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For over two decades, policy makers and economic development professionals have stressed the importance of encouraging and supporting industry clusters to promote job creation and regional competitiveness. Several researchers-Michael Porter and Christian Ketels, among others-have developed the study of cluster-based economic development and touted the employment and competitive benefits of cluster-based development strategies (Ketels, 2013; Ketels & Memedovic, 2008; Porter, 2008). Several studies have quantified the benefits of clusters in terms of employment growth and competitiveness as it relates to patent rates, with Delgado, Porter, and Stern (2014) being the most comprehensive. Yet other economic benefits along the dimensions of productivity, wage, and income growth have been largely overlooked. In this study, we assess the benefits of clusters across several traditional measures of economic performance. This study is organized as follows: We first discuss key concepts related to clusters in a brief literature review, including a discussion on the role of related and unrelated variety as they are connected to cluster definitions. Second, we present the data, analytical methods, and the rationale and construction for three measures of regional cluster characteristics, namely strength, diversity, and growth. These three measures are applied to both traded and local/nontraded clusters. The third section reports the empirical results, with the fourth section discussing the findings and conclusions about the usefulness of our measures. Review of the Literature Industry clusters are agglomerations of closely related industries (Delgado, Porter, & Stern, 2010). One might say that clusters are a network of economic relationships that create a competitive advantage for the related firms in a particular region. This advantage then becomes an enticement for similar industries to develop or relocate to a region. Developing industry clusters has become a key goal for regional economic development, as clusters have been shown to strengthen competitiveness by increasing productivity, stimulating innovative new partnerships (even among competitors), and presenting opportunities for new businesses.

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Only a handful of studies on innovation empirically analyze the links between firm innovation and the sources of that innovative activity of sources of innovation on types of innovation. To fill this gap in the literature, this study provides one of the first tests to identify how important sources of new information (suppliers, customers, other business people in the industry, workers, and university) are associated with types of innovations (product, process, and marketing). Data come from the 2014 National Survey of Business Competitiveness sponsored by the Economic Research Service at the United States Department of Agriculture (n = 10,952). The results show that innovation ideas emanating from customers, workers, and universities are positively associated with all types of innovations, suggesting that these sources are critical for developing different types of innovation. In particular, universities as a source of innovation activity are especially important. In contrast, other sources, such as suppliers and people in industry do not seem to be as important as a source of innovation.

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