The issue of determining the fair value of shares has become particularly significant in Ukraine since 2017, following the large-scale implementation of mandatory buyout procedures of minority shareholders’ shares by majority shareholders (squeeze-out). In practice, these procedures have generated numerous disputes due to the substantial undervaluation of buyout prices. Such problems are largely caused by imperfections in national legislation and by the possibility of manipulating valuation methodologies in favor of controlling shareholders. According to Ukrainian national valuation standards, three main methodological approaches are used in property valuation: the asset-based approach, the income approach, and the market (comparative) approach. However, in practical valuation reports prepared for squeeze-out procedures, the asset-based approach is often disregarded, typically justified by the alleged lack of necessary accounting information or by claims regarding the priority of the income approach. This practice creates opportunities for significant underestimation of the fair value of shares. An analysis of judicial practice, including decisions of the Supreme Court of Ukraine, demonstrates that the asset-based approach should be applied alongside other valuation methods. Within this framework, the fair value of a share may be determined based on the company’s net asset value divided by the total number of outstanding shares. Empirical comparisons between actual squeeze-out prices and the net asset value per share reveal considerable discrepancies, confirming systematic undervaluation in a number of cases. Furthermore, large joint-stock companies in Ukraine prepare financial statements in accordance with International Financial Reporting Standards (IFRS), which require periodic revaluation of assets at fair value. Consequently, the necessary data for applying the asset-based approach are generally available in financial reporting. It is also important to emphasize that international valuation standards cannot substitute national valuation regulations, which remain legally binding for valuation activities in Ukraine. In judicial disputes related to squeeze-out procedures, courts rely primarily on forensic economic examinations rather than valuation reports commissioned by majority shareholders. Such examinations must be conducted in accordance with national valuation standards and relevant methodological guidelines for determining the value of shares. Therefore, the application of the asset-based approach in the valuation of shares during mandatory buyout procedures is essential for ensuring a fair price and protecting the rights of minority shareholders. The final valuation should be determined in accordance with the principle of the highest and best use of the enterprise as an integrated property complex.

IMF technical assistance (TA) supported the Central Bank of Seychelles (CBS) in strengthening its emergency liquidity assistance (ELA) framework and collateral policies to enhance the CBS’s liquidity backstop while safeguarding its balance sheet. ELA is a targeted, bilateral liquidity instrument distinct from standard liquidity operations, aimed at preserving or restoring financial stability while mitigating moral hazard. Built on solid legal foundations, the framework rests on a public regulation, internal procedures, and a clarified role for the fiscal authority in the provision of ELA. The TA reviewed existing ELA arrangements and highlighted the importance of a coherent and clearly articulated framework encompassing eligibility criteria, forward looking solvency and viability assessments, and well defined decision making processes. The report provided guidance on communicating the ELA framework to key stakeholders—including financial institutions, government entities, and the broader public—in ways that support effectiveness, promote sound market practices, and manage expectations. A key component of the TA addressed internal preparedness, including clearly documented procedures for assessing ELA requests, calibrating financial terms, evaluating funding plans, and designing appropriate ELA related conditionality. The TA also provided guidance on internal responsibilities and the need for effective interdepartmental coordination in conducting ELA operations. On collateral policy, the TA underscored the need to strengthen readiness for stress scenarios by enhancing operational capacity to accept, value, and manage a broader range of collateral. Through concrete case studies, the TA highlighted the importance of systematic collateral scanning, pre positioning arrangements, robust valuation methodologies, and risk based haircut calibration to contain the financial risks associated with emergency lending.

