Do Environmental Values Drive Sustainable Investment Choices? Evidence on Individual Preferences for SDG 15-Linked Funds

Abstract

Sustainable finance is expected to mobilize private capital toward the Sustainable Development Goals, yet retail investors may not convert favorable environmental attitudes into sustainable portfolio choices. This study examines adult respondents’ preferences for investment funds linked to Sustainable Development Goal 15 (Life on Land), focusing on environmental values, the perceived credibility of sustainable funds, perceived individual impact, expected return, and risk. A quantitative, cross-sectional survey was administered to adults and included eight hypothetical investment-choice scenarios. The final analytical sample comprised 105 respondents. Spearman correlations, robust ordinary least squares models, and clustered logistic comparisons were used. Environmental values, credibility, and perceived impact were positively interrelated, but none significantly predicted the number of SDG 15-linked choices, either directly or through moderation. Respondents selected sustainable alternatives in 4.33 of eight scenarios on average (54.17%). Sustainable-choice frequencies differed substantially across the presented scenario groups: 67.62% when the SDG 15-linked alternative offered higher return and lower risk, 46.03% under lower return and lower risk, and 39.05% under higher return and higher risk. Because return and risk varied simultaneously across fixed scenarios, these differences should not be interpreted as separate attribute effects. The findings reveal a descriptive attitude–behavior gap and are consistent with a three-dimensional view of investment choice in which sustainability is considered alongside return and risk. However, because these attributes were not independently varied, their separate contributions cannot be identified. Fund managers and regulators should combine verifiable biodiversity outcomes with transparent, financially competitive products.

1. Introduction

Sustainable finance has moved from a specialist practice to a central component of capital-market policy. Its underlying proposition is that investment decisions can pursue financial objectives while incorporating environmental, social, and governance considerations. Under the United Nations 2030 Agenda, private savings are expected to complement public resources and help close the financing gaps associated with the Sustainable Development Goals (SDGs). This transition has expanded the supply of investment funds marketed as sustainable and has encouraged regulators, asset managers, financial advisers, and households to reconsider what constitutes value in portfolio selection (Giglio et al., 2021; Haro Sarango et al., 2024; Starks, 2023). From an investor-utility perspective, sustainability can operate as an additional portfolio attribute whose relevance depends on financial preferences, including risk aversion and the expected risk–return profile of sustainable assets (Aslan & Posch, 2022).

Within this broader agenda, SDG 15—Life on Land—addresses the protection, restoration, and sustainable use of terrestrial ecosystems, sustainable forest management, desertification, land degradation, and biodiversity loss. These issues are financially material because firms depend on ecosystem services, natural inputs, resilient supply chains, and stable regulatory environments. Recent evidence suggests that capital markets have begun to recognize corporate biodiversity exposure, particularly following major international policy and disclosure initiatives (Garel et al., 2024). Nevertheless, biodiversity finance remains less standardized than climate finance. Carbon emissions can be expressed through comparatively familiar indicators, whereas biodiversity impacts are multidimensional, location-specific, and difficult to aggregate. Investors may therefore face considerable uncertainty about whether a labeled financial product produces genuine ecological outcomes (Han et al., 2026; Popescu et al., 2022).

The credibility problem is particularly relevant for retail investors. Sustainable-finance disclosure and product classifications seek to improve comparability, but the coexistence of labels, ratings, and methodologies can create additional complexity. Divergence among sustainability assessments and concern about greenwashing may weaken confidence in the claims made by financial institutions. A fund may be marketed as environmentally responsible while its holdings, engagement strategy, or real-world contribution remains unclear. If investors doubt the authenticity or environmental additionality of the product, even strong environmental values may fail to translate into investment (Busch, 2023; Horn, 2024). This problem is compounded by limited sustainable-finance literacy: households may possess conventional financial knowledge while lacking the specific ability to identify and assess the sustainability characteristics of financial products (Filippini et al., 2024). Evidence published in Sustainability similarly indicates that sustainable-finance literacy and the perceived environmental impact of financial instruments are positively related to sustainable-investment attitudes (Yucel et al., 2023).

Behavioral research further indicates that investment preferences are not determined exclusively by expected return and variance. Investors can derive non-pecuniary utility from aligning their portfolios with their environmental values. Accordingly, individuals who seek consistency between their environmental values and economic decisions may be more likely to select SDG 15-linked funds. However, translating this orientation into effective choice may depend on product credibility, perceived environmental impact, and the financial characteristics of the alternatives. This attitude–behavior gap may reflect information constraints, limited financial literacy, perceived ineffectiveness, status-quo bias, social-desirability effects, or an unwillingness to sacrifice expected return or accept additional risk (Aulia et al., 2024; Bauer et al., 2021; Heeb et al., 2023; Zieleman, 2024). Recent evidence also confirms that conventional investment motives interact with sustainability considerations: stronger profit-maximization motives can reduce willingness to accept green trade-offs, while risk preferences and investment horizons can help explain heterogeneity in sustainable-investment choice (Hinrichs & Sobol, 2024; Faradynawati & Söderberg, 2022).

Despite this growing literature, the relationship between environmental orientation and effective investment choice remains particularly uncertain for biodiversity-related products, whose environmental outcomes are difficult for individual investors to observe and verify. Three research gaps remain. First, much of the evidence concerns sustainable or ESG investment in general, whereas comparatively little is known about retail preferences for products specifically linked to biodiversity and terrestrial ecosystems. Second, studies frequently examine sustainable attitudes or investment intentions without comparing them with repeated choices involving explicit financial trade-offs. Third, credibility and perceived impact are generally treated as direct determinants, although they may also condition whether environmental values are translated into effective investment decisions. Addressing these gaps requires a design that simultaneously considers environmental attitudes, trust in sustainability claims, perceived individual efficacy, expected return, and risk.

Accordingly, this study examines the determinants of individual preferences for investment funds linked to SDG 15 through eight hypothetical choice scenarios. The analysis distinguishes declared environmental orientation from repeated scenario-based behavior and tests whether credibility and perceived impact directly explain sustainable choice or moderate the relationship between environmental values and investment decisions. It also evaluates how sustainable preference changes across different combinations of expected return and risk.

