Understanding information systems continuance: The case of Internet-based learning technologies

Moez Limayem; Christy M.K. Cheung

doi:10.1016/j.im.2008.02.005

Understanding information systems continuance: The case of Internet-based learning technologies

Moez Limayem^*, Christy M.K. Cheung

^*Corresponding author for this work

Research output: Contribution to journal › Journal article › peer-review

427 Citations (Scopus)

Abstract

Our research model expanded the Bhattacherjee's IS continuance model by adding a moderating effect (IS habit) to IS continuance intention and IS continued usage, postulating direct links between satisfaction and IS continued usage, as well as between prior behavior and IS continued usage. The model was tested with an Internet-based learning technology in a longitudinal setting. Data collected from 505 students were examined using partial least squares analysis. The results presented strong support for the theoretical links of IS continuance model, and for the new moderating effect. Both satisfaction and prior behavior were found to have significant impact on IS continuance. In addition, our findings confirmed the theoretical argument that the strength of intention to predict continuance was weakened by a high level of IS habit.

Original language	English
Pages (from-to)	227-232
Number of pages	6
Journal	Information and Management
Volume	45
Issue number	4
DOIs	https://doi.org/10.1016/j.im.2008.02.005
Publication status	Published - Jun 2008

User-Defined Keywords

e-Learning
Habit
Information systems continuance
Internet-based learning technology
Prior behavior
Satisfaction

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10.1016/j.im.2008.02.005

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title = "Understanding information systems continuance: The case of Internet-based learning technologies",

abstract = "Our research model expanded the Bhattacherjee's IS continuance model by adding a moderating effect (IS habit) to IS continuance intention and IS continued usage, postulating direct links between satisfaction and IS continued usage, as well as between prior behavior and IS continued usage. The model was tested with an Internet-based learning technology in a longitudinal setting. Data collected from 505 students were examined using partial least squares analysis. The results presented strong support for the theoretical links of IS continuance model, and for the new moderating effect. Both satisfaction and prior behavior were found to have significant impact on IS continuance. In addition, our findings confirmed the theoretical argument that the strength of intention to predict continuance was weakened by a high level of IS habit.",

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AU - Limayem, Moez

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N2 - Our research model expanded the Bhattacherjee's IS continuance model by adding a moderating effect (IS habit) to IS continuance intention and IS continued usage, postulating direct links between satisfaction and IS continued usage, as well as between prior behavior and IS continued usage. The model was tested with an Internet-based learning technology in a longitudinal setting. Data collected from 505 students were examined using partial least squares analysis. The results presented strong support for the theoretical links of IS continuance model, and for the new moderating effect. Both satisfaction and prior behavior were found to have significant impact on IS continuance. In addition, our findings confirmed the theoretical argument that the strength of intention to predict continuance was weakened by a high level of IS habit.

AB - Our research model expanded the Bhattacherjee's IS continuance model by adding a moderating effect (IS habit) to IS continuance intention and IS continued usage, postulating direct links between satisfaction and IS continued usage, as well as between prior behavior and IS continued usage. The model was tested with an Internet-based learning technology in a longitudinal setting. Data collected from 505 students were examined using partial least squares analysis. The results presented strong support for the theoretical links of IS continuance model, and for the new moderating effect. Both satisfaction and prior behavior were found to have significant impact on IS continuance. In addition, our findings confirmed the theoretical argument that the strength of intention to predict continuance was weakened by a high level of IS habit.

KW - e-Learning

KW - Habit

KW - Information systems continuance

KW - Internet-based learning technology

KW - Prior behavior

KW - Satisfaction

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DO - 10.1016/j.im.2008.02.005

M3 - Journal article

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VL - 45

SP - 227

EP - 232

JO - Information and Management

JF - Information and Management

IS - 4

ER -

Understanding information systems continuance: The case of Internet-based learning technologies

Abstract

User-Defined Keywords

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