IoT and AI for Smart Government: A Research Agenda

The Internet of things (IoT) is the network of objects/things that contain electronics, software, sensors, and actuators, which allows these things to connect, interact, and exchange data. The users, sensors, and networks generate huge amounts of data from which governments can develop applications and gain knowledge using Artificial Intelligence (AI) techniques. Thus, IoT and AI can enable the development of valuable services for citizens, businesses, and public agencies, in multiple domains, such as transportation, energy, healthcare, education, and public safety. This guest editorial for the special issue on IoT and AI for Smart Government, identifies the challenges involved in implementing and adopting these technologies in the public sector, and proposes a comprehensive research framework, which includes both IoT and AI elements for smart government transformation. Subsequently, the editorial provides a brief introduction of the six papers in this special issue. Finally, an agenda for future research on IoT and AI for smart government is presented, based on the proposed framework and gaps in existing literature, supported by the papers that were submitted to this special issue. The agenda comprises four directions i.e., conducting domain-specific studies, going beyond adoption studies to examine implementation and evaluation of these technologies, focusing on specific challenges and thus quick wins, and expanding the existing set of research methods and theoretical foundations used.     

An attention-based view of AI assimilation in public sector organizations: The case of Saudi Arabia

Artificial Intelligence (AI) has been suggested to have transformative potential for public sector organizations through enabling increased productivity and novel ways to deliver public services. In order to materialize the transformative potential of AI, public sector organizations need to successfully assimilate AI in their operational activities. However, AI assimilation in the public sector appears to be fragmented and lagging the private sector, and the phenomena has really limited attention from academic research community. To address this gap, we adopt the case study approach to explore three Saudi-Arabian public sector organizations and analyze the results using the attention-based view of the organization (ABV) as the theoretical lens. This study elucidates the challenges related AI assimilation in public sector in terms of how organizational attention is focused situated and distributed during the assimilation process. Five key challenges emerged from the cases studied, namely (i) misalignment between AI and management decision-making, (ii) tensions with linguistics and national culture, (iii) developing and implementing AI infrastructure, (iv) data integrity and sharing, and (v) ethical and governance concerns. The findings reveal a re-enforcing relationship between the situated attention and structural distribution of attention that can accelerate the successful assimilation of AI in public sector organizations.     

The rise of GovTech: Trojan horse or blessing in disguise? A research agenda

As GovTech solutions are steadily entering the public sector, they have yet to find their way into the mainstream literature. GovTech refers to socio-technical solutions – that are developed and operated by private organisations – intertwined with public sector components for facilitating processes in the public sector. GovTech solutions promise a superior customer journey for citizens and businesses compared to current government portals and front desks. GovTech solutions can be a blessing in disguise for governments struggling in their digital transformation journey, carrying the burden of public service innovation and replacing legacy systems with modern GovTech solutions. Yet, there are also concerns that GovTech solutions are a Trojan horse, exploiting the lack of technical knowledge at public agencies and shifting decision-making power from public agencies to market parties, thereby undermining digital sovereignty and public values. This paper develops a research agenda for GovTech based on a conceptual framework. This framework reveals four interrelated design areas for GovTech: institutional, governance, technical and human-centred design. Governments can employ the conceptual framework to further align and develop their strategies by focussing on GovTech governance, referring to the ability to manage the various interdependencies between the four design areas.     

Digital transformation toward AI-augmented public administration: The perception of government employees and the willingness to use AI in government

Government employees play a critical role in adopting and using new technologies in government, and their attitude and willingness to use them matter in creating a sustainable and meaningful digital transformation. This study explores how the perception of government employees shapes the willingness to support the use of AI technologies in government. Based on a survey data on current government employees in the U.S., our analysis reveals that the willingness to implement and use AI technologies in government was contingent upon a series of positive and negative perceptions about the new technologies, long-term outlook on the role of AI technologies in society, and the familiarity and experience in using some form of AI applications in the past. In particular, the perception of AI enhancing the efficiency and effectiveness of the work and a positive and longer-term outlook on AI's future about human labor (as an assistant or a competitor), the perception of the technology's ultimate harm or benefit (does it harm or benefit humanity), its ability to eventually make ethical and moral judgments influenced the willingness to support AI technologies in government. A substantial proportion of the government employees in the survey sample responded that they had experienced using some form of AI applications in their work and this familiarity had a strong positive influence on their support for AI. Our findings point to the importance of training the government employees in AI technologies to improve their understanding and perception about the new technologies as well as their potentials in government that will foster a culture of innovation toward sustainable and impactful digital transformation.     

