Categorizing Top Fortune Company Mission And Vision Statements Via Text Mining

Abstract

Purpose - The paper seeks to categorize mission and vision statements into clusters and demonstrate how these clusters can be profiled in the context of Globalization, Innovation and Strategy Centric features for assessment of strategic alignment, positioning and direction. Based on text mining methodology, mission and vision statements of the top 772 Fortune companies were analyzed to understand: 1) How mission and vision statements can be meaningfully categorized into clusters, 2) How attributes of each cluster can be meaningfully evaluated in the context of the degree to which Globalization, Innovation and Strategy Centric Mission and Vision statements are discovered. Clustering Toolkit (CLUTO) software was used for text mining the data collected from two websites. A recursive bisection approach has been followed to reach the desired number of six clusters, which were further analyzed through Wordle software for visual representation. The study clustered the companies in the dataset into groups in which globalization, innovation, and strategy issues were dominant. The epistemological contribution of this research includes how text mining can be used to meaningfully categorize a large dataset consisting of mission and vision statements of 772 Fortune corporations, how knowledge contained in a large dataset can be managed through the use of text mining in analyzing cluster attributes, and how these clusters can be profiled in the context of Globalization, Innovation and Strategy Centric features for assessment of strategic alignment, positioning, and direction.