Auction Platform Research Articles

Regulated Agricultural Marketing Infrastructural Development in Punjab

Agricultural regulated markets have been playing a pivotal role in the procurement of farm produce. Punjab state accounts for about six per cent of the total regulated markets in the country. With the rising agricultural production and growth of regulated marketing facilities, Punjab has become one of the leading states in development of marketing infrastructure and facilities for orderly marketing of agricultural produce. in the best interests of both producers and consumers. Basic infrastructural facilities like pucca auction platforms, parking, drinking water, electricity, mandi lights, internal roads, rest houses, toilets, bank and post office etc. were present in almost all the markets. Market information system was quite efficient in all the sampled markets. Thus all the markets are performing well on physical as well as financial front and the number, capacity and existing infrastructure of the regulated agricultural markets in the state comfortably meets the requirements of the increasing farm produce in the state. Nearly half of the total expenditure incurred by the Punjab State Agricultural Marketing Board during 2011–12 was for the infrastructural development in the agricultural markets. The study concluded that an efficient agricultural marketing system can be evolved by improving, strengthening and optimally utilising the existing market infrastructure in the state.

Expertise in Online Markets

We examine the effect of the presence of expert buyers on other buyers, the platform, and the sellers in online markets. We model buyer expertise as the ability to accurately predict the quality, or condition, of an item, modeled as its common value. We show that nonexperts may bid more aggressively, even above their expected valuation, to compensate for their lack of information. As a consequence, we obtain two interesting implications. First, auctions with a “hard close” may generate higher revenue than those with a “soft close.” Second, contrary to the linkage principle, an auction platform may obtain a higher revenue by hiding the item’s common-value information from the buyers. We also consider markets where both auctions and posted prices are available and show that the presence of experts allows the sellers of high-quality items to signal their quality by choosing to sell via auctions. This paper was accepted by J. Miguel Villas-Boas, marketing.

Expertise in Online Markets

We examine the effect of the presence of knowledgeable buyers (experts) in online markets where auctions with a hard close and posted prices are widely used. We model buyer expertise as the ability to accurately predict the quality, or condition, of an item. In auctions with a hard close, sniping – submitting bids in the last minute – emerges as an equilibrium strategy for experts. We show that non-experts bid more aggressively as the proportion of experts increases. As a consequence, we establish that the auction platform may obtain a higher revenue by (i) enforcing a hard close and allowing sniping, and (ii) withholding information regarding the quality of the item. Moreover, in online markets where both auctions and posted prices are available, we show that the presence of experts allows the sellers of high quality items to signal their quality by choosing to sell via auctions.

Unobserved heterogeneity and reserve prices in auctions

This article shows how reserve prices can be used to control for unobserved object heterogeneity to identify and estimate the distribution of bidder values in auctions. Reserve prices are assumed to be monotonic in the realization of unobserved heterogeneity, but not necessarily set optimally. The model is estimated using transaction prices from a used car auction platform to show that the platform enables sellers to capture a large fraction of the potential value from selling their vehicle. Individual sellers benefit mostly from access to a large set of buyers, but the magnitude depends on accounting for unobserved heterogeneity.

Leveraging Social Networks to Combat Collusion in Reputation Systems for Peer-to-Peer Networks

In peer-to-peer networks (P2Ps), many autonomous peers without preexisting trust relationships share resources with each other. Due to their open environment, the P2Ps usually employ reputation systems to provide guidance in selecting trustworthy resource providers for high reliability and security; however, node collusion impairs the effectiveness of reputation systems in trustworthy node selection. Although some reputation systems have certain mechanisms to counter collusion, the effectiveness of the mechanisms is not sufficiently high. In this paper, we leverage social networks to enhance the capability of reputation systems in combating collusion. We first analyzed real trace of the reputation system in the Overstock online auction platform, which incorporates a social network. The analysis reveals the impact of the social network on user purchasing and reputation rating patterns. We, thus, identified suspicious collusion behavior patterns and propose a social network-based mechanism, SocialTrust, to counter collusion. SocialTrust adaptively adjusts the weight of ratings based on the social distance and interest relationship between peers. Experiment results show that SocialTrust can significantly strengthen the capability of current reputation systems in combating collusion.

Google, Facebook, Amazon, eBay: Is the Internet driving competition or market monopolization?

This paper discusses the general characteristics of online markets from a competition theory perspective and the implications for competition policy. Three important Internet markets are analyzed in more detail: search engines, online auction platforms, and social networks. Given the high level of market concentration and the development of competition over time, we use our theoretical insights to examine whether (a) leading Internet platforms have non-temporary market power and, based on this analysis, (b) whether any specific market regulation beyond general competition law rules is warranted in these three online markets.

Auction Platform Design and the Linkage Principle

This paper examines an auction platform in which the monopoly platform maximizes profits by adjusting participation fees and choosing an auction format. The seller has private information on the quality of the good, and each participating buyer receives a private signal about his valuation of the good. The choice of auction format determines the allocation of trading surplus between the seller and buyers. This paper shows that when the seller's type is affiliated with the buyers' signals, the platform can charge higher participation fees on both sides by choosing a first-price or descending auction rather than a second-price or ascending auction. It also examines the effect of allowing participating buyers to acquire information on the seller's type and shows that the platform can charge higher participation fees on both sides by restricting communication between the seller and buyers.

