## 5 Discussion  
While there is a scarcity of research focused on service quality in the context of electric vehicle (EV) charging stations, prior studies, such as those by [PERSON] and [PERSON], have made valuable contributions by introducing a novel Quality of Service (QoS) index that captures EV owners'/drivers' preferred disposable charging time [17]. This approach aims to cater to their specific needs and preferences, thereby striking a balance between cost-effective charging station placement and fulfilling charging reliability and QoS expectations.  
This study considers two major influence indicators: the total waiting time for all charging services and the total number of unserved taxis across all charging stations. These indicators provide additional insights into the operational efficiency and overall service quality of the EV charging infrastructure, enabling the further refinement of strategies for charging station deployment and enhancing the overall charging experience for EV drivers.  
First, by focusing on these two indicators, this study offers a more comprehensive evaluation of the operational efficiency and service quality of the EV charging infrastructure. While previous research has made valuable contributions, such as the QoS index based on preferred disposable charging time, this study provides additional metrics that are crucial for assessing the overall performance of, and user satisfaction with, EV charging stations.  
The results demonstrate a reduction of approximately 6% in the total waiting time and a decrease of roughly 19% in the total number of unserved taxis across all charging stations when using the proposed IKQT algorithm, suggesting that this method can effectively improve the operational efficiency of the EV charging infrastructure. This aligns with the goals of prior studies that aimed to balance cost-effective charging station placement with high charging reliability and QoS expectations. By considering both waiting time and unserved demand, this study offers a more nuanced understanding of how these factors interact and can be optimized to enhance the overall charging experience for EV drivers.  
Figure 6: Trends in the total waiting time of all charging services (min.).  
In comparison to the QoS index proposed by [PERSON] and [PERSON], this study offers a more operationally focused evaluation of the EV charging infrastructure. While their QoS index aims to capture EV owners'/drivers' preferences and needs, the indicators in this study focus on the tangible outcomes of charging station deployment--namely, reduced waiting times and fewer unserved taxis. By combining these two perspectives, future research could develop a more holistic framework for assessing and optimizing the EV charging infrastructure, taking into account both user preferences and operational efficiency.  
In summary, this study contributes to the existing literature by providing additional insights into the operational efficiency and service quality of the EV charging infrastructure, while also highlighting areas for improvement and future research. By comparing the findings to those of prior studies, we can build upon existing knowledge and work towards developing more effective and user-centric charging station deployment strategies.