Public value creation in digital government

Public value theory offers innovative ways to plan, design, and implement digital government initiatives. The theory has gained the attention of researchers due to its powerful proposition that shifts the focus of public sector management from internal efficiency to value creation processes that occur outside the organization. While public value creation has become the expectation that digital government initiatives have to fulfil, there is lack of theoretical clarity on what public value means and on how digital technologies can contribute to its creation. The special issue presents a collection of six papers that provide new insights on how digital technologies support public value creation. Building on their contributions, the editorial note conceptualizes the realm of public value creation by highlighting: (1) the integrated nature of public value creation supported by digital government implementations rather than enhancing the values provided by individual technologies or innovations, (2) how the outcome of public value creation is reflected in the combined consumption of the various services enabled by technologies and (3) how public value creation is enabled by organizational capabilities and configurations.     

Challenges in the adoption of crisis crowdsourcing and social media in Canadian emergency management

When a disaster occurs, government agencies are responsible for managing the response and recovery efforts of the impacted communities and infrastructure. Crowdsourcing and social media are widely used in disaster response, yet their primary implementation and application are often via non-governmental agencies and private citizens. A review of the literature suggests that government emergency management agencies in Canada have made little documented progress in adopting crowdsourcing or social media for emergency management. Most of the literature around crowdsourcing and social media for emergency management focus on its use or role outside of Canada (e.g. the USA, Australia, etc.). In order for government agencies in Canada to progress, it is important to identify the Canada-specific barriers and constraints. This study offers a new perspective from Canadian government emergency management agencies to address this gap. Through a series of semi-structured interviews with 15 government officials from 14 agencies, this study identifies the primary challenges and constraints faced by Canadian agencies looking to adopt crisis crowdsourcing. Results indicate that organizational factors, policies, and federal legislation in Canada present barriers to crisis crowdsourcing (including crowdsourcing through social media) adoption within agencies at various levels of government. Based on these results, recommendations are made to support the adoption of crisis crowdsourcing amongst Canadian government agencies.     

Close encounters of the digital kind: A research agenda for the digitalization of public services

This paper contributes to e-government research by presenting a review and discussion on how digitalization of public services has affected the interaction between citizens and government. We argue for a conceptualization and critical reflection on the nature of the underlying interaction between citizens and public officials - the public encounter - that digital public services are developed to support. We apply a qualitative and hermeneutic approach and illustrate that digital public services change public encounters concerning when, where, and how interactions occur, what each actor does, and the skills required of them. By relating these changes to emerging digital technologies (e.g. data mining, machine learning, sensor technology, and service automation), we illustrate that while these new technologies carry the potential to further digitalize service provision and fulfill the democratic goals of digital government, authorities can apply the same technology to restrict, control, and surveil citizens. Based on a critical discussion on what digitalization might entail for society, we identify problem areas arising from this development and propose a research agenda for understanding this phenomenon further. We raise questions and ethical concerns regarding accountability and reskilling of citizens and public officials as public service provision becomes citizen self-service.     

Towards a comprehensive understanding of digital government success: Integrating implementation and adoption factors

When analyzing the causes that lead to digital government success or failure, state of the art research is often divided into two main areas: (1) implementation of these initiatives by government agencies and (2) their adoption by citizens, as some of the most important users. Each of these two perspectives has its own concepts, measurements, and theoretical models. This separation becomes significant when trying to have a comprehensive understanding of digital government success and when facing practical problems since factors affecting both governments and citizens contribute to the success or failure of digital government initiatives. Therefore, this paper proposes a comprehensive digital government success model that attempts to integrate implementation and adoption perspectives. In addition, based on data from the 32 states of Mexico, the paper provides an illustrative example of how the proposed model could be used.     

Building context-based knowledge of government social media communication through an ethnographic study of the US Coast Guard

Governments are increasing digital communication with citizens, yet little is known about how the public sector influences communicators’ daily social media activities. This ethnographic study uses interviews, documents, and participant observation to offer a rare emic view of the US Coast Guard (USCG) social media program. Breaking up the monolithic public sector communication context, influences on social media communication were nested within five contexts: organization, military, parent agency, federal government, and the US public sector. By observing how the contexts and related attributes influence personnel and the program, the study provides insights related to social media communication processes rather than merely content products. Findings extend theoretical and practical applications by identifying enablers and challenges to government social media communication within an applied context. USCG's culture and history of transparency and engagement drive the strategy, while resource constraints and a devaluing of social media within the decentralized organization constrain program effectiveness and real-time engagement.     

