Market Diffusion Research Articles

Spatial feasibility prediction of green hydrogen scale-up in China under decarbonization policies: Based on improved diffusion model

Hydrogen production from renewable electrolysis is a suitable transformative technology for driving a cleaner energy mix, mitigating climate change, and achieving sustainable development and has been given the color value definition of "green hydrogen". However, this low-carbon technology is still in its infancy, and the pathways for expanding market supply have not been analyzed. To address the problems of unclear factors influencing the diffusion of green hydrogen technology innovation, unclear technology diffusion laws, and inaccurate predictions of regional green hydrogen production capacity under the goal of decarbonization policy, this work constructs a spatial assessment framework of the feasibility of low-carbon technology development in response to climate change on the basis of the theory of technological innovation systems, the improved technology diffusion model, and the feasibility of climate change spatial concepts to analyze and predict the diffusion law and regional green hydrogen production capacity of hydrogen production by renewable energy under the goal of carbon neutrality. The results of the study on the development of renewable hydrogen technology in China show that it follows the law of diffusion of low-carbon technologies in both the formation and growth stages. The diffusion of green hydrogen technology in the formation stage is slow, and the regional green hydrogen capacity in the near term cannot meet the decarbonization policy target demand in 2030. Before the spatial inflection point of technology diffusion feasibility, the demand-pull of the phase decarbonization policy target dominated the stability and sustainability of the green hydrogen supply market. After the inflection point, the internal growth of technology diffusion plays a key role in market diffusion and ultimately reaches a saturation value under the joint regulation of policy and the market to realize a carbon-neutral target capacity demand in 2060. The uncertainty of diffusion model parameters leads to anomalies in the feasibility space of technology diffusion, and risks such as overcapacity or insufficient demand in some regions may occur. Overall, this work provides a systematic assessment system for analyzing and predicting the pathways and characteristics of expanding renewable hydrogen production in specific regions under decarbonization policy objectives.

Hybrid Simulation Model of Lifecycle Simulation and Replacement Simulation Considering Carbon Lock-In by Coal-Fired Power Plants

To meet the temperature goal set by the Paris Agreement, cumulative CO2 emissions must be kept below 300 GtCO2. Road transportation accounted for approximately 18% of the CO2 emissions from fuel combustion in 2017. Electric vehicles (EVs) have been rapidly adopted by environmentally conscious consumers in many countries to reduce CO2 emissions. EVs have lower emission intensities than do internal combustion engine vehicles (ICEVs) in most parts of the world, except where the penetration of renewable energy is low in the energy production mix. In such places, the CO2 emissions of EVs are larger than those of ICEVs. Despite the obvious need to increase renewable energy sources to reduce CO2 emissions, Japan and many other countries around the world have yet to shift away from fossil fuels. This is due in part to carbon lock-in, which refers to prior decisions related to technologies and infrastructure that constrain the implementation of better paths toward low-carbon technologies. Coal-fired power plants are the most problematic in terms of carbon lock-in because of their high carbon intensities and long physical lives. In addition, because carbon lock-in by coal-fired power plants has a significant impact on the embodied CO2 intensity of grid power, it impacts society through products that use electric power. In this study, we propose a hybrid simulation model of lifecycle simulation and replacement simulation, considering carbon lock-in by coal-fired power plants. In the replacement simulation, we simulated the replacement of end-of-life coal- and oil-fired power plants with renewable energy power plants using a probability called the lock-in rate and estimated the changes in the embodied CO2 intensity of grid power in Japan. In the lifecycle simulation, we evaluated cumulative CO2 emissions from entire product lifecycles of ICEVs and EVs based on three different EV diffusion scenarios. The results showed that the lock-in rate of coal-fired power plants strongly affects the decarbonization effect due to the market diffusion of EVs.

