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Journal articles on the topic 'Origin and destination survey'

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Published: 4 June 2021

Last updated: 7 February 2022

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Kuwahara, Masao, and Edward C. Sullivan. "Estimating origin-destination matrices from roadside survey data." Transportation Research Part B: Methodological 21, no. 3 (1987): 233–48. http://dx.doi.org/10.1016/0191-2615(87)90006-3.

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Jou, Yow-Jen, Hsun-Jung Cho, Pei-Wei Lin, and Chih-Yin Wang. "Incomplete Information Analysis for the Origin-Destination Survey Table." Journal of Urban Planning and Development 132, no. 4 (2006): 193–200. http://dx.doi.org/10.1061/(asce)0733-9488(2006)132:4(193).

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Nurbaeti, Nurbaeti, Janianton Damanik, Muhammad Baiquni, and Nopirin Nopirin. "DAYA SAING TEKNOLOGI DESTINASI PARIWISATA DKI JAKARTA BERDASARKAN PERSEPSI WISATAWAN." Kepariwisataan: Jurnal Ilmiah 9, no. 03 (2015): 31–42. http://dx.doi.org/10.47256/kepariwisataan.v9i03.137.

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This study aims to examine and analyze the use of technology in improving the competitiveness of the tourism destination based on tourists’ perception, and also to see the difference level of technology competitiveness. This research has been conducted specifically to analyse the technology competitiveness at the three main tourist destinations mentioned above based on the visitors’s perception, and why the perception could be different. This study is a survey research which explains social phenomena and causal relationship among the variables of socio-economic characteristics (group of origin, level of education, and and income level) towards the competitiveness of technology parameter in the three tourist destination through hypothesis testing. Information was collected from 300 respondents using the questionnaire, and for each tourist destination, for the-100 respondent, the unit analyzed are individuals (tourists). Sample are tourists to the three main destinations in Jakarta during May, August, and September 2014. The selected samples are those who have visited the three different tourist destination within the last three years whose age are 15 years or more. The collected data were then analyzed using Kruskall-Walls statistical test, i.e. nonparametric analysis instrument to see whether there are any difference between two conditions. Based on group of origin, level of education, and income level of the respondents, the results showed have no differences in perception to technology competitiveness of the three tourist destinations. Keywords: tourist destination, tourists’ perception, tourism destination competitiveness

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Egu, Oscar, and Patrick Bonnel. "How comparable are origin-destination matrices estimated from automatic fare collection, origin-destination surveys and household travel survey? An empirical investigation in Lyon." Transportation Research Part A: Policy and Practice 138 (August 2020): 267–82. http://dx.doi.org/10.1016/j.tra.2020.05.021.

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Chapleau, Robert, Martin Trέpanier, Pierre Lavigueur, and Bruno Allard. "Origin-Destination Survey Data Dissemination in Metropolitan Context: A Multimedia Experience." Transportation Research Record: Journal of the Transportation Research Board 1551, no. 1 (1996): 26–35. http://dx.doi.org/10.1177/0361198196155100104.

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Since the early 1970s, the Montreal Urban Community Transit Commission has held a series of six major origin-destination surveys in the greater Montreal area. These studies, which include approximately 50,000 households per survey, benefit from a totally disaggregate approach. This framework permits the spatialization of each trip end at the x-y coordinate level and associates multiple variables to every recorded trip. The dissemination of such a vast quantity of data requires different levels of resolution with respect to processing methods and software, zonal aggregation, itineraries, and sociodemographic variables. In this context, two tools have been created for public use: MADEOD (Origin-Destination Survey Data Disaggregate Analysis Model) and MADGEN (Trip Generator Disaggregate Analysis Model). Because of the recent and rapid evolution of multimedia technology, these tools have been developed in an interactive Microsoft Excel worksheet format and in hypertext markup language for the Groupe MADITUC's World Wide Web site on the Internet. Stand-alone multimedia presentations and a Windows help file have also been developed for tutorial use.

