An international examination of market orientation and performance in residential property management
Bibliographic record
Abstract
Purpose The paper offers clarity to the market orientation (MO) and performance relationship in real estate by examining the limited relevant literature, presenting international results and discussing the implications for market orientation researchers and real estate practitioners. Design/methodology/approach Based on a survey of 1,251 individual renters in the USA, the United Kingdom (UK) and Canada, this study examines the relationship between residential property managers’ MO and performance. It extends MO research in real estate by focusing on property management as opposed to property development. Findings The results show that MO and performance are correlated in all three countries. Commitments to understanding and serving customers and differentiating from competitors are shown to enhance performance measures including residential tenants’ loyalty toward the property manager, trust in the property manager, pride in rental accommodation and commitment to paying rent on time. Originality/value This study is one of the largest MO studies in real estate in terms of sample size and offers a unique international perspective. The research is novel as MO is evaluated by tenants as opposed to self-assessed by firms. The paper offers a new measure of property manager performance and provides strategic directives for real estate professionals seeking to enhance competitiveness.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".