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Despite the considerable research into China's industrial relation system, little attention has been focused on what do Chinese unions at the enterprise level do and how their daily work influences employees' work-related outcomes. Drawing on the theory of planned behavior, this paper aims to examine the impact of Chinese enterprise union practices on employees' change-oriented organizational citizenship behavior through the mediating roles of psychological safety, perceived insider status, and role breadth self-efficacy.

Data were collected from 450 employees at 45 unionized enterprises in China through a three-wave survey. Multilevel analyses were conducted to test the hypothesized effects.

Chinese enterprise union practices positively predicted change-oriented organizational citizenship behavior. Critically, psychological safety and role breadth self-efficacy mediated the positive relationship between Chinese enterprise union practices and change-oriented organizational citizenship behavior.

This study provides new evidence on the effectiveness of Chinese enterprise union practices from a perspective of employees' work-related outcomes. It also enriches the existing literature on antecedents of change-oriented organizational citizenship behavior and provides a “planned” perspective to understand the mechanism that underlies the relationship between Chinese enterprise union practices and change-oriented organizational citizenship behavior.

The purpose of this study involves analysing the factors of and barriers to innovation and their respective impacts (directly and indirectly) on the competitiveness of both destination and their host companies.

Based on primary data collected by questionnaire from a sample of 119 companies operating in the tourism sector in the autonomous region of Madeira (Portugal), the authors applied a quantitative methodology with recourse to econometric models and multiple linear regression.

Comprehensive results based on a conceptual model are obtained through the analysis of competitiveness tourism-based and innovation factors. The study identifies and empirically tests the existing and underlying relationships between innovation (factors and barriers) as the means of leveraging the competitiveness of destinations and their companies.

The results hold important theoretical and practical implications contributing towards innovation for competitiveness and filling a shortcoming identified in the literature.

Point-of-interest (POI) recommendation techniques play a crucial role in mitigating information overload and delivering tailored services. To address limitations in conventional POI recommendation systems, constrained by sparse user-POI interactions and incomplete consideration of temporal dynamics, POI recommendation based on the spatial-temporal graph (STG-POI) is proposed.

Spatial-temporal sequence graphs from geographical locations and user interaction history data are constructed, which are used to mine spatial-temporal sequence information. Using the data filtered by the band-pass filter, graph neural networks with distance-awareness and sequence-awareness are applied to capture high-order spatial-temporal connections within diverse graph topologies. The model leverages contrastive learning for self-supervised disentanglement of graph representations, providing self-supervised signals for sequential and geographical intent perception, thereby achieving more precise POI personalization.

Compared to the baseline model GSTN, experiments on the Foursquare and Gowalla data sets reveal that STG-POI improves testing AUC by 2.0%, 2.1%, 2.0% and decreases logloss by 1.9%, 3.3%, 0.3%, respectively. These results indicate the model’s effectiveness in capturing spatial-temporal information, surpassing mainstream POI recommendation baseline models.

This approach constructs a dual graph from user interaction data, harnessing sequential and geographical information as self-supervised signals. It yields decoupled representations of these influences, offering a comprehensive insight into user behaviors and preferences within location-based social networks, thus enhancing recommendation accuracy and interpretability. This approach addresses the challenge in graph convolutional network where only rough and smooth features are conducive to recommendation by using band-pass filters to significantly reduce computational complexity, thereby enhancing recommendation speed by filtering out noise data that does not contribute to recommendation performance. Experimental results indicate that this model surpasses current mainstream approaches in POI recommendation tasks, effectively integrating both geographical and temporal features.

The construction industry has experienced an irreversible digital transformation to smart construction. Many countries have published supporting policies to encourage the development of smart construction. However, there is no universally valid approach. This paper thus aims to evaluate smart construction policies issued by 24 pilot cities in China and identify applicable policy tools and their impact.

This paper collected 33 governmental documents on smart construction through the official websites in China. Different policy tools were classified into supply-side, demand-side and environment-side categories. The supporting policies of smart construction development in pilot cities were quantitatively evaluated by using a policy modeling consistency index (PMC-index) model.

Supply-type and environment-type policy instruments were used more frequently than demand-type policies in 24 pilot cities. Most of the 24 pilot cities had an evaluation of PMC-index over 8, realizing the consistency of smart construction policies. Eight pilot cities had an evaluation of PMC-index of 6–7.99, realizing acceptable consistency. Only Foshan City has an evaluation of PMC-index below 4, which may reflect a poor consistency of policy implementation. The paper proposes consistencies of smart construction policies of 24 pilot cities and valid policy instruments, including the presale of commercial residential buildings, additional bonus points in the tendering process and cooperating with multiple departments when promoting smart construction.

This paper contributes to expanding policy evaluation studies in the smart construction field and provides concrete suggestions for policymakers to formulate more effective and specific policies and strategies for the development of smart construction.

This study aimed to identify barriers impeding circular economy (CE) uptake in the construction industry in literature, categorize them for the development of a framework and to seek the interrelationships among the categorized barriers. This allowed for identifying integrated solutions to holistically address the barriers. The study also sought to identify the “hot” themes, the knowledge gaps and future research directions on barriers impeding CE.

Forty-eight relevant articles were desk reviewed from different construction peer-reviewed journals and published conference papers. A scientometric analysis allowed for co-occurrence of keywords relating to CE. A content analysis enabled the identification of 79 barriers impeding the uptake of CE in the construction industry which were further categorized into six distinct categories for the development of a framework showing the interrelationships among the categorized barriers.

The identified barriers include construction sector inertia, lack of design standards, lack of knowledge, awareness and understanding, design cost, and perception of second-hand materials as substandard among others. The study categorized the identified barriers for better understanding into six different groups: cultural barriers, social barriers, environmental barriers, economic barriers, technical barriers and technological barriers. Strategies to address the barriers were also proposed. The interrelationships among the various barriers were also shown in a proposed framework to educate professionals on the interconnectivity of the barriers.

Categorization of the various barriers impeding CE uptake contributes to the body of knowledge. Also, the interrelationships among the various categorized barriers in the framework will enable construction professionals make informed decisions regarding the successful integration of CE in the industry, better appreciate the barriers that impede CE uptake and apply strategies to holistically address the barriers. This will expand current knowledge outside the narrow scope of isolated barriers.

To the global construction industry, the review presents a list of barriers and their interrelationships that could provide implementation strategies for the uptake of CE in the industry.

The geographical scope of this study is not limited, and therefore encourages wide applicability of the findings to the global construction industry.