Encouraging pro-environmental behaviours: a review of methods and approaches. ESRI Working Paper No. 645 December 2019

Many urgent environmental problems can be mitigated with more sustainable use of resource. An acknowledgement of which is a growing interest among policy practitioners in encouraging pro-environmental behaviour change initiatives. The effect of anthropic pressure on the environment is long known and the first pro-environmental behaviour studies date back to the middle 1970s. Despite this, the scientific literature has not yet answered several questions: what are the most suitable ways to encourage behavioural changes? What are the barriers to project implementation? What are the long run effects of behavioural change projects? With this in mind, this contribution offers a review of the existing literature on behavioural change case studies and provides a categorisation of treatments and guidelines for successful project implementation. Five different approaches have been considered: education and awareness, social influence, relationship building, incentives and nudges, which have been used in experimental studies. On balance the case studies suggest that all approaches are suitable but their selection should be based on specific objectives and target population. Interestingly, the choice of the behaviour to change is rarely discussed before project implementation. This analysis also highlights that little is known on whether behaviour change projects achieve sustained pro-environmental behavioural change over time

Citizen Social Lab: A digital platform for human behaviour experimentation within a citizen science framework

Cooperation is one of the behavioral traits that define human beings, however we are still trying to understand why humans cooperate. Behavioral experiments have been largely conducted to shed light into the mechanisms behind cooperation and other behavioral traits. However, most of these experiments have been conducted in laboratories with highly controlled experimental protocols but with varied limitations which limits the reproducibility and the generalization of the results obtained. In an attempt to overcome these limitations, some experimental approaches have moved human behavior experimentation from laboratories to public spaces, where behaviors occur naturally, and have opened the participation to the general public within the citizen science framework. Given the open nature of these environments, it is critical to establish the appropriate protocols to maintain the same data quality that one can obtain in the laboratories. Here, we introduce Citizen Social Lab, a software platform designed to be used in the wild using citizen science practices. The platform allows researchers to collect data in a more realistic context while maintaining the scientific rigour, and it is structured in a modular and scalable way so it can also be easily adapted for online or brick-and-mortar experimental laboratories. Following citizen science guidelines, the platform is designed to motivate a more general population into participation, but also to promote engaging and learning of the scientific research process. We also review the main results of the experiments performed using the platform up to now, and the set of games that each experiment includes. Finally, we evaluate some properties of the platform, such as the heterogeneity of the samples of the experiments and their satisfaction level, and the parameters that demonstrate the robustness of the platform and the quality of the data collected.Comment: 17 pages, 11 figures and 4 table

Non-Invasive Ambient Intelligence in Real Life: Dealing with Noisy Patterns to Help Older People

This paper aims to contribute to the field of ambient intelligence from the perspective of real environments, where noise levels in datasets are significant, by showing how machine learning techniques can contribute to the knowledge creation, by promoting software sensors. The created knowledge can be actionable to develop features helping to deal with problems related to minimally labelled datasets. A case study is presented and analysed, looking to infer high-level rules, which can help to anticipate abnormal activities, and potential benefits of the integration of these technologies are discussed in this context. The contribution also aims to analyse the usage of the models for the transfer of knowledge when different sensors with different settings contribute to the noise levels. Finally, based on the authors’ experience, a framework proposal for creating valuable and aggregated knowledge is depicted.This research was partially funded by Fundación Tecnalia Research & Innovation, and J.O.-M. also wants to recognise the support obtained from the EU RFCS program through project number 793505 ‘4.0 Lean system integrating workers and processes (WISEST)’ and from the grant PRX18/00036 given by the Spanish Secretaría de Estado de Universidades, Investigación, Desarrollo e Innovación del Ministerio de Ciencia, Innovación y Universidades

Review and Comparison of Intelligent Optimization Modelling Techniques for Energy Forecasting and Condition-Based Maintenance in PV Plants

Within the field of soft computing, intelligent optimization modelling techniques include various major techniques in artificial intelligence. These techniques pretend to generate new business knowledge transforming sets of "raw data" into business value. One of the principal applications of these techniques is related to the design of predictive analytics for the improvement of advanced CBM (condition-based maintenance) strategies and energy production forecasting. These advanced techniques can be used to transform control system data, operational data and maintenance event data to failure diagnostic and prognostic knowledge and, ultimately, to derive expected energy generation. One of the systems where these techniques can be applied with massive potential impact are the legacy monitoring systems existing in solar PV energy generation plants. These systems produce a great amount of data over time, while at the same time they demand an important e ort in order to increase their performance through the use of more accurate predictive analytics to reduce production losses having a direct impact on ROI. How to choose the most suitable techniques to apply is one of the problems to address. This paper presents a review and a comparative analysis of six intelligent optimization modelling techniques, which have been applied on a PV plant case study, using the energy production forecast as the decision variable. The methodology proposed not only pretends to elicit the most accurate solution but also validates the results, in comparison with the di erent outputs for the di erent techniques

