{"title":"Managing risk concerns with ordered backlogs in the semiconductor industry: An empirical study","authors":"Ashutosh Singh , Surajit Bag , Tsan-Ming Choi , Surender Munjal","doi":"10.1016/j.ijpe.2024.109326","DOIUrl":null,"url":null,"abstract":"<div><p>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.</p></div>","PeriodicalId":14287,"journal":{"name":"International Journal of Production Economics","volume":null,"pages":null},"PeriodicalIF":9.8000,"publicationDate":"2024-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Production Economics","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S092552732400183X","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, INDUSTRIAL","Score":null,"Total":0}
引用次数: 0
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.
期刊介绍:
The International Journal of Production Economics focuses on the interface between engineering and management. It covers all aspects of manufacturing and process industries, as well as production in general. The journal is interdisciplinary, considering activities throughout the product life cycle and material flow cycle. It aims to disseminate knowledge for improving industrial practice and strengthening the theoretical base for decision making. The journal serves as a forum for exchanging ideas and presenting new developments in theory and application, combining academic standards with practical value for industrial applications.