Chian-Hsueng Chao

Intelligent Classroom with Motion Sensor and 3D Vision for Virtual Reality e-Learning

e-learning is getting more and more popular. In certain situation classes need to show 3D stereographs to illustrate subjects, such as geographic or mathematics. Our study is to help teachers to create the 3D stereographs they need in an easy and intuitive way. “3T in 3D” is a 3D motion sensor teaching system. A motion sensor and with 3D technologies, 3D objects can be manipulated by teachers and students. In this way, students can easily to understand the complex 3D objects. This is a preliminary study on the applications of motion sensor with 3D technologies in e-learning. It is hope that the data gathered in this study will help to develop a more complete 3D e-learning system.

Reconceptualizing the Mechanism of Internet Human Flesh Search: A Review of the Literature

The development of Internet technologies and popularity of social network enable the netizens to search, process, broadcast, and share information in a more efficient and collaborative way. Opinions of netizens in the cyberspace have emerged and become one of the major public opinions in the real world. One of the phenomenon rising recently over the Internet that most represent the influence between the virtual and real world is human flesh search (HFS). Usually, the HFS object is incompatible with social justice or violation of the mainstream moral characters, or events. This ¡§violation of moral¡¨ triggers the HFS process either in the cyberspace or in the real world. HFS has arose numerous controversies, especially the dilemmas between privacy violation and public opinion. Literatures and studies of HSF are mainly from China. International journals or periodical literatures target on this issue are very few. In addition, current studies are mainly qualitative studies lacking of quantitative and theoretical model building and empirical research. Therefore, it is necessary to acquire better understanding of HSF structure and evolving process. The purpose of this paper is to provide a broad discussion and summarized attributes of HFS. Based on reviews of more than twenty journal papers and articles regarding HFS, this study hopes to formulate a reference framework for future HFS studies.

The Framework of Information Processing Network for Supply Chain Innovation in Big Data Era

The challenges of the global marketplace and the growing complexity of business philosophies and technologies mix, the enterprises are forced to utilize knowledge, capabilities, and resources to be found within and outside their information processing networks. The enterprises are demanding more than just access to data, they want processed and refined big data and information to help them to reach more responsive and effective tactical decisions. Under this paradigm shift, data and information-oriented productivity depends on the sharing of knowledge and skills among workers, so that enterprise strategies can be driven by the collective intelligence and competence of the group to face business challenges and enable organizational learning and innovations. In the cloud computing and big data era, management of enterprise knowledge to create business values and competitive advantages is especially important for supply chain practices. This paper focuses on the development of enterprise information processing network and application framework that bind organizational strategies, business processes, data, information, technologies, and people together to better utilize knowledge in business practices. The ultimate goal is the transformation of an enterprise network into a knowledge network for supply chain organic innovations!

Analysis of Human Flesh Search in the Taiwanese Context

Human flesh search (HFS) is a recent internet phenomenon. Majority of the academic studies on HFS are in the Chinese context. Many HFS incidents have been reported locally but have been difficult to access by the international community. To resolve this issue and to supplement existing HFS reviews by Chen and Sharma [1], the current study provides a brief HFS analysis in the Taiwanese context with three additional research directions. Together with the reviews of Chen and Sharma [1], and of Chao [2], a comprehensive knowledge of HFS is obtained and can be a useful reference framework for future HFS research and policymaking.

How online tacit knowledge learning influences traditional classroom learning? A case study

Abstract In a traditional classroom scenario, students easily learn from the lectures on subject-related concepts or theories, but these do not include practical experiences that require hands-on practice, case studies or discussion. Explicit knowledge online learning has been widely applied and proven to be effective, but its counterpart, tacit knowledge has yet to be proven. Accordingly, this study intends to explore whether online learning for tacit knowledge can reinforce or substitute the effects of traditional classroom learning. Using Web design guidelines as an example for articulable tacit knowledge, the experiment result has shown that online learning effect was significant on substituting but not on reinforcing classroom learning. Meanwhile, with appropriate design and arrangement, online tacit knowledge learning can also significantly facilitate classroom learning. Nevertheless, the gap between perception and application levels could not be closed through online tacit knowledge learning that still requires years of accumulated practical experiences.

