"Enabling Multichannel Participation through ICT Adaptations for Participatory Budgeting ICT-enabled platform” (EMPATIA) is a multi-channel participatory budgeting (PB) platform that represents a significant social innovation process of democratic deliberation and decision-making, involving citizens within complex public-institution structures. EMPATIA was targeted to deliver socio-economic and political benefits, such as enhancing citizen-government engagement, increasing public value through PB process, promoting ‘inclusiveness’ among the marginalized groups of citizens, and impeding political discontent that underpins distrust and skepticism towards the government. The attainment of these benefits will be driven by the EMPATIA's performance. Hence, a performance measurement tools is needed to enable assessment of EMPATIA, empirically. With an aim to propose an integrated performance evaluation metrics, this study presents a set of assessment criteria for multi-channel digitally enabled PB service platforms – especially EMPATIA. Findings from a qualitative, multi-strategies research approach suggest that the metrics should include five key technical and non-technical performance indicators, to be used as basis for the development of future evaluation instruments. Of major signposts, the metrics would inform key performance aspects to be considered during the PB platform development, and evaluated to indicate the PB platform performance.

Government organisations have been shifting to cloud-based services in order to reduce their total investments in IT infrastructures and resources (e.g. data centers), as well as capitalise on cloud computing’s numerous rewards. However, just like any other technology investments there are also concerns over the potential risks of implementing cloud-based technologies. Such concerns and the paucity of scholarly literature focusing on cloud computing from a governmental context confirm the need for exploratory research and to draw lessons for government authorities and others in order to ensure a reduction in costly mistakes. This paper therefore investigates the implementation of cloud computing in both a practical setting and from an organisational user perspective via three UK local government authorities. Through the qualitative case study enquiries, the authors are able to extrapolate perceived rewards and risks factors which are mapped against the literature so that emergent factors can be identified. All three cloud deployments resulted in varying outcomes which included key rewards such as improved information management, flexibility of work practices and also posed risks such as loss of control and lack of data ownership to the organisations. These findings derived from the aggregated organisational user perspectives will be of benefit to both academics and practitioners engaged in cloud computing research and its strategic implementation in the public sector.

Government legislation and calls for greater levels of oversight and transparency are leading public bodies to publish their raw datasets online. Policy makers and elected officials anticipate that the accessibility of open data through online Government portals for citizens will enable public engagement in policy making through increased levels of fact based content elicited from open data. The usability and benefits of such open data are being argued as contributing positively towards public sector reforms, which are under extreme pressures driven by extended periods of austerity. However, there is very limited scholarly studies that have attempted to empirically evaluate the performance of government open data websites and the acceptance and use of these data from a citizen perspective. Given this research void, an adjusted diffusion of innovation model based on Rogers’ diffusion of innovations theory (DOI) is proposed and used in this paper to empirically determine the predictors influencing the use of public sector open data. A good understanding of these predictors affecting the acceptance and use of open data will likely assist policy makers and public administrations in determining the policy instruments that can increase the acceptance and use of open data through an active promotion campaign to engage-contribute-use.

Big Data (BD), with their potential to ascertain valued insights for enhanced decision-making process, have recently attracted substantial interest from both academics and practitioners. Big Data Analytics (BDA) is increasingly becoming a trending practice that many organizations are adopting with the purpose of constructing valuable information from BD. The analytics process, including the deployment and use of BDA tools, is seen by organizations as a tool to improve operational efficiency though it has strategic potential, drive new revenue streams and gain competitive advantages over business rivals. However, there are different types of analytic applications to consider. Therefore, prior to hasty use and buying costly BD tools, there is a need for organizations to first understand the BDA landscape.Given the significant nature of the BDand BDA, this paper presents a state-ofthe- art review that presents a holistic view of the BD challenges and BDA methods theorized/proposed/ employed by organizations to help others understand this landscape with the objective of making robust investment decisions. In doing so, systematically analysing and synthesizing the extant research published on BD and BDA area. More specifically, the authors seek to answer the following two principal questions: Q1 –What are the different types of BD challenges theorized/proposed/confronted by organizations? and Q2 – What are the different types of BDA methods theorized/proposed/employed to overcome BD challenges?. This systematic literature review (SLR) is carried out through observing and understanding the past trends and extant patterns/themes in the BDA research area, evaluating contributions, summarizing knowledge, thereby identifying limitations, implications and potential further research avenues to support the academic community in exploring research themes/patterns. Thus, to trace the implementation of BD strategies, a profiling method is employed to analyze articles (published in English-speaking peer-reviewed journals between 1996 and 2015) extracted from the Scopus database. The analysis presented in this paper has identified relevant BD research studies that have contributed both conceptually and empirically to the expansion and accrual of intellectual wealth to the BDA in technology and organizational resource management discipline.

The race against ‘Digital Darwinism’ in public sector had caused failures of several high profile large-scale Digitally Enabled Service Transformation (DEST) projects. While technical and managerial issues are often emphasised as the factors underpinning such failures, the vital role of key actors and the interplay between these actors and structures is underplayed when examining the causes of DEST failure. To enable a richer understanding of DEST, this paper proposes an analytical lens combining Institutional Theory (IT) and Structuration Theory (ST) to explore the case of ‘Universal Credit’, a very large and ambitious DEST project in the UK. Analysis reveals that the institutional actors and structures played significant roles in the transformation process. Albeit governing the actors’ actions, institutional structures are shaped through actions that are influenced by knowledge, power and norms. Hence, recognising and addressing these subliminal factors are critical to promote actions that can facilitate DEST success. The contributions of this case study are two-folds. Theoretically, it provides a distinctive conceptual approach to study DEST; and practically, the lessons help in signposting better managerial practices.