242 Dawn G. Gregg and Steven Walczak E-commerce AuctionRESEARCH Agents

E-commerce Agents and Abstract Online- are one of the most suc- Online-auction Dynamics cessful types of electronic markets. They bring together buyers and sellers on a massive scale. However, using an electronic medium DAWN G. GREGG AND STEVEN WALCZAK for conducting auctions has fundamental differences from traditional English-style auctions. One difference is the availability of agents that can facilitate many aspects of online-auction participation. The addition of software agents into online- auctions is already having an impact on the dynamics of online-auctions. This study examines existing agent technologies with regard to their effect on online-auctions. In addition, future directions for research related to online-auction agents and the possible benefits of these agents are also discussed. INTRODUCTION sellers face greater competition Keywords: e-commerce, online auctions, from other sellers in order to effec- intelligent agents The Web has dramatically changed tively reach the potential buyers how people buy and sell goods. In (Bichler et al. 2002; Hahn 2001). recent years new types of electronic Buyers and sellers would both ben- marketplaces have been created to efit if the process of determining leverage information technology to appropriate prices, where to partici- create more efficient markets (Bakos pate, and how best to bid could be 1998). Web usage and commerce automated. Software agents provide is increasing dramatically, with an a solution to the time and infor- estimated $6.8 trillion in online mation demands of online-auction retail sales by the year 2003 participants (Ye et al. 2001). (Forrester Research 2001). One of Broadly defined, a software agent is the most successful types of elec- a program that acts on behalf of a tronic marketplaces has been the user to find and filter information, DOI: 10.1080/1019678032000092237 online auction. Online auctions automate complex tasks, monitor

Downloaded By: [Schmelich, Volker] At: 15:05 16 March 2010 allow businesses and consumers to events and procedures or negotiate easily buy or sell anything to anyone for services (Maes 1994). Research anywhere in the world. is needed to examine the impact of One real-world example of a suc- software agents that can automatically cessful online auction is eBay.com. collect large volumes of auction Authors eBay is the largest online-auction data and make recommendations Dawn G. Gregg site currently operating on the Web based on that data. ([email protected]) is an and has nearly 7 million items avail- Currently online-auction sites Assistant Professor at the University of able for sale on any given day. The provide software agents that can be Colorado, Denver. Her current research success of online-auctions has given used by both buyers and sellers (e.g. focus is on the use of artificial buyers access to greater product search agents and proxy intelligent agents to organize and diversity with potentially lower agents). In this article, the impact maintain Web-based content so that it 2003 Electronic Markets prices. Conducting business online of Web agents operating in online can be better used to meet business ᮊ reduces transaction costs by elimi- B2C and C2C auctions is examined needs. nating the time and place aspects and likely agent developments from Steven Walczak of offline markets (Bichler et al. current and future research are ([email protected]) is an Copyright Associate Professor of Information Volume 13 (3): 242–250. www.electronicmarkets.org 2002). It has also allowed sellers to explored. The remainder of this Systems in the Business School at the reach a greater number of potential paper is organized as follows: the University of Colorado at Denver. His buyers. However, buyers must next section provides background current research interests are in applied incur higher search costs to locate information pertaining to B2C and artificial intelligence systems including desired products within larger and C2C online auctions and agents agents and neural networks and larger numbers of products and operating in the B2C and C2C knowledge management systems. 242 Electronic Markets Vol. 13 No 3 243

