Image de Google Jackets
Vue normale Vue MARC vue ISBD

Analyzing Work Departure Time Variability in Brussels

Par : Contributeur(s) : Type de matériel : TexteTexteLangue : français Détails de publication : 2004. Sujet(s) : Ressources en ligne : Abrégé : – This study explores the dynamics of departure time for the afternoon commute, which has received little attention both in theoretical and empirical work. Reported monthly and weekly departure time data, obtained from a survey of Brussels commuters, are used to study the impact of socio-economic, transportation and workrelated variables on the propensity of afternoon departure time changes. Binary and ordered probit models are used to estimate the impacts of these factors on two measures of departure time change propensity. The first one is the reported frequency of departure time changes in a month and the second measure is the time (in minutes) that a respondent left earlier or later than their normal time during the last five working days. In the first measure, the respondent selects his or her own threshold for reporting departure time change, whereas in the second measure the respondent merely provides the deviation from his or her normal departure time. The two measures together suggest three types of respondent groups: A group that perceives a wide-window (greater than or equal to 30 minutes) of regular departure times as normal, a group that perceives a narrow window of departure time as normal and change departure time occasionally and a third group that does not change their normal departure time. Statistical evidence indicates that work-related factors, particularly tolerant policy of the employer toward leaving work earlier, flextime and occupation type (scientific and executive professions) are associated with higher propensity of departure time changes. The implications of the findings are discussed.
Tags de cette bibliothèque : Pas de tags pour ce titre. Connectez-vous pour ajouter des tags.
Evaluations
    Classement moyen : 0.0 (0 votes)
Nous n'avons pas d'exemplaire de ce document

34

– This study explores the dynamics of departure time for the afternoon commute, which has received little attention both in theoretical and empirical work. Reported monthly and weekly departure time data, obtained from a survey of Brussels commuters, are used to study the impact of socio-economic, transportation and workrelated variables on the propensity of afternoon departure time changes. Binary and ordered probit models are used to estimate the impacts of these factors on two measures of departure time change propensity. The first one is the reported frequency of departure time changes in a month and the second measure is the time (in minutes) that a respondent left earlier or later than their normal time during the last five working days. In the first measure, the respondent selects his or her own threshold for reporting departure time change, whereas in the second measure the respondent merely provides the deviation from his or her normal departure time. The two measures together suggest three types of respondent groups: A group that perceives a wide-window (greater than or equal to 30 minutes) of regular departure times as normal, a group that perceives a narrow window of departure time as normal and change departure time occasionally and a third group that does not change their normal departure time. Statistical evidence indicates that work-related factors, particularly tolerant policy of the employer toward leaving work earlier, flextime and occupation type (scientific and executive professions) are associated with higher propensity of departure time changes. The implications of the findings are discussed.

PLUDOC

PLUDOC est la plateforme unique et centralisée de gestion des bibliothèques physiques et numériques de Guinée administré par le CEDUST. Elle est la plus grande base de données de ressources documentaires pour les Étudiants, Enseignants chercheurs et Chercheurs de Guinée.

Adresse

627 919 101/664 919 101

25 boulevard du commerce
Kaloum, Conakry, Guinée

Réseaux sociaux

Powered by Netsen Group @ 2025