Additive Manufacturing (AM) is viewed as a disruptive technology with the potential to replace many manufacturing processes. With its rapid proliferation in recent years, it is crucial to understand how to measure this technology’s social impacts. There are many studies available in the existing literature regarding the economic and environmental impacts of AM technology. However, research regarding the social impacts of this technology is still scarce. To this end, this research has developed a framework based on Social Life Cycle Assessment (SLCA) methodology to measure AM products’ social impacts throughout their life cycle stages. The proposed framework includes an underlying mathematical model that was developed to allow for the aggregation of indicator scores. Additionally, cut-off scores were determined to differentiate between positive and negative social impacts. This framework can be applied to case studies, which provides a final score that quantifies the social impacts of an AM product throughout all its life cycle stages. It also provides scores for each stakeholder category and life cycle stage, which facilitates the identification of hotspots that require attention from organizations.
Purpose
Supply chain resilience (SCR) has recently become an important issue for organizations all around the world. In order to decrease the risk of failures, managers and decision makers are constantly looking for practices to enhance SCR. The purpose of this paper is to propose a research model that mainly focuses on the effect of information sharing (IS) to enhance SCR.
Design/methodology/approach
Survey method is used in this research. Data were collected from the supply chain, procurement, executive and IT managers of 82 of Tehran’s stock exchange production companies. Structural equation modeling with SmartPLS3 software is used to analyze the collected data.
Findings
Research results show that IS significantly enhances SCR.
Research limitations/implications
Data were collected at one point in time, and therefore a longitudinal study can further investigate the results of this study. The research was carried out in production companies in Iran. Future research can examine the research model in other industry sectors, e.g. services, in other countries to validate the accuracy of the findings.
Practical implications
The findings of this research should help managers, and decision makers create more resilient supply chains for their own and partners’ organizations.
Originality/value
The research model provides insightful results regarding the significance of IS in the SCR context.
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