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Osuva on Vaasan yliopiston avoin julkaisuarkisto. Osuva sisältää Vaasan yliopiston omat julkaisut, opinnäytteet ja tieteellisten artikkeleiden rinnakkaistallenteet. Osuvaan sisältyy julkaisujen viitetietoja, tiivistelmiä ja kokotekstejä. Sähköisten arkistokokoelmien sisältö ei ole luettavissa verkossa.

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Viimeksi tallennetut

  • The MOI impact framework: a catalyst for systemic change in museums
    Hamari, Pirjo; Runnel, Pille; Uusikylä, Petri; Aljas, Agnes (Frontiers media, 2026)
    Artikkeli
    This article examines a practice-based approach to museum development in the context of the growing necessity for systemic change in contemporary museum practice, adding to current debates in museum and cultural management studies on organisational change and impact. As museums operate in increasingly complex environments, they are expected not only to manage internal processes but also to demonstrate social impact and public value. From this perspective, the article outlines three interrelated approaches to museum development: managerial, audience-centred, and systemic. These are positioned as a conceptual framework through which the article presents the “Museums of Impact” (MOI) framework (MOI Framework). As opposed to traditional evaluation models focused on external assessment and performance measurement, the MOI framework is designed as an internally driven, developmental tool that supports organisational learning and change. Building on an abductive, co-creative process involving museum professionals across Europe into building a tool and a secondary research phase, the MOI framework is introduced as an approach to organisational self-evaluation that supports reflective dialogue and impact-oriented development. Drawing on developmental evaluation and systems thinking, the framework merges strategic, participatory, and structural dimensions of change. The article discusses the framework as a tool for organisational learning and internal development, and considers its relevance for supporting systemic approaches to change within the museum sector.
  • Assessment of Post-Fault Voltage Recovery in IBRs-Dominated Grids: Evaluating the Role of Grid-Forming Converters
    Aljarrah, Rafat; Salem, Qusay; Karimi, Mazaher; Abuishmais, Ibrahim; Jaber, Hamza (Institution of engineering and technology, 2026)
    Artikkeli
    Conventional Synchronous Generators (SGs) are increasingly being replaced by Inverter-Based Resources (IBRs) for integrating Renewable Energy Sources (RESs). However, this transition introduces significant challenges, as most existing IBRs employ Grid-Following (GFL) converters that depend on a strong grid connection for stable operation. Consequently, their ability to provide dynamic voltage support and maintain post-fault voltage recovery might be limited in IBR-dominated grids. To address these issues, grid-forming (GFM) converters have emerged as a promising alternative. Unlike GFL converters, GFM units can emulate SG behaviour by autonomously establishing grid voltage and frequency, thereby enhancing both steady-state performance and dynamic response during disturbances. This study investigates the potential role that GFM converters may play in improving dynamic voltage support and post-fault voltage recovery in IBR-dominated grids. It first examines post-fault voltage recovery in conventional SG-based systems, then evaluates various IBR penetration scenarios, with low, medium, and high penetrations of IBRs based on both traditional GFL and emerging GFM converters, integrated to replace large and central SGs. Finally, a correlation-based sensitivity analysis is introduced to systematically quantify the relationship between fault-induced voltage nadir and voltage recovery speed across network locations and penetration levels of IBRs. Through simulations and analysis using a modified IEEE 9-bus test system modelled in DIgSILENT PowerFactory, the study demonstrates the vital role of GFM converters in ensuring robust post-fault voltage response and overall grid stability in renewable-rich power systems.
