Aug 2026· International Journal of Drug Delivery Technology· 0 citations· 20 references
TL;DR
Examining the impact of Artificial Intelligence adoption on the economic, environmental, and social dimensions of sustainable business performance among Indian MSMEs is expected to demonstrate that AI adoption significantly improves operational efficiency, innovation capability, environmental responsibility, and financial performance among MSMEs.
Abstract
Artificial Intelligence (AI) has emerged as a transformative technology that enables organizations to enhance operational
efficiency, optimize resource utilization, improve customer engagement, and support sustainable business practices. For
Micro, Small, and Medium Enterprises (MSMEs), AI adoption presents significant opportunities to overcome resource
constraints, improve competitiveness, and achieve long-term sustainability. Despite increasing government initiatives
promoting digital transformation in India, empirical evidence regarding the relationship between AI adoption and
sustainable business performance among Indian MSMEs remains limited. This study aims to examine the impact of
Artificial Intelligence adoption on the economic, environmental, and social dimensions of sustainable business
performance among Indian MSMEs.
The study adopts a quantitative research approach using a structured questionnaire administered to MSME owners,
managers, and entrepreneurs across selected industrial clusters in India. Primary data are collected from 400 respondents
through convenience and purposive sampling techniques. Statistical tools such as Descriptive Statistics, Reliability
Analysis, Exploratory Factor Analysis (EFA), Confirmatory Factor Analysis (CFA), Structural Equation Modeling
(SEM), and Multiple Regression Analysis are employed to test the proposed hypotheses. The study considers AI adoption
as the independent construct comprising intelligent automation, predictive analytics, customer relationship management,
decision support systems, and process optimization, while sustainable business performance is measured through
economic sustainability, environmental sustainability, and social sustainability indicators. The findings are expected to
demonstrate that AI adoption significantly improves operational efficiency, innovation capability, environmental
responsibility, and financial performance among MSMEs. The study also highlights the role of organizational readiness
and digital capabilities in facilitating successful AI implementation. The research contributes to the growing literature on
AI-enabled sustainability by providing empirical evidence from the Indian MSME sector and offers practical
recommendations for policymakers, entrepreneurs, technology providers, and researchers. The outcomes of this study are
expected to support India's vision of digital transformation, sustainable industrial development, and enhanced global
competitiveness of MSMEs
This study investigates how AI adoption enhances organizational innovation capability and, in turn, improves economic, environmental, and social dimensions of business performance, and links digital transformation with sustainability outcomes.
S. P, Sriharan M, S. P et al.· International Journal for Re...· 0 citations
Artificial Intelligence (AI) is increasingly being adopted as a strategic capability within the Indonesian telecommunications industry to support digital transformation, enhance operational efficiency, and achieve long-term sustainability performance amid intensifying competition. However, successful AI adoption is determined not only by technological readiness but also by organizational conditions, environmental pressures, and psychological assurances related to trust and data privacy. This study aims to examine the effects of the Technology–Organization–Environment (TOE) framework, Trust in AI, and privacy assurance on organizational Intention to Adopt AI, as well as their subsequent influence on actual AI use behavior and corporate sustainability performance within the Indonesian telecommunications sector. A quantitative research approach was employed using survey data collected from 231 managerial and technical professionals across telecommunications firms. The data were analyzed using Structural Equation Modeling (SEM) with SmartPLS 4 software. The findings indicate that technological, organizational, and environmental readiness, together with trust and privacy assurance, have significant positive effects on Intention to Adopt AI. Furthermore, Intention to Adopt AI is found to be a strong predictor of actual AI use behavior, indicating that adoption intention translates into practical implementation rather than merely reflecting favorable attitudes. Consistent and integrated AI utilization subsequently contributes significantly to corporate sustainability performance, encompassing economic, operational, and environmental dimensions. These results suggest that the sustainability benefits of AI emerge when contextual readiness and psychological assurance jointly enable organizations to move beyond adoption intention toward sustained AI utilization. This study provides valuable insights for industry practitioners and policymakers in designing AI adoption strategies that support sustainable business performance in emerging telecommunications markets.
