One App for Everything: A Multidisciplinary Review of Super Apps
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
Super apps have become a defining feature of digital ecosystems and an integral part of everyday life for millions of users, yet scholarship on the topic remains fragmented across disciplines and regions. This paper provides a multidisciplinary, PRISMA-guided systematic review of 177 publications and maps the field through a structured bibliographic analysis and a qualitative synthesis of a subset of 126 papers from the social sciences and legal studies. Our results reveal significant imbalances in the literature: a pronounced focus on Asian markets and few super app case studies (i.e. WeChat, KakaoTalk, LINE), as well as uneven coverage across service domains. We outline the key factors shaping user adoption and continued use, and summarize how prevailing platform strategies, often built around closed ecosystems, raise questions about competition, data governance, and systemic resilience. Beyond commercial platforms, municipalities and agencies are beginning to assemble ‘local super apps’ that unify public-service access, signaling a parallel public sector trajectory. Our results serve as an accessible entry point to the super app literature and set out clear lines for future research, calling for stronger interdisciplinary designs, comparative work beyond Asia, better conceptualizations of super apps, and more robust evaluations of societal, regulatory, and welfare impacts.
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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 | 0.016 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.009 | 0.007 |
| Research integrity | 0.001 | 0.012 |
| 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