Search Results (358)

Online ride-hailing platforms increasingly rely on differentiated incentive mechanisms to regulate driver participation and balance supply and demand. However, drivers’ adaptive responses to such incentives introduce dynamic feedback and uncertainty that static equilibrium models fail to capture. This study develops a dual-layer Stackelberg–evolutionary game framework in which the platform acts as a strategic leader setting the order allocation rates and prices, while heterogeneous drivers adapt their working-hour strategies through evolutionary dynamics. Using operational data from Ningbo, China, we calibrated the demand elasticity and driver cost parameters and identified endogenous fatigue-cost thresholds that govern regime shifts in strategy dominance. Simulation results show that uniform incentives tend to drive the system toward single-strategy lock-in, whereas differentiated order allocation and pricing effectively sustain multi-strategy coexistence and mitigate extreme supply polarization. The findings reveal how platform-led differentiation reshapes the evolutionary fitness landscape of drivers, providing actionable guidance for incentive design aimed at stabilizing supply structures, improving platform revenue, and protecting driver welfare. Full article

This study examines how zoning regimes mediate the capitalization of officially assessed land values into housing prices in a high-density metropolitan housing market. Using transaction-level housing data from New Taipei City, Taiwan, we estimate a hedonic pricing model combined with a boundary-based spatial comparison that restricts observations to properties located near zoning borders. The results indicate that official land values are significantly associated with housing prices but are only partially capitalized, with an estimated elasticity of approximately β ≈ 0.37 in the baseline specification. Interaction models further reveal that capitalization elasticities vary systematically across zoning regimes, suggesting that planning regulations influence how administratively determined land values are translated into market prices. These heterogeneous capitalization patterns remain stable across alternative boundary bandwidths and model specifications. The findings highlight the institutional role of zoning systems in shaping the relationship between administratively assessed land values and housing market outcomes. More broadly, the study contributes to the literature on housing market regulation by demonstrating how land-use institutions mediate price formation processes in densely developed urban environments. Full article

While pricing policy has emerged as a critical demand-side lever for decarbonizing mobility, its bidirectional effects on modal shift remain unexplored. Dynamic pricing in high-speed rail (HSR) creates a double-edged environmental outcome: advance discounts attract passengers from aviation, yet last-minute premiums may reverse these gains. Using 2.4 million price observations from Madrid–Barcelona (2019), we introduce a carbon leakage framework that quantifies this phenomenon within a multi-source validated framework. Our analysis reveals a structural tension: while early-bird pricing attracts 274,431 annual passengers from aviation—saving 23,650 tonnes CO₂/year—last-minute scarcity premiums systematically drive passengers back to air travel. Multi-source calibrated elasticity ($\epsilon =-0.95$, validated through triangulation across CNMC corridor data, meta-analytic evidence, and recent empirical studies within the range $[-1.91,-0.75]$) shows that 22.3% of last-minute tickets exceed the EUR 120 aviation threshold, creating 1511 tonnes CO₂ leakage annually (6.4% offset of gross savings). Critically, this leakage ratio is shown to be structurally independent of elasticity specification, being determined by the price distribution shape rather than demand parameters. Scenario analysis suggests that under static assumptions, price caps at EUR 110–120 would eliminate leakage while preserving an estimated 94% of operator revenue, though general equilibrium effects remain unmodeled. These findings identify illustrative scenario thresholds for carbon-aware revenue management, demonstrating that demand-side decarbonization requires not only attracting passengers to sustainable modes but also preventing their reversal to high-carbon alternatives. Full article

This paper develops a bilevel multi-market coupling optimization framework to analyze the strategic participation of nuclear power plants in modern electricity systems where energy, reserve, and capacity markets are simultaneously cleared. The upper-level problem represents the Independent System Operator’s objective of maximizing system-wide social welfare under network, reserve, and carbon-cap constraints, while the lower-level problem captures the nuclear operator’s profit maximization subject to ramping limits, minimum uptime requirements, fuel-cycle depletion, and deliverability restrictions. By embedding these technical constraints into a bilevel structure reformulated through tractable complementarity conditions, the model captures the interdependence of nuclear scheduling, reserve deployment, capacity commitments, and carbon compliance in a single optimization environment. The proposed framework is applied to a stylized but realistic case study with 96-h time resolution, 12-bus network topology, and detailed representations of wind variability, demand elasticity, and emission caps. The model quantifies how nuclear participation displaces 40,000 tCO₂ over the horizon, raises producer surplus by 12 percent, and increases total social welfare by nearly 18 percent when all three markets are coupled, relative to an energy-only benchmark. Nuclear profitability is shown to be highly sensitive to renewable volatility, with ±20 percent swings in wind uncertainty altering profits by 0.24 million USD. Reserve deliverability emerges as the second most influential driver, while policy variables such as carbon price shifts play a smaller role. Reliability analysis based on the complementary cumulative distribution of unserved energy demonstrates that joint market clearing reduces the probability of load shedding at the 0.5 percent threshold from 8 percent in energy-only markets to 2 percent under full coupling. Overall, the study provides the first integrated modeling treatment of nuclear bidding across energy, reserve, and capacity markets within a bilevel optimization framework. By jointly considering operational constraints and policy targets, the framework reveals how nuclear power can simultaneously improve economic efficiency, enhance system reliability, and support carbon mitigation. The results highlight that nuclear’s value extends well beyond baseload energy provision, with multi-market strategies offering measurable gains for both individual operators and social welfare under conditions of uncertainty and constraint. Full article