online-auction domains, the third section analyses the (Matsubara 2001; Teich, Wallenius, Wallenius and effects of auction agents on online-auction dynamics, Zaitsev 1999). Other auction sites more closely resemble the penultimate section discusses the effect of future traditional auctions and attempt to limit last minute agent research and development on online B2C and bidding by providing a ‘Going, Going, Gone’ period. C2C auctions. On these sites (e.g. Amazon.com and Ubid.com) the auction closing time is automatically extended by 10 minutes if a bid is received within 10 minutes of the BACKGROUND current closing time. One of the inherent risks in participating in online Online-auctions are an increasingly popular mechanism auctions is the virtual anonymity of the transactions. In for exchanging goods and services via the Web (Ye et al. order to foster trust between unknown buyers and 2001). An online auction is a Web application that acts sellers, most auction sites provide ratings that reflect as an intermediary between sellers and buyers. In both the number of online auction transactions the online auctions, resource allocation and prices are participant has completed and amount of positive and determined with an explicit set of rules based on bids negative feedback the participant has received. It from market participants (Bichler 2001; Hahn 2001). has been suggested that these reputation systems help Online auctions can be categorized into three main to foster better behaviour in both buyers and sellers dimensions: business-to-consumer (B2C); consumer- because they seek to enhance their online-auction to-consumer (C2C); and business-to-business (B2B). reputation (Resnick, et al. 2000). While all three types of online auctions can use similar Conducting trade on the Web enables vendors to auction mechanisms, the purchasing decision making reach more consumers and at significantly lower cost processes of consumers and businesses differ substan- (Deveaux et al. 2001). The use of the Web to establish tially. The focus of this paper is on how software virtual/online-auctions permits auctioneers to establish agents can benefit individual consumers participating a necessary and critical mass of bidders as individuals in B2C or C2C online auctions. may participate from any location around the world B2C or C2C online-auctions allow either single (Guttman et al. 1999). This will in turn optimize the items or multiple items to be auctioned at one time. auction outcomes for the seller. A successful online Singles item auctions work very similarly to traditional auction shows positive network effects; that is, the English-style auctions. Bidders bid against each other more traffic it has, the more desirable it is to new and the winning bidder is the one that bids the highest participants (Feldman 2000). price first. Multiple item auctions offer multiple identical In May 2001, research from Nielsen/NetRatings items for sale and bidders bid for the price and quantity and Harris Interactive, indicated US auction websites they are interested in purchasing. The price winning generated $556 million in revenue. The revenue share bidders pay depends on the type of multiple-item-auction for top US B2C & C2C auction sites is shown in being conducted. In ‘Yankee auctions’ each winning Table 1. EBay, as the first-mover in the online-auction Downloaded By: [Schmelich, Volker] At: 15:05 16 March 2010 bidder pays the final amount they bid for the item(s). arena, has gained an advantage over other online- In ‘Dutch or Vickery auctions’ all winning bidders pay auction sites. In addition to being a first-mover, the amount bid by the lowest successful winning bidder EBay’s advantage also comes from developing a busi- (Bapna et al. 2001a). ness strategy that integrates the asynchronous and Most online auctions are started with a low mini- global reach of the , low overhead of a virtual mum bid price which is used to attract Web traffic marketplace, vertical integration of support markets, (e.g., during a 1-week period in February 2002, 13.2% and a focus on customer satisfaction that promotes of 7,263 auctions at eBay had a minimum bid price of customer return (Kambil and Van Heck 2002). It has one dollar or less). Some online auctions also use a considerable market power, and the greatest revenue reserve price to specify the lowest price for which a share with 64.3% of all online-auction revenue. In seller is willing to sell an item. In order to win the addition, its higher traffic has resulted in a conversion auction, a bidder must meet or exceed the reserve price rate of 22.5%, more than double that of its nearest and have the highest bid (Teich, Wallenius, Wallenius competitor (Anonymous 2001). and Zaitsev 1999). In addition, all online auctions Previous e-commerce agent research has utilized the have a bid increment that defines the minimum consumer buyer behaviour model (Guttman et al. amount that can be bid next (Anonymous 2002). 1999), in which consumers are modelled as decision B2C and C2C auction durations typically range makers. Online-auction buyers must determine what from a few days to three weeks (Hahn 2001). Some they want to buy, from whom they want to buy, and auction sites use an ascending bid protocol with a fixed how much they are willing to spend. Unfortunately, end time (e.g. eBay.com and Yahoo.com). At these the easy access to auctions (via the Web) also increases 243 sites the practice of last minute bidding is prevalent the quantity of uninformed consumers (little auction 244 Dawn G. Gregg and Steven Walczak E-commerce Auction Agents

Table 1. Top US auction sites, ranked by revenue share

Auction Site Number of items for Revenue share† (May 2001) Conversion rate‡ (May 2001) sale (1 day Feb 2002) (%) (%)

EBay.com 6,957,080 64.3 22.5 UBid.com 1,133,661 14.7 11.0 Egghead.com* (Onsale.com) * 4.0 8.0 Yahoo! Auctions 455,570 2.4 4.4 Amazon Auctions 936,231 2.0 6.5

