The conception of the consumer–brand relationship has been receiving immense and escalating attention, and it is considered essential for capitalizing the performance of brands. The purpose of this study is twofold: Foremost part of the study comprehends valuable consumer–brand relationships and antecedents of brand equity. The second part is measuring the significant variations in hypothetical model under consumers’ gender and age perspective. The structural equation model is used for analyzing 425 questionnaires through SmartPLS3. Analysis has been conducted several times for combine data and data sets of gender and age groups to identify variations in model relationships. The findings of this study revealed the significant relationship among constructs of the hypothetical model. Brand love emerged as not only one of the significant antecedents of brand loyalty but also the strongest predictor of brand equity. Significant variations have been identified as male, and older consumers are transforming their love into loyalty and equity more than female and young consumers, respectively. The study has revealed guidelines for designing consumer–brand relationship and identified some significant variations that can be helpful in designing such relationship and marketing offers for multiple market segments.

The COVID-19 pandemic has had a substantial impact on the retail industry around the globe, including in the vast market of India. The response to the pandemic required stores to close and develop new ways to approach shoppers more efficiently. The worldwide usage of social media enabled the growth of social commerce (s-commerce). Influencers on s-commerce platforms use live broadcasting on their channels to promote endorsed products. The features of s-commerce influencers enhance users' trust in the online community and s-commerce intention, impacting their online purchasing intentions. In this study, we collected data from 379 Indian consumers to test the measurement and structural model using Partial Least Square-Structural Equation Modeling (PLS-SEM) to verify our conceptual framework. We found that trust in the online community and s-commerce intention are antecedents of online purchase intentions. Additionally, the results demonstrate that trust in Indian social media influencers and s-commerce intentions are vital for boosting consumers' purchase intention, verifying the hypothesized mediating effect of these factors. Based on these results, we suggest several managerial actions that could enhance the value of s-commerce for franchises, executives, e-retailers, and e-marketplaces.

Digital transformation has become an important channel for firms to build a competitive advantage in the digital economy. However, user participation, an important source of external knowledge for firms, has received limited attention in research related to digital transformation. Drawing on the knowledge-based view, the study uses a sample of 247 Chinese firms to investigate the impact of digital transformation on firm performance. The study examines the mediating role of user participation between digital transformation and firm performance and the moderating role of both environmental dynamics and absorptive capacity on the relationship between user participation and firm performance. Findings herein encourage digital transformation firms to pay attention to user participation, strengthen their ability to establish good relationships with users, improve their ability to absorb their knowledge, and make a strong effort to cultivate digital users.

With the rapid development of Generative AI technology, businesses need their marketers to adopt it to assist in completing their job tasks. However, marketers are not entirely optimistic and may feel anxious and concerned about it. This research explores how AI anxiety affects marketers' AI-generated content intention. Based on social cognitive theory, this study empirically examines the impact of anxiety on marketers' intention to use AI-generated content, including the mediating role of AI trust and the moderating effect of AI self-efficacy. Using survey data from 495 marketers, we found that AI privacy, bias, and opacity anxiety negatively correlate with AI trust and weaken marketers' intention to use AI-generated content. Furthermore, this relationship is moderated by AI self-efficacy, where the negative relationship is significantly mitigated when marketers possess AI self-efficacy. These findings enrich the research on Generative AI in marketing and help organizations focus on marketers' anxious resistance to adopting Generative AI and reduce the adverse effects of AI anxiety.

Purpose: In today’s global and competitive e-commerce market spaces, social media influencers (SMIs) exert substantial influence on consumer behavior. This study aims to examine how electronic word of mouth (e-WOM), Instagram usage and the credibility of SMIs shape the dynamics of consumer purchase behavior (PB). Design/methodology/approach: Information was gathered from 498 users in Ghana through judgmental sampling using SmartPLS 4. Findings: The findings revealed that influencers’ credibility has a substantial impact on their followers’ parasocial interactions. As a promotional tool, Instagram plays a significant role in how followers perceive the credibility of influencers by modifying the associations between parasocial connections, e-WOM and consumer PB. Research limitations/implications: The findings offer valuable information for marketing professionals looking to improve their advertising efforts by collaborating with influencers, along with unique perspectives on influencer dynamics in a diverse socioeconomic context, extending beyond conventional boundaries. Originality/value: Through an examination of the complex mechanisms underlying social media influencer advertisements on an e-commerce platform, namely, Instagram, this research uncovered the essence of customer behavior in the digital era, including the human need for connection, authenticity and trust, thus contributing to the literature empirical data from Africa, a region often overlooked in academic studies.

Purpose: This study aims to explore the intricate dynamics around the adoption of generative AI (GenAI) in India’s retail industry. The study uncovers the dynamic relationships between the antecedents of GenAI adoption and the impact of GenAI adoption on employee efficiency, business value creation and firm performance.Design/methodology/approach: This research used data from 188 Indian retail employees through purposive sampling, and the PLS-SEM technique was employed for the analysis.Findings: The findings state that top management support, openness to innovation and competitive pressure positively impact the adoption of GenAI. Moreover, GenAI positively influences the employee’s efficiency. The moderating impact of data-driven culture emphasizes the significance of data-driven culture in strengthening (weakening) the effect of GenAI on employee efficiency.Research limitations/implications: Overall, adopting GenAI improves efficiency, lowers operating costs and saves time. Resource Based View (RBV) advises that internal resources and business strategy must be coordinated to gain a competitive edge. Better business outcomes result from this increased capacity for decision-making, which is bolstered by insights derived from data.Practical implications: Overall, adopting GenAI improves efficiency, lowers operating costs and saves time. RBV advises that internal resources and business strategy must be coordinated to gain a competitive edge. Better business outcomes result from this increased capacity for decision-making, which is bolstered by insights derived from data.Originality/value: The mediating role of employee efficiency and the moderating impact of data-driven culture provides extraordinary findings. It emphasizes the significance of employee efficiency as a means through which GenAI transformed into tangible organizational outcomes.