Digital government transformation as an organizational response to the COVID-19 pandemic

Many public organizations struggle to adapt to digital transformation. Whereas previous research has identified internal drivers of change, an unpredictable factor from the external environment such as the COVID-19 pandemic can trigger public innovation. In this study, we aim to investigate if and how the COVID-19 pandemic has influenced the digital government transformation. In more detail, we explore how the COVID-19 pandemic has affected different organizational aspects that are expected to be affected by a digital transformation. Findings from case studies of ten organizations from the Austrian federal administration indicate that the pandemic has not only led to an increased use of technological means but also influenced various organizational aspects such as employees' attitudes toward technology and organizational culture toward innovation. In particular, organizations heavily affected by the pandemic have benefited from a greater degree of digital transformation. Consequently, the pandemic has influenced a spirit of innovation and accelerated the speed of digital transformation.     

Implementing challenges of artificial intelligence: Evidence from public manufacturing sector of an emerging economy

The growing Artificial Intelligence (AI) age has been flooded with several innovations in algorithmic machine learning that may bring significant impacts to industries such as healthcare, agriculture, education, manufacturing, retail etc. But challenges such as data quality, privacy and lack of a skilled workforce limit the scope of AI implementation in emerging economies, particularly in the Public Manufacturing Sector (PMS). Therefore, to enhance the body of relevant literature, this study examines the existing challenges of AI implementation in PMS of India and explores the inter-relationships among them. The study has utilized the DEMATEL method for identification of the cause-and-effect group factors. The findings reveal that poor data quality, managers' lack of understanding of cognitive technologies, data privacy, problems in integrating cognitive projects and expensive technologies are the main challenges for AI implementation in PMS of India. Moreover, a model is proposed for industrial decision-makers and managers to take appropriate decisions to develop intelligent AI enabled systems for manufacturing organizations in emerging economies.     

Enabling AI capabilities in government agencies: A study of determinants for European municipalities

Artificial Intelligence (AI) is gradually becoming an integral part of the digital strategy of organizations. Yet, the use of AI in public organizations in still lagging significantly compared to private organizations. Prior literature looking into aspects that facilitate adoption and use of AI has concentrated on challenges concerning technical aspects of AI technologies, providing little insight regarding the organizational deployment of AI, particularly in public organizations. Building on this gap, this study seeks to examine what aspects enable public organizations to develop AI capabilities. To answer this question, we built an integrated and extended model from the Technology-Organization-Environment framework (TOE) and asked high-level technology managers from municipalities in Europe about factors that influence their development of AI capabilities. We collected data from 91 municipalities from three European countries (i.e., Germany, Norway, and Finland) and analyzed responses by means of structural equation modeling. Our findings indicate that five factors – i.e. perceived financial costs, organizational innovativeness, perceived governmental pressure, government incentives, regulatory support – have an impact on the development of AI capabilities. We also find that perceived citizen pressure and perceived value of AI solutions are not important determinants of AI capability formation. Our findings bear the potential to stimulate a more reflected adoption of AI supporting managers in public organizations to develop AI capabilities.     

Breaking the chain: Governmental frugal innovation in Kerala to combat the COVID-19 pandemic

As the COVID-19 pandemic causes unprecedented disruptions in citizens' lives and work, prompting a wide range of responses from governments across the globe. The southern Indian state of Kerala, India's COVID-19 “ground zero”, stands out with a fatality rate at a fraction of other richer Indian states and countries. This has happened despite the state presenting strong vulnerabilities to COVID-19. Using the theoretical lens of frugal innovation, I analyse how the Kerala State Government (KSG) combated the spread of COVID-19. This research uncovers the mechanisms at play as KSG implemented and used frugal technologies as platforms that helped decision making and strategy to fight the pandemic. I find a rich interplay of frugal innovations promoted by the government, in partnership with research institutes and private sector actors, which are cheap and efficacious. The study defines and promotes the concept of government frugal innovation (GFI) and provides valuable insights and tools to help governments navigate and effectively respond to this crisis, encouraging the rest of the world to learn from Kerala's experience. My conceptual model characterizes GFI as involving collaborative aspects, and holds practical implications beyond the times of crises.     

