Auction Method Research Articles

Experimental approach to assessing actual wine purchase behavior

PurposeThe use of intentions to forecast behavior follows from the assumption that intentions are a strong indicator of an individual's actual purchase behavior. Yet most studies found the relationship between intent and actual behavior varies considerably. The purpose of this study was to explore how marketers should combine expressed measures of intention with other available data to forecast the probability of purchase and thus to set pricing decisions.Design/methodology/approachThrough a two‐stage approach, this study measured consumer psychographics and expressed purchase intention to predict actual purchase behavior using an online survey, the Vickrey auction method, and logistic regression.FindingsThe results found that individuals' attitudes and intentions are strong predictors of actual behavior. However, of particular interest are lower‐purchase‐intention individuals, who acted in line with their expressed willingness to pay more than individuals with higher purchase intentions.Research limitations/implicationsThe study was restricted to the investigation of one product. The model should be tested with different styles of wine products purchased on a regular basis.Practical implicationsMost product positioning research focuses on individuals who express high levels of purchase intention, positive attitudes, and positive values. However, basing a wine product's pricing on a high‐purchase‐intention group may lead to an overpriced product and a lack of follow‐through on the part of consumers.Originality/valueResults suggest a new method to approach purchase intention using a combination of actual purchase data and survey data.

Actuator Task Assignment Based on Auction Method in Wireless Sensor and Actuator Networks

A typical Wireless Sensor Network (WSN) only performs the action of sensing the environment, the needs of smart interaction with the environment have led to the emergence of Wireless Sensor and Actuator Network (WSAN). With the presence of actuators, WSAN is heterogeneous, which brings about new challenges that need to be addressed. In this paper, the task assignment of actuators in overlapping area is studied. Firstly, a new utility function is defined, which is the standard to choose the proper action actuators in overlapping area. Then, based on the new utility function, a distributed solution called localized auction method to solve task assignment problem in overlapping area is proposed. Simulation results demonstrate that the proposed auction method can assign tasks to the unique actuator and meet the action completion bound.

Scrambling for Slaves: Captive Sales in Colonial South Carolina

Based in part on previously neglected sales records, this article offers the first detailed analysis of slave sales by the method known as ‘the scramble’. In eighteenth-century South Carolina, the scramble was the preferred sales mechanism for newly arrived Africans, with auction sales generally reserved for slaves already in the colony. Analysis of the sales and other records suggest that the scramble was an economically rational way to sell imported slaves, but that it fell out of favor after the American Revolution as problems of currency and credit rendered it too cumbersome. The article concludes by proposing that the scramble helped to shape colonial slave society by allowing poorer whites greater access to slaves than the auction method.

An Efficient Stochastic Clustering Auction for Heterogeneous Robotic Collaborative Teams

Stochastic Clustering Auctions (SCAs) constitute a class of cooperative auction methods that enable improvement of the global cost of the task allocations obtained with fast greedy algorithms. Prior research had developed Contracts Sequencing Algorithms (CSAs) that are deterministic and enable transfers, swaps, and other types of contracts between team members. In contrast to CSAs, SCAs use stochastic transfers or swaps between the task clusters assigned to each team member and have algorithm parameters that can enable tradeoffs between optimality and computational and communication requirements. The first SCA was based on a "Gibbs Sampler" and constrained the stochastic cluster reallocations to simple single transfers or swaps; it is applicable to heterogeneous teams. Subsequently, a more efficient SCA was developed, based on the generalized Swendsen-Wang method; it achieves the increased efficiency by connecting tasks that appear to be synergistic and then stochastically reassigning these connected tasks, hence enabling more complex and efficient movements between clusters than the first SCA. However, its application was limited to homogeneous teams. The contribution of this work is to present an efficient SCA for heterogeneous teams; it is based on a modified Swendsen-Wang method. For centralized auctioning and homogeneous teams, extensive numerical experiments were used to provide a comparison in terms of costs and computational and communication requirements of the three SCAs and a baseline CSA. It was seen that the new SCA maintains the efficiency of the second SCA and can yield similar performance to the baseline CSA in far fewer iterations. The same metrics were used to evaluate the performance of the new SCA for heterogeneous teams. A distributed version of the new SCA was also evaluated in numerical experiments. The results show that, as expected, the distributed SCA continually improves the global performance with each iteration, but converges to a higher cost solution than the centralized SCA. The final discussion outlines a systematic procedure to use SCA in various aspects of the application of multi-robot cooperative systems.

