Recommendation for Future Research

This study has several limitations and suggests possible improvements for future research.

1. Network variables

This study only included connected airports in East Asia due to data limitation.

Although spatially proximate connected airports are likely to have a direct influence, further inclusion of connected airports out of East Asia would increase the accuracy of the results.

Moreover, this study only included first-layer connected airports, i.e., connected airports that are directly linked to the origin or destination airport. Given that air traffic operates in a network, non-directly linked connected airports are also likely to have an influence on a route’s delays, although such an influence may be weaker than that of first-layer connected airports.

2. Dependent variables

This study only estimated models with the dependent variable in continuous form, i.e., the minute difference between actual and scheduled arrival (departure) times. In future research, dependent variables in other forms, such as log, binary, or multinomial, may be examined to improve the robustness of the empirical results of this study or to acquire a new discovery regarding this research topic.

3. Independent variables

Although several variables are significant, the overall goodness-of-fit of the regression models is low, which means that several important variables are still not included in the models. For example, weather is an important determinant of flight delays.

ATC is also one of the most important factors of the serious delays of China’s airports

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and carriers. However, we cannot obtain such data. If they can be acquired, then the goodness-of-fit of the models may be enhanced.

4. Interviewees

Only airlines, airports, and competent authorities in Taiwan are interviewed in this study. If interviews with other countries’ stakeholders can be realized, then possible determinants in other East Asian countries may be identified, and an accurate understanding of the existing variables in the East Asian context can be acquired.

5. Discrimination among carriers and routes

This study used the daily average delay of a route as the dependent variable. As a result, no discrimination among carriers is conducted. However, careful discrimination among different carriers, discrimination between flag and non-flag carriers, and discrimination between traditional full-service and low-cost carriers can be performed. Discrimination between international and domestic routes may also be done to further clarify possible differences.

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Azadian, F., Murat, A. E., & Chinnam, R. B. (2012). Dynamic routing of time-sensitive air cargo using real-time information. Transportation Research Part E: Logistics and Transportation Review, 48(1), 355-372

Bendinelli, W. E., Bettini, H. F., & Oliveira, A. V. (2016). Airline delays, congestion internalization and non-price spillover effects of low cost carrier entry.

Transportation Research Part A: Policy and Practice, 85, 39-52

Bergman, J. (2016). This is why China’s airports are a nightmare. BBC. Retrieved February 8, 2018, from http://www.bbc.com/capital/story/20160420-this-is-why-chinas-airports-are-a-nightmare

Brueckner, J. K. (2002). Airport congestion when carriers have market power. American Economic Review, 92(5), 1357-1375

BTS. (2017). On-time performance – Flight delays at a glance. Bureau of Transportation

Statistics. Retrieved August 13, 2017, (in

https://www.transtats.bts.gov/HomeDrillChart.asp).

Chang, Y. H. (2012). Air Transportation (3rd ed.). Taipei, Taiwan: Hwa Tai. (in traditional Chinese).

Diana, T. (2009). Do market-concentrated airports propagate more delays than less concentrated ones? A case study of selected US airports. Journal of Air Transport Management, 15(6), 280-286

Diana, T. (2017). Has market concentration fostered on-time performance? A case study of seventy-two US airports. Journal of Air Transport Management, 58, 1-8 Duval, D. T. (2014). Scale and scope of commercial air transport in the Asia Pacific. In

D. T. Duval (Ed.), Air transport in the Asia Pacific (pp. 1-10). Farnham, England:

Ashgate

Fan, L., Wu, F., & Zhou, P. (2014). Efficiency measurement of Chinese airports with flight delays by directional distance function. Journal of Air Transport Management, 34, 140-145

FlightStats. (2015). 2015 airport on-time departure performance: All regions. 2015 On-Time Performance Service Awards Data. Retrieved July 30, 2017, from

114

http://www.flightstats.com/company/media/on-time-performance-awards/2015-on-time-performance-service-awards-data/

FlightStats. (2017). Airports by size and region - May 2017. Airport On-Time Performance Reports. Retrieved August 13, 2017, from http://www.flightstats.com/company/monthly-performance-reports/airports/

Greene, W. H., & Econometric Software, Inc. (2012). LIMDEP Version 10: Econometric Modeling Guide. NY: Econometric Software, Inc.

