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This study aims to form a new concept of power-to-gas-based virtual power plant (GVPP) and propose a low-carbon economic scheduling optimization model for GVPP considering carbon emission trading.

In view of the strong uncertainty of wind power and photovoltaic power generation in GVPP, the information gap decision theory (IGDT) is used to measure the uncertainty tolerance threshold under different expected target deviations of the decision-makers. To verify the feasibility and effectiveness of the proposed model, nine-node energy hub was selected as the simulation system.

GVPP can coordinate and optimize the output of electricity-to-gas and gas turbines according to the difference in gas and electricity prices in the electricity market and the natural gas market at different times. The IGDT method can be used to describe the impact of wind and solar uncertainty in GVPP. Carbon emission rights trading can increase the operating space of power to gas (P2G) and reduce the operating cost of GVPP.

This study considers the electrical conversion and spatio-temporal calming characteristics of P2G, integrates it with VPP into GVPP and uses the IGDT method to describe the impact of wind and solar uncertainty and then proposes a GVPP near-zero carbon random scheduling optimization model based on IGDT.

This study designed a novel structure of the GVPP integrating P2G, gas storage device into the VPP and proposed a basic near-zero carbon scheduling optimization model for GVPP under the optimization goal of minimizing operating costs. At last, this study constructed a stochastic scheduling optimization model for GVPP.

Coal and power generation are related upstream and downstream industries. Coal price marketization and electricity price regulation have caused the price of coal to be sensitive to the benefits of generators. The paper aims to discuss these issues.

As a financial tool, contracts for differences can both help balance interests and reduce risks caused by spot price fluctuation. This thesis regards coal demand as a triangular fuzzy stochastic variable while directing a levelling consideration towards risk returns for coal and power enterprises that are involved in coal generation contracts for differences. Risk and benefit measurement models were established between coal suppliers and power generators, and risk and benefit balance optimization models for contract negotiation were constructed.

A numerical example showed that the above models can be effectively used to avoid the risks of coal-electricity parties.

This thesis regards coal demand as a triangular fuzzy random variable while directing a levelling consideration towards the risk return to coal and power enterprises that are involved with coal generation contracts for differences. The features of this thesis are the following: demand information is regarded as a fuzzy random variable instead of a random variable. With historical data, sales experience and increasingly clear macro-economic conditions, coal and power enterprises are able to make a fuzzy decision – to a certain extent – when the transaction approaches. Accurate market information enables the supply chain system to satisfy the clients’ needs better, improve the profit level or avoid severe financial damages; by developing a feasible set of contracts for different parameters, it is possible to estimate whether the price difference enables supply chain coordination, requires changes or gives accounts to all involved parties of the supply chain; and without the assumption that the traditional M-V rule is unfavourable to decision makers, this thesis proposes the prospect M-V rule, which involves decision makers’ projections of future coal generation prices and enables wide applicability of the response method to contracts for differences.

The purpose of this paper is to study the influence of different trade modes on the electricity market.

A linear model between power units' output and their bidding prices is presented and optimal models to minimize the purchase power cost of power grid companies are presented, applying static games and dynamic games, respectively. Then the relation between power generation amount and units' bidding price is settled by using difference methods. In addition, optimization models are established to optimize profits of units at discriminatory bidding or uniform marginal price applying static game and dynamic game. Finally, the economic benefits and fair competition are compared and analyzed.

If impartiality is emphasized, the detailed history bidding information should not be opened. Also, it is fairer but difficult to control units' speculative behavior at uniform marginal price.

A supposition has been made that all participants are rational.

The paper presents useful advice for improving the trade mode of the electricity market.

Power units' bidding models and strategies are presented at discriminatory bidding price or at uniform marginal price applying non‐cooperation static game and dynamic game, respectively.

Long-term contract is an important developing direction of China's coal industry coordination. This paper aims to discuss how to use contract for difference (CFD) to avoid risk and effectively increase the benefit of both coal and thermal power plants in the coal-electricity supply chain.

Based on prospect theory, this paper takes the risks and benefits of the coal and coal-fired power plants in the coal supply chain under CFD into balanced consideration to construct the contract coordination mechanism. In this mechanism, the coal demand in the coal supply chain equilibrium under centralized decision-making is regarded as the total annual volume of transactions needed to design the contract coordination mechanism and solve double marginalization. Then, based on prospect theory, in the construction of CFD, this paper takes the income of power and coal enterprises when they are in equilibrium under Stackelberg non-cooperative game as the reference point. In addition, considering that coal demand is a random variable, the CFD with a one-year trading session can be designed.

The research derives the coal price of the contract for difference, contract trading volume and its proportion of the total trading volume. A numerical example shows that the model above can be used to effectively avoid the risk of both coal and electricity sides.

