Public Sector Applications Research Articles

Security Audit of The Public Sector Application Using COBIT 5 and ITIL V4 Framework

The use of information system-based applications has become commonplace in various sectors, including government agencies such as the Social Service and hundreds of villages in North Lampung. One of the applications used is SIKS-NG (Social Welfare Information System - Next Generation) which aims to facilitate the management of population data and community welfare programs. However, along with technological developments, data security is increasingly important to pay attention to. Cybercrime attacks, data leaks, and privacy violations are threats that must be taken seriously. The aim of this final assignment is to determine the extent of the security of the SIKS-NG application based on the results of COBIT 5 and ITIL V4 calculations and provide recommendations for improvements to increase information system security. The method used is the COBIT 5 and ITIL V4 method using the Align, Plan and Organize (APO13), Deliver, Support and Service (DSS05), Investment Management (IM14) domains. Data analysis uses the Capability Level, Maturity Level and Linkert Scale methods. The results of this research show that the Capability Level for the APO13 subdomain process obtained an average of 4.24 with a Gap of -0.24, DSS05 obtained an average value of 4.20 with a Gap of -0.20. From the overall results, the APO13 and DSS05 subdomain framework is at level 4 and has a Gap of -O.22, which means that at this level it shows that this subdomain has been achieved and fulfilled. Meanwhile, the Maturity Level for the IM13 subdomain process is on Scale 4 with an average value of 4.17 with a Gap of 0.83, which means it has not reached the target as expected. So this means that the security of the SIKS-NG application information system has the status of being well managed and must continue to be optimized, it's just that the program performance must be repaired and improved further. Keywords— System Security, COBIT 5, ITIL V4, Capability Level, Maturity Level

The Roles of Big Data for Supporting E-Government Application and Usage in Public Sector, Dubai

The Roles of Big Data for Supporting E-Government Application and Usage in Public Sector, Dubai

The uneven deployment of algorithms as tools in government: evidence from the use of an expert system

Abstract While governments have long discussed the promise of delegating important decisions to machines, actual use often lags. Consequently, we know little about the variation in the deployment of such delegations in large numbers of similar governmental organizations. Using data from crime laboratories in the United States, we examine the uneven distribution over time of a specific, well-known expert system for ballistics imaging for a large sample of local and regional public agencies; an expert system is an inference engine joined with a knowledge base. Our statistical model is informed by the push-pull-capability theory of innovation in the public sector. We test hypotheses about the probability of deployment and provide evidence that the use of this expert system varies with the pull of agency task environments and the enabling support of organizational resources—and that the impacts of those factors have changed over time. Within this context, we also present evidence that general knowledge of the use of expert systems has supported the use of this specific expert system in many agencies. This empirical case and this theory of innovation provide broad evidence about the historical utilization of expert systems as algorithms in public sector applications.

E-Government in Nigeria: Can Generative AI Serve as a Tool for Civic Engagement?

This paper examines the potential for using generative artificial intelligence (AI) to boost civic participation in Nigeria’s developing e-government ecosystem. Emerging generative technologies like ChatGPT demonstrate intriguing capabilities to make governance more interactive and engaging through conversational interfaces. Thoughtfully implemented AI tools could increase access and understanding of e-government, particularly for underserved groups. However, risks around bias, privacy, security and capability limitations pose challenges for public sector applications. Additionally, Nigeria’s substantial digital divides and defective trust in government institutions hamper e-government participation currently. This paper analyses opportunities and limitations for applying generative AI to advance civic engagement given Nigeria’s unique socio-cultural context. Findings suggest that while AI holds promise, targeted strategies focused on inclusion, accessibility, education and institutional legitimacy building are critical to realise benefits. Cautious optimism, human-centric design and responsible governance frameworks are needed to employ generative systems successfully. If challenges are addressed, AI could open innovative possibilities for energising civic participation. But further research and controlled pilot applications are required to determine optimal implementation.

Advancing the frontiers of genomic public administration: From genetics to administrative attitudes, behaviors, and practices

AbstractBiology's increasing applicability to the social sciences can inspire new approaches to public administration research and practice. Drawing on advances in behavioral genetics, genomic public administration may push its frontiers by examining the genetic foundations of administrative behaviors. While public administration scholars have pioneered the use of the twin design to assess the heritability of public sector employment and public service motivation, they may also use molecular genetics to explore how specific genes interact with environmental factors to shape administrative attitudes, traits, and behaviors. We highlight how relevant studies in management and political science may serve as models for similar explorations in public administration. We also outline four research agendas for genomic public administration. In addition to complementing traditional public administration theory by examining the genetic roots of administrative behaviors and practices, genomic public administration may enrich genetic inquiries by adding public sector applications.

