Service composition enables the integration of multiple services to create new functionalities, optimizing resource utilization and supporting diverse applications in critical domains such as safety-critical systems, telecommunications, and business operations. This paper addresses the challenges in comparing load-balancing algorithms within service composition environments and proposes a novel dynamic load-balancing algorithm designed specifically for these systems. The proposed algorithm aims to improve response times, enhance system efficiency, and optimize overall performance. Through a simulated service composition environment, the algorithm was validated, demonstrating its effectiveness in managing the computational load of a BMI calculator web service. This dynamic algorithm provides real-time monitoring of critical system parameters and supports system optimization. In future work, the algorithm will be refined and tested across a broader range of scenarios to further evaluate its scalability and adaptability. By bridging theoretical insights with practical applications, this research contributes to the advancement of dynamic load balancing in service composition, offering practical implications for high-tech system performance.

This study examines conditions that impact PPP delivery success or failure in the roadways sector in India using Qualitative Comparative Analysis. QCA is well-suited for problems where multiple factors combine to create pathways leading to an outcome. Past investigations have compared PPP and non-PPP project delivery performance, but this study examines performance within PPPs by uncovering a set of conditions that combine to influence the success or failure road PPP project delivery in India. Based on data from 21 cases, pathways explaining project delivery success or failure were identified. Specifically, PPPs with high concessionaire equity investment and low regional industrial activity led to project delivery success. Projects with lower concessionaire equity investment and low reliance on toll revenue and with either: (a) high project technical complexity or (b) high regional industrial activity, led to project delivery failure. The pathways identified did not have coverage values that they were extremely strong. Coverage strength was hindered by lack of access to information on additional conditions that could be configurationally important. Further, certain characteristics of the Indian market limit generalization. Identification of combinations of conditions leading to PPP project delivery success or failure improves knowledge of the impacts of structure and characteristics of these complex arrangements. This study is one of the first to use fuzzy QCA to understand project delivery success/failure in road PPP projects. Moreover, this study takes into account factors specific to a sector and delivery mode to explain project delivery performance.

In today's highly competitive environment, enterprises strive for competitive advantages by actively responding to changes in the network environment through digital technology. This approach fosters continuous innovation and establishes new paradigms by creating new network structures and relationships. However, research on the relationship and transmission mechanisms between digital technology and innovation performance in dynamic environments is still in its early stages, which does not fully address the demands of current social practice. Therefore, exploring the impact mechanisms of digital technology applications on enterprise innovation performance is an important research area. Based on the dynamic capability theory, this paper utilized SPSS 26.0 and AMOS 24.0 software to conduct an empirical analysis of 490 valid samples from the network perspective, exploring the pathways through which digital technology capability influences enterprise innovation performance. The results indicate that (1) digital technology capability is positively correlated with enterprise innovation performance; (2) digital technology capability is positively correlated with network responsiveness; (3) network responsiveness is positively correlated with enterprise innovation performance; (4) network responsiveness plays a mediating role in the impact of digital technology capability on enterprise innovation performance; (5) environmental dynamism positively moderates the relationship between digital technology capability and enterprise innovation performance. This paper enhances the understanding of how digital technology capability influences enterprise innovation performance in dynamic environments, offering new insights for future research. The results suggest that enterprises should focus on enhancing their digital technology capabilities, optimizing network structures, and strengthening network relationships to drive digital innovation.

This research investigates the impact of modern technological methods of knowledge management (KM) and total quality management (TQM) on the performance of faculty members in educational colleges in Jordan. Drawing on a survey conducted with 306 faculty members, the study examines the influence of technology on teaching methodologies and academic quality within the Jordanian higher education context. The study utilizes the Technology Acceptance Model (TAM) to back up the modern technological methods of knowledge management (KM) and total quality management (TQM) models. The findings reveal a generally positive perception among respondents regarding the beneficial effects of modern technological tools on teaching effectiveness, collaboration, and innovation. Additionally, technology-enhanced TQM practices were found to contribute to improvements in curriculum design, student engagement, and administrative processes. Regression and correlation analyses support significant relationships between technology-enabled KM and TQM practices and faculty performance, highlighting the transformative role of technology in shaping the future of higher education in Jordan. Recommendations are provided for educational institutions to enhance the integration of technology and foster a culture of innovation and continuous improvement among faculty members.

Entrepreneurial Orientation (EO) emphasizes the identification and exploitation of business opportunities, while entrepreneurial action learning (EAL) underscores the acquisition of knowledge through practical experience and continuous improvement. Breakthroughs in both aspects contribute to maintaining flexibility, adapting to changes, and enabling success in competitive markets. The key to the development of small and medium-sized enterprises (SMEs) lies in a clear Entrepreneurial Orientation, a focus on Entrepreneurial Action Learning, and the cultivation of innovation spirit through continuous practice and experience accumulation, thereby enhancing entrepreneurial performance (EP). This study aims to explore the impact of Entrepreneurial Orientation on the Entrepreneurial Performance of SMEs, clarify the mediating role of Entrepreneurial Action Learning between Entrepreneurial Orientation and Entrepreneurial Performance, and investigate the variability of Entrepreneurial Performance among different industries. By means of data collection from 598 SMEs, data analysis was conducted using Structural Equation Modeling (SEM) and Analysis of Variance (ANOVA). The analysis results indicate that entrepreneurial orientation has a positive impact on entrepreneurial action learning and entrepreneurial performance, and entrepreneurial action learning has a positive impact on entrepreneurial performance. The study also found that entrepreneurial action learning partially mediates the relationship between entrepreneurial orientation and entrepreneurial performance. There are certain differences in entrepreneurial performance among different industries. This study enriches the relevant literature in the field of entrepreneurship. Additionally, research on entrepreneurial orientation, entrepreneurial action learning, and entrepreneurial performance in specific regional contexts is very limited, making this study valuable for subsequent research in related areas.