Demand-supply Interaction Research Articles

Development of a deep-learning based gap index for addressing demand–supply interactions in ride-sourcing services

Development of a deep-learning based gap index for addressing demand–supply interactions in ride-sourcing services

Integrated train timetable with supply–demand interactions at the Chinese high-speed railway

In traditional Chinese railway operations, train timetable and unit assignment are usually separated from pricing and seat allocation, resulting in a decrease in revenue and an increase in operating costs. In this paper, we study the integrated problem of train timetable, unit assignment, pricing, and seat allocation, where passenger choice behavior is modeled by the multinomial logit (MNL) model. This integration enables us to explicitly capture supply–demand interactions. The problem is formulated as a mixed integer nonlinear programming model with the objective of maximizing total profit. By converting the MNL model into its equivalent convex form, we recast the model as a tractable reformulation, allowing the use of a general-purpose solver to solve practical-sized instances. Based on real data from high-speed railway lines in China, three sets of case studies are conducted to validate the effectiveness and efficiency of the proposed approach.

Data-driven vulnerability analysis of shared electric vehicle systems to cyberattacks

Disruptions to electric vehicle charging infrastructure can hinder consumers’ confidence and impact the performance of shared electric vehicle (SEV) systems. This study focuses on SEV systems’ vulnerability to emerging cyberattacks at the system level utilizing city-scale SEV trajectory data in Beijing, China. A data-driven simulation model is developed to account for realistic charging demand–supply interactions extracted from the data. The results show that among different types of disruptions, cybersecurity threats present unique challenges to SEV systems. Compared with attacking the most highly utilized charging stations, attacking popular ones on the city’s outskirts is more likely to significantly increase stress on the charging infrastructure and reduce the accessibility of SEVs. Meanwhile, the interactions between SEVs and infrastructure could either amplify the impacts by triggering cascading failures or relieve the adversarial effects. These findings provide insights into designing policies and solutions to enhance the resilience of SEV systems against cyberattacks.

Land Use Intensity Alters Ecosystem Service Supply and Demand as Well as Their Interaction: A Spatial Zoning Perspective

Clarifying the interaction between ecosystem service supply (ESS) and demand (ESD) and its response to land use change is essential for achieving ecological security. Previous research mainly focused on how land use change affects ESS, ignoring its impact on the interaction between ESS and ESD, making it difficult to guide regional sustainability in social–ecological coupled systems. Taking the Yangtze River Delta as the study area, after evaluating five types of ESS and ESD during 2000–2020, this study analyzed the interaction between changes in ESS and ESD using Geodetector from a spatial zoning perspective and subsequently explored the impact of land use intensity on ESS, ESD, and their interaction using Spearman correlation analysis and regression analysis. The results showed that there was obvious spatial–temporal heterogeneity in ESS and ESD. Different ecosystem services varied in their interaction between ESS and ESD, and the demand changes in water conservation and soil retention significantly influenced their supply changes, while supply changes in carbon sequestration were not influenced by its demand changes. The effect of ESD changes on ESS changes also showed spatial heterogeneity. All interactions between ESS changes and ESD changes, except carbon sequestration, were significant in the Supply Increases–Demand Increases zone. Soil retention and water conservation showed a significant supply–demand interaction in the Supply Decreases–Demand Decreases zone and the Supply Decreases–Demand Increases zone, respectively, while no ecosystem service showed significant supply–demand interaction in the Supply Increases–Demand Decreases zone. Land use intensity had linear and nonlinear effects on different ESS and ESD, and it was also found that the effect of ESD changes on corresponding ESS changes was relatively obvious in regions with dramatic land use change. Finally, this paper incorporated the changes in ESS and ESD, as well as their interaction, into land use management, which can provide implications for regional sustainability.

Cooperative operation for multiple virtual power plants considering energy-carbon trading: A Nash bargaining model

With the development of the energy and carbon markets, it has become a trend for multiple virtual power plants (MVPP) that aggregate distributed resources from different regions to participate in market trading through cooperative operation. In order to study the energy-carbon interactions between VPPs and the supply-demand interactions for MVPP and users, this paper introduces a load aggregator (LA) and establishes a cooperative alliance consisting of MVPP and LA. Firstly, a carbon emission allowance allocation and transaction mechanism for MVPP is proposed based on the modified Shapley value method, which considers the impact of energy interactions within the alliance on the carbon emissions. Then, a cooperation model for the MVPP-LA alliance is established based on Nash bargaining theory, and it is decomposed into two subproblems of the maximal alliance benefits and the optimal benefit distribution. In terms of benefit distribution, this paper modifies the bargaining mechanism based on the contribution of each VPP to the alliance benefit. A dynamic penalty factor-based alternating direction method of multipliers (DP-ADMM) is used to solve the two subproblems in a distributed manner. Finally, the validity of the proposed trading mechanism, allocation method and solution algorithm are verified through several cases.

