Abstract: This study examines whether international food price dynamics provide a reliable signal of undernourishment and human development outcomes relevant to the attainment of SDG 2 (Zero Hunger) by 2030. We apply wavelet coherence analysis to the FAO Food Price Index and the prevalence of undernourishment (SDG Indicator 2.1.1) over 2001–2023, testing statistical significance against an AR(1) red-noise null hypothesis. Hybrid ARIMA–Random Forest models generate probabilistic price forecasts through 2030. Despite strong raw coherence (R² ≈ 0.77), only 7.8% of time–frequency cells achieve statistical significance, indicating that apparent co-movement largely reflects autocorrelation rather than substantive dependence. Where significant coherence emerges, it concentrates at medium-run horizons (3–6 years), consistent with undernourishment as a habitual dietary adequacy measure linked to sustained affordability pressures affecting health, productivity, and human capital formation. Rolling correlation analysis reveals a regime shift around 2012—from negative to positive correlation—coinciding with a slowdown in progress toward reducing hunger. Price forecasts exhibit rapidly widening confidence intervals (by ±131 index points by 2030), underscoring fundamental limits to predictability. These findings caution against mechanistic inferences from global price indices to hunger and human development outcomes, redirecting policy emphasis toward domestic transmission channels and nutrition-sensitive safety nets.

Abstract: The Phillips curve remains central to monetary policy, yet its functional form has been intensely debated following the 2021–2023 inflation surge. This paper offers novel empirical evidence by providing the first symmetric comparison of regime-dependent nonlinearities in the inflation–slack relationship between the United States and the Euro Area, using identical threshold and smooth-transition frameworks on quarterly data extending through 2025Q4, the most recent available. Core PCE inflation (US) and core HICP excluding energy, food, alcohol, and tobacco (Euro Area) are modeled as functions of unemployment and output gaps, with controls for oil shocks and inflation expectations. TAR/SETAR and LSTAR estimations uncover statistically significant steepening in tight labor-market regimes. In the US, the slope more than doubles when the unemployment gap falls below –0.61 percentage points. In the Euro Area, a comparable kink emerges near zero (–0.048 pp), with smoother transitions reflecting greater wage and price rigidities. Post-2019 subsamples exhibit amplified nonlinearity, consistent with supply-shock transmission in high-pressure conditions. Extensive robustness checks affirm these findings. The results establish a state-dependent sacrifice ratio, with sharply higher disinflation costs in tight regimes, and highlight substantial risks of monetary policy miscalibration in future high-pressure episodes.

Abstract: This study as part of a postdoctoral research takes a critical look into Corporate business incubators (CBIs) value co-creation by adopting an integrative and meta-model approach. An integrative review aids the aggregation of studies fragmented with diverse views and perspective or approaches without a cogent agreeable framework; while meta-modelling aids the development of new models from an existing one. Based on paradigms with meta models from different perspectives and areas of studies (philosophical, entrepreneurial, psychological, innovation), this study aggregates them into a compounded framework of study for easier audience digest. Based on this, the study uses a multi-level analyses for the methodological synthesis of CBI value co-creation concepts capturing the holistic view based on CBIs classifications taxonomy and typology, scope and pathways based on CBI activities with an outlook on CBI Business Models. In addition to this, an emerging and captivating concept of cognitive schema of CBI actors is applied to the model capturing the attributes, relationships and CBI sub-schemas and their value co-creation outcomes based on response to environmental conditions and innate organizational capabilities. The study identifies three meta models which are based on CBIs core components and functions, CBIs Value Co-creation and UBI (University Business Incubators), CBIs Core Business Models, Classifications and Value Co-creation and also addresses the complementarities towards a compounded CBI framework. The evolving model(s) would serve as the conceptual framework on which further CBIs co-creation research study with UBIs would be built.