This study empirically examines the relationships among business model (BM) types, social impact efficiency, impact composition, and valuation methodologies within social ventures. Drawing on monetized performance data from 122 Korean social ventures, we explore the alignment patterns between hybrid organizational modes and social value creation. The findings reveal that BM types do not yield statistically significant differences in overall impact efficiency, suggesting that the scale of impact is driven more by the integrative density between social mission and business operations than by the outward BM form. In contrast, the composition of social impact varies systematically across BM types, as social ventures tend to concentrate on specific impact domains aligned with their underlying operational mechanisms. Furthermore, the selection of impact valuation methodologies differs by BM type, reflecting variations in how social performance is conceptualized and measured. Collectively, these results indicate that business models are not mere determinants of impact scale per se; they serve as structural frameworks that shape how social impact is structured, interpreted, and validated. By shifting the focus from simple efficiency metrics to the patterned interplay among BMs, impact composition, and valuation methodologies, this study provides a robust empirical foundation for a contingency-based perspective on social venture performance.

This study critically examines the deterministic methodology used to calculate the Net Single Premium (NSP), also referred to as Premi Tunggal Netto (PTN), for Credit Life Insurance (CLI) in the Indonesian market using the statutory Indonesian Mortality Table IV (TMI IV). The benefit structure of CLI, which is directly linked to a decreasing outstanding loan balance, necessitates the application of a Decreasing Term Assurance (DTA) framework. However, a quantitative review of commonly applied pricing practices reveals a systematic structural bias arising from the inappropriate use of a Level Term Assurance (LTA) model. Using verified actuarial inputs entry age =18, policy term =20 years, male mortality rates from TMI IV, and an inferred constant technical interest rate of approximately =7.50% the results indicate that the LTA approach overstates the required net annual premium by approximately 71.2% compared to the correct DTA valuation. This paper establishes a rigorous DTA pricing framework by explicitly incorporating the loan amortization schedule and conducts a comprehensive sensitivity analysis of the constant interest rate assumption. The findings highlight the importance of aligning premium valuation methodologies with the underlying benefit structure and suggest that reliance on generalized mortality tables alone may be insufficient for accurately capturing the risk characteristics of credit life insurance portfolios.

As a critical carbon offset mechanism, China’s Certified Emission Reduction (CCER) plays a pivotal role in achieving the “dual carbon” targets. With the relaunch of its trading market, refining the CCER valuation framework has become imperative. This study develops a multidimensional CCER valuation methodology based on both the income and market approaches. Under the income approach, two probabilistic models—discrete and continuous emission distribution frameworks—are proposed to quantify CCER value. Under the market approach, a Geometric Brownian Motion (GBM) model and a Long Short-Term Memory (LSTM) neural network model are constructed to capture nonlinear temporal dynamics in CCER pricing. Through a systematic comparative analysis of the outputs and methodologies of these models, this study identifies optimal pricing strategies to enhance CCER valuation. Results reveal significant disparities among models in predictive accuracy, computational efficiency, and adaptability to market dynamics. Each model exhibits distinct strengths and limitations, necessitating scenario-specific selection based on data availability, application context, and timeliness requirements to strike a balance between precision and efficiency. These findings offer both theoretical and practical insights to support the development of the CCER market.

Different methods, different values: Policy implications of alternative valuation methods

Purpose and Design: This paper develops and empirically validates a SMART-based SEFVF framework to reform Egypt’s existing financial valuation standards (EFVS). Using a mixed-method approach that combines quantitative analysis and embedded case studies, the study benchmarks SEFVF against IVS and IFRS. The results show that the proposed SEFVF substantially improves valuation accuracy, transparency, and ethical consistency, reducing disputes compared to current practices. Method and Approach: “We analyze a stratified sample of 50 Egyptian listed and large unlisted firms and conduct six embedded case studies to examine implementation frictions”. We benchmark the proposed SMART-based SEFVF against IVS/IFRS requirements and Egypt’s EFVS. Quantitatively, we build composite indices (e.g., Transparency, Ethical-Compliance) and estimate a confirmatory SEM to test the causal links among SEFVF adoption, valuation accuracy, and reporting quality. Comparative benchmarking is performed against International Valuation Standards (IVS) and IFRS guidance, while Structural Equation Modeling (SEM) and scenario analysis test the hypotheses and framework validity. Findings: The results reveal that the SMART-based framework significantly improves valuation accuracy, reduces variation among valuers, enhances compliance with international standards, and increases stakeholder confidence in reported values. Case studies demonstrate that applying SMART principles leads to better risk management, fairer asset pricing, and improved decision-making in privatization, mergers, and capital market transactions. SEFVF is associated with significantly higher valuation accuracy and report transparency relative to EFVS; results are robust in the SEM (standardized paths > 0.30, p Originality and Value: This study is the first in Egypt to propose a comprehensive SMART framework for valuation reform, combining advanced digital tools, international benchmarking, and applied evidence from local case studies. It provides both academic and policy contributions by linking theory with practice. Theoretical Practical and Social Implications: Theoretically, it extends asset valuation theory by embedding SMART criteria. Practically, it equips regulators, auditors, and valuers with a structured methodology for consistent valuation. Socially, it contributes to protecting public wealth, reducing corruption opportunities, and fostering investor trust in Egypt’s financial markets.

