Digital technologies could offer solutions for climate change mitigation and adaptation; however, challenges such as data privacy, energy consumption, and digital inequality could hinder their adoption. This study develops integrated step-wise weight assessment ratio analysis (SWARA) and complex proportional assessment (COPRAS) methods under a spherical fuzzy (SF) environment to evaluate digital technology applications for climate mitigation and adaptation. To this end, seven key challenges were identified through a systematic literature review and evaluated by a panel of 10 experts. SF-SWARA results show that data privacy and security (weight = 0.28) and energy consumption and environmental impact (0.20) are the most influential challenges. Eight digital technology applications were ranked using SF-COPRAS according to the weighted challenges. The case study in Lithuania demonstrates that smart resource saver achieves the highest utility score (100), followed by virtual commutes (93.9). Moreover, the sensitivity analysis across 20 scenarios confirms that smart resource saver consistently remains the best option. Overall, the study shows that the spherical fuzzy multi-criteria decision-making (MCDM) approach effectively handles uncertainty in expert judgment, offering a robust tool for policy and planning in climate-tech adoption.
Saraji et al. (Sat,) studied this question.
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