Price Auction Research Articles

An exact method for the combinatorial bids generation problem with uncertainty on clearing prices, bids success, and contracts materialization

We address a new variant of the Bid Construction Problem (BCP) with stochastic clearing prices in combinatorial auctions for the procurement of truckload transportation service that tackles uncertainty on bids success and auctioned contracts materialization. We propose the first exact method to generate multiple non-overlapping bids while ensuring a non-negative profit for the carrier regardless of the auction outcomes and auctioned contracts materialization. Our exact method iteratively solves a relaxed then a restricted version of the BCP with stochastic clearing prices while checking all routes generated in each optimal solution and dynamically adds cuts to forbid what we define as risky routes. Risky routes are the ones that could yield a negative profit if some bids are lost or some auctioned contracts do not materialize later. Our experimental study highlights the good performance of our exact approach and points out the potential gains in profits yielded by our new variant compared to a standard BCP.

IMPLEMENTATION OF ONLINE AUCTION SERVICES (E-AUCTION) AT KANTOR PELAYANAN KEKAYAAN NEGARA DAN LELANG (KPKNL) BEKASI CITY

Electronic government and electronic government, namely a change in the manual system of government to an electronic one, one example is the Online auction (E-auction), which is an auction site and procurement of goods based on electronics/online through applications or websites and can be used for executable auctions, non-auction mandatory execution, as well as voluntary non-execution auctions. In addition, they can bid online via the internet on their cell phones without having to be present at the auction venue or auction office, accessible whenever and wherever they are because it is more efficient in time, accommodation and transportation to the auction place. This online auction is conducted via e-mail so that auction participants can bid repeatedly without interference from outside parties outside the auction, unlike conventional auctions where other people can interfere or participate in bidding on the auction price until the time specified. set out. This study aims to implement the e-auction and analyze the obstacles that occur and the efforts to overcome obstacles at the Bekasi City State Wealth and Auction Service Office (KPKNL). The research paradigm is Constructivism, a case study research design. Using the purposive sampling technique, qualitative research methods with data collection techniques using observation and in-depth interviews. The results of the study indicate that the implementation of the online auction system (e-auction) in Bekasi has been used since 2015 until now, with the implementation of the system running quite well due to annual human resource training, more complete facilities and infrastructure, and fast service. responsive. However, deficiencies such as a lack of socialization about the website and the auction sales target are still not achieved.

Are female skins sold at a lower price? Evidence from the Fortnite game

ABSTRACT Much significant research has been done to shed light on discrimination of females in, for example, labour markets. Less is known, in contrast, about the amount of discrimination in the virtual world of online gaming. In an early study, Castronova (2004), using data for the EverQuest game, finds that female avatars receive about 10% lower prices in online auctions. In this research note, we re-examine the pricing of avatars using data for the Fortnite game and find small and statistically insignificant price difference between female and male avatars.

Carbon and Biodiversity Policies

Wildfires are a concern in many European countries, and they might occur more frequently given climate change. Carbon sequestration is an ecosystem service provided by forests that is affected by fires and is neglected in traditional markets. Recently, the European Union (EU) has created environmental policies that address climate change, wildfires, and biodiversity conservation through payment for ecosystem services schemes. This study aims to estimate the monetary carbon savings of avoiding wildfires in five Mediterranean countries using historical wildfire emissions data and the auction prices in the EU Carbon Market. Portugal is further studied since the country has a new ecosystem services payment policy. The results indicate that, by avoiding fires, the countries could have annual benefits in the order of millions of euros. For Portugal, the value of the policy incentive is inferior to the value of the carbon sequestration service provided by avoiding fires and could be reexamined.

The influence of state politics on solar energy auction results

In this paper, we analyze the impact of policy-induced opportunity costs and restrictions on the outcomes of auctions to subsidize ground-mounted photovoltaic (PV) systems in Germany since 2015. First, we examine the incidence of opportunity cost reductions for some suppliers in a simple theoretical auction model. Second, we descriptively study the volumes and prices in PV auctions in Germany. Finally, we analyze a quasi-experiment: the opening of auctions for farmland in disadvantaged areas in some German states from 2017. We show that policy-induced opportunity cost reductions lead to greater success in PV auctions only in the state of Bavaria, which has more generous quantity restrictions and is generally expected to be more supportive of solar power suppliers after 2017. As a result, there is an interregional redistribution in favor of a single state that enables and administratively effectively implements support for disadvantaged areas.