This article explores the critical role of “new money” in Dutch WHOA restructuring proceedings. Based on recent case law and international comparisons, the analysis distinguishes between interim financing – needed to keep operations running during the restructuring process – and new financing, which is essential for implementing the restructuring plan itself and enabling the company to continue operating going concern. The Dutch WHOA, inspired by U.S. Chapter 11 and UK practices, applies a priority rule that requires that any value created through restructuring must be distributed fairly among creditors in accordance with their legal rank. New investors can inject capital and receive returns, but only up to the value they contribute, unless parties agree otherwise or there is a reasonable ground for deviating from this priority rule. Valuation methodologies, such as the Discounted Cash Flow (DCF) model, are used to determine the “reorganisation value” – the total distributable value after restructuring, i.e. “post-restructuring value”. Case law illustrates how Dutch courts balance the interests of existing creditors and new financiers, sometimes permitting changes in creditor ranking or security rights to facilitate investments. Ultimately, the WHOA framework provides a transparent, equitable, and flexible environment for restructuring. After almost five years since its enactment, it is our observation that the WHOA contributes to the success of consensual out-of-court restructurings, as intended by the Dutch legislator when drafting the WHOA. This development not only enables successful recoveries but also strengthens the Dutch insolvency system, offering a robust solution for companies facing financial distress.

Purpose This paper aims to investigate the background to the introduction of a recurrent property tax on residential property in Ireland. Within the European Union only two countries did not have a recurrent property tax on residential property, namely, Ireland and Malta. However, as from 2013, Ireland took the important step to re-introduce a residential property tax known as the Local Property Tax (LPT). The implementation of a new recurrent property tax represented a significant reform and challenge for the authorities, particularly in terms of the valuation of properties, where initally some 1.9 million dwellings had to be valued. Design/methodology/approach The paper is based on an extensive review of government led commissions and published reports on the Local Property Tax both prior to and post implementation. In addition, a detailed analytical review of published research has identified the thinking behind government decisions in relation to how the LPT could be implemented within a very short period of time. Findings Preparatory groundwork to introduce a new recurrent property tax took about four years. However, once the signal by the government was given the actual implementation took less than one year. This major tax reform was successful if measured against efficiency of implementation, the use of a simplified valuation methodology and reliance of owners’ declaration of value. Research limitations/implications There were no research limitations encountered. Practical implications The paper highlights a number of key policies that were critical to the successful implementation of the LPT in Ireland. In this regard, two policies were to the fore, namely, the use of simplified valuation structure based on value banding and in adopting self-declared valuations provided by property owners. The LPT has now been in place for some 12 years and has been successful in raising stable and predictable revenue for local government. The implementation strategy adopted by Ireland should be of interest to other countries and/or jurisdictions when reviewing their options for property tax reform. Social implications The paper has outlined the implementation of a property tax that has a reach of some 1.4 million taxpayers. It clearly provides evidence of impact and tax liability. Originality/value The paper has provided some unique insights into the implementation and performance of the LPT. It has also contributed to the literature on the innovative use of value banding. In addition, the paper provides a solid basis upon which other countries/jurisdictions could evaluate this as a potential reform solution.

