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Journal articles on the topic 'Online reverse auctions'

Author: Grafiati

Published: 4 June 2021

Last updated: 13 February 2022

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1

Emiliani, M. L., and D. J. Stec. "Wood pallet suppliers' reaction to online reverse auctions." Supply Chain Management: An International Journal 10, no. 4 (2005): 278–87. http://dx.doi.org/10.1108/13598540510612758.

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PurposeThe purpose of this paper is to quantitatively assess wood pallet suppliers' reaction to online reverse auctions and its impact on their business policies and practices.Design/methodology/approachSurvey method was used to determine how pallet suppliers react to online reverse auctions.FindingsDetermines that pallet suppliers do not realize the benefits claimed by online reverse auction service providers. Identifies new sources of costs which accrue to buyers and are not accounted for in so‐called “total cost” request for quotes including: retaliatory pricing practices, less cooperative relationships, and sourcing work back to the original supplier. The qualitative benefits identified for suppliers by third‐party online reverse auction service providers are overstated or false.Research limitations/implicationsThe present work can be extended to other commodity categories to identify similarities and differences in how suppliers react to online reverse auctions, understand the domain of successful and unsuccessful application of the online reverse auction tool, and provide further insight into the evolution of buyer‐seller relationships, including embedded organizational routines such as power‐based bargaining.Practical implicationsFindings mirror the results found in a previous study that examined aerospace parts suppliers' reaction to online reverse auctions, and indicates that market makers have consistently overstated the benefits of online reverse auctions to both sellers and buyers, and the use of this tool will typically result in unfavorable outcomes for both buyers and sellers.Originality/valueThis paper will be of interest to buyers, sellers, and market makers, as it identifies important problems with online reverse auctions, and suggests questions that buyers should ask market makers to ensure better sourcing decisions.

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Mora Cortez, Roberto, and Wesley J. Johnston. "How to recover B2B relationships after a failed online reverse auction." Journal of Business & Industrial Marketing 35, no. 3 (2019): 551–63. http://dx.doi.org/10.1108/jbim-02-2019-0095.

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Purpose This paper aims to explore the possible scenarios after a failed reverse auction to continue a current buyer–seller relationship. Design/methodology/approach The authors developed a further understanding of reverse auctions through the examination of a longitudinal case study in the mining industry based on grounded theory. Findings The study indicates that losing a reverse auction is not a death sentence for the current supplier. Four factors influence the potential scenarios: buyer factors, supplier factors, buyer–seller factors and contextual factors. If the overall evaluation favors the current buyer–seller relationship, the supplier can continue the business interaction by full renegotiation or discrete step-by-step reconsideration. Conversely, the buyer–seller relationship would reach a state of dissolution. Originality/value This manuscript contributes to the understanding of reverse auction, an under-researched theme in organizational buying behavior theory. This paper is the first attempt to link buyer–seller relationship dissolution and reverse auctions. The authors suggest that more academic endeavors are needed to study online reverse auctions.

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Jap, Sandy D., and Ernan Haruvy. "Interorganizational Relationships and Bidding Behavior in Industrial Online Reverse Auctions." Journal of Marketing Research 45, no. 5 (2008): 550–61. http://dx.doi.org/10.1509/jmkr.45.5.550.

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The authors model (1) the impact of the supplier's relationship propensity before the auction on the supplier's bidding aggressiveness in the auction (in terms of the number of bids it submits, the rate at which the bids are submitted, and the price concessions offered) and (2) the impact of bidding behaviors in the auction on the buyer–supplier relationship after auction through longitudinal survey data from 12 online reverse auctions across various product categories. The results suggest that incumbency, many bidders, and a willingness to make specific investments lead to less aggressive bidding, whereas the total number of bids from competing suppliers increases aggressiveness. In turn, aggressive bidding behavior reduces suppliers' disposition toward developing a relationship with the buyer and sours incumbent satisfaction with the relationship. Finally, auctions that are longer in duration can improve the relationship but may risk bidding competition. Collectively, the results suggest that pricing and relationships are intertwined and traded off against each other in complex ways and that the auction does not operate in isolation of key organizational variables.

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A. Majid, Kashef, Andrew Bryant, and Pradeep A. Rau. "“Name your price” – online auctions and reference prices." Journal of Product & Brand Management 23, no. 6 (2014): 420–28. http://dx.doi.org/10.1108/jpbm-06-2014-0626.

