scholarly journals Research on Bidding Game and Its Application Based on Copetition Scenario

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Yanyong Sun
Keyword(s):  
Decision Making ◽  
Functional Relationship ◽  
Bidding Strategy ◽  
Bidding Behavior ◽  
Bidding Game ◽  
Matrix Modeling ◽  
Business Behavior

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.

A Priority Decision Making Based Bidding Strategy for Interactive Aggregators

2018 ◽  
Vol 54 (6) ◽  
pp. 5569-5578 ◽  
Author(s):  
Tianguang Lu ◽  
Wei-Jen Lee ◽  
Qian Ai ◽  
Songtao Lu
Keyword(s):  
Decision Making ◽  
Bidding Strategy ◽  
A Priority

scholarly journals Bidding Strategy to Support Decision-Making Based on Comprehensive Information in Construction Projects

2016 ◽  
Vol 2016 ◽  
pp. 1-15 ◽  
Author(s):  
Ru Liang ◽  
Zhaohan Sheng ◽  
Feng Xu ◽  
Changzhi Wu
Keyword(s):  
Decision Making ◽  
Quadratic Programming ◽  
Construction Projects ◽  
Individual Performance ◽  
Bidding Strategy ◽  
Collaborative Performance ◽  
Comprehensive Information ◽  
Support Decision Making ◽  
Unified Method ◽  
Individual Information

This paper develops a unified method to support contractor for bidding selection in construction projects. A cross-functional contractor with 28 candidate units distributed in the three departments (construction units, design units, and suppliers) is used as an example. This problem is first formulated as a 0-1 quadratic programming problem through optimizing individual performance and collaborative performance of the candidate units based on individual information and collaborative information. Then, a multiobjective evolutionary algorithm is designed to solve this problem and a bidding selection problem for a major bridge project is used to demonstrate our proposed method. The results show that the decision-maker (DM) obtains a better contractor if he pays more attention to collaborative performance.

A Study of Bidding Behavior in Voluntary-Pay Philanthropic Auctions

2018 ◽  
Vol 82 (3) ◽  
pp. 124-141 ◽  
Author(s):  
Ernan Haruvy ◽  
Peter T.L. Popkowski Leszczyc
Keyword(s):  
Corporate Social Responsibility ◽  
Boundary Conditions ◽  
Bidding Strategy ◽  
Bidding Behavior ◽  
Late Entry ◽  
Compliance Behavior ◽  
Jump Bidding ◽  
Charity Auctions ◽  
Corporate Social ◽  
Auction Formats

The authors investigate compliance behavior and revenue implications in winner-pay and voluntary-pay auctions in charity and noncharity settings. In the voluntary-pay format, the seller asks all bidders to pay their own high bid. The authors explore motives and boundary conditions for compliance behavior based on internal and external triggers of social norms. The voluntary-pay format generates higher revenue than the winner-pay format for charity auctions, despite imperfect compliance, but it generates lower revenues in noncharity settings. To characterize bidding strategy, the authors study time to bid, auction choice, and jump bidding and find evidence that bidders in voluntary-pay auctions more commonly use jump bidding and late entry. The findings have important implications for marketing managers, augmenting the growing stream of empirical auction studies and work on corporate social responsibility. Specifically, combining an auction with a charitable cause may result in increased revenues, but managers should ensure that they are accounting for differential compliance rates between auction formats. Even if low-compliance bidders can be identified and screened out, doing so is not advantageous, because noncompliant bidders bid up prices.

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

2016 ◽  
Vol 15 (01) ◽  
pp. 63-81 ◽  
Author(s):  
Ziho Kang ◽  
Thomas Morin
Keyword(s):  
Decision Making ◽  
Imperfect Information ◽  
Vital Role ◽  
Decision Makers ◽  
Decision Making Process ◽  
Bidding Game ◽  
Multi Attribute Decision Making ◽  
Integrated Decision Making ◽  
Internet Business ◽  
Uncertain Outcomes

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.

Neuroeconomics

2020 ◽  
pp. 64-83
Author(s):  
Torben Larsen
Keyword(s):  
Decision Making ◽  
Behavioral Economics ◽  
Carbon Emission ◽  
Health Science ◽  
Emission Tax ◽  
Economic Knowledge ◽  
Relative Poverty ◽  
The Public ◽  
Business Behavior

A neuroeconomic psychology establishes behavioral economics as a positivist discipline connecting health science and ecology. This makes “economic ecology” and “neuroeconomics” important new sub-disciplines of economics. Pigovian carbon emission tax (CET) is the most effective intervention towards the “green-house effect.” However, in the short-term, democratic center-coalitions are too weak to implement CET due asymmetric levels of economic knowledge between economists and the public. However, neuroeconomic research indicates that training can improve decision-making about complex issues as CET. A second-best strategy is presented as green hybrid multilevel transition (GHMT). Besides GHMT preparing doe CET, neuroeconomic psychology delivers a series of science-based advices on effective behaviors: a consumer pattern that integrates individual satisfaction with environmental conscience, efficacious business behavior like an entrepreneur, long-term political suspension of relative poverty by universal basic income, and cognitive training by meditative in-depth relaxation.

