An empirical study on digitalization's impact on operational efficiency and the moderating role of multiple uncertainties

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
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: Publisher Copyright: IEEE
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: 15 Jul 2024 08:33
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: 2024-06-01
Authors: LIU, Linlin
LEE, Peter K.C. (ORCID Profile 0000-0001-5100-0316)
YEUNG, Andy C.L.
CHENG, T.C.E.
WANG, Tienan

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