Auction Approaches for Resource Allocation in Wireless Systems: A Survey

As wireless systems evolve with new mobile technologies, they tend to become complicated in terms of architectures and managements. Auction theory, as a subfield of economics and business management, has been introduced to provide an interdisciplinary technology for radio resource allocation (e.g., subchannels, time slots, and transmit power levels) in the wireless systems. By using various auction approaches, such radio resources are efficiently allocated among users and providers of services in the systems. Participants (i.e., users and providers) of an auction have their own strategies that follow the incentives and rules brought by the auction. Auction methods are widely employed in areas such as cognitive radio, cellular networks, and wireless mesh networks. This paper gives a comprehensive survey of recent auction approaches (i.e., auction-based applications and mechanisms) applied in wireless and mobile systems. First, auction theory and different types of auction are introduced. The motivation of using auction in wireless systems is given. Then, the reviews of auction approaches applied in the single-hop and multi-hop wireless networks are provided. Finally, the open research issues are discussed.

Auction Methods of Homogeneous Goods such as Mine and Energy Material

Multi-object auctions usually involve the sale of many homogeneous or heterogeneous objects. Aiming at homogeneous goods auction (such as mine auction, energy material auction), this paper introduces the research history and the newest research trends, and presents many widespread theoretical and applications problems. Moreover, assumptions, main ideas, and conclusions of literature related to homogeneous goods auction are reviewed and commented.

Auction Mechanism and Methods for Heterogeneous Goods Such as Multiple Polymer Materials

Multi-object auctions can be divided into homogeneous goods auction and heterogeneous goods auction. In this paper, the auction mechanism and methods for heterogeneous goods such as multiple polymer materials (rubber, plastic, polymer fibre, adhesive, polymer coating) is investigated. Concretely, the research history and the newest research trends are introduced, and many widespread theoretical and applied problems are presented. In addition, assumptions, main ideas, and conclusions of literature related to heterogeneous goods auction are commented and reviewed.

DECENTRALIZED SUPPLY CHAIN FORMATION USING MAX‐SUM LOOPY BELIEF PROPAGATION

Supply chain formation is the process by which a set of producers within a network determine the subset of these producers able to form a chain to supply goods to one or more consumers at the lowest cost. This problem has been tackled in a number of ways, including auctions, negotiations, and argumentation‐based approaches. In this paper we show how this problem can be cast as an optimization of a pairwise cost function. Optimizing this class of energy functions is NP‐hard but efficient approximations to the global minimum can be obtained using loopy belief propagation (LBP). Here we detail a max‐sum LBP‐based approach to the supply chain formation problem, involving decentralized message‐passing between supply chain participants. Our approach is evaluated against a well‐known decentralized double‐auction method and an optimal centralized technique, showing several improvements on the auction method: it obtains better solutions for most network instances which allow for competitive equilibrium (Competitive equilibrium in Walsh and Wellman is a set of producer costs which permits a Pareto optimal state in which agents in the allocation receive non‐negative surplus and agents not in the allocation would acquire non‐positive surplus by participating in the supply chain) while also optimally solving problems where no competitive equilibrium exists, for which the double‐auction method frequently produces inefficient solutions.