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Purpose – This paper aims to investigate the presence of varying price points on the impact of product valuations in both English and reverse auctions on potential bidders, that is, those not yet engaged in the auction. Internet auctions, both English style and reverse, constitute one of the success stories of digital commerce. Design/methodology/approach – As its method of research, this paper uses an experimental approach to explore the effects of multiple reference prices. Findings – While previous research has done well to show that a lower initial price decreases barriers to entry and can lead to a higher final price in English-style auctions, this research shows that such a strategy may harm potential bidders’ product perceptions due to multiple reference prices. The authors explore situations of multiple reference prices in the context of reverse auctions, where both higher and lower reference prices are shown to be able to increase product valuations. Research limitations/implications – Additional research of a variety of products and using a representative sample would enhance the findings of this paper. Practical implications – The findings show that reference prices have differing impacts, which are dependent upon the goal of either maximizing or minimizing the distance between the initial price and the price consumers are willing to pay in an online auction. Originality/value – The investigation links differing goals created by the type of auction to the potential impact of the reference price. In addition, we explore the effects of multiple reference prices on consumer valuations.

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5

Emiliani, M. L., and D. J. Stec. "Realizing savings from online reverse auctions." Supply Chain Management: An International Journal 7, no. 1 (2002): 12–23. http://dx.doi.org/10.1108/13598540210414355.

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6

Jap, Sandy D. "An Exploratory Study of the Introduction of Online Reverse Auctions." Journal of Marketing 67, no. 3 (2003): 96–107. http://dx.doi.org/10.1509/jmkg.67.3.96.18651.

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Buyers are increasingly turning to online reverse auctions in their negotiations with suppliers. How do these price competition mechanisms affect buyer–supplier relationships? The author considers this question in the context of a quasi experiment involving six online reverse auctions conducted in the supply base of a major industrial buyer. The results indicate that these auctions increase both new and current suppliers’ beliefs that buyers act opportunistically, particularly in open-bid auctions. Current suppliers are generally more willing than new suppliers to make dedicated investments toward the buyer. Paradoxically, in sealed-bid auctions, both current and new suppliers increase their willingness to make dedicated investments toward the buyer. Although these auctions can yield cost savings, the savings are category specific and are not systematically related to an open- or sealed-bid format. The author also discusses implications for the use of online reverse auctions in industrial sourcing activities.

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7

Emiliani, M. L., and D. J. Stec. "Aerospace parts suppliers’ reaction to online reverse auctions." Supply Chain Management: An International Journal 9, no. 2 (2004): 139–53. http://dx.doi.org/10.1108/13598540410527042.

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8

Pham, Long, Jeffrey Teich, Hannele Wallenius, and Jyrki Wallenius. "Multi-attribute online reverse auctions: Recent research trends." European Journal of Operational Research 242, no. 1 (2015): 1–9. http://dx.doi.org/10.1016/j.ejor.2014.08.043.

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9

Schoenherr, Tobias, and Vincent A. Mabert. "Online reverse auctions: Common myths versus evolving reality." Business Horizons 50, no. 5 (2007): 373–84. http://dx.doi.org/10.1016/j.bushor.2007.03.003.

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10

Charki, Mohamed Hédi, and Emmanuel Josserand. "Online Reverse Auctions and the Dynamics of Trust." Journal of Management Information Systems 24, no. 4 (2008): 175–97. http://dx.doi.org/10.2753/mis0742-1222240407.

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11

Tayaran, Hojat, and Mehdi Ghazanfari. "A Framework for Online Reverse Auction Based on Market Maker Learning with a Risk-Averse Buyer." Mathematical Problems in Engineering 2020 (October 6, 2020): 1–13. http://dx.doi.org/10.1155/2020/5604246.

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The online reverse auction is considered as a new e-commerce approach to purchasing and procuring goods and materials in the supply chain. With the rapid and ever-expanding development of information technology as well as the increasing usage of the Internet around the world, the use of an online reverse auction method to provide the required items by organizations has increased. Accordingly, in this paper, a new framework for the online reverse auction process is provided that takes both sides of the procurement process, namely, buyer and seller. The proposed process is a multiattribute semisealed multiround online reverse auction. The main feature of the proposed process is that an online market maker facilitates the seller’s bidding process by the estimation of the buyer’s scoring function. For this purpose, a multilayer perceptron neural network was used to estimate the scoring function. In this case, in addition to hiding the buyer’s scoring function, sellers can improve their bids using the estimated scoring function and a nonlinear multiobjective optimization model. The NSGA II algorithm has been used to solve the seller model. To evaluate the proposed model, the auction process is simulated by considering three scoring functions (additive, multiplicative, and risk-aversion) and two types of open and semisealed auctions. The simulation results show that the efficiency of the proposed model is not significantly different from the open auction, and in addition, unlike the open auction, the buyer information was not disclosed.