* Since May 2001 Egghead.com contracted out website management to Amazon.com and no longer hosts independent auctions. † Revenue share is the percentage of the online auction market space captured by the corresponding site, where share is determined by auction close dollars. ‡ Conversion rate is the percentage of auction items listed that result in a sale (item receives a bid and bidder pays for the item). Source: eMarketer, online at: http://www.emarketer.com/estatnews/estats/ecommerce_b2c/20010706_nn_harris.html, July 6, 2001.

experience). These uninformed consumers are poor Information retrieval agents auction decision makers and have been found to pay an average of 18.5 percent more than experienced bid- There are currently several different types of services ders in one research study (Bapna et al. 2001b). The offered at the major online-auction sites. The most use of agents to search for products and conduct auto- basic service provided by the auction sites is the search matic bidding helps to reduce time costs and certain service. The search service is so common that it is dif- other types of frictional costs (Ye et al. 2001). They ficult to classify it as an agent-based service at all. can also serve to level the playing field between experi- However, it is essential to the operation of online- enced and newer auction participants by providing auction sites. For example, on a single day eBay had information that can educate inexperienced buyers and nearly 7 million auctions running at one time grouped sellers. into 9,522 different product categories. There is little differentiation between the information retrieval services currently provided by the different auction sites, how- CURRENT ONLINE AUCTION AGENTS ever, there is room for improvement to these services that would substantially improve the efficiency of Online auctions are not just electronic markets that searches on different auction sites. Such improvements

Downloaded By: [Schmelich, Volker] At: 15:05 16 March 2010 connect buyers and sellers; they also are services that would include the ability to exclude terms, choosing can be used to improve the purchasing/sales efficiency inclusive or any search types, and specifying terms from and decision making of auction participants (Kambil particular fields such as location. and Van Heck 2002). Much literature has been written Information retrieval agents can also be used to on the use of ‘comparison-shopping’ agents to auto- improve the decision making of auction participants mate the search for price and product information by enabling them to determine appropriate prices across multiple online merchants simultaneously (Clark (valuations) for products. Four of the seven online-auction 2000; Crowston 1996; Doorenbos et al. 1997). sites provide the ability to search recently closed auctions. Online auctions provide potential buyers and sellers This feature enables online-auction users to determine with a unique ability to use similar software agents to what recent closing prices have been on items similar improve their purchase and sales outcomes. This section to ones they are considering purchasing (or selling). If examines the availability and use of agents on several utilized, this capability could help to level the playing B2C and C2C online-auction sites to gain a better field between new and more experienced auction understanding of how agents impact online-auction participants and lessen the likelihood that bidders will processes. pay more for an item than its value (known as the The first part of this study involved gathering data ‘winner’s curse’) (Mehta and Lee 1999). on auction site activity and the availability of different software agents at various online-auction sites. This data was used to determine what agent-based services Bidding agents are currently being provided at different online-auction sites. The various types of agent-based services are Two different types of bidding agents are currently discussed in the remainder of this section. being used on most online-auction sites. The first type 244 Electronic Markets Vol. 13 No 3 245

of bidding agent is a ‘proxy-bidding agent’. Proxy bid- Watch agents ding means that a bidder can submit a maximum bid amount they are willing to pay and the proxy-bidding Other agents are used to keep auction participants agent will bid in their absence. Proxy bidding agents aware of what is going on in auctions in which they are place their bids based on the previous high bid amount, interested. Several auction sites provide “Watch the minimum bid increment and on any reserve price. agents” which track auctions the participant might be In order to assess the impact of proxy bidding agents, interested in but at which they have not yet decided the ratio of proxy bids placed to the total number of to place a bid. The three auction sites eBay.com, bids placed was examined. To do so, in-depth data from Ubid.com and Cityauction.com, provide auction noti- the eBay active online-auction market was collected using fication agents that will search new auction postings an information retrieval agent. The information retrieval and notify potential buyers when specific items they are agent gathered publicly available data on individual interested in are posted on their online auctions. These auctions including the item description and the bid sites also use another type of watch agent to notify history. The data was collected for all online-auctions bidders if they have been outbid or if they have won ending during a single week (12 February 2002 to 18 an auction. Yahoo.com extends this practice to allow February 2002) for 7 pre-specified product categories. notification of auction participants if an auction they The target categories were: Intel Celeron Desktop are participating in has closed or was cancelled, if a Computers, Fax Machines, DVD Drives, US Airmail previously losing bid was reinstated due to another Stamps, New Age Compact Discs, Business Database bidders bid being retracted or if a feedback rating was Software and Teeny Beanie Babies. Information on a posted for the participant. The ability to watch inter- total of 7,290 auction items gathered from the eBay esting auctions or to notify auction participants about auction site is summarized in Table 2. important auction events can serve to stimulate more A total of 21,910 bids were placed on 4,262 differ- interest in the auction than would be possible without ent items across the seven product categories. Proxy the use of such agents. bidding agents placed 34.3 % of the bids recorded on the 4,262 items. This indicates that proxy agent bidding plays a dramatic role in the outcome of most Seller agents online-auctions. The data also indicates that the auc- tion categories with a higher percentage of items being Software agents can benefit both sellers and buyers. For sold tend to have a higher percentage of bidding done example, Amazon.com, Ubid.com and AuctionAddict. by proxy agents. For example, the data in Table 3 com use agents to track bidding at their auctions. show that 66.07% of DVD drives that were placed on These agents automatically extend an online-auction if auction at eBay were sold and that 55.22% of the bids a bid occurs during some predetermined interval prior placed on these items were placed by proxy bidding to the auction closing time (10 minutes for Amazon agents. Conversely, only 30.66% of the Teeny Beanie and Ubid, 24 hours for AuctionAddict). This more

