The research aims to explore the dynamic relationship between digital service innovation (DSI), artificial intelligence (AI) and business performance (BPer) in service-based models with a focus on how AI-enhanced insights from service use and customer feedback can strengthen business strategies. The aims are to show that DSI and AI are key to driving growth and efficiency in the digital economy and to underscore AI’s role in utilizing contextual data to improve decision-making and business outcomes.
The study uses general structural equation modeling to analyze Spanish manufacturing firms, focusing on medium-sized enterprises and including both business-to-business and business-to-consumer orientations. Data are drawn from the Iberian Balance Analysis System [Sistema de Análisis de Balances Ibéricos (SABI)] database, complemented by a Qualtrics survey to assess the integration of AI in decision-making processes. The methodology is designed to evaluate the interplay between DSI, AI and BPer, with the aim of identifying actionable insights for service-based business orientations.
The study clarifies the relationships between DSI, AI and BPer, providing new theoretical and empirical insights. The findings confirm DSI's direct positive impact on performance and suggest AI’s nuanced mediating role, emphasizing the need for strategic DSI-AI integration in manufacturing firms for enhanced performance.
The research explains the synergistic bond between DSI and AI in boosting BPer and discovering how by-product data can be transformed into strategic insights.
This study advises manufacturing sector leaders to integrate DSI and AI for enhanced performance and competitive advantage, emphasizing the value of high-quality, contextual data for AI learning and decision-making.
Researchers will observe that the study confirms the positive impact of DSI on BPer, while also highlighting the significant role of AI in enhancing this effect.
