Organizations are integrating big data technologies with Enterprise Resource Planning (ERP) systems with an aim to enhance ERP responsiveness (i.e., the ability of the ERP systems to react towards the large volumes of data). Yet, organizations are struggling to manage the integration between the ERP systems and big data technologies, leading to lack of ERP responsiveness. For example, it is difficult to manage large volumes of data collected through big data technologies and to identify and transform the collected data by filtering, aggregating and inferencing through the ERP systems. Building on this motivation, this research examined the factors leading to ERP responsiveness with a focus on big data technologies. The conceptual model which was developed through a systematic literature review was tested using Structural equation modelling (SEM) performed on the survey data collected from 110 industry experts. Our results suggested 12 factors (e.g., big data management and data contextualization) and their relationships which impact on ERP responsiveness. An understanding of the factors which impact on ERP responsiveness contributes to the literature on ERP and big data management as well as offers significant practical implications for ERP and big data management practice.
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http://dx.doi.org/10.1007/s10796-023-10374-w | DOI Listing |
J Integr Neurosci
December 2024
Department of Computer Science and Engineering, Shaoxing University, 312000 Shaoxing, Zhejiang, China.
Background: Motor imagery (MI) plays an important role in brain-computer interfaces, especially in evoking event-related desynchronization and synchronization (ERD/S) rhythms in electroencephalogram (EEG) signals. However, the procedure for performing a MI task for a single subject is subjective, making it difficult to determine the actual situation of an individual's MI task and resulting in significant individual EEG response variations during motion cognitive decoding.
Methods: To explore this issue, we designed three visual stimuli (arrow, human, and robot), each of which was used to present three MI tasks (left arm, right arm, and feet), and evaluated differences in brain response in terms of ERD/S rhythms.
JACS Au
December 2024
Natural Products Research Institute, College of Pharmacy, Seoul National University, Seoul 08826, Republic of Korea.
Four new macrolides, spirosnuolides A-D (-, respectively), were discovered from the termite nest-derived sp. INHA29. Spirosnuolides A-D are 18-membered macrolides sharing an embedded [6,6]-spiroketal functionality inside the macrocycle and are conjugated with structurally uncommon side chains featuring cyclopentenone, 1,4-benzoquinone, hydroxyfuroic acid, or butenolide moieties.
View Article and Find Full Text PDFJAMIA Open
February 2025
Medical Oncology, IRCCS Sacro Cuore Don Calabria Hospital, 37024 Negrar di Valpolicella, Verona, Italy.
Objectives: In recent years, the rise of big data and artificial intelligence has led to an increasing expansion of databases and web services in biomedical research. cBioPortal is one of the most widely used platforms for accessing cancer genomic and clinical data. The primary objective of this study was to develop a tool that simplifies programmatic interaction with cBioPortal's web service.
View Article and Find Full Text PDFFront Plant Sci
December 2024
Chongqing Key Laboratory of Big Data for Bio Intelligence, Chongqing University of Posts and Telecommunications, Chongqing, China.
Introduction: Orchids are renowned for their intricate floral structures, where sepals and petals contribute significantly to ornamental value and pollinator attraction. In Section , the distinctive curvature of these floral organs enhances both aesthetic appeal and pollination efficiency. However, the molecular and cellular mechanisms underlying this trait remain poorly understood.
View Article and Find Full Text PDFFront Public Health
December 2024
School of Economics and Management, Huainan Normal University, Huainan, China.
China's "14th Five-Year Plan" proposes the construction of a "Digital China," posing the challenge of digital transformation to coal mining enterprises. It is critical to compare the effectiveness of investing in digital devices with that of human capital. This study establishes a structural equation model based on the 'regulation-situation-behavior' theoretical framework.
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