Algorithmic management (AM) automated systems for monitoring, scheduling and decision-making have quickly altered banking workplaces using AI-driven platforms and data-driven performance tools. While productivity improvements have been well established, the human-centered consequences of AM remain unknown, specifically how employees adapt, interact with automation and maintain their performance. This study bridges the gap by looking into human–automation collaboration and job redesign in algorithmically managed banking environments. The study asks: How can algorithmic systems influence work structure, experience, outcomes and how can collaboration increase productivity while protecting employee well-being? The analysis is based on three sub-questions: How do employees interact with AM systems in their daily tasks? What digital, data and socio-emotional competencies promote autonomy and engagement? How can HR managers adapt work and training to strike a balance between efficiency and human values? The study uses a quantitative methodology in Nigerian banking sectors, where algorithmic decision tools are critical for credit evaluation, compliance and performance analytics. The sample will comprise relationship officers, credit analyzers and digital operations personnel. Data will be gathered using validated survey tools that measure AM functions (monitoring, scheduling, evaluation), job demands/resources (workload, autonomy, technostress) and outcome (engagement and performance). Analytical techniques will include confirmatory factor analysis and structural equation modeling to test relationships within the proposed framework. The paper makes a new contribution by providing a multidimensional sociotechnical framework for human–automation collaboration in banking. This approach combines job design principles, competency development methodologies and algorithmic transparency rules, providing HR practitioners and policymakers with actionable insights to improve AM systems while fostering autonomy, capability growth and organizational resilience.

This study examines how inclusive leadership theory can be aligned with process design principles to strengthen the implementation of Diversity, Equity, Inclusion, and Belonging (DEIB) initiatives within arts and cultural organizations. Although DEI has become a critical priority across different sectors, progress toward actual inclusion and representation remain inconsistent. Research shows that many diversity practices are ineffective, despite significant awareness and investment. Recent political shifts have intensified resistance, threatening to reverse past gains. Within the arts and cultural sectors, the mission to create spaces of belonging and visibility for all highlights the need for more structured, sustainable approaches to DEIB work, as institutional needs and operational realities diverge from those in other fields.

Method
This study adopts a conceptual research design supported by a narrative literature review. This approach connects the literature on DEIB, inclusive leadership theory, and process-improvement methodologies to explore their connections. Through interpretive analysis, the review will examine how principles associated with inclusive leadership align with the structural stages of the Six Sigma DMAIC framework with the objective of identifying how process design concepts can support systematic DEIB implementation within the cultural sector.

Results
The structured progression of the DMAIC model offers a systematic method for defining inclusion objectives, measuring organizational progress, analyzing barriers, improving practices, and controlling for long-term sustainability. These parallels suggest that integrating Six Sigma principles may provide cultural organizations with ways to operationalize inclusion more consistently and effectively. In applying the DMAIC model in this sector, we expect to identify new insights as to its applicability in both diversity and the cultural sector.

Conclusion
The findings propose that combining process improvement methodologies with DEIB goals can create a pathway for embedding equity and belonging into everyday organizational activity. This conceptual integration offers a potential model for institutions seeking to transform aspirational intentions into measurable progress.

The accelerated technological transformation that public administrations are undergoing presents new opportunities to connect with citizens, but it also highlights the limitations of traditional models of citizen participation, which are often symbolic and have little impact on public decision-making. This study proposes evolving towards participatory procedures based on citizen science, utilising open data and hybrid intelligence that combines collective and artificial intelligence (AI) capabilities to generate public value.

The aim of this research is to define and validate a framework for citizen co-governance, supported by digital platforms and learning algorithms, that can automatically transform the data generated by citizens into concrete public actions. To this end, we conduct a systematic analysis of the literature on participation and citizen science, from the classic vision of Arnstein (1969) to the current proposals of Fung (2006), OECD (2018) and Ataman (2025), which integrate inclusion and democratic legitimacy, identifying a gap in the operational mechanisms that translate citizen participation into tangible decisions. This analysis is complemented by the study of the CitizenBack pilot, developed in the Urban Sandbox of Valencia, which acts as a transversal government infrastructure and citizen digital twin. The pilot has been used to empirically evaluate data flows, citizen interactions, and the response mechanisms of AI algorithms, generating qualitative data, such as user perceptions, and quantitative data, including usage metrics, participation patterns and assessments of public management. Additionally, it is complemented by interviews with public managers to gain a deeper understanding of the institutional challenges involved in adopting such systems.

The results propose a new organisational model that automates public collection, analysis, prioritisation and response in real-time. Although there are challenges, such as the digital divide, algorithmic ethics, and change management within institutions, the study provides an operational framework for achieving data-driven, people-centred and AI-driven public co-management, thereby strengthening citizen democracy.

