An Investigation into the Determinants of Flight Cancellations

This paper uses Bureau of Transportation data on 35 million US domestic flights between 1995 and 2001 to investigate the determinants of flight cancellations. The paper is novel in two regards, it focuses exclusively on flight cancellations, and it explores the service quality–flight revenue relationship. We find that carriers have some control over the occurrence of flight cancellations given that cancellations are significantly less likely on Thursdays, Fridays and Sundays and for the last flight of the day. There is some evidence linking cancellations with revenue.

[1]  Jeffrey S. DeSimone,et al.  Airline Schedule Recovery after Airport Closures: Empirical Evidence since September 11 , 2005 .

[2]  Q. Vuong Likelihood Ratio Tests for Model Selection and Non-Nested Hypotheses , 1989 .

[3]  Jan K. Brueckner,et al.  Airport Congestion When Carriers Have Market Power , 2002 .

[4]  Jonathan F. Bard,et al.  Multiple fleet aircraft schedule recovery following hub closures , 2001 .

[5]  C. Hoxby,et al.  Appendices to : “ Does Competition among Public Schools Benefit Students and Taxpayers ? , 2004 .

[6]  C. Winston,et al.  Deregulation of Network Industries: What's Next? , 2000 .

[7]  Harumi Ito,et al.  Assessing the impact of the September 11 terrorist attacks on U.S. airline demand , 2004, Journal of Economics and Business.

[8]  S. Foreman,et al.  Publication of Information and Market Response: The Case of Airline on Time Performance Reports , 1999 .

[9]  Nicholas G. Rupp,et al.  Airline Schedule Recovery after Airport Closures: Empirical Evidence Since September 11th , 2003 .

[10]  Yoshinori Suzuki,et al.  The relationship between on-time performance and airline market share: a new approach , 2000 .

[11]  Michael J. Mazzeo Competition and Service Quality in the U.S. Airline Industry , 2003 .

[12]  Darin Lee,et al.  Entry Patterns in the Southwest Airlines Route System , 2004 .

[13]  C. Hoxby Does Competition Among Public Schools Benefit Students and Taxpayers? , 1994 .

[14]  R. Kranton Competition and the Incentive to Produce High Quality , 2003 .

[15]  Tae Hoon Oum,et al.  GLOBALIZATION AND STRATEGIC ALLIANCES: THE CASE OF THE AIRLINE INDUSTRY , 2000 .

[16]  H. Haes Annual report 2001 , 2002 .

[17]  W. Härdle,et al.  Bootstrap Methods for Time Series , 2003 .

[18]  Janet S. Netz,et al.  Why do all the flights leave at 8 am?: Competition and departure-time differentiation in airline markets , 1999 .

[19]  Rebecca Stratling,et al.  Deregulation of Network Industries. What’s Next? , 2001 .

[20]  Martin Dresner,et al.  COMPETITIVE RESPONSES TO LOW COST CARRIER ENTRY , 1999 .

[21]  Jonathan F. Bard,et al.  Balancing user preferences for aircraft schedule recovery during irregular operations , 2000 .

[22]  Shangyao Yan,et al.  A decision support framework for handling schedule perturbation , 1996 .

[23]  J. MacKinnon,et al.  Estimation and inference in econometrics , 1994 .

[24]  Clifford Winston,et al.  The Evolution of the Airline Industry , 1994 .