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Sánchez-Martínez, Gabriel E. "Inference of Public Transportation Trip Destinations by Using Fare Transaction and Vehicle Location Data." Transportation Research Record: Journal of the Transportation Research Board 2652, no. 1 (2017): 1–7. http://dx.doi.org/10.3141/2652-01.

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Origin–destination matrices provide vital information for service planning, operations planning, and performance measurement of public transportation systems. In recent years, methodological advances have been made in the estimation of origin–destination matrices from disaggregate fare transaction and vehicle location data. Unlike manual origin–destination surveys, these methods provide nearly complete spatial and temporal coverage at minimal marginal cost. Early models inferred destinations on the basis of the proximity of possible destinations to the next origin and disregarded the effect of waiting time, in-vehicle time, and the number of transfers on path choice. The research reported here formulated a dynamic programming model that inferred destinations of public transportation trips on the basis of a generalized disutility minimization objective. The model inferred paths and transfers on multileg journeys and worked on systems that served a mix of gated stations and ungated stops. The model is being used to infer destinations of public transportation trips in Boston, Massachusetts, and is producing better results than could be obtained with earlier models.

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Harrison, Robert. "Using Brokers to Determine North American Free Trade Agreement Truck Origins and Destinations at Texas-Mexico Border." Transportation Research Record: Journal of the Transportation Research Board 1719, no. 1 (2000): 136–39. http://dx.doi.org/10.3141/1719-17.

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U.S.-Mexico trade continues to grow, much of it crossing into Texas, where bridges over the Rio Grande carry the vehicular and rail traffic. Currently, more than 70 percent of North American Free Trade Agreement U.S.-Mexico trade is by truck, and substantial delays and other social costs are a feature of border port-of-entry systems. New bridge locations are being proposed, and each site must be carefully evaluated to ensure that it is economically feasible. As part of this evaluation process, origin and destination surveys are used to determine bridge location and demand. Many of the truck trailers are moved by drayage companies or by drivers who have not brought the load from its origin or who will deliver it to the final destination. It is argued that surveys of these drivers are flawed and give limited data. A report is made on a method with which to interview and survey customs brokers to derive truck origin and destination data; this report was successfully employed at the Anzalduas International Bridge site near McAllen, Texas. Because many ports of entry in Texas are similar to McAllen, the survey method can be applied across the whole border.

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Gómez-Déniz, Emilio, Jorge V. Pérez-Rodríguez, and José Boza-Chirino. "Modelling tourist expenditure at origin and destination." Tourism Economics 26, no. 3 (2019): 437–60. http://dx.doi.org/10.1177/1354816619840845.

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This article proposes a model of foreign tourist expenditure, based on expenditure in the country of origin (i.e. reservation of accommodation and transport) and on goods and services at the destination. The study focuses on two measures reflecting the two types of expenditure: the tourist budget share and the difference in growth rates between expenditure at origin and at destination. The random nature of each of these variables is taken into account. The tourist budget share is determined using a fractional response model, based on the beta distribution. This approach allows us to accommodate certain aspects of the empirical budget share distribution, such as skewness, and to represent the results as bounded between 0 and 1, but also to include covariates. The empirical analysis was conducted using data obtained by the Canary Islands Tourist Expenditure Survey, focusing on German and British tourists in particular. The results obtained show that the fractional regression model proposed represents the behaviour of the relevant variables reasonably well and surpasses the performance of the linear regression model.

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Blum, Jeremy J., Anoop Sridhar, and Tom V. Mathew. "Origin–Destination Matrix Generation from Boarding–Alighting and Household Survey Data." Transportation Research Record: Journal of the Transportation Research Board 2183, no. 1 (2010): 1–8. http://dx.doi.org/10.3141/2183-01.

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Bhat, Suhail Ahmad, and Mushtaq Ahmad Darzi. "Antecedents of tourist loyalty to tourist destinations: a mediated-moderation study." International Journal of Tourism Cities 4, no. 2 (2018): 261–78. http://dx.doi.org/10.1108/ijtc-12-2017-0079.