Downloaded By: [Schmelich, Volker] At: 15:05 16 March 2010 Babies that were placed on auction at eBay were sold accurately simulates traditional English-style auctions and proxy-bidding agents placed only 14.66% of the that are kept open during active bidding. In addition, bids placed in this product category. However, the extending auctions can reduce ‘slamming’. Slamming correlation is weak and further research will be neces- is the practice of placing a last second bid so that other sary to determine if this relationship exists across other bidders will not have the opportunity to place another categories. bid before the auction closes. Two online-auction

Table 2. eBay proxy bidding data summary

Number of auctions % items receiving Number of bids Percentage of bids closed bids placed placed by proxy

Celeron computer 715 73.15 4492 34.17 Fax machine 792 69.44 3223 25.38 DVD drive 1176 66.07 6302 55.22 US airmail stamp 1098 63.02 2675 23.03 New Age CD 1874 62.01 3390 21.27 Database program 425 44.00 1105 21.90 Teeny Beanie Baby 1210 30.66 723 14.66 Total 7290 58.46 21910 34.31 245 246 Dawn G. Gregg and Steven Walczak E-commerce Auction Agents

Table 3. Prevalence of last minute bidding at eBay

Number of auctions Percentage of items Percentage of items receiving bids closed receiving bids bid on in the last 10 minutes

Celeron computer 715 73.15 96.94 Fax machine 792 69.44 73.45 DVD drive 1176 66.07 87.00 US airmail stamp 1098 63.02 50.00 New Age CD 1874 62.01 30.38 Database program 425 44.00 89.30 Teeny Beanie Baby 1210 30.66 35.58 Total 7290 58.46 60.65

characteristics enable slamming. First, the hard auction ability for sellers to ‘blacklist’ specific bidders (e.g. close times make it difficult to respond fast enough to eBay and Yahoo in Table 4). Under this system an a late bid, and second it is more difficult to judge the agent watches the seller’s auctions and automatically interest and availability of other bidders in the online bounces bidders that appear on the sellers blacklist. environment. Table 3 shows how prevalent the practice While this system does not yet allow sellers to block all of slamming is on eBay (an auction site that does not bidders with a specific feedback profile, it does allow extend its auctions if there are last minute bids). The them some mechanism for blocking undesirable bidders. data was collected for all eBay auctions ending during Online auction sites currently provide differing a single week (12 February 2002 to 18 February 2002) agent-based services. The various services discussed for 7 pre-specified product categories. The data indicates above are summarized in Table 4 for seven different that over 60% of auctions that receive any bids, receive B2C and C2C online-auction sites. bids within the last 10 minutes of the auction. The data also indicates that auction categories that have a greater percentage of their items receive bids; also tend Third-party agents to have a higher incidence of slamming. In the Celeron Computer category, 96.94% of the auctions that received In addition to agents provided by specific online-auction bids, received at least one bid in the last 10 minutes of sites, third-party agents have been developed to provide the auction! information retrieval and watch services. Agents found A second type of agent that is beneficial to auction at ‘BidXS.com’ and ‘McFind.com’ may be used to sellers is one that allows them to control the types of compare offerings across multiple online-auction sites.

