Technological capabilities in the era of the digital economy for integration into cyber-physical systems and the IoT using decision-making approach

In the digital economy, innovators have to deal with the value-capture problem, which necessitates different capabilities. They need to be fully aware of the dynamics of platforms and ecosystems. Such capabilities are needed to enable technologies mainly focused on in the present study. The current digital economy (where businesses are experiencing a big shift from a traditional setting to a widely-digitalized setting) requires companies and enterprises to incorporate innovation into their performance. The present paper aims to offer a novel realm of modern technologies by recognizing the roles the technological capabilities could play in the digital economy regarding for integration of cyber-physical systems (CPS) and the Internet of Things (IoT) into the digital economy. This paper develops an integrated decision-making framework called the Pythagorean fuzzy (PF)- method based on the removal effects of criteria (MEREC)-rank sum (RS)-double normalization-based multiple aggregation (DNMA) model by combining the PF-MEREC-RS and PF-DNMA methods. In this framework, the PF-MEREC-RS method computes the subjective and objective weights of the technological capabilities of the digital economy for the integration of IoT and the CPS. The PF-DNMA method uses to obtain the firms’ preference order over various technological capabilities in the digital economy for integration of the IoT and the CPS. In addition, this paper involves an empirical case study evaluating the key technological capabilities in the digital economy for integration of the IoT and the CPS. Furthermore, comparison and sensitivity investigation are made to show the superiority of the developed framework.