COVID-19 Evidence Reviews website: a VA effort to catalog and curate COVID-19 evidence reviews

Background:The COVID-19 pandemic has sparked a wave of SARS-CoV-2 and COVID-19 research that organizations around the world have been synthesizing in evidence reviews to provide high-quality evidence to support policymakers and clinicians. The urgency of these efforts opens these organizations to the risk of duplicated efforts, which could waste valuable time and resources.Case Presentation:The VA Evidence Synthesis Program (VA ESP) formed a COVID Response Team that launched an online catalog of COVID-19 evidence reviews in March 2020 (https://www.covid19reviews.org/). The goal of this website is to capture the work of evidence synthesis groups in the US and around the world to maximize their collective contributions to patients, frontline clinicians, researchers, and policymakers during the COVID-19 pandemic and avoid duplicating efforts.Conclusions:This ongoing and evolving project provides a helpful catalog of evidence reviews at various stages of production; in addition, the website provides further value with informational icons, review collections, and links to similar resources. The VA ESP will maintain this website to continue to support the needs of policymakers, clinicians, and researchers both within the VA and around the world throughout the COVID-19 pandemic.     

How and where is artificial intelligence in the public sector going? A literature review and research agenda

To obtain benefits in the provision of public services, managers of public organizations have considerably increased the adoption of artificial intelligence (AI) systems. However, research on AI is still scarce, and the advance of this technology in the public sector, as well as the applications and results of this strategy, need to be systematized. With this goal in mind, this paper examines research related to AI as applied to the public sector. A review of the literature covering articles available in five research databases was completed using the PRISMA protocol for literature reviews. The search process yielded 59 articles within the scope of the study out of a total of 1682 studies. Results show a growing trend of interest in AI in the public sector, with India and the US as the most active countries. General public service, economic affairs, and environmental protection are the functions of government with the most studies related to AI. The Artificial Neural Networks (ANN) technique is the most recurrent in the investigated studies and was pointed out as a technique that provides positive results in several areas of its application. A research framework for AI solutions for the public sector is presented, where it is demonstrated that policies and ethical implications of the use of AI permeate all layers of application of this technology and the solutions can generate value for functions of government. However, for this, a prior debate with society about the use of AI in the public sector is recommended.     

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.     

COVID-19 impact on the Chinese top academic libraries: Libraries' response to space,collection and services

In 2020, the COVID-19 pandemic was a major public health emergency on a global scale. The literature regarding the pandemic and its impact on academic libraries is still rising. This article examines the two-year process of developing a flexible service scenario and the broader picture by analyzing data on Chinese top university libraries' programmes and outreach initiatives prior to, during, and the normal COVID-19 pandemic (Sept. 2019–Sept. 2021). COVID-19 is found to have a significant impact on the physical space, collection development, and service of the library, demonstrating the characteristics of space access restricted by security measures, collection digitization, and online service. This research also examines the previous year's initiatives and programmes and discusses the next phase of “new normal” procedures. Hopefully, this study will give insight on how Chinese libraries responded to the recent pandemic, informing libraries' outreach and efforts to be better prepared to take imperative, swift, and decisive action in the post-COVID-19 era and beyond.     

Whether AI adoption challenges matter for public managers? The case of Polish cities

A growing body of literature shows that despite the significant benefits of artificial intelligence (AI), its adoption has many unknowns and challenges. However, theoretical studies dominate this topic. Completing the recent works, this article aims to identify challenges faced by public organizations when adopting AI based on the PRISMA Framework and an empirical assessment of these challenges in the opinion of public managers using survey research. The adopted research procedure is also an added value because it could be replicated in other context scenarios. To achieve this paper's aim, the Systematic Literature Review (SLR) and survey research among authorities in 414 Polish cities were carried out. As a result, a list of 15 challenges and preventive activities proposed by researchers to prevent these challenges have been identified. Empirical verification of identified challenges allows us to determine which of them limit AI adoption to the greatest extent in public managers' opinion. These include a lack of strategy or plans to initial adoption / continued usage of AI; no ensuring that AI is used in line with human values; employees' insufficient knowledge of how to use AI; insufficient AI policies, laws, and regulations; and different expectations of stakeholders and partners about AI. These findings could help practitioners to prioritize AI adoption activities and add value to digital government theory.     

Can AI communication tools increase legislative responsiveness and trust in democratic institutions?