Using ZMET to Construct the Consensus Map of the Users on Yahoo Auction Platforms

Many consumers often collect the related product information before shopping, for price negotiating and accordingly purchasing the product if the negotiation is successfully executed. Therefore, the online auction gradually becomes the important mean of the consumer shopping behavior. In this paper, the Zaltman Metaphor Elicitation Technique (ZMET) is proposed to construct the integrated mental model of the users on Yahoo auction platforms by utilizing the behavior model of C2C consumer to deeply verbally interview the user peer-topeer and the non-verbal (pictures, photos) analysis is also fulfilled at the same time. As a result, the ZMET outcomes could provide the valuable reference for the businesses which are interested to build the on-line auction website in the future.

The end of Internet Service Providers liability as we know it – Uncovering the consumer interest in CJEU Case C-324/09 (L'Oréal/eBay)

In the case of L'Oreal/eBay the Court of Justice of the European Union answered preliminary questions concerning a number of Directives regarding the liability of online auction sites in the sale of fake goods as well as parallel imports. While the decision is not directly concerned with the interests of consumers, and primarily dealing with the protection of trade mark owners, it is likely to have important effects on consumers since they will be the ultimate beneficiaries of a marked change in the way Internet Service Providers' liability will be assessed and force online auction platforms to better police their sites.

Identification in the Roy Model with an Application to Auctions

The paper presents conditions for non-parametric identification of a joint distribution when the marginal distributions are identified and the joint distribution is partially identified. Specifically, the paper considers the problem of estimating a J-dimensional Roy Model. The paper extends Heckman and Honore (1990) by providing an additional identification result with reasonable data requirements and without strong parametric assumptions. The result is applied to sealed bid auctions where bidders face competing auctions for substitutes, such as in auction platforms like eBay or Google Adwords.

A Study of Online Auction Sellers’ Intention to Switch Platform: The Case of Yahoo!Kimo Versus Ruten_eBay*

ABSTRACTThe study of consumers’ switching from one service provider to another has a long tradition in economics, information systems, and marketing. The emergence of electronic commerce presents new challenges in understanding consumers’ switching intentions in the context of e‐commerce in general and online auctions in particular. With the abundance of literature on online auctions, there is a surprising lack of research on auction sellers’ intentions to switch from one online auction platform to another. Using the competition between Yahoo!Kimo and Ruten_eBay, two leading auction platforms in Taiwan, as the backdrop, we developed a research model and collected empirical data based on this real case to study what factors influence auction sellers to switch to a competing service provider. We find that the higher the procedural switching costs, financial switching costs, relational switching costs, site design quality, or interaction quality, the lower the intention of an auction seller to switch to a competing auction service provider. A higher perceived transaction fee, however, leads to a higher switching intention.

Combining ranking concept and social network analysis to detect collusive groups in online auctions

Due to the popularity of online auction markets, auction fraud has become common. Typically, fraudsters will create many accounts and then transact among these accounts to get a higher rating score. This is easy to do because of the anonymity and low fees of the online auction platform. A literature review revealed that previous studies focused on detection of abnormal rating behaviors but did not provide a ranking method to evaluate how dangerous the fraudsters are. Therefore, we propose a process which can provide a method to detect collusive fraud groups in online auctions. First, we implement a Web crawling agent to collect real auction cases and identify potential collusive fraud groups based on a k-core clustering algorithm. Second, we define a data cleaning process to remove the unrelated data. Third, we use the Page-Rank algorithm to discover the critical accounts of the groups. Fourth, we developed a ranking method for auction fraud evaluation. This method is an extension of the standard Page-Rank algorithm and combines the concepts of Web structure and risk evaluation. Finally, we conduct experiments using the Adaptive Neuro-Fuzzy Inference System (ANFIS) neural network and verify the performance of our method by applying it to real auction cases. In summary, we find that the proposed ranking method is effective in identifying potential collusive fraud groups.

Design and Promotion Strategy of Marketing Platform of Aquatic Auction based on Internet

For the online trade and promotion of aquatic products and related materials through the network between supply and demand, the design content and effective promotional strategies of aquatic auctions online marketing platform is proposed in this paper. Design elements involve the location of customer service, the basic function of the platform including the purchase of general orders, online auctions, information dissemination, and recommendation of fine products, human services, and payment preferences. Based on network and mobile e-commerce transaction support, the auction platform makes the transaction of aquatic products well in advance. The results are important practical value for the design and application of online marketing platform of aquatic auction.

Water Quality Credit Trading: Developments in 2011

Water quality credit trading is being used in a number of watersheds throughout the country in a variety of forms and with a menagerie of rules, which vary based upon the state jurisdiction. October marked the end of the second year of active nutrient credit trading in Pennsylvania and the Pennvest public auction platform. This article provides the latest information on the use of water quality credits in Pennsylvania in 2011. A free commodity market like Pennsylvania's credit trading market can be a good tool to match price with demand, except when speculators enter the market, as we experienced this year. Discussion in this article includes results from the November 2 Pennvest auction, analysis of most current trends and unexpected challenges encountered this year by credit buyers and sellers in the Commonwealth.