A merger is a corporate strategy that aims to strengthen capital structure, expand business scope, and improve operational efficiency. On February 1, 2021, three state-owned Islamic banks, namely Bank Syariah Mandiri, BNI Syariah, and BRI Syariah, officially merged to form Bank Syariah Indonesia (BSI), making it the largest merger in the history of Islamic banking in Indonesia. This study aims to analyze the application of PSAK 22 in the merger process, particularly regarding the assessment of the fair value of assets and liabilities, the recognition of goodwill, and the quality of disclosure in the consolidated financial statements. This study utilizes a qualitative descriptive approach by analyzing BSI's 2021–2023 financial audit reports, OJK publications, and IAI regulations. The findings indicate that BSI has met the formal compliance standards of PSAK 22 through the implementation of the Purchase Price Allocation (PPA) and the evaluation of goodwill impairment. However, transparency regarding the valuation methodology, cash flow assumptions, discount rates, and valuation sensitivity is still lacking, giving rise to the risk of information asymmetry and the possibility of goodwill overvaluation. Therefore, increased transparency in disclosure is necessary to ensure that the quality of BSI's reporting is comparable to global best practices and to strengthen stakeholder confidence after the merger.

This paper illustrates the valuation of chooser options within the broader intellectual lineage of modern option pricing theory, providing both a theoretical and methodological framework. Our analysis is anchored in the discrete-time valuation methodology proposed by Cox, Ross, and Rubinstein, commonly known as the CRR model, which remains one of the most influential and practical approaches for demonstrating no-arbitrage pricing. While acknowledging the continuous-time paradigm of the BlackScholesMerton (BSM) model as a theoretical benchmark, we leverage the intuitive and adaptable nature of the binomial framework to deconstruct the chooser options unique structure. Furthermore, by drawing a conceptual parallel to the work on barrier options by Reiner and Rubinstein, we argue that the analytical treatment of path-dependent but contractually fixed boundaries provides a blueprint for decomposing the choosers distinctive payoff mechanism. The core contribution of this work lies in the systematic construction of a binomial pricing model tailored to this instrument. We conclude by outlining pathways for future research, including the extension of this framework to the more complex American-style chooser optiona challenge that requires advanced numerical methods such as the Least-Squares Monte Carlo (LSM) algorithm. Finally, this study proposes a testable hypothesis for future validation: that the structural flexibility embedded in the chooser option may justify a higher premium. Further empirical research is needed to confirm this conjecture and to highlight its potential for both practical implementation and continued academic exploration in complex financial contexts.

Subject of study. Land valuation activities in Ukraine, especially in the context of European integration, including legal, economic, technological, and institutional aspects. The aim of the study. To analyze the current state of land valuation practices in Ukraine, identify key challenges, and outline prospects for improvement and alignment with European standards. Research methods. The study uses a comprehensive analytical approach, including review of regulatory frameworks, assessment of digitalization trends, analysis of cadastral data processing methods, and examination of international practices and standards. Results of work. The research identifies obstacles such as outdated legal regulations, lack of a unified digital land information system, and the need for harmonization with international valuation methodologies. It emphasizes the importance of using innovative technologies (e.g., GIS), improving data transparency, and developing a national land market data base. The study offers recommendations for aligning Ukrainian practices with EU standards, enhancing professional training systems, creating a digital registry of valuation results, and establishing mechanisms for public oversight of land values. Particular attention is given to the impact of legislative changes and economic factors on the dynamics of land valuation processes. The article explores current trends in the digitalization of land valuation, the potential for adopting new technologies, and the creation of a national database of market data. The research lays the foundation for developing effective recommendations for the gradual adoption of European approaches to land valuation, improving the professional training system for specialists, developing a unified digital registry of valuation results, and establishing mechanisms for public oversight of land plot values. The proposed solutions have practical significance for the modernization of national land policy and promote Ukraine’s integration into the European land relations framework.

