Research on Bidding Game and Its Application Based on Copetition Scenario

Bidding decision is not only a science, an art, but also a game. The more intense the competition, the more important the game. In practice, there is the possibility of collaboration between bidders and even hidden competing behaviors such as bidding rigging. In this study, the optimized low-price bid winning method was discussed, and the characteristics and application of the bidding game under the copetition scenarios were studied. The results show the following: (1) Under the copetition scenario, the rational bidding behavior of bidders will deviate according to the different information advantages, and there is a game of making bidding strategy decisions according to the competitive scenario. (2) There is a close functional relationship between the winning bid result and the evaluation elimination factor, the number of bidders, and the number of bidders who operate bidding rigging. (3) Based on the quotation strategy matrix modeling, it enables the quantitative decision making bid amount, offer score, and deviation risk. This study enriches the theory of quota decision in copetition scenarios and is enlightening for similar business behavior game decisions.

Optimal Electricity Allocation Model Under China's Planning-Market Double-Track Mechanism Considering Bidding Game of Generation Companies

In China, under the planning-market double-track mechanism implemented on the generation side of electricity, unreasonable market-oriented power generation proportion may lead to unnecessary vicious competition and market price changes, and it is against the will of power exchange (PX). Given this background, in this study, a bi-level model for planning-market electricity allocation that considers the bidding game of generation companies is proposed for a smooth transition of power system reform. In the upper level of the model, the proportion of planned electricity is optimized by PX to minimize the average social electricity purchase price. In the lower level of the model, considering the impact of market power on the bidding strategy of generation companies, the bidding strategy of generation companies set as price makers is proposed using the residual demand curve analysis method, while the price takers adopt the lowest bidding strategy. Simulations based on data from a provincial electricity market in China illustrate that the proposed model can effectively reflect the impact of market-oriented electricity proportion on market power and market-clearing price, thus providing a quantitative basis for PX to determine the proportion of market-oriented electricity in total electricity consumption.

Resource Allocation Scheme for One-to-Many Cooperative Wireless Systems Using the Bidding Game Strategy

In this paper, we propose a new scheme for optimal resource (i.e, power) allocation in a cooperative wireless communication system, using a type of game called the Bidding game. Previous related works have all considered networks with multiple source nodes interacting with either single or multiple relays, without paying so much attention to how partners are selected for cooperation. However because of the importance of partner selection as an integral part of an efficient cooperative communication network, which also includes resource allocation, we propose this new game-based resource allocation scheme, in which the conventional theories of economic bidding are applied. In this work, we model the cooperative communication network as a single-user, multi-relay system in which the source acts as the auctioneer while the relays or partners act as the bidders in the game. The resource being auctioned here is power. The relay which offers the highest bid in terms of price is first selected by the source node and then allocated power by the source node. Our proposed scheme is aimed at answering the question of how maximally or optimally the power should be allocated in the network by the source node so as not to violate the power constraint. We show that there exists bidding and pricing mechanisms or strategies that lead to the maximization of network throughput or utility in cooperative communication networks. We also see in our simulation results that there is convergence to the Nash equilibrium which proves the correctness of our scheme.

Land bidding game with conflicting interest and its quantum solution

Recently, the first conflicting interest quantum game based on the nonlocality property of quantum mechanics has been introduced in A. Pappa, N. Kumar, T. Lawson, M. Santha, S. Y. Zhang, E. Diamanti and I. Kerenidis, Phys. Rev. Lett. 114 (2015) 020401. Several quantum games of the same genre have also been proposed subsequently. However, these games are constructed from some well-known Bell inequalities, thus are quite abstract and lack of realistic interpretations. In the present paper, we modify the common interest land bidding game introduced in N. Brunner and N. Linden, Nat. Commun. 4 (2013) 2057, which is also based on nonlocality and can be understood as two companies collaborating in developing a project. The modified game has conflicting interest and reflects the free rider problem in economics. Then we show that it has a fair quantum solution that leads to better outcome. Finally, we study how several types of paradigmatic noise affect the outcome of this game.

Game-based learning in construction management courses: a case of bidding game

Purpose – The game-based learning has been used very successfully in some areas of formal education. In construction management, there is an increased uptake of games in teaching and learning. Focusing on a bidding game, the purpose of this paper is to evaluate its ability in enhancing students’ learning. The specific objectives are to: examine the effectiveness of the game as a teaching mechanism; explore students’ learning experience, preference and motivation to participate in the game; and identify the relationship between game features and students’ learning experience and overall satisfaction. Design/methodology/approach – This paper adopted a survey research design. A questionnaire survey was conducted in two universities in Australia, involving 100 students in the gameplay. Findings – The results show that the overall student feedback is positive with the vast majority of the students enjoying the learning experience. Students from both institutions have indicated their preference for group-based game sessions. However, the students have divergent opinions about the game incentive and motivation. It is found that there are significant correlations between some of the game features and students’ learning experience and overall satisfaction. Practical implications – The bidding game clearly has potential for adaptation in construction bidding-related courses. Educators could consider incorporating the significant game features towards improving students’ learning experience and overall satisfaction. Originality/value – Given there are limited studies that aimed at evaluating educational games, the student feedback in this research should facilitate more critical and reflective process for incorporating similar form of games in teaching construction management and bidding-related courses.

Multi-Attribute Decision Making in a Bidding Game with Imperfect Information and Uncertainty

Human preferences or attitudes towards risk should play a vital role in a decision making task with imperfect information and uncertain outcomes. We introduce a method to characterize human preferences and how they are integrated into the decision making process of a complex probability-based card bidding game. When assessing the preferences, a utility-to-preference (UP) function is devised for easier mapping between preferences and how much a player is willing to bid. Using the developed approach, we can better identify how different human preferences and their interaction affect the game outcomes. We focus on a highly addictive poker game that has become a multi-billion dollar internet business. The method was evaluated through data obtained from two decision makers (DMs) with different expertise. The integrated decision making process was designed and automated through Monte Carlo simulation. The results show that different preferences to the multi-attributes can lead to different profit outcomes. The results can further serve as a basis to identify vulnerable populations1 for the socio-technical online bidding game.