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PurposeThe purpose of this paper is to analyze the impact of destination image on satisfaction level and tourist loyalty toward the various tourist destinations in Jammu and Kashmir. The study, also, attempted to investigate the mediating role of satisfaction and moderating role of gender, past experience and tourist origin in the proposed model.Design/methodology/approachThe study was carried out in the state of Jammu and Kashmir spread over three divisions, i.e., Jammu, Kashmir and Ladakh. The study employs questionnaire survey method for data collection. Purposive sampling was adopted for data collection and data analysis was carried out through exploratory factor analysis, confirmatory factor analysis and structural equation modeling techniques.FindingsThe study has found that cognitive image, affective image and unique image are the significant dimensions of destination image, which in turn has a positive effect on satisfaction level and tourist loyalty. It was also found that destination image has both direct and indirect effect on tourist loyalty.Research limitations/implicationsThe state of Jammu and Kashmir has been badly affected by ongoing political instability, which has caused huge losses to the tourism industry. The results of the study will be helpful to policymakers in designing various strategies and programs for maximizing tourist inflow and growth of tourism industry in the state of Jammu and Kashmir.Practical implicationsFurther, finding of the study will assist destination managers in understanding consumer behavior for promoting destination shopping activities. This will enhance tourist expenditure at destinations and thus provides direct benefits to the local economy.Originality/valueVery little research has been conducted on moderating role of gender, past experience and tourist origin in the destination image and its association with satisfaction and tourist loyalty in the state of Jammu and Kashmir. Managing destination image and quality of tourist experience are critical to induce favorable expectations of destination in the tourist’s mind.

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Quiroga, Cesar, Russell Henk, and Marc Jacobson. "Innovative Data Collection Techniques for Roadside Origin-Destination Surveys." Transportation Research Record: Journal of the Transportation Research Board 1719, no. 1 (2000): 140–46. http://dx.doi.org/10.3141/1719-18.

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Described are the results of a pilot application intended to automate the data collection and data reduction phases of roadside origin-destination (O-D) studies. Most techniques used to obtain O-D data are quite labor intensive, during both the data collection and the data reduction phase. Frequently, they result in extensive data quality checks and long turnaround periods between the data collection work and the submittal of the corresponding survey report. The application described automates the data collection and data reduction phases by using portable, handheld data collection devices. These devices can be connected to a desktop or laptop computer to transfer the O-D data to a depository database. Included are a brief background discussion, a description of the hardware and software used and the design and development of O-D applications, a description of two applications of the handheld data collection devices, and a list of lessons learned.

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Güler, Hakan. "AN EMPIRICAL MODELLING FRAMEWORK FOR FORECASTING FREIGHT TRANSPORTATION." TRANSPORT 29, no. 2 (2014): 185–94. http://dx.doi.org/10.3846/16484142.2014.930927.

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This paper presents a framework which includes empirical modelling methods to estimate freight transportation between defined zones. In this method, observed origin and destination matrices for each type of freight are constituted based on the link counts and the roadside truck survey data. The gravity method is selected to estimate origin and destination matrices by using observed link flows, gross domestic product by provinces and interzonal distances. Advanced statistical techniques and regression analyses are used to estimate the coefficients of the gravity method. The final freight transportation matrix is calibrated with the link flows data by using iterative techniques. The developed method was applied to find the origin and destination matrix of the total freight transportation in Turkey and successful results were obtained.

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Ashtakala, Bala, and A. S. Narasimha Murthy. "Intraprovincial trip distribution model." Canadian Journal of Civil Engineering 13, no. 4 (1986): 438–44. http://dx.doi.org/10.1139/l86-068.

