Whole of government critical success factors towards integrated E-government services: a preliminary review

Electronic Government (E-government) becomes one of the key elements for sustainable development of the country. Previous studies on E-government indicate that most governments are performing well in E-government implementation. However, the issues of process duplication and bureaucracy in services should be addressed to build trust and increase citizens’ satisfaction. Currently, there is a necessity to focus on the development of integrated and tailored-made services that suit with citizens’ needs. This initiative entails high commitment and collaboration from agencies, which can be achieved through the whole of government (WoG) approach. This study aims to identify the critical success factors of WoG towards the development of integrated E-government services. A preliminary review was conducted on previous studies and reports to get some insights of the subject being studied. The identified data were coded and analysed using content analysis method. The findings demonstrate that there are a number of critical success factors for WoG, which consist of technical and non-technical aspects. The findings act as a theoretical framework for better understanding about WoG approach for integrated E-government services

Strategies and Approaches for Exploiting the Value of Open Data

Data is increasingly permeating into all dimensions of our society and has become an indispensable commodity that serves as a basis for many products and services. Traditional sectors, such as health, transport, retail, are all benefiting from digital developments. In recent years, governments have also started to participate in the open data venture, usually with the motivation of increasing transparency. In fact, governments are one of the largest producers and collectors of data in many different domains. As the increasing amount of open data and open government data initiatives show, it is becoming more and more vital to identify the means and methods how to exploit the value of this data that ultimately affects various dimensions. In this thesis we therefore focus on researching how open data can be exploited to its highest value potential, and how we can enable stakeholders to create value upon data accordingly. Albeit the radical advances in technology enabling data and knowledge sharing, and the lowering of barriers to information access, raw data was given only recently the attention and relevance it merits. Moreover, even though the publishing of data is increasing at an enormously fast rate, there are many challenges that hinder its exploitation and consumption. Technical issues hinder the re-use of data, whilst policy, economic, organisational and cultural issues hinder entities from participating or collaborating in open data initiatives. Our focus is thus to contribute to the topic by researching current approaches towards the use of open data. We explore methods for creating value upon open (government) data, and identify the strengths and weaknesses that subsequently influence the success of an open data initiative. This research then acts as a baseline for the value creation guidelines, methodologies, and approaches that we propose. Our contribution is based on the premise that if stakeholders are provided with adequate means and models to follow, then they will be encouraged to create value and exploit data products. Our subsequent contribution in this thesis therefore enables stakeholders to easily access and consume open data, as the first step towards creating value. Thereafter we proceed to identify and model the various value creation processes through the definition of a Data Value Network, and also provide a concrete implementation that allows stakeholders to create value. Ultimately, by creating value on data products, stakeholders participate in the global data economy and impact not only the economic dimension, but also other dimensions including technical, societal and political

Political Science and Digitalization – Global Perspectives

Digitalization is not only a new research subject for political science, but a transformative force for the discipline in terms of teaching and learning as well as research methods and publishing. This volume provides the first account of the influence of digitalization on the discipline of political science including contributions from 20 different countries. It presents a regional stocktaking of the challenges and opportunities of digitalization in most world regions

Political Science and Digitalization – Global Perspectives

Digitalization is not only a new research subject for political science, but a transformative force for the discipline in terms of teaching and learning as well as research methods and publishing. This volume provides the first account of the influence of digitalization on the discipline of political science including contributions from 20 different countries. It presents a regional stocktaking of the challenges and opportunities of digitalization in most world regions

Electronic participation through social media citizens' acceptance factors at local government level

