Direct Teacher: Professor Ng Reporter: Cindy Pineapple 1 Summarized from ：

Introduction(1/5)  This study examines whether creating a more professional online e-image can signal consumers about unobservable product or company quality, and whether this signal influences their willingness to transact with the company, and they are willing to pay for the company’s goods and services. 2

Introduction(2/5)  An e-image is the electronic image presented by a business or individual. Research suggests that the choice of an e- image is often consciously made to create a distinct online identity.  E-image is composed of a variety of factors, which for online auction businesses include identity (username), website appearance and information content, reputation rank from the reputation systems, and any reputation feedback. 3

Introduction(3/5)  The experiment involved establishing and running two online auction businesses for one year. All aspects of the businesses were kept identical except for the e-images of the two businesses. 4

Introduction(4/5)  One business was given a professional e- image by electing a professional sounding user identity and maintaining a high quality website that provided clear return and shipping policies and a professional looking listing style.  The second business’s e-image appeared to be a more casual business with a less than professional user identity and a much lower quality website that provided only limited product information, no shipping or return policies, and a simple listing design. 5

Introduction(5/5)  Actual sales of identical products were used to answer the following research questions:  (1) Does e-image affect willingness to transact with the online auction business?  (2) Does e-image affect prices received at online auctions?  (3) Are these e-image effects influenced by risks associated with different product types? 6

Information Economics  In most online auctions, the consumer is entirely dependent on the business for information related to the product, its quality, and its condition.  This information asymmetry makes it very difficult for consumers to assess product quality before purchase. 7

What is Signaling theory ?  Signaling theory states that in situations where there is information asymmetry a signal is an action of the business that credibly relays information about unobservable product (or company) quality to the consumer.  In environments with incomplete information, consumers must rely on signals provided by businesses to evaluate their ability to produce (and deliver) quality products. 8

Website Quality  The first stream has resulted in the development and testing of instruments to measure website quality.These instruments have been tested on a variety of selling and non-selling sites using experienced online shoppers, student web users, and web developers.  Other studies assessing consumer impressions of online auction provider sites found that the layout of information, the accuracy of standardized information, and website security influenced user impressions of website quality and their intention to bid. However, these studies provided no information on the importance of e-image quality to individual online auction businesses. 9

Theory and Hypotheses  This study is concerned with assessing the impact of choices made by online auction businesses with respect to their e-image on consumers’ willingness to transact and on price premiums—holding all other auction factors constant. 10

E-image  The e-image of two e-image factors examined are user name/identity and website quality attributes that can be controlled by the online auction business. 11

Willingness to Transact  Since e-image can signal consumers about unobservable product or company quality, exchange theory suggests that improving e-image will increase a consumer’s willingness to transact with the online businesses.  H1: There is a positive relationship between e-image and willingness to transact. 12

Price Premiums  Price premiums help compensate preferred businesses for reducing transaction risks. Increasing e-image quality can improve the information available for consumer decision making and help to remove uncertainty surrounding the transaction and consequently reduce perceived risk.  H2: There is a positive relationship between e-image and price premiums. 13

Product Risk(1/3)  The used products are believed to have higher transaction-specific risks because there is the increased possibility that the condition or functionality of the product being sold will not be captured completely in the product description. 14

Product Risk(2/3)  Perceptions of risk can influence online transactions in two ways:  First, prior research has found that increased perceptions of risk decrease consumers’ willingness to transact.  Second, perceptions of risk can increase consumers’ price sensitivity. Businesses that reduce transaction-specific risks may receive price premiums. 15

Product Risk(3/3)  H3a: The relationship between e-image and willingness to transact is stronger for high-risk products (e.g., used goods) than for low risk products (e.g., new goods).  H3b: The relationship between e- image and price premiums is stronger for high-risk products(e.g., used goods) than for low risk products(e.g., new goods). 16

Hypotheses 17 H1 H2 H3b H3a

Research Methods  This experiment controls for two specific factors of e-image: professionalism of user identity and website quality, specifically through the listing quality of information content controlled by the businesses. 18

