Mapping the Scientific Research on Mass Customization Domain: A Critical Review and Bibliometric Analysis
Bibliographic record
Abstract
Researchers of the Mass Customization domain face not only challenges of proper and timeless identification of latest practical trends, but also difficulties in rational analyses on the numerous existing scientific studies in this field as well as a need for a comprehensive and multidimensional state-of-the-art overview of the Mass Customization research domain in the last three decades. Therefore, the present research article aims to provide a critical standpoint and reveal the main research directions and content at systemic, bibliometric and historical research levels in the period of 1990–2020. Four types of bibliometric clustering techniques and a visualization of results in a format of two-dimensional maps by the VOSviewer software were applied in the analysis on 1783 scientific papers from the Clarivate Analytics Web of Science Core Collection. The analysis reveals six historical periods in the Mass Customization research domain, from which, in the last three decades, three are identified as influencing modern Mass Customization research areas and objects. Results confirmed a shift from a stand-alone scientific approach to the customization of tangible products in the manufacturing field and their risk management, to a hybrid scientific approach with a focus on the customization of non-tangible products and personalized customer behavior in online environments.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | Bibliometrics Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Observational | high |
| gpt | Bibliometrics Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Other design | high |
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 | 0.016 | 0.054 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.070 | 0.063 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".