The research question is therefore: to what extent do environmental values, fund credibility, perceived impact, expected return, and risk explain individual preference for investment funds linked to SDG 15? The results show that environmental values, credibility, and perceived impact form a coherent attitudinal structure but do not significantly explain the number of sustainable choices. In contrast, the return–risk configuration is strongly associated with selection. The study contributes to sustainable-finance research by showing that sustainability operates as a third dimension of investment choice that complements, but does not displace, expected return and risk.

2. Theoretical Framework and Hypotheses

2.1. From Mean–Variance Choice to a Three-Dimensional Utility Framework

Classical portfolio theory explains investment choice primarily through the relationship between expected return and risk. In the mean–variance framework, investors select portfolios that maximize expected return for a given level of variance or minimize variance for a given expected return (Markowitz, 1952). Although this approach remains fundamental to financial decision-making, the development of sustainable finance has expanded the set of attributes that investors may consider. Environmental, social, and governance characteristics can affect investment utility by representing both financially material information and non-financial preferences. Sustainability can therefore enter the decision process as an additional portfolio attribute rather than as a substitute for expected return and risk (Aslan & Posch, 2022).

The distinction between financial value and personal values is particularly relevant in this context. Investors motivated by financial value may incorporate sustainability information because they expect environmental and social factors to affect long-term cash flows, volatility, regulatory exposure, or downside risk. By contrast, values-oriented investors may derive non-pecuniary utility from holding assets that are consistent with their environmental or ethical convictions, even when the financial consequences are uncertain (Starks, 2023; Delsen & Lehr, 2019). These motivations are not mutually exclusive. An individual may simultaneously seek competitive financial performance, avoid environmentally harmful activities, and contribute to positive environmental outcomes. Sustainable investment choice can therefore be represented through a three-dimensional utility framework in which expected return, risk, and sustainability jointly influence investor preferences.

The relative importance of the three dimensions is likely to vary across individuals and decision contexts. An investor may express a strong general preference for sustainability but assign greater weight to expected return or risk when faced with a concrete product choice. Conversely, another investor may be willing to accept a limited financial trade-off in exchange for stronger alignment with environmental values. The relevant question is therefore not whether investors care about sustainability in the abstract, but whether sustainability continues to influence choice when financial attributes are explicitly presented. This framework provides the theoretical basis for examining whether environmental values predict the selection of SDG 15-linked funds and whether this relationship depends on product credibility, perceived impact, and the financial conditions of the investment.

2.2. SDG 15, Biodiversity, and Financial Materiality

Biodiversity loss has progressively moved from being regarded as an exclusively environmental problem to being recognized as a financially material source of risk. Economic activity depends on ecosystem services such as water provision, soil fertility, pollination, biological resources, climate regulation, and the resilience of natural and productive systems. The deterioration of these services can generate physical, transition, regulatory, litigation, market, and reputational risks, particularly for sectors such as agriculture, forestry, food production, pharmaceuticals, tourism, infrastructure, and financial services. Evidence from international equity markets suggests that investors have begun to incorporate corporate biodiversity exposure into asset valuations, especially following major international biodiversity and disclosure initiatives (Garel et al., 2024).

SDG 15—Life on Land—addresses the protection, restoration, and sustainable use of terrestrial ecosystems, the sustainable management of forests, the prevention of desertification and land degradation, and the conservation of biodiversity. Achieving these objectives requires the mobilization of public, philanthropic, and private capital. Nevertheless, biodiversity finance remains less developed and standardized than climate finance. Whereas greenhouse-gas emissions can be expressed through relatively familiar carbon-based indicators, biodiversity is multidimensional, location-specific, non-linear, and difficult to aggregate. Its measurement may involve species abundance, habitat condition, ecosystem integrity, land-use change, water systems, supply-chain dependencies, and the spatial and temporal boundaries adopted in the assessment (Khan & Shehzad, 2025; Sayn-Wittgenstein et al., 2025).

These measurement difficulties create an important distinction between sustainability alignment and environmental impact. An investment fund may select companies associated with conservation activities, exclude businesses with substantial environmental footprints, or claim alignment with SDG 15. However, these characteristics do not necessarily demonstrate that the investment generates additional conservation or restoration outcomes. Portfolio composition, capital allocation, corporate behavior, and real-world environmental change represent related but analytically distinct levels. Recent research on nature finance identifies substantial fragmentation in biodiversity metrics and a disconnect between the indicators developed by environmental organizations and those used in financial products and investment practice (Sayn-Wittgenstein et al., 2025).

Biodiversity-related investment may nevertheless provide both financial and non-financial utility. Investors may value alignment with conservation objectives, while companies with substantial biodiversity dependencies or impacts may face increasing regulatory, litigation, supply-chain, and transition risks. Biodiversity finance can consequently be represented through a three-dimensional framework involving expected return, financial risk, and biodiversity impact. Investments with favorable risk–return characteristics may attract private capital directly, whereas projects with substantial ecological value but less attractive financial profiles may require public support, philanthropic capital, guarantees, or blended-finance mechanisms to improve their investability (Flammer et al., 2023).

For retail investors, the complexity of biodiversity measurement increases dependence on labels, sustainability disclosures, ratings, fund classifications, and external verification. Individual investors are unlikely to possess the technical information or analytical capacity required to evaluate ecological additionality, supply-chain impacts, or the reliability of biodiversity indicators independently. Consequently, the credibility of an SDG 15-linked fund depends not only on the environmental activities represented in its portfolio but also on whether its claims are specific, transparent, comparable, and verifiable. SDG 15 therefore provides a particularly relevant setting in which to examine whether environmental values and perceived impact are translated into sustainable investment choices when product credibility and conventional financial attributes remain uncertain.

2.3. Environmental Values

Environmental values may influence investment decisions by providing non-financial utility. Investors can derive satisfaction from aligning their portfolios with their environmental principles and avoiding activities considered harmful (Starks, 2023; Delsen & Lehr, 2019). However, environmental concern is not sufficient to ensure sustainable investment, as actual choices also depend on financial motives, product characteristics, available information, and behavioral constraints (Aulia et al., 2024).

This distinction is especially relevant to SDG 15. Biodiversity outcomes are difficult for retail investors to observe, potentially weakening the connection between general environmental values and specific fund choices. Moreover, investors differ in their willingness to accept financial trade-offs: some may sacrifice part of the expected return to achieve value alignment, whereas others support sustainability only when the product offers a competitive risk–return profile (Aslan & Posch, 2022; Bauer et al., 2021; Delsen & Lehr, 2019). Accordingly, individuals with stronger environmental values are expected to select SDG 15-linked alternatives more frequently.

