The impact of intangible assets on firm value. Some empirical evidence from the European-listed firms in the tourism industry

In recent decades, intangible assets (IAs) have become one of the most important resources for enhancing innovation and creating competitive advantages, by positively influencing firms' organizational and financial performance (Ivanov & Mayorova, 2015; Khan, Yang, & Waheed, 2018; Ocak & Findik, 2019; Piekkola, 2020; Silva & Oliveira, 2020). Prior papers have provided empirical evidence that IAs have a positive effect on firm sustainability and market value (Kamasak, 2017; Mendoza, 2017; Hintzmann, Lladós-Masllorens, & Ramos, 2021; Xu & Liu, 2021).

According to IAS 38, IAs are non-physical resources that generate future financial gains and long-term competitive advantages. Examples of these include goodwill, human capital, brand reputation and intellectual property. Theoretical frameworks highlight the strategic role of IA. Endogenous growth theory (Romer, 1990) connects knowledge-based investments to long-term performance, while the resource-based view (Barney, 1991) emphasizes their potential to generate sustainable competitive advantages.

The growing importance of IA is well-documented. Aon (2019) reported that for the top five S&P 500 firms, the market value of IA rose from $0.122 trillion in 1975 to $21 trillion in 2018, while tangible assets declined proportionally. Similarly, Ocean Tomo (2020) found that IA represented just 17% of total market value in 1975, compared to 90% in 2020. These shifts highlight the increasing weight of intangible resources in firm valuation (Mozolea & Anton, 2021).

The tourism industry is a major contributor to Europe's economy, accounting for around 10% of gross domestic product and employing 12.6 million people as of 2019 (Eurostat, 2022; Pernice, 2022). As the world's leading tourist destination, Europe offers a tourism product that combines tangible and intangible elements to shape the overall visitor experience (Evans, 2009; UNWTO, 2022). In this context, IA, such as branding, innovation, intellectual capital and digital presence, are key determinants of value creation (Vodeb, 2012). Despite the strategic importance, research on the relationship between IA and firm valuation in the tourism industry remains fragmented and limited. While some studies have analyzed intellectual capital, knowledge management and advertising (Engström, Westnes, & Furdal Westnes, 2003; Sigala & Chalkiti, 2007; Zigan & Zeglat, 2010; Qi, Cárdenas, Mou, & Hudson, 2018; Omoush, 2019), their research is often country-specific and focused on particular intangibles rather than a comprehensive assessment. Moreover, most prior studies have employed linear modeling frameworks, usually ordinary least squares (OLS), which assumes a homogeneous effect of IA on firm value (Kamasak, 2017; Ocak & Findik, 2019). Applying this methodology carries the risk of overlooking the heterogeneous impacts of intangibles across firms that differ significantly in size, business models and intangible intensity, particularly relevant in a highly competitive, experience-driven industry such as tourism.

This study addresses literature gaps by providing cross-country evidence on how firm value is impacted by IA across 242 publicly listed European companies over a 15-year period (2007–2021). We employ panel quantile regression (QR), which is particularly suited to capturing non-linear and heterogeneous effects across the distribution of firm value (Coad & Rao, 2008). Firm fixed effects are included to account for unobserved heterogeneity across firms, following standard panel data methods (Wooldridge, 2010). To validate the robustness of the analysis, several additional tests were conducted. The model was re-estimated using an alternative proxy for firm size and on a sub-sample restricted to hospitality firms. Finally, to address potential endogeneity, a smoothed instrumental variable quantile regression (IV-QR) with lagged covariates was applied, in line with Chernozhukov and Hansen (2006). The findings remain robust across these checks, reinforcing the evidence of heterogeneous and non-linear effects of IA and the distinctive role of goodwill. The results indicate that IA have a consistently positive influence on firm value, although the strength of this effect differs across quantiles. Firms with greater intangible intensity are associated with higher market valuations, but the magnitude of the impact is not uniform. Goodwill is significant only for firms in the lowest and highest quantiles (Q10 & Q90), highlighting its role in supporting investors' confidence, but also in capturing the value of competitive advantages not visible in traditional financial metrics.

