2020年及2022年面臨新冠肺炎疫情影響，國內遊覽觀光產業快速緊縮及國外來臺觀光旅遊人次驟降，對遊覽車客運業的營運成本更是雪上加霜，且整體遊覽車不論是行駛里程或行駛天數均受新冠疫情影響明顯下降，然而同一時期肇事件數未見等同比例的降低。公部門歷年來為降低遊覽車行車事故，制訂各項法規暨管理安全措施，運用科技化管理方式，建立違規預警扣分制度及車輛動態資訊平台，監管遊覽車行車狀況，然道安資訊查詢網顯示遊覽車行車事故仍未顯著減少，遊覽車所發生的事故原因可能來自不同因素，如車輛本身安全設備、天候因素、駕駛員工時過久及靠行車管理不易等，皆會影響遊覽車服務品質及行車安全。世界各國對於行車安全訂為首要目標，更何況遊覽車多屬大型巴士，載客人數多，業者行車安全風險性是極高的，因此，政府必須迫切重視遊覽車營運產業及行車安全議題。
本研究搜集109家雲嘉南地區之業者，資料區間為2019年至2021年三年年資料，並依照遊覽車業者行車事故的數量與肇事責任比例，計算出業者的肇事權重分數，區別其行車安全風險的等級，考慮的影響變數包含違規預警扣分分數、動態資訊平台告警次數、交通車承攬比例、靠行比例及評鑑等第等5項，建構出遊覽車業者肇事權重分數、行車事故次數，以及行車安全風險等級的可能影響因素之模式，並且分別以迴歸模型、卜瓦松迴歸及二元羅吉特模式等研究方法進行分析，再根據研究結果，提出具體建議以供政府與遊覽車客運業如何源頭管理，減少行車事故的發生，藉以提升行車安全。
本研究的結果簡述如下：迴歸模式結果顯示交通車承攬比例與動態資訊平台告警次數對肇事權重分數有顯著的正向效果；卜瓦松迴歸結果顯示交通車承攬比例、動態資訊平台告警次數，與違規預警扣分分數對行車事故次數有顯著的正向效果；二元羅吉特模式結果顯示交通車承攬比例、動態資訊平台告警次數，與違規預警扣分分數對行車事故次數有顯著的正向效果，而模式中當此三個變數增加1單位時，高風險業者相對於低風險業者的勝算比增加分別為4.01倍、1.24倍、6.13倍，然而靠行比例對業者行車安全風險等級有顯著的負向效果。顯見遊覽車客運業者之違規預警扣分分數、動態資訊平台告警次數，以及交通車承攬比例等三項為風險控管之關鍵特徵。

The Covid-19 pandemic had a disastrous impact on the tourism industry both domestically and internationally from 2020 to 2022. At the time, the tour bus industry suffered significant losses in revenue as a result of lower average mileage and fewer rental days. To reduce the number of accidents involving tour buses, the authorities have formulated various regulations and safety measures over the years. For example, a penalty point system based on early warnings given for traffic violations (PSEW) and the vehicle dynamic information platform (VDIP) were established to monitor the driving patterns of tour bus drivers. However, statistics on road safety suggest that the rate of tour bus accidents has not decreased accordingly. The causes of tour bus accidents may come from different factors, such as safety equipment of tour bus, weather factor, long working hours of driver, and companies that are unable to supervise their drivers etc. Thus, the quality of tour bus service and road safety are affected. In general, road safety is seen as a priority in traffic management. As a large vehicle, a tour bus carries many passengers and potentially presents a high risk to road safety. Therefore, the government urgently needs to pay attention to the operations of the tour bus industry and to the corresponding impact on road safety.
For this study, operational data was collected in relation to 109 tour bus operators located in the area encompassing the cities of Yunlin, Chiayi, and Tainan, in southwestern Taiwan, during the three-year period from 2019 to 2021. The accident weighted score of an operator is calculated by number of its accidents and corresponding accident responsibility ratios. Then the traffic safety risk level of an operator can be distinguished based on the ranking of accident weight scores. A number of potentially influential variables were taken into consideration in the analyses: the number of points accumulated for PSEW; the number of alerts on the VDIP; the ratio of shuttle bus business; the ratio of license-leasing buses belonging to an operator; and the evaluation performance of an operator. To identify potential risk factors for accidents involving tour buses, three models were developed: (1) a regression model was applied to the operator’s accident weighted score; (2) a Poisson regression model was used to examine the number of accidents per tour operator; and (3) a binary logistic regression model was used to assess the level of risk to road safety. Specific suggestions are drawn from the results of the study to the government and tour bus industry in order to reduce tour bus accidents and enhance road safety.
The results of this study can be summarized as follows. In the results of the regression showed that the ratio of shuttle bus businesses and the number of alerts on the VDIP had a significant positive effect on the weighted score for the accidents involving each operator. In the Poisson regression revealed that the ratio of shuttle bus businesses, the number of alerts on the VDIP, and the PSEW had a significant positive effect on the number of accidents per operator. Based on the binary logistic regression, the ratio of shuttle bus businesses, the number of alerts on the VDIP, and the PSEW had a significant positive effect on the extent of the risk to road safety posed by an operator. Of particular interest is the finding that, for each unit of increase in each of these three variables, the odds ratios for the high-risk operators were 4.01 times, 1.24 times, and 6.13 times higher, respectively, compared to those for the low-risk operators. However, the ratio of license-leasing buses belonging to an operator had a significant negative effect on the level of the risk to road safety of an operator. Therefore, the ratio of shuttle bus businesses, the number of alerts on the VDIP, and the PSEW played key roles in risk control with regards to the tour bus industry.

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