Tese de Doutoramento em Information System and TechnologyMuitas das iniciativas de Participação Eletrónica (e-Participação) − vistas neste estudo como o uso das Tecnologias de Informação e Comunicação (TIC) para facilitar a participação do cidadão no processo de tomada de decisão política −, não têm conseguido alcançar o sucesso esperado no que concerne ao nível de envolvimento do cidadão atingido. Esta falta de envolvimento é particularmente evidente nas iniciativas lideradas e disponibilizadas pelos governos (iniciativas governamentais de e-Participação). Embora o rápido crescimento das redes sociais, especialmente do Facebook, seja apontado como um meio promissor para fomentar e melhorar o nível de participação do cidadão, o problema do baixo nível de aceitação e de envolvimento do cidadão em iniciativas de e-participação persiste. Importa, pois, compreender, conceptualizar e teorizar sobre os fatores que afetam o nível de aceitação evidenciado pelo cidadão em relação a esse tipo de iniciativas. Assim, é finalidade deste estudo investigar os fatores relevantes que influenciam a intenção dos cidadãos de aceitarem e de se envolverem nas iniciativas governamentais de e-Participação disponibilizadas através do Facebook, baseando-se na Teoria do Comportamento Planeado (Theory of Planned Behavior (TPB)), devidamente estendida pela incorporação de um conjunto de fatores relevantes que emergiram da literatura relevante. Os resultados quantitativos de um questionário respondido por 400 cidadãos Jordanos, mostram que a atitude do cidadão (citizen attitude (ATT)), a eficácia de participação (participation efficacy (PE)), e o controlo comportamental percecionado (perceived behavioral control (PBC)) afetam direta e positivamente a intenção de participação do cidadão. Por sua vez, a atitude do cidadão é determinada pela eficácia de participação (participation efficacy (PE)), utilidade percecionada e compatibilidade do Facebook (perceived usefullness (PU) e compatibility (COMP)), e valor percecionado do envolvimento do cidadão nas iniciativas governamentais de e- Participação (perceived value (PV)). Contrariamente, nem as normas sociais (social norms (SN)) nem a confiança do cidadão no Facebook (citizen’s trust in Facebook (CT_FB)) têm impacto significativo na intenção e atitude do cidadão. Adicionalmente, o valor percecionado (perceived value (PV)) é influenciado pela perceção de facilidade de utilização do Facebook (perceived ease of use (PEOU)) e pela confiança dos cidadãos no governo (citizen’s trust in government (CT_GOV)). O estudo mostra ainda que os cidadãos Jordanos apresentam uma atitude positiva em relação ao envolvimento em iniciativas governamentais de e participação disponibilizadas através do Facebook mas apresentam uma intenção moderada de participar em tais iniciativas. Por ser um dos poucos trabalhos conhecidos focado no estudo da intenção dos cidadãos de aceitarem e de se envolverem em iniciativas governamentais de e-Participação disponibilizadas através das redes sociais, o estudo aqui descrito aporta contribuições relevantes para o desenvolvimento do conhecimento teórico e prático no domínio da participação eletrónica.Electronic Participation (e-Participation) initiatives, seen as the use of information and communication technologies (ICT) for facilitating citizen participation in the process of policy decision-making, have often had a limited success of citizens' engagement, particularly those initiatives sponsored by governments (government-led e-Participation initiatives). While the rapid growth of using social media networks, specifically Facebook, represented a new promising venue for enhancing citizens’ participation, the problem of low-level citizens’ acceptance and engagement remains. Hence, conceptual clarity on what factors affect citizens’ acceptance of such initiatives are yet to be theorized. This study aims at investigating relevant factors that influence citizens’ intention to accept and to engage in government-led e-Participation initiatives through Facebook, based on extended Theory of Planned Behavior (TPB) through the incorporation of a set of factors that emerged from relevant literature. Using data from a survey of 400 Jordanian citizens, the quantitative results proved that citizen attitude (ATT), participation efficacy (PE), and perceived behavioral control (PBC) directly and positively affect citizen’s intention to participate. Citizen attitude, in turn, is determined by participation efficacy (PE), perceived usefulness and compatibility of Facebook (PU and COMP), and perceived value of citizen’s involvement in government-led e-Participation initiatives (PV). However, neither social norms (SN) nor citizen’s trust in Facebook (CT_FB) have significant impact over citizen intention or attitude. Further, perceived value (PV) is influenced by perceived ease of use of Facebook (PEOU), and citizen’s trust in government (CT_GOV). Additionally, the study found that Jordanian citizens uphold relatively high positive attitude toward engaging in government-led e-Participation initiatives through Facebook but they have a moderate intention to participate in those initiatives. As the present work is one of very few studies addressing citizens’ intention to accept and to engage in e-Participation initiatives through social media in government context, the study provides important implications for theory and practice

Political Science and Digitalization – Global Perspectives

Digitalization is not only a new research subject for political science, but a transformative force for the discipline in terms of teaching and learning as well as research methods and publishing. This volume provides the first account of the influence of digitalization on the discipline of political science including contributions from 20 different countries. It presents a regional stocktaking of the challenges and opportunities of digitalization in most world regions