This study contributes to the literature by examining the role of IA in shaping firm value among listed tourism companies across Europe, while accounting for firm-level and macroeconomic controls. Unlike earlier studies that focus on single countries or average effects, our cross-country approach, combined with QR, uncovers important differences in how IAs influence firms across the value spectrum. By doing so, the study challenges assumptions of uniformity and provides a more layered understanding of how strategic investments in intangibles, such as brand equity and goodwill, can create value in a highly experience-driven industry.

The paper is structured as follows. Section 2 reviews the literature on IA and firm value in the tourism industry. Section 3 outlines the data and methodology. Section 4 presents empirical findings and robustness checks, while the final section discusses key conclusions, limitations and directions for future research.

The growing importance of IA is grounded in strong theoretical frameworks. Endogenous growth theory (Romer, 1990) emphasizes that investments such as R&D, innovation and brand development support sustainable growth, while the resource-based view (Barney, 1991) argues that resources that are valuable, rare and difficult to imitate, such as intellectual capital, advertising and goodwill, provide firms with sustainable competitive advantages. These theoretical foundations have inspired extensive empirical work showing that IA significantly impact firm valuation and performance across industries and regions (Jennings, Robinson, Thompson, & Duvall, 1996; Kamasak, 2017; Mendoza, 2017; d,’Arcy & Tarca, 2018; Xu & Liu, 2021).

In modern economies, IA are often prioritized over traditional ones such as land and labor (Tsai, Lu, & Yen, 2012; Kim & Han, 2000). Firms with high intangible intensity tend to outperform competitors, particularly as the association between revenues and stock prices has weakened (Brown, Lo, & Lys, 1999; Xu & Liu, 2021). Gupta, Golec, and Giaccotto (2018) and Sahut, Boulerne, and Teulon (2011) argue that intangibles explain stock prices better than tangibles, while Seo and Kim (2020) show that R&D, human capital and advertising support small and medium enterprises' growth. At the financial policy level, Falato, Kadyrzhanova, Sim, and Steri (2022) find that higher intangible investment increases corporate cash holdings in US firms, emphasizing the role of intellectual property.

During a crisis, intangibles also play a critical role in firm resilience. In Italy and Turkey, they supported survival and growth despite financial risks (Landini, Arrighetti, & Lasagni, 2018; Ocak & Fındık, 2019), while relationship-building and innovation strengthened international competitiveness (Shih & Yang, 2019). COVID-19 exposed their vulnerability, as European firms faced depreciation and impairment adjustments (Quinn, 2020; Hintzmann et al., 2021). However, reputation and brand power were proven critical for tourism firms in the United Arab Emirates and Thailand (Aburumman, 2020; Intara & Suwansin, 2024). Overall, tourism remains highly exposed to crisis, with recovery often delayed (Uğur & Akbıyık, 2020).

Country-specific studies confirm the positive role of intangibles, though effects vary with geography and institutions. Dancaková, Sopko, Glova, and Andrejovská (2022) find that intellectual capital improves Tobin's Q in European firms. In Indonesia, higher intangible intensity supports return on assets (ROA), Tobin's Q and dividends (Nagaraja & Vinay, 2017), while in Japan, R&D boosts Tobin's Q, but advertising effects depend on context (Andersson & Saiz, 2018). In Latin America, intangibles strongly affect ROA but show less consistent market-based outcomes (Lopes & Carvalho, 2021).