Ghana faces significant challenges in solid waste management, with inadequate collection services, poor disposal practices, and limited recycling infrastructure affecting urban and rural communities alike. This study investigates public willingness to pay (WTP) for enhanced solid waste management services across selected regions in Ghana, examining the economic feasibility of service improvements and identifying factors that influence household payment decisions. Using a mixed-methods approach, this research employs contingent valuation methodology through structured surveys administered to 200 households across Techiman Municipal. The study assesses current waste management practices, households’ maximum willingness to pay for improved services, including regular waste collection, Tenancy agreement, proper disposal facilities, recycling programs, and community education initiatives. Key variables examined include household income, gender, and age, education levels, current service quality, academic qualification, amount of money willing to pay, and demographic characteristics. It was revealed that the predominantly working-age population 25 years and above capable of contributing to service delivery remains compromised by prohibitive collection costs and unprofessional conduct among waste collectors. The study also discovered that out of the 200 respondents, 56% were willing to pay for the services of waste collectors. The findings also became clear that there is a gendered dimension to waste management participation, with women assuming greater responsibility for household waste collection activities compared to their male counterparts. Significantly, the educated demographic also demonstrates understanding of the health and environmental consequences of improper waste disposal. The findings recommended the enforcement of sanitation laws, environmental education, and waste management strategies.

Abstract The objective of this study is to estimate the welfare economic costs of premature cardiopulmonary disease (CPD) mortality in Europe and Asia Minor under a middle-of-the-road scenario for global warming. It projects future heat-related CPD fatalities in urban areas over the next 25 years for 317 regions of 39 countries by applying regionalized exposure-response functions for heat- and air pollution–related premature mortality. These functions are derived from datasets of daily counts of CPD deaths from 1994 to 2018 for over 30 million people, capturing the different sensitivities to heat across climate gradients. As using simple average summer temperatures can mask important variations, methodologically we operationalize heat spell intensity based on the Eurostat metric of cooling degree-days. We find that heat-related CPD mortality could triple by midcentury from its pre-1990 level. Based on Organisation for Economic Co-operation and Development (OECD) methodology for the economic valuation of premature mortality, this amounts to an estimated EUR 90 billion in annual welfare economic costs. For 10 countries in southeastern Europe, costs may well exceed 1% of their annual GDP, reaching up to 4% in a heat wave year. A further important outcome of the study stems from its exploration of the interactive effects of air pollution and heat spells for premature mortality. We find that deep reductions in air pollution, beyond requirements in the EU’s recently revised Ambient Air Quality Directive, could prevent up to 190 000 heat-related deaths over the next 25 years, positioning air quality improvements as a critical adaptation strategy. Our findings underscore the urgency of better-integrated climate and public health policies. Significance Statement Our findings about the significant health impacts of heat on premature cardiopulmonary mortality in Europe challenge assumptions inherent in previous economic studies on the social costs of carbon from global warming. We find mortality impacts in Europe to increase exponentially with temperature, a relationship thought to be linear or even nonexistent in recent efforts to account for the social costs of carbon. This bears implications for future economic evaluation studies, as the value of climate change mitigation to reduce the costs of midcentury deadly heat spells is likely higher than previously assumed, even in a relatively mild scenario of global warming.

