Implementing seller agent in multiple online auctions

Online auctions are becoming extremely popular because of the convenience that it offers to the consumers. Much work has been done in designing bidding strategy that can be utilized by bidders who want to participate in online auctions. However, very little work has been done on the seller's strategy for online auctions. In any online auction, the final selling price of the item is unknown until the auction closes. This price is dependent on several factors such as the number of bidders participating in the auction, how much each bidder is willing to pay for the product, how many online auctions are selling the same item as well as the duration of each auction. Each item to be auctioned off has a reserved price set by the seller. Setting the reserved price too high for the item will result in the item not being sold and setting the price too low may result in profit reduction or even loss. Deciding on the reserved price of an item to be auctioned off is not a straightforward decision. This chapter reports on a preliminary implementation of a seller agent that recommends a reserved price for a given item to be auctioned off by the seller. The seller agent's objective is to suggest a reservation price that guarantees the sale of the item within a given period (as required by the seller) with a profit

Coordination of Purchasing and Bidding Activities Across Markets

In both consumer purchasing and industrial procurement, combinatorial interdependencies among the items to be purchased are commonplace. E-commerce compounds the problem by providing more opportunities for switching suppliers at low costs, but also potentially eases the problem by enabling automated market decision-making systems, commonly referred to as trading agents, to make purchasing decisions in an integrated manner across markets. Most of the existing research related to trading agents assumes that there exists a combinatorial market mechanism in which buyers (or sellers) can bid (or sell) service or merchant bundles. Todayâ??s prevailing e-commerce practice, however, does not support this assumption in general and thus limits the practical applicability of these approaches. We are investigating a new approach to deal with the combinatorial interdependency challenges for online markets. This approach relies on existing commercial online market institutions such as posted-price markets and various online auctions that sell single items. It uses trading agents to coordinate a buyerâ??s purchasing and bidding activities across multiple online markets simultaneously to achieve the best overall procurement effectiveness. This paper presents two sets of models related to this approach. The first set of models formalizes optimal purchasing decisions across posted-price markets with fixed transaction costs. Flat shipping costs, a common e-tailing practice, are captured in these models. We observe that making optimal purchasing decisions in this context is NP-hard in the strong sense and suggest several efficient computational methods based on discrete location theory. The second set of models is concerned with the coordination of bidding activities across multiple online auctions. We study the underlying coordination problem for a collection of first or second-price sealed-bid auctions and derive the optimal coordination and bidding policies.

A river of risk : a diagram of the history and historiography of risk management

The history of risk and risk management can be evaluated through the historiography of the subject. Writings on the history of risk and risk management can also be treated as pieces of evidence. A diagram is proposed describing some of the subjects and influencing the development of risk management, focused through the theme of records management. A detailed exploration of the historiography is undertaken to indicate the relevance of the history of risk management to its present interdisciplinary status

Stochastic Deadlines: A Comparison of Parallel Multiple Auction Designs

In online auction platforms, offers are listed side by side and may end at the same point in time. While theoretical studies predict efficient coordination across auctions, experimental and empirical studies observe efficiency losses, i.e. goods remain unsold. In order to mitigate this coordination failure, we contribute to the literature of auction design by introducing a stochastic deadline in parallel multiple auctions. In these parallel Candle Auctions, several auctions start at the same time but end (separately) due to a stochastic process. We think that the stochastic ending rule decreases the coordination failure because the threat of a sudden termination forces the bidders to coordinate across auctions early in the auction process. Indeed, we find that coordination is less pronounced in parallel Candle Auctions resulting in higher efficiencySimultaneous Auctions, Internet, Auction Design, Experimental Economics

