Business, Economics and Management

Abstract: Against the background of severe farmland fragmentation and continuous rural labor outflow in developing countries, land consolidation through land transfer has long been regarded as the primary path to realize large-scale agricultural production. However, land transfer faces institutional and market constraints in smallholder-dominated regions. This paper takes China’s full-process agricultural production service pilot policy as a quasi-natural experiment, adopting 2006–2023 provincial panel data and staggered DID to explore how service-oriented scale reshapes cultivated land use patterns and boosts staple grain supply. We find that agricultural production services raise total grain output mainly via expanding cultivated land sown area (extensive margin) rather than lifting per-unit land yield. By popularizing mechanized operations in labor-intensive sowing and harvesting stages, the policy alleviates seasonal labor constraints, raises per capita cultivated acreage, increases multiple cropping index and optimizes grain-oriented cropping structure, thus mitigating farmland abandonment. Although the policy significantly promotes rural land transfer, the pre-existing land transfer level cannot strengthen its grain-promoting effect, which verifies that service-based scale can operate without large-scale land right consolidation. Further evidence shows the policy also improves agricultural total factor productivity, realizing coordinated optimization of land, labor and machinery factor allocation. This study supplements the land economics literature by distinguishing two scale development paths (land transfer vs service aggregation), and provides a land governance reference for smallholder economies to stabilize grain security under fragmented farmland.

Abstract: The circular economy (CE) decreases food waste, enhances food security and maintains food. This study assesses the acceptance of CE in the Eastern Province of Saudi Arabia and identifies its factors. Primary data were collected from 384 Saudi citizens aged 18 years and above through a structured questionnaire using a cross-sectional technique. Data analysis comprised descriptive statistics and OLRM. The CE level was calculated based on 40 questions asked to the participants on recyclable bread, dates, cooked rice, cooked pasta, stewed veggies, stewed meat and fruit. Cronbach’s alpha was 0.931 for all queries. Adult CE adoption is low (3.1 %), mid (34.4 %), and high (62.5 %). OLRM studies demonstrate that CE applications and platforms improve CE levels. Participants who disagreed that not retaining leftover food wastes food had 7.89 times increased probability of having high CE levels. CE levels are 4.94 times higher when food purchases are not out of boredom. The results support the development of food recycling apps and platforms, educational and awareness efforts, and regulatory frameworks and regulations. They support change in behavior, food security, reduction in food waste and sustainable food systems.

Abstract: This paper examines how circular economy (CE) policies relate to sustainable economic growth and environmental sustainability across eight major emerging economies between 2005 and 2023, with particular attention to how that relationship shifts across time horizons. Much of the existing literature suffers from a temporal aggregation problem: short- and long-run dynamics get averaged together into a single coefficient, which can obscure the underlying relationship or, worse, produce a misleading sign. We address this by decomposing two central CE variables—renewable energy share and energy intensity—into short-, medium-, and long-term frequency components using a Level-2 discrete wavelet transform. Each component is then estimated via two-way fixed-effects panel regressions; given the constraints of a relatively small panel, we validate inference using a Wild Cluster Bootstrap procedure. Three findings stand out. First, although the growth elasticity of renewable energy rises across horizons—a descriptive pattern consistent with short-run adjustment costs giving way to longer-run sustainable gains—Wild Cluster Bootstrap (WCB) inference indicates that these structural coefficients are not statistically significant in this sample. Second, the energy intensity coefficient reverses sign, moving from a weakly significant negative short-run effect (p < 0.10) to positive estimates in the longer run; these longer-run effects, however, also fail to reach statistical significance, and so offer only suggestive theoretical alignment with the macroeconomic Jevons Rebound Effect rather than firm empirical confirmation of it. Third, Industry Value Added stands out as the one robust macroeconomic factor in the model, remaining a significant and positive driver of sustainable development at every frequency horizon. Taken together, these results suggest that while CE transitions display suggestive multi-horizon dynamics, industrial expansion remains the more statistically dependable engine of sustainable growth across these emerging markets. Although the statistical significance is by the sample size, the identified trajectories provide a useful structural diagnosis for policymakers who need to plan different investment horizons for the sustainable green transition.

