Investigating the potential domino effect of a dazzling fiscal-period on CSR performance: a luxury brand scenario

Abstract

A consensus and buying pattern regarding luxury brands has endured a paradigm shift from being envied to being questioned or entirely overlooked. The pandemic has led to a fair share of economic implications. Brands are forced to watch their product range fully, except for reserving a portion of merchandise optimistic for brand jingoism. The study aims to quantify the impacts of financial metrics utilized to gain goodwill amidst an average consumer’s mindset. A composite Corporate Social Responsibility (CSR) score represents the extent of a luxury brand’s efforts in contributing to social and environmental concerns. The CSR score is hypothesized against these brands’ financial and brand-value metrics. A Few Research questions are proposed on the same. A Panel-level analysis is undertaken to quantify the dependence and obtain insights. Relevant data is collected, with metrics identified from financial statements. The impacts of financial metrics and the firm’s age on the CSR score are determined. While the Profit Margin, firm size, Tobin’s Q, and Firm Age contribute positively to the CSR score, the firm’s Return on Assets has a surprising negative influence. The impact of net income accrued is negligible, as inferred.

Introduction

Often synonymous with the wealthiest segment of society, luxury brands can captivate even the average shopper. Extravagant advertising and captivating marketing strategies have bolstered their popularity beyond the targeted audience spectrum (Septianto et al., 2020). Cases of a brand’s unscathed and unquestioning obsession are common phenomena, and brands seem to understand this Achilles’ heel quite well. Social media has quite a reputation for aggravating such magnetic loyalty and a constant increase of brand-conscious berserkers (Zhang, 2022). This section of consumers usually looks forward to luxury brands with motives to raise their affluence in society and the pride one exhibits in possession.

Trends, however, indicate a considerable shift in purchasing intentions, with impending job losses and curtailment of the regular flowing income (D’Arpizio et al., 2020). Luxury brands have come under the radar for being indifferent to ethical practices and are reportedly caught up in the storm of unjustified hate (Guzzetti et al., 2023). A calculated revamp of marketing and branding approaches specific to the period could restore the brand’s image (Loranger & Roeraas, 2023). Endeavors like Fendi’s contribution to the restoration of the iconic Roman Trevi fountain (Hagan, 2021) have catered to the emotions of the common folk, and there is no denying the potential for such legacy events to continue as practical means of solidifying brands’ legacies in the minds of everyday consumers.

Across the larger picture, consistently maintaining this level of goodwill is imperative. Luxury brands tend to note this by involving socially viable practices and responsible actions encompassing the interests and needs of various consumer classes (Demangeot et al., 2019). One such strategy that firms target the most is the acts of Corporate Social Responsibility (CSR). CSR encompasses endeavors aimed at enhancing a company’s environmental and social standing. This concept has evolved into a broader societal framework, effectively encapsulating the essence of the entire study (Aslaksen et al., 2021). With environmental concerns surmounting day by day (Bick et al., 2018) and an increasing number of lawsuits accusing corporate firms of causing irreplaceable damage to the ecosystem (Butterworth, 2014), CSR strategies come as a valuable respite to cement a firm’s reputation (Boadi et al., 2019). This has motivated us to study the relevance of a CSR score from a Luxury Brand perspective and its association with the financial and brand value metrics.

Luxury brands have become our particular area of interest, especially given the current times that have led to skewed perceptions about these brands. Entities catering to the ultra-rich, such as Oceangate, have faced criticism for their extravagant nihilistic ambitions that extend beyond the mindset of the average consumer. Brands have equally responded with unconventional tactics, exemplified by Coach’s pop-up cafe shophouse in Singapore. This move showcases a commitment to inclusiveness beyond mere affordability; it is a deliberate choice to promote bespoke ness within everyday settings. As brands continue to accomplish noteworthy feats that capture public attention and influence policymaking with mere everyday deeds, our curiosity is drawn to this captivating category of brands. It has motivated us to consider luxury brand’s perspective for CSR scores and its association with financial and brand value metrics. Accordingly, the following research questions are proposed in the study.

• RQ1: How do recent financial performance metrics of a luxury brand impact the company’s CSR evaluation score?

