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.

Abstract
The recent pandemic crisis has greatly impacted startups, and some changes are expected to be long-lasting. Small businesses usually have fewer resources and are more vulnerable to losing customers and investors, especially during crises. This study investigates how startups’ business processes were affected and how entrepreneurs managed this sudden change brought by the COVID-19 outbreak. Data were analyzed using qualitative research methods through in-depth interviews with the co-founders of eighteen startups. Results show that the three core business processes affected by the COVID-19 crisis were marketing and sales, logistics and operations, and organizational support. The way to succeed is to be flexible, agile, and adaptable, with technological knowledge focusing on digital channels to find novel opportunities and innovate. Additionally, resilience, self-improvement, education, technology readiness and adoption, close relationship with customers and other stakeholders, and incubation experience seem to shield startups against pandemic crisis outbreaks.