Capital Allocation and Sustainable Rural Development in Emerging Markets: A Multi-Criteria Analysis of Investment Priorities

1. Introduction

The increasing urgency of climate change, environmental degradation, and socio-economic inequality has placed sustainable finance at the center of global development agendas. In emerging markets, where structural constraints and development gaps remain pronounced, the allocation of financial resources plays a decisive role in shaping long-term growth trajectories. Sustainable finance is no longer confined to environmental objectives alone. It encompasses a broader effort to align capital flows with economic resilience, social inclusion, and institutional stability (UNEP, 2016; OECD, 2020). Despite this conceptual expansion, a persistent question remains: to what extent do actual investment decisions reflect these multidimensional objectives?

This question is particularly relevant in the context of rural development. Rural areas in emerging markets are characterized by a dual reality. On one hand, they face significant challenges, including limited infrastructure, constrained access to finance, institutional fragility, and heightened exposure to climate risks (World Bank, 2019). On the other hand, they offer substantial opportunities for sustainable transformation through sectors such as renewable energy, sustainable agriculture, and tourism-based activities. These sectors not only contribute to economic diversification but also generate employment, preserve ecosystems, and strengthen local communities. Recent cross-country analyses highlight persistent disparities in rural development performance and structural constraints across regions (Chen et al., 2025), reinforcing the need for more targeted and context-sensitive investment frameworks.

However, empirical evidence suggests that investment flows into rural areas remain uneven and often misaligned with development needs. Capital tends to concentrate in projects that are scalable, capital-intensive, and compatible with standardized financial instruments, while locally embedded and socially oriented activities receive comparatively less attention. This pattern reflects a broader tension within sustainable finance: the coexistence of market-driven investment logic and policy-driven development objectives.

The literature on sustainable finance has extensively explored macro-level dynamics, including climate-aligned investment, ESG integration, and regulatory frameworks. At the same time, research on rural development and tourism has emphasized sustainability outcomes, such as environmental protection and community well-being (Sharpley, 2002; Lane & Kastenholz, 2015). Yet, there remains a limited understanding of the decision-making mechanisms that connect these two domains, particularly at the level of investment selection. In other words, while we know what sustainable development should achieve, we know far less about how investors actually prioritize among competing options in practice.

Recent advances in multi-criteria decision-making (MCDM) provide a promising avenue for addressing this gap. Systematic reviews highlight the growing use of MCDM approaches in sustainability analysis, particularly for integrating economic, environmental, and social criteria into coherent evaluation frameworks (Kandakoglu et al., 2019; Yuan et al., 2022). These methods are especially relevant in contexts where decisions involve trade-offs among heterogeneous objectives and incomplete information, which are typical characteristics of rural investment environments (Gebre et al., 2021).

Among these approaches, the Analytic Hierarchy Process (AHP) has emerged as one of the most widely applied tools due to its flexibility, transparency, and ability to incorporate expert judgment (Saaty, 1987; Ishizaka & Labib, 2011). AHP has been successfully applied in various domains, including infrastructure planning, environmental management, and investment evaluation (Mardani et al., 2015). In rural development contexts, it has been used to prioritize livelihood strategies and assess regional sustainability (Baffoe, 2019; Jež Rogelj et al., 2024). However, existing applications largely focus on development outcomes or policy evaluation, rather than on investor behavior and capital allocation decisions. This perspective is consistent with recent work linking capital accumulation dynamics with sustainable development outcomes in resource-dependent economies (Shi & Xu, 2023).

This distinction is crucial. Investment decisions are not neutral; they reflect underlying preferences, risk perceptions, and institutional constraints. Studies applying AHP to investment problems, particularly in energy and infrastructure sectors, demonstrate that financial performance and risk considerations often dominate decision-making processes (Saracoglu, 2015; Nguyen et al., 2023). At the same time, recent contributions emphasize the integration of environmental, social, and governance (ESG) criteria into multi-criteria investment models (Lombardi Netto et al., 2026), suggesting a gradual shift toward more holistic evaluation frameworks.

Nevertheless, the extent to which such frameworks alter actual investment priorities remains contested. On one side of the debate, proponents of ESG integration argue that incorporating sustainability criteria into financial decision-making will naturally redirect capital toward environmentally and socially beneficial activities. On the other side, critics point to persistent market failures – such as short-termism, risk aversion, and information asymmetries – that may limit the effectiveness of these approaches, particularly in emerging markets (OECD, 2020). This divergence highlights the need for empirical analysis that explicitly captures the interaction between financial and non-financial criteria in investment decisions.

In parallel, sector-specific studies provide additional insights into the dynamics of rural investments. Research on agro-based industries and rural economies indicates that while these sectors play a vital role in employment generation and local development, they often face structural disadvantages in attracting private capital due to lower profitability and higher perceived risks (Kumar, 2024). Similarly, evaluations of rural financing mechanisms reveal inefficiencies and mismatches between funding allocation and development outcomes, underscoring the need for more targeted and performance-oriented approaches (ECA, 2018). Sustainable investment strategies increasingly emphasize the integration of financial, environmental, and social objectives, particularly in the context of rural development and emerging markets (Scarlet, 2024).

