Abstract
In many e-commerce platforms user communities share product information in the form of reviews and ratings to help other consumers to make their choices. This study develops a new theoretical framework generating a bipartite network of products sold by Amazon.com in the category musical instruments, by linking products through the reviews. We analyze product rating and perceived helpfulness of online customer reviews and the relationship between the centrality of reviews, product rating and the helpfulness of reviews using Clustering, regression trees, and random forests algorithms to, respectively, classify and find patterns in 2214 reviews. Results demonstrate: (1) that a high number of reviews do not imply a high product rating; (2) when reviews are helpful for consumer decision-making we observe an increase on the number of reviews; (3) a clear positive relationship between product rating and helpfulness of the reviews; and (4) a weak relationship between the centrality measures (betweenness and eigenvector) giving the importance of the product in the network, and the quality measures (product rating and helpfulness of reviews) regarding musical instruments. These results suggest that products may be central to the network, although with low ratings and with reviews providing little helpfulness to consumers. The findings in this study provide several important contributions for e-commerce businesses' improvement of the review service management to support customers' experiences and online customers' decision-making.

Abstract
The internet massification and e-commerce growth that have been driven by “millennials” and the coronavirus pandemic cannot remain indifferent to luxury brands. These brands have had to adapt to e-commerce and develop an online shopping experience which satisfies its customers, so that they repeat purchase. Therefore, the main objective of this research is to understand the main impacts of shopping experience on luxury brand websites on satisfaction and loyalty. A model which analyzes the relationship between the three constructs was developed and information was gathered through an online survey, from which resulted 356 valid answers. Through the analysis of data collected and using a structural equation model, using SmartPLS software, we realized that online shopping experience is positively related to satisfaction. Loyalty, in turn, is positively affected by brand satisfaction. This study makes an important contribution to luxury brands and to people in charge of marketing and online platforms selling luxury goods. It helps brands understand that enhancing online shopping experience can positively impact satisfaction and loyalty levels. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Abstract
Companies are increasingly focusing on audiovisual content as part of their strategy, and YouTube being a massive video hosting platform that makes content sharing possible has been the most successful platform for reaching their consumers products and services. Researches have proven that user-generated content impacts brand engagement, loyalty and firm revenue. Therefore, it is necessary to determine what factors stimulate the creation of consumers perceived value from user-generated content, on social media. We analyze the driving factors of user-generated content on YouTube and its influence on consumers perceived value. The sample data consists of 282 YouTube users’ responses collected through an electronic survey. This research contributes toward the digital content marketing literature by complementing existing research exploring consumer behavior on social media, assessing the driving factors of user-generated content and its impacts on customer perceived value. The study findings provide academic contributions and several challenges for firm and user-generated content, on actions they can tackle. Finally, based on the study limitations, we discuss future research in generated content in social media, providing insights for future research directions. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Abstract
In this paper we examine prior research, which has been studying the effects of switching costs on customer retention, within online and offline markets. The empirical studies in the area reveal contrasting results: (1) switching costs are a stronger predictor of customer retention than customer satisfaction alone; (2) the main effect of switching costs moderates the relationship between satisfaction and customer retention; (3) conversely, the lack of main effects reflects the interaction effects indicating that switching costs have an even greater impact on customer retention than under satisfaction variation levels. These power asymmetries reveal a conflicting role of switching costs across industry and marketplaces. We also observe a significant bias in favor of service industries with high switching costs. Based on this meta-analytical research we propose a theoretical base to support the path structural relationship between the constructs providing a nomological framework to future research. Finally we draw some conclusions, suggest future research directions and make managerial recommendations. © 2009 IADIS.

Abstract
In this paper we examine how the virtual recommendation may influence co-shopping behavior specifically associated with "match dyad" within online social networks. Drawing on better match theory in economics and social network literature, we develop and propose a conceptual model describing how different antecedents of customer's recommendation influence their intentions and leads to positive outcomes, such as recommendation behavior and coshopping influence. We also describe which consumer and network characteristics accentuate this influence examining the moderator effect of customers' incentives, network structure and interactivity. The study contributes to propose that "match dyad" in small social network provide high-quality valuable information that will improve the match between the product and the potential customer and, matched online social connections, act as a proxy for information about the potential market that is difficult and expensive to measure or observe directly such as customer needs, and to access. The paper concludes with a consideration of the implications of predictions for marketing practice.

Abstract
Artificial intelligence (AI) has altered our world in numerous ways. Although its application has benefits, the underlying issues surrounding privacy and security in AI need to be understood, not only by the organizations that use it but also by the users that are susceptible to its vulnerabilities. To better understand the impact of privacy and security in AI, this chapter reviews the current literature on artificial intelligence, trustworthiness, and privacy and security concepts and uses bibliometric techniques to understand and identify current trends in the field. Finally, the authors highlight the challenges facing AI and machine learning and discuss the results obtained from the bibliometric analysis, which provides insight into the several implications for managers and contributions to future research and policy. © 2023, IGI Global. All rights reserved.