Trust building and risk mitigation via smart contracts on Amazon Mechanical Turk
- Amazon Mechanical Turk (MTurk) allows organizations and individuals to benefit from a collective source of intelligence, skills and insights from a global population, but MTurk withdraws from responsibilities and the obligation of overlooking payment transactions. Consequently, there is no contractual agreement between the crowd worker and the requester on when payments should be authorized. Requesters even obtain ownership of the work without having to pay for it. This situation of lock-up poses a serious issue for crowd workers. As a solution to this problem, the present study introduces smart contracts to transactions on crowd work platforms, arguing that smart contracts can mitigate risks from lock-up situations and support trust, through non-alterable terms and conditions imprinted into the code of a smart contract. This research conceptualizes an online experimental study to validate the trust building and risk mitigating effects of smart contracts in crowd work transactions onAmazon Mechanical Turk (MTurk) allows organizations and individuals to benefit from a collective source of intelligence, skills and insights from a global population, but MTurk withdraws from responsibilities and the obligation of overlooking payment transactions. Consequently, there is no contractual agreement between the crowd worker and the requester on when payments should be authorized. Requesters even obtain ownership of the work without having to pay for it. This situation of lock-up poses a serious issue for crowd workers. As a solution to this problem, the present study introduces smart contracts to transactions on crowd work platforms, arguing that smart contracts can mitigate risks from lock-up situations and support trust, through non-alterable terms and conditions imprinted into the code of a smart contract. This research conceptualizes an online experimental study to validate the trust building and risk mitigating effects of smart contracts in crowd work transactions on Amazon Mechanical Turk.…
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| Author: | Moritz BrucknerORCiDGND, Adeline FrenzelORCiDGND, Daniel VeitORCiDGND |
|---|---|
| URN: | urn:nbn:de:bvb:384-opus4-832411 |
| Frontdoor URL | https://opus.bibliothek.uni-augsburg.de/opus4/83241 |
| URL: | https://aisel.aisnet.org/amcis2020/virtual_communities/virtual_communities/11/ |
| ISBN: | 978-1-7336325-4-6OPAC |
| Parent Title (English): | AMCIS 2020 Proceedings: Americas Conference on Information Systems, Sep 12-16, 2020, Salt Lake City, UT, USA |
| Publisher: | AISeL |
| Place of publication: | New York, NY |
| Editor: | Bonnie Anderson, Jason Thatcher, Rayman Meservy, Kathy Chudoba, Kelly Fadel, Sue Brown |
| Type: | Conference Proceeding |
| Language: | English |
| Date of Publication (online): | 2021/02/05 |
| Year of first Publication: | 2020 |
| Publishing Institution: | Universität Augsburg |
| Release Date: | 2021/02/05 |
| First Page: | 11 |
| Institutes: | Wirtschaftswissenschaftliche Fakultät |
| Wirtschaftswissenschaftliche Fakultät / Institut für Betriebswirtschaftslehre | |
| Wirtschaftswissenschaftliche Fakultät / Institut für Betriebswirtschaftslehre / Lehrstuhl für Information Systems und Management | |
| Dewey Decimal Classification: | 3 Sozialwissenschaften / 33 Wirtschaft / 330 Wirtschaft |
| Licence (German): |  Deutsches Urheberrecht |
