comparison matrix to fix customers need. Thus, a comparison matrix is a tool created to help customers make in-depth comparisons among a number of products in an online store (Haubl et. al, 2003). When customers type in what they are looking for in the product category, it is determined by price, warranty period, physical dimensions, or other performance-related features through a comparison matrix (Wan et. al, 2007). It can make a customer be more focused in their purchase decision process because the consideration range is becoming smaller and the quality is also improving (Haubl et. al, 2003). In addition, what we need to be noted is that the evaluation involves both objective and subjective information, so that every consumer may have different evaluations of the same product (Wan et. al, 2007).
To sum up, “Comparison Matrix is a tool for organizing product information” (Haubl and Murray, 2003).
Section Summary本节小结
The coming of the Internet has dramatically changed, thus, the current scholars mostly concentrate on online stores (Doherty et al., 1999; Reynolds, 1999) in order to attract consumers to the e-store as well as to deal with the problems regarding customer retention.，互联网的到来已经发生了极大地改变，因此，目前学者大多集中于网上商店以吸引消费者到电子商店，同时处理客户的忠诚度问题。 On the one hand, in order to gain high quality information to potential support for consumers to improve their decision making process through online decision aids. On the other hand, online decision aids enable enterprise to run the business for 24hours a day in order to make more profits as well as replacing some workers to reduce enterprises’ costs.