To solve the conflict between coal enterprises and thermal power plants, let the coal-electricity supply chain be converted from non-cooperative game to cooperative game. Based on the prospect theory, this paper takes the income of the non-cooperative game of coal and thermal power plants as a reference point and considers how to design the coordination mechanism, the contract for difference, so as to make the two parties cooperate to solve the double marginal utility of the non-cooperative game in a chain supply. The main innovation of the work lies in the following: first, the coal demand when the coal-electrical supply chain is in balance under centralized decision-making is taken as the total annual trading volume needed to design the contract coordination mechanism and solve double marginalization. Second, based on prospect theory, in the construction of CFD, the benefits of coal-fired power plants and coal enterprises when both sides are in equilibrium under the Stackelberg non-cooperative game are taken as the reference points, and coal demand is taken as a random variable to design the CFD with a one-year transaction period. The price of coal that is not traded through CFD is calculated according to the daily market price. Third, this paper proposes the prospect M-V criterion of the risk-benefit equilibrium of both power and coal enterprises, which means that the risk-benefit equilibrium of both sides is the prospect variance effect of both sides relative to the reference point benefit divided by the prospect expectation effect.

Contractor selection is critical in green buildings (GBs) since the preferred contractor has the responsibility to achieve construction sustainability as well as relationship sustainability. The developer satisfaction reflecting requirements can boost the cooperative relationship among stakeholders and act as an evaluation scale for the success of GB projects, which needs to be emphasized in the selection process but little involved in the existing research. This study explores improving GB contractor (GBC) selection by integrating developer satisfaction into selection procedures.

A systematic framework of GBC selection including twenty-five criteria from literature review and experts survey is firstly constructed. Both tactical and strategic criteria are further classified into Kano categories (must-be, one-dimensional, and attractive categories) using the fuzzy Kano model (FKM), and weighted by the developer satisfaction index. The model proposed by this study combining FKM and TOPSIS divides the selection process into the filtration phase and selection phase by Kano categories. The proposed model is finally verified through performance comparison among multiple methods in a case.

Selection criteria are measured linearly and nonlinearly, showing criteria having nonlinear satisfaction change accounts for two-thirds of all. Criteria at tactical level tend to be must-be or one-dimensional categories for the developer, and most strategic criteria are classed as the attractive category, indicating that adding strategic criteria is necessary for long-term cooperation. The proposed model, using developer satisfaction to improve the selection process, ensures the selected GBC to be the most satisfactory with requirements of the developer and makes the performance of GBCs easily distinguishable.

This study contributes to the existing body of knowledge for promoting relationship sustainability by supplementing an integrated model with emphasis on developer satisfaction in GBC selection, so as to establish a good initial foundation due to the match between performances of GBCs and needs of developers. It not only helps maximize developer satisfaction in GBC selection by applying satisfaction to pre-construction management, but also instructs GBCs to prioritize performance improvements. The framework is also conducive for developers to classify selection criteria and select other participants (like green suppliers) from the satisfaction perspective in GBs.

Insufficient intra-organizational diffusion of prefabricated construction (PC) technology hinders its implementation benefits. More research on intra-organizational diffusion of PC technology is required to improve organizational performance in PC implementation. This study aims to explore the antecedents and consequence of intra-organizational diffusion of PC technology.

This study established an antecedent and consequence model of intra-organizational diffusion of PC technology from the perspective of contingency theory. The model was empirically tested by 91 valid questionnaires using partial least squares-structural equation modeling (PLS-SEM).

The results indicate that organizational support (OSU), organizational climate (OC) and mechanistic organizational structure (OST) positively influence intra-organizational diffusion of PC technology, which further positively influences organizational performance. The relationship between OC and intra-organizational diffusion of PC technology is mediated by OSU. Technological turbulence negatively moderates the relationship between OSU and intra-organizational diffusion.

This is the first paper to study the antecedents and consequence of intra-organizational diffusion of PC technology and an expansion of contingency theory in the research field of PC technology. This study helps to theoretically stimulate future research on intra-organizational diffusion and practically promote intra-organizational diffusion of PC technology along with improving organizational performance in its implementation.

Although prefabricated construction (PC) technology has attracted considerable attention worldwide because of its significant role in the global fight against COVID-19, market-driven adoption is still limited. The mechanisms for PC technology adoption have yet to be defined, which inhibits its diffusion in the construction market. This study aims to reveal the intrinsic motivation and action mechanism for PC technology adoption.

Drawing on the technology acceptance model (TAM), the study integrates characteristics from the diffusion of innovation theory to propose a multifaceted model for explaining practitioners’ PC technology adoption behavior from technology, organization and environment contexts. The proposed theoretical model was empirically examined via a survey of 234 professionals in mainland China using the partial least squares-structural equation modeling technique.

The outcomes indicated that relative advantage, corporate social responsibility and market demand are significantly positively related to practitioners’ perceived usefulness from PC technology. Regulatory support and trading partner support have noticeable positive effects on practitioners’ perceived ease of use from PC technology. Perceived ease of use is found to positively influence perceived usefulness, and both of them have a positive influence on the attitude toward adopting PC technology. Attitude is further confirmed as an important predictor of adoption intention, which would lead to actual PC technology adoption behavior.

