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Purpose - Since technology adoption is frequently replicated with minor tweaks and extensions; the theoretical perspective from other fields is used to shed additional light on an individual’s technology acceptance. The Entrepreneurial Event Model (EPM) is an intentional model, which measures the volitional aspect of the behaviour. The current study seeks to revise and validate this model in the technology acceptance context, and investigate IT innovation adoption. Design/methodology/approach - In order to test the proposed research model, data are collected through a questionnaire survey from 1000 entrepreneurs involved in providing professional services in manufacturing, telecommunication, education, banking and finance, service, and agriculture within Malaysia. Structural equation modelling technique was used to evaluate the research model. Finding - The results of the study revealed that the model is a robust model to measure individual dimensions towards technology adoption. The results indicated that the propensity to use, perceived desirability and perceived feasibility are significantly and positively related to the intention to use IT innovation. EPM was able to account for 82 percent of the variance in usage intention, and provide a useful tool for managers to access the likelihood of success for new technologies. Originality/value - This paper has positive implications for academic, managers and policy makers. Applying EPM model in technology acceptance will shed additional light on this area, and reveal new knowledge perspectives. Policy makers could encourage early adopter entrepreneurs to adopt and use IT innovation in their businesses, which in turn, will encourage others to look to early adopter and emulate them, thus increasing the rate of adoption and the use of IT innovation.
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Stored only when both papers are in the corpus — 33 citations exist upstream.
Papers that cite the same references — the relational fallback while embeddings are still backfilling.
Imported from OpenAlex (CC0) — nothing here is generated.