Building motivation above trust: A blockchain-based NFT GameFi model for construction workload assessment

Mingqi Yang; Manli Zhao

doi:10.54254/2755-2721/21/20231108

Research Article

Open access

Published on 23 October 2023

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Yang,M.;Zhao,M. (2023). Building motivation above trust: A blockchain-based NFT GameFi model for construction workload assessment. Applied and Computational Engineering,21,13-19.

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Building motivation above trust: A blockchain-based NFT GameFi model for construction workload assessment

Mingqi Yang ¹, Manli Zhao *^,2,

¹ Nanyang Tethnological University
² Nanyang Tethnological University

* Author to whom correspondence should be addressed.

https://doi.org/10.54254/2755-2721/21/20231108

Abstract

In the VUCA (Volatile, Uncertain, Complex, Ambiguous) era, construction management faces unique challenges, particularly in the realm of workload assessment. This paper proposes an innovative solution to address these challenges: a blockchain-based GameFi model for construction workload assessment. This model leverages blockchain Non-Fungible Token (NFT) technology to issue various badges, reliably representing employees' workload. The technology ensures the authenticity and tamper-proof nature of the badges, thereby fostering employee motivation through a distributed trust system. This study provides fresh insights into the construction industry's digital transformation and is anticipated to lay the groundwork for similar applications in other sectors.

Keywords

Blockchain, construction industry, NFT, GameFi

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Cite this article

Yang,M.;Zhao,M. (2023). Building motivation above trust: A blockchain-based NFT GameFi model for construction workload assessment. Applied and Computational Engineering,21,13-19.

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The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

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About volume

Volume title: Proceedings of the 5th International Conference on Computing and Data Science

Conference website: https://2023.confcds.org/

ISBN：978-1-83558-033-2(Print) / 978-1-83558-034-9(Online)

Conference date: 14 July 2023

Editor：Roman Bauer, Alan Wang, Marwan Omar

Series: Applied and Computational Engineering

Volume number: Vol.21

ISSN：2755-2721(Print) / 2755-273X(Online)

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