Beyond theory: a systematic review of strengths and limitations in technology acceptance models through an entrepreneurial lens

Abstract

In today’s fiercely competitive business landscape, startups face numerous challenges in achieving scalability and sustainability. The integration of cutting-edge technologies such as Artificial Intelligence (AI), blockchain, and the Internet of Things (IoT) presents promising solutions to these challenges. However, understanding the intricacies of technology acceptance within the startup environment becomes paramount. Technology Acceptance Models (TAMs) have long served as foundational frameworks for understanding technology adoption and integration, but their effectiveness is hindered by inherent limitations. These limitations demand further exploration, particularly when viewed through the entrepreneurial lens. This paper offers a comprehensive analysis of the strengths and limitations inherent in TAM and its extensions, alongside other prominent technology acceptance models. By incorporating an entrepreneurial perspective, the analysis reveals additional challenges stemming from the dynamic nature of startup ecosystems. From a pragmatic standpoint, this paper provides actionable insights for technology-driven entrepreneurial organizations to navigate innovation and technology adoption decisions more intelligently. From a theoretical perspective, it contributes to the refinement and evolution of technology acceptance models, particularly in the context of entrepreneurial ventures. In light of these limitations, the paper offers strategic recommendations for future research endeavors. These include encouraging interdisciplinary collaboration, contextualizing models to suit startup dynamics, conducting longitudinal studies to capture evolving user perceptions, accounting for individual differences in technology adoption, and validating emerging models to reflect contemporary realities. Emphasis is placed on the entrepreneurial imperative of agility and adaptability in navigating the ever-changing landscape of technology acceptance. Moreover, the paper underscores the importance of a multidisciplinary approach and delineates practical implications for organizations and practitioners aiming to sustain technology acceptance and successful implementation within dynamic startup environments. By addressing these constraints, researchers can pave the way for the development of more robust and comprehensive models, better equipped to clarify and predict technology acceptance and usage patterns. Ultimately, this research underscores the critical need for ongoing refinement and innovation within the realm of technology acceptance, providing actionable insights to propel both scholarly discourse and entrepreneurial practice forward.