Media attention and electric vehicle adoption: Evidence from 275 cities in China

Can changes in consumer psychology induced by media attention lead to pro-environmental transportation behaviors or choices? In response, we match a unique dataset on media attention with electric vehicle (EV) sales data in China, employing a two-way fixed effects model and an instrumental variable (IV) method to estimate the impact of media attention on EV adoption. Our research found that media attention significantly accelerates the market diffusion of EVs. This result is substantiated through IV tests and a series of robustness checks. Additionally, the mediation effect model revealed that media attention indirectly influences EV adoption through consumer EV attention, government EV focus, EV technological innovation, and EV purchase subsidies. We also discovered that the effect of media attention on EV adoption is not only positively moderated by the level of consumer policy awareness and education but is also more pronounced in areas with high population density, high income, high education levels, and a high air quality index. Our findings not only provide empirical evidence for understanding the role of social psychological factors and external media stimuli in promoting behavioral changes towards environmental protection but also offer guidance for policymakers and businesses in implementing effective market promotion strategies and formulating relevant policies, especially in enhancing public cognition and acceptance of EVs.

Rapidly declining costs of truck batteries and fuel cells enable large-scale road freight electrification

Low-carbon road freight transport is pivotal in mitigating global warming. Nonetheless, electrifying heavy-duty vehicles poses a tremendous challenge due to high technical requirements and cost competitiveness. Data on future truck costs are scarce and uncertain, complicating assessments of the future role of zero-emission truck (ZET) technologies. Here we derive most likely cost developments for price setting ZET components by meta forecasting from more than 200 original sources. We find that costs are primed to decline much faster than expected, with significant differences between scientific and near-market estimates. Specifically, battery system costs could drop by 64% to 75% and fall below €150 kWh−1 by no later than 2035, whereas fuel cell system costs may exhibit even higher cost reductions but are unlikely to reach €100 kW−1 before the early 2040s. This fast cost decline supports an optimistic view on the ZET market diffusion and has substantial implications for future energy and transport systems.

Prospects of forward osmosis-based membranes for seawater mining: Economic analysis, limitations and opportunities

Processes for separating solutes from water, including desalination, are based on synthetic membranes using the forward osmosis (FO) technique. The industrial-level success of these membrane techniques has been astounding. Modern desalination membranes, however, cannot extract a single metal ion with precision from a commingled ion solution. Lithium, cobalt, uranium, and other energy-critical elements will soon be in greater demand than they can meet, thus elevating their importance as geopolitical resources. Critical metals can be found in seawater, an essential yet unconventional supply. Gold mining and ore processing are activities of great economic importance. However, they are related to generating extremely polluted effluents containing high concentrations of heavy metals and low pH. The review highlights the most recent design and deployment of FO desalination technologies, their application in sea mining, and the remaining challenges and prospects. This work also highlights the enormous potential of FO sea mining and how it is crucial to optimize the operating parameters, including draw solutions and energy consumption, and raise attention toward the economic aspect and market diffusion of FO sea mining.

The social network perspective on power system co-evolution: responses to "double carbon target" realization in China.

The introduction of dual carbon targets will significantly impact power system development. Despite this, there is currently limited research on achieving system evolution and transition while ensuring safety, low-carbon output, and efficiency, as well as quantitatively analyzing the resulting changes dual carbon targets will have on the power system. Co-evolution of the power system offers a solution to balance the impact of dual carbon goals and enhance interaction among system entities, thereby facilitating the achievement of these goals. Our study focuses on constructing an evolutionary topological network by analyzing the dynamic evolution rule of power systems. We investigate the co-evolution pattern of power systems by analyzing the relationship between the role of power system agents and their dynamic structures. Furthermore, we analyze the future structural changes of power systems, which can provide theoretical support for achieving dual carbon goals in the power system. Our findings highlight key measures to promote synergistic evolution, including increasing energy storage capabilities, stabilizing renewable energy supply, breaking inter-provincial barriers in electricity transmission, and developing a multi-level intelligent power system. Through link analysis, we discover that future power systems will maintain a mild coordination among agents rather than implementing large-scale realignment and reconfiguration. We posit that overcoming obstacles can be achieved by fostering cohesion between the network and agents through technological innovation and widespread market diffusion to drive co-evolution.

