Highlights
Abstract
Keywords
1. Introduction
2. Theoretical background
3. Research methods
4. Results
5. Discussion
6. Conclusion
Appendix A. Prior studies included in this review
Appendix B. Measurement instruments for Habit
References
Abstract
Habit has been modeled in different ways in information systems (IS) research. It is theorized to directly impact system use (SU), moderate the impact of behavioral intention (BI) on SU, indirectly impact SU through BI and other variables, mediate the effects of other variables on BI and SU, and moderate the effects of other variables on BI. Prior studies empirically examined models of habit in various settings such as different types of respondents and geographic regions. Unsurprisingly, empirical findings on the relationships involving habit have been inconsistent and mixed. This study proposes that the variations in empirical results may be due to the various models of habit and the study characteristics. An exploratory meta-analysis and review of habit and its relationships is conducted by synthesizing findings across 130 samples reported in 114 published studies. Implications for research and practice are discussed.
1. Introduction
Habit has gained prominence in information systems (IS) research and practice over the last decade. As IS engender considerable investments and become more prevalent within organizations and societies, the adoption, use, and continuance of IS by individuals continue to garner attention among researchers and practitioners. Although traditional explanations of individuals’ IS adoption, use, or continuance are largely based on rational calculations (e.g., ease of use) and affective emotions (e.g., satisfaction), there is greater recognition of the role of habit in the IS domain (Ashraf, Tek, Anwar, Lapa, & Venkatesh, 2021)
Habit is of considerable importance to practice since it implies and underlies individuals’ repeated engagements with IS (Limayem, Hirt, & Cheung, 2007). It relies on the automaticity of responses of individuals to environmental cues in using IS rather than rational or affective responses (Kim et al., 2005, Limayem et al., 2007, Ortiz de Guinea and Markus, 2009, Venkatesh et al., 2012). Habit is applicable in both voluntary use contexts such as online shopping, social media, and instant messaging (Lankton et al., 2020, Pahnila and Warsta, 2010, Sun et al., 2017) and mandatory use contexts such as learning management systems (Ain et al., 2016, Kumar and Bervell, 2019). Habit can maximize IS use by individuals and enable organizations to realize returns on their IS investments.
Consistent with the notion of automatic response, habit was initially portrayed as an antecedent to explain the system use (SU) behaviors of individuals, and also a moderating influence on the relationship between behavioral intention (BI) and SU (e.g., Limayem & Hirt, 2003; Limayem et al., 2007). Over time, habit has been modeled in different ways including as a direct effect on BI (Liao, Palvia, & Lin, 2006), an indirect effect on SU through BI (Baptista & Oliveira, 2015) or other variables (Wilson, Mao, & Lankton, 2010), and as a mediator of other effects on SU (Khang, Han, & Ki, 2014) or BI (Chiu, Hsu, Lai, & Chang, 2012).