Exploring open IT-based co-creation in government : a revelatory case study

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Factors Influencing the Adoption of Open Government Data in The Public Sector: A Systematic Literature Review

Open Government Data (OGD) adoption has been extensively studied; however, few have examined the success factors of OGD adoption in the public sector context. The benefits of leveraging data in enhancing public service delivery have been a significant concern to the top management of the public sector in providing them insight for strategic planning together with timely decision making. The aim of this paper is to review recent literature from the year 2010 to 2018 on OGD adoption at the organizational level in the public sector context. We systematically searched all English papers that were indexed in seven electronic journal databases (Scopus, Emerald, Web of Science, Science Direct, ACM, Springer and IEEE) which include journals, proceedings, books and book chapters. Few papers were acquired from snowballing techniques and ResearchGate webpage. A total of 886 publications were identified in this process and 25 papers have finally been selected which are deemed as relevant papers for the analysis stage. As derived from 25 selected papers, this study has identified 16 factors that influence the OGD adoption which has been categorized into three main dimensions: Technological, Organizational and Environmental (T-O-E). Policy, technological competence, top management support and organization culture are among the most influential factors of OGD adoption. Therefore, this study is expected to assist other researchers to understand the current stage of OGD adoption in terms of influential factors, research domains and research methodology

Barriers to Data Sharing among Private Sector Organizations

In today’s digital world, sharing data among private sector organizations to realm mutual benefits, such as innovation and value co-creation, is considered a promising yet barely explored and realized approach. Although private sector organizations are pursuing data sharing, successful real-world examples are sparse due to a multitude of barriers. However, knowledge on barriers to data sharing among private sector organizations is scarcely existent in scientific literature. Therefore, we apply an exploratory research approach by triangulating insights from fourteen expert interviews and a systematic literature review to identify barriers which we group along five distinct perspectives. By exploring the multi-faceted barriers to data sharing among private sector organizations, our work contributes to a better understanding of data sharing in this field and lays the foundation for future studies. For practitioners, we identify key challenges to successful data sharing among private sector organizations and, hence call for additional endeavors in data sharing

Factors influencing the adoption of open government data in the public sector: a systematic literature review

Open Government Data (OGD) adoption has been extensively studied; however, few have examined the success factors of OGD adoption in the public sector context. The benefits of leveraging data in enhancing public service delivery have been a significant concern to the top management of the public sector in providing them insight for strategic planning together with timely decision making. The aim of this paper is to review recent literature from the year 2010 to 2018 on OGD adoption at the organizational level in the public sector context. We systematically searched all English papers that were indexed in seven electronic journal databases (Scopus, Emerald, Web of Science, Science Direct, ACM, Springer and IEEE) which include journals, proceedings, books and book chapters. Few papers were acquired from snowballing techniques and ResearchGate webpage. A total of 886 publications were identified in this process and 25 papers have finally been selected which are deemed as relevant papers for the analysis stage. As derived from 25 selected papers, this study has identified 16 factors that influence the OGD adoption which has been categorized into three main dimensions: Technological, Organizational and Environmental (T-O-E). Policy, technological competence, top management support and organization culture are among the most influential factors of OGD adoption. Therefore, this study is expected to assist other researchers to understand the current stage of OGD adoption in terms of influential factors, research domains and research methodology

Open data for open innovation:managing absorptive capacity in SMEs

Open Data (OD) utilisation has been encouraged by governments because of its potential to fuel digital innovation. Despite this, there is a paucity of study into the role of OD for SMEs, in contrast to the growing literature that has focused on the collection and sharing of OD by the public sector. As such, our study contributes to open innovation research by analysing the main capabilities needed to overcome existing barriers to successfully manage OD in SMEs. Building upon the recent SME-oriented OI literature and adopting an interpretative absorptive capacity framework, we analyse the data collected from 30 semi-structured interviews with experts working in UK organisations adopting OD-based OI strategies. We find a number of core factors that shape OD acquisition, assimilation, transformation and exploitation by SMEs. Results show that without the specific OD capabilities identified in our study, it will be difficult for SMEs to successfully use OD, which may explain why the uptake of OD by SMEs more broadly has so far been limited. These unique OD capabilities need to be better developed by OD using SMEs, if this \u2018raw material\u2019 for the digital economy is to be fully exploited