Centralized and distributed task allocation in multi-robot teams via a stochastic clustering auction

This article considers the problem of optimal task allocation for heterogeneous teams, for example, teams of heterogeneous robots or human-robot teams. It is well-known that this problem is NP-hard and hence computationally feasible approaches must develop an approximate solution. Here, we propose a solution via a Stochastic Clustering Auction (SCA) that uses a Markov chain search process along with simulated annealing. This is the first stochastic auction method used in conjunction with global optimization. It is based on stochastic transfer and swap moves between the clusters of tasks assigned to the various robots and considers not only downhill movements, but also uphill movements, which can avoid local minima. A novel feature of this algorithm is that, by tuning the annealing suite and turning the uphill movements on and off, the global team performance after algorithm convergence can slide in the region between the global optimal performance and the performance associated with a random allocation. Extensive numerical experiments are used to evaluate the performance of SCA in terms of costs and computational and communication requirements. For centralized auctioning, the SCA algorithm is compared to fast greedy auction algorithms. Distributed auctioning is then compared with centralized SCA.

Multi-robot coalition formation in real-time scenarios

Task allocation is one of the main issues to be addressed in multi-robot systems, especially when the robots form coalitions and the tasks have to be fulfilled before a deadline. In general, it is difficult to foresee the time required by a coalition to finish a task because it depends, among other factors, on the physical interference. Interference is a phenomenon produced when two or more robots want to access the same point simultaneously. This paper presents a new model to predict the time to execute a task. Thanks to this model, the robots needed to carry out a task before a deadline can be determined. Within this framework, the robots learn the interference and therefore, the coalition’s utility, from their past experience using an on-line Support Vector Regression method (SVR). Furthermore, the SVR model is used together with a new auction method called ’Double Round auction’ (DR). It will be demonstrated that by combining the interference model and the DR process, the total utility of the system significantly increases compared to classical auction approaches. This is the first auction method that includes the physical interference effects and that can determine the coalition size during the execution time to address tasks with deadlines. Transport like tasks run on a simulator and on real robots have been used to validate the proposed solutions.

Fuzzy Logic and Interval Arithmetic-Based TOPSIS Method for Multicriteria Reverse Auctions

Most of the existing reverse auction methods are restricted to the price dimension and assume that the qualitative criteria are fixed prior to competitive source selection. Multicriteria reverse auctions (MCRAs) facilitate the negotiation of price and other qualitative and quantitative criteria. In this paper, the winner determination (WD) problem of MCRAs is formulated as a multicriteria decision-making problem. An extension of the TOPSIS (technique for order preference by similarity to ideal solution) method based on fuzzy logic and interval arithmetic is proposed to solve the WD problem where some attributes are qualitative and imprecise in nature and others are quantitative but difficult to represent in precise numerical values. In some cases, precise values are inadequate to model the criteria in real life. Moreover, because of the personalities of human beings, the decision is based less on information and more on personal judgments, resulting in a biased decision. Therefore, fuzzy linguistic variables are used here to map qualitative criteria, and at the same time intervals, data are used for quantitative preferences that are difficult to represent in exact numerical values. The correlation coefficient and standard deviation integrated method is used for automatic enumeration of the criteria weights, and a mechanism is also developed to determine the preferences of qualitative criteria using fuzzy linguistic variables. We present illustrative example to demonstrate the applicability of the proposed method.

Hybrid Genetic Algorithms for Solving Winner Determination Problem in Combinatorial Double Auction in Grid

Nowadays, since grid has been turned to commercialization, using economic methods such as auction methods are appropriate for resource allocation because of their decentralized nature. Combinatorial double auction has emerged as a major model in the economy and is a good approach for resource allocation in which participants of grid, give their requests once to the combination of resources instead of giving them to different resources multiple times. One problem with the combinatorial double auction is the efficient allocation of resources to derive the maximum benefit. This problem is known as winner determination problem (WDP) and is an NP-hard problem. So far, many methods have been proposed to solve this problem and genetic algorithm is one of the best ones. In this paper, two types of hybrid genetic algorithms were presented to improve the efficiency of genetic algorithm for solving the winner determination problem. The results showed that the proposed algorithms had good efficiency and led to better answers. DOI: http://dx.doi.org/10.11591/ij-ai.v1i2.443