• RQ2: Does a luxury brand’s CSR performance still rely on its relevance and heritage as an effective booster?

The study’s objectives are to assess the impact of financial metrics on evaluating a luxury brand company’s CSR score and its association with brand value metrics. A composite Corporate Social Responsibility (CSR) score represents the extent of a luxury brand’s efforts in maintaining a good social impact among the masses. The CSR score is hypothesized against these brands’ financial metrics and brand-value attributes. A Panel-level analysis is undertaken to quantify the dependence and to gain further insights.

“Literature review” section discusses the literature review and highlights the gaps in the literature. “Research methodologies and proposed hypothesis” section describes the research methodology and develops a hypothesis for further analysis. Based on the proposed hypothesis in “Research methodologies and proposed hypothesis” section, the regression models are proposed and discussed in detail in “Proposed regression models” section. Later, the underlying information structure based on the results is presented in “Results and inferences” and “Business and practical implications” sections.

Literature review

Research articles on luxury brands and consequent CSR initiatives are collected and analyzed as a part of the review process, and the same is given in Table 1 for easy reference. The articles discussed here helped us to understand the current trends in luxury brand management and the steps each entity takes to cement its status as a socially responsible entity. Table 1 highlights suitable sources and current research work differences for better understanding. Information from various perspectives helps us present the research in a lively manner, and we pick recent articles catering to the above-put-forward stipulation.

Table 1 Summary of the literature review and relevant findings

Prior research has examined how consumers perceive luxury brands based on inferences on brand activity regarding sustainability and good governance. Brands themselves have found these results on consumer perception to be valuable indicators that later culminate to employ critical action plans regarding CSR and Environment, Social and Governance (ESG). Dekhili & Achabou, 2016 identified potential reasons for brand-ecological perception, which may indicate a reluctance among luxury brands to promote sustainability. Nickerson et al. (2022) conclude that different situations based on which brands engage in corporate social responsibility (CSR) yield contrasting results regarding subsequent sales and post-purchase popularity. A study by Olsanova et al. (2022) quantified how a positive CSR contribution can lead to an improved intention to purchase or experience brands, and they also investigated how demographics and gender mediate this behavior. Another study by Wu et al. (2012) discusses how an increasing number of consumers are expected to be drawn to brands in terms of luxury affordability. Shahid et al. (2023) and Alexandra and Cerchia (2018) examine various aspects of affordable luxury, such as loyalty, awareness, status, and uniqueness, which drive consumer engagement.

Prior research has also addressed the curious case of luxury brand performance after implementing CSR and ESG action plans. Donato et al. (2019) discuss the case of four luxury brands in the food and fashion industries. They explore responsible practices such as adopting a circular economy and redirecting raw material profits into viable CSR initiatives. Research such as Morea et al., 2021, explores whether CSR can be attributed to specific management practices. On the other hand, cases like Olatubosun et al., 2021, identify whether brands are willing to recognize that CSR can lead to potential profits.

While studying the influence and value of luxury brands with their involvement in CSR, it was also necessary to establish a dependence based on other related brand parameters. Prior research compared other essential factors in luxury brand activities, namely economic indicators, to establish a consumer foothold. However, to the best of our knowledge, there needs to be more literature available on the computation of CSR scores that considers financial and brand value metrics from a luxury brand’s perspective. Therefore, this study fills this gap by assessing the impact of financial metrics on evaluating Luxury Brand CSR score and its association with brand value metrics.

It was also necessary to quantify the same over particular circumstances of economic conundrum, namely the COVID-19 pandemic and global recession. In contrast, Panagiotopoulos (2021) analyzed how luxury brands leveraged crises as opportunities for CSR enhancement through strategy-specific communication and workplace transformation. A study conducted by Cvik and Pelikanova (2021) reports that brands are hesitant to move forward with CSR, particularly during the COVID-19 pandemic. Although the cited studies shed light on CSR strategies in luxury brand management and consumer perception, some gaps still need to be addressed.

