Outputs (184)

Defining student learning experience through blended learning (2020)
Journal Article
Bouilheres, F., Viet Ha, L. T., McDonald, S., Nkhoma, C., & Jandug-Montera, L. (2020). Defining student learning experience through blended learning. Education and Information Technologies, 25, 3049–3069. https://doi.org/10.1007/s10639-020-10100-y

This paper aims to explore the benefits of Blended Learning towards students' learning experiences at an offshore campus of an Australian university located in Ho Chi Minh City, Vietnam. At the university campus, the Blended Learning practice in use... Read More about Defining student learning experience through blended learning.

Clustering, growth and inequality in China (2020)
Journal Article
Guo, D., Jiang, K., Xu, C., & Yang, X. (2020). Clustering, growth and inequality in China. Journal of Economic Geography, 20(5), 1207–1239. https://doi.org/10.1093/jeg/lbz038

This study examines the effects of China's industrial clusters on regional economic growth and urban-rural income inequality within a region. A density-based index (DBI) is developed to capture the unique features of cluster development in China. Fro... Read More about Clustering, growth and inequality in China.

Agile Identities: Fragile Humans? (2020)
Book Chapter
Coupland, C., & Spedale Latimer, S. (2020). Agile Identities: Fragile Humans?. In A. D. Brown (Ed.), Oxford Handbook of Identities in Organizations (833-847). Oxford University Press. https://doi.org/10.1093/oxfordhb/9780198827115.013.4

Recent growth in interest in identities is linked to societal changes, including an unprecedented degree of freedom in the industrialized West (Bauman, 1988; Ritzer, 1999; Sennett, 1998). Choice suggests autonomy but it also burdens us with responsib... Read More about Agile Identities: Fragile Humans?.

Exchange Rate Flexibility: How Should We Measure It? (2020)
Journal Article
Bleaney, M., & Tian, M. (2020). Exchange Rate Flexibility: How Should We Measure It?. Open Economies Review, 31(4), 881–900. https://doi.org/10.1007/s11079-019-09577-z

This paper first examines some recent exchange rate classification schemes. There is little evidence of a trend towards greater agreement between schemes. There is a probability of between 16 and 28 percent that a peg in one classification scheme is... Read More about Exchange Rate Flexibility: How Should We Measure It?.