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Prior research has advanced several explanations for social media influencers' (SMIs’) success in the burgeoning computer-mediated marketing environments but leaves one key topic unexplored: the moderating role of SMIs in service failure and recovery strategies.

Drawing on a social constructivist perspective and an inductive approach, 59 in-depth interviews were conducted with millennials from three European countries (Italy, France and the United Kingdom). Building on social influence theory and commitment-trust theory, this study conceptualises four distinct pathways unifying SMIs' efforts in the service failure recovery process.

The emergent model illustrates how source credibility and message content moderate service failure severity and speed of recovery. The insights gained from this study model contribute to research on the pivotal uniqueness of SMIs in service failure recovery processes and offer practical explanations of variations in the implementation of influencer marketing. This study examines a perspective of SMIs that considers the cycle of their influence on customers through service failure and recovery.

The study suggests that negative reactions towards service failure and recovery are reduced if customers have a relationship with influencers prior to the service failure and recovery compared with the reactions of customers who do not have a relationship with the influencer.

This study examined the links between user-generated content (UGC), dissatisfied customers and second-hand luxury fashion brands. A central premise of luxury fashion brands is the perceived status and privilege of those who own such items. Despite their marketing logic emphasising exclusivity and rarity, they have broadened their reach by integrating new digital marketing practices that increase access to luxury brand-related information and create opportunities for consumers to purchase products through second-hand sellers.

Building on an inductive qualitative study of 59 millennials from three European countries (France, Italy and the UK) and by examining the mediating role of UGC and dissatisfied customers, this paper develops a conceptual framework of three clusters of second-hand luxury fashion goods customers: spiritual consumers, entrepreneurial recoverer consumers and carpe diem consumers.

The proposed SEC framework (spiritual consumers, entrepreneurial recoverer consumers, and carpe diem consumers) illustrates how the emerging themes interconnect with the identified consumers, revealing significant consumer actions and attitudes found in the second-hand luxury goods sector that influence the usage of UGC and its integration into service failure and recovery efforts

This study suggested that the perceptions of consumers seeking second-hand luxury fashion products differ from those who purchase new or never previously owned luxury fashion products. Overall, this research sets the stage for scholars to forge a path forward to enhance the understanding of this phenomenon and its implications for luxury fashion companies.

This study aims to explore children’s cognitions about data flows online and their understandings of algorithms, often referred to as algorithmic literacy or algorithmic folk theories, in their everyday uses of social media and YouTube. The authors focused on children ages 8 to 11, as these are the ages when most youth acquire their own device and use social media and YouTube, despite platform age requirements.

Nine focus groups with 34 socioeconomically, racially and ethnically diverse children (8–11 years) were conducted in California. Groups discussed data flows online, digital privacy, algorithms and personalization across platforms.

Children had several misconceptions about privacy risks, privacy policies, what kinds of data are collected about them online and how algorithms work. Older children had more complex and partially accurate theories about how algorithms determine the content they see online, compared to younger children. All children were using YouTube and/or social media despite age gates and children used few strategies to manage the flow of their personal information online.

The paper includes implications for digital and algorithmic literacy efforts, improving the design of privacy consent practices and user controls, and regulation for protecting children’s privacy online.

Research has yet to explore what socioeconomically, racially and ethnically diverse children understand about datafication and algorithms online, especially in middle childhood.

This paper aims to expand the scope and mitigate the biases of extant archival indexes.

The authors use automatic entity recognition on the archives of the Dutch East India Company to extract mentions of underrepresented people.

The authors release an annotated corpus and baselines for a shared task and show that the proposed goal is feasible.

Colonial archives are increasingly a focus of attention for historians and the public, broadening access to them is a pressing need for archives.

The case is designed to be used with the digital business model framework developed by Peter Weill and Stephanie Woerner of Massachusetts Institute of Technology (MIT) (Weill and Woerner, 2015) and is referred to as the W & W framework. This approach provides a useful structure for thinking through the strategic options facing environments ripe for digital transformation.

Research for this case was conducted through face-to-face interviews with the protagonist, as well as through a review of their business planning documents and other data and documentation provided by the founder. Some of the market and industry data were obtained using secondary research and industry reports. Interviews were digitally recorded and transcribed to ensure accuracy.

The case follows the story of Kurt Waltenbaugh, a Minnesota entrepreneur who shared the dream of using data analytics to reduce costs within the US health-care system. In early 2014, Waltenbaugh and a physician colleague founded Carrot Health to bring together their personal experience and expertise in both consumer data analytics and health care. From the beginning, they focused on how to use data analytics to help identify high-risk/high-cost patients who had not yet sought medical treatment. They believed that they could use these insights to encourage early medical interventions and, as a result, lower the long-term cost of care.

Carrot’s initial success found them in a consultative role, working on behalf of insurance companies. Through this work, they honed their capabilities by helping their clients combine existing claims data with external consumer behavioral data to identify new potential customers. These initial consulting contracts gave Carrot the opportunity to develop its analytic tools, business model and, importantly, to earn some much-needed cash flow during the start-up phase. However, they also learned that, while insurance companies were willing to purchase data insights for one-off market expansion projects, it was much more difficult to motivate them to use data proactively to eliminate costs on an ongoing basis. Waltenbaugh believed that Carrot’s greatest potential lay in their ability to develop predictive models of health outcomes, and this case explores Carrot’s journey through strategic decisions and company transformation.

This case is intended for either an undergraduate or graduate course on entrepreneurial strategy. It provides an effective introduction to the unique structure and constraints which apply to an innovative start-up within the health-care industry. The case also serves as a platform to explore the critical criteria to be considered when developing a digital transformation strategy and exposing students to the digital business model developed by Weill and Woerner (2015) at MIT (referred to in this instructor’s manual as the W&W framework). The case was written to be used in an advanced strategy Master of Business Administration (MBA) class, an undergraduate specialty health-care course or as part of a health-care concentration in a regular MBA, Master of Health Care Administration (MHA) or Master of Public Health (MPH). It may be taught toward the end of a course on business strategy when students are building on generic strategy frameworks and adapting their strategic thinking to the characteristics of specific industries or sectors. However, the case can also be taught as part of a course on health-care innovation in which case it also serves well as an introduction to the health-care payments and insurance system in the USA. Finally, the case can be used in a specialized course on digital transformation strategy in which case it serves as an introduction to the MIT W&W framework.

The case is particularly well-suited to students who are familiar with traditional frameworks for business strategy and business models. The analysis builds on this knowledge and introduces students interested in learning about the opportunities and challenges of digital strategy. Equally, the case works well for students with clinical backgrounds, who are interested in how business strategy can influence changes within the health-care sphere. Finally, an important aspect of the case design was to develop students’ analytical confidence by encouraging them to “get their hands dirty” and to carry out some basic exploratory data analytics themselves. As such, the case requires students to combine and correlate data and to experience the potentially powerful combination of clinical and consumer data. Instructors should find that the insights from these activities give students unique insights into the potential for of data analytics to move health care from a reactive/treatment ethos to a proactive/intervention ethos. This experience can be particularly revealing for students with clinical backgrounds who may initially be resistant to the use of clinical data by commercial organizations.