This paper investigates the fundamental mechanisms of technological change in complex systems by analyzing how the evolution of embedded subsystems dictates the trajectory and sets the tempo of a host technology. Building on the theoretical framework of technological parasitism, the study conceptualizes host systems having a modular architecture—such as smartphones—as evolving through dynamic, coevolutionary interactions with their constituent subsystems. These relations gradually shift from parasitic reliance to mutualistic and ultimately symbiotic interactions. Central to this research is the concept of subsystems as pacemakers. Methodologically, this research employs a longitudinal, mixed-methods approach, combining an 18-year case study of the iPhone (2007–2025) with time-series regression and log–log hedonic pricing models. Key findings are: (a) Temporal precedence: Advances in subsystems (e.g., Bluetooth protocols) consistently precede host releases. The integration lag has contracted from three years to one, signaling an acceleration in symbiotic coupling and highlighting Bluetooth as a systemic pacemaker whose evolutionary tempo anticipates shifts in the wider smartphone architecture. (b) Differential evolutionary pressure in technological host systems: While camera resolution exhibited the highest exponential growth (+16.73%), it remained a secondary driver of systemic evolution. (c) Economic pacemakers: Hedonic analysis identifies battery life as the dominant evolutionary predictor (standardized beta = 0.77). With an elasticity of approximately 0.30, a 1% gain in battery performance correlates to a 0.3% increase in nominal price, whereas display and camera resolution exert significantly less influence on the system’s valuation and trajectory. These findings reveal that subsystems evolve—and exert influence—at different speeds and with different degrees of systemic leverage. Overall, the proposed theory shows that subsystem evolution functions as a leading indicator of forthcoming host–system transitions. By identifying which subsystems act as temporal pacemakers, this research contributes new design rules for forecasting technological generations and optimizing R&D strategies in complex, multi-component innovations. Hence, the study demonstrates that mastering complex innovation requires a granular understanding of the asynchronous rhythms between a host technology and its constitutive parts. Full article

Background: This study revisits whether oil revenue windfalls translate into higher socio-economic welfare in oil-exporting economies and explains why oil price booms often fail to generate sustained gains in real GDP per capita. Methods: Using annual data for ten oil-exporting countries over 1990–2024, we estimate country-specific ARDL/ECM models under a unified specification. The dependent variable is log real GDP per capita, explained by log real oil prices, the log share of government expenditure in GDP, population growth, and world GDP growth, with political and devaluation dummies where relevant. Results: Cointegration and significant error correction terms hold for most exporters, but adjustment speeds differ sharply. Long-run oil price elasticities are heterogeneous: strongly positive in Qatar, weak or insignificant in several cases (including Azerbaijan), and negative in a post-rentier pattern (UAE/Oman). Fiscal and demographic channels emerge as systematic constraints: government expenditure shares are often negatively associated with long-run welfare, and population growth typically reduces GDP per capita. World GDP growth is generally positive but uneven in significance. Conclusions: Resource use is conditional: welfare outcomes depend on fiscal regimes, demographic pressures, and structural transformation rather than windfall size alone. Full article

Virtual power plants efficiently aggregate distributed energy resources with small capacities but large quantities to participate in electricity market transactions through advanced control technologies. As the number of distributed power sources increases, issues such as output volatility and optimal decision-making need to be addressed. To tackle these problems, this paper proposes an optimal economic dispatch strategy for virtual power plants that accounts for flexible resource responses under uncertain scenarios. First, a combined prediction model based on variational mode decomposition (VMD) and an improved bidirectional multi-gated long short-term memory network is established to achieve accurate prediction of renewable energy output. On this basis, a price–demand elasticity matrix is constructed to characterize the spatiotemporal coupling effect of time-of-use electricity prices on load, and a demand response model based on optimal time-of-use electricity pricing is established. Meanwhile, an improved Particle Swarm Optimization (PSO) algorithm is employed to achieve efficient and precise solutions. Finally, the effectiveness and feasibility of the proposed method are validated and illustrated through an improved IEEE-33 bus test system. Full article

