This paper aims to reassess evidence on value added intellectual coefficient (VAIC) and firm performance in emerging economies by examining the algebraic dependence between human capital efficiency (HCE) and structural capital efficiency (SCE). The study combines analytical derivation with a systematic review and model-level meta-analytic specification audit of 94 articles, published through 31 December 2025, and 644 regression models. The 16-case coefficient-sign audit covers 357 models from 77 articles. A source-validated random-effects synthesis covers 159 paired effects from 32 articles, with article-level dependence adjustments and sensitivity analyses. Because SCE = 1–1/HCE, regressions jointly including original HCE and SCE are nonlinear HCE models, not linear models of independent components. SCE is significant in 201 of 357 classifiable models (56.3%; article-weighted prevalence: 54.8%). At the HCE mean, 22 of 208 comparisons (10.6%) reverse the sign implied by the published HCE coefficient. Dependence-adjusted pooled associations are r = 0.223 for the linear HCE term and r = −0.133 for the hidden reciprocal term, with substantial heterogeneity. The evidence base is limited to published articles whose full texts could be retrieved, and incomplete reporting restricts effect-size conversion and marginal-effect diagnostics. The synthesis is therefore diagnostic rather than causal. The screening audit distinguishes explicit exclusions from records with unresolved eligibility and potentially eligible records whose full texts were unavailable. VAIC component coefficients should not inform recommendations concerning employees, systems, databases or processes unless the HCE–SCE dependence and implied nonlinear curve are examined. Building on the known HCE–SCE dependence, this study documents its prevalence and consequences across emerging-market research and distinguishes construct-validity, specification and managerial interpretation implications.
Purpose This research aims to examine how knowledge flows circulate within a public innovation unit, how multidisciplinary teams interact and what these dynamics reveal about knowledge management (KM) maturity. Design/methodology/approach A survey-based case study with embedded qualitative responses was conducted at CeMEPI-PGE. Data were collected through a structured questionnaire administered to researchers from different teams. Closed-ended responses were analyzed using descriptive statistics, while open-ended responses were examined through thematic content analysis. Findings Semantic knowledge boundaries emerged as the most salient perceived integration barrier among the dimensions assessed, although collaborative potential remained high. Research limitations/implications The study is limited to a single case and relies primarily on questionnaire data, which restricts statistical generalization. Future research could adopt longitudinal and comparative designs to examine the evolution of KM maturity in emerging public innovation units. Practical implications The findings highlight the importance of strengthening knowledge governance through structured repositories, standardized documentation practices and institutionalized knowledge-sharing routines. Social implications Strengthening KM in public organizations contributes to improving the quality of public decision-making and the effectiveness of institutional innovation initiatives. By promoting better knowledge integration, organizational learning and preservation of institutional memory, KM practices can support more transparent, efficient and evidence-based public administration. In contexts such as public research and innovation centers, improved knowledge flows may enhance the State’s capacity to design and implement policies, optimize public resources and expand access to justice and public services. Originality/value This study contributes to the KM literature by proposing an interpretive lens through which early-stage maturity in newly created organizations may be understood in relation to institutional newness rather than solely as organizational deficiency. It also extends knowledge-boundary theory to multidisciplinary public research and innovation environments.
Purpose This paper aims to examine how organisations hold governance knowledge stable enough to execute reliably yet revisable as policies and conventions change. It develops a temporality-focused conceptual elaboration of knowledge management (KM) for executable governance, reading market data rules as boundary objects whose validity is bounded in time. Design/methodology/approach The study is a retrospective analysis of an existing design artefact – a Python repository for an equity trading ecosystem, built by the authors for an earlier project – from which design knowledge is abstracted using design science research principles, a documented coding protocol and analytic generalisation. Findings The artefact carries governance knowledge in effective-dated fee regimes resolved deterministically, explicit session and settlement conventions, schema exemplars and fixtures without a validation gate, and reporting treated as an audit output. It supports a lightweight provenance analogue, not formal provenance, answering “what rule applied when” through inspectable configuration and deterministic resolution. Five artefact-level validations pass and are independently reproducible. Research limitations/implications One artefact, analysed by those who built it, can support claims about how executable governance may be structured, not about adoption or effectiveness. Propositions are theoretically derived and stated with falsification conditions. Practical implications Fee schedules, calendars, schemas and reporting templates should be treated as versioned executable controls, and their defaults as governance decisions requiring review. Originality/value Boundary-object theory treats interpretive flexibility as the source of an object’s coordinating power. Executable governance inverts this: flexibility is removed at execution and preserved at review. Naming that inversion, and the design knowledge following from it, is the contribution.
Purpose This study aims to examine the factors influencing metaverse adoption in education, addressing a context that remains underexplored and contested. It aims to identify and structure the key determinants shaping stakeholder adoption decisions while highlighting the metaverse’s implications for knowledge management through immersive and experiential learning. Design/methodology/approach The study adopts a multimethod design combining the task-technology fit model and the extended resource-based view. Expert insights were analysed using fuzzy ordinal priority approach (F-OPA) to prioritise factors, modified Total Interpretive Structural Modeling (m-TISM) to examine interrelationships and develop a hierarchical framework and MICMAC analysis to classify factors by driving power and dependence value. Findings Fourteen factors influencing metaverse adoption were identified and grouped into four categories: infrastructure, pedagogy, accessibility and socioeconomic conditions. The findings show that adoption depends on both enabling capabilities and contextual constraints. The metaverse can enhance knowledge creation, sharing and application through immersive learning, but adoption is limited by infrastructure readiness, equitable access and socioeconomic disparities. Originality/value This study offers novel empirical evidence on metaverse adoption in education by integrating task-technology fit with the extended resource-based view and applying a combined F-OPA, m-TISM and MICMAC approach to generate prioritised and interpretive insights.
Purpose This paper aims to explain how knowledge management processes (KMP), which encompass the identification, organisation, creation, sharing and utilisation of knowledge, contribute to increased organisational productivity among information professionals in academic libraries. It proposes how enhancing knowledge can effectively transform library operations daily. This study examines how information professionals can use KMP to enhance organisational productivity, drawing on experience in academic libraries. Design/methodology/approach This paper chose the quantitative research method based on a systematic literature review. The preferred reporting items for systematic reviews and meta-analyses guidelines were adopted for data collection, where 120 articles were retrieved from the Scopus database; after exclusions and inclusions, 39 were included in the study analysis. Findings This paper offers empirical evidence on how KMP supports information professionals in driving organisational productivity through innovation. It indicates that information professionals have new responsibilities as content creators, influencing users’ information needs and discovering new knowledge that can be recorded, organised, disseminated and used for career advancement. This study suggests that implementing KMP would enhance library services by facilitating the sharing of tacit knowledge among information professionals. Practical implications This study can serve as a blueprint for user awareness and education among other information professionals in academic libraries. This study can actively promote a culture of tacit knowledge sharing among information professionals. Originality/value This study found that information professionals can adopt KMPs by deepening their understanding of how tacit and explicit knowledge are used to enhance organisational productivity, service delivery and competitiveness in academic libraries.
