A Comparative Study of Two Combinatorial Reverse Auction Models

Online group-buying is one of the most innovative business models employed by many companies. From the perspective of buyers, quantity based discounts provide a huge incentive to form coalitions and take advantage of lower prices without ordering more than their actual demand. Traditional group-buying mechanisms are usually based on a single item and uniform cost sharing. One way to reduce the cost for acquiring the required items is to take into account the complementarities between items provided by the sellers. By holding a combinatorial reverse auction, the total cost to acquire the required items will be significantly reduced due to complementarities between items. However, combinatorial reverse auctions suffer from high computational complexity. If there are multiple buyers, there are two different business models for procurement based on combinatorial reverse auctions: (1) independent combinatorial reverse auctions: each buyer may hold a combinatorial reverse auction independently and (2) combinatorial reverse auctions based on group buying: multiple buyers delegate the auction to a group buyer and the group buyer holds only one combinatorial reverse auction for all the buyers. In developing an effective tool to support the decision of multiple buyers’ procurement, a comparative study on the performance and efficiency of these two different business models is needed. In this paper, we compare the performance as well as the computational efficiency for these two combinatorial reverse auction models. Our analysis indicates that group buying combinatorial reverse auction outperforms multiple separate combinatorial reverse auctions not only in performance but also in efficiency

Online Reverse Auctions for Procurement of Services

Online reverse auctions, in which a buyer seeks to select a supplier and suppliers compete for contracts by bidding online, revolutionized corporate procurement early this century. Shortly after they had been pioneered by General Electric, many companies rushed to adopt reverse auctions but the adoption soon slowed down due to the negative effects of auction-induced competition. Today, as firms continue to experiment with the reverse auctions, it is important to understand how the interplay of the auction context, the service characteristics, and buyer-supplier relationships affects auction outcomes and the success of the auctioned projects. This PhD dissertation investigates online reverse auctions in service industries (e.g. software development, building construction). The differences between services and products (services can be more difficult to describe and require more intensive communication) challenge theories that try to explain auction outcomes. We study several aspects of auctioning service contracts: the buyer’s choice between auctions and negotiations; the contract allocation decisions in auctions; the heterogeneity of buyers’ procurement behaviour; and the effect of auction outcomes on buyer-supplier relationships and project performance during the project execution. Some of the key findings are: 1) that the buyer’s repeat exchange interaction with vendors as well as the satisfaction with a vendor’s past performance lead to the buyer’s preference for using bilateral negotiation to allocate the next project; 2) that there are five buyers’ tactics that allow to increase the likelihood of contract allocation; 3) that the outcomes of online reverse auctions can aggravate project managers’ role constraints and that project managers can use relational exchange competences to overcome these constraints. Overall, buying services through online reverse auctions is quite different from buying products. This thesis makes the first steps to develop theoretical knowledge to account for that difference

Designing Coalition-Proof Reverse Auctions over Continuous Goods

This paper investigates reverse auctions that involve continuous values of different types of goods, general nonconvex constraints, and second stage costs. We seek to design the payment rules and conditions under which coalitions of participants cannot influence the auction outcome in order to obtain higher collective utility. Under the incentive-compatible Vickrey-Clarke-Groves mechanism, we show that coalition-proof outcomes are achieved if the submitted bids are convex and the constraint sets are of a polymatroid-type. These conditions, however, do not capture the complexity of the general class of reverse auctions under consideration. By relaxing the property of incentive-compatibility, we investigate further payment rules that are coalition-proof without any extra conditions on the submitted bids and the constraint sets. Since calculating the payments directly for these mechanisms is computationally difficult for auctions involving many participants, we present two computationally efficient methods. Our results are verified with several case studies based on electricity market data

Evaluating eREVERSE auctions (EeRA): A research note

This eGISE network paper seeks to evaluate issues relating to the implementation of electronic reverse auctions (eRA) within local government procurement processes. The adoption of an eRA invites pre-qualified suppliers to compete with each other for a specified good or service. Consequently, there is a unique opportunity for the buyer to receive a reduced cost through the successful bidder. However, the literature identifies a number of adverse effects within these arrangements depending upon the nature of the buyer/supplier relationship. The objectives of the research involves identifying a set of business scenarios to demonstrate the impact of different eRA strategies in this respect. This will be achieved through a structured case analysis approach to enable qualitative data to be modelled through a visual toolset simulation. It is believed the outcome of the investigation will provide valuable insights into the complexities associated with the eProcurement process

Information Disclosure in Open Non-Binding Procurement Auctions: an Empirical Study

The outcome of non-binding reverse auctions critically depends on how information is distributed during the bidding process. We use data from a large European procurement platform to study the impact of different information structures, specifically the availability of quality information to the bidders, on buyers' welfare and turnover of the platform. First we show that on the procurement platform considered bidders indeed are aware of their rivals' characteristics and the buyers preferences over those non-price characteristics. In a counterfactual analysis we then analyze the reduction of non-price information available to the bidders. As we find, platform turnovers in the period considered would decrease by around 30%, and the buyers' welfare would increase by the monetary equivalent of around 45% of turnover of the platform

Modeling On-Line Art Auction Dynamics Using Functional Data Analysis

In this paper, we examine the price dynamics of on-line art auctions of modern Indian art using functional data analysis. The purpose here is not just to understand what determines the final prices of art objects, but also the price movement during the entire auction. We identify several factors, such as artist characteristics (established or emerging artist; prior sales history), art characteristics (size; painting medium--canvas or paper), competition characteristics (current number of bidders; current number of bids) and auction design characteristics (opening bid; position of the lot in the auction), that explain the dynamics of price movement in an on-line art auction. We find that the effects on price vary over the duration of the auction, with some of these effects being stronger at the beginning of the auction (such as the opening bid and historical prices realized). In some cases, the rate of change in prices (velocity) increases at the end of the auction (for canvas paintings and paintings by established artists). Our analysis suggests that the opening bid is positively related to on-line auction price levels of art at the beginning of the auction, but its effect declines toward the end of the auction. The order in which the lots appear in an art auction is negatively related to the current price level, with this relationship decreasing toward the end of the auction. This implies that lots that appear earlier have higher current prices during the early part of the auction, but that effect diminishes by the end of the auction. Established artists show a positive relationship with the price level at the beginning of the auction. Reputation or popularity of the artists and their investment potential as assessed by previous history of sales are positively related to the price levels at the beginning of the auction. The medium (canvas or paper) of the painting does not show any relationship with art auction price levels, but the size of the painting is negatively related to the current price during the early part of the auction. Important implications for auction design are drawn from the analysis.Comment: Published at http://dx.doi.org/10.1214/088342306000000196 in the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org