Smart replies, writing enhancements, and virtual assistants powered by artificial intelligence (AI) language technologies are becoming part of consumer products and everyday experiences. This study explores the opportunities and risks of using language-generating AI systems in politics to increase legislative responsiveness. Legislators receive a large volume of constituent communication and often cannot devote individual consideration and timely response to each. Here, AI language technologies may allow legislators to process constituent communication more efficiently. For example, AI writing tools can suggest reply snippets when a staffer responds to a common concern. However, legislative human-AI collaboration could reduce constituent trust or undermine the representative process. In two experiments, we compared constituents' impressions of human-written legislative correspondence to correspondences partially or fully generated by GPT-3, a state-of-the-art language model. Our results suggest that legislative correspondence generated by AI with human oversight may be received favorably and increase constituent trust compared to generic auto-responses that busy legislators may employ. However, poorly performing AI language technologies may damage confidence in the legislator. Our findings highlight the potential and risks of introducing AI-mediated communication to the representation process. We discuss the importance of disclosure, transparency, and maintaining human-in-the-loop accountability for political deployments of AI language technologies.     

Virtual healthcare in the new normal: Indian healthcare consumers adoption of electronic government telemedicine service

Digital healthcare is in the spotlight due to the prevailing COVID-19 situation. To get the deeper understanding of the healthcare consumers' adoption of e-government telemedicine service (EGTMS), the present research extends the unified model of e-government adoption (UMEGA) with perceived severity, self-efficacy, and political trust. The extended UMEGA model is empirically validated with 452 valid Indian healthcare consumers' responses. The findings reported that performance expectancy, perceived severity, effort expectancy, and perceived risk significantly influenced Indian healthcare consumers' attitudes towards EGTMS. Further political trust showed significant influence over social influence. However, social influence is observed as non-significant. Furthermore, attitude, political trust and facilitating conditions significantly influenced individuals' behavioral intentions towards EGTMS and observed significant influence of self-efficacy on effort expectancy. This is the first study that reveals the critical factors of Indian healthcare consumers' behavioral intention towards EGTMS. With the upsurge in e-government healthcare services, the outcomes of the study will benefit stakeholders such as governmental agencies, marketers, public administrators, and healthcare professionals as they provide suitable strategic recommendations to design and implement e-government telemedicine services.     

Health sciences librarian research and instruction services in pandemic information environments

This study examined research and instruction services provided by academic health sciences librarians in the United States during the COVID-19 pandemic. A total of 205 respondents (N = 205) completed an anonymous online survey about academic health sciences librarian involvement in providing research and instruction services during the global pandemic. In-depth literature searching services (86%, n = 176), curated COVID-19 research through guides (66%, n = 135), and systematic review consultations (53%, n = 109) were reported as the top three research services in demand. Librarians supported online teaching and learning at their institutions by providing online instruction for a course (92%, n = 189), facilitating access to licensed resources (73%, n = 150), and identifying open access and open educational resources (62%, n = 127). Overall, this study contributes to understanding pandemic-responsive academic library services to meet the unique needs of health sciences education and research in evolving COVID-19 pandemic information environments.     

2020年中国图书情报与档案管理领域研究热点回顾

[目的/意义]本文旨在系统综述中国图情档学界在2020年的核心研究热点。[方法/过程]论文采用内容分析法,通过文本编码发现热点集中表现在新冠疫情下的信息管理,国家重大战略中的信息管理,新技术、新事业与新文科三个方面。[结果/结论]作者认为2020年本领域学术研究呈现出三个特点:对重大危机的关切前所未有,响应国家重大战略需求的意识与行动形成合力,学科百年荣耀与未来险阻并存。     

Employees' intentions toward complying with information security controls in Saudi Arabia's public organisations

Ensuring employees' compliance with information security controls is a major challenge experienced by the management of information security in organisations. While the investment in information security has been increased recently, many organisations around the world have failed to avoid security threats and data breaches because of noncompliant employees. This study proposes a model to explore employees' differences and identifies the factors that can shape their perceptions and intentions toward compliance. The model was examined and validated in a Saudi Arabian government organisation using partial least square structural equation modelling. The results of this study support the validity of the research model and disclose the factors that have a significant influence on employees' intentions toward compliance, particularly in Saudi Arabia's public organisations. To the best of our knowledge, this is the first study to investigate employees' perceptions and intentions toward complying with information security controls in public organisations across all regions of Saudi Arabia. The study contributes to the information security management domain in terms of the model's validity, which can be used to explore the influence of the identified factors on employees' perceptions and intentions toward complying with information security controls in different cultural and environmental contexts.     

