## 6 Conclusions and Implementations  
This study aimed to examine the factors influencing injury severity among Young Adult Motorcyclists (YAMs) by comparing crashes on local roads in urban and rural areas. The model development utilized data from motorcycle crashes throughout Thailand from 2018 to 2020. Geographic Information System (GIS) tools were employed to identify whether a crash took place on an urban or rural local roadway. The method employed was a Random Parameter Logit Model with Unobserved Heterogeneity in Means and Variances (RPLMV). The McFadden \(\rho^{2}\) value fell within acceptable limits. This research contributes to the understanding of YAM-related crashes and offers policy recommendations that serve as guidelines for reducing injury severity among YAMs involved in local road crashes. In summary, the analysis yielded several key findings. Firstly, both the urban and rural models exhibited parameter values that shared the same direction, indicating some level of consistency in their respective relationships with the variables under consideration. Nevertheless, notable distinctions emerged in terms of the Marginal Effects (ME), with certain variables demonstrating significance exclusively in one of the models. In the context of the urban local roadway model, variables associated with high marginal effects included instances where the rider did not possess a driver's license, occurrences of male drivers exceeding speed limits, accidents transpiring at night without adequate lighting, and accidents occurring at night with adequate lighting. These factors collectively contributed to an elevated likelihood of fatal outcomes for YAMs. Conversely, variables such as proximity to intersections, accidents transpiring in foggy or smoky conditions, and those transpiring during the afternoon and morning hours appeared to hold the potential to mitigate the severity of YAM fatalities in this urban context. Conversely, the rural local roadway model identified a distinct set of variables that exerted a pronounced influence on collision outcomes. This set of variables included male drivers, instances where the driver did not possess a valid driver's license, and accidents attributed to drivers exceeding legal speed limits. Conversely, accidents occurring during rain, around curves, those involving local riders, and those transpiring during the daytime and nighttime hours were associated with a reduced likelihood of YAM fatalities in the rural setting. In conclusion, the analysis underscores the nuanced dynamics at play within urban and suburban contexts, revealing variations in the significance and impact of specific variables on the severity of accidents involving young adult males. These findings provide valuable insights for crafting targeted safety measures and interventions in these distinct roadway environments. Policy recommendations to reduce injury severity in YAM crashes were derived from notable marginal effect values. Exceeding the speed limit is the primary cause of YAM crashes, leading to a high likelihood of fatalities, particularly on rural roads. For rural roads, it is recommended to increase law enforcement measures. However, due to the extensive spatial areas, this may be challenging. As a result, it is advisable to initially focus on areas with high motorcycle crash density. Subsequently, CCTV cameras can be installed to monitor speed in these areas. Additionally, traffic engineering principles can be applied, such as installing speed warning signs and utilizing pavement on urban roads [41]. Despite the presence of stringent speed control measures, checkpoints at night should also be established in areas with high concentrations of motorcycle crashes. Another issue identified in this study is the involvement of unlicensed YAMs in crashes, who were found to have a higher fatality risk. Parameter values revealed that urban local roads had higher fatality rates.