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This paper explores a district government's role in using school networks to transform turnaround schools in rural Shanghai, China.

Qualitative case studies were conducted.

Findings showed that the C District government varied its power in initiating school networks; collaborative networks were developed but addressed local problems in a limited manner and collaborative networks had difficulties innovating to solve novel problems.

This article presents an “external-internal context” framework for understanding local government's role in school networks and turnaround school transformation in China.

This study aims to examine the effects of iPad distribution on all teachers in a university and its application in teaching and student learning at home via wireless network during the coronavirus (COVID-19) pandemic. The attitude towards the use of iPads, behavioural intentions and the impact on the quality of teaching were evaluated.

This study used the technology acceptance model to explore the use of iPad smart mobile devices in multimedia teaching applications by university teachers. Furthermore, it used the structural equation modelling (SEM) for data analysis to explore the causal relationship between model variables, and it aimed to examine the causal relationship between variables to verify the theory. The SEM analysis included the following two stages: measurement model analysis and structural model analysis.

The “Internet information environment” had a significant positive impact on “perceived usefulness” and “perceived ease of use”. Amongst them, perceived usefulness had a significant positive effect on the use attitude, and use attitude had a significant positive effect on behaviour intention.

The findings confirmed that a good information network environment will directly and positively affect the perceived usefulness and the ease of use of iPad smart devices, of which the perceived usefulness will further positively affect teachers' perception of iPad smart devices. The attitude and behaviour of using such devices will in turn positively affect the quality of teaching. The results of the quality performance evaluation can be referenced further by manufacturers and scholars regarding the use of iPad smart devices for work at home during the COVID-19 pandemic.

Recently, electric vehicles have been widely used in the cold chain logistics sector to reduce the effects of excessive energy consumption and to support environmental friendliness. Considering the limited battery capacity of electric vehicles, it is vital to optimize battery charging during the distribution process.

This study establishes an electric vehicle routing model for cold chain logistics with charging stations, which will integrate multiple distribution centers to achieve sustainable logistics. The suggested optimization model aimed at minimizing the overall cost of cold chain logistics, which incorporates fixed, damage, refrigeration, penalty, queuing, energy and carbon emission costs. In addition, the proposed model takes into accounts factors such as time-varying speed, time-varying electricity price, energy consumption and queuing at the charging station. In the proposed model, a hybrid crow search algorithm (CSA), which combines opposition-based learning (OBL) and taboo search (TS), is developed for optimization purposes. To evaluate the model, algorithms and model experiments are conducted based on a real case in Chongqing, China.

The result of algorithm experiments illustrate that hybrid CSA is effective in terms of both solution quality and speed compared to genetic algorithm (GA) and particle swarm optimization (PSO). In addition, the model experiments highlight the benefits of joint distribution over individual distribution in reducing costs and carbon emissions.

The optimization model of cold chain logistics routes based on electric vehicles provides a reference for managers to develop distribution plans, which contributes to the development of sustainable logistics.

In prior studies, many scholars have conducted related research on the subject of cold chain logistics vehicle routing problems and electric vehicle routing problems separately, but few have merged the above two subjects. In response, this study innovatively designs an electric vehicle routing model for cold chain logistics with consideration of time-varying speeds, time-varying electricity prices, energy consumption and queues at charging stations to make it consistent with the real world.

This paper investigates the factors affecting individual dispositions toward intentions. Specifically, this study aims to investigate the effects of emotional intelligence, entrepreneurial motivation and creativity on the entrepreneurial intentions of university students in Jordan.

The data were gathered through self-administered questionnaires from a sample of 745 university students in Jordan. The hypotheses were tested using partial least squares (PLS) analysis.

The results indicate a robust relationship between entrepreneurial motivation and creativity and entrepreneurial intention. However, an insignificant relationship was found between emotional intelligence and entrepreneurial intention. The findings of this study reveal that both creativity and emotional intelligence exert a significant and positive indirect effect on entrepreneurial intentions through the mediation of entrepreneurial motivation.

This work suggests that university administrators should consider the significant roles that emotional intelligence, entrepreneurial motivation and creativity play in shaping the entrepreneurial intentions of university students.

While there is limited existing research on this matter within the Middle Eastern context, especially in Jordan, this study aims to address this gap in the Jordanian entrepreneurial literature. As the first of its kind conducted within Jordanian universities, this study contributes significantly to the understanding of entrepreneurial dynamics in the region. Using the Wong and Law Emotional Intelligence Scale, this study evaluates emotional intelligence in Jordan. The results contribute to social psychology literature and suggest actionable government measures, integrated into education systems, to encourage entrepreneurial paths for students and alleviate graduate unemployment.

The purpose of this study is to examine the impact of industry specialization of audit partners and audit committee members on the level of tax avoidance in Australian banks.

This study uses a multivariate regression analysis based on hand-collected data consisting of 180 observations from Australian domestic banks between 2010 and 2018.

The primary results of the empirical analysis indicate that audit partner industry specialization is negatively associated with the level of tax avoidance in Australian banks. Regarding the audit committee, the proportion of industry specialists among audit committee members reduces the magnitude of tax avoidance. These results are robust, as they hold the same for alternative measures of tax avoidance and industry specialization of audit partner and audit committee members. Results from supplementary analysis reveal that the interactive effect of both audit firm and audit partner industry specialization strengthens the auditors’ effectiveness in reducing the level of tax avoidance.

As this study highlights the importance of the industry specialization in decreasing tax avoidance, it can be beneficial for policymakers to assess the impact of good governance on the level of tax avoidance in the banking industry.

Even though the existing studies examine the link between the governance actors’ industry specialization and tax avoidance in nonfinancial firms, this paper explores the banking industry that differs from nonfinancial firms in among others; accounting and fiscal regulations. This study further provides unique evidence indicating that industry specialization of the audit partner constitutes a significant determinant of minimizing the bank’s level of tax avoidance.

The main purpose of this paper is to explore whether the nature of innovation is accumulative or radical and to what extent past year accumulation of technology stock can predict future innovation. More importantly, the authors are concerned with whether a change of policy regime or a variance in the quality of technology will moderate the nature of innovation.

The authors examined a dataset of 3.6 million Chinese patents during 1985–2015 and constructed more than 5 million citation pairs across 8 sections and 128 classes to track knowledge spillover across technology fields. The authors used this citation dataset to calculate the technology innovation network. The authors constructed a measure of upstream invention, interacting the pre-existing technology innovation network with historical patent growth in each technology field, and estimated measure's impact on future innovation since 2005. The authors also constructed three sets of metrics – technology dependence, centrality and scientific value – to identify innovation quality and a policy dummy to consider the impact of policy on innovation.

Innovation growth is built upon past year accumulation and technology spillover. Innovation grows faster for technologies that are more central and grows more slowly for more valuable technologies. A pro-innovation and pro-intellectual property right (IPR) policy plays a positive and significant role in driving technical progress. The authors also found that for technologies that have faster access to new information or larger power to control knowledge flow, the upstream and downstream innovation linkage is stronger. However, this linkage is weaker for technologies that are more novel or general. On most occasions, the nature of innovation was less responsive to policy shock.

This paper contributes to the debate on the nature of innovation by determining whether upstream innovation has strong predictive power on future innovation. The authors develop the assumption used in the technology spillover literature by considering a time-variant, directional and asymmetric matrix to model technology diffusion. For the first time, the authors answer how the nature of innovation will vary depending on the technology network configurations and policy environment. In addition to contributing to the academic debate, the authors' study has important implications for economic growth and industrial or innovation management policies.