H1. 

Stronger environmental values increase the preference for investment funds linked to SDG 15.

2.4. Credibility and Greenwashing

Credibility concerns the extent to which investors believe that a sustainability label corresponds to genuine environmental practices and outcomes. Disclosure regulation can reduce information asymmetry, but technical classifications are not always understood by retail clients. Moreover, rating disagreement and inconsistent labeling may undermine trust (Han et al., 2026; Popescu et al., 2022; Busch, 2023). Credibility should therefore affect choice directly and may also condition whether values are translated into action.

H2. 

Greater perceived credibility of sustainable funds increases preference for SDG 15-linked funds.

H3. 

Credibility positively moderates the relationship between environmental values and sustainable fund preference.

2.5. Perceived Impact and Individual Efficacy

Perceived impact refers to the belief that an individual investment decision can contribute to environmental protection. Investors who expect their choices to produce real-world outcomes may derive greater utility from sustainable funds and show a higher willingness to select them (Yucel et al., 2023; Heeb et al., 2023). However, financial investment and environmental change are connected through complex transmission mechanisms, making it difficult for retail investors to assess additionality.

Recent evidence shows that retail investors may overestimate the climate impact of green funds relative to academic experts. Providing information about expert assessments reduces both perceived impact and willingness to pay, confirming that impact beliefs can influence investment decisions (Heeb et al., 2025). In the context of SDG 15, perceived impact may therefore affect choice directly and may also strengthen the translation of environmental values into sustainable investment.

H4. 

Greater perceived impact of individual investment increases the preference for investment funds linked to SDG 15.

H5. 

Perceived impact positively moderates the relationship between environmental values and the preference for investment funds linked to SDG 15.

2.6. The Attitude–Behavior Gap

Positive environmental attitudes do not necessarily result in sustainable investment. General expressions of support involve no financial cost, whereas fund choices require investors to evaluate return, risk, credibility, and expected impact simultaneously. Information costs, behavioral biases, limited trust, and uncertainty about product outcomes can therefore prevent favorable attitudes from becoming effective choices (Aulia et al., 2024; Bauer et al., 2021).

Recent research distinguishes investment intentions from actual allocation decisions and emphasizes that trust, perceived control, and access to understandable ESG information can affect the transition from attitudes to behavior (Sesini et al., 2026). This distinction is central to the present study because environmental orientation is measured separately from the choices made across eight scenarios. A weak association between these measures would indicate that declared environmental values are insufficient to predict sustainable fund selection when financial trade-offs are explicit.

H6. 

A gap exists between declared environmental orientation and effective sustainable fund choice.

2.7. Return, Risk, and Financial Trade-Offs

Sustainability does not eliminate the importance of return and risk in investment decisions. Investors may value environmental attributes while remaining unwilling to accept substantially lower expected returns or greater financial risk. Accordingly, sustainable assets are more likely to be selected when they offer a competitive financial profile (Aslan & Posch, 2022; Hinrichs & Sobol, 2024; Faradynawati & Söderberg, 2022).

Empirical evidence does not establish a general performance penalty for sustainable funds. European funds with higher sustainability ratings may achieve comparable or favorable financial performance, while ESG characteristics can contribute to risk-adjusted portfolio evaluation (Abate et al., 2021; Ashwin Kumar et al., 2016). Nevertheless, findings vary across markets, methodologies, sustainability measures, and investor expectations (Kräussl et al., 2024). The relevant issue in the present study is therefore not the actual performance of sustainable funds, but how respondents react to the return–risk characteristics presented in each scenario. If sustainability is treated as an additional investment attribute, its influence should weaken when the SDG 15-linked alternative involves an explicit financial disadvantage.

H7. 

Preference for SDG 15-linked funds decreases when sustainable choice requires giving up expected return or assuming greater risk.

3. Materials and Methods

3.1. Research Design and Procedure

The study used a quantitative, cross-sectional, non-experimental design. Data were collected through a voluntary questionnaire administered to adults. Participants received information about the study and provided consent before answering. No direct identifiers were collected, and results were analyzed in aggregate. The instrument included questions on financial experience, three attitudinal measures, eight investment-choice scenarios, and sociodemographic characteristics. The complete wording of the eight choice scenarios, together with their expected-return, risk, and sustainability characteristics, is reproduced in Appendix A.

The scenarios presented alternative investment funds with different combinations of financial and sustainability characteristics and were shown to all respondents in the same fixed order. Participants selected one option in each scenario. The design was hypothetical and did not involve real monetary incentives. Consequently, the resulting choices are better interpreted as structured preferences than as observed portfolio transactions. Nevertheless, the scenarios impose explicit comparisons and therefore reduce reliance on broad declarations of support for sustainable finance.

3.2. Sample and Data Preparation

The initial database contained 119 questionnaires. During data-quality screening, 21 records were identified in which responses had shifted across adjacent columns following form export. These records were reconstructed according to the original questionnaire sequence, the response format, and the permissible values of each variable. Three-option responses were reassigned to their corresponding investment scenarios, five-point responses to the attitudinal items, and the remaining responses to the appropriate sociodemographic variables. The reconstructed scenario responses were subsequently checked against the original option structure and scenario-specific SDG 15 coding. Of the 21 reconstructed records, 18 met the consent and complete-scenario criteria and were included in the final analytical sample. Reconstruction only reassigned existing responses to their original variables; no missing values were statistically imputed.

Eligibility for the main sample required informed consent and complete responses to all eight scenarios. Of the original records, 117 included consent and 106 completed all scenarios; applying both criteria produced a final sample of 105 respondents, representing 88.24% of the starting database. A binary indicator identifying reconstructed records was retained for verification and sensitivity analysis. The de-identified analytical dataset, variable codebook, and Stata 16 replication code are available from the corresponding author upon reasonable request, subject to applicable ethical and data-protection requirements.

The mean age was 28.85 years (SD = 11.67; median = 24; range 18–63), based on 101 valid observations. Gender was almost balanced. University education was reported by 47.62% and vocational education by 34.29%. Most respondents lived in municipalities with fewer than 20,000 inhabitants. The sample was non-probabilistic and relatively young and educated; thus, the analysis identifies associations within the sample rather than population prevalence among Spanish investors. Previous investment-fund experience was reported by 27 respondents (25.71%), whereas 76 (72.38%) had no previous fund experience and 2 (1.90%) did not answer this question. Accordingly, the sample represents adult respondents with varying levels of investment experience rather than a group composed exclusively of active retail investors. Sociodemographic characteristics of the sample are given in Table 1.

