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Enregistrement W321240126

Flextime and Telecommuting: Examining Individual Perceptions

2006· article· en· W321240126 sur OpenAlexaboutno aff
Thomas W. Gainey, Beth F. Clenney

Notice bibliographique

RevueSouthern business review · 2006
Typearticle
Langueen
DomaineSocial Sciences
ThématiqueWork-Family Balance Challenges
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésTelecommutingWorkforceWork (physics)BusinessQuarter (Canadian coin)Public relationsMarketingDemographic economicsOperations managementEconomicsEngineeringPolitical scienceGeographyEconomic growth
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

As individuals increasingly experience conflicts between their personal lives and the demands of the workplace, many employers offer alternative work arrangements that are designed to help workers achieve a better balance in their lives (Harris, 2003; Shamir & Salomon, 1985). Two such alternatives, flextime and telecommuting, have proven particularly instrumental in helping employees meet the many demands on their time, and these programs have grown dramatically over the past twenty years (Bailey & Kurlan, 2002; Thornthwait & Sheldon, 2004). Indeed, reports from the Bureau of Labor Statistics (BLS, 2005; 2006) show that the number of workers with flexible schedules increased from about 13.1 million in 1985 to around 38.0 million in 2004, representing an annual growth rate of just under 6 percent. Similarly, the number of telecommuters has grown at an annual rate of just over 5 percent, from about 17.3 million in 1986 to around 45.1 million in 2005 (Kraut, 1989; ITAC, 2005). And, while statistics show that the growth rate of both flextime and telecommuting has leveled off during the past five years, it is estimated that more than a quarter of the workforce is presently involved with one of these work options (BLS, 2005; ITAC, 2005).The advantages of both flextime and telecommuting have been widely reported in the popular press, perhaps leaving some managers to conclude that employees will be highly receptive to these alternative work programs and willingly participate when they are offered. However, given some basic differences between flextime and telecommuting, it is reasonable to assume that not all individuals will view these programs in a similar manner. Therefore, the purpose of this study was to examine individual perceptions of flextime and telecommuting. Further, this research explored the role that personality, demographics, and work experiences play in forming these perceptions.Flextime and TelecommutingWhile both flextime and telecommuting can be useful in helping employees balance the various demands on their time, there is a significant difference between these programs. Flextime involves building flexibility into an employee's work schedule. With flextime programs, employees are often required to be at work during certain core hours when all workers are typically needed to satisfy customer demand. However, employees are then granted some latitude in scheduling their remaining hours. These programs provide individuals with the ability and autonomy to schedule work around the demands of their personal life. In general, these programs have resulted in reduced turnover and absenteeism, higher employee morale and productivity, and improved worker well-being (Gale, 2001; Gill, 1998; Lucas & Heady, 2002).Alternatively, telecommuting programs permit flexibility by allowing employees to work from different locations. In a nutshell, telecommuting is the practice of using electronic communication technology to perform work from remote locations. Some employees telecommute on a full-time basis, while others may only spend one or two days a week outside of the traditional workplace. While some studies have identified potential problems with telecommuting (McCloskey & Igbaria, 2003; Tietze, 2005), overall results have been positive (Greer, Buttross, & Schmelzle, 2002; Kurland & Bailey, 1999) . For instance, as a result of their telecommuting program, Merrill Lynch reported over a 15 percent increase in productivity, 3.5 fewer sick days per year, and about a 6 percent decrease in turnover (Wells, 21).Sample and ResultsRespondent ProfileThe sample for this study was comprised of 242 management students at a southeastern university that has a relatively large number of nontraditional students. Four classes, each of which were taught by one of the authors, were surveyed. Participation was strictly voluntary.Two surveys were administered to the students. …

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,003
score de la tête « metaresearch » (Gemma)0,007
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,005
Score d'incertitude au seuil0,015

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0030,007
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0010,001
Études des sciences et des technologies0,0010,001
Communication savante0,0030,002
Science ouverte0,0010,002
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0040,001

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.

Tête enseignante Opus0,048
Tête enseignante GPT0,305
Écart entre enseignants0,258 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations25
Publié2006
Routes d'admission1
Résumé présentoui

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