A Re-Examination of Diversification and Firm Productivity

Abstract

The advantages and disadvantages of diversification have been widely debated by academics, as well as business professionals, and the majority of studies suggest that diversification destroys firm value. The effect of overall diversification (without categorizing whether such diversification is related or unrelated to the business) on productivity has been investigated as well, but with similar conflicting results. In this paper, we investigate the effects of the two types of diversification on productivity. We find that related diversification enhances firm productivity, whereas unrelated diversification reduces firm productivity. We also find that the previously recorded link between diversification and firm value is partially mediated by productivity. Our paper offers further empirical evidence toward resolving the conflicting findings of prior research, and provides practitioners with additional points for consideration when engaging in firm diversification.

An Empirical Study of Strategic Positioning and Production Efficiency

“…The BCC model estimates the production efficiency scores of the firms in the Compustat database, and the second stage relates the production efficiency scores to our strategy variables. We follow Chang et al [21] in our choice of input and output variables. We consider three inputs and one output in the DEA model.…”

“…DEA measures the relative production efficiency relative to all other firms in the dataset. Therefore, we follow Chang et al [21] and partition our main dataset into the different industry categories, using the Fama-French 12 industry classification 2 . This enables us to estimate DEA for each industry dataset separately and compute efficiency scores for each firm relative to similar firms in the same industry.…”

“…Studies [52] have also used this approach to capture the efficiency of universities. Further, this approach is widely used to evaluate the performance of firms in studies evaluating research questions beyond specific industries (see, e.g.,: [21,53,54]). Following OLS regression model for the second stage estimation as used by Chang et al [55], McDonald [43], and Cummins et al [49] we estimate the following estimation model:…”

“…Prior studies[68][69][70][71] have used this classification and found it as a reasonably homogenous industry grouping.3. We estimate production efficiency assuming Hicksian neutral technical change and follow the procedure specified in Chang et al[21].…”

Detection of cost leaders using non-central principal component analysis and data envelopment analysis

“…Balsam et al (2011) showed that firms pursuing cost leadership strategy are able to put more emphasis on the executive compensation for increasing sales volume and by lowering price. Chang et al (2013) showed that derived ratios, such as sales, general and administrative cost per sales, R&D expense per sales, sales per cost of goods sold, etc., generated from such cost elements are inevitable to distinguish cost leaders from the differentiators. These variables are indeed under the control of the management.…”