Time–HOBI: Index for optimizing star queries

One of the important research and technological problems in data warehouse query optimization concerns star queries. So far, most of the research focused on optimizing such queries by means of join indexes, bitmap join indexes, or various multidimensional indexes. These structures neither support navigation well along dimension hierarchies nor optimize joins with the Time dimension, which in practice is used in most of the star queries. In this paper we propose an index, called Time–HOBI, for optimizing the star queries that compute aggregates along dimension hierarchies. Time–HOBI, created on a dimension hierarchy, is composed of (1) a Hierarchically Organized Bitmap Index (HOBI), where one bitmap index is maintained for one dimension level, and (2) a Time Index (TI) that implicitly encodes time in every dimension. HOBI allows to quickly search for fact rows satisfying predicates defined on different levels of dimension hierarchies. With the support of TI joining a fact table with the Time dimension is avoided. Thus, Time–HOBI supports a broad class of star queries. In this paper we explain how query execution plans for star queries can profit from Time–HOBI. We show, based on experiments, the efficiency of Time–HOBI for different classes of queries, as compared to HOBI and a traditional bitmap index. Based on the experiments, we also demonstrate how sensitive Time–HOBI is to variable selectivity of queries. We also analyze the maintenance time of Time–HOBI as compared to HOBI and a traditional bitmap index. The experiments used in the paper have been conducted on a real dataset, coming from the biggest East-European Internet auction platform Allegro.pl. The experiments show that Time–HOBI can be successfully applied to the optimization of star queries as it offers promising performance improvement.

Ethnic Discrimination and Signals of Trustworthiness in an Online Market: Evidence from Two Field Experiments

Summary Results of two field experiments which were designed to identify possible ethnic discrimination on a German internet auction platform are discussed. A first set of results was produced by a secondary analysis of an earlier experiment. The second experiment then tested whether costly signals could help to overcome problems of trust between buyers and sellers in online markets. The evidence is rather mixed with respect to ethnic discrimination, and it does not support the signaling hypothesis.

Tax Evasion and Fraud Detection: A Theoretical Evaluation of Taiwan’s Business Tax Policy for Internet Auctions

Only registered businesses can charge and collect taxes on goods and services made in Taiwan. As auction sites are places where individuals can conduct business activities for profit without paying business taxes, Taiwan’s tax authority has ruled that profit-seeking individuals must register as businesses and pay taxes. However, the anonymity of sellers on Internet auction platforms poses challenges to the ability of the tax authority to enforce this ruling. This paper examines business tax policy for online auctions in Taiwan and then assesses the prospects of taxing sales on online auctions using a game theory model. Analytical results suggest that seller anonymity will allow a vendor to continue to disguise business identity and the tax authority will not aggressively pursue tax evaders.

Identification and Estimation with Competing Auctions

The paper presents conditions for non-parametric identification of a joint distribution when the marginal distributions are identified and the joint distribution is only identified for a subset of the domain. This result is applied to sealed bid auctions where bidders face competing auctions for substitutes, such as in auction platforms like eBay or Google Adwords. A bivariate normal copula function is estimated for pick up trucks sold in eBay auctions. The results suggest the F-150 and Silverado are close substitutes and the F-150 seller’s optimal reserve should fall 5-10% when faced with a competing Silverado auction.

Spiral of hatred: social effects in Internet auctions. Between informativity and emotion

An auction platform is a dynamic environment where a rich variety of social effects can be observed. Most of those effects remain unnoticed or even hidden to ordinary users. The in-depth studies of such effects should allow us to identify and understand the key factors influencing users' behaviour. The material collected from the biggest Polish auction house has been analyzed. NLP algorithms were applied to extract sentiment-related content from collected comments and to measure informativity. Emotional distance between negative, neutral and positive comments has been calculated. The obtained results confirm the existence of the spiral-of-hatred effect but also indicate that much more complex patterns of mutual relations between sellers and buyers exist. The last section contains a several suggestions which can prove useful to improve trustworthiness of users' reports and security of an auction platform in general.

A multi-agent platform for auction-based allocation of loads in transportation logistics

This paper describes an agent-based platform for the allocation of loads in distributed transportation logistics, developed as a collaboration between CWI, Dutch National Center for Mathematics and Computer Science, Amsterdam and Vos Logistics Organizing, Nijmegen, The Netherlands. The platform follows a real business scenario proposed by Vos, and it involves a set of agents bidding for transportation loads to be distributed from a central depot in the Netherlands to different locations across Germany. The platform supports both human agents (i.e. transportation planners), who can bid through specialized planning and bidding interfaces, as well as automated, software agents. We exemplify how the proposed platform can be used to test both the bidding behaviour of human logistics planners, as well as the performance of automated auction bidding strategies, developed for such settings. The paper first introduces the business problem setting and then describes the architecture and main characteristics of our auction platform. We conclude with a preliminary discussion of our experience from a human bidding experiment, involving Vos planners competing for orders both against each other and against some (simple) automated strategies.