Is consumers' willingness to pay premium for agricultural brand labels sustainable?: evidence from Chinese consumers' random n-price auction experiment

PurposeConsumers' willingness to pay premium (WTPP) for two different types of agricultural brand labels (enterprise and regional), are evaluated through a non-hypothetical Random n-price auction experiment during the online purchase of fresh agricultural products. The purpose of this paper is to evaluate the two WTPP, compare their differences, and explore their sustainability.Design/methodology/approachData were collected in July–August 2020 from a sample of 310 consumers in Liaoning Province, China. A nonhypothetical random n-price auction experiment was implemented in a simulated online shopping environment.FindingsThe results show that WTPP exists, and WTPP level of regional brand labels is higher than that of enterprise brand labels. Consumers' WTPP is sustainable. Consumers with low WTPP for enterprise brand labels and consumers with high WTPP for regional brand labels have stronger willingness to repurchase.Practical implicationsThe results have direct practical implications for developing brand agriculture and encouraging “brand consumption”. The results can provide theoretical reference for policymakers, enlightenment for the development and effective dissemination of agricultural brand labels and important information to e-retailers on how to sale agricultural products with agricultural brand labels.Originality/valueTo the best of the authors' knowledge, no previous study has related WTPP and its sustainability for agricultural brand labels in China. We try to fill a gap in literature on consumers' WTPP for agricultural brand labels. And the authors explore the sustainability of WTPP by analyzing the impact of WTPP on repurchase intention and recommendation intention respectively.

Signaling in Posted Price Auctions

We study single-item single-unit Bayesian posted price auctions, where buyers arrive sequentially and their valuations for the item being sold depend on a random, unknown state of nature. The seller has complete knowledge of the actual state and can send signals to the buyers so as to disclose information about it. For instance, the state of nature may reflect the condition and/or some particular features of the item, which are known to the seller only. The problem faced by the seller is about how to partially disclose information about the state so as to maximize revenue. Unlike classical signaling problems, in this setting, the seller must also correlate the signals being sent to the buyers with some price proposals for them. This introduces additional challenges compared to standard settings. We consider two cases: the one where the seller can only send signals publicly visible to all buyers, and the case in which the seller can privately send a different signal to each buyer. As a first step, we prove that, in both settings, the problem of maximizing the seller's revenue does not admit an FPTAS unless P=NP, even for basic instances with a single buyer. As a result, in the rest of the paper, we focus on designing PTASs. In order to do so, we first introduce a unifying framework encompassing both public and private signaling, whose core result is a decomposition lemma that allows focusing on a finite set of possible buyers' posteriors. This forms the basis on which our PTASs are developed. In particular, in the public signaling setting, our PTAS employs some ad hoc techniques based on linear programming, while our PTAS for the private setting relies on the ellipsoid method to solve an exponentially-sized LP in polynomial time. In the latter case, we need a custom approximate separation oracle, which we implement with a dynamic programming approach.

Real-time Bidding for Time Constrained Impression Contracts in First and Second Price Auctions - Theory and Algorithms

We study an optimal bidding and allocation problem that builds upon the earlier work of [4]. The model we study is of interest in online real-time advertising where the demand of a large number of advertisers is aggregated by an intermediary who bids in the advertising auction market on their behalf. This intermediary is referred to as a Demand Side Platform (DSP).

Determinants of the Price Paid at Auctions of Contemporary Art for Artworks by Twelve Artists

The use of regression modelling to understand how characteristics of artworks, of artists, and of the circumstances of sale affect the price paid at auction is well-established among cultural economists. Drawing on auction sales data provided by Artprice (accessed on 20 March 2022) I use regression modelling to investigate the determinants of the price paid for artworks by twelve artists at auctions of contemporary art over the period from 1984 to 2019. Each of the artists is modelled separately. For nine of the twelve artists, there was a clear preference among collectors for paintings with specific titles rather than untitled paintings or paintings with generic titles such as ‘abstract’ or ‘composition’. For the other explanatory factors included in the models, my analysis complements and re-contextualizes previous scholarship, showing how collectors’ preferences differed between the contexts examined. Size was a stronger driver of the price paid than in the contexts examined in other studies, and for most artists, collectors were not deterred by the largest artworks. Paintings in oil have continued to appeal to some collectors. Although the number of artists looked at is small, there are some suggestive patterns in how the age of the artist at execution affected the auction price, which might merit further investigation. My models also give some insights into change within the auction market for contemporary art.