Table 1. Sociodemographic characteristics of the final sample.

Variable	Category or Statistic	n	%
Age	Mean	28.85	—
	Standard deviation	11.67	—
	Median	24	—
	Minimum–maximum	18–63	—
	Valid observations	101	96.19
	No response	4	3.81
Gender	Female	52	49.52
	Male	51	48.57
	Other gender identities	2	1.90
Educational level	No formal education	3	2.86
	Primary or lower-secondary education	16	15.24
	Vocational education and training	36	34.29
	University education	50	47.62
Monthly household income	Less than EUR 900	4	3.81
	EUR 900–1500	26	24.76
	EUR 1501–2500	47	44.76
	More than EUR 2500	25	23.81
	No response	3	2.86
Employment status	Employee	45	42.86
	Student	31	29.52
	Self-employed	9	8.57
	Civil servant	7	6.67
	Unemployed	7	6.67
	Other employment status	5	4.76
	No response	1	0.95
Municipality size	Fewer than 5000 inhabitants	46	43.81
	5001–20,000 inhabitants	27	25.71
	20,001–100,000 inhabitants	19	18.10
	100,001–500,000 inhabitants	8	7.62
	More than 500,000 inhabitants	5	4.76

Source: own compilation. Note: N = 105, except age (101 valid observations). Percentages use the final sample as denominator. Original identity responses were retained in the data.

3.3. Measures

3.3.1. Dependent Variable: Sustainable Fund Preference

For each scenario, alternatives explicitly linked to SDG 15 were coded 1, and the remaining alternatives were coded 0. This classification was pre-specified in the study design and based exclusively on the substantive environmental contribution stated in the original Spanish questionnaire, rather than on the option number. In Scenario 4, two alternatives explicitly referred to terrestrial ecosystems, and both were therefore coded as SDG 15-linked choices. Appendix A provides the original Spanish wording of the relevant alternatives, a direct English translation, the scenario-by-scenario coding, and the return–risk classification. The individual Sustainable Preference Index (SPI) was calculated as the sum of the eight binary decisions, ranging from 0 to 8. A percentage measure was obtained as SPI/8 × 100.

The index gives equal weight to each scenario and captures the frequency with which a respondent selected an alternative explicitly linked to SDG 15. It is a descriptive indicator of SDG 15-linked choices and does not isolate sustainability preferences from preferences for the financial or other characteristics of the alternatives. Scenario-specific distributions were also retained because aggregate scores can conceal sensitivity to the return–risk configuration.

3.3.2. Environmental Values, Credibility, and Perceived Impact

Environmental-value consistency was measured by asking: “To what extent do you try to ensure that your economic decisions—consumption, saving, or investment—are consistent with your environmental values?” Thus, the item captures declared consistency between environmental values and economic decisions rather than the broader construct of environmental values. Credibility was measured by asking how credible respondents considered the claim that a fund labeled sustainable genuinely contributes to SDG 15. Perceived impact was measured by asking to what extent individual investment decisions can make a real contribution to protecting terrestrial ecosystems.

Each item used a five-point ordinal scale: 1 = not at all, 2 = slightly, 3 = somewhat, 4 = considerably, and 5 = very much. Higher scores indicated stronger environmental orientation, greater credibility, and greater perceived efficacy. The use of one item per construct kept the questionnaire concise and directly aligned with the theoretical mechanisms, but may have reduced measurement precision and attenuated the estimated associations.

3.3.3. Control Variables

Potential controls comprised age, gender, education, household income, employment status, marital status, household size, municipality size, and prior investment-fund experience. Given the sample size, the expanded specification used a parsimonious subset: age, female gender, university education, and prior fund experience. Sparse categories were not entered separately, avoiding an excessive parameter-to-observation ratio.

3.4. Statistical Strategy

Data management and analysis were conducted using Stata 16 and combined descriptive, bivariate, multivariate, moderation, and choice-level analyses. Continuous variables were summarized by means, standard deviations, medians, ranges, and 95% confidence intervals; categorical variables were summarized by counts and percentages. Spearman coefficients were used for the three ordinal attitudinal measures and for their bivariate associations with the SPI. Bootstrap standard errors and confidence intervals for attitude correlations used 2000 replications.

Four ordinary least squares models with heteroskedasticity-robust standard errors were estimated. Model 1 included environmental values, credibility, and perceived impact. Model 2 added the four controls. Models 3 and 4 added, separately, the centered environmental-values × credibility and environmental-values × perceived-impact interactions. Separate interaction models limited complexity and facilitated interpretation.

For descriptive comparison, scenario decisions were pooled and grouped according to whether the sustainable alternative offered (a) higher return and lower risk, (b) lower return and lower risk, or (c) higher return and higher risk. A scenario in which two alternatives were linked to SDG 15 was reported separately and excluded from the principal comparison. A choice-level logistic model with standard errors clustered by participant was used to estimate predicted probabilities and pairwise differences between the three predefined scenario groups. Clustering accounted for repeated decisions by the same respondent, but the analysis did not identify separate return or risk effects because these attributes varied simultaneously across fixed scenarios and could not be separated from other scenario-specific characteristics.

All tests were two-sided with α = 0.05. Coefficients were interpreted as associations rather than causal effects because the study was cross-sectional and non-experimental. Statistical significance was assessed together with coefficient signs, magnitudes, 95% confidence intervals, and model fit. The sample exceeded Green’s indicative threshold of N ≥ 50 + 8m for the three-predictor model and a limited expanded specification, although this criterion does not replace a formal power analysis (Green, 1991).

4. Results

4.1. Attitudes Toward Sustainable Finance

The three attitudinal measures were centered near the midpoint. Environmental values (Table 2) had the highest mean (2.97), followed by perceived impact (2.92) and credibility (2.86). Only 26.66% reported high environmental orientation, 22.86% high credibility, and 24.76% high perceived impact (Table 3). Credibility also displayed the largest proportion of low responses, indicating skepticism about whether sustainable funds genuinely contribute to SDG 15.

Table 2. Descriptive statistics for sustainable-finance attitudes.

