Pregled bibliografske jedinice broj: 1154871
Model for improvement of nonprofit student organizations funding by machine learning and digital transition to blockchain
Model for improvement of nonprofit student organizations funding by machine learning and digital transition to blockchain // 32nd Central European Conference on Information and Intelligent System (CECIIS 2021) - Proceedings / Vrček, Neven ; Pergler, Elisabeth ; Grd, Petra (ur.).
Varaždin: Fakultet organizacije i informatike Sveučilišta u Zagrebu, 2021. str. 229-236 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
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Naslov
Model for improvement of nonprofit student
organizations funding by machine learning and
digital transition to blockchain
Autori
Vasilj, Matea ; Skender, Sven ; Horvat, Marko
Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni
Izvornik
32nd Central European Conference on Information and Intelligent System (CECIIS 2021) - Proceedings
/ Vrček, Neven ; Pergler, Elisabeth ; Grd, Petra - Varaždin : Fakultet organizacije i informatike Sveučilišta u Zagrebu, 2021, 229-236
Skup
32nd Central European Conference on Information and Intelligent Systems (CECIIS 2021)
Mjesto i datum
Varaždin, Hrvatska, 13.10.2021. - 15.10.2021
Vrsta sudjelovanja
Predavanje
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
blockchain, machine-learning, fundraising, smart-contract, non-profit organization
Sažetak
Most student organizations can be classified as nonprofits. Sponsorships are their main source of income and fundraising is a key activity responsible for allocating sufficient funds required for project realization. Typically, companies are the principal outside stakeholders concerned with the success of student organizations' projects and their main sponsors. Financial transparency and accountability for nonprofits are crucial for their public image, mission, and achievement of planned goals. Student organizations cannot be successful and build longterm relationships with enterprises without being transparent in how the donated funds are being spent. By introducing the blockchain-based smart contracts model a student organization could publicly declare the amount of capital required for every project, its distribution as well as fundraising deadlines. As the data on the blockchain is completely transparent it can be effortlessly utilized as an input data set for building machine learning models. By employing the proposed model fundraisers could maximize project income and reduce costs by using generated predictions.
Izvorni jezik
Engleski
Znanstvena područja
Računarstvo
POVEZANOST RADA
Ustanove:
Fakultet elektrotehnike i računarstva, Zagreb
Profili:
Marko Horvat
(autor)
