AI tool adoption as a driver of digital business model innovation and retail firm performance

Artificial Intelligence Adoption and Sustainable Business Performance: The Mediating Role of Innovation Capability

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.

From individual acceptance to organizational agility: how e-commerce SMEs can transform AI adoption into marketing capabilities

This study demonstrates the joint influencing mechanism of organizational and individual factors, providing empirical evidence to engage with the micro-foundations debates within the theoretical framework of dynamic capabilities.

Digitalization, analytics capabilities and digital leadership: how innovation capabilities and business intelligence mediate sustainable performance

In today's business world, organizations that lack innovation capabilities face substantial barriers to achieving sustainable performance. In manufacturing firms operating in the sports industry, sustainable performance increasingly depends on a strong understanding of digitalization. Accordingly, this study examines the effects of digitalization, analytics capabilities (AC) and digital leadership (DL) on sports firms' sustainable performance (SFSP), with particular. Data for this study were collected through a structured survey administered to 339 managers and executives from Chinese sports companies. A purposive sampling technique was employed. Statistical software packages SPSS and SmartPLS were used for data analysis. In addition, descriptive statistics, Pearson correlation, regression analysis and moderation analysis were conducted to examine the relationships among the variables. The results indicate that digitalization, AC and DL have significant positive effects on innovation capabilities (IC) and business intelligence (BI). In turn, both IC and BI positively contribute to the sustainable performance of sports firms. These findings suggest that strengthening digital and analytical capabilities can enhance sustainable performance through improved innovation and intelligence mechanisms. The present study provides valuable implications for a range of stakeholders, including sports firms, technology developers, policymakers and practitioners. It assists these stakeholders in formulating and implementing strategies to enhance SFSP. Furthermore, the study underlines the nexus between digital transformation and sustainability by explaining how dynamic capabilities drive innovation and support sustainable performance in sports companies. The knowledge gained from this study is important to navigate the evolving challenges of sports companies in the manufacturing sector. Its significant contribution to the dynamic capability theory offers a fresh insight into how sports firms can develop, build and seize IC and business intelligence to improve SFSP, which is the uniqueness of our study.

Digital Transformation and Innovation Performance in Manufacturing Firms: The Mediating Role of Absorptive Capacity and the Moderating Role of R&D Human Capital

This study empirically investigated the effect of digital transformation on innovation performance in manufacturing firms and examined the mediating role of absorptive capacity and the moderating role of R&D human capital. As manufacturing industries increasingly experience rapid technological changes driven by artificial intelligence (AI), big data, the Internet of Things (IoT), and smart manufacturing systems, digital transformation has emerged as a critical strategic factor for enhancing organizational competitiveness and innovation capability. However, prior studies have suggested that the adoption of digital technologies alone does not necessarily guarantee sustainable innovation performance. Therefore, this study attempted to explain the relationship between digital transformation and innovation performance from the perspectives of organizational learning and human capital. Data were collected from 402 employees working in Korean manufacturing firms through online and offline surveys. The collected data were analyzed using Structural Equation Modeling (SEM) with SPSS 29.0 and SmartPLS 4.0. The results indicated that digital transformation had a significant positive effect on innovation performance and absorptive capacity. In addition, absorptive capacity positively influenced innovation performance and partially mediated the relationship between digital transformation and innovation performance. Furthermore, R&D human capital significantly moderated the relationship between digital transformation and innovation performance, indicating that the positive effect of digital transformation on innovation performance was stronger in firms with higher levels of R&D human capital. The findings suggest that digital transformation contributes to innovation performance not only through technological efficiency but also through enhanced organizational learning and knowledge utilization capabilities. This study provides academic implications by integrating digital transformation, absorptive capacity, and R&D human capital into a comprehensive research framework. In addition, it offers practical implications for manufacturing firms by emphasizing the importance of organizational learning systems and the development of R&D personnel capabilities alongside digital technology investment.

THE IMPACT OF 2026 DIGITAL MARKETING TRENDS ON BUSINESS PERFORMANCE OF MSMEs IN COIMBATORE: A STRUCTURAL EQUATION MODELING APPROACH

This research paper examines the transformative impact of 2026 digital marketing trends on the business performance of Micro, Small, and Medium Enterprises (MSMEs) in Coimbatore, India. By 2026, the marketing landscape has shifted significantly toward artificial intelligence (AI)-driven personalization, social commerce, and sustainable marketing practices. Utilizing a Structural Equation Modeling (SEM) approach with AMOS 28.0, this study investigates how these trends influence critical performance dimensions such as consumer trust, brand loyalty, and purchase intention. Data collected from a sample of MSMEs across Coimbatore's industrial and retail sectors reveals that AI adoption and localized data-driven advertising are major predictors of enhanced business outcomes. Specifically, the integration of predictive analytics and automated customer engagement tools has been shown to strengthen the relationship between brand identity and consumer satisfaction. The findings offer a strategic roadmap for Coimbatore business owners to leverage advanced marketing technologies to maintain competitive relevance in a rapidly evolving digital economy.

A Study of the Impact of Digital Transformation on Business Performance in Manufacturing Enterprises