Challenges and Solutions
Featured An Unsupervised Machine Learning Analysis of Sustainability Indicators Using the k-Means Clustering Algorithm Among 2,485 Global Corporations
Paper Presentation in a Themed Session Gloria Schmitz
Large corporations contribute to waste proliferation and global environmental degradation; however, more research is needed to understand these trends. Unsupervised machine learning can provide unique insights into how firms cluster on different sustainability indicators with relevance for the circular economy (CE) framework (i.e., metrics related to waste reduction and promotion of reuse). This study uses data from 2010 – 2020 for 2,485 global companies to explore how firms cluster together on sustainability metrics and whether a firm’s headquarter location and industry determine its clustering. Using the k-means unsupervised machine learning algorithm, one-way ANOVA, and Chi-square tests for key variables (e.g., industry, location of headquarters, total environmental cost and progress toward the UN Sustainable Development Goals 12.2, 14.1 and 14.2) across clusters, I found that the majority of firm-year observations cluster together (n = 13,313), with a small minority of firm-years (n = 39) with the most negative CE and environmental impacts clustered together, as well. The key findings indicated that the k-means algorithm grouped firms into four distinct clusters. Firms headquartered in the EU were not more likely to be in the most sustainable cluster, while firms in extractive industries (e.g., fossil fuel and mining) were more likely to be in the least sustainable cluster. These results can help policymakers identify key factors that could influence firms to adopt business practices aligned with circular economy goals worldwide while also enhancing the understanding of complex interfaces between corporate sustainability and public policy.
Is Mass-Production Agriculture Sustainable?: A Cross-cultural Environmental Study of Meat-Dairy Production
Paper Presentation in a Themed Session John Pauley
Mass production of pork and beef presents environmental problems that may not be solvable. In this essay, I detail these problems drawing from a two-year research project comparing mass-production hog-beef production in the Midwest United States and mass-production beef-dairy production in Ireland. In my analysis, the ecological-environmental problems, which are catastrophic, are connected to economic, political, and social conditions, assumptions, and mythologies. Ultimately, arriving at sustainability in agriculture is a matter of deep and relentless interdisciplinary pursuit which must synthesize disciplines. I endeavor to make this clear. A major part of the interdisciplinary focus is cultural and involves how Irish and United States citizens understand their own environments and landscapes, which further involves aesthetics and ecological history. Cultural understanding of the environment is, in turn, a crucial element in environmental justice. I then argue that mass-production makes use of cultural biases that distort the understanding of the ecology and landscape. I conclude with a philosophical analysis of the manner in which "innovation" in mass-production agricultural is itself the result of a cultural bias which further supports the underlying concepts and practices of mass production.
The Link Between the Turkish Wheat Sector and the Sustainable Development Goals Along with Recommendations for Turkeys SDG 2050 Targets
Paper Presentation in a Themed Session Hatice Camgoz Akdag
The aim of this study is to summarize the current situation based on the targets and to present a report on what can be done to achieve the targets set. The linkage between the Sustainable Development Goals (SDGs) and food waste is evident, with Goals 2,7,12 and 13 serving as pivotal starting points for the project efforts. Furthermore, one of the objectives is to project the present data scenario in Turkey for the year 2050. Considering that the components will directly and indirectly affect the entire problem, it will be possible to address in a cyclical manner. Minimizing food waste is critical due to its economic, social, ecological and health implications, and the impact of the solution will be significant. This research focuses on examining the issue through an economic lens, exploring aspects such as production and consumption, the climate crisis, and renewable energy. In this study, the interconnection of the 4 SDGs examined are explained through the wheat market. These four main items have been chosen due to the consideration that wheat is integrated in every aspect from the cultivation process to processing and consumption. When wheat production is considered as a circular chain, the selected SDGs can be evaluated as gears that make up this chain. However, it is also aimed to prove that these SDGs are interconnected in the same way, and the existence of significant linkages that can be proposed between ESG-SDG and wheat is emphasized.
