Investigating male gamers' behavioral intention to play PUBG: Insights from playful-consumption experiences
Bibliographic record
Abstract
This research investigates the factors that affect male gamers' behavioral intention to play PlayerUnknown's Battlegrounds (PUBG), which is one of the most widely played online games of today's era. We examine the factors through the lens of the hedonic consumption model (i.e., playful-consumption experiences) and use the gratification theory to predict behavioral intention to play PUBG. Data from 248 male PUBG gamers were analyzed using PLS-SEM analyses. The study involved an initial stage where an estimation model (i.e., measurement model) was analyzed to assess the constructs' reliability and validity. Following this, the second stage involved assessing the theoretical model to test the relationship between the principle constructs. The study found that playful-consumption experience factors, such as escapism, emotional involvement, sensory experience, enjoyment, and arousal, significantly influenced the behavioral intentions to play PUBG. The research findings further indicate that role-projection and fantasy failed to impact consumers' intention to play PUBG. This study provides both theoretical and practical implications. It fills the literature gap by focusing on predicting the behavioral intention to play PUBG through the playful-consumption experiences of a popular online multiplayer game. Practically, this study could potentially open avenues for gaming companies to address how different playful-consumption experiences impact game users' behavioral intentions.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".