SUSTAINABLE PRINT MANAGEMENT VIA DATA-DRIVEN APPROACHES - Dhawas, Nitin; Sonar, Reshma; Bhandari, Mahesh Ashok; Wankhade, Shalini; Ghuge, Kalyani; Shelke, Ganesh Chandrabhan; Kokane, Chandrakant (ShodhKosh: Journal of Visual and Performing Arts, 2026)
Sustainable print management has become an issue of paramount importance in respect to organizations that want to mitigate the effects they have on the environment whilst still being able to operate efficiently. The conventional print management systems tend to be based on fixed set of rules and manual controls hence resulting in wastage of paper, energy and unchecked waste. The research is a proposed comprehensive data-oriented system of sustainable print management, which combines data analytics, predictive modeling, and optimization methods in order to allow intelligent, adaptative, and resource-efficient printing environments. The suggested solution will take advantage of past print logs, device level energy logs, and patterns of user behavior to predict print demand, uncover inefficiencies, and make informed decisions. Predictive models are also used to forecast print volumes in future and possible waste in order to allow proactive measures to be taken like job consolidation, duplex enforcement and digital alternatives. The optimization algorithms also contribute to sustainability by dynamically assigning the print jobs to devices which consume less energy and scheduling workloads to reduce maximum consumption of energy. Moreover, user-friendly analytics is also integrated in order to gain an insight into the printing activity and implement nudging technologies that promote responsible printing without interfering with productivity. The experimental results show that there are quantifiable decreases in the amount of paper, energy use, and print-related emissions in comparison with the traditional systems and serviceable levels are attained. The results show the possibility of the data-driven strategies to make print management more of a proactive sustainability contributor as opposed to an operational reactive mechanism.