Within this context, tourism represents a particularly interesting domain. Rural and nature-based tourism has been widely recognized as a driver of sustainable development, offering opportunities for income diversification, cultural preservation, and environmental conservation. However, tourism investments vary significantly in their characteristics, ranging from capital-intensive infrastructure projects to small-scale, community-based initiatives. Understanding how investors prioritize among these alternatives is essential for designing effective policy interventions.

Building on these insights, this study aims to contribute to the literature by explicitly modeling investment decision-making in rural development using a multi-criteria framework. The central objective is to examine how different criteria – financial, environmental, social, infrastructural, and institutional – influence the prioritization of investment options.

Despite the growing literature on sustainable finance, rural development, and multi-criteria decision-making, limited research has examined how alternative weighting structures influence investment prioritization in emerging markets. Existing AHP-based studies largely focus on project evaluation, sectoral assessments, or local development planning, while insufficient attention has been devoted to the structural relationship between investor preferences and policy-driven sustainability objectives. This study addresses that gap by integrating sustainable finance perspectives with multi-criteria investment analysis and introducing a comparative scenario framework that evaluates how investor-oriented and policy-oriented priorities shape capital allocation outcomes. By doing so, the study contributes to the literature on sustainable finance and rural transformation by identifying areas of convergence and divergence between market-based and development-oriented investment strategies.

Investment decisions are traditionally explained through risk-return frameworks, which assume that investors allocate capital toward projects offering the most attractive combination of expected returns and acceptable levels of risk. Although sustainable finance has expanded the range of decision criteria by incorporating environmental, social, and governance considerations, empirical evidence suggests that financial performance and risk assessments continue to dominate investment behavior, particularly in emerging markets characterized by institutional uncertainty and resource constraints (Markowitz, 1952; OECD, 2020; Shi & Xu, 2023). Consequently, investment alternatives generating broader social and environmental benefits may receive lower priority when evaluated through conventional investment logic. The analysis is guided by the following hypothesis (H1): Investment priorities in sustainable rural development are predominantly shaped by financial and risk-related considerations, resulting in higher rankings for economically efficient investment alternatives compared to alternatives generating primarily social and environmental benefits.

To test this hypothesis, the study applies an AHP-based model to evaluate six representative investment alternatives: eco-tourism, agro-tourism, renewable energy, digital tourism platforms, sustainable agriculture, and cultural heritage tourism. These alternatives capture a broad spectrum of rural development pathways, ranging from technology-driven and capital-intensive investments to locally embedded and community-oriented activities.

The contribution of this paper is threefold. First, it provides a methodologically rigorous framework for analyzing investment allocation decisions in a sustainability context, integrating multiple criteria within a coherent structure. Second, it offers empirical evidence on the relative importance of different decision criteria, shedding light on the underlying drivers of investor behavior. Third, through a comparative scenario analysis, it demonstrates how changes in weighting structures – reflecting policy priorities – can significantly alter investment rankings.

This comparative perspective is particularly important, as it highlights the potential divergence between market-based allocation and policy objectives. By contrasting investor-driven and policy-oriented scenarios, the study provides insights into the extent to which current investment patterns align with sustainable development goals.

Rather than focusing on a specific country or investment portfolio, this study adopts a broader emerging-market perspective. The objective is to identify general patterns in investment prioritization that may be relevant across different institutional and development contexts. Such an approach allows for the examination of structural relationships between financial, environmental, social, and institutional criteria that frequently characterize investment decisions in emerging economies.

Furthermore, the paper builds on recent work in multi-criteria investment analysis, including applications in consumer behavior and green investment prioritization (Šostar & Ristanović, 2023; Ristanović et al., 2024), extending these approaches to the domain of rural development. In doing so, it contributes to a growing body of literature that seeks to operationalize sustainability within decision-making processes.

The remainder of the paper is structured as follows. Section 2 presents the methodological framework, including the AHP model and expert panel design. Section 3 reports the empirical results, including the baseline analysis and scenario comparison. Section 4 discusses the implications of the findings in relation to the research hypothesis and existing literature. The final section concludes with policy recommendations and directions for future research.

2. Methodology

2.1. Analytical Framework

To examine how investment decisions in rural development are formed under multiple and potentially conflicting objectives, this study employs the Analytic Hierarchy Process (AHP). This method is widely used in multi-criteria decision-making due to its ability to structure complex problems, incorporate qualitative and quantitative factors, and derive consistent priority weights from expert judgments (Saaty, 1987; Saaty, 2008; Ishizaka & Labib, 2011).

