-
1678
-
1053
-
703
-
536
-
491
Research on the Acceptance of Crowdsourced Translation Platform Technologies by Translators
DOI:
https://doi.org/10.30564/fls.v6i3.6522Abstract
In the current era marked by rapid digitalization and globalization, crowdsourced translation platforms have emerged as key players in the global translation market, prized for their flexibility and efficiency. This new model of translation services not only provides a means to address large-scale translation demands but also introduces challenges and shifts in conventional translation workflows. This study investigates translators’ acceptance of paid crowdsourced translation platform technologies, with the aim of identifying the primary factors that influence technology acceptance and understanding how these factors impact translators’ work attitudes and behaviors. Through a mixed-methods approach that integrates surveys and in-depth interviews, the study gathers data from 300 translators with varied experiences and backgrounds. Utilizing the Technology Acceptance Model (TAM), the research reveals the significant effects of perceived usefulness and perceived ease of use on translators’ acceptance of technology. It is particularly noteworthy that translators show a high sensitivity to their perceptions of the platforms’ efficiency and potential changes in their income. Furthermore, job satisfaction emerges as a key factor in determining translators’ willingness to continue using crowdsourced platforms. This research not only provides insights into how to enhance the relationship between crowdsourced translation platforms and translators but also offers valuable recommendations for the advancement of translation education and the professional development of translators.
Keywords:
Crowdsourced translation platforms; Technology Acceptance Model (TAM); Translators’ acceptance; Mixed-methods research; Job satisfactionReferences
Anastasiou, D., Gupta, R., 2011. Comparison of crowdsourcing translation with Machine Translation. Journal of Information Science. 37(6), 637–659. DOI: https://doi.org/10.1177/0165551511418760
Crespo, M.Á.J., 2016. Mobile apps and translation crowdsourcing: The next frontier in the evolution of translation. Tradumàtica: traducció i tecnologies de la informació i la comunicació. (14), 75–84.
Cukur, L., 2024. Towards an ethical framework for evaluating paid translation crowdsourcing and its consequences. The Translator. 30(1), 47–62. DOI: https://doi.org/10.1080/13556509.2023.2278226
Flanagan, M., 2016. Cause for concern? Attitudes towards translation crowdsourcing in professional translators’ blogs. The Journal of Specialised Translation. 25(1), 149–173.
Jaziri, R., Miralam, M. (2019). Modelling the crowdfunding technology adoption among novice entrepreneurs: An extended tam model. Entrepreneurship and Sustainability Issues. 6 (4), 2159–2179.
Jiménez-Crespo, M.A., 2021. The impact of crowdsourcing and online collaboration in professional translation: Charting the future of translation? Babel. 67(4), 395–417. DOI: https://doi.org/10.1075/babel.00230.jim
Jiménez-Crespo, M.A., 2018. Crowdsourcing and translation quality: Novel approaches in the language industry and translation studies. Translation quality assessment: From principles to practice. Springer: Cham. DOI: https://doi.org/10.1007/978-3-319-91241-7_4 69-93
Kang, J.H., Hong, J.W., 2020. Volunteer translators as ‘committed individuals’ or ‘providers of free labor’? The discursive construction of ‘volunteer translators’ in a commercial online learning platform translation controversy. Meta. 65(1), 51–72. DOI: https://doi.org/10.7202/1073636ar
Khalilizadeh Ganjalikhani, M., Hesabi, A., Ketabi, S., 2023. Toward crowdsourcing translation post-editing: A thematic systematic review. Iranian Journal of Applied Language Studies. 15(2), 1–18. DOI: https://doi.org/10.22111/IJALS.2023.46015.2358
Lee, C.S., Yang, Y., Low, K.Y., et al., 2024. Doing good for others or self: A study of crowdsourced translation on digital labor platforms. Computers in Human Behavior Reports. 13, 100373. DOI: https://doi.org/10.1016/j.chbr.2024.100373
Li, B., 2024. Crowdsourced translation as immaterial labour: A netnographic study of Communities of Practice in the TED translation project. The Translator. 30(1), 63–77. DOI: https://doi.org/10.1080/13556509.2023.2274118
Lu, X., Li, J., (editors), 2022. Ethical study on problems and development of the online crowdsourcing translation platform Yeeyan based on big data. 2022 3rd International Conference on Big Data and Social Sciences (ICBDSS 2022); 2022 Aug 19-21; Hulunbuir, China. pp. 746–757. DOI: https://doi.org/10.2991/978-94-6463-064-0_77
Moreno García, L.D., 2020. Researching the motivation of Spanish to Chinese fansubbers: A case study on collaborative translation in China. Translation, Cognition & Behavior. 3(2), 165–188. DOI: https://doi.org/10.1075/tcb.00039.mor
Ni, X., Tang, L., 2023. Motivation for user-generated translation on chinese online video platform. International Journal of Translation and Interpretation Studies. 3(3), 21–28. DOI: https://doi.org/10.32996/ijtis.2023.3.3.3
Piróth, A., Baker, M. (2020). Volunteerism in translation: Translators without borders and the platform economy. The Routledge handbook of translation and globalization. Routledge: London. pp. 406–424.
Sakamoto, A., 2019. Unintended consequences of translation technologies: From project managers’ perspectives. Perspectives. 27(1), 58–73. DOI: https://doi.org/10.1080/0907676X.2018.1473452
Salam, Z.M., Akil, M., Rahman, A.Q., 2017. Translation errors made by Indonesian-English translators in crowdsourcing translation application. ELT Worldwide. 4(2), 195–204.
Vieira, L.N., O’Sullivan, C., Zhang, X., et al., 2023. Machine translation in society: Insights from UK users. Language Resources and Evaluation. 57(2), 893–914. DOI: https://doi.org/10.1007/s10579-022-09589-1
Yves, G., 2019. Impact of technology on translation and translation studies. Russian Journal of Linguistics. 23(2), 344–361. DOI: https://doi.org/10.22363/2312-9182-2019-23-2-344-361
Zhang, J., Wu, Y., 2020. Providing multilingual logistics communication in COVID-19 disaster relief. Multilingua. 39(5), 517–528. DOI: https://doi.org/10.1515/multi-2020-0110
Zhang, M., Huang, Z., 2022. Crowdsourcing used in higher education: An empirical study on a sustainable translation teaching mode based on crowdsourced translation. Sustainability. 14(6), 3140. DOI: https://doi.org/10.3390/su14063140
Downloads
How to Cite
Issue
Article Type
License
Copyright © 2024 Hui Zhao, Ali Bin Selama, Kaiyisah Hanis Binti Mohd Azm
This is an open access article under the Creative Commons Attribution 4.0 International License.