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• W2022740080 abstract "Alaskan Airline Markets: A Case Study in Spatial Decision Making N eil S o r en so n Instructor, Social Science Division Bellevue Community College, Bellevue, WA 98007-6484 Introduction A ir l in e s FREQUENTLY ADD AND DELETE city-pair mar­ kets. These changes, along with flight frequency adjustments, are the result of airline decision makers attempting to increase profits by “optimizing” their networks. Network changes are made by elimi­ nating markets that are unprofitable, adding markets projected to be money makers, and adjusting the number of flights in existing mar­ kets. Market decisions can be influenced by an airline’s competitive environment, competitive strategy, and the risk associated with ac­ tual and potential loss. Adjustments to the various markets served by an airline require decisions that affect the firm’s survival and the geography of the airline’s network. The purpose of this paper is to examine the nature of market decisions made by airlines operating within Alaska. This includes all Alaskan carriers with schedules appearing in the Official Airline Guide. The focus will be on variables, internal and external to the 62 SORENSON: Alaskan Airline Markets 63 firm, associated with airline decisions to either add markets, delete markets, or retain markets within their system. This type of decision falls into the “discrete choice” category since the selection of one alternative precludes the selection of either of the other two. Since the late 1960s, there has been a growing body of literature on the application of discrete-choice analysis to transportation prob­ lems. M ost studies have been related to consumer choice. For example, Morrison and Winston (1986, 1989) used discrete-choice analysis to calculate consumer benefits related to airline deregula­ tion. Mannering and Hamed (1988) used the technique to examine the impact of frequent flier programs on consumer choice, and Mannering and Winston (1991) developed discrete-choice models to evaluate the influence of brand loyalty on automobile consump­ tion. In geography the technique has been used to study travel behavior related to mode and destination choice (Pipkin 1986). This paper uses discrete-choice analysis to examine market deci­ sions made by Alaskan airline firms in the 1988 through 1993 period. During this time, airlines operated a total of 1,176 markets. They added 429 markets, deleted 399, and retained 348. In this paper the logit model format (discussed on page 65) is used to gain insights into factors influencing additions, deletions, and no-change decisions. The first section of the paper discusses some fundamental aspects of discrete-choice analysis and the logit model. The second section discusses the variables included in the analysis. The third section examines two models of market choice in Alaska. The first model inspects factors that were most influential across the entire state, and the second model looks at factors influencing mar­ ket decisions in the Northwest region. The models strongly suggest that major variables influencing decisions within Alaska included changing levels of competitive rivalry, network configuration, and changes in fleet composition. The final section of the paper exam­ ines the significant variables. 64 APCG YEARBOOK • VOLUME 58 • 1996 Discrete-Choice Analysis Many relational models employed by geographers have relied on regression analysis, in which the researcher assumes some linear re­ lationship between a dependent variable and a set of independent variables. The relationship takes on the form: Y.=b +b.Z..+b7 Z7+...b Z . (1) i o 1 ] 2 2j n nj v 7 where b through bnare coefficients to be determined. The degree to which there is a relationship between the variables is frequently cal­ culated using the least squares method. In least squares, a “line” representing the smallest deviation relative to the observed data is determined by minimizing the sum of the square of the deviations or: min y (bg,b.)= X (Y- b - bx Z. )2 (2) l (Mannering and Kilareski 1990) This method helps establish relationships between independent and dependent variables. However, the method generally assumes the dependent variable is continuous compared to the independent variables. For example, the relationship between numbers of trips away from home and household characteristics such as income, type of employment, neighborhood, and number of people in a household would be..." @default.
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• W2022740080 title "Alaskan Airline Markets: A Case Study in Spatial Decision Making" @default.
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• W2022740080 doi "https://doi.org/10.1353/pcg.1996.0010" @default.
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