Open Government Data (OGD) has been considered as a potent instrument for value creation and innovation by a range of stakeholders. Given that individual ingenuity is a function of individual and environmental factors, it is important to understand how the OGD adoption and usage is a factor of creative performance behaviors (CPB), viz., Problem Identification (PI), Information Search (IS), Idea Generation (IG) and Idea Promotion (IP) as well as creative self-efficacy (CSE). Invoking the adapted Unified Theory of Acceptance and Use of Technology (UTAUT) constructs alongside the moderating effects of CPB and CSE constructs and also gender, the present study seeks to underline the behavioural intention towards OGD adoption and usage among 362 undergraduate and postgraduate university students in India. The guiding research question is: “Is there any difference among the males and females in terms of their OGD adoption and usage as far as their creative propensities are concerned?” Findings from the PLS-SEM (Partial Least Squares-Structural Equation Modeling) procedures show that there are gender differences across the CPB and CSE constructs. The study's contribution lies in furthering our understanding of OGD adoption and use with the additional determinants of creativity literature.

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This study aims to analyze the impacts of Artificial Intelligence (AI) and automation in the supermarket sector, focusing on three main areas: tasks, jobs, and automation processes. The research builds on studies about technology adoption and its impact on employment, including Christensen approach on disruptive innovation, Huang & Rust [19] on artificial intelligence in services, and Jarrahi [27] on human-AI symbiosis. A multiple case study approach was employed, involving interviews with four groups: cashiers, managers, customers who use self-checkouts, and customers who do not use self-checkouts. The interviews were analyzed using qualitative methods to identify emerging subcategories. Many customers prefer manned checkouts due to convenience. Self-service checkout technology is primarily used for small purchases, and younger customers find it easier to use. Employees do not currently feel threatened by automation, but there is a trend toward job reduction and relocation to roles requiring analytical, intuitive, and emotional skills. Managers do not see the need to prepare employees for a future without self-service checkouts, focusing instead on current training. Future research should analyze other supermarket functions that could be impacted by AI automation and investigate more deeply the acceptance and impact of these technologies on the labor market.

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While previous research on Open Government Data (OGD) has primarily focused on reuse and adoption, this study aims to explore the implications of the Public Service Logic (PSL) and Public Service Motivation (PSM) dimensions in the context of OGD initiatives. This study is contextualized in Tanzania wherein the OGD initiatives are at an evolving stage. For the present study, the perspectives of the 15 public officials involved in the management of the OGD initiatives are being solicited. Findings underscore the need for furthering the marketing and refurbishing the OGD initiatives' quality alongside the increased involvement of the stakeholders to engage in value co-creation. Furthermore, as a study contextualized in a developing country to understand the involvement of the public personnel in the refurbishment of the OGD initiatives, the study contributes to the extant OGD literature while identifying the OGD publisher-side challenges and strengths in a still-evolving OGD initiative. Finally, with its societal implications in terms of the impact on societal stakeholders' engagement with OGD given the PSL-PSM of the public officials, the study's relevance is also clinched.

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Purpose: The purpose of the study is to understand the moderating impact of perceived technological innovativeness (PTI) in terms of gender differences as far as adoption and usage of Open Government Data (OGD) is concerned. Design/methodology/approach: Partial least squares-structural equation modelling (PLS-SEM) methodological approach is used wherein the adapted unified theory of acceptance and use of technology (UTAUT) model is being used for estimating the research model. Findings: PTI has been attested to have moderating impact on the UTAUT-BI relationships in select cases (SI, SQ, IQ, TR-BI). Furthermore, gender differences were observed as far as far as the PTI's moderating role on UTAUT-BI relationships were concerned. Originality/value: While there has been ample impetus upon the OGD adoption and usage propensities underscoring the role of different variables, the present study's contribution lies in terms of understanding the moderating role of PTI as far as individual-centric analysis is concerned.

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The academic interest in the Open Government Data (OGD) domain has been burgeoning over the years. Conceding that the prime focus of an OGD initiative is its further re-use for value creation and innovation by stakeholders, the present study seeks to underscore the role of HEXACO personality traits on behavioral intention (BI) to adopt and use OGD in developing countries' context. We investigate the direct, indirect, and moderating effects of HEXACO personality traits provide a better understanding of how and to what extent personality traits influence future behavioral intention to use OGD. The results demonstrate that Trust and Performance Expectancy are positive predictors of BI to adopt and use OGD. Users with higher Openness to Experience tend to have higher Effort and Performance Expectancy; are characterized by exposure to Social Influence; have higher level of Trust and positive experience of Facilitating Conditions and Information Quality. Agreeable people are more likely to Voluntarily Use OGD. Conscientiousness enhances the individual's perception of OGD quality-related factors. Excessive Emotionality affects negative perception to System and Information Quality issues. Honesty–Humility and Extraversion are able to maintain the effect of OGD Information Quality and Trust on users' BI. Our findings could be useful for practitioners to level the divergence between actual and potential use of OGD by considering the user's personality traits.

