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Social commerce has brought about a significant transformation in consumer experience due to diverse factors. As a result, users often find themselves prone to impulsive buying behaviour when exposed to such an environment. Prior research was limited to demonstrating the expanding influence of celebrities on social media and the linkage between social engagement and impulse buying context. Furthermore, the impulse buying tendency of consumers on social media in the context of celebrity posts has yet to be validated. This paper aims to assess the influence of consumer awareness, consumer trust and observational learning on the latent state-trait (LST) theory regarding celebrity posts on impulse buying tendencies.

The empirical research builds on a sample survey involving 750 students from the “Big Four” economics universities in Hanoi. The proposed model was analysed using a partial least squares structural equation modelling technique.

The authors find that consumer trust and observational learning from celebrity’ posts positively affect impulse buying tendency. Yet celebrity influence awareness directly impacts trust in celebrity’ posts rather than directly impacting impulse buying tendency. Perceiving the importance of interactive and authentic posts by a celebrity in influencing consumers’ purchase behaviour on social media, this research offers valuable insights for stakeholders in the digital celebrity sphere of communication and marketing.

Perceiving the importance of interactive and authentic posts by a celebrity in influencing consumers’ purchase behaviour on social media, this research offers valuable insights for stakeholders in the digital celebrity sphere of communication and marketing.

From a theoretical perspective, this expands the applicability of the LST theory in social commerce to promote impulse buying tendencies. Second, this contributes to the literature on the emerging phenomenon of social media celebrities, as existing literature does not clarify their influence on impulse buying behaviour. Third, this research applies the concept of observational learning in online shopping through key features of social media platforms, namely, likes, shares and comments, to investigate their influence on the impulse buying tendency of consumers. Concerning managerial implications, the authors propose practical recommendations for practitioners, particularly those involved or interested in the commercial services industry and social media marketing (namely, celebrities and partner companies).

There is limited research examining the relationship between social media and green food purchasing behaviour. In the current study, we examine the factors that affect consumers’ green food purchasing behaviour in Türkiye.

Data collected from the participants by survey method were analysed using Smart PLS 4.0 with IBM SPSS 26 and PLS to run SEM.

Our findings have revealed that from all the structural elements in the theory of planned behaviour (TPB), only attitude and perceived behavioural control contribute to consumers’ green food purchasing behaviour, while subjective norms do not contribute to consumers’ green food purchasing behaviour. Additionally, it was found that social media usage (SMU) and digital marketing interactions (DMI) have a positive and significant effect on green food purchasing behaviour. More information, experiences, opinions and recommendations on green foods in social media channels can encourage consumers to buy more green food.

This study first evaluates the applicability of the TPB model in explaining green food purchasing behaviour. This study is extended with two new factors included in the original framework of the TPB model, namely, SMU and DMI.

This chapter examines how information and communication technology (ICT) initiatives affect customers’ everyday routines with an emphasis on how electronic word of mouth (eWOM) affects their purchasing decisions and determines if eWOM might serve as a useful trust factor when making purchasing decisions. This chapter is based on both primary and secondary data and examines how eWOM affects customers’ buying decisions in this era of increasing social media platform usage. One hundred individuals from various regions of Karachi provided the primary data, collected through an online survey. Secondary data are also employed, such as details from business websites, scientific papers, and other related publications of businesses. In Karachi’s developing digital market, it was discovered that eWOM via social media used to have a substantial impact on consumers’ shopping habits. The effectiveness of social media content depends greatly on how appropriate it is for the intended audience. Social media marketing doesn’t quite simply aim to improve consumers’ impressions or directly advertise things. It also entails maintaining and fostering relationships between businesses and prospective customers. According to the research, consumers’ recommendations and ratings of goods and services made on social media, whether through eWOM or another channel, influenced their decisions to buy. Customers consider social media to be trustworthy when making decisions about what to buy. Customers are currently adopting social media as opposed to more conventional means to learn about new products. Most customers believe that eWOM from social media greatly affected their shopping choices, according to the results of the study.

The purpose of this study is to comprehend how AI aids marketers in engaging customers and generating value for the company by way of customer engagement (CE). CE is a popular area of research for scholars and practitioners. One area of research that could have far-reaching ramifications with regard to strengthening CE is artificial intelligence (AI). Consequently, it becomes extremely important to understand how AI is helping the marketer reach customers and create value for the firm via CE.

