This work presents an overarching data-driven evaluation of the viability of bioplastics as alternatives to petroleum-based shopping bags, considering multiple criteria associated with the sustainability agenda. Subsequently, it proposes a novel integration of stochastic multi-criteria acceptability analysis (SMAA) and combinative distance-based assessment (CODAS), hereby coined as SMAA-CODAS, to identify the most preferred bioplastic substitute.
Thorough review of the domain literature with inputs from an expert team identified 12 criteria, comprehensively spanning environmental (i.e. composition of bio-based materials, biodegradability through natural processes, biodegradability through industrial processes, feedstock sustainability, greenhouse gas (GHG) emissions and water footprint), technical (i.e. fitness of domain application, bulk density, tensile strength and impact strength) and economic (i.e. market price and market demand) attributes. The dataset comprising the evaluation of 12 bioplastic alternatives was extracted from different sources in the literature, including journal articles, reports and policy documents, with data expressed as real, interval or fuzzy numbers to capture the uncertainty arising from inconsistencies in data across sources. In the proposed approach, each Monte Carlo simulation run constructs a real-valued decision matrix drawn from the imprecise dataset. Subsequently, CODAS implements the evaluation, while SMAA implements multiple runs and reports insightful statistics as outputs.
After 10,000 runs, polyglycolic acid (PGA) emerged as the most robust alternative, ranking first 85.39% of the time (rank acceptability index) and achieving the highest holistic acceptability index, followed by polylactic acid (PLA) and polyhydroxyalkanoates (PHA), while polyethylene terephthalate made from bio-based sources (Bio-PET) ranks last. Also, the central weight vector shows that PGA, PLA and PHA were primarily contributed to by biodegradability through industrial and natural processes and by the composition of bio-based materials, except for PGA, which had the lowest GHG emissions. Comparative analysis with other SMAA variants yields a correlation coefficient of at least 0.92. Sensitivity analysis shows that the evaluation of bioplastics is highly influenced by the criteria weights, allowing policymakers to reflect their preferences across specific scenarios.
Findings from this work suggest that research and development of PGA must be a priority in investment decisions, including feedstock choice, production scalability and cost-optimization measures. Although PGA emerges as the most preferred choice, its current commercial deployment is constrained by relatively higher production costs and limited large-scale manufacturing infrastructure compared to conventional plastics and more established bioplastics such as PLA. Thus, when cost trade-offs are substantial, PLA may be considered a second-preferred alternative, as it exhibits properties closely comparable to PGA while incurring lower costs. Also, this work finds that biodegradability criteria (natural or industrial) are instrumental in evaluating bioplastics, emphasizing the criticality of end-of-life considerations.
This work is the first to integrate SMAA and CODAS into a unified stochastic multi-criteria decision-making framework and applies it to pioneer a comprehensive evaluation of bioplastics for shopping bags.
