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Marketing Strategy Innovation via AI Adoption: A Study on Bangladeshi SMEs in the Context of Industry 5.0

Tahsina Khan · Md Mehedi Hasan Emon · Sadia Rahman

33 citations0/0 files storedInternational Conference on Sustainable Technologies for Industry 5.0 (STI)

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Impact of AI and Big Data on Business and Society Technology Adoption and User Behaviour Digital Innovation in Industries

Abstract

This study investigates the impact of Artificial Intelligence (AI) adoption on marketing strategy innovation among small and medium enterprises (SMEs) in Bangladesh, within the context of Industry 5.0. The research aims to identify the factors influencing AI-driven marketing innovation and how these factors contribute to strategic advancements. A quantitative research design was employed, collecting data from 165 SMEs through a structured questionnaire. Structural Equation Modelling (SEM) using SmartPLS was applied to examine the relationships between the independent variables— Perceived Usefulness (PU), Perceived Ease of Use (PEOU), Industry 5.0 Readiness (I5), Organizational Support (OS), Competitive Pressure (CP), and Cost of AI Implementation (CAI)—and the dependent variable, Marketing Strategy Innovation (MSI). The findings revealed that PEOU, I5, OS, and CP positively influence marketing strategy innovation, while PU was found to have an insignificant impact. Additionally, CAI negatively impacted innovation, though SMEs with strong organizational support and external pressures still innovated despite cost concerns. These results underscore the importance of organizational readiness and user-friendly AI systems in driving innovation. The study's limitations include a focus on Bangladeshi SMEs, which may limit generalizability. Further research is needed across different regions and industries. This research offers insights for SME managers and policymakers to focus on improving AI accessibility and support structures to foster marketing innovation. By highlighting the role of AI in marketing innovation, the study emphasizes the need for technological upskilling and capacity building in developing economies. This study contributes to the literature by exploring AI adoption in the context of Industry 5.0 within Bangladeshi SMEs, addressing a gap in research on AI-driven innovation in developing economies. The limitations of the study include generalizability to other industries and regions, as well as a limited sample size.

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References

1989Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology 1981Structural Equation Models with Unobservable Variables and Measurement Error: Algebra and Statistics 2019Assessing measurement model quality in PLS-SEM using confirmatory composite analysis 2020Small business awareness and adoption of state-of-the-art technologies in emerging and developing markets, and lessons from the COVID-19 pandemic 2023Investigating the Influence of Artificial Intelligence on Business Value in the Digital Era of Strategy: A Literature Review 2021Innovative Finance, Technological Adaptation and SMEs Sustainability: The Mediating Role of Government Support during COVID-19 Pandemic 2024Quantifying the influence of supplier relationship management and supply chain performance 2023The impact of artificial intelligence in marketing on the performance of business organizations: evidence from SMEs in an emerging economy

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