## 6 Conclusions  
This study examined the relationship between bike-sharing infrastructure and user-perceived benefits in the context of Smart Cities, focusing on the Silesian region of Poland. Through a combination of statistical and regression analyses, this research provides evidence for how infrastructure influences system effectiveness, user satisfaction, and sustainable mobility outcomes. Addressing Q1, the most valued benefits identified by users were health-related improvements (e.g., physical fitness) and environmental advantages, such as reduced emissions and congestion. These findings align with broader urban sustainability goals [44; 63]. In response to Q2, users highlighted infrastructure shortcomings, including fragmented cycling networks, uneven station distribution, and inconsistent bike maintenance. These issues were particularly limiting in peripheral areas, reducing access and frequency of use. Regarding Q3, the analysis confirmed that infrastructure quality directly affects user satisfaction. Key factors include bike condition, station density, and integration with public transport. Features like real-time availability, booking via mobile apps, and cashless payments significantly enhance user experience and operational appeal [31; 32; 33; 34; 35; 36; 37; 38; 74; 75]. For Q4, the regression models demonstrated moderate to high explanatory power, especially for benefits linked to maintenance, station placement, and multimodal integration. However, external factors, such as weather, seasonal variation, and individual preferences, may also influence outcomes and warrant further study. Policy implications include expanding bike lane networks, optimising station placement, integrating bike-sharing with public transit through unified payment systems, and leveraging technologies like real-time tracking and AI-based fleet management. While this study provides robust insights, its regional focus limits its generalisability. Future \begin{table}
\begin{tabular}{c c c} \hline \hline
**Key Area** & \multicolumn{2}{c}{**Main Findings**} \\ \hline
**Bike-Sharing Benefits** & - & Health benefits: improved physical fitness, increased mobility. \\
**-** & Environmental sustainability: reduced CO2 emissions, decreased congestion. \\
**-** & Economic advantages: affordable transportation, increased tourism, local \\  & business support. \\ \hline
**Infrastructure Assessment** & - & Station density and bike availability are critical factors affecting user satisfaction. \\
**-** & Gaps in bike path networks and uneven station placement limit accessibility. \\  & - & Poor maintenance negatively impacts safety and efficiency. \\ \hline
**Technological Integration** & - & Users value real-time tracking, mobile apps, and contactless payment systems. \\
**-** & Integration with public transportation increases system efficiency and adoption. \\  & - & IoT and predictive maintenance could enhance long-term sustainability. \\ \hline
**Challenges Identified** & - & Inconsistent infrastructure across different city zones. \\
**-** & Need for better policy support and urban planning for sustainable mobility. \\  & - & Social perception and user engagement still require improvement. \\ \hline
**Policy and Smart City** & - & Post-industrial regions like Silesia can become models for sustainable \\  & & bike-sharing. \\
**Integration** & - & Strategic urban revitalization can improve bike-friendly infrastructure. \\  & - & Data-driven approaches can optimise system operations and accessibility. \\ \hline
**Research Implications** & - & Multidimensional regression models explain variations in perceived benefits. \\
**-** & Future research should explore long-term infrastructure development and user \\  & - & Policy interventions are crucial for ensuring equitable bike-sharing accessibility. \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Summary of Main Findings. research should include comparative analyses across diverse urban settings and examine behavioural and cultural factors shaping system adoption.