Intercity Networks Research Articles

A case for altruistic cities

Intercity cooperation appears to be thriving, as evidenced by the growing number of regional and international intercity networks. However, a closer examination of these interactions reveals that their scope and depth are often limited, with information sharing, delegation visits, and mutual learning being the most common forms of engagement. Consequently, cities are frequently perceived as participating in intercity networks to “add flowers to the brocade”—a gesture of enhancement—rather than to achieve any substantial improvement in their functional capacities.

How much is too much? Inter-city brokerage in ICT industry innovation networks

ABSTRACT In today’s world, where global connectivity drives economic growth, it is essential to understand how cities can leverage intercity networks for innovation. This study explores the role of strategic network brokerage in enhancing cities’ innovation performance in the Information and Communications Technology (ICT) sector. We propose an inverted U-shaped relationship between inter-city network brokerage and ICT innovation performance, suggesting that optimal brokerage levels can maximize innovation outputs. Furthermore, we anticipate that city ICT specialization and internet maturity will positively moderate this relationship. Our analysis, using negative binomial regression on a panel of 65 cities from 2002 to 2015, largely supports our hypotheses, highlighting that cities with advanced ICT capabilities achieve higher levels of innovation at the same brokerage level. We discuss the implications of these findings for city policymakers and ICT firms.

The formation of external innovation linkages of the periphery within multiplex regional networks: a multilayer exponential random graph modelling approach

ABSTRACT Innovation in peripheral areas relies more on external linkages to overcome peripherality than in core areas. We study how these linkages are formed, especially through the interaction with diverse networks like transport and investment networks that connect the periphery with external areas. Using data from peripheral Zhejiang, China, we construct a four-layer network with co-patenting and three explanatory layers: transport, investment, and university headquarters-branch linkages. We use multilayer exponential random graph modelling to examine factors driving the formation of the co-patent network, specifically cross-layer interactions between co-patenting and the other three networks. Results show a tendency for the periphery to be linked to the core through co-patenting. All the other three layers have a positive association with the co-patent network, and their intersections show a stronger correlation with the network. This is especially true for the university headquarter-branch network and its intersection with the investment network. The main contribution of this paper is expanding the analysis of peripheral innovation by considering broader intercity networks rather than solely focusing on innovation linkages. Our findings also have policy implications for overcoming innovation constraints in peripheral areas and reducing spatial disparities in Zhejiang and similar regions.

Addressing uneven development through state-steered intercity cooperation? Insights from Shenzhen–Ganzhou cooperation plan-making

ABSTRACT Attention being paid to the implications of intercity networks on uneven development is increasing. To inform the discussion, this study examines China’s state-steered matching programme that is characterised by ‘forming city networks under hierarchy’. By investigating the interactive dynamics of the plan-making process and the nature of the collaboration plan generated under the particular institutional arrangement, we argue that the presence of the nation-state and the ‘left-behind’ city’s proactive strategies are important to ensure commitment from the developed city and thus make the cooperation plan fulfil both parties’ needs. We conclude by discussing the potential mechanisms and implications of the state-steered matching programme on addressing uneven development.

Adiabatic weak coherent MHz linewidth O-band single-photon carrier for low erroneous phase decoding

For weak coherent single-photon secure data communication among short-reach metropolitan intra-/inter-city networks at the O-band (1250-1350 nm), the commercially available semiconductor laser sources are emerging but still suffering from high single-mode-fiber (SMF) loss, broad linewidth, and unstable wavelength. To overcome such disadvantages for enabling the efficient phase-coding link with sufficient secure key rate, a specifically designed adiabatic package with active temperature-/current-feedback control is proposed for the paired O-band MHz-linewidth master-to-slave injection-locked DFBLDs and a polarization-maintaining 1-bit-delay interferometer is stabilized with using a passively adiabatic cell to achieve accurate differential phase decoding. Even though, the phonon-induced phase fluctuation still occurs at rising and falling edges of the decoded long-pattern secure data bits delivered from the slave DFBLD, which is mainly attributed to the intra-cavity heating under excessive free-carrier generation via the master DFBLD injection. To stabilize the differential-phase-shift (DPS) keying protocol, the phase-code distortion caused by over-injection-induced Auger heating is effectively suppressed by reducing the overly biased injection with precise master-injection-level control. The rising-/falling-edge damping distortion of the phase-shift-encoded secure bit-stream envelope is suppressed by appropriately decreasing the DC bias current and adjusting the AC encoding amplitude of the master DFBLD. Such operation reduces the incorrect π phase shift in the injection-locked slave DFBLD biased at optimized below-threshold DC offset, thus allowing single-photon DPS-keying data transmission over 15-km SMF with slightly increasing the single-photon bit-error ratio from <3% (0-km) to 6.2% (15-km).

