[go: up one dir, main page]

Abbink et al., 2001 - Google Patents

Adaptive learning versus punishment in ultimatum bargaining

Abbink et al., 2001

View PDF
Document ID
9504264142511955988
Author
Abbink K
Bolton G
Sadrieh A
Tang F
Publication year
Publication venue
Games and Economic Behavior

External Links

Snippet

Adaptive learning and a fairness motive we call “punishment” are the basis for two prominent and substantially different types of theories of ultimatum bargaining behavior. We compare adaptive learning and fairness in an experiment that involves punishment and …
Continue reading at www.e-business.ovgu.de (PDF) (other versions)

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06Q—DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Systems or methods specially adapted for a specific business sector, e.g. utilities or tourism
    • G06Q50/10—Services
    • G06Q50/20—Education
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06Q—DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00—Commerce, e.g. shopping or e-commerce
    • G06Q30/02—Marketing, e.g. market research and analysis, surveying, promotions, advertising, buyer profiling, customer management or rewards; Price estimation or determination
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06Q—DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management, e.g. organising, planning, scheduling or allocating time, human or machine resources; Enterprise planning; Organisational models
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computer systems based on biological models
    • G06N3/02—Computer systems based on biological models using neural network models
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06Q—DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q40/00—Finance; Insurance; Tax strategies; Processing of corporate or income taxes
    • G—PHYSICS
    • G09—EDUCATION; CRYPTOGRAPHY; DISPLAY; ADVERTISING; SEALS
    • G09B—EDUCATIONAL OR DEMONSTRATION APPLIANCES; APPLIANCES FOR TEACHING, OR COMMUNICATING WITH, THE BLIND, DEAF OR MUTE; MODELS; PLANETARIA; GLOBES; MAPS; DIAGRAMS
    • G09B7/00—Electrically-operated teaching apparatus or devices working with questions and answers
    • G09B7/06—Electrically-operated teaching apparatus or devices working with questions and answers of the multiple-choice answer-type, i.e. where a given question is provided with a series of answers and a choice has to be made from the answers
    • G09B7/07—Electrically-operated teaching apparatus or devices working with questions and answers of the multiple-choice answer-type, i.e. where a given question is provided with a series of answers and a choice has to be made from the answers providing for individual presentation of questions to a plurality of student stations

Similar Documents

Publication Publication Date Title
Abbink et al. Adaptive learning versus punishment in ultimatum bargaining
Sarin et al. Risk aversion for decisions under uncertainty: Are there gender differences?
Thomas et al. Legitimacy and collective action
Duffy et al. Giving little by little: Dynamic voluntary contribution games
Henrich Does culture matter in economic behavior? Ultimatum game bargaining among the Machiguenga of the Peruvian Amazon
Fischbacher et al. Social preferences, beliefs, and the dynamics of free riding in public goods experiments
Croson Thinking like a game theorist: factors affecting the frequency of equilibrium play
Greiner et al. Is avatar-to-avatar communication as effective as face-to-face communication? An Ultimatum Game experiment in First and Second Life
Powdthavee et al. Would you pay for transparently useless advice? A test of boundaries of beliefs in the folly of predictions
Baranski Voluntary contributions and collective redistribution
Munier et al. High stakes and acceptance behavior in ultimatum bargaining
Davis et al. Individual characteristics and behavior in repeated games: An experimental study
Zou et al. Ingroup bias in a social learning experiment
Faravelli et al. Single versus multiple-prize all-pay auctions to finance public goods: An experimental analysis
Gosenpud The prediction of simulation performance as it is affected by time
Greiff et al. Incomplete information strengthens the effectiveness of social approval
Bjedov et al. Communication and Coordination in a Two‐Stage Game
Basteck et al. Aiding applicants: Leveling the playing field within the immediate acceptance mechanism
Anderson et al. Inequality, group cohesion, and public good provision: an experimental analysis
Schwartz et al. Behavioral implications of information systems on disclosure fraud
Komorita et al. Level of aspiration in coalition bargaining.
Wilson Results on the Condorcet winner: a committee experiment on time constraints
Lukas Contract design in dynamic agency: An experimental analysis
Ogawa et al. Conducting an Experiment at Multiple Sites with Small Subject Pools: How is Raven Score Effective as a Covariate?
Davis et al. What-if analysis and the illusion of control