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12

Schoenherr and Mabert. "Goal Orientation and Preparation Process in Online Reverse Auctions:." Transportation Journal 53, no. 4 (2014): 381. http://dx.doi.org/10.5325/transportationj.53.4.0381.

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13

Schoenherr, Tobias, and Vincent A. Mabert. "The use of bundling in B2B online reverse auctions." Journal of Operations Management 26, no. 1 (2007): 81–95. http://dx.doi.org/10.1016/j.jom.2007.05.001.

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14

Emiliani, M. L. "Executive decision‐making traps and B2B online reverse auctions." Supply Chain Management: An International Journal 11, no. 1 (2006): 6–9. http://dx.doi.org/10.1108/13598540610642411.

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15

Long, Pham, and Le Trung Thanh. "NegotiAuction." International Journal of Strategic Decision Sciences 7, no. 3 (2016): 70–85. http://dx.doi.org/10.4018/ijsds.2016070104.

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NegotiAuction, a computer system which combines aspects of auctions and negotiations, is expected to overcome limitations in online reverse auctions and multi-attribute online reverse auctions. However, no studies have been conducted to investigate its possible adoption. This study has drawn on an extensive review of literature on theories about innovation adoption, and has proposed a conceptual model for NegotiAuction adoption. Based on the structural equation modeling technique, both linear and non-linear effects on intention to use NegotiAuction were tested. The results show that perceived image was statistically significant in influencing perceived benefit and in turn perceived benefit was statistically significant in influencing intention to use. Practical implications and future studies are also discussed.

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16

Smart, Alan, and Alan Harrison. "Online reverse auctions and their role in buyer–supplier relationships." Journal of Purchasing and Supply Management 9, no. 5-6 (2003): 257–68. http://dx.doi.org/10.1016/j.pursup.2003.09.005.

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17

Jap, S. D. "Online Reverse Auctions: Issues, Themes, and Prospects for the Future." Journal of the Academy of Marketing Science 30, no. 4 (2002): 506–25. http://dx.doi.org/10.1177/009207002236925.

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18

Emiliani, M. L. "Regulating B2B online reverse auctions through voluntary codes of conduct." Industrial Marketing Management 34, no. 5 (2005): 526–34. http://dx.doi.org/10.1016/j.indmarman.2004.12.003.

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19

Schoenherr, Tobias. "Diffusion of online reverse auctions for B2B procurement: an exploratory study." International Journal of Operations & Production Management 28, no. 3 (2008): 259–78. http://dx.doi.org/10.1108/01443570810856189.

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20

Kumar, Sameer, and Megan Maher. "Are the temptations of online reverse auctions appropriate for your business?" Supply Chain Management: An International Journal 13, no. 4 (2008): 304–16. http://dx.doi.org/10.1108/13598540810882198.

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21

Emiliani, M. L. "Sourcing in the global aerospace supply chain using online reverse auctions." Industrial Marketing Management 33, no. 1 (2004): 65–72. http://dx.doi.org/10.1016/j.indmarman.2003.08.012.

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22

Hu, Ying, Yingjie Wang, Yingshu Li, and Xiangrong Tong. "An Incentive Mechanism in Mobile Crowdsourcing Based on Multi-Attribute Reverse Auctions." Sensors 18, no. 10 (2018): 3453. http://dx.doi.org/10.3390/s18103453.

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In order to avoid malicious competition and select high quality crowd workers to improve the utility of crowdsourcing system, this paper proposes an incentive mechanism based on the combination of reverse auction and multi-attribute auction in mobile crowdsourcing. The proposed online incentive mechanism includes two algorithms. One is the crowd worker selection algorithm based on multi-attribute reverse auction that adopts dynamic threshold to make an online decision for whether accept a crowd worker according to its attributes. Another is the payment determination algorithm which determines payment for a crowd worker based on its reputation and quality of sensing data, that is, a crowd worker can get payment equal to the bidding price before performing task only if his reputation reaches good reputation threshold, otherwise he will get payment based on his data sensing quality. We prove that our proposed online incentive mechanism has the properties of computational efficiency, individual rationality, budget-balance, truthfulness and honesty. Through simulations, the efficiency of our proposed online incentive mechanism is verified which can improve the efficiency, adaptability and trust degree of the mobile crowdsourcing system.

