Silmäile
Hakuohje

Osuva

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.

Kokoelmat Osuvassa

Viimeksi tallennetut

  • Managing Diversity in SMEs in Practice
    Šilenskytė, Ausrine (toim.) (Vaasan yliopisto, 2026-09-30)
    Kirja
    Diversity is no longer a peripheral issue for small and medium-sized enterprises (SMEs). It shapes their resilience and innovation capabilities, influences talent management and customer relationships. This book brings together authentic cases from technology and service businesses, inviting readers to grapple with managerial situations that involve diversity management in the context of SME business development, including product and service development, strategy implementation, project management, team management, and other related areas. Combining practical relevance with evidence-based perspectives, this edited volume presents a rich collection of cases that equip current and future managers, as well as learners, with the knowledge, skills, and strategic capabilities required to build and grow inclusive organisations. The book is accompanied by detailed teaching notes (available online in open-access format) that demonstrate how each case can be used in higher and vocational education to model managerial actions and decision-making in inclusive organisations.
  • Human factors in generative AI companions: a systematic literature review of trust, relational dependence, psychosocial outcomes, and responsible adoption
    Piispanen, Joni-Roy; Myllyviita, Tinja; Vakkuri, Ville; Rousi, Rebekah (Elsevier, 2026)
    Artikkeli
    Context Generative AI companions and socially oriented chatbots are systems designed or used to sustain social, affective, or relational interaction. They increasingly function as persistent interaction partners across systems ranging from earlier rule-based, retrieval-based, and pre-LLM architectures to contemporary generative AI companions. Prior reviews and conceptual models have largely examined user-facing relational mechanisms or specific ethical and legal issues. Yet, how these mechanisms connect with platform, organizational, and regulatory conditions remains fragmented. Objectives This study addresses this gap by synthesizing human-factor and responsible-adoption concerns across technology generations and developing an evidence-calibrated multi-stakeholder framework spanning human, organizational, technological, and regulatory layers. Methods We conducted a PRISMA-guided systematic literature review of records retrieved from Scopus, ACM Guide to Computing Literature via the ACM Digital Library, Web of Science Core Collection + MEDLINE, and IEEE Xplore. We examined English-language, peer-reviewed publications made available between 2005 and 2024. From 1699 identified records, 42 publications were included and analyzed using thematic synthesis. Results Four analytical themes were identified: usability and relational affordances in interaction; trust, attachment, over-reliance, and psychosocial outcomes; responsible adoption, platform design, and organizational mediation; and governance, privacy, and accountability. Technology emerged as a cross-cutting mediator linking design features, user experience, organizational practice, and governance concerns. The first two themes drew on 29 and 33 materially contributing publications, whereas the latter themes each drew on 12 and represent emerging synthesis areas. Conclusion The review shows that responsible adoption of AI companion systems requires attention not only to user experience, but also to platform incentives, design affordances, data practices, service continuity, and governance mechanisms. The framework's distinctive contribution is to connect these concerns across stakeholder layers while preserving differences in evidentiary maturity. It is a provisional analytical heuristic, not a validated causal model.
  • Artificial intelligence, inclusion, and the future of work at European SMEs
    Diduc, Sniazhana; Boey, Anita; Šilenskytė, Aušrinė (toim.); Fletcher, Margaret (toim.); Butkevičienė, Jurgita (toim.); Jayton, Chenthuran (toim.) (Edward Elgar, 2026)
    Artikkeli
    Consulting4Future, an Austrian consulting firm led by CEO Barbara Sabitzer, is reassessing its service portfolio aimed at supporting small- and medium-sized enterprises (SMEs) in Europe with technological solutions and training for the effective use of artificial intelligence (AI) in the workplace. Drawing on customer feedback, the company has identified that differences in employees’ vocational backgrounds, academic qualifications, and non-linear career paths often complicate communication, onboarding, and skill development when AI-enabled tools are introduced in SMEs. At the same time, the adoption of AI-driven solutions has raised ethical concerns related to employee profiling, bias, and fairness. While Consulting4Future initially concentrated on delivering technical AI solutions, the firm is now increasingly integrating diversity, equity, and inclusion (DEI) considerations into its approach, particularly with respect to multilingualism and neurodiversity in everyday work practices. The case invites learners to critically examine how AI can simultaneously promote and undermine inclusion in SMEs.
  • Hierarchical multi-agent drl-based secondary control for real-time voltage and frequency regulation in renewable-integrated microgrids
    Razmi, Darioush; Razmi, Peyman; Rodriguez, Jose; Garcia, Cristian; Zhang, Zhenbin (Elsevier, 2026)
    Artikkeli
    The integration of inverter-based microgrids (MGs) often induces variations in system characteristics and disturbances in the network. In islanded operation, voltage and frequency oscillations arise due to the lack of synchronization with the main grid. Ensuring reliable operation under such conditions requires advanced control techniques and proactive monitoring. This paper proposes an intelligent multi-agent secondary control architecture based on the Deep Deterministic Policy Gradient (DDPG) algorithm, where reinforcement learning (RL) agents dynamically adjust the parameters of proportional–integral (PI) controllers to mitigate disturbances and adapt to system uncertainties and varying operating conditions. The proposed framework employs a two-layer hierarchical structure. At the lower layer, two independent RL agents regulate frequency and voltage by tuning PI controller gains in real-time, ensuring stable operation under fluctuating loads and distributed generation. The upper layer incorporates a supervisory agent that monitors harmonic distortion and computes corrective signals sent to the droop controller, enabling coordinated adaptation and enhancing dynamic stability by reducing transient oscillations. As a proof-of-concept, the proposed multi-agent framework is implemented on a single DG unit within a four-converter microgrid, demonstrating the potential for improved dynamic performance under realistic operational scenarios. Validation in MATLAB/Simulink demonstrates substantial improvements in system performance. Frequency settling time decreased from 0.19 s (at Kp=0.3) to 0.10 s (at Kp=0.1), and voltage settling time decreased from 0.20 s (at Kp=0.3) to 0.13 s (at Kp=0.1). Total harmonic distortion (THD) significantly reduced from 2.07% (at Kp=0.3) and 2.03% (at Kp=0.2) to 0.68% (at Kp=0.1). These results highlight the scalability and effectiveness of the proposed multi-agent DDPG-based secondary control, offering a reliable and intelligent solution for advanced MG energy management under realistic operating conditions.
  • Entrepreneurial bricolage in the branding efforts of international new ventures
    Kusi Appiah, Emmanuel (Elsevier, 2026)
    Artikkeli
    This study examines how B2B international new ventures (INVs) develop their brands through bricolage-driven improvisational practices and how these practices influence brand coherence as the ventures progress through different phases of development. Drawing on entrepreneurial bricolage and entrepreneurial branding research, the study employs a comparative, interview-based multiple case design involving eight Finnish B2B INVs. The dataset comprises 19 semi-structured interviews and firm-generated materials, analysed through an iterative and abductive coding process. The findings reveal two practices, namely identity patchworking and improvisational signalling, which show how bricolage shapes branding in resource-constrained internationalisation contexts. These practices are most visible in the transition from early to growth phases and they produce distinctive branding outcomes. Yet coherence drift is most likely when these practices accumulate without stable reference points or strategic anchoring as the venture evolves. This demonstrates that bricolage exerts a double-edged influence on B2B INV branding by fostering brand development under constraint while also producing accumulated improvisations that can erode coherence. This study contributes to B2B marketing and entrepreneurial branding research by developing a retrospective reconstruction of an inferred branding trajectory model and advancing propositions that explain how bricolage influences branding in INVs.