Emerging & data technologies applied to public sector: An AI- copiloted systematic literature review

This paper explores citizens’ stances toward the use of artificial intelligence (AI) in public services in Norway. Utilizing a social contract perspective, the study analyzes the government–citizen relationship at macro, meso, and micro levels. A prototype of an AI-enabled public welfare service was designed and presented to 20 participants who were interviewed to investigate their stances on the described AI use. We found a generally positive attitude and identified three factors contributing to this: (a) the high level of trust in government (macro level); (b) the balanced value proposition between individual and collective needs (meso level); and (c) the reassurance provided by having humans in the loop and providing transparency into processes, data, and model’s logic (microlevel). The findings provide valuable insights into citizens’ stances for socially responsible AI in public services. These insights can inform policy and guide the design and implementation of AI systems in the public sector by foregrounding the government–citizen relationship.

The article considers the place and role of public trust in the functioning of public sector institutions. Trust in government is a multi-conceptual category, which is based on a combination of economic, social, and political interactions between government authorities at different levels and citizens. The authors of the article propose to conduct an epistemological study of trust in government at three main (micro-, meso-, macro-) and intermediate levels. At the micro-level, it is proposed to determine trust based on the results of economic agents' cooperation with public authorities through the provision of public services. At the meso level, trust in the government is defined by the competence of central government agencies that formulate and implement public policy in the relevant field, to solve economic and social problems of society, as well as their ability to generate positive expectations for citizens future well-being. At the macro level, trust in the government is derived from the economic efficiency of the "whole government." The authors propose to consider the intermediate level as trust in local governments, which is determined by both the quality of public services and the efficiency of public administration. It was shown that trust in the institutions of the public sector of the economy could not be formed separately from the personal characteristics of its Chairman or head. In the historical context of the development of Ukraine's statehood, systematic events related to corruption in the management of the public institution that receives wide media coverage have led to systemic distrust of economic actors towards public sector institutions and the state as a whole. The authors found that certain levels of trust in government interact, and therefore, the erosion of trust at one level can affect trust at others, which, accordingly, leads to a deterioration in the results of public policy in general. Strengthening trust at one level due to the synergetic effect will help strengthen trust in government in general. The article also shows that trust in government institutions and the government in general reduces the risk of opportunistic behavior and, consequently, can push society to give preference to long-term results of public policy over short-term benefits.

Maximising the Opportunities of Artificial Intelligence for People Living With Cancer

A scoping review into the explanations for differences in the degrees of shared decision making experienced by patients

As the digital reform unfolds at an incredible pace, the continuing higher education faces opportunities to transform and upgrade. Although emerging technologies such as 5G, Internet and artificial intelligence are gaining a foothold in continuing education, the continuing higher education must deal with challenges and issues in education orientation, teaching mode, talent training, etc. There is an urgent need of standardized management, reform and development. This paper aims to establish the accurate orientation and staggered development path for continuing education in colleges and universities on the macro, meso and micro levels. On the macro level, it studies the accurate orientation and staggered development path of continuing education in the digital reform era; on the meso level, it explores the standardized management of continuing higher education and reform measures of digital talent training mode; on the micro level, it discusses how to leverage the advantages in colleges and universities, build role models in digital reform education programs and learning bases, reform the standardized management and talent training mode, and propel the high-quality development of continuing higher education.

This research analyzes the development of technology in the academic environment and its consolidation in technological businesses in micro, meso and macro organizational levels. Based on the content analysis of reports regarding a governmental Brazilian innovation incentive program, the Programa de Incentivo a Inovacao, the research highlights the diffused actions of researchers-entrepreneurs in the micro level, which oscillates around the undertaking and the licensing of technology when creating spinoffs. In the meso level, among clients, competitors, partners and suppliers, the academic spinoffs operate under tight knit rules of regulatory agencies, as well as a strict dependence of financial support from research agencies and governmental programs for their startup. In the macro level, the political, legal, economical, technological, sustainable and cultural dispositions of the environment are important references for innovation agents to act. The findings of this study contribute to the formulation and evaluation of public policies and programs, as well as academic-business practices aimed at innovation and development of technologies.