VALUE IN THE MASH: EXPLORING THE BENEFITS, BARRIERS AND ENABLERS OF OPEN DATA APPS

The open government paradigm relies on the provision and reuse of open government data (OGD) to improve transparency and create new sources of valu. This study aims to progress understanding of OGD beyond a theoretical commentary by exploring the perceived sources of valu of mashups (online services that combine diverse OGD), and to examine issus that impact on, and facilitate, the delivery of this valu from an ˜insider´ perspective. Based on open-ended interviews with 17 individuals actively involved in OGD application design, use, and advocacy in New Zealand (ranked fourth in the 2013 Global Open Data Barometer) nine key sources of valu were identified: Ease of discovery, improved data quality, bringing knowledge into relevant contexts, economic benefits, social benefits, cost reduction and efficiencies, predictive valu, transparency, and ability to explore and play. Twelve barriers to delivering this valu were found, ranging from change-related issus to problems relating to sustainability. Six facilitators were identified as helping to overcome these barriers and realise the valu of OGD

Acceptance and use predictors of open data technologies: Drawing upon the unified theory of acceptance and use of technology

AbstractPolicy-makers expect that open data will be accepted and used more and more, resulting in a range of benefits including transparency, participation and innovation. The ability to use open data partly depends on the availability of open data technologies. However, the actual use of open data technologies has shown mixed results, and there is a paucity of research on the predictors affecting the acceptance and use of open data technologies. A better understanding of these predictors can help policy-makers to determine which policy instruments they can use to increase the acceptance and use of open data technologies. A modified model based on the Unified Theory of Acceptance and Use of Technology (UTAUT) is used to empirically determine predictors influencing the acceptance and use of open data technologies. The results show that the predictors performance expectancy, effort expectancy, social influence, facilitating conditions and voluntariness of use together account for 45% of the variability in people's behavioral intention to use open data technologies. Except for facilitating conditions, all these predictors significantly influence behavioral intention. Our analysis of the predictors that influence the acceptance and use of open data technologies can be used to stimulate the use of open data technologies. The findings suggest that policy-makers should increase the acceptance and use of open data technologies by showing the benefits of open data use, by creating awareness of users that they already use open data, by developing social strategies to encourage people to stimulate each other to use open data, by integrating open data use in daily activities, and by decreasing the effort necessary to use open data technologies

Opening Moves – Drivers, Enablers and Barriers of Open Data in a Semi-public Organization

Governments around the world are opening up their data to increase transparency and stimulate re-use of their data. Semi-public organizations follow, but often for different purposes as they also aim to realize commercial gains with their data. Many organizations, however, find the process of opening up data cumbersome as changes need to be made to different organizational layers. This paper identifies drivers, enablers, and barriers of open data, by reviewing literature and by conducting a case study of open data in a semipublic organization in the Netherlands. We found that while the drivers for opening up data remain the same in every phase of the process, the enablers and barriers shift between the different phases. While in the beginning of the process, organizational factors such as having an implementation strategy and ensuring data quality gained much attention, this attention shifted to factors related to re-use of data. Further research should thus focus on how to develop valuable open data business models, how to foster re-use and build strategic partnerships with user

Factors influencing user acceptance of public sector big open data

In recent years Government departments and public/private organizations are becoming increasingly transparent with their data to establish the whole new paradigm of big open data. Increasing research interest arises from the claimed usability of big open data in improving public sector reforms, facilitating innovation, improving supplier and distribution networks and creating resilient supply chains that help improve the efficiency of public services. Despite the advantages of big open data for supply chain and operations management, there is severe shortage of empirical analyses in this field, especially with regards to its acceptance. To address this gap, in this paper we use an extended Technology Acceptance Model (TAM) to empirically examine the factors affecting users’ behavioural intentions towards public sector big open data. We outline the importance of our model for operations and supply chain managers, the limitations of the study, and future research directions

