920 resultados para Travel Motivations


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Notre compréhension de la migration du retour est encore très limitée. Ce sujet n’a que peu retenu l’attention des spécialistes de la migration et il existe peu d’études qui donnent une vision différenciée sur les divers types de « retourné-e-s », leurs motivations à retourner dans leurs pays, les défis qu’ils/elles affrontent et les ressources dont ils/elles disposent pour parvenir à se réinsérer dans les pays d’origine. Il existe en particulier un manque important d’études qui examinent en détail la situation spécifique du retour des migrant-e-s sans-papiers et l’impact de l’aide de programmes gouvernementaux pour leur réinsertion socio-économique. Cette lacune est particulièrement marquée dans le cas de la Suisse. Confronté à la situation d’absence d’évaluations des programmes d’appui au retour des sans-papiers, et dans le but d’y apporter des améliorations possibles à son propre programme, le Service de la Population du canton de Vaud a chargé Yvonne Riaño de mener une recherche sur la situation de retour des sans-papiers retournés en Équateur entre 2008-2010 avec l’appui du programme. La recherche présentée ici se base sur un travail de terrain réalisé en Équateur en 2010. Nous avons rencontré 25 familles (70% du total des familles rentrées avec l’aide du Canton de Vaud) habitant dans diverses régions du pays et avons recueilli leurs expériences de retour. La méthodologie choisie pour la récolte des données est qualitative et combine entretiens narratifs et semi-directifs. La recherche examine les raisons d'émigration et du retour des personnes interviewées ainsi que la situation actuelle de leurs projets de réinsertion, leurs ressources disponibles et le défis auxquels elles font face pour la réalisation de leurs projets. Six principes clés sont proposés pour repenser l’aide au retour de façon à pouvoir garantir un retour viable.

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Recent research showed that past events are associated with the back and left side, whereas future events are associated with the front and right side of space. These spatial-temporal associations have an impact on our sensorimotor system: thinking about one's past and future leads to subtle body sways in the sagittal dimension of space (Miles, Nind, & Macrae, 2010). In this study we investigated whether mental time travel leads to sensorimotor correlates in the horizontal dimension of space. Participants were asked to mentally displace themselves into the past or future while measuring their spontaneous eye movements on a blank screen. Eye gaze was directed more rightward and upward when thinking about the future than when thinking about the past. Our results provide further insight into the spatial nature of temporal thoughts, and show that not only body, but also eye movements follow a (diagonal) "time line" during mental time travel.

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We report a new analysis of data from a multi-year study, some of which were previously published in the current journal. A longitudinal sample of 380 computer specialists was followed over two years, yielding three measures each of job satisfaction, organizational commitment, and turnover intentions, as well as actual turnover, and reasons for leaving, at Times 2 and 3. Career paths were more diverse than the classical distinction between stayers and leavers implies. Furthermore, although the largest single group of leavers cited “push” reasons, conforming to the classical withdrawal model, a sizable number were attracted to another job (“pull motivation”). In a three-wave structural equation model, job (dis)satisfaction predicted turnover, while organizational commitment exerted its influence only via its association with job satisfaction. As expected, however, attitudes predicted turnover only for participants with push motivation. Quitting, in turn, predicted an improvement in both satisfaction and commitment, indicating that it paid off for the individual. The necessity to study consequences of turnover and to distinguish between different subgroups of stayers and leavers is emphasized.

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Firms confront three problems: (1) shirking (sub-optimal provision of effort), (2) smooth transfer of knowledge, and (3) eliciting new knowledge. The motivations possessed by firm members are four: (a) instrumental rationality (i.e., self-interest), (b) moral motivations and integrity, (c) intrinsic motivations, and (d) fairness motivations. The trick for the firm is to manage motivations in a way that solves its particular problems. The purpose of this paper is to provide the foundations for moral motivations and moral integrity, and to discuss the kinds of problems that they can and cannot solve, particularly in context of the complex motivational mix.

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Background. Irritable bowel syndrome is a gastrointestinal disorder that is potentially linked to international travel at an undetermined frequency.^ Methods. A self-administered questionnaire was distributed through mail to five hundred and ninety-one patients that were twice diagnosed with irritable bowel syndrome at Kelsey Seybold Clinic in Houston, TX. Responses to survey questions were used to assess patient travel history, IBS symptomology, and disease classification.^ Results. Of the five hundred and ninety-one patients that were mailed a questionnaire, two hundred and twenty one patients returned questionnaires and two hundred and one met inclusion criteria. Of the participants reporting international travel within six months of developing their chronic intestinal disorder, 60% were classified as having PI-IBS, while 25% had IBS, 10% had PI-UFBD, and 5% had UFBD. A majority of the subjects who traveled six months before onset of their functional bowel disease had a post-infectious form of IBS and reported a start and worsening of symptoms with an acute bout of diarrhea. It was common for those traveling six months before travel and labeled PI-IBS to have enteric symptoms that led to lifestyle adjustments. ^ Conclusion. International travel had a significant effect on the classification of IBS among patients which relates to the differences in IBS symptoms and perhaps pathogenesis among travelers versus non-travelers. ^