A detailed approach using both systematic review and bibliometric analysis was used. It involved identifying key research areas, the most influential authors, studies, journals, countries and organisations. Then, a comprehensive analysis of 50 papers was carried out in the four identified clusters through co-citation analysis. Furthermore, a content analysis of 42 articles for the past six years was also conducted.

Emerging themes explored through cluster analysis are CE concepts and value creation, social media strategies, big data innovation and significance of AI in tertiary industry. Identified themes for content analysis are CE conceptualisation, CE behaviour in social media, CE role in value co-creation and CE via AI.

CE has emerged as a topic of great interest for marketers in recent years. With the rapid growth of digital media and the spread of social media, firms are now embarking on new online strategies to promote CE (Javornik and Mandelli, 2012). In this review, the authors have thoroughly assessed multiple facets of prior research papers focused on the utilisation of AI in the context of CE. The existing research papers highlighted that AI-powered chatbots and virtual assistants offer real-time interaction capabilities, swiftly addressing inquiries, delivering assistance and navigating customers through their experiences (Cheng and Jiang, 2022; Naqvi et al., 2023). This rapid and responsive engagement serves to enrich the customer’s overall interaction with the business. Consequently, this research can contribute to a comprehensive knowledge of how AI is assisting marketers to reach customers and create value for the firm via CE. This study also sheds light on both the attitudinal and behavioural aspects of CE on social media. While existing CE literature highlights the motivating factors driving engagement, the study underscores the significance of behavioural engagement in enhancing firm performance. It emphasises the need for researchers to understand the intricate dynamics of engagement in the context of hedonic products compared to utilitarian ones (Wongkitrungrueng and Assarut, 2020). CEs on social media assist firms in using their customers as advocates and value co-creators (Prahalad and Ramaswamy, 2004; Sawhney et al., 2005). A few of the CE themes are conceptual in nature; hence, there is an opportunity for scholarly research in CE to examine the ways in which AI-driven platforms can effectively gather customer insights. As per the prior relationship marketing studies, it is evident that building relationships reduces customer uncertainty (Barari et al., 2020). Therefore, by using data analysis, businesses can extract valuable insights into customer preferences and behaviour, equipping them to engage with customers more effectively.

The rapid growth of social media has enabled individuals to articulate their thoughts, opinions and emotions related to a brand, which creates a large amount of data for VCC. Meanwhile, AI has emerged as a radical way of providing value content to users. It expands on a broader concept of how software and algorithms work like human beings. Data collected from customer interactions are a major prerequisite for efficiently using AI for enhancing CE. AI not only reduces error rates but, at the same time, helps human beings in decision-making during complex situations. Owing to built-in algorithms that analyse large amounts of data, companies can inspect areas that require improvement in real time. Time and resources can also be saved by automating tasks contingent on customer responses and insights. AI enables the analysis of customer data to create highly personalised experiences. It can also forecast customer behaviour and trends, helping businesses anticipate needs and preferences. This enables proactive CE strategies, such as targeted offers or timely outreach. Furthermore, AI tools can analyse customer feedback and sentiment across various channels. This feedback can be used to make necessary improvements and address concerns promptly, ultimately fostering stronger customer relationships. AI can facilitate seamless engagement across multiple digital channels, ensuring that customers can interact with a brand through their preferred means, be it social media, email, or chat. Consequently, this research proposes that practitioners and companies can use analysis performed by AI-enabled systems on CEB, which can assist companies in exploring the extent to which each product influences CE. Understanding the importance of these attributes would assist companies in developing more memorable CE features.

This study examines how prominent CE and AI are in academic research on social media by identifying research gaps and future developments. This research provides an overview of CE research and will assist academicians, regulators and policymakers in identifying the important topics that require investigation.

The authors argue that privacy is integral to the well-being of consumers and an essential component in not only corporate social responsibility (CSR) but what they term uniquely as social media responsibility (SMR). A conceptual framework is proposed that delineates the privacy issues companies should pay attention to in artificial intelligence (AI)-fueled social media environments.