The adoption of Artificial Intelligence (AI) continues to drive change across various business activities, including in the Micro, Small, and Medium Enterprises (MSME) sector. In the fashion industry, AI-based design platforms have become essential tools for supporting marketing strategies through more engaging, efficient, and consistent visual communication. This study analyzes the impact of using Canva AI on the quality of business decision-making among fashion MSMEs in Bandung, with digital literacy and user experience serving as moderating variables. The method employed is a quantitative explanatory survey, with data collected from 253 fashion MSME owners in Bandung who actively utilize Canva AI in their business operations. Analysis was conducted using SPSS and SmartPLS 4 through validity and reliability tests, factor analysis, and structural equation modeling. The results indicate that the use of Canva AI is positively associated with improved business decision-making quality. However, digital literacy and user experience were not found to significantly moderate the relationship between Canva AI usage and business decision-making quality. These findings indicate that AI-based design technology can enhance promotional effectiveness, strengthen brand identity consistency, and support faster, more accurate, and adaptive decision-making processes in response to market dynamics. This study expands the body of research on AI-based decision support systems for SMEs and provides practical insights for fashion business owners.
Khairunnisa Aghniya Putri, Fanesa Agustina, Hana Fauziah Rahayu et al.· International Journal Admini...· 0 citations
Artificial Intelligence (AI) is increasingly recognized as a transformative tool for improving efficiency, accuracy, and decision-making in construction project management. Despite its potential, the level of AI adoption among small and medium-sized construction businesses (SMEs) in developing economies remains uneven and poorly understood. This study investigates the key determinants influencing AI adoption among construction SMEs in Nigeria. A quantitative research design was employed, informed by Innovation Diffusion Theory and underpinned by the Technology-Organisation-Environment (TOE) framework and the Technology Acceptance Model (TAM). Data were collected through structured questionnaires administered to 382 randomly selected registered construction SMEs, of which 360 valid responses were analysed. Exploratory factor analysis reduced 18 AI adoption variables into three core dimensions: AI functions, AI utilisation, and perceived AI effectiveness. Multiple regression analysis revealed that Technological Infrastructure Readiness was the strongest positive predictor of AI adoption (β = 0.471, p < 0.001). In contrast, Workforce Training and Skills, Industry Collaboration, Regulatory/Institutional Support, and Top Management Support did not significantly influence AI adoption. High implementation costs, resistance to cultural change, and lack of skilled expertise emerged as significant barriers to AI adoption among Nigeria's construction SMEs. The study contributes empirical evidence from a developing-country construction context. It provides practical insights for policymakers, industry regulators, and SME managers seeking to accelerate digital transformation in Nigeria's construction sector.
Samuel Abiodun Alara, P. Kuroshi, I. Anum· Cureus Journal of Business a...· 0 citations
The objective of this study is to examine how artificial intelligence (AI) enabled digital strategy causes to improve business sustainability through marketing innovation and environmental sustainability in United Arab Emirates (UAE). Data collection and analysis used structured questionnaire to gather data from 278 owners and managers of tourism-based micro, small, and medium enterprises (MSMEs). Data was collected using both face-to-face and internet methods that allowed for a large sample pool from many different regions of country. Data was analyzed using Smart PLS structural equation modeling. Results showed that AI enabled digitalization strategies support overall business sustainability, specifically via innovation strategy, whereas environmental management did not provide any significant mediation effects individually. However, both marketing innovation strategies and environmental management contributed independently to the positive outcomes. While digitalization can significantly support sustainable business outcomes, barriers to business sustainability are limited or reduce the positive effects of digitalization during times of high constraints. Finally, the findings of this research demonstrate the necessity of integrating digital tools into innovative practices to obtain long term success for all three factors of sustainability: economically, environmentally, and socially in UAE. In addition, this study contributed to Sustainable Development Goal (SDG) 12 and Sustainable Development Goal (SDG) 13.
A. Aljumah, M. Nuseir, G. El-Refae et al.· Discover Sustainability· 0 citations
Purpose: This study examines the adoption of Artificial Intelligence (AI) among Small and Medium Enterprises (SMEs) in the Kathmandu Valley.
Design/Methodology/Approach: The study employs an explanatory research design to investigate causal relationships among variables. The target population comprises owners, managers, and employees directly involved in decision-making or daily operations within SMEs in the Kathmandu Valley. A probability sampling technique was used to ensure representativeness, yielding a robust sample of 318 respondents. Data were analyzed using Structural Equation Modeling (SEM), a multi-factor statistical framework capable of examining relationships between latent (unobservable) and observed variables.
Findings: The research provides a comprehensive overview of AI adoption patterns among SMEs in the Kathmandu Valley, highlighting both the opportunities for digital transformation and the challenges impeding widespread implementation.
Originality/Value: This study contributes to the limited empirical literature on AI adoption in developing economies, particularly within Nepal’s SME sector.
Keywords: artificial intelligence, attitude, AI adoption, SMEs, Kathmandu valley, structural equation modeling
Aman Lama· SAIM Journal of Social Scien...· 0 citations