Tourism, which integrates hospitality, transportation, intermediaries, attractions and entertainment (Camilleri, 2018), depends heavily on service quality, brand reputation, customer loyalty and corporate social responsibility (CSR). Yet evidence remains fragmented (Bontis, Janošević, & Dženopoljac, 2015; Jerman & Janković, 2018). Studies highlight that intellectual capital and knowledge management drive innovation in Jordanian agencies (Omoush, 2019), improve short- and long-term performance in Singapore (Pew Tan, Plowman, & Hancock, 2008), and enhance competitiveness in Latin America (Camfield, Giacomello, & Sellitto, 2018; Acuña-Opazo & González, 2021). In Europe and the US, FitzPatrick, Davey, Muller, and Davey (2013) show that intellectual capital and branding strengthen competitiveness, while Rudež and Mihalič (2007) identify customer relationship capital as the only direct driver of financial performance in Slovenian hotels, with other forms acting indirectly. Natsir and Bangun (2021) also confirm its positive effect on Tobin's Q in tourism firms.

Recent research reinforces these findings. Attia et al. (2023) show that brand reputation is central to firm value, in line with Dzhandzhugazova, Blinova, Orlova, and Romanova (2017). Innovation and brand loyalty improve liquidity and reduce uncertainty (Rather, Tehseen, & Parrey, 2018; Nemlioglu and Mallick, 2020), while Wang (2015) demonstrates that corporate governance amplifies the role of intellectual capital in Taiwanese tourism firms. Advertising also emerges as a key intangible, improving loyalty, brand value and performance (Joshi & Hanssens, 2010; Assaf, Josiassen, Mattila, & Knežević Cvelbar, 2015; Qi et al., 2018; Liu, Hultman, Eisingerich, & Wei, 2020). In India, disclosure of intangibles has been shown to strengthen hotel valuations, with software most frequently reported (Kulkarni & Malhotra, 2015).

Goodwill stands out as a specific intangible with long-term implications. Park and Jang (2012, 2021) show that goodwill positively impacts firm valuation in restaurants and franchises. Pauna and Filip (2015) discuss the challenges of measuring service-related intangibles in hospitality, while Belkaoui (1992) distinguishes between identifiable intangibles (e.g. patents) and unidentifiable intangibles (e.g. goodwill). More recent studies find goodwill to be a strong predictor of long-term outcomes: Pechlivanidis, Ginoglou, and Barmpoutis (2022) show that goodwill improves profitability forecasts and Heiens, Leach, Newsom, and McGrath (2016) conclude that goodwill outperforms other intangibles in sustaining long-term financial returns.

Most existing studies continue to use linear econometric models, such as OLS or static panel regressions (Kamasak, 2017; Ocak & Fındık, 2019). Some studies turn to structural equation modeling (SEM) and its variant partial least squares structural equation modeling (PLS-SEM) to capture the indirect effects of intangibles. These models show that the impact of resources such as intellectual capital or CSR often operates through mediating and moderating mechanisms rather than simple direct links (Rubio-Andrés, del Mar Ramos-González, & Sastre-Castillo, 2022). Others rely on Necessary Condition Analysis, which highlights that certain intangible resources are essential for achieving high performance, even if they are not sufficient on their own (Dul, 2016). While these methods provide valuable insights, they rely on strong theoretical assumptions. By contrast, our use of QR directly models heterogeneity in firm value without imposing predefined interaction structures, making it particularly well suited for a sector as diverse and competitive as tourism.

Overall, existing literature reveals three key gaps. First, research on tourism firms is still fragmented, with little comprehensive cross-country evidence. Second, the non-linear and heterogeneous effects of intangibles on firm value are rarely explored. Third, the specific role of goodwill remains underdeveloped, despite growing indications of its importance. This study addresses these gaps by analyzing the impact of IA on firm value in publicly listed European tourism companies using panel QR. By focusing on heterogeneity across the value distribution, it provides new insights into the differentiated contribution of goodwill. Based on the reviewed literature, the following hypotheses are proposed:

Our final sample consists of 242 listed firms from 22 European countries ^[1] over the period 2007–2021 and 1,571 firm-year observations ^[2]. Financial information was obtained from the Osiris database (Bureau Van Dijk), a widely used source for standardized financial and market data in academic research, including studies employing Tobin's Q. The unbalanced panel data sample uses firms belonging to the tourism industry according to Statistical Classification of Economic Activities in the European Community (NACE) Rev. 2 ^[3]. Unconsolidated financial statements are used in the models following the current state of the existing research (Anton, 2021).