Specifically, quantifying how a firm’s financial metrics influence its CSR performance in a luxury brand setup has yet to be accurately established. Our study aims to bridge this gap by conducting a panel-level analysis to quantify how each identified financial metric can positively impact CSR behavior. In literature, research has been conducted to understand luxury brand strategies during the pandemic; however, our study addresses a gap by examining the phenomenon of Corporate Social Responsibility (CSR) within the context of economic uncertainty. In our analysis, we also consider the firm’s age as a pertinent attribute to gain additional insights into the impacts of brand relevance. The panel-level analysis allows us to seamlessly examine various parameters’ individual and combined effects while accounting for unforeseen variability that provides valuable insights. We emphasize evaluating the importance of the individual effects of each financial metric before analyzing them using the model. This approach helps us ascertain the relevance of each financial metric in a simplified manner. Moreover, this study assesses the financial and brand value metric performance concerning the CSR scores. Consequently, the research methodology and hypothesis are discussed in the subsequent section for further analysis.

Research methodologies and proposed hypothesis

Despite experiencing individualistic financial setbacks, luxury brands are known to allocate a particular portion of their resources to solidify their influence among the masses (Alshehhi et al., 2018). As conglomerates, many of these brands rely on partnerships with other organizations out of a sense of urgency to promote sustainability and responsibility through joint ventures (Gutsatz & Heine, 2018). The study considers distinct Dimensional and Non-Dimensional metrics related to financial performance and brand value.

Luxury brands have been vocal about their recent financial accounts (Singh & Hameed, 2018), ensuring that the overall financial performance and any incurred upheavals are accurately reflected within these specified reports. These metrics were identified by examining the relevant financial statements of parent firms and analyzing each metric’s capacity to capture the necessary trends and compliance. Non-dimensional metrics, namely the Net Profit Margin (NPM), Return on Assets (ROA), and Tobin’s Q, have significant advantages in communicating effectively with external and internal financial data users (Lawrenz & Zorn, 2018). Selected studies have reported the impact of each of the discussed metrics and their piecewise contributions to the CSR rating (Olthuis & Oever, 2020). The discussed metrics are suitable for analysis since they do not complicate our analysis and adhere to the defined research questions. Additional considerations revolve around the idea that the pandemic has profoundly affected consumers and brands (Kirk & Rifkin, 2020). In short, any engagement in CSR practices is assumed to depend on the brand’s recent financial performance, with the discussed metrics quantifying the above mentioned performance.

Net Profit Margin (NPM)

A brand’s NPM is the profit or net income ratio to its revenue incurred in a consideration period (Bitar et al., 2018). Higher the value, the brand is more likely to endure any chances of economic downfalls and focus on its subsequent revival. The net profit parameter stands determinable in influencing a CSR performance (Ekatah et al., 2011). Increased profitability reflects increased interest within stakeholders and capital sources, of trust and goodwill. With higher profitability incurred, the company must think about long-standing sustenance and garnering crucial goodwill amidst the masses. Therefore, steps towards improving the CSR are often seen as prominent (Gupta & Krishnamurthi, 2021). With these notions, the following hypothesis can be proposed to gain insights.

• H1: The Net Profit Margin of a Brand directly influences its CSR score.

Return on Assets (ROA)

The Return on Assets (ROA) indicates how efficiently an entity can garner additional earnings from its assets. It proves beneficial in studying the nuances of a firm’s economic behavior. This quality is made possible by its impeccable capability to absorb corporate governance’s underlying trend (Rostami et al., 2016). Corporate governance dictates the rules and resolutions by which it explains corporate behavior. Effective communication of corporate governance can help stakeholders entrust a firm. Such an act deciphers a more robust chapter in firm-investor partnerships. In addition to the valuable profitability metrics accumulated, good governance helps create sound incentives and increased trust with the progressing days (Kyere and Ausloos, 2021). Therefore, the following hypothesis can be proposed to validate its significance in the context of CSR scores.

• H2: The entity’s Return on Assets positively correlates with the CSR.

Tobin’s Q or Q Ratio

Tobin’s Q or the Q ratio is a parameter that elucidates how much the firm’s assets pit against its market worth. The rate highlights if a particular business entity is overvalued or undervalued. The equilibrium of value indicates that the firm’s assets’ total replacement cost equals its current market value. Studies have asserted that more significant involvement in environmentally sustainable and socially responsible practices can increase an entity’s Q ratio (Wong et al., 2021). Tobin’s Q is an essential reference to judge any future for coming to an entity’s ownership structure and acts as a beacon point indicating a capital increase. Tobin’s Q ratio can encompass an organization’s performance data. Such an occurrence is accomplished with its ability to correlate with ownership patterns and board structure positively (Pradhan, 2016). Consequently, the given hypothesis is proposed to test its relevance from a luxury brand perspective.

