Sustainable provider selection for artificial intelligence-powered robotic systems: a framework and evaluating methodology

Purpose Due to fierce competition, manufacturing enterprises must intensely focus on improving every operational link for business continuity. Selecting a sustainable service provider of artificial intelligence (AI)-powered robotic systems in reverse logistics function is a vital link to increase competitive edge in manufacturing firms and still requires investigation. Thus, this study proposes a criteria framework for manufacturing enterprises to select a sustainable provider of AI-powered robotic sorting systems (AIRSS) – a typical AI-powered robotic systems. Design/methodology/approach Using the grey analytical hierarchy process, weightage was assigned to sustainable provider selection criteria in order to give clarity on the significance degree. Then, using fuzzy technique for order of preference by similarity to ideal solution, the best AIRSS service provider was selected, catering to the most significant criteria based on sustainable performance scores. The proposed evaluating methodology was verified via empirical evidence in Nigeria, and sensitivity analysis was conducted for its validation. Findings The results highlight the economic dimension as the most significant, followed by social and environmental. Also, the results pinpoint pricing, customer support, quality, ethical considerations, accessibility and security as the most significant sustainable service provider criteria for AIRSS. As well, the ranking of five AIRSS providers was done to select the best. Research limitations/implications This study will assist the manufacturers to overcome the risk of erroneous assessment of AIRSS providers and encourage the AI service providers to enhance their performance in terms of the critical criteria for increased competitive edge in a rapidly moving market. Originality/value This study is a pioneering attempt to develop a criteria framework and propose evaluating methodology for sustainable service provider selection of AIRSS in a developing nation based on triple-bottom-line (TBL) dimensions and G-AHP-F-TOPSIS, respectively.