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Since its launch in 2005, YouTube has provided a unique platform for users worldwide to share and engage with content, leading to a rise in user-generated content (UGC), especially among youth. One of the most prevalent, yet under-explored, subgenres of UGC is the user-generated music video, where users integrate music and images with an element of performance or narrative; the current research deploys longitudinal analysis to describe the trends in youth-created music videos and how these trends have evolved in the early years of YouTube. Using a sample of 100 youth-created user-generated music videos uploaded to YouTube in 2007 and 2013, the authors investigate trends in production strategies, narrative content, and demographics. Compared to videos posted in 2007, youth-created music videos posted in 2013 featured more complicated editing techniques, less linear narratives, younger actors, more women, and were more likely to celebrate the self, mimicking the recent emergence of “selfie culture.” These findings are discussed with respect to YouTube’s role in reducing barriers to entry and providing a virtual space for youth-oriented content communities that thrive on engagement and social networking as strategies of identity development.

It has been well established that organizations often need to restructure themselves to meet new technological challenges. We review the organizational impact of a recent technological development, sometimes referred to as Web 2.0 that enables users to leverage the Internet and generate “user-generated content” by acting as a supplier, co-producer, or even innovator of products and services. We draw on the social studies of technology, including actor-network theory to develop a conceptual understanding of how this phenomenon is challenging deeply entrenched mental models among managers and management theorists as well as problematizing the way organizational boundaries are conventionally drawn.

This research is to identify how user-generated contents (UGC) affect a pre-trip decision on the booking of a guesthouse among international travelers. Online surveys are conducted among social network users who have booked an ecolodge in the past year. A snowball sampling is used, which posts a questionnaire link in social networks including Twitter, Facebook, and Instagram in addition to travel blogs. This study indicates a positive relationship between UGC and lodging selection. UGC is considered as a significant predictor of booking an environmentally friendly guesthouse. Among the UGCs, travelers' review is the most important one influencing guesthouse selection. Future studies may focus on other IT potentials such as “Gamification” or other types of content such as “Podcasts” or “live videos” to engage independent travelers.

This article reviews the quantitative marketing literature on artificial intelligence (AI) through an economics lens. We apply the framework in Prediction Machines: The Simple Economics of Artificial Intelligence to systematically categorize 96 research papers on AI in marketing academia into five levels of impact, which are prediction, decision, tool, strategy, and society. For each paper, we further identify each individual component of a task, the research question, the AI model used, and the broad decision type. Overall, we find there are fewer marketing papers focusing on strategy and society, and accordingly, we discuss future research opportunities in those areas.

The emergence of the platform economy is reorganizing work, employment, and value creation. The authors argue that the digital platforms are fracturing work itself as the places and types of work are being reorganized into a myriad of platform organized work arrangements with workplaces being potentially anywhere with Internet connectivity. The authors differ from most traditional narratives that focus solely upon either work displacement, a single type of platform-organized value-creating activity, or David Weil’s concentration solely upon the workplace. The authors recognize that even as some work is replaced, other work is being transformed; new work and old work in new arrangements is being created and recreated. The taxonomy begins with the workers employed directly by the platform and its contractors. The authors then introduce the category, platform-mediated work, which we divide into three groups: marketplaces such as Amazon; in-person service provision such as Uber and Airbnb; and remote service provision such as Upwork. The next category, “platform-mediated content creation,” is complex. The authors identify three groups of activities: consignment content creators that include services such as the app stores, YouTube, and Amazon Self-Publishing; non-platform organization content producers, which refers to the enormous number of workers occupied with creating and maintaining websites; and user-generated content which is the non-compensated value creation that ranges from content uploaded to Facebook, Instagram, etc. to reviews on sites such as Yelp. It is only when work and value creation is considered in all of these platform-based manifestations that we can understand the ultimate dimensions of the platform economy and comprehensively understand its implications for work.

We provide an overview of how artificial intelligence is transforming the identification, structuring, and prioritization of customer needs – known as the voice of the customer (VOC). First, we summarize how the VOC helps firms gain insights on using user-generated data. Second, we discuss the types of user-generated data and the challenges associated with analyzing each type of data. Third, we describe common methods, matched to the firms' goals and the structure of the data, that are used to analyze the VOC. Fourth, and most importantly, we map the methods to relevant applications, providing guidance to select the appropriate method to address the desired research questions.

Professional journalism has recently been studied through the lens of audience participation in the production of news online. While initial enthusiasm for democratisation and community reinforcement was significant, empirical evidence points towards unwillingness for fundamental reconstruction of journalistic practices. This chapter aims to map participatory journalism in Greece through the synthesis of accumulated research on the adoption of participatory features and practices in online news media and on audience perspectives of engaging in new roles during news process. Professionals seem hesitant to support a different but the traditional relationship with the users, while even users themselves get involved in activities that require little time and effort, not challenging journalistic norms via creative content production. However, both journalists and audience are positive towards a new collaborative way of managing and exploiting user-generated content, which can support participatory environments that reshape the incorporation of users' contributions in the daily workflows.

Advances in artificial intelligence have ushered in new opportunities for marketers in the domain of content generation. We discuss approaches that have emerged to generate text and image content. Drawing on the customer equity framework, we then discuss the potential applications of automated content generation for customer acquisition, relationship development, and customer retention. We conclude by discussing important considerations that businesses must make prior to adopting automated content generation.

This chapter is about online hate speech propagated via platforms operated by social media companies (SMCs). It examines the options open to states in forcing SMCs to take responsibility for the hateful content that appears on their sites. It examines the technological and legal context for imposing legal obligations on SMCs, and analyses initiatives in Germany, the United Kingdom, the European Union and elsewhere. It argues that while SMCs can play a role in controlling online hate speech, there are limitations to what they can achieve.