How Online Decision Aids Affect Online Purchasing Behaviour of digital products
Introduction
網上購物具有很多優勢。由于互聯網的軟件技術在過去幾年有了顯著增長,消費者在網上購物使用互動媒體的數量也迅速增加。由于現在在市場上有這么多不同的形式和品牌,消費者需要花費更多的時間在選擇所購買的產品上,因此,選擇網上種類繁多的產品,對于消費者真的很難。
Online shopping has abundant advantages. Due to internet software and technology have grown dramatically over the past several years, the number of consumers who use interactive media for online shopping has also rapidly increased. Because there are now so many different forms and brands available in the market, consumers need to spend more time on selecting which product to buy, and therefore, making decisions online with a vast range of products is really difficult for consumers. There is no doubt low price is the biggest attractor of all for consumers, but with a market of perfect information, how to look for low price is the key, and that is where online decision aids come into play.
In the age of the internet, the consumer shopping model and the enterprises’ business model have changed progressively. As a result, consumers now have a new shopping alternative that is online shopping. Online shopping has abundant advantages. For instance, it is a 24 hour market, and there is no time or area limits. Furthermore, it enables consumers to search for particular products easily and it is more cost-saving. For the abovementioned reasons, enterprises have started to focus on e-commerce. Due to internet software and technology have grown dramatically over the past several years, the number of consumers who use interactive media for online shopping has also rapidly increased (Haubl and Trifts, 2000).
Interestingly, nowadays, consumers have a vast amount of alternative products to choose from. However, sometimes too many choices could confuse the consumers, for example, even when they just intend to purchase a common product such as headache medication. Because there are now so many different forms and brands of headache medication available in the market, consumers need to spend more time on selecting which product to buy (Murray and Haubl, 2008).
As a result, making decisions online with a vast range of products is really difficult for consumers. In contrast, in traditional stores, the shopkeeper can offer face to face service to individual consumers to assist them in determining what they need. Employees need to solve this problem in order to attract consumers to approach online shopping. Therefore, most online stores have decision aids to help consumers select products and attract them to purchase the items they are interested in (Punj and Rapp, 2003).
The same situation can be applied to buying luxuries products online, as it is hard to choose from so many brands and official sites, not to mention one luxuries brand may have thousands of products to choose from. Potential customers may have the financial power to shop, but without appropriate online help, they may turn to sites that make their life easier with better online decision aids.
Literature Review
The objective of this research is to examine luxurious brands’ online decision aids aiming to help when customers are shopping online. The research involves information systems study, and the literature review section is thus divided into four main categories. The first part of the literature review discusses the issue of online store. The second part describes the environment of electronic shopping. The third part explains about Interactive Consumer Decisions Aids which includes Recommendation Agent as well as Comparison Matrix. The fourth part it covers the key motivation studies of the customer behavior as well as the repeat purchase decision.
In the age of the internet, the consumer shopping model and enterprises’ business model has changed progressively. As a result, consumers now have a new shopping alternative that is online shopping. Online shopping has abundant advantages. For instance, it is a 24 hour market, there is no time or area limits. Furthermore, it enables consumers to search for particular products easily and it is more cost-saving. For the abovementioned reasons, enterprises have started to focus on e-commerce. Over the past several years, internet software and technology has grown dramatically. The number of consumers who use interactive media for online shopping has also rapidly increased (Haubl and Trifts, 2000).
Nowadays, customers have a vast amount of alternative products to choose from. For instance, a Wal-Mart supercenter has over 100,000 items (Yoffie, 2005), Home Depot has more than 50,000 items (Murray and Chandrasekhar, 2006), and traditional grocery shops have over 30,000 items (Schwartz, 2005). There is no need to say how much items an online store has, because e-Bay and Amazon both offer millions of products (Murray and Haubl, 2008). However, sometimes too much choice confuses the consumers, even when a customer just wants to purchase a common product such as headache medication because there are now so many different forms and brands of headache medication so the consumer needs to spend a lot of time on selecting the product (Murray and Haubl, 2008).. They need to select between the chemical composition, brand name, generic, packaging, and concentration (Murray and Haubl, 2008).
It is worth pointing out that:
“There is a cost to processing information, and cost rises as the complexity of the decision increases” Murray and Haubl, (2008).
As a result, making decisions online with a vast range of products is really difficult for consumers. In contrast, in traditional stores, the shopkeeper can offer face to face service to individual consumers to help give the consumer what they need. Online stores need to
solve this problem in order to attract
http://www.mythingswp7.com/Thesis_Writing/Marketing/ consumers to online shopping. Therefore, that is why most online stores have decision aids to help consumers select products and attract them into purchase the items (Punj and Rapp, 2003).
Furthermore, in regards to the stages of the decision making process in an electronic commerce environment which are two main stages during the decision making process of the online shopping product search environment in order to make a decision (Haubl and Trifts, 2000). The first stage is screening the products, and the second stage is comparing the products’ different features and details. During these two stages that customers enable to use Interactive Consumer Decisions Aids in order to support their purchasing process as well as make purchase decisions.
