Sustainable Development Using SPSS an Emerging Software Tool: A Quantitative Analysis

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Noorjahan Sherfudeen

Abstract

Incorporating economic, social, and environmental considerations into policymaking and corporate practices is essential for achieving sustainable development, which is multidimensional. This study looks into how statistical software tool like SPSS can be used to test and model the processes of long-term growth in a number of different areas. The study looks at big datasets from a lot of different industries and regions to find out how they measure important sustainability indicators like carbon emissions, resource efficiency, and socioeconomic equity. This is done by using complex quantitative methods to look at the data. Integrating classic and modern statistical software is made novel in this study; which makes easier to simulate complicated sustainability patterns and gives policymakers and companies information they can put into practice. Using data mining, AI-enhanced features, and machine learning algorithms in these tools, the research finds links between sustainability factors and the success of different sustainability initiatives that were not known before. Even though these software tools have a lot of potential, the study points out some limitations like the data quality, complexity to judge the long-term benefits of sustainability and to make sure that different measurement frameworks used in different regions and industries. The findings demonstrate that businesses may enhance their long-term profitability and environmental impact by incorporating sustainable development objectives into their operations. Additionally, the research highlights the importance of using data to inform decision-making in the creation of sustainable policies. Using SPSS has several benefits, such as improving predictive capacities, processing massive information accurately, and providing a thorough study of sustainable development initiatives. This study adds to theoretical and practical knowledge by providing a data-driven strategy for achieving global sustainability objectives.

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