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The groundwork of intellectual capital (IC) management, measuring IC, attracts much attention from academics and practitioners. The purpose of this paper is to design a measurement model and a qualitative index system of IC, so as to provide a good tool for enterprises to manage their IC. Based on a review of several IC measurement models proposed by western researchers, IC is classified into human capital, structural capital, innovation capital and customer capital, and thereupon a qualitative index system for the above four IC elements is designed through an analysis of their contents. Through an empirical study, it is found that there is a significant relationship between the scores of the four IC elements of a company and its business performance, which proves the validity and rationality of the IC measurement model and the qualitative index system. In the meantime, the empirical study further proves that there is a remarkable relationship between the four IC elements. Therefore enterprises must manage and improve their IC from an integrative perspective.

This paper examines the different features of China's economic development in different stages of economic globalization. The study finds that the investment- and export-based growth model drove China's high-speed economic growth between 2000 and 2007, which came into existence around 2000 when China plugged into the global production network.

This paper also finds that China slowed down to the New Normal because of the disruption to the socio-economic underpinnings of this growth model. As China adapts to and steers the New Normal, supply-side structural reforms can channel excess capacity to the construction of underground pipe networks in rural areas of central China and fix capital while advance rural revitalization.

At the same time, enterprises must strive to build a key component development platform for key component innovation and the standard-setting power in global manufacturing.

The establishment of a domestic production network integrating the integrated innovation-driven core enterprises and modular producers at different levels can satisfy the dynamic demand structure of China in which standardized demands and personalized demands coexist.

Applying the internationalization process model (IPM) and the strategic fit perspective, this research aims to test the effects of firm age on Chinese firms’ outward foreign direct investment (OFDI) in developing and developed countries.

Using data on some Chinese firms, this study applied the zero-inflated negative binomial model and Heckman two-stage model to do the analyses.

This research found that firm age has different effects on Chinese firms’ OFDI in developed and developing countries. State ownership and industry munificence independently and jointly can moderate these effects.

This study contributes to the IPM and solves the theoretical conflict about the firm age–OFDI relationship.

Motivated by empirical features that characterize cryptocurrency volatility data, the authors develop a forecasting strategy that can account for both model uncertainty and heteroskedasticity of unknown form. The theoretical investigation establishes the asymptotic optimality of the proposed heteroskedastic model averaging heterogeneous autoregressive (H-MAHAR) estimator under mild conditions. The authors additionally examine the convergence rate of the estimated weights of the proposed H-MAHAR estimator. This analysis sheds new light on the asymptotic properties of the least squares model averaging estimator under alternative complicated data generating processes (DGPs). To examine the performance of the H-MAHAR estimator, the authors conduct an out-of-sample forecasting application involving 22 different cryptocurrency assets. The results emphasize the importance of accounting for both model uncertainty and heteroskedasticity in practice.

The growth of the Chinese economy has resulted in a significant increase in construction and demolition waste (CDW), and regional differences in CDW generation are gradually increasing. The purpose of this study is to investigate the regional differences in CDW generation and the driving factors that influence CDW generation in different areas of China. To provide a systematic advisement for local governments to select the appropriate policy, reduce CDW generation.

The generation of CDW was calculated by region, based on the area estimation method, from 2005 to 2018. The relationship between CDW generation and economic development, and the driving factors of CDW generation in different regions of China, was investigated using the environmental Kuznets curve (EKC) model and the STIRPAT theoretical model.

CDW generation of China increased at the average annual growth rate of 10.86% from 2005 to 2018. The main areas of CDW generation were concentrated in the eastern and central regions, while the proportion of CDW generation in the northeast region decreased gradually, and the changes varied significantly across different regions. The EKC between CDW generation and economic development was established for the whole country, North China, Northeast China, East China, Central South China, Southwest China and Northwest China. Three main factors based on the STIRPAT theoretical model were identified and explained into a framework to reduce CDW generation. The results provided a useful theoretical basis and data support guide for devising effective policies and regulations for the Chinese context.

