Ordinal Time Series Analysis
Methodology and Applications in Management Strategy and Policy
Herausgeber: Ruefli, Timothy
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Written for corporate strategic planners and market researchers as well as students of management, this book offers the most complete introduction to the methodology and applications of ordinal time series analysis available in book form. Particularly useful for managers who seek a reliable and accessible means of analyzing the strategic performance of firms, products, industries, or political entities, the ordinal time series approach uses simple data, longitudinal analysis, and rank positions to produce results that more accurately reflect the dynamics of competitive position and corporate p...
Written for corporate strategic planners and market researchers as well as students of management, this book offers the most complete introduction to the methodology and applications of ordinal time series analysis available in book form. Particularly useful for managers who seek a reliable and accessible means of analyzing the strategic performance of firms, products, industries, or political entities, the ordinal time series approach uses simple data, longitudinal analysis, and rank positions to produce results that more accurately reflect the dynamics of competitive position and corporate performance than those generated by more traditional methods which rely on absolute numbers and complicated analyses. The level of mathematical sophistication required is that of college introductory mathematics for business, making the methodology widely accessible. The contributors explain how to use the methodology and how to collect the appropriate data, review the statistical procedures involved, and examine numerous real-world applications of ordinal time series analysis. The book begins by introducing the notion of formalizing managerial intuition about strategic situations by employing rankings over time to describe the performance of products, firms, and departments, for example. Having established the advantages of using ordinal data, the contributors illustrate the use of rank statistics and show how to incorporate uncertain aspects of strategic situations in an ordinal context. A separate chapter covers information statistics that describe the aggregate behavior of a group of organizations over time. The contributors then present a series of examples demonstrating the wide applicability of ordinal time series analysis to various types of situations. Included are an analysis of the transportation industry over a 30-year period, an ordinal analysis of corporate performance, the application of ordinal analysis to the problem of product strategy, a look at world export activity, and an examination of international competition in the microelectronics industry. Throughout, particular attention is given to providing the reader with the background and information necessary to successfully employ ordinal time series methodology in his or her own environment.
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