Internal sustainability efforts (ISE) refer to a wide range of internal corporate policies focused on employees. They promote, for example, work-life balance, gender equality, and a harassment-free working environment. At times, however, companies fail to keep their promises by not publicizing truthful reports on these practices, or by overlooking employees voices on how these practices are implemented. To partly fix that, we developed a deep-learning framework that scored four fifths of the S&P 500 companies in terms of six ISEs, and a web-based system that engages users in a learning and reflection process about these ISEs. We evaluated the system in two crowdsourced studies with 421 participants, and compared our treemap visualization with a baseline textual representation. We found that our interactive treemap increased by up to 7% our participants opinion change about ISEs, demonstrating its potential in machine-learning driven visualizations
Visualizing Internal Sustainability Efforts in Big Companies / Ceccarini, Chiara; Bogucka, Edyta Paulina; Sen, Indira; Constantinides, Marios; Prandi, Catia; Quercia, Daniele. - In: IEEE COMPUTER GRAPHICS AND APPLICATIONS. - ISSN 0272-1716. - 42:3(2022), pp. 87-98. [10.1109/mcg.2022.3163063]
Visualizing Internal Sustainability Efforts in Big Companies
Quercia, Daniele
2022
Abstract
Internal sustainability efforts (ISE) refer to a wide range of internal corporate policies focused on employees. They promote, for example, work-life balance, gender equality, and a harassment-free working environment. At times, however, companies fail to keep their promises by not publicizing truthful reports on these practices, or by overlooking employees voices on how these practices are implemented. To partly fix that, we developed a deep-learning framework that scored four fifths of the S&P 500 companies in terms of six ISEs, and a web-based system that engages users in a learning and reflection process about these ISEs. We evaluated the system in two crowdsourced studies with 421 participants, and compared our treemap visualization with a baseline textual representation. We found that our interactive treemap increased by up to 7% our participants opinion change about ISEs, demonstrating its potential in machine-learning driven visualizationsFile | Dimensione | Formato | |
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https://hdl.handle.net/11583/2996116