Techno-economic assessment of building energy efficiency systems using behavioral change: A case study of an edge-based micro-moments solution

Energy efficiency based on behavioral change has attracted increasing interest in recent years, although, solutions in this area lack much needed techno-economic analysis. That is due to the absence of both prospective studies and consumer awareness. To close such gap, this paper proposes the first techno-economic assessment of a behavioral change-based building energy efficiency solution, to the best of the authors' knowledge. From the one hand, the technical assessment is conducted through (i) introducing a novel edge-based energy efficiency solution; (ii) analyzing energy data using machine learning tools and micro-moments, and producing intelligent, personalized, and explainable action recommendations; and (iii) proceeding with a technical evaluation of four application scenarios, i.e., data collection, data analysis and anomaly detection, recommendation generation, and data visualization. On the other hand, economic assessment is performed by examining the marketability potential of the proposed solution via a market and research analysis of behavioral change-based systems for energy efficiency applications. Also, various factors impacting the commercialization of the final product are investigated before providing recommended actions to ensure its potential marketability via conducting a Go/No-Go evaluation. In conclusion, the proposed solution is designed at a low cost and can save up to 28%-68% of the consumed energy, which results in a Go decision to commercialize the technology. 2021 Elsevier LtdThis paper was made possible by National Priorities Research Program (NPRP) grant No. 10-0130-170288 from the Qatar National Research Fund (a member of Qatar Foundation). The statements made herein are solely the responsibility of the authors.Scopu

EVERYDAY AUTOMATION : Setting a research agenda

Publisher Copyright: © 2022 selection and editorial matter, Sarah Pink, Martin Berg, Deborah Lupton, Minna Ruckenstein.This chapter discusses the Sarah Pink discusses how ethics and trust in AI and ADM have become bound up in industry and government frameworks which treat them as commodities which can be extracted from faceless publics and invested in machines. The second reason that automated technologies receive high levels of publicity or promotion is when they have saved, or are predicted to save, lives: for instance, through accident prevention, medical and pharmaceutical interventions or in humanitarian domains. In contrast, experiences and processes of automation as part of quotidian routines in our everyday lives in our homes, transport, at work and in education have slipped under the radar of much popular and academic attention. The messiness of the ADM and AI fields might be seen as a problem, and one way forward involves engaging in a cross-disciplinary mapping of ADM and AI definitions to produce taxonomies and classifications for a shared vocabulary.Peer reviewe

Social Cues as Digital Nudges in Information Systems Usage Contexts

Analysing human cognition and decision-making has become highly relevant in information systems (IS) research. Yet, although the notion of cognitive biases has been studied for more than 40 years in psychology and other related fields, IS researchers have only recently expressed explicit interest in this phenomenon. Even more nascent is the IS stream that emphasizes the usage and understanding of biases in the favor of humanistic outcomes (e.g., the well-being of individuals) beyond previous scientific endeavors to pursue instrumental goals (e.g., the profit of companies). This fact is reflected in the recent emergence and call for digital nudges - influences that rely on heuristics and biases to guide individuals to beneficial decisions through modest adjustments of the digital choice environments. To advance the emergent research in this field, this thesis targets one of the major bias categories: the social bias (i.e., systematic errors that result from an individual’s interpretation of social cues). Within four articles, the thesis addresses the role of social cues as digital nudges in various IS usage contexts. The first two articles investigate how directly-traceable social cues can overcome service adoption hurdles: Precisely, the first article investigates how employing a verbal (i.e., platform self-disclosure) and a nonverbal social cue (i.e., message interactivity) in a conversational agent (i.e., chatbot) influence users to voluntary self-disclose private information (i.e., e-mail addresses). Moreover, the results revealed that the analysed social cues do not have individual effects, but in fact boost each other through their interaction. The second article deals with the application of various directly-traceable social cues (e.g., pictures of human avatars) as well as the role of personalized recommendations in financial advisory services to improve investors’ financial well-being. The results demonstrate that not only directly-traceable social cues but also recommendations can increase a user’s perceived social presence during the interaction, which in turn influences potential investors to invest higher amounts. The third article continues with recommendations as social cues, yet analyses them from an indirectly-traceable perspective and is devoted to investigating whether the source of the recommendation (i.e., seller or other customers) influences the acceptance of the recommendation in augmented reality applications to help customers in finding the best product for their needs. The findings indicate that customer recommendations reduce a customer’s perceived fit uncertainty of a product, resulting in a higher intention to purchase of a product that previous customers recommended. However, customers refrain from adhering to an automatically-generated recommendation despite recent technological advances that may provide more personalized and thus more suitable recommendations than generic customer recommendations. The fourth and last article examines the impact of displaying sold-out products on campaign success in reward-based crowdfunding. The valuable information indicate how potential backers make use of displayed sold-out product as social cues to derive information for their decision-making from previous backing behavior. In addition, the findings also showed that sold-out products do not have an impact on their own, however, their effect is also influenced by other factors in the environment, namely discount amount and the number of backers (i.e., another social cue). Thus, the article provides learnings for project creators on the design of reward option menus. Overall, this thesis showcases the variety and importance of social cues in numerous applications and is, therefore, to be understood as a first approach to expanding the understudied research field. Furthermore, the results enrich previous research and elucidate various underlying explanatory mechanisms of how and why biased decision-making takes place and how these mechanisms may be used to nudge users in directions beneficial for them and for the employer of these nudges. The overarching contributions of this thesis for research consists of (1) investigating the existence and effects of various social cues on user decision-making, and (2) probing social cues in several IS usage contexts with their unique circumstances and influences, not only in a vacuum but also in conjunction with other interacting variables. Additionally, this thesis provides interesting and sometimes even counterintuitive recommendations as well as actionable and generalizable guidelines on social cues that practitioners can easily apply to various contexts

