Ordinal Time Series Methodology for Industry and Competitive Analysis
提出一种序数时间序列分析方法，利用序数数据消除基数分析中的假设和计算要求，可衡量行业或企业群体的位置、波动性、移动方向和相对不确定性，并通过运输业最大企业的数据演示其应用。
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.