  • Consumer Cultural Renaissance: Conceptualisation, Scale Development, and Validation
    Lee, Richard; Khan, Huda; Li, Jianyao; Saeed, Muhammad Rashid (John Wiley & Sons, 2026)
    Artikkeli
    As incessant globalisation leads to the pervasive erosion of traditional Asian culture by Western consumerism, a recent phenomenon has emerged that allures Asian consumers to reconnect with their traditional culture via consumption. We postulate that this behaviour is rooted in a self-identity, consumer cultural renaissance (CCR), that has not been studied empirically. The primary aim of this study is to develop and validate a scale for CCR. With China as context, Study 1 developed a 7-item scale for CCR (CCRSCALE), and Study 2 validated that CCR is distinct from other social identities: ethnic identity, cultural identity and consumer ethnocentrism. Study 3 then demonstrated the influence, as well as the underlying mechanism, of CCR on product evaluation. The findings revealed that consumers with higher CCR dispositions evaluated products that symbolised traditional Chinese culture more favourably. Furthermore, they associated symbolic attributes (closeness, sense-of-belonging, and kinship) with the products. These attributes mediated the influence of CCR on product evaluation. A key theoretical contribution is that CCR extends the boundary of what is currently known about self-identities. The CCRSCALE will facilitate further research, and guide marketers in developing effective strategies to tap this nascent self-identity.
  • AI-driven HVAC control optimisation for enhancing energy efficiency and indoor environmental quality: A review of recent advances and emerging approaches
    Otoo, Christopher; Lu, Tao; Lü, Xiaoshu; Katsuyuki, Haneda; Yuan, Yanping (Elsevier, 2026)
    Artikkeli
    Heating, ventilation, and air-conditioning (HVAC) systems are central to building decarbonisation, yet improving indoor environmental quality (IEQ) often increases energy demand. This paper presents a systematic literature review of AI-driven HVAC control optimization for jointly improving energy efficiency and indoor environmental quality across different building types and climatic contexts. Following a PRISMA-based screening process, the review synthesizes 143 recent peer-reviewed studies published between 2020 and 2025. The analysis revealed supervised learning as the dominant ML technique for prediction and surrogate modelling and is frequently embedded in model predictive control (MPC). Reinforcement learning and deep reinforcement learning are increasingly applied to multi-objective supervisory control of setpoints, airflow, dampers and HVAC components because they offer model-free adaptability. Hybrid and ensemble approaches are emerging to improve robustness and trade-offs between energy efficiency and IEQ. Across diverse building typologies and climates, the reviewed studies reported an average energy savings of 40% compared with baseline cases, with several studies achieving savings above 50% while maintaining excellent IEQ. Despite these promising results, real-world validation remains limited as only 8 of 130 studies progressed to field or testbed deployment, highlighting a concerning gap between simulation-based research and practical validation. This review provides a comprehensive, context-sensitive mapping of AI-driven HVAC applications for enhancing both energy efficiency and IEQ in buildings.
  • Structural holes and brokering in triadic supply networks in industrial digital service innovations
    Momeni, Beheshte; Kohtamäki, Marko (Emerald, 2026)
    Artikkeli
    Purpose This study explores how industrial firms structure their relationships with technology providers and customers in digital service innovations (DSIs) – the use of digital technologies to create new value-added services. DSIs challenge supply network structures by reshaping roles and creating new dependencies. Therefore, understanding these changes is critical as they affect innovation outcomes, control over customer access, technology integration, and strategic positioning. Drawing on structural holes and brokerage, the study examines how industrial firms manage disconnections in these settings. Design/methodology/approach The study employs a qualitative multiple-case study approach across four DSIs. While each case has a triadic analytical setting, the empirical material is collected through 21 interviews with Finnish industrial firms and technology providers. Findings The study identifies that structural holes in DSIs are multidimensional, extending beyond relational gaps to include knowledge, cognitive, technical, and temporal gaps. Industrial firms structure triadic relationships through brokerage practices, including streamlining workflows, balancing priorities, controlling the flow of information and access, and mediating customer knowledge across firm boundaries. These practices allow industrial firms to selectively preserve, reshape, and connect relationships across gap dimensions and project phases. Originality/value The study extends research on structural holes, brokerage, and digital service innovation. The findings move the discussion beyond the binary of connected vs. disconnected by showing that actors may become connected in one dimension while other gaps remain. The study further shows that industrial firms sustain brokerage in DSIs through a synthesis capability: they filter, translate, sequence, and align customer, technical, and business knowledge without necessarily owning all digital capabilities. Finally, the continued acceptance of brokerage depends on whether other actors perceive the industrial firm's intermediation as adding value through coordination, customer understanding, and technology integration.