Mapping the Innovation DNA of Agribusiness Firms: A Multi‐Method Analysis of Strategic Capabilities and Performance

ABSTRACT Innovation is essential for competitiveness in agribusiness facing dynamic environments. This study examines how market orientation, marketing, relational, and social capabilities influence innovation performance. Using data from 751 Spanish firms and a multi‐method approach that integrates Structural Equation Modeling (PLS‐SEM), Necessary Condition Analysis (NCA), and fuzzy‐set Qualitative Comparative Analysis (fsQCA), the research explores linear, non‐linear, and configurational relationships. Results show that market orientation, marketing, and social capabilities show significant linear relationships, while relational capabilities exhibit an inverted U‐shaped relationship. NCA identifies marketing and relational capabilities as necessary conditions within the SEM framework; however, none meet the strict necessity thresholds under fsQCA. Configurational analysis reveals multiple successful capability combinations, supporting the concept of equifinality. These findings contribute to innovation theory by integrating variance‐ and set‐theoretical approaches, offering a nuanced view of capability orchestration. Practical implications include guidance for managers on capability development and for policymakers aiming to strengthen innovation ecosystems in agribusiness.

Authors

Institutions

Publication Details

Journal
Agribusiness
Published
2026-02-25
DOI
https://doi.org/10.1002/agr.70078
Primary Topic
Qualitative Comparative Analysis Research
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Mapping the Innovation DNA of Agribusiness Firms: A Multi‐Method Analysis of Strategic Capabilities and Performance

B. C. Martínez‐Azúa, Á. Dias
Agribusiness
Qualitative Comparative Analysis Research
article

Mapping the Innovation DNA of Agribusiness Firms: A Multi‐Method Analysis of Strategic Capabilities and Performance

B. C. Martínez‐Azúa, Á. Dias
article en

Abstract

ABSTRACT Innovation is essential for competitiveness in agribusiness facing dynamic environments. This study examines how market orientation, marketing, relational, and social capabilities influence innovation performance. Using data from 751 Spanish firms and a multi‐method approach that integrates Structural Equation Modeling (PLS‐SEM), Necessary Condition Analysis (NCA), and fuzzy‐set Qualitative Comparative Analysis (fsQCA), the research explores linear, non‐linear, and configurational relationships. Results show that market orientation, marketing, and social capabilities show significant linear relationships, while relational capabilities exhibit an inverted U‐shaped relationship. NCA identifies marketing and relational capabilities as necessary conditions within the SEM framework; however, none meet the strict necessity thresholds under fsQCA. Configurational analysis reveals multiple successful capability combinations, supporting the concept of equifinality. These findings contribute to innovation theory by integrating variance‐ and set‐theoretical approaches, offering a nuanced view of capability orchestration. Practical implications include guidance for managers on capability development and for policymakers aiming to strengthen innovation ecosystems in agribusiness.

Agribusiness
Iscte – Instituto Universitário de Lisboa (PT), Universidad de Extremadura (ES)
Junta de Extremadura, Fundação para a Ciência e a Tecnologia, European Regional Development Fund
Industry, innovation and infrastructure
Openalex Percentile: Top 37%
Qualitative Comparative Analysis Research
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.