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23

Kim. "Online Reverse Auctions for Outsourcing Small Software Projects: Determinants of Vendor Selection." e-Service Journal 6, no. 3 (2009): 40. http://dx.doi.org/10.2979/esj.2009.6.3.40.

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24

Emiliani, M. L., and D. J. Stec. "Squaring online reverse auctions with the Caux Round Table Principles for Business." Supply Chain Management: An International Journal 7, no. 2 (2002): 92–100. http://dx.doi.org/10.1108/13598540210425849.

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25

Charki, Mohamed Hédi, Emmanuel Josserand, and Nabila Boukef Charki. "Toward an Ethical Understanding of the Controversial Technology of Online Reverse Auctions." Journal of Business Ethics 98, no. 1 (2010): 17–37. http://dx.doi.org/10.1007/s10551-010-0532-z.

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Sameer Kumar. "Is Your Supply Chain Business Operation a Good Fit for Online Reverse Auctions?" Transportation Journal 52, no. 1 (2013): 121. http://dx.doi.org/10.5325/transportationj.52.1.0121.

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Hatipkarasulu, Yilmaz, and James H. Gill. "Identification of shareholder ethics and responsibilities in online reverse auctions for construction projects." Science and Engineering Ethics 10, no. 2 (2004): 283–88. http://dx.doi.org/10.1007/s11948-004-0024-6.

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28

Sehwail, Loay M., Ricki G. Ingalls, and David B. Pratt. "Business-to-business online reverse auctions: a literature review and a call for research." International Journal of Services and Operations Management 4, no. 4 (2008): 498. http://dx.doi.org/10.1504/ijsom.2008.017432.

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29

Li, Zhipeng, Xiaoyu Zhou, and Shoujun Huang. "Managing skill certification in online outsourcing platforms: A perspective of buyer-determined reverse auctions." International Journal of Production Economics 238 (August 2021): 108166. http://dx.doi.org/10.1016/j.ijpe.2021.108166.

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30

Tsai, Kune-muh, and Feng-chin Chou. "Developing a Fuzzy Multi-attribute Matching and Negotiation Mechanism for Sealed-bid Online Reverse Auctions." Journal of theoretical and applied electronic commerce research 6, no. 3 (2011): 13–14. http://dx.doi.org/10.4067/s0718-18762011000300007.

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31

Wang, Shilei, Shaojian Qu, Mark Goh, M. I. M. Wahab, and Huan Zhou. "Integrated Multi-stage Decision-Making for Winner Determination Problem in Online Multi-attribute Reverse Auctions Under Uncertainty." International Journal of Fuzzy Systems 21, no. 8 (2019): 2354–72. http://dx.doi.org/10.1007/s40815-019-00757-0.

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32

Decarolis, Francesco, Maris Goldmanis, and Antonio Penta. "Marketing Agencies and Collusive Bidding in Online Ad Auctions." Management Science 66, no. 10 (2020): 4433–54. http://dx.doi.org/10.1287/mnsc.2019.3457.

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The transition of the advertising market from traditional media to the internet has induced a proliferation of marketing agencies specialized in bidding in the auctions that are used to sell ad space on the web. We analyze how collusive bidding can emerge from bid delegation to a common marketing agency and how this can undermine the revenues and allocative efficiency of both the generalized second-price auction (GSP, used by Google, Microsoft Bing, and Yahoo!) and the Vickrey–Clarke–Groves (VCG) mechanism (used by Facebook). We find that despite its well-known susceptibility to collusion, the VCG mechanism outperforms the GSP auction in terms of both revenues and efficiency. This paper was accepted by Gabriel Weintraub, revenue management and market analytics.

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Emiliani, M. L., and D. J. Stec. "Online reverse auction purchasing contracts." Supply Chain Management: An International Journal 6, no. 3 (2001): 101–5. http://dx.doi.org/10.1108/13598540110399066.

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34

Li, Ao, Zhaoman Wan, and Zhong Wan. "Optimal Design of Online Sequential Buy-Price Auctions with Consumer Valuation Learning." Asia-Pacific Journal of Operational Research 37, no. 03 (2020): 2050012. http://dx.doi.org/10.1142/s0217595920500128.