Data management maturity assessment of public sector agencies

To determine how critical data assets are conceptualized and managed in the public sector, we conducted a large-scale empirical study at 15 government agencies. We use the Data Management Maturity (DMM) reference model framework to conduct a systematic multi-level analysis (inter-agency, intra-agency, and cross-case analysis). To aid the comparative assessment of multiple independent agencies, we propose and test the DMM Index. The study not only examines the maturity of data management practices in government agencies, but also provides guidance on how an enterprise-wide, systematic assessment may be conducted. The approach presented in the paper can be replicated at other large government entities and private conglomerates. Public and private sector agencies may apply the approach to develop custom roadmaps for data management improvements that align with the organization's business goals.     

Public AI canvas for AI-enabled public value: A design science approach

Public agencies have a strong interest in artificial intelligence (AI) systems. However, many public agencies lack tools and frameworks to articulate a viable business model and evaluate public value as they consider investing in AI systems. The business model canvas used extensively in the private sector offers us a foundation for designing a public AI canvas (PAIC). Employing a design science approach, this study reports on the design and evaluation of PAIC. The PAIC comprises three distinctive layers: (1) the public value-oriented AI-enablement layer; (2) the public value logic layer; and (3) the public value-oriented social guidance layer. PAIC offers guidance on innovating the business models of public agencies to create and capture AI-enabled value. For practitioners, PAIC presents a validated tool to guide AI deployment in public agencies.     

Distribution channel management in e-government: Addressing federal information policy issues

Part of the promise of electronic government (e-government) is its ability to transform the delivery of information services and products from government to users. E-government allows federal agencies to supplement and even supplant private sector roles intermediating between government agencies and users, creating unintended consequences in terms of policy, theory, and practice. The problem is called “channel conflict” in the marketing literature, and the typical response is called distribution channel management (DCM). After reviewing the literatures of e-government, information policy, and DCM, the paper explores differing DCM philosophies of two federal agencies: the Internal Revenue Service and the U.S. Census Bureau. An examination of these two DCM programs provides insights on how federal agencies may be able to manage their various channels for e-government offerings despite tensions in the current legal and policy context. The paper concludes by using DCM literature to help frame options for dealing with these tensions.     

Smart cities & citizen discontent: A systematic review of the literature

Governments across the world are experimenting with smart city technologies but recent studies suggest that not all citizens support this development. However, a comprehensive understanding of citizen discontent with the smart city is missing. This study systematically reviews academic research addressing citizen discontent with the smart city. Based on a set of 58 articles, two perspectives on citizens' discontent are identified. One perspective focuses on active discontent: citizens are dissatisfied with the technology, democratic process, and societal impact of the smart city and show different types of behavior to express their discontentment. The other perspective emphasizes passive discontent: citizen discontent does not manifest itself due to citizens' lack of awareness and skills and the absence of channels to express their discontentment. Both perspectives on discontent suggest different government responses respectively to overcome citizen discontent through ‘the right technologies’, ‘the right rules’, and ‘the right information’, or to stimulate critical citizenship through ‘the right to smart city education and empowerment’ and the ‘right to participate and challenge’. Based on our findings, a fine-grained understanding of attitudes and behavior, and government actions to address citizen discontent is developed.     

Artificial intelligence for the public sector: results of landscaping the use of AI in government across the European Union

Artificial Intelligence is increasingly being used by public sector organisations. Previous research highlighted that the use of AI technologies in government could improve policy making processes, public service delivery and the internal management of public administrations. In this article, we explore to which extent the use of AI in the public sector impacts these core governance functions. Findings from the review of a sample of 250 cases across the European Union, show that AI is used mainly to support improving public service delivery, followed by enhancing internal management and only in a limited number assist directly or indirectly policy decision-making. The analysis suggests that different types of AI technologies and applications are used in different governance functions, highlighting the need to further in-depth investigation to better understand the role and impact of use in what is being defined the governance “of, with and by AI”.     

Government Digital Transformation: Understanding the Role of Government Social Media

Government social media has been integrated as part of the government administrative tools to improve public service and promote public goals. However, the current government information literature is limited to understanding government social media adoption and its purpose for political marketing. The present study seeks to understand the role of government social media in promoting government digital initiatives (i.e., government-backed digital currency). The study validated the inter-relationships between government social media effort, privacy concerns, trust in technology, reachability, and citizens' participation in government-initiated digital innovations. A total of 505 responses from Chinese citizens were collected through an online self-administered questionnaire survey, and the data was submitted to a two-stage Partial Least Squares Structural Equation Modelling-Artificial Neural Network analysis. The analytic results revealed that privacy concerns, trust in technology, and reachability positively influence digital participation. In addition, the information quality and perception of trust in government social media have significant positive influences on government social media engagement. The study provides strategic practical suggestions to government agencies in effectively utilizing social media as a communication platform to foster citizens' participation in government's digital initiatives.     