To the best of the authors’ knowledge, this paper is the first attempt to explore industry perceptions toward PC technology adoption, providing valuable guidance for the effective diffusion of PC technology and laying a reliable foundation for research on other construction innovation adoption in post-COVID-19.

Off-site construction (OSC) has been regarded as a clean and efficient production approach to help the construction industry towards sustainability. Different levels of OSC technologies vary greatly in their implementations and adoptions. Compared to low OSC level technologies have been applied widely, the adoption of high OSC level technologies (HOSCLTs) in practice remains limited. The adoption mechanism for HOSCLTs by firms has not been clear, hindering their promotion. This study aims to explore the mechanism combining subjective and objective adoption for HOSCLTs.

This study developed an integrated model illustrating mechanism for HOSCLTs adoption based on the technology acceptance model (TAM), which has strong capacity to explain potential adopters' subjective intentions to adoption, and the task-technology fit (TTF) theory, which well describes the linkages between the task, technology and performance in technology adoption. The proposed model was then empirically evaluated through a survey of 232 practitioners in the Chinese OSC industry using partial least squares structural equation modeling.

The results indicate that both task characteristics (TAC) and technology characteristics (TEC) positively affect TTF of HOSCLTs. TAC, TTF, firm conditions and stakeholder influence have significant positive effects on perceived usefulness (PU), which further positively influence attitude towards adoption. TEC and firm conditions are significantly related to perceived ease of use (PEU). TTF, PEU and attitude towards adoption are good predictors of behavior intention to HOSCLTs adoption. PEU only significantly influences adoption intention and is not observed to influence attitudes and PU, unlike prior research on common OSC adoption.

This study contributes to the body of knowledge by exploring HOSCLTs adoption in the industry based on distinguishing the levels of OSC technologies and supplementing an integrated model for explaining the mechanism with the combination of subjective and objective adoption. The study also provides useful insights into understanding and promoting HOSCLTs adoption for policy makers and stakeholders actively involved in the OSC field.

This study aims to focus on the sustainability of prefabricated medical emergency buildings (PMEBs) renovation after the epidemic, to address the problem that large numbers of PMEBs may be abandoned for losing their original architectural functions. This study develops an evaluation system to identify and measure sustainable factors for PMEBs’ renovation schemes. Qualitative and quantitative analysis of PMEBs’ renovation scheme was conducted based on cloud model evaluation method and selected the renovation scheme in line with sustainable development. The study promotes evaluation methods and decision-making basis for the renovation design of global PMEBs and realizes the use-value of building functions again.

By referring to the existing literature, design standards and expert visiting a set of evaluation index systems which combines the renovation of the PMEBs and the sustainability concept has been established, which calculates the balanced optimal comprehensive weight of each indicator utilizing combination weighting method, and quantifies the qualitative language of different PMEBs’ renovation schemes by experts through characteristics of the cloud model. This paper takes Huoshenshan hospital a representative PMEB during the epidemic period as an example, to verify the feasibility of the cloud model evaluation method.

The research results of this paper are that in the PMEBs’ renovation scheme structural reformative (T11) and corresponding nature with the original building (T13) have the most important influence; the continuity of architectural cultural value (T22) and regional development coherence (T23) are the key factors affecting the social dimension; the profitability of renovated buildings (T34) is the key factor affecting the economic dimension; the environmental impact (T41), resource utilization (T42) and ecological technology (T43) are the key factors in the environmental dimension.

This study contributes to the existing body of knowledge by supplementing a set of scientific evaluation methods to make up for the sustainability measurement of PMEBs’ renovation scheme. The main objective was to make renovated PMEBs meet the needs of urban sustainable development, retain the original cultural value of the buildings, meanwhile enhance their social and economic value and realize the renovation with the least impact on the environment.

The coordinated development of the urbanization and construction industry is crucial for the sustainable development of cities. However, the coupling relationship and coordination mechanism between them remain unclear. To bridge this gap, this study attempts to explore the level of coupling coordination between new urbanization and construction industry development and investigate the critical driving factors influencing their coupling coordination degree.

By referring to the existing literature, two index systems were established to evaluate the development level of the new urbanization and construction industry. The spatiotemporal characteristics of the coupled coordinated development of the new urbanization and construction industry in China from 2014 to 2020 were investigated using the coupling coordination model. The Markov chain and geographic detector were adopted to understand the transition probability and driving factors of the coupling coordination degree.

The results indicate that the coupling degree of China's new urbanization and construction industry is high, and the two systems exhibit obvious interaction phenomena. However, the construction industry in most provinces lags behind the new urbanization. A positive interactive relationship and coordination mechanism has not been established between the two systems. Furthermore, the  coupling contribution degree of the driving factors from high to low is as follows: market size > labor resource concentration > government investment ability > economic development level > industrial structure > production efficiency > technology level. Accordingly, a driving mechanism including market, policy, economic, and production technology drivers was developed.

This study contributes to the existing body of knowledge by providing a set of scientific analysis methods to address the deficiency of coordination mechanism research on new urbanization and the construction industry. The results also provide a theoretical basis for decision makers to develop differentiated sustainable development policies.