Variable	N	Mean	Standard Deviation	Median	Minimum	Maximum
Environmental values	105	2.97	0.97	3	1	5
Sustainable fund credibility	105	2.86	1.02	3	1	5
Perceived impact of individual investment	105	2.92	1.01	3	1	5

Source: own compilation. Note: The variables were measured on a five-point scale ranging from 1 = Not at all to 5 = Very much. Higher scores indicate stronger environmental values, greater perceived credibility of sustainable funds, and greater perceived impact of individual investment decisions, respectively.

Table 3. Distribution of sustainable-finance attitudes.

Variable	Not at All, n (%)	Slightly, n (%)	Somewhat, n (%)	Considerably, n (%)	Very Much, n (%)
Environmental values	7 (6.67)	23 (21.90)	47 (44.76)	22 (20.95)	6 (5.71)
Credibility	10 (9.52)	26 (24.76)	45 (42.86)	17 (16.19)	7 (6.67)
Perceived impact	7 (6.67)	28 (26.67)	44 (41.90)	18 (17.14)	8 (7.62)

Source: own compilation. Note: N = 105. Percentages were calculated using the final sample as the denominator. Variables were measured on a five-point scale ranging from 1 = Not at all to 5 = Very much.

4.2. Relationships Among Environmental Values, Credibility, and Perceived Impact

All three Spearman correlations were positive and statistically significant (Table 4). Environmental values correlated with credibility at ρ = 0.364 and with perceived impact at ρ = 0.410. The strongest relationship was between credibility and perceived impact (ρ = 0.513). Thus, respondents who trusted sustainable-fund claims also tended to believe more strongly that individual investment can protect terrestrial ecosystems. The coefficients were moderate rather than redundant, supporting the conceptual distinction among personal orientation, trust in the product, and perceived efficacy.

Table 4. Spearman correlations among sustainable-finance dimensions.

Relationship	Spearman’s ρ	Bootstrap Standard Error	95% CI	p-Value
Environmental values and credibility	0.364	0.102	[0.165, 0.564]	<0.001
Environmental values and perceived impact	0.410	0.092	[0.229, 0.590]	<0.001
Credibility and perceived impact	0.513	0.093	[0.330, 0.696]	<0.001

Source: own compilation. Note: N = 105. Bootstrap standard errors and 95% confidence intervals were calculated using 2000 bootstrap replications. All tests were two-tailed.

4.3. Scenario Choices and the Sustainable Preference Index

Option shares varied sharply across the eight scenarios (see Table 5). No option occupied the same substantive position across scenarios, so option numbers should not be treated as an ordinal sustainability scale. Scenario 2 had the greatest concentration, with 70.48% selecting Option 2, whereas Scenario 5 was nearly evenly divided. After the sustainability coding was applied, SDG 15 choice ranged from 30.48% in Scenario 1 to 81.90% in Scenario 4 (Table 6). The high value in Scenario 4 partly reflects the presence of two qualifying alternatives.

Table 5. Distribution of responses in the eight investment scenarios.

Scenario	N	Option 1, n (%)	Option 2, n (%)	Option 3, n (%)
1	105	52 (49.52)	32 (30.48)	21 (20.00)
2	105	17 (16.19)	74 (70.48)	14 (13.33)
3	105	55 (52.38)	25 (23.81)	25 (23.81)
4	105	64 (60.95)	22 (20.95)	19 (18.10)
5	105	35 (33.33)	34 (32.38)	36 (34.29)
6	105	50 (47.62)	41 (39.05)	14 (13.33)
7	105	36 (34.29)	55 (52.38)	14 (13.33)
8	105	16 (15.24)	68 (64.76)	21 (20.00)

Source: own compilation. Note: Option numbers indicate the position of each alternative within the corresponding scenario and do not represent an increasing level of sustainability. N denotes the number of valid responses in each scenario.

Table 6. SDG 15-linked choices by scenario.

Scenario	SDG 15-Linked Choices, n	Percentage
1	32	30.48
2	74	70.48
3	55	52.38
4	86	81.90
5	35	33.33
6	50	47.62
7	55	52.38
8	68	64.76

Source: own compilation. Note: N = 105 per scenario. In Scenario 4, both Options 1 and 2 were linked to SDG 15 and were therefore classified as sustainable choices.

The most frequent SPI value (Table 7) was five sustainable choices, observed for 30.48% of respondents. Overall, 76.19% selected an SDG 15-linked option in at least four scenarios. Seven respondents made no sustainable choices, while three selected a sustainable alternative in all eight scenarios. The mean was 4.33 (SD = 1.81), equivalent to 54.17% of decisions; the median was five, and the 95% confidence interval for the mean was 3.98–4.68 (see Table 8).

Table 7. Distribution of the SDG 15 sustainable preference index.

Number of Sustainable Choices	n	Percentage
0	7	6.67
1	2	1.90
2	6	5.71
3	10	9.52
4	24	22.86
5	32	30.48
6	16	15.24
7	5	4.76
8	3	2.86
Total	105	100.00

Source: own compilation. Note: The Sustainable Preference Index represents the number of scenarios in which each respondent selected an investment alternative linked to SDG 15. The index ranges from 0 to 8, with higher values indicating a stronger preference for sustainable investment funds.

Table 8. Descriptive statistics for preference for SDG 15-linked funds.

Variable	N	Mean	Standard Error	Standard Deviation	Median	Minimum	Maximum	95% CI
Number of sustainable choices	105	4.33	0.177	1.81	5	0	8	[3.98, 4.68]
Percentage of sustainable choices	105	54.17	2.21	22.65	62.50	0	100	[49.78, 58.55]

Source: own compilation. Note: The percentage of sustainable choices was calculated by dividing the number of sustainable choices by eight and multiplying the result by 100. CI denotes confidence interval.

4.4. Attitude–Behavior Gap

None of the three attitudes correlated significantly with the SPI. Environmental values produced ρ = 0.104 (95% CI [−0.112, 0.312], p = 0.293), credibility ρ = 0.061 (95% CI [−0.148, 0.266], p = 0.539), and perceived impact ρ = 0.111 (95% CI [−0.102, 0.315], p = 0.260). Respondents with high environmental orientation averaged 4.46 sustainable choices, compared with 4.29 among the remaining respondents. The mean difference was 0.179 choices (95% CI [−0.727, 1.084], p = 0.697). Low sustainable preference was observed among 32.14% of respondents with high environmental orientation and 20.78% of the remaining respondents, although the association was not statistically significant (two-sided Fisher’s exact p = 0.300). As reported in Table 9, these results are consistent with a descriptive attitude–behavior gap but do not provide inferential evidence of a systematic association.