In line with previous research (Wang, 2015; Alathamneh, Obeidat, Almomani, Almomani, & Darkal, 2025; Kolawole, Alabi, & Awotomilusi, 2025), we selected Tobin's Q indicator as the dependent variable. It is particularly suitable for tourism firms because market valuations incorporate expectations about brand strength, service quality and other intangibles that accounting measures don't fully capture. Following prior studies (Megna & Klock, 1993; Appelbaum, Calla, Desautels, & Hasan, 2017), the key explanatory variables are the ratios of IAs and goodwill to total assets. PIA refers to the total IAs figure, which includes goodwill; it is also extracted and analyzed separately to capture its specific economic role within the broader category of intangibles. Control variables include firm size (log of total assets), liquidity (current ratio), sustainable growth rate, Altman Z-score (bankruptcy risk), leverage, profitability (ROA) and two crisis dummies to account for the global financial crisis (2008–2009) and the COVID-19 pandemic (2020–2021), which had a strong impact on the tourism sector and may otherwise distort the relationship between intangibles and firm value. Table 1 summarizes all variable definitions.

where: TobinsQ_i,t is the market value of firm i at time t; PIA_i,t represents the ratio of IA to the total assets for firm i over year t; FIRM_i,t refers to firm-specific variables, such as firm size, current ratio, sustainable growth rate, Altman Z-score, leverage and ROA; GFC is a dummy variable for the global financial crisis that takes the value 1 for the years 2008 and 2009, and 0 for the others; CoC is a dummy variable for the COVID-19 pandemic that takes the value 1 for the years 2020 and 2021, and 0 for the others; β₁, …, β_n represent the coefficients of the variables; ɛ_i,t represents the error term.

In our empirical investigation, we employed QR, which offers more details regarding the link between IA and firm value. Additionally, this econometric technique can overcome some statistical issues such as outliers and non-Gaussian error distribution (Coad & Rao, 2008). Given these advantages, several studies (Ku & Yen, 2016; Conyon & He, 2017) have recently used the QR technique in their publications on corporate finance.

Koenker and Bassett (1978) elaborated the QR approach with the following equation:

where y_i,t stands for firm value, x_i,t represents regressors, βθ is the vector coefficient estimates for each quantile, uθ_i,t is the error, i indexes firm (in our case, i = 1,..., 242) and t indexes time (in our case, t = 1,..., 15).

Table 2 presents the descriptive statistics for the variables used in the analysis. To reduce the impact of outliers, variables were winsorized at the 1^st and 99^th percentiles. Tobin's Q has a median of 0.51 and a mean of 0.92, indicating a right-skewed distribution. This supports the choice of QR, which is better suited to capture such heterogeneity.

Table 3 shows a positive correlation between IA and firm value, while the low correlation coefficients suggest that multicollinearity is not a concern.

Furthermore, the variance inflation factor (VIF) values were computed and presented in Table 4 to examine any potential collinearity between explanatory variables. Given that none of the VIF values is above the limit of 10.00 (Hair, Black, Babin, & Anderson, 2010), we believe that multicollinearity may be ruled out.

Table 5 reports the QR results (columns 2–6) alongside OLS estimates (column 1), used only as a benchmark (Anton, 2021). Unlike QR, OLS focuses on the mean and therefore masks differences across Tobin's Q quantiles. Although OLS shows a positive link between intangibles and firm value (0.7253), this result is misleading, as it hides distributional variation.

