Purpose: This research examines the underlying psychological process of customers' impulsive buying on social media through the lens of customer inspiration. Drawing on the customer inspiration theory, it identifies the factors influencing customer inspiration on social media from three perspectives: source characteristics, platform characteristics and personal characteristics, which subsequently lead to impulsive buying. Since the conceptualization of source credibility includes three mostly reported components: attractiveness, expertise and trustworthiness, it further contrasts the effects of three dimensions of source credibility on customer inspiration.Design/methodology/approach: A structural equation model of customers' impulsive buying on social media was developed through the lens of customer inspiration. An online survey with 625 participants was conducted to test the hypotheses, and the partial least squares (PLS3) method was used.Findings: This research found that source credibility, social presence and customer innovativeness are antecedents of customer inspiration on social media, which positively influence the inspired-by state of the customers, which impacts the inspired-to state and further leads to impulsive buying. By comparing the three dimensions of source credibility, the authors found that attractiveness and expertise positively affect the inspired-by state, while trustworthiness has no significant effect.Originality/value: This research establishes the link between impulsive buying and customer inspiration, which provides a new psychological perspective to understand impulsive buying. In addition, it investigates the source characteristics of customer inspiration by comparing the effect of three dimensions of source credibility on customer inspiration, which provides the first evidence for connecting customer inspiration and source credibility.

Purpose: This research draws on self-determination theory and self-construal theory to investigate the effects of achievement-related gamification features on customers' brand attachment in online brand communities.Design/methodology/approach: Survey data (N = 523) were collected from customers of typical gamified online brand communities. The research model was examined with structural equation modeling using SmartPLS 3.2.Findings: Achievement-related gamification features positively affect customers' brand attachment via the intrinsic motives of autonomy, competence and relatedness, but not extrinsic motives. Relatedness motive exerts the strongest mediating effect between achievement-related gamification features and brand attachment, followed by competence and autonomy. Moreover, interdependent self-construal positively moderates the effects of achievement-related gamification features on intrinsic (autonomy, competence and relatedness) and extrinsic motives.Originality/value: Theoretically, this study contributes to the brand marketing literature by identifying gamification as a new antecedent for brand attachment. It also contributes to the gamification literature by demonstrating that achievement-related gamification features strengthen brand attachment via intrinsic motives but not extrinsic motives in the specific context of the online brand community. Meanwhile, the relatedness motive exerts the strongest mediating effect between achievement-related gamification features and brand attachment, followed by competence and autonomy. Moreover, this research provides the first empirical evidence that interdependent self-construal moderates the effects of achievement-related gamification features on intrinsic and extrinsic motives. Practically, managers can learn from the results that achievement-related gamification features should be designed to foster customers' intrinsic motives and brand attachment, especially those high in interdependent self-construal levels.

Modern commercial organizations have started to embrace the metaverse platform as a new channel for marketing their products and services. As prominent brand representatives, virtual influencers are responsible for strengthening consumer–brand connections in the metaverse. However, the ways in which virtual influencers contribute to consumers’ brand fidelity and evangelistic behaviors remain unknown. To address this gap, this work explores the essential factors that impact consumers’ intention to trust virtual influencers in the metaverse, purchase the products that they promote, and engage in brand evangelistic behaviors. Specifically, a new framework is developed that integrates metaverse virtual influencers’ marketing efforts, perceived coolness, anthropomorphism, brand evangelism, and brand fidelity into a comprehensive conceptual research model. Survey results obtained from 713 respondents in the US demonstrate that marketing efforts, perceived coolness, and anthropomorphism positively influence brand evangelism. The findings also indicate that consumers’ brand fidelity encourages brand evangelism and mediates the relationship between virtual influencers’ features, marketing efforts, and consumers’ brand evangelistic behavior. This study’s significance lies in its focus on the evolving marketing dynamics in the metaverse. It considers how virtual influencers’ features and marketing efforts impact consumers’ brand-related attitudes and behaviors in the metaverse, offering valuable insights for the advancement of metaverse marketing research and practice.

The coronavirus disease (COVID-19) pandemic has flooded public health organizations around the world, highlighting the significance and responsibility of medical crowdfunding in filling a series of gaps and shortcomings in the publicly funded health system and providing a new fundraising solution for people that addresses health-related needs. However, the fact remains that medical fundraising from crowdfunding sources is relatively low and only a few studies have been conducted regarding this issue. Therefore, the performance predictions and multi-model comparisons of medical crowdfunding have important guiding significance to improve the fundraising rate and promote the sustainable development of medical crowdfunding. Based on the data of 11,771 medical crowdfunding campaigns from a leading donation-based platform called Weibo Philanthropy, machine-learning algorithms were applied. The results demonstrate the potential of ensemble-based machine-learning algorithms in the prediction of medical crowdfunding project fundraising amounts and leave some insights that can be taken into consideration by new researchers and help to produce new management practices.