A Continues Double Auction Method for Resource Allocation in Economic Grids

Sharing and optimized usage of resources utilities are one of the most essential goals in Grid systems. In such environments, patterns and aims of the resource providers and users for supply/demand differ. Beside, resource allocation algorithms attempt to provide the condition in which firstly providers are encouraged to keep on sharing their own computing resources and secondly the users are promoted to use the available resources to execute their jobs. Resource allocation ability to satisfy both sides, along with considering the users and providers mutual benefits, is a challenging task in grid market places. By a method suggested in this paper Continuous Double Auction, which is one of the most used methods in grid marketing, is improved through updating bids by the auctioneer itself. Also in this paper a method is presented for the providers to determine the resource price based on their workload and for users to determine their bids based on jobs deadlines. The results show an improvement in both economic utilization and scheduling utilization compared to the standard Continuous Double Auction.

An experimental analysis of Colonel Blotto Games under alternative environments

Bu makalede, bir savas alani ya da pazara daha fazla birlik ya da kaynak tahsis eden oyuncunun o alani kesinlikle kazanacagi ilkesine dayanan, muzayede yontemi ile isleyen ve tam bilgi ile tanimli bir deney tasarlanmistir. Makaledeki tasarimin mevcut literature katkisi, ayni oyuncunun bu oyunu ardi sira degisen alternatif karar durumlarinda (simetrik ve asimetrik kaynaklar, farkli sayida savas alani), rasyonel bir oyuncu olan bilgisayara karsi oynamasidir. Teorik beklentilerle uyumlu olarak; oyuncularin esit veya daha fazla kaynaga sahip olduklari durumda cogunlukla ‘tumuyle kapsama’ stratejisini, rakiplerinden daha az kaynaga sahip olduklarinda ise cogu zaman ‘gerilla’ stratejisini uyguladiklari saptanmistir. Ayrica, rakibiyle esit veya daha fazla kaynaga sahip olan oyuncularin gorece daha basarili olduklari gozlenmistir. Son olarak hem belirli bir oyun icinde, hem de benzer oyunlar arasinda, oyuncularin denge davranisini yineleme baglaminda kendilerini gelistirdikleri gozlemlenmis ve bu gelisimin ‘ogrenme’ argumani ile aciklanabilecegi sonucuna varilmistir.

An effective early fraud detection method for online auctions

While online auctions continue to increase, so does the incidence of online auction fraud. To avoid discovery, fraudsters often disguise themselves as honest members by imitating normal trading behaviors. Therefore, maintaining vigilance is not sufficient to prevent fraud. Participants in online auctions need a more proactive approach to protect their profits, such as an early fraud detection system. In practice, both accuracy and timeliness are equally important when designing an effective detection system. An instant but incorrect message to the users is not acceptable. However, a lengthy detection procedure is also unsatisfactory in assisting traders to place timely bids. The detection result would be more helpful if it can report potential fraudsters as early as possible. This study proposes a new early fraud detection method that considers accuracy and timeliness simultaneously. To determine the most appropriate attributes that distinguish between normal traders and fraudsters, a modified wrapper procedure is developed to select a subset of attributes from a large candidate attribute pool. Using these attributes, a complement phased modeling procedure is then proposed to extract the features of the latest part of traders’ transaction histories, reducing the time and resources needed for modeling and data collection. An early fraud detection model can be obtained by constructing decision trees or by instance-based learning. Our experimental results show that the performance of the selected attributes is superior to other attribute sets, while the hybrid complement phased models markedly improve the accuracy of fraud detection.

The impact of timber-sale tract, policy, and administrative characteristics on state stumpage prices: An econometric analysis

An econometric analysis was conducted to assess how tract, policy, and administrative factors of public timber sales influence willingness to pay for stumpage. To do so, we obtained an electronic database containing multiple years of MN DNR timber-sale records. Each record contained information on the timber sale's total appraised volume, species-product composition, tract acres, date of sale, date of sale expiration, method of sale, purchasing firm, and tract location. A total of 4,395 records of MN DNR timber tracts sold from 2001 to 2006 were analyzed. By incorporating physical, ecological, policy, and administrative factors of a timber sale, our model was able to explain approximately 63% of the variation in the natural log of stumpage prices. Sale-specific characteristics found to be significant drivers of stumpage prices are species-product composition, tract location, end-product market conditions, season of sale, harvestable volume density, length of the sale contract, seasonal operating restrictions, total appraised volume, and auction method.

