Abstract
Handheld controllers are standard in immersive virtual reality (iVR), but the rise of natural hand-based interactions exposes the limitations of hand gestures, especially for point-and-click tasks with graphical user interfaces (GUI). This shows the need to explore alternative hands-free selection methods. Unlike most studies focusing on the selection task itself, this work evaluates the impact of such methods on multiple dimensions when selections occur alongside another primary task. The tested methods were: head gaze + dwell, leaning, and voice; eye gaze + dwell, leaning, blinking, and voice; and voice-only. Controllers served as the baseline. Methods were further analyzed by pointing and confirming mechanisms. Four dimensions were analyzed: (1) iVR experience, (2) user satisfaction, (3) usability, and (4) efficiency and effectiveness. With 72 participants, results show hands-free methods provide comparable experiences to controllers, suggesting selection methods have a lower impact on the user experience when users focus on a primary task.

Abstract
This study provides a comprehensive quantitative review of the determinants of aggregate productivity growth using bibliometric and network-based methods. Drawing on 523 peer-reviewed articles published between 1973 and 2024 in Scopus and Web of Science, the study systematically maps the intellectual foundations, research fronts, and conceptual evolution of the field. Results show that research has remained overwhelmingly macro-focused, with 85%-90% of studies addressing aggregate-level determinants. Innovation, institutions, and technology diffusion dominate the literature, while firm-level (microeconomic) explanations, though increasing since the mid-2000s, remain secondary, largely addressing resource allocation. Competition, firm-level innovation, and organizational capabilities are underexplored despite their relevance for aggregate outcomes. By combining co-citation, bibliographic coupling, and keyword co-occurrence analyses, the study reveals the multilevel structure of productivity research, illustrating how macro theories, meso-level sectoral mechanisms, and micro-level firm dynamics interact. These findings highlight the limits of macro-centric explanations of productivity slowdowns and underscore the need to explore cross-level mechanisms, firm heterogeneity, and institutional interactions. This study offers a novel methodological benchmark and a structured agenda for research and policy, aiming to enhance productivity growth.

Abstract
We analyse a Stackelberg duopoly in which the leader faces uncertainty about the intercept demand, while the follower observes the realised demand and decides whether to enter the market after the uncertainty is resolved. The leader evaluates the uncertainty by maximising a mean-variance utility function that captures its risk aversion. We show that the leader's best-response problem admits a unique equilibrium. Our main result establishes the existence of a no-entry threshold for risk aversion: when the leader's risk aversion exceeds this threshold, entry is not optimal. This threshold is shown to be equal to the ratio of the expected value of the intercept demand to its standard deviation. Conditional on entry and on the realisation of the lowest demand outcome, three scenarios may arise for the leader: competition; monopoly without dumping, yielding zero profit; and monopoly with dumping, generating negative profit. We fully characterise the ex-ante expected profits of both firms, and also the corresponding ex-ante isoprofit curve in the model's parameter space.

Abstract
This paper aims to examine how Portugal and Brazil leveraged digital marketing to redefine their country brands during and after the COVID-19 pandemic. By focusing on the application of innovative digital strategies in tourism and culture, the research highlights the transformative potential of digital tools in overcoming pandemic-related challenges. Specifically, the study identifies key approaches such as the use of social media, data analytics, virtual reality, and influencer marketing that were strategically employed to maintain global engagement, foster international visibility, and support economic recovery. The results demonstrate that integrating digital marketing into country branding strategies not only sustained international recognition but also accelerated the adoption of sustainable tourism practices. By analyzing the cases of Portugal and Brazil, this paper provides actionable insights for policy-makers and practitioners seeking to align tourism growth with global sustainability goals. These findings underscore the critical importance of digital transformation in enhancing the resilience and competitiveness of the tourism sector in a post-pandemic world.

Abstract
Since its founding in 2003, the Journal of Academic Ethics (JAET) has established itself as a central venue for scholarship on the ethical dimensions of higher education, research, and academic governance. Despite its prominence, no systematic analysis has charted the evolution of its intellectual profile over time. This study offers a comprehensive bibliometric overview of JAET's publications from 2003 to 2025, mapping patterns of authorship, citation, and thematic development. The dataset comprises records retrieved from Scopus for the period 2005-2025 and from JAET's own archives for 2003-2004. Using bibliometric indicators and network visualizations generated with VOSviewer, the analysis identifies key shifts in the journal's conceptual orientation, from early emphases on misconduct and plagiarism toward broader engagements with institutional integrity, governance, diversity, and the ethics of digital transformation. A narrative comparison with related journals situates JAET's distinctive integrative role in linking philosophical reflection with empirical inquiry and policy discourse. The findings reveal increasing interdisciplinarity, international collaboration, and methodological diversification, marking the maturation of academic ethics as a field. Looking forward, emerging challenges such as artificial intelligence, open science, and global research governance underscore JAET's continuing function as both a barometer and catalyst of ethical thought in academia.

Abstract
Speckle-based fiber optic sensors are well-known to offer high sensitivity but are strongly limited on the in terrogation side by low camera frame rates and dynamic range. To address this limitation, we present a novel interrogation framework that explores event-based vision to achieve high throughput, high bandwidth, and low-latency speckle analysis of a multimode optical fiber sensor. In addition, leveraging an optimized decomposition of the raw event streams through multi-point calibration and machine learning optimization, our approach also proves capable of isolating simultaneous deformations applied at distinct points. The experimental results vali date the methodology by separating the signals of four piezoelectric actuators over a 400 Hz-20 kHz range with minimal crosstalk applied over varying distances from 3 cm to 75 cm. Overall, these results establish event-driven speckle interrogation as a new versatile platform for real-time, multi-point acoustic sensing and pave the way for its application in complex and unstructured environments in future works.