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Buy-price auction has been successfully used as a new channel of online sales. This paper studies an online sequential buy-price auction problem, where a seller has an inventory of identical products and needs to clear them through a sequence of online buy-price auctions such that the total profit is maximized by optimizing the buy price in each auction. We propose a methodology by dynamic programming approach to solve this optimization problem. Since the consumers’ behavior affects the seller’s revenue, the consumers’ strategy used in this auction is first investigated. Then, two different dynamic programming models are developed to optimize the seller’s decision-making: one is the clairvoyant model corresponding to a situation where the seller has complete information about consumer valuations, and the other is the Bayesian learning model where the seller makes optimal decisions by continuously recording and utilizing auction data during the sales process. Numerical experiments are employed to demonstrate the impacts of several key factors on the optimal solutions, including the size of inventory, the number of potential consumers, and the rate at which the seller discounts early incomes. It is shown that when the consumers’ valuations are uniformly distributed, the Bayesian learning model is of great efficiency if the demand is adequate.

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35

Zhang, Hongkun, and Xinmin Liu. "Reverse Auction-Based Services Optimization in Cloud Computing Environments." Security and Communication Networks 2021 (March 17, 2021): 1–10. http://dx.doi.org/10.1155/2021/6666628.

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Cloud-based services have been increasingly used to provide on-demand access to a large amount of computing requests, such as data, computing, resources, and so on, in which it is vitally important to correctly select and assign the right resources to a workload or application. This paper presents a novel online reverse auction scheme based on online algorithm for allocating the cloud computing services, which can help the cloud users and providers to build workflow applications in a cloud computing environment. The online reverse auction scheme consists of three parts: online algorithm design, competitive ratio calculation, and performance valuation. The online reverse auction-based algorithm is proposed for the cloud user agent to choose the final winners based on Vickrey–Clarke–Groves (VCG) mechanism and online algorithm (OA). The competitive analysis is applied to calculate the competitive ratio of the proposed algorithm compared with the offline algorithm. This analysis method is significant to measure the performance of proposed algorithm, without the assumption of the distribution of cloud providers’ bids. The results prove that the proposed online reverse auction-based algorithm is the appropriate mechanism because it allows the cloud user agent to make purchase decisions without knowing the future bids. The difference of auction rounds and transaction cost can impressively influence and improve the performance of the proposed reverse auction algorithm.

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36

Zhou, Yan Yue, Chen Li, and Ge Zhu. "Online Multi-Attribute Reverse Auction Mechanism Design Based on Utility." Advanced Engineering Forum 1 (September 2011): 405–10. http://dx.doi.org/10.4028/www.scientific.net/aef.1.405.

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A good auction mechanism is able to release the information who owns to the other side who lacks of. In order to ensure a positive flow of information and to improve the active participation of suppliers, negotiation mechanism is introduced, and suppliers can participate in the design of auction mechanism. Several rounds of English auction is applied to determining the final winner. Taking into account that the buyer has a preference on the property, we use AHP to calculate final weights, and use multi-attribute utility function to calculate the greatest utility as the winner.

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Lin, Chia-Chen, Ya-Fen Chang, Chin-Chen Chang, and Yao-Zhu Zheng. "A Fair and Secure Reverse Auction for Government Procurement." Sustainability 12, no. 20 (2020): 8567. http://dx.doi.org/10.3390/su12208567.

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With the development of e-commerce, the electronic auction is attracting the attention of many people. Many Internet companies, such as eBay and Yahoo!, have launched online auction systems. Many researchers have studied the security problems of electronic auction systems, but few of them are multi-attribute-based. In 2014, Shi proposed a provable secure, sealed-bid, and multi-attribute auction protocol based on the semi-honest model. We evaluated this protocol and found that it has some design weaknesses and is vulnerable to the illegal operations of buyers, which results in unfairness. In this paper, we improved this protocol by replacing the Paillier’s cryptosystem with the elliptic curve discrete (ECC), and we designed a novel, online, and multi-attribute reverse-auction system using the semi-honest model. In our system, sellers’ identities are not revealed to the buyers, and the buyers cannot conduct illegal operations that may compromise the fairness of the auction.