Integrating Reward Maximization and Population Estimation: Sequential Decision-Making for Internal Revenue Service Audit Selection

We introduce a new setting, optimize-and-estimate structured bandits. Here, a policy must select a batch of arms, each characterized by its own context, that would allow it to both maximize reward and maintain an accurate (ideally unbiased) population estimate of the reward. This setting is inherent to many public and private sector applications and often requires handling delayed feedback, small data, and distribution shifts. We demonstrate its importance on real data from the United States Internal Revenue Service (IRS). The IRS performs yearly audits of the tax base. Two of its most important objectives are to identify suspected misreporting and to estimate the "tax gap" -- the global difference between the amount paid and true amount owed. Based on a unique collaboration with the IRS, we cast these two processes as a unified optimize-and-estimate structured bandit. We analyze optimize-and-estimate approaches to the IRS problem and propose a novel mechanism for unbiased population estimation that achieves rewards comparable to baseline approaches. This approach has the potential to improve audit efficacy, while maintaining policy-relevant estimates of the tax gap. This has important social consequences given that the current tax gap is estimated at nearly half a trillion dollars. We suggest that this problem setting is fertile ground for further research and we highlight its interesting challenges. The results of this and related research are currently being incorporated into the continual improvement of the IRS audit selection methods.

The state’s role in governing artificial intelligence: development, control, and promotion through national strategies

Numerous governments worldwide have issued national artificial intelligence (AI) strategies in the last five years to deal with the opportunities and challenges posed by this technology. However, a systematic understanding of the roles and functions that the governments are taking is lacking in the academic literature. Therefore, this research uses qualitative content analysis and Latent Dirichlet Allocation (LDA) topic modeling methodologies to investigate the texts of 31 strategies from across the globe. The findings of the qualitative content analysis highlight thirteen functions of the state, which include human capital, ethics, R&D, regulation, data, private sector support, public sector applications, diffusion and awareness, digital infrastructure, national security, national challenges, international cooperation, and financial support. We combine these functions into three general themes, representing the state’s role: development, control, and promotion. LDA topic modeling results are also reflective of these themes. Each general theme is present in every national strategy’s text, but the proportion they occupy in the text is different. The combined typology based on two methods reveals that the countries from the post-soviet bloc and East Asia prioritize the theme “development,” highlighting the high level of the state’s involvement in AI innovation. The countries from the EU focus on “control,” which reflects the union’s hard stance on AI regulation, whereas countries like the UK, the US, and Ireland emphasize a more hands-off governance arrangement with the leading role of the private sector by prioritizing “promotion.”

Assessing Brunei Darussalam Public and Private Sector Readiness Towards Big Data Application

This exploratory study aims to assess and investigate Brunei Darussalam’s readiness in developing and applying big data technologies for its public and private sectors, using Social, Technological, Environmental and Policy (STEP) framework. The results show that the population are digitally literate (Social) and utilises smart devices as well as internet network connectivity that is widely offered by the local telecommunications company (Technology). The government of Brunei Darussalam established multiple digital transformation initiatives including implementation of 5G connectivity as well as digital economy masterplan to digitally transformed in the near future (Environment). Regardless of the absence of national digital data privacy policy (Policy) in Brunei, the recent nation’s successful big data application in public sector – BruHealth Application – to contain Covid-19 community spread was achieved. Alas, the existence of such policy in the near future will create opportunities for the local private sectors to capitalise big data technologies to their business strategies.

Issues in Requirements Specification in Malaysia’s Public Sector: An Evidence from a Semi-Structured Survey and a Static Analysis

Requirement specifications (RS) are essential and fundamental artefacts in system development. RS is the primary reference in software development and is commonly written in natural language. Bad requirement quality, such as requirement smells, may lead to project delay, cost overrun, and failure. Focusing on requirement quality in the Malaysian government, this paper investigates the methods for preparing Malay RS and personnel competencies to identify the root cause of this issue. We conducted semi-structured interviews that involved 17 respondents from eight critical Malaysian public sector agencies. This study found that ambiguity, incompleteness, and inconsistency are the top three requirement smells that cause project delays and failures. Furthermore, based on our static analysis, we collected the initial Malay RS documents from various Malaysian public sector agencies; we found that 30% of the RS were ambiguous. Our analysis also found that respondents with more than 10 years of experience could manually identify the smells in RS. Most respondents chose the Public Sector Application Systems Engineering (KRISA) handbook as a guideline for preparing Malay RS documents. Respondents acknowledged a correlation between the quality of RS and project delays and failures.