• H3: The Q ratio of the firm is a direct indicator of its CSR score.

Net income

The Net income indicates the metric used to describe the resulting profit in a firm once all expenses and taxes are deducted from the net revenue incurred in a final period. Net income is primarily seen as a moderating variable and considered entirely irrelevant while analyzing a firm’s social acts. However, its ability to provide information about a firm’s capacity to increase its overall value (Bortoli et al., 2020) is seen as an X factor regarding CSR score dependence. Thus, it is essential to include this in the further assessment, and accordingly, the hypothesis is developed further.

• H4: The Net Income incurred by a firm can ensure an improved CSR score.

Total assets

A firm’s total assets indicate the cumulative value of the entities corresponding to significant economic value. In addition to encompassing data regarding the brand value, one can estimate the firm size metrics by knowing facts on the total assets (Colucci et al., 2020; Dang et al., 2018). The natural logarithm of the firm’s Total assets is taken as an indicator of the firm size. The subsequent transformation also ensures better scaling and minimal skew regarding modeling. A firm’s total assets also help us understand how likely a firm is on the verge of bankruptcy. This characteristic thus gives a direct idea about indulgence in CSR activities (Shen et al., 2016). Hence, this metric is considered and accordingly, the hypothesis is proposed for further analysis.

• H5: The Natural Logarithm of a firm’s Total assets is a positive indicator of its CSR score.

Firm age

The parameter is straightforward. It accounts for the longevity of the considered firm’s operations. We precisely include the number of years since which the targeted firm has its operations established. The firm’s age could shed light on how keen the entity is to buttress its reputation over time (Desai et al., 2008). The involvement in exemplary acts could reinforce the placed forward cause. A hypothesis is not made owing to the discussed nature of this parameter.

CSR score

The composite CSR score of a firm reflects the extent to which it has inculcated relevant CSR principles onto its core frameworks and business planning. The consequent scoring is also bolstered by the ability of the firm to disclose responsible practices across several fronts (Amin et al., 2021). A composite CSR score from the discussed sources is considered to perform our analysis. According to the discussed metrics, data have thus been accrued from sources corresponding to the parent companies of the specified luxury brands. The modeled dataset is obtained based on information about firms from numerous discussed sources and relevant calculations from the author’s side. Sources for the same are tabulated to aid researchers looking to pursue studies on a similar front.

Furthermore, firms are categorized according to specific sectors and geographical regions based on origin to ensure compliance with a fixed effects model. The classification can be found in Table 2. The subsequent section discusses the regression models developed based on the proposed hypothesis.

Table 2 Attributes discussed and source

Proposed regression models

Based on the initially collected data, a panel-level regression methodology is considered to model the scenario. The dataset is checked for compliance with regression requirements in the following stages to ensure its suitability for appropriate regression models. With the author’s calculations forming the foundation of the predictor and influencing attributes, the need to speculate about missing values is avoided. However, if any data is missing due to confidentiality restrictions, it is imputed based on the parent company or through summary statistics. The highly skewed nature of the values corresponding to the firm’s total assets calls for log normalization, which is performed to achieve a more precise interpretation. Table 3 shows the descriptive statistics for the variables used for analysis.

Table 3 Classification rubrics of brands used for analysis

An issue of multicollinearity could nullify the individual effects of attributes due to a strong dependence between two or more attributes. The Pearson Correlation test is used to identify potential collinearity between any two attributes. The results of this test are tabulated in Table 4. Collinearity can be detected by comparing the magnitudes against a certain threshold (0.7). The results suggest an absence of a highly positive or pairwise collinearity. However, overall collinearity between three or more column attributes is still possible. This condition is termed multicollinearity, and a suitable metric to assess this would be the Variance Inflation Factor (VIF). The VIF for each attribute is calculated and tabulated as described in Table 5.