Greenfield, D. (2014). Competition and service quality: New evidence from the airline industry. Economics of Transportation, 3(1), 80-89

Gu, M., Yu, Y., & Ping, Y.-C. (2018). Analysis of China's airspace management system.

Legal System and Society, 09, 27-28 (in Simplified Chinese).

Hao, L., Hansen, M., Zhang, Y., & Post, J. (2014). New York, New York: Two ways of estimating the delay impact of New York airports. Transportation Research Part E: Logistics and Transportation Review, 70, 245-260

He, W. (2013). Causes and Solutions of Flight Delay for Air Traffic Management.

Journal of Civil Aviation Flight University of China, 24(4), 35-37

IATA. (2017). WSG Annex 11.6. Contact list for Level 2 and Level 3 Airports. Retrieved February 8, 2018, from http://www.iata.org/policy/slots/Documents/wsg-annex-11.6.xlsx

ICAO. (2011). Appendix 1. Tables relating to the world of air transport in 2011.

Retrieved July 29, 2017, from

https://www.icao.int/publications/Documents/9975_en.pdf

ICAO. (2017). Table 4. Regional distribution of scheduled traffic — 2017. Retrieved October 12, 2018, from https://www.icao.int/annual-report-2017/Documents/Annual.Report.2017_Air%20Transport%20Statistics.pdf Mayer, C., & Sinai, T. (2003). Network effects, congestion externalities, and air traffic

delays: Or why not all delays are evil. The American Economic Review, 93(4), 1194-1215

Mazzeo, M. J. (2003). Competition and service quality in the US airline industry. Review of Industrial Organization, 22(4), 275-296

Paleari, S., Redondi, R., & Malighetti, P. (2010). A comparative study of airport connectivity in China, Europe and US: which network provides the best service to passengers? Transportation Research Part E: Logistics and Transportation Review, 46(2), 198-210

Prince, J. T., & Simon, D. H. (2009). Multimarket contact and service quality: Evidence from on-time performance in the US airline industry. Academy of Management Journal, 52(2), 336-354

115

Prince, J. T., & Simon, D. H. (2014). Do incumbents improve service quality in response to entry? Evidence from airlines' on-time performance. Management Science, 61(2), 372-390

Rupp, N. G. (2009). Do carriers internalize congestion costs? Empirical evidence on the internalization question. Journal of Urban Economics, 65(1), 24-37

Rupp, N. G., Owens, D., & Plumly, L. (2006). Does competition influence airline on-time performance. Advances in Airline Economics: Competition Policy and Antitrust, 1, 251-272

Santos, G., & Robin, M. (2010). Determinants of delays at European airports.

Transportation Research Part B: Methodological, 44(3), 392-403

UN. (2018). World Economic Situation and Prospects. Retrieved October 10, 2018, from

https://www.un.org/development/desa/dpad/wp-content/uploads/sites/45/publication/WESP2018_Full_Web-1.pdf

VariFlight. (2017). Asia Pacific airports, monthly flights equal to or more than 2,000.

Global airport on-time rate ranking. Retrieved July 19, 2018, from https://data.variflight.com/analytics/OTPRankingbyAirport (in Simplified Chinese).

Washington, S. P., Karlaftis, M. G., & Mannering, F. L. (2011). Statistical and Econometric Methods for Transportation Data Analysis (2nd ed.). Boca Raton, FL: Taylor & Francis.

Yimga, J. O. (2017). Airline code-sharing and its effects on on-time performance. Journal of Air Transport Management, 58, 76-90

Yue, R.-T., & Wei, Z.-Q. (2014). The correlation of flight delays among multi-airports based on matter-element secondary extension and delay prediction. Science Technology and Engineering, 14(28), 298-315 (in simplified Chinese).

