A novel machine-learning approach for evaluating rebounds-associated environmental footprint of households and application to cooperative housing.

Multiple environmental policies aim to increase resource efficiency and reduce consumption of goods and services with high environmental impact. This may lead to cost-savings and, consequently, additional consumption with environmental impacts (rebound effects). In this study, a supervised machine-learning model (i.

What drives and inhibits researchers to share and use open research data? A systematic literature review to analyze factors influencing open research data adoption.

Both sharing and using open research data have the revolutionary potentials for forwarding scientific advancement. Although previous research gives insight into researchers' drivers and inhibitors for sharing and using open research data, both these drivers and inhibitors have not yet been integrated via a thematic analysis and a theoretical argument is lacking. This study's purpose is to systematically review the literature on individual researchers' drivers and inhibitors for sharing and using open research data.

Volunteers in the Smart City: Comparison of Contribution Strategies on Human-Centered Measures.

Provision of smart city services often relies on users contribution, e.g., of data, which can be costly for the users in terms of privacy.