Table 9. Relationships between declared attitudes and sustainable-fund preference.

Analysis	Variable or Comparison	N	Estimate	95% CI	p-Value
Spearman correlation with SPI	Environmental values	105	ρ = 0.104	[−0.112, 0.312]	0.293
Spearman correlation with SPI	Sustainable-fund credibility	105	ρ = 0.061	[−0.148, 0.266]	0.539
Spearman correlation with SPI	Perceived impact	105	ρ = 0.111	[−0.102, 0.315]	0.260
Mean SPI comparison	High environmental orientation vs. remaining respondents	28 vs. 77	Difference = 0.179	[−0.727, 1.084]	0.697
Low sustainable preference	High environmental orientation vs. remaining respondents	28 vs. 77	32.14% vs. 20.78%	[15.88%, 52.35%] vs. [12.37%, 31.54%]	0.300

Source: own compilation. Note: SPI denotes the Sustainable Preference Index, ranging from 0 to 8. High environmental orientation corresponds to responses of “Considerably” or “Very much.” Low sustainable preference was defined as fewer than four sustainable choices. Bias-corrected bootstrap confidence intervals for Spearman coefficients were calculated using 2000 replications. The mean difference was estimated as high environmental orientation minus the remaining respondents using heteroskedasticity-robust standard errors. Confidence intervals for group proportions are exact binomial intervals, and their association was assessed using the two-sided Fisher’s exact test. All tests were two-tailed.

4.5. Multivariate Models

The baseline OLS model (Table 10) was not globally significant (R² = 0.024; p = 0.692). Environmental values, credibility, and perceived impact all had positive coefficients, but all confidence intervals included zero. Adding age, gender, university education, and prior fund experience increased R² to 0.089 but did not produce significant predictors. The coefficients for the three main attitudes remained positive and imprecisely estimated.

Table 10. Robust linear models of preference for SDG 15-linked funds.

Model	Variable	Coefficient	Standard Error	95% CI	p-Value
Model 1	Environmental values	0.165	0.235	[−0.301, 0.631]	0.484
	Credibility	0.031	0.240	[−0.446, 0.508]	0.897
	Perceived impact	0.145	0.242	[−0.335, 0.625]	0.550
Model 2	Environmental values	0.154	0.267	[−0.377, 0.685]	0.566
	Credibility	0.236	0.243	[−0.247, 0.718]	0.334
	Perceived impact	0.196	0.255	[−0.311, 0.703]	0.444
	Age	0.018	0.016	[−0.014, 0.051]	0.261
	Female	−0.218	0.407	[−1.027, 0.592]	0.594
	University education	0.312	0.414	[−0.510, 1.134]	0.452
	Prior investment fund experience	0.303	0.370	[−0.432, 1.039]	0.415
Model 3	Mean-centered environmental values	0.152	0.266	[−0.377, 0.681]	0.569
	Mean-centered credibility	0.254	0.242	[−0.227, 0.734]	0.298
	Mean-centered perceived impact	0.228	0.253	[−0.274, 0.730]	0.369
	Environmental values × credibility	−0.174	0.196	[−0.564, 0.216]	0.378
Model 4	Mean-centered environmental values	0.159	0.268	[−0.375, 0.692]	0.556
	Mean-centered credibility	0.229	0.243	[−0.254, 0.711]	0.349
	Mean-centered perceived impact	0.180	0.246	[−0.309, 0.669]	0.467
	Environmental values × perceived impact	0.062	0.188	[−0.311, 0.436]	0.742

Source: own compilation. Note: The dependent variable is the Sustainable Preference Index, measured as the number of SDG 15-linked alternatives selected across the eight investment scenarios. The models were estimated using ordinary least squares with heteroskedasticity-robust standard errors. Model 1 includes the three main explanatory variables. Model 2 adds age, gender, university education, and prior investment fund experience. Models 3 and 4 include the corresponding interaction terms and the control variables from Model 2. Model 1: N = 105, R² = 0.024, model p = 0.692. Models 2–4: N = 97. CI denotes confidence interval. All statistical tests were two-tailed.

Neither moderation hypothesis was supported. The values × credibility interaction was negative (b = −0.174, p = 0.378), while the values × perceived-impact interaction was small and positive (b = 0.062, p = 0.742). Marginal effects of environmental values were not significant at low, medium, or high levels of either moderator.

4.6. Descriptive Differences Across Return–Risk Scenario Groups

The clearest descriptive differences in sustainable choice appeared across the three predefined return–risk scenario groups (Table 11). When the SDG 15-linked alternative simultaneously offered higher expected return and lower risk, it was selected in 67.62% of decisions. The corresponding shares were 46.03% in the lower-return/lower-risk group and 39.05% in the higher-return/higher-risk group. A choice-level logistic comparison with standard errors clustered by participant identified significant overall differences among these scenario groups (Wald χ²(2) = 32.12, p < 0.001).

Table 11. Sustainable choice by return–risk combination.

Characteristics of the Sustainable Alternative	Sustainable Choices	Total Decisions	Percentage	95% CI
Higher return and lower risk	142	210	67.62	[59.34, 75.90]
Lower return and lower risk	145	315	46.03	[39.45, 52.61]
Higher return and higher risk	82	210	39.05	[32.83, 45.27]
Both alternatives linked to SDG 15	86	105	81.90	Not included in the main comparison

Source: own compilation. Note: The confidence intervals for the first three groups were obtained from predicted probabilities estimated using a choice-level logistic model with standard errors clustered at the participant level. Clustering accounts for repeated decisions by the same respondent but does not control for unobserved differences between the fixed scenarios. The scenario containing two SDG 15-linked alternatives is reported separately and was excluded from the main grouped comparison. The results represent descriptive differences between scenario groups and should not be interpreted as independent return or risk effects. CI denotes confidence interval.

Relative to the higher-return/lower-risk scenario group, the predicted probability of selecting the sustainable alternative was 21.6 percentage points lower in the lower-return/lower-risk group and 28.6 points lower in the higher-return/higher-risk group (Table 12). Both descriptive contrasts were statistically significant at p < 0.001. The 7.0-point difference between the latter two groups was not statistically significant (p = 0.150). Because return and risk varied simultaneously across fixed scenarios, and other scenario-specific differences may remain, these comparisons do not identify the independent effect of either financial attribute.

