Integrated Causal and Structural Modeling for Green-Digital Management Capability
Provider: Ministerstvo školství, mládeže a tělovýchovy
Programme: Operační program Jan Amos Komenský - výzkum
Implementation period: 01.07.26 - 30.06.28
Workplace:
Fakulta ekonomicko-správní - Oddělení projektů FES
Investigator: Zapletalová LucieTeam member: Kotková Stříteská Michaela | Myslivcová Kateřina | Zapletal David | Boháčová Hana
Description:
In management, demonstrating and quantifying causal relationships between various indicators is a fundamental task. Over time, there has been a shift from purely regression-based models to more advanced methods that allow for examining causality from multiple perspectives. The project will combine three complementary approaches: structural equation modeling (e.g., PLS-SEM), qualitative-comparative analysis (e.g., fsQCA), and causal inference methods (particularly Treatment Effect Analysis – TEA), which will be used to verify causal relationships between managerial practices, digital maturity, and sustainable innovations in firms within the framework of the Green-Digital Management Capability (GDMC) concept. The objective is: (i) to define and measure latent GDMC as the complementarity of managerial practices and digital maturity; (ii) to design and test an integrated SEM–QCA–TEA framework; (iii) test the proposed causal chains within GDMC, e.g., whether GDMC increases the likelihood of adopting green management or whether green practices mediate the effect of GDMC on innovation, and whether operational resilience mediates or moderates the relationship between digital maturity and green innovation; (iv) analyze the heterogeneity of effects between Central and Eastern European (CEE) countries and other European countries. The project addresses a methodological gap by applying a combination of SEM with TEA and QCA with TEA in the field of management, as well as a thematic gap, namely the use of integrated capability-based models for CEE countries.
In management, demonstrating and quantifying causal relationships between various indicators is a fundamental task. Over time, there has been a shift from purely regression-based models to more advanced methods that allow for examining causality from multiple perspectives. The project will combine three complementary approaches: structural equation modeling (e.g., PLS-SEM), qualitative-comparative analysis (e.g., fsQCA), and causal inference methods (particularly Treatment Effect Analysis – TEA), which will be used to verify causal relationships between managerial practices, digital maturity, and sustainable innovations in firms within the framework of the Green-Digital Management Capability (GDMC) concept. The objective is: (i) to define and measure latent GDMC as the complementarity of managerial practices and digital maturity; (ii) to design and test an integrated SEM–QCA–TEA framework; (iii) test the proposed causal chains within GDMC, e.g., whether GDMC increases the likelihood of adopting green management or whether green practices mediate the effect of GDMC on innovation, and whether operational resilience mediates or moderates the relationship between digital maturity and green innovation; (iv) analyze the heterogeneity of effects between Central and Eastern European (CEE) countries and other European countries. The project addresses a methodological gap by applying a combination of SEM with TEA and QCA with TEA in the field of management, as well as a thematic gap, namely the use of integrated capability-based models for CEE countries.
