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Do SG&A expenses predict future profitability? : an industry-specific analysis of intangible investments

Sarlak, Nahid (2024-12-11)

 
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Sarlak, Nahid
N. Sarlak
11.12.2024
© 2024, Nahid Sarlak. Tämä Kohde on tekijänoikeuden ja/tai lähioikeuksien suojaama. Voit käyttää Kohdetta käyttöösi sovellettavan tekijänoikeutta ja lähioikeuksia koskevan lainsäädännön sallimilla tavoilla. Muunlaista käyttöä varten tarvitset oikeudenhaltijoiden luvan.
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:oulu-202412117178
Tiivistelmä
In today's global economy, intangible investments are seen as essential assets for a firm's long-term success. Thus, this study investigates whether current intangible investments, proxied by Selling, General, and Administrative expenses at the current year (SG&Ait), influence future profitability or Return on Assets at one year ahead (ROAit+1) across different industries. It also examines how industry-specific factors affect the relationship between SG&Ait and ROAit+1. Utilizing a dataset of approximately 2,000 publicly listed European firms over five years (2018-2022), we employed Ordinary Least Squares (OLS) and Robust Regression (RR) models to assess the predictive power of SG&Ait on ROAit+1. The models controlled for current profitability (ROAit), firm size (logATit), sales growth (SalesGrit), debt ratio (Debt Ratioit), and liquidity (Current Ratioit) to isolate the effect of SG&Ait.

The analysis revealed that SG&Ait does not universally predict ROAit+1 across all industries. However, RR models uncovered both positive and negative significant associations in specific sectors and combined industries. In industries such as Information Technology and Materials as well as combined industries, SG&Ait had a positive and significant impact on ROAit+1, suggesting that strategic investments in marketing, innovation, and administrative functions enhance future profitability. Conversely, in the Consumer Staples sector, a significant negative relationship was observed, indicating that higher SG&Ait expenditures may lead to inefficiencies or diminishing returns. These findings highlight the contingent nature of SG&Ait's effectiveness, heavily influenced by industry-specific operational dynamics and competitive environments.

Consistently, ROAit emerged as a strong predictor of future profitability across both OLS and RR models, underscoring the persistence of financial performance over time. Additionally, logATit positively influenced ROAit+1 in several industries, suggesting that larger firms benefit from economies of scale and greater resource availability. Conversely, higher SalesGrit and Current Ratioit were often associated with lower future profitability, indicating potential operational inefficiencies and underutilization of assets. Debt Ratioit showed a positive relationship with ROAit+1 in the combined data but exhibited varying effects across individual industries, reflecting the contingent benefits of leverage based on sector-specific characteristics.

The findings suggest that the impact of SG&Ait on ROAit+1 is highly dependent on industry-specific factors and that robust regression techniques are crucial for uncovering significant relationships obscured by outliers. Firms should consider their industry context when making strategic decisions about SG&Ait expenditures. In industries where SG&Ait positively affects ROAit+1, investments in marketing, innovation, and administrative efficiency can yield significant returns. Conversely, in sectors like Consumer Staples, firms should critically evaluate and optimize their SG&Ait spending to prevent inefficiencies and align investments with strategic growth objectives.

This study contributes to the understanding of how intangible investments impact future profitability across different industries. By highlighting the varying effects of SG&Ait expenses and the importance of employing robust analytical techniques, it offers valuable insights for managers and policymakers in strategic planning and resource allocation.
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