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PurposeThe purpose of this study is for examining the evolution of stakeholder influence and the trans-period effect (TPE) of process performance of public–private partnerships (PPPs). TPE refers to the ripple effect of project performance across different phases of a PPP.Design/methodology/approachSocial network analysis is used to analyze each stakeholder’s influence on PPP performance. For examining the TPE, partial least squares structural equation modelling is conducted.FindingsThe performance in the five phases (e.g. initiation and planning, procurement, construction, operation and transition) of PPPs exhibits significant TPE. The stakeholder network varies in different phases. The most influential stakeholder is a public authority, followed by a public initiator and a private consortium.Research limitations/implicationsThe project type of PPPs is not considered in the stakeholder network analysis. Future work should focus on developing a multidimensional stakeholder network by considering the typology of the project. Moreover, the TPE cannot reflect the relationships between the KPIs in the different phases, and thus, further study is required.Practical implicationsThis research provides a useful tool for measuring the life cycle outputs and outcomes of PPPs through enhanced process-oriented performance measurement. The developed PMS enable practitioners to have a better understanding of the process performance of the projects and then ensure informed decision-making about actions to be required and taken to improve future performance.Originality/valueThis study contributes to knowledge of performance management by simultaneously addressing the process and stakeholder management theories within the context of PPPs. The proposed PMS provides an insight into managing stakeholders’ influences to enhance the life cycle performance of PPPs.

Sustainability development is a core issue and policy-priority in China to meet the long-term ecological civilization and economic growth. In this paper, the sustainability of the 31 Chinese provincial-level administrative regions (provinces for short) was investigated using a composite sustainability indicator (CSI). The CSI was constructed by aggregating thirty sustainability indicators involving economic, social, and environmental dimensions hierarchically. Moreover, a piecewise mean range normalization method was developed for weakening the impact of outlier(s). The results indicate that further improvement of the provinces’ sustainability is needed, since only three provinces (accounting for 9.68%) showed better performance and development momentum, simultaneously. However, over half of the provinces showed comparatively optimistic sustainability prospect, indicating a possibility of further sustainability improvement in China under a positive and effective guidance. In terms of the individual provinces, the decline of the sustainability of Liaoning and Tianjin was significant whereas Anhui, Hunan, and Hubei showed more optimistic development prospects. For the four regions, Middle China was on the rise, the decline of Northeastern China was serious, and East China and West China showed better development, but they should also keep vigilance on the possible decline because of the decline of competitive advantages.

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The existing LBL (lecture-based learning) and CBL (case-based learning) teaching modes of English majors in colleges and universities do not contribute to cultivating students’ inquisitive thinking and independent learning ability, whereas the problem-centered PBL (problem-based learning) teaching mode can precisely make up for these shortcomings. This study firstly constructed a PBL “four-step” teaching mode and then realized the innovative application of PBL teaching model in the teaching of English majors in new universities. Then, we designed a method of English classroom resource optimization based on IMOCS-BP neural network, and then, the classroom resource optimization reconstructs the teaching process with unique connotation essence. The experiments show that the BL “four-step” teaching model is designed to achieve the four key elements of “flexible English learning environment, transformed learning the culture, customized content and professional educators”; the designed neural network has optimized the English classroom resources.

Sustainability development is a core issue in autonomous regions’ construction and development. The paper evaluated the sustainability development of the five autonomous regions in Western China from 2010 to 2019. In order to further analyze the sustainable development level of the autonomous regions, it is compared with the three provinces with the largest GDP in Central China in the past three years, and similarly, with the three provinces in Eastern China. A new weighting method was proposed by combining the grey relational analysis (GRA) and set pair analysis (SPA) methods that not only analyze the correlation between indicators and ideal points but also analyze the status and development trend. The method can ensure the objectivity of indicator weight. Firstly, the ideal reference point is determined by the grey correlation degree between the indicator and the ideal positive point. Secondly, the indicator and the ideal reference point constitute a set pair system, and the relation number is used further to analyze the status and development trend of the indicator to determine the weight objectively. The sustainability results showed that the progress of the autonomous regions’ sustainable development in China was increased slowly in 2010–2019. For example, Ningxia and Xinjiang saw the slowest growth. The prime reason is that economic sustainability has declined severely. Although Inner Mongolia presented the highest increasing trends, the growth rate value was 0.75%. In contrast, other autonomous regions showed a negative growth trend. Regarding sustainable development in three dimensions, the economic sustainability performance of autonomous regions is not ideal, but the environmental sustainability performance is the most ideal. This conclusion implicates the necessity and urgency of improving the coordinated development of the three dimensions of autonomous regions in China.