Table 4 Descriptive statistics of variables involved in modelling

Table 5 Correlation matrix of independent variables

With a threshold value of 5 being set as the limit for multicollinearity, we find no attribute columns in the scrutinized domain that exceed this threshold. Therefore, it is decided to proceed further without worrying about potential multicollinearity. The target attribute is checked for normality based on a quantile–quantile plot (Q-Q plot) in (Fig. 1), and the reliable Shapiro–Wilk test is used to confirm normality with the smaller sample size, justifying it over other alternatives. The resulting W statistic or the p-value can help us obtain inferences. The null hypothesis is that the values are normally distributed. An incurring p-value of 0.085 (p > 0.050) in the Shapiro–Wilk test, as well as the results from the Q-Q plot (Fig. 1) suggest a near adherence to the bounds and, help us ascertain normality.

Fig. 1

Compliance of CSR Scores with Normal Distribution (Q-Q Plot). Observed quartiles from the CSR score attributes in the dataset are plotted against theoretical quartiles from the Normal Distribution. Deviations indicate corresponding departures from the idealized distribution, while points along the diagonal reference line indicate compliance with normality

Going by another assumption of a panel-level regression model, The Goldfields Quandt test is performed to check for homoscedasticity, an assumption that the residuals have constant variances across different subgroups or panel levels. The testing is based on the previously established assumption of normality. The data is conveniently split into high and low subgroups, whose variances are compared.

Null Hypothesis: There is no significant difference in variance across groups.

P value: 0.3362 (p > 0.050).

The obtained p-value is above the considered significance level , thus enabling us to conclude that there is insufficient evidence to reject the null hypothesis. Therefore, homoscedasticity is assumed for the model. The following flowchart (Fig. 2) summarises the steps undertaken to validate the compliance of a regression model.

Fig. 2

Flowchart Documenting the Regression Flow. The first level establishes the assumption, and the succeeding levels indicate corresponding tests to validate the assumption, as well as provide further inferences aiding in decision-making

The regression models are developed to examine the influence of selected financial and brand value metrics (Net Profit Margin (NPM), Net Income, Return on Assets (ROA), Tobin’s Q, Firm’s Age, the natural logarithm of total assets) on the CSR score of brands. Initially, an Ordinary Least Squares (OLS) regression model is employed. This model provides insights into the overall relationship between the predictors and the CSR score. Following the OLS regression, fixed effects models are utilized. Fixed effects models account for unobserved heterogeneity. These models allow for the region and sector-specific factors influencing the CSR score, providing more robust estimates.

Model 1: OLS

$$CSR\,SCORE_i=\beta_0+\beta_{1}.NPM_i+\beta_{2}.ROA_i+\beta_{3}.TOBIN'S\,Q_i+\beta_{4}.NET\,INCOME_i+\beta_{5}.FIRMAGE_i+\beta_{6}.Ln\left(TOTAL\,ASSETS\right)_i+\in_i$$

(1)

The sector and geographic region attributes are also considered for the succeeding models and are accounted for in addition to the selected metrics. The sector fixed effects model (model 2) and the geographic region fixed effects model (model 3) are subsequently developed.

Model 2: Sector fixed effects

$$CSR\,SCORE_{is}=\beta_{1}.NPM_{is}+\beta_{2}.ROA_{is}+\beta_{3}.TOBIN'S\,Q_{is}+\beta_{4}.NET\,INCOME_{is}+\beta_{5}.FIRMAGE_{is}+\beta_{6}.Ln \left(TOTAL\,ASSETS\right)_{is}+\in_{is}+\alpha_{i}+\lambda_{s}$$

(2)

Model 3: Geographic region fixed effects

$$CSR\,SCORE_{ig}=\beta_{1}.NPM_{ig}+\beta_{2}.ROA_{ig}+\beta_{3}.TOBIN'S\,Q_{ig}+\beta_{4}.NET\,INCOME_{ig}+\beta_{5}.FIRMAGE_{ig}+\beta_{6}.Ln\left(TOTAL\,ASSETS\right)_{ig}++\in_{ig}+\alpha_{i}+\lambda_{g}$$

(3)

Both the fixed effects are considered to obtain Model 4.