scholarly journals A Wind Energy Supplier Bidding Strategy Using Combined EGA-Inspired HPSOIFA Optimizer and Deep Learning Predictor

Energies ◽  
2021 ◽  
Vol 14 (11) ◽  
pp. 3059
Author(s):  
Rongquan Zhang ◽  
Saddam Aziz ◽  
Muhammad Umar Farooq ◽  
Kazi Nazmul Hasan ◽  
Nabil Mohammed ◽  
...  
Keyword(s):  
Deep Learning ◽  
Wind Energy ◽  
Large Scale ◽  
Learning Algorithm ◽  
Evolutionary Game ◽  
Market Price ◽  
Bidding Strategy ◽  
Bidding Behavior ◽  
Hybrid Particle Swarm Optimization ◽  
Improved Firefly Algorithm

As the integration of large-scale wind energy is increasing into the electricity grids, the role of wind energy suppliers should be investigated as a price-maker as their participation would influence the locational marginal price (LMP) of electricity. The existing bidding strategies for a wind energy supplier faces limitations with respect to the potential cooperation, other competitors’ bidding behavior, network loss, and uncertainty of wind production (WP) and balancing market price (BMP). Hence, to solve these problems, a novel bidding strategy (BS) for a wind power supplier as a price-maker has been proposed in this paper. The new algorithm, called the evolutionary game approach (EGA) inspired hybrid particle swarm optimization and improved firefly algorithm (HPSOIFA), has been proposed to handle the bidding issue. The bidding behavior of power suppliers, including conventional power suppliers, has been encoded as one species to obtain the equilibrium where the EGA can explore dynamically reasonable behavior changes of the opponents. Each species of behavior change has been exploited by the HPSOIFA to improve the optimization solutions. Moreover, a deep learning algorithm, namely deep belief network, has been implemented for improving the accuracy of the forecasting results considering the WP and BMP, and the uncertainty revealed in the WP and BMP has been modeled by quantile regression (QR). Finally, the Shapley value (SV) has been calculated to estimate the benefits of cooperative power suppliers. The presented case studies have verified that the proposed algorithm and the established bidding strategy exhibit higher effectiveness.

scholarly journals Bidding Model Based on Balance Programming between Target and Chance

2012 ◽  
Vol 6-7 ◽  
pp. 226-232
Author(s):  
Gang Lu ◽  
Fu Shuan Wen
Keyword(s):  
Electricity Market ◽  
Programming Model ◽  
Numerical Test ◽  
Optimal Decision ◽  
Bidding Strategy ◽  
Bidding Behavior ◽  
Bidding Strategies ◽  
Generation Company ◽  
Optimal Bidding ◽  
New Research

In a pool-based single-buyer electricity market, a Generation Company (GENCO) is required to considering the decision risk when building the optimal bidding strategy due to the stochastic bidding behavior of the rivals. The optimal decision is to maximize the profit while minimizing the risk, however, they are contradicting targets. This paper proposes a new research framework about risk-constrained optimal bidding strategies based on the stochastic programming method, termed as balance programming between target and chance (BPTC). And this method can favor the GENCO to make the stochastic decision in a more rational, flexible, and applicable manner. A genetic algorithm with Monte Carlo simulation is employed to solve the programming model. The effectiveness of the proposed method is shown through a numerical test.

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

2021 ◽  
Vol 9 ◽  
Author(s):  
Jinrui Cui ◽  
Yating Li ◽  
Chuan He ◽  
Zhi Zhang ◽  
Haichao Wang ◽  
...  
Keyword(s):  
Market Power ◽  
Electricity Market ◽  
Demand Curve ◽  
Market Price ◽  
Smooth Transition ◽  
Bidding Strategy ◽  
Allocation Model ◽  
Bidding Game ◽  
Double Track ◽  
The Impact

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.

Analyzing Bidding Strategy for Pavement Engineering with Multi-Criteria Decision-Making

2013 ◽  
Vol 723 ◽  
pp. 798-804
Author(s):  
Chin Rung Chiou ◽  
Jyh Dong Lin ◽  
Guan Jia Huang
Keyword(s):  
Decision Making ◽  
Large Scale ◽  
Success Factors ◽  
Bidding Strategy ◽  
Multi Criteria Decision Making ◽  
Price Forecast ◽  
Key Success Factors ◽  
Pavement Engineering ◽  
Optimal Bidding ◽  
Public Construction

This study analyzes key success factors of bidding results and provides the optimal bidding strategy for the pavement engineering. According to Public construction bidding management system data of Public Construction Commission of Executive Yuan, we found that the optimal bidding strategies in the most studies only focused on bidding prices and winning bid amounts. However, public constructions are usually on a large scale with great investments, it is critical to control budgets under quality and duration considerations. In addition, it is complicated for bidders to implement the optimal bidding strategy under multiple bidding factors. Hence, this study applies statistical analysis to find key success factors of bidding data in Taoyuan pavement engineering from 2008 to 2012 for evaluating the optimal bidding strategy with the multi-criteria decision-making method. Our research results show that bidders can increase the probability of winning bids and enables to allocate their resources with accurate bidding price forecast. In particular, the differences between the award amounts and base prices after applying the optimal bidding strategy are also provided.

Sign in / Sign up

Export Citation Format

Share Document