## 5 Discussion and Conclusions  
### Key Findings  
With the arrival of the industry 5.0 era, collaborative robot innovation technology will become the leading robot technology in the future [98], and this innovative technology will also bring significant benefits to the development of enterprises [35]. Firstly, this study explains the first research question by using a combined model of the TOE framework and DOI theory at three levels: technical, organizational, and environmental. Comparative advantage, compatibility, complexity, observability, and trialability at the technical level, top management support and organizational readiness at the organizational level, and competitive pressure, vendor support, and government support at the environmental level are the enterprise-level determinants of collaborative robot innovation adopted by SMEs. Secondly, to address the second research question, this study aims at China, the world's largest collaborative robot market, and conducts an empirical analysis of the impact of enterprise-level determinants on SMEs' adoption of collaborative robot innovation. Among the determinants of technology, absolute advantage and compatibility have significant positive impacts on SMEs' adoption of collaborative robot innovation. This finding is consistent with the previous research results on e-commerce adoption factors of SMEs in Malaysia and Romania [56; 57]. It shows that SMEs have begun to recognize the potential benefits of collaborative robot innovation and are ready to adopt it, which meets the necessary conditions for innovation to be adopted [30]. At the same time, this study finds that complexity has a significant negative impact on SMEs' adoption of collaborative robot innovation. This result is consistent with the results of earlier studies that complexity is negatively correlated with adoption [30; 39; 58; 59]. This shows that SMEs will have concerns and anxiety about the knowledge and skills required for collaborative robot innovation when considering collaborative robot innovation, such as the complexity of programming [4]. In addition, the trialability and observability factors in this study have significant positive impacts on SMEs' adoption of collaborative robot innovation. This result is consistent with previous studies, such as the adoption of big data analysis innovation by SMEs in Iran [78], the adoption of enterprise application (EA) innovation by SMEs in England [99], and the adoption of e-commerce (EC) innovation by Brunei SMEs [100]. A possible explanation is that the collaborative robot has the advantages of being small in size, lightweight, and plug-and-play [23; 41; 42], which eases the operational difficulty for SMEs to perceive the observability and trialability of collaborative robot innovation. Among the organizational determinants, top management support has a significant positive impact on the adoption of collaborative robot innovation by SMEs, and this result is consistent with the finding in the previous research on the adoption of cloud computing \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Hypothesis** & \(\beta\) & **STDEV** & **T Statistics** & \(p\) **Values** & **Result** \\ \hline H8: CP \(\rightarrow\) AI & 0.047 & 0.053 & 0.895 & 0.371 & Reject \\ \hline H9: VS \(\rightarrow\) AI & 0.181 & 0.047 & 3.854 & 0.000 & Support \\ \hline H10: CS \(\rightarrow\) AI & \(-\)0.006 & 0.052 & 0.118 & 0.906 & Reject \\ \hline Gender & \(-\)0.021 & 0.045 & 0.480 & 0.632 & - \\ \hline Age & 0.064 & 0.042 & 1.511 & 0.131 & - \\ \hline Education & \(-\)0.079 & 0.045 & 1.757 & 0.079 & - \\ \hline Job position & \(-\)0.012 & 0.044 & 0.279 & 0.780 & - \\ \hline \hline \end{tabular} Note: RA-Relative Advantage, CB-Compatibility, CX-Complexity, OB-Observability, TR-Triability, TMS-Top Management Support, OR-Organizational Readiness, CP-Competitive Pressure, VS-Vendor Support, GS-Government Support, AI-Adoption Intention.  
\end{table} 
Table 4: _Cont._by SMEs and green supply chain management innovation [64; 65].