An Experimental Analysis of Parallel Multiple Auctions

At online auction platforms we often observed that substitutable goods are auctioned concurrently with auctions ending at the same time. I introduce an experimental setup of three sellers and four buyers in an ascending second price auction environment where every seller runs one auction with a homogeneous good and the buyers are confronted with single unit demand. I find that sellers revenue is significantly lower than theory predicts due to the fact that some auctions did not receive bids whereas other auctions concentrated the bids of all bidders. Moreover, I observe a statistically higher revenue of sellers setting the minimum starting price. Furthermore, my study shows that the buyers submit bids which are significantly lower than the private valuation every buyer receives. Comparing the efficiency of the parallel multiple auction setup to a double auction control experiment, I find a significant lower efficiency in parallel multiple auctions due to the coordination failure of the buyers.simultaneous auctions, internet auctions, market design, electronic business

Coordination of Purchasing and Bidding Activities Across Markets

In both consumer purchasing and industrial procurement, combinatorial interdependencies among the items to be purchased are commonplace. E-commerce compounds the problem by providing more opportunities for switching suppliers at low costs, but also potentially eases the problem by enabling automated market decision-making systems, commonly referred to as trading agents, to make purchasing decisions in an integrated manner across markets. Most of the existing research related to trading agents assumes that there exists a combinatorial market mechanism in which buyers (or sellers) can bid (or sell) service or merchant bundles. Today’s prevailing e-commerce practice, however, does not support this assumption in general and thus limits the practical applicability of these approaches. We are investigating a new approach to deal with the combinatorial interdependency challenges for online markets. This approach relies on existing commercial online market institutions such as posted-price markets and various online auctions that sell single items. It uses trading agents to coordinate a buyer’s purchasing and bidding activities across multiple online markets simultaneously to achieve the best overall procurement effectiveness. This paper presents two sets of models related to this approach. The first set of models formalizes optimal purchasing decisions across posted-price markets with fixed transaction costs. Flat shipping costs, a common e-tailing practice, are captured in these models. We observe that making optimal purchasing decisions in this context is N P-hard in the strong sense and suggest several efficient computational methods based on discrete location theory. The second set of models is concerned with the coordination of bidding activities across multiple online auctions. We study the underlying coordination problem for a collection of firstor second-price sealed-bid auctions and derive the optimal coordination and bidding policies

Determining Successful Negotiation Strategies: The Evolution of Intelligent Agents

Due to the desire of almost all departments of business organizations to be interconnected and to make data accessible at any time and any place, more and more multi-agent systems are applied to business management. As numerous agents are roaming through the Internet, they compete for the limited resource to achieve their goal. In the end, some of them will succeed, while the others will fail. However, when agents are initially created, they have little knowledge and experience with relatively lower capability. They should also strive to adapt themselves to the changing environment. It is advantageous if they have the ability to learn and evolve. This paper addresses evolution of intelligent agents in virtual enterprises. Agent fitness and fuzzy multi-criteria decision-making approach are proposed as evolution mechanisms, and fuzzy soft goal is introduced to facilitate the evolution process. Genetic programming operators are employed to restructure agents in the proposed multi-agent evolution cycle. We conduct a series of experiments to determine the most successful strategies and to see how and when these strategies evolve depending on the context and negotiation stance of the agent’s opponent

Using priced options to solve the exposure problem in sequential auctions

We propose a priced options model for solving the exposure problem of bidders with valuation synergies participating in a sequence of online auctions. We consider a setting in which complementary-valued items are offered sequentially by different sellers, who have the choice of either selling their item directly or through a priced option. In our model, the seller fixes the exercise price for this option, and then sells it through a first-price auction. We analyze this model from a decision-theoretic perspective and we show, for a setting where the competition is formed by local bidders (which desire a single item), that using options can increase the expected profit for both sides. Furthermore, we derive the equations that provide minimum and maximum bounds between which the bids of the synergy buyer are expected to fall, in order for both sides of the market to have an incentive to use the options mechanism. Next, we perform an experimental analysis of a market in which multiple synergy buyers are active simultaneously. We show that, despite the extra competition, some synergy buyers may benefit, because sellers are forced to set their exercise prices for options at levels which encourage participation of all buyers.</jats:p