Artificial Intelligence (AI) has become one of the most prominent topics in public policy and administration studies over the last years. Despite the attention to AI in this field isn’t entirely new, the universality of these group of technologies has radically increased the attention of scholars around the globe. This expansion of AI in the public sector entails the exploration of renovated foundations of analysis, not only to understand the novelty of these technologies, but also to connect these processes of adoption and implementation with other debates in public policy and administration. To do so, in this article we debate the need of an analytical framework of AI in the public sector based on the three levels of public administration: macro , meso , and micro . Also, we review the state-of-the-art in the field using the articles presented in the special issue on Artificial Intelligence and Public Administration: Actors, Governance, and Policy . Form here, we propose studying AI using a combination of macro , meso , and micro levels of public administration. We assume this will help to broadly apprehend how and why people, policies, and institutions interrelate with AI in public sector settings, and which effects can be expected from these processes in public administration.

Public and private value creation using artificial intelligence: An empirical study of AI voice robot users in Chinese public sector

In today's public sector, there is an urgent need for efficiency, effectiveness and rapid response to economic and social changes. This change is supported by tremendous technological progress, where artificial intelligence (AI) is one of the most important pillars of digital technology that can dramatically change all sectors of society, including the public sector, its leaders and public servants. It may also help in playing a new role and giving a new legitimacy to the public sector and government work based on modern technology. To the best of our knowledge and due to the lack of a comprehensive vision, a hypothesis that establishes for the possibility of applying artificial intelligence in the public sector. This study aims to shed some light on the need of public sector leaders to Gain a comprehensive and deep understanding of the scope and impact of AI-based applications in the public sector as their organizations are fully digitized. Previous studies discussed the application of artificial intelligence, often partially, specialized in the business sector, which generated a research gap that did not address the specificity of the public sector and government work. The methodology of this study is based on collecting, analyzing, and linking relevant ideas from published scientific research to provide an integrated overview of the applications of artificial intelligence in the government sector, taking into account the significant role that this sector plays in the lives of citizens and the rest of the vital sectors. This study examined the specificity of the application of artificial intelligence in the government sector, the role of governments in ensuring the successful implementation of the artificial intelligence strategy in their departments, and the enormous opportunities and capabilities that artificial intelligence provides to the public sector. The study also focused on the most prominent issues and challenges faced by artificial intelligence in government work, the great role that the partnership between the public and private sectors plays for the success of the application, and how government leaders can play an important role in the development and strengthening of the artificial intelligence community.

Purpose: The present study was conducted with the aim of examining the indicators of barriers and challenges of virtual education at macro, meso, and micro levels. Methods and Materials: The method employed in this research is a mixed-methods approach. In the qualitative section, documents from the Ministry of Education of the Islamic Republic of Iran, including the "Fundamental Theoretical Foundations for Formal and Public Education Transformation," the "Fundamental Transformation Document of Education," and the "National Curriculum Document," were analyzed. In the quantitative section, two non-random sampling methods were used: non-probability sampling and snowball sampling, which is a non-probability sampling method commonly used in sociology and statistical research. The research population consisted of 150 students from Farhangian University and 10 faculty members from the same institution. Interviews were conducted based on a competency model, and the appropriate tool was developed and implemented after determining its validity and reliability using Cronbach's alpha (α = 0.92). Findings: Based on the findings, 150 digital teacher competencies were categorized into 9 sections, which were further divided into three main areas: curriculum design, barriers to virtual education, and the quality of virtual teaching. The challenges identified in the study were categorized at macro, meso, and micro levels, and the results are applicable for identifying the indicators of barriers and challenges in virtual education. Conclusion: The results of the study indicate that, at the macro level, poor policy-making is the primary issue, at the meso level, budget disruptions are prominent, and at the micro level, students, more than parents, teachers, and professors, believe that the barriers and challenges of virtual education are greater than those of in-person education.

