An Application of Planned Behavior Theory for the Examination of Mobile Banking Adoption: Personality as a Moderator
Bibliographic record
Abstract
As banks begin to shift their focus to a more transaction based revenue model, it is important for them to be able to meet the diverse needs of their clients in securing their transactional patronage. Mobile banking is predicted to continue to grow and become more important for the banking industry. Although there is significant growth globally, Canada is considerably behind in the adoption of mobile banking. This study explores the adoption behavior of online banking in Canada by an extension of the theory of planned behavior. A model was adopted in an effort to increase the robustness of the theory of planned behavior model by addressing its rational bias. Additionally, an increased focus was placed on the determinants of attitude to increase the level of importance in developing intention. In doing so the mediating effect of attitude toward the adoption of mobile banking is observed between the three components of the theory of planned behavior and behavioral intention. Behavioral beliefs are represented by perceived usefulness and perceived risk, normative beliefs are represented by subjective norms, and control beliefs are represented by perceived ease of use and access barriers. The moderating effects of personality construct, openness to experience was also analyzed in an effort to discover significance of personality within the theory of planned behavior. In assessing the relationships among the preceding constructs, moderated hierarchical regression was employed. Prior to carrying out these analyses, confirmatory factor analysis was performed. The results indicate support for attitude toward the adoption of mobile banking as a mediator between behavioral intention and two of the three components of the theory of planned behavior, specifically behavioral beliefs and normative beliefs. Although openness to experience showed a positively direct effect on attitude toward the adoption of mobile banking, its moderating effects were not supported. Research implications for academia and business practices were discussed.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.019 | 0.045 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".