The results show that the influence of IA on firm value is not uniform across the distribution (see also Figure 1 for a graphical representation). The positive effect persists throughout, but the magnitude increases at higher quantiles, indicating that firms with higher market valuations benefit more from intangible investments. These findings validate the first hypothesis and confirm a consistent positive link between IA and firm value, showing that allocating more resources to IA can create greater value for shareholders.

This evidence supports earlier studies highlighting the strategic importance of intangibles (Mendoza, 2017; Gupta et al., 2018; Xu & Liu, 2021), but it also nuances the debate by showing that their impact is not constant across all firms. Unlike prior research relying on OLS estimations (Kamasak, 2017; Ocak & Findik, 2019), which assume a homogeneous effect, our quantile approach captures this variation more accurately.

Regarding the control variables, firm size has a negative effect on firm value at higher quantiles (Q50, Q75, and Q90), possibly reflecting challenges such as operational complexity or market saturation. Liquidity (current ratio) is positively associated with firm value across most quantiles, while leverage generally has a negative impact, highlighting the valuation risk of high indebtedness. Profitability (ROA) has a consistently positive and significant effect, in line with prior studies (Alghifari, Triharjono, & Juhaeni, 2013; Farčnik, Kuščer, & Trobec, 2015). The global financial crisis dummy is not statistically significant in any quantile, whereas the COVID-19 dummy is positive and significant throughout, suggesting that market valuations reacted more strongly to the pandemic than to the previous crisis.

The second part of the analysis examines the link between goodwill and firm value using the full sample (2007–2021). Table 6 shows that goodwill has a positive and statistically significant effect only in the lower (Q10) and higher quantiles (Q90), confirming the second hypothesis.

For lower-valued firms, goodwill signals credibility and boosts investor confidence in future earnings. Whereas previous studies (Seo & Kim, 2020; Falato et al., 2022) indicated the wider applicability of goodwill, we find that the importance of goodwill is particularly relevant for firms with lower market capitalizations. For these firms, goodwill can act as a compensating mechanism, giving confidence to stakeholders regarding the firm's long-term existence and brand power, reducing information asymmetry for investors when other observable indicators are weaker.

In contrast, the effect disappears at higher quantiles, where firms already have established market positions and stronger financial performance. However, at the top of the distribution, goodwill also has a positive impact. Highly valued firms often have substantial brand portfolios and rely on growth strategies that involve acquisitions, where goodwill complements traditional metrics by reflecting accumulated value and the intensity of their competitive advantages.

To test the robustness of our key findings, we conducted three additional sets of analyses.

First, we re-estimated the model using a sub-sample of firms operating strictly within the hospitality sector. The tourism industry is broad, consisting of travel agencies, transport services, sports activities and attractions; therefore, isolating the hospitality sector (hotels and restaurants) allows a focused examination of whether the main results persist in a more homogeneous sub-industry.

The findings in Table 7 support our main conclusions: IA continue to exhibit a positive relationship with firm value, particularly for firms located in the lower quantiles of the firm value distribution (Q10 and Q25). This suggests that while IA remain important drivers of firm value in hospitality firms, other factors may have relatively greater weight in this sub-sector.

These results further reinforce the outcome that the influence of IA is non-uniform and context-specific, even within the broader tourism industry. Therefore, firms operating in environments that are more reliant on tangible services, such as hospitality, may gain advantages from adopting a balanced investment approach that combines both intangible and tangible assets.

Second, motivated by prior research (Dang, Li, & Yang, 2017), which emphasizes that firm size represents a major source of heterogeneity in firm performance, we reran the baseline model using the natural logarithm of sales (SIZE 1) instead of total assets as an alternative proxy for firm size. The results of this additional robustness check are presented in Table 8.

The positive association between IA and firm value remains robust when firm size is proxied by sales rather than total assets. The coefficients on the IAs ratio (PIA) maintain their positive signs and statistical significance across quantiles. This finding is significant because it reduces the possibility that the relationships that have been observed are the result of the particular size measure that was used. It demonstrates that whether firm size is measured using output-related metrics (sales) or balance-sheet variables (total assets), the strategic contribution of IA to firm value remains constant.

