Ordinal Time Series Analysis: Methodology and Applications in Management Strategy and Policy

Ordinal Time Series Analysis: Methodology and Applications in Management Strategy and Policy

Ordinal Time Series Analysis: Methodology and Applications in Management Strategy and Policy

Ordinal Time Series Analysis: Methodology and Applications in Management Strategy and Policy

Synopsis

This book offers a comprehensive introduction to the methodology and applications of ordinal time series analysis. 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 reports that more accurately reflect the dynamics of competitive position, corporate performance, etc. than those generated by more traditional methods. 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.

Excerpt

The title of this book, while an accurate description of its contents, is likely to conjure visions of complicated mathematics, axioms, theorems, proofs, and lemmas, coupled with hypothetical applications based on data well- abstracted from reality. What the reader will find, however, is a straightforward, but practicable, approach to incorporating time series of data in strategic analysis. This approach was developed from situations faced by corporate strategists and researchers and is accessible to anyone who remembers only the barest essentials from a college course on probability and statistics.

Managers intuitively view the world in terms of the relative positions of competitors, suppliers, divisions, departments, etc. Extending that intuition to specific data over time and formalizing the approach is the essence of Ordinal Time Series Analysis. All that is required is to replace the absolute numbers traditionally used in time series analysis with the rank position of those numbers. What emerges when rankings rather than absolute numbers are employed are patterns of strategic behavior relevant to the products, firms, or other entities being analyzed.

The methodology presented here has been tested over a period of seven years with Ph.D. students, managers, and MBA students. Employing Ordinal Time Series Analysis as a methodology, Ph.D. students have been able to design and carry out original research within a span of a semester that has either made contributions to knowledge or shed new light on existing findings. Both of the latter two groups have been able to grasp the basic principles of Ordinal Time Series and to quickly apply them to product, firm, or industry analyses in a matter of a couple of hours. These applications have consistently yielded important strategic insights--even with not-so-reliable data.

There are aspects of thinking about the world in terms of time series of rankings that do require some adjustment from approaches to dealing . . .

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