(This summary has been generated by AI. Generate your own summaries: https://www.welcome.alviss.ai/alboard/#/editorial) Introduction : rapid technology identification and selection stand as the significant determinants of technology adoption success in the digital transformation era. Decision makers need more flexible and scalable contextual frameworks for technology selection in digitalization. Aim: this study proposes a technology selection framework that utilizes the three dimensions and combines ahp with a qfd inspired intervention matrix and an optimization model by mixed integer programming. At the same time, data analytics and sensor technologies occurred as the most critical tools. Materials and methods : international journal of innovation and technology management, ahead of print. Study selection : case studies on digital technology selection are rare in manufacturing smes from developing country context in the literature. Result : significant challenges of digital technology adoption are insufficient expert know how and budget constraints. Conclusion : since digital technologies offer both benefits and challenges, the decision making models should reflect this dialectic nature of industry 4.0 adoption and contextually optimize their decisions by combining multiple quantitative methods for technology identification.