Using Statistical Models of Book Sales to Assess the GHG reduction potential of Print on Demand

Stephen Wood, Chris W Preist, Lauren Basson

Research output: Chapter in Book/Report/Conference proceedingConference Contribution (Conference Proceeding)

Abstract

Significant volumes of remainders and returns add to the environmental burden of book publishing. The use of digital print technology to print books on demand has been advocated as a means to reduce this. Using a statistical model of books sales we estimate the greenhouse gas emissions savings that might be achieved through the displacement of conventional print fulfillment models with print-on-demand and short run digital print technologies. Under our assumptions we found a reduction in emissions of over 10% could result when digital print runs of around 2000 copies become economic. Industry literature indicates this condition is likely to be met by emerging digital printing presses, suggesting that this technology can play a role in helping the industry reach targets for reducing greenhouse gas emissions. This work demonstrates the utility of statistical simulations of markets for estimating the effect on emissions of changes in print-on-demand economics. Future work would refine the model by incorporating the impact of different genres on sales patterns, and also the impact of sales figures on return rates, rather than using an industry average figure.
Original languageEnglish
Title of host publicationProc. 2012 IEEE International Symposium on Sustainable Systems and Technology
Pages1-6
DOIs
Publication statusPublished - 18 May 2012

Fingerprint Dive into the research topics of 'Using Statistical Models of Book Sales to Assess the GHG reduction potential of Print on Demand'. Together they form a unique fingerprint.

Cite this