The impact of R&D classification shifting in high-technology industries

Nika Qiao

Asian Review of Accounting, 2024, vol. 33, issue 1, 107-131

Abstract: Purpose - This study investigates the motivations and consequences of classification shifting from cost of sales to research and development (R&D) in high-technology industries. Design/methodology/approach - This study conducts a multivariate analysis using logistic and ordinary least squares regression methods on panel data of high-technology firms for the period 1988–2012 to examine the effect of R&D classification shifting on gross margin benchmarks and future performance. Findings - The results show that R&D classification shifting increases the likelihood of meeting or beating gross margin benchmarks. They also show that firms engaged in R&D classification shifting exhibit lower future R&D productivity, stock returns, and operating performance. The findings indicate that the short-term benefits of achieving gross margin benchmarks are offset by the long-term negative impact of R&D misclassification. Practical implications - This paper provides insights that can help regulators develop clearer guidelines for the appropriate classification of R&D costs. Originality/value - Moving beyond the core earnings management paradigm, this study demonstrates the use of R&D classification shifting as a tool to manipulate gross profits and R&D in high-technology industries. Most prior studies focused on the determinants of R&D classification shifting, while few investigated the impact of the practice. The findings in this study provide initial evidence of the consequences of R&D classification shifting for future R&D productivity and firm performance in high-tech industries. Using five methods, this study also validates R&D classification shifting and addresses the alternative explanation of R&D overinvestment.

Keywords: R&D; R&D classification shifting; High-technology industries (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eme:arapps:ara-11-2023-0326

DOI: 10.1108/ARA-11-2023-0326

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