AHP is particularly suitable in the context of sustainable finance, where investment decisions are influenced not only by financial considerations but also by environmental, social, and institutional dimensions. Unlike single-criterion approaches, AHP enables the explicit modeling of trade-offs among heterogeneous criteria, making it well suited for analyzing capital allocation in rural development settings.

Classical AHP was selected because it provides a transparent and widely accepted framework for structuring complex investment decisions and deriving priorities from expert judgments. While advanced approaches such as Fuzzy AHP, TOPSIS, VIKOR, and Best-Worst Method (BWM) may further address uncertainty and ranking robustness, the objective of this study was to establish a clear and interpretable decision structure suitable for comparing investment priorities across multiple sustainability dimensions.

The decision problem is hierarchically structured into three levels. The first is the new objective (goal), where the most desirable investment alternative is selected. The second level is the criteria, which represent the key dimensions that influence investment decisions. The third level is the alternatives that become available options for rural investments. This hierarchical structure ensures transparency and allows for a systematic evaluation of both criteria and alternatives. This approach enables the integration of financial and non-financial dimensions, which is essential in evaluating sustainability-oriented investments (Triantaphyllou, 2000). Recent applications further demonstrate the relevance of AHP in agricultural and rural investment contexts, including strategic site selection and innovation planning (Roa-Ortiz et al., 2026).

2.2. Model Specification

Based on the literature on sustainable finance, rural development, and investment decision-making (OECD, 2020; World Bank, 2019; Mardani et al., 2015), six criteria were selected (Table 1): Financial performance (F1), Risk and resilience (F2), Infrastructure and accessibility (F3), Environmental sustainability (F4), Social impact (F5), and Institutional feasibility (F6). These criteria capture both market-based investment logic (F1, F2) and policy-oriented sustainability dimensions (F4, F5), while also accounting for structural constraints (F3, F6).

The six investment alternatives were selected based on their frequent appearance in the literature on sustainable rural development, sustainable finance, and rural transformation strategies. Eco-tourism, agro-tourism, and cultural tourism represent tourism-based development pathways that promote local employment, territorial identity, and income diversification. Renewable energy reflects the growing importance of climate-aligned investments and green infrastructure in emerging economies. Digital tourism captures the role of digitalization, innovation, and technology-enabled service delivery in rural areas. Sustainable agriculture was included due to its central contribution to food security, environmental stewardship, and rural livelihoods. Collectively, these alternatives represent distinct yet complementary approaches to achieving sustainable rural development and provide a suitable basis for comparing investment priorities across multiple sustainability dimensions.

Six investment alternatives were selected to reflect typical rural development pathways observed in emerging markets: Eco-tourism (A1), Agro-tourism (A2), Renewable energy projects (A3), Digital tourism platforms (A4), Sustainable agriculture (A5), and Cultural tourism (A6). These alternatives differ in terms of capital intensity, scalability, risk profile, and contribution to sustainability objectives, making them suitable for comparative evaluation.

2.3. Pairwise Comparison and Weight Derivation

The relative importance of criteria and alternatives was assessed using pairwise comparison matrices based on the Saaty (1987) fundamental scale, ranging from 1 (equal importance) to 9 (extreme importance).

For each matrix, the priority vector w was derived using the principal eigenvector method (Equation 1):

$$A\bullet w={\lambda }_{max}\bullet w$$

(1)

, where:

• A is the comparison matrix
• w is the vector of weights
• λ max is the maximum eigenvalue

This approach ensures a consistent estimation of relative priorities across all elements.

2.4. Consistency Assessment

To evaluate the reliability of expert judgments, the consistency of each pairwise comparison matrix was tested using the Consistency Index (CI) and Consistency Ratio (CR), in Equations 2 and 3:

$$CI={\displaystyle \frac{{\lambda }_{max}-n}{n-1}}$$

(2)

$$CR={\displaystyle \frac{CI}{RI}}$$

(3)

, where:

• n is the number of elements
• RI is the Random Index

A threshold of CR < 0.10 was applied, consistent with standard AHP practice (Saaty, 1987). All matrices in this study satisfy this condition, indicating acceptable consistency.

2.5. Aggregation Procedure

The overall priority of each alternative was calculated using a linear aggregation approach (Equation 4):

$$P_j={\displaystyle {\sum }_{i=1}^n}{w}_i\bullet a_{ij}$$

(4)

, where:

• w_i is the weight of criterion i
• a_ij is the local priority of alternative j under criterion i

This procedure yields a global ranking of alternatives based on the combined influence of all criteria.

2.6. Expert Panel and Data Collection

The pairwise comparison matrices were constructed based on expert judgments obtained through a structured elicitation process. In line with established practice in Analytic Hierarchy Process applications, a purposive sampling approach was employed to ensure the relevance and reliability of inputs.