Table 12. Pairwise comparisons of predicted probabilities of sustainable choice.

Comparison	Probability Difference	Standard Error	95% CI	p-Value
Lower return and lower risk vs. higher return and lower risk	−0.216	0.050	[−0.314, −0.118]	<0.001
Higher return and higher risk vs. higher return and lower risk	−0.286	0.048	[−0.379, −0.192]	<0.001
Higher return and higher risk vs. lower return and lower risk	−0.070	0.049	[−0.165, 0.025]	0.150

Source: own compilation. Note: Differences are expressed in probability points and were calculated by subtracting the predicted probability of the reference category, shown after “vs.”, from that of the first category. Standard errors were clustered at the participant level. CI denotes confidence interval. All tests were two-tailed.

4.7. Hypothesis Summary

As summarized in Table 13, H1, H2, H3, H4, and H5 were not supported. H6 received descriptive but not inferential support. H7 received limited descriptive support because sustainable-choice frequencies were lower in the two less favorable scenario groups than in the higher-return/lower-risk group. However, the design did not identify separate return or risk effects.

Table 13. Summary of hypothesis tests.

Hypothesis	Main Result	Conclusions
H1. Environmental values increase sustainable choice.	Positive but statistically non-significant coefficients	Not supported
H2. Credibility increases sustainable choice.	Positive but statistically non-significant coefficients	Not supported
H3. Credibility strengthens the effect of environmental values on sustainable choice.	Interaction: b = −0.174, p = 0.378	Not supported
H4. Perceived impact increases sustainable choice.	Positive but statistically non-significant coefficients	Not supported
H5. Perceived impact strengthens the effect of environmental values on sustainable choice.	Interaction: b = 0.062, p = 0.742	Not supported
H6. An attitude–behavior gap exists.	Descriptive evidence, but no statistically significant differences	Partially supported at the descriptive level
H7. Sustainable choice decreases under less favorable financial conditions.	Descriptive differences between predefined scenario groups; separate return and risk effects were not identified	Limited descriptive support

Source: own compilation. Note: The conclusions refer exclusively to the evidence obtained from the analyzed sample. “Not supported” indicates that the available evidence was insufficient to support the corresponding hypothesis; it does not demonstrate that the proposed relationship is absent from the population.

4.8. Sensitivity to Reconstructed Records

Eighteen of the 105 observations in the final analytical sample had been reconstructed following the form-export column shift. The mean Sustainable Preference Index was 4.36 among the 87 unaffected records and 4.22 among the reconstructed records. As a sensitivity analysis, the principal attitudinal models were re-estimated after excluding all reconstructed observations. Environmental values, credibility, and perceived impact remained non-significantly associated with the Sustainable Preference Index in the bivariate model and in the specification including sociodemographic controls. Thus, excluding the reconstructed observations did not alter the main conclusion concerning the absence of statistically significant attitudinal associations (Appendix A Table A2).

5. Discussion

5.1. Main Interpretation

The results reveal a separation between sustainable-finance attitudes and scenario-based investment choices. Environmental values, credibility, and perceived impact were positively related, indicating a coherent attitudinal structure. However, none of these variables significantly predicted the number of SDG 15-linked choices. By contrast, sustainable-choice frequencies differed substantially across the predefined return–risk scenario groups.

These findings do not imply that sustainability was irrelevant. Respondents selected an SDG 15-linked alternative in 54.17% of all decisions, and 76.19% made at least four sustainable choices. Nevertheless, sustainable choice was highest in scenarios in which the environmental alternative also offered higher return and lower risk. This pattern is consistent with a three-dimensional interpretation in which sustainability is considered alongside conventional financial attributes, although the design cannot identify their separate contributions (Starks, 2023; Aslan & Posch, 2022; Markowitz, 1952). The results are also consistent with evidence that investment motives and sustainability preferences interact rather than operate independently (Hinrichs & Sobol, 2024; Faradynawati & Söderberg, 2022; Kräussl et al., 2024).

5.2. Environmental Values and the Attitude–Behavior Gap

Environmental values did not significantly predict the Sustainable Preference Index. Although respondents with stronger environmental orientation made slightly more sustainable choices, the difference was small and statistically non-significant. This contrasts with evidence that investors may prefer sustainable products when environmental attributes are clearly presented or incorporated into incentivized decisions (Bauer et al., 2021; Muñoz-Muñoz et al., 2024).

The result nevertheless supports the distinction between general attitudes and context-specific behavior. Environmental values reflect a predisposition, whereas fund selection also requires investors to assess expected return, risk, credibility, and environmental impact (Aulia et al., 2024; Hinrichs & Sobol, 2024; Delsen & Lehr, 2019). In the present study, 32.14% of respondents with high environmental orientation made fewer than four sustainable choices, indicating a descriptive attitude–behavior gap. However, the absence of statistical significance means that H6 should be considered only partially supported. The findings therefore suggest that environmental concern alone may be insufficient to predict sustainable investment when financial trade-offs and uncertainty about biodiversity outcomes are explicit.

5.3. Credibility, Greenwashing, and Perceived Impact

Credibility received the lowest mean score, indicating skepticism about whether sustainable funds genuinely contribute to SDG 15. Although credibility was positively related to environmental values and perceived impact, it did not significantly predict sustainable choice or strengthen the effect of environmental values. Thus, H2 and H3 were not supported.

These findings may reflect the difficulty retail investors face when interpreting sustainability labels, divergent ESG ratings, and environmental-impact claims (Misiuda & Lachmann, 2022; Shi & Yao, 2025; Muñoz-Muñoz et al., 2026; Hauff, 2022). A single ESG score may also conceal heterogeneous preferences and provide limited information to investors interested in specific environmental objectives (Assaf et al., 2024). Evidence from French retail investors confirms substantial heterogeneity in how ESG attitudes relate to willingness to pay and ownership of sustainable products.

Perceived impact likewise failed to predict choice or moderate the relationship between values and behavior. Therefore, H4 and H5 were not supported. Investors may value environmental impact while remaining uncertain about the mechanisms through which purchasing a sustainable fund produces additional ecological outcomes (Heeb et al., 2023, 2025).