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A town (or city) in a province generates external trips to other towns and cities for various purposes. A cordon origin–destination (O – D) survey shows the origin and destinations of the external trips of a town. An individual external trip distribution model is developed for a town using the cordon O – D survey data. The external trips are recognized as intra provincial trips and therefore the model is called intraprovincial trip distribution model. The data used in this study is taken from cordon O – D surveys done in Alberta.In the formulation of the model, a functional form that uses a linear relationship between the dependent and the independent variables and power transformations on the independent variable is considered. The parameters in the model are obtained by regression analysis. The models are validated by statistical measures and tests. In this paper, an individual model is developed for each of the seven cities and towns chosen for this study. The formulation and development of the model, regression analysis, and validity tests are described in detail. Key words: cordon survey, intraprovincial trips, model, power transformations, regression analysis, trip distribution.

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Findlay, A. M., F. L. N. Li, A. J. Jowett, M. Brown, and R. Skeldon. "Doctors Diagnose Their Destination: An Analysis of the Length of Employment Abroad for Hong Kong Doctors." Environment and Planning A: Economy and Space 26, no. 10 (1994): 1605–24. http://dx.doi.org/10.1068/a261605.

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Much contemporary skilled international migration involves the transient movement of skills between a migrant's country of origin and the destination. This paper shows that international circulation amongst Hong Kong doctors is neither new nor random. A survey of Hong Kong doctors with overseas work experience was undertaken by the authors to examine the factors influencing the length of employment overseas and the propensity to return. Statistical analysis of the results indicates that holding a foreign passport, previous overseas training, and the country of destination were key factors in detennining the length of residence abroad and propensity to return to Hong Kong. In the light of the changing importance for Hong Kong professionals of obtaining residency rights abroad, and given the widely varying immigration policies of the main destination countries in relation to issues such as recognition of Hong Kong qualifications, it is suggested that professional groups such as doctors choose their migration destinations in line with a predetermined migration strategy for either temporary emigration or for longer-term resettlement overseas. The survey results are of wider significance in the understanding of changing patterns of skill exchange involving the upper echelons of the populations of newly industrialising countries.

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Park, Man-Bae, and Robert L. Smith. "Development of a Statewide Truck-Travel Demand Model with Limited Origin-Destination Survey Data." Transportation Research Record: Journal of the Transportation Research Board 1602, no. 1 (1997): 14–21. http://dx.doi.org/10.3141/1602-03.

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A simple statewide truck-travel demand model for Wisconsin was developed using only readily available data, including a small amount of data from origin-destination travel surveys (O-D) and fairly extensive truck-classification count data. A simple trip-rate trip-generation model based on zonal population was used to estimate the initial internal trip productions and attractions. Despite the small amount of O-D survey data that were available, gravity-model friction-factor curves were developed for three trip types. The calibrated gravity models produced trip tables that were good matches for the O-D survey data. The calibrated gravity models were then used as the modeling framework for the adjustment of zonal productions and attractions by selected-link-based (SELINK) analysis. SELINK adjustment factors were computed for all zones with trips on one or more of the selected links. The adjustments were made so that the ratio of the actual volume for the selected link (ground count) to the total assigned volume approached 1 for all selected links. The SELINK analysis produced a calibrated model after only three iterations when either 16 or 32 selected links were used statewide for the calibration. The overall accuracy of the calibrated model was measured by using classification count data for 154 locations around the state. The model provided a good fit based on a wide variety of measures, including percent root-mean-square error and comparisons for screenlines, functional class, areas, and vehicle kilometers traveled.

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Malema, H. K., and W. Musakwa. "TWEETS AND FACEBOOK POSTS, THE NOVELTY TECHNIQUES IN THE CREATION OF ORIGIN-DESTINATION MODELS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B2 (June 8, 2016): 555–62. http://dx.doi.org/10.5194/isprsarchives-xli-b2-555-2016.

