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Bankruptcy prediction in the agribusiness sector: Lessons from quantitative and qualitative approaches

Katarzyna Boratyńska and Emilia Grzegorzewska

Journal of Business Research, 2018, vol. 89, issue C, 175-181

Abstract: This study used the complexity theory to present an asymmetric and critical thinking approach. Its main purpose is fsQCA implementation for bankruptcy prediction of agribusiness entities and comparison with classical quantitative methods. The research comprises three phases: (1) calculation and evaluation of the predictive abilities and classification errors of 35 selected quantitative bankruptcy methods, both domestic and foreign, namely, multivariate discriminant analysis and logistic regression models; (2) fsQCA implementation for bankruptcy prediction of 14 agribusiness entities, comprising conditions that are typical of the agribusiness sector and financial and macroeconomic data; and (3) indication and comparison of the advantages and disadvantages of fsQCA against a background of classical bankruptcy prediction models. The findings indicate that managers should carefully build or/and select existing methods of bankruptcy prediction, and adjust them to the type, size, and risk of business activity.

Keywords: fsQCA; Complexity theory; Asymmetric thinking; Bankruptcy prediction models; Agribusiness (search for similar items in EconPapers)
Date: 2018
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Handle: RePEc:eee:jbrese:v:89:y:2018:i:c:p:175-181