The expert panel consisted of eight specialists selected through purposive sampling based on their demonstrated expertise in sustainable finance, rural development, tourism, agriculture, renewable energy, public policy, and investment analysis. All experts possessed substantial professional experience and direct involvement in policy design, project implementation, academic research, or investment evaluation related to sustainable development. The use of a multidisciplinary panel was intended to capture diverse perspectives and reduce sector-specific bias. While expert-based approaches inevitably involve subjective judgment, consistency testing was applied to assess the reliability of pairwise comparisons, and the inclusion of experts from different professional backgrounds helped mitigate the risk of individual dominance or disciplinary bias. Detailed information on the composition of the expert panel is provided in Appendix A.

Pairwise comparisons were collected using a structured questionnaire based on the Saaty scale (1-9). Experts independently assessed both the relative importance of criteria and the performance of alternatives. To enhance consistency, standardized guidance was provided, and responses were reviewed for logical coherence.

Individual judgments were aggregated using the geometric mean, preserving the reciprocal properties of the comparison matrices and ensuring methodological consistency in group decision-making.

A summary of the expert panel is provided in Appendix A (Table A1), while detailed selection criteria and additional information are available in the Supplementary Material, ensuring transparency and reproducibility.

2.7. Scenario Design

To assess the sensitivity of results to changes in decision priorities, a comparative scenario analysis was conducted. Two scenarios were defined:

• Investor-oriented scenario (baseline). Weights derived directly from expert judgments, reflecting prevailing investment logic dominated by financial performance and risk considerations.
• Policy-oriented scenario. Adjusted weights reflecting sustainability-oriented priorities, with increased emphasis on environmental (F4) and social (F5) criteria, and reduced emphasis on financial performance (F1).

To evaluate the sensitivity of investment outcomes to alternative decision priorities, a policy-oriented scenario was developed and compared with the baseline investor-oriented scenario. The resulting ranking shifts provide an additional robustness assessment by examining how changes in criteria weights affect investment preferences.

The policy scenario reflects a reweighting consistent with sustainability-oriented policy frameworks, enabling comparison between market-driven and development-oriented allocation logics.

The methodological contribution of this study lies in combining a structured AHP framework, a multi-stakeholder expert panel and a comparative scenario analysis. This integrated approach allows for a more nuanced understanding of investment decision-making processes, bridging the gap between financial evaluation and sustainability-oriented policy analysis.

3. Results

3.1. Criteria Weights and Consistency Analysis

The priority weights of the decision criteria were derived using the principal eigenvector method within the Analytic Hierarchy Process framework. The results indicate a strong dominance of financial and risk-related criteria, confirming the central role of traditional investment logic in rural development financing.

Financial performance (F1) receives the highest weight (0.445), followed by risk and resilience (F2) (0.226). Together, these two criteria account for approximately 67% of total decision weight, highlighting the predominance of profitability and risk considerations in investment decision-making. Infrastructure and accessibility (F3) hold a moderate position (0.120), while environmental sustainability (F4) (0.097), institutional feasibility (F6) (0.070), and social impact (F5) (0.042) receive comparatively lower weights.

Table 2. Criteria Weights and Consistency Indicators.

Criterion	Weight (Eigenvector)	Consistency Indicators
F1 Financial Performance	0.445	λmax (max eigenvalue) = 6.042
F2 Risk & Resilience	0.226	CI (Consistency Index) = 0.008
F3 Infrastructure	0.120
F4 Environmental	0.097	RI (Random Index, n=6) = 1.24
F6 Institutional	0.070	CR (Consistency Ratio) = 0.007
F5 Social	0.042

Source: Authors’ calculation. Note: The consistency ratio (CR) is below the acceptable threshold of 0.10, indicating a high level of consistency in expert judgments within the Analytic Hierarchy Process framework.

Table 2. Criteria Weights and Consistency Indicators.

Criterion	Weight (Eigenvector)	Consistency Indicators
F1 Financial Performance	0.445	λmax (max eigenvalue) = 6.042
F2 Risk & Resilience	0.226	CI (Consistency Index) = 0.008
F3 Infrastructure	0.120
F4 Environmental	0.097	RI (Random Index, n=6) = 1.24
F6 Institutional	0.070	CR (Consistency Ratio) = 0.007
F5 Social	0.042

Source: Authors’ calculation. Note: The consistency ratio (CR) is below the acceptable threshold of 0.10, indicating a high level of consistency in expert judgments within the Analytic Hierarchy Process framework.

The results provide initial support for the study hypothesis. Financial Performance (44.5%) and Risk & Resilience (22.6%) jointly account for 67.1% of total decision weight, substantially exceeding the combined importance assigned to environmental, social, and institutional dimensions. This weighting structure indicates that investment priorities remain strongly influenced by traditional financial considerations.

The consistency of the pairwise comparison matrix is confirmed by a maximum eigenvalue of λmax = 6.042, resulting in a consistency index (CI) of 0.01 and a consistency ratio (CR) of 0.007. This value is well below the acceptable threshold (CR < 0.10), indicating a high level of internal consistency and reliability in the expert evaluations.

