An Implementation of a New Type of Online Auction

In recent years, there has been an increased interest in the types of online auction. Yet many auctions with fixed-end times are experiencing “sniping” or submission of bids in the final minute of an auction. Late bidding deprives rivals of the ability of seeing one’s bid and undercutting it. Late bidding facilitates colludes or independent pricing well above that predicated by auction mechanism. This article aims to propose and implement a new type of online auction called Least and Unique Price (LUP). In the LUP auction, the winner will be the bidder who submits the least and unique price. Moreover, late bidding and specific closing time also be overcome by the LUP auction. In addition, this article presents the practical implementation of the proposed auction. In order to evaluate the proposed auction a comparative analysis of different auction types and the proposed one has been done.

Can Web Seals Work Wonders for Small E-Vendors in the Online Trading Environment? A Theoretical Approach

Trust is a major issue in e-markets. It is an even more prominent issue when online shoppers trade with small, less-established e-vendors. Empirical studies on Web seals show that small e-vendors could promote consumers’ trust and increase Web sales by displaying Web seals of approval. This article takes a theoretical approach to examine online trading when seals are used in e-markets. We establish an online shopper’s decision-making model to reveal the online shopper’s decision-making criteria. Criteria include when to trade with a well-established e-vendor and when to trade with a small, less-established e-vendor, with or without a Web seal. Based on our analysis of the research results, we reveal the price effect, the seal effect, the reputation effect, and their impact on a shopper’s decision-making process. Meanwhile, a social welfare analysis is conducted to further demonstrate the positive impact of Web seals on small, less-established e-vendors.

The Driving Forces of Customer Loyalty

In this study we examine the driving forces of customer loyalty in the broadband market in Hong Kong. We developed and empirically tested a model to examine the antecedents of customer loyalty towards Internet service providers (ISPs) in Hong Kong. Structural equation modeling (SEM) was used to evaluate the proposed model. A total of 737 valid returns were obtained through a questionnaire survey. The results show that customer satisfaction, switching cost, and price perception are antecedents that lead directly to customer loyalty, with customer satisfaction exerting the greatest influence. Although we found that service quality significantly influences customer satisfaction, which in turn leads to customer loyalty, we did not find a direct relationship between service quality and customer loyalty. Our results also reveal that corporate image is not related to customer loyalty. Our empirical investigation suggests that investing huge resources in building corporate image can indeed be a risky strategy for ISPs.

E-Consumer Behaviour

Shopping online has emerged as one of the most popular Internet applications, providing a plethora of purchasing opportunities for consumers and sales challenges for retailers. The aim of this paper is to shed further light on the past and present status of the e-consumer phenomenon, by looking into online shopping behaviour and by examining the major reasons for being motivated or being de-motivated from buying online, focusing on the trust element. Building on that analysis, the possible future status of e-consumer behaviour is presented via an examination of ubiquitous retailing, which denotes the next stage of that retail revolution.

Exploring Decision Rules for Sellers in Business-to-Consumer (B2C) Internet Auctions

The recent growth of business-to-consumer (B2C) Internet auctions challenges researchers to develop empirically-sound explanations of critical factors that allow merchants to earn price premiums in these auctions. The absence of a comprehensive model of Internet auctions leads us to conduct an exploratory study to elucidate and rank critical factors that lead to price premiums in Internet auctions. We employ Classification and Regression Trees (CART), a decision-tree induction technique, to analyze data collected in a field study of eBay auctions. Our analysis yields decision trees that visually depict noteworthy factors that may lead to price premiums and that indicate the relative importance of these factors. We find shipping cost, reputation, initial bid price, and auction ending time as the factors most predictive of price premiums in B2C Internet auctions.

Nibbling, Sniping, and the Role of Uncertainty in Second-Price, Hard-Close Internet Auctions

Internet auctions have gained widespread appeal as an efficient and effective means of buying and selling goods and services. This study examines buyer behavior on eBay, one of the most well-known Internet auction Web sites. eBay’s auction format is similar to that of a second-price, hard-close auction, which gives a rational participant an incentive to submit a bid that is equal to his or her maximum willingness to pay. But while traditional second-price, hard-close auctions assume that participants have reliable information about their own and other bidders’ reservation prices, eBay participants usually do not. This raises the possibility that eBay participants may adapt their bidding strategies and not actually bid their reservation prices because of increased uncertainty. In this article, we empirically examine the bidding patterns of online auction participants and compare our findings to the behavior of bidders in more conventional auction settings.

E-Business Decision Making by Agreement

Gathering customer data over the Internet is largely limited to collecting the responses to a set of easily answerable questions, such as Yes/No questions and Likert scale questions. These data are then analyzed to identify customer trends or other items of interest to management. The data can be useful, but key to their usage is the application of suitable mathematical tools. Traditionally little more than standard statistics has been used in the analysis of ordinal, or category, data. This can be inaccurate and in some cases, misleading. This paper introduces measures of agreement and dissent to the field of eBusiness analysis and shows how ordinal data can be analyzed in more meaningful ways.

Product Choice Strategy for Online Retailers

An important strategic issue for managers planning to set up online stores is the choice of product categories to retail. While the “right” product category would depend on a number of factors, here we focus on the following two factors: compatibility of the product with the online channel, and the competition between the traditional brick and mortar channel and the online channel. This is to acknowledge two well-known facts: Certain products are more suitable for selling through the Web than through other channels; and an online retailer competes with not only other online retailers, but also traditional brick and mortar retailers. To determine the right product category, we develop a game theoretical model that allows for competition between the retailers. We study both Stackelberg and Bertrand competition models, as these two models capture the essence of different types of competition on the Web. Based on our results, we propose that, under all types of competition, the optimal product is one that is only moderately compatible with the Internet.

Exploratory Study on the Perceived Importance of Various Features of the Internet Service as Influenced by the Perceived Necessity of the Internet and the Size and Type of Small Businesses

In the new era of e-commerce, small businesses have emerged as the driving force because these firms comprise a significant proportion of economic activity. The spending of small businesses on IT activities continues to grow as they rely more and more on the Internet to be competitive. All these indicate a potential lucrative market for Internet Service Providers (ISPs) to serve small businesses. But how to do so? This study attempts to identify Internet service features that are important to small businesses as a way for the ISPs to exploit this potential lucrative market. It explored how various features of the Internet service were associated with the “perceived necessity” of the internet and the “size” and “type” of small businesses. Understanding these associations might help the ISPs better package their service and more successfully serve their small business clients.

The Measurement of Electronic Service Quality

Several measurement scales have been designed by both practitioners and researchers to evaluate perceptions of electronic service Quality. This chapter tests three of the main academically developed scales: Sitequal (Yoo & Donthu, 2001), Webqual 4 (Barnes & Vidgen, 2003) and EtailQ (Wolfinbarger & Gilly, 2003) and compares them against the scale ensuing from our research: NetQual (Bressolles, 2006). Based on 204 evaluations of consumers that participated in a laboratory experiment involving two Canadian Websites in travel and online insurance, NetQual best fits the data and offers the highest explanatory power. Then the impact of nature of task and success or failure to complete the task on the evaluation process of electronic service quality and attitude toward the site is examined and discussed on over 700 respondents that navigated on six different Websites.