Second-hand luxury goods feature both characteristics of luxury products like perceived value including social, emotional, and quality value, and second-hand goods like price-performance ratio. Enlarging the second-hand luxury market is of significance to protect the environment and save rare and valuable natural resources, and thus investigating the determinants of purchase intention is meaningful. From the perspective of the psychology of consumers, the influence of factors related to consumers (recycling awareness, subjective norms, attitudes, perceived behavioral control) and products (perceived value, price-performance ratio) on the intention to buy second-hand luxury goods is explored in this study through an online survey with Chinese consumers as a sample. The results are analyzed using the structural equation model (SEM) and show that consumers’ attitudes, perceived behavioral control, and recycling awareness will promote the intention of purchasing second-hand luxury goods, and the perceived value and price-performance ratio of second-hand luxury goods also have a positive impact on the purchase intention. However, there is no significant relationship between subjective norms and purchase intention. In addition, this study also explores the interrelationship between constructs and draws corresponding conclusions, providing references for the subsequent development of the second-hand luxury market.

This research aims to identify the key indicators of land-use change that affect ecosystem service in the coastal city of Xiamen. The methods of transfer matrix and land-use dynamic degree are used to analyze land-use change, and the spatial distribution of ecosystem service values (ESV) is mapped from 1989 to 2018 using cluster analysis. During this 30-year period, the built-up land expanded rapidly through occupation of farmland and landfilling of the watershed. The biggest contribution to the reduction of ESV in this stage is the loss of farmland followed by the loss of watershed. By 2018, the spatial distribution of ESV had become very unbalanced and polarized. The high-value areas are mainly distributed in the northern mountainous areas, with the low-value areas concentrated in the flat areas near the coastline, and only a few medium-value areas of ESV remained. Generally, from 1989 to 2018, the ESV in Xiamen decreased by about CNY 200 million in total, with the largest proportion of ESV reduction (CNY 120 million) occurring in the 2000–2010 period. Considering ESV categories, the significant reduction of Regulating Service (53.5–57.8%) was mainly due to the loss of water areas (CNY −70 million) to low ESV areas (built-up land) in urbanization, followed by the loss of farmland (CNY −50 million). This means that Xiamen should strengthen the protection of ecological lands in future urban planning to alleviate and reverse the current ecological imbalance.

BIM is a key technology for the digital transformation and sustainable development of the construction industry through enhanced productivity, transparency, and fostered innovation. Although scholars have investigated the constructs driving BIM adoption intention, a comprehensive framework has seldom been adopted, and thus some vital factors have been overlooked, such as collaboration partner pressure. Meanwhile, the targeted group is usually practitioners of a certain type of company while a construction project requires the participation of multiple types of companies. To address these research gaps, the aim of this study is to explore the factors driving various stakeholders’ intention to adopt BIM by applying the TOE framework, considering nine factors across three dimensions. A total of 512 valid responses from owners, consulting firms, design firms, construction companies, suppliers, engineering surveying firms, and universities or research institutes were collected and analyzed through the structural equation modeling (SEM) method. The SEM results indicated that six factors were positively related to the intention to employ BIM, among which management commitment (β = 0.182, p < 0.001) and perceived ease of use (β = 0.180, p < 0.001) exhibited the strongest effects. However, three factors (perceived usefulness, supporting technical facilities, and mimetic pressure) exerted no significant influence. The findings of this study may provide a valuable reference for promoting the application of BIM technology in the construction industry.

Effective tunnel construction and demolition (C&D) waste management is a critical issue in the context of sustainable development, and C&D waste management measures guided by 3R principles (Reduce, Reuse, and Recycle) comply with the circular economy. In this study, an extended theory of planned behavior model based on the existing literature was proposed to identify the drivers of tunnel construction managers’ intention to implement effective waste management measures; then, the respondents were classified into four groups according to personality traits to explore the effects of personality profile on the heterogeneity in relationships between psychological drivers and C&D waste management intention and behaviors. The results show that all TPB constructs, policies, and environmental concern are significant predictors of managers’ intention to manage C&D waste properly. Then, considerable variance in the driving effects of various psychological drivers across different groups is witnessed. For the positive and temperate participants, subjective norms and policies are the most effective driving factors. However, PBC and environmental concern show a stronger relationship with the conservative and introverted participants’ intentions to adopt effective waste management measures. The findings are beneficial to developing corresponding management measures to promote effective C&D waste management.

The electricity-saving behavior of construction workers is helpful in reducing construction costs, protecting the ecological environment, and preventing global climate change. However, there is insufficient research on the electricity-saving behavioral mechanisms of tunnel-construction workers, and their behavior is influenced by their surrounding people including supervisors and co-workers because they are nested in various construction sites and isolated from other acquaintances. This study aims to develop a hierarchical linear model that explores the interrelationships between tunnel-construction workers’ electricity-saving behavior and four influencing factors theoretically and empirically. An organizational-level factor, electricity-saving climate, and three individual-level factors, including attitude, perceived behavioral control, and moral norms, are considered, and 1567 tunnel-construction workers from 41 construction sites mainly located in the southwest of China participated in this study. A six-step procedure for statistical analyses is adopted to test eight hypotheses using questionnaire survey data. The results supported all the hypotheses within the multi-level model and showed that the organizational-level factor played a leading role in predicting workers’ electricity-saving intentions with three individual-level factors positively associated with workers’ electricity-saving intentions. Further, the organizational electricity-saving climate also indirectly affects workers’ electricity-saving intentions through three mediators (individual-level factors), and electricity-saving intention is positively associated with electricity-saving behavior. Consequently, cultivating an electricity-saving climate within an organization is of great benefit to electricity conservation and environmental protection, and several recommendations are provided to improve the practical operability of results. The findings enable a better understanding of electricity-saving behavioral mechanisms and promote a low-carbon lifestyle among tunnel-construction workers.

Few studies focus on exploring the relationship between psychological factors and drivers’ violation intention in the tunnel sections which feature several adverse characteristics like poor lighting and a monotonous driving environment. In this study, hierarchical multiple regression is adopted to test the predictive effect of the demographic parameters, standard theory of planned behavior (TPB) constructs, and three additional constructs of moral norms, past behavior, and perceived stress to account for intentions to violate traffic rules while driving through road tunnels. In this study, three typical violations while driving inside tunnels including changing the lane, overtaking, and speeding are selected. A sample of drivers (N = 384; 50.3% are men and 49.7% women) were surveyed through a self-report questionnaire. Hierarchical multiple regression analyses show that age appears to be the only significant predictor of violation intention among demographic parameters, and theory of planned behavior (TPB) components account for the majority of the variance in violation intention. In addition, moral norms show a negative significant relationship with violation intention while perceived stress is positively associated with violation intention. The findings could provide an important reference for the development of corresponding interventions.