Abstract: Background: Antimicrobial resistance (AMR) poses a significant threat to global health and economic development. In Malawi, the economic costs associated with AMR remain largely unknown which may hinder resource allocation and policy prioritization. Method: The study used instrumental variable 2-stage least squares regression to analyze patient level cost data at tertiary and secondary level facilities primarily collected from 610 patients with urinary tract infection (UTI) or blood stream infection (BSI) using a questionnaire. Results: Findings indicate that E. coli (43%) followed by K. pneumoniae (14%), and S. aureus (10%) were common pathogens overall. UTI was common (51%) compared to BSI (49%) yet BSI had a higher average cost than UTI for both susceptible and resistant patient categories. In terms of costs, a patient spent MK283,815.10 (US$163.71) on average as a result of AMR infection. The total cost reached as high as MK13,500,000 (US$7,786.90). Patients with a resistant infection incurred, on average MK161,785 (US$93.32) more than patients whose infection was susceptible, with the additional costs being driven by prolonged hospitalization among other factors. The direct medical costs averaged MK37,165.29 (US\(21.44) while direct non-medical costs averaged MK61,908.71 (US\)35.71). Productivity losses for the patient and guardian(s) were a major cost averaging MK160,322.80 (US$92.49). The regression results further showed that having a bank account as a proxy of wealth, non-farm business, longer travel duration, BSI, and K. pneumoniae as causing pathogens were significantly associated with increased cost burden among the patients. Conclusions: AMR imposes substantial economic burden on Malawi's health system, with most costs falling on patients. Further strengthening of AMR surveillance and stewardship are needed as critical elements of Malawi’s National Action Plan. However, measures should also be taken to mitigate the economic consequences related to AMR, especially for patients who bear the brunt of these costs for lack of financial protection in Malawi’s health system.

Abstract: Despite growing international commitments to green finance, it remains an open empirical question whether such transfers translate into inclusive green growth (IGG) in developing countries. This study addresses this gap by examining how countries’ levels of development and executive corruption condition the effects of green finance on IGG. To this end, we draw on a comprehensive sample of 99 developing countries spanning 2000–2024 and employ instrumental-variable and quantile regression techniques for the analysis. Three clear findings emerge. First, we find robust evidence that green finance promotes IGG, but only in low-income countries. Second, we show that executive corruption significantly reduces the IGG-enhancing effects of green finance in low-income countries, whereas no comparable effect is observed in higher-income developing countries. Third, the evidence reveals notable heterogeneity in the conditional distribution of IGG, with countries at the lower end of IGG performance experiencing relatively larger gains from green finance. Overall, the findings indicate that the effectiveness of green finance in promoting inclusive green growth depends critically on countries' levels of development and the prevalence of executive corruption.

Abstract: This study examines the nonlinear relationship between loan portfolio diversification and credit risk in Vietnamese commercial banks. While diversification is generally con-sidered an effective risk management strategy, its impact on credit risk may vary de-pending on the degree of diversification. Using an unbalanced panel dataset of Viet-namese commercial banks from 2012 to 2025, this study employs the two-step System Generalized Method of Moments (System GMM) estimator to address endogeneity, unobserved heterogeneity, and the dynamic persistence of credit risk. Loan portfolio diversification is measured using the Shannon Entropy Index, and a quadratic specifi-cation is applied to capture potential nonlinear effects. The results reveal a significant U-shaped relationship between diversification and credit risk. Moderate diversification reduces the non-performing loan ratio by mitigating sectoral concentration risk, whereas excessive diversification increases credit risk because higher monitoring costs and in-formation asymmetry outweigh the benefits of risk dispersion. The estimated turning point indicates that diversification improves loan quality only up to an optimal level. Credit risk is also found to be highly persistent over time, while inflation has a positive effect on non-performing loans. These findings suggest that maintaining an optimal level of diversification is essential for effective credit risk management and banking sector stability.

Abstract: The Gulf Cooperation Council (GCC) countries face the challenge of balancing their re-liance on hydrocarbon resources with ambitious renewable energy transition goals, in-cluding initiatives such as Saudi Vision 2030. Despite these commitments, renewable energy deployment in the region remains relatively limited, highlighting the need to better understand the factors that drive renewable energy consumption. This study investigates the macro-economic determinants of renewable energy consumption in the six GCC countries over the period 2000-2024 using a hybrid methodology of stepwise regression analysis and Random Forest machine learning. Panel data were compiled from the World Bank and the International Energy Agency. The econometric results identify Research and Development (R&D) expenditure and trade openness as the two most important determinants of renewable energy consumption, jointly explaining approximately 63% of the variation (Adjusted R² = 0.629). The Random Forest model supports these findings by ranking R&D expenditure as the most influential predictor, followed by trade openness. GDP, foreign direct investment, and inflation were dropped significantly from the final model because of multicollinearity and the struc-tural characteristics of GCC economies. The Random Forest model also achieved an out-of-sample R-squared of 0.425 with a low RMSE (0.032), demonstrating satisfactory predictive performance. Sub-period analysis further shows that the influence of R&D expenditure and trade openness become more pronounced after 2015, alongside the implementation of national energy transition strategies across the GCC. These findings underline the importance of technological innovation and economic openness in sup-porting the region’s energy transition that greater investment in R&D and stronger in-ternational trade integration can help renewable energy adoption.