This paper presents a processual perspective on stakeholder modelling, developed through a systematic review of the stakeholder networking literature. The review followed the PRISMA (Preferred Reporiting Items for Systematic Reviews and Meta-Analyses) protocol and included searches across Scopus, Web of Science, and Business Source Complete, applying inclusion criteria focused on studies addressing stakeholder networks and their dynamics. This rigorous approach enabled the identification and synthesis of diverse theoretical insights, which informed the development of a processual viewpoint that moves beyond traditional static network models. By synthetically drawing on insights from different stakeholder networking perspectives, this paper concludes four characteristics inherent to the stakeholder networking process. The first characteristic is the temporal stakeholder–stakeholder relationship, indicating that the connection between two stakeholders is not enduring but exists within a specific timeframe. The second characteristic highlights the directional aspect of stakeholder interaction, where the interaction between two stakeholders can fluctuate in strength, being either weaker or stronger according to situational dynamics. The third characteristic pertains to stakeholder power multiplicity, suggesting that the collective power of the network surpasses the sum of the individual powers of its stakeholders. Lastly, the fourth characteristic is the issue-specific network lifecycle, which divides the network into different stages, from inception to maturity, and ultimately to expiration or stabilization. In light of the procedural perspective, this paper explores the practical implications for stakeholder management strategies in addressing the complexities of multi-stakeholder dynamics.

This study undertakes a systematic and a bibliometric review of the literature on artificial intelligence as a cognitive extension within the domain of entrepreneurship, with particular emphasis on how computational systems interact with and enhance key dimensions of entrepreneurial cognition. Employing co-citation, co-occurrence, and thematic network analyses, this review maps the intellectual evolution of research that links AI capabilities to opportunity recognition, analytical reasoning, and early-stage decision making. Prior scholarship suggests that generative and predictive models broaden the scope of entrepreneurs' informational searches, enabling the discernment of patterns that typically elude unaided human judgment. Studies on problem-solving underscore the role of language-based and reasoning-oriented systems in fostering structured ideation and refining cognitive strategies. Concurrently, research in decision support highlights the utility of machine learning in forecasting, facilitating more systematic evaluations under conditions of uncertainty. Drawing insights from these intersecting literatures, this review delineates methodological imperatives for investigating AI-augmented cognition, including considerations of model interpretability, alignment between task and technological affordances, and the appraisal of human–AI reasoning dynamics. The resulting conceptual framework positions AI not as a replacement for entrepreneurial judgment but as an auxiliary cognitive apparatus that reshapes how entrepreneurs acquire information, construct alternative courses of action, and appraise nascent opportunities.

This study presents a systematic and bibliometric review of the evolving conceptualization of emotional intelligence as leadership increasingly unfolds within intelligent, technology-mediated environments. Through co-citation mapping, co-occurrence analysis, and thematic structure identification, this research traces the trajectory of scholarship concerned with leaders’ socio-emotional competencies in contexts shaped by algorithmic systems, automated communication tools, and digitally mediated collaboration. The literature suggests that the integration of intelligent technologies reconfigures the channels through which leaders perceive, interpret, and express emotion, thereby necessitating novel strategies for rapport-building, conflict resolution, and interpersonal sensemaking. Studies into AI-enabled communication platforms reveal shifts in how affective cues are decoded and enacted. At the same time, research on data-driven decision infrastructures highlights the imperative of aligning relational sensitivity with computational guidance. By synthesizing methodological patterns across these strands, the review elucidates key challenges in studying emotional intelligence within technologically saturated leadership contexts, including the adaptation of measurement frameworks, the analysis of leader–technology interactional dynamics, and the assessment of distributed socio-emotional processes. It advances a conceptualization of emotional intelligence as a dynamic and context-contingent leadership capability, increasingly shaped by digital interfaces and central to the coordination, motivation, and relational coherence of hybrid human–machine organizational systems. Ultimately, the review establishes a conceptual foundation for reinterpreting socio-emotional leadership capabilities as intelligent technologies that become embedded within core organizational processes.

Institutional integrity has become an important pillar for achieving sustainable governance and implementing UN 2030 Agenda. The relationship between the indicators of integrity and the SDGs is insufficiently studied in Romania, so this paper provides an analysis of the alignment between the indicators of institutional integrity and SDGs with reference to SDG 16 (Peace, Justice and Strong Institutions), SDG 17 (Partnerships for the Goals) and SDG 11 (Sustainable Cities and Communities). The paper is set to formulate a mapping matrix between ethical, transparency and digital integrity mechanisms to SDG targets based on web-based data to support how the local public institutions consider the incorporation of integrity mechanisms into the wider sustainability agenda. The research is based on mixed methodology with a content analysis of the institutional reports and the statistical correlation between the scores of integrity and the corresponding SDG targets that are currently set. The analysis gives empirical insight into the contribution of data-driven policymaking in institutional integrity to larger EU strategies of inclusive and sustainable governance. Early results indicate a moderate-to-high degree of institutional adherence to integrity norms and municipalities, which are more ethically oriented in terms of integrity levels, are also more advanced in digital governance or citizen participation practices. Good procurement ethics, information openness and governance that is citizen-facing are found to be the drivers of policy coherence for sustainable development. Geographic inequalities contribute towards performance, but the performance is in relation to administrative capacity and a proactive model of governance. In contrast, the weak integrity is positively associated with fragmented implementation of the SDGs and lower public trust. The results highlight the increased correspondence between integrity-based governance and SDG framework. The conclusions canbe used as an evidence base as by policymakers to share the strategies of enhancing digital integrity platforms (e-integrity), conflicts of interest and digitization of administrative processes.

