Systematicity and generalizability in business process redesign methodologies: A systematic literature review

Context: Business Process Management (BPM) plays a central role in helping organizations improve efficiency and service delivery, particularly in environments with rising demands and limited resources. Within this field, Business Process Redesign (BPR) has emerged as a way to rethink and restructure processes in response to continuous change. However, many existing BPR methodologies fall short—they lack methodological rigor and are often too narrowly tailored to specific industries or use cases. Objectives: This study explores whether BPR methodologies are both systematically structured and broadly applicable across domains. It addresses three key questions: whether current approaches are methodologically grounded, whether they can be applied across diverse contexts, and what core elements are necessary to support both structure and generalizability in BPR design. Methods: A systematic literature review (SLR) was conducted, applying an eight-step protocol to assess sixty-four primary BPR methodologies drawn from academic databases. Each methodology was evaluated against two sets of criteria: five indicators of systematic design (e.g., defined phases, interdependencies, evaluation checkpoints), and five indicators of generalizability (e.g., cross-domain adaptability, notation flexibility, heuristic support). A concept-centric synthesis was used to analyze the findings. Results: Of the methodologies reviewed, thirty-eight demonstrated systematic features, while only eight met broader applicability standards. Only one methodology satisfied all ten criteria, revealing a notable gap in the field and a need for more balanced, reusable frameworks. Conclusion: The study highlights a significant gap in the current BPR methodologies and presents the BPR Application Framework —a structured yet adaptable methodology that combines phase-based design with heuristic integration and notation-aware modeling. Compared with established references like BPM CBOK and Lean Six Sigma, it offers a clearer, more actionable path for practitioners and researchers seeking both rigor and flexibility in BPR.24810339

Constraint Programming and Simulated Annealing Approaches for Parallel-Machine Scheduling with Conflict Constraints, Server Setups, and Flexible Maintenance

This paper addresses a parallel-machine scheduling problem where jobs require setups performed by a single server and must respect conflict constraints that prevent certain jobs from running simultaneously. This type of problem can find applications in logistics and transport operations, particularly when scheduling vehicle fleets that share limited resources. The server is also subject to a fixed-duration maintenance activity that must be scheduled alongside the jobs. The objective is to minimize the makespan. We develop both constraint programming and simulated annealing approaches to solve this problem. Experimental results demonstrate that the constraint programming model, executed on the Minizinc solver, successfully obtains optimal solutions for small instances with 10 jobs. For larger problems with 15 jobs, simulated annealing is a good alternative since it allows to obtain solutions at 2.3\% of the optimum on average despite a fixed calculation time of 10 seconds.1302310Proceedings of the 15th International Conference on Operations Research and Enterprise System

A Pattern-Oriented Ontology and Workflow Modeling Approach for the Sui Move Programming Language

Smart contracts are vulnerable to critical, design-level Business Logic Flaws (BLFs) that conventional analysis tools often fail to detect. To address this semantic gap, this study introduces a novel ontological framework that formally models the link between high-level architectural intent and low-level Sui Move code. The methodology employs a rigorous Linked Open Terms (LOT) approach to construct a comprehensive ontology, integrated with a library of secure design patterns and process-aware Object-Centric Dynamic Condition Response (OC-DCR) graphs. Qualitative validation was conducted on four canonical security patterns (Access Control, Circuit Breaker, Time Incentivization, Escapability) drawn from the official Sui Framework, confirming the framework’s representational adequacy and logical consistency. Ultimately, this work contributes the first machine-readable semantic layer for Sui Move, decoupling reasoning from raw code availability, and providing the essential semantic foundation for the future development of pattern-aware auditing tools.171

Are They AI-Competent? Future Teachers’ Readiness to Use Conversational Agents as Learning Assistants

This study examines the perceptions of student teachers regarding artificial intelligence technologies particularly their knowledge, their willingness to use them, any concerns and perceived benefits and challenges in relation to the Digital Competence Framework for Citizens (DigComp) 2.2 digital competence framework. Our mixed-methods research, involving 372 undergraduate student teachers, revealed correlations among these aspects, indicating that frequent AI users have a stronger intention to use AI, while infrequent users express greater concerns about it. Student teachers acknowledge AI’s time-saving benefits as well as the convenience and academic enhancement it provides, but also voice concerns about its misuse and reliability and the potential impact on skill development and learning. These concerns are in agreement with digital competence areas of information literacy and safe technology use. Reflecting on these perceptions, it is essential to maximise the educational benefits of effective and responsible AI integration into higher education and foster the digital competencies of future teachers.16231832

Variable Neighborhood Programming for Job Shop Scheduling Problems

The Job Shop Scheduling Problem is a classic combinatorial optimization problem and one of the most well-studied scheduling problems. Several methodologies, both exact and metaheuristic, have already been proposed for the solution of this computationally difficult problem. This work presents for the first time a solution approach based on Variable Neighborhood Programming for the Job Shop Scheduling Problem. Variable Neighborhood Programming is a recent methodology which constitutes a combination of Genetic Programming and Variable Neighborhood Search. In addition, some encouraging comparative computational results are also shown against the state-of-the-art Gurobi optimization solver using medium- and large-scale benchmark instances. The findings of this work have a plethora of modern applications in Manufacturing-as-a-Service online platforms. All experimental evaluations were performed on the Google Cloud Platform.16256120133Variable Neighborhood Searc