Abstract: The rapid development of artificial intelligence, digital infrastructures, and autonomous production systems has generated increasing debate about the future direction of economic organization. For centuries, economic thought has been primarily concerned with scarcity: how societies allocate limited resources among unlimited needs. However, recent technological transformations reveal the emergence of new economic dynamics based on scalability, information abundance, network effects, and continuous value generation. This article empirically investigates whether elements of the proposed Infinity Economy are already visible within contemporary economic systems. Through a comparative analysis of artificial intelligence applications, digital knowledge platforms, open-source ecosystems, decentralized infrastructures, and automated production environments, the study examines how new forms of value creation differ from traditional scarcity-based models. The findings suggest that current economies remain hybrid systems where scarcity and abundance coexist. Nevertheless, important transformations are occurring: knowledge assets are becoming increasingly scalable, AI systems are generating new forms of cognitive production, and decentralized networks are enabling alternative models of coordination and value exchange. The article contributes to economic transformation research by providing empirical evidence for understanding the emergence of generative economic systems while highlighting the governance, ethical, and ecological challenges associated with their expansion.

Abstract: Three decades of research on finance and growth in the Middle East and North Africa disagree with one another. This paper argues the disagreement is manufactured by measurement and identification, not by the economies themselves. A transparent coverage rule fixes the sample at ten MENAT economies (the Middle East and North Africa plus Turkiye) over 1995-2021, and cointegration is assessed with a factor-based test suited to the data's strong common movements. Bank-ratio finance proxies carry only a weak and unstable long-run signal: the within-country correlation between the ratio and remittances has no common sign across economies, and the remittance term beside the ratio coefficient switches sign and significance across samples, so no stable estimate can be anchored on the ratio. Reframing the object of measurement resolves the impasse. A capabilities factor combining the multidimensional financial-institutions index with schooling carries a long-run elasticity of 0.16 to 0.24 per standard deviation, agreeing across pooled mean group, dynamic fixed effects with cross-sectionally robust errors, group-mean fully modified least squares, and a dynamic common correlated effects estimator reading the relationship through common factors. Trade openness contributes robustly across specifications. Policy that treats finance and education as separate levers asks the region the wrong question.

Abstract: For more than two centuries, economic theory has been grounded in the assumption that scarcity constitutes the fundamental condition of human societies and that the principal task of economic systems is the efficient allocation of finite resources. However, the accelerating convergence of artificial intelligence (AI), autonomous production systems, advanced robotics, additive manufacturing, decentralized digital infrastructures, and emerging quantum technologies increasingly challenges this foundational premise. These technological transformations are creating unprecedented capacities for continuous value generation, radically reducing the dependence of economic production on traditional constraints of labor, capital, and material scarcity. Consequently, the scarcity paradigm that has shaped classical, neoclassical, and even many contemporary economic theories is becoming progressively inadequate for explaining the dynamics of emerging socio-economic systems.This article introduces the Infinity Economy as a novel conceptual framework for understanding post-scarcity economic systems in the age of AI and quantum abundance. Rather than conceptualizing economics as the science of allocating scarce resources, the Infinity Economy redefines it as the science of designing and governing generative systems capable of continuously producing cognitive, informational, technological, and relational value. Integrating insights from complexity economics, artificial intelligence, innovation studies, digital political economy, systems theory, and governance scholarship, the paper develops a theoretical architecture that explains how autonomous production, distributed intelligence, decentralized infrastructures, and AI-mediated coordination are transforming wealth creation, exchange mechanisms, and institutional organization.The article makes three principal contributions. First, it critically examines the theoretical limitations of scarcity-based economics under conditions of accelerating technological abundance. Second, it proposes the Infinity Economy as an integrative paradigm grounded in generative value creation, distributed governance, cognitive capital, and regenerative economic systems. Third, it identifies the institutional, ethical, ecological, and governance challenges associated with the transition toward post-scarcity societies while outlining a future research agenda for economics beyond scarcity. By reconceptualizing economic systems as adaptive, self-generating, and AI-enabled ecosystems, the Infinity Economy provides a foundation for rethinking economic theory, public policy, and sustainable development in the twenty-first century.