Abstract: Against the backdrop of the high-quality development of the digital economy, exploring the impact of data assetisation on corporate investment efficiency with fintech as the core tool is of great significance for driving the steady and orderly development of enterprises...Taking A-share listed companies from 2012 to 2023 as the research sample, and further classifying them into self-used data assets and transactional data assets based on the types of data assets., the study finds: (1) Data assetisation significantly enhances corporate investment efficiency, with self-use data assets demonstrating a stronger driving effect.(2) Mechanism analysis reveals that data assetisation alleviates underinvestment by easing financing constraints and leveraging the "talent effect". Concurrently, it mitigates overinvestment by reducing agency problems and accelerating digital transformation, thereby enhancing investment efficiency. (3) Heterogeneity tests indicate that the positive impact of data assetisation on investment efficiency is more pronounced among growth-stage enterprises, technology-intensive firms, and companies operating in regions with high bank liquidity.(4) Banking fintech positively moderates the enhancement of corporate investment efficiency through data assetisation, with a more pronounced effect on alleviating underinvestment. However, it may also exacerbate overinvestment. Consequently, enterprises should vigorously develop data assetisation, applying different types of data assets to specific use cases to unlock data dividends. This approach supports the scientific development of corporate investment decisions and enhances investment efficiency.

Abstract: This study examines household demand for drinking water in rural central India using a revealed preference framework applied to a stratified sample of households across villages with and without piped water supply. Departing from the contingent valuation methods prevalent in earlier literature, the study employs a discrete choice model to identify the determinants of water source selection. In settlements without piped supply, distance to the water source and female educational attainment emerge as the principal determinants of safe water preference, whilst household income is not significant. Where piped supply exists, income, price, and household size shape the decision to opt for a private yard connection. The monetary value of time spent collecting water indicates a substantial willingness to pay. The findings demonstrate that rural households already behave as rational economic agents in their water decisions, undermining paternalistic assumptions embedded in India's supply-driven policy framework. The paper argues for a tiered service model that guarantees a minimum standard of provision for all whilst permitting enhanced service levels for those willing and able to pay, thereby reconciling equity commitments with financial sustainability.

Abstract: The article explains the narcissism leadership paradox in the existing organizations in relation to the rhetoric of ethics used strategically to legitimize the use of control. The loss of trust in leaders and in employees are both practiced in the sense that leaders manifest the disjunction between organizational discourses and reality by instantiating values in superficial ways in what they say and in real ways in what they do. The study relies on three guiding questions: (1) How do narcissistic leaders legitimize themselves by thinking that they are right in the moral sense? (2) What are a few of the stressors related to employees where ethics and practice collide? (3) Does dissonance cause organizational cynicism? Semi-structured interviews with 24 employees working in Higher Education Institutes were used to collect qualitative data to answer the following questions: The similar patterns and their comparison across cases were determined by coding and performing thematic analysis in computer through excel. The outcomes show 3 broad themes. First, the Virtue Costume demonstrates that both virtues signaling and moral language are being offered to fulfill personal interest and acquire power. Second, Branding the Self as the Company causes us to concentrate on how egoistic leaders project their own image as the identity and values of the company. Third, the Contagion of Cynicism explains how employees who become disillusioned, cynical and detached respond when they feel hypocrisy in the words and actions of their leaders. The paper associate’s impression management and moral justification of narcissist leaders with falling trust and calls on authentic leadership and open cultural supervision to restrain cynicism and provide theoretical and practical organizational knowledge. This study’s implications build on the dark triad perspective advanced by Alowais and Suliman, which demonstrated that Leader Dark Triad (LDT) traits can cascade into Employee Dark Triad (EDT) behaviors within organizational settings. Extending this logic, the present study shows that narcissistic leaders’ ethical rhetoric can similarly shape organizational climates in ways that reinforce manipulative dynamics, highlighting how seemingly ethical leadership signals may mask deeper patterns of influence and behavioral contagion.