Identifying and minimizing critical driving range thresholds for electric vehicles in intercity networks

It is well known that range anxiety faced by electric vehicle (EV) drivers nowadays can be effectively mitigated by either increasing the driving range of vehicles or increasing the distribution density of charging stations. To enact an effective research and development plan, vehicle manufacturers should understand well the relationship between the EV adoption and usage rates and the performance level of battery and energy management technologies. On the other hand, the underlying relationship between EV adoption and usage rates and the number and distribution of charging stations is also critical for charging infrastructure investors in determining their construction plans. This paper is dedicated to analytically identifying two critical driving range thresholds and further reducing these driving range thresholds as much as possible by optimally deploying charging station locations in intercity highway networks. These critical thresholds represent the turning points of individual routing convenience conditions or satisfaction levels for long-distance trips, implying that the inconvenient travel restrictions may be largely overcome if the driving range of EVs goes beyond these thresholds. For this purpose, we develop two integer programming models and dynamic programming algorithms for the driving range threshold identification problems, and extend the modeling framework to accommodate two relevant driving range threshold minimization problems as well, which are solved by a branching algorithm encapsulating the aforementioned dynamic programming procedures. The output of this research offers a set of new analytical tools for EV manufacturers to make strategic decisions on extending the driving range of their products and for charging infrastructure investors to make planning decisions on selecting charging station locations.

Estimating the Railway Network Capacity Utilization with Mixed Train Routes and Stopping Patterns: A Multiobjective Optimization Approach

Railway capacity estimation problem is typically defined as estimating the maximum number of trains that can be operated in a railway section within a given time interval. However, trains with different speeds, routes, and stopping patterns in a railway network will likely compete for the limited capacity of network nodes and sections. As these trains may provide different services, it is ambiguous to simply indicate the network capacity by a scalar number of trains. To comprehensively estimate and interpret the railway capacity considering the capacity competition between heterogeneous trains, we propose a multiobjective perspective for the capacity estimation problem to enrich the capacity theory while handling the competition among trains with different routes and stopping patterns. Based on a time-space network timetable saturation model, we extend the multiobjective capacity estimation approach to the detailed timetable level by optimizing the saturated timetable under capacity estimation objectives with respect to different routes and stopping patterns. With the ε-constraint method, we can obtain the Pareto front of saturated timetables, i.e., a set of nondominated optimized timetables that no more candidate train can be additionally scheduled. The result is a more comprehensive capacity representation than a single absolute scalar number. A case study is conducted on a combined high-speed and intercity network of Zhengzhou Railway group in China. An extensive set of Pareto-optimal saturated timetables describing the effects on the capacity of the railway network is obtained. The results can help infrastructure managers select saturated timetables as the capacity utilization reference by considering the trade-off between time indexes from passengers’ and operators’ perspectives.

Integration of migration and attention flow data to reveal association of virtual–real dual intercity network structure

The study of intercity network structure from the perspective of flow space can effectively reveal the connection patterns, hierarchical laws, and spatial organization of cities. However, current studies mostly focus on a single real or virtual space, neglecting the comprehensive perspective. Furthermore, the research subject of network relationships is usually the complex original aligned network rather than the spatially cohesive network structure. In this study, spatial network structures are constructed and extracted based on the migration flow and attention flow, which represent people's objective behavior and subjective will, respectively. This study then reveals the association between virtual and real networks from three aspects: node location, node attributes, and local network structure characteristics. Results indicate that compared with the real network structure, the virtual network structure has a strong same-level node agglomeration and a significant node size difference. Spatial dislocations are observed in the high association of the various measures of China's real and virtual network structures. The degree of differences in network structures between virtual and real spaces varies spatially. This paper reveals the dynamics of urban development in different spaces, helping build a human-centered, high-quality space governance system for virtual and real spaces.

