Urban destinations increasingly deploy events as strategic instruments to amplify competitiveness, stimulate visitation and sustain demand beyond peak seasons. However, their effective contribution to destination management, particularly in the post-pandemic urban tourism landscape, remains insufficiently evidenced. This study examines Lisbon through a mixed-methods design that combines a structured intercept survey of 388 non-resident visitors with a focus group involving nine directors of four- and five-star hotels in the metropolitan area. Quantitatively, events emerge as a relevant but segmented pull factor: their importance is concentrated among short-stay visitors, younger and highly educated travellers, and full-time professionals, who also register the highest satisfaction with event experiences. Satisfaction with events is generally favourable and is closely associated with their experiential, symbolic and emotional value. Qualitatively, hotel directors describe large concerts, congresses and public programmes as decisive triggers of demand, generators of extended stays and catalysts of repeat visitation, while noting that these effects are systematically under-captured by hotel booking and reporting systems. The discussion further reveals structural coordination gaps, including limited communication between event organisers, municipalities and accommodation providers, the absence of an integrated events calendar, and the lack of shared data on event-motivated travel. The study argues that events in Lisbon operate not only as temporal attractors but as experiential enhancers of destination image, memorability and competitiveness. Yet, their strategic potential remains only partially realised due to governance and information constraints that limit integrated planning and evidence-based management. Read more

Sustainable fashion is gaining interest from consumers. However, when buying apparel, individuals look for benefits and try to circumvent or lower barriers. This study aims to document motives and barriers in online buying of sustainable apparel, exploring the tendency of buying from online second-hand vendors, as well as platform features, and information deemed necessary when considering buying such products. The research employed a qualitative methodology, combining in-depth interviews with focus groups. A sample comprising 20 Romanian consumers for the in-depth interviews and 16 for the focus groups was used. Thematic analysis was employed to analyse the collected data. The study indicates sought-after benefits and envisaged barriers when buying online sustainable apparel, displaying perspectives particular to online second-hand vendors, provides evidence about online platform features considered important by consumers when buying sustainable fashion, clarifies what information is important in the buying decision of sustainable clothes and indicates reasons for using second-hand platforms to purchase clothes. The study expands the literature by investigating consumer behaviour constructs in a broad manner, by employing a dual-qualitative methodology and by providing information about the Romanian market. Practical recommendations are made to vendors and online platforms. Read more

Climate change represents one of the most pressing existential threats of our time, requiring coordinated, cross-domain responses that integrate technological, financial, and policy-oriented knowledge. This paper investigates the behavior of selected clean energy stock indices before, during, and after the COVID-19 crisis and applies  advanced machine learning methodologies, specifically Recurrent Neural Networks (RNNs) and Gated Recurrent Units (GRUs), to predict clean energy stock prices. The results provide new insights into the nonlinear dynamics of financial markets linked to the clean energy sector and show that both LSTM and GRU models outperform VAR in stock price forecasting, delivering superior accuracy. This research highlights the effectiveness of integrating traditional statistical models with deep learning techniques to improve forecasting performance. It promotes a deeper understanding of the behavior of this crucial industry, providing a bridge between finance, technology, and sustainability topics, necessary to achieving a resilient and equitable low-carbon economy. Read more