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Interorganizational collaboration has been a major source of exploratory innovation. Despite much research, the authors’ understanding about how partner cultural distance is harnessed for exploratory innovation is limited. The authors’ conceptual framework aims to address this gap by explaining the social-psychological processes between perceived partner cultural distance and exploratory innovation.

Drawing on research in organizational learning and culture mixing, the authors propose a multilevel model with two parallel processes – cultural brokering and cultural defense. If managers are engaged in the former and are protected from the latter, then the partnership will produce more exploratory innovation. Cultural brokering is encouraged by prompting a learning mindset, while cultural defense is preempted by dampening social categorization across organizational boundaries.

Cultural brokering can be encouraged by building operational-level managers' (OLMs') collaborative strength through developing a learning orientation, allowing them delivery for exploration, cultivating mutual trust with partners. Cultural defense can be preempted by protecting OLMs from intergroup anxieties through providing organizational support to the OLMs, bridging social categorization faultlines and setting shared collaborative goals. Whether an alliance can unleash its potential depends on not just how cultural brokering is enabled but also how cultural defense is curtailed.

This paper takes a microfoundational approach and considers micro-level processes in a partnership. Furthermore, the model takes the operational managers' perspective and defines culture at the organizational level. All these differences allow us to provide a nuanced picture of how diverse partnerships can be harnessed for exploratory innovation through a few easily-implementable measures.

Toyota's internationally coordinated production system in Asia and its selection of supply bases in South America and South Africa highlights the significance of recognizing global network firms and the global hub-and-spoke logistics system that has been developed to meet their needs. This system underpins the expansion of container shipping, air freight and telecommunications. Recognition of Main Street, linking Europe, Asia and North America with cui-desacs in Africa, Australasia and Central and South America, provides a framework for examining the relative importance of the system's hubs and terminals across different modes and regions. This analysis provides the basis for identifying and ranking key regional logistics platforms in Northeast Asia and their attraction as headquarter sites for global network firms. Examining the logistical situation pertaining after the end of the Cold War in the early 1990s and a decade later is used to gauge progress towards regional economic integration in Northeast Asia.

Today’s software engineers often work in teams to develop complex software systems. Therefore, successful software engineering in practice require team members to possess not only sound programming skills such as analysis, design, coding and testing but also soft skills such as communication, collaboration and self-management. However, existing examination-based assessments are often inadequate for quantifying students’ soft skill development. The purpose of this paper is to explore alternative ways for assessing software engineering students’ skills through a data-driven approach.

In this paper, the exploratory data analysis approach is adopted. Leveraging the proposed online agile project management tool – Human-centred Agile Software Engineering (HASE), a study was conducted involving 21 Scrum teams consisting of over 100 undergraduate software engineering students in multi-week coursework projects in 2014.

During this study, students performed close to 170,000 software engineering activities logged by HASE. By analysing the collected activity trajectory data set, the authors demonstrate the potential for this new research direction to enable software engineering educators to have a quantifiable way of understanding their students’ skill development, and take a proactive approach in helping them improve their programming and soft skills.

To the best of the authors’ knowledge, there has yet to be published previous studies using software engineering activity data to assess software engineers’ skills.

This study aims to investigate the efficiency changes of 23 major Asian container ports for the period from 2000 to 2007. In addition to assess the general trend, it also attempts to decompose the overall efficiency change into technological efficiency change, technical efficiency change and scale efficiency change to help port authorities to devise operational strategies.

The Malmquist index method is used, which is derived from data envelopment analysis. In this model, technological improvement comes from using state-of-the-art technologies, technical improvement is from rationalizing of port inputs and scale efficiency is from adjustment of port operational scales.

On average, the investigated ports have improved their efficiencies by 14.3 per cent. Such efficiency gains can be attributed to a 41 per cent increase in pure technical efficiency, a 47.5 per cent increase in scale efficiency and a 30.5 per cent decrease in technological efficiency. The scale efficiency contributes the most to the overall efficiency improvement, while technical and technological effects seem to have less impact. The fact that technological efficiency has little variance seems to suggest that this source of efficiency gain may not bring substantial competitive advantage.