Personalized information retrieval based on time-sensitive user profile

Les moteurs de recherche, largement utilisés dans différents domaines, sont devenus la principale source d'information pour de nombreux utilisateurs. Cependant, les Systèmes de Recherche d'Information (SRI) font face à de nouveaux défis liés à la croissance et à la diversité des données disponibles. Un SRI analyse la requête soumise par l'utilisateur et explore des collections de données de nature non structurée ou semi-structurée (par exemple : texte, image, vidéo, page Web, etc.) afin de fournir des résultats qui correspondent le mieux à son intention et ses intérêts. Afin d'atteindre cet objectif, au lieu de prendre en considération l'appariement requête-document uniquement, les SRI s'intéressent aussi au contexte de l'utilisateur. En effet, le profil utilisateur a été considéré dans la littérature comme l'élément contextuel le plus important permettant d'améliorer la pertinence de la recherche. Il est intégré dans le processus de recherche d'information afin d'améliorer l'expérience utilisateur en recherchant des informations spécifiques. Comme le facteur temps a gagné beaucoup d'importance ces dernières années, la dynamique temporelle est introduite pour étudier l'évolution du profil utilisateur qui consiste principalement à saisir les changements du comportement, des intérêts et des préférences de l'utilisateur en fonction du temps et à actualiser le profil en conséquence. Les travaux antérieurs ont distingué deux types de profils utilisateurs : les profils à court-terme et ceux à long-terme. Le premier type de profil est limité aux intérêts liés aux activités actuelles de l'utilisateur tandis que le second représente les intérêts persistants de l'utilisateur extraits de ses activités antérieures tout en excluant les intérêts récents. Toutefois, pour les utilisateurs qui ne sont pas très actifs dont les activités sont peu nombreuses et séparées dans le temps, le profil à court-terme peut éliminer des résultats pertinents qui sont davantage liés à leurs intérêts personnels. Pour les utilisateurs qui sont très actifs, l'agrégation des activités récentes sans ignorer les intérêts anciens serait très intéressante parce que ce type de profil est généralement en évolution au fil du temps. Contrairement à ces approches, nous proposons, dans cette thèse, un profil utilisateur générique et sensible au temps qui est implicitement construit comme un vecteur de termes pondérés afin de trouver un compromis en unifiant les intérêts récents et anciens. Les informations du profil utilisateur peuvent être extraites à partir de sources multiples. Parmi les méthodes les plus prometteuses, nous proposons d'utiliser, d'une part, l'historique de recherche, et d'autre part les médias sociaux. En effet, les données de l'historique de recherche peuvent être extraites implicitement sans aucun effort de l'utilisateur et comprennent les requêtes émises, les résultats correspondants, les requêtes reformulées et les données de clics qui ont un potentiel de retour de pertinence/rétroaction. Par ailleurs, la popularité des médias sociaux permet d'en faire une source inestimable de données utilisées par les utilisateurs pour exprimer, partager et marquer comme favori le contenu qui les intéresse. En premier lieu, nous avons modélisé le profil utilisateur utilisateur non seulement en fonction du contenu de ses activités mais aussi de leur fraîcheur en supposant que les termes utilisés récemment dans les activités de l'utilisateur contiennent de nouveaux intérêts, préférences et pensées et doivent être pris en considération plus que les anciens intérêts surtout que de nombreux travaux antérieurs ont prouvé que l'intérêt de l'utilisateur diminue avec le temps. Nous avons modélisé le profil utilisateur sensible au temps en fonction d'un ensemble de données collectées de Twitter (un réseau social et un service de microblogging) et nous l'avons intégré dans le processus de reclassement afin de personnaliser les résultats standards en fonction des intérêts de l'utilisateur.En second lieu, nous avons étudié la dynamique temporelle dans le cadre de la session de recherche où les requêtes récentes soumises par l'utilisateur contiennent des informations supplémentaires permettant de mieux expliquer l'intention de l'utilisateur et prouvant qu'il n'a pas trouvé les informations recherchées à partir des requêtes précédentes.Ainsi, nous avons considéré les interactions récentes et récurrentes au sein d'une session de recherche en donnant plus d'importance aux termes apparus dans les requêtes récentes et leurs résultats cliqués. Nos expérimentations sont basés sur la tâche Session TREC 2013 et la collection ClueWeb12 qui ont montré l'efficacité de notre approche par rapport à celles de l'état de l'art. Au terme de ces différentes contributions et expérimentations, nous prouvons que notre modèle générique de profil utilisateur sensible au temps assure une meilleure performance de personnalisation et aide à analyser le comportement des utilisateurs dans les contextes de session de recherche et de médias sociaux.Recently, search engines have become the main source of information for many users and have been widely used in different fields. However, Information Retrieval Systems (IRS) face new challenges due to the growth and diversity of available data. An IRS analyses the query submitted by the user and explores collections of data with unstructured or semi-structured nature (e.g. text, image, video, Web page etc.) in order to deliver items that best match his/her intent and interests. In order to achieve this goal, we have moved from considering the query-document matching to consider the user context. In fact, the user profile has been considered, in the literature, as the most important contextual element which can improve the accuracy of the search. It is integrated in the process of information retrieval in order to improve the user experience while searching for specific information. As time factor has gained increasing importance in recent years, the temporal dynamics are introduced to study the user profile evolution that consists mainly in capturing the changes of the user behavior, interests and preferences, and updating the profile accordingly. Prior work used to discern short-term and long-term profiles. The first profile type is limited to interests related to the user's current activities while the second one represents user's persisting interests extracted from his prior activities excluding the current ones. However, for users who are not very active, the short-term profile can eliminate relevant results which are more related to their personal interests. This is because their activities are few and separated over time. For users who are very active, the aggregation of recent activities without ignoring the old interests would be very interesting because this kind of profile is usually changing over time. Unlike those approaches, we propose, in this thesis, a generic time-sensitive user profile that is implicitly constructed as a vector of weighted terms in order to find a trade-off by unifying both current and recurrent interests. User profile information can be extracted from multiple sources. Among the most promising ones, we propose to use, on the one hand, searching history. Data from searching history can be extracted implicitly without any effort from the user and includes issued queries, their corresponding results, reformulated queries and click-through data that has relevance feedback potential. On the other hand, the popularity of Social Media makes it as an invaluable source of data used by users to express, share and mark as favorite the content that interests them. First, we modeled a user profile not only according to the content of his activities but also to their freshness under the assumption that terms used recently in the user's activities contain new interests, preferences and thoughts and should be considered more than old interests. In fact, many prior works have proved that the user interest is decreasing as time goes by. In order to evaluate the time-sensitive user profile, we used a set of data collected from Twitter, i.e a social networking and microblogging service. Then, we apply our re-ranking process to a Web search system in order to adapt the user's online interests to the original retrieved results. Second, we studied the temporal dynamics within session search where recent submitted queries contain additional information explaining better the user intent and prove that the user hasn't found the information sought from previous submitted ones. We integrated current and recurrent interactions within a unique session model giving more importance to terms appeared in recently submitted queries and clicked results. We conducted experiments using the 2013 TREC Session track and the ClueWeb12 collection that showed the effectiveness of our approach compared to state-of-the-art ones. Overall, in those different contributions and experiments, we prove that our time-sensitive user profile insures better performance of personalization and helps to analyze user behavior in both session search and social media contexts