The authors review literature on privacy issues in social media and AI in the academic and practitioner literatures. Based on the review, arguments focus on the need for an SMR framework, proposing responsible use of consumer data that is attentive to consumers' privacy concerns.

Implications from the framework are a path forward for social media companies to treat consumer data more fairly in this new environment. The framework has implications for companies to reduce potential harms to consumers and consider addressing their power and responsibility. With social media and AI transforming consumer behavior so profoundly, there are a variety of short- and long-term social implications.

Since AI tools are becoming integral to social media company activities, this research addresses the changing responsibilities social media companies have in securing consumers' data and enabling consumers the agency to protect their privacy effectively. The authors propose an SMR framework based on CSR research and AI tools employed by social media companies.

Social media marketing has become a powerful strategic tool for many brands, but scholarly research in this domain is still in its infancy. This study aims to examine the effects of social media marketing activities on consumer online impulse buying intentions via brand resonance and emotional responses by incorporating the direct and moderating effects of social network proneness toward fashion retail brands.

By using snowball sampling, this study recruited 441 netizens (who were using fashion retail brands) and obtained their responses through an online survey. Structural equation modeling was applied to 394 responses for analysis.

The findings discovered that social media marketing activities significantly influenced brand resonance, consumer emotional responses and online impulse buying intentions. Likewise, brand resonance and emotional responses were positively associated with online impulse buying intentions and acted as decisive mediators. Social network proneness’s direct and moderating effects significantly increased consumer online impulse-buying intentions toward fashion retail brands.

This study provides recommendations to retail managers for creating and executing brand positioning, segmenting and targeting strategies to enhance consumers’ intentions for engaging in online impulsive purchases for fashion brands.

This original research contributes to the branding literature and stimulus–organism–response theory by focusing on social media marketing activities, brand resonance, emotional responses, social network proneness and consumer online impulse buying intentions toward fashion retail brands.

This study aims to examine the influence of social media usage (SMU) on minimalist consumption and how the fear of missing out (FoMO) underlies this effect.

Four preregistered correlational/experimental studies (n = 1,763) are used. A pilot study (n = 436) examines the correlations between SMU, FoMO and minimalism. Studies 1 (n = 409), 2 (n = 415) and 3 (n = 503) further investigate the influence of SMU on minimalist consumption intentions, including mindful purchase, forgoing free products and decluttering, and test for evidence of mediation via FoMO by measuring or manipulating FoMO.

The results show that a high SMU makes consumers susceptible to FoMO, leading to impulsive purchases and careless product acquisition. However, when campaigners promote minimalism as a social media movement, they can activate FoMO, persuading consumers to practice decluttering.

Future research might examine how subjective age affects FoMO and minimalist consumption tendencies. Could campaigners use young social cues to make older consumers more susceptible to FoMO appeals? Could old social cues cause younger consumers to perceive greater social responsibility and to embrace minimalist consumption?

Minimalist lifestyles can promote sustainable consumption. This research provides insights into how SMU is a double-edged sword – it can cause FoMO users to disdain minimalism. However, it can promote minimalism if a minimalist campaign is strategically positioned as a social media movement using a FoMO-laden appeal.

Extant consumer behavior research on minimalism has just begun to investigate the antecedents of minimalist consumption. FoMO is conceptually related to minimalism, but the relationship between FoMO and minimalist consumption has not yet been empirically tested. This research fills these gaps by examining SMU and the associated FoMO as antecedents of minimalist consumption. Empirical evidence for the impact of SMU on various minimalist consumption behaviors and the mediating role of FoMO is provided.

This study aims to reveal the knowledge structure of social media influencer marketing literature by performing science mapping analysis through a state-of-the-art bibliometric approach to determine the current and future trends. Social media influencer marketing is one of the most effective approaches to presenting a brand and offering value to consumers via social media.

This study evaluates the knowledge structure to uncover the emerging trends and future predictions in social media influencer marketing through bibliographic coupling and co-word analysis. In total, 917 journal publications were retrieved from the Web of Science database and analyzed using VOSviewer software.

The central theme in social media influencer marketing reflects digital engagement between influencers and followers and communication between influencers and followers. The theoretical and managerial implications are discussed.

