Coordinates: 31°53′36″N 35°52′23″E / 31.89333°N 35.87306°E / 31.89333; 35.87306University of Petra is a private university in Amman, Jordan. The University offers the Bachelor and Master Program and has more than 33 nationalities from Arab and foreign countries. The University is located on the airport road and features a green campus as well as facilities such as workplaces, laboratories, ceremonies and studios. It offers an applied education..
Purpose This study addresses how small and medium-sized enterprises (SMEs) in turbulent emerging markets translate Corporate Social Responsibility (CSR) into performance gains. We develop and test the Legitimacy-Enabled Capability Activation (LECA) model, which positions Digital Transformation (DT) as the central mechanism linking CSR to performance, and examine the contingent role of market turbulence (MT).Design/methodology/approach Integrating Resource-Based View, Dynamic Capabilities, Stakeholder, and Contingency theories, we test a moderated-mediation model using PLS-SEM on survey data from 536 owner-managers of Jordan's food-processing SMEs.Findings CSR strongly fosters DT, which in part mediates the CSR-performance relationship. Furthermore, market turbulence intensifies the DT-performance link, strengthening the indirect effect of CSR on performance through DT.Practical implications Managers should treat CSR as a strategic legitimacy-building resource, not a peripheral activity, as it lowers barriers to digital transformation. Policymakers can amplify this effect by linking CSR incentives with direct support for digital infrastructure and skills. In emerging markets where disruptions are common and institutions are often weak this coordinated approach helps SMEs sustain employment and maintain vital stability within their communities.Originality/value We introduce the LECA framework, providing the first empirical evidence of a moderated mediation process where CSR boosts performance through DT, with this effect amplified under high market turbulence. This advances dynamic capabilities theory by framing turbulence as a capability activator and offers actionable insights for SMEs in volatile environments.
Accurate estimation of energy requirements for biomass pyrolysis is essential for designing cost‑efficient and sustainable thermochemical conversion systems. This study addresses the challenge of predicting pyrolysis energy requirement by integrating comprehensive feedstock compositional data with process operational parameters, analyzed through a machine learning (ML)‑based framework. A curated dataset of 633 experimentally validated records from peer‑reviewed publications was compiled, encompassing elemental composition (C, H, N, S, O, and ash content), biochemical composition (protein, lipid, and carbohydrate), and operational parameters. Models were trained and validated using a 9:1 split with five-fold cross‑validation to ensure robust generalization. Eight algorithms, including decision tree, adaptive boosting (AdaBoost), random forest, K‑nearest neighbors (KNN), ensemble learning, convolutional neural network (CNN), support vector regression (SVR), and multilayer perceptron (MLP), were optimized via hyperparameter tuning and evaluated through the coefficient of determination (R2), mean squared error (EMS), and average absolute relative error (EAAR). Results demonstrated that AdaBoost and random forest achieved superior generalization on unseen data (test R2≥0.893 and test EAAR≤7.18
A simple and sensitive electrochemical sensor based on a thiourea-modified platinum electrode (TU–Pt) was developed for the quantitative determination of catechol (CC) in tea samples. For the detection of catechol (CC) in tea samples, a straightforward and sensitive electrochemical sensor based on a thiourea-modified platinum electrode (TU–Pt) was created. Cyclic voltammetry and SEM-EDX analysis verified the surface modification, indicating improved electroactive surface characteristics of the TU-Pt electrode. At roughly 0.50 V, catechol showed a distinct oxidation peak in differential pulse voltammetry. The suggested sensor had a detection limit of 0.05 µM and a broad linear range of 1.0 µM to 5.0 mM with good linearity (R2 = 0.998). Corresponding with recovery values (83.94 − 86.71
This study aimed to examine athletes' perceptions of the Talent Development Environments (TDEs) in Ondo, Nigeria, and identify differences in the quality of the TDEs according to sex, type of sport, and environment type. Six hundred and fifty-two athletes, across 20 sports, completed the Talent Development Environment Questionnaire-9S (TDEQ-9S). The results revealed that Fostering Athlete Understanding and Clear Long-term Development Priority & Preparation were the highest scoring factors, while Active Management of Holistic Development (Education, Parents, Life Management), and Coherent and Approachable Expert Support Network in Sport were the lowest scoring factors. MANOVA tests revealed statistically significant differences across TDEQ-9S factors for sport, age, and environment type but not sex. Statistically significantly higher scores were apparent for individual sports and older athletes across four and six factors, respectively. Significantly higher scores were found for state-managed TDEs across all TDEQ-9S factors, except for Fostering Athlete Understanding. Item-by-item analysis revealed more nuanced findings, highlighting the complementary ways these TDEs are serving Nigerian athletes, and the areas for improvement that can be targeted in an efficient way. Implications for both the Nigerian context and more broadly for researchers and practitioners in other developing countries are discussed.
This paper mainly presents upper bounds for the singular values and unitarily invariant norms of the product of two complex matrices. The obtained bounds refine many celebrated results in the literature, such as the celebrated matrix arithmetic-geometric mean inequality and its variants.
