Abstract
A key challenge facing today's business leaders in the E-waste industry is managing the uncertainty associated with adopting advanced e-waste technologies within the urban mining process. This study examines how the alignment between task requirements, technological characteristics, and user capabilities influences technology adoption within Sri Lanka's e-waste sector. Guided by an exploratory sequential mixed-methods design, the research first conducted 45 semi-structured interviews and two focus group discussions to identify the key dimensions of task–technology fit relevant to the e-waste urban-mining process. These insights informed the development of a quantitative survey administered to 279 employees across formal and informal e-waste businesses in Sri Lanka. Building on the Task–Technology Fit (TTF) framework, the study conceptualises a decomposed Task–Technology–User Fit (TTUF) model comprising five characteristics, such as interoperability, usefulness, scalability, flexibility, and innovativeness, and incorporates user competence as a moderator of the attitude–adoption relationship. Covariance-Based Structural Equation Modelling (CB-SEM) reveals that usefulness, scalability, and innovativeness are significantly associated with employee attitudes, while user competence strengthens the translation of positive attitudes into technology adoption. A multi-group analysis demonstrates that usefulness is consistently influential across both formal and informal sector businesses; however, innovativeness plays a stronger role in formal sector businesses, whereas competence exerts a comparatively greater moderating role in informal sector businesses. This study provides empirical evidence for the proposed TTUF model in the context of e-waste urban mining, advancing theoretical understanding of fit-based technology adoption mechanisms and offering actionable implications for technology developers, managers, and policymakers seeking to accelerate the uptake of sustainable technologies in developing economies.
| Original language | English |
|---|---|
| Article number | 101026 |
| Pages (from-to) | 1-21 |
| Number of pages | 21 |
| Journal | Computers in Human Behavior Reports |
| Volume | 22 |
| DOIs | |
| Publication status | Published - Mar 2026 |
Bibliographical note
Publisher Copyright:© 2026 The Authors.
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