Wu and Lederer 2009: A Meta-Analysis of the Role of Environment-Based Voluntariness in Information Technology Acceptance
Jiming Wu and Albert L. Lederer 2010. A Meta-Analysis of the Role of Environment-Based Voluntariness in Information Technology Acceptance. MIS Quarterly (33:2), June 2009, pp. 419-432.
I read this article as an exemplar of a systematic literature review (specifically, a meta-analysis) in IS research.
- Rationale: The technology acceptance model (TAM) has been much researched and refined, based on its basic propositions that ease of use -> perceived usefulness, ease of use -> behavioural intention, perceived usefulness -> behavioural intention, and behavioural intention -> usage. However, one theoretically relevant moderating factor that has been overlooked is whether the usage context was voluntary or not; while much studied, this consideration has not been factored into TAM studies.
- Objectives: Ascertain whether voluntariness of the usage context moderates the TAM variable relationships.
- Theoretical background: This meta-analysis applies the theory on the effect of voluntariness on IT adoption to the theory base of TAM.
- Key questions: "Environment-based voluntariness will moderate the correlation between H1: perceived usefulness and behavioral intention; H2: perceived ease of use and behavioral intention; H3: perceived usefulness and usage; H4: perceived ease of use and usage" and "H5: Environment-based voluntariness will not moderate the correlation between perceived ease of use and perceived usefulness."
- Methodology: This study employs meta-analysis, using weighted least squares regression to test the hypotheses, where each study was weighted based on its sample size. Five models were tested, one for each hypothesis.
- Variables and data sources, if any: The independent variable for all five models was a four-item measure of voluntariness based on Moore and Benbasat (1991). The authors went through each study and coded this variable based on the descriptions, since the studies included generally did not explicitly measure voluntariness. The dependent variables were the correlations reported in each study between the two concepts in each of the respective hypotheses (for example, for model 1, the IV was voluntariness, and the DV was the correlation between perceived usefulness and behavioral intention, as in H1). A total of 71 studies were used, though H1 and H2 had 52 studies, H3 and H4 had 21 studies, and H5 had 65 studies.
- Key findings: H1 and H2 were validated: voluntariness was found to moderate the relationships between perceived usefulness and behavioral intention, and between perceived ease of use and behavioral intention, respectively. H3 and H4 were not supported (perhaps due to the small sample of 21 studies), indicating that perhaps voluntariness does not moderate the relationship with actual usage. As predicted in H5, there was no moderation detected for the relationship between perceived ease of use and perceived usefulness.
- Key contribution to knowledge and implications: Voluntariness does indeed moderate the relationships between perceived usefulness and behavioral intention, and between perceived ease of use and behavioral intention. This moderating effect must be taken into account in future TAM studies.
- Key implications: Implications are presented only for researchers: in TAM studies with nonvoluntary technologies, the effects of perceived ease of use and perceived usefulness are likely to be muted because of the context. This must be taken into consideration when conducting and evaluating such studies. However, this study only tested environment-based voluntariness; it did not test users' perceptions of voluntariness; these effects might or might not be different.
- Comments: This is a rigorously executed, clear meta-analysis. However, it goes beyond regular meta-analysis in that the authors theorized the influence of a variable which normally was not studied, and then coded this variable into their studies. (They did not include studies with insufficient description to support this particular coding.) Thus, they could "read between the lines" to not merely aggregate results—which they did not even bother to do in this study—but rather identify (with theory) and demonstrate (with meta-analysis) the effect of a hidden variable.
Moore, G.C. and Benbasat, I. "Development of an Instrument to Measure the Perceptions of Adopting an Information Technolgy Innovation," Information Systems Research, 2, 3 (September 1991), 192-222.