Belém Barbosa

Abstract
Technological developments are presenting new ways for companies to organize their businesses and offer new products, services, and experiences to their customers. The Metaverse allows the participation and interaction of individuals in immersive experiences that merge virtual and real worlds. The adoption of metaverse platforms by companies worldwide is growing steadily, with the potential to change business in various industries, including tourism. However, the literature on the Metaverse applied to tourism is very scarce. This chapter addresses this gap by exploring a case study of the implementation of a Metaverse strategy by a Portuguese wine brand, Sandeman, as part of their wine tourism experience offerings. The case study is built on secondary data, observation, and interviews with tourists. © 2025, IGI Global Scientific Publishing. All rights reserved.

Abstract
This study investigates the use of 9-ending pricing strategies in e-commerce by analyzing over 50,000 shoe prices. Using web scraping and a logit model from a German online retailer, the research assesses how product attributes influence the adoption of 9-ending prices. Key findings reveal that 9-ending prices are predominantly used for female and newly introduced products, as well as for items with lower and standard prices. The study also explores the effects of exclusivity and sustainability on pricing strategies, showing that their impact varies with different 9-ending price categories. Overall, this research demonstrates the complex nature of 9-ending pricing strategies, with the 9-zero removal model supporting all hypotheses, whereas the 99c and 95c models show differential effects. This extends our understanding of pricing tactics in online retail and highlights the significance of product attributes for marketing and sales strategies.

Abstract
The main aims of this chapter were to explore metaverse branding by identifying the main trends and contributions in extant literature. Through a bibliometry and the critical analysis of the main contributions in the literature, the chapter proposes a metaverse branding conceptualization, which shows how immersive metaverse experiences that provide multi- dimensional value enhance brand engagement, which leads to increased brand awareness, brand love, satisfaction, trust, and brand equity. These factors ultimately drive online and offline purchases and strengthen brand loyalty. Overall, this chapter and the proposed framework provide relevant insights for both managers defining metaverse branding strategies, and researchers interested in these topics. © 2025, IGI Global Scientific Publishing. All rights reserved.

Abstract
The telecommunications sector faces a major challenge of high customer churn. Despite this, there is still a lack of research that explores the switching intention for telecommunication services, particularly with bundle services that currently dominate the market. This study aims to provide insight into consumer behaviour regarding bundle telecommunication services by examining the factors that impact satisfaction and switching intention, both directly and indirectly. Eighteen hypotheses were defined based on the literature, and were tested through a quantitative study with 910 bundle service customers using structural equation modelling with Smart-PLS. The results show that internet and television services have the strongest indirect impact on switching intention, mediated by overall satisfaction and loyalty. Additionally, the results indicate that switching costs and barriers do not significantly affect switching intention, and surprisingly, perceived contractual lock-in positively influences switching intention. This study provides a comprehensive understanding of the customer experience with bundled telecommunications services and offers relevant insights for telecommunication managers to prevent customer loss to competitors.

Abstract
This study aims to test the forecasting accuracy of recently implemented econometric tools as compared to the forecasting accuracy of widely used traditional models when predicting cash demand at ATMs. It also aims to verify whether the pandemic-driven change in market conditions impacted the predictive power of the tested models. Our conclusions were derived based on a data set that consisted of daily withdrawals from 61 ATMs of one of the largest European ATM networks operating in Krakow, Poland, and covered the period between January 2017 and April 2021. The results proved that the recently implemented methods of forecasting ATM withdrawals were more accurate as compared to the traditional ones, with XGBoost providing the best forecasts in the majority of the tested cases. Moreover, it was found that the pandemic-driven change in market conditions affected the predictive power of the models. Both of these results seem particularly useful for improving the efficiency of ATM networks.