Abstract: As artificial intelligence (AI) becomes increasingly embedded in organizational processes, questions about its impact on leadership have gained prominence. Yet the existing literature remains fragmented. Studies often focus separately on strategy, leadership skills, governance structures, or ethical concerns, without explaining how these dimensions connect to shape leadership effectiveness in AI-driven environments. This study conducts a PRISMA-guided systematic review of 63 peer-reviewed articles to examine how AI-embedded leadership is conceptualized across contexts. By synthesizing findings across strategic, human, and governance domains, the analysis identifies recurring patterns and structural relationships in the literature. The review shows that effective leadership in AI-intensive settings does not result simply from adopting advanced technologies or developing digital competencies. Instead, it depends on the alignment between how deeply AI is integrated into decision-making processes, how leaders interpret and oversee algorithmic outputs, and how governance mechanisms ensure transparency, accountability, and trust. On this basis, the study introduces the AI-Leadership Configurational Framework (ALCF), a multi-level model that explains leadership effectiveness as the outcome of systemic alignment. The framework integrates previously disconnected debates and offers a clear foundation for future empirical research on leadership in the algorithmic age.

Abstract: Artificial intelligence (AI) is increasingly embedded in development systems, enabling new capabilities for poverty prediction, social protection targeting, and service delivery optimisation across sectors such as finance, agriculture, health and education, yet its implications for poverty governance in low- and middle-income settings remain fragmented. This study conducted a systematic literature review of South Africa’s DHET peer-reviewed journal articles and scholarly book chapters published within the last decade, screening studies for relevance to AI-enabled poverty reduction applications including predictive analytics, high-resolution poverty mapping, digital financial inclusion, precision agriculture, health diagnostics, educational personalisation, and public-sector digital transformation. A thematic synthesis was applied to identify cross-cutting patterns related to system performance, implementation processes, governance considerations, and contextual constraints. The reviewed evidence indicates that AI can improve poverty governance through multimodal data integration, enhanced targeting accuracy, automated administrative processes, expanded access to financial and basic services, and strengthened rural livelihood systems. However, persistent challenges include biased or incomplete datasets, infrastructural and computational limitations, weak interoperability, regulatory gaps, and ethical risks regarding privacy, accountability and exclusion, which may reinforce structural inequalities through misclassification and unequal access. The review contributes an integrated evidence base and highlights that developmental gains from AI depend on robust data governance, inclusive digital infrastructure, context-sensitive design, algorithmic transparency, and institutional capacity, while future research should prioritise impact evaluation, fairness-aware and explainable AI, participatory design, and scalable approaches for low-resource environments.

Abstract: Firms in carbon-intensive industries face rising sustainability pressures that increasingly shape financing conditions and performance outcomes. This study examines whether management control systems (MCS) and environmental management control systems (EMCS), conceptualized as control packages, influence capital structure decisions (leverage) and, in turn, dual performance (financial and environmental) among Indonesian listed coal-mining firms. Using a census of 28 firms and survey-based measures analyzed with PLS-SEM, we test direct and mediated relationships among MCS, EMCS, leverage, and performance. The results show that both MCS and EMCS positively affect leverage decisions. Leverage, in turn, has a strong positive effect on overall firm performance. EMCS also exhibits a significant direct effect on performance, whereas the direct effect of MCS on performance is not significant. Mediation analysis indicates that leverage fully mediates the MCS–performance relationship and partially mediates the EMCS–performance relationship. These findings suggest that, in a carbon-intensive setting, control packages contribute to sustainability-relevant outcomes primarily by improving the quality of financing choices that enable sustained investment and risk management. The study highlights leverage as a key financial mechanism linking sustainability governance to performance and offers implications for integrating environmental controls into budgeting and capital-structure policy to support transition readiness.

