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1 – 10 of 17Alexandra Garcia-Guix, Juan Ignacio Mestre-Pinto, Judit Tirado-Muñoz, Antonia Domingo-Salvany and Marta Torrens
Juan A. Marin-Garcia, Jose A.D. Machuca and Rafaela Alfalla-Luque
To determine how to best deploy the Triple-A supply chain (SC) capabilities (AAA-agility, adaptability and alignment) to improve competitive advantage (CA) by identifying the…
Abstract
Purpose
To determine how to best deploy the Triple-A supply chain (SC) capabilities (AAA-agility, adaptability and alignment) to improve competitive advantage (CA) by identifying the Triple-A SC model with the highest CA predictive capability.
Design/methodology/approach
Assessment of in-sample and out-of-sample predictive capacity of Triple-A-CA models (considering AAA as individual constructs) to find which has the highest CA predictive capacity. BIC, BIC-Akaike weights and PLSpredict are used in a multi-country, multi-informant, multi-sector 304 plant sample.
Findings
Greater direct relationship model (DRM) in-sample and out-of-sample CA predictive capacity suggests DRM's greater likelihood of achieving a higher CA predictive capacity than mediated relationship model (MRM). So, DRM can be considered a benchmark for research/practice and the Triple-A SC capabilities as independent levers of performance/CA.
Research limitations/implications
DRM emerges as a reference for analysing how to trigger the three Triple-A SC levers for better performance/CA predictive capacity. Therefore, MRM proposals should be compared to DRM to determine whether their performance is significantly better considering the study's aim.
Practical implications
Results with our sample justify how managers can suitably deploy the Triple-A SC capabilities to improve CA by implementing AAA as independent levers. Single capability deployment does not require levels to be reached in others.
Originality/value
First research considering Triple-A SC capability deployment to better improve performance/CA focusing on model's predictive capability (essential for decision-making), further highlighting the lack of theory and contrasted models for Lee's Triple-A framework.
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María Isabel Roldán Bravo, Juan Manuel Maqueira-Marin and José Moyano-Fuentes
The purpose of this paper is twofold: firstly, to provide a measurement instrument for supply chain 4.0 ambidexterity by applying the theoretical perspective of ambidexterity to…
Abstract
Purpose
The purpose of this paper is twofold: firstly, to provide a measurement instrument for supply chain 4.0 ambidexterity by applying the theoretical perspective of ambidexterity to advance Industry 4.0; secondly, to empirically analyse how supply chain 4.0 ambidexterity and lean supply chain management contribute to enhancing the focal firm’s operational performance.
Design/methodology/approach
Empirical results are obtained through analysis of survey data from a sample of 209 Spanish focal firms in industrial sectors in an intermediate position in the supply chain. Structural equation modelling was performed to test the three proposed hypotheses.
Findings
Drawing on resource orchestration theory and the relational resource-based view, this study empirically demonstrates the full mediating role of lean supply chain management in the relationship between supply chain 4.0 ambidexterity and the focal firm’s operational performance.
Originality/value
Although recent research has highlighted the pertinence of applying inter-organisational ambidexterity to foster Industry 4.0 (Hofmann et al., 2019), to the best of the authors’ knowledge, this is one of the first studies to apply this theoretical framework to explain the transition to supply chain 4.0. In addition, to date, to the best of the authors’ knowledge, no study exists that has developed a measurement scale and used this concept in an empirical analysis to advance theory development.
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Diessica de Oliveira-Dias, Juan Manuel Maqueira Marín and José Moyano-Fuentes
The significant changes that supply chains (SCs) are undergoing and the emergence of disruptive technologies have led to a growing effort to integrate novel and mature…
Abstract
Purpose
The significant changes that supply chains (SCs) are undergoing and the emergence of disruptive technologies have led to a growing effort to integrate novel and mature technologies into existing SC strategies. Thus, this study investigates the relationships between mature information technologies (ITs), emerging IT and the lean supply chain (LSC) and agile supply chain (ASC) strategies.
Design/methodology/approach
An empirical study based on structural equation modeling of survey data from 256 Spanish focal companies has been conducted to test six hypotheses.
Findings
Drawing on resource orchestration, our results point to mature IT use being an enabler of both LSC and ASC strategy implementation. The results also show an LSC mediating effect on the relationship between mature IT and ASC when SCs follow both strategies. Also, the implementation of emerging IT requires a process of consolidation over time to be genuinely useful as a facilitating mechanism for developing both the lean and agile strategies along the SC. In this sense, a suitable mix needs to be orchestrated between emerging and mature IT.
Originality/value
This study sheds light on the relevance of the mature IT and emerging IT in the context of two SC strategies (lean/agile) and provides practical and theoretical implications.
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