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Institution

Hong Kong Polytechnic University

EducationHong Kong, China
About: Hong Kong Polytechnic University is a education organization based out in Hong Kong, China. It is known for research contribution in the topics: Tourism & Population. The organization has 29633 authors who have published 72136 publications receiving 1956312 citations. The organization is also known as: HKPU & PolyU.


Papers
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Journal ArticleDOI
TL;DR: In this article, the authors present a protocol that can be used to guide the allocation of work to four categories, namely: habitual action/non-reflection, understanding, reflection, and critical reflection.
Abstract: Where courses have as an aim the promotion of reflective practice, it will enhance the achievement of the goal if the level of reflective thinking is assessed. To do this in a satisfactory way requires a reliable protocol for assessing the level of reflection in written work. This article presents a protocol that can be used to guide the allocation of work to four categories, namely: habitual action/non‐reflection, understanding, reflection, and critical reflection. Intermediate categories can also be used. Detailed descriptors of each category to guide the process are provided. The protocol was tested by four assessors independently using it to grade a set of written work, and very good agreement was obtained.

329 citations

Journal ArticleDOI
01 Apr 2001-Energy
TL;DR: In this article, a model for estimating the intensities of the embodied and demolition energy for buildings has been developed and two typical high-rise residential buildings, the Housing Authority Harmony 1 and the New Cruciform blocks, are analyzed based on the developed model.

329 citations

Journal ArticleDOI
TL;DR: Aerosol samples for PM10 and PM2.5 were collected by high-volume (hi-vol.) samplers and the concentrations of major elements, ions, organic and elemental carbons were quantified.

328 citations

Journal ArticleDOI
TL;DR: The increasing prevalence of CRE strains in China is attributed to dissemination of conservative mobile elements carrying blaNDM or blaKPC-2 on conjugative and non-conjugative plasmids.

328 citations

Journal ArticleDOI
TL;DR: This paper compares the conditions under which covariance-based multigroup analysis is more appropriate as well as those under which there either is no difference or the component-based approach is preferable, and finds that when data are normally distributed, with a small sample size and correlated exogenous variables, the component's approach is more likely to detect differences between-group than is the covariance's approach.
Abstract: Multigroup or between-group analyses are common in the information systems literature. The ability to detect the presence or absence of between-group differences and accurately estimate the strength of moderating effects is important in studies that attempt to show contingent effects. In the past, IS scholars have used a variety of approaches to examine these effects, with the partial least squares (PLS) pooled significance test for multigroup becoming the most common (e.g., Ahuja and Thatcher 2005; Enns et al. 2003; Zhu et al. 2006). In other areas of social sciences (Epitropaki and Martin 2005) and management (Mayer and Gavin 2005; Song et al. 2005) research, however, there is greater emphasis on the use of covariance-based structural equation modeling multigroup analysis. This paper compares these two methods through Monte Carlo simulation. Our findings demonstrate the conditions under which covariance-based multigroup analysis is more appropriate as well as those under which there either is no difference or the component-based approach is preferable. In particular, we find that when data are normally distributed, with a small sample size and correlated exogenous variables, the component-based approach is more likely to detect differences between-group than is the covariance-based approach. Both approaches will consistently detect differences under conditions of normality with large sample sizes. With non-normally distributed data, neither technique could consistently detect differences across the groups in two of the paths, suggesting that both techniques struggle with the prediction of a highly skewed and kurtotic dependent variable. Both techniques detected the differences in the other paths consistently under conditions of non-normality, with the component-based approach preferable at moderate effect sizes, particularly for smaller samples.

327 citations


Authors

Showing all 30115 results

NameH-indexPapersCitations
Jing Wang1844046202769
Xiang Zhang1541733117576
Wei Zheng1511929120209
Rui Zhang1512625107917
Jian Yang1421818111166
Joseph Lau140104899305
Yu Huang136149289209
Dacheng Tao133136268263
Chuan He13058466438
Lei Zhang130231286950
Ming-Hsuan Yang12763575091
Chao Zhang127311984711
Yuri S. Kivshar126184579415
Bin Wang126222674364
Chi-Ming Che121130562800
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
20241
2023229
2022971
20216,743
20206,207
20195,288