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Purpose - This study aims to examine the links between knowledge-oriented leadership (KOL), organizational learning (OL), knowledge sharing (KS), organizational performance (OP) and ISO 9001, as well as the mediating role of OL and KS in the relationship between KOL and OP; and the moderating effect of KS on the relationship between KOL and OP to improve service quality in Iraq's telecommunications and Internet industries. Design/methodology/approach - In-person data collection from 220 employees of 20 Iraqi companies used simple random sampling. The approach comprises path analyses through structural equation modeling, mediation and moderation analyses, respectively. Findings - The findings show that KOL improves OL but not KS. KOL positively and significantly affects OP. OL positively influences OP, whereas KS does not. KS is unaffected by ISO 9001 while OL and OP are. OL significantly and partially mediates the connection between KOL and OP. KS does not mediate the relationship between the KOL and the OP. KS significantly moderates the interaction between KOL and OP. Research limitations/implications - The survey was limited to Iraqi companies and received few responses. Results may not be indicative of the nation. The study evaluated telecommunications and internet companies using self-reported survey data from the COVID-19 period, plus a small amount of demographic data. The study did not cover digital platforms in KS. Originality/value - The study addresses a research gap in learning organization theory by investigating the links between KOL, OL, KS, ISO 9001 and OP in Iraq.
This study aims to identify and prioritize the key factors influencing export performance among Turkish exporters, based on the resource-based view (RBV) and industrial organization theory (IO), categorizing the factors as internal and external, and employing the Stepwise Weight Assessment Ratio Analysis (SWARA). Twenty-five factors across Internal (IF) and External (EF) categories were evaluated through expert assessments. Results reveal that Internal Factors (58.0%) significantly dominate External Factors (42.0%), indicating that Turkish exporters possess substantial control over their export competitiveness. The top five critical factors are Management and Leadership (9.6%), Strategy (6.2%), Technological Change (5.3%), Industry and Sector Activity (5.0%), and Competitors (5.0%). Surprisingly, traditional factors such as firm size, international experience, and digitalization ranked much lower, challenging conventional assumptions about export success. A leave-one-out (LOO) sensitivity analysis further validated the robustness of these rankings, with Management and Leadership, and Strategy emerging as the most stable and dominant factors across all scenarios. The predominance of management and strategic factors over structural characteristics suggests that even smaller, less experienced companies can achieve export success through effective leadership and strategic planning. These findings contribute theoretically by supporting the notion that the resource-based view has a greater impact on export performance than the industrial organization theory, and they provide practical guidance for companies to focus on managerial and leadership skills, organizational capabilities, and strategic approaches to enhance export investments. The study presents the first comprehensive SWARA-based ranking of export performance factors in the Turkish context, providing empirical evidence to support the internal-external factor debate in the international business literature.
The digital transformation of the textile industry poses unique challenges due to its labor-intensive processes, complex global supply chains, and coexistence of traditional methods and emerging technologies. Despite the urgency of this transition, existing digital maturity models lack sector-specific frameworks and often fail to integrate multi-criteria decision-making (MCDM) methodologies for quantitative performance assessment. This study addresses these gaps by proposing a novel digital maturity model tailored specifically to the textile sector. The research employs an integrated decision-making framework using the Method Based on the Removal Effects of Criteria (MEREC) to determine objective criterion weights and the Operational Competitiveness Rating Analysis (OCRA) method to rank firm-level digital maturity performance. The findings indicate that Strategy is the most influential dimension, whereas Technology receives the lowest weight. At the sub-criterion level, Management Support, Market Analysis, and Vision and Strategic Awareness are the most critical factors, while Technology Usage Competency is less influential. The performance evaluation shows that Company A3 achieves the highest level of digital maturity, whereas Company A2 ranks lowest. The robustness of the proposed framework is comprehensively validated through a scenario-based sensitivity analysis and a comparative evaluation using the Additive Ratio Assessment System (ARAS) method. Overall, the results suggest that successful digital transformation in the textile sector depends primarily on strategic vision and managerial support rather than on technological infrastructure alone.
This study investigates the impact of carbon emissions, real oil prices, income inequality, economic growth, and trade openness on renewable energy consumption (REC) in twenty-three (23) OECD economies. The study employs the Westerlund panel cointegration technique to verify the existence of long-run equilibrium and the Augmented Mean Group (AMG) estimator to assess the long-run relationship between the variables, which allows for slope heterogeneity and cross-sectional dependency. Moreover, the panel causality test of Dumitrescu and Hurlin (DH) is utilized to gauge the causal relationship between the variables. The findings of our study reveal that REC is positively related to economic growth, real oil prices, income inequality, and trade openness, but negatively related to CO2 emissions in OECD countries. In addition, there is one-way causality from GDP per capita to renewable energy consumption and a bidirectional causality between income inequality and REC. Furthermore, the results indicate that OECD policymakers and governments should regard foreign trade as a “clean energy fostering mechanism” while developing energy demand policies that are environmentally friendly.
This study examines the impact of artificial intelligence (AI) on the critical thinking (CT) abilities of language instructors in higher education. To this end, 10 university language instructors participated in semi-structured interviews, which were analyzed thematically. Having adapted the CT framework, the data were discussed in four key domains: clarification, advanced clarification, basis of inference, and inference. Participants highlighted the benefits of AI for concept clarification and a subtle understanding of information. Furthermore, they pinpointed the potential of AI to facilitate advanced clarification and a deeper analysis of underlying assumptions. However, regarding the basis of inference, the reliance on AI is reduced, suggesting the need for a practical integration of AI in educational practices. In conclusion, this research highlights the complex perspectives of instructors and underscores the pivotal role of AI in CT in higher education contexts, while emphasizing the need for further research on its implications to inform AI-integrated pedagogical approaches.