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Open Government efforts are criticized for providing limited value. Instead of looking at a value, we investigate the usefulness of web-based open government portals and apps. Specifically, we investigated the relationship between digital transparency and usefulness. We analyzed perceived digital transparency and usefulness in a survey of 112 respondents using Partial Least Square (PLS) and Structural Equation Modelling (SEM). The results show that perceived functionality, transparency, and efficiency influence usefulness but that functionality of apps and efficiency are more important than transparency. Usefulness can be created without having high levels of transparency, as the public wants answers to their questions. Apps should be designed for efficient use, as users have limited time and resources. Apps having pre-defined functional views can be useful to provide quick insight but might limit transparency by not offering other views and insights. Opening raw data using portals can provide higher levels of transparency, although more time and effort are needed to analyze. Both portals providing access to raw data and apps having pre-defined views are needed for open government and transparency as they serve other stakeholder groups and purposes.@en

Purpose: The purpose of this paper is to highlight the drivers, barriers, benefits and risks affecting the integration of Internet of Things (IoT) into the e-government and to provide a future research agenda. Design/methodology/approach: Existing literature examining the relationships between e-government and IoT is scanned and evaluated by conceptualizing the IoT concept in the e-government perspective. Findings: The study shows that there are drivers to integrate IoT in e-government, such as ensuring the economy, efficiency and effectiveness of government operations, which would largely establish a relationship between the government and the citizens. Furthermore, there are barriers to such integration, given the lack of political will, the appropriate information technology infrastructure, the training of the stakeholders with a focus on the employee and the like. Originality/value: The integration of IoT in e-government is a novel and weakly explored concept, particularly in the light of new advances such as blockchain in the e-government, which requires further exploration and conceptualization, thereby achieving a shared/common vision and body of knowledge for its further successful and sustainable adoption – to the best of the authors’ knowledge, the current study is one of these initial attempts.@en

Open government data (OGD) include the provision of government data, which have so far been reserved for the provision of public utilities and services, wherein different stakeholders may create value out of the same source. Recently, OGD initiatives around the world have dampened or were found to be inadequate for one or other reasons. The present study seeks to underline the root causes behind these inadequate or stalled initiatives with a specific focus on the developing countries. This article undertakes a literature review of the most significant studies in this area, followed by a root cause analysis wherein the database across Scopus and Web of Science has been explored with the set inclusion and exclusion criteria being set in line with the research focusing on the hinderances and bottlenecks behind the failure of OGD initiatives (n ~ 15), thus not only summarizing what has been revealed in previous studies but also identifying these “root-cause” relationships, which are responsible for the stalled OGD projects. A deep understanding of the literature on OGD shows that research of OGD barriers repeat each other. The results show that the main root causes include politico-administrative, social, technological, legal and organizational (inter- and intra) dimensions including aspects like state of the economy, infrastructural issues, the tendency to copy the OGD initiative without need to institutionalize the same, and so forth. Whereas a number of studies are available covering the barriers in the roll-out and implementation of OGD initiatives, the root causes behind the existence of these barriers have not been identified so far-the present study seeks to plug this gap. Besides being a contribution to the extant OGD literature in general, the study seeks to leave academic and practical implications for furthering up deliberations and discussions on the OGD themes with specific impetus upon the cause analysis of the failure in OGD initiatives and the manner in which the same may be corrected or preempted.@en

Open Government Data (OGD) research has focused for a long on the adoption and usage from the perspectives of users across different contexts. The underlying rationale for this specific focus is that OGD initiatives are undertaken to further citizen engagement with OGD for value generation and innovation purposes. Conceding that usage propensity is different across individuals, it is important to understand the influence of personality traits vis-à-vis OGD adoption and usage. Given that OGD has been regarded as a sophisticated "technology"and the role of personality traits has been considered as important in the adoption and usage of "technologies"in general, therefore, the present study contributes to the extant OGD-focused literature from a novel dimension. The study invokes the adapted model of the Unified Theory of Technology Adoption and Use (UTAUT) alongside the HEXACO-100 inventory constructs for studying the relationships between the constructs with a sample of 530 respondents. The results demonstrate that higher user Openness to Experience contributes to their higher Effort and Performance Expectancy; exposure to Social Influence; an increased level of Trust; and a more positive perception of Facilitating Conditions and Information Quality. Agreeable people are more likely to voluntarily use OGD. An individual's conscientiousness improves their perception of factors related to OGD quality. Excessive emotionality leads to a more critical perception of systems and information quality issues. Our findings also attest to the moderating impact of Honesty-Humility across Information Quality-Behavioral Intention positively; Extraversion across Information Quality-Behavioral Intention negatively and Extraversion across Trust-Behavioral Intention positively. Honesty turns out to be important for considering Information Quality vis-à-vis OGD adoption and usage but whilst extroverts are concerned about Information Quality, i.e. flawless information retrieval via OGD sources, Introverts are concerned about OGD trustworthiness, i.e. credible OGD for its adoption and usage and Extroverts find the OGD reliable and credible. With pointers for further research across the personality traits-OGD adoption and usage theme, the study closes with practitioner implications.@en