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Social media and big data have emerged to be a useful source of information that can be used for planning purposes, particularly transportation planning and trip-distribution studies. Cities in developing countries such as South Africa often struggle with out-dated, unreliable and cumbersome techniques such as traffic counts and household surveys to conduct origin and destination studies. The emergence of ubiquitous crowd sourced data, big data, social media and geolocation based services has shown huge potential in providing useful information for origin and destination studies. Perhaps such information can be utilised to determine the origin and destination of commuters using the Gautrain, a high-speed railway in Gauteng province South Africa. To date little is known about the origins and destinations of Gautrain commuters. Accordingly, this study assesses the viability of using geolocation-based services namely Facebook and Twitter in mapping out the network movements of Gautrain commuters. Explorative Spatial Data Analysis (ESDA), Echo-social and ArcGis software were used to extract social media data, i.e. tweets and Facebook posts as well as to visualize the concentration of Gautrain commuters. The results demonstrate that big data and geolocation based services have the significant potential to predict movement network patterns of commuters and this information can thus, be used to inform and improve transportation planning. Nevertheless use of crowd sourced data and big data has privacy concerns that still need to be addressed.

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Qureshi, Mohammad A., Ho-Ling Hwang, and Shih-Miao Chin. "Comparison of Distance Estimates for Commodity Flow Survey: Great Circle Distances Versus Network-Based Distances." Transportation Research Record: Journal of the Transportation Research Board 1804, no. 1 (2002): 212–16. http://dx.doi.org/10.3141/1804-28.

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A study was conducted to compare distance estimates derived from great circle distances (GCD) with distance estimates derived from a network-based model. The study used a sample of shipments from the 1993 commodity flow survey (CFS). For each shipment in the sample, the distance from the zip code of origin to the zip code of destination was calculated by using the Oak Ridge National Laboratories National Highway Network and assuming that the minimum impedance path was utilized. For each of these origin–destination pairs, the GCD and several variations of the GCD also were estimated. Finally, the network-based estimates and the GCD-based estimates were statistically compared. As expected, distance estimates based on GCD were found to be different from network-based estimates. However, applying a constant circuity factor of 1.22 or using variable circuity factors based on distance category did not result in a statistical bias in these distance estimates. Examination of distance estimates at the level of origin–destination pair revealed that distance estimates could vary as much as 75%. A comparison of published values for the 1997 CFS with values derived from GCD-based distance estimates shows that approximately 5% to 35% of the GCD-based values for the 1997 CFS would fall outside a two standard error interval. Although GCD-based estimates, under some conditions, may produce unbiased estimates of the mean distance, this does not eliminate the need for network-based estimates.

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Abdel-Aty, Mohamed A., and Hassan T. Abdelwahab. "Toll Road Origin-Destination Travel Survey: Internet and Mail-Back Response Analysis and Implications for Future Surveys." Transportation Research Record: Journal of the Transportation Research Board 1768, no. 1 (2001): 61–70. http://dx.doi.org/10.3141/1768-08.

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Moyo, T., and W. Musakwa. "USING CROWDSOURCED DATA (TWITTER & FACEBOOK) TO DELINEATE THE ORIGIN AND DESTINATION OF COMMUTERS OF THE GAUTRAIN PUBLIC TRANSIT SYSTEM IN SOUTH AFRICA." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences III-2 (June 2, 2016): 143–50. http://dx.doi.org/10.5194/isprs-annals-iii-2-143-2016.

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The study of commuters’ origins and destinations (O_D) promises to assist transportation planners with prediction models to inform decision making. Conventionally O_D surveys are undertaken through travel surveys and traffic counts, however data collection for these surveys has historically proven to be time consuming and having a strain on human resources, thus a need for an alternative data source arises. This study combines the use social media data and geographic information systems in the creation of a model for origin and destination surveys. The model tests the potential of using big data from Echo echo software which contains Twitter and Facebook data obtained from social media users in Gauteng. This data contains geo-location and it is used to determine origin and destination as well as concentration levels of Gautrain commuters. A kriging analysis was performed on the data to determine the O-D and concentration levels of Gautrain users. The results reveal the concentration of Gautrain commuters at various points of interest that is where they work, live or socialise. The results from the study highlight which nodes attract the most commuters and also possible locations for the expansion for Gautrain. Lastly, the study also highlights some weakness of crowdsourced data for informing transportation planning.