This paper develops finite-series solutions of a hybrid system of interconnected partial differential equations for computing the conditional moments of regime-switching extended constant elasticity of variance processes with generalized drift and diffusion coefficients. The regime-switching mechanism is modeled by a continuous-time, finite-state, irreducible Markov chain with m regimes, for any integer $m\ge 1$. For any real $\gamma >0$, we identify a tractable class of processes where the ${\gamma }^{\mathrm{th}}$ conditional moment admits an explicit finite power series representation in the initial state, arising from the polynomial structure. The analytical framework is derived via a Feynman–Kac representation adapted for regime-switching diffusions and validated for accuracy and efficiency using Monte Carlo simulations. In addition, we investigate the asymptotic behavior of the first conditional moment for a two-state regime-switching constant elasticity of variance process with nonlinear drift, emphasizing the effects of symmetry in the Markov intensity matrix and comparisons with the corresponding linear-drift case. Applications in futures pricing demonstrate the framework’s relevance for derivative pricing and risk management. Full article

Drought is a slow-onset hazard whose economic impacts can propagate across sectors with multi-year delays. This study develops a non-linear autoregressive model with exogenous drought inputs (ARX) to assess whether U.S. drought severity, measured by the Drought Severity and Coverage Index (DSCI), contains incremental predictive information for monthly stock returns. Using weekly DSCI and stock price data from 2013 to 2023, we constructed monthly compound returns and multi-year drought lags spanning 1–5 years for four sector-representative firms: a water utility (American Water Works, AWK), two food service firms (Chipotle Mexican Grill, CMG; Starbucks, SBUX), and an industrial manufacturer (Tesla, TSLA). We compared regularized linear ARX baselines (Elastic Net, Ridge) with a non-linear Histogram Gradient Boosting Regressor (HGB) ARX model and used permutation importance to diagnose drought-relevant lag horizons. Results showed a clear, delayed drought signal for the water utility, with a dominant ~48-month drought lag, consistent with multi-year transmission through operations, regulation, and investment cycles. In contrast, drought lags added limited or unstable information for the food service firms and negligible information for TSLA, whose dynamics were dominated by non-drought drivers. Overall, the findings indicate that drought–return relationships are sector-specific and can emerge at multi-year lags, and that non-linear ARX models provide a flexible tool for detecting these delayed climate-risk signals. Full article

This paper analyzes long-term trends in the apparent consumption and external deficit of wood and wood-derived products in Tunisia using annual data covering the period of 1975–2024. Tunisia’s limited forest resources and increasing domestic demand have generated a structural dependence on imports, reflected in a persistent and widening trade imbalance. To investigate the determinants of this situation, ten econometric log–log models were estimated for the major product categories, including sawnwood, panels, veneers and plywood, newsprint, printing paper, and wrapping paper. The models assess how apparent consumption and external deficits could be explained through changes in income levels (GDP per capita), prices, technological progress, and labor costs. Income elasticity is found to be the primary driver of demand, while price effects remain relatively weak across most categories. Based on the estimated elasticities, demand projections were developed up to 2050 under three alternative income growth scenarios: a trend scenario (1.2% annual growth), a pessimistic scenario (0.6%), and an optimistic scenario (2%). Under the trend scenario, total demand for wood and wood-derived products is projected to increase by about 52% by 2050, leading to a further widening of the gap between domestic supply and demand, with higher growth rates under the optimistic scenario and more moderate increases under the pessimistic one. These findings highlight the challenges Tunisia faces in managing the increasing pressure on its forest resources and underscore the need for strategic planning to ensure the long-term sustainability of the wood and wood-derived industries. Full article

Background/Objectives: Sugar-sweetened beverage (SSB) consumption has been linked to obesity, metabolic diseases, and rising healthcare costs. This study aimed to assess the impact of a 20% excise tax on SSBs in Brazil on obesity/overweight prevalence, seven musculoskeletal and cardiovascular diseases, and related healthcare costs, with their associated impacts on health inequalities. Methods: Using 2017/2018 Brazilian Household Budget Survey data for baseline consumption and own- and cross-price elasticities for taxed beverages, we estimated changes in caloric consumption for the entire population and for lower- and upper-income quartiles. The PRIMEtime dynamic individual-level simulation model projected body weight changes, lifetime Quality-Adjusted Life-Years (QALYs), healthcare costs (discounted at 5%), and disease cases (20-year horizon). Results: A 20% excise SSB tax was projected to reduce obesity prevalence by 1.7 percentage points in men and 1.5 percentage points in women, from baseline rates of 19.8% and 23.6%, respectively. Lifetime gains were estimated at 17,878 QALYs per million men and 12,181 per million women, alongside healthcare cost savings of Int$520 million. Impacts varied by income, with smaller health gains in the lowest quartile and higher among the wealthiest. Over 20 years, the tax could avert 1784 cases of type 2 diabetes mellitus/100,000 adults (52% in men) and 1070 cases of ischemic heart disease/100,000 adults (80% in men). Conclusions: A 20% excise SSB tax in Brazil could yield large health and cost benefits. With the recent approval of the Selective Tax under Complementary Law 214/2025, Brazil has a timely opportunity to translate these projected benefits into effective public health policy. Full article

