Empowering the Women Working in Pakistan's Textile Industries: A Multi-Actor Multi-Criteria Analysis for Sustainability Assessment of E-Health Technologies

Shanza Naeem; Muhammad Khurram Ali; Muhammad Bilal

doi:10.31181/dma31202572

Authors

Shanza Naeem Department of Industrial Engineering, University of Engineering and Technology, Taxila, Pakistan https://orcid.org/0009-0001-5076-1647
Muhammad Khurram Ali Department of Industrial Engineering, University of Engineering and Technology, Taxila, Pakistan https://orcid.org/0000-0001-9578-7034
Muhammad Bilal Department of Industrial Engineering, University of Engineering and Technology, Taxila, Pakistan https://orcid.org/0009-0000-6836-3746

DOI:

https://doi.org/10.31181/dma31202572

Keywords:

Diversity, Equity, and Inclusion, Analytic Hierarchy Process, Sustainable Development, Health Care, Decision Support Systems, Multicriteria Decision Making

Abstract

While civilized nations around the world are witnessing an unprecedented evolutionary shift towards embracing diversity, equity, and inclusion (DEI), developing societies continue to struggle with deep-rooted socio-economic disparities. Working women in Pakistan continue to face many challenges including health and safety issues in the workplace. This research establishes a decision-making framework for the adoption of electronic health (e-health) technologies among the women in Pakistan's textile industry. It is based on the sustainability assessment of screened e-health alternatives across four domains: technological, environmental, economic, and socio-political. Three stakeholders including the female workers, health practitioners, and policymakers are taken on board for the main phase of multi-actor multi-criteria analysis (MAMCA). There is an interesting variation in the obtained criteria weights among all stakeholders with the highest weights assigned to ‘cost-effectiveness’ and ‘carbon footprint’. Wearable devices have the highest overall ranking apart from policymaker opinions which place it at second rank. Sensitivity analysis ensures the model's robustness which is followed by a validation step using the technique for order preference by similarity to ideal solution (TOPSIS). Obtained rankings of sustainability criteria and e-health technologies can be utilized by a broader range of stakeholders including investors, researchers, female industry workers, industrialists, and DEI promotors.

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