Open Access Academic Publications: Benefits and Risks

The presentation focuses on both the benefits and the risks that emerge during the process of academic publishing under the Open Access model. Within this context, the Library of the University of Macedonia is conducting a study aimed at mapping the views and experiences of the university’s researchers regarding the advantages and challenges they encounter when publishing in Open Access journals. The results of this research are expected to significantly contribute to the development of informed policies and support services tailored to the actual needs of the research community. 31o Πανελλήνιο Συνέδριο Ακαδημαϊκών Βιβλιοθηκών – 22-24/10/2025 Ιωάννινα Το κείμενο της ανακοίνωσης (conference paper) είναι διαθέσιμο στο: https://olympias.lib.uoi.gr/jspui/handle/123456789/39352 In addition, the presentation includes the findings of an analysis of the journals in which researchers from the University of Macedonia published during the period 2020–2024, compared against the Finnish journal evaluation system Jufo (Julkaisufoorumi). The goal is to explore to what extent journals with a high CiteScore in the Scopus database are also considered high-quality according to Jufo's classification. The analysis revealed that although most titles with a high CiteScore are ranked in the higher Jufo tiers (levels 2 and 3), there are cases of journals with high impact but low or no quality rating in Jufo (levels 1 and 0), indicating the need for a multidimensional evaluation of publication. Finally, the presentation highlights the need for institutional guidance and support for researchers, the development of Open Access policies that ensure the quality of scholarly communication, and the strengthening of the role of libraries as hubs of support, evaluation, and awareness about Open Access publishing

Factors Affecting Internet Users’ Effectiveness to Detect Phishing

Phishers target Internet users and send them phishing emails or create phishing websites to deceive victims and extract financial gains. This study investigated the factors that affect Internet users in phishing detection. The responses of 252 participants to an online survey were collected and analysed. Participants were mostly careful when a website requested urgent action, its content had errors, or an email message asked recipients to give personal information or click a suspicious link. They believed that education about phishing, email filtering software, and connecting directly to the official website, and not through a link, were the best practices. They also stated that they could learn how to easily detect phishing attempts and evaluate whether an email was spam, advertising, phishing, or a scam. It was also found that the creation of blacklists and whitelists did not provide sufficient protection against phishing, active warnings were more effective than passive warnings, and users were receiving phishing emails that escaped email filtering and antivirus software. Further statistical analysis of their responses revealed that there was a moderate positive correlation between each of the variables Self-Efficacy in Phishing Detection, Information Evaluation Skills, E-Banking Phishing Detection Skills with Phishing Detection Effectiveness. Finally, it was found that the Facilitating Conditions for Phishing Detection, E-Banking Phishing Detection Skills, and E-Mail Phishing Detection Skills influenced Phishing Detection Effectiveness.244255002

Inverted VEA for worst-practice benchmarking: with an application to distress prediction of European banks

In this paper we introduce managerial preferences in the assessment of worst-practices by means of Value Efficiency Analysis (VEA). Our model involves the choice of a Decision Making Unit (DMU) being on the worst-practice frontier, that has the least desirable input/output structure by view of a Decision Maker (DM). The method then assesses all DMUs based on the worst favorable sets of input/output weights for the chosen DMU. The scores of the associated linear program, referred to as Inverted VEA, are larger than or equal to the respective Inverted DEA scores. Higher (lower) differences between Inverted DEA and Inverted VEA scores highlight DMUs with an input–output bundle that is farther (closer) to the least desirable ones. This aids central management to identify DMUs which should be marked for closer monitoring and inspection or put through a restructuring process. We illustrate the usefulness of the method by applying it to assess the relative financial distress of 33 major European banks that were evaluated by the European Banking Authority in the 2018 stress test.347147149

Perceptions of generative AI in education: Insights from undergraduate and master’s-level future teachers

As AI continues to transform educational practices, understanding its potential benefits, limitations, and ethical implications is critical. This study explores future educators‘ perceptions of generative ΑΙ in higher education. Through a mixed-methods approach, this research gathered insights from undergraduate and master‘s level students on their familiarity with, willingness to use, and concerns about AI-driven educational tools. Findings highlight a general positivity toward AI‘s utility in learning and teaching, with key advantages including personalised feedback, time efficiency, and academic support. Conversely, challenges related to reliability, academic integrity, and the potential for over-reliance reveal areas for further guidance and digital literacy enhancement. Post-intervention data suggests that hands-on experience with AI can reduce concerns and foster a balanced perspective on AI adoption in education. This study underscores the need for ethical frameworks and policy guidance to support the responsible integration of AI in educational contexts.928910

Efficient Visualization of 3D Urban Environments in the Metaverse by Integrating GIS and Unreal Engine

Geography and geographical space play an important role in many aspects of life and in many areas of online activity. In terms of loading and visualizing 3D urban environments and city-scale scenes, in real-time rendering, current approaches still require excessive use of CPU, GPU and video memory usage. In this research study we emphasize new technologies and game engines like Unreal Engine in order to efficiently visualize 3D urban environments in the metaverse. The metaverse is a virtual 3D world where individuals can create and control their own avatars, offering three-dimensional and immersive virtual environments. Geographic information systems (GIS) and the metaverse are both complex and rapidly evolving fields with many possible applications. The integration of GIS with the Unreal Engine, a popular game engine and a powerful real-time 3D creation tool, allows the creation and efficient visualization of photoreal virtual environments, while GIS data and layers could be used to create more realistic digital 3D environments in the metaverse, including terrain, buildings and other relevant factors allowing users to explore a three-dimensional virtual representation of city-scale scenes. The aim of this study is to present a methodology for an efficient and detailed visualization of 3D urban environments in the Metaverse by integrating Unreal Engine and GIS.3273322025 8th International Conference on Information and Computer Technologies (ICICT