Experimental evidence on consumers’ willingness to pay in the sustainable fashion industry

Analysis of social and environmental preferences

Table 1 presents the descriptive statistics of the variables used in the Purchase Intention dataset from the large-scale survey. As shown, the mean purchase intention for Bags B and C were similar, at 5.95 and 5.96, respectively, on a 10-point Likert scale. This suggests that, at least hypothetically, respondents expressed comparable interest in both bags, regardless of the differences in their production characteristics.

Regarding environmental preferences, respondents rated individual behavioral preferences (mean = 3.50) as more important than preferences related to firm behavior (mean = 2.87). To examine the influence of these variables on purchasing behavior, a categorization was conducted based on respondents’ environmental preferences—both individual and enterprise-related. Specifically, a dummy variable was constructed to indicate whether a respondent exhibited above-average environmental concern (“Environmental preference: high” = 1) or concern less than or equal to the average (“Environmental preference: low” = 1).

Based on the data described thus far, we conducted a descriptive analysis of the distribution of purchase intention according to corporate and individual social preferences. As previously noted, prosocial preferences appear to be a key driver influencing purchase intention¹⁷.

Figure 4 illustrates this relationship for Bag B, displaying purchase intention by level (low = blue, high = orange) of both corporate and individual social preferences. Respondents with higher levels of social preferences consistently demonstrated significantly greater purchase intentions. This pattern held true for both corporate (left bars) and individual (right bars) social preferences.

A similar trend was observed for Bag C, as depicted in Fig. 5. Again, higher social preferences were associated with greater purchase intention, while lower preferences corresponded with reduced interest. While this suggests a potential relationship between social and environmental preferences and purchase behavior, it is necessary to examine the correlations between these preference dimensions. These correlations are presented in Table 2.

The results indicated a positive and significant correlation (0.597) between individual and corporate environmental attitudes, suggesting that individual environmental concerns were reflected in both purchasing choices and expectations regarding market supply. Similarly, individual and corporate social attitudes were positively correlated (0.189), underscoring the importance of considering both dimensions within the broader context of sustainability and decision-making drivers. Notably, a strong correlation (0.91) was observed between corporate social and environmental preferences, indicating that these two factors were closely interrelated in shaping corporate strategies. Therefore, it was essential to treat them as distinct determinants in the regression analysis to more accurately capture hypothetical market behavior and decision-making dynamics.

To gain deeper insight into the purchase intentions for Bags B and C, we conducted a linear regression analysis using the ordinary least squares (OLS) estimator. This method allowed us to assess the isolated effect of each explanatory variable on the dependent variable (hypothetical purchase intention), measured on a 10-point scale for both bags. The primary explanatory variables were social and environmental preferences at both individual and corporate levels. Given the high correlations observed among these variables, we opted to run separate regressions for each set of preferences for each bag. Specifically, Table 3 reports the econometric estimates as follows: columns 1 and 2 present the estimated coefficients of social preferences (corporate and individual) on purchase intentions for Bags B and C, while columns 3 and 4 report the coefficients for environmental preferences (corporate and individual) for the same bags. Additionally, we included sociodemographic controls (income level, gender, age, presence of minors in the household) to evaluate their influence on purchase intention. This analysis provided a clearer understanding of the factors shaping consumer purchasing decisions and revealed significant associations among the variables considered.

As shown in columns 1 and 2, social preferences emerged as a significant determinant of purchase intentions for Bags B and C. Among these, preference for corporate social sustainability practices (e.g., fair labor conditions, absence of exploitative practices) emerged as the most influential factor. Notably, the coefficient was slightly higher for Bag C (1.445, compared to 1.372 for Bag B), indicating greater consumer sensitivity to the socially responsible attributes associated with this product.

The analysis also indicated that individual social preferences (e.g., prosocial behavior) had a positive impact on purchase intention for Bag C, albeit at the 10% level of statistical significance. This suggests that consumer sensitivity to social factors varied depending on the specific product. In contrast, sociodemographic variables did not significantly account for variation in purchase intention for either bag within the sample.

Turning to columns 3 and 4, the findings revealed that environmental preferences, like social preferences, significantly influenced purchase intention for both Bags B and C. Preference for corporate environmental sustainability (e.g., environmentally friendly production) emerged as the most relevant factor, with statistical significance at the 5% level. Again, the coefficient was higher for Bag C, suggesting heightened consumer awareness of this product’s environmental features. However, individual pro-environmental behaviors did not exhibit a statistically significant impact on purchase intention. This may be due to the fact that the products in question were already perceived as environmentally sustainable. As with social preferences, sociodemographic variables again failed to significantly explain variation in purchase intention.