Model 4: Sector and geographic region fixed effects

$$CSR\,SCORE_{isg}=\beta_{1}.NPM_{isg}+\beta_{2}.ROA_{isg}+\beta_{3}.TOBIN'S\,Q_{isg}+\beta_{4}.NET\,INCOME_{isg}+\beta_{5}.FIRMAGE_{isg}+\beta_{6}.Ln\left(TOTAL\,ASSETS\right)_{isg}+\in_{isg}+\alpha_{i}+\lambda_{sg}$$

(4)

By employing the fixed effects framework, we can investigate the notion that diversified sectors or geographic regions do not exert sporadic influence on a brand’s sustainability and socially responsible actions. Instead, these brands integrate these policies from the grassroots level (Al-Mamun and Seamer, 2021). An in-depth analysis is also conducted with appropriate inferences from the proposed model.

Results and inferences

The four models’ results at a confidence bound of 97.5% and a p-value (> 0.010) are summarized and presented in Table 6. The relevant values are tabulated and are used in tandem for necessary insights. Each regression model is statistically significant, with the confidence bounds exceeding the lower thresholds. The final model (Model 4) represents an improvement over Model 1, incorporating sector and geographic region fixed effects. Model 4 provides a more comprehensive and nuanced understanding of the relationships between the chosen metrics and CSR scores by including these fixed effects layers. Given the depth and complexity of the model’s layering, Model 4 becomes pivotal in determining the acceptance or rejection of individual hypotheses.

Table 6 Variance infiltration factor for independent variables

As inferred from Model 1, The OLS model indicates that the following have substantial positive influences on the CSR score by their regression coefficients. From Model 1 in Table 7, NPM (1.374), Tobin’s Q (0.537), Ln (Total Assets) (0.741), and Firm Age (0.024) with p (> 0.01). Though the brand’s Net Income positively influenced the CSR score (Close to zero (0.0006)), the magnitude is too low to be deemed significant. However, we oblige significance regarding the magnitude of the Firm age attribute offers. The unique instance of Net Income can potentially indicate a change in companies’ allocation of funds towards CSR practices, influenced by the additional income acquired.

Table 7 Regression results for different models

The introduction of sector-wise fixed effects did not inflict any noticeable changes, except for minor shifts in the magnitudes of intercepts. As inferred from the sector-wise fixed effects model, the coefficients indicate that the following have considerable positive influences on the CSR score (from Model 2 in Table 7), NPM (1.400), Tobin’s Q (0.662), Ln (Total Assets) (0.329), and Firm Age (0.029). As of the preceding case, Net income had minuscule influences on the CSR score (0.001). With the introduction of geographical region-wise fixed effects, only noticeable changes in the intercepts are observed, with no signs of polarity reversal. The incurred results indicate that the following have considerable positive influences on the CSR score (from Model 3 in Table 7), NPM (2.157), Tobin’s Q (0.509), Ln (Total Assets) (0.663), and Firm Age (0.025). The minimal contribution from Net Income (Very close to zero (0.0006) does not change from the previous case.

As indicated in Model 4, the following considerably positively influence the CSR score. For illustration, NPM (1.785), Tobin’s Q (0.647), Ln (Total Assets) (0.287), and Firm Age (0.028). This crucial model resonates with Net income’s similar minuscule positive influence on the target variable (0.001). The relative impacts of each factor are visualized effectively through a split bubble chart (Fig. 3), which offers insights into both the magnitude and the directional influence. Contrary to common notions, brands’ Return on assets (ROA) metric consistently negatively influences the CSR score. Therefore, hypothesis H2, corresponding to ROA, is readily accepted. As evident from the pivotal model and the rest, Net income was never statistically significant to the cause, though it was not entirely irrelevant either. Thus, we dismiss the metric regarding our target cause, rejecting hypothesis H4.

