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As organizations navigate an increasingly dynamic digital landscape, the challenge of achieving consistent product success has intensified. This study investigates how key management factors-customer-driven product development, open innovation networks, organizational digital agility, and AI-integrated project management-influence digital product outcomes. Special attention is given to the dual role of artificial intelligence: as a potential enabler of innovation and a possible constraint when applied in rigid or misaligned ways. A quantitative survey was conducted among 239 professionals engaged in product-related roles across diverse industries and regions. Data were analyzed using linear regression, moderation analysis, and non-parametric testing to assess both direct and interaction effects among the variables. The results reveal that customer-driven product development, open innovation networks, and organizational digital agility each have a statistically significant positive impact on product success, with customer-driven development emerging as the strongest predictor. In contrast, AI-integrated project management does not demonstrate a significant direct effect. Notably, AI negatively moderates the relationship between open innovation networks and product success, suggesting that while AI may enhance structured knowledge-sharing, it can also diminish the creative and collaborative elements essential for innovation if not carefully managed. These findings highlight the strategic complexity of integrating AI into digital product development. While AI can enhance operational efficiency and knowledge flows, its impact on innovation outcomes is context-dependent and may disrupt the balance between human creativity and automated decision-making. The study underscores the need for hybrid models in which AI complements-not replaces-human expertise. Insights from this research offer valuable guidance for organizations aiming to design resilient, customer-centric, and innovation-driven digital product strategies in an AI-enhanced environment.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC12396679 | PMC |
http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0331229 | PLOS |
JMIR Med Inform
September 2025
Global Health Economics Centre, Public Health and Policy, London School of Hygiene and Tropical Medicine, London, United Kingdom.
Background: Artificial intelligence (AI) algorithms offer an effective solution to alleviate the burden of diabetic retinopathy (DR) screening in public health settings. However, there are challenges in translating diagnostic performance and its application when deployed in real-world conditions.
Objective: This study aimed to assess the technical feasibility of integration and diagnostic performance of validated DR screening (DRS) AI algorithms in real-world outpatient public health settings.
Food Chem
September 2025
Group of Chemical Analysis and Chemometrics, Department of Chemistry, Federal University of Paraná, P.O. Box: 19032, Curitiba, PR 81531-980, Brazil. Electronic address:
Yerba mate, a key crop in South America, is prized for its pleasant taste and high organoleptic quality, often linked to lower branch content. To quantify branch content and authenticate high-quality samples (less than 30 % m/m branch content), a Chemometrics-assisted Color Histogram-based Analytical System (CACHAS) was employed. Using Hue-Saturation-Value (HSV) histograms, Partial Least Squares (PLS) demonstrated excellent predictive performance, achieving a root mean square error (RMSEP) of 4.
View Article and Find Full Text PDFAppl Radiat Isot
September 2025
Kahramanmaraş İstiklal University, Department of Energy Systems Engineering, Kahramanmaraş, Türkiye.
The rapid advancement of three-dimensional (3D) printing technologies has significantly expanded their potential applications such as sensors and detector technology. In this study, the gamma-ray shielding performance of ulexite-doped composite resins fabricated via Digital Light Processing (DLP) 3D printing was experimentally investigated to evaluate radiation attenuation capacity. Composite resins containing different ulexite loadings (0, 1, 3, and 5 wt%) were exposed to gamma rays at energies of 356, 662, 1173, and 1333 keV to evaluate their attenuation characteristics.
View Article and Find Full Text PDFACS Nano
September 2025
Eastern Institute for Advanced Study, Eastern Institute of Technology, Ningbo, Zhejiang 315200, P. R. China.
Ni-Fe (oxy)hydroxides are among the most active oxygen evolution reaction (OER) catalysts in alkaline media. However, achieving precise control over local asymmetric Fe-O-Ni active sites in Ni-Fe oxyhydroxides for key oxygenated intermediates' adsorption steric configuration regulation of the OER is still challenging. Herein, we report a two-step dealloying strategy to fabricate asymmetric Fe-O-Ni pair sites in the shell of NiOOH@FeOOH/NiOOH heterostructures from NiFe Prussian blue analogue (PBA) nanocubes, involving anion exchange and structure reconstruction.
View Article and Find Full Text PDFPLoS One
September 2025
College of Economics and Management, Inner Mongolia Agricultural University, Hohhot, China.
Against the backdrop of grassland ecological degradation, grassland transfer has become a crucial pathway for optimizing livestock resource allocation and promoting sustainable pastoral development. Based on survey data from 383 herder households in the farming-pastoral ecotone of Inner Mongolia, China, this study applies Heckman models, mediation models, and moderation models to examine the impact of digital technology on herders' grassland leasing-in decisions and the underlying mechanisms. The results indicate that digital technology significantly increases both the probability and the scale of grassland leasing-in among herders.
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