coauction 1.0

This repository contains the source codes of our research paper in economics titled: "Addictive auctions: using lucky-draw and gambling addiction to increase participation during auctioning".

collaborative-auction

This repository contains the source codes of our research paper in economics titled: "Addictive auctions: using lucky-draw and gambling addiction to increase participation during auctioning".

Paper Title: Addictive auctions: Using lucky-draw and gambling addiction toincrease participation during auctioning

Author: Ravin Kumar

Publication: 18th January 2021.

Publication Journal: International Journal of Management Research and Economics

Publication House: SvedbergOpen

Publication link: https://www.svedbergopen.com/files/1612268008_(5)_IJMRE28112020MTN007_(p_68-74).pdf

Cite as:

Ravin Kumar (2021). Addictive auctions: Using lucky-draw and gambling addiction to increase participation during auctioning.
International Journal of Management Research and Economics. 1(1),68-74.

Doi: https://doi.org/10.51483/IJMRE.1.1.2021.68-74

Also available on Elsevier-SSRN eJournals: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3795556

• Behavioral & Experimental Economics eJournal.
• Microeconomics: Welfare Economics & Collective Decision-Making eJournal.
• Microeconomics: Production, Market Structure & Pricing eJournal.

Earlier Preprints:

• OSF Preprints : https://doi.org/10.31219/osf.io/darvs
• Cornell University LIbrary, arXiv.org : https://arxiv.org/abs/1906.03237

Steps for using the library

import coauction
# total_candidates : total number of participants
# bidding_sequence: arrary containing timeseries data in format [[candidate_id,candidate_offer],[candidate_id,candidate_offer] ....]
# relation_list: array containing relationship in form of [[sender,receiver],..] here 1 represents the person who won the bidding, 2 repreents the second last bidding candidate etc.
# alpha: it determine the discount ratio for each relationship present in relation_list
results=coauction.response(total_candidates,bidding_sequence,relation_list,alpha)
# results[0] contains complete list of amount each candidate gets, and results[1] contains the amount in form of a dictionary,
# with candidate_id as key, and amount as value.

Installing module using PyPi:

pip install coauction

In our system, the candidate_id begins with 1 in the dictionary based response.

Copyright (c) 2019 Ravin Kumar
Website: https://mr-ravin.github.io

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation 
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