Abstract: This study analyzes the relationship between stock market returns and investment flows in investment funds in Spain. Through a quantitative analysis covering the pe-riod from December 2001 to June 2025, it examines not only the existence of a correla-tion but also its temporal structure, functional form, and heterogeneity across different geographical areas (U.S., Europe, Japan, and Spain). Using monthly data on net flows from INVERCO and market indices, the study employs Ordinary Least Squares (OLS) regression models, segmented regressions, and fixed-effects panel models to obtain robust estimates. The results confirm a positive and statistically significant relation-ship between past returns and subsequent investment flows, with a temporal lag ranging from one to three months. This delay varies notably by geographical region, suggesting the existence of different investor profiles and information channels. The study also finds evidence of a convex relationship, indicating that investors react asymmetrically, aggressively pursuing high returns more than penalizing low ones. These findings, interpreted through the lens of behavioral finance, point to pro-cyclical and reactive behavior of Spanish investors, driven by biases such as loss aversion, trend-following, and delays in information processing. The study contributes to the academic literature by providing updated and methodologically robust evidence on Spain, a market that has traditionally been underexplored, and offers practical impli-cations for investors, fund managers, and regulators in terms of financial education and risk management.

Abstract: Cruise calls in medium-sized Mediterranean ports concentrate visitor flows along short urban connectors, intensifying congestion and localized environmental externalities. This study evaluates cruise passengers’ willingness to pay (WTP) for an electric tram linking Gaženica Port with Zadar’s historic center, an intervention designed to cut travel time and reduce on-street crowding and emissions. A two-wave, two-site, face-to-face survey was administered over two seasons at the port and in the city center. The instrument adopts a double-bounded dichotomous choice contingent valuation design with randomized starting bids calibrated via a pre-test that benchmarked prevailing transport prices. Primary WTP estimates are obtained from a binary choice model with socio-demographic and environmental covariates; inference relies on cluster-robust errors. Robustness is assessed through three complementary checks that do not require additional data: (i) a bivariate specification to accommodate within-respondent correlation between first and follow-up bids; (ii) Turnbull nonparametric bounds for the interval-censored WTP distribution; and (iii) starting-point tests via bid-set indicators and split-sample estimation. Where applicable, a spike adjustment based on “no–no at the lowest bid” responses is explored. Beyond methodological contribution, this research advances the sustainable tourism development discourse by quantifying visitors’ monetary support for low-emission urban mobility infrastructure that mitigates environmental pressures while preserving resident quality of life. The findings provide a decision-ready valuation input for port–city mobility planning in historic Mediterranean cores, aligning cruise tourism management with the broader objectives of resilient and sustainable urban destinations.

Abstract: This study examines predictors of workplace adoption of artificial intelligence (AI) in a Norwegian employee sample (N = 196). Hierarchical logistic regression tested whether education, sector, sex, age, leadership, strengths-based leadership (SBL), training, and engagement predicted AI use. Education was the strongest predictor. Employees with a bachelor’s degree were 3.64 times, and those with a master’s degree more than 11.15 times, more likely to use AI than those with secondary education. Knowledge-intensive sector employees were 2.52 times more likely to adopt AI than those in skills-focused sectors. Men were 2.94 times more likely than women to use AI. Neither age nor leadership role showed significant effects. SBL independently predicted adoption (OR = 1.89). Training and engagement were unrelated to adoption. Overall, findings show that structural, sociodemographic, and organizational factors shape AI adoption, underscoring the need for targeted strategies to ensure equitable, effective uptake across the workforce.