Shedding Light on the Failure Factors of Subsea Critical Fastener Bolts

Offshore facilities, such as oil and gas rigs, wind turbines, and related subsea equipment, typically use flanges fastened using bolts and nuts as the main connectors. In this study, multidisciplinary parameters, namely the preload torque used to tighten bolts, simulated subsea water currents, water temperature, and impressed current cathodic protection, were applied to ASTM A193 B7 bolts. An experimental supervisory control and data acquisition system was designed to obtain measurements every 5 min throughout a 21-day experiment. Finite element analysis was performed to predict the structurally vulnerable areas of the bolts. A strong correlation was found between the reference electrode readings and the measured electrical current, tightening torque, and water temperature. As the water temperature rises during the day, the reference electrode reading becomes less negative and the electrical current decreases. Subsea water currents cause about a four-time increase in the bolt corrosion rate, with unprotected bolts suffering a nine-time-higher corrosion rate than protected bolts. A unique supply–demand interaction is observed; less protection is supplied to areas with lower corrosion rates (lower demand for protection). Finally, scanning electron microscopy examination reveals new insights into the failure mechanisms of subsea bolts.

Ridesourcing platforms thrive on socio-economic inequality

Limited available market share data seems to suggest that ridesourcing platforms benefit from, even thrive on, socio-economic inequality. We suspect that this is associated with high levels of socio-economic inequality allowing for cheap labour as well as increasing the share of travellers with a considerably above-average willingness to pay for travel time savings and comfort. We test the relation between inequality and system performance by means of an agent-based simulation model representing within-day and day-to-day supply-demand interaction in the ridesourcing market. The model captures travellers’ mode choice with a heterogeneous perception of relevant time components, as well as job seekers’ participation choice with heterogeneous reservation wage. Our experiments cover scenarios for the entire spectrum ranging from perfect equality to extreme inequality. For several of such scenarios, we explore alternative platform pricing strategies. Our analysis shows a strong, positive relationship between socio-economic inequality and ridesourcing market share. This is the outcome of the combination of cheap labour and time-sensitive ridesourcing users, reinforced by network effects inherent to ridesourcing markets. We find that driver earnings are minimal in urban areas with large socio-economic inequality. In such contexts, drivers are likely to face a high platform commission, and yet, fierce competition for passengers.

A simplified assessment method based on Hooke's law to estimate the grid-friendly ability of buildings

The development of grid-friendly buildings helps to enhance the supply–demand interaction, thereby improving the energy system efficiency. The relevant evaluation indicators are mainly based on the building operation results and the aspect of effect evaluation. Even the flexible prediction of buildings is executed using operation results prediction. Although effect evaluations are accurate, the data requirements are high, and a certain threshold for promotion occurs. This inability to evaluate grid-friendly buildings rapidly prompted the development of a method to estimate the influence of buildings on the grid based on planned capacity by referring to Hooke's law. First, the relationship between building flexibility, power grid, and end-user fluctuation is quantified by analogy to Hooke's Law. The electricity equivalent and intermittent consideration are then used to establish a calculation method for the degree of influence. The rationality of the method is then verified by simulating the running results of different planning schemes using a testing platform built in Python. The traditional method is then conducted. The consistency between the traditional method and the proposed method is analyzed, as well as the grid-friendly potential and response effect of different energy technologies.