Analysis of Visual and Vestibular Information on Motion Sickness in Flight Simulation

Virtual reality (VR) is in its nascent technological advancement and market diffusion stages. Interestingly, the scientific exploration concerning the impact of non-isometric mapping disparities within visual–vestibular stimuli on motion sickness remains deficient. This investigation focuses on scrutinizing the visual–vestibular implications for motion sickness within the context of flight simulation. The developed motion platform, offering specific pitch and roll ranges of ±16 and ±17 degrees, respectively, was employed to induce varying ratios of simulated visual–vestibular cues. Involving a cohort of five participants, the study exposed them to two prevalent simulated mission profiles, subsequently assessing their motion sickness symptoms. Sixty responses were analyzed using the subjective assessment of the Simulator Sickness Questionnaire (SSQ). The findings reveal a reduction in cybersickness severity with congruent visual–vestibular stimuli in proportion to the variance observed among visual–vestibular coupling ratios. A comparative analysis of SSQ sub-categories demonstrates that disorientation holds the most significance in the hierarchy of motion sickness contributors, followed by oculomotor discomfort, with nausea manifesting as the least influential. This study can lead to situation awareness analysis by integrating VR-based flight-simulation setups in the formal training of pilots and UAV operators.

Multi-period optimization of hydrogen refueling station layouts considering refueling satisfaction and hydrogen fuel cell vehicle market diffusion

The strategic site selection of hydrogen refueling stations (HRSs) in the network and user satisfaction mutually influence each other, presenting a typical bilevel planning problem for optimizing the hydrogen refueling network.

Network evolution of diffusion in enterprise digitalization and intellectualization transformation: A technology-organization-environment framework perspective.

Enterprise digitalization and intellectualization (EDI) is a crucial aspect of China's modernization process. However, uncertainty in market and business decisions hinders the EDI diffusion process in China. Therefore, this research aims to solve the uncertainty problem of EDI diffusion by examining market demand and government policy coordination. First, we utilize complex network game theory and establish a technology-organization-environment framework for the factors that influence the elements of EDI transformation by combining evidence from existing studies. Second, the network game model is constructed to analyze and optimize the updating rules in the network as a diffusion strategy that enterprises under the uncertain market can adopt. Finally, the impact of adjusting government subsidies and different premiums on the diffusion of EDI transformation strategies is examined. The degree of market diffusion and average revenue of EDI are higher after the optimization of network node strategy updating rules compared to before optimization. Further analysis reveals that only the premium effect of product pricing and inverted U-shaped subsidy support from the government affect the degree of market diffusion and the average revenue of EDI, while the other premium effects are not significant. These findings enrich research related to complex networks and nonlinear dynamic strategies. They also indicate recommendations for government policies to enhance diffusion efficiency and reasonable pricing for enterprises to promote returns.

Evolutionary game analysis of shared parking market diffusion under government management

Abstract The imbalance between supply and demand in urban settings poses a significant barrier to the sustainable advancement of urban transportation. Shared parking serves as a viable solution to mitigate these challenges. Nevertheless, for its sustained growth, a regulatory mechanism enforced by the government is imperative. To promote shared parking market diffusion, we construct an evolutionary game model that incorporates the government, enterprises and parking demanders. It explores stabilization strategies for these stakeholders and identifies multiple equilibrium states under different parameter conditions. The results show that the rate and stability of these evolutionary strategies are constrained by the mutual benefits derived by the three parties. Furthermore, such stakeholders are reciprocally influenced by their willingness to engage in shared parking to varying degrees. Government subsidies serve as a determining factor for the strategic choices made by both enterprises and demanders, albeit at different evolutionary rates. Demanders who have a higher value of time tend to park on-street, thereby influencing enterprise strategies. To foster the long-term growth of the shared parking market, the government must enact appropriate subsidy policies, maintain consistent regulations and advocate for increased subsidies for parking demanders to reduce the effect of temporal heterogeneity on parking behavioural choices.

