Browsing by Author "Rahman, M. A.,"

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Exploring Key Factors in Predicting the Adoption of AI Technologies in E-Commerce Firms
(IEEE, 2024-12-20) Khan, T.,; Emon, M. M. H.,; Rahman, M. A.,; Aziz, A.,; Nath, A.
This study aims to explore the key factors influencing the adoption of artificial intelligence (AI) technologies in e-commerce firms in Bangladesh. Utilizing the Technology-Organization-Environment (TOE) framework, the research identifies the determinants such as perceived relative advantage, technological complexity, compatibility with existing systems, top management support, organizational readiness, employee expertise/training, and competitive pressure that affect AI adoption. A quantitative research approach was adopted, using a structured questionnaire distributed to 350 employees from various e-commerce firms in Bangladesh. The study employed convenience sampling and received 231 responses, out of which 215 were deemed valid for analysis. Structural equation modeling (SEM) was conducted using SmartPLS to test the hypotheses and validate the model. The results indicated that PRA, CES, TMS, OR, ET, and CP positively influence AI adoption in e-commerce firms, while TC showed a negative, though not statistically significant, impact. The R-square value of 0.73 demonstrates the model's robustness in explaining AI adoption variance. The findings provide valuable insights for e-commerce firms, highlighting the importance of organizational support and readiness, as well as employee training, in facilitating AI adoption. The study underscores the role of AI in driving digital transformation and its potential to enhance business efficiency, contributing to economic development in emerging markets like Bangladesh. This research fills a gap in the literature by focusing on AI adoption in the context of Bangladeshi e-commerce, providing a nuanced understanding of the influencing factors using the TOE framework.
Factors Influencing the Usage of Artificial Intelligence among Bangladeshi Professionals: Mediating role of Attitude Towards the Technology
(IEEE, 2024-12-19) Emon, M. M. H.,; Khan, T.,; Rahman, M. A.,; Siam, S. A. J.
This study investigates the factors influencing the usage of artificial intelligence (AI) among Bangladeshi professionals, with a focus on the mediating role of attitude towards technology. The purpose is to enhance understanding of AI adoption using elements from the Unified Theory of Acceptance and Use of Technology (UTAUT) and the Technology Acceptance Model (TAM). A quantitative research design was employed, utilizing a questionnaire distributed to 490 professionals, resulting in 190 usable responses. Data were analyzed using SmartPLS to assess the relationships among performance expectancy, effort expectancy, social influence, facilitating conditions, perceived usefulness, perceived ease of use, attitude towards technology, and behavioral intention to use AI. The findings indicate that performance expectancy, effort expectancy, social influence, facilitating conditions, and perceived usefulness significantly influence AI adoption. Social influence and perceived ease of use exhibit mediated effects through attitude towards technology. The research is limited by its use of convenience sampling and a single-country focus, which may affect the generalizability of the findings. The study's practical implications include guiding policymakers and industry leaders in designing targeted strategies to promote AI adoption among professionals. Social implications highlight the importance of addressing social factors and perceived ease of use to foster positive attitudes towards AI. This research contributes originality by integrating UTAUT and TAM models in a developing country context, providing nuanced insights into AI adoption among professionals. Future research should explore AI adoption across different developing countries and consider longitudinal and qualitative studies for a deeper understanding of technology adoption dynamics.
Measuring the Influence of Brand Image on Consumer Behavioral Intentions by using AI: Exploring the Mediating Role of Trust
(IEEE, 2024-09) Rahman, M. A.,; Emon, M. M. H.,; Khan, T.,; Siam, S. A. J.
This study investigates the influence of various dimensions of brand image—perceived brand quality, brand loyalty, brand awareness, perceived value, brand personality, and brand communication—on consumer behavioral intentions, with trust acting as a mediating factor. Using survey data from 130 respondents and employing structural equation modeling (SEM) via Smart PLS, the research finds that brand loyalty, awareness, perceived value, personality, and communication significantly impact consumer intentions. Notably, trust mediates the relationships between perceived value and consumer intentions, and between brand communication and consumer intentions. However, perceived brand quality shows no direct impact on consumer intentions. The study acknowledges limitations such as convenience sampling and self-reported data, suggesting avenues for future research to enhance generalizability through diverse samples and longitudinal studies. Practical implications suggest that marketers should focus on strengthening these brand dimensions to build consumer trust and drive favorable behaviors, thereby potentially enhancing brand reputation and societal well-being. The study contributes to theoretical advancements by emphasizing trust as a pivotal mediator in brand-consumer relationships, offering valuable insights for strategic brand management in competitive market environments.