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Dynamics in the European Air Transport Network, 2003–9: An Explanatory Framework Drawing on Stochastic Actor-Based Modeling

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Abstract

In this paper, we outline and test an explanatory framework drawing on stochastic actor-based modeling to understand changes in the outline of European air transport networks between 2003 and 2009. Stochastic actor-based models show their capabilities to estimate and test the effect of exogenous and endogenous drivers on network changes in this application to the air transport network. Our results reveal that endogenous structural effects, such as transitivity triads, indirect relations and betweenness effects impact the development of the European air transport network in the period under investigation. In addition, exogenous nodal and dyadic covariates also play a role, with above all the enlargement of the European Common Aviation Area having benefitted its new members to open more air routes between them. The emergence of major low-cost airline-focused airports also significantly contributed to these changes. We conclude by outlining some avenues for further research.

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Notes

  1. Under this concept, an airport becomes a commercial hub, in which a bundle of diversified service propositions and products are offered to an enlarged category of target customers.

  2. Even though the air transport industry experienced the single largest 21st century decline between our the two observation points of 2003 and 2009 due to the SARS epidemic and economic downturn (MacDonald 2011), SABM seems capable of capturing the network change mechanisms between the two observations.

  3. This paper only considers airports where their located cities have a high global network connectivity (GNC) index (Neal 2012). Some tourist destinations in Italy or Spain may, therefore, not be included in the analysis.

  4. These four network effects correspond to nonstop route, one-stop route, hubbing and interconnected subgroup consisting of air transport network in practice.

  5. The LCC bases included in this paper are BCN, BFS, BGY, BRS, CGN, CRL, DUB, DUS, EDI, EMA, FCO, GLA, GVA, HHN, KRK, LGW, LPL, LTN, MAD, MAN, MXP, NCE, NYO, ORY, OSL, RIX, STN, STR, SXF, VIE, VLC.

  6. The difference between the Wald test and the score-type test is that the former is based on the parameter estimates and thereby integrates estimating and testing, whereas the latter tests a parameter without estimating it.

  7. It should be noted that betweenness used to define ‘hubs’ here only shows their spatial characteristics, but not the temporal properties (e.g., the adoption of the wave-system structures to coordinate inbound and outbound flights (Burghouwt and de Wit 2005; O’Kelly 2010)).

  8. For simplicity, we assume that airport A neither locates in a country being a new ECAA member nor a LCC base. In this way, the objective function only includes the four network effects.

References

  • Albers S, Koch B, Ruff C (2005) Strategic alliances between airlines and airports—theoretical assessment and practical evidence. J Air Transp Manag 11:49–58

    Article  Google Scholar 

  • Andrew SA (2009) Regional integration through contracting networks an empirical analysis of institutional collection action framework. Urban Aff Rev 44:378–402

    Article  Google Scholar 

  • Barrat A, Barthelemy M, Pastor-Satorras R, Vespignani A (2004) The architecture of complex weighted networks. Proc Natl Acad Sci U S A 101:3747–3752

    Article  Google Scholar 

  • Boccaletti S, Latora V, Moreno Y, Chavez M, Hwang D-U (2006) Complex networks: structure and dynamics. Phys Rep 424:175–308

    Article  Google Scholar 

  • Boccaletti S, Bianconi G, Criado R, Del Genio C, Gómez-Gardeñes J, Romance M, Sendiña-Nadal I, Wang Z, Zanin M (2014) The structure and dynamics of multilayer networks. Phys Rep 544:1–122

  • Buchmann T, Pyka A (2013) The evolution of innovation networks: the case of a German automotive network. FZID Discussion Papers

  • Burghouwt G (2007) Airline network development in Europe and its implications for airport planning. Ashgate Publishing Limited, Hampshire

    Google Scholar 

  • Burghouwt G, de Wit J (2005) Temporal configurations of European airline networks. J Air Transp Manag 11:185–198

    Article  Google Scholar 

  • Burghouwt G, Hakfoort J (2001) The evolution of the European aviation network, 1990–1998. J Air Transp Manag 7:311–318

    Article  Google Scholar 

  • Cheadle JE, Stevens M, Williams D, Goosby BJ (2013) The differential contributions of teen drinking homophily to new and existing friendships: an empirical assessment of assortative and proximity selection mechanisms. Soc Sci Res 42:1297–1310

  • De Neufville R (2004) The Future of Secondary Airports: nodes of a parallel air transport network? Working Papers, http://ardent.mit.edu/airports/ASP_papers/Cahiers%20S%20du%20Transport%20English%2005--%20Neufville.pdf