The present study examined the impact of agricultural exports on economic growth in Lambayeque, Peru, during the period 2010–2023. An ordinary least squares (OLS) econometric model was employed to analyze the relationship between gross value added (GVA) and key macroeconomic variables, including agricultural exports, private investment, real wages, terms of trade, and the real multilateral exchange rate. The findings indicate that the model possesses considerable explanatory power (R² = 0.973) and that agricultural exports exert a positive and significant influence on regional GVA. In addition, private investment and real wages demonstrate positive elasticities, while terms of trade exhibit a negative relationship with regional economic growth. This highlights Lambayeque’s vulnerability to external price shocks. The study thus underscores the pivotal role of the Olmos Project, which has been instrumental in transforming arid land into fruitful agricultural zones through the implementation of an irrigation system encompassing over 22,000 hectares. This initiative has not only augmented agricultural exports, accounting for an impressive 90% of Lambayeque’s supply, but also contributed significantly to regional economic development by supporting employment generation and poverty reduction. Nevertheless, the presence of negative terms of trade indicates that the regional economy exhibits structural vulnerability in the face of external shocks. Notwithstanding the intrinsic limitations of regional, trade, and macroeconomic statistics, an understanding of the correlation between agro-exports and economic growth in a paradigmatic region of northern Peru provides substantial evidence for formulating policies to enhance the competitiveness and sustainability of the agro-export model. Full article

Community public sport facilities are core carriers of the national fitness public service system, with their supply–demand alignment directly linked to megacity governance efficiency and residents’ well-being. To address structural issues, such as “human–land imbalance” in facility layout, this study uses the 2010–2024 panel data from Shanghai’s 16 districts, applies supply–demand equilibrium theory, and integrates quantitative methods to analyze spatio-temporal supply–demand coupling and identify key influencing factors. The study yields four key findings: (1) The spatial distribution of facilities and population demonstrates a differentiated evolutionary trajectory marked by “central dispersion and suburban stability”. (2) Supply–demand alignment has continuously improved, as evidenced by the increase in coordinated administrative districts from six to thirteen. Nonetheless, the distance between sports facilities and population centers widened, suggesting that spatial adaptation remains incomplete. (3) Urban population growth exerts a significant positive impact on facility supply. Elasticity coefficients are generally high in suburban areas, while negative elasticity is detected in some central urban areas due to population outflow. (4) Facility construction intensity and residential activity intensity are core driving factors, with economic conditions, transportation infrastructure, and housing prices acting as key supporting factors. This study overcomes traditional aggregate-quantity research limitations, reveals megacity facility supply–demand “spatial mismatch” dynamics, and provides a scientific basis for targeted public sports facility layout and refined governance. Full article

Domestic and foreign capital and consumption goods are imperfect substitutes in production and demand functions of the growth model by Bardhan–Lewis. We extend the model by introducing exogenous technical progress and allow for foreign debt dynamics without dropping domestic capital goods. Trade and growth are mutually affecting each other. Trade may speed up or decrease growth in theory with and without technical progress in comparison with the Solow–Swan model. Steady-state growth rates include that of world income, and the income and price elasticities of export demand. The dynamic process of the economy is analyzed in terms of exports and foreign debt, and both as a share of a stock of imported capital goods. There are multiple steady states where imported capital goods are paid for by high exports and debt, low debt and low exports, or even negative debt and low exports. A stable VAR with data for Brazil shows that the high-debt steady state is relevant for this country. Steady states with high and low debt are saddle-point stable and the steady-state medium debt is stable. Neoclassical standard results appear as two special cases. We link the model to several strands of literature. Full article

We analyze the relationship between collusion sustainability in an infinitely repeated game using trigger strategies and the elasticity of substitution. To this end, we adopt a demand function with constant elasticity of substitution between the differentiated goods. Since our model exhibits a one-to-one relationship between the elasticity of substitution and demand price elasticity, we demonstrate that a larger elasticity decreases the sustainability of collusion. Intuitively, a more elastic demand function causes the increase in deviation profits to compensate for the increase in collusive profits, making collusion less easily sustained. This result holds regardless of whether firms compete in quantities or prices. Full article