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During the summer of 2003, a ground-penetrating radar survey around the North Greenland Icecore Project (NorthGRIP) deep ice-core drilling site (75°06' N, 42°20' W; 2957 m a.s.l.) was carried out using a shielded 250 MHz radar system. The drill site is located on an ice divide, roughly 300 km north-northwest of the summit of the Greenland ice sheet. More than 430 km of profiles were measured, covering a 10 km by 10 km area, with a grid centered on the drilling location, and eight profiles extending beyond this grid. Seven internal horizons within the upper 120 m of the ice sheet were continuously tracked, containing the last 400 years of accumulation history. Based on the age-depth and density-depth distribution of the deep core, the internal layers have been dated and the regional and temporal distribution of accumulation rate in the vicinity of NorthGRIP has been derived. The distribution of accumulation shows a relatively smoothly increasing trend from east to west from 145 kg/m**2/a to 200 kg/m**2/a over a distance of 50 km across the ice divide. The general trend is overlain by small-scale variations on the order of 2.5 kg/m**2/a/km, i.e. around 1.5% of the accumulation mean. The temporal variations of the seven periods defined by the seven tracked isochrones are on the order of +-4% of the mean of the last 400 years, i.e. at NorthGRIP ±7 kg/m**2/a. If the regional accumulation pattern has been stable for the last several thousand years during the Holocene, and ice flow has been comparable to today, advective effects along the particle trajectory upstream of NorthGRIP do not have a significant effect on the interpretation of climatically induced changes in accumulation rates derived from the deep ice core over the last 10 kyr.

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The purpose of this study was to evaluate summer and fall residency and habitat selection by gray whales, Eschrichtius robustus, together with the biomass of benthic amphipod prey on the coastal feeding grounds along the Chukotka Peninsula. Thirteen gray whales were instrumented with satellite transmitters in September 2006 near the Chukotka Peninsula, Russia. Nine transmitters provided positions from whales for up to 81 days. The whales travelled within 5 km of the Chukotka coast for most of the period they were tracked with only occasional movements offshore. The average daily travel speeds were 23 km/day (range 9-53 km/day). Four of the whales had daily average travel speeds <1 km/day suggesting strong fidelity to the study area. The area containing 95% of the locations for individual whales during biweekly periods was on average 13,027 km**2 (range 7,097-15,896 km**2). More than 65% of all locations were in water <30 m, and between 45 and 70% of biweekly kernel home ranges were located in depths between 31 and 50 m. Benthic density of amphipods within the Bering Strait at depths <50 m was on average ~54 g wet wt/m**2 in 2006. It is likely that the abundant benthic biomass is more than sufficient forage to support the current gray whale population. The use of satellite telemetry in this study quantifies space use and movement patterns of gray whales along the Chukotka coast and identifies key feeding areas.

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Synthetic seismograms are constructed from check shot-corrected velocity and density measurements collected during Ocean Drilling Program (ODP) Leg 180 at Sites 1109, 1115, and 1118. The synthetic seismograms facilitate direct correlation of a coincident multichannel seismic (MCS) profile with borehole data collected at the three sites. The MCS data and the synthetic seismograms correlate very well, with most major reflectors successfully reproduced in the synthetics. Our results enable a direct calibration of the MCS data in terms of age, paleoenvironment, and subsidence history. Seismic reflectors are time correlative within stratigraphic resolution but are often observed to result from different lithologies across strike. Our results facilitate the extrapolation of the sedimentation history into an unsampled section of Site 1118 and enable a full correlation between the three sites using all the data collected during ODP Leg 180. This study forms the foundation for regionalizing the site data to the northern margin of the Woodlark Basin, where the transition from continental rifting to seafloor spreading is taking place.