Downloaded By: [Schmelich, Volker] At: 15:05 16 March 2010 bidders they will allow to bid at their auctions. For McFind.com allows simultaneous category browsing example, some online-auction bidders demonstrate a or searching of both Amazon.com and Yahoo.com. pattern of unacceptable bidding or fail to follow through BidXS.com provides a more complete buyer’s agent on auction purchases. Some auction sites provide the that allows keyword searches, searches by category and

Table 4. Agent services currently provided by selected online-auction sites

Auction site Search Search Activity Proxy Watch Bidder Auction Notification** Auction closed manager bid blacklist agent* extension

EBay.com yes yes yes yes yes yes yes ob, win, cls – Ubid.com yes – yes yes yes – yes ob, win 10 min Amazon.com yes – yes yes – – – ob, win 10 min Yahoo.com yes yes yes yes yes yes – ob, win, can, no bids cls, resb, rat Auctionaddict.com yes yes yes yes – – – ob, win 24 hrs Cityauction.com yes yes yes yes yes – yes ob, win – Intershopzone.com yes – yes yes yes – – ob, win –

* An auction agent will wait for a specific item to be listed & notify buyer. ** outbid (ob), win, cancellation (can), auction close (cls), bid resubmit (resb), rating posting (rat). 246 Electronic Markets Vol. 13 No 3 247

searches by price. In addition, it can simultaneously all major auction sites provide only rudimentary search conduct searches on 118 different auction sites. services (Table 4). The search capabilities of all online- BidXS provides other agent-based services to auction auction sites could be improved substantially. Often buyers. BidXS has partnered with StrongNumbers to auction searches retrieve hundreds of products – many make past price trends available for online-auction of which an auction participant is not interested in. items. The process for obtaining past-price histories is Improved search agents could allow participants to simpler on BidXS than that provided by the individual check the products they are and are not interested in auction sites examined. On BidXS, users need only and then a more accurate search could be constructed click on a price tag icon that appears on the bottom of automatically – greatly improving the efficiency of auction every search results page and the recent price history searches. for that item is displayed. This allows potential buyers When evaluating past auctions, the maximum, mini- (and sellers) to determine what other people paid for mum and average selling price for items could also be the same item at previous auctions. calculated automatically. In addition, the starting BidXS also provides an auction agent that has the prices of items that did not sell could also be tabulated. ability to look at multiple auction sites to determine This would provide valuable information to aid auction when a desired item comes up for auction. The agent decision-making. For example, assume a consumer is can then alert participants by email when it does. This interested in purchasing a digital camera at auction and type of agent is currently only provided by .com, finds a camera with a starting price of $780 plus a $20 Ubid.com and Cityauction.com. The advantage of shipping fee. If an improved information retrieval third-party auction agents is that they allow users to agent indicates that similarly featured digital cameras locate items and compare prices and terms across multiple have closed at prices as low as $550, the consumer would online-auction sites. know that the seller has set too high of a price. Similarly One hurdle to developing and implementing more sellers can use auction history information to determine sophisticated third-party auction agents is that some optimal reserve pricing to maximize the opportunity auction sites have placed restrictions on the use of for sale and still achieve the desired profit. agents to gather information on their websites. For Auction shopping software agents could also example, both eBay.com and Amazon.com have agent access multiple online-auction sites to determine if exclusion policies. Anybody interested in developing a desired item is up for auction (e.g BidXS and auction agents for use on these sites must get written StrongNumbers.com). Combining the auction-shopping permission before using the agents to gather any data. agent with an information retrieval agent would allow the retrieval of additional auction data like the time left in the auction until it closes and relative bidder activ- FUTURE DIRECTIONS FOR AUCTION AGENTS ity. A buyer would then be able to choose from among multiple auctions at multiple sites and evaluate which For online auctions to remain competitive, they must auction would most likely result in a winning bid

Downloaded By: [Schmelich, Volker] At: 15:05 16 March 2010 continue to improve the services they provide. Online- within the buyer’s budget. Another addition to the auction sites that provide additional services to end-users auction shopping agent would be to retrieve the online and allow them to increase their efficiency and decision- retail price from the manufacturer. This information making are the ones that will be the most successful in would allow the consumer to know if they should drop the future (Kambil and Van Heck 2002). In this section, out of an auction due to uninformed bidders raising directions for further improvements in agent technology the price above standard retail. and capabilities are explored and the corresponding effect on online-auction dynamics is inferred. Advanced bidding agents