The sample period is 2000-2007, so the impact from the Asian financial crisis or the economic downturn was not covered. Also, the port throughputs data do not separate shipment and transhipment.

This study provides valuable suggestions to improve efficiency for container ports along the “Maritime Silk Road.”

Motivated by the significant role of uncertainty in affecting investment decisions and China's economic leadership in Asia, this paper investigates the predictive role of exposure to Chinese economic policy uncertainty at the individual stock level in large Asian markets.

We estimate the monthly uncertainty exposure (beta) for each stock and then employ the portfolio-level sorting analysis to investigate the relationship between the China’s uncertainty exposure and the future returns of major Asian markets over multiple trading horizons. The raw returns of the high-minus-low portfolios are then adjusted using conventional asset pricing models to investigate whether the relationship is explained by common risk factors. Finally, we check the robustness of the portfolio-level results through firm-level Fama and MacBeth (1973) regressions.

Applying portfolio-level sorting analysis, we reveal that exposure to Chinese uncertainty is negatively related to the future returns of large stocks over multiple trading horizons in Japan, Hong Kong and India. We discover this is unexplained by common risk factors, including market, size, value, profitability, investment and momentum, and is robust to the specification of stock-level Fama and MacBeth (1973) regressions.

Our analysis demonstrates the spillover effects of Chinese economic policy uncertainty across the region, provides evidence of China's emerging economic leadership, and offers trading strategies for managing uncertainty risks.

The findings of the study significantly improve our understanding of stock return predictability in Asian markets. Unlike previous studies, our results challenge the leading role of the US by providing a new intra-regional return predictor, namely, China’s uncertainty exposure. These results also evidence the continuing integration of the Asian economy and financial markets. However, contrary findings for some Asian markets point toward certain market-specific features. Compared with market-level research, our analysis provides deeper insights into the performance of individual stocks and is of particular importance to investors and other market participants.

Global climate change speeds up ice melting and increases flooding incidents. China launched a sponge city policy as a holistic nature-based solution combined with urban planning and development to address flooding due to climate change. Using Weibo analytics, this paper aims to study public perceptions of sponge city.

This study collected 53,586 sponge city contents from Sina Weibo via Python. Various artificial intelligence tools, such as CX Data Science of Simply Sentiment, KH Coder and Tableau, were applied in the study.

76.8% of public opinion on sponge city were positive, confirming its positive contribution to flooding management and city branding. 17 out of 31 pilot sponge cities recorded the largest number of sponge cities related posts. Other cities with more Weibo posts suffered from rainwater and flooding hazards, such as Xi'an and Zhengzhou.

To the best of the authors’ knowledge, this study is the first to explore the public perception of sponge city in Sina Weibo.

The conducted examination of programming affordances and constraints had the purpose of adding knowledge and value that facilitate the on-going national curricula revision; knowledge that also could be of general interest outside the Swedish K-12 context.

With a qualitative approach, the study was conducted as a document analysis where submitted lesson plans were the base for a directed content analysis.

This study presents findings on how the involvement of programming in mathematics and technology have potential to foster engagement and motivation among students. Findings also indicate that the implementation of programming can develop important general skills that go beyond the boundaries of mathematics and technology. Moreover, the identified constraints could be valuable to improve the on-going curriculum development for K-12 mathematics and technology.

This qualitative study was conducted on a relatively small number of teachers where the majority has taken the courses on a voluntary basis. An important complement would be to conduct a larger quantitative study with data from a more general sample of K-12 teachers.

Results and discussions provide guidance for K-12 teachers and other stakeholders who want to introduce programming as a complementary tool in teaching and learning activities.

The study has a contribution to the on-going implementation of the Swedish national curricula for K-12 mathematics and technology.

During the last years, many studies have been published on teacher training in programming, and how the training can be improved. This study goes beyond the actual teacher training and examine aspects teachers translate to theirs daily work after completing the training.