Examining the Acceptance and Adoption of Digital Job Matching Platforms Using A Modified Technology Acceptance Model: A Case Study of Hahujobs and Afriwork in Addis Ababa, Ethiopia
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Date
2024-04
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Addis Ababa University
Abstract
Digital job matching platforms have emerged as powerful tools in the labor market, facilitating efficient and effective connections between job seekers and employers. These platforms utilize technology to aggregate and match job opportunities with qualified candidates, offering a streamlined and convenient approach to the job search process. The objective of this research was to examine the acceptance and adoption of digital job matching platforms using a Modified Technology Acceptance Model, focusing on a case study of HahuJobs and AfriWork in Addis Ababa, Ethiopia. Using the Modified Technology Acceptance Model, data from 304 respondents on Afriwork and HaHuJobs were collected via Google Form. Analysis involved SPSS (v27) with descriptive statistics, factor analysis, and regression to identify associated factors. Additionally, Simple and Multiple Linear Regression Analysis was conducted, with statistical significance declared at P-value <0.05 and a 95% confidence interval. A Modified TAM-based analysis with qualitative insights was done to triangulate and validate results of quantitative analysis. Results revealed that this model is applicable for assessing the acceptance and adoption of digital job matching platforms. User perception and experience were found to be the strongest determinant factors for the acceptance and adoption of digital job matching platforms. In addition, intentions and attitudes toward platform use was found to be the strongest determinant factor for the acceptance and adoption of digital job matching platform. Qualitative analysis has revealed that digital job matching platforms, valued for their efficiency, and streamlined job search process, resonate with users due to their user-friendly design (TAM's PEU) and ability to save time (TAM's PU). While personalization enhances user satisfaction, platform trustworthiness is crucial. Addressing concerns about information quality, user experience, and clear communication solidified these platforms' role in the job market, ultimately empowering users with a more efficient and successful job search. Analyzing the reach and effectiveness of government programs aimed at equipping citizens with the digital skills needed to navigate job search platforms effectively was also undertaken. This involved collaborating with government agencies to collect data on program participation rates and user feedback on the effectiveness of these initiatives in improving digital literacy.
Keywords: Technology acceptance model (TAM),Confirmatory Factor Analysis
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Keywords
Technology acceptance model (TAM), , Confirmatory Factor Analysis