This study unleashes the knowledge structure according to the fundamental literature of social media influencer marketing and the underlying themes related to the phenomenon.

This study aims to provide a holistic review of social media influencers (SMIs) research based on a unique approach of bibliometric analysis and content analysis between 2011 and 2020. The review examines the main influential aspects, themes and research streams to identify research directions for the future.

The sample selection and data collection were done from the Scopus database. The sample dataset was refined based on the inclusion and exclusion criteria to determine the final dataset of 183 articles. The dataset was exported in the BibTeX format and then imported into the BiblioShiny app for bibliometric analysis. The content analysis was done following the theory-context-methodology framework.

The several findings of this study include (1) Co-word analysis of most used keywords; (2) Longitudinal thematic evolution; (3) The focus of the research papers as per the theory-context-methodology review protocol are persuasion knowledge model, fashion and beauty industries, Instagram and content analysis, respectively; and (4) The network analysis of the research studies is known as the co-citation analysis and depicts the intellectual structure in the domain. This analysis resulted in four clusters of the research streams from the literature and two emergent themes (Chen et al., 2010)

In general, the previous reviews in the area are either domain, method or theory-based. Thus, this study aims to complement and extend the existing literature by presenting the overall picture of the SMI research with the help of a unique combined approach and further highlighting the trends and future research directions based on the findings of this study.

This study explores the key platform affordances that online social platform providers need to offer digital creators to strengthen the creator ecosystem, one of the leading accelerators for platform growth. Specifically, it aims to investigate how these affordances make the dynamic combinations for high platform quality across diverse platform types and demographic characteristics of digital creators.

This study adopts a multi-method approach. Drawing upon the affordance theory, Study 1 aims to identify the key affordances of online social platforms based on relevant literature and the qualitative interview data collected from 22 digital creators, thereby constructing a conceptual framework of key platform affordances for digital creators. Building on the findings of Study 1, Study 2 explores the dynamic combinations of these platform affordances that contribute to platform quality using a configurational approach. Data from online surveys of 185 digital creators were analyzed using fuzzy set qualitative comparative analysis (fsQCA).

The results of Study 1 identified key online social platform affordances for digital creators, including Storytelling, Socialization, Design, Development, Promotion, and Protection affordance. Study 2 showed that the combinations of these platform affordances for digital creators are diverse according to the types of platforms, creators’ gender, and their professionality.

Like many studies, this research also has several limitations. One limitation of the research is the potential constraint of the extent of how well the data samples represent the group of creators who are actively producing digital content. Despite the addition of screening questions and meticulous data filtering, it is possible that we did not secure sufficient data from creators who are actively engaged in creative activities. In future research, it is worth contemplating the acquisition of data from actual groups of creators, such as creator communities. Future researchers anticipate obtaining more in-depth and accurate data by directly involving and collaborating with creators.

This study highlights the need for online social platforms to enhance features for storytelling, socializing, design, development, promotion, and protection, fostering a robust digital creator ecosystem. It emphasizes clear communication of these affordances, ensuring creators can effectively utilize them. Importantly, platforms should adapt these features to accommodate diverse creator profiles, considering differences in gender and expertise levels, especially in emerging spaces like the Metaverse. This approach ensures an equitable and enriching experience for all users and creators, underlining the importance of dynamic interaction and inclusivity in platform development and creator support strategies.

This study underscores the social implications of evolving digital creator ecosystems on online platforms. Identifying six key affordances essential for digital creators highlights the need for platforms to enhance storytelling, socializing, design, development, promotion, and product protection. Crucially, it emphasizes inclusivity, urging platforms to consider diverse creator profiles, including gender and expertise differences, particularly in transitioning from traditional social media to the Metaverse. This approach nurtures a more robust creator ecosystem and fosters an equitable and enriching experience for all users. It signals a shift towards more dynamic, adaptive online environments catering to diverse creators and audiences.

For academics, this study builds the conceptual framework of online social platform affordances for digital creators. Using the configurational approach, this study identified various interdependent relationships among the affordances, which are nuanced by specific contexts, and suggested novel insights for future studies. For practices, the findings specified by creators and platform types are expected to guide platform providers in developing strategies to support digital creators and contribute to platform growth.