Abstract: Digital services coordinate production networks, so restrictions on digitally enabled trade may propagate beyond the regulating economy. We model global manufacturing as a bounded system of country-sector nodes linked by fixed bilateral trade weights. The panel combines OECD Digital Services Trade Restrictiveness Index data with input-output-derived participation for 35 countries, 14 sectors, and 2014-2021 (3,904 observations). Country-sector, sector-year, and country-year fixed effects distinguish domestic regulation from partner exposure and test moderation by pre-sample network position and sector digital intensity. Country-clustered inference is supplemented by 999 restricted wild-cluster bootstrap replications. Average domestic and partner-exposure coefficients are imprecise. In contrast, partner exposure is more negatively associated with participation among top-quartile position nodes (interaction = -0.0947 per 0.1 index point; wild p = 0.007; Holm-adjusted p = 0.028). One exposure standard deviation corresponds to 3.9% of mean participation. The differential is concentrated in forward participation, persists with lagged exposure and multi-year pre-sample position, and remains negative in every leave-one-country-out estimate. It weakens under a within-country position cutoff, while sector digital intensity does not robustly moderate the association. The evidence is associational and supports a network-contingent rather than uniform account of digital trade restrictions.

Abstract: This paper examines the nexus between climate policy uncertainty, green transition dynamics, and macroeconomic productivity through a unified theoretical and empirical framework. Drawing on concepts from differential geometry, catastrophe theory, and nonlinear macroeconomics, we model the climate-macro system as a dynamic manifold in which observer-dependent climate expectations and curvature in economic state space interact to generate regime shifts and potential tipping points. The theoretical contribution extends existing integrated assessment and DSGE climate models by introducing a conceptual metric tensor that captures asymmetric information and heterogeneous beliefs among economic agents. We derive analytical conditions for equilibrium stability, bifurcation thresholds, and climate-induced singularities. Empirically, using an unbalanced panel of 100 countries over 1995–2025, we combine nonlinear panel threshold regression, Markov-switching VAR, quantile connectedness analysis, and dynamic factor-geometric estimation to identify the causal pathways through which climate policy uncertainty depresses total factor productivity growth. Results reveal a statistically and economically significant threshold effect: the negative impact of carbon intensity on productivity more than doubles when climate policy uncertainty exceeds an estimated threshold of 48.3 index points. Quantile connectedness analysis further documents pronounced tail-risk spillovers at the lower and upper quantiles, suggesting that green transition shocks propagate nonlinearly across countries and sectors. Robustness checks using system-GMM, two-stage least squares with geopolitical risk instruments, and sub-period analysis confirm the stability of the main findings. The analysis has concrete policy implications for the design of credible and gradual climate transition pathways, particularly for developing and emerging economies.

Abstract: overty-alleviation relocation has been a key policy for breaking spatial poverty traps, but post-relocation sustainability depends on livelihood reconstruction. This study investigates the association between women’s non-agricultural employment and the economic resilience of relocated households, with attention to intra-household resource allocation. Drawing on four-wave household survey data from southern Shaanxi (2016, 2018, 2020, 2022), we develop an analytical framework linking female employment, household capabilities, and resilience, and apply Tobit regression, propensity-score matching, and pathway analysis. Results show a robust positive association, controlling for household characteristics and sample-composition differences. Pathway evidence reveals that women’s employment enhances buffering capacity (higher income and savings, lower debt), learning capacity (greater development-oriented spending and children’s cultural participation), and self-organization capacity (expanded internet use, social networks, policy awareness, and access to support). These findings suggest that women’s non-agricultural employment restructures household resource allocation and developmental investment, rather than merely shifting labor from farm to market. Policies supporting women’s employment, skills training, public services, digital access, and care systems are thus essential for consolidating poverty-alleviation gains and fostering resilient communities.