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38

Tu, Yanbin, James R. Shock, and Joe Z. Shangguan. "Online Auction Market of Preannounced Product." International Journal of Online Marketing 9, no. 2 (2019): 39–52. http://dx.doi.org/10.4018/ijom.2019040104.

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This article examines how an online auction of a preannounced product, the Microsoft Xbox 360, proceeds and performs before its official launch on eBay. Data from the eBay marketplace is examined after the date of the preannouncement in May 2005 until the launch in November 2005. Specifically, the authors look to see if auction success rates from one day affect the success rates on the following day. They also examine if the winning bid prices of one day affect the winning bids on the following day. The results show that auction success rates on one day do not have a significant impact on the following day's success rates. Regarding winning bid prices, there is strong evidence that the winning price series is a nonstationary process, and daily prices show a reverse trending pattern. The authors discuss the managerial implications of their findings.

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39

Caldentey, René, and Gustavo Vulcano. "Online Auction and List Price Revenue Management." Management Science 53, no. 5 (2007): 795–813. http://dx.doi.org/10.1287/mnsc.1060.0646.

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40

Rosenkrans, Ginger. "Online Auctions as Advertising Revenue in the Media Mix." Journal of Interactive Advertising 6, no. 1 (2005): 14–28. http://dx.doi.org/10.1080/15252019.2005.10722104.

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41

Aloini, Davide, Riccardo Dulmin, and Valeria Mininno. "E‐reverse auction design: critical variables in a B2B context." Business Process Management Journal 18, no. 2 (2012): 219–49. http://dx.doi.org/10.1108/14637151211225180.

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PurposeThis paper attempts to provide an empirical cross‐industrial study on critical success factors impacting on “price” and “process” performance in business‐to‐business (B2B) e‐reverse auction design.Design/methodology/approachBased on an online survey to a panel of academic experts and practitioners, the paper presents the empirical validation of a previous conceptual model using a confirmatory factor analysis (CFA) approach.FindingsResults demonstrate that a multi facet construct consisting of six main dimensions impacts on e‐auction performance. Moreover, these dimensions differently impact on price and process performance.Research limitations/implicationsBecause of the complexity of the framework, the sample size and the qualitative nature of experts' observations, results should be seen as more indicative than conclusive and therefore generalization should be additionally tested.Practical implicationsFindings provide useful information for the formulation of managerial decisions in designing the auction event/process and supporting the definition of different negotiation strategies.Originality/valueThis article is a first attempt to test a conceptual framework on critical factors impacting on e‐reverse auction performance in a B2B context. A lot of conceptual papers try to systematize the numerous variables affecting e‐auction success and their complex relationships into a single comprehensive framework; nevertheless there is a lack of empirical evidence supporting these models especially in the B2B context.

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42

Bimpikis, Kostas, Wedad J. Elmaghraby, Ken Moon, and Wenchang Zhang. "Managing Market Thickness in Online Business-to-Business Markets." Management Science 66, no. 12 (2020): 5783–822. http://dx.doi.org/10.1287/mnsc.2019.3497.

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We explore marketplace design in the context of a business-to-business platform specializing in liquidation auctions. Even when the platform’s aggregate levels of supply and demand remain fixed, we establish that the platform’s ability to use its design levers to manage the availability of supply over time yields significant value. We study two such levers, each using the platform’s availability of supply as a means to incentivize participation from buyers who decide strategically when/how often to participate. First, the platform’s listing policy sets the ending times of incoming auctions (hence, the frequency of market clearing). Exploiting a natural experiment, we illustrate that consolidating auctions’ ending times to certain weekdays increases the platform’s revenues by 7.3% mainly by inducing a higher level of bidder participation. The second lever is a recommendation system that can be used to reveal information about real-time market thickness to potential bidders. The optimization of these levers highlights a novel trade-off. Namely, when the platform consolidates auctions’ ending times, more bidders may participate in the marketplace (demand-side competition); but ultimately auctions for substitutable goods cannibalize one another (supply-side competition). To optimize these design decisions, we estimate a structural model that endogenizes bidders’ dynamic behavior, that is, their decisions on whether/how often to participate in the marketplace and how much to bid. We find that appropriately designing a recommendation system yields an additional revenue increase (on top of the benefits obtained by optimizing the platform’s listing policy) by reducing supply-side cannibalization and altering the composition of participating bidders. This paper was accepted by Vishal Gaur, operations management.

