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Customer engagement marketing—defined as a firm’s deliberate effort to motivate, empower, and measure customer contributions to marketing functions—marks a shift in marketing research and business practice. After defining and differentiating engagement marketing, the authors present a typology of its two primary forms and offer tenets that link specific strategic elements to customer outcomes and thereby firm performance, theorizing that the effectiveness of engagement marketing arises from the establishment of psychological ownership and self-transformation. The authors provide evidence in support of the derived tenets through case illustrations, as well as a quasi-experimental field test of the central tenet of engagement marketing.

Studies about Islamist‐inspired terror attacks in the Western world have identified a recently declining impact on public opinion. What explains this development? I argue that the wider audience of terrorist attacks has become desensitized. Cognitive desensitization occurs when citizens increasingly expect an attack, reducing the likelihood of attitudinal change. Emotional desensitization occurs when audiences lose sensitivity to attacks, tempering emotional arousal. To assess the implications of desensitization, I analyze a survey conducted around the Berlin Christmas market attack in 2016 and account for baseline information of the surveyed individuals, an approach not used before due to data limitations. I find that attitudes like trust in government, national identification, and views of Islam remain unchanged. Sadness and anger are heightened in the immediate aftermath of the attack. The wider German audience may thus have expected an attack but still be emotionally sensitive to it in the short term. These findings are relevant as political leaders have justified important policy changes in fields like migration and even war making with reference to supposed shifts in public opinion after attacks.

By learning the PM2.5 readings and meteorological records from 2010-2015, the severity of PM2.5 pollution in Beijing is quantified with a set of statistical measures. As PM2.5 concentration is highly influenced by meteorological conditions, we propose a statistical approach to adjust PM2.5 concentration with respect to meteorological conditions, which can be used to monitor PM2.5 pollution in a location. The adjusted monthly averages and percentiles are employed to test if the PM2.5 levels in Beijing have been lowered since China's State Council set up a pollution reduction target. The results of the testing reveal significant increases, rather than decreases, in the PM2.5 concentrations in the years 2013 and 2014 as compared with those in year 2012. We conduct analyses on two quasi-experiments-the Asia-Pacific Economic Cooperation meeting in November 2014 and the annual winter heating-to gain insight into the impacts of emissions on PM2.5. The analyses lead to a conclusion that a fundamental shift from mainly coal-based energy consumption to much greener alternatives in Beijing and the surrounding North China Plain is the key to solving the PM2.5 problem in Beijing.

Word of mouth (WOM) plays an increasingly important role in shaping consumers’ behavior and preferences. In this paper, we examine whether latent personality traits of online users accentuate or attenuate the effectiveness of WOM in social media platforms. To answer this question, we leverage machine-learning methods in combination with econometric techniques utilizing a novel quasi-experiment. Our analysis yields two main results. First, there is a positive and statistically significant effect of the level of personality similarity between two social media users on the likelihood of a subsequent purchase from a recipient of a WOM message after exposure to the WOM message of the sender. In particular, exposure to WOM messages from similar users in terms of personality, rather than dissimilar users, increases the likelihood of a postpurchase by 47.58%. Second, there are statistically significant effects of specific pairwise combinations of personality characteristics of senders and recipients of WOM messages on the effectiveness of WOM. For instance, introverted users are responsive to WOM, in contrast to extroverted users. Besides this, agreeable, conscientious, and open social media users are more effective disseminators of WOM. In addition, WOM originating from users with low levels of emotional range affects similar users, whereas for high levels of emotional range, increased similarity usually has the opposite effect. The examined effects are also of significant economic importance, as, for instance, a WOM message from an extrovert user to an introvert peer increases the likelihood of a subsequent purchase by 71.28%. Our findings are robust to several alternative methods and specifications, such as controlling for latent user homophily and network structure roles based on deep-learning models. By extending the characteristics that have been theorized to affect the effectiveness of WOM from the observable to the latent space, tapping into users’ latent personality characteristics, and illustrating how companies can leverage the abundance of unstructured data in social media, our paper provides actionable insights regarding the future potential of social media advertising and advanced microtargeting based on big data and deep learning. The online appendix is available at https://doi.org/10.1287/isre.2017.0768 .

Conversational agents (CAs) primarily adopt knowledge scaffolding (KS) or emotional scaffolding (ES) to intervene in learners' knowledge gain and emotional experience in online learning. However, the ill-defined design for KS and ES, as well as insufficient understanding of their interactive effects on learning outcomes, have hindered the advancement of CAs in theory and practice. This study proposed systematic KS and ES design principles based on Zone of Proximal Development and growth mindset theories. We investigated their individual and combined impacts on knowledge gain and emotional experience. A quasi-experiment was conducted with 128 undergraduate students divided into four groups, corresponding to four distinct CAs: a non-scaffolding control group (CG), ES, KS, and Knowledge and Emotional Scaffolding (K＆ES) CA. The results showed that K＆ES-based CA had a significant impact on knowledge gain and emotional experience, with both being slightly improved compared to CG. Besides, KS-based CA had a positive effect on knowledge gain and emotional experience, while ES-based CA only slightly improved emotional experience compared to CG. The results validated the effectiveness of the proposed ES and KS design principles. The fine-grained analysis revealed a significant correlation between the achievement positive emotion and knowledge transfer, highlighting the importance of integrating KS and ES. In conclusion, this study offers valuable theoretical, methodological, and empirical insights for utilizing CAs to optimize online learning experiences.