Abstract: Sustainability research explains pro-environmental conduct largely through conscious attitudes, awareness and stated intentions, yet a substantial psychological literature indicates that agents have no transparent access to the determinants of their own behaviour. This paper asks whether an environmental norm can remain evolutionarily stable when the agents who carry it cannot say why they act. Constitutive self-opacity is formalised as a microfoundation of the mutation term in a replicator-mutator dynamic defined on a two-strategy conformity game with a private cost of green action. Opacity is decomposed into an intensity parameter and a directional narrative bias, and the resulting cubic vector field is studied through Lyapunov and bifurcation methods with supporting numerical continuation. Three results follow. Opacity destroys both absorbing states and compresses the set of long-run outcomes towards the narrative bias. The green attractor is strictly more fragile than the brown one, by a factor determined by the ratio of the conformity benefit to the private cost. Above a critical intensity bounded above by half the conformity benefit, bistability collapses through a saddle-node bifurcation whose surviving branch is green if and only if the narrative bias exceeds the coordination threshold. Awareness-centred policy therefore acts on a channel that self-opacity has already closed, whereas the composition of the circulating narrative stock remains operative.

Abstract: For nearly a century, development has been measured through increasingly sophisticated but still incomplete lenses. Gross Domestic Product (GDP) helped governments quantify national production after the Great Depression and became central to post-war macroeconomic management. The Human Development Index (HDI) later shifted the debate from national income to human choices, health, education, and living standards. Yet today’s development challenges are more dynamic, multidimensional, spatially uneven, and uncertain than the instruments designed to measure them. Moving forward, countries need metrics that not only describe current welfare but also predict future human potential and identify where public and private investments can unlock the highest developmental returns. This paper proposes two connected concepts: the Dynamic Human Potential Index (DHPI) and Predictive Development Economics (PDE). DHPI would measure the evolving capacity of individuals, households, communities, and economies at large to convert endowments into productive, resilient, and dignified lives. PDE would use frontier computing powers of artificial intelligence, predictive analytics, geospatial data, household surveys, administrative records, climate models, and economic complexity tools to guide investment choices. Applied globally, and especially in low-income Sub-Saharan African contexts, this approach could help countries move from static rankings built on past performance to actionable investment typologies over the time horizon. The proposal is intentionally open: economists, social scientists, statisticians, technologists, governments, investors, and communities should collaborate to build, test, govern, and adapt the model responsibly.

Abstract: This research analyses the heterogeneous effects of digital infrastructure on sustainable economic growth in five developing countries (Egypt, India, Kenya, Saudi Arabia and Sudan) using the period 2014-2025. We use panel fixed effects with Driscoll-Kraay standard errors to investigate the effect of internet penetration, mobile broadband and fixed broadband on the GDP per capita growth. Our results suggest that digital infrastructure has a statistically and economically significant impact on economic growth. Internet penetration yields the largest benefits, followed by mobile broadband, whereas fixed broadband is not statistically significant in the full model, which is reflective of limited access in these countries. An exploratory Random Forest analysis with the important caveat of limited sample size suggests that internet penetration is the most important predictor of growth, followed by mobile broadband and human capital. However, these machine learning results should be considered exploratory given the small sample (N=60, or N=48 when excluding Sudan) and should not be over-interpreted. Our heterogeneity analysis finds that internet penetration drives growth in middle-income countries (Egypt, India), while mobile broadband drives growth in low-income countries (Sudan, Kenya). The moderation by human capital is large: the marginal impact of internet penetration more than doubles once average education exceeds six years. However, we note that this threshold is illustrative, based on the distribution of the sample and not necessarily a policy cutoff. The results have implications for SDG 4 (quality education), SDG 9 (infrastructure and innovation) and SDG 10 (inequality reduction). However, with our purposively selected five-country sample, these results are better considered as case-based evidence rather than statistically representative of all developing economies. The stark digital divide is evident in the 87% internet penetration in MENA countries compared to 44% in Sub-Saharan Africa and underscores the need for context-specific policy approaches. We suggest that low-income countries focus on expanding mobile broadband and middle-income countries make complementary investments in internet infrastructure and human capital, but emphasize that these policy suggestions are indicative rather than conclusive.