Energy supply-demand interaction model integrating uncertainty forecasting and peer-to-peer energy trading

With the penetration of large amounts of renewable energy resources into energy system, the interaction between energy supply and demand has become more complex and diverse. The complexity and diversity make it more difficult to achieve real-time, efficient, accurate and dynamic matching of energy supply and demand. Therefore, the study proposes an efficient energy supply-demand interaction model integrating uncertainty forecasting and peer-to-peer energy trading. First, to reduce the impact of supply and demand uncertainty on the energy supply and demand matching, gate recurrent unit and long short-term memory models are used to forecast power generation and consumption. Then, based on the results of forecasting, an energy supply-demand interaction model is proposed to assist the energy system in achieving dynamic energy supply-demand matching. Finally, the effectiveness of the proposed energy supply-demand interaction model has been verified through experiments. The proposed energy supply-demand interaction model that considers supply and demand uncertainty and economic benefits helps to better achieve transparent, efficient, stable, and sustainable matching of supply and demand. This study can reduce the impact of supply and demand uncertainty by forecasting power generation and consumption. In addition, this study considers the preferences of prosumers in their trading, reduces the cost of electricity for prosumers, and realizes the profitability of multiple subjects involved in the trading.

Linking supply-demand balance of ecosystem services to identify ecological security patterns in urban agglomerations

Ecological security patterns (ESP) is an effective approach to identify the priority conservation areas and maintain regional ecological security. The previous ESP studies only focused on the supply of ecosystem services (ESs), but ignored the supply-demand interaction of ESs. In this study, a novel large-scale ESP framework was proposed by introducing the supply-demand scarcity of ESs to revise identification of ecological sources. According to the scarcity theory “the severer ESs imbalance, the higher priority of protection”, the ESs scarcity supply capacity (ESSSC) was reconstructed by combining ESs supply with two adjust factors of the urgency of regional eco-protection (UEP) and the priority of ESs type (PET). Finally, ecological sources integrating ESSSC and ecological sensitivity, ecological corridors, and ecological nodes were identified to establish a cross-regional ESP. The results show: (1) the reconstructed ESSSC approach significantly increased ecological sources areas of developed cities in urban agglomerations with the severer overall and structural imbalance, and effect of PET exceeds UEP; (2) appropriate allocation of key protection areas in regions with low supply but high demand and the priority protection of the severely imbalanced ESs types can alleviate environmental injustice; and 3) the extracted 160 ecological corridors and 16 ecological nodes effectively enhanced connectivity among ecological sources (36.2% of the study area), and formed a complete and connected ESP. The scarcity idea for regional coordination can guide the trans-administrative ecological decision making.

Intraday rolling optimal dispatch model of power system considering supply-demand interaction

The participation of demand-side resources in grid operation and regulation, in coordination with the generation side, can jointly ensure a stable supply of electricity. The application of control technology in the energy field makes demand-side resource control methods more flexible and intelligent, thus providing a technical guarantee for demand-side resources to participate in the power market. This paper discusses the interaction between demand-side resources and the generation side and establishes an intraday rolling optimal dispatch model for demand-side resources. Finally, it is demonstrated through simulation that refining the multi-dimensional response characteristics of demand-side resources in the intraday dispatch model can improve the operational economy of the system and the flexibility of the scheduling model to cope with uncertainties.

Assessment of spatial equity of urban park distribution from the perspective of supply-demand interactions

Urban parks have been widely recognized for the critical functions they provide in enhancing health and wellbeing. However, parks are known to be inadequately provided and non-uniformly distributed in cities, leading to an increasing interest to examine spatial equity of park distribution. Such studies have mostly focused on the distributional attributes of park supply in determining spatial equity, while the role of residents’ demand is usually ignored or not adequately assessed. In addition, people’s preferences for park use were normally ignored and nearest parks were assumed as supplier of park services. Moreover, even though equity assessment is scale-dependent, few studies adopt a multi-scale assessment. We report on a study to address these gaps. A multi-scale Supply-Demand Equity Index (SDEI) was developed to assess spatial equity of park distribution from the perspective of supply and demand interactions, and data were collected at a fine scale of neighborhood level. Residents’ accessibility to their most often used parks and nearest parks were used to assess and compare supply level; while residents’ perceptions obtained from surveys and population density were used to assess and compare demand level. Results showed that supply measured by accessibility to most often used park more accurately reflects supply, and demand assessment on the basis of perception could reflect variations among different social groups and reveal otherwise hidden patterns of spatial inequity. It was also shown that SDEI could identify areas where mismatch between supply and demand occurs. We demonstrated in a single study that different definitions and approaches of quantifying spatial equity can lead to distinct conclusions, therein highlighting that the complex nature of equity requires nuanced approaches and providing a broader view of equity assessment. In addition, the implications of this study for urban park planning and management were highlighted.

