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http://hdl.handle.net/10397/107510
Title: | An empirical study on digitalization's impact on operational efficiency and the moderating role of multiple uncertainties | Authors: | Liu, L Lee, PKC Yeung, ACL Cheng, T Wang, T |
Issue Date: | 2024 | Source: | IEEE transactions on engineering management, Date of Publication: 14 June 2024, Early Access, https://doi.org/10.1109/TEM.2024.3414831 | Abstract: | While many organizations are increasingly willing to invest in adopting digitalization in recent years, they might not be aware that different levels of uncertainty within and outside their organizations may impend digitalization's effectiveness. This study aims to empirically explores the performance impact from digitalization on organizations and the effect from uncertainty on the impact. More specifically, the objectives are pertinent to examining 1) the association between digitalization and operational efficiency and 2) the moderating effect of macro-level uncertainty, industrial-level uncertainty, and firm-level uncertainty on this association. Using a dataset collected from multiple sources employing innovative methodologies including natural language processing (NLP) to analyze digitalization announcements from Factiva and measuring operational efficiency based on the stochastic frontier approach (SFA), this study analyzes the impact from digitalization via 2,520 samples from 496 listed firms in North America during 2015-2021. The results show that digitalization significantly enhances operational efficiency, and this positive impact from digitalization is weakened by macro-level uncertainty and industrial-level uncertainty. Our findings provide researchers and practitioners with useful insights into digitalization's important role in enhancing operational efficiency and guidance indicating the business environments deserve extra attention so as to retain digitalization's positive impact. | Keywords: | Digitalization NLP Operational efficiency Uncertainty |
Publisher: | Institute of Electrical and Electronics Engineers | Journal: | IEEE transactions on engineering management | ISSN: | 0018-9391 | EISSN: | 1558-0040 | DOI: | 10.1109/TEM.2024.3414831 |
Appears in Collections: | Journal/Magazine Article |
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