Advanced information retrieval agents A further extension of the auction shopping agent is to enable consumers to engage in simultaneous auctions Information retrieval agents have been developed for for the same item on multiple online-auction sites. other domains, but are still in their infancy for the Currently, bidding agents work on a single site for a online-auction domain. The purpose of information single item. Building agents that can bid for the same retrieval agents is to make the seller or consumer more item on multiple simultaneous auctions is significantly informed about the auction process and also the pricing more complex (Greenwald and Stone 2001), since the of goods. Agents would automatically retrieve bidding consumer may desire to win only a single item auction. and auction close information. With detailed information Benyoucef et al. (2001) have demonstrated a model for regarding the historical performance of specific auction negotiating for multiple items from multiple retailers items, buyers and sellers will be better informed regarding in the B2C marketplace. Modifications to this B2C 247 an optimal price and even a bidding strategy. Currently, negotiation model are required for efficient handling 248 Dawn G. Gregg and Steven Walczak E-commerce Auction Agents

of a single item bid on multiple online-auction sites. e-commerce sites (e.g., Amazon.com) to suggest retail The agent would monitor selected auction sites and (B2C) items for purchase based on the shopper’s current maintain active bids so that only one bid at a time was and past purchases or inquiries. Preference-learning current and would be the minimum cost across all agents should be incorporated into auction decision auctions. support systems (Hess et al. 2000), and would advance Another problem with current online-auctions is the state of auction watch agents. These preference- that buyers and sellers are matched with regard to price based watch agents would monitor auction activity of a alone (Teich, Wallenius, and Wallenius 1999; Teich user and may additionally monitor, at the user’s option, et al. 2001). A buyer or seller may have other criteria. other activities such as web-browsing to gain a better Agents are not limited to only bidding or looking perspective on the interests of the user. The watch for items with regard to price, but instead may be agents would then be able to notify a user whenever programmed with multiple search/bidding criteria. any item of potential interest comes up for auction, Criteria of interest to a buyer in addition to price may not just those items explicitly specified by the user. include: seller rating, cost of shipping, willingness to ship outside of the local area of the seller, shipping method, time left in the auction, quality or evaluation of Other advanced agents the item. All of these pieces of information are available at most online-auction sites. The new multi-criteria Agents may also be used to assist auction sites. A tech- bidding agent would then maximize the buyer’s return nique that is sometimes employed to raise the interest with regard to all specified criteria, perhaps paying a and current bid level is the use of a shill who makes little more to get an item sooner or from a seller with bids on merchandise to bid up the price and keep the a better reputation (rating). action alive, but with the foreknowledge that the shill Optimizing return for buyers and sellers is the goal will not have to purchase the auctioned item (Reynolds of auction agents. All the auction sites evaluated in 1996a). At auction houses, bidders may watch for Table 4 permit proxy or automatic bidding through items that are set aside after close to indicate the use of simple single-item bidding agents. Current bidding a shill, but online a seller could employ one or more agents can artificially increase the current bid for an shills without any visible signs. To minimize this practice, item by competing against each other. Future bidding agents can be used to determine if a seller posts an agents could incorporate more sophisticated bidding item for auction that is the same as one they recently strategies to minimize costs and maximize returns. sold (e.g. in the last two-weeks). If the seller repeats this Deveaux et al. (2001) examined three different behav- pattern this may be an indication to the online-auction iours (conceding, boulware, and imitative) in bidding site that the seller is employing a shill. agents and found that different behaviours produce Finally, an ongoing challenge for Web agents is their optimal results under different situations, implying the ability to communicate with other agents, systems, and need for an adaptive approach. Elements needed to users (Devaux et al. 2001; Hess et al. 2000). If multi-

