All you can stream: Investigating the role of user behavior for greenhouse gas intensity of video streaming

The information and communication technology sector reportedly has a relevant impact on the environment. Within this sector, video streaming has been identified as a major driver of CO2-emissions. To make streaming more sustainable, environmentally relevant factors must be identified on both the user and the provider side. Hence, environmental assessments, like life cycle assessments (LCA), need to broaden their perspective from a mere technological to one that includes user decisions and behavior. However, quantitative data on user behavior (e.g. streaming duration, choice of end device and resolution) are often lacking or difficult to integrate in LCA. Additionally, identifying relevant determinants of user behavior, such as the design of streaming platforms or user motivations, may help to design streaming services that keep environmental impact at a passable level. In order to carry out assessments in such a way, interdisciplinary collaboration is necessary. Therefore, this exploratory study combined LCA with an online survey (N= 91, 7 consecutive days of assessment). Based on this dataset the use phase of online video streaming was modeled. Additionally, factors such as sociodemographic, motivational and contextual determinants were measured. Results show that CO2-intensity of video streaming depends on several factors. It is shown that for climate intensity there is a factor 10 between choosing a smart TV and smartphone for video streaming. Furthermore, results show that some factors can be tackled from provider side to reduce overall energy demand at the user side; one of which is setting a low resolution as default.Comment: 7th International Conference on ICT for Sustainability (ICT4S

Resource management in Big Data initiatives: processes and dynamic capabilities

© 2016 The Authors. Effective management of organizational resources in big data initiatives is of growing importance. Although academic and popular literatures contain many examples of big data initiatives, very few are repeated in the same organization. This suggests either big data delivers benefits once only per organization or senior managers are reluctant to commit resources to big data on a sustained basis. This paper makes three contributions to the Special Issue’s theme of enhancing organizational resource management. One is to establish an archetype business process for big data initiatives. The second contribution directs attention to creating a dynamic capability with big data initiatives. The third identifies drawbacks of resource base theory (RBT) and it’s underpinning assumptions in the context of big data. The paper discusses lessons learnt from the case study and draws out implications for practice and business research. The paper’s intellectual and practical contributions are based on an in-depth case study of the European Poles of Excellence (EIPE) big data initiative and evidence from the extant literature

Energy-efficient management and control in video distribution networks: "legacy" hardware based solutions and perspectives of virtualized networking environments

The chapter focuses in particular on energy-efficiency issues in the context of video distribution networks (VDNs), where additional paradigms, as content delivery and caching operations, play a relevant role. We first provide a short review on the current state and on energy-related aspects in VDNs; then, we focus on Local Control Policies / Network Control Policies in this context, and the possible role of the Green Abstraction Layer (GAL), a recent ETSI standard, to provide an abstract interface to convey energy efficiency related parameters to the management and control entities. In doing this, we consider both \u2018traditional\u2019 networking architectures based on specialized hardware, and the evolution towards virtualized infrastructures, where the GAL can still play a significant role, if suitably adapted to the specific environment