Capturing Relatedness: Comprehensive Measures based on Secondary Data

Abstract

This paper presents new measures of technological and customer-side relatedness constructed from widely available secondary data. Relatedness is a concept central to predicting the existence and nature of a relationship between corporate diversification and firmperformance. Yet, finding appropriate measures has been an ongoing struggle. The widely used SIC-based entropy measure has low construct validity, and survey-based measures are hard to replicate across firms and industries and over time. The measures we develop significantly outperform established measures in explaining variation in firm performance across firms and over time, and both sources of relatedness are found to be independent and significant explanations of firm performance.

Does the Diversification–Firm Performance Relationship Change Over Time? A Meta‐Analytical Review

“…Given our finding that the performance effects of related and unrelated diversification have become more similar over time, we believe that future research should also re‐conceptualize the very notion of (un‐)relatedness. In recent work, Nocker et al () argued that supply‐side measures of relatedness (based on product categories and industry classifications) should be complemented by demand‐side ones (relatedness of customer groups / market segments). In addition, we believe it would be worthwhile to consider relatedness in terms of commonality between business models (Teece, ) across different lines business pursued by a firm.…”

“…In this study, we adopt this practice, following the approach taken in prior meta-analyses in this field (e.g., Palich et al, 2000). Relatedness can be defined in multiple ways (e.g., resource-based, capabilities-based, market-based), but is widely measured as relatedness between product or service markets (Markides and Williamson, 1994;Nocker et al, 2016). In contrast to unrelated businesses, related ones tend to share common firm-specific assets (Li and Greenwood, 2004;Stern and Henderson, 2004;Tanriverdi and Lee, 2008) and to give rise to resource complementarities (Ennen and Richter, 2010).…”

Portfolio configuration and foreign entry decisions: A juxtaposition of real options and risk diversification theories

“…To test Hypothesis , we create a variable Diversification that takes into account both the number of industries in which a firm operates and the relatedness between the industries in terms of characteristics of the underlying resources. Given the well‐known concerns about entropy and concentric indices, we follow Nocker, Bowen, Stadler, and Matzler's (2016) approach to construct a matrix of industry relatedness by focusing on three salient resource characteristics: capital intensity (total capital/employees), material intensity (material costs/sales), and R&D intensity. We construct the matrix based on data for all publicly listed firms in Japan using the Development Bank of Japan database.…”

The effects of ownership identity on corporate diversification strategy of Chinese companies in foreign markets

“…As Barai, and Mohanty (2014) have suggested, in emerging countries, the stricter definition of relatedness and diversification are more laborious to generate due to lack of data at the firm-level reporting. We also did our best to find alternative measures of diversification as detailed in the literature (Ramaswamy et al, 2002;Sun, Peng & Tan, 2017;Nocker, Bowen, Stadler & Matzler, 2016;Li, He, Lan & Yiu, 2012;Neffke, Henning & Boschma, 2011;Haleblian & Finkelstein, 1999), but we did not find consistent data for all the acquirers and targets in our sample.…”