Centralization of a Company’s Cash Management and Leadership Using Digital Techniques

Dolle, Nicolas; Hösle, Thomas; Kuzmina-Merlino, Irina

doi:10.1007/978-3-030-96196-1_42

Cited by 1 publication

(1 citation statement)

References 15 publications

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“…This term is closely linked to the adoption of a BPMN (business process model and notation) tool in making business processes more transparent through the effective exploitation and use of technological resources [46,67,68]. Additionally, BPMN is very useful in graphically representing gaps in information flows and serves as a foundation for automating business processes, designing flexible and adaptive processes, and enhancing dynamic and intelligent capabilities for systems [69][70][71][72].…”

Section: Analysis Of Future Prospectsmentioning

confidence: 99%

A Quantitative Review of the Research on Business Process Management in Digital Transformation: A Bibliometric Approach

Truong,

Nguyen-Duc,

Van

2023

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In recent years, research on digital transformation (DT) and business process management (BPM) has gained significant attention in the field of business and management. This paper aims to conduct a comprehensive bibliometric analysis of global research on DT and BPM from 2007 to 2022. A total of 326 papers were selected from Web of Science and Scopus for analysis. Using bibliometric methods, we evaluated the current state and future research trends of DT and BPM. Our analysis reveals that the number of publications on DT and BPM has grown significantly over time, with the Business Process Management Journal being the most active. The countries that have contributed the most to this field are Germany (with four universities in the top 10) and the USA. The Business Process Management Journal is the most active in publishing research on digital transformation and business process management. The analysis showed that “artificial intelligence” is a technology that has been studied extensively and is increasingly asserted to influence companies’ business processes. Additionally, the study provides valuable insights from the co-citation network analysis. Based on our findings, we provide recommendations for future research directions on DT and BPM. This study contributes to a better understanding of the current state of research on DT and BPM and provides insights for future research.

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