Zhang, J., Xu, S.-H., Wang, F., & Wei, D.-X. (2010). Airport delay performance evaluation based on fuzzy linear regression model. Journal of Traffic and Transportation Engineering, 10(4), 109-114 (in simplified Chinese).

Zhang, K. (2016). Research on correlation flight delays among multi airports.

(Unpublished master's thesis), Civil Aviation University of China, Tianjin, China.

(in simplified Chinese).

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Appendix A. Study airports, slot control level, number of connections and hub size

Airport^a Slot^b Country Conn.^b Hub size^c Airport Slot Country Conn. Hub size

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Airport^a Slot^b Country Conn.^b Hub size^c Airport Slot Country Conn. Hub size WNZ Level 1 China 22 small YIH Level 1 China 8 non-hub WUA Level 1 China 3 non-hub YIN Level 1 China 4 non-hub WUH Level 1 China 60 medium YIW Level 1 China 9 non-hub WUS Level 1 China 3 non-hub YKH Level 1 China 2 non-hub WUT Level 1 China 1 non-hub YNJ Level 1 China 8 non-hub WUX Level 1 China 23 small YNT Level 1 China 24 small WXN Level 1 China 3 non-hub YNZ Level 1 China 10 non-hub XFN Level 1 China 3 non-hub YSQ Level 1 China 1 non-hub XIC Level 1 China 3 non-hub YTY Level 1 China 15 small XIL Level 1 China 3 non-hub YUS Level 1 China 3 non-hub XIY Level 3 China 77 large YZY Level 1 China 2 non-hub XMN Level 1 China 57 medium ZAT Level 1 China 3 non-hub XNN Level 1 China 22 small ZHA Level 1 China 12 non-hub XUZ Level 1 China 8 non-hub ZHY Level 1 China 1 non-hub YBP Level 1 China 6 non-hub ZQZ Level 1 China 3 non-hub YCU Level 1 China 12 non-hub ZUH Level 1 China 24 small YGJ Level 1 Japan 1 non-hub ZYI Level 1 China 10 non-hub

a IATA code of the airport.

b Slot: slot control level of the airport; conn.: total number of destinations served by the airport.

c According to Santos and Robin (2010), small, medium, and large airports are airports with 15-44, 45-69, and 70+ destinations.

120 Appendix B. Interview records (in Traditional Chinese)¹⁰

訪談記錄(AL001)

10 Since the original geographical scope of this study is Asia Pacific, some interview questions were asked and answered based on Asia Pacific. However, as the interviewees are Taiwanese authorities and carriers, and most of the Asian Pacific countries they mentioned are in East Asia, these interviews should still be applicable for this study.

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受到機場的何種特性影響？吞吐量相近之機場，準點率亦會有所差異，您認為 可能是甚麼原因所造成？A 航空公司會如何處理其影響？

機場對於準點率有極高的影響力。

首先，機場有大有小，通常大機場延誤較嚴重。不過，不是完全正相關，因為小機 場也可能因機坪（parking bay）、跑道等設施不足而造成延誤。本身的設施條件會 影響準點率。

在航務設施如跑道、滑行道、飛航輔助設施方面，機坪多寡影響同一時間能容納的 航班數量，機坪數量不夠即會造成航班無法停靠而必須延遲抵達機門。

在運務設施如地勤人員、航站設施規劃等方面，航站規劃影響到乘客走到登機門、

更換登機門與轉機時所需花費的時間，若乘客不及登機而航班必須等待，也會造成 延誤。而因為機坪數量有限，一個航班延誤，就會遞延影響到後續航班的準點率。

一般而言，機場規模與航班延誤情形是正相關的。

再者，機場的性質或所受管制也會影響準點率。例如，松山、台中、台南、花蓮機 場等是軍民合用機場，因為軍機場會有諸多管制，其塔臺設施、氣象預報等皆歸軍 方管，且通常不如民用機場準確，因而經常造成延誤的情形。另外，在台灣僅有桃 園機場沒有宵禁，其他機場均有宵禁，亦會對延誤有影響。

