Introduction: The growing competitiveness and the importance of data availability for organizations have created a demand for intelligent information systems capable of analyzing data to support strategy and decision-making. Organizations are generating more and more data due to new technologies associated with Industry 4.0 and Logistics 4.0, making it essential to transform this data into relevant information to streamline decision-making processes. This paper examines the influence of these technologies on gaining a competitive advantage, specifically in a logistics company, which is scarce in the literature.
Methods: A case study was conducted in a Portuguese company using the Delphi method with 61 participants-employees who use the company's integrated BI tool daily. The participants were presented with a questionnaire via the online platform Welphi, requiring qualitative responses to various statements based on the literature review and the results of semi-structured meetings with the company.
Results: The study aimed to identify areas where employees believe more investment/ development is needed to optimize processes and improve the use of the BI tool in the future. The results indicate that BI is a crucial technology when aligned with a company's objectives and needs, highlighting the necessity of top management's involvement in optimizing the BI tool. Encouraging employees to use the BI tool emerged as a significant factor, underscoring the importance of leadership in innovative projects to achieve greater competitive advantage for the company.
Discussion: This study aims to understand the importance of Business Intelligence (BI) and how its functionalities should be adapted according to a company's strategy and objectives to optimize decision-making processes. Thereby, the discussion focused on the essential role of BI technologies in leveraging the company's competitive advantage.
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http://dx.doi.org/10.3389/frai.2024.1469958 | DOI Listing |
Sci Total Environ
January 2025
State Key Laboratory of Marine Environmental Science/College of the Environment and Ecology, Xiamen University, Xiamen 361005, China; Key Laboratory of Marine Ecology & Environmental Sciences, Institute of Oceanology, Chinese Academy of Sciences, Qingdao 266071, China. Electronic address:
Understanding metabolic activities involved in bloom formation during a single-species algal bloom has improved greatly. However, little is known about metabolic activities during a multi-species algal bloom. Here, we investigated protein expression profiles at different bloom stages of a mixed dinoflagellate bloom caused by Karenia mikimotoi and Prorocentrum obtusidens (syn.
View Article and Find Full Text PDFJ Theor Biol
January 2025
Faculty of Mathematics, Technion - IIT, Haifa, 32000, Israel. Electronic address:
The competitive exclusion principle in epidemiology implies that when competing strains of a pathogen provide complete protection for each other, the strain with the largest reproduction number outcompetes the other strains and drives them to extinction. The introduction of various trade-off mechanisms may facilitate the coexistence of competing strains, especially when their respective basic reproduction numbers are close so that the competition between the strains is weak. Yet, one may expect that a substantial competitive advantage of one of the strains will eventually outbalance trade-off mechanisms driving less competitive strains to extinction.
View Article and Find Full Text PDFToxicology
January 2025
Key Laboratory of Chemical Safety and Health, National Institute for Occupational Health and Poison Control, Chinese Center for Disease Control and Prevention, Beijing, China; China State Key Laboratory of Trauma, Burn and Combined Injury, China. Electronic address:
Patients with benzene-induced leukemia undergo a continuous transformation from myelosuppression to malignant proliferation. However, the underlying mechanisms in this process remain unknown. Our previous studies have shown that the pathways involved in self-renewal capacity of bone marrow (BM) cells in Mll-Af9 mice exposed to benzene for life are significantly activated after severe blood toxicity.
View Article and Find Full Text PDFJ Clin Epidemiol
January 2025
Univ Rennes, CHU Rennes, Inserm, EHESP, Irset (Institut de recherche en santé, environnement et travail) - UMR_S 1085, Centre d'investigation clinique de Rennes (CIC1414), Rennes, France; Institut Universitaire de France (IUF), Paris, France.
Guided by the FAIR principles (Findable, Accessible, Interoperable, Reusable), responsible data sharing requires well-organized, high-quality datasets. However, researchers often struggle with implementing Data Management and Sharing Plans (DMSPs) due to lack of knowledge on how to do this, time constraints, legal, technical and financial challenges, particularly concerning data ownership and privacy. While patients support data sharing, researchers and funders may hesitate, fearing the loss of intellectual property or competitive advantage.
View Article and Find Full Text PDFInterdiscip Sci
January 2025
Institute for Complexity Science, Henan University of Technology, Zhengzhou, 450001, China.
Artificial intelligence technology has demonstrated remarkable diagnostic efficacy in modern biomedical image analysis. However, the practical application of artificial intelligence is significantly limited by the presence of similar pathologies among different diseases and the diversity of pathologies within the same disease. To address this issue, this paper proposes a reinforced collaborative-competitive representation classification (RCCRC) method.
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