Intercity networks and urban performance: a geographical text mining approach

ABSTRACT Compared to the burgeoning literature discussing the importance of agglomeration externalities for development, limited attention has been given to network externalities. This is largely due to limited data availability. We propose a general measure to proxy city network externalities based on toponym co-occurrences that indicate the relatedness between cities. This paper extracts intercity relationships based on the co-occurrence of Chinese place names on 2.5 billion webpages. We calculate and map absolute and relative network positions, which we use to explain urban labour productivity. We found that a stronger embeddedness in networks of cities is significantly and positively associated with urban productivity. Smaller cities benefit comparatively more from being well embedded in city networks, suggesting that these relations can compensate for a lack of agglomeration externalities. We also compare the importance for urban performance of city network externalities vis-à-vis agglomeration externalities. City network externalities turn out to be more important in explaining urban performance than agglomeration externalities. This calls for new theorizing on a relational approach to urban and regional development. Rather than stimulating further concentration of urbanization, our findings suggest that fostering relationships between cities is a viable alternative urban development strategy. We conclude with suggestions for a research agenda that delves deeper into city network externalities.

Knowledge complexity and brokerage in inter-city networks

Knowledge complexity and brokerage in inter-city networks

Influence of Intercity Network on Land Comprehensive Carrying Capacity: A Perspective of Population Flow

The world is experiencing the largest wave of urban growth in history. Maintaining the rapid growth of cities without causing land and resource shortages is a severe problem that must be solved urgently. With the rapid development of globalization and information technology, the meaning of land comprehensive carrying capacity presents new changes. It is no longer entirely dependent on local resources and is likely to benefit from intercity connections beyond urban boundaries. However, can an inter-city network be a non-local solution to sustain urban growth without increasing land pressure? To address this question, this study adopted 287 cities in China as the research object to describe the spatial carrying characteristics of land at the national level by constructing an evaluation index system for land comprehensive carrying capacity. Furthermore, we constructed a population flow network model through social network analysis to explore the influence of intercity network on land comprehensive carrying capacity. Our findings are as follows: (1) The regional differentiation characteristics of land comprehensive carrying capacity at the national scale are evident, and reveal a spatial pattern significantly related to the urban economic development level. (2) The weighted in-degree, weighted degree centrality, and betweenness centrality in the intercity network positively impact the land comprehensive carrying capacity, and land use efficiency has a partial mediating effect. (3) Land comprehensive carrying capacity can be determined by non-local factors rather than local factors. As an effective non-local channel, strengthening intercity population flow and network integration can flexibly manage urban land scarcity.

Network centrality, support organizations, exploratory innovation: Empirical analysis of China's integrated circuit industry

Exploratory innovation is critical to the breakthrough of core technologies in the integrated circuit (IC) industry, and cooperative innovation is a promising form of IC industry development. According to the viewpoint of social network, this paper constructs intercity networks of the IC industry by using a data set of cooperation patents from 2011 to 2020 in China. We uncover the evolution characteristics of the innovation networks, explore the relationship between network centrality and exploratory innovation in a city, and consider universities and development zones, named support organizations, as moderating variables. The results of the social network analysis (SNA) and dynamic panel system generalized method of moments model (System-GMM) are given as follows: Cities are increasingly inclined to collaborate with counterparts over time for innovation, but the overall network scale remains small. Beijing occupies core position in the networks. A cooperative innovation model driven by peripheral cities has been formed as the number of the peripheral cities has gradually increased. The network centrality of a city has a positive effect on its exploratory innovation. Both universities and development zones positively moderate the effect of network centrality on exploratory innovation. Based on the characteristics of the network, our study reveals the importance of taking the internal structure of the network and the node support environment into the same framework, which provides guidance for the innovative development of the world IC industry.