Abstract: Organizations increasingly confront persistent tensions that require leaders to pursue competing demands simultaneously. Although prior research highlights paradox mindset as an orientation toward embracing tensions, less is known about the capabil-ity-based microfoundations that enable leaders to enact paradoxical leadership behaviors in practice. Addressing this gap, this study develops a cognitive–emotional capability framework that focuses on two developable resources: integrative complexity (IC)—a cognitive ca-pacity for differentiating and integrating competing demands—and emotion regulation (ER)—an affective capacity for sustaining engagement under tension. Using survey data from 264 Japanese managers, we examine the independent and joint effects of IC and ER strategies on paradoxical leader behaviors (PLB). Results show that IC and cognitive reappraisal are positively associated with PLB. Pol-ynomial regression and response surface analyses further reveal that PLB increases as IC and cognitive reappraisal rise together. However, when the two capabilities are im-balanced, PLB tends to be higher in profiles where IC exceeds reappraisal than in the opposite configuration. These findings suggest an asymmetric form of complementarity in which integrative complexity functions as a foundational capability while reappraisal provides supportive leverage. Overall, the study shifts attention from trait-like mindsets to trainable lead-ership capabilities and clarifies how cognitive–emotional capability configurations enable the enactment of paradoxical leadership.

Abstract: This paper investigates the transition of euro area inflation dynamics from a stable regime to persistent cyclical behavior through the lens of nonlinear macroeconomic theory. We develop and estimate a nonlinear New Keynesian Phillips Curve (NKPC) model augmented with endogenous monetary policy feedback and regime-dependent dynamics. The analysis shows that increasing Phillips curve convexity, rising inflation persistence, and variations in policy responsiveness can push the system through a Hopf bifurcation, leading to the emergence of endogenous limit cycles. Empirical results based on euro area data (2000–2025) confirm significant nonlinearities, structural breaks around major crisis episodes, and a narrowing stability margin over time. Robustness checks—including alternative inflation measures, estimation methods, subsample tests, and country-group heterogeneity—support the central findings. Welfare comparisons across alternative policy rules indicate that nonlinear dynamics alter the ranking of monetary strategies and that aggressive policy responses are not universally stabilizing. The results provide a unified explanation for the euro area’s regime transitions and offer concrete guidance for central bank design in environments characterized by structural nonlinearities and shock amplification.

Abstract: Corporate governance reforms in emerging and frontier markets frequently assume that strengthening board oversight, audit committees, and ownership monitoring will improve audit quality and enhance firm value. Yet, in weak institutional environments, these mechanisms often function symbolically rather than substantively. This study rethinks the governance–audit–value nexus by integrating Agency Theory, Institutional Theory, and the concept of symbolic governance to explain why governance may appear structurally robust while failing to constrain managerial discretion. Using panel data from Ghanaian listed firms between 2015 and 2023, the analysis shows that audit committee independence and board independence are negatively associated with both audit quality and firm value, indicating that formal independence without expertise, authority, or enforcement capacity does not translate into meaningful oversight. By contrast, institutional and managerial ownership positively influence both outcomes, suggesting that incentive alignment and informed monitoring can substitute for weak formal governance. Foreign ownership improves firm value but does not consistently enhance audit quality, while macroeconomic conditions such as inflation and GDP growth further shape firm performance. The study advances the literature by reconceptualising governance effectiveness in weak institutional environments, demonstrating that governance mechanisms may exist in form without functioning in substance. The findings underscore the need for governance reforms that prioritise enforcement capacity, board expertise, and audit committee competence rather than structural compliance alone.

Abstract: Automobiles have been the pivotal instrument shaping the cities' structures and urban lives. While promising numerous benefits, the successful introduction of self-driving cars depends not only on their technical completeness, but mostly on the market acceptance for these disruptive transformations. To gauge the market response, we first summarize the most recent 15 research applying technical acceptance model (TAM) to compare their objectives, findings, and applied constructs around the countries. Then we examine to identify some influential factors whether or not the public use these self-driving machines, using 519 Korean samples. We use three groups as the system characteristics, social influence, and individual differences to do the quantitative survey and the structure equation model (SEM). The findings show that technical completeness, law and regulations, media support, perceived cost, trial and experience influence significantly on perceived usefulness and again on the usage intention while perceived safety do not significantly influence perceived usefulness. The results of this study help to strengthen existing knowledge about the self-driving cars by emphasizing the key elements that drive the intention to use the self-driving cars in the future.

