Strategic Group Analysis

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The primary objective of this article is to examine the strategy-performance of the firm. The paper studies the issue of strategic group from different theoretical point of views. There are some researchers suggest that it is beneficial to consider the firm characteristics while other researchers recommend studying the industry as a whole. The strategic group discipline is the center focus of the individual firm and industry, which helps in achieving explanatory study between the firm strategy and performance of the company. The paper aims to provide a foundation to understand the relationship between the American small telecommunication companies and its performance.
Hunt (1972) introduces the strategic group concept. The Hunt concept explains
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There are two forms of studies to identify the strategic dimensions, a narrow view and broader terms. However For the purpose of the paper, a broader scale used to capture the complexity of the small telecom firm 's strategy construct. The benefit of using the broader terms includes a wide range of variables that has the prospective to increase the probability of integrating relevant group –defined in the analysis.
Variables
The study identifies and tests three variables. The three dimensions stated by Price and Newman (2003) recognized as a strategy content, strategy process, and strategy context. Strategy content is the formulation that produces scope and mode of competition. Each organization differentiates itself by offering different products or services in a way that set it apart from its rivals. Principally, there are two strategies; the price differentiation and quality differentiation. The companies operate in price differentiation strategy produce products or services at lower prices. On the other side, the quality differentiation the company aim to satisfy the customer satisfaction. On the quality differentiation strategy the cost is not the primary concern of the company, but still
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The importance of the cluster analysis is finding K clusters. The one cluster will determine the similarities in the firm’s strategies are similar to each other while firms of different clusters are dissimilar. Cluster analysis aims to identify a true typology, model fitting, prediction based on groups, hypothesis testing, data exploration, hypothesis generation, and data reduction (Everitt, 1974). The SPSS 22.0 offers three methods of cluster analysis: K-Means, Hierarchical Cluster, and two steps cluster analysis. The advantage of the K-Mean clustering analysis the numbers of clusters are known before performing the test. The disadvantage of the hierarchical cluster there is one pass through the data. Thus, any error on data will lead to wrong results. The algorithm used during the hierarchical cluster analysis to determine an initial guess about the number of clusters. Moreover, the cluster Centroids accepted as the starting point for the K-means criterion validity and assessed by ANOVA significance test with the performance variables (Kitchen & Shock, 1996, p.

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