Enhancing electric vehicle market diffusion modeling: A German case study on environmental policy integration

In order to reduce national and global greenhouse gas (GHG) emissions, many countries worldwide have committed themselves to a more sustainable development of their transport sector. Promoting the use of electrical vehicles (EVs) rather than combustion engine cars is one political strategy to achieve a reduction in GHG emissions. To implement targeted and effective promotion measures governments can refer to market diffusion models for EVs. However, in our study we identify that in existing models the consideration of environmental measures is underrepresented. Hence, this paper addresses this gap in current market diffusion models for EVs by particular focusing on environmental effects as additional influencing factors of the market diffusion. Results are drawn for the German car market with a market diffusion simulation until 2050 applying the market diffusion model ALADIN considering the introduction of distinct CO2 tax trajectories. The results are analyzed based on scenarios, where (i) no CO2 tax, (ii) the current governmental plan for a CO2 tax, and (iii) a considerable high CO2 tax is applied. Additional insights when incrementally increasing the CO2 tax are provided. The scenario analysis shows that the market diffusion is highly dependent on the evolution of external factors. A CO2 tax considerably higher than the current governmental plan by 2030 (such as 150€/t, based on its monetary value by 2020) is required to have a meaningful impact on the market diffusion of EVs. Moreover, applying a considerable high CO2 tax leads to a slower growth of BEV and PHEV from 2040 onwards that is compensated by a growth in FCEV vehicles.

Coordinated charging station search in stochastic environments: A multiagent approach

Range and charge anxiety remain essential barriers to a faster electric vehicle (EV) market diffusion. To this end, quickly and reliably finding suitable charging stations may foster an EV uptake by mitigating drivers' anxieties. Here, existing commercial services help drivers to find available stations based on real‐time availability data but struggle with data inaccuracy, for example, due to conventional vehicles blocking the access to public charging stations. In this context, recent works have studied stochastic search methods to account for availability uncertainty in order to minimize a driver's detour until reaching an available charging station. So far, both practical and theoretical approaches ignore driver coordination enabled by charging requests centralization or sharing of data, for example, sharing observations of charging stations' availability or visit intentions between drivers. Against this background, we study coordinated stochastic search algorithms, which help to reduce station visit conflicts and improve the drivers' charging experience. We model a multiagent stochastic charging station search problem as a finite‐horizon Markov decision process and introduce an online solution framework applicable to static and dynamic policies. In contrast to static policies, dynamic policies account for information updates during policy planning and execution. We present a hierarchical implementation of a single‐agent heuristic for decentralized decision making and a rollout algorithm for centralized decision making. Extensive numerical studies show that compared to an uncoordinated setting, a decentralized setting with visit intentions sharing decreases the system cost by 26%, which is nearly as good as the 28% cost decrease achieved in a centralized setting. Even in long planning horizons, our algorithm reduces the system cost by 25% while increasing each driver's search reliability.

Effects of mixed policies on the cooperative and noncooperative strategies of auto manufacturers and charging infrastructure operators considering consumer preferences

ABSTRACT The dual-credit policy for auto manufacturers and the subsidy policy for charging infrastructure operators have become important policies to guide and promote the development of the automotive industry. However, few studies consider the impact of mixed policies on the market strategies of auto manufacturers and charging infrastructure operators considering consumer green preferences. To fill the gap, this article establishes optimization models to analyze and compare the effects of mixed policies on the decision-making of auto manufacturers and charging infrastructure operators under the cooperative and noncooperative modes considering consumer preference. The results reveal four main insights: (1) Two types of policies all have direct positive effects on the market diffusion of electric vehicles. Under the noncooperative mode, the dual-credit policy has no spillover effect. Under cooperative mode, two types of policies all have spillover effects. The dual-credit policy and charging infrastructure subsidy policy have positive superposition effects on the optimal number of charging piles, and the optimal demands for electric vehicles. (2) When the credit price is less than a certain threshold, there is a substitutive effect between the charging infrastructure subsidy policy and the dual-credit policy on promoting the market diffusion of electric vehicles. (3) There is a substitutive effect between high-level consumers’ green preference and policies on promoting the market diffusion of electric vehicles. (4) Under the cooperative mode, the direct and spillover effects of policies are more than that are under the noncooperative mode. These insights demonstrate the effectiveness and limitations of policies and the importance of providing complementary policies for consumers. The government should encourage market cooperation between auto manufacturers and charging infrastructure operators, maintain a stable price level for credits, and introduce incentive policies for green consumption.

