New home warranty schemes: developing a theoretical comparative framework using qualitative content analysis
Bibliographic record
Abstract
Purpose The housing construction industry is one of the most lucrative sectors for developed countries. However, homebuyers are often vulnerable when left with latent building defects in their new-build house. Many nations have thus implemented new home warranty schemes to protect consumers and stimulate residential production. These warranty programs vary excessively from state to state given the distinct nature of environments. Previous studies have attempted to compare one with another but did not apply a consistent comparative method when doing so. Therefore, the purpose of this study is to identify the characteristics defining a new home warranty and to develop a standardised comparative framework. Design/methodology/approach After evaluating the characteristics outlined in multiple home warranty programs, a qualitative content analysis method was used to establish coding, categories and themes in order to create the framework. The methodology relied mostly on cross-referencing from academic papers, methodical reviews, government documents and professional consultant reports. Findings This paper reviewed warranty schemes from six countries: Canada, United Kingdom, Australia, Japan, France and Malaysia. The findings suggest that home warranty programs are defined by five main themes: political involvement; homeowner protection; financial sustainability; quality management; and dispute resolution. At the end, the research created a comparative framework of 101 codes that could be used to accurately measure the efficiency of a home warranty scheme. Originality/value Gathering all defining characteristics of new housing warranties into a unique comparative framework rectifies a gap in the literature. Such a flexible tool will aid future practitioners in the field to undertake comparative case study analysis through qualitative research methods.
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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 | 0.100 | 0.068 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.021 | 0.018 |
| Science and technology studies | 0.010 | 0.025 |
| Scholarly communication | 0.014 | 0.019 |
| Open science | 0.005 | 0.013 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".