Inter-organizational collaboration among healthcare institutions is widely recognized to improve healthcare services. Because there is a research gap in examining the management barriers to inter-organizational collaboration in countries with less efficient healthcare systems and the reasons for non-implementation of innovations, the aim of this study was to identify key management barriers to inter-organizational collaboration in the preoperative treatment of patients with hip or knee osteoarthritis in Slovenia using a mixed-methods approach with key stakeholders. A cross-sectional study was conducted using multiple methods. An online survey (n = 135) and a multilevel qualitative approach were used, interviewing patients (n = 21), healthcare professionals, and other stakeholders (n = 42). The overall assessment of barriers affecting the integrated approach at the macro, meso, and micro levels revealed that macro-level factors were statistically significantly perceived as the major barriers, while micro-level factors were the minor barriers. There was no significant difference between public and private sector respondents in the barriers at the three levels. However, there were significant differences in the perceptions of different professional groups at the micro and meso levels, but not at the macro level. The analysis of the in-depth interviews confirmed the importance of macro-level barriers. A culture of noncooperation combined with “managerial indecision” prevails in the Slovenian healthcare system due to weak management support for inter-organizational collaboration, with managers and other key stakeholders failing to make urgent decisions due to a lack of autonomy. Interviewees commonly noted that one of the major barriers to inter-organizational collaboration was a lack of resources and staff, particularly of primary care physicians and nurses. In the preoperative treatment of patients with hip or knee osteoarthritis, the culture of non-collaboration and executive indecision are the major macro-level barriers to inter-organizational collaboration in Slovenia.

Purpose This paper aims to assume the responsibility of examining the shifting patterns of legal liability for failures that result from the integration of artificial intelligence (AI) in the public domain. It explores aspects such as the current legal implications, accountability mechanisms of AI errors and potential concerns and issues and proffered solutions for the complex issues that surround AI-related mistakes in public administration. Toward this end, the study outlines a central problem that is defined by the complex nature of errors that arise when AI is applied within the public service. Design/methodology/approach AI systems have recently been implemented into the public sectors and have influenced positive changes in efficiency and decision-making. However, the development and complication of AI technologies have raised profound worries on accountability in the case of mistakes in public sector. Findings As international governments increasingly rely on AI for critical selection and planning processes, establishing a clean prison system to educate and allocate responsibility when errors occur is paramount. What it has been found to have the potential to guide policy makers, criminologists and AI planners toward the challenges of implementing AI in the public sector easy to navigate. Finally, the research seeks to assess the potential of AI in public administration and will also serve to create a certain level of transparency, accountability and public trust. Research limitations/implications To provide a comprehensive response, the research employs a multifaceted methodology that encompasses a thorough literature review, in-depth legal analysis, regulatory assessment, exploration of various liability models, consideration of challenges and ethical considerations and real-world case studies. This holistic approach aims to shed light on the intricate web of legal responsibility and accountability entwined with AI in the public sector. Practical implications Although as a tool, AI is different from the human agents who use it, and defining and attributing legal responsibility for such errors becomes a challenging task because of the classification of AI as either software or a tool, and the accountability of its human users. Social implications Consequently, the primary research question emerges: “‘Employing’ AI in the public sector: how can legal responsibility for errors be assigned and governed in ways that respond to the plural employment-aspects of AI?” Originality/value The significance of this research lies in its ability to address the emerging challenges associated with AI adoption in the public sector. As international governments increasingly rely on AI for critical selection and planning processes, establishing a clean prison system to educate and allocate responsibility when errors occur is paramount. What it has been found to have the potential to guide policy makers, criminologists and AI planners toward the challenges of implementing AI in the public sector.