5.4. Scenario Differences and Sustainable Product Design

The largest descriptive differences in sustainable choice were observed across the predefined return–risk scenario groups. The SDG 15-linked alternative was selected in 67.62% of decisions in the higher-return/lower-risk group, compared with 46.03% in the lower-return/lower-risk group and 39.05% in the higher-return/higher-risk group. These patterns provide limited descriptive support for H7 and are consistent with sustainability being considered alongside conventional financial criteria. However, they do not establish that return and risk were the strongest determinants of choice (Aslan & Posch, 2022; Hinrichs & Sobol, 2024; Faradynawati & Söderberg, 2022; Markowitz, 1952).

The findings are consistent with evidence that investors’ willingness to pay for sustainable attributes is heterogeneous and depends on the financial and sustainability characteristics presented in the choice task (Mirón Sanguino et al., 2025). They should not, however, be interpreted as evidence that sustainable funds necessarily perform worse, since previous research reports mixed or favorable risk-adjusted outcomes (Abate et al., 2021; Ashwin Kumar et al., 2016; Kräussl et al., 2024). Because return and risk varied simultaneously across fixed scenarios, their individual effects cannot be separated from one another or from other scenario-specific characteristics. The results only show that SDG 15-linked choices were most frequent in the scenario group combining higher return and lower risk. Because this alternative was also financially dominant, its selection cannot be attributed specifically to sustainability and is consistent with conventional mean–variance choice.

5.5. Regulatory and Managerial Implications

SDG 15-linked funds should provide clear information on portfolio holdings, biodiversity objectives, impact indicators, engagement strategies, and verification procedures. This transparency is particularly important because ambiguous claims, selective disclosure, and opaque methodologies can increase greenwashing risk and undermine investor trust (Muñoz-Muñoz et al., 2026; Dempere et al., 2024). Regulators should therefore promote comparable biodiversity metrics and ensure that sustainability labels accurately reflect the underlying investment strategy.

Fund managers should also distinguish portfolio alignment from additional environmental impact. Holding companies associated with biodiversity protection does not necessarily demonstrate that the fund generates outcomes that would not otherwise occur. Biodiversity disclosure frameworks should consequently address dependencies, impacts, risks, and measurable nature-positive outcomes (Senanayake et al., 2024). For retail investors, this information must be accessible rather than excessively technical. Financial advisers should identify whether clients prioritize value alignment, measurable impact, or financial performance and recommend products consistent with those preferences. Improving sustainable-finance literacy may further strengthen investors’ ability to evaluate labels, risk, and impact claims (Filippini et al., 2024; Yucel et al., 2023).

5.6. Limitations and Future Research

This study has several limitations. The convenience sample was small, relatively young and educated, concentrated in smaller municipalities, and composed primarily of respondents without previous investment-fund experience, limiting the generalizability of the results to active retail investors. The cross-sectional design prevents causal interpretation, while hypothetical choices may differ from decisions involving participants’ own money. Moreover, environmental values, credibility, and perceived impact were measured using single items, which may reduce construct reliability, attenuate correlations, and limit the statistical sensitivity of the analysis. Consequently, the non-significant associations should not be interpreted as evidence that these relationships are absent from the broader population.

The scenarios did not vary return, risk, and sustainability independently; consequently, the SPI cannot distinguish an isolated sustainability preference from preferences for financially favorable alternatives, and the separate attribute effects cannot be identified. The Sustainable Preference Index also assigned equal weight to all scenarios. Future studies should use larger representative samples, validated multi-item scales, incentivized decisions, and factorial designs that vary return, risk, fees, credibility, and biodiversity impact independently. Following stated-preference guidance, future research should also improve scenario consequentiality and test for hypothetical bias (Johnston et al., 2017). Longitudinal and cross-country studies could examine whether stated preferences predict actual portfolio behavior.

5.7. Contribution to Sustainable-Finance Research

This study contributes to sustainable-finance research in three ways. First, it extends retail-investor research from general ESG products to investment funds linked specifically to biodiversity and SDG 15, an area in which measurement and impact attribution remain particularly difficult (Khan & Shehzad, 2025; Sayn-Wittgenstein et al., 2025). Second, it distinguishes mutually reinforcing attitudes from effective choices. Although environmental values, credibility, and perceived impact were positively related, they did not explain scenario-based behavior, supporting integrated approaches that consider psychological, financial, product-related, and contextual determinants simultaneously (Pasquino & Lucarelli, 2025; Li et al., 2025).

Third, the study shows that sustainability preferences are heterogeneous and conditional on product attributes (Assaf et al., 2024). The findings therefore refine the attitude–behavior gap: environmentally oriented investors are not necessarily inconsistent when they reject a sustainable product but may be responding to financial disadvantages, uncertain impact, or weak credibility. Sustainable-investment research should consequently analyze the interaction between investor characteristics, product information, and financial trade-offs rather than treating environmental attitudes as sufficient predictors of choice.

6. Conclusions

This study examined whether environmental values, sustainable-fund credibility, perceived individual impact, return, and risk explain preferences for investment funds linked to SDG 15. Among 105 respondents facing eight investment scenarios, the mean number of sustainable choices was 4.33, representing 54.17% of all decisions. Environmental values, credibility, and perceived impact were positively associated with one another, but none significantly predicted effective sustainable choice. The proposed moderating effects of credibility and perceived impact were also unsupported.

The clearest descriptive differences appeared across the predefined return–risk scenario groups. Sustainable choice reached 67.62% in the higher-return/lower-risk group, compared with 46.03% in the lower-return/lower-risk group and 39.05% in the higher-return/higher-risk group. These findings provide limited descriptive support for H7. Because return and risk varied simultaneously across fixed scenarios, the analysis cannot identify their separate effects or establish their relative importance as determinants of choice.

From a theoretical perspective, the findings are compatible with sustainability being considered as an additional dimension of investment choice alongside return and risk. However, the design does not allow the separate contribution of each dimension to be identified. From a practical perspective, mobilizing retail savings toward terrestrial ecosystems requires more than a sustainability label. Funds should combine competitive financial characteristics with credible biodiversity objectives, transparent portfolio information, comparable impact indicators, and a clear explanation of how investment decisions may contribute to real-world environmental outcomes (Senanayake et al., 2024).

The findings are exploratory and should be interpreted considering the small, non-probabilistic sample, the hypothetical choices, and the absence of independent variation in return, risk, and sustainability. Future research should use larger representative samples, incentivized choices, and experimental designs that vary financial attributes, credibility, and biodiversity impact independently (Johnston et al., 2017). Longitudinal evidence would also help determine whether stated preferences are reflected in actual portfolio decisions.