Net versus combinatory effects of firm and industry antecedents of sales growth

Alexander Leischnig; Stephan C. Henneberg; Sabrina C. Thornton

doi:10.1016/j.jbusres.2016.01.005

Net versus combinatory effects of firm and industry antecedents of sales growth

Alexander Leischnig, Stephan C. Henneberg, Sabrina C. Thornton

Research output: Contribution to journal › Article › peer-review

20 Citations (Scopus)

Abstract

This study examines antecedents of sales growth using a two-step mixed-method approach including analyses of net effects and combinatory effects. Based on a sample of 453 respondents from manufacturing and service firms, this article shows how the combination of structural equation modeling (SEM) and fuzzy set Qualitative Comparative Analysis (fsQCA) provides more detailed insights into the causal patterns of factors to explain sales growth. This article contributes to the extant literature by highlighting fsQCA as a useful method to analyze complex causality (specifically combinatory effects of antecedent conditions) and by discussing options regarding how this approach can be used to complement findings from conventional causal data analysis procedures that analyze net effects.

Original language	English
Pages (from-to)	3576-3583
Number of pages	8
Journal	Journal of Business Research
Volume	69
Issue number	9
Early online date	2 Feb 2016
DOIs	https://doi.org/10.1016/j.jbusres.2016.01.005
Publication status	Published - 1 Sep 2016

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title = "Net versus combinatory effects of firm and industry antecedents of sales growth",

abstract = "This study examines antecedents of sales growth using a two-step mixed-method approach including analyses of net effects and combinatory effects. Based on a sample of 453 respondents from manufacturing and service firms, this article shows how the combination of structural equation modeling (SEM) and fuzzy set Qualitative Comparative Analysis (fsQCA) provides more detailed insights into the causal patterns of factors to explain sales growth. This article contributes to the extant literature by highlighting fsQCA as a useful method to analyze complex causality (specifically combinatory effects of antecedent conditions) and by discussing options regarding how this approach can be used to complement findings from conventional causal data analysis procedures that analyze net effects.",

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