The gig economy's secret weapon: ChatGPT

Ali Nawaz Khan and Naseer Abbas Khan

Technological Forecasting and Social Change, 2024, vol. 209, issue C

Abstract: ChatGPT has the potential to transform the gig economy by amplifying worker efficiency and productivity. This study aims to examine the effect of innovative use of ChatGPT on gig worker performance using a mediating role of gig worker attitudes towards ChatGPT. This study also aims to determine the moderating role of gig worker agility in the association between the innovative application of ChatGPT and gig worker performance. This study employed a time lag approach involving two time waves and the final sample for this study was 418 gig workers. The data was collected via an online survey that involved the use of questionnaires which were developed on a five point Likert scale. The findings of this study indicate that the innovative use of ChatGPT has a significant positive direct influence on gig worker attitudes towards ChatGPT use and further on the level of performance of the gig workers. The results further confirmed the mediation effect of gig worker attitudes towards ChatGPT. Moreover, gig workers' agility significantly moderated the relationship between innovative use of ChatGPT and gig worker performance. These insights have important implications for individuals and organizations looking to meet the challenges and opportunities of the gig economy.

Keywords: Innovative use of ChatGPT; Gig worker attitude towards ChatGPT; Gig worker performance; Gig worker agility; Task technology fit theory (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0040162524006061
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:tefoso:v:209:y:2024:i:c:s0040162524006061

DOI: 10.1016/j.techfore.2024.123808

Access Statistics for this article

Technological Forecasting and Social Change is currently edited by Fred Phillips

More articles in Technological Forecasting and Social Change from Elsevier
Bibliographic data for series maintained by Catherine Liu ().