Towards realizing best-in-class civil aviation strategy scenarios

Developed and less developed countries follow different approaches during the formulation of aviation strategic plans. Additionally, there exists no pre-defined framework to guide developing countries in formulating civil aviation strategies matching their macro-environment and competitiveness levels while addressing their future vision for growth or sustainability. Instead, civil aviation planning over-look these priorities and is often dictated by local political pressures, and mostly influenced by uncoordinated foreign aid assistance. Hence, developing countries use dissimilar and un-structured approaches to reach what is known as “civil aviation master plan” or “draft civil aviation policy”. Recognizing that a problem exists in the mechanism for civil aviation planning in this part of the world, research is encouraged to highlight this substantial topic. This paper uses a scenario-based approach to study the roles played by the macro-environment and industry-level performance in realizing best-fit national civil aviation strategies. The goals are achieved through utilizing a two-stage performance benchmarking technique named Data Envelopment Analysis (DEA) on country level data on a sample of 52 countries in different stages of development, followed by truncated regression. Results of the best performing countries—in terms of output efficiency, indicate that the country's macro-environment and air transport sector's performance serve as guidelines to identify aviation policy elements that are considered to impact efficiency. The regression results indicate that a more liberal air services approach is said to be of positive influence on efficiency levels. Further, we show that private airports are more efficient, while public airports are even less efficient than those with mixed ownership/management model. Hence, policy makers are encouraged to adopt an efficient peer analysis approach based on influential policy elements to bridge performance gaps, achieve better operating capacity, direct and prioritize investments in the civil aviation sector.

[1]  Abraham Charnes,et al.  Measuring the efficiency of decision making units , 1978 .

[2]  C Murillo-Melchor,et al.  AN ANALYSIS OF TECHNICAL EFFICIENCY AND PRODUCTIVITY CHANGES IN SPANISH AIRPORTS USING THE MALMQUIST INDEX , 1999 .

[3]  C. Barros,et al.  Measuring the economic efficiency of airports: A Simar–Wilson methodology analysis , 2008 .

[4]  M. Abbott,et al.  Total Factor Productivity and Efficiency of Australian Airports , 2002 .

[5]  Joseph Sarkis,et al.  Performance based clustering for benchmarking of US airports , 2004 .

[6]  Jean C. Bedard Use of data envelopment analysis in accounting applications : evaluation and illustration by prospective hospital reimbursement , 1985 .

[7]  T. Oum,et al.  MEASURING AIRPORTS' OPERATING EFFICIENCY: A SUMMARY OF THE 2003 ATRS GLOBAL AIRPORT BENCHMARKING REPORT , 2004 .

[8]  Anthony D. Ross,et al.  An analysis of operations efficiency in large-scale distribution systems , 2004 .

[9]  Carl A. Scheraga,et al.  Operational efficiency versus financial mobility in the global airline industry: a data envelopment and Tobit analysis , 2004 .

[10]  Jose L. Tongzon,et al.  Efficiency measurement of selected Australian and other international ports using data envelopment analysis , 2001 .

[11]  Noriyoshi Nakayama,et al.  A Comparison of Parametric and Non-Parametric Distance Functions , 2003 .

[12]  Nicole Adler,et al.  Measuring airport quality from the airlines' viewpoint: an application of data envelopment analysis , 2001 .

[13]  Kenneth Button,et al.  X-inefficiency and regulatory regime shift in the UK , 1993 .

[14]  Cláudia S. Sarrico,et al.  Data Envelopment Analysis: A Comprehensive Text with Models, Applications, References and DEA-Solver Software , 2001, J. Oper. Res. Soc..

[15]  A. Zhang,et al.  Effects of competition and policy changes on Chinese airport productivity: An empirical investigation , 2008 .

[16]  F Salazar de la Cruz A DEA APPROACH TO THE AIRPORT PRODUCTION FUNCTION , 1999 .

[17]  Vicente Pina,et al.  Analysis of the efficiency of local government services delivery. An application to urban public transport , 2001 .

[18]  Hidekazu Itoh Effeciency Changes at Major Container Ports in Japan: A Window Application of Data Envelopment Analysis , 2002 .

[19]  Yaakov Roll,et al.  An application procedure for DEA , 1989 .

[20]  Eric Pels,et al.  A note on airline alliances , 2001 .

[21]  W. Brian Arthur,et al.  On designing economic agents that behave like human agents , 1993 .

[22]  F Pedraja-Chaparro,et al.  On the quality of the data envelopment analysis model , 1999, J. Oper. Res. Soc..

[23]  Martin Dresner,et al.  NORTH AMERICAN CONTAINERPORT PRODUCTIVITY: 1984-1997 , 2004 .

[24]  P. Nijkamp,et al.  Inefficiencies and scale economies of European airport operations , 2003 .

[25]  B. Vasigh,et al.  SIZE VERSUS EFFICIENCY: A CASE STUDY OF US COMMERCIAL AIRPORTS , 2003 .

[26]  John F. O׳Connell,et al.  A macro-environment approach to civil aviation strategic planning , 2014 .

[27]  Ilona Jaržemskienė,et al.  Applying the method of measuring airport productivity in the Baltic region , 2012 .

[28]  Elton Fernandes,et al.  CAPITAL STRUCTURE IN THE WORLD AIRLINE INDUSTRY , 2004 .

[29]  Sergio Perelman,et al.  A comparison of parametric and non-parametric distance functions: With application to European railways , 1999, Eur. J. Oper. Res..

[30]  T. Oum,et al.  Ownership Forms Matter for Airport Efficiency: A Stochastic Frontier Investigation of Worldwide Airports , 2008 .

[31]  T. Oum,et al.  A comparative analysis of productivity performance of the world's major airports: summary report of the ATRS global airport benchmarking research report—2002 , 2003 .

[32]  Ayoe Hoff,et al.  Second stage DEA: Comparison of approaches for modelling the DEA score , 2007, Eur. J. Oper. Res..

[33]  W. Cooper,et al.  Data Envelopment Analysis: A Comprehensive Text with Models, Applications, References and DEA-Solver Software , 1999 .

[34]  Anne Graham Fundamentals for airport privatization and concession policies , 2009 .

[35]  David Gillen,et al.  DEVELOPING MEASURES OF AIRPORT PRODUCTIVITY AND PERFORMANCE: AN APPLICATION OF DATA ENVELOPMENT ANALYSIS , 1997 .

[36]  A. U.S.,et al.  Measuring the efficiency of decision making units , 2003 .

[37]  D. Gillen,et al.  NON-PARAMETRIC MEASURES OF EFFICIENCY OF U.S. AIRPORTS , 2001 .

[38]  Ali Emrouznejad,et al.  Data Envelopment Analysis Model for the Appraisal and Relative Performance Evaluation of Nurses at an Intensive Care Unit , 2010, Journal of Medical Systems.

[39]  D. McFetridge Competitiveness Concepts and Measures , 1995 .

[40]  Attah K. Boame THE TECHNICAL EFFICIENCY OF CANADIAN URBAN TRANSIT SYSTEMS , 2004 .

[41]  P. W. Wilson,et al.  Estimation and inference in two-stage, semi-parametric models of production processes , 2007 .

[42]  David Gillen,et al.  The evolution of airport ownership and governance , 2011 .

[43]  Paolo Malighetti,et al.  The impact of airport competition on technical efficiency: A stochastic frontier analysis applied to Italian airport , 2012 .

[44]  K. Kerstens Technical efficiency measurement and explanation of French urban transit companies , 1996 .