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Silver, Dan, Julia Seltzer, Stan Hsieh, Dara Seidl, Farhad Siraj, and Mindy Rhindress. "Exclusion of Nonspecific Geocodes and the Representation of Ridership Profiles in Survey Data." Transportation Research Record: Journal of the Transportation Research Board 2643, no. 1 (2017): 28–33. http://dx.doi.org/10.3141/2643-04.

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To construct responsive travel models, transportation modelers must have accurate geocoding data; only the addresses with specific geocodes (i.e., addresses with high specificity) are retained in the data, and addresses with nonspecific geocodes (i.e., addresses with low specificity, such as at the municipality level) are excluded, replaced, or imputed. Whether this practice introduces bias in the data and leads to potential inaccuracies in models that are subsequently constructed has not been evaluated. Between December 2014 and November 2015, the Metro-North Railroad (MNR) Origin and Destination Survey collected data from Hudson Line riders, who were asked to chronicle trips from start to finish. The accuracy and specificity of the address data varied. Some respondents provided information in all possible data fields (street address or intersection, city, state, and zip code), but their addresses were geocoded to a lower level of geographic accuracy because the batch geocoder could not interpret a valid address from the combined data. The differences between MNR riders who provided specific destination addresses and MNR riders who provided nonspecific destination addresses in New York City were analyzed. The primary cause for this difference was found to be a respondent’s reasons for traveling and destination type and not a respondent’s demographic profile or specific destination location within the New York City region.

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Sana, Bhargava, Joe Castiglione, Drew Cooper, and Dan Tischler. "Using Google’s Passive Data and Machine Learning for Origin-Destination Demand Estimation." Transportation Research Record: Journal of the Transportation Research Board 2672, no. 46 (2018): 73–82. http://dx.doi.org/10.1177/0361198118798298.

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Origin-destination (OD) data collection methods are steadily attempting to move from conventional survey techniques (roadside interview, license plate, etc.) toward using passively collected big data sources such as those based on global positioning system (GPS) and cell phone call detail records (CDR). In this study, a new passive data source, Google’s Aggregated and Anonymized Trips (AAT), was used to derive hourly OD demand matrices for the San Francisco Bay Area. Since the AAT dataset contains relative flows or weights as opposed to absolute trips, machine learning techniques were applied to convert them with the help of observed OD flows from expanded household travel survey. Several machine learning models were trained to perform quite well for both training and test data. However, it was found that the multi-layer perceptron (MLP), a neural networks approach, resulted in the best performing model for the conversion. Additionally, all models were used for predictions in a hypothetical application context where input AAT data were scaled by different growth factors. This exercise showed that, even though the trip predictions of all models were close to each other initially, they varied widely for different magnitudes of OD markets and growth factors.

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Chimba, Deo, Daniel Emaasit, and Boniphace Kutela. "Integrating Origin-Destination Survey and Stochastic User Equilibrium: A Case Study for Route Relocation." Journal of Transportation Technologies 02, no. 04 (2012): 297–304. http://dx.doi.org/10.4236/jtts.2012.24032.

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Watling, David P. "Maximum likelihood estimation of an origin-destination matrix from a partial registration plate survey." Transportation Research Part B: Methodological 28, no. 4 (1994): 289–314. http://dx.doi.org/10.1016/0191-2615(94)90003-5.

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Pérez-Messina, Ignacio, Eduardo Graells-Garrido, María Jesús Lobo, and Christophe Hurter. "Modalflow: Cross-Origin Flow Data Visualization for Urban Mobility." Algorithms 13, no. 11 (2020): 298. http://dx.doi.org/10.3390/a13110298.

