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The purpose of this study is to analyze the effect of foreign direct investment (FDI) on pollution emissions and how environmental regulation affects this relationship.

In the empirical research, the authors selected panel data for 30 provinces in China from 2005 to 2019 as samples. First, the authors used the instrumental variable method to verify the existence of the above hypotheses in China. Then, the authors analyzed the moderating effect of different types of environmental regulations on the environmental effects of FDI. Next, in further discussion, the authors analyzed the difference between the environmental effect and the moderating effect in different time periods and regions, respectively. Finally, the authors discussed whether the different intensities of environmental regulations lead to the transfer effect of FDI in choosing investment destinations.

The result shows that FDI can help reduce pollution emissions and create a “pollution halo” effect, which is enhanced by command-and-control regulation but suppressed by market-based incentives. The heterogeneity analysis reveals that the 18th National Congress of the Communist Party has weakened the pollution halo effect of FDI, while the environmental effect of FDI in the eastern region is not significant, but in the middle and western regions, there is a significant pollution halo effect and a positive moderating effect of environmental regulations. Finally, further analysis reveals that FDI has a transfer effect under command-and-control environmental regulations.

First, the main purpose of this paper is to study the relationship between FDI and pollution emissions from the perspective of heterogeneous environmental regulation. Therefore, there is no detailed discussion on their effect mechanism of them. Second, limited by data, the authors adopt the single index to measure the stringency index of command-and-control and market-based incentive environmental regulations in China. The single index may not be able to fully reflect the intensity of regional environmental regulation, so the construction of a composite indicator is necessary. These shortcomings are the focus of the authors' future research.

Under the guidance of high-quality development, the conclusions above can provide reference for adjusting FDI policies and improving environmental regulation policies.

The innovations in this paper can be summarized as the following four dimensions: First, the authors use the instrumental variable (IV) method to address endogeneity in the relationship between FDI and pollution emission, which can further ensure the robustness of the research results and increases the credibility of the paper. Second, the authors distinguish between two types of environmental regulations to investigate their moderating effect on the environmental impact of FDI. Third, the authors consider the temporal and spatial heterogeneity of both the environmental effects of FDI and the moderating effect of regulation. Last, the authors analyze the spatial spillover of environmental regulation through the study of the transfer effect.

The operation of water environment treatment Public-Private Partnership projects (WETP-PPP) is crucial to the project effectiveness. However, there are often problems in projects that attach importance to construction and neglect operation management, which seriously affect the project operation effect. To ensure the good operation effect of the WETP-PPP, an evolutionary game model of the regulation strategy during the operation period of WETP-PPP is constructed.

An evolutionary game model of regulation is established which considers the government, the project company and the public in water environment treatment Public-Private Partnership projects (WETP-PPP). Five scenarios of equilibriums and the game's evolutionary stable strategies are analyzed, and the corresponding stability conditions are then obtained. Finally, through the simulation, the influence of different factors on the choice of the three-party strategy is analyzed.

First, the key factors that affect the evolution game are the regulation costs and performance rewards of the government, the project company's operation costs and penalties for opportunism and the public supervision costs and rewards. Second, in order to ensure the operation effect, the government needs the performance incentive from the superior government. Third, the public's supervision enthusiasm needs to be mobilized by the government. Last, the penalty strength of speculative operation should be strong enough to play a deterrent role.

The theoretical research in this paper has some limitations. Initially, due to the large number of participants in WETP-PPP, in addition to the government department, the project company and the public studied in this paper, it also involves the consulting industry and financial institutions. In the future, more participants can be added to form four-party interest relationships and conduct four-party evolutionary game research. Second, the operation environment of WETP-PPP is complex and changeable, and various influencing factors are intertwined, the number of parameters involved in this paper is limited, and further detailed research is needed in the future.