Results of the lab experiment

This section analyzes the determinants of reservation prices for the three bags. Following the methodology proposed by Morone et al.²¹, we examined both average WTP for each bag and the aggregate demand curve.

Table 4 presents the descriptive statistics of the variables used in the experiment. Among the three bags, the basic model made from recycled material showed the highest average WTP (approximately €15). Bag C1 ranked second (average WTP of approximately €12), followed by Bag C2. Regarding product characteristics, participants were asked to evaluate their purchase intention, perceived product quality, and perceived cost using a 10-point Likert scale.

With regard to purchase intention, a similar pattern emerged: Bag B received the highest rating, followed by Bags C1 and C2. Bag B was also rated as having the highest perceived quality, while Bag C1 was perceived as slightly more expensive than the others.

Among the product attributes assessed, we included potential utility or disutility associated with being a fast fashion product or being made from recycled materials. To determine the salience of these aspects to consumers, we asked whether participants typically sought out fast fashion clothing (1 = no; 2 = yes) and whether they sought goods made from recycled materials (1 = no; 2 = yes). We then used these two indicators as proxies for prior experience with sustainable products, expecting a positive relationship between such experience and WTP, as discussed in Sect. 2.

With regard to sociodemographic variables, we collected data on seven household income categories, gender, and household composition (specifically, the presence of minors). We did not collect information on age or education, as all respondents were university students of similar age and educational background.

We continued the analysis by assessing the statistical significance of differences between the distributions of WTP, as shown in Fig. 56(left). To this end, we performed a Kolmogorov–Smirnov test to compare the cumulative distribution functions. Bag 1.0 was found to be statistically different from all other bags at the 1% significance level. In contrast, no statistically significant difference was detected between Bags C1 and C2. Regarding purchase intention (Fig. 6, right), a divergence emerged, as Bag C1’s distribution of purchase intention was statistically superior to that of Bag C2.

This analysis thus supported the conclusion that Bag 1.0 commanded a higher WTP, while Bags C1 and C2 appeared to share a comparable market position, irrespective of aesthetic differences.

Following Morone et al. (2020), we constructed demand curves for the three products by aggregating individual reservation prices. We then applied the local polynomial regression fitting (LOESS) method to estimate smoothed demand curves by bag type. The results indicated a broadly similar distribution of WTP across the products, with Bag 1.0 again displaying higher values in the average WTP range.

The overall similarity in the shape of the demand curves suggested comparable elasticities and consumer price sensitivities across all bag types (Fig. 7). Nevertheless, the lower average WTP for the re-recycled variants (C1 and C2) was confirmed, particularly in the central portion of the demand curves.

We next examined the determinants of individual WTP. As discussed in the preceding sections, social and environmental preferences were integral to explaining purchase intention, which, in turn, constituted a key variable in predicting WTP. Figure 8 provides initial graphical evidence by showing the relationship between high purchase intention (above average) and corresponding WTP levels for the three bags. T-test results revealed that high purchase intention was associated with a €10 increase in WTP for Bag B (p < 0.01), an €11 increase for Bag C1 (p < 0.01), and a €5 increase for Bag C2 (p < 0.10).

These findings align with the previous results: although recycled bags had similar WTPs, Bag C2 not only attracted lower purchase intention but also exhibited a weaker link between purchase intention and WTP. This may be attributed to aesthetic differences that distinguished it from the other models.

We incorporated all these aspects into an OLS regression model with robust standard errors. As previously noted, we included neoclassical factors influencing consumer choice, such as disposable income, perceived cost/price, and purchasing preferences—captured through purchase intention. In addition, we accounted for product attributes, including the use of sustainable materials (i.e., materials not associated with fast fashion), the search for recycled content, and perceived product quality. Sociodemographic controls were also included. The results are reported in Table 5.