Whilst extant literature on Open Government Data (OGD) focuses upon value creation and innovation, there is scant emphasis upon the Value Co-Creation (VCC) that might result with the engagement of the public sector agencies and the users at large. The present study seeks to appreciate the barriers towards OGD VCC by adopting a qualitative research methodology wherein interviews are being conducted with key personnel manning the OGD initiatives in Brazil. Impediments veering around VCC may be counted the internal, social and cultural and data factors. Findings from the present study lend credence to the fact that a systematic strategizing is important for the success of OGD VCC lest Value Co-Destruction (VCD) happen. From a developing country's perspective, the present study acts as a sounding-board for bearing in mind the caveats deduced vis-a-via the success of the VCC processes.@en

While assessing the potential of a particular digital innovation initiative, especially when it has implications for a range of societal stakeholders, it becomes pertinent to understand the possible bottlenecks in its acceptability as well. In this regard, the present study seeks to understand how the Open Government Data (OGD) initiatives in Brazil are being confronted with bottlenecks in terms of their execution and acceptability. This exploratory study adopts a qualitative cross-sectional research approach wherein interviews are being conducted with 11 managers working in public organizations and are directly associated with the OGD initiatives. Findings from the interview responses delineate internal and external factors, resource availability, data maintenance, and lack of knowledge as the key determinants for the bottlenecks associated with the execution and acceptability of OGD initiatives by the societal stakeholders. The study's originality lies in its theoretical contribution towards an understanding of how a novel digital innovation-OGD, in the present case- is fraught with impediments in terms of its execution and acceptability. The study concludes with directions for further research and practitioner implications.@en

Under pressure to fight corruption, hold public officials accountable, and build trust with citizens, many governments pursue the quest for greater transparency. They publish data about their internal operations, externalize decision-making processes, establish digital inquiry lines to public officials, and employ other forms of transparency using digital means. Despite the presence of many transparency-enhancing digital tools, putting such tools together to achieve the desired level of digital transparency, to design entire government systems for digital transparency, remains challenging. Design principles and other design guides are lacking in this area. This article aims to fill this gap. We identify a set of barriers to digital transparency in government, define 16 design principles to overcome such barriers, and evaluate these principles using three case studies from different countries. Some principles apply to projects, others to systems, yet others to entire organizations. To achieve digital transparency, before building and deploying digital solutions, government organizations should build technological and institutional foundations and use such foundations to organize themselves for transparency. The proposed design principles can help develop and apply such foundations.

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There are large varieties of governmental organizations using clouds in different ways. The purpose of this article is to explore and classify the types of public organizations using cloud computing. This will help to improve our understanding of cloud adoption and use by governments. For this, a systematic review of literature on cloud government (CloudGov) was performed by searching for articles in several databases. The review resulted into the main elements of the framework for classifying cloud use. In addition, using diffusion of innovation and institutional theory a categorization of public organizations was made. When applying the CloudGov framework empirically in government organizations, we identified three types of organizations: Leaders, Followers and Laggers. The types differ in various ways including their technology expertise, attitude towards innovation and level of political support. In further research, we recommend investigating which drivers influence the type of CloudGov users and generalize the framework to other contexts.

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Computational artificial intelligence (AI) algorithms are increasingly used to support decision making by governments. Yet algorithms often remain opaque to the decision makers and devoid of clear explanations for the decisions made. In this study, we used an experimental approach to compare decision making in three situations: humans making decisions (1) without any support of algorithms, (2) supported by business rules (BR), and (3) supported by machine learning (ML). Participants were asked to make the correct decisions given various scenarios, while BR and ML algorithms could provide correct or incorrect suggestions to the decision maker. This enabled us to evaluate whether the participants were able to understand the limitations of BR and ML. The experiment shows that algorithms help decision makers to make more correct decisions. The findings suggest that explainable AI combined with experience helps them detect incorrect suggestions made by algorithms. However, even experienced persons were not able to identify all mistakes. Ensuring the ability to understand and traceback decisions are not sufficient for avoiding making incorrect decisions. The findings imply that algorithms should be adopted with care and that selecting the appropriate algorithms for supporting decisions and training of decision makers are key factors in increasing accountability and transparency.

