Digital pollution, encompassing energy consumption, e-waste, and the environmental impact of digital technologies, poses a significant and increasingly pressing environmental challenge that has received insufficient research attention. This study explores public perceptions, attitudes, and behaviors related to digital pollution, focusing on both individuals’ willingness to pay for environmentally friendly digital solutions and their actions to reduce digital environmental impact. Through a comprehensive survey of 300 UK participants, we examined the associations between demographic factors, knowledge levels, perceptions, and environmental actions. While traditional demographic factors such as age and income showed no significant correlation with willingness to pay, we found strong positive correlations with the frequency of environmental consideration (r = 0.47), willingness to act (r = 0.42), and perceived importance of digital pollution (r = 0.40). Notably, knowledge of digital pollution was not correlated with willingness to pay, while self-assessed tech-savviness and environmental knowledge had positive correlations with both willingness to pay and actions taken. Based on a robust cluster analysis, we identified four distinct participant groups: ’Engaged Eco-Tech Enthusiasts’ (youngest, most tech-savvy, and with the highest willingness to act), ‘Knowledgeable Traditionalists’ (oldest, highest knowledge scores, and moderate action), ‘Unengaged Pragmatists’ (lowest engagement), and ‘Affluent Moderates’ (wealthiest and with moderate engagement). These findings provide valuable insights for developing targeted interventions and communication strategies to address this emerging environmental challenge.

The widespread integration of digital technologies into the industry, institutions, and everyday life has introduced environmental challenges known as digital pollution, including the carbon footprint of data centers, energy consumption of digital devices, and electronic waste (e-waste). While general environmental education is extensively studied, public awareness and understanding of digital pollution remain overlooked. This study investigates how demographic factors, including age, education level, income, and occupation, in addition to the perception of environmental knowledge and self-assessed tech-savviness, are associated with environmental and digital pollution literacy. A cross-sectional survey of 300 participants from the UK was conducted, assessing the associations between demographic characteristics, environmental knowledge, and digital pollution awareness. The findings reveal that education level and income are not significantly correlated with literacy scores, whereas age and tech-savviness display meaningful associations with digital pollution literacy. Additionally, general environmental knowledge is positively correlated with digital pollution literacy, suggesting that enhancing environmental literacy may foster a deeper understanding of digital sustainability issues. Notably, a gap emerged between self-reported and actual knowledge, highlighting the need for educational interventions. These findings suggest practical implications for developing targeted educational programs and policies that promote sustainable digital practices and reduce environmental impacts.

Information Systems (IS) analysts are tasked with analyzing customer needs and designing the requisite information system, commonly using models. Ensuring the high quality of these models is crucial for the success of workflow-oriented IS. This study investigates how process thinking influences the ability of novices to produce high-quality process models in IS education, focusing on quality metrics such as completeness, correctness, and irredundancy. We conducted a detailed examination of 181 students enrolled in an IS Analysis and Design course (130 students in the final sample), employing a unique three-task methodology to assess their initial process thinking levels and subsequent model quality throughout the course. Our findings reveal that students with high initial process thinking proficiency continued to excel in subsequent modeling tasks, while those with lower initial proficiency narrowed the gap and improved the quality of their models in subsequent tasks due to learning. Additionally, we found a moderate positive correlation (r = 0.233, p = 0.008) between creativity and success in modeling tasks, suggesting that fostering creativity could enhance the quality of process models. Based on these insights, we recommend that IS training include targeted error correction, preliminary workshops for foundational skill enhancement including training in process thinking, and the integration of creativity into the curriculum. These recommendations aim to better prepare students for the complexities of IS planning and design, contributing to the development of proficient IS analysts capable of producing high-quality process models, thereby directly impacting the overall quality of software development processes.