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Pervasive data have become a key source of information for mobility and transportation analyses. However, as a secondary source, it has a different methodological origin than travel survey data, usually relying on unsupervised algorithms, and so it requires to be assessed as a dataset. This assessment is challenging, because, in general, there is not a benchmark dataset or a ground truth scenario available, as travel surveys only represent a partial view of the phenomenon and suffer from their own biases. For this critical task, which involves urban planners and data scientists, we study the design space of the visualization of cross-origin, multivariate flow datasets. For this purpose, we introduce the Modalflow system, which incorporates and adapts different visualization techniques in a notebook-like setting, presenting novel visual encodings and interactions for flows with modal partition into scatterplots, flow maps, origin-destination matrices, and ternary plots. Using this system, we extract general insights on visual analysis of pervasive and survey data for urban mobility and assess a mobile phone network dataset for one metropolitan area.

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Levels, Mark, Jaap Dronkers, and Gerbert Kraaykamp. "Immigrant Children's Educational Achievement in Western Countries: Origin, Destination, and Community Effects on Mathematical Performance." American Sociological Review 73, no. 5 (2008): 835–53. http://dx.doi.org/10.1177/000312240807300507.

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This article explores the extent to which macro-level characteristics of destination countries, origin countries, and immigrant communities help explain differences in immigrant children's educational achievement. Using data from the 2003 PISA survey, we analyze the mathematical performance of 7,403 pupils from 35 different origin countries in 13 Western countries of destination. While compositional differences offer some explanatory power, they cannot fully explain cross-national and cross-group variance. Contextual attributes of host countries, origin countries, and communities are also meaningful. In this regard, strict immigration laws explain immigrant children's better educational performance in traditional immigrant-receiving countries. Results further suggest that origin countries' level of economic development can negatively affect immigrant children's educational performance, and that immigrant children from more politically stable countries perform better at school. Finally, socioeconomic differences between immigrant communities and a native population, and relative community size, both shape immigrant children's scholastic achievement.

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Trépanier, Martin, and Robert Chapleau. "Analyse orientée-objet et totalement désagrégée des données d'enquêtes ménages origine-destination." Canadian Journal of Civil Engineering 28, no. 1 (2001): 48–58. http://dx.doi.org/10.1139/l00-106.

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Large urban household surveys produce a huge quantity of data, generally processed with database management systems (DBMS). In most cases, data are compiled, aggregated, and then integrated in traditional transportation models. Based on another perspective, the totally disagregate approach (TDA) uses a unified survey data file in which every piece of information is preserved. The data file is used for individual analysis of households, people, and trips. The addition of an object-oriented modeling to the totally disaggregate approach permits the instantiation of survey data into objects. These objects are manipulated along with their properties and methods. New objects are derived from survey declaration and then reused in the process: status, trip generators. The enriched object-model is used for visualization, analysis, and presentation. This widens the possibilities of usage of household survey data.Key words: urban transportation, household surveys, modeling, oriented-object approach.

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Chiswick, Barry R., Yew Liang Lee, and Paul W. Miller. "A Longitudinal Analysts of Immigrant Occupational Mobility: A Test of the Immigrant Assimilation Hypothesis." International Migration Review 39, no. 2 (2005): 332–53. http://dx.doi.org/10.1111/j.1747-7379.2005.tb00269.x.

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This article develops a model of the occupational mobility of immigrants and tests the hypotheses using data on males from the Longitudinal Survey of Immigrants to Australia, Panel I. The theoretical model generates hypotheses regarding a U-shaped pattern of occupational mobility from the “last job” in the origin, to the “first job” in the destination, to subsequent jobs in the destination, and regarding the depth of the “U.” The survey includes data on pre-immigration occupation, the “first” occupation in Australia (at six months) and the occupation after about three-and-a-half years in Australia. The hypotheses are supported by the empirical analysis.

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Wonjae Jang. "Estimating Origin-Destination Trip Matrices from Roadside Survey Data with Consideration of Passing Traffic Data." Journal of Transport Research 16, no. 1 (2009): 1–14. http://dx.doi.org/10.34143/jtr.2009.16.1.1.

