Dining with dogs: investigating the impact of parenting styles on shared human-dog experiences
Bibliographic record
Abstract
Purpose This paper aims to investigate the impact of different dog-directed parenting styles on consumers’ experience of dining out with dogs. Specifically, it explores authoritative and authoritarian dog-directed parenting styles as predictors of consumers’ hedonic pleasure and intentions to dine out with their dogs. In addition, this work tests the effects of providing a menu with items specific to dogs on increasing intentions to dine out. Design/methodology/approach Two studies consisting of a quantitative survey (n = 630) and an experimental study (n = 200) targeting dog-owners explore the effect of dog-directed parenting styles on intentions to dine out with dogs. Findings Authoritative dog-directed parenting styles predict expectations of hedonic pleasure and intentions to dine out with dogs. Both authoritative intrinsic and authoritative training dog-directed parenting styles positively predict dining out intentions. Conversely, an authoritarian corrective dog-directed parenting style does not lead to greater hedonic pleasure or intentions to dine out with dogs. Furthermore, this research finds that providing specific menu items for dogs can increase consumer intentions to dine, word-of-mouth and increase overall spending. Originality/value This work contributes to the growing research involving pets in hospitality experiences and provides managerial insights to promote dog-friendly dining. It contributes to the work on dog-directed parenting styles and extends it to a shared consumption context where the human-dog relationship is not the focus. From a managerial perspective, this research helps to better understand how to include pets in consumption experiences and which consumers are most responsive to such initiatives.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".