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Under the sunlight of social commerce, few concepts have blossomed like value co-creation. But when blurred strategies are implemented, the opportunity to wilt a brand is high. To avoid the miscues and the controversies, an ascendant step is to engage consumers with social commerce sites. The purpose of this paper is to propose three antecedents to engage consumers with social commerce sites, namely, social support, social commerce value and social commerce information sharing, and the effect of brand engagement on the intention of brand co-creation.

This study used survey data from 234 Iranians with experience using social commerce sites. Variance-based structural equation modeling using the partial least squares path modeling approach was adopted to analyze the structural model.

The authors found that social support, social commerce value and social commerce information sharing positively foster brand engagement. The study also revealed that brand engagement is a significant predictor of brand co-creation intention.

The study is the first study that considers and explains brand engagement from social support theory, social commerce value theory and social commerce information exchange. Also, the study shows how consumers can be an integral part of a brand. Unlike other studies which were done in industrialized countries, this study was employed in Iran.

Given the growing importance and demand for online food purchases, this study explores the new advancements in information and communication technologies (ICTs) by examining the key features of social commerce, trust and product’s attributes in the e-commerce environment. The aim is to investigate possible ICTs-related entrepreneurial opportunities in the food and beverage (F&B) industry.

The study uses a survey to collect data and applies Smart partial least squares to test the model.

The structural equation modelling results illustrated that social commerce constructs significantly impact trust, leading to customer’s purchase intention. Additionally, product’s attributes was found to have a significant relationship with customer’s purchase intention with trust being the most pertinent driver.

This study contributes to the F&B literature by highlighting the role of new forms of technologies in entrepreneurship activities, especially for small and medium-sized enterprises.

Social media is still influencing consumers and is extending social commerce (S-Commerce) use. Different social media activities can influence the users' trust and e-satisfaction at different levels, which in turn influence the purchase intentions. This is evident for the food and beverage industry as S-Commerce mediated by social media can help realise a shorter time to market and meet buyer demands. In addition, credibility factors may influence trust and purchase intentions. Understanding the various factors of influence such as social constructs, namely ratings, reviews and referrals; design constructs such as credibility and features and behavioural constructs such as trust, satisfaction and motivation; and analysing the relationship between these factors and how they influence purchase intentions can provide deeper insights into S-Commerce research, decision-making process and purchase intentions particularly from a food and beverage context.

Drawing on trust through social media activities and surface credibility as well as e-commerce satisfaction, the authors have proposed a research model to investigate the purchase intention of consumers in S-Commerce platforms. Survey data were collected from six countries in Asia and analysed using SEM-PLS.

Results indicated that both trust and surface credibility significantly influence e-commerce satisfaction leading to purchase intention. Furthermore, surface credibility, which is a novel predictor for purchase intention in S-Commerce context, is highly significant on e-commerce satisfaction. Besides, encouraged by surface credibility, it was identified that trust significantly affects e-commerce satisfaction and results in purchase intention. This research adds contribution to theory and practice in S-Commerce stream as discussed at the end of the paper.

The results of this research contribute to the S-Commerce literature and have practical implications for practitioners in the food and beverage industry. As such, focussing on these constructs, this paper analyses the relationship between the social media activities, trust, e-commerce satisfaction, surface credibility and intention to buy.

The recent proliferation of social media platforms has witnessed a growth in social commerce by using social media to facilitate interactivity between customers and vendors. While emergent studies on social commerce are growing, their focus tends to be on millennials and cross-age groups. Given the growth of digital natives in shaping the online shopping experience of the future, we deemed an application to Generation Z necessary and overdue.

We draw on the existing literature and develop a framework to understand social commerce dynamics for digital natives. We employ PLS and CB-SEM to test our proposed model.

Our findings demonstrate the importance of social commerce information sharing activities in facilitating social support, a sense of warmth and belongingness, and online trust for Generation Z platform users. We also investigate the roles of online trust and perceived risk on intention to purchase and find support for both relationships. Finally, we discuss the findings in terms of theoretical and managerial contributions and conclude the study with limitations and future research directions.

This research is unique by using social commerce theory to explore Gen Z platform users. The finding will contribute to information system literature by expanding the social commerce research stream.

E-commerce and social media technologies can significantly benefit the food and beverage industry by reducing costs, streamlining supply activities, and, most importantly, engaging users in active interaction and enhancing social presence. This research aims to propose a model to examine the role of trust and social presence on loyalty in the food and beverage industry. Moreover, the mediating role of trust is the link between social presence and loyalty examined in this study.

A survey has been conducted to examine the structural model. The research model is tested using structural equation modelling (PLS-SEM).

The result indicated the effect of Social presence and Trust in social media on Customer loyalty in the context of online shopping. Our finding contributes remarkable insights into the food and beverage industry, particularly in the COVID-19 era, as more consumers buy through e-commerce platforms.

This study expands the understanding of the role of the managers of social commerce websites in maintaining customer loyalty. Hence, the social commerce site managers can use this finding to develop strategies for building customer trust and, ultimately, customer loyalty.

Consumers may enjoy the information sharing and social support made available when a social media platform is used for pre-purchase research; however, do consumers reevaluate the privacy and security of the platform differently when ordering and payment capabilities are added? As social media systems have evolved into social commerce platforms (SCPs), individuals are often faced with whether to complete a purchase they have been researching or switch to a traditional e-commerce platform to complete the transaction. This research examines consumer trust formation in the SCP channel and how consumer interest and engagement in the channel are maintained and influence consumer decisions to purchase via the SCP.

