LIU, Linlin, LEE, Peter K.C., YEUNG, Andy C.L., CHENG, T.C.E. and WANG, Tienan (2024). An empirical study on digitalization's impact on operational efficiency and the moderating role of multiple uncertainties. IEEE Transactions on Engineering Management, 71 , pp. 11463-11478.
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.
Publication DOI: | https://doi.org/10.1109/tem.2024.3414831 |
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Divisions: | College of Business and Social Sciences > Aston Business School > Operations & Information Management College of Business and Social Sciences College of Business and Social Sciences > Aston Business School |
Additional Information: | Copyright © 2024 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. |
Uncontrolled Keywords: | Investment,NLP,Natural language processing,Productivity,Social networking (online),Surveys,Technological innovation,Uncertainty,digitalization,operational efficiency,uncertainty,Electrical and Electronic Engineering,Strategy and Management |
Publication ISSN: | 0018-9391 |
Last Modified: | 18 Nov 2024 18:04 |
Date Deposited: | 08 Jul 2024 09:24 |
Full Text Link: | |
Related URLs: |
https://ieeexpl ... cument/10557667
(Publisher URL) http://www.scop ... tnerID=8YFLogxK (Scopus URL) |
PURE Output Type: | Article |
Published Date: | 2024-06-14 |
Published Online Date: | 2024-06-14 |
Accepted Date: | 2024-06-02 |
Authors: |
LIU, Linlin
LEE, Peter K.C. ( 0000-0001-5100-0316) YEUNG, Andy C.L. CHENG, T.C.E. WANG, Tienan |