An extensive literature in economics and finance has documented home bias , the tendency that transactions are more likely to occur between parties in the same geographical area rather than outside. Using data from a large online crowdfunding marketplace and employing a quasi-experimental design, we find evidence that home bias still exists in this virtual marketplace for financial products. Furthermore, through a series of empirical tests, we show that rationality-based explanations cannot fully explain such behavior and that behavioral reasons at least partially drive this remarkable phenomenon. As crowdfunding becomes an alternative and increasingly appealing channel for financing, a better understanding of home bias in this new context provides important managerial, practical, and policy implications. This paper was accepted by Lee Fleming, entrepreneurship and innovation .

Social-networking functions are increasingly embedded in online rating systems. These functions alter the rating context in which consumer ratings are generated. In this paper, we empirically investigate online friends’ social influence in online book ratings. Our quasi-experimental research design exploits the temporal sequence of social-networking events and ratings and offers a new method for identifying social influence while accounting for the homophily effect. We find that rating similarity between friends is significantly higher after the formation of the friend relationship, indicating that with social-networking functions, online rating contributors are socially nudged when giving their ratings. Exploration of contingent factors suggests that social influence is stronger for older books and for users who have smaller networks, and that relatively more recent and extremely negative ratings cast more salient influence. The online appendix is available at https://doi.org/10.1287/isre.2017.0741 .

Introduction/Main Objectives: This research aims to explore and analyze the effect of the COVID-19 pandemic on mental health status as measured by DASS-21. Background Problems: The prolonged impact of the COVID-19 pandemic on the global economy may have adversely affected mental health. A decrease in income and consumption and the uncertainties surrounding job security and business performance have been some of the main factors contributing to mental health issues. Novelty: This paper aims to evaluate the effect of the COVID-19 pandemic—as a natural experiment—on mental health measured by DASS-21 and how the effect of the pandemic varied across different socioeconomic subgroups. Research Methods: We conducted an online survey across Indonesia to collect self-reported mental health status and socioeconomic characteristics before and during the COVID-19 pandemic to measure its impacts on mental health. Finding/Results: Our results suggest that the COVID-19 pandemic has had an adverse impact on mental health, particularly in terms of anxiety and stress. The effect has been higher among individuals with lower self-efficacy, lower expenditure, and lower education levels. Conclusion: The health and economic crisis driven by the COVID-19 pandemic affected individuals' mental health, suggesting the need for appropriate policy responses.

Statistics anxiety is recognised as a major challenge facing students at all academic levels. It particularly affects their performance in statistics and research methods courses. This study investigates changes in students’ statistics anxiety based on the perceived utility of learning resources and class attendance within an introductory statistics course. Through the application of social cognition theory, we also examine the role of previous performance in mathematics, perceived competence in mathematics, and statistical self-efficacy as contributors to statistics anxiety. A quasi-experimental approach was used with undergraduate students completing a survey at the start and end of an introductory statistics course. Paired sample t-tests indicated a significant reduction in statistics anxiety. Additionally, Pearson correlation points to negative correlations between posttest statistics anxiety scores, perceived competence in mathematics, and statistical self-efficacy. Using hierarchical regression, class attendance was found to predict posttest statistics anxiety, with the smaller classes having a greater impact on statistics anxiety. These findings highlight the need for further interrogation of the role of class size and classroom activities with explorations of how these may reduce students’ statistics anxieties.

Purpose This study aims to examine if the participation of live-stream influencers (LSIs) affects tipping frequency on live streaming platforms, and further investigate the mediating and moderating mechanisms. Design/methodology/approach Quasi-experiment and difference-in-differences models are used for data analysis. Propensity score matching is used to address potential unobservable endogeneity. Findings Real-time live streaming data reveal that LSIs’ participation significantly improves tipping frequency in live streaming rooms. Also, more users are attracted to the live streaming rooms and more users become active in participation. Additionally, the positive impact of LSIs’ participation is enhanced in the live streaming rooms with a greater number of relationship links between users. Research limitations/implications The findings clarify the new role of influencers and reveal the mechanisms on how LSIs benefit the platforms. Practical implications The findings offer novel insights into implementing influencer marketing to interactive social media platforms, by encouraging influencer participation, user relationship building and influencer network growth. Originality/value This study highlights the value of LSIs for interactive social media platforms in terms of organic growth, revenue generation and cost reduction.