Does Health Consciousness Matter to Adopt New Technology? An Integrated Model of UTAUT2 With SEM-fsQCA Approach.

Every emerging technology has its pros and cons; health-conscious users pay more importance to healthy and environment-friendly technologies. Based on the UTAUT2 model, we proposed a comprehensive novel model to study the factors influencing consumers' decision-making to adopt the technology. Compared to prior studies that focused on linear models to investigate consumers' technology adoption intentions and use behavior. This study used a Structural Equation Modeling-fuzzy set qualitative comparative analysis (SEM-fsQCA) approach to account for the complexity of customers' decision-making processes in adopting new technology. We collected valid responses from 830 consumers, analyzed them, and evaluated them using a deep learning SEM-fsQCA technique to capture symmetric and asymmetric relations between variables. We have extensively incorporated a health-consciousness attitude as a predictor and mediator to understand better the decision-making toward technology adoption, specifically 5G technology. All the factors tested in our model are statistically significant except the economic factors. Health-consciousness attitude (HCA) and behavioral intention (BI) found significant predictors and valid mediators in the process of 5G technology adoption. FsQCA provided six configurations to achieve high 5G adoption. The findings have significant practical ramifications for telecom corporations, advertisers, government officials, and key policymakers. Additionally, the study added substantial theoretical literature to technology adoption, particularly the adoption of 5G technology.

Role of Social Media Marketing Activities in Influencing Customer Intentions: A Perspective of a New Emerging Era.

The aim of this study is to explore social media marketing activities (SMMAs) and their impact on consumer intentions (continuance, participate, and purchase). This study also analyzes the mediating roles of social identification and satisfaction. The participants in this study were experienced users of two social media platforms Facebook and Instagram in Pakistan. A self-administered questionnaire was used to collect data from respondents. We used an online community to invite Facebook and Instagram users to complete the questionnaire in the designated online questionnaire system. Data were collected from 353 respondents, and structural equation modeling (SEM) was used to analyze the data. Results show that SMMAs have a significant impact on the intentions of users. Furthermore, social identification mediates the relationship between social media activities and satisfaction, and satisfaction mediates the relationship between social media activities and the intentions of users. This will help marketers how to attract customers to develop their intentions. This is the first novel study that used SMMAs to address the user intentions with the role of social identification and satisfaction in the context of Pakistan.