Clustered airline flight scheduling: Evidence from airline deregulation in Korea

Abstract

a b s t r a c tThis paper explores the impacts of competition level on airline scheduling in the Korean domestic shorthaul routes where a hub-and-spoke system is not the optimal air transport network strategy. The empirical findings using the Korean airline panel data for the period 2006e2010 suggest that competition leads to less differentiated departure flight times as expected from spatial competition theory. Unlike the previous study on the U.S airline industry, the degree of this tendency for less differentiation differs across the type of routes: the Jeju island routes (leisure type) and the inland routes (business type), in the deregulated period. Following the May 2008 Deregulation Act we find an increasingly clustered pattern of airline scheduling in the Jeju island routes where there have been competitive pressures associated with new low cost entrants. This recent evidence would imply that airline carriers strategically schedule departure flight times and allocate flights between routes as competition increases in the deregulated period.

Airline Sustainability Modeling: A New Framework with Application of Bayesian Structural Equation Modeling

“…This involves utilizing the Gibbs sampler [37] to obtain samples of arbitrary size to summarize the posterior distribution for describing the parameters of interest. With these samples, the point estimates, standard deviations and interval estimates can be To analyze airline sustainability, different statistical methods are employed, such as analysis of variance (ANOVA) [18,19], panel data modeling [20][21][22], time series [4,23,24], data envelopment analysis (DEA) [25][26][27][28], neural networks [29], neuro-fuzzy systems [30], and Classical-SEM [8,31].…”