Orchestrating artificial intelligence for urban sustainability

Artificial intelligence (AI) is regarded as the next digital frontier in government, with many potential applications for economic development as well as sustainable urbanization. Governments have started experimenting with AI, but empirical research on how to leverage and implement AI remains limited. This study analyzed two cases of AI implementation in a large city and identified various AI capabilities useful for government. More importantly, purposeful orchestration of AI-related resources such as data, knowledge, algorithms, and information systems is necessary for developing strong AI capabilities. The findings indicate two different types of orchestration: policy-driven orchestration focuses on the integration of resources, while innovation-driven orchestration focuses on triangulation. This study contributes to the growing body of knowledge on AI in government by revealing and conceptualizing different paths and approaches to AI implementation. They also serve to inform practitioners' planning of AI implementation.     

Government Information Locator System and Government Information Management in the United States

20世纪90年代中期以后,随着电子政府服务的发展,美国联邦政府一些跨机构工作小组开始致力于政府信息定位服务(GILS)的相关调查研究,并在大量合作项目的基础上构建起联邦政府的GILS框架。此后,美国各州政府和机构也在此基础上探索构建了各具特色的GILS服务。GILS现已逐渐融合到美国电子政府整体建设之中,不仅通过因特网为公民提供政府数字信息,而且还可提供广泛的政府服务。各种类型的GILS服务之间的交流与合作也在积极展开。     

Multichannel marketing: An experiment on guiding citizens to the electronic channels

Governments have a variety of channels at their disposal to help them interact with their citizens. Having realized that citizens still prefer the traditional channels, governments are now focusing on ways to lead them to the web. Previously, we have shown that citizens prefer the use of soft instruments, such as communication. Communication instruments are characterized by the transfer of information from government to citizens, for example, by means of mass media or a letter. This study focuses on how a communication instrument—in this case a personal letter—can be used to lead citizens to the digital channel. We also show the effects of the instrument both in terms of channel usage and citizen perceptions. Based on a field experiment, carried out in cooperation with a Dutch national government agency, we show that unobtrusive channel marketing can be effectively used to increase usage of government e-services, without negatively affecting citizens' current level of satisfaction with service delivery.     

Channel choice and public service delivery in Canada: Comparing e-government to traditional service delivery

This study examines channel choice and public service delivery in Canada, comparing e-government to traditional service delivery channels such as the phone or visiting a government office. Factors studied include the digital divide, the nature of the citizen interaction with government, public service values, and satisfaction with services received by citizens. These factors are used to determine whether they impacted choice of channel and satisfaction with that channel. This study, through logistic regression of a public opinion survey of Canadian residents, found indications suggesting a digital divide in accessing e-government; found that government websites were most commonly used for information purposes, while the phone was most commonly used to solve problems. In regards to citizens' satisfaction, the apparent digital divide was bridged when females and older Canadians were more satisfied with their contact with a government website. In addition, a positive experience with service delivery and positive public service values lead to greater website satisfaction. The results of this study imply that the phone is a more effective service channel for solving problems, and the website is more effective for getting information. Therefore, governments need to provide multiple contact channels for citizens, depending upon their task at hand, while ensuring consistency of information and service response across channels. Creating a positive experience for citizens when they received a service translates into a more satisfied experience with e-government.     

Artificial Intelligence for data-driven decision-making and governance in public affairs

Literature shows there is a growing interest in studies involving Artificial Intelligence (AI) in the public sector; and while there is evidence of many governmental initiatives that have been established to harness the power of AI, empirical research on the topic and evidence-based insights are rather lacking. The aim of this Special Issue on Artificial Intelligence for Data-Driven Decision-Making and Governance in Public Affairs is to extend both the theoretical and practical boundaries of AI research in the public sector in order to improve governmental decision-making and governance, thus enhancing public value creation. The papers in this special issue focus on AI risks and guidelines, AI governance, the risks of governmental implementation of AI to citizens' privacy, increasing citizen satisfaction through AI-enabled government services, the enablers and challenges of AI implementation in specific public sectors, and using AI to study political opinion. These papers not only advance our knowledge and understanding of the use of AI in government and public governance, but they also help to set out a renewed research agenda. Future research should, among other things, focus on inter- and multi-disciplinary empirical studies that call for the collaboration of a variety of stakeholders; on the longitudinal dynamics of creating public value through the breadth and depth of AI assimilation; and on the investigation of the ethical challenges (particularly data privacy) in AI implementation.