Search results

The author proposed a mobile learning model of pervasive animated games which allows college students to learn via games accessed through a smartphone. It can develop the process of field observation and self-reflection to enhance learning effectiveness, and the motivation, and attitude of students towards learning.

The author proposed a model for teaching via pervasive animated games. The author used SPSS software and Pearson's correlation coefficients to explore different mobile learning strategies and their relationship with learning attitudes and achievement. Participants were vocational technology college students, who each experienced animated games in individual and group learning settings.

The results found that the learning performance of students in the individual learning group was better than that of the group learning group. A higher level of digital experience was associated with better learning performance, and a more positive attitude towards using mobile phones was associated with better learning performance.

The learning method still has its limitations, the learner's digital information level, learning mode, learning attitudes will have an impact on the student playing teaching pervasive animation games. Therefore, improving student information level is one of the important topics of teaching pervasive animation games and mobile learning.

The author proposed a mobile learning strategy based on pervasive animated games. The result in the strategy of mobile learning shows that the level of students' digital experience and the overall design of animated games are important criteria for successful implementation.

Since business competition has become more intense throughout the world, most enterprises are seeking to engage in business cooperation with other partners in order to enhance their competitive strengths. However, they do not necessarily develop mature information technologies’ (ITs) capabilities and skills internally but rather outsource them to IT providers. Therefore, the benefits received by firms which adopt the approach of business cooperation with IT providers have become an interesting issue for managers and shareholders.

This study adopted an event study methodology for apprising the short-term business value from the stock market. The authors predicted that investors will react as they receive news coverage about the strategy of business cooperation between outsourcing firms and an IT provider, International Business Machines (IBM) Corporation. The authors then collected all news coverage regarding the firms which had announced business cooperation with IBM and observed different types of abnormal returns.

On analyzing 53 announcements of cooperation with IBM from 2008 to 2016, the authors found that the announcement of business cooperation had a significantly positive influence on companies' market value.

To the best of the authors’ knowledge, this is the first study to investigate the issue for market reaction to the announcement of business cooperation with IBM.

The purpose of this paper is to extend an integrated model of the antecedents that help explain and predict team performance in relation to empowering leadership behaviors. To this end, the authors examine the intervening roles of knowledge sharing and team cohesion in the relationship between empowering leadership and performance in teams.

Data were obtained from 261 team members from 79 management teams in a major international fast‐food chain restaurant operating in Taiwan. Confirmatory factor analysis and multiple regressions were used for data analysis.

It was found that two indirect effects supplemented the direct effect of empowering leadership on team performance, the mechanisms of knowledge sharing and team cohesion. In other words, knowledge sharing and team cohesion, respectively, mediated the relationship between empowering leadership and performance in management teams.

This study extended existing research to the links between team characteristics, team cohesion, and knowledge sharing. Particularly, it explored the effect of team cohesion and knowledge sharing on team performance. The authors further investigated the mediating effect of team cohesion and knowledge sharing on the relationship between empowering leadership and team performance.

This is one of the first studies in empowering leadership applying different intervention and its process of a management team to the study of knowledge sharing as a team process and team cohesion as an emergent state.

The demand to reduce carbon emissions has become an increasingly important social factor due to the unprecedented impacts of climate change. However, most existing publications have focused on minimizing emissions during the operational phase of buildings. At the same time, there is a lack of comprehensive research conducted on carbon emissions, specifically during the construction phase. The purpose of this paper is to identify, review and classify current practices related to carbon emissions management in construction operations to gain greater insight into how to reduce and mitigate emissions and achieve more sustainable solutions.

This study reviewed the published literature on carbon emissions from construction. A total of 198 bibliographic records were extracted from the Scopus collection database and analyzed using Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA). PRISMA is used as a basis for reporting possible trends, research methods and strategies used in published literatures. A total of 99 papers related to carbon emissions in the construction operations were further reviewed and analyzed. This review paper draws on existing research and identifies current carbon management patterns in construction projects.

Data indicated an upward trend in the number of publications in carbon emissions research during the last few years, particularly in 2015, 2017 and 2019. The most significant contributions to the domain were reported from China, Europe and the USA. This paper found that most studies conduct the Life Cycle Assessment (LCA) method to estimate carbon emissions. This paper found that the primary studies have focused on construction machinery and equipment emissions. The strategies such as establishing uniform standards for carbon emissions policies and regulations, equipment and logistic planning and low carbon design material will potentially impact carbon emissions reductions.

This paper provides information that will be beneficial for the construction industry to design and manage construction operations. It will also be of interest to those looking to reduce or manage construction emissions.

Although there is a diversity of current thinking related to the practical estimation and management of carbon emissions in construction projects, there is no consolidated set of keys of standardized carbon emissions management in practice. By assessing the existing paradigms of carbon assessment methods and tactics in the construction industry, this study contributed to the existing knowledge base by providing insights into current techniques in the construction sector for monitoring and mitigating emissions.

This paper aims to extract the comment targets in Chinese online shopping platform.

The authors first collect the comment texts, word segmentation, part-of-speech (POS) tagging and extracted feature words twice. Then they cluster the evaluation sentence and find the association rules between the evaluation words and the evaluation object. At the same time, they establish the association rule table. Finally, the authors can mine the evaluation object of comment sentence according to the evaluation word and the association rule table. At last, they obtain comment data from Taobao and demonstrate that the method proposed in this paper is effective by experiment.

The extracting comment target method the authors proposed in this paper is effective.

First, the study object of extracting implicit features is review clauses, and not considering the context information, which may affect the accuracy of the feature excavation to a certain degree. Second, when extracting feature words, the low-frequency feature words are not considered, but some low-frequency feature words also contain effective information.

Because of the mass online reviews data, reading every comment one by one is impossible. Therefore, it is important that research on handling product comments and present useful or interest comments for clients.

The extracting comment target method the authors proposed in this paper is effective.