3.2. Alternative Performance Across Criteria

The evaluation of alternatives across individual criteria reveals clear and consistent patterns, reflecting the multidimensional nature of investment decision-making (Table 3).

Under the Financial Performance (F1) criterion (CR = 0.023), renewable energy projects (A3) achieve the highest weight (0.350), followed by digital tourism platforms (A4) (0.216). Eco-tourism (A1) ranks third (0.153), while sustainable agriculture (A5), cultural tourism (A6), and agro-tourism (A2) follow with lower values. This distribution indicates a strong preference for scalable, capital-intensive investments with higher expected returns, while more localized and smaller-scale activities are less competitive.

A similar ranking structure emerges under the Risk and Resilience (F2) criterion (CR = 0.040). Renewable energy (0.313) and digital tourism (0.236) dominate, reflecting their perceived stability and resilience. Eco-tourism (0.161) occupies a middle position, while agro-tourism (0.117), sustainable agriculture (0.094), and cultural tourism (0.079) are considered relatively more exposed to uncertainty. These results suggest that technologically driven and standardized investments are perceived as less risky.

In terms of the Infrastructure and Accessibility (F3) criterion (CR = 0.015), digital tourism platforms (0.317) outperform all other alternatives, reflecting their limited dependence on physical infrastructure. Renewable energy (0.248) ranks second, while eco-tourism (0.155) and other alternatives lag behind. This highlights the importance of infrastructure constraints in shaping investment attractiveness, particularly in rural areas.

Under the Environmental Sustainability (F4) criteria (CR = 0.028), renewable energy (0.332) maintains its leading position, followed by sustainable agriculture (0.196) and agro-tourism (0.182). Cultural tourism (0.109), digital tourism (0.092), and eco-tourism (0.089) show lower contributions. This shift indicates that nature-based and resource-efficient activities perform better when environmental priorities are emphasized.

The ranking under the Social Impact (F5) criteria (CR = 0.013) mirrors the environmental dimension. Renewable energy (0.323) remains dominant, followed by sustainable agriculture (0.199) and agro-tourism (0.186). Cultural tourism and eco-tourism show moderate performance, while digital tourism ranks lowest (0.083). These results reflect the strong local development potential of agriculture- and community-based activities.

Under the Institutional Feasibility (F6) criterion (CR = 0.012), renewable energy (0.321) and digital tourism (0.226) again achieve the highest scores. Eco-tourism (0.168) follows, while other alternatives show lower values. This suggests that projects aligned with established regulatory frameworks and financing mechanisms are more attractive to investors.

3.3. Cross-Criteria Comparison

A comparison across all criteria reveals a consistent pattern:

• Renewable energy (A3) ranks first or second across all criteria
• Digital tourism (A4) performs strongly in financial, infrastructure, and institutional dimensions
• Agro-tourism (A2) and sustainable agriculture (A5) perform well in environmental and social dimensions but lag in financial and risk criteria
• Eco-tourism (A1) and cultural tourism (A6) occupy intermediate positions

This distribution reflects a clear distinction between:

• market-oriented investments (financially driven, scalable)
• development-oriented activities (locally embedded, socially beneficial)

3.4. Cross-Criteria Comparison

To assess the sensitivity of investment outcomes to changes in decision priorities, a comparative scenario analysis was conducted. The baseline scenario reflects investor-oriented preferences derived from expert-based pairwise comparisons within the Analytic Hierarchy Process framework. A second, policy-oriented scenario was constructed through a normative reweighting of criteria, placing greater emphasis on environmental sustainability and social impact while reducing the dominance of financial performance. The policy scenario reflects a reweighting consistent with sustainability-oriented policy frameworks, enabling comparison between market-driven and development-oriented allocation logics (Table 4).

The policy-oriented scenario was developed as a normative benchmark reflecting priorities frequently emphasized in sustainable development and sustainable finance frameworks. Unlike the investor-oriented scenario, which is derived directly from expert pairwise comparisons, the policy scenario assigns greater relative importance to environmental sustainability, social impact, and long-term resilience while maintaining the relevance of financial and institutional criteria. This approach is consistent with recommendations found in international policy frameworks and sustainable investment literature, which emphasize balancing economic efficiency with broader development outcomes (UNEP, 2016; OECD, 2020; Scarlet, 2024). The purpose of the scenario is not to replace investor preferences, but to assess how alternative policy priorities influence capital allocation outcomes in rural development.

The policy-oriented weights reflect widely recognized development priorities, including environmental protection, social inclusion, and long-term resilience, while maintaining the relevance of financial and institutional considerations. Importantly, the reweighting is moderate rather than extreme, ensuring that all criteria remain influential and preserving the internal balance of the decision model.

The resulting rankings differ significantly between the two scenarios investor-driven and policy-oriented scenario, as shown in Figure 1.