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Chu, Leon Yang, Hamid Nazerzadeh, and Heng Zhang. "Position Ranking and Auctions for Online Marketplaces." Management Science 66, no. 8 (2020): 3617–34. http://dx.doi.org/10.1287/mnsc.2019.3372.

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Online e-commerce platforms, such as Amazon and Taobao, connect thousands of sellers and consumers every day. In this work, we study how such platforms should rank products displayed to consumers and utilize the top and most salient slots. We present a model that considers consumers’ search costs and the externalities sellers impose on each other. This model allows us to study a multiobjective optimization, whose objective includes consumer and seller surplus as well as the sales revenue, and derive the optimal ranking decision. In addition, we propose a surplus-ordered ranking mechanism for selling some of the top slots. This mechanism is motivated in part by Amazon’s sponsored search program. We show that the Vickrey–Clarke–Groves mechanism would not be applicable to our setting and propose a new mechanism. This mechanism is near optimal, performing significantly better than those that do not incentivize sellers to reveal their private information regarding each consumer purchase, such as their profit. Moreover, we generalize our model to settings in which platforms can provide partial information about the products and facilitate the consumer search and show the robustness of our findings. This paper was accepted by David Simchi-Levi, operations management.

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44

Jap, Sandy D. "The Impact of Online Reverse Auction Design on Buyer–Supplier Relationships." Journal of Marketing 71, no. 1 (2007): 146–59. http://dx.doi.org/10.1509/jmkg.71.1.146.

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Kanoria, Yash, and Hamid Nazerzadeh. "Incentive-Compatible Learning of Reserve Prices for Repeated Auctions." Operations Research 69, no. 2 (2021): 509–24. http://dx.doi.org/10.1287/opre.2020.2007.

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How can an auctioneer optimize revenue by learning the reserve prices from the bids in the previous auctions? How should the long-term incentives and strategic behavior of the bidders be taken into account? Motivated in part by applications in online advertising, in “Incentive-Compatible Learning of Reserve Prices for Repeated Auctions,” Kanoria and Nazerzadeh investigate these questions. They show that if a seller attempts to dynamically update a common reserve price using the bidding history, buyers will shade their bids, which can hurt the revenue. However, when there is more than one buyer, using personalized reserve prices, the auctioneer can achieve a near-optimal revenue. In their proposed mechanism, the personal reserve price for each buyer is determined using the historical bids of other buyers.

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Boukef, Nabila, Paul W. L. Vlaar, Mohamed-Hédi Charki, and Anol Bhattacherjee. "Understanding Online Reverse Auction Determinants of Use: A Multi-Stakeholder Case Study." Systèmes d'information & management 21, no. 1 (2016): 7. http://dx.doi.org/10.3917/sim.161.0007.

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ZHAO, Bin. "Approach to allocate computational grid resources based on online reverse auction technology." Journal of Computer Applications 28, no. 2 (2008): 283–85. http://dx.doi.org/10.3724/sp.j.1087.2008.00283.

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Yu, Ya-Wen, Chia-Li Lee, and Hsiao-Cheng Yu. "B2B online reverse auction: factors that affect the e-procurement performance in Taiwan." Journal of Information and Optimization Sciences 28, no. 4 (2007): 505–21. http://dx.doi.org/10.1080/02522667.2007.10699757.

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Othman, Muhaini, Siti Najiha Shamsudin, Mohd Hafizul Afifi Abdullah, Munirah Mohd Yusof, and Rozlini Mohamed. "iBid: A Competitive Bidding Environment for Multiscale Tailor." JOIV : International Journal on Informatics Visualization 1, no. 4-2 (2017): 256. http://dx.doi.org/10.30630/joiv.1.4-2.81.

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Nowadays, various online auction web services are available, allowing people to bid on items to be purchased at a competitive price. The same approach is applicable to allow people to bid on projects on Freelancer website. Here, we present an environment for customers to publish a project online, whereby marketers are able to bid on projects, called the iBid system. The iBid system demonstrates an application of bidding system which is capable of assisting customers find local tailors according to three criteria namely location, type of sewing and cost. Reversed auction mechanism is used where the customer will control the business. The prototyping methodology approach has been used to develop the system running on a PHP server and a MySQL database.

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Lee, Ho Mu, and Byong Hun Ahn. "When more bidders count less: item characteristics and sellers' revenue in online auctions." International Journal of Electronic Business 6, no. 5 (2008): 498. http://dx.doi.org/10.1504/ijeb.2008.021184.

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