The T-O-E framework enjoys robust scholarly accolade but it rarely espouses clearly task and individual factors. Although task and individual contexts had been separately addressed by task-technology-fit (TTF) and unified theory of acceptance and use of technology (UTAUT), respectively, the purpose of this paper is to complement and/or extend the T-O-E’s insights by integrating TTF and UTAUT frameworks, and developing and empirically testing a 12-factor framework that spans five contexts.
Survey data were proportionally collected from six groups of small service enterprises with strong operations in Port Harcourt, Nigeria and the mode of sampling was purposive and snow-ball while analysis involved logistic likelihood regression.
The relationship between adoption and the factors within the contexts of technology, organization, environment and task were statistically supported though some had negative coefficients. For individual context, social factor had a statistically significant negative coefficient but hedonistic drive was not statistically supported.
The study is limited by its scope of coverage; therefore, extended data are needed to apply the findings to other sectors/industries and to factor in the implementation and post-adoption phases and business-to-business adoption in order to forge a more integrated and holistic adoption framework.
The findings encourage vendors and policy makers to place more premiums on organizational and task factors than on technological, environmental and individual factors and to craft informed marketing programs that would appeal to actual and potential adopters and cause them to progress in the loyalty ladder.
This paper contributes to the growing research on technology adoption; it uses factors within the T-O-E, TTF and UTAUT frameworks to explain adoption of technologies and to establish the underlying relationships amongst T-O-E factors through integrating other useful frameworks.
Awa, H.O., Ojiabo, O.U. and Orokor, L.E. (2017), "Integrated technology-organization-environment (T-O-E) taxonomies for technology adoption", Journal of Enterprise Information Management, Vol. 30 No. 6, pp. 893-921. https://doi.org/10.1108/JEIM-03-2016-0079
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