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World
Special Issues
Data-Driven Strategic Approaches to Public Management
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Data-Driven Strategic Approaches to Public Management

A special issue of World (ISSN 2673-4060).

Deadline for manuscript submissions: 28 February 2026 | Viewed by 8547

Special Issue Editors

Prof. Dr. Sotirios Bersimis

E-Mail Website
Guest Editor
Department of Business Administration, University of Piraeus, 18534 Piraeus, Greece
Interests: business analytics; statistical machine learning; statistical monitoring; public health monitoring; environmental moni-toring
Dr. Andreas Fousteris

E-Mail Website
Guest Editor
Department of Business Administration, University of Piraeus, 18534 Piraeus, Greece
Interests: technology systems; environmental management; technology and innovation management; business plans and feasibility studies; energy management; public economics
Prof. Dr. Dimitrios A. Georgakellos

E-Mail Website
Guest Editor
Department of Business Administration, University of Piraeus, 18534 Piraeus, Greece
Interests: technology systems; environmental management; technology and innovation management; business plans and feasibility studies; energy management
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Data-driven strategic approaches to public management are related to the application of data-driven methodologies such as Data Analytics (DA), Statistical Learning (SL), and Artificial Intelligence (AI) in the field of public administration and governance. Data-driven strategic approaches to public management aim to enhance the efficiency, effectiveness, and responsiveness of government agencies by leveraging the power of data and analytics. By making informed decisions and optimizing resource utilization, governments can better address the needs of their constituents and improve overall governance.

Today, the use of DA, SL, and AI in public management has become increasingly prevalent, offering transformative benefits in terms of efficiency, decision-making, and service delivery. However, it is important to note that while DA, SL, and AI offer numerous benefits, there are also ethical considerations, including privacy concerns, biases in algorithms, and the need for transparency. Implementing these technologies in public management requires careful planning, governance frameworks, and a commitment to ethical practices to ensure responsible and effective use.

In this Special Issue, we aim to collect high-quality studies related to the application of Data-driven strategic approaches to public management (e.g., innovative applications of data-driven methods in public health management, optimizing transportation routes, predicting service demand, and detecting and preventing fraud in public programs). We welcome studies attempting to address global challenges such as public health management, public financial management, climate change monitoring and environmental pollution monitoring, education management, and others. We are also interested in contributions that provide insights into how data analytics can lead to a sustainable society. This collection of studies is expected to help formulate solutions to address the overall challenges and develop interdisciplinary research directions for our advancement to a sustainable world. Empirical or review studies, as well as other acceptable article types, are welcome.

In this Special Issue, original research articles and reviews are welcome. Studies of interest include, but are not limited to, data-driven strategic approaches in the following fields:

  • Predictive analytics for policy planning;
  • Optimizing public service delivery;
  • Fraud detection and prevention in public health;
  • Enhancing public safety;
  • Environmental monitoring and sustainability;
  • Automated decision-making;
  • Data-driven policy evaluation;
  • Citizen engagement and feedback;
  • Healthcare planning and management;
  • Resource optimization;
  • Smart city initiatives;
  • Human resource management;
  • Emergency response and disaster management;
  • Education planning and resource allocation;
  • Social services optimization;
  • Regulatory compliance and monitoring;
  • Economic development and planning;
  • Public transportation optimization;
  • Public health surveillance;
  • Tax revenue optimization;
  • Fraud detection in taxation;
  • Energy consumption optimization;
  • Urban planning and development;
  • Public-private partnerships (PPPs) optimization;
  • Sustainable production management and efficient use of natural resources;
  • Sustainable tourism management;
  • Sustainable management of energy;
  • Sustainable transportation and supply chain;
  • Responsible energy lifestyle patterns;
  • Eco-design and energy-efficient design;
  • Circular economy;
  • Climate-neutral production and consumption.

We look forward to receiving your contributions.

Prof. Dr. Sotirios Bersimis
Dr. Andreas Fousteris
Prof. Dr. Dimitrios A. Georgakellos
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. World is an international peer-reviewed open access quarterly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1200 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • data-driven strategic approaches
  • public management
  • public health
  • public sector efficiency
  • data analytics
  • statistical learning
  • artificial intelligence
  • sustainability

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Published Papers (6 papers)