Fig. 3

Comparison of Predictor Coefficients. Visually illustration of the relative magnitudes of various predictor coefficients and their contrasts with each other. The baseline input is Model 4 (Sector and Region Fixed Effects), with colour coding indicating the direction of influence

With NPM showing the highest positive significance among other attributes, hypothesis H1 is accepted without deliberation. The positive significance of NPM on CSR performance suggests that profits accrued are often directed towards sustainable and responsible initiatives, which directly or indirectly bolster the brand’s perception (Suryani, 2013). The fluctuating importance of the scaled Total assets can be a consideration; however, the overall metric remains significant to the CSR score of brands (Odeh et al., 2020). With the analysis having a limited number of predictors, it is decided to consider the direct importance of the variable accounting for Total assets, and the hypothesis H5 is also accepted. The trend with Tobin’s Q remains relatively stable, supported by concrete evidence from the pivotal model results. The Firm value often directly impacts markets (Bannier et al., 2019), although individual effects studies may suggest otherwise. Considering this impact, we accept hypothesis H3 as well. The magnitude of the firm Age attribute may seem distant from the other attributes with positive impacts. Despite this uncertainty, the consistent positive values indicate a positive dependence.

Business and practical implications

In a broader context, luxury firms are anticipated to establish a pervasive presence. Beyond marketing, they must be synonymous with endeavors that embrace diverse cultural interests and foster goodwill (Wang & Lee, 2020). This approach retains its significance in multicultural settings such as India, where brands are frequently remembered for participating in extensive initiatives and ventures more than the products they provide (Mitra, 2011). Proper resource allocation and a team within the firm dedicated to society-specific tasks are essential. This need resonates even more substantially in luxury brands, as the expectations are set relatively high, and people from all economic classes and backgrounds are expected to take time to purchase luxury products (Mundel et al., 2021).

Initiating Corporate Social Responsibility (CSR) practices from the ground level can entail significant initial expenses. Luxury brands comprehend the economic implications well. Even as they navigate economic uncertainty, luxury brands should remain vigilant about maintaining their commitment to sustainability and environmentally friendly initiatives. It is possible for firms to inadvertently neglect CSR efforts while allocating excessive attention to areas such as advertising and pursuing potentially unproductive ventures (Lo & Ha-Brookshire, 2018). However, it is crucial to acknowledge the importance of monitoring evolving consumer mindsets and ethical considerations. A misstep in brand-ethics could trigger a butterfly effect, cascading further through the brand’s image.

Conclusion

The study remained focused on identifying and analyzing the relationships between the proposed financial and brand value metrics and how they influence the corporate social responsibility (CSR) strategies of the luxury brands under investigation. Relevant data was collected from various sources as indicated and further transformed into valuable variables based on the stated calculations. The potential implications of each predictor on the CSR score are discussed. The data was initially pre-processed and subsequently checked for regression compliance through multicollinearity tests, assessment of normality, and homoscedasticity.

Four different regression models are developed, including an Ordinary Least Squares (OLS) model and three models with piecewise assumptions to account for all possible patterns in the data. While each of the four models has strengths and weaknesses, the fourth model, which incorporates two fixed attributes, is considered more significant in evaluating each proposed hypothesis. The intercepts for each predictor considered did not exhibit substantial fluctuations across all the models except for occasional variations in magnitude. A firm’s Net Profit Margin (NPM) during the targeted period is crucial in determining its CSR score. This understanding is well-founded, as higher profitability indicates the firm’s potential to engage in sustainable practices in a given period. It allows the firm to address internal shortcomings and concerns regarding responsible operations and social impact. This relationship is evident across different geographic regions and industry sectors, where a robust financial position enables the effective allocation of resources to support CSR initiatives. However, it is essential to note that not all profits are necessarily channeled toward CSR goals. In the case of luxury brands that are not usually associated with cost-cutting approaches, there are paradoxical instances where some firms employ cost-cutting strategies to appeal to a broader consumer base.

Additionally, certain esteemed firms may adopt strategies to achieve a monopolistic position in the market, driven by concerns about potential competitors entering the market (Tan, 2016). These unique approaches are taken despite their status as luxury brands. The study’s findings presented an unexpected result, as the Return on Assets (ROA) metric negatively influenced CSR performance. Initially, it was anticipated that a positive relationship would exist, considering that ROA reflects a firm’s efficiency in utilizing its assets to generate earnings. However, contrary to expectations, the observed negative influence suggests that the efforts made by the firms may need to be more effectively contributing to CSR improvements. Instead, these firms may channel their resources into more immediate goals, such as research and development or exploring new and challenging markets (Seo and Buchanan-Oliver, 2015).