Abstract: Technological innovation is changing virtually every aspect of business practices and operational procedures. Regardless if we talk about simple automation of paper inputs, or complex multi-step processing of large data sets, we can see that there is one common thing – the pace of innovation increases and so do the efforts and resources needed to stay in line with the latest developments. Introduction of large language models and various types of intelligent processing, commonly referred to as artificial intelligence presents an even bigger change request to cope with. In this paper we analyze the impact of intelligent data modelling on corporate finance practices and suggest an approach to assess its full impact. We develop an estimation technique, based on real option analysis (ROA) in an attempt to quantify various implementation details and build a more robust way for analyzing various effects from using AI-driven solutions in support for corporate finance decisions and analyses.

Abstract: This paper employs simultaneous equation modeling to analyze the political economy of public health in Jammu and Kashmir, examining the interrelationships between fiscal allocation, infrastructure development, and health outcomes. Using data from the Union Budget 2026-27, J&K Budget documents, NFHS-5, and administrative health statistics, we specify and estimate a three-equation system addressing: (1) the paradoxical relationship between fiscal dependency and superior health outcomes, (2) the curative-preventive imbalance in resource allocation, and (3) the emerging epidemiological transition. The results reveal that fiscal dependency enables health investment (elasticity 0.42, p<0.01) while simultaneously reducing local accountability (direct effect -0.18, p<0.05), with net positive effect on outcomes. The curative share of expenditure negatively affects population health (coefficient -0.23, p<0.01) and exacerbates male anaemia (coefficient -0.31, p<0.01), confirming gender bias in nutrition programming. Non-communicable disease burden responds significantly to urbanization (0.34, p<0.01), aging (0.41, p<0.01), and curative expenditure share (0.19, p<0.05). Policy simulations indicate that reallocating 5% of curative spending to prevention would reduce IMR by 1.2 points and male anaemia by 3.1 percentage points. The findings support targeted interventions including workplace iron supplementation, population-wide screening, and nutrition-specific budget lines.

Abstract: The contemporary green transformation of the economy is a strategic imperative for businesses, especially small and medium-sized enterprises (SMEs) operating in the energy market, forcing the integration of sustainable practices in decision-making processes, including investment efficiency assessment. Classic financial tools, such as the internal rate of return and net present value, commonly used in the SME sector, do not always adequately account for environmental, regulatory, and social risks associated with green transformation. The goal of the study was to determine the impact of nominal and real discount rates, adjusted for a synthetic measure of green transformation, on investment decisions. The research methodology combines advanced multicriteria analysis techniques with sustainable finance concepts, offering an innovative approach to investment decision-making in the SME sector. The study shows that integrating environmental factors increases the cost of capital and reduces the net present value while maintaining the profitability of the analysed projects. Incorporating green components into the discount rate enhances valuation appropriateness and improves investment risk management, especially in conditions of macroeconomic uncertainty. The findings contribute to the development of research on dynamic methods of evaluating investment projects.

Abstract: This paper examines the relationship between decentralisation, human resource development (HRD), and operational efficiency in water utilities managed by state and local governments across Madhya Pradesh, Chhattisgarh, and Jharkhand, India. Drawing on a random sample of 200 towns and villages, the study quantifies how decentralisation influences HRD investment and how both variables jointly shape service delivery outcomes. The findings challenge the widely held assumption — promoted by international donors and development institutions — that devolving authority to lower tiers of government inherently improves public service performance. Results indicate that decentralisation, as practised in India's drinking water sector, does not enhance operational efficiency. Instead, vocational training — the primary measure of HRD employed here — emerges as the principal driver of improved performance. Since decentralisation is negatively correlated with HRD investment, transferring authority without commensurate workforce development commitments risks compounding existing inefficiencies rather than resolving them.