Implementing Web 2.0 in secondary schools: impacts, barriers and issues

One of the reports from the Web 2.0 technologies for learning at KS3 and KS4 project. This report explored Impact of Web 2.0 technologies on learning and teaching and drew upon evidence from multiple sources: field studies of 27 schools across the country; guided surveys of 2,600 school students; 100 interviews and 206 online surveys conducted with managers, teachers and technical staff in these schools; online surveys of the views of 96 parents; interviews held with 18 individual innovators in the field of Web 2.0 in education; and interviews with nine regional managers responsible for implementation of ICT at national level

Design of an E-learning system using semantic information and cloud computing technologies

Humanity is currently suffering from many difficult problems that threaten the life and survival of the human race. It is very easy for all mankind to be affected, directly or indirectly, by these problems. Education is a key solution for most of them. In our thesis we tried to make use of current technologies to enhance and ease the learning process. We have designed an e-learning system based on semantic information and cloud computing, in addition to many other technologies that contribute to improving the educational process and raising the level of students. The design was built after much research on useful technology, its types, and examples of actual systems that were previously discussed by other researchers. In addition to the proposed design, an algorithm was implemented to identify topics found in large textual educational resources. It was tested and proved to be efficient against other methods. The algorithm has the ability of extracting the main topics from textual learning resources, linking related resources and generating interactive dynamic knowledge graphs. This algorithm accurately and efficiently accomplishes those tasks even for bigger books. We used Wikipedia Miner, TextRank, and Gensim within our algorithm. Our algorithm‘s accuracy was evaluated against Gensim, largely improving its accuracy. Augmenting the system design with the implemented algorithm will produce many useful services for improving the learning process such as: identifying main topics of big textual learning resources automatically and connecting them to other well defined concepts from Wikipedia, enriching current learning resources with semantic information from external sources, providing student with browsable dynamic interactive knowledge graphs, and making use of learning groups to encourage students to share their learning experiences and feedback with other learners.Programa de Doctorado en Ingeniería Telemática por la Universidad Carlos III de MadridPresidente: Luis Sánchez Fernández.- Secretario: Luis de la Fuente Valentín.- Vocal: Norberto Fernández Garcí

Theory-driven Visual Design to Support Reflective Dietary Practice via mHealth: A Design Science Approach

Design for reflection in human-computer interaction (HCI) has evolved from focusing on an abstract and outcome-driven design subject towards exposing procedural or structural reflection characteristics. Although HCI research has recognized that an individual\u27s reflection is a long-lasting, multi-layered process that can be supported by meaningful design, researchers have made few efforts to derive insights from a theoretical perspective about appropriate translation into end-user visual means. Therefore, we synthesize theoretical knowledge from reflective practice and learning and argue for a differentiation between time contexts of reflection that design needs to address differently. In an interdisciplinary design-science-research project in the mHealth nutrition promotion context, we developed theory-driven guidelines for “reflection-in-action” and “reflection-on-action”. Our final design guidelines emerged from prior demonstrations and a final utility evaluation with mockup artifacts in a laboratory experiment with 64 users. Our iterative design and the resulting design guidelines offer assistance for addressing reflection design by answering reflective practice’s respective contextual requirements. Based on our user study, we show that reflection in terms of “reflection- in-action” benefits from offering actionable choice criteria in an instant timeframe, while “reflection-on-action” profits from the structured classification of behavior-related criteria from a longer, still memorable timeframe

Exploiting the conceptual space in hybrid recommender systems: a semantic-based approach

Tesis doctoral inédita. Universidad Autónoma de Madrid, Escuela Politécnica Superior, octubre de 200