Currency devaluation presents formidable challenges to business valuation, particularly in emerging markets like Nigeria where macroeconomic volatility is endemic. This study explores how the 2023 naira floatation and ensuing devaluation impacted valuation outcomes for Nigerian listed firms involved in mergers and acquisitions (M&A). Using case studies for Access Bank, MTN Nigeria, and Dangote Cement, this study explores how foreign exchange losses, inflation pressures, and enterprise value distortions rewrote valuation methods and investment plans. The study concludes that pre-devaluation valuation methodologies employed extensively relative stability assumptions for exchange rates, leading to inflated enterprise values and minimal FX risk incorporation. The post- devaluation scenarios, however, show extreme dollar-based valuation volatility, reset discount rates, increased cost of capital, and increased currency exposure due diligence. MTN Nigeria recorded over ₦740 billion in FX losses, while Access Bank and Dangote Cement experienced declining valuation multiples as well as distressed capital positions. The evidence further reveals that devaluation triggered strategic shifts in acquisition structuring such as staggered payment and FX-indexed terms in transactions. Investor behavior parted ways—foreign investors employed conservative, hedge-based approaches, while local investors utilized valuation arbitrage to acquire assets at discounted dollar-equivalent prices. The study finds that devaluation of currency has turned business valuation into a strategic decision-making process of a high order as opposed to a fixed financial calculation based on macroeconomic, regulatory, and operating considerations. Proposed recommendations are adaptive building of valuation models by analysts, managers, and policymakers; acceptance of flexible deal structures; and macroeconomic transparency for establishing investor confidence in volatile currency markets.

In this article, we examine the role of financial assets as a key instrument for improving enterprise management efficiency, with a particular focus on marketing activities under the conditions of globalization, digital transformation, and increasing competition. We substantiate the relationship between financial asset management and the effectiveness of marketing decision-making, emphasizing that strategically managed financial resources strengthen enterprise adaptability, stability, and innovation capacity. We compare approaches to financial asset evaluation according to NAS 13 and IFRS, identifying major differences in classification detail, valuation methodology, and disclosure requirements. We also analyze key risks – credit, liquidity, and market – and develop recommendations for incorporating risk assessment into marketing budget formation and resource planning. In our analysis, we identify the main functions of financial assets in marketing, including ensuring liquidity, financing promotional campaigns, supporting pricing strategies, and fostering customer relationship management, brand development, and digital transformation. We critically review domestic and international research to reveal the absence of a unified methodological framework for classifying and assessing financial assets and to justify the need for integrating financial and marketing analytics. We propose directions for improving financial asset management systems that align liquidity, profitability, and risk indicators with marketing performance metrics such as ROI and CLV. Our findings show that rational financial asset management enhances the return on marketing investments, stabilizes communication cycles, minimizes underfunding risks, and supports the creation of sustainable competitive advantages. We argue that companies can use these approaches to react more dynamically to market changes, maintain brand continuity, and allocate financial resources more effectively to achieve sustainable growth in both national and global markets. Ultimately, we demonstrate that strategic financial asset management serves as a catalyst for increasing marketing effectiveness and strengthening the overall competitiveness of enterprises.

The integration of artificial intelligence and advanced financial data analytics represents a paradigmatic transformation in mergers and acquisitions valuation methodologies within contemporary investment banking practices. This comprehensive research review examines the revolutionary impact of machine learning algorithms, predictive modeling frameworks, and big data analytics on traditional valuation approaches, revealing how technological innovation enhances accuracy, reduces uncertainty, and accelerates decision-making processes in complex transactional environments. Through systematic analysis of AI-driven methodological innovations, this study demonstrates how intelligent systems can process vast datasets, identify subtle market patterns, and generate sophisticated valuation insights that transcend conventional analytical limitations. The investigation explores the multifaceted implications of AI integration in M&A workflows, examining its capacity to transform due diligence processes, risk assessment methodologies, and strategic positioning analysis. By analyzing empirical evidence and theoretical frameworks, this review illuminates how AI-enhanced valuation systems create competitive advantages for investment banking institutions while establishing new standards for transactional accuracy and strategic insight generation. The findings reveal that successful AI implementation requires sophisticated integration of technological capabilities with domain expertise, regulatory compliance frameworks, and client relationship management systems.

