Exploring research trends of <i>procrastination</i>: a bibliometric analysis during 2010 to 2020
Bibliographic record
Abstract
Purpose The aim of this paper is to offer insight into procrastination over the past decade using bibliometric analysis to gauge the evolving journey of this concept. Thus, the concept of procrastination is examined in terms of authors, affiliating institutions, countries, citation patterns, bibliometric coupling and co-occurrence analysis. Design/methodology/approach For exploring the research work on procrastination, the bibliometric analysis was conducted for co-authorship, co-occurrence of keywords, citation network analysis, most influential authors, document and country wise bibliometric coupling by taking 630 publications between the years 2010–2020 into consideration. Software like VOSviewer and Tableau was used for result analysis. In addition, the content analysis was used for the top research papers amongst the eleven different clusters. Findings The study reveals the nature and direction of research over the past decade on procrastination. The most prominent journals, authors, articles, institutions, countries and keywords have been identified. The topic shows an upward trend of research as no consolidation or maturity in the pattern is observed. Frontiers In Psychology had the highest number of publications followed by Personality And Individual Differences. The top three contributors are Sirosis, F.M., Feng, T. and Ferrari, J.R. The country-wise analysis shows the USA leading followed by Germany, China and Canada. UiT The Arctic University of Norway was having the most significant contribution followed by The Ohio State University, DePaul University and Tel Hai Academic College. The most prominent themes and documents are reported. In addition, the content analysis depicted the need to conduct the research work on the certain themes which may usher the researchers towards more conceptual clarity and strategizing. Originality/value Sufficient discourse and relevant literature are available about procrastination, bedtime procrastination and academic procrastination and related areas. However, procrastination is becoming a universal issue, especially in the field of human resources and workforce development. This paper attempts to facilitate the policy-makers, regulators, researchers and practitioners to explore allied and less explored areas of procrastination that need future investigation.
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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 | 0.005 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.035 | 0.052 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| 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, 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".