Examining the effect of Knowledge Management factors on Mobile Learning adoption through the use of Importance-Performance Map Analysis (IPMA)

A tremendous amount of research indicated that KM factors have significant impacts on different technologies at the organizational level. What is not yet clear is the influence of these factors on technology adoption at the individual level. On the other hand, the understanding of students’ behavior...

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Bibliographic Details
Main Authors: Al-Emran, Mostafa, Mezhuyev, Vitaliy
Format: Conference or Workshop Item
Language:English
Published: Universiti Malaysia Pahang 2019
Subjects:
Online Access:http://umpir.ump.edu.my/id/eprint/26461/1/46.1%20Examining%20the%20effect%20of%20Knowledge%20Management%20factors.pdf
http://umpir.ump.edu.my/id/eprint/26461/
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Institution: Universiti Malaysia Pahang
Language: English
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Summary:A tremendous amount of research indicated that KM factors have significant impacts on different technologies at the organizational level. What is not yet clear is the influence of these factors on technology adoption at the individual level. On the other hand, the understanding of students’ behavioral intention to use m-learning systems is still an ongoing research issue. Thus, the main theoretical contribution of this study is to investigate the impact of KM factors (i.e., acquisition, sharing, application, and protection) on m-learning adoption at the individual level, and to identify the importance and performance of each factor using the importance-performance map analysis (IPMA) technique through SmartPLS. A total of 319 IT undergraduate students enrolled at Al Buraimi University College in Oman took part in the study by the medium of online survey. In terms of importance, the empirical data analysis through IPMA exhibited that knowledge protection is the most important factor in determining the students’ behavioral intention to use m-learning. Concerning performance, the findings also triggered out that both knowledge sharing and knowledge protection perform well in determining the students’ behavioral intention to use m-learning.