Purpose: This study aims to examine the impact of AI service robots on restaurant customers' engagement and acceptance and the moderating role of robot anthropomorphism on the relationship between AI robot service quality and customer engagement.Design/methodology/approach: Using a three-wave time-lagged design, 416 customers of service robots-enabled restaurants participated in the study. Mplus was used to examine the hypotheses.Findings: The results confirmed that customers' perception regarding automation, personalization, efficiency and precision of robot service quality determine customer engagement, which further influences customer acceptance of AI service robots. Additionally, robot anthropomorphism moderates the relationships between AI robot service quality in terms of automation, personalization, efficiency and precision and customer engagement. This study confirms that AI service robots-customer engagement contributes to better acceptance of AI service robots.Practical implications: The proposed framework can be used as a diagnostic tool to enhance customer acceptance of AI service robots in restaurant settings. This research provides guidelines to restaurant owners to employ AI service robots in front-line services that provide better quality, ultimately enhancing customer engagement and acceptance.Originality/value: This study fills the gap in the literature by investigating the influence of AI robot service quality on customer engagement and customer acceptance with the moderating effect of robot anthropomorphism in an emerging market context.

Recent studies have highlighted the importance of research on consumers’ green behavior in emerging markets. This study aims to determine the variables of the theory of planned behavior (TPB) that influence green purchasing intentions in Mexico. Into the model, we incorporated ecological conscience, moral obligation, and willingness to pay as additional variables. A sample of 300 consumers was obtained through an online survey and data were analyzed statistically using partial least squares structural equation modeling (PLS-SEM). The results revealed that perceived purchase control, ecological conscience, and moral obligation directly influence purchase intention. The study contributes to the current literature by strengthening the existing knowledge about the factors that influence the purchasing behavior of green products in emerging countries.

Small and medium enterprises (SMEs) in the construction sector play a pivotal role in any emerging market economy. These construction SMEs provide ancillary services to various industries, increase employment opportunities, and contribute to maintaining regional economic equilibrium. Technological innovations, particularly those based on artificial intelligence (AI), can significantly benefit SMEs by enhancing competitiveness and improving sustainability. However, the adoption of AI is slow among construction SMEs, and the factors that influence these enterprises’ adoption of AI-based technology are not well understood, creating a critical research gap. In this article, we present a theoretical model grounded in knowledge management theory and the unified theory of acceptance and use of technology to explore the factors that affect SMEs’ adoption of AI-based technology in developing countries. The data were collected from 422 construction SMEs, and structural equation modeling was employed to examine the hypotheses. The analysis of data collected from construction SMEs reveals that openness to innovation impacts perceived knowledge, which in turn influences performance expectations, ultimately affecting the adoption of AI-based technology in construction SMEs. Additionally, knowledge integration moderates the adoption and actual usage of AI-based technology.

This study aimed to examine the impact of information publicity on the intention of tourists to visit rural destinations in developing countries. Based on the theory of planned behavior (TPB), we examined the indirect effect of information publicity on intention to visit via subjective norms and further investigated the moderating effect of social media disposition and social media use. The study used data from a time-lagged design with three waves which supported the hypothesized model. The findings revealed that information publicity has an influence on the intention of tourists to visit through the mediating effect of subjective norms. Moreover, the social media disposition strengthened the relationship between information publicity and subjective norms. Furthermore, social media use positively moderated the relationship between subjective norms and intention to visit. Besides the core TPB constructs, the added variables indeed exerted a substantial impact on the visit intention of tourists. The study contributed to the tourism-related literature on social media and the practical implications were discussed.