PERFORMANCE MEASUREMENT AND BENCHMARKING IN FACILITIES MANAGEMENT: A SURVEY OF NORTH AMERICAN UNIVERSITIES
Notice bibliographique
Résumé
Traditionally facilities management (FM) performance has not been analyzed extensively by FM professionals, especially in educational institutions. Performance management mostly focused on quantitative financial and operational measures. However, given the increased emphasis on customer orientation and optimum utilization of scarce resources it has become necessary to have a balanced view of FM performance.\n\nThis study attempted to examine the performance indicators for FM operation in universities from Balanced Scorecard perspective. It collected data on the key performance indicators tracked by FM in North American (Canada and United States) universities. It also sought organizational issues that hindered benchmarking to other organizations.\n\nA survey was administered via four modes—mail, fax, e-mail and the internet (on-line completion) to FM directors in 200 North American universities seeking information on perceived importance of various performance indicators, and their measurement and usage. A response rate of eighteen percent was attained.\n\nThe results indicated that although benchmarking and performance management is slowly gaining acceptance in universities there was an imbalance in the use of key performance indicators by FM professionals. Most of the indicators perceived important, measured, and/or used, were lag measures. Use of financial and operational indicators was also predominant. The study revealed that the association between measurement of performance indicators and their perceived importance was not always positive as\nanticipated. With respect to financial and customer perspectives there was a statistically significant negative correlation whereas for the other two perspectives the relationship was positive. The study also found no significant relationship between strategic\ndevelopment of FM departments and their drive towards CQI initiative. Relationship between strategy, and measurement and use of performance indicators were also unsubstantiated.\n\nThe results also indicated that the influence of the respondent universities' background on their FM performance could not be properly explained. In future studies, case analysis may be performed to examine the effect of this variable on FM performance. Furthermore, BSC assertion that strategy-driven organizations would have performance indicators in place to track the progress towards the goal—needs to be revisited as well.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,004 | 0,008 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,002 | 0,003 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».