Artificial intelligence–driven open innovation for sustainable service innovation leading to ethical and organizational pathways to enhanced business performance management
Examining how Artificial Intelligence capabilities positively influence the performance and development of sustainable service innovation (SSI) within banks of Saudi Arabia provided insight in relation to how to implement AI technology as a structured process in the development of sustainable and competitive high performance financial services.
Abstract
The current research examined how Artificial Intelligence (AI) capabilities positively influence the performance and development of sustainable service innovation (SSI) within banks of Saudi Arabia. Research explored both the internal and external knowledge sources to identify potential mediators between AI capacity and developing SSI. This research utilized quantitative approach and data collection was preferred by employees of banks. Structural equation modeling was utilized to identify key findings that indicated positive impacts of AI capacity on SSI development directly and indirectly with the use of internal knowledge, however, did not validate external knowledge as a mediator. SSI development was determined to have a positive impact on financial performance for financial institutions resulting in an opportunity to demonstrate ethical and customer focused business value for innovative development. Theoretical contributions related to the resource-based view (RBV) and open innovation models were achieved through illustrations of the relationships between AI capacity, knowledge processes, and practices with the organization. Practically this study provided insight in relation to how to implement AI technology as a structured process in the development of sustainable and competitive high performance financial services.
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
The capacity to coordinate human capital and knowledge resources to sustainable innovation has emerged as the final boundary to organizational survival in the transition to a global green economy. This research paper explains the strategic design of Green Human Resource Management (GHRM), Green Knowledge Sharing (GKS), and Green Innovation (GI) as an integrated architecture towards the optimal Organizational Environmental Performance (OEP). Based on the Knowledge-Based View (KBV) and the Natural Resource-Based View (NRBV), the study outlines how manufacturing companies develop path-dependent capabilities in which human capital and knowledge intangibles are integrated into ecological excellence. The empirical data were collected via a multi-respondent approach from an initial sample of 500 manufacturing SMEs from China, yielding 309 final valid and complete responses. The outcomes of Covariance-Based Structural Equation Modeling (CB-SEM) conducted via AMOS v.26 demonstrate strong evidence that GHRM positively influences GKS and leads to enhanced green innovation, which subsequently improves OEP. In particular, the results support the view that green knowledge is a strategic-level resource, concomitant with KBV, that enables the smooth incorporation of idiosyncratic environmental knowledge into routine operations. This study provides a clear strategic road map, which holds that the harmonization of human resource systems with knowledge-based resources is the most plausible path to achieving high levels of environmental performance in an ever-more institutionalized, environmentally conscious global supply chain.
Yujun Gao, Kashif Ali, Nawal abdalla adam et al.· The Journal of Environment &...· 0 citations
Organizations increasingly face strategic pressure to translate sustainability‐oriented knowledge and digital transformation initiatives into measurable environmental and organizational outcomes. In response, this study investigates how green knowledge management (GKM) contributes to sustainable business performance through the organizational mechanisms of green human capital, green leadership, green technological innovation, and green management innovation. Drawing on the knowledge‐based view and sociotechnical systems theory, the study further conceptualizes artificial intelligence (AI) adoption as an enabling organizational and digital capability that strengthens firms' ability to operationalize sustainability‐oriented knowledge. A cross‐sectional survey was conducted among Algerian manufacturing and service firms, and the data were analyzed using partial least squares structural equation modeling (PLS‐SEM). The findings reveal that GKM enhances sustainable performance indirectly through green human capital, green leadership, and green management innovation. Moreover, AI adoption strengthens the effectiveness of GKM in facilitating green human capital development, supporting green innovation processes, and enabling sustainability‐oriented organizational transformation. However, the direct relationship between GKM and sustainable performance was not significant, suggesting that the strategic value of sustainability‐oriented knowledge depends on complementary organizational capabilities and execution mechanisms. This study contributes to sustainability strategy literature by explaining how firms orchestrate interconnected knowledge, innovation, leadership, and digital capabilities to support sustainable organizational performance, particularly within the underexplored context of emerging economies.
Hafiz Mudassir Rehman, Sofiane Laradi, Sandra Moffett et al.· Business Strategy and the En...· 0 citations
The research shows that AI implementation has the potential to positively impact supply chain performance, directly and indirectly, through marketing innovation and organisational agility, and technological preparation reinforces the connection between marketing innovation and performance.
Abhishek Shrivastav· Journal of Supply Chain Mana...· 0 citations
This research investigates the relationship between artificial intelligence-integrated digital ecosystem, digital maturity, organisational resilience, and the mechanism of sustainable value co-creation and performance results in small and medium-sized firms in East Java, Indonesia. It aims to elucidate how these five factors collectively foster long-term resilience and sustainability in increasingly information-dense business environments.The Quantitative Method was applied with the SEM-PLS approach in the SmartPLS 3.2 program. The survey included 151 SMEs with different demographic characteristics. The model was evaluated for predictive relevance (Q2), common method bias, bootstrapped path coefficients, confirmatory factor analysis, correlation analysis, multicollinearity, and construct reliability. Data were obtained between December 2025 and April 2026.The results reveal that AI-enabled digital ecosystems have a remarkable and favourable effect on organisational resilience and sustainable value co-creation, hence improving sustainable performance. Digital maturity serves as an important enabler and mediator, further enhancing the benefits of these AI-enabled solutions. Moreover, sustainable value co-creation is found as the main predictor of sustainable performance, and the link between resilience and co-creation is reciprocal, showing a reinforcing dynamic.This study contributes to the current literature by extending the conceptualisation of SME success to include economic, social and environmental factors. Moreover, it provides a solid basis for understanding the role of AI ecosystems and digital maturity in supporting resilience and sustainability, allowing resource-constrained SMEs to retain their competitive advantage, while also supporting international sustainability agendas such as the Sustainable Development Goals and Environmental, Social, and Governance standards.
Eka Ananta Sidharta, Yona Octiani Lestari, Ersa Tri Wahyuni et al.· Journal of Intelligent Decis...· 0 citations
Artificial intelligence (AI) is increasingly used by small- and medium-sized enterprises (SMEs), but its role in sustainable business transformation remains unclear, especially in emerging economies where adoption is often fragmented and experimental. This study examines how AI use is associated with Sustainable Value Creation through Entrepreneurial Reconfiguration Capability (ERC) and Business Model Innovation (BMI). ERC refers to a firm’s capability to interpret AI-enabled opportunities, recombine existing resources, govern experimentation with new value configurations, and decide which AI-related initiatives should be scaled. Using survey data from 385 SMEs in four Ecuadorian sectors and Partial Least Squares Structural Equation Modeling (PLS-SEM), the study tests a sequential model linking AI use, ERC, BMI, and Sustainable Value Creation. The findings show positive associations between AI use and ERC, ERC and BMI, and BMI and Sustainable Value Creation. The results suggest that AI adoption alone is unlikely to be associated with sustainable value unless SMEs develop entrepreneurial capabilities that connect AI use with business model innovation. The study contributes by shifting the focus from AI adoption to AI-enabled entrepreneurial transformation in SMEs from an emerging-economy context. Future research should examine moderating factors related to digital maturity, institutional support, environmental dynamism, firm size, and sectoral conditions.
Alexander Sánchez-Rodríguez, J. Rodríguez-Flores, Reyner Pérez-Campdesuñer et al.· Sustainability· 0 citations