Amid a global decline in fertility rates, China's consistently low birth rate has highlighted the importance of understanding the fertility attitudes of women of childbearing age. While previous studies have largely focused on fertility anxiety, less attention has been paid to anti-fertility anxiety-women's psychological resistance to societal pressures and expectations surrounding childbearing. To address this research gap, this study explores how women construct and articulate these seemingly conflicting attitudes, as well as the sociopsychological mechanisms that enable their coexistence. Using grounded theory and natural language processing techniques, the study analyzed 4,495 Weibo posts (fertility anxiety = 2,761; anti-fertility anxiety = 1,734) through three-level coding, semantic network analysis, and sentiment analysis. The findings indicate that both fertility anxiety and anti-fertility anxiety are shaped by sociocultural and media narratives at the macro level, family and workplace dynamics at the meso level, and personal values and experiences at the micro level. Fertility anxiety discourse is primarily situated at the macro and meso levels, reflecting women's feelings of insecurity and powerlessness in the face of societal pressures, maternal penalties and unequal family burdens. Anti-fertility anxiety is more rooted in micro-level expression, emphasizing reproductive autonomy and identification with motherhood amid a broader feminist awakening. The emotional tendency of fertility anxiety is predominantly negative, with intensity decreasing from the macro to the meso and micro levels. Anti-fertility anxiety is associated with more positive emotions, with emotional intensity declining from the micro to the meso and macro levels. This study highlights the psychological tension between structural constraints and subjective desires in women's fertility decisions, reinforcing explanations for conflicting fertility attitudes in the context of social media empowerment. These insights contribute to the conceptual understanding of anti-fertility anxiety and also offer practical recommendations for enhancing women's reproductive autonomy, psychological well-being, and fertility-related policies and support systems.

Aim/Purpose: This study aims to investigate the influence of e-government public services on public trust at the local government level, addressing the pressing need to understand the factors shaping citizen perceptions and trust in government institutions. Background: With the proliferation of e-government initiatives worldwide, governments are increasingly turning to digital solutions to enhance public service delivery and promote transparency. However, despite the potential benefits, there remains a gap in understanding how these initiatives impact public trust in government institutions, particularly at the local level. This study seeks to address this gap by examining the relationship between e-government service quality, individual perceptions, and public trust, providing valuable insights into the complexities of citizen-government interactions in the digital age. Methodology: Employing a quantitative approach, this study utilises surveys distributed to users of e-government services in one of the regencies in Indonesia. The sample consists of 278 individuals. Data analysis is conducted using Partial Least Squares Structural Equation Modelling, allowing for the exploration of relationships among variables and their influence on public trust. Contribution: This study provides insights into the factors influencing public trust in e-government services at the local government level, offering a nuanced understanding of the relationship between service quality, individual perceptions, and public trust. Findings: This study emphasises information quality and service quality in e-government-based public services as crucial determinants of individual perception in rural areas. Interestingly, system quality in e-government services has no influence on individual perception. In the individual perception, perceived security and privacy emerge as the strongest antecedent of public trust, highlighting the need to guarantee secure and private services for citizens in rural areas. These findings emphasise the importance of prioritising high-quality information, excellent service delivery, and robust security measures to foster and sustain public trust in e-government services. Recommendations for Practitioners: Practitioners must prioritise enhancing the quality of e-government services due to their significant impact on individual perception, leading to higher public trust. Government agencies must ensure reliability, responsiveness, and the effective fulfilment of user needs. Additionally, upholding high standards of information quality in e-government services by delivering accurate, relevant, and timely information remains crucial. Strengthening security measures through robust protocols such as data encryption and secure authentication becomes essential for protecting user data. With that in mind, the authors believe that public trust in government would escalate. Recommendation for Researchers: Researchers could investigate the relation between system quality in e-government services and individual perception in different rural settings. Longitudinal studies could also elucidate how evolving service quality, information quality, and security measures impact user satisfaction and trust over time. Comparative studies across regions or countries can reveal cultural and contextual differences in individual perceptions, identifying both universal principles and region-specific strategies for e-government platforms. Analysing user behaviour and preferences across various demographic groups can inform targeted interventions. Furthermore, examining the potential of emerging technologies such as blockchain or artificial intelligence in enhancing e-government service delivery, security, and user engagement remains an interesting topic. Impact on Society: This study’s findings have significant implications for fostering public trust in government institutions, ultimately strengthening democracy and citizen-government relations. By understanding how e-government initiatives influence public trust, policymakers can make informed decisions to improve service delivery, enhance citizen engagement, and promote transparency, thus contributing to more resilient and accountable governance structures. Future Research: Future research could opt for longitudinal studies to evaluate the long-term effects of enhancements in service quality, information quality, and security. Cross-cultural investigations can uncover universal principles and contextual differences in user experiences, supporting global e-government strategies in rural areas. Future research could also improve the research model by adding more variables, such as risk aversion or fear of job loss, to gauge individual perceptions.

