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In today’s globalized and heavily industrialized economy, sustainability issues that negatively affect the human population and external environment are on the rise. This study aims to investigate a synergistic combination of supply chain management and quality management practices in strengthening the sustainability performance of Malaysian manufacturing firms.

A total sample of 177 usable surveys was collected. Given the contributions and acceptability of the artificial neural network (ANN) approach in evaluating the findings of this study, this study uses ANN to measure the relationship between each predictor (i.e. supply chain integration [SCI], quality leadership [QL], supplier focus [SF], customer focus (CF) and information sharing [IS]) and the dependent variable (i.e. sustainability performance). Via sensitivity analysis, the relative significance of each predictor variable is ranked based on the normalized importance value.

The sensitivity analysis indicates that CF has the greatest effect on sustainability performance (SP) with 100% normalized relative importance, followed by QL (75%), IS (61.5%), SF (57.3%) and SCI (46.7%).

The findings of this study have the potential to provide valuable guidance and insights that can help all manufacturing firms enhance their SP from the optimum combination of the selected SCQM practices with a focus on sustainability.

Soft total quality management (STQM) practices are essential for promoting value-added organizational citizenship behaviour (OCB) among employees in quality-focussed manufacturing firms. This study intends to investigate how STQM practices (empowerment, training, teamwork and involvement) affect OCB under the moderating influence of collectivism among employees for excellence in business performance using social exchange and social cognitive theories (SET-SCT).

A total of 245 useable surveys were gathered from manufacturers. Given the importance of the two-staged structural equation modelling–partial least squares–artificial neural networks (SEM-PLS-ANN) technique, this study used a two-staged SEM-PLS-ANN analysis to capture both linear and compensatory PLS models and nonlinear and noncompensatory ANN models.

The findings confirmed that empowerment, involvement and training had a significant impact on OCB. However, teamwork had no impact on OCB. Interestingly, collectivism was found to have a significant and positive moderating effect on training and OCB.

The study contributes significantly to the literature on TQM and human resource management. First, the study broadens researchers’ understanding of how to apply SET by including a collective value from SCT as positive reciprocity to foster positive workplace behaviour. Second, the authors offer a solid management strategy for organizations to assist them in understanding an STQM model that promotes OCB while including collectivism for superior business performance.

This research aims to examine the relationships between supply chain quality management (SCQM), organizational learning capability (OLC) and product innovation performance (PIP) among small and medium-sized manufacturing enterprises (SMMEs) in Malaysia.

This is a quantitative study in which 163 valid responses were empirically collected from SMMEs in Malaysia via self-administered structured questionnaires.

Performing a partial least squares–structural equation modelling analysis, the findings revealed that the relationships between SCQM, OLC and PIP are positive and significant. Moreover, OLC partially mediates the relationship between SCQM and product innovation. Serving as a practical guideline, the results of this study stress the fact that managers of SMMEs need to look into the role-specific context of the firm before determining which practices would be effective for their companies.

The value-added additional testing of the mediating effect of OLC is the highlight of this study. This research represents another leap towards redefining and advancing SCQM, especially for SMMEs in the Asian context.

This research investigates the mechanism by which big data capability enables superior supply chain resilience (SCRe) by empirically examining the links among big data analytics (BDA), supply chain flexibility (SCF) and SCRe, with innovation-focused complementary assets (CA-I) as the moderator.

Extensive surveys were conducted to gather 308 responses from Malaysian manufacturing firms in order to explore this framework. The structural and measurement models were examined and evaluated by using partial least squares structural equation modelling.

The findings revealed that BDA is linked to flexibilities in a manufacturing firm’s value chain, which in turn is related to the firm’s SCRe. However, the association between BDA and SCRe is surprisingly non-significant. Additionally, CA-I was discovered to moderate the connections between all of the constructs, except for the relationship between BDA and SCRe. Such findings imply that with the aim of enhancing resilience, a company should concentrate on SCF; and that BDA capability is a prerequisite for increasing these flexibilities.

This research extrapolates the findings of previous studies regarding BDA’s influence on SCRe by investigating the indirect effect of SCF, as well as the moderating influence of CA-I. This research is one of the first few studies to empirically examine the relationships between BDA, SCF and SCRe across manufacturing firms, with CA-I acting as a moderator.