Based on the evolutionary game theory, this article discusses the evolution law of the tripartite game behavior of the government department, the project company and the public, which is helpful to clarify the strategy evolution path of the tripartite in the WETP-PPP, and the generation condition and evolution mechanism of the equilibrium strategy of the tripartite game. The key parameters affecting the tripartite strategy selection are analyzed through simulation, which can provide reference for the government department to formulate relevant measures. At the same time, it broadens the application field of evolutionary games and supplements the research on the management mechanism of WETP-PPP during the operation period.

Based on the evolutionary game theory, this paper introduces the supervision behavior of the public, which can provide a new perspective for researchers to conduct relevant research. Secondly, for the regulation during the operation of WETP-PPP, this paper can provide reference for the government department to establish a scientific public supervision system, improve the government supervision mechanism and other relevant measures, which can help promote the public supervision willingness, improve the regulation efficiency of the government and guide the project company to reduce speculation, so as to ensure the effect of water environment management.

This paper focuses on the regulation of WETP-PPP during the operation period to research interactions among the government, the project company and the public. Based on the analysis of the evolutionary game, some suggestions are put forward, such as perfecting the government regulation mechanism, optimizing the reward and punishment system for the project company and broadening the channels of public supervision. The research results of this paper can provide support for the government's regulation of WETP-PPP and ensure the project operation effect.

The green innovation behavior of construction enterprises is the key to reducing the construction industry's carbon emissions and realizing the green transformation of the construction industry. The purpose of this study is to reveal the evolutionary mechanism of green innovation behavior in construction enterprises.

This study is based on resource-based theory, Porter's hypothesis and signaling theory. First, a measurement model of the green innovation behavior of construction enterprises was constructed from three aspects: environmental regulation, enterprise resources and public opinion through hierarchical analysis. Then, the state values of the measurement model of green innovation behavior of construction enterprises were calculated through the time series data from 2011–2018. Finally, the Markov chain model was used to predict the evolutionary trend of green innovation behavior of construction enterprises, and the accuracy of the prediction effect of the Markov chain model was verified using the time series data of 2019.

The Markov chain model of green innovation behavior of construction enterprises constructed in this study has high accuracy. This model finds that the transition of the growth state of green innovation behavior in China's construction industry is fluid and predicts the evolution trend of the innovation behavior of construction enterprises. In the future, the green innovation behavior of construction enterprises has a probability of 70.17% to be in a continuous growth state and 40.27% to be in a rapid growth state.

Based on the Markov chain model of green innovation behavior of construction enterprises, this study finds that the transition of the growth state of green innovation behavior of construction enterprises in China has the characteristics of liquidity. In addition, it reveals the development process of the green innovation behavior of construction enterprises from 2011–2018 and predicts the evolution trend of the green innovation behavior of construction enterprises.

The purpose of this paper is to analyse the policy instruments used by the China's Government on prefabricated construction (PC) development, with the aim to clarify the pattern and discover the focus of the policy instruments using the methods of bibliometric analysis and content analysis.

Through a thorough screening by all researchers, 25 policies were identified from 1995 to 2021 were selected and analysed. The external attribute analysis clarified the issuing year, organisation, and the format of each policy. The content analysis was adopted firstly to analyse the policy instrument. An analysis framework including environmental instruments, supply instruments and demand instruments was applied in categorising and counting of each policy instrument. The bibliometric analysis was then carried out to extract keywords of the policy instruments, construct a co-word network and complete the cluster analysis.

The results indicate that the policies lack consistency and had relatively low authority. The results of content analysis show that the policy system relies heavily on environmental and supply instruments, whilst the use of demand instruments seems to be grossly inadequate. The results of the bibliometric analysis identify the core ideas of each policy instrument category, discuss the existing problems and then put forward the corresponding countermeasures.

This study comprehensively and systematically analysed the policy instruments on facilitating the development of PC in China which broaden the research perspectives of the PC development by introducing the methods of political science. The research findings afford helpful information for future policy adjustments and elucidate the effective delivery of policies to facilitate PC development for developing countries.

This study provides an in-depth understanding of policy instruments used by China's Government on PC development. By integrating the policy instrument analysis framework into the mixed methods of content analysis and bibliometric analysis, this study provides an innovative way to conduct policy instrument analysis.

