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The emergence of social media platforms has revolutionized how brands develop partnerships with social media influencers (SMIs). However, users are seeking more meaningful engagement with SMIs, and little is known about how brands can shift their focus from transient engagements to continued engagement that builds long-term brand–consumer relationships. Extant research has provided inconsistent findings regarding consumer engagement behavior. To address this knowledge deficit, we contribute to the consumer engagement literature by developing and testing a conceptual model that explores and explains the relationships between the factors that influence continued engagement intention (CEI), a form of behavioral intention.

A literature review was conducted to identify gaps and develop a theoretically informed conceptual model and hypotheses. Survey data from 604 Instagram SMI followers were analyzed using partial least squares structural equation modeling using SmartPLS 3.3.3 to assess the structural model relationships and conduct post hoc analysis.

The findings suggest that it is important to positively influence consumer responses to elicit CEI. Furthermore, homophily attitudes toward SMIs moderate the relationship between SMI experience and CEI.

Brands must work with SMIs to create positive SMI experiences and develop CEI. Furthermore, SMIs should focus on brands that fit their lifestyles to enhance homophily attitudes and forge CEI.

This study contributes to the literature by combining social exchange and flow theories to develop and test a holistic framework for examining CEIs regarding SMIs and brands. The findings show that creating positive SMI experiences benefits brands seeking CEI.

Brands are seizing their latitude in the metaverse – this study conceptualizes a digital doppelgänger as the sense of embodiment of the physical person and unpacks their effect on consumer brand engagement by examining the mediating role of digital doppelgänger’s brand interactions.

Data was collected through an online self-administered questionnaire employing criterion-based judgment sampling, resulting in 475 qualified responses. The data was validated through a two-step SEM (structural equation modeling) application of Hayes’s Process in the SmartPLS4 package. The IMPA analysis technique identified the most important and influential factor driving brand performance in the metaverse.

The study reveals that digital doppelgänger’s brand interactions mediate the relationship between the digital doppelgänger (embodiment of the person) and consumer brand engagement. Brand interaction manifests enjoyment, relaxation and reputation felt by the physical person. The result indicates that digital doppelgänger’s brand interaction drives brand performance in the metaverse.

Our study is an original attempt to conceptualize a digital doppelgänger as the sense of embodiment of the physical person and their brand interactions in the metaverse influence consumer brand engagement to produce enjoyment, relaxation and reputation – this is a novel contribution to interactive marketing literature.

Over recent years, public health threats, economic losses and crises of confidence resulting from adverse events along the global food chains have pressured food traceability systems to operate more efficiently. Based on that, this paper aims to expand the body of knowledge on the connection between Industry 4.0 technologies and food chain traceability and how they have been integrated.

Before conducting a systematic literature review (SLR), we consulted academic experts in traceability and Industry 4.0 technologies to define the leading 4.0 technologies adopted. We then developed protocols and criteria for article selection. Based on the developed codebook, we performed a content analysis, refining it through discussions with experienced researchers.

This paper identified seven Industry 4.0 technologies applied in conjunction with support and device systems. These combinations hold promise for generating value for food chain traceability systems. Value for the food supply chain originates from five sources: trust, process improvement, data processing, security, sustainability and regulation. Besides, three barriers to implementing such traceability technologies were identified: resources, lack of structure, stakeholders and values.

While this study focused specifically on the food chain, the technology combinations, values, barriers and categories identified herein can inform analyses for other chains, e.g. the pharmaceutical chain. Moreover, due to the recent growth of this topic, some existing values and barriers may not have been fully explored and the technology combinations may vary slightly.

The results of this study provide food chain professionals with a comprehensive understanding of the values and corresponding barriers associated with employing Industry 4.0 traceability technologies. This knowledge can be leveraged to develop effective strategies and implement improvements in traceability, thereby benefiting society and addressing identified barriers.

This study expands the literature on using Industry 4.0 technologies for traceability in food chains, providing valuable directions to build safer, more efficient, transparent and potentially more sustainable food chains. Additionally, we provide promising avenues for future research.