Social entrepreneurship is increasingly recognized as a transformative force, given its dual capacity to address societal challenges and foster sustainable development. Higher education institutions have sought to strengthen social entrepreneurship education to cultivate the next generation of changemakers, Learning by Doing (LBD) has emerged as one of the most effective experiential approaches for developing entrepreneurial competencies (EC) and social entrepreneurial intention (SEI). Despite its growing importance, limited research has examined how LBD operates within structured, practice-based environments in the Global South. In response to this gap, our study examines Enactus Morocco, the country’s leading organization applying LBD to foster social entrepreneurship, SEI, and EC among university students while also considering prior knowledge and supportive learning environments as secondary moderating factors within an integrated theoretical framework.

Adopting a qualitative exploratory design, covering two complementary perspectives: the perspective of the organization Enactus Morocco and that of its student members. Ten semi-structured interviews were conducted with participants, ensuring ethical compliance and methodological rigor. The data were analyzed thematically using NVivo15.

The findings validated the proposed theoretical model, confirming that LBD effectively fosters EC and SEI, with the supportive environment emerging as a critical catalyst. Prior knowledge facilitated adaptation; however, students without such experience were able to compensate through the experiential nature of LBD, which accelerated skill acquisition. The results showed additional influencing factors, such as emotional support, a clear learning path, and Networking. Data saturation was achieved in the ninth interview.

Our study provides the first context-based framework linking LBD, SEI, and EC in a non-Western setting. It enhances theoretical understanding, guides educators, practitioners, and policymakers in designing transformative educational ecosystems, and underscores the potential of LBD to empower the next generation of socially responsible leaders. Our future research will expand this work through quantitative validation of the proposed model.

Disruptive technologies from Industry 4.0 have transformed sectors worldwide, making digital transformation essential for maintaining competitive advantage and increasing productivity. Despite the importance of digital transformation on a global scale, little is known about digital maturity models and how they specifically relate to the retail industry.

Purpose: This study aims to pinpoint the essential elements of current Digital Maturity Models across a variety of industries. In addition, this study attempts to fill in the research gap in the context of retail businesses by comparing and contrasting the SLR's findings with their actual use in the retail industry.

Methodology: This study is based on a Systematic Literature Review (SLR), which identifies important aspects of digital maturity models from research studies published between 2011 and 2024. Relevant studies were gathered using databases like Science Direct, EBSCO, Google Scholar, and consulting reports from companies like McKinsey and Deloitte. According to predetermined inclusion criteria, a total of 20 studies were chosen, and Rossmann's (2018) Digital Maturity Model turned out to be the best framework for the retail industry. To ensure data rigor, PRISMA protocol is being used. Meanwhile, the empirical study is still ongoing.

Findings: SLR findings indicate that strategy, culture, and technology are the three main digital transfomation dimensions. These are highly aligned with preliminary findings from the empirical study. The identified dimensions serve as a theoretical framework for future studies in the same topic.

Practical Implications: This study sets the ground for a theoretical framework to measure the level of digital matury in the retail sector. Dimesions such as strategy and technology in particular are considered as key forces behind digital transformation. Other dimensions like governance and leadership point to areas that still need improvement. These revelations advance our knowledge of the practical applications of digital maturity models in emerging markets such as Albania.

In the dynamically changing world of higher education, the administration and structuring of curricula have become significant aspects in fostering institutional efficiency, academic transparency, and student performance. This study explores strategic approaches to university curriculum governance, emphasizing adaptability, stakeholder involvement, and quality assurance mechanisms. By drawing on contemporary European and international frameworks, this paper examines the methodologies employed by higher education institutions to align their curricular structures with societal expectations, labor market exigencies, and accreditation benchmarks. It highlights the complexities involved in reconciling autonomy with accountability, ensuring that curricular determinations are reflective of both scholarly principles and practical outcomes. The investigation employs a mixed-methods methodology, amalgamating document analysis with semi-structured interviews conducted with curriculum managers and academic leaders across European universities. The findings suggest that effective curriculum management is contingent upon participatory governance, transparent communication, and ongoing evaluation, all facilitated by digital technologies. The article posits that strategic curriculum management ought to incorporate a long-term vision, inclusivity, and innovation in order to maintain institutional resilience and relevance amidst a period characterized by rapid educational transformations. This research contributes to the ongoing discourse surrounding leadership, strategic management, and quality enhancement within university administration, proffering practical recommendations for academic policymakers and administrators.