The project selection process is a crucial step in sustainable development. Effective sustainable development depends on the ability to select the appropriate sustainable project to implement to ensure that the desired goals are met. Some of the most common characteristics or criteria used in evaluating sustainable projects include novelty, uncertainty, skill and experience, technology information transfer, and project cost. Prioritizing these criteria based on relative importance helps project managers and decision makers identify elements that require additional attention, better allocate resources, as well as improve the selection process when evaluating different sustainable project alternatives. The aim of this research is to use the fuzzy analytic hierarchy process (FAHP) methodology in which fuzzy numbers are utilized to realistically represent human judgment to rank the different project criteria based on relative importance and impact on sustainable projects. The results from the FAHP show that the most important criterion to consider in sustainable project selection is project cost, followed by novelty and uncertainty as the second and third most important criteria, respectively. The two least important criteria out of the total of five examined in this research were the skill and experience and technology information transfer, respectively. These results will help project managers and decision makers identify selection criteria with higher weights of importance. Given that the selection criteria chosen for this research are not limited to the evaluation of a specific type of sustainable projects or a specific location, they can be used to evaluate different types of sustainable projects in different environments and locations.

The discovery of plastic caused a true transformation in human lives and it is used in many essential applications. Despite its significance, humanity struggles to control plastic waste and stop its infiltration into the natural environment. This study aims to review the existing waste management system in Saudi Arabia and evaluate environmental impacts of different plastic waste management scenarios by conducting a life-cycle assessment (LCA). This study covered five scenarios: landfill, incineration with energy recovery, mechanical recycling with incineration of residuals, pyrolysis with incineration of residuals, and combined mechanical recycling and pyrolysis with incineration of residuals. For all scenarios in this study, the CML-IA Baseline method was used, utilizing OpenLCA software. Sources of data for this study were obtained from the Ecoinvent 3.9.1 database and from published peer-reviewed reports. The LCA study revealed that the combined mechanical recycling and pyrolysis with incineration of residuals scenario has the lowest environmental impact. Additionally, the combined scenario can accept a broader range of plastic waste, which improves the overall waste management system towards shifting to circular economy. Therefore, to meet the various recycling requirements, it is recommended to establish a portfolio of plastic waste management techniques in Saudi Arabia to produce high-quality recycled products. It is also recommended to utilize renewable energy for electricity generation in Saudi Arabia, since it was shown in this study that it has a significant positive environmental impact across all impact categories.

The degradation of the environment in China is accelerating along with economic expansion. Adoption of renewable energy technologies (RETs) is crucial for reducing the adverse impacts of economic growth on the environment and fostering sustainable development. This study attempts to identify the green innovation drivers and sub-drivers that affect the adoption of RETs in China and provide solutions for boosting their implementation. The study prioritized the drivers, sub-drivers, and strategies of green innovation by combining the Analytical Hierarchy Process (AHP) and Simple Additive Weighting (SAW) methods. In the study, the triple bottom line (TBL) approach has been used to determine the economic, societal, and environmental driving forces. The study also suggests strategies for encouraging the use of RETs. The results of the AHP method revealed that economics is the most crucial driver, with a weight of 0.376, followed by environmental (0.332), and social (0.291) drivers. The findings of the SAW method indicated that government green innovation initiatives, consumer initiatives, and industry initiatives are the most significant strategies for deploying RETs in China. This study has important theoretical and practical ramifications for encouraging China to adopt RETs. The suggested approaches can help researchers, business professionals, and policymakers promote sustainable development in China.