Ordinal Time Series Methodology for Industry and Competitive Analysis

Timothy W. Ruefli and Chester L. Wilson
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Timothy W. Ruefli: IC 2 Institute, The University of Texas, Austin, Texas 78705-3594
Chester L. Wilson: IC 2 Institute, The University of Texas, Austin, Texas 78705-3594

Management Science, 1987, vol. 33, issue 5, 640-661

Abstract: Ordinal time series analysis is a new methodology that is especially appropriate for industry and competitive analysis along multiple dimensions of performance over periods of time. The methodology, by using ordinal data, eliminates the requirements encountered in cardinal analysis for further assumptions and calculations concerning model specifications, appropriate discount rates, and re-scaling of data to facilitate presentation. Using longitudinal data, ordinal time series analysis allows the strategy analyst to develop empirical measures of the position, volatility, direction of movement, and relative uncertainty associated with an industry or with groups of firms within that industry. Using these statistical patterns of industry behavior, key strategic dimensions and relationships among and across performance measures, groups of firms, and industries can be identified. The methodology is illustrated by using published data to perform a comparative ordinal time series analysis of the largest firms in the transportation industry over the last quarter century.

Keywords: corporate strategy; industry analysis; ordinal statistics (search for similar items in EconPapers)
Date: 1987
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