A tale of five cities: The role of municipalities in the market diffusion of wooden residential multistory construction and retrofits

To enhance sustainable urban development, cities may contribute to the market diffusion of wooden multistory residential construction (WMC) and to wood use in the renovations of old multistory residential buildings (i.e., wooden retrofits). For the construction sector, building with wood enables a shift from the dominant concrete-based building regime, which has hindered the industrialization of building processes and the use of prefabricated modules. Although industrial wood construction has become more common in Finland in the 2000s, WMC and especially wooden retrofits have remained niche systems in residential building markets. The aim of our study is to provide information on how municipalities, especially cities at the core of urban development, may contribute to the market diffusion of WMC and wooden retrofits through policy instruments and via their involvement in local business ecosystems (BE). The interview data of the study were mainly gathered from 40 professionals representing the five case cities, but we also included other experts connected to local BEs that linked with the WMC and wooden renovation cases. We employed qualitative methods in the analyses. Our study shows that WMC and wooden retrofits could be catalyzed by both policy instruments and collaboration in BEs. Results show that policy instruments have been more effective when they include characteristics of the building projects (e.g., instrument usability differs between municipalities or private persons as building owners). To be powerful actors, municipalities could take on more active collaborative roles within the local BEs (e.g., as initiators of projects as building owners or as active enablers). As an implication of these results, city-level experimentation could benefit from a full range of policy measures and mixes to accelerate the diffusion of WMC and wooden retrofits.

Electric vehicles adoption: A systematic review (2016–2020)

AbstractAiming to diversify the energy matrix, mainly regarding the transport sector, electric vehicles have been used as an option to reduce emissions. Despite many advantages of this technology, such as zero operational GHG emission, better energy efficiency compared to conventional vehicles, and low maintenance costs, the purchase cost is still high in several countries, compromising their adoption by many customers. In this context, this paper aims to evaluate the factors that impact electric vehicles (EV) adoption. A systematic review was conducted considering peer‐reviewed papers published in English from 2016 to 2020, and results were separated into clusters to enable the assessment. The main factors found in the literature that most impacted EV market diffusion negatively were the purchase price and the risks related to the market infancy, while subjective norm, perceived behavior, prior knowledge and experience with EV and government incentives influenced EV adoption positively.This article is categorized under:Human and Social Dimensions > Behavioral ScienceCities and Transportation > Electric MobilityEnergy and Power Systems > Electrification

Trends in Automotive Battery Cell Design: A Statistical Analysis of Empirical Data

Lithium-ion (Li-ion) batteries have become the preferred power source for electric vehicles (EVs) due to their high energy density, low self-discharge rate, and long cycle life. Over the past decade, technological enhancements accompanied by massive cost reductions have enabled the growing market diffusion of EVs. This diffusion has resulted in customized and cost-effective Li-ion battery cell designs tailored to automotive requirements. This study describes design trends in Li-ion batteries from the pack to the electrode level based on empirical data, including pack energy, cell capacity, outer cell dimensions and formats, energy density, specific energy, and electrode properties, such as active material selection, porosities, and component thicknesses. Market share-weighted findings imply several trends, such as (1) increasing cell dimensions, with the longest cells reaching 500 mm (pouch) and almost 1000 mm (prismatic) in 2021, (2) increasing differentiation between either high-energy or low-cost cathode and anode materials, and (3) increasing cell energy, equivalent to gaining about 100% (energy density) and 70% (specific energy) compared to the 2010 and 2021 averages. Despite these improvements, this study finds that the widespread market diffusion of the latest cell technologies proceeds slower than industry announcements suggest and that several well-known, literature-proofed potentials are not yet fully exploited.