Rankıng value-creatıng green approach practıces and choosıng ıdeal green marketıng strategy for logıstıcs companıes

The deterioration of environmental factors, economic and technological development, the formation of complexity in societies, the rise of complex structures have made the environment and green management practices more important. Especially value-creating green approaches are considered as critical components in both public and private sector applications and defined as indicators of success in terms of sustainability. On the other hand, green marketing strategies are also important practices that have a positive impact on the environment and should be carefully emphasized for the inheritance of nature to future generations. Recently, it has been on the agenda quite a lot and it is understood for all sectors.In this study, it is aimed to determine the criteria for value-creating green approach practices in logistics companies operating in the TR A1 region due to the above mentioned importance and to choose the most ideal green marketing strategy. In solving this problem, Multi Criteria Decision Making (MCDM) methods, which are a complex decision-making method, have been used. According to the results of the research, it was determined that the most important criterion in value creating green approach applications as Environmental Focused Strategic Decisions (C3), and the least important criterion as Environmental Life Cycle Analysis (C2). It has been determined that the most ideal green marketing strategy is Green Innovation (A1). Accordingly the importance of the environmental based strategic decisions is revealed in terms of creating green marketing strategy for companies.

Assessing Brunei Darussalam Public and Private Sector Readiness Towards Big Data Application

This exploratory study aims to assess and investigate Brunei Darussalam’s readiness in developing and applying big data technologies for its public and private sectors, using Social, Technological, Environmental and Policy (STEP) framework. The results show that the population are digitally literate (Social) and utilises smart devices as well as internet network connectivity that is widely offered by the local telecommunications company (Technology). The government of Brunei Darussalam established multiple digital transformation initiatives including implementation of 5G connectivity as well as digital economy masterplan to digitally transformed in the near future (Environment). Regardless of the absence of national digital data privacy policy (Policy) in Brunei, the recent nation’s successful big data application in public sector – BruHealth Application – to contain Covid-19 community spread was achieved. Alas, the existence of such policy in the near future will create opportunities for the local private sectors to capitalise big data technologies to their business strategies.

Machine-Learning-Enabled Intrusion Detection System for Cellular Connected UAV Networks

The recent development and adoption of unmanned aerial vehicles (UAVs) is due to its wide variety of applications in public and private sector from parcel delivery to wildlife conservation. The integration of UAVs, 5G, and satellite technologies has prompted telecommunication networks to evolve to provide higher-quality and more stable service to remote areas. However, security concerns with UAVs are growing as UAV nodes are becoming attractive targets for cyberattacks due to enormously growing volumes and poor and weak inbuilt security. In this paper, we propose a UAV- and satellite-based 5G-network security model that can harness machine learning to effectively detect of vulnerabilities and cyberattacks. The solution is divided into two main parts: the model creation for intrusion detection using various machine learning (ML) algorithms and the implementation of ML-based model into terrestrial or satellite gateways. The system identifies various attack types using realistic CSE-CIC IDS-2018 network datasets published by Canadian Establishment for Cybersecurity (CIC). It consists of seven different types of new and contemporary attack types. This paper demonstrates that ML algorithms can be used to classify benign or malicious packets in UAV networks to enhance security. Finally, the tested ML algorithms are compared for effectiveness in terms of accuracy rate, precision, recall, F1-score, and false-negative rate. The decision tree algorithm performed well by obtaining a maximum accuracy rate of 99.99% and a minimum false negative rate of 0% in detecting various attacks as compared to all other types of ML classifiers.

Public Choice Theory: Its Application and Challenges in Public-Sector

This paper deals with the application and challenges of Public Choice Theory (PCT) in public-sector. The public-sector plays foundational roles in social change. Citizens and customers perception and expectation of the government is increasing. They are pressurizing the public-sector more than ever before. Hence, I analyzed, critiqued, and contrasted PCT in terms of contemporary authors for performance efficiency and quality in the public-sector. The application of PCT in public-sector seemed more challenging than the application of the theory in private-sector. In transferring concepts and applications to the public-sector, it requires developing principles and tools for the less competitive and a different context of this sector. The article gave a critical overview of the different definitions, ideas, principles of the PCT, and improvement as applied in the public-sector to bring about quality public service and good governance. This paper based on the overall review of literature, such as relevant books, journals, articles, research results, newspapers, and web pages attempted to identify the challenges and remedies of enhancing service effectiveness and quality in public-sector and the study found out that the PCT is not universally applicable in the public-sector. Keywords: Public choice theory, Public-Sector, new public management, quality service, customer, citizen. DOI: 10.7176/JAAS/66-02 Publication date: July 31 st 2020

Climate-related financial disclosures in the public sector

Expectations for the Task Force on Climate-related Financial Disclosure’s framework to drive climate action in the private sector are high, and there is growing interest in its relevance for guiding public sector climate action. However, consideration of the framework’s limitations is critical prior to public sector application.

