Abstract:

This article examines whether Polish and European Union legal frameworks, supported by institutional oversight, provide consumers with sufficient protection against the adverse consequences of decisions made by artificial intelligence (AI) systems, and whether legal gaps persist in this area. The study aims to identify and assess these gaps and to formulate recommendations for strengthening consumer safeguards in the age of algorithmic decision-making. A qualitative descriptive analysis was applied to selected Polish and international legal acts and scholarly literature, including the Act on Competition and Consumer Protection of 16 February 2007 and Regulation (EU) 2024/1689 of the European Parliament and of the Council (the AI Act), along with expert opinions from Polish legal scholars. The findings indicate that while existing Polish and EU provisions, reinforced by institutional supervision, afford consumers a degree of protection, this coverage does not extend to all potential risks associated with AI use in consumer markets. Significant legal gaps remain, and the development of new laws that keep pace with the rapid evolution of AI poses a substantial legislative challenge. As a result, fully eliminating these gaps in the near future may prove difficult, if not impossible.

Abstract:

Systematic literature reviews (SLR) are essential for synthesizing research across disciplines, yet their manual execution is time-consuming and increasingly challenging due to the rapid proliferation of academic publications. This study examines the role of artificial intelligence (AI) in the SLR process within management sciences. Drawing on established SLR methodologies, particularly from health sciences where automation is widely applied, this research identifies AI’s role in contributing to key review stages, including literature identification, selection, data extraction, synthesis, and reporting. This study itself applied a systematic literature review methodology, querying Scopus and Web of Science, complemented by AI-based tools (Elicit and SciSpace) to extend coverage. Backward and forward citation searches were also conducted, resulting in a final sample of 93 publications. The findings from this sample suggest that AI enables researchers to shift roles from literature examiners to managers of the review process, overseeing AI tools executing repetitive and timeconsuming tasks. However, despite the benefits of using AI in generating SLRs, its application in management research presents challenges, particularly in handling context-dependent and interpretative analyses. The study highlights both the transformative potential and the critical need for human oversight in AI-assisted reviews. Limitations include the reliance on existing automation techniques developed for health sciences and the exclusion of certain literature sources. Future research should explore AI’s effectiveness in managing SLRs, ethical considerations, and hybrid human–AI collaboration models. AI’s growing role in academic research entails the need to balance automation with scholarly rigor and methodological integrity.

Abstract:

The phenomenon of hype is a central element of the contemporary computer game market, yet its role as an independent factor mediating consumer decision-making remains under-researched. This article aims to identify the importance of hype in consumers’ purchasing decisions and to assess whether hype can be regarded as a commercialization tool in the computer game industry. The study is based on an integrative literature review and a multiple case study of four AAA titles: Red Dead Redemption II, Cyberpunk 2077, Grand Theft Auto VI and The Witcher 4. Gartner’s Hype Cycle is adapted to the computer game market and combined with marketing indicators (e.g., trailer views, social media engagement, pre-orders, sales dynamics, user and critic ratings) to propose an operationalization of hype across pre-release and post-release phases. The analysis shows that hype is not a spontaneous phenomenon but the outcome of deliberate and capital-intensive promotional strategies that can significantly shape consumer expectations, emotions and fear of missing out, and thereby influence purchasing decisions. At the same time, mismanaged hype may lead to disappointment, reputational damage and regulatory scrutiny, as illustrated by the case of Cyberpunk 2077. The article concludes that hype functions as a powerful, albeit risky, commercialization tool.

Abstract:

Worries and concerns are long recognized as barriers to technology adoption in organizations (Bedué & Fritzsche, 2022; Mariani et al., 2022). Artificial intelligence (AI) exemplifies this tension: While it promises significant benefits (Wilson & Daugherty, 2018), individuals and organizations also fear its potential harms, from job loss (Kelly, 2023) to biased or opaque decision making (Rainie et al., 2021). Such concerns can shape both individual behavior (Shell & Buell, 2022) and organizational adoption strategies, particularly for generative AI (e.g., ChatGPT) (IBM Institute for Business Value, 2024).

This study analyzes survey data from over 10,000 U.S. adults (Pew Research Center, 2021) to investigate whether worries about AI and related technologies are expressed uniformly or cluster into distinct attitudinal patterns. Using cluster analysis and ANOVA, we identify three groups with differing levels of concern and show that these groups vary systematically across specific technologies, following a consistent directional order.

Our findings contribute to research on technology acceptance by highlighting attitudinal heterogeneity and by linking individual-level dispositions to organizational challenges in AI adoption. They also provide practical insights for managers seeking to address concerns that may otherwise slow the integration of AI into organizational practice.

Abstract:

Objective: This article clarifies how the terms university “spin-off” and “spin-out” are used across scholarship, institutional reporting, and policy, and proposes operational definitions to distinguish the two notions that enhance measurement comparability while accommodating contextual diversity.

Methodology: We conduct a narrative review with emphasis on post-2020 work, synthesize institutional standards (OECD/Eurostat, European Commission, AUTM), and run an exploratory co-occurrence mapping of Scopus-indexed publications (2015–2025) using VOSviewer with a harmonizing thesaurus.

Findings: Two complementary lenses – IP-centric and knowledge-/founder-linked – structure the conceptual landscape, while institutional regimes create distinct “measurement windows.” Bibliometric analysis reveals five clusters (technology transfer, ecosystems, finance/policy, definitional core, HEI entrepreneurship). Overlay results show growing emphasis on ecosystems and finance. We propose operational definitions of academic spin-off and spin-out, supported by a minimal descriptor set for comparability.

Practical implications: Dual reporting using standardized descriptors enables universities, TTOs, and policymakers to better capture both IP-intensive and software/data-driven pathways, including those common in CEE systems with indirect commercialization routes.

Originality/value: The framework aligns scholarly lenses with the EU’s shift from “intellectual property” to “intellectual assets,” offering operationally useful definitions that support cross-study and cross-country comparability. Research limitations/implications: Results reflect Scopus coverage and keyword indexing. Further work should integrate transaction-level data and mixed-method evidence from founders and TTOs.