Factors affecting e-government adoption in the state of Qatar

Electronic government (e-government) initiatives are in their early stages in many developing countries and faced with various issues pertaining to their implementation, adoption and diffusion. Although e-government has increased transparency and improved communication and access to information for citizens, digital diffusion of information is often achieved at high cost to government agencies. Conversely, citizens’ adoption of e-government services has been less than satisfactory in most countries. While studies by researchers continue to outline the most salient adoption constructs, as well as various frameworks and models for understanding adoption, research by independent consultancy/research organisations has produced a host of statistics and league tables of good and bad practices of service delivery. Like many other developing countries, the e-government initiative in the state of Qatar has faced a number of challenges since its inception in 2000. This study utilises the Unified Theory of Acceptance and Use of Technology (UTAUT) to explore the adoption of e-government services in the state of Qatar. 1179 citizens were surveyed to collect primary data. A regression analysis was conducted to examine the influence of the factors adapted from the UTAUT on e-government adoption. Reliability test reported values of the various constructs vary between (0.74) and (0.91). The findings reveal that effort expectancy and social influences determine citizens’ behavioural intention towards e-government. Additionally, facilitating conditions and behavioural intention were found to determine citizens’ use of e-government services in Qatar. Implications for practice and research are discussed

Human experience in the natural and built environment : implications for research policy and practice

22nd IAPS conference. Edited book of abstracts. 427 pp. University of Strathclyde, Sheffield and West of Scotland Publication. ISBN: 978-0-94-764988-3

Towards an evaluation framework for medical web applications

Copyright @ 2013 EMCIS.The main aim of this study is to review and analyse various evaluation frameworks used to assess the operational effectiveness of various Information Technology (IT) processes/applications and identify their strengths in order to form a new holistic framework for economic evaluation of web applications. This research aims to address the need for a new holistic evaluation framework for the purpose of the evaluation of the medical web applications. Over the last decade more and more, companies used accountancy techniques such as the frameworks analysed in this research. This new holistic framework that was developed will include also steps regarding the indirect and intangible costs and benefits identification and their incorporation in the evaluation process. Moreover the new emerging market of the medical websites and the embedded on them web applications requires also a new evaluation framework that will provide accurate results in the estimation of the efficiency of an investment on them. The paper first presents an introduction about why economic evaluation is important when evaluating the Information Technology in organizations. Various studies are reviewed, which highlight the ever increasing importance of integrating economic evaluation processes, such as Cost Benefit Analysis (CBA) and Return on Investment (ROI), into systems and processes of organizations and economic organizations, and analyse the factors that govern their role. Finally, the evaluation frameworks and methods that are found in these studies should be used as a part of a proactive systematic action plan that the organizations could use to avoid budget reduction due to incorrect planning. The next part of this study includes a comprehensive presentation and review of past frameworks used to evaluate Information Technology. The frameworks that are reviewed are the Framework for evaluation of information systems, the Information Technology Adoption Model (ITAM), the Total Evaluation and Acceptance Methodology (TEAM) framework, the ROI Process Model and HOT-fit evaluation framework for Health Information Systems

Serotonin and Noradrenaline Reuptake Inhibitors Improve Micturition Control in Mice

Poor micturition control may cause profound distress, because proper voiding is mandatory for an active social life. Micturition results from the subtle interplay of central and peripheral components. It involves the coordination of autonomic and neuromuscular activity at the brainstem level, under the executive control of the prefrontal cortex. We tested the hypothe- sis that administration of molecules acting as reuptake inhibitors of serotonin, noradrenaline or both may exert a strong effect on the control of urine release, in a mouse model of overac- tive bladder. Mice were injected with cyclophosphamide (40 mg/kg), to increase micturition acts. Mice were then given one of four molecules: the serotonin reuptake inhibitor imipra- mine, its metabolite desipramine that acts on noradrenaline reuptake, the serotonin and nor- adrenaline reuptake inhibitor duloxetine or its active metabolite 4-hydroxy-duloxetine. Cyclophosphamide increased urine release without inducing overt toxicity or inflammation, except for increase in urothelium thickness. All the antidepressants were able to decrease the cyclophosphamide effects, as apparent from longer latency to the first micturition act, decreased number of urine spots and volume of released urine. These results suggest that serotonin and noradrenaline reuptake inhibitors exert a strong and effective modulatory ef- fect on the control of urine release and prompt to additional studies on their central effects on brain areas involved in the social and behavioral control of micturition