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How Much Do Industry, Corporation, and Business Matter, Really? A Meta-Analysis
Author(s) -
Bart Vanneste
Publication year - 2017
Publication title -
strategy science
Language(s) - English
Resource type - Journals
eISSN - 2333-2077
pISSN - 2333-2050
DOI - 10.1287/stsc.2017.0029
Subject(s) - variance (accounting) , standard deviation , corporation , econometrics , sample (material) , ordinary least squares , economics , measure (data warehouse) , statistics , sample size determination , mathematics , accounting , computer science , chemistry , finance , chromatography , database
The academic field of strategy seeks to explain differences in firm performance. A consensus exists that industry, corporate, and business effects together account for most performance differences, but there is debate over how much each factor explains. Previous studies have used three different effect size measures: sum of squares, variance, or standard deviation. These measures yield different results for a given sample, which precludes direct comparison. Using simulation analysis, I show that the sum-of-squares measure is sensitive to sample dimensions (e.g., the number of industries, the number of businesses per industry). Using 25 samples from nine studies (N = 212,112), I find that this sensitivity is strong in practice: knowing only the dimensions of a sample is sufficient to predict well the sum-of-squares measure. A meta-analysis is conducted using the variance and standard deviation measures instead (18 samples from 16 studies, N = 225,183). With the variance measure, the effect sizes are 0.08 f...

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