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Abstract: Purpose: This study aims to theorize and empirically validate a recursive and mediated support process for online knowledge creation in organizational contexts. Drawing on the IEM model—which comprises internalized expression, explicit collaboration, and mediated integration—the research challenges the conventional assumption that face-to-face interaction is a prerequisite for effective knowledge generation. Study design/methodology/approach: A large-scale nationwide survey was conducted with 2,408 business professionals in Japan. Structural equation modeling (SEM) was employed to examine the hypothesized relationships among the IEM model constructs, including a feedback loop structure from mediated integration to internalized expression. Findings: The analysis revealed that all three phases—internalized expression, explicit collaboration, and mediated integration—are not only sequentially connected but also mutually reinforcing. The recursive feedback from mediated integration to internalized expression was statistically significant, underscoring the adaptive and cyclical nature of digital knowledge creation. Originality/value: This study introduces a theoretically grounded and empirically validated IEM model for online knowledge creation. By demonstrating that effective knowledge generation can be sustained through digitally mediated, empathy-supported processes, the study provides a novel framework with strong implications for remote collaboration and knowledge management in hybrid work environments.
Keywords: knowledge creation, online communication, digital collaboration
Published in ReVIS: 19.09.2025; Views: 243; Downloads: 2
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Abstract: Purpose: The study aims to assess whether dropout rates in Slovenian higher education have increased over time, focusing on persistence and potential trends between 2011 and 2019. It also seeks to evaluate how robust and Bayesian statistical methods can improve dropout analysis when only limited data are available. Study design/methodology/approach: The research uses aggregated dropout data from nine consecutive student cohorts (2011–2019) within the Targeted Research Programme (CRP V5-2360). The analysis combines descriptive statistics, robust methods (Theil–Sen estimator with bootstrap confidence intervals), and Bayesian regression modelling with weakly informative priors. This mixed methodological framework is particularly suitable for short time series and allows probabilistic interpretation of results. Findings: The results reveal that dropout in Slovenia is persistently high, averaging around 51%. Two distinct phases were identified: a decline between 2011 and 2015, followed by renewed growth from 2016 onwards. While classical robust methods yielded inconclusive results regarding a linear trend, Bayesian analysis indicated with high posterior probability (>95%) that dropout has been increasing by about one percentage point per year since 2015. Originality/value: This study contributes substantively by confirming that Slovenia belongs to the group of European countries with exceptionally high and persistent dropout levels. Methodologically, it demonstrates the added value of applying robust and Bayesian approaches to small-sample educational data, offering more reliable and nuanced insights than conventional frequentist techniques.
Keywords: higher education dropout, dropout persistence, trend analysis, Theil–Sen estimator, Bayesian approach, Slovenian higher education syste
Published in ReVIS: 19.09.2025; Views: 313; Downloads: 8
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Abstract: Purpose: This study examines how experiences of informal learning and its management diverge and converge across organizational levels in a knowledge-intensive organization. The study bridges a gap in comparative perspectives concerning informal learning leadership by examining managerial and employee points of view. Study design/methodology/approach: The study employed a qualitative, cross-sectional case study design with 18 semi-structured interviews with managers and employees from within a multinational IT and consulting organization.  Data analysis was conducted by an inductive thematic analysis, enabling the emergence of themes related to informal learning, learning modalities, leadership engagement and organizational support structures. Findings: The findings indicate a consensus among managers and employees that informal learning is important, but there is significant disagreement regarding its visibility, support and linkage to career development. Managers tended to depict their role as enabling autonomy, while employees perceive a lack of structured support and recognition. Informal learning was found to be prevalent but extremely invisible in formal organizational processes. Originality/value: This study deepens understanding of the leadership of informal learning by highlighting the concept of "symbolic autonomy", where support for learning is rhetorically there without substantive mechanisms. It provides a theoretical contribution by positioning the relational and systemic aspects of informal learning leadership in the front line and offering practical understanding of how informal learning can be embedded more effectively within organizational practice.
Keywords: informal learning, knowledge work, leadership, self-directed learning, symbolic autonomy, organizational learning
Published in ReVIS: 19.09.2025; Views: 252; Downloads: 6
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Abstract: This study explores the integration of nursing within higher education curricula, using a case study from a South African University of Technology. It investigates how academic staff across faculties conceptualise, plan for, and embed numeracy in their teaching practices, particularly in the context of curriculum transformation and widening access. Drawing on Legitimation Code Theory (LCT) as the primary analytical framework, the study employs a qualitative case study approach, analysing interviews, curriculum documents, and planning artefacts. The findings highlight varying levels of awareness, conceptual clarity, and pedagogical strategies among lecturers when it comes to numeracy integration. The study identifies challenges including disciplinary silos, lack of shared understanding, and limited institutional support. However, it also surfaces promising practices, such as interdisciplinary collaborations and reflective curriculum design, that offer pathways for embedding numeracy meaningfully. The study argues that planning for numeracy requires both epistemological and social accountability, particularly in universities serving diverse student populations. It concludes by proposing a framework for enhancing numeracy through deliberate curriculum planning, cross-faculty dialogue, and professional development. The insights aim to inform higher education policy and practice in contexts grappling with curriculum transformation, equity, and academic literacy in quantitative reasoning.
Keywords: numeracy integration, legitimation code theory, curriculum transformation, south african higher education
Published in ReVIS: 19.09.2025; Views: 256; Downloads: 7
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Abstract: Purpose: The purpose of this paper is to investigate the effectiveness of a hiring pipeline designed to be cost effective and improve customer experience (CX)—with an emphasis on candidate experience—to increase time to hire, candidate satisfaction, and eventual first year retention across supporting functions in sales, support, and operations in high-volume hiring firms. Design/methodology/approach: A mixed-methods design was utilized and was derived from ATS, CRM logs, industry standards, and AI simulations. Quantitative information was based on a before-and-after quasi-experimental design. In contrast, qualitative information was based on natural language processing (NLP) of recruiter-candidate exchanges using total AI and anonymized candidate surveys. Human-in-the-loop controls and bias checks (metrics) assured flexibility in AI deployment. Findings: Implementation of AI resulted in significant operational and experiential gains. Time to hire decreased from 28.4 to 14.7 days (−48.2%), candidate satisfaction was increased by 40% (6.2 to 8.7), and first-year retention was increased by 19% (72.5% to 86.3%). Qualitative data confirmed operational efficiencies, personalization, and increased perceived fairness. Research limitations/implications: The study was limited to a single large service-focused company, which is based on a pre–post design, without a randomized control group design, and therefore, the findings are not generalizable. Future research should examine AI-driven CX-enhanced hiring in more diverse organizational contexts and longitudinal or controlled experimental designs. Practical implications: With proper AI governance (e.g., bias audits, oversight checkpoints, and transparency), large volume hiring organizations can reduce hiring cycle time; improve retention; and reduce cost via AI-CX. Originality/value: This study demonstrates how AI can jointly improve efficiency and the candidate experience and identifies governance practices needed for ethical and sustainable adoption at scale.
Keywords: Artificial Intelligence, Customer Experience, High Volume Hiring, Talent Acquisition, First Year Retention, Human in the Loop
Published in ReVIS: 19.09.2025; Views: 290; Downloads: 6
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