## 5 Discussion
\begin{table}
\begin{tabular}{c c c c} \hline \hline  & **Essence** & **Indicators** & **Results (Effects)** \\ \hline \multirow{2}{*}{Model 1} & Control Variables & Constants, Education, Gender, & \multirow{2}{*}{Strongly Supported} \\  & & and Experience & \\ \hline Model 2 & Independent Variables & AI-based KM and Innovation & Strongly Supported \\ \hline Model 3 & Moderating Variable & E-Goverance & Strongly Supported \\ \hline Model 4 & Moderating Test & Innovation x E-Goverance & Strongly Supported \\ \hline Model 5 & Mediating Test & AI-based KM, Innovation, and E- & Strongly Supported \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Characteristics of the evaluation models of artificial intelligence-based technological-oriented knowledge management, innovation, and e-service delivery in smart cities. through technological innovation. Following the theoretical framework, the findings corroborate our hypothesis that enhancing innovation must be driven by the interaction effects of knowledge management and city performance. [PERSON] and [PERSON] [85] explored the role of innovation on a city's performance to determine when and how technology-oriented sources are substitutive. This paper advances a research gap by examining the interaction effects of technology-oriented knowledge management and e-service delivery on innovation and the contextual role of e-governance between innovation and e-service delivery. City governments must implement diverse approaches regarding e-service offering and e-service delivery protocols by ensuring innovation and e-governance, fostering good e-governance with innovation. Table 4 shows a diverse range of results. All the correlations between knowledge management, innovation, e-governance, and smart city performance indicators were positive and statistically significant. Table 4 provides evidence that several independent knowledge management elements do not correlate with different aspects of performance measures. One plausible interpretation of these findings is that comparative performance metrics may struggle from a halo effect, wherein city governors sensationalize their own cities' effectiveness. Besides that, knowledge management is not the only factor that influences performance, and other factors, such as the city's innovative or e-government environment, may substantially impact performance. The relationship between knowledge management and innovation was theoretically established in the literature, but statistical evidence was inadequate. Consequently, in this study, a city that is proficient in knowledge management attributes is more innovative. According to a common assumption, intangible knowledge is more complicated for contenders to access and replicate. Therefore, this type of knowledge has a tremendous opportunity to transform competitive advantages [86], improving performance. The findings that are presented in this study are significant because they demonstrate that knowledge is just as essential as what we do with that knowledge to be innovative. Smart cities with well-developed technology-oriented knowledge management behavioral patterns are more likely to generate greater performance (i.e., e-service delivery) and develop incremental innovations supporting our proposed H1 and H2 substantially. Moreover, municipalities with well-developed innovations and technology are more strongly predictive of e-service delivery, with the fact that technological innovation is critical for providing electronic services in smart cities, supporting our assertion in H3. These conclusions are also supported by an analysis of individual knowledge management factors.