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.

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.

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.

Open Government Data (OGD) is a build-up of the data accumulated in the government organisations pertaining to the structural and functional dimensions and it is imperative for OGD to be high-value for facilitating value creation and innovation. The present study purports to provide a launchpad to the aforementioned truism by advancing the concept of Open Government Data Capital (OGDC) resting on the principles of Knowledge Management (KM) given that the high-value OGD can result only with the engagement of the concerned administrative agencies in knowledge sharing for being made accessible for wider use via dedicated web portals. To drive home the arguments, an empirical investigation is conducted with four top-notch countries, viz., Canada, Australia, New Zealand and the United States, in terms of the quantitative evaluation of their OGD portals’ quality and inferences are drawn as to how OGDC may be furthered with the provision and maintenance of high-value datasets. Thus, it is shown that the Australian OGD portal is qualitatively robust and leads in terms of OGDC which may be beefed up with more integration of the KM practices in terms of the inter-governmental agencies’ coordination and the other countries are lagging behind in terms of the quality parameters.

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.

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.

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.

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.

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.

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.

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.

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.

Purpose: Many governments are working toward a vision of government-wide transformation that strives to achieve an open, transparent and accountable government while providing responsive services. The purpose of this paper is to clarify the concept of transparency-by-design to advance open government. Design/methodology/approach: The opening of data, the deployment of tools and instruments to engage the public, collaboration among public organizations and between governments and the public are important drivers for open government. The authors review transparency-by-design concepts. Findings: To successfully achieve open government, fundamental changes in practice and new research on governments as open systems are needed. In particular, the creation of “transparency-by-design” is a key aspect in which transparency is a key system development requirement, and the systems ensure that data are disclosed to the public for creating transparency. Research limitations/implications: Although transparency-by-design is an intuitive concept, more research is needed in what constitutes information and communication technology-mediated transparency and how it can be realized. Practical implications: Governments should embrace transparency-by-design to open more data sets and come closer to achieving open government. Originality/value: Transparency-by-design is a new concept that has not given any attention yet in the literature.