In the luxury brands sector, especially in the automobile industry, firms navigate uncharted territories as they venture into foreign markets. Each market poses unique challenges with strict regulations, requiring these firms to adapt and revise their strategies and methodologies accordingly (Aybaly et al., 2017). This dynamic and ever-changing landscape may explain the unexpected negative influence of ROA on CSR performance, as firms prioritize other aspects of their business to establish a foothold in these new markets.

Tobin’s Q, functioning as a metric for assessing a company’s valuation effectiveness, yielded positive results on the CSR score. As much of a firm’s value is centered on intangible assets such as goodwill and brand reputation, companies must enhance their value by building a positive public reputation by engaging in socially responsible activities. Luxury brands have frequently employed such practices to counter allegations of involvement in defamation lawsuits and safeguard their brand identity (Díaz-Bustamante et al., 2016). Given the economic challenges caused by the COVID-19 pandemic and the subsequent economic slowdown, it is understandable that firms’ net income has shown minimal dependence on CSR performance. The fashion sector, in particular, has been severely impacted, as evidenced by the cancellation or modification of several iconic fashion weeks (Black, 2020) and a paradigm shift in terms of brand engagement, marked by the surprisingly active involvement of typically reserved and secretive brands (Pini & Timergaleeva, 2021).

In such a challenging situation, firms prioritize using their income to address previous deficits and focus on immediate sustainability rather than embarking on extensive societal initiatives (Sinha & Sainy, 2021). The prevailing economic uncertainties and the need for financial stability have compelled many firms to re-evaluate their priorities and allocate resources strategically. As a result, CSR initiatives may take a backseat temporarily as brands navigate the challenges posed by the pandemic and work towards overcoming the economic hardships faced by the industry. Once the situation stabilizes, firms may resume their focus on CSR and sustainable practices.

The natural logarithm of total assets, which serves as a reliable measure of firm size, is found to have a positive impact on the CSR score. As assets increase and firms expand, a wide range of ideas circulates among top management, resulting in a diversified approach and the ability to make multicultural and inclusive decisions (Youn et al., 2015). Although including the Firm age metric deviates from our primary focus on analyzing financial performance impacts, it aims to shed light on the often-discussed aspect of brand relevance. The positive correlation between firm age and CSR score is unsurprising, highlighting the consistent engagement in CSR activities over the years. However, its moderate impact suggests that these so-called ‘heritage brands’ heavily rely on their established reputation with comparatively less emphasis on sustainability efforts (Halwani, 2019). These findings may be surprising, as many brands, regardless of longevity, are finding significant ways to maintain positive societal engagement (Liu et al., 2021). Further investigation into this finding is limited, as the Firm age metric is considered for mere inference alongside the emphasized financial metrics.

The study has compiled a conclusive evidence regarding the relationship between economic and brand value metrics and the CSR score, providing compelling answers to the research questions. However, the study needs to discuss the broader context. While the examined metrics are likely sufficient for analysis, this may only hold across some markets. Specific metrics could be less significant in emerging markets where persistent regulations mandate CSR. Additionally, additional insights and trends could have been obtained by incorporating more data points. Certain firms operate in multiple sectors and are classified according to their primary trade. Introducing more precise classifications could enhance the analysis. However, pursuing such an undertaking would necessitate a larger dataset. A more extensive dataset would also facilitate a more thorough scrutiny of each attribute discussed individually, resulting in a more robust conclusion.

Future research endeavors could enhance our study by incorporating supplementary sector-level classifications and broader financial metrics. Time-fixed effects are also a valuable addition to control for any time-specific influences. However, in the context of our study, the exclusion of time-based effects is justified due to the unique timeframe of the COVID-19 pandemic and the subsequent economic downturn that forms the basis of our research. Conducting a more comprehensive study incorporating additional corporate responsibility parameters would be beneficial. Since our research is focused on the specific timeline of the pandemic, conducting similar studies beyond this timeframe may reveal new and unexpected insights. This aspect can serve as a valuable addition to be considered in future research undertakings.