Purpose-The purpose of this paper is to present a multi-faceted summary and classification of the existing literature in the field of quality of service for e-government and outline the main components of a quality model for e-government services. Design/methodology/approach-Starting with fundamental quality principles the paper examines and analyzes 36 different quality approaches concerning public sector services, e-services in general and more specifically e-government services. Based on the dimensions measured by each approach the paper classifies the approaches and concludes on the basic factors needed for the development of a complete quality model of e-government services. Findings-Based on the classification of literature approaches, the paper provides information about the main components of a quality model that may be used for the continuous monitoring and measuring of public e-services' quality. The classification forms the basis for answering questions that must be addressed by the quality model, such as: What to assess?; Who will perform the assessment? and How the assessment will be done? Practical implications-This model can be used by the management of public organizations in order to measure and monitor the quality of e-services delivered to citizens. Originality/value-The results of the work presented in this paper form the basis for the development of a quality model for e-government services.

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Abstract:In recent years, persuasive interventions for inducing sustainable mobility behaviours have become an active research field. This review paper systematically analyses existing approaches and prototype systems as well as field studies and describes and classifies the persuasive strategies used for changing behaviours in the domain of mobility and transport. We provide a review of 44 papers on persuasive technology for sustainable transportation aiming to (i) answer important questions regarding the effectiveness of persuasive technology for changing mobility behaviours, (ii) summarize and highlight trends in the technology design, research methods, strategies and theories, (iii) uncover limitations of existing approaches and applications, and (iv) suggest directions for future research.

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Purpose – The purpose of this paper is to perform an extensive literature review in the area of decision making for condition-based maintenance (CBM) and identify possibilities for proactive online recommendations by considering real-time sensor data. Based on these, the paper aims at proposing a framework for proactive decision making in the context of CBM. Design/methodology/approach – Starting with the manufacturing challenges and the main principles of maintenance, the paper reviews the main frameworks and concepts regarding CBM that have been proposed in the literature. Moreover, the terms of e-maintenance, proactivity and decision making are analysed and their potential relevance to CBM is identified. Then, an extensive literature review of methods and techniques for the various steps of CBM is provided, especially for prognosis and decision support. Based on these, limitations and gaps are identified and a framework for proactive decision making in the context of CBM is proposed. Findings – In the proposed framework for proactive decision making, the CBM concept is enriched in the sense that it is structured into two components: the information space and the decision space. Moreover, it is extended in a way that decision space is further analyzed according to the types of recommendations that can be provided. Moreover, possible inputs and outputs of each step are identified. Practical implications – The paper provides a framework for CBM representing the steps that need to be followed for proactive recommendations as well as the types of recommendations that can be given. The framework can be used by maintenance management of a company in order to conduct CBM by utilizing real-time sensor data depending on the type of decision required. Originality/value – The results of the work presented in this paper form the basis for the development and implementation of proactive Decision Support System (DSS) in the context of maintenance.

Rendering transport behaviours more sustainable is a pressing issue of our times. In this paper, we rely on the deep penetration of mobile phones in order to influence citizens' behavior through data-driven mobility and persuasive profiles. Our proposed approach aims to nudge users on a personalized level in order to change their mobility behavior and make more sustainable choices. To achieve our goal, first we leverage pervasive mobile sensing to uncover users' mobility patterns and use of transportation modes. Second, we construct users' persuadability profiles by considering their personality and mobility behavior. With the use of the aforementioned information we generate personalized interventions that nudge users to adopt sustainable transportation habits. These interventions rely on persuasive technologies and are embedded in a route planning application for smartphones. A pilot study with 30 participants using the system for 6 weeks provided fairly positive evaluation results in terms of the acceptance of our approach and revealed instances of behavioural change.

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