Do menu costs lead to hysteresis in aggregate output? The experiences of some agent-based simulations

AbstractThe transitory shock of the financial crisis of 2008 pushed most economies to permanently lower-level growth paths than those prevalent before the crisis, which can be considered as a manifestation of hysteresis. It is well known that some fixed adjustment costs lead to hysteresis in aggregate output. This paper investigates within an agent-based model, whether the fixed costs of price adjustment (menu costs) lead to the same result. Hysteresis emerges in some simple variants of the model independently of firms being assumed boundedly or perfectly rational, but these model variants fit to the empirical data poorly. The model's empirical performance can be improved by assuming that firms are hit by idiosyncratic productivity shocks, but these shocks eliminate hysteresis generated by menu costs. However, hysteresis survives even in their presence, if it is generated by demand-supply interactions, i.e., positive feedbacks from the output gap to potential output. Our conclusion is that if one would like menu costs to serve as an at least as relevant explanation for the hysteretic dynamics of aggregate output as demand-supply interactions, one has to find an alternative assumption to replace idiosyncratic productivity shocks as a mechanism to assure good empirical fit for the model.

How can virtual water trade reshape water stress pattern? A global evaluation based on the metacoupling perspective

With water scarcity increasingly becoming a growing global risk, it is prevalent to explore water supply-demand interaction within and beyond national borders driven by global virtual water trade and its effects on water sustainability. However, there is little study on system integration of differential environmental impacts of various types of trade. Based on metacoupling framework highlighting human-nature interactions across space- within a place (intracoupling), between adjacent places (pericoupling), and between distant places (telecoupling), this study quantified the linkages and intensities of three kinds of coupling processes during global virtual water trade for the first time. Correspondingly, water stress changes under a set of trade scenarios were evaluated based on the indicator of UN SDG 6.4.2 to distinguish the influence of trade taking place on different spatial scales. Results show that during 2005–2015, local water resources supported 80% of global water consumption. Distant virtual water import was about 5 times in volume as large as adjacent virtual water import, alleviating 99.8% of global average water stress. Virtual water trade reduced water stress in 86% of developed countries and increased that in 71% of developing countries in 2005. Owing to trade, water stress in many countries with poor water resources endowment declined while that of many with relatively good endowment went up from 2005 to 2015. Our findings can help to systematically understand the influence of virtual water trade on water stress change and provide scientific guidance for sustainable water management and regional regulations.

Service pricing strategy of food delivery platform operators: A demand-supply interaction model

This study explores the pricing strategy for online food delivery platform operators using the demand-supply interaction model, and taking into account the relationship between consumer demand and courier supply as well as the impact of consumer choice behavior and price variation per order on platform profit. A mathematical model is formulated to determine the optimal service fee and wage rate under profit maximization. Results show that service fee reduction indeed brings in more orders and greater revenue. However, increase in revenue cannot compensate for decrease in service fee collected and extra courier wage costs due to increase in orders. Hence, platforms suffer profit decrease. Moreover, a high market share does not guarantee maximum profit for platforms. Findings reveal that profit can be maximized through increasing both service fee and courier wage. On one hand, fee increases do not reduce demand because consumers are less sensitive to higher price than longer waiting time. On the other hand, higher courier wage would ensure courier supply and delivery capacity. These results provide useful reference for online food delivery platforms in devising optimal service fee for attracting consumers and appropriate wage for enticing couriers so as to stay profitable in the competitive business environment.

Sustainable Mobility as a Service: Dynamic Models for Agenda 2030 Policies

Growth trends in passenger transport demand and gross domestic product have so far been similar. The increase in mobility in one area is connected with the increase in GDP in the same area. This increase is representative of the economic and social development of the area. At the same time, the increase in mobility produces one of the most negative environmental impacts, mainly determined by the growth of mobility of private cars. International attention is given to the possibilities of increasing mobility and, therefore, social and economic development without increasing environmental impacts. One of the most promising fields is that of MaaS: Mobility as a Service. MaaS arises from the interaction of new user behavioral models (demand) and new decision-making models on services (supply). Advanced interaction arises from the potentialities allowed by emerging ICT technologies. There is a delay in the advancement of transport system models that consider the updating of utility and choice for the user by means of updated information. The paper introduces sustainability as defined by Agenda 2030 with respect to urban passenger transport, then examines the role of ICT in the development of MaaS formalizing a dynamic model of demand–supply interaction explicating ICT. Finally, the advanced Sustainable MaaS, defined SMaaS, is analyzed, evidencing the contribution to achieving the goals of Agenda 2030.