Downloaded By: [Schmelich, Volker] At: 15:05 16 March 2010 develop a bidding strategy for an agent are the rules of auction bidding agents are employed and if an item has the auction, the valuation of the item by the bidder, M agents and individuals bidding for a specific item, and an estimate of other bidder’s strategies and but there are N of these items for sale on various valuations (Reynolds 1996b). Embedding machine auction sites (where M ≤ N), then from an economic learning into advanced bidding agents would allow the perspective supply exceeds demand and all agents and agents to modify bidding strategies and valuations on individuals should be able to obtain the item. Agents future auctions based on the results of current and past that detect only minimal bidding activity on a group of auctions. Other re-estimates of the current valuation the same item across multiple online-auction sites and consequently the maximum bid may be performed should then open a dialogue with the other agents and if the identity of another bidder (from their email or individual users to negotiate an equitable price and allow account name) indicates an individual with special all of the M agents and individual bidders to acquire knowledge of the object, such as an art critic bidding one of the items for the negotiated price. Unfortunately, on a particular piece of art (Reynolds 1996a). although several agent communication protocols have been developed (e.g., KQML (Finin et al. 1997)) they are not used and consequently agents developed under Advanced watch agents different platforms cannot communicate with each other. Developing inter-agent communication is imperative Watch agents notify a user when a particular item to future agent technology development. comes up for auction at an online-auction site. Current Communication between agents and users is the watch agents (Table 4) are limited to ‘watching’ for other aspect of the agent communication problem. specific items detailed by the user. However, prefer- Natural language processing and production can be ence grouping agents are already employed at various embedded within agents to enable users to specify 248 Electronic Markets Vol. 13 No 3 249

search/watch criteria and bidding strategies using Anonymous (2002) ‘EBay Help Basics’, online at: http:// natural language. The development of better natural pages.ebay.com/help/basics/ [accessed 5 February 2002]. language parsing algorithms will facilitate the use of Bakos, Y. (1998) ‘The Emerging Role of Electronic auction agents by all users, regardless of background. Marketplaces on the Web’, Communications of the ACM 41(9), September, 35–42. Bapna, R., Goes, P. and Gupta, A. (2001a) ‘Insights and SUMMARY Analyses of Online Auctions’, Communications of the ACM 44(11), November, 42–50. The software agents already in use on auction websites Bapna, R., Goes, P. and Gupta, A. (2001b) ‘Comparative have the potential to alter dramatically the dynamics of Analysis of Multi-item Online Auctions: Evidence from online-auctions. For example, proxy bidding agents the Laboratory’, Decision Support Systems 32(2), 135–53. place bids for potential buyers up to a maximum Benyoucef, M., Alj, H., Vézeau, M. and Keller, R. F. predetermined bid amount. However, these agents (2001) ‘Combined Negotiations in E-Commerce: currently do not react to changes in the bidding envi- Concepts and Architecture’, Electronic Commerce ronment as a real bidder would. If another bidder were Research 1(3), 277–99. repeatedly bidding against the proxy agent, it would Bichler, M. (2001) The Future of e-markets: immediately increase its bid to the next possible mini- Multidimensional Market Mechanisms, Cambridge: mum bid amount. A real bidder, on the other hand, Cambridge University Press. might wait to raise their bid and perhaps avoid getting Bichler, M., Kalagnanam, J., Katircioglu, K., King, A. J., into a bidding war with the other bidder. Lawrence, R. D., Lee, H. S., Lin, G. Y. and Lu, Y. Agents that can be used to provide price histories (2002) ‘Application of Flexible Pricing in Business-to- and other auction information help to educate auction business Electronic Commerce’, IBM Systems Journal participants. Buyers will know what a reasonable price 41(2), 287–302. for a given item is and can avoid paying too much. Clark, D. (2000) ‘Shopbots Become Agents for Business Sellers can use the same information to determine Change’, Computer, February, 18–21. appropriate minimum and reserve prices for their auc- Crowston, K. (1996) ‘Market Enabling Web Agents’, in tions. The availability of this information can help to J. I. DeGross, S. Jarvenpaa and A. Srinivasan (eds), even the playing field between experienced and newer Proceedings of the Seventeenth International Conference auction players and reduce the occurrence of ‘winner’s on Information Systems, Cleveland, OH, December, curse’, thus opening online auctions as a viable and 381–90. satisfactory commerce alternative for a much larger Deveaux, L., Paraschiv, C. and Latourrette M. (2001) consumer population. ‘Bargaining on an Web Agent-based Market: Behavioral Agents in general have great potential for helping vs. Optimizing Agents’, Electronic Commerce Research buyers and sellers to set-up auctions, find specific 1(4), 371–401. items, and place appropriate bids. Future agents will be Doorenbos, R. B., Etzioni, O. and Weld, D. S. (1997) ‘A

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