The comparison reveals three distinct patterns. First, renewable energy (A3) maintains its leading position across both scenarios, indicating strong performance across financial, environmental, and institutional dimensions. This confirms its role as a convergent investment category, aligned with both investor and policy priorities. Second, a clear divergence emerges for digital tourism (A4) and eco-tourism (A1), both of which decline under policy weighting. Their initial advantage is largely driven by financial and infrastructure-related criteria, which become less dominant in the policy scenario. Third, sustainable agriculture (A5) and agro-tourism (A2) experience the most significant upward shifts. These alternatives benefit from increased weighting of environmental sustainability and social impact, where they demonstrate strong relative performance. This result highlights their importance in achieving broader rural development objectives. In contrast, cultural tourism (A6) remains consistently low-ranked across both scenarios, suggesting limited competitiveness under both market-driven and policy-oriented frameworks.

The scenario analysis demonstrates that investment outcomes are highly sensitive to the underlying weighting structure. The observed shifts are not driven by changes in the intrinsic performance of alternatives, but by the relative importance assigned to evaluation criteria.

This finding reinforces the central argument of the study – capital allocation patterns in rural development are structurally shaped by decision priorities, rather than determined solely by project characteristics.

In practical terms, the results suggest that without policy intervention, investment flows are likely to remain concentrated in financially efficient and scalable sectors. Conversely, targeted policy frameworks that elevate environmental and social criteria can significantly improve the relative attractiveness of locally embedded and development-oriented activities.

4. Discussion

4.1. Evaluation of the Hypothesis

The central hypothesis of this study (H1) posits that investment decisions in rural development are primarily driven by financial performance and risk considerations, resulting in the systematic under-prioritization of projects with stronger social and environmental benefits. The empirical results provide strong support for this hypothesis.

The findings provide strong support for the study hypothesis. The dominance of Financial Performance and Risk & Resilience demonstrates that investment priorities in sustainable rural development continue to be driven primarily by economic considerations. Although sustainability-related criteria are incorporated into decision-making frameworks, their influence on final outcomes remains comparatively limited. This pattern is consistent with classical investment theory and recent evidence from sustainable finance literature emphasizing the persistent importance of risk-return considerations in capital allocation decisions (Markowitz, 1952; OECD, 2020; Shi & Xu, 2023).

The dominance of financial performance (0.445) and risk and resilience (0.226), together accounting for approximately two-thirds of total decision weight, confirms that investor preferences remain firmly anchored in traditional economic logic. This finding is consistent with classical investment theory, where decision-making is shaped by expected returns and risk minimization (Markowitz, 1952), and aligns with empirical studies applying multi-criteria approaches to investment selection (Saracoglu, 2015; Nguyen et al., 2023).

At the level of alternatives, the consistent top ranking of renewable energy and digital tourism under financial and risk criteria further reinforces this interpretation. These investment types are characterized by scalability, standardization, and compatibility with existing financial instruments, which makes them more attractive within a market-driven framework (IRENA, 2021).

Conversely, agro-tourism and sustainable agriculture – despite their strong performance in environmental and social dimensions – remain under-prioritized in the overall ranking. This outcome directly confirms the second part of H1, indicating that non-financial benefits are insufficient to offset lower profitability and higher perceived risk.

4.2. Comparison with Existing Literature

The findings are broadly consistent with the growing body of literature on multi-criteria decision-making in sustainability contexts. Systematic reviews highlight that while MCDM methods enable the inclusion of diverse criteria, the resulting rankings often remain sensitive to the weighting structure, particularly when financial criteria dominate (Kandakoglu et al., 2019; Yuan et al., 2022).

In rural development research, studies applying AHP have typically emphasized the importance of social and environmental factors in shaping sustainable outcomes (Baffoe, 2019; Jež Rogelj et al., 2024). However, these studies often adopt a policy-oriented perspective, implicitly assuming that sustainability criteria should carry greater weight. The present analysis differs by explicitly modeling investor-driven preferences, thereby revealing a divergence between normative and actual decision structures.

This divergence is also reflected in sector-specific studies. Research on agro-based industries indicates that such sectors face persistent challenges in attracting private investment due to structural disadvantages, including lower margins and higher uncertainty (Kumar, 2024). Similarly, evaluations of rural financing mechanisms point to inefficiencies in resource allocation and a lack of alignment with development outcomes (ECA, 2018).

In the context of sustainable finance, recent contributions have emphasized the integration of environmental, social, and governance (ESG) criteria into investment decisions (Lombardi Netto et al., 2026; Thanh et al., 2025). While these frameworks represent an important step toward more holistic evaluation, the present results suggest that ESG integration does not automatically translate into a reordering of investment priorities, unless accompanied by a substantive shift in weighting structures.

The findings also resonate with previous paper (Šostar & Ristanović, 2023; Ristanović et al., 2024), which demonstrate the applicability of AHP in capturing decision-making behavior in both consumer and investment contexts. Extending this line of research, the current study shows how similar methodological approaches can be used to uncover structural biases in capital allocation. Also, these findings are consistent with recent applications of AHP in rural development contexts, which emphasize the importance of structured decision-making in agricultural innovation and investment planning (Roa-Ortiz et al., 2026).

