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This study aims to construct an evaluation system for farmers’ livelihood capital in minority areas and evaluate the impact of relocation in response to climate change on farmers’ livelihood capital.

According to the characteristics of Yunnan minority areas, the livelihood capital of farmers in minority areas is divided into natural, physical, financial, social, human and cultural capital. The improved livelihood capital evaluation system measures farmers’ livelihood capital from 2015 to 2021. The net impact of relocation on farmers’ livelihood capital was separated using propensity score matching and the difference-in-difference (PSM-DID) method.

The shortage of livelihood capital makes it difficult for farmers to resist climate change, and the negative impacts of climate change further aggravate their livelihood vulnerability and reduce their livelihood capital. Relocation has dramatically increased the livelihood capital of farmers living in areas with poor natural conditions by 15.67% and has enhanced their ability to cope with climate change and realise sustainable livelihoods.

An improved livelihood capital evaluation system is constructed to realise the future localisation and development of livelihood capital research. The PSM-DID method was used to overcome endogeneity problems and sample selection bias of the policy evaluation methods. This study provides new ideas for academic research and policy formulation by integrating climate change, poverty governance and sustainable livelihoods.

Considering the substantial benefits derived from the use of Building Information Modeling (BIM) in construction projects, governments and its related sectors have introduced mandatory policies requiring the use of BIM. However, little is known about the impact of mandatory policies on BIM-based project performance. Therefore, the purpose of this paper is to provide a systematical understanding on the impact of policy interventions on the implementation practice of innovative technologies.

This paper utilizes the propensity score matching and difference in differences (PSM-DID) method to investigate the impact of policy interventions on BIM-based project performance. Using the panel data collected from 2015 to 2021 in the Hong Kong construction industry, this paper explores the impact of the first mandatory BIM policy on the BIM-based project performance of three key stakeholders.

The subjective BIM performance and BIM return on investment (ROI) have significantly improved after implementing the mandatory BIM policy. The promotion effect of mandatory BIM policy on BIM-based project performance gradually increases over time. Moreover, the promotion effect of mandatory BIM policy on BIM performance shows significant heterogeneity for different stakeholders and organizations of different sizes.

This study examined the impact of policy interventions on BIM-based project performance. The research findings can provide a holistic understanding of the potential implications of innovative mandatory policy in performance improvement and offer some constructive suggestions to policymakers and industry practitioners to promote the penetration of BIM in the construction industry.

Carbon reduction in the construction industry is related to the achievement of carbon emission peaks and carbon neutrality targets. Therefore, exploring the influence of current carbon reduction policies on the construction industry is necessary. China’s low-carbon pilot (LCP) policy has been extensively studied, while LCPs mechanism and effectiveness on carbon reduction in the construction industry remain to be explored.

This study selected four provincial LCP regions as case studies and adopted the grounded theory method for case studies to analyze the implementation mechanism of the LCP policy on carbon reduction in the construction industry. Then, this study adopted the propensity score matching and difference-in-differences regression (PSM-DID) approach to evaluate the influence of the LCP policy on carbon intensity (CI) in the construction industry by using panel data taken from 30 provinces in China between 2008 and 2017.

The authors found that (1) the LCP policy promotes carbon reduction in the construction industry through the crossing implementation mechanism of five vertical support approaches and five horizontal support approaches. (2). The LCP policy can significantly reduce CI in the construction industry.

The study not only explored how is the LCP policy implemented, but also examined the effectiveness of the LCP policy in the construction industry. The policy implications of this study can help policy-makers better achieve low-carbon development targets in the construction industry.

The role of energy or emission intensive firms face contradictory demands from advancing economic development and environmental improvement and protection and thus require appropriate policy interventions to balance the two needs. China's “Green Credit” policy that restricts loans to energy or emission intensive firms provides an example to study the impact of these kinds of policy intervention.

Using the data of all A-share listed companies in Shanghai and Shenzhen stock exchanges, our paper empirically analyzes the impact of the Green Credit Policy on performance of these energy or emission intensive firms.

