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The purpose of this paper is to develop a suitable framework of sustainable urbanization performance evaluation from the view of efficiency for mitigating the unbalance between the theoretical research of sustainable urbanization and the practical need of sustainable urbanization.

A slack-restricted slack-based measure data envelopment analysis (DEA) model and two sustainable urbanization benchmarking methods with individual and centralized view, respectively, are developed based upon the classical DEA theory.

The empirical results show that China is now suffering a relatively low level of sustainable urbanization. Too much waste water emission, too small an urban population proportion, and too much resource wastage are the major factors that drive China’s urbanization away from sustainability.

Having the overall aim of practical urbanization, the proposed framework can help stakeholders recognize different sustainable urbanization performance levels by offering them accurate sustainable urbanization performance scores. The framework can also direct governments to improve the sustainable urbanization performance. The empirical analysis of China’s provincial region sustainable urbanization performance with the proposed framework further demonstrates the theoretical and practical value of this research.

Selection of standardized modular containers (SSMC) is counted as one of the most important driving factors that ensure the Physical Internet (PI) to realize the varieties of goals of sustainability simultaneously, thus overcoming the great challenge of modern logistics in nowadays global supply chain. However, previous research studies on SSMC seldom paid attention to freight behavior and shippers’ segment, which are described in several fundamental conceptual works as the most essential factors that should be taken into account when doing SSMC.

This paper defines two preference matrices to characterize the freight behavior and shippers’ segment, and then integrates these two matrices into a centralized multi-criteria method to determine the optimal SSMC.

The SSMC derived by the proposed methodology is found to be Pareto-optimal. A managerial implication for shippers to further improve efficiency is summarized as well.

First, the authors characterized the freight behavior and shippers’ segment by two preference matrices and then integrated them into a centralized multi-criteria method. To the best of the authors’ knowledge, this is the first SSMC-related paper that takes shippers' behaviors and preferences into consideration when making the selection. The authors’ attempt is expected to fill in the research gap that has existed until now. Second, the SSMC derived by the proposed methodology is found to be Pareto-optimal, ensuring the required sustainability. Finally, the authors summarized a managerial implication for shippers to further improve the efficiency from the aspects of production and design.

The purpose of this paper is to generate quantitative managerial insights for the improvement of the energy-saving potential and the coordinated development between economic growth and environmental protection.

A novel data envelopment analysis (DEA) model, based on the classical DEA theory, is developed from the perspective of emission reduction.

The empirical results indicate that China’s overall environmental efficiency is low and that there is huge improvement space for energy saving. Under the concerns of emission reduction, the energy-saving potential of the central region exceeds that of both the eastern and western regions. With regard to water, electricity and gas consumption, the electricity-saving potential exceeds the potential for both water saving and gas saving.

Previous studies rarely focused on the energy-saving potential, while considering environmental pollution. This paper applies a novel DEA method to evaluate the energy-saving potential of 30 Chinese provinces for 2015 with a focus on emission reduction concerns. Furthermore, both regional differences and energy type differences of the saving potential were analyzed.

The purpose of this paper is to analyze manufacturers' production decisions and governments' low-carbon policies in the context of influencer spillover effects.

This paper investigates the impact of the social influencer spillover effect on manufacturers' production decisions when they collaborate with intermediary platforms to sell products through marketplace or reseller modes. Game theory and static numerical comparison are used to analyze our models.

Firstly, under low-carbon policies, the spillover effect does not always benefit manufacturer profits and changes non-monotonically with an increasing spillover effect. Secondly, in cases where there are both a carbon emission constraint and a spillover effect present, if either the manufacturer or intermediary platform holds a strong position, then marketplace mode benefits manufacturer profits. Thirdly, regardless of business mode used when environmental damage coefficient is high for products; government should implement cap-and-trade regulation to optimize social welfare while reducing manufacturers’ carbon emissions.

This study offers theoretical and practical research support to assist manufacturers in optimizing production decisions for compliance with carbon emission limits, enhancing profits through the development of effective influencer marketing strategies, and providing strategies to mitigate carbon emissions and enhance social welfare while sustaining manufacturing activities.

This paper addresses the limitations of prior research by examining how the social influencer spillover effect influences manufacturers' business mode choices under government low-carbon policies and analyzing the social welfare of different carbon emission restrictions when such spillovers occur. Our findings provide valuable insights for manufacturers in selecting optimal marketing strategies and business modes and decision-makers in implementing effective regulations.

The purpose of this paper is to present the landscape of the cash-per-publication reward policy in China and reveal its trend since the late 1990s.

This study is based on the analysis of 168 university documents regarding the cash-per-publication reward policy at 100 Chinese universities.

Chinese universities offer cash rewards from USD30 to USD165,000 for papers published in journals indexed by Web of Science, and the average reward amount has been increasing for the past ten years.

The cash-per-publication reward policy in China has never been systematically studied and investigated before except for in some case studies. This is the first paper that reveals the landscape of the cash-per-publication reward policy in China.