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.

Using the Auction Price Method to Estimate Payment for Forest Ecosystem Services in Xin’an River Basin in China: A BDM Approach

Accurately estimating the forest farmers’ protection costs for forest ecosystem services has become a hot issue in ecological economics. In this research, we propose a novel method of using an auction price model to evaluate the forest ecosystem services. We establish a functional relationship between forest farmers and the forestland that belongs to them based on experimental data from Xin’an River Basin in China. The results indicate that the average willingness of farmers to accept payment for forest ecosystem service protection in the low, middle, and high levels of forest quality is 17,123.10, 23,493.75, and 31,064.40 yuan/ha/year, respectively. Moreover, farmers with different individual characteristics, household characteristics, planting characteristics, policy cognition, and ecological awareness are also willing to be paid differently. This research can provide a reference for forest ecosystem protection policies and assist the sustainable forestry development.

The impact of renewables on the incidents of negative prices in the energy spot markets

In this paper we analyze the impact of growing renewable energy generation on the instances of negative day-ahead auction prices. We perform a simulation that is based on the real-world day-ahead wholesale supply and demand curves from the German-Luxembourg coupled market to gain insights about which developments in instances of negative market clearing prices could be expected in the short to middle term period with more intermittent energy in the system. This is achieved through transforming the real-world supply curves to include more renewable generation and recalculating the market clearing prices. The results of the spatial analysis suggest that keeping the strong fiscal support for renewables, auction design, and marginal cost bidding in place unchanged would gradually lead to more instances of negative prices in the coming years. Conclusively, we discuss the implications of the observed phenomena on the energy policy.

Emotional Differences between Isomorphic Auctions

First price and Dutch auctions are theoretically isomorphic, but previous experiments report that the institutions are not behaviorally isomorphic. This article uses facial analysis of video recordings of laboratory experiments to investigate whether these auctions invoke different emotional responses from bidders. The results indicate that bidders are angrier during the Dutch auction and that winners exhibit more contempt after the first price auction. Overall, subjects in both auctions appear to be mostly bored and depressed, but there is evidence that bidders exhibit more positive emotions as prices fall in the Dutch auction.

How to design efficient renewable energy auctions? Empirical insights from Europe

An increasing number of countries use auctions to allocate support for renewable energies. One major objective of policymakers when designing auctions is support cost efficiency, i.e., achieving low awarded prices. Based on a holistic database with auction outcomes from Europe covering the years 2012–2020, we conduct a fixed effects panel data regression to assess the effects of several auction design elements on the awarded prices. According to our results, policymakers aiming for low prices in renewable energy auctions should avoid restricting auctions to small-scale projects, implement ceiling prices, and ensure high levels of competition. Multi-technology auctions can also lead to higher efficiency, while quotas should be avoided. While PV tends to achieve lower prices in auctions restricted to small-scale projects, onshore wind performs better in auctions open to large-scale projects. Feed-in premia, multi-criteria auctions and allowing bidders to deviate from their awarded project capacity show no significant impact. The introduction of financial prequalification requirements and the length of the realisation period should be chosen carefully, as their effects are interrelated. While our results for individual design elements are largely in line with existing literature, we are able to produce new insights on the interdependencies between various auction design elements.

Mechanism Design for Perturbation Stable Combinatorial Auctions

Motivated by recent research on combinatorial markets with endowed valuations by (Babaioff et al., EC 2018) and (Ezra et al., EC 2020), we introduce a notion of perturbation stability in Combinatorial Auctions (CAs) and study the extent to which stability helps in social welfare maximization and mechanism design. A CA is γ-stable if the optimal solution is resilient to inflation, by a factor of γ ≥ 1, of any bidder’s valuation for any single item. On the positive side, we show how to compute efficiently an optimal allocation for 2-stable subadditive valuations and that a Walrasian equilibrium exists for 2-stable submodular valuations. Moreover, we show that a Parallel 2nd Price Auction (P2A) followed by a demand query for each bidder is truthful for general subadditive valuations and results in the optimal allocation for 2-stable submodular valuations. To highlight the challenges behind optimization and mechanism design for stable CAs, we show that a Walrasian equilibrium may not exist for γ-stable XOS valuations for any γ, that a polynomial-time approximation scheme does not exist for (2 − ε)-stable submodular valuations, and that any DSIC mechanism that computes the optimal allocation for stable CAs and does not use demand queries must use exponentially many value queries. We conclude with analyzing the Price of Anarchy of P2A and Parallel 1st Price Auctions (P1A) for CAs with stable submodular and XOS valuations. Our results indicate that the quality of equilibria of simple non-truthful auctions improves only for γ-stable instances with γ ≥ 3.