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La relación entre la estructura urbana y la movilidad ha sido estudiada desde hace más de 70 años. El entorno urbano incluye múltiples dimensiones como por ejemplo: la estructura urbana, los usos de suelo, la distribución de instalaciones diversas (comercios, escuelas y zonas de restauración, parking, etc.). Al realizar una revisión de la literatura existente en este contexto, se encuentran distintos análisis, metodologías, escalas geográficas y dimensiones, tanto de la movilidad como de la estructura urbana. En este sentido, se trata de una relación muy estudiada pero muy compleja, sobre la que no existe hasta el momento un consenso sobre qué dimensión del entorno urbano influye sobre qué dimensión de la movilidad, y cuál es la manera apropiada de representar esta relación. Con el propósito de contestar estas preguntas investigación, la presente tesis tiene los siguientes objetivos generales: (1) Contribuir al mejor entendimiento de la compleja relación estructura urbana y movilidad. y (2) Entender el rol de los atributos latentes en la relación entorno urbano y movilidad. El objetivo específico de la tesis es analizar la influencia del entorno urbano sobre dos dimensiones de la movilidad: número de viajes y tipo de tour. Vista la complejidad de la relación entorno urbano y movilidad, se pretende contribuir al mejor entendimiento de la relación a través de la utilización de 3 escalas geográficas de las variables y del análisis de la influencia de efectos inobservados en la movilidad. Para el análisis se utiliza una base de datos conformada por tres tipos de datos: (1) Una encuesta de movilidad realizada durante los años 2006 y 2007. Se obtuvo un total de 943 encuestas, en 3 barrios de Madrid: Chamberí, Pozuelo y Algete. (2) Información municipal del Instituto Nacional de Estadística: dicha información se encuentra enlazada con los orígenes y destinos de los viajes recogidos en la encuesta. Y (3) Información georeferenciada en Arc-GIS de los hogares participantes en la encuesta: la base de datos contiene información respecto a la estructura de las calles, localización de escuelas, parking, centros médicos y lugares de restauración. Se analizó la correlación entre e intra-grupos y se modelizaron 4 casos de atributos bajo la estructura ordinal logit. Posteriormente se evalúa la auto-selección a través de la estimación conjunta de las elecciones de tipo de barrio y número de viajes. La elección del tipo de barrio consta de 3 alternativas: CBD, Urban y Suburban, según la zona de residencia recogida en las encuestas. Mientras que la elección del número de viajes consta de 4 categorías ordinales: 0 viajes, 1-2 viajes, 3-4 viajes y 5 o más viajes. A partir de la mejor especificación del modelo ordinal logit. Se desarrolló un modelo joint mixed-ordinal conjunto. Los resultados indican que las variables exógenas requieren un análisis exhaustivo de correlaciones con el fin de evitar resultados sesgados. ha determinado que es importante medir los atributos del BE donde se realiza el viaje, pero también la información municipal es muy explicativa de la movilidad individual. Por tanto, la percepción de las zonas de destino a nivel municipal es considerada importante. En el contexto de la Auto-selección (self-selection) es importante modelizar conjuntamente las decisiones. La Auto-selección existe, puesto que los parámetros estimados conjuntamente son significativos. Sin embargo, sólo ciertos atributos del entorno urbano son igualmente importantes sobre la elección de la zona de residencia y frecuencia de viajes. Para analizar la Propensión al Viaje, se desarrolló un modelo híbrido, formado por: una variable latente, un indicador y un modelo de elección discreta. La variable latente se denomina “Propensión al Viaje”, cuyo indicador en ecuación de medida es el número de viajes; la elección discreta es el tipo de tour. El modelo de elección consiste en 5 alternativas, según la jerarquía de actividades establecida en la tesis: HOME, no realiza viajes durante el día de estudio, HWH tour cuya actividad principal es el trabajo o estudios, y no se realizan paradas intermedias; HWHs tour si el individuo reaiza paradas intermedias; HOH tour cuya actividad principal es distinta a trabajo y estudios, y no se realizan paradas intermedias; HOHs donde se realizan paradas intermedias. Para llegar a la mejor especificación del modelo, se realizó un trabajo importante considerando diferentes estructuras de modelos y tres tipos de estimaciones. De tal manera, se obtuvieron parámetros consistentes y eficientes. Los resultados muestran que la modelización de los tours, representa una ventaja sobre la modelización de los viajes, puesto que supera las limitaciones de espacio y tiempo, enlazando los viajes realizados por la misma persona en el día de estudio. La propensión al viaje (PT) existe y es específica para cada tipo de tour. Los parámetros estimados en el modelo híbrido resultaron significativos y distintos para cada alternativa de tipo de tour. Por último, en la tesis se verifica que los modelos híbridos representan una mejora sobre los modelos tradicionales de elección discreta, dando como resultado parámetros consistentes y más robustos. En cuanto a políticas de transporte, se ha demostrado que los atributos del entorno urbano son más importantes que los LOS (Level of Service) en la generación de tours multi-etapas. la presente tesis representa el primer análisis empírico de la relación entre los tipos de tours y la propensión al viaje. El concepto Propensity to Travel ha sido desarrollado exclusivamente para la tesis. Igualmente, el desarrollo de un modelo conjunto RC-Number of trips basado en tres escalas de medida representa innovación en cuanto a la comparación de las escalas geográficas, que no había sido hecha en la modelización de la self-selection. The relationship between built environment (BE) and travel behaviour (TB) has been studied in a number of cases, using several methods - aggregate and disaggregate approaches - and different focuses – trip frequency, automobile use, and vehicle miles travelled and so on. Definitely, travel is generated by