Perceptions on IS Risks and Failure Types: A Comparison of Designers from the United States, Japan and Korea
Journal of Global Information Management(2003)
Abstract
Information systems (IS) designers from the United States, Japan, and Korea were surveyed to explore potential similarities and differences in their views on two IS risk factors, various types of IS failure and the overall failure rate on IS projects. While there were only a few differences between the U.S. and Japan, there were a number of differences in the views of designers from the U.S. and Korea. The results revealed that a lack of user involvement and a lack of experienced IS personnel were perceived as greater risk factors in Korea than in the U.S. and Japan. The data also revealed that unmet project goals and missed deadlines were perceived by designers from Korea as more likely to contribute to IS failure than did the designers from Japan and the U.S. Finally, the designers from Korea perceived a higher overall failure rate on IS projects than did the designers from the U.S. The findings were discussed in terms of the importance of national differences in technology development and national culture.
MoreTranslated text
上传PDF
View via Publisher
AI Read Science
AI Summary
AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
Example
Background
Key content
Introduction
Methods
Results
Related work
Fund
Key content
- Pretraining has recently greatly promoted the development of natural language processing (NLP)
- We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
- We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
- The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
- Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
Upload PDF to Generate Summary
Must-Reading Tree
Example

Generate MRT to find the research sequence of this paper
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper
Summary is being generated by the instructions you defined