Data set: Operations Performance in Manufacturing Industry: The Roles of Agility, Supply Chain Sustainability, and Risk Management
Description
This study investigates the role of sustainable supply chain practices and risk management in enhancing manufacturing agility and operational performance, with a focus on the underexplored context of developing countries such as Indonesia. Data were collected from 255 managers and executives across the manufacturing, operations, logistics, and supply chain sectors using a structured questionnaire based on a five-point Likert scale. The collected responses were then analyzed using SmartPLS. The results indicate that environmental practices have a positive impact on both manufacturing agility and operational performance, although the effect on operational performance is relatively weaker yet remains statistically significant. Risk management is identified as a critical enabler, contributing positively to both agility and performance outcomes. Among the examined variables, manufacturing agility exerts the strongest influence on operational performance, underscoring its pivotal role in achieving competitive advantage. By integrating supply chain sustainability, risk management, manufacturing agility, and operational performance into a unified framework, this study addresses important research gaps and offers valuable theoretical and practical insights. The findings carry significant implications for practitioners and policymakers seeking to enhance supply chain resilience and drive operational excellence in volatile, resource-constrained environments.
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Steps to reproduce
This study employed a quantitative approach using a 5-point Likert scale to measure respondents' perceptions, with 1 representing "strongly disagree" and 5 representing "strongly agree." Data were collected through an online survey targeting logistics, manufacturing, and supply chain managers and executives. The online survey method ensured wide geographic reach and convenience for respondents. Data analysis was conducted using SmartPLS, a structural equation modeling (SEM) tool that allows for the assessment of complex relationships between latent variables. This approach enabled a robust examination of the proposed hypotheses while ensuring the reliability and validity of the constructs.
Institutions
- Bina Nusantara University