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Research

18 pages, 396 KiB  
Article
Shadow Economy Drivers in Bosnia and Herzegovina: A MIMIC and SEM Approach
by Bojan Baškot, Ognjen Erić, Dragan Gligorić and Milenko Krajišnik
World 2025, 6(2), 85; https://doi.org/10.3390/world6020085 - 11 Jun 2025
Viewed by 780
Abstract
This study explores the drivers and evolution of the shadow economy in Bosnia and Herzegovina—a transitional, post-conflict country facing persistent institutional fragility. Using the Multiple Indicators and Multiple Causes (MIMIC) model, an extension of Structural Equation Modeling, the paper estimates the size and [...] Read more.
This study explores the drivers and evolution of the shadow economy in Bosnia and Herzegovina—a transitional, post-conflict country facing persistent institutional fragility. Using the Multiple Indicators and Multiple Causes (MIMIC) model, an extension of Structural Equation Modeling, the paper estimates the size and dynamics of the shadow economy from 1996 to 2022. The model integrates macroeconomic indicators (employment rate, GDP per capita, tax revenues) and institutional variables (rule of law, control of corruption), with data primarily sourced from the World Bank. The results show that institutional quality, tax burden, and labor market conditions are significant determinants of the informal sector. The model demonstrates strong statistical validity (CFI = 0.986, RMSEA = 0.05), supported by robustness checks including unit root tests, structural break analysis, and the exclusion of controversial benchmarking methods. The shadow economy responds markedly to major shocks such as the 2008 global financial crisis and the 2014 floods. Findings provide valuable policy insights: strengthening institutions, simplifying tax systems, and encouraging formal labor market participation can significantly reduce informality. The study supports evidence-based reforms to enhance transparency, resilience, and sustainable development in Bosnia and Herzegovina. Full article
(This article belongs to the Special Issue Data-Driven Strategic Approaches to Public Management)
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19 pages, 310 KiB  
Article
Artificial Intelligence and Public Sector Auditing: Challenges and Opportunities for Supreme Audit Institutions
by Dolores Genaro-Moya, Antonio Manuel López-Hernández and Mariia Godz
World 2025, 6(2), 78; https://doi.org/10.3390/world6020078 - 1 Jun 2025
Viewed by 770
Abstract
The application of artificial intelligence (AI) is growing exponentially in public entities, contributing to the improvement of the design and provision of services, as well as to the internal management and efficiency of public institutions. However, the potential of artificial intelligence systems for [...] Read more.
The application of artificial intelligence (AI) is growing exponentially in public entities, contributing to the improvement of the design and provision of services, as well as to the internal management and efficiency of public institutions. However, the potential of artificial intelligence systems for the public sector also entails a set of risks related, among other areas, to privacy, confidentiality, security, transparency or bias and discrimination. The Supreme Audit Institutions (SAIs), when auditing public services and policies, must adapt their human and technological resources to this new scenario. This paper analyses the implications of AI penetration in the public sector, as well as the challenges that these technological developments pose to SAIs to improve effectiveness and efficiency in their auditing tasks. This paper presents a conceptual and exploratory analysis, informed by documentary evidence and case illustrations. Given the dynamic evolution of AI research, the findings should be interpreted as a contribution to ongoing debates, rather than definitive conclusions. It also reviews the status of the audits of systems based on algorithms carried out by some SAIs. Full article
(This article belongs to the Special Issue Data-Driven Strategic Approaches to Public Management)
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17 pages, 2994 KiB  
Article
Similarity and Homogeneity of Climate Change in Local Destinations: A Globally Reproducible Approach from Slovakia
by Csaba Sidor, Branislav Kršák and Ľubomír Štrba
World 2025, 6(2), 68; https://doi.org/10.3390/world6020068 - 15 May 2025
Viewed by 424
Abstract
In terms of climate change, while tourism’s natural resources may be considered climate vulnerable, a large part of tourism’s primary industries are high carbon consumers. With the growth of worldwide efforts to adopt climate resilience actions across all industries, Destination Management Organizations could [...] Read more.
In terms of climate change, while tourism’s natural resources may be considered climate vulnerable, a large part of tourism’s primary industries are high carbon consumers. With the growth of worldwide efforts to adopt climate resilience actions across all industries, Destination Management Organizations could become focal points for raising awareness and leadership among local tourism stakeholders. The manuscript communicates a simple, reproducible approach to observing and analyzing climate change at a high territorial granularity to empower local destinations with the capability to disseminate quantifiable information about past, current, and future climate projections. In relation to Slovakia’s 39 local destinations, the approach utilizes six sub-sets of the latest high-resolution Köppen–Geiger climate classification grid data. The main climate categories’ similarity for local destinations was measured across six periods through the Pearson Correlation Coefficient of Pairwise Euclidean Distances between the linkage matrices of hierarchical clusters adopting Ward’s Linkage Method. The Shannon Entropy Analysis was adopted for the quantification of the homogeneity of the DMOs’ main climate categories, and Weighted Variance Analysis was adopted to identify the main climate categories’ weight fluctuations. The current results indicate not only a major shift from destination climates classified as cold to temperate, but also a transformation to more heterogeneous climates in the future. Full article
(This article belongs to the Special Issue Data-Driven Strategic Approaches to Public Management)
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26 pages, 2776 KiB  
Article