Advances on Smart Cities and Smart Buildings

Modern cities are facing the challenge of combining competitiveness at the global city scale and sustainable urban development to become smart cities. A smart city is a high-tech, intensive and advanced city that connects people, information, and city elements using new technologies in order to create a sustainable, greener city; competitive and innovative commerce; and an increased quality of life. This Special Issue collects the recent advancements in smart cities and covers different topics and aspects

Institutionalisation of digitally-enabled service transformation in the UK public sector

This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonThe successful institutionalisation of digitally-enabled service transformation (DEST) in the UK public sector has always been a challenge for the government. Associated with technology and managerial impediments, the derailment of several DEST projects in recent years has attracted much scholarly debate. Nonetheless, overt emphasis on the antecedents and effects of DEST institutionalisation has concealed the real events underpinning the transformation process, especially the ‘social’ interactions between the institutional actors and structures, as well as their role in the DEST institutionalisation process. Hence, this research aims to explore the roles of the actors and structures in DEST institutionalisation as working practice in public institutions. To do so, this research develops a conceptual framework grounded on Institutional Theory and Structuration Theory concepts, derived from the analysis of four past DEST cases in the UK. The framework is used in a qualitative enquiry that explores the well-publicised Universal Credit transformation case through interviews, focus groups and review of documentary and parliamentary-select-committee-media evidence. The findings offer insights into the deinstitutionalisation and structuration processes in the study of DEST institutionalisation to better understand the implementation of change in public institutions. This study concludes that actors and structures play important roles in structuring the DEST institutionalisation process as working practice in public institutions. Actors could manipulate structures of meaning, power and norms to promote desired actions in shaping practices that support DEST institutionalisation