Examining chatbot usage intention in a service encounter: Role of task complexity, communication style, and brand personality
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This study investigates the role of chatbot communication style (task vs. social oriented), task complexity (high vs. low), brand personality (sophisticated vs. sincere), and anthropomorphism on consumer trust and chatbot usage intention. Data is collected through three experiments conducted among US respondents ( N = 328, 200, and 336). The results offer mixed insights as only one experiment supports that task complexity moderates the effect of communication style on trust, such that, task-oriented communication style of the chatbot leads to higher trust under high task complexity conditions. No significant differences in the moderating effect of task complexity on the relationship between communication style and trust is observed between sincere and sophisticated brands. Consistent across the three studies, it is observed that perceived anthropomorphism mediates the effect of communication style on trust which, in turn, affects intention to use the chatbot. The study contributes to literature on AI-enabled conversational agents, human computer interaction , anthropomorphism, and trust. Practically, the study offers insights for managers and service providers who wish to integrate chatbots and other AI enabled technology to enhance service delivery by providing efficient, cost-effective, and consistent support.
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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 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it