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The opening of data has been credited for improving transparency and for providing a window on government functioning. Although this relationship is intuitively apparent, it is in fact complex and the mere opening of data might not actually yield transparency. In this paper, a comprehensive model of determinants that enable or impede transparency enabled by open government data and the expected effects have been derived by surveying public administration and information systems literature. Public administration literature tends to be focused on factors such as participation and trust, whereas information systems literature focuses on factors such as user interface, user experience, and data quality. Digital government literature attempts to bridge these elements. The Window Theory is introduced, in order to unify existing models by integrating a broad range of factors within a single model. The Window Theory can be used to develop context-dependent models that are both comprehensive and parsimonious.

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The number of Open Statistical Data available for reuse is rapidly increasing. Linked open data technology enables easy reuse and linking of data residing in different locations in a simple and straightforward manner. Yet, many people are not familiar with the technology standards and tools for making use of open statistical data. In this tutorial, we will introduce Linked Open Statistical Data (LOSD) and demonstrate the use of LOSD technologies and tools to visualize open data obtained from various European Countries. We will also give the participants the opportunity to use these tools thus obtaining a personal experience on their capabilities.

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Dashboards visualize a consolidated set data for a certain purpose which enables users to see what is happening and to initiate actions. Dashboards can be used by governments to support their decision-making and policy processes or to communicate and interact with the public. The objective of this paper is to understand and to support the design of dashboards for creating transparency and accountability. Two smart city cases are investigated showing that dashboards can improve transparency and accountability, however, realizing these benefits was cumbersome and encountered various risks and challenges. Challenges include insufficient data quality, lack of understanding of data, poor analysis, wrong interpretation, confusion about the outcomes, and imposing a pre-defined view. These challenges can easily result in misconceptions, wrong decision-making, creating a blurred picture resulting in less transparency and accountability, and ultimately in even less trust in the government. Principles guiding the design of dashboards are presented. Dashboards need to be complemented by mechanisms supporting citizens' engagement, data interpretation, governance and institutional arrangements.

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Organizations are looking for ways to gain advantage of big and open linked data (BOLD) by employing statistics, however, how these benefits can be created is often unclear. A reference architecture (RA) can capitalize experiences and facilitate the gaining of the benefits, but might encounter challenges when trying to gain the benefits of BOLD. The objective of the research to evaluate the benefits and challenges of building IT systems using a RA. We do this by investigating cases of the utilization of a RA for Linked Open Statistical Data (LOSD). Benefits of using the reference architecture include reducing project complexity, avoiding having to “reinvent the wheel”, easing the analysis of a (complex) system, preserving knowledge (e.g. proven concepts and practices), mitigating multiple risks by reusing proven building blocks, and providing users a common understanding. Challenges encountered include the need for communication and learning the ins and outs of the RA, missing features, inflexibility to add new instances as well as integrating the RA with existing implementations, and the need for support for the RA from other stakeholders.

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Demographic, economic, social and other datasets are often used in policy-making processes. These types of statistical data are opened more and more by governments, which enables the use of these datasets by the public. However, statistical data needs often to combine different datasets. Data cubes can be used to combine datasets and are a multi-dimensional array of values typically used to describe time series of geographical areas. While Linked Open Statistical Data (LOSD) cube software is still in an initial stage of maturity, there is a need for evaluation the software platforms used to process this open data. Yet there is a lack of evaluation methods. The objective of this ongoing research paper is to identify functional requirements for open data cubes infrastructures. Eight main processes are identified and a list of 23 functional requirements are used to evaluate the OpenCube platform. The evaluation results of a LOSD platform show that many functions are not automated and need to be manually executed. We recommend the further integration of the building blocks in the platform to reduce the barriers for the use of datasets by the public.@en

Virtual Research Environments (VREs) offer new opportunities for collaboratively analysing open research data. This workshop builds on a workshop that we gave at CeDEM16 and aims to refine and discuss requirements for collaboratively analysing Open Government Data (OGD) and open research data through a secure, trusted and multidisciplinary VRE. Presentations about innovative use cases for reusing governmental and research data will be given, and participants will discuss and develop innovative use cases. The conditions for sharing their public or research data with others in a VRE will be discussed. This provides the basis for a discussion on the prioritization of requirements derived from the use cases. Participants are encouraged to provide their view on requirements for a VRE that offers governmental research data as well as directions for VRE projects.@en