(1) Using difference-in-difference (DID) and propensity score matching (PSM)-DID method and the dynamic effect method, we found that from 2012 to 2015, the Green Credit Policy had an inhibiting effect on the performance of energy or emission intensive firms. This inhibiting effect was gradually weakened in 2016, and it turned into a positive promoting effect in 2017; (2) The performance's change of these firms around 2015 showed that Green Credit promoted the green transformation and upgrading of these firms; (3) Loans were helpful to the performance of energy or emission intensive firms to some extent, but government subsidies were not significant.

The results suggest that the government, banks and other institutions should dynamically assess the implementation results of the Green Credit Policy on energy or emission intensive firms.

The Belt and Road Initiative (BRI) is the most comprehensive and substantial international cooperation platform, creating a new market influenced by economic and political factors. In this paper, the authors aim to examine whether and how the BRI impacts the Chinese enterprises' corporate environmental responsibility (CER).

Based on China's listed firms' database from 2011 to 2018, the authors use the PSM-DID method, an econometrics method combined with propensity score matching (PSM) and difference-in-differences (DID), to conduct causal inference between the BRI and Chinese enterprises' CER and conduct a series of robustness analyses. Moreover, the authors explore the mechanisms underlying the main effect from both market and non-market perspectives.

The results suggest that the BRI significantly increases Chinese enterprises' CER. Further analyses show that market competition and government support are two possible mechanisms through which the BRI has an effect on the enterprises' CER.

The research study supplements existing work on the environmental effects of the BRI at a microlevel and adds to the literature on the drivers of CER. The findings offer valuable insights into governments and scholars by demonstrating that CER is a crucial tool for Chinese enterprises to gain a competitive advantage in the increasingly competitive markets along the BRI.

Waiting time, as an important predictor of queue abandonment and patient satisfaction, is important for resource utilization and patient experience management. Medical institutions have given top priority to reforming the appointment system for many years; however, whether the increased information transparency brought about by the appointment scheduling mechanism could improve patient waiting time is not well understood. In this study, the authors examine the effects of information transparency in reducing patient waiting time from an uncertainty perspective.

Leveraging a quasi-natural experiment in a tertiary academic hospital, the authors analyze over one million observational patient visit records and design the propensity score matching plus the difference in difference (PSM-DID) model and hierarchical linear modeling (HLM) to address this issue.

The authors confirm that, on average, improved information transparency significantly reduces the waiting time for patients by approximately 6.43 min, a 4.90% reduction. The authors identify three types of uncertainties (resource, process and outcome uncertainty) in the patient visit process that affect patients' waiting time. Moreover, information transparency moderates the relationship between three sources of uncertainties and waiting time.

The authors’ work not only provides important theoretical explanations for the patient-level factors of in-clinic waiting time and the reasons for information technology (IT)-enabled appointment scheduling by time slot (ITASS) to shorten patient waiting time and improve patient experience but also provides potential solutions for further exploration of measures to reduce patient waiting time.

The aim of this study was to investigate the impact of low-carbon city pilots (LCCPs) policy using Chinese city-level data from 2009 to 2018 and examine the mechanisms of LCCP policy using a mediation effect model.

The authors measured carbon emissions by high-resolution carbon emission data and used difference-in-difference (DID) and propensity matching score-difference-in-difference (PSM-DID) model to investigate the relationship between LCCP policy and urban carbon intensity. The complex relationship between policy and carbon intensity was evaluated through a mediation model.

The results show that LCCP policy can reduce urban carbon intensity (−0.287), but its effects are different in different sectors. The impact of LCCP policy is greater in the industrial enterprise sector than in the transport sector than in the agricultural sector. Second, the authors find that LCCP policy under market-driven is more effective than government intervention. Third, there is a spillover effect of LCCP policy, which is decreasing with distance. Finally, the authors explore the mechanisms of LCCP policy from multiple perspectives, such as optimizing industrial structure, green areas, promoting public transport travel, population migration and innovation. In addition, the flow of these factors can also explain the spillover effects of LCCP policy.

