Fun as the Principle Experience: A Systematic Review of Gamification in Marketing
Bibliographic record
Abstract
Gamification is a novel concept that seemingly comes out of nowhere and is gaining popularity. Therefore, many industries have quickly adopted this innovation for its ability to motivate customers and the ability to achieve high, genuine engagement. Although the application does not limit to any specific industry, the marketing industry has become one of the major beneficiaries of this concept. Through the application of gamification the brand can communicate and interact with the customer more effectively. Due to its novel nature, studies in this concept are scattered with many only focuses on a subset in marketing with examples such as retail marketing, product marketing and service marketing. Because there has not been a comprehensive review on this topic, this paper sought to review the literature on gamification in marketing and to provide a comprehensive review to guide gamification application in the marketing industry from a holistic perspective. An evidence-based systematic literature review method was employed in this study. A total of 27 studies published in peer-reviewed journals since 2010 are selected through the PRISMA framework from the Ryerson database. Some of the key findings in this study confirmed gamification does have a positive effect on marketing, and it is more effective in a digital environment than a physical retail environment especially in developed countries. Furthermore, point and badge systems were found to be ineffective in motivating customers nor enhancing loyalty. This study concluded by proposing a framework that would benefit industry practitioners by guiding them into designing a successful gamified experience multi-dimensionally. However, the breadth of this study may be limited due to the utilization of a convenient database to retrieve the literature needed for this systematic literature review. Furthermore, many of the findings in this study are situational specific therefore the generalizability may be affected. Moreover, this study provides a review for both academia and industry with a comprehensive depiction of the application of gamification in marketing, how it can stimulate consumer engagement, and provide guidance for brands to develop a successful gamified service. While this study comprehensively reviews the academic literature on gamification in marketing from a holistic perspective, it also highlights the key contribution of scholarly peer-reviewed studies to the knowledge base of gamification and translates the knowledge to the marketing industry.
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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 | 0.015 | 0.058 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.006 |
| Bibliometrics | 0.014 | 0.011 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| 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".