Climate change and impacts in the urban systems

A thesis submitted in partial fulfillment of the requirements for the degree of Doctor in Information Management, specialization in Geographic Information SystemsUrban systems are not only major drivers of climate change, but also impact hotspots. The processes of global warming and urban population growth make our urban agglomerations vulnerable to chain reactions triggered by climate related hazards. Hence, the reliable and cost-effective assessment of future climate impact is of high importance. Two major approaches emerge from the literature: i) detailed spatially explicit assessments, and ii) more holistic approaches consistently assessing multiple cities. In this multidisciplinary thesis both approaches were addressed. Firstly, we discuss the underlying reasons and main challenges of the applicability of downscaling procedures of climate projections in the process of urban planning. While the climate community has invested significant effort to provide downscaling techniques yielding localised information on future climate extreme events, these methods are not widely exploited in the process of urban planning. The first part of this research attempts to help bridge the gap between the communities of urban planners and climatologists. First, we summarize the rationale for such cooperation, supporting the argument that the spatial scale represents an important linkage between urban and climate science in the process of designing an urban space. Secondly, we introduce the main families of downscaling techniques and their application on climate projections, also providing the references to profound studies in the field. Thirdly, special attention is given to previous works focused on the utilization of downscaled ensembles of climate simulations in urban agglomerations. Finally, we identify three major challenges of the wider utilization of climate projections and downscaling techniques, namely: (i) the scale mismatch between data needs and data availability, (ii) the terminology, and (iii) the IT bottleneck. The practical implications of these issues are discussed in the context of urban studies. The second part of this work is devoted to the assessment of impacts of extreme temperatures across the European capital cities. In warming Europe, we are witnessing a growth in urban population with aging trend, which will make the society more vulnerable to extreme heat waves. In the period 1950-2015 the occurrence of extreme heat waves increased across European capitals. As an example, Moscow was hit by the strongest heat wave of the present era, killing more than ten thousand people. Here we focus on larger metropolitan areas of European capitals. By using an ensemble of eight EURO-CORDEX models under the RCP8.5 scenario, we calculate a suite of temperature based climate indices. We introduce a ranking procedure based on ensemble predictions using the mean of metropolitan grid cells for each capital, and socio-economic variables as a proxy to quantify the future impact. Results show that all the investigated European metropolitan areas will be more vulnerable to extreme heat in the coming decades. Based on the impact ranking, the results reveal that in near, but mainly in distant future, the extreme heat events in European capitals will be not exclusive to traditionally exposed areas such as the Mediterranean and the Iberian Peninsula. Cold waves will represent some threat in mid of the century, but they are projected to completely vanish by the end of this century. The ranking of European capitals based on their vulnerability to the extreme heat could be of paramount importance to the decision makers in order to mitigate the heat related mortality. Such a simplistic but descriptive multi-risk urban indicator has two major uses. Firstly, it communicates the risk associated with climate change locally and in a simple way. By allowing to illustratively relate to situations of other capitals, it may help to engage not only scientists, but also the decision makers and general public, in efforts to combat climate change. Secondly, such an indicator can serve as a basis to decision making on European level, assisting with prioritizing the investments and other efforts in the adaptation strategy. Finally, this study transparently communicates the magnitude of future heat, and as such contributes to raise awareness about heat waves, since they are still often not perceived as a serious risk. Another contribution of this work to communication of consequences of changing climate is represented by the MetroHeat web tool, which provides an open data climate service for visualising and interacting with extreme temperature indices and heat wave indicators for European capitals. The target audience comprises climate impact researchers, intermediate organisations, societal-end users, and the general public