SAMPLE 1  The eBay username for the positive e- image business was selected as “CollegiateSales”.  To create a high quality online auction listing for the positive e-image business : Actual product descriptions, terms of sale, and customer service policies were taken from several of the better listings identified during the sorting process. 19

Positive E-Image Online Auction Listing 20

SAMPLE 2  The eBay business ID for the negative e-image seller was “NotAPro2003.” It was chosen to reflect the type of less professional name chosen by many sellers on eBay.  The negative e-image listing included minimal product information, no sales or service polices, and no aesthetic features. 21

Negative E-Image Online Auction Listing 22

Experiment Design(1/3)  The empirical study utilized data obtained from actual transactions conducted at the eBay auction site over the course of one year.  The CollegiateSales online auction business sold items using the positive e- image listing style.  The NotAPro2003 online auction business sold items using the negative e-image listing style. 23

Experiment Design(2/3)  Both auction businesses were started on the same day at eBay.  All attributes of the businesses and of the auctions were kept identical over the course of the experiment except for the e-image. 24

Experiment Design(3/3)  Starting prices for items sold by the two businesses were identical and were set based on the current market for the item.  At the conclusion of each auction the closing price, number of bids received, number of bidders, timing of the first bid, and reputation score were recorded. 25

Results(1/4)  Evaluation of the individual dependent variables show that e-image had a significant effect on the timing of the first bid with positive e-image businesses receiving their first bid 1.26 days sooner than negative e-image businesses (on average). 26

Results(2/4)  The fact that the positive e-image business receive first bids significantly sooner than the negative e-image business (when starting prices for both businesses are identical) and more bidders bid at the positive e-image auctions clearly indicate that consumers have an increased willingness to transact with businesses with positive e-images, supporting hypothesis 1. 27

Results(3/4)  This produced an average price premium of percent, supporting hypothesis 2.  This indicates that consumers prefer purchasing from positive e-image businesses regardless of the perceived product risk, causing us to reject hypothesis 3a. 28

Results(4/4)  This indicates that positive e-image businesses do receive significantly more when selling their products at online auctions but these price premiums are highly dependent on product risk, supporting hypothesis 3b. 29

Discussion and Conclusions(1/3)  The goal of this study is to better understand the impact e-image, specifically business user name choice and listing quality, has on willingness to transact and price premiums for online auction retailers.  Our hypotheses are largely supported and suggest that e-image has a significant impact in the online auction domain. 30

Discussion and Conclusions(2/3)  A second finding that product risk (e.g., new versus used products) does not moderate the relationship between e- image and willingness to transact demonstrates that consumers have a clear preference for purchasing from positive e-image businesses even when the product risk was very low (a new DVD or new USB drive). 31

Discussion and Conclusions(3/3)  Although buyers prefer transacting with the positive e-image business, they are not willing to pay significantly more if the risk associated with the product is very low.  Consumers willing to assume greater risks still bid on higher risk products but expect a low price in order to compensate for those risks. 32

Implications and Future Research(1/3)  A primary contribution of this research is that it demonstrates the ability to use eBay as an experimental laboratory for testing hypotheses about purchasing behavior online.  This research also contributes to our understanding of the e-image aspects of website quality and identity selection. 33

Implications and Future Research(2/3)  The finding of this study suggests that it is important for online auction businesses to spend the time and resources necessary to present themselves and their products using positive e-images. 34

Implications and Future Research(3/3)  The experimental methodology applied in this paper could be extended to other e-marketplaces (e.g., Amazon’s zShops) to examine the relative importance of e- image on website types and determine whether websites with higher perceived quality can charge more than sites with lower quality. 35

Whether the paper is related to MIS field?  It’s related to E-commerce. it can be extrapolated to online stores. Positive image. Example: Apple’s website.Apple’s website  It’s also related with CRM system. They considerate about service polices and return policies. It’s an infrastructure of customer-oriented. So business should establish their CRM system more complete. 36

The contributions in MIS field  MIS should consider information transparency. Clear information make people trusted more. Also can reduce the conflict between businesses and customers.  Organizations must establish a positive image on e-commerce. The study found positive image made price premiums and more attractive. 37

The End. Thanks for listening. 38