- 學位論文
航空公司託運行李處理失誤之影響因素分析 –以 C 航空集團為例
Determinants of Baggage Mishandling – A Case Study of the C Aviation Group
摘要
隨著全球旅運人口的逐年增長，為航空運輸業帶來豐厚利潤的同時，也同時對航空公司、機場及相關地勤業現有的基礎設施和營運流程造成壓力，致使相關行業不斷加強關注、投資以期改善行李遞送失誤。本研究以C航空集團2018年桃園機場進出之客運定期航線資料，輔以航班（不含加班機/包機）開立之處理失誤行李報告，依行李延誤(包含遺失)及行李毀損(包含內容物丟失)進行分析。建構三類比例反應迴歸模式，用以了解託運行李在遞送過程中造成處理失誤的影響因素及其相對重要性，以期提供相關業別在處理託運行李流程、設備等方面的調整和改善參考，以降低營運成本並提升旅客的飛行體驗。結果顯示，模式確實存在異方差的問題，選用異方差之普羅比模式分析較為合理；個別因素方面，行李自動分揀系統有助於降低行李延誤與損毀、窄體機型與轉機行均會導致較高之行李延誤與損毀、飛航酬載限制會產生可觀之行李延誤、行李總件數與總重量則分別對延誤與損毀有負面之影響、所使用航站亦會造成顯著之延誤與損毀績效差異。
並列摘要
As the global travel population grows year by year, it brings huge not profits to the air transport industry but also gives pressure on the existing infrastructure and processes of airlines, airports and related ground handling companies, resulting in continuous attention and investment in related industries to improve the occurrence of mishandled baggage. This study is based on the handling of the baggage report issued by the C Aviation Group during the whole year from January to December 2018 at the Taoyuan Airport for passenger scheduled flights (excluding extra/charter), depending on baggage delay (including lost) and baggage damage. (including pilferage) for analysis. To compare the three models of the fractional response regression, Fractional Probit Model, the Fractional Probit with Heteroskedastic Model, and the Fractional Logit Model . Discuss the probability of the mishandled baggage and model building analysis and understand the influencing factors of the mishandled baggage caused by the checked baggage during the delivery process, and providing the airline, ground handling agency, airport company and related industries in handling the checked baggage process and adjustments and improvements to equipment and other aspects to reduce operating costs and enhance the passenger's flight experience.