Augmented reality (AR) is a potentially disruptive technology that enriches the consumer experience and transforms marketing. With the surging popularity of AR in marketing practice, academic efforts to investigate its effects on consumer experience, response, and behavior have increased significantly. To obtain an integrated and comprehensive view of the front-line in AR marketing research and identify the gaps for future research, we analyze the existing AR marketing literature through a systematic literature review. Using 99 journal articles selected from the Web of Science core collections, this research sheds light on the general characteristics such as publication year, publication outlet, research design, and research method. Moreover, this research also gains insight into the AR marketing relevant factors such as application area, application context, AR type, and theoretical lenses. The findings of the analyses reveal the state-of-the-art of scholarly publications on AR marketing research. First, the number of journal articles on AR marketing increased rapidly in the past few years, and the journals that published articles on AR marketing cover a wide range of disciplines. Second, the empirical studies in most literature adopted the quantitative research design and used survey or experiment methods. Third, the studies in more than half of the journal articles used mobile AR applications in various online contexts. Fourth, the Technology Acceptance Model (TAM) and the Stimulus-Organism-Response (S-O-R) framework are the two most widely used theoretical lenses used in the literature. After that, the major application areas of AR in marketing are retail, tourism, and advertising. To identify the focal themes discussed in the three application areas, this research summarizes the studies by the outcome variables. Specifically, the outcome variables have five categories: technology-related, product-related, brand-related, tourist destination-related, and advertisement-related. Finally, this research proposes the agenda for future academic efforts in AR marketing.

Online discussion forums are an essential and standard setup in online courses to facilitate interactions among learners. However, learners’ inadequate participation in online discussion forums is a long-standing challenge, which necessitates instructor intervention and the design consideration of online learning platforms. This research proposes and studies the role of mandatory participation, i.e., learners’ participation in online course forums by instructors’ requirements, in fostering their voluntary participation and boosting their learning performance. This novel effect link between mandatory participation and voluntary participation has not been assessed in previous research. An empirical study is conducted using a large-scale dataset of 27,767 learners from a leading massive open online course (MOOC) platform in China. The findings indicate that besides its direct effect on learning performance, learners’ mandatory participation has a significant positive effect on their voluntary participation in online course forums, enhancing learning performance. Moreover, the effect of mandatory participation on voluntary participation varies across learner groups, being more prominent for early registrants than late registrants and part-time learners than full-time learners. This research contributes to the online learning literature by introducing mandatory participation as a viable approach to foster voluntary participation and boost learning performance through enhanced voluntary participation. It provides evidence on the effectiveness of the novel design feature of MOOC platforms that enables and facilitates the mandatory participation mechanism in online learning.

Purpose: This research investigates the impact of learners' non-substantive responses in online course forums, referred to as online listening responses, on e-learning performance. A common type of response in online course forums, online listening responses consist of brief, non-substantive replies/comments (e.g. “agree,” “I see,” “thank you,” “me too”) and non-textual inputs (e.g. post-voting, emoticons) in online discussions. Extant literature on online forum participation focuses on learners' active participation with substantive inputs and overlooks online listening responses. This research, by contrast, stresses the value of online listening responses in e-learning and their heterogeneous effects across learner characteristics. It calls for recognition and encouragement from online instructors and online forum designers to support this activity.Design/methodology/approach: The large-scale proprietary dataset comes from a leading MOOC (massive open online courses) platform in China. The dataset includes 68,126 records of learners in five MOOCs during 2014–2018. An ordinary least squares model is used to analyze the data and test the hypotheses.Findings: Online listening responses in course forums, along with learners' substantive inputs, positively influence learner performance in online courses. The effects are heterogeneous across learner characteristics, being more prominent for early course registrants, learners with full-time jobs and learners with more e-learning experience, but weaker for female learners.Originality/value: This research distinguishes learners' brief, non-substantive responses (online listening responses) and substantive inputs (online speaking) as two types of active participation in online forums and provides empirical evidence for the importance of online listening responses in e-learning. It contributes to online forum research by advancing the active-passive dichotomy of online forum participation to a nuanced classification of learner behaviors. It also adds to e-learning research by generating insights into the positive and heterogeneous value of learners' online listening responses to e-learning outcomes. Finally, it enriches online listening research by introducing and examining online listening responses, thereby providing a new avenue to probe online discussions and e-learning performance.

With a surging number of online courses on MOOC (Massive Open Online Course) platforms, online learners face increasing difficulties in choosing which courses to take. Online course reviews posted by previous learners provide valuable information for prospective learners to make informed course selections. This research investigates the effects of reviewer experience and expertise on reviewer competence in contributing high-quality and helpful reviews for online courses. The empirical study of 39,114 online reviews from 3276 online courses on a leading MOOC platform in China reveals that both reviewer experience and expertise positively affect reviewer competence in contributing helpful reviews. In particular, the effect of reviewer expertise on reviewer competence in contributing helpful reviews is much more prominent than that of reviewer experience. Reviewer experience and expertise do not interact in enhancing reviewer competence. The analysis also reveals distinct groups of reviewers. Specifically, reviewers with low expertise and low experience contribute the majority of the reviews; reviewers with high expertise and high experience are rare, accounting for a small portion of the reviews; the rest of the reviews are from reviewers with high expertise, but low experience, or those with low expertise, but high experience. Our work offers a new analytical approach to online learning and online review literature by considering reviewer experience and expertise as reviewer competence dimensions. The results suggest the necessity of focusing on reviewer expertise, instead of reviewer experience, in choosing and recommending reviewers for online courses.

Augmented reality (AR) has been widely used in sports broadcasting. However, little is known about viewer experience with AR in sports event videos. To identify key AR features as well as its advantages and drawbacks in sports event videos, this research conducted a qualitative study through a semi-structured interview with 30 participants. Content analysis on the interview transcript identified four salient features of AR in the sports event video context, i.e., informativeness, novelty, vividness, and telepresence. It also revealed three key advantages of AR to sports audiences, including game comprehension, enjoyment, and fan socialization, as well as two drawbacks, including distraction and inauthenticity. The qualitative study provides a theory-building process and results in a conceptual model, which, based on the net valence approach, postulates the relationships between AR features and viewers’ behavioral intentions through the mediation of perceived advantages and drawbacks.

The business environment is increasingly uncertain due to the rapid development of disruptive information technologies, the changing global economy, and the COVID-19 pandemic. This brings great uncertainties to investors to predict the performance changes and risks of companies. This research proposes a sequential data-based framework that aggregates data from multiple sources including both structured and unstructured data to predict the performance changes. It leverages data generated from the early risk warning system in China stock market to measure and predict organization performance changes based on the risk warning status changes of public companies. Different from the models in existing literature that focus on the prediction of risk warning of companies, our framework predicts a portfolio of organization performance changes, including business decline and recovery, thus helping investors to not only predict public company risks, but also discover investment opportunities. By incorporating sequential data, our framework achieves 92.3% macro-F1 value on real-world data from listed companies in China, outperforming other static models.