Captive Offshoring, Innovation and Market Diffusion: Evidence from the Swedish Community Innovation Survey

AbstractAlthough the effects of captive offshoring on firm innovation have increasingly become a subject of study, the literature did so far not distinguish between the effects on introducing innovation as opposed to the effects their market diffusion. This distinction is important. By integrating insights from the innovation diffusion literature, we argue that the effects of captive offshoring on home base innovation are likely to differ between the generation and the diffusion phases. Using a matched employer-employee panel dataset drawn from consecutive waves of the Swedish Community Innovation Survey (CIS) between 2009 and 2015, it is shown that captive offshoring, as measured by the share of employees at foreign locations, has an inverted u-shape effect on innovation propensity (with positive effects for the average firm). In contrast, employment offshoring does not, on average, affect the rate of diffusion as measured by the share of turnover from new products. For firms with more novel product innovations, the effects are even negative.

Research on the evolution of disruptive technological innovation cooperation network: a case study of blockchain and automatic driving technology

ABSTRACT Overcoming technological R&D barriers and market diffusion pressures through innovative cooperation is an important channel in the evolution of disruptive technologies. Aiming at the evolution of disruptive technological innovation cooperation network, this paper combines technology life cycle theory with social network analysis method, the overall evolution and individual evolution characteristics of disruptive technological innovation cooperation network are analysed. The research results show that in the life cycle, disruptive technology has the characteristics of latent in the early stage and explosive after maturity. In terms of overall evolution, the scale of disruptive technological innovation cooperation network is expanding, but the cohesion and small-world level are decreasing, the intensity of knowledge exchange and information transmission is declining. About the core subject, there is a synergistic dynamic mechanism between the market and the government. In the evolution of cooperation model, it shows the development trend from poor cooperation model to exploring cooperation mode and cultivating cooperation mode. The research conclusion enriches and expands the theoretical research in the field of disruptive innovation, and can provide inspiration for the policy design and management optimisation of disruptive technological innovation cooperation network.

Fuel Cell Products for Sustainable Transportation and Stationary Power Generation: Review on Market Perspective

The present day energy supply scenario is unsustainable and the transition towards a more environmentally friendly energy supply system of the future is inevitable. Hydrogen is a potential fuel that is capable of assisting with this transition. Certain technological advancements and design challenges associated with hydrogen generation and fuel cell technologies are discussed in this review. The commercialization of hydrogen-based technologies is closely associated with the development of the fuel cell industry. The evolution of fuel cell electric vehicles and fuel cell-based stationary power generation products in the market are discussed. Furthermore, the opportunities and threats associated with the market diffusion of these products, certain policy implications, and roadmaps of major economies associated with this hydrogen transition are discussed in this review.

Grid-friendly pricing mechanism for peer-to-peer energy sharing market diffusion in communities

As a novel trading mode, the peer-to-peer (P2P) energy market cannot be accepted by the end-users immediately. There is an adoption process before all the energy prosumers participate in the P2P trading market. Therefore, we first employ a generalized Bass model to depict the P2P energy market diffusion process in the communities. Since the P2P market is still in the diffusion stage, we develop a hybrid P2P energy market consisting of traditional pool-based and P2P trading modes. Then, we establish the cost minimization models of energy prosumers, community managers, and system operators to analyze the market equilibrium in such a hybrid P2P energy market. The dynamic network usage costs are included in the system operator’s model to guarantee the market operation considering the heterogeneous prosumers. Finally, we propose a hybrid market-clearing method consisting of deep reinforcement learning and optimization algorithms. We model the generalized Bass model as an equivalent Markov process. The community manager and system operator can learn the near-optimal prices in their Markov decision processes with prosumers’ partial information. Numerical simulations demonstrate that the Markovian Bass model describes the P2P market adoption process precisely. The trading and network usage prices with and without considering the P2P energy market diffusion are compared and analyzed.