Sustainability in the Fourth Industrial Age: Technologies, Systems and Analytics
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ItemPrinciples of Green Data Mining( 2019-01-08)This paper develops a set of principles for green data mining, related to the key stages of business un- derstanding, data understanding, data preparation, modeling, evaluation, and deployment. The principles are grounded in a review of the Cross Industry Stand- ard Process for Data mining (CRISP-DM) model and relevant literature on data mining methods and Green IT. We describe how data scientists can contribute to designing environmentally friendly data mining pro- cesses, for instance, by using green energy, choosing between make-or-buy, exploiting approaches to data reduction based on business understanding or pure statistics, or choosing energy friendly models.
ItemInfluence on Intention to Adopt Green IS: Boosting Endogenous Motivations with Persuasive Systems Design( 2019-01-08)Because pro-environmental behavior is often perceived as burdensome, encouraging sustainable habits can be a challenging task. Green IS provide additional means to instill proper sustainable manners in its users. However, even adoption of Green IS is not necessarily easy and is likely to require both motivation and persuasion. In this paper, we analyze the impact of Persuasive Systems Design on endogenous motivations linked to the attitude formation and subsequent intention to adopt Green IS. Based on the presented theoretical background, we construct a research model capturing relationships among persuasive design categories, different types of motivations, attitude and intention to adopt Green IS. Using structural equation modeling, we analyze the data collected with the survey. Findings of our study prove that the researched concepts are interrelated showing impact of computer-human dialogue support, system credibility support, and social support on extrinsic motivation and suggesting importance of enhancing Green IS with Persuasive Systems Design.
ItemOn Making a Difference: Towards an Integrative Framework for Green IT and Green IS Adoption( 2019-01-08)Organizations and society nowadays face significant challenges. Organizations are required to fundamentally digital transform by assimilating Information Technology (IT) and Information System (IS) assets. Society faces an increasingly severe global climate disruption and needs to become more environmentally friendly. Green IT (GIT) and Green IS (GIS), as technologies and initiatives that seek to reduce the negative impacts of IT/IS on the environment, are a response to this. They can help organizations to gain a competitive advantage while also addressing broad-scale environmental issues. We undertake a literature review to frame the general GIT/GIS adoption process. We provide an overarching understanding by modeling a sequence of five cognitive adoption phases (outset, pre-adoption, adoption, post-adoption, and outcome) on four levels (environmental, societal, organizational, and individual). By recognizing that GIT/GIS adoption has multiple drivers and outcomes, we provide an extensive perspective on GIT/GIS adoption.
ItemDecentralized Multi-Agent System Applied to the Decision Making Process of the Microgrid Restoration Procedure towards Sustainability( 2019-01-08)A significant procedure to ensure the consumer supply is Power System Restoration (PSR). Due to the increase of the number of distributed generators in the grid, it is possible to shift from the conventional PSR to a new strategy involving the use of distributed energy resources (DER). In this paper, a decentralized multi-agent system (MAS) is proposed to cope with the restoration procedure in a microgrid (MG). Each agent is assigned to a specific consumer or microsource (MS), communicating with other agents at every stage of the restoration procedure so that a common decision is reached. The 0/1 knapsack problem is the problem that every agent solves to determine the best load connection sequence during the restoration of the MG. Two different case studies are used to test the MAS on a dynamically modeled benchmark MG: a total blackout and a partial blackout. Regarding the partial blackout case, demand response emergency programs are considered to manage the loads in the MG. The MAS is developed in Matlab/Simulink environment and by performing the corresponding dynamic simulations it is possible to validate this system towards sustainability.