Shedding Light on Participation in Open Government Arenas: Determinants of Platform Activity of Web and App Users

This article develops and tests a model to explain web-based and mobile devices usage by citizens to interact with their local government. By employing literature from diverse fields of information systems research, the authors derive an integrated model that investigates citizen participation on a city improvement platform. The model proposes three overall influences on platform activity: technological influences (perceived ease of use, perceived usefulness), motivational influences (intrinsic motivation and prosocial motivation), and socio-demographic influences (gender, age, education), and is tested among two groups of users (i.e. web page and mobile app users). Empirical results show that platform activity of both web and mobile users is mainly driven by intrinsic and prosocial motivation. Whereas perceived usefulness is positively associated with platform behavior of web users, TAM variables have not effect on mobile users’ activity. While gender and age play a role regarding web activity, age and education influence mobile participation

Who Do You Think We Are? The Data Publics in Digital Government Policy

This study provides conceptual clarity on open data users by connecting an empirical analysis of policy documents to emerging theoretical research on data publics. Releasing files to the public for reuse is the primary objective of policy on open government data. Recent public sphere scholarship provides insights into who reuses data by defining a data public as people who actively construct narratives with openly available digital sources. A content analysis of United States federal policy documents identified the language used to represent people who might reuse data. An inductive qualitative analysis of mandated digital strategy reports generated a taxonomy that characterizes people mentioned in open data policy. In addition to the taxonomy, this research contributes a set of propositions to predict data reuse based on these characteristics. The results encourage further dialog between public sphere and digital government scholars to establish testable explanations about data publics

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

Determinants of Continuance Intention to Use Open Data Website: An Insight from Indonesia

Open data is a flagship initiative in open government program to increase transparency, social and commercial value, and participatory governance. Open data is a relatively new field and the factors affecting its continuance use by citizen has not been widely studied. A better understanding of these factors can help government to formulate policies and strategies that can improve the acceptance and use of open data website. The research model is based on the Theory of Planned Behavior and integrated with the technology quality and trust factors. Data collection was conducted using questionnaire. Structural Equation Modeling (SEM) was used to test the research model. The results show that attitude, subjective norm, perceived behavioral control and trust directly affect continuance intention to use open data website. Systems quality affects perceived ease of use, while information quality positively affects perceived usefulness, perceived ease of use, and trust. Both perceived usefulness and perceived ease of use affect user’s attitude. The analysis of this study suggests that each influencing factor provides implications for government to stimulate the continuance use of open data website. Available at: https://aisel.aisnet.org/pajais/vol11/iss2/5

“Os cidadãos querem ser informados”: estudo de caso sobre o papel do design no acesso e uso de dados abertos do Governo

Governos em todo o mundo estão gradualmente disponibilizando os seus dados não confidenciais em plata-formas online, para facilitar o acesso público a essas informações. Porém, a maior parte das plataformas de Dados Aberto do Governo (DAG) não são tão inclusivas quanto se propõem pois, apesar da ênfase política no “envolvimento do cidadão”, seus verdadeiros usuários são profissionais técnicos. Este trabalho usa aborda-gens de Design Participativo e é feito em parceria com o poder público, para identificar modos de envolver o público na co-criação de valor e significado para os DAG, estabelecendo boas práticas para a promoção e uso desse material. Este artigo discute os resultados preliminares das duas primeiras fases, de três planeadas: entrevistas com integrantes das duas instituições públicas estudadas e o Mapa do Sistema dos dados de am-bas. Essas ferramentas contribuem para perceber nuances dos serviços e os objetivos da instituição. Isto é importante para alinhar as expectativas do poder público e dos cidadãos sobre o projeto, aquando da realiza-ção de dinâmicas participativas com a comunidade. A terceira fase da pesquisa, que ainda será desenvolvida, será guiada pelos princípios de Design Inclusivo, procurando contribuir para soluções apropriadas e desejá-veis para um leque variado de pessoas.Governments worldwide are gradually making their non-confidential data available online, to facilitate public access to that information. However, research shows that most Open Government Data (OGD) platforms are not as inclusive as they propose because, despite the political emphasis on “citizen involvement”, their real users are technical professionals. This study uses participatory design approaches and is conducted in partnership with public authorities, to identify ways of involving the public in the co-creation of value and meaning for OGD, in order to establish a best practices for the dissemination and use of such materials. This article discusses the preliminary results of the first two of three planned research phases: interviews with members of the two partner public institutions and the Ecosystem Map of the government data of both. These tools contribute to understanding the nuances of the services and the objectives of the institution. This is important to align both the government and citizens’ expectations of the project, when carrying out participatory design intiatives with the community. The third phase of the research, which is yet to be developed, will be guided by Inclusive Design principles, thus seeking to contribute to appropriate and desirable solutions for a wide range of people

User Perception of the U.S. Open Government Data Success Factors

This quantitative correlational study used the information systems success model to examine the relationship between the U.S. federal departments\u27 open data users\u27 perception of the system quality, perception of information quality, perception of service quality, and the intent to use open data from U.S. federal departments. A pre-existing information system success model survey instrument was used to collect data from 122 open data users. The result of the standard multiple linear regression was statistically significant to predict the intent to use the U.S. open government data F(3,99) = 6479.916, p \u3c0.01 and accounted for 99% of the variance in the intent to use the U.S. open government data (R²= .995), adjusted R²= .995. The interdependent nature of information quality, system quality, and service quality may have contributed to the value of the R². Cronbach\u27s alpha for this study is α=.99, and the value could be attributed to the fact that users of open data are not necessarily technical oriented, and were not able to distinguish the differences between the meanings of the variables. The result of this study confirmed that there is a relationship between the user\u27s perception of the system quality, perception of information quality, perception of service quality, and the intent to use open data from U.S. federal departments. The findings from this study might contribute to positive social change by enabling the solving of problems in the healthcare, education, energy sector, research community, digitization, and preservation of e-government activities. Using study, the results of this study, IT software engineers in the US federal departments, may be able to improve the gathering of user specifications and requirements in information system design

Implementation evaluation model to measure virtual learning environment success factors among Malaysian teachers

Despite the various benefits offered by Virtual Learning Environment (VLE), its usage among Malaysian teachers is still low, indicating that the system is not in the right track of success. Therefore, this study aims to develop a model to measure VLE success among Malaysian teachers based on the updated DeLone & McLean IS Success Model (D&M). This study employed an explanatory sequential mixed method design. Eight hundred and fifty (850) questionnaires were distributed to respondents across the northern region of Malaysia using simple random sampling procedure. The QR code was used to speed up the data collection without violating the rules of probability sampling. As a result, 719 questionnaires were returned and 643 are usable for the main analysis. The quantitative data analysis was conducted using Partial Least Squares-Structural Equation Modeling (PLS-SEM). Most of hypothesized direct relationships are supported, except for Use to Intention to Use, which is fully mediated by User Satisfaction. The result also confirmed the positive moderating role of Workload. However, the moderating role of Personal Characteristics is not supported. Furthermore, the issue of recursive relationships, which produced two R² and Q² in certain endogenous variables, was investigated by comparing five possible models. Consequently, the produced model can be analyzed on a single structural model and therefore, provides valid predictive accuracy and relevance. This analysis has become a major methodological contribution of the study that provides a foundation for further investigations on the relevancy of the recursive relationships in D&M. Based on the final model, the VLE implementation strategy was produced and presented to 14 practitioners. Next, the validation was done using qualitative content analysis. The result indicates that the implementation strategy can be applied in Malaysian schools. Finally, this study contributes to the body of knowledge by providing a model to measure VLE success among teachers