Community charging places electric vehicle (EV) chargers in communal spaces such as shopping malls, public parking, and activity centers embedded in local street networks. It creates a spatial equilibrium problem with an access and coupling structure that corridor charging along freeways does not exhibit. Multiple origin–destination pairs and routes converge on the same community charger via overlapping local arterials, so charger waiting times depend on the aggregate inflow from many paths and a single hardware capacity simultaneously constrains feasible flow for many travelers. On the physical network, these features make the generalized link costs non-separable across the links feeding a shared station. We formulate community charging as a capacity-constrained spatial equilibrium with station-level capacity side constraints, and we show it is exactly a Beckmann program with arc-capacity side constraints on a station-expanded network, restricted to range- and access-feasible paths. The capacitated user-equilibrium theory therefore applies, while the community-charging structure lies in the admissible paths and in the queueing origin of the station cost and capacity. We prove the cross-link symmetry that certifies the potential on the physical network, characterize the KKT solution as a generalized user equilibrium with endogenous station prices, and establish uniqueness of equilibrium flows under strict convexity. To solve the program, we develop a primal–dual decomposition: an outer augmented-Lagrangian loop adjusts station-level shadow prices on capacity, and an inner column-generation loop solves parallelizable path-flow subproblems for each OD pair under the current prices. Numerical experiments on a toy network, the Sioux Falls network, and two real-world community-charging networks show that the proposed method consistently attains equilibrium (to the reported tolerances) and outperforms a path-based interaction-ignored algorithm and a link-based interaction-aware Frank–Wolfe algorithm in computational efficiency.
This paper examines impulse response estimation in macroeconomic analysis using Vector Autoregression (VAR), Local Projections (LP), Empirical-Bayes Minnesota BVAR (EB-BVAR), Penalised Local Projections (PLP), and Bayesian Network Vector Autoregression (BNVAR). We conduct Monte Carlo simulations calibrated to a U.S. macroeconomic dataset and consider sparse, dense, moving-average, and network data-generating processes. The results reveal substantial differences in finite-sample performance across estimators and highlight the importance of regularisation. BNVAR performs particularly well under sparse and network structures, while EB-BVAR achieves the lowest RMSE under the dense and moving-average designs. PLP consistently improves upon standard LP. Overall, the findings show that the relative performance of impulse response estimators is strongly dependent on the underlying dynamic structure, with BNVAR providing a competitive regularised approach, particularly in sparse and network-driven environments.
To develop the traffic potential of regional markets, general aviation (GA) airports have gradually been integrated into the public transport network in recent years. This study develops an integrated model for hub selection, flight frequency assignment, network connectivity and aircraft type determination. The results show that the integration of GA airports leads to more hubs and more concentrated route structures. The transfer connections are significantly enhanced; the triangular linkage among hubs improves network stability and efficiency. Airport functions become further differentiated across regions, with transfer hubs and primary hubs clearly separated, which is also reflected in the differences in their intra- and extra-region connectivity. We further analyze fleet composition and offer strategic recommendations for airlines to explore regional markets, such as forming alliances or introducing new aircraft types. These findings provide decision support for airline regional market strategies and government policy formulation.
The reach and direction of supplier–customer relationships are key to understanding firms’ market access and regional economic integration. We examine inland–coastal connectivity and the factors associated with supplier–customer tie dynamics in China’s corporate supply-chain network. Using major relationship disclosures by A-share listed firms for 2014, 2017, 2020, and 2023, we combine spatial analysis of directed networks with stochastic actor-oriented models for three consecutive transitions. The analysis identifies three main findings: (i) Network expansion accompanies asymmetric regional integration. Inland-supplier-to-coastal-customer ties increased from 22.6
When identifying buildings constituting consistent streetscape skeletons with small differences in the heights and setbacks, we face the following challenges from a pedestrian’s perspective: (1) how to precisely define the spatial extent of streetscape skeletons; and (2) how to identify consistent 3D streetscape skeletons. Although methods have been developed for quantifying the degree of difference between the heights and setbacks of adjacent buildings on a 2D map, called the relative spatial variability in building heights and setbacks, the relative spatial variability in streetscape skeletons forming a 3D streetscape is yet to be quantified. This is because the neighbourhood relations among buildings composing 3D streetscape skeletons, based on what a pedestrian sees on the street, remain unclear. To address these issues, when buildings composing a 3D streetscape at a location on the street centreline are projected onto the virtual screen, vertical to the ground, and street centreline, they are regarded as being adjacent to one another on the screen, which is the neighbourhood relations in terms of 3D streetscape composition. This study thus aims (1) to develop a method for visualising this neighbourhood relation on a 2D map; and (2) to identify consistent streetscape skeletons from a pedestrian’s perspective based on a new local indicator of spatial association considering this neighbourhood relation. The method can help urban planners evaluate the effectiveness of policies for maintaining consistent streetscape skeletons by identifying where buildings forming consistent or inconsistent 3D streetscape skeletons are spatially clustered from a pedestrian’s perspective via a 2D map.