There is a growing body of literature discussing the green logistics practices (GLPs) that companies could introduce to reduce the logistics environmental impact. Current approaches also identify several influencing factors within firms that could serve as barriers to, or enablers of, GLPs. However, less is known about the role of extra-firm stakeholders, even though these are crucial to operationalizing green logistics effectively. This study merges current theoretical understanding with empirical evidence to provide a detailed stakeholder analysis of GLPs.

Using stakeholder theory as a theoretical lens, the authors aimed at offering a mid-range contribution by conducting multiple embedded case studies examining Italian logistics service providers and shippers. GLPs and the related influencing factors were examined as sub-units of analysis within broader companies' environmental sustainability strategies.

The authors identified cascading effects among factors influencing the adoption of GLPs (e.g. key economic factors are affected by external factors which also influence organizational and collaboration factors). These effects are moderated by interdependencies between primary and secondary stakeholders, and the study highlights the prominent involvement of secondary stakeholders, such as final consumers.

This paper contributes to better understanding how and why companies adopt GLPs, emphasizing the wide set of stakeholders involved and illustrating how different stakeholders impact on GLPs adoption by affecting a set of influencing factors. By combining insights from the available literature with contemporary empirical data, the authors emphasize how Logistics Service Providers (LSPs) and shippers can no longer address the adoption of GLPs as “focal companies”, but only as part of a “focal network of interconnected stakeholders”, all of them influencing GLPs adoption.

Platform ecosystem governance is a decisive issue for orchestrators, as the motivation and behaviors of the complementors in an ecosystem can be distinctly different, shaped by the specific arrangements they have within the ecosystem. However, knowledge about adaptation in the governance of platform ecosystems is quite limited. First, the authors hardly know which obstacles are arising for orchestrators due to typical governance settings and their consequences. Second, the authors know less about governance strategies by orchestrators that help deal with these obstacles.

The authors follow an inductive, multistep case-study-based approach with multiple cases using guidelines proposed by Yin (2018). Based on predefined criteria, the authors selected 41 platform ecosystems with a “hub and spoke” system within and across several industries and collected a wide range of data. The authors conducted 14 interviews with executives of these platform ecosystems to gain further insights, transcribed and/or summarized all interviews, and analyzed the data.

Based on the dataset, the authors identify four significant obstacles and ten strategies of orchestrators in platform ecosystems. This approach allows us to gain insight into innovative approaches orchestrators conduct to cope with these challenges.

The authors already have a broad range of studies on ecosystem governance in the literature. However, research dealing with the dynamics of governance regimes is quite rare. The study examines how orchestrators of platform ecosystems react to emerging obstacles they are confronted with during the evolution of their platform ecosystems. Partly, these strategies might be expected, but mostly they show innovative approaches for handling these obstacles that have not been reported in research so far.

Innovation ecosystems (IEs) have attracted the attention of policymakers and researchers because of their potential to positively affect territories, creating shared value. However, due to the fragmentation of IEs, how this happens in different IEs has been explored only partially. This research aims to bridge this gap, aiming to support policymakers in understanding how to foster shared value in diverse IEs.

The paper identifies, based on the literature, two “drivers of aggregation” of IE's actors as key dimensions characterizing shared value in IEs, namely physical proximity and dominant issue. If these are combined, three archetypes emerge: Hub- and Chain-Driven, Place-Driven, Competence- and Issue-Driven IEs.Then, elements useful for understanding shared value creation in these archetypes are framed and studied in real cases.

Results reveal that aggregation drivers affect shared value creation, which differ among archetypes: in Competence- and Issue-Driven IEs alignment is challenged by the low physical proximity, which in Place-Driven IEs is high, but not enough to grant shared value; in Hub- and Chain-Driven IEs, the hub is the orchestrator, representing both a driver and a risk.