Strategies to Develop the Use of 4R Intermodality as a Combination of Rail Motorways and Motorways of the Sea

This paper introduces the concept of R4 (road-rail-ro-ro), a concept increasingly used in transport and logistics research circles that defines the modern concept of the transport chain as it passes through the intermodal use of rail, road, and ship via ro-ro. The integration of the new rail-road freight services into the reference supply model allows us to define the supply model for the design scenario on which the evaluation is now focused in terms of service-mode demand shares and in terms of design network flows and performance indicators carried out by demand-supply interaction models applied to all available service-modes. The use of strength-weaknesses-opportunities-threats analysis (SWOT) allows for the identification of some strategies to enhance and improve the current rail and maritime corridors in order to attract more customers using the different services, ultimately triggering the involvement of more actors in generating bigger and better integrated logistic chains using intermodality. The SWOT analysis allows the identification of a series of measures in order to adapt, maintain, enhance or exploit the aspects arising from the expert analysis.

A ridesharing simulation model that considers dynamic supply-demand interactions

This paper presents a new ridesharing simulation model that accounts for dynamic driver supply and passenger demand, and complex interactions between drivers and passengers. The proposed simulation model explicitly considers driver and passenger acceptance/rejection on the matching options, and cancelation before/after being matched. New simulation events, procedures and modules have been developed to handle these realistic interactions. Ridesharing pricing bounds that result in high matching option accept rate are derived. The capabilities of the simulation model are illustrated using numerical experiments. The experiments confirm the importance of considering supply and demand interactions and provide new insights to ridesharing operations. Results show that higher prices are needed to attract drivers with short trip durations to participate in ridesharing, and larger matching window could have negative impacts on overall ridesharing success rate. Comparison results further illustrate that the proposed simulation model is able to replicate the predefined “true” success rate, in the cases that driver and passenger interactions occur.

Exploring the dynamics of the equity–commodity nexus: A study of base metal futures

AbstractThis empirical exercise explores different aspects of the time‐varying linkage between the commodity and equity markets in India, focusing on base metal futures. The Dynamic Conditional Correlation model (2002) and Diebold–Yilmaz spillover index (2012) are employed to ascertain the presence, pattern, direction, and magnitude of the connectedness between the returns of base metal futures and related equity indices over the period of 2006–2019. The study builds on a less‐studied “input” channel of linkage between the two, reckoning with the economic fundamentals of demand–supply interaction. Our results show that 36% of the return forecast error variance originates from spillovers, to which the contribution of equity indices is minimal. It indicates segmentation between the two markets which offer the scope for potential diversification. Further, base metal futures are the net transmitters and equity indices are the net recipients of spillovers. Positive correlations outweigh the negative correlations, in both frequency and magnitude.

Simulating the impact of demand-side policies on low-carbon technology diffusion: A demand-supply coevolutionary model

Alleviating the pressure of climate and energy calls for an improved understanding of how policy interventions influence the diffusion of low-carbon technologies (LCTs) among enterprises. With the rapid convergence of supply-side policy effects, implementing demand-side policies to drive LCT diffusion may be a promising area for carbon abatement action. This study proposes a demand-supply coevolutionary model embedded in two-layer network is to capture the LCT diffusion among supply-side enterprises and low-carbon consumption diffusion among demand-side consumers. Using this model, we simulate the effects of demand-side policies, including public procurement, financial incentives for consumers, public information dissemination, and policy mixes combined with these instruments on LCT diffusion. The results show that public procurement can effectively facilitate LCT diffusion and restrain the magnitudes of market fluctuations caused by demand-side dynamics in the diffusion process. The high consumer incentives facilitate the rapid diffusion of LCTs, but there are noticeable diminishing marginal effects; even if subsidies are only used on the demand side, the promotion effect on LCT can still be achieved through the demand-supply interaction. Furthermore, the public information dissemination improves LCT diffusion and stabilizes the adaptive behavior of enterprises, but its time-lag effect leads to the pattern of “hot policies and cold markets.” The introduction of policy mixes verifies these findings and reveals that although the public information dissemination is constrained by other policies, it may still be the premise of large-scale LCT diffusion. This study develops a valuable framework that enriches the modeling practice of LCT and provides insights for implementing well-designed policy packages.