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 main aim of this chapter is to study the digital touchpoints influencing customers' decisions in the five-star hospitality industry. This chapter adopted a qualitative methodology in the form of semi-structured interviews. The findings suggest the preeminent role of online travel agencies and hotel websites as the two most powerful touchpoints influencing the decision-making of the customer and serving as the principal means of making the reservation at the hotel. It also stresses the growing influence of customer-owned touchpoints, particularly user-generated content, in influencing customer perception. This research emphasizes the significance of personalized engagement in influencing customer satisfaction and loyalty. Overall, the study presents practical managerial implications for hoteliers, offering insights on how to effectively interact with customers at each stage of their journey, thereby enhancing both service delivery and overall guest experience. © 2025, IGI Global Scientific Publishing. All rights reserved.

Abstract
The main aim of this chapter is to explore the role of social media in the internationalization of business-to-business (B2B) companies, addressing a remaining gap in the literature. It includes a qualitative study, where data from semi-structured interviews was subject to thematic content analysis. The study found that social media acts as a facilitator of internationalization in the B2B setting. While social media alone does not determine the success of internationalization efforts, it has become an essential tool for firms seeking to engage with global markets and maintain a competitive edge.The study provides relevant insights for managers, recommending that businesses should track social media performance to understand its impact on internationalization efforts and adjust strategies accordingly.

Abstract

Abstract
The development of artificial intelligence (AI) in the last decade has reshaped government operations and raised privacy concerns as automated processes become commonplace. This study aims to identify the main privacy issues associated with government use of AI in public services. Using a bibliometric analysis that includes co-citation of references and authors, bibliographic coupling, and keyword co-occurrence approaches, the study analyzed the literature on this topic through VOSViewer and the Web of Science database. Findings highlight significant privacy concerns: (i) opaque data-driven decisions, (ii) bias in predictive algorithms, (iii) difficulty obtaining explanations for decisions, (iv) mistrust in AI systems, (v) ethical lapses in AI execution, and (vi) trust deficit in government AI use. Additionally, 18 research questions are defined, addressing ethical limits of privacy in AI government use. A consensus in the literature urges governments to enact laws ensuring data privacy "by default" in AI decision-making and data management/transfer to third parties. © The Editor and Contributing Authors Severally 2025. All rights reserved.