Differences in shared value creation processes relate to the set-up of the IE, which has relevant implications for policy definition. In Competence- and Issue-Driven IEs, policies at diverse levels align in funding and promoting the IE; in Place-Driven IEs, policies support anchors' development on-site; in Hub- and Chain-Driven IEs, policies, sometimes absent, should foster partnerships for projects for the territory, IE's enlargement and resilience.

An important and challenging question for air transportation regulators and airport operators is the definition and specification of airport capacity. Annual capacity is used for long-term planning purposes as a degree of available service volume, but it poses several inefficiencies when measuring the true throughput of the system because of seasonal and daily variations of traffic. Instead, airport throughput is calculated or estimated for a short period of time, usually one hour. This brings about a mismatch: air traffic forecasts typically yield annual volumes, whereas capacity is measured on hourly figures. To manage the right balance between airport capacity and demand, annual traffic volumes must be converted into design hour volumes, so that they can be compared with the true throughput of the system. This comparison is a cornerstone in planning new airport infrastructures, as design-period parameters are important for airport planners in anticipating where and when congestion occurs. Although the design hour for airport traffic has historically had a number of definitions, it is necessary to improve the way air traffic design hours are selected. This study aims to provide an empirical analysis of airport capacity and demand, specifically focusing on insights related to air traffic design hours and the relationship between capacity and delay.

By reviewing the empirical relationships between hourly and annual air traffic volumes and between practical capacity and delay at 50 European airports during the period 2004–2021, this paper discusses the problem of defining a suitable peak hour for capacity evaluation purposes. The authors use information from several data sources, including EUROCONTROL, ACI and OAG. This study provides functional links between design hours and annual volumes for different airport clusters. Additionally, the authors appraise different daily traffic distribution patterns and their variation by hour of the day.

The clustering of airports with respect to their capacity, operational and traffic characteristics allows us to discover functional relationships between annual traffic and the percentage of traffic in the design hour. These relationships help the authors to propose empirical methods to derive expected traffic in design hours from annual volumes. The main conclusion is that the percentage of total annual traffic that is concentrated at the design hour maintains a predictable behavior through a “potential” adjustment with respect to the volume of annual traffic. Moreover, the authors provide an experimental link between capacity and delay so that peak hour figures can be related to factors that describe the quality of traffic operations.

The functional relationships between hourly and annual air traffic volumes and between capacity and delay, can be used to properly assess airport expansion projects or to optimize resource allocation tasks. This study offers new evidence on the nature of airport capacity and the dynamics of air traffic design hours and delay.

This study reveals the green building development path and analyzes the optimal government subsidy equilibrium through evolutionary game theory and numerical simulation. This was done to explore the feasible measures and optimal incentives to achieve higher levels of green building in China.

First, the practice of green building in China was analyzed, and the specific influencing factors and incentive measures for green building development were extracted. Second, China-specific evolutionary game models were constructed between developers and homebuyers under the market regulation and government incentive mechanism scenarios, and the evolutionary paths were analyzed. Finally, real-case numerical simulations were conducted, subsidy impacts were mainly analyzed and optimal subsidy equilibriums were solved.

(1) Simultaneously subsidizing developers and homebuyers proved to be the most effective measure to promote the sustainability of green buildings. (2) The sensitivity of developers and homebuyers to subsidies varied across scenarios, and the optimal subsidy level diminished marginally as building greenness and public awareness increased. (3) The optimal subsidy level for developers was intricately tied to the building greenness benchmark. A higher benchmark intensified the developer’s responsiveness to losses, at which point increasing subsidies were justified. Conversely, a reduction in subsidy might have been appropriate when the benchmark was set at a lower level.

The expeditious advancement of green buildings holds paramount importance for the high-quality development of the construction industry. Nevertheless, the pace of green building expansion in China has experienced a recent deceleration. Drawing insights from the practices of green building in China, the exploration of viable strategies and the determination of optimal government subsidies stand as imperative initiatives. These endeavors aim to propel the acceleration of green building proliferation and materialize high-quality development at the earliest juncture possible.

The model is grounded in China’s green building practices, which makes the conclusions drawn more specific. Furthermore, research results provide practical references for governments to formulate green building incentive policies.