Introduction. The paper has developed a new scheme of a multimodal logistics system for grain transportation for export to Iran using links and graphs. It is proposed to consider the functioning of road transport in a multimodal logistics system for grain export from the standpoint of a systematic approach at the micro, meso and macro levels based on the newly introduced concept of transport capacity of the simulated graph. To determine the optimal modes of road transport functioning (with the further aim of increasing its efficiency of functioning) in the logistics links of export grain supplies at the micro level, it is proposed to perform using the ‘Sowing fields – regional barn-floors’ graph, at the meso level – the ‘Regional barn-floors – regional grain storages’ graph, at the macro level – the ‘Regional grain storages – port grain storages’ graph. Graphs modelling, determining the transport capacity of vertices, fixing vertices for barn-floors, regional grain storages and port grain storages make it possible for agro–industrial enterprises to plan the volume of grain exports, to use their acreage rationally considering crop yields while fulfilling an important condition - ensuring food security for the population of the Russian Federation. Road transport planning at the micro level is directly linked to the operation of agricultural enterprises, and at the meso level to grain storages. At the macro level, road transport serves the three largest port grain receiving points of the Volgograd region. Multimodal transportation of grain from a specific farm in the region to the port of Enzeli in Iran has been organized using road transport and VOLGO-BALT 239 river-sea vessel.Materials and methods. The paper uses methods of statistical analysis of winter wheat supplies for export to Iran from the Volgograd region. At the micro level, graphoanalytic methods are used to model the location schemes of filling bunkers when working in a team of one, three or nine combines, indicating their number of appearance on the field in the xOy coordinate plane. The methods of system analysis were used to correctly divide the international multimodal logistics system for the transportation of export grain into micro, meso and macro levels with the definition of the place and role of transport. Methods of solving the linear programming problem are the optimization of the assignment of consumers to suppliers at all levels under consideration.Results. It is revealed that complex international multimodal logistics systems for the delivery of export grain must be considered using a systematic approach. It is proposed to consider the system at the micro, meso and macro levels. At each of the levels, it is necessary to plan the operation of transport based on calculations of the ‘transport capacity’ of the ‘Sowing fields – regional barn-floors’, ‘Regional barn-floors – regional grain storages’, ‘Regional grain storages – port grain storages’ graph nodes. OOO Progress, the agro-enterprise of the Volgograd region, has been given the opportunity to plan its work taking into account new information technologies that ensure higher efficiency of agricultural activities in the cultivation of winter wheat with partial sale for export to Iran.Discussion and conclusions. The improvement of the organisation of road transport functioning in the international multimodal logistics system of grain export supplies cannot exist without the use of precision farming technologies in harvesting and transport processes. The use of the right logistics technologies in road transport and in the organisation of winter wheat cultivation has a great impact on the final cost of grain and on the guaranteed food security of the Russian Federation. Research in this direction is currently relevant.