the need to undertake activities and obtain services, and there is a general consensus that urban components affect TB. However researches are still needed to better understand which components of the travel behaviour are affected most and by which of the urban components. In order to fill the gap in the research, the present dissertation faced two main objectives: (1) To contribute to the better understanding of the relationship between travel demand and urban environment. And (2) To develop an econometric model for estimating travel demand with urban environment attributes. With this purpose, the present thesis faced an exhaustive research and computation of land-use variables in order to find the best representation of BE for modelling trip frequency. In particular two empirical analyses are carried out: 1. Estimation of three dimensions of travel demand using dimensions of urban environment. We compare different travel dimensions and geographical scales, and we measure self-selection contribution following the joint models. 2. Develop a hybrid model, integrated latent variable and discrete choice model. The implementation of hybrid models is new in the analysis of land-use and travel behaviour. BE and TB explicitly interact and allow richness information about a specific individual decision process For all empirical analysis is used a data-base from a survey conducted in 2006 and 2007 in Madrid. Spatial attributes describing neighbourhood environment are derived from different data sources: National Institute of Statistics-INE (Administrative: municipality and district) and GIS (circular units). INE provides raw data for such spatial units as: municipality and district. The construction of census units is trivial as the census bureau provides tables that readily define districts and municipalities. The construction of circular units requires us to determine the radius and associate the spatial information to our households. The first empirical part analyzes trip frequency by applying an ordered logit model. In this part is studied the effect of socio-economic, transport and land use characteristics on two travel dimensions: trip frequency and type of tour. In particular the land use is defined in terms of type of neighbourhoods and types of dwellers. Three neighbourhood representations are explored, and described three for constructing neighbourhood attributes. In particular administrative units are examined to represent neighbourhood and circular – unit representation. Ordered logit models are applied, while ordinal logit models are well-known, an intensive work for constructing a spatial attributes was carried out. On the other hand, the second empirical analysis consists of the development of an innovative econometric model that considers a latent variable called “propensity to travel”, and choice model is the choice of type of tour. The first two specifications of ordinal models help to estimate this latent variable. The latent variable is unobserved but the manifestation is called “indicators”, then the probability of choosing an alternative of tour is conditional to the probability of latent variable and type of tour. Since latent variable is unknown we fit the integral over its distribution. Four “sets of best variables” are specified, following the specification obtained from the correlation analysis. The results evidence that the relative importance of SE variables versus BE variables depends on how BE variables are measured. We found that each of these three spatial scales has its intangible qualities and drawbacks. Spatial scales play an important role on predicting travel demand due to the variability in measures at trip origin/destinations within the same administrative unit (municipality, district and so on). Larger units will produce less variation in data; but it does not affect certain variables, such as public transport supply, that are more significant at municipality level. By contrast, land-use measures are more efficient at district level. Self-selection in this context, is weak. Thus, the influence of BE attributes is true. The results of the hybrid model show that unobserved factors affect the choice of tour complexity. The latent variable used in this model is propensity to travel that is explained by socioeconomic aspects and neighbourhood attributes. The results show that neighbourhood attributes have indeed a significant impact on the choice of the type of tours either directly and through the propensity to travel. The propensity to travel has a different impact depending on the structure of each tour and increases the probability of choosing more complex tours, such as tours with many intermediate stops. The integration of choice and latent variable model shows that omitting important perception and attitudes leads to inconsistent estimates. The results also indicate that goodness of fit improves by adding the latent variable in both sequential and simultaneous estimation. There are significant differences in the sensitivity to the latent variable across alternatives. In general, as expected, the hybrid models show a major improvement into the goodness of fit of the model, compared to a classical discrete choice model that does not incorporate latent effects. The integrated model leads to a more detailed analysis of the behavioural process. Summarizing, the effect that built environment characteristics on trip frequency studied is deeply analyzed. In particular we tried to better understand how land use characteristics can be defined and measured and which of these measures do have really an impact on trip frequency. We also tried to test the superiority of HCM on this field. We can concluded that HCM shows a major improvement into the goodness of fit of the model, compared to classical discrete choice model that does not incorporate latent effects. And consequently, the application of HCM shows the importance of LV on the decision of tour complexity. People are more elastic to built environment attributes than level of services. Thus, policy implications must take place to develop more mixed areas, work-places in combination with commercial retails.