Not all elderly are the same: fostering trust through mobile banking service experience
Bibliographic record
Abstract
Purpose This study seeks to examine the impact of mobile service experience on trust of elderly consumers in their financial institution and assess whether age (55–64 years vs 65+ years) exerts a moderating influence. Design/methodology/approach A self-administered questionnaire was completed online by 390 panelists (aged 55 years or more) who use their mobile devices to conduct banking activities. A multigroup analysis was conducted to assess the moderating role of age. Findings Results confirm the presence of links between four out of five dimensions of the mobile banking service experience (cognitive, positive affective/sensory, negative affective and social) and trust. Findings further point to age-specific variation in the impact of mobile service experience dimensions on trust, thus supporting the notion that the elderly represents a clientele with different experiential needs. More specifically, whereas the social dimension has a greater influence on trust in individuals 65 years of age and over (seniors), the positive affective/sensory dimension exerts a deeper marked impact on trust in individuals 55–64 years of age (pre-retirees). Research limitations/implications Although generations and chronological age are powerful segmentation variables, it might be interesting to consider perceived age. Redoing the study in a post-COVID context would also be an interesting avenue of research. Practical implications The ageing market is important for banks. This study highlights, in an m-banking context, which dimension of experience to focus on in order to improve trust in banks for pre-retirees (emotional/sensory dimension) and seniors (social dimension). Originality/value This study is the first to consider mobile service experience of elderly individuals as well as the impact of each of the experience dimensions on an important relational variable, namely trust. By considering the age of individuals as a moderating variable, this study also provides an in-depth examination of age-related links and presents a number of relevant recommendations for financial institutions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".