  • Dennis N (2005) Industry consolidation and future airline network structures in Europe. J Air Transp Manag 11:175–183

    Article  Google Scholar 

  • Deutsches Zentrum für Luft- und Raumfahrt (DLR) (2011) Low cost monitor 1/2011

  • Dobruszkes F (2006) An analysis of European low-cost airlines and their networks. J Transp Geogr 14:249–264

    Article  Google Scholar 

  • Dobruszkes F (2009) New Europe, new low-cost air services. J Transp Geogr 17:423–432

    Article  Google Scholar 

  • Dobruszkes F, Van Hamme G (2011) The impact of the current economic crisis on the geography of air traffic volumes: an empirical analysis. J Transp Geogr 19:1387–1398

    Article  Google Scholar 

  • Doganis R (2006) The airline business. Routledge, London

    Google Scholar 

  • Ducruet C, Beauguitte L (2014) Spatial science and network science: review and outcomes of a complex relationship. Netw Spat Econ 14:297–316

    Article  Google Scholar 

  • EUROCONTROL (2013) Challenges of growth 2013: task 4: European air traffic in 2035

  • Fan T (2006) Improvements in intra-European inter-city flight connectivity: 1996–2004. J Transp Geogr 14:273–286

    Article  Google Scholar 

  • Fischer M, Ingold K, Sciarini P, Varone F (2012) Impacts of market liberalization on regulatory network: a longitudinal analysis of the Swiss telecommunications sector. Pol Stud J 40:435–457

    Article  Google Scholar 

  • Forsyth P (2010) Competition between major and secondary airports: implications for pricing, regulation and welfare. In: Peter Forsyth DG (ed) Airport competition: the European experience. Ashgate, Surrey, pp 77–87

    Google Scholar 

  • Francis G, Humphreys I, Ison S (2004) Airports’ perspectives on the growth of low-cost airlines and the remodeling of the airport–airline relationship. Tour Manag 25:507–514

    Article  Google Scholar 

  • Goedeking P (2010) Networks in aviation: strategies and structures. Springer, Heidelberg

    Book  Google Scholar 

  • Guimera R, Amaral LAN (2004) Modeling the world-wide airport network. Eur Phys J B 38:381–385

    Article  Google Scholar 

  • Ingold K, Fischer M (2014) Drivers of collaboration to mitigate climate change: an illustration of Swiss climate policy over 15 years. Glob Environ Chang 24:88–98

    Article  Google Scholar 

  • Jarach D (2001) The evolution of airport management practices: towards a multi-point, multi-service, marketing-driven firm. J Air Transp Manag 7:119–125

    Article  Google Scholar 

  • KINNE BJ (2013) Network dynamics and the evolution of international cooperation. Am Polit Sci Rev 107:766–785

    Article  Google Scholar 

  • Liu X, Derudder B, Garcíad CG (2013a) Exploring the co-evolution of the geographies of air transport aviation and corporate networks. J Transp Geogr 30:26–36

    Article  Google Scholar 

  • Liu X, Derudder B, Liu Y (2013b) Regional geographies of intercity corporate networks: the use of exponential random graph models to assess regional network-formation. Papers in Regional Science, n/a-n/a doi:10.1111/pirs.12060

  • Liu X, Derudder B, Liu Y, Witlox F, Shen W (2013c) A stochastic actor-based modelling of the evolution of an intercity corporate network. Environ Plan A 45:947–966

    Article  Google Scholar 

  • MacDonald M (2011) Annual analyses of the EU air transport market – 2010

  • Malighetti P, Paleari S, Redondi R (2008) Connectivity of the European airport network: “self-help hubbing” and business implications. J Air Transp Manag 14:53–65

    Article  Google Scholar 

  • Malighetti P, Paleari S, Redondi R (2009) Airport classification and functionality within the European network. Probl Perspect Manag 7:183–196

    Google Scholar 

  • Neal Z (2012) Structural determinism in the interlocking world city network. Geogr Anal 44:162–170

    Article  Google Scholar 

  • Niemeier PDHM, Forsyth PP, Müller PDJ, Gillen PD (2012) Airport competition: the European experience. Ashgate, Aldershot

    Google Scholar 

  • O’Connor K (2003) Global air travel: toward concentration or dispersal? J Transp Geogr 11:83–92

    Article  Google Scholar 

  • O’Connor K, Fuellhart K (2013) Change in air services at second rank cities. J Air Transp Manag 28:26–30

    Article  Google Scholar 

  • O’Kelly ME (1998) A geographer’s analysis of hub-and-spoke networks. J Transp Geogr 6:171–186

    Article  Google Scholar 

  • O’Kelly ME (2010) Routing traffic at hub facilities. Netw Spat Econ 10:173–191

    Article  Google Scholar 

  • O’Kelly M (2014) Network hub structure and resilience. Netw Spat Econ 1–17. doi:10.1007/s11067-11014-19267-11061.