Periphery, uncertainty, and legacy: networks of global service firms within the former Soviet Union space

ABSTRACT This paper discusses intercity networks within the former Soviet Union (FSU), a semi-periphery of the global economic system of interactions. Intercity networks are constructed following an assumption that interaction between offices of the same corporation indicates connectivity between cities. In the FSU global corporations operate against a backdrop of continuous uncertainty. Consequently, it is possible to estimate temporal dynamics and spatial distribution of uncertainty by looking at the evolving structures of global companies with the example of global advanced producer service (APS) companies. These companies are regarded as brokers, integrating the region into the global business activities. The dataset comprises structures of the APS firms within the region in 2015 and 2018. A comparative analysis of networks in 2015 and 2018 demonstrates temporal dynamics of network reconfiguration and unequal spatial distribution of corporate offices in uncertain conditions. Through the lens of the network transformation, we reveal the continuous restructuring and peripheralization of the region.

Advantages of Asynchronous Measurement-Device-Independent Quantum Key Distribution in Intercity Networks

The new variant of measurement-device-independent quantum key distribution (MDI-QKD), called asynchronous MDI-QKD or mode-pairing MDI-QKD, offers similar repeater-like rate-loss scaling but has the advantage of simple technology implementation by exploiting an innovative post-measurement pairing technique. We herein present an evaluation of the practical aspects of decoy-state asynchronous MDI-QKD. To determine its effectiveness, we analyze the optimal method of decoy-state calculation and examine the impact of asymmetrical channels and multi-user networks. Our simulations show that, under realistic conditions, aynchronous MDI-QKD can furnish the highest key rate with MDI security as compared to other QKD protocols over distances ranging from 50 km to 480 km. At fiber distances of 50 km and 100 km, the key rates attain 6.02 Mbps and 2.29 Mbps respectively, which are sufficient to facilitate real-time one-time-pad video encryption. Our findings indicate that experimental implementation of asynchronous MDI-QKD in intercity networks can be both practical and efficient.

Urban Geographies of Financial Convergence: Situating Indian Financial Centers across Global Production and Financial Networks

Recent advancements in the global production networks (GPNs) literature seek to better emphasize the role of finance by identifying where and how global financial networks (GFNs) intersect with GPNs. Financial centers (FCs) operate as key sites for articulating financial convergence, understood as the merging of financial and nonfinancial sectors enacted by cross-sectoral investments. Yet, how such entanglement both feeds on and impacts intercity networks, affecting metropolitan hierarchies, remains largely overlooked. Using a novel data set of 12,147 intersectoral, cross-border and domestic merger and acquisition deals involving finance and insurance firms throughout the period of 2000–20, this article unpacks the sectoral dynamics that underpin the intersection of GFNs with GPNs at the city level in India, the fifth largest economy in the world. Our longitudinal and multiscalar analysis demonstrates how uneven patterns of financial convergence, structured around the rising entanglement between finance and information technology (IT), have reshaped intercity networks and affected the landscape of FCs in India. If Mumbai remains India’s financial capital, Bangalore and New Delhi gained power in domestic and international flows, well ahead of other Indian cities. The article emphasizes how the IT firms, as recipients of transnational investments, and central governments, through direct interventions and state-hybrid investors, operate as key drivers in articulating GFNs with GPNs through intercity networks, changing urban geographies of finance, raising methodological and conceptual questions for future research on financial geography.

Evolution of intercity network shaped by global expansion of Chinese financial enterprises

Evolution of intercity network shaped by global expansion of Chinese financial enterprises

Economic geographies of Asian international financial centers: A sympathetic critique

Through a comprehensive review of economic geography studies on Asian international financial centers (IFCs) published from 2009, this paper aims to provide a sympathetic critique of the key research trajectories of financial geographies and to outline research gaps where economic geographers could contribute to the relevant literature. Economic geographers have identified a prominent change in the geographies of the international finance industry, with the rapid development and the emergence of inter-city networks among Asian IFCs, and suggested how the emerging FinTech industries could reshape the competitive dynamics and thus the financial landscape of IFCs. The literature has unpacked the general mechanisms of how Asian IFCs grow and evolve as well as their spatial patterns but has neglected the macro political-economic contexts that drive the development dynamics of Asian IFCs. To maintain the long-term prospects of financial geography, we call for efforts to theorize (Asian-based) financial geographies and develop the corresponding analytical frameworks with rigorous quantitative and qualitative methods to examine the development trajectories of Asian IFCs and their socio-political and geo-economical mechanisms. Moreover, economic geographers could develop a set of composite parameters to capture the attributes and structures that could (re)shape the development trajectories of inter-city and intra-city financial networks and their level of resilience to external shocks.