A motivational local trading framework with 2-round auctioning and settlement rules embedded in smart contracts for a small citizen energy community

We propose a motivational local trading framework with a 2-round auctioning system and a novel settlement approach to stimulate local transactions on the electricity surplus of a small community. Two auction price systems and several settlement mechanisms are formulated and compared to assess local trading profit and local market efficiency. We also implement a SC-based mechanism that embeds the auction results and rules to increase trust in the bidding and settlement processes. Our simulations use actual consumption and generation data from 11 houses with smart appliances and self-generation capabilities. We show that auctions, if used consistently, can help the development of a local trade by encouraging people to buy from their neighbors and invest in more generating facilities, knowing that there is a local market on which to rely. Compared to the hybrid - Pay-as-Bid (PaB) in the 1st round plus Uniform Price (UP) in the 2nd round - approach, the pure 2-round UP auction was shown to decrease trading with the retailer by 7.5%. The market indicators are quite similar for the two pricing methods, whereas the proposed settlement mechanism reduces the buyers' payments by 7% and increases sellers' encashments by around 8%.

Price Formation in Auctions for Financial Transmission Rights

Financial Transmission Rights (FTRs) are financial derivatives in wholesale electricity markets that are sold in auctions. The revenue collected from FTR auctions is passed through to electricity customers to reimburse them for transmission congestion payments they make in the spot energy market. On average, electricity customers’ congestion payments greatly exceed auction reimbursements in electricity markets across the United States. We study the issue of auction revenue deficiency through the lens of Auction Revenue Rights (ARRs), which is the predominant mechanism used in U.S. electricity markets to distribute auction revenue to electricity customers. We demonstrate how the ARR process influences fundamental supply conditions in the FTR auction market and show how divergent auction equilibria emerge under different ARR decision-making regimes. Using market data from PJM, we find empirical evidence that variation in ARR management strategies helps explain differences between an FTR’s auction price and its realized ex post value.

Nonparametric estimation of first price auctions via density–quantile function

We propose a nonparametric estimator of bidders’ value function based on a kernel estimator of the density–quantile function of bids in first price auctions. This estimator provides certain advantage over the conventional approach that relies on the distribution/density ratio of the bids. We use a boundary-adaptive kernel for boundary bias correction and propose a practical method of bandwidth selection. Our numerical experiments demonstrate good performance of the proposed method in the estimation of first price auctions with risk neutral and risk averse bidders.

Auction Competitive Dynamics and Guide (List) Prices in a Bubble Market

The auction literature finds that competition drives price outcomes and has both rational and psychological components. In bubble markets, emotional factors are heightened, potentially impacting on the interaction between the strategic setting of guide prices by auctioneers, competitive bidding and final auction price outcomes, themes not explored in the extant literature. In a real estate bubble, we find evidence that auction prices anchor on guide prices and that any emotional impact on competitive bidding associated with auction fever does not occlude the assimilative role for the guide price as an anchor. Interestingly, however, we find evidence consistent with real estate agents systematically setting guide prices at deep discounts relative to fundamentals, prima facie consistent with a belief in the reversal-of-the-anchoring effect, suggesting their actions may, paradoxically, dampen the effect of the bubble rather than amplify it.

Bid signaling in first-price royalty auction

It is common that seller’s post-auction input affects winner’s valuation in the widely used royalty auctions. This study considers bidders’ signaling incentives and seller’s choice of reserve price in the first-price royalty auction. We first characterize the unique symmetric D1 PBE in which the quasi-separating bidding strategy can be decomposed into the equilibrium bid without signaling incentive and the signaling premium. The signaling premium increases in bidder’s type, indicating that a higher type has more incentive to raise bid to induce more effort from the seller. The optimal reserve price is lower than that under the post-auction complete information scenario, which leads to a more efficient allocation and a higher payoff for the seller. The optimal reserve price is non-monotonic in royalty rate while the seller’s equilibrium payoff increases in it, and full surplus extraction is obtained when the royalty rate approaches 100%.