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題名：航空保費影響因素與風險管理策略之研究
作者：林宜欣 引用關係
作者(外文)：Yi-Hsin Lin
校院名稱：國立成功大學
系所名稱：交通管理學系碩博士班
指導教授：張有恆
學位類別：博士
出版日期：2007
主題關鍵詞：航空公司；航空保險；風險分析；風險管理；航空保費影響因素；灰色關聯分析法；模糊層級分析法；Aviation Insurance；Risk Analysis；Airline；Determinants of Aviation Insurance；Fuzzy Analytic Hierarchy Process；Risk Management；Grey Relational Analysis
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　　源起於911事件的發生，使得航空保險相關課題開始受到重視，但過去有關航空保險的研究較為匱乏，探討的議題也偏重法規面。但航空保險的歷史發展、種類應用、核保與理賠及影響保費的因素等，卻與航空公司的經營息息相關。因此本研究的目的，主要藉由蒐集航空保費客觀的歷史資料與主觀的專家意見，以對航空保險有更深入的瞭解，並確認影響航空保費的重要因素與相對重要性。
　　為達成研究目的，本研究利用專家訪談及文獻回顧，以窮取影響保費之因素；並運用灰色關聯分析，對1999年國籍航空公司的保費資料進行因素重要性排序，而後利用專家問卷進行認知之探索，融合非量化因素加以分析排序，以獲取影響航空保費的重要因素。最後，分析兩種資料所得之結果，並由航空公司的損失經驗提出風險管理策略。
　　根據灰色關聯分析的結果發現，影響航空保費的指標排序為：損失經驗、機隊組成、營運狀況、航空人員績效及財務狀況；而重要影響因素( )分別為：前一年造成的死亡人數與賠款、收益旅客公里數(RPKs)、失事次數、航務人員缺失率、機隊可售座位數、飛機架數、主要航線地區之安全指標、事故次數、平均機齡與飛機每年使用小時。模糊層級分析法的評估結果，前五個指標為：損失經驗、機隊組成、營運狀況、駕駛員績效與技術性慣例；而前一年度造成的傷亡人數、前一年度的損失率、機隊價值、前一年度的理賠金額、起降次數、RPKs/RPMs、額外自負額或保險、IATA營運安全稽核、平均機齡及駕駛員的失事報告則是最重要的十個影響因素。
　　本研究利用國內六家航空公司的損失嚴重度與頻率加以分析，依對風險的承受能力歸類至風險分析矩陣中。利用保險來移轉風險是每家航空公司必要的風險管理策略，除此之外，損失嚴重度與頻率皆高的航空公司，宜利用避免並控制損失的策略；若風險頻率發生高，但嚴重度不大，適合運用預防並降低風險策略；在航空公司風險幅度與嚴重度都不高的情況下，若企業能力許可，可以利用承擔風險策略，來減少額外的風險處理開支。最後，並依據研究目的進行回顧與結論，並提出本研究的管理實務意涵，及對國內航空公司的具體建議，與未來研究的發展方向。
Aviation insurance has become a heavy burden for the airline industry business since September 11, 2001. Most of the literature written for and about the airlines has concentrated on the operation and management of the industry, but very few studies have examined the question of aviation insurance. The purpose of this thesis is to survey the historical data of aviation insurance premiums and investigate expert opinions to identify determinants of aviation insurance and their priority.
First, this study adopted literature review and in-depth interview with experts is working in airline and insurance company was conducted to categorize factors of influence aviation insurance. Following this study applied quantitative historical data (1999~2000) and grey relation analysis (GRA) to identify the primary factors influencing ratemaking for aviation insurance premiums. Fuzzy analytic hierarchy process (FAHP) was used to analysis the priority of influencial factors from expert quesionnair. Finally, to compare the outcome between GRA and FAHP to suggest risk management strategies throuth loss experience of individual airlines.
Both of results from subjective and objective methods showed that the loss experience and performance of individual airlines were the key elements associated with aviation insurance premiums paid by each airline. After normalizing original loss data, this research used a risk analysis matrix to compare the loss severity against loss frequency of the six airlines and to suggest the best risk management strategies at different loss severity and frequency levels. By identifying and understanding the primary factors influencing ratemaking for aviation insurance, airlines will better understand their relative operational strengths and weaknesses, and further help top management identify areas for further improvement. Knowledge of these factors combined with effective risk management strategies could potentially result in lower premiums and a reduction in expenditures for airline companies.
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