Data-Driven Strategic Approaches to Road Safety Management: Truth and Lies of Official Statistics
by Artur I. Petrov
World 2025, 6(1), 3; https://doi.org/10.3390/world6010003 - 1 Jan 2025
Viewed by 1444
Abstract
Approximately 1.25–1.30 million people die annually in road traffic accidents worldwide, and up to 50 million are injured. The UN General Assembly Resolution 74/229 emphasizes the utmost importance of addressing the issue of reducing road traffic accidents. Achieving the ambitious goal of reducing [...] Read more.
Approximately 1.25–1.30 million people die annually in road traffic accidents worldwide, and up to 50 million are injured. The UN General Assembly Resolution 74/229 emphasizes the utmost importance of addressing the issue of reducing road traffic accidents. Achieving the ambitious goal of reducing road traffic fatalities and injuries by at least 50% during 2021–2030 is associated with numerous challenges, one of which is ensuring the reliability of official statistics. The accuracy of official data in reflecting the actual situation depends on multiple factors: the quality of the data collection and identification system for road accidents, the responsibility of the officials, and, to a significant extent, the willingness and ability of those in charge to present desired outcomes as reality, thereby distorting the relevant statistics. The issue of inaccurate statistical data and its negative impact on subsequent socio-economic management processes has long been recognized. Different countries address this issue with varying degrees of success. Using data on the characteristics of the road traffic accident rate as an example, the problem of statistical data accuracy in Russia and African countries is considered. A comparison of such countries was chosen to illustrate the real problem of the low credibility of official statistical information available for analysis. Unfortunately, the low quality of statistical information does not allow for drawing accurate conclusions about the actual situation in Russia and African countries, and hence, competently and rationally managing socio-economic processes. This conclusion is based both on the analysis of the results of previous studies and on the original statistical analysis of officially available information. Full article
(This article belongs to the Special Issue Data-Driven Strategic Approaches to Public Management)
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16 pages, 1480 KiB  
Article
Assessing Police Technical Efficiency and the COVID-19 Technological Change from the Pact for Life Perspective
by Isloana Karla de França Barros, Thyago Celso Cavalcante Nepomuceno and Fernando Henrique Taques
World 2024, 5(3), 789-804; https://doi.org/10.3390/world5030041 - 23 Sep 2024
Cited by 1 | Viewed by 1505
Abstract
The Pact for Life program was one of Brazil’s most successful initiatives in coping with an elevated incidence of deliberate lethal violent crimes (CVLI) within the jurisdiction of Pernambuco. It delineated the state into 26 Integrated Security Areas (AIS) and applied strategies to [...] Read more.
The Pact for Life program was one of Brazil’s most successful initiatives in coping with an elevated incidence of deliberate lethal violent crimes (CVLI) within the jurisdiction of Pernambuco. It delineated the state into 26 Integrated Security Areas (AIS) and applied strategies to combine investigative and ostensive policing. Nevertheless, the pandemic shifted the production possibility of public security in directions that justify empirical investigations, not sufficiently covered in the current literature. This study employs variable returns to scale data envelopment analysis (DEA) and Malmquist productivity index (MPI) models to measure police efficiency and technology changes from 2019 to 2020. The proposed framework can be particularly suitable to capture changes in the production frontier resulting from technological advancements or regressions, which might otherwise be overlooked. Through a quantitative analysis, this research offers a comprehensive assessment of AISs and the operational performance of the Civil Police, emphasizing efficiency metrics and avenues for enhancement within a production-oriented context. Full article
(This article belongs to the Special Issue Data-Driven Strategic Approaches to Public Management)
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18 pages, 3811 KiB  
Article
Data-Driven Strategies for Optimizing Albania’s Utilization of Renewable Energy Sources from Urban Waste: Current Status and Future Prospects
by Sonila Vito, Ilirjana Boci, Mohammad Gheibi, Klodian Dhoska, Ilirjan Malollari, Elmaz Shehu, Reza Moezzi and Andres Annuk
World 2024, 5(2), 258-275; https://doi.org/10.3390/world5020014 - 26 Apr 2024
Viewed by 2213
Abstract
Albania is now implementing a range of steps as part of its journey towards European Union integration, based on agreements that have been achieved. Key to these initiatives is the extensive adoption of circular economy concepts through comprehensive waste management systems. This collaboration [...] Read more.
Albania is now implementing a range of steps as part of its journey towards European Union integration, based on agreements that have been achieved. Key to these initiatives is the extensive adoption of circular economy concepts through comprehensive waste management systems. This collaboration is based on systematically implementing measures that align with the fundamental principles of the waste management hierarchy. Albania wants to lead in waste-to-energy conversion exploration by focusing on trash minimization, reuse, recycling, and energy generation from residual waste. Although there has been notable advancement, especially in aligning laws with EU requirements, there are practical obstacles, especially in the execution of waste-to-energy projects. The challenges involve the need for effective waste segregation, higher recycling rates, and the use of advanced waste-to-energy technologies. The essay utilizes meticulously selected data on Albania’s waste generation from reputable organizations and the legal framework regulating waste management to assess the current situation and predict future possibilities, which may be advantageous for government ministries and agency platforms. Full article
(This article belongs to the Special Issue Data-Driven Strategic Approaches to Public Management)
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