Search Results - subject:"Big Data/Analytics"

Industry 4.0 and Six Sigma : a systematic review of the literature and research agenda proposal

Maia, Daniele dos Reis Pereira; Lizarelli, Fabiane Letícia - In: Benchmarking : an international journal 31 (2024) 3, pp. 1009-1037

Persistent link: https://www.econbiz.de/10015397300

The determinants of export performance in the digital transformation era : empirical evidence from manufacturing firms

AL-Khatib, Ayman Wael - 2024

Persistent link: https://www.econbiz.de/10015375523

Can big data analytics capability promote firm innovation? : a moderated mediation model of organizational learning and market orientation

Song, Moxi; Liao, Yuanhong - In: Baltic journal of management : BJM 19 (2024) 5, pp. 531-548

Persistent link: https://www.econbiz.de/10015400768

Adoption of big data analytics (BDA) technologies in disaster management: A Decomposed Theory of Planned Behavior (DTPB) approach

Zaman, Umer; Zahid, Hasan; Habibullah, Muzafar Shah - In: Cogent Business & Management 8 (2021) 1, pp. 1-20

Big data analytics (BDA) technologies have emerged as a cornerstone for predicting, preparing, and preventing natural …

Persistent link: https://www.econbiz.de/10014001670

Adoption of big data analytics and its impact on organizational performance in higher education mediated by knowledge management

Marchena Sekli, Giulio Franz; De la Vega Hernández, … - In: Journal of Open Innovation: Technology, Market, and … 7 (2021) 4, pp. 1-22

generated, and technologies such as big data analytics are needed to create opportunities for open innovation by obtaining … valuable knowledge. The purpose of this paper is to investigate the factors that influence the adoption of big data analytics … compatibility, an adequate organizational data environment, and external support as factors required to adopt big data analytics …

Persistent link: https://www.econbiz.de/10014329480

Korherr, Philipp; Kanbach, Dominik - In: Review of Managerial Science (2021), pp. 1-28

context of Big Data Analytics (BDA). This paper provides a holistic framework of human-related capabilities that organizations …

Persistent link: https://www.econbiz.de/10014501765

No Longer Out of Sight, No Longer Out of Mind? How Organizations Engage with Process Mining-Induced Transparency to Achieve Increased Process Awareness

Eggers, Julia; Hein, Andreas; Böhm, Markus; Krcmar, Helmut - In: Business & Information Systems Engineering 63 (2021) 5, pp. 491-510

In recent years, process mining has emerged as the leading big data technology for business process analysis. By extracting knowledge from event logs in information systems, process mining provides unprecedented transparency of business processes while being independent of the source system....

Persistent link: https://www.econbiz.de/10014502095

Prospects of artificial intelligence and machine learning application in banking risk management

Milojević, Nenad; Redzepagic, Srdjan - In: Journal of Central Banking Theory and Practice 10 (2021) 3, pp. 41-57

measured and well-prepared further application of artificial intelligence, machine learning, deep learning and big data … analytics can have further positive impact, especially on the following risk management areas: credit, market, liquidity …

Persistent link: https://www.econbiz.de/10014558436

Determinants factors of intention to adopt big data analytics in Malaysian public agencies

In: Journal of Industrial Engineering and Management (JIEM) 14 (2021) 2, pp. 269-293

Purpose: This research objective was to analyze factors affecting IT practitioners' behavioral intentions in adopting (BDA) using a combination of Initial Trust Model (ITM), Unified Theory Of Acceptance And Use Of Technology (UTAUT) AND Task-Technology Fit (TTF) Model acceptance models....

Persistent link: https://www.econbiz.de/10013326236

Financial statistics and data analytics

Liu, Shuangzhe (contributor); Sathye, Milind (contributor) - 2021

Modern financial management is largely about risk management, which is increasingly data-driven. The problem is how to extract information from the data overload. It is here that advanced statistical and machine learning techniques can help. Accordingly, finance, statistics, and data analytics...

Persistent link: https://www.econbiz.de/10012606038