L’innovation gouvernementale comme moteur de la modernisation de l’administration publique algérienne

L’innovation gouvernementale constitue une piste privilégiée de résolution des problèmes rencontrés par le secteur public en perspective de sa modernisation. Cet article s’intéresse à l’innovation comme moteur de modernisation durable dans les organisations publiques, et ce, précisément au regard de l’expérience de mise en place de la plateforme de collaboration et de participation gouvernementale au Québec, qui semble réunir les préalables, les outils et les mécanismes nécessaires à son application dans le secteur public Algérien. Sur la base d’une approche qualitative et au moyen d’une démarche d’analyse processuelle, l’étude montre, à travers le cas de l’organisation publique algérienne, que cette innovation regroupe les instruments et mécanismes permettant son intégration comme moteur de modernisation de l’administration d’un pays émergent. Codes JEL : H83, O30, O31, O32, O33, O38

Using the security triad to assess blockchain technology in public sector applications

This conceptual paper explores the impact of blockchain technology on public sector processes through the lens of information security. It includes an overview of the evolution of e-government, a synopsis of existing applications of blockchain technology, and innovative blockchain developments. We utilize the Confidentiality-Integrity-Accessibility (CIA) triad to guide our discussion of the security, governance, and regulatory implications of this technology. Leveraging the CIA triad model, we provide context for public managers who may consider blockchain technologies, and we highlight certain advantages arising from the “non-reputability” of distributed ledgers.In particular, we highlight the advantages of blockchain technologies with regards to non-reputability to help public managers understand how to best leverage blockchain technology to transform operations.

Mapping potential impact areas of Blockchain use in the public sector

While the financial sector was the first to investigate the potential of Blockchain, and in more general terms, Distributed Ledger Technology (DLT), with an initial focus on digital currencies including cryptocurrencies such as Bitcoin and Ether, the study of potential uses of this technology is gradually expanding to also include other areas of application including public-sector applications. Academic and non-academic publications on the subject have so far burgeoned mainly in and around the so-called fintech (financial technology) area, a fact that is underlined by a surprisingly high number of literature reviews already performed in this relatively novel area of research. For the public sector and the study domain of Digital Government, Blockchain and DLT have remained under-researched topics, and the number of respective publications is still relatively low. The aim of this meta-level literature study is to map the existing Blockchain and DLT-related body of knowledge and link its prevalent concepts to known needs and requirements studied in the context of the public sector and in Digital Government. Among the concepts, which intersect the existing literature on Blockchain strongly with the public sector-related research and practice, the study found cost reduction, innovation, regulation, taxation, security, privacy, transparency, among others, all of which deserve increased attention from scholars active in the domain of Digital Government research.

Project management: peculiarities of key concepts and application in public sector

Project management: peculiarities of key concepts and application in public sector

A Pathway to the Athermal Impact Initiation of Energetic Azides

Energetic materials (explosives, propellants, and pyrotechnics) are used in a broad range of public and private sector applications. The design of novel, safe materials is therefore of critical imp...

Artificial Intelligence and the Public Sector—Applications and Challenges

ABSTRACT Advances in artificial intelligence (AI) have attracted great attention from researchers and practitioners and have opened up a broad range of beneficial opportunities for AI usage in the public sector. Against this background, there is an emerging need for a holistic understanding of the range and impact of AI-based applications and associated challenges. However, previous research considers AI applications and challenges only in isolation and fragmentarily. Given the lack of a comprehensive overview of AI-based applications and challenges for the public sector, our conceptual approach analyzes and compiles relevant insights from scientific literature to provide an integrative overview of AI applications and related challenges. Our results suggest 10 AI application areas, describing their value creation and functioning as well as specific public use cases. In addition, we identify four major dimensions of AI challenges. We finally discuss our findings, deriving implications for theory and practice and providing suggestions for future research.