Abstract: Countries in European union possesses formidable institutional assets, characterized by world-class research, robust regulatory frameworks, and a tradition of human-centric governance, however continues to lag behind the United States, China, Japan, and South Korea in translating knowledge into markable and scalable, innovation and economic growth. With a population of approximately 449 million, the EU represents one of the world's largest markets, yet its GDP per capita now stands at nearly 30 percent below that of the United States, with medium-term growth projections remaining weak as reported the International Monetary Fund (IMF). While European innovators lead in AI and quantum patent filings, the continent captures only 6% of global AI venture capital compared to 75% for the United States. The demographic dividend of Europe's relatively youthful population, albeit aging population, represent yet another potential for development in the era of digital speed. However, youth unemployment averaging 14.5% across the EU, rising to over 20% in southern member states constitute yet another challenge. Drawing on institutional economics and comparative analysis of Northeast Asian models, we propose a Knowledge- Institutions -Execution, Markets -Human Welfare framework to diagnose Europe's bottlenecks and chart a path for strategic renewal over the next decade. Drawing on the foundational work of North (1990), Acemoglu and Robinson (2012), and the transaction cost economics of Coase (1937), we argue that Europe's competitiveness challenge is fundamentally institutional characterized by slow pace to connect research excellence to execution, scale, and market deployment. The window of opportunity remains largely open, but closing it requires moving from regulatory stewardship to executional urgency, transforming institutional quality from a source of inertia into a competitive advantage. We propose new performance metrics centered on institutional velocity, youth innovation absorption, and AI deployment velocity to monitor progress towards strategic renewal.

Abstract: In the arid regions of southeastern Tunisia, international migration—often driven by declining agricultural yields under the effects of climate change—can strengthen agro system resilience when part of the remitted funds is invested in adaptation practices. However, its effect may become neutral or even negative when remittance volumes are low or when beneficiaries are reluctant to invest. This study aims to analyze the impact of migration on climate change adaptation practices and agricultural production in the coastal oases of southeastern Tunisia. The methodology relies on a literature review, a field survey of 212 households, and statistical and econometric analyses. Descriptive analysis by migration status reveals a slight predominance of migrant households in terms of adaptation practices and agricultural outputs. Furthermore, the econometric model shows decreasing returns to scale (0.52 + 0.45 = 0.97 < 1). Although capital and labor influence production in a less than proportional manner, migration plays a significant role in improving income and the share saved for productive self financing. For identical levels of capital and labor, migrant households produce on average 35.67% more than non migrant households. The study highlights gaps and opportunities for adaptation through migrant remittances. Policies should further mobilize migrants to engage in climate change adaptation processes, particularly in vulnerable regions, by relying on reforms in agricultural investment, awareness raising, extension services, and cooperative land management governance.

Abstract: Ecological efficiency of grain production has attracted growing scholarly interest in recent decades. Agricultural insurance alleviates operational risks embedded in grain cultivation, which further promotes improvements in ecological efficiency. Using provincial panel data covering 31 provincial-level administrative regions of China over the period 2001–2021, this study adopts the super-efficiency SBM model to quantify and analyze agricultural insurance development as well as the ecological efficiency of grain production nationwide. The empirical results yield three core conclusions: (1) the advancement of agricultural insurance significantly raises grain production ecological efficiency. (2) Carbon emissions exert a significantly negative impact on ecological efficiency, demonstrating that carbon abatement policies are effective in boosting the green performance of grain production. (3) carbon emissions serve as a significant moderator in both Eastern and Western China. Specifically, the enforcement of carbon reduction policies amplifies the positive marginal effect of agricultural insurance on grain ecological efficiency. Drawing on the above empirical evidence, we propose three policy implications to improve grain production ecological efficiency: sustain the high-quality development of agricultural insurance, formulate differentiated eco-environmental regulations that accommodate regional heterogeneity, and expand fiscal subsidy programs for grain producers.

Abstract: This study examines manufacturing firms listed on China’s A-share market from 2014 to 2024 using a triple-difference model to investigate the effect of green investment on the strategic resilience of semiconductor firms under Sino-US trade shocks. The results show that green investment considerably enhances strategic resilience, and this effect remains robust across parallel-trend and other robustness tests. Mechanism analysis indicates that green investment improves resilience by reducing operational performance volatility and increasing equity concentration. Heterogeneity analysis shows that the positive effect on human capital resilience is stronger among non-heavily polluting firms and firms in highly marketized and non-Eastern regions. Meanwhile, the effect on innovation resilience is more pronounced among non-heavily polluting firms and firms in highly marketized and Eastern regions. These findings provide practical and policy insights for strengthening human capital and innovation resilience in semiconductor firms, enhancing their capacity to withstand external shocks, and optimizing green investment strategies.