In order to address potential endogeneity (e.g. reverse causality or omitted variable bias), a smoothed IV-QR with lagged covariates has been employed ^[4]. This econometric approach has the advantage of increasing the statistical accuracy of computation, yielding more stable and reliable estimations (Kaplan, 2022). The results are presented in Table 9. The IV-QR results indicate that the impact of IA on firm value varies across the distribution. The positive relationship is observed at higher quantiles (Q50-Q90), suggesting that firms with superior market valuations derive greater benefits from intangible investments.

The results of this study provide new insights into how IA impact firm value in the European tourism sector. By applying panel QR with fixed effects to a panel of 242 listed firms from 22 countries over the period 2007–2021, the analysis captures heterogeneous and non-linear effects that are not visible through ordinary least squares regressions, which focus only on mean relationships. Data were drawn from the Osiris database, with Tobin's Q as the dependent variable. The main explanatory variables are the ratios of IA and goodwill to total assets, while controls include firm size, liquidity, sustainable growth, Altman Z-score, leverage, profitability and two dummy variables for global financial crisis and COVID-19 pandemic.

Findings show that IA positively impact firm value, though the strength of this relationship varies across the value distribution. The positive effect becomes more pronounced at higher quantiles of Tobin's Q, indicating that firms with stronger market positions benefit more from intangible investments. This evidence highlights the heterogeneous and non-linear contribution of intangibles and confirms that average-based models underestimate their complexity.

The analysis also identifies a distinctive role for goodwill. Unlike the broader set of intangibles, goodwill has a statistically significant effect among firms in the lowest and highest quantiles of Tobin's Q (Q10 & Q90), as it compensates for weaker resources and signals sustainability, while at the top of the distribution, it captures the accumulated value of reputation and strategic acquisitions. For firms in the middle of distribution, market participants appear to assign greater weight to operational efficiency and profitability, reducing the relative importance of goodwill. This differentiated pattern adds a new dimension to the literature on tourism, where goodwill is often mentioned but rarely analyzed.

Robustness checks support the reliability of these findings. A subsample analysis limited to hospitality firms (hotels and restaurants) confirmed the positive role of IA, though with somewhat smaller coefficients, suggesting variability across subsectors. Using an alternative proxy for firm size, measured by sales instead of total assets, produced consistent results. Finally, a smoothed IV-QR with lagged covariates was employed to address potential endogeneity. The IV-QR estimations confirmed the baseline findings, showing that the positive effect of IA remains significant for firms in higher quantiles.

These results have several implications. For management, they highlight the strategic value of intangibles in creating sustainable competitive advantages. Investments in intellectual capital, brand reputation, and goodwill can strengthen resilience and long-term growth, particularly for smaller firms where tangible resources are weaker.

For investors, the evidence shows that intangibles are not equally priced across firms: while high-value firms capture the largest returns from intangible intensity, goodwill provides valuable signals for assessing lower-valued firms.

At the policy level, encouraging investment in intangibles, improving transparency and reducing related costs could enhance the sector's competitiveness and stability in the face of recurring crises. In addition, policies that enhance the clarity and consistency of goodwill reporting may therefore support better market assessment, especially for lower-valued firms.

Overall, the study contributes to the literature by providing cross-country evidence on the heterogeneous and non-linear effects of IA and by identifying goodwill as a particularly relevant driver for firms in weaker market positions. The results show that tourism companies should treat intangibles not only as accounting entries but as strategic resources that influence both market perception and long-term sustainability.

This study has several limitations, the most important being its focus on aggregating IA and goodwill, without distinguishing the effects of different types of intangibles. Future research could extend this analysis by including other regions/sub-regions, considering additional intangible categories such as R&D and digital capabilities and exploring the moderating role of institutional environments.