4.3. Insights from Scenario Analysis

The introduction of a policy-oriented scenario provides additional insight into the dynamics of investment decision-making. By rebalancing criteria weights toward environmental sustainability and social impact, the scenario effectively simulates a decision environment aligned with public policy objectives.

The resulting shifts in rankings are both substantial and revealing. Sustainable agriculture and agro-tourism move from lower positions under the investor scenario to higher positions under the policy scenario, while digital tourism experiences a notable decline. These changes confirm that investment outcomes are highly sensitive to the prioritization of criteria, rather than being solely determined by the intrinsic characteristics of the alternatives.

At the same time, renewable energy maintains its leading position across both scenarios, highlighting its role as a convergent investment category. This suggests that certain types of investments can simultaneously satisfy financial, environmental, and policy objectives, making them particularly attractive in both market and policy contexts.

The scenario analysis thus reinforces a key insight – the observed allocation of capital is not an inevitable outcome, but a function of the underlying decision framework.

4.4. Structural Misalignment and Its Implications

Taken together, the results point to a structural misalignment between investor-driven capital allocation and sustainable rural development objectives. While policy frameworks emphasize inclusiveness, environmental protection, and long-term resilience, investor preferences continue to favor projects that are scalable, standardized, and financially efficient. This aligns with broader discussions on sustainable investment strategies, which highlight the need to reconcile financial performance with long-term development objectives (Scarlet, 2024). The observed misalignment between capital allocation and development outcomes is consistent with global evidence on structural barriers in rural development systems (Chen et al., 2025).

This mismatch reflects the higher perceived risk associated with locally rooted activities, lower short-term profitability of agricultural and community-based projects, and limited institutional capacity to support complex or small-scale investments.

These findings are consistent with broader critiques of sustainable finance, which highlight the gap between capital flows and sustainability needs, particularly in emerging markets (OECD, 2020). Importantly, the results do not suggest that investors disregard sustainability altogether. Rather, they indicate that sustainability considerations are secondary to financial criteria, unless explicitly prioritized or supported by external incentives. The under-prioritization of socially embedded activities also reflects broader challenges related to financial literacy, local capacity, and institutional support in rural areas (Kyeyune & Ntayi, 2025). The observed ranking shifts illustrate how different weighting structures can influence investment decisions, supporting the argument that capital allocation outcomes are shaped not only by project characteristics but also by the policy priorities embedded within decision frameworks.

4.5. Policy and Theoretical Implications

From a policy perspective, the findings underscore the need for targeted interventions to bridge the gap between investment behavior and development objectives. Instruments such as blended finance, public guarantees, and targeted subsidies can help reduce perceived risks and improve the financial attractiveness of socially beneficial projects.

In addition, strengthening institutional frameworks and improving access to information can enhance the feasibility of investments in rural areas. These measures are particularly important for sectors such as agro-tourism and sustainable agriculture, which demonstrate strong development potential but remain underfunded.

From a theoretical perspective, the study contributes to the literature by showing that the inclusion of sustainability criteria is not sufficient and that the relative weight of the criteria is decisive. This insight reinforces the importance of distinguishing between the formal inclusion of criteria and their effective impact on decision outcomes.

4.6. Limitations and Future Research

While the study provides valuable insights, several limitations should be acknowledged. First, the analysis is based on expert judgments, which, although carefully selected and validated, may not fully capture the diversity of investor behavior. Second, the model does not incorporate dynamic factors such as changing market conditions or policy incentives.

The findings should be interpreted as a framework-based assessment of investment priorities rather than as evidence derived from a specific national or regional investment dataset. Future research may apply the proposed framework to individual countries, regions, or sector-specific investment portfolios to assess contextual differences and improve external validity.

Future research could address the limitations by expanding the expert panel, applying other MCDM approaches (phased or hybrid), integrating data on actual investments, and/or exploring regional variations in emerging markets.

5. Conclusions

This study examined how investment decisions in rural development are shaped when financial, environmental, social, and institutional criteria are evaluated simultaneously. By applying the Analytic Hierarchy Process (AHP), the analysis provided a structured assessment of investor preferences across a diverse set of rural investment alternatives, including tourism, agriculture, and renewable energy.

The results reveal a clear hierarchy of decision priorities, with financial performance and risk considerations dominating the allocation of capital. These two criteria jointly account for the majority of decision weight, confirming that investment behavior remains largely grounded in traditional economic logic. In contrast, environmental sustainability, social impact, and institutional feasibility, although formally included in the evaluation framework, exert a comparatively limited influence on final outcomes.

At the level of alternatives, renewable energy consistently emerges as the most preferred option, reflecting its ability to combine financial viability with environmental benefits. Digital tourism also performs strongly under investor-driven conditions, particularly due to its scalability and lower dependence on physical infrastructure. In contrast, agro-tourism and sustainable agriculture – despite their substantial contributions to local development, employment, and environmental sustainability – remain under-prioritized due to lower expected returns and higher perceived risks.