Mapping the challenges of Artificial Intelligence in the public sector: Evidence from public healthcare

The nascent adoption of Artificial Intelligence (AI) in the public sector is being assessed in contradictory ways. But while there is increasing speculation about both its dangers and its benefits, there is very little empirical research to substantiate them. This study aims at mapping the challenges in the adoption of AI in the public sector as perceived by key stakeholders. Drawing on the theoretical lens of framing, we analyse a case of adoption of the AI system IBM Watson in public healthcare in China, to map how three groups of stakeholders (government policy-makers, hospital managers/doctors, and Information Technology (IT) firm managers) perceive the challenges of AI adoption in the public sector. Findings show that different stakeholders have diverse, and sometimes contradictory, framings of the challenges. We contribute to research by providing an empirical basis to claims of AI challenges in the public sector, and to practice by providing four sets of guidelines for the governance of AI adoption in the public sector.     

Health informatics publication trends in Saudi Arabia: a bibliometric analysis over the last twenty-four years

Objective:Understanding health informatics (HI) publication trends in Saudi Arabia may serve as a framework for future research efforts and contribute toward meeting national “e-Health” goals. The authors’ intention was to understand the state of the HI field in Saudi Arabia by exploring publication trends and their alignment with national goals.Methods:A scoping review was performed to identify HI publications from Saudi Arabia in PubMed, Embase, and Web of Science. We analyzed publication trends based on topics, keywords, and how they align with the Ministry of Health''s (MOH''s) “digital health journey” framework.Results:The total number of publications included was 242. We found 1 (0.4%) publication in 1995–1999, 11 (4.5%) publications in 2000–2009, and 230 (95.0%) publications in 2010–2019. We categorized publications into 3 main HI fields and 4 subfields: 73.1% (n=177) of publications were in clinical informatics (85.1%, n=151 medical informatics; 5.6%, n=10 pharmacy informatics; 6.8%, n=12 nursing informatics; 2.3%, n=4 dental informatics); 22.3% (n=54) were in consumer health informatics; and 4.5% (n=11) were in public health informatics. The most common keyword was “medical informatics” (21.5%, n=52). MOH framework–based analysis showed that most publications were categorized as “digitally enabled care” and “digital health foundations.”Conclusions:The years of 2000–2009 may be seen as an infancy stage of the HI field in Saudi Arabia. Exploring how the Saudi Arabian MOH''s e-Health initiatives may influence research is valuable for advancing the field. Data exchange and interoperability, artificial intelligence, and intelligent health enterprises might be future research directions in Saudi Arabia.     

Managing Remote Projects Effectively with an Action Dashboard

Abstract

During the early stages of the COVID-19 pandemic, the College’s library, learning center, & archives and the office of institutional research & training (OIRT), along with all departments of our college, shifted to working from home (WFH) during the COVID-19 pandemic. As we continue to work from home, in this column we share with you a follow-up to our previous column, specifically what worked and didn’t work in regards to the techniques and tools we continue to use to manage our staff remotely with communication tools (Slack, Zoom Calls, FlipGrid) and a project management tool (Notion) during the early stages of the pandemic. We added a new technique to the mix since our last publication—an Action Dashboard in Notion, and describe how we built it, and our plans for next steps using Notion as a comprehensive project management tool moving forward.     

Digital government transformation in turbulent times: Responses,challenges, and future direction

We are living in turbulent times, with the threats of COVID-19 and related social conflicts. Digital transformation is not an option but a necessity for governments to respond to these crises. It has become imperative for governments worldwide to enhance their capacity to strategically use emerging digital technologies and develop innovative digital public services to confront and overcome the pandemic. With the rapid development of digital technologies, digital government transformation (DGT) has been legitimated in response to the pandemic, contributing to innovative efficacy, but it also has created a set of challenges, dilemmas, paradoxes, and ambiguities. This special issue’s primary motive is to comprehensively discuss the promises and challenges DGT presents. It focuses on the nature of the problems and the dilemmatic situation in which to use the technologies. Furthermore, it covers government capacity and policy implications for managerial and institutional reforms to respond to the threats and the uncertainty caused by disruptive digitalization in many countries. To stimulate discussion of the theme of this special issue, this editorial note provides an overview of previous literature on DGT as a controlling measure of the pandemic and the future direction of research and practice on DGT.