The findings from this study can ultimately support policymakers and waste managers in formulating effective policies for waste management strategies and CDW-specific legislation. Additionally, it can help the coordinated reduction of CDW generation across regions in China and can support construction enterprises (in their development strategies), similar developing economies and foreign firms planning to operate in China.

This study contributes to the field through the STIRPAT model on driving factors of CDW generation in the Chinese context, in different regions.

This paper aims to clarify the spatial connection characteristics and organization mode of logistics economy of 21 cities in Guangdong Province under the background of the integrated development of Guangdong, Hong Kong and Macao Bay area, and explore the spatial development characteristics and influencing factors of logistics economy in Guangdong Province.

This paper constructs the development level model of urban logistics economy in Guangdong Province from three aspects: demand level, supply level and support level, and uses the entropy weight method to measure the development level index of urban logistics economy in Guangdong Province. Then, the traffic accessibility index model is used to measure the traffic accessibility index between cities in Guangdong Province. Finally, using the social network analysis method, combined with the development level index of urban logistics economy in Guangdong Province and the urban traffic access index in Guangdong Province, this paper analyzes the spatial connection characteristics and influencing factors of logistics economy network in Guangdong Province.

There are regional differences in the development level of logistics economy in Guangdong Province; The overall network density of its logistics economic connection is large, but there is an imbalance in the network structure, and the core edge phenomenon is obvious; Logistics economic space presents the characteristics of double core development.

Because the research object is the spatial connection characteristics of logistics economy in Guangdong Province, the research results may lack universality. Therefore, researchers are encouraged to put forward further tests.

By studying the spatial connection mode of logistics economy in 21 cities in Guangdong Province, China, this paper promotes the original methods and empirical contributions, and constructs the research framework of spatial relationship of logistics economy. This research framework is universal to a certain extent.

This paper is conducive to promoting the integrated development of logistics economy in Guangdong Province and improving the balance of regional development of logistics economy.

Firstly, this study provides a new perspective to understand the spatial relationship and spatial spillover of logistics economy from relational data rather than attribute data. Secondly, This study enriched and broadened the research topic of spatial correlation of logistics economy. Thirdly, this research aims to promote the original methods and empirical contributions. Specifically, this study establishes a comprehensive research framework on the spatial network structure of logistics economy.

This study aims to examine how virtual influencers (VIs) affect purchase intentions in tourism and hospitality e-commerce live streaming (THCLS) by focusing on the roles of VIs’ source credibility, trust in products, trust in VIs, emotional engagement, parasocial relationships and influencer–product congruence.

Survey data from 416 active viewers of VIs in THCLS were analysed using partial least squares structural equation modelling.

This study highlights the importance of the VIs’ source credibility, which positively affects trust in the product, trust in VIs and emotional engagement. However, source credibility does not have a positive impact on parasocial relationships. Trust in products positively influences trust in VIs. Emotional engagement and trust in VIs significantly influence parasocial relationships, which, positively affects purchase intentions. Influencer–product congruence strengthens the link between parasocial relationships and purchase intentions but does not moderate the relationship between trust in VIs and purchase intentions. No significant gender differences were observed, although minor discrepancies were noted in the effect of trust in products on trust in VIs. The importance–performance map analysis revealed that parasocial relationships are the most important factor influencing purchase intentions, while influencer–product congruence has the highest performance, trust in products is the least important and VIs’ source credibility has the lowest performance.

This study provides actionable insights for marketers leveraging VIs in the THCLS sector, emphasizing strategies to enhance VI credibility, foster parasocial relationships, ensure influencer–product congruence and adopt gender-neutral marketing approaches to effectively influence purchase intentions.

This study offers theoretical and practical insights into the role of VIs in THCLS, illuminating their impact on consumer behaviour and purchase intentions.