Based on trust and involvement literature, a research model was conceptualized to capture consumer beliefs about SCP privacy and security and whether the SCP can be trusted, using these inputs into subsequent consumer interest, engagement and decisions on whether to use the SCP for purchasing. The research model was empirically tested using the panel data's structural equation modeling (AMOS) (n = 405). The data showed acceptable reliability and convergent validity, while the original research model provides predictive validity and theory-confirming insights.

Results confirm that consumer perceptions of privacy and security play a crucial role as decision criteria, informing their judgments of whether a new social commerce channel can be trusted enough to conduct purchases. Further, consumer trust supports their interest in the SCP, resulting in enduring and enhanced behavioral use and, to a lesser extent, purchase intent. Still, a majority of this sample declined to purchase using the SCP and rather preferred to transact on tried and trusted traditional e-commerce sites.

This study is among the first to examine trust formation in new SCPs, where consumers are deciding to expand their engagement level from social and informational to commercial.

Innovative firms leverage big data analytics (BDA) benefits in optimising value creation, particularly in business-to-business (B2B) contexts. Examples of this are found in new product success and product innovation performance. However, knowledge of how innovative firms and their corporate customers generate insights from big data, develop new products and gain higher-quality service from intra- and inter organisations' resources is limited. This knowledge manifests in the form of opportunities available in BDA and through the adoption of the co-creation approach to generate value in the form of new product innovation. BDA reflects an excellent means of enhancing a firm's customer agility, but how this is possible remains largely unknown.

In this research, the authors hypothesise that new product success is a function of a firm's customer agility and product innovation performance moderated by environmental turbulences. In turn, the firm's customer agility is enhanced by the effect of big data aggregation and analytical tools. These hypotheses have been confirmed by a survey in an emerging market.

The authors use structural equation modelling to test the authors’ hypotheses. The main contribution of this research is the conceptualisation and test of an integrative framework identifying the links among a firm's customer agility, new product success and BDA capabilities.

The study established that BDA tools – the effective use of data aggregation tools and the effective use of data analysis tools – shape customer agility in achieving new product success. This study contributes to one’s understanding of the relevance of BDA in B2B value creation contexts.

The study findings show that BDA shapes a firm's customer agility in achieving new product success.

Social commerce (SC) is a new genre in electronic commerce (e-commerce) that has great potential. This study proposes a new research framework to address deficiencies in existing social commerce research frameworks (e.g. the information model).

In the era of Industrial Revolution 4.0 technologies and new social commerce (s-commerce) models, the authors believe that there is an immediate need for a new research framework. The authors analysed the progress of the s-commerce paradigm between 2003 and 2023 by applying longitudinal science mapping. The authors then developed a research framework based on the themes in the strategic diagrams and evolution map.

From 2003 to 2010, studies on s-commerce mainly focused on social networking sites, virtual communities, social shopping and analytic approaches. From 2011 to 2015, it shifted to s-commerce, consumer behaviour, Web 2.0, artificial intelligence, social technologies, online shopping, user studies, data gathering methods, applications, service-based social commerce constructs, e-commerce and cognitive factors. Social commerce remained the primary research paradigm from 2017 to 2023.

The SC framework may be analogous to popular research frameworks such as technology-organisation-environment (T-O-E) and stimulus-organism-response (S-O-R). Based on this SC framework, researchers may gain a better understanding by determining the factors of the social, commercial, technological and behavioural dimensions.

The authors redefined s-commerce and developed an SC framework. Practical guidelines for the SC framework and an exemplary research model are presented. Overall, this study offers a new research agenda for the extant understanding of s-commerce, with the SC framework as the next frontier of the theoretical advancements and applications of s-commerce.

The advantages of applying big data analytics for organizations to boost innovation performance are enormous. By collecting and analysing substantial amounts of data, firms can discern what works for their customer needs and update existing products while innovating new ones. Notwithstanding the evidence about the effects of big data analytics, the link between big data analytics and innovation performance is still underestimated. Especially in today's fast-changing and complicated environments, companies cannot simply take big data analytics as one innovative technical tool without fully understanding how to deploy it effectively.

This study tries to investigate this relationship by building on the knowledge absorptive capacity perspective. The authors conceptualized effective use of big data analytics tools as one general absorptive capacity rather than a simple technical element or skill. Specifically, effectively utilize big data analytics tools can provide values and insights for new product innovation performance in a turbulent environment. Using online survey data from 108 managers, the authors assessed their hypotheses by applying the structural equation modelling method.

The authors found that big data analytics capacity, which can be conceptualized as one absorptive capacity, can positively influence product innovation performance. The authors also found that environmental turbulence has strong moderation effects on these two main relationships.

These results establish big data analytics can be regarded as one absorptive capacity, which can positively boost an organization's innovation performance.

The emergence of social media has brought the influencer marketing landscape to an unprecedented level, where many ordinary people are turning into social media influencers. The study aims to construct and validate a model to yield strategic insights on the relevance of content curation, influencer–fans interaction and parasocial relationships development in fostering favorable endorsement outcomes (i.e. purchase intention).

The present study analyzes data from a survey of 411 consumers using partial least squares-structural equation modelling (PLS-SEM) and fuzzy set qualitative comparative analysis (fsQCA) to understand the net and combined effects of content attributes, interaction strategies and parasocial relationships on purchase intention.

PLS-SEM results reveal that content attributes (i.e. prestige and expertise) and interaction strategies (i.e. interactivity and self-disclosure) positively influence parasocial relationships, and in turn, lead to high purchase intention. Findings from fsQCA indicate six solutions with different combinations of content attributes, interaction strategies and parasocial relationships that sufficiently explain high purchase intention.

The present study demonstrates the roles of content attributes and interaction strategies in engendering parasocial relationship and the endorsement outcome (i.e. purchase intention) from both linear and non-linear (complexity) perspectives.