Managing Risk Concerns with Ordered Backlogs in the Semiconductor Industry: An Empirical Study

Abstract

Today, the semiconductor industry is integral to the functionality of many critical goods and processes that are highly valued. The increasing demand across various semiconductor-related industries has correspondingly amplified the risks faced by firms within this sector. In this study, we empirically explore the potential of ordered backlogs as a means to mitigate the risks confronting semiconductor firms. Utilizing a dataset comprising publicly traded semiconductor firms in the USA, over a duration from 1998 to 2021, we quantitatively validate our hypotheses. Our findings reveal that a substantial volume of ordered backlogs is indeed correlated to a diminished level of firm risk. However, it is important to note that this risk-mitigating effect is lessened as the marketing and research intensities of these firms escalate. Moreover, we observe that the advantageous impact of ordered backlogs in risk reduction is more subdued in large workforce firms, whereas the presence of a sizable top management team aids in lessening the impact of ordered backlogs on risk. These managerial insights are invaluable in advancing both theoretical understanding and managerial practices within the realm of the semiconductor industry.

Publication DOI: https://doi.org/10.1016/j.ijpe.2024.109326
Divisions: College of Business and Social Sciences > Aston Business School > Economics, Finance & Entrepreneurship
College of Business and Social Sciences
Additional Information: Copyright © 2024 Elsevier B.V. This accepted manuscript version is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License [https://creativecommons.org/licenses/by-nc-nd/4.0/].
Uncontrolled Keywords: Empirical Studies,Firm-related factors,Ordered backlogs,Risk mitigation,Semiconductor firms,Economics and Econometrics,General Business,Management and Accounting,Industrial and Manufacturing Engineering,Management Science and Operations Research
Publication ISSN: 0925-5273
Last Modified: 11 Nov 2024 09:06
Date Deposited: 14 Aug 2024 10:53
Full Text Link:
Related URLs: https://www.sci ... 92552732400183X (Publisher URL)
http://www.scop ... tnerID=8YFLogxK (Scopus URL)
PURE Output Type: Article
Published Date: 2024-09
Published Online Date: 2024-07-02
Accepted Date: 2024-06-29
Authors: Singh, Ashutosh
Bag, Surajit
Choi, Tsan-Ming
Munjal, Surender (ORCID Profile 0000-0002-8713-687X)

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Version: Accepted Version

Access Restriction: Restricted to Repository staff only until 2 January 2026.

License: Creative Commons Attribution Non-commercial No Derivatives


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