This study confirms that LCCP policy is an effective tool for achieving urban sustainable development. Government policy-makers should consider the differences in the impacts of LCCP policy in different sectors and the spillover effects of LCCP policy. And, it shows that the effects of LCCP policy are larger by market-driven. These findings imply that the government should take full account of city characteristics and marketisation processes when formulating carbon reduction policies.

This study analyzed the relationship between LCCP policy and urban carbon intensity based on high-resolution carbon emission data. Urban panel data are used to discuss the impacts of LCCP policy under government intervention and market-driven and the mechanisms at play. The study reveals that LCCP policy mainly acts on the industrial enterprise sector, the spillover effects and the market-driven effects.

This article's purpose is to examine the effect of a Classification-Based Forest Management (CFM) program on farmers' income and determine whether its effect varies with the degree of farmers' concurrent occupations.

The authors use representative panel survey data from Longquan to explore the welfare effects of CFM on farmers. The analysis uses differences-in-differences with propensity score matching (PSM-DID) estimation techniques to deal with endogeneity problems when farmers make the decision to participate in CFM.

The results show that CFM has a positive effect on part-time forestry households (where forestry income accounts for between 5 and 50% of total income). In contrast, it has a negative impact on full-time forestry households (forestry income accounts for more than 50%), and no clear effect on nonforestry households whose forestry income is less than 5%. This research also shows that the positive effect of CFM on farmers' total income is mainly due to increase of off-farm income driven by CFM, while the negative effects consist of CFM's reduction of forestry income.

The extent of CFM's economic benefits to farmers is uncertain and largely unexplored. This paper analyzes the impact of CFM on income structure to explore the mechanisms explaining its effects on farmers' income. There are still challenges in ensuring the reliability and accuracy of CFM assessment. This paper collected natural experimental data and used the estimation technology of PSM-DID to solve the possible endogeneity problems.

This study examines whether the national innovative city pilot policy (NICP) influences urban entrepreneurship (UE). To examine the underlying causal mechanism, this study modeled the city-level intellectual capital index and financing capacity (FC) in the relationship between NICP and UE.

An empirical model of NICP, intellectual capital, FC and entrepreneurship is conceptualized based on theoretical analysis. Using a quasi-natural experiment of China’s NICP, with a sample of 280 prefecture-level cities in China from 2003 to 2018, propensity score matching with difference-in-differences (PSM-DID) is used to empirically test the NICP’s impact on UE, mediating effects of intellectual capital and moderation effects of FC.

The results show that the NICP can significantly motivate UE. Intellectual capital plays mediating effects on the relationship between NICP and UE. Moreover, the NICP and intellectual capital’s effects on UE are moderated by FC.

This study provides an important reference for promoting UE through intellectual capital and FC in the construction of the NICP.

This is a pioneering study that develops a theoretical model to incorporate NICP, intellectual capital, FC and UE. This paper applies experimental governance theory in innovative urban scenarios, and verifies its applicability and particularity in the Chinese context.

The purpose of this paper is to assess the effectiveness of the Silk Road Economic Belt (SREB) strategy and its role of industrial productivity in China.

To identify the causal effect of this strategy on industrial sustainable development, the authors first use the slacks-based measure model to calculate industries’ total-factor productivity (TFP) considered with CO₂ emissions as undesirable output on the provincial level. Then, the authors use the PSM-DID method to identify the difference of TFPs between provinces and industries before and after the implementation of SREB strategy.

However, the authors find that there is no difference or even a relative decrease in TFPs of industries in target provinces after the implementation of the strategy, which reveals that the SREB strategy does not play a positive role of the industries’ sustainable development in years of 2014 and 2015.

The value of this result is to identify the short-term impact of SREB strategy and to seek for probable causes and appropriate solutions.