Assessing the Performance of Chinese Land Lease Auctions: Evidence from Beijing

This paper investigates the pricing impact of the Chinese land lease auction method when compared to non-auction methods. Using land lease transactions in Beijing from 2003 to 2010, we show that, after controlling for land characteristics, the selling mechanism matters and that the auction method yields a higher land lease transaction price than non-auction selling mechanisms. More importantly, bidder type significantly affects the auction premium. This evidence seems to indicate that the results of an auction might be predictable from the bidder composition of the auction.

Evaluación de preferencias hacia las mandarinas en el mercado británico. Aplicación de las subastas Vickrey

The objective of this work is to analyse British consumer preferences towards five varieties of mandarins (two of them from Spain) under three different information conditions: visual inspection, peeling and consumption. Therefore, the paper deals with the purchase process from two perspectives: before and after experiencing the product and considering both search and experience attributes. Besides, it is intended to study the market possibilities of the Spanish varieties in British market. The research employed the second price Vickrey experimental auction method using two treatments applied to different subgroups of the total sample. Half of the groups evaluated the fruit characteristics at each stage of the experimental process before making the auction bids while the other half of the groups offered bids without giving an evaluation of the fruit. Main results are: (1) significant changes in evaluation and willingness to pay for mandarins as consumer move forward the purchase-consumption process, (2) both experimental groups behaved similarly, (3) juiciness, sweetness and acidity are the attributes most closely correlated with the overall evaluation of the different varieties, (4) Spanish varieties are well evaluated, but only after consumption. The main recommendation for Spanish citrus producer is to find a way to communicate Spanish mandarin excellence in some search attributes, which cannot be evaluated by visual inspection, but are significant at post-purchase valuation.

Thai Consumers Willingness to Pay for Food Products with Geographical Indications

Geographical Indication (GI) is a name, or sign, that refers to a specific characteristic of geographical location or origin. GI is used to both protect and guarantee that the product has a unique characteristic, resulting from being qualifiedly produced in a specific place. There are many products in Thailand that have been certified by the Ministry of Commerce, carrying the GI label. The purpose of conducting this research is to study Thai consumers’ willingness to pay (WTP) for products with GI labels. This experiment was carried out under the nth price auction method on Doi Tung coffee, Tung Kula Ronghai Thai Hom Mali rice, and Chaiya salted eggs. Sixty participants were asked to offer bids for three products each with different types of labels, a normal label; a label stating the product’s origin; and a label which stated the product’s origin and contained a GI sign. The results show that Thai consumers’ WTPs are influenced by the origin of the product. However, the WTPs of GI labels do not significantly differ from the WTPs of labels which state the product’s origin. This implies that Thai consumers value the product’s origin, but do not recognize the importance of the GI label.

Numerical simulations of asymmetric first-price auctions

The standard method for computing the equilibrium strategies of asymmetric first-price auctions is the backward-shooting method. In this study we show that the backward-shooting method is inherently unstable, and that this instability cannot be eliminated by changing the numerical methodology of the backward solver. Moreover, this instability becomes more severe as the number of players increases. We then present a novel boundary-value method for computing the equilibrium strategies of asymmetric first-price auctions. We demonstrate the robustness and stability of this method for auctions with any number of players, and for players with mixed types of distributions, including distributions with more than one crossing. Finally, we use the boundary-value method to study large auctions with hundreds of players, to compute the asymptotic rate at which large first-price and second-price auctions become revenue equivalent, and to study auctions in which the distributions cannot be ordered according to first-order stochastic dominance.