The findings confirmed the previous insights: for Bags B and C1, purchase intention significantly and positively predicted WTP. However, this relationship did not hold for Bag C2, which was characterized by distinctive aesthetic features. Here, a gap between intention and behavior emerged, as higher purchase intention did not translate into increased WTP. This divergence suggests that aesthetic considerations may override behavioral intentions in certain cases. Perceived production costs were positively associated with WTP for both recycled bags, while perceived quality was a significant predictor of WTP only for Bag C1. Overall, sensitivity to product attributes was most pronounced in the case of Bag C1. Specifically, the presence of recycled materials—common to both C1 and C2—only led to a statistically significant increase in WTP for Bag C1, and not for the glossy version (C2), which underwent more radical aesthetic modifications. As the results show, prior experience played a significant role in shaping WTP for recycled products, but only in the case of the fully recycled bag. This suggests the presence of an “experience effect,” whereby familiarity with recycled products may increase consumers’ valuation of such goods. However, when additional attributes—particularly niche or unconventional aesthetic features—were introduced, the experience effect diminished and became statistically insignificant. These more eccentric design elements appeared to have undermined the positive influence of prior experience. Thus, while experience may enhance the perceived value of specific product attributes, its impact may weaken in the presence of conflicting or polarizing elements, such as aesthetic risk.

Based on these findings, we concluded that sustainable attributes may be a secondary concern for consumers—considered only when perceived quality and cost are comparable. If this were the case, it would be essential to introduce products to the market that were not only sustainable, but that also featured specific design elements that enhanced consumer perception, thereby improve purchasing attitudes and supporting broader market adoption.

To validate this hypothesis, we consulted a group of expert stakeholders with a demonstrated interest in environmental sustainability, particularly in the context of sustainable fashion. These experts were involved in the PEACE project (“Protecting the Environment: Advances in Circular Economy”), funded by the Italian Ministry of University and Research under the PRIN initiative and supported by the European Union’s Next Generation EU fund. The PEACE project aims to identify policy pathways to advance the Sustainable Development Goals through a circular economy framework. The consulted stakeholders—primarily academics and industry professionals specializing in circular economy and sustainable innovation—participated in the project’s kick-off meeting held in Rome on November 8, 2024. Their involvement was tied to the fashion-related case study of the PEACE project, which investigates sustainable practices in the fashion sector, focusing on circular production models and their associated social and environmental impacts. During this scientific outreach event, we conducted a targeted survey with this expert group. After presenting three types of bags (Bags B, C1, and C2), we asked participants to evaluate various product attributes via a structured questionnaire.

The questionnaire, adapted from Dinh et al.⁵⁴, was administered using a Likert scale ranging from 0 (completely disagree) to 10 (completely agree). The instrument was designed to capture perceptions of the strengths and weaknesses of eco-design in sustainable products. To structure the evaluation, the attributes were organized into four main categories:

1. 1.

   1. Functional attributes (FUN): assessing the product’s functional characteristics.

1. 2.

   2. Aesthetic attributes (AES): assessing the product’s aesthetic qualities.

1. 3.

   3. Eco-material attributes (MAT): assessing the use of eco-friendly materials.

• – MAT01: This product is made from recycled materials.

• – MAT02: This product is made from biodegradable materials.

• – MAT03: Natural and green sources of raw material are used in the production of this product.

• – MAT04: This product is made using minimal materials.

1. 4.

   4. Eco-production attributes (PRO): assessing attributes related to eco-friendly production.

• – PRO01: The production of this product causes no direct or indirect damage to the environment.

• – PRO02: This product is made using renewable energy/resources.

• – PRO03: New and advanced equipment is used to produce this product.

We received 33 valid responses to this questionnaire, offering valuable expert insights into the sustainable attributes of the bags under consideration. These responses helped to identify the perceived strengths and weaknesses of eco-design elements, contributing to a more nuanced understanding of how such attributes are evaluated in expert discourse. The results are presented in Fig. 9.

As shown by the mean values, expert perceptions of the bags’ sustainable characteristics were generally high across product types (see, e.g., top row, first graph). In particular, Bags C1 and C2 were perceived as incorporating a greater use of recycled materials, in alignment with their actual design features (second row, fourth graph).

Notably, the results for aesthetic and functional attributes revealed a more nuanced pattern. Bag C2 was perceived as visually unattractive, with less appealing aesthetic features, such as color. Furthermore, it was rated lower in terms of quality and durability (second row, second graph).

These findings supported our hypothesis regarding the perceived inferiority of Bag C2, which appeared to influence rational consumer decision-making, particularly in terms of WTP. Participants showed a preference for products perceived as higher in quality, even when sustainability levels were held constant. This underscores the idea that the “green premium,” describing consumers’ additional WTP for environmentally sustainable products, may be conditional upon maintaining conventional product standards, particularly those related to quality and aesthetics.