The Open Data and Voices of Social Communities: Case of Kaohsiung

With the advancement and rapid growth of Internet and online community, users can browse, post, reply to, and share messages/posts on social platform. Therefore, the cost of online civic engagement is relatively low. The level of civic engagement of Taiwanese on Internet is twice as in the real world. On the other hand, the net opinions are also a source of public opinion for the government that should pay attention to. In addition, the social network can better reflect the opinion of people which contains a lot more valuable information. In view of this, this study uses text mining technique to analyze the contents over the online community. The above data will be combined with government open data to find out the trend of the online community and the level of concerns toward government policies. In such a way the government management team will get close to public opinions. Wish to be able to provide the relevant units with results of valuable data analysis, so as to implement the development of smart city.

Visualizing the intellectual structure and evolution of innovation systems research: a bibliometric analysis

Commercial business simulation games (BSGs) have been well developed since 1956, and thus they have been extensively adopted and researched. Faria et al. (2009) published an insightful 40-year review of BSGs. However, the articles of the analysis was only from Simulation and Gaming Journal for answering why BSG was adopted and how it was used. This research used the Web of Science academic online research database and CiteSpace software for additional bibliometrics analyses to demonstrate visually intellectual structures and developments. The present study uses citation analysis to detect and visualize disciplinary distributions, keyword co-word networks and references co-citation networks, as well as highly cited references to demonstrate the use of a science mapping approach to perform the review. Such that the researchers may apply the procedure to the review of a scientific domain of their own interest. And secondly, to identify major areas of research activities concerning science mapping, intellectual milestones in the development of key specialties, evolutionary stages of major specialties involved, and the dynamics of transitions from one specialty to another in business simulation games research from 2002 to 2018.

Effects of Emotion and Trust on Online Social Network Adoption toward Individual Benefits: Moderating Impacts of Gender and Involvement

For the past decade, the advanced development of Online Social Network (OSN) has demonstrated a considerable contribution to the industries and society. The current research proposes and examines the research models that incorporate types of emotion and trust as the antecedents of OSN adoption to describe individual benefits (IB) for positive emotion (PE) and negative emotion (NE) groups. A salient consideration is to examine the moderating effects of gender and involvement on the relationships between independent and dependent variables for both groups. Based on the analysis of 522 valid samples, research results show that (1) for PE group, attentive and active show significant effects on OSN adoption, respectively. (2) for NE group, only ashamed presents a significant influence on OSN adoption. (3) moderators of PE group report that alert, attentive, and active are significant, indicating that female reveals significant effects while male reveals insignificant effects for both alert and attentive, and low involvement reveals significant effects for inspired and active while high involvement reveals significant effects for attentive and active. (4) moderators of NE group report that upset, ashamed, and afraid are significant, indicating that female reveals a significant effect for upset while male reveals a significant effect for ashamed, and high involvement shows significant effects for both ashamed and afraid. Discussion and implications are also addressed.

Theorizing the application of Transaction-Oriented Web usage Mining on typical e-commerce Web sites

Abstract The purpose of this research is to show the importance of theorizing the application of transaction-oriented Web usage mining methods in typical-structured e-commerce Web sites via a reference model. This paper presents findings from the analysis of a simulated case with embedded rules that are generated by three Web usage mining methods and triggered in three user-interactive scenarios. A two-phase simulation experiment was conducted to mine and collect the user data in the first phase and to test mining performance in the second phase. The design of the experiment was based on suggestions of previous critical reviews on virtual field experiment and guides for the applicability and use of Web experiments in information system research. The results showed that two out of the three Web usage mining methods deduced from the proposed reference model did increase significant transaction volumes via personalized recommendations. The paper is an original study and hopefully provides a valuable simulated case with insightful application of the reference model and corresponding data analyses.