Ali Selcuk Can

Purpose: This study compares the effectiveness of metahuman and human social media influencers in promoting cultural city brands. It examines how influencers shape tourists’ brand loyalty through brand charisma and reputation, and whether brand familiarity moderates the link between social media influencer (SMI) type and brand charisma. Design/methodology/approach: We conducted two randomised, between-subjects online experiments, each set in a different UNESCO World Heritage city (Rome and Safranbolu) and on a distinct platform (Instagram and Facebook). Findings: Metahuman SMIs had a greater positive effect on brand loyalty than human influencers. Brand charisma emerged as the key driver, operating in sequence with brand reputation, whereas reputation alone did not significantly mediate the relationship. The influence of metahuman SMIs on brand charisma diminished when people were already familiar with the cultural city brand. Research limitations/implications: The findings are based on controlled experiments with non-probability online samples, which limits generalisability. Future research should incorporate real social media interaction data and behavioural measures, revalidate the charisma construct and examine how charisma relates to brand image and brand equity. Practical implications: Metahuman SMIs can help lesser-known cultural city brands build brand charisma and loyalty. Marketers can use AI tools to identify target audiences where metahumans will be most effective and tailor campaigns accordingly. Social implications: Metahuman SMIs offer a scalable and innovative approach to promoting cultural city brands globally, thereby supporting lesser-known cities in attracting new visitors. Originality/value: This study is among the first to demonstrate that metahuman SMIs can build brand loyalty through a sequential pathway: elevating brand charisma, which then strengthens brand reputation and, in turn, loyalty. Grounded in Social Influence Theory and Meaning Transfer Theory, the study provides clear, context-specific insights for influencer strategy in social media advertising for cultural city brands.

Purpose: Brands are exploring innovative strategies to engage their target audience online by leveraging human and AI-generated metahuman influencers. This study examines the impact of endorsements from human and AI-generated metahuman influencers on online brand engagement, comparing each to a brand-only condition. Additionally, it assesses whether this impact is direct, indirect or moderated by influencer–brand fit. Design/methodology/approach: We deploy two experiments with two real brands. In the first experiment (n = 199), the comparison was between a human influencer endorsement condition and a brand-only condition. In the second experiment (n = 297), we introduced an additional metahuman influencer endorsement condition, enabling us to examine responses to both human and metahuman influencer endorsements relative to the brand-only baseline. Findings: The findings reveal that brand endorsements by human influencers significantly enhance online brand engagement compared to the brand-only condition, primarily through attachment transfer. While metahuman influencers can also drive engagement, the moderation effect – where the fit between the influencer and the brand strengthens attachment transfer – applies exclusively to human influencers. Originality/value: This study is among the first to examine the effects of brand endorsements by human and AI-generated metahuman influencers, each compared to a brand-only control, on online brand engagement. It uses attachment transfer and brand fit as key mechanisms to uncover the dynamics of this relationship. The findings provide valuable insights into the role of social media influencers in brand marketing communications, thus contributing to a deeper understanding of their influence in today’s dynamic digital marketing landscape.

The selection of relevant variables is critical for providing personalized product and service recommendations on e-commerce businesses. However, the integration of e-loyalty-related features into recommender systems remains underexplored. This study aims to investigate the impact of incorporating e-loyalty indicators, such as purchase frequency and platform engagement, on the performance of recommender systems in the context of e-commerce businesses. Using three well-established recommender system models and four real-world datasets, we conducted computational experiments to assess performance improvements when e-loyalty features are incorporated. The results show that integrating e-loyalty-related features significantly enhances the performance of recommendation systems, with sequential deep neural networks outperforming other algorithms. Our study contributes to the literature by highlighting the value of leveraging customer loyalty data to enhance recommendation accuracy. Theoretical implications include underscoring the importance of using longitudinal user engagement data in recommender systems to move beyond static personalization toward adaptive, behavior-aware technologies. From a practical perspective, our findings suggest that incorporating e-loyalty features can improve recommendation accuracy, offering valuable insights for e-commerce businesses seeking to personalize their services. This research offers original contributions by focusing on the role of loyalty-driven features in improving recommender systems, an area that remains largely underexplored.

As sustainable tourism gains momentum, understanding the impact of Cittaslow promotion on tourist behavior is crucial yet remains unexplored. This study addresses this gap by investigating the effect of Cittaslow promotion on tourists’ behavioral responses, especially within social media contexts and small urban tourism destinations. Applying signaling theory, we conducted a field experiment with real Instagram advertisements (n ₁ = 51,089 impressions) and an online experiment (n ₂ = 212). Results reveal that Cittaslow promotion campaign directly enhances tourists’ interest in the Cittaslow destination, willingness to visit, and likelihood to recommend. Furthermore, Cittaslow promotion indirectly influences these behaviors through destination brand identification, brand quality, and brand attachment. Notably, the serial mediation effect through destination brand quality and attachment is stronger for travelers with a higher need for restoration. These insights suggest that small urban tourism destinations can enhance tourist interest in the destination, brand identification, and brand quality, and foster emotional bonds through Cittaslow promotion campaigns.

Destinations are increasingly focusing on sustainability awareness through tourism campaigns, but effective communication remains challenging. This research, rooted in consumption value theory, delves into the influence of message appeal (environmental vs. personal benefit) and information type (objective vs. subjective) on tourists’ behavioral intentions through two online experiments. Study 1 demonstrates the positive impact of environmental benefit message appeals on behavioral intentions toward destinations, both directly and indirectly, by enhancing destination brand quality and perceived green value. Study 2 validates these findings and extends the analysis to include click-through behavior as a proxy for real behavior. Our research emphasizes the importance of environmental benefits alongside objective information in destinations’ sustainability messages within social media advertisements. This approach serves to bolster destination brand quality, perceived green value, and ultimately, positive behavioral intentions.