Energy sustainability and financial efficiency are growing priorities for the healthcare sector. This article explores new methodologies to optimize investments in photovoltaic (PV) systems in public hospitals. An advanced real options valuation methodology is presented to evaluate investments in PV systems in Colombian public hospitals, integrating technological advances, local climate considerations, and financial incentives, thus optimizing strategic decision-making under conditions of uncertainty. A binomial model adapted to the specific Colombian context evaluated three strategic scenarios: immediate execution, strategic postponement, and phased implementation in two representative hospitals in Barranquilla. The approach quantified the economic impacts using parameters such as the initial investment (USD 150,000), projected annual savings (USD 45,000), the risk-free discount rate (6.7%), market volatility (25%), and a five-year evaluation horizon. Factors such as regional tropical weather patterns (which reduce PV efficiency by 20–30%), existing emergency diesel generators as alternative backup solutions, current innovations in battery technologies (such as solid-state and sodium-ion batteries), and the potential integration of hybrid wind-PV systems were incorporated. Real options analysis provided superior strategic flexibility compared to traditional Net Present Value (NPV = USD 29,672 with 6.7% discount rate), generating an additional USD 10,000 through strategic deferral and USD 12,500 through phased implementation over a 5-year horizon. Sensitivity analyses revealed additional financial advantages when considering future improvements in battery technology, specialized pricing for the healthcare sector, and incentives for pilot projects supported by international cooperation. The inclusion of existing diesel generators highlighted significant operational savings and immediate feasibility compared to current battery investments. Monte Carlo simulation with 10,000 iterations confirmed model robustness with Expected NPV of USD 29,450 (95% CI: USD 18,200-USD 41,800) and Real Options Value of USD 41,200 (95% CI: USD 28,900-USD 54,600). The application of real options analysis not only improves the valuation and strategic flexibility of solar energy investments but also drives the adoption of hybrid solutions and attracts international financing, thus contributing to the resilience and sustainability of Colombia's hospital system.

Purpose The article presents a novel approach to the development of a taxonomy and methodological framework for the valuation of ecosystem services. It addresses the complex challenge that economists face in capturing the full and incremental changes in services across diverse ecosystems, particularly those affected by human activities. This work aims to fill the gaps in current valuation methodologies by incorporating a psychological perspective, suggesting that public understanding of ecosystems significantly diverges from that of conventional economists. Design/methodology/approach The article draws on insights from psychoanalytic psychology, environmental psychology and recent experimental psychology research. It explores how ecological identities form across various levels of decision-making – from local to global – and revisits key psychological concepts such as the self-other dichotomy and connection with nature. The proposed framework advocates for a paradigm shift towards relational goods and reciprocity, integrating interdisciplinary collaboration in the process of ecosystem service valuation. Findings The study highlights the insufficiency of traditional market-based and even advanced valuation techniques, such as the contingent valuation method, in fully capturing the complexity of ecosystem services. It demonstrates that psychological constructs such as ecological identity are crucial to understanding how individuals value ecosystems, suggesting that valuation must go beyond utilitarian considerations. Originality/value This article offers an innovative and interdisciplinary framework that reimagines the dichotomy between market, non-market and missing market valuations. By emphasising relational and psychological dimensions, it promotes a more inclusive and nuanced approach to ecosystem service valuation that challenges conventional economic paradigms and opens new avenues for policy and practice.

The science and technology innovation board (STIB) is a critical initiative to support the high-quality development of technology innovation enterprises. Accurate valuation of STIB-listed enterprises is essential for optimizing resource allocation and enhancing capital market efficiency. However, existing valuation methods face significant challenges, including the presence of nonlinear data and low accuracy when assessing these enterprises. Given the capability of machine learning methods to address such issues, this study proposes a hybrid approach that combines Spearman correlation analysis and XGBoost feature selection to identify key indicators. The selected features are subsequently input into a GA-BP neural network for training and simulation. The empirical results, based on a dataset of 1558 observations, demonstrate that the XGBoost-GA-BP neural network model achieves a coefficient of determination (R2) exceeding 97% and maintains a mean absolute percentage error (MAPE) below 10%. These findings indicate that the proposed model can effectively assess the valuation of science and technology innovation enterprises with high accuracy, underscoring its robust practical applicability and reliability. This study not only advances methodologies for enterprise valuation but also provides actionable insights for stakeholders to optimize resource allocation and enhance enterprise value.