  • O’Kelly M, Luna H, de Camargo R, de Miranda G Jr. (2014) Hub location problems with price sensitive demands. Netw Spat Econ 1–29. doi:10.1007/s11067-11014-19276-11060.

  • Oum TH, Adler N, Yu C (2006) Privatization, corporatization, ownership forms and their effects on the performance of the world’s major airports. J Air Transp Manag 12:109–121

    Article  Google Scholar 

  • Pels E (2008) Airline network competition: full-service airlines, low-cost airlines and long-haul markets. Res Transp Econ 24:68–74

    Article  Google Scholar 

  • Redondi R, Malighetti P, Paleari S (2011) New routes and airport connectivity. Netw Spat Econ 11:713–725

    Article  Google Scholar 

  • Redondi R, Malighetti P, Paleari S (2013) European connectivity: the role played by small airports. J Transp Geogr 29:86–94

    Article  Google Scholar 

  • Ripley RM, Snijders TAB, Preciado P (2013) Manual for RSiena

  • Snijders T (1995) Methods for longitudinal social network data: review and Markov process models. New Tr Prob Stat 3:211–227

    Google Scholar 

  • Snijders TA (2001) The statistical evaluation of social network dynamics. Sociol Methodol 31:361–395

    Article  Google Scholar 

  • Snijders TA (2011) Actor-based models for dynamics of two-sided relations

  • Snijders TA, Steglich CE, Schweinberger M (2007) Modeling the co-evolution of networks and behavior. In: Van Montfort, K., Oud, J., Satorra, A. (Eds.), Longitudinal models in the behavioral and related sciences, 41–71

  • Snijders TA, Van de Bunt GG, Steglich CE (2010) Introduction to stochastic actor-based models for network dynamics. Soc Networks 32:44–60

    Article  Google Scholar 

  • Tretheway M, Kincaid I (2010) Competition between airports: occurrence and strategy. In: Peter Forsyth DG (Ed). Airport competition: the European experience. Ashgate Publishing Ltd., Aldershot, pp. 119–136

  • Van de Bunt GG, Groenewegen P (2007) An actor-oriented dynamic network approach the case of interorganizational network evolution. Organ Res Methods 10:463–482

    Article  Google Scholar 

  • Van De Vijver E, Derudder B, Witlox F (2014) Exploring causality in trade and air passenger travel relationships: the case of Asia-Pacific, 1980–2010. J Transp Geogr 34:142–150

    Article  Google Scholar 

  • Waite JK (2009) The impact of airline bankruptcies on airports. Airport Cooperative Research Program Sponsored by the Federal Aviation Administration 3–61. http://onlinepubs.trb.org/onlinepubs/acrp/acrp_lrd_006.pdf

  • Xie F, Levinson D (2009) Modeling the growth of transportation networks: a comprehensive review. Netw Spat Econ 9:291–307

    Article  Google Scholar 

  • Zanin M, Lillo F (2013) Modelling the air transport with complex networks: a short review. Eur Phys J Spec Top 215:5–21

    Article  Google Scholar 

  • Zhang S, Derudder B, Witlox F (2013) The impact of hub hierarchy and market competition on airfare pricing in US hub-to-hub markets. J Air Transp Manag 32:65–70

    Article  Google Scholar 

  • Zhang S, Derudder B, Witlox F (2014) The determinants of full-service carriers airfares in European hub-to-hub markets. Eur J Transp Infrastruct Res 14:449–467

    Google Scholar 

Download references

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Authors and Affiliations

  1. Ghent Universty, Ghent, Belgium

    Shengrun Zhang, Ben Derudder & Frank Witlox

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  1. Shengrun Zhang
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  2. Ben Derudder
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  3. Frank Witlox
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Correspondence to Ben Derudder.

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Zhang, S., Derudder, B. & Witlox, F. Dynamics in the European Air Transport Network, 2003–9: An Explanatory Framework Drawing on Stochastic Actor-Based Modeling. Netw Spat Econ 16, 643–663 (2016). https://doi.org/10.1007/s11067-015-9292-8

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