This paper seeks to examine the way quality management practices (QMPs) impact quality outcome, R&D process, and business performance, using investigation data from Chinese firms. The possible moderating effects of industrial types and competition on the above influencing relationships were investigated as well.

A two‐round questionnaire survey was conducted to 196 manufacturing and service firms in West China, and hypotheses were verified using a structural equation model with LISREL software.

The results suggest that quality management practices do not have a positive impact on firms' business performance directly, but have an indirect impact on business performance mediated by quality performance and R&D performance. Furthermore, the authors find that industrial type can moderate the relationships between quality management practices and business performance, while competition does not.

The findings make a significant contribution to understanding how QMPs impact firms' performance. In addition, the authors' research provides empirical evidence for the fact that QMPs' contribution to firms' financial and marketing performance is greater in service firms, which partly reflects the actual situation in China and other similar developing countries.

This research aims at explaining the phenomenon of the “black children” (heihaizi), a very little-known generation who lived with concealment under the one-child policy in China. The one-child policy was officially introduced to nationwide at the end of 1979 by permitting per couple to have one child only, later modified to a second child allowed if the first was a girl in rural China in 1984. It was officially replaced by a nation-wide two-child policy and most existing research focused on the parents’ sufferings and policy changes. The term “black children” has been mainly used to describe their absence from their family hukou registration and education. However, this research aims at expanding the meaning of being “black” to explain the children who were concealed more than at the level of family formal registration, but also physical freedom and emotional bond. What we do not yet know are the details of their lived experiences from a day-to-day base: where did they live? How were they raised up? Who were involved? Who benefited from it and who did not? In this way, this research challenges the existing scholarship on the one-child policy and repositions the “black children” as primary victims, and reveals the family as a key figure in co-producing their diminished status with the support of state power. It is very important to understand these children’s loss of citizenship and human freedom from the inside of the family because they were concealed in so many ways away from public view and interventions. This research focuses on illustrating how their lack of access to continued, stabilized, and reciprocally recognized family interactions framed their very idea of self-worth and identity.

Sometimes regarded as the best method of prioritizing budgetary expenditures, Zero-Based Budgeting (ZBB) was introduced into China in the early 1990s and systematically adopted since the recent budgeting reform although it has experienced numerous failures in many countries. This study examines ZBB as practiced in Hubei province in China. In Hubei, although the reformers are intended to create ZBB as a general budgeting framework, eventually, it was a Chinese style Target-Based Budgeting (TBB) rather than ZBB that has been put into place. Interestingly, ZBB has not disappeared but is deliberately applied to budgetary decisions of one type of expenditures under the Chinese style TBB. However, even in the field where ZBB is practiced, its achievements are at best moderate. The Chinese experiment of ZBB presents something new not only for the theory of ZBB but also for the budgeting literature.

This paper aims to design a deep neural network for object instance segmentation and six-dimensional (6D) pose estimation in cluttered scenes and apply the proposed method in real-world robotic autonomous grasping of household objects.

A novel deep learning method is proposed for instance segmentation and 6D pose estimation in cluttered scenes. An iterative pose refinement network is integrated with the main network to obtain more robust final pose estimation results for robotic applications. To train the network, a technique is presented to generate abundant annotated synthetic data consisting of RGB-D images and object masks in a fast manner without any hand-labeling. For robotic grasping, the offline grasp planning based on eigengrasp planner is performed and combined with the online object pose estimation.

The experiments on the standard pose benchmarking data sets showed that the method achieves better pose estimation and time efficiency performance than state-of-art methods with depth-based ICP refinement. The proposed method is also evaluated on a seven DOFs Kinova Jaco robot with an Intel Realsense RGB-D camera, the grasping results illustrated that the method is accurate and robust enough for real-world robotic applications.

A novel 6D pose estimation network based on the instance segmentation framework is proposed and a neural work-based iterative pose refinement module is integrated into the method. The proposed method exhibits satisfactory pose estimation and time efficiency for the robotic grasping.

The purpose of this paper is to draw on triadic reciprocal determinism and social exchange theory to examine how “induced-type” and “compulsory-type” union participation influence union commitment and job involvement, and how union participation in the west differs from that in China. It also examines whether the role of both organizational justice and employee participation climate (EPC) functions in the Chinese context.

Cross-sectional data are collected from 694 employees in 46 non-publicly owned enterprises, both Chinese and foreign, in the Pearl River Delta region of China. A multi-level moderated mediation test is used to examine the model of this research.

Union participation is positively related to organizational justice, union commitment and job involvement. In addition, organizational justice acts as the mediator among union participation, union commitment and job involvement. Specifically, the mediating role of organizational justice between union participation and union commitment, and between union participation and job involvement, is stronger in high-EPC contexts than low-EPC contexts.

Instead of examining the impacts of attitudes on union participation, as per most studies in the western context, this research examines the impacts of union participation in the Chinese context on attitudes, including union commitment and job involvement. It also reveals the role of both organizational justice and EPC in the process through which union participation influences union commitment and job involvement.