Modeling and Solving Line Planning with Mode Choice

We present a mixed-integer linear program (MILP) for line planning with mode and route choice. In contrast to existing approaches, the mode and route decisions of passengers are modeled depending on the line plan and commercial solvers can be applied to solve the corresponding MILP. The model aims at finding line plans that maximize the profit for the railway operator while estimating the corresponding passenger demand with aggregate choice models. Hence, the resulting line plans are not only profitable for operators but also attractive to passengers. By suitable preprocessing we are able to apply any aggregate choice model for mode choices using linear constraints. We provide and test means to improve the computational performance. Our experiments on the Intercity network of the Randstad, a metropolitan area in the Netherlands, show that models which assume a fixed passenger assignment to modes cannot attract the passenger numbers they were designed for and therefore lead to inferior profit compared with our new model. Supplemental Material: The online appendices are available at https://doi.org/10.1287/trsc.2022.1171 .

Effects of electric vehicle adoption for state-wide intercity trips on emission saving and energy consumption

Electric vehicles (EVs) mitigate fossil fuel dependency and reduce emissions; they are considered sustainable alternatives to conventional vehicles. To support EVs’ intercity trips, a recent study proposed a charging infrastructure planning framework implemented for the intercity network of Michigan, considering different projected EV market shares for 2030. This study aims to estimate emission savings, including CO2, HC, CO, and NOx, associated with the projected electrification rate and the proposed infrastructure for light-duty vehicles in the earlier study. To this end, a state-of-the-art emission estimation framework is proposed for state-wide intercity trips. The main contributions of the proposed framework include (1) Incorporating a micro emission estimation model (MOVES) for the simulated vehicle trajectories in a large-scaled network considering monthly travel demand, temperature variations, and heterogeneity of vehicles; (2) Contrasting the required investment in charging infrastructure to support EVs intercity trips with the associated emission savings. To this end, the proposed emission estimation framework is benchmarked against a traditional method based on vehicle miles traveled (VMT). Then, different scenarios of EV adoption are explored to assess potential emission savings. The results suggest that the annual CO2 savings (as the most critical emission) due to intercity travel electrification ranges from 0.34 to 1.45 million ton. The societal cost savings justify the investment in network electrification. Note that only 3.8%–8.8% of the EV energy demand must be satisfied by the DC fast charger network proposed by the charging infrastructure planning framework. This requires 22.45–51.60 BWh annual energy consumption for Michigan’s EV market share for 2030.

Mapping carbon emissions of China's domestic air passenger transport: From individual cities to intercity networks

As a significant carbon emission source with high growth potential, the air transport sector plays a crucial role in China's decarbonisation efforts. However, the spatial pattern and evolutionary dynamics of aviation carbon emissions in China have not been thoroughly studied. This study proposed a framework to reveal the spatial characteristics and influencing factors of aviation carbon emissions at the city level. Using data from 2019 to construct the aviation carbon emissions network of China (ACENC), the novelty of the study lies in the subdivision of carbon emissions of air passenger transport into cities and intercity lines in China, which helps to reveal the spatial characteristics of individual cities in the intercity network. Beijing, Shanghai, Shenzhen, Chengdu, and Guangzhou were the cities with the highest carbon emissions, and the routes between these cities caused a significant amount of carbon emissions. >80 % of the total carbon emissions can be attributed to two communities in the network, owing to their large size and strong connections. Correlation analysis indicates that a city's carbon emissions are significantly related to its demographic and economic attributes as well as its connection with other cities, while a city's carbon emission intensity may be influenced by its centrality in the whole network and the structure of the community to which it belongs. Overall, the presented results provide directions for stakeholders and policymakers to regulate carbon emissions from air transportation.