The scenario analysis provides a critical extension of these findings. By introducing a policy-oriented weighting structure that places greater emphasis on environmental and social criteria, the ranking of alternatives shifts significantly. Sustainable agriculture and agro-tourism improve their positions, while digital tourism declines. Notably, renewable energy retains its leading position across both scenarios, highlighting its role as a strategically aligned investment category capable of satisfying both market and policy objectives.

These findings provide clear support for the study hypothesis. Financial performance and risk considerations dominate the investment decision process and significantly influence the ranking of investment alternatives. While sustainability criteria are formally included in the evaluation framework, they exert a comparatively weaker effect on final investment outcomes unless their importance is explicitly increased through policy intervention.

From a theoretical perspective, the study contributes to the literature by bridging sustainable finance and rural development through a decision-making lens. Rather than focusing solely on outcomes or policy frameworks, it explicitly models the process through which investment priorities are formed. This approach highlights the importance of weighting structures in shaping results and provides a more nuanced understanding of how sustainability objectives are translated into practice.

From a methodological standpoint, the study demonstrates the value of multi-criteria approaches in capturing the complexity of investment decisions in emerging markets. The integration of a structured AHP framework with scenario analysis enables a transparent comparison between investor-driven and policy-oriented perspectives, offering insights that cannot be obtained through single-criterion models.

From a policy perspective, the results point to a fundamental challenge: market-based investment mechanisms alone are unlikely to achieve balanced and inclusive rural development. Without targeted interventions, capital will continue to favor projects that are financially efficient but not necessarily aligned with broader development goals. This underscores the need for policy instruments that can adjust the risk-return profile of underfunded sectors.

In particular, mechanisms such as blended finance, public guarantees, targeted subsidies, and technical assistance can play a critical role in improving the attractiveness of investments in agro-tourism, sustainable agriculture, and other locally embedded activities. Strengthening institutional capacity and regulatory frameworks can further enhance investment feasibility and reduce perceived risks.

At the same time, the identification of renewable energy as a convergent investment category suggests that policy efforts should also focus on scaling sectors that naturally align financial and sustainability objectives. Such sectors can serve as anchors for broader development strategies, facilitating the transition toward more sustainable and resilient rural economies. Although the panel was intentionally diversified across sectors and expertise areas, the findings remain dependent on expert judgment and should be interpreted as a structured assessment of priorities rather than a direct representation of all investor or policy-maker preferences in emerging markets.

Despite its contributions, the study has certain limitations. The reliance on expert-based judgments, while methodologically justified, may not fully capture the diversity of real-world investment behavior. In addition, the static nature of the model does not account for evolving market conditions or policy changes. Future research could address these limitations by incorporating dynamic data, expanding the range of stakeholders, and applying hybrid or fuzzy multi-criteria approaches. Also, future research may extend the present framework by integrating alternative multi-criteria decision-making techniques, including Fuzzy AHP, TOPSIS, VIKOR, or BWM, to further examine ranking stability and uncertainty in expert evaluations. Such approaches may provide additional insights into investment prioritization under varying decision environments and institutional contexts.

Finally, the study highlights a central tension in sustainable finance, as aligning capital allocation with sustainability goals requires not only the inclusion of environmental and social criteria, but also a fundamental rebalancing of priorities in decision-making.

Only by addressing this structural dimension can investment strategies in emerging markets effectively support rural development pathways that are economically viable, socially inclusive, and environmentally sustainable in the long term.

Appendix A.1

This appendix provides a concise overview of the expert panel involved in the pairwise comparison process. The panel was designed to ensure a balanced representation of relevant domains, including finance, rural development, tourism, and environmental policy. All experts met the predefined selection criteria outlined in the Supplementary Material.

Table A1. Expert Panel Characteristics.

Expert ID	Sector	Experience (years)
E1	Finance / Investment	15
E2	Rural Development Policy	12
E3	Tourism Development	10
E4	Environmental Policy	14
E5	Sustainable Finance	11
E6	Agriculture / Rural Economy	13
E7	Public Administration	9
E8	International Development	16

Note: Expert identities are anonymized to ensure confidentiality and to minimize potential bias. The distribution reflects a multi-stakeholder structure combining academic, policy, and practitioner perspectives.

Table A1. Expert Panel Characteristics.

Expert ID	Sector	Experience (years)
E1	Finance / Investment	15
E2	Rural Development Policy	12
E3	Tourism Development	10
E4	Environmental Policy	14
E5	Sustainable Finance	11
E6	Agriculture / Rural Economy	13
E7	Public Administration	9
E8	International Development	16

Note: Expert identities are anonymized to ensure confidentiality and to minimize potential bias. The distribution reflects a multi-stakeholder structure combining academic, policy, and practitioner perspectives.