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Accurate power forecasting from renewable energy sources (RES) is crucial for integrating additional RES capacity into the power system and realizing sustainability goals. This work emphasizes the importance of integrating decentralized spatio-temporal data into forecasting models. However, decentralized data ownership presents a critical obstacle to the success of such spatio-temporal models, and incentive mechanisms to foster data-sharing need to be considered. The main contributions are a) a comparative analysis of the forecasting models, advocating for efficient and interpretable spline LASSO regression models, and b) a bidding mechanism within the data/analytics market to ensure fair compensation for data providers and enable both buyers and sellers to express their data price requirements. Furthermore, an incentive mechanism for time series forecasting is proposed, effectively incorporating price constraints and preventing redundant feature allocation. Results show significant accuracy improvements and potential monetary gains for data sellers. For wind power data, an average root mean squared error improvement of over 10% was achieved by comparing forecasts generated by the proposal with locally generated ones.

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Establishing the relationship between online communication channels and the stages of the consumer decision-making process was the aim of this research. A review of online communication channels and consumer behavior models was conducted for this purpose. Subsequently, three experiments (car glass repair, retail of clothing and sports equipment, and retail of books and technological products) were carried out that consisted of questionnaires that were applied in companies belonging to different industries. The questionnaires were used to measure the expectations and preferences of consumers at each stage for each channel. The results showed that there is no relationship between online communication channels and the stages of the decision-making process. They also revealed a gap between expectations and preferences for each channel in each phase. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

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This paper explores the main challenges and barriers to VR/AR adoption and categorizes common activities performed with these technologies, explaining each specific factor affecting them. After reviewing literature on metaverse retailing, channel strategies, VR/AR technologies, and user experiences, a conceptual framework was developed. Data from the Voice of the Consumer: Digital Survey (20202024) in over 20 countries was analyzed, using Pearson's correlation, factor analysis, and multiple linear regressions. The results point that key challenges for VR/AR adoption include security, privacy, content, price, headset-free experiences, digital fatigue, and poor experiences. Gaming is the most common VR/AR activity, while metaverse retailing activities like shopping and virtual try-ons have fewer users. Practical considerations drive metaverse retailing, unlike gaming, which is mainly hedonic. Privacy concerns, safety risks, poor experiences, and lack of knowledge surprisingly increase VR/AR usage for metaverse retailing, indicating informed consumers or threshold characterization of these variables. Additional insights were found for tourism, hospitality, and gaming activities. Theoretical implications, insights, and potential actions for retailers and tech companies are discussed, along with limitations and suggestions for further research.

Abstract
Decred is a cryptocurrency with its own blockchain and has several similarities with bitcoin but implements a governance model that resembles a company with thousands of investors. These stakeholders invest their coins, receive the right to direct the project as they see fit and are rewarded for doing so. Everyone else not invested may use the coin as means of exchange, trading it for goods or services or consuming other services provided by the blockchain as the digital notary. This paper investigates how Decred project created its own version of money and implemented security measures to improve governance and remove trusted third parties from money issuance and e-voting. This topic is particularly relevant to understand how blockchain technologies improve governance and avoid the tyranny of the majority. In order to reach our goal, we use multi-agent simulation and statistical modelling to verify to what extent Decred is capable of providing a predictable, scarce, trustworthy digital asset. We show that Decred increased blockchain security with its hybrid proof-of-work+proof-of-stake (PoW + PoS) security mechanism, making an attack more expensive. © 2025 Inderscience Enterprises Ltd.