最後，機場本身、進駐之航空公司及乘客的習慣及文化也會影響準點率。

A 航空公司處理航班延誤的方式大致有以下五種：

(1) 經濟帶油（Fuel tankering）：航空公司因為目的地站油價較高，或目的地站油不

夠，會在前一站先將油加好。若以經濟帶油的方式，會節省加油的時間以及等 油車的時間，會使準點率較好。

(2) 快速掉頭（Quick turnaround，QTA）：有時航空公司會在兩次飛行任務之間進行

QTA，亦即以較減省的方式進行客艙清理，以縮短飛機在地面停留的時間。為 了避免下次飛行任務的延誤，航空公司有時會採取 QTA，使乘客能準時登機。

(3) 提早/準時關櫃：乘客遲到也是航班延誤的原因之一。航空公司為了使航班準點 起飛，有時會通知旅客會提前或是準時關閉 check-in 櫃台，不等待遲到的乘客。

(4) 改變航行之空層（flight level）或增加航行速度：由於不同空層的風速會有差異，

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航空公司有時會選擇高度較高，航行風速較快之空層，以縮短飛行時間，使航 班能準點抵達或彌補起飛之延誤。另外，也可能會增加航行速度，以彌補延誤 的情形。

(5) 不等待（部分）轉機旅客或行李：航空公司有時會選擇不等待（部分）轉機旅 客，使原航班得以準時起飛。另外，有時航空公司也會選擇不等待轉機行李裝 載完畢而先行起飛，行李則交由後續航班或是其他航空公司協助運送。

3. A 航空公司的航線在國際線方面，是以兩岸航線及亞太區域之區域型航線為

主。這樣的航線安排，是否對於 A 航空公司之準點率有影響？兩岸航線及亞 太區域航線的準點率是否有差別？A 航空公司會如何處理其影響？

有，且兩者差異很大。

兩岸航線方面，由於中國的空域是由軍方管制，時常會有航空管制，而有流量限制 之情形，航空器需要在地面等待；另外，由於中國航班多，機場繁忙，而且很多機 場屬於軍方管轄由於上述原因，兩岸航班通常延誤情形很嚴重。

亞太區域其他航線，則多受到一般性因素的影響，如天氣等自然環境、地勤代理作 業速度等人為因素。另外，人的因素亦會有所影響。

A 航空公司對於此等影響的處理方式和 2.所述相同。

4. 「連結機場」，亦即與起迄機場相連之機場，是否及如何影響 A 航空公司的準

點率？A 航空公司會如何處理其影響？

連結機場會有影響。由於航管是一個網絡（network），若某地的航管有流量管制，

例如上海浦東流管，或夏天雷雨季香港經常有流管，則會要求在桃園機場的飛機先 不要起飛，在地面等待。又由於港台線航班特多，一度是世界上流量最大的航線，

因此，例如原本一小時該航線有四班航班，現在香港流量管制一小時只能放行一班，

則桃園機場出發之機場就延誤了，但延誤原因是來自香港的流量管制。

但若以航線為單位來看，以巨觀的角度，整體航空網絡會受連結機場影響；但以微 觀的角度，通常連結機場來的航班延誤，但該航空器不一定有後續任務，如果沒有，

就不會影響到後續航班。另外，即使該航班有後續任務，但若有延誤嚴重的情形，

通常會調另外的航空器來執行後續的飛行任務。因此，以微觀的角度，則連結機場 影響可能不大。

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另外，亞太區域航空運輸市場近年來有爆炸型的成長，相應的制度、設備卻不完善，

另外民族性也差異甚大，亦為本區域航空運輸市場的特色。

9. 除了上述提及之因素，您是否認為有其他重要但未被納入之因素呢？

無。

10. 您是否願意提供本研究其他寶貴的意見？

可以參考 IATA delay code，亦即 IATA 所歸納的各航班延誤原因。

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訪談記錄(AL002)

訪 談 編 號 AL002

訪 談 時 間 2018 年 3 月 12 日 11 時 00 分至 12 時 24 分

訪 談 地 點 台北市咖啡店

訪 談 地 點 台北市咖啡店