Distributed ascending proxy auction — A cryptographic approach

In recent years, auctions have become a very popular price discovery mechanism in the Internet. The common auction formats are typically centralized in nature. The peer-to-peer paradigm demands gearing up auctions for decentralized infrastructures. In this context, this paper proposes a distributed mechanism for ascending second-price auctions that relies on standard cryptographic algorithms. In essence, the auction protocol has the capability of preserving the privacy of the winning bidder’s true valuation. The auction protocol makes use of a high number of auctioneers divided into several groups. A bidder creates an encrypted chain of monotonously increasing bidding steps, where each bidding step can be decrypted by a different auctioneer group. This considerably reduces the attack and manipulation possibilities of malicious auctioneers. In addition, this secure approach does not require bidders to be online unless they are submitting their bid chain to the auctioneers.     

The trade-offs between Fog Processing and Communications in latency-sensitive Vehicular Fog Computing

In a vehicular fog computing paradigm, connected autonomous vehicles are envisioned as processing nodes (i.e. fog nodes) so that end-devices may offload processing tasks to them. As such, both local and distributed processing on fog nodes will depend heavily on wireless network conditions and the current traffic demand. In this work, we investigate the trade-offs on the operation of fog nodes under different vehicle densities and network conditions and formalize a Time Constrained One-Shot Open First Price Auction for resource allocation in vehicular fog computing. Through a large-scale simulation study, we assess important aspects of the performance of fog nodes in Vehicular Fog Computing. We show that current wireless network standards may dictate the limits of processing despite the availability of processing power of fog nodes. Our results indicate the existence of trade-offs on the operation of fog nodes regarding message overhead and processing redundancy to achieve high task completion ratio. Finally, we evaluate the social welfare distribution of the task allocation achieved using the auction where higher message rates lead to higher costs.     

Supplier selection and order lot sizing modeling: A review

With globalization and the emergence of the extended enterprise of interdependent organizations, there has been a steady increase in the outsourcing of parts and services. This has led firms to give more importance to the purchasing function and its associated decisions. One of those decisions which impacts all firms’ areas is the supplier selection. Since the 1950s, several works have addressed this decision by treating different aspects and instances. In this paper, we extend previous survey papers by presenting a literature review that covers the entire purchasing process, considers both parts and services outsourcing activities, and covers internet-based procurement environments such as electronic marketplaces auctions. In view of its complexity, we will focus especially on the final selection stage that consists of determining the best mixture of vendors and allocating orders among them so as to satisfy different purchasing requirements. In addition, we will concentrate mainly on works that employ operations research and computational models. Thereby, we will analyze and expose the main decision's features, and propose different classifications of the published models.     

User evaluation of a market-based recommender system

Recommender systems have been developed for a wide variety of applications (ranging from books, to holidays, to web pages). These systems have used a number of different approaches, since no one technique is best for all users in all situations. Given this, we believe that to be effective, systems should incorporate a wide variety of such techniques and then some form of overarching framework should be put in place to coordinate them so that only the best recommendations (from whatever source) are presented to the user. To this end, in our previous work, we detailed a market-based approach in which various recommender agents competed with one another to present their recommendations to the user. We showed through theoretical analysis and empirical evaluation with simulated users that an appropriately designed marketplace should be able to provide effective coordination. Building on this, we now report on the development of this multi-agent system and its evaluation with real users. Specifically, we show that our system is capable of consistently giving high quality recommendations, that the best recommendations that could be put forward are actually put forward, and that the combination of recommenders performs better than any constituent recommender.     

How to obtain full privacy in auctions

Privacy has become a factor of increasing importance in auction design. We propose general techniques for cryptographic first-price and (M+1)st-price auction protocols that only yield the winners' identities and the selling price. Moreover, if desired, losing bidders learn no information at all, except that they lost. Our security model is merely based on computational intractability. In particular, our approach does not rely on trusted third parties, e.g., auctioneers. We present an efficient implementation of the proposed techniques based on El Gamal encryption whose security only relies on the intractability of the decisional Diffie—Hellman problem. The resulting protocols require just three rounds of bidder broadcasting in the random oracle model. Communication complexity is linear in the number of possible bids.     

Doing their bidding: An empirical examination of factors that affect a buyer’s utility in Internet auctions

What factors make individual bidders pay more or less for the same item in online auctions? We use data on over 55,000 bids over a three-year period collected by a customized Internet software agent. These data are used to perform a within-bidders quasi-experiment, testing bidders who bid on the exact same item at different times during a 30-day period in online auctions. With theories from information systems and consumer behavior as our theoretical lens, we then examine factors that make individuals pay more for the exact same item in online auctions. We find that the same individual will tend to pay more for items sold on a weekend, for items with a picture, and for items sold by experienced sellers. We also find that the same individual is willing to pay more for the same item if others express an interest in that item, exhibiting a type of herd effect. Our results are generalizable to other auctions, and shed light on electronic commerce sales in general, where firms try to sell products for the highest possible price.