Electronic shopping Environment
The study of Steckel et al. (2005) suggests during the internet boom of the late 1990s-early 2000s, pure internet enterprises are less common today. Web and electronic businesses are important for today’s industry drivers; meanwhile, it is applying digital technology to commercially transact between units and individuals. Before further discussion, it is important to understand what is online shopping. In Papazafeiropoulou (2010) study “electronic commerce is buying and selling over digital media.” In addition, Habib (2001) identified that electronic commerce has three digital dimensions. They are: the product (service) being sold, the process, and the delivery agent (or intermediary). Additionally, Keen and McDonald (2000) suggest that online stores are not about the aesthetics that are the processes behind the click (Keen and McDonald, 2000). It means that the capability of the online store of the effect is no need to say.
However, the new tendency to enterprises is using electronic commerce (electronic or online stores) as a part of business strategy to apply websites in order to enhance their traditional stores or moreover to be their primarily market channel. Accordingly, customers have to determine how to implement on the electronic shopping environment. Online stores provide customers with a vast range of alternative products and immense convenience. Unfortunately, providing the right amount of information and finding products that match the customer needs is not an easy assignment for these online stores (Pfeiffer et al., 2008). As most electronic shopping environments are featured with a dynamic flow of data, a great number of choices, and multiple decision standards, this may defeat customers (Punj and Rapp, 2003). Therefore, an online store applying the right tools can influence its survival; useful product recommender tools are progressively known by online stores as a means to sell more products. Inversely, websites that do not adapt intelligent tools will not only see bad purchase volumes but also undergo poor traffic as customers are more likely to come back to online stores adapting intelligent tools (Castagnos et. al, 2009). Furthermore and more importantly, the process of making purchase decision are represent in Haubl and Trists (2000) study there are two main stages during the making decision process of an online product search environment in order to make a decision. In the first stage, a customer identifies a number of products they want to compare known as the consideration set or the basket. Experts refer to this stage as product breaking (Mase et.al, 1999). As for the second stage, in order to make a decision, the customer will compare the features and details of these products. Experts refer to this stage as product comparison. (Castagnos et. al, 2009) In addition, Haubl et al. (2003) points out that one of the most interesting sights of the electronic shopping environment is that they make enterprises build personalized customer interfaces. It means that customer interfaces of online stores can be designed to be adjustable to particular needs, interests, and preferences of each customer at specific points in time. Such personalization can offer an individual shopper interface, dependent on what the website is able to infer, or what the website knows about specific customers.
Interactive Consumer Decisions Aids (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). 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; it is a lack of physical constraints about product display (Haubl and Trifts, 2000).
A crucial issue about decision-making in the electronic environment is that it is often unable to help individuals evaluate all available choices (Beach, 1993). 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:
Clerk - help consumers to search for products.
Advisor – apply consumers’ actions to make product recommendations.
Banker – provide banking information to help consumers to finish transactions.
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)
The capability of recommendation agent as Haubl and Trifts once stated:
“To allow consumers to efficiently screen the (potentially very large) sets of alternatives available in an online shopping environment” (Haubl and Trifts, 2000).#p#分頁標題#e#
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)
Haubl and Trifts (2000) suggest “A comparison matrix is designed to help with in-depth comparisons among selected alternatives.” #p#分頁標題#e#
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
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. 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.
Customer Behavior / The Repeat Purchase Decision
Lu and Lin (2002) stated that just like the traditional market, enterprises need to build and maintain customer loyalty to attract new consumers in the marketplace. Meanwhile, nevertheless, the particular factors of the internet have changed the rules for marketing. The consumers’ retention is faced with great challenges for online enterprises today (Hoffman and Novak, 2000). The Wide Web World offers a unique market-space that grants enterprises, and their consumer can have multilateral communications as well as the likelihood of creating a one to one relationship between the seller and the buyer (Ghosh, 1998). Additionally, through the marketing channel, enterprises can recognize their consumers’ needs more precisely. Thus, increase consumers’ satisfaction and retention (Elofson and Robinson, 1998). According Kotler (1967) study the consumer-oriented market-space concept is no longer an illusion. Further more and more important, the Wide Web World offers an appropriate space in order to develop virtual communities, with strong relations between the provider and the user (Hagel III and Armstrong, 1997). Hagel III and Armstrong (1997) have expressed a view that enterprises having a successful virtual community can gain consumers loyalty and retain consumers easily.
另一方面,阿雷利和卡蒙指出,發生在購物的過程中,是同一個網站的關鍵階段,可能會影響一個人的年底的購物體驗。對于這個問題關注,完成的購物過程中可能比信息的數量和質量的選擇更發揮了至關重要的作用,在提供給客戶(魯賓斯坦,2002年)這方面。
On the other hand, Ariely and Carmon (2000) indicated that the extremely important part of the shopping experience happens at the end of the shopping process which is critical stage may affect one’s possibility of coming back to the same website. This issue is concerned that the completion side of the shopping process may play a crucial role than the information quality and the quantity of choice that is available to the customer (Reibstein, 2002). The retention just like the circumstances of traditional shopping, after a while, the consumers’ online behavior will become a routine. In addition, according to Alba and Hutchinson (1987), once the consumer usually shops at a particular website or location, the decision process will become habitual. Dholakia and Baggozi (2001) emphasize on that the decision to come back to the same website is the same as the decision to buy the same brand. Thus, the capability of the website and the purchase process are crucial issue.
Summary
Many works have been done focusing on online decision aids; however, little connection has been made to luxurious brands. With online shopping becoming more and more popular and luxury brands valuing this channel of sales increasingly, it is interesting to see to what extent online decision aids play its part during the purchasing process.