A Longitudinal Categorization of US Airline Industry via Dynamic Stock Return Method
International Journal of Economics, Finance and Management Sciences
Volume 6, Issue 2, April 2018, Pages: 35-42
Received: Feb. 20, 2018; Accepted: Mar. 11, 2018; Published: Apr. 2, 2018
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Seong-Ho Cho, School of Business Administration, Hongik University, Seoul, Korea
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In this exploratory paper, the dynamic stock return method (DSRM) initially proposed as an effective and replicable method by [14], [4], [5], [6] is deliberately applied to the US airline industry over the period from 1979 to 1992 (14 years). The longitudinal categorization or strategic group (SG) results from the DSRM show good face validity. They are consistent with the industry’s fact-based historical progress. We also observe that the operational measures such as market share or productivity tend to support the grouping results. Furthermore, the results of 15- and 7-year analysis of relative closeness of stock responsive movements between two representative airline firms (American and Hawaiian airlines, respectively) could be inferred that the SGs derived from the DSRM are valid and robust over a longer time span. We conclude that the DSRM could be a good alternative instrument for the longitudinal study of industry substructure.
Categorization, Strategic Group, Niche, Industry Substructure, Cluster, US Airline Industry, Longitudinal Structural Dynamics, Longitudinal Study
To cite this article
Seong-Ho Cho, A Longitudinal Categorization of US Airline Industry via Dynamic Stock Return Method, International Journal of Economics, Finance and Management Sciences. Vol. 6, No. 2, 2018, pp. 35-42. doi: 10.11648/j.ijefm.20180602.11
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This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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