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Soltész, Tamás, Attila Aba, Miklós Bánfi, and Miklós Kózel. "PFS method for pedestrian origin-destination surveys of enclosed areas." Transportation Research Procedia 27 (2017): 680–87. http://dx.doi.org/10.1016/j.trpro.2017.12.082.

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Watson, Kathleen B., Geoffrey P. Whitfield, Stacey Bricka, and Susan A. Carlson. "Purpose-Based Walking Trips by Duration, Distance, and Select Characteristics, 2017 National Household Travel Survey." Journal of Physical Activity and Health 18, S1 (2021): S86—S93. http://dx.doi.org/10.1123/jpah.2021-0096.

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Background: New or enhanced activity-friendly routes to everyday destinations is an evidence-based approach for increasing physical activity. Although national estimates for some infrastructure features surrounding where one lives and the types of nearby destinations are available, less is known about the places where individuals walk. Methods: A total of 5 types of walking trips (N = 54,034) were defined by whether they began or ended at home (home based [HB]) and trip purpose (HB work, HB shopping, HB social/recreation, HB other, and not HB trip) (2017 National Household Travel Survey). Differences and trends by subgroups in the proportion of each purpose-oriented trip were tested using pairwise comparisons and polynomial contrasts. Results: About 14% of U.S. adults reported ≥1 walking trip on a given day. About 64% of trips were HB trips. There were few differences in prevalence for each purpose by subgroup. For example, prevalence of trips that were not HB decreased significantly with increasing age and increased with increasing education and household income. Conclusions: Given age-related and socioeconomic differences in walking trips by purpose, planners and other professionals may want to consider trip origin and destination purposes when prioritizing investments for the creation of activity-friendly routes to everyday destinations where people live, work, and play.

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Siahaan, L. Denny. "Kajian Estimasi Variabel Pemudik Lebaran di Pulau Jawa Tahun 2010 dan 2011 Dengan Survei Rumah Tangga." Warta Penelitian Perhubungan 23, no. 3 (2019): 292. http://dx.doi.org/10.25104/warlit.v23i3.1070.

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Homecoming, called "mudik" in bahasa, at Lebaran is a culture in Indonesia to visit the family at the hometmvn. Hence, it needs bigger transportation capacity than usual. Infrastructure planning for all transportation mode needs the prediction of travelers number, origin and destination of travelers, the utilization preference of all transportation mode, the distribution of travelers per day as the basic availability of transport infrastructure and the prediction of economic effects by the travelers to the local destination. Whereas, there was household survey at 6 big cities in Java Island i.e Jabodetabek (Jakarta, Bogar, Depok, Tangerang and Bekasi), Serang, Bandung, Semarang, Yogyakarta, and Surabaya as the origin of travelers to five provinces destination within Java Island (excluded DKI Jakarta) and outside Java Island. The result of survey analysis from 34.3 million citizen at big cities in 2010 with 6,580 household samples which consist of 22,949 respondents found that 23.9% travelers, using cars 27%, buses 40%, motorcycles 14%, trains 12%, ships 1 %, airplanes 3%, and others 3%. The peak time of travelers held on the first, second, and third day before Lebaran and the seventh day after Lebaran. The economic effects from the travelers of five provinces approximately three trillion from the travelers.Keywords: travelers, transportation and lebaran economic

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Al-Battaineh, Omar, and Isam A. Kaysi. "Genetically-optimized origin-destination estimation (GOODE) model: application to regional commodity movements in Ontario." Canadian Journal of Civil Engineering 34, no. 2 (2007): 228–38. http://dx.doi.org/10.1139/l06-127.

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The problem of origin-destination (O-D) matrix estimation has attracted significant research attention in the past few decades. This paper proposes a novel approach to estimate a regional freight O-D matrix using different data sources. The genetically optimized origin-destination estimation (GOODE) model takes advantage of the genetic algorithm's (GA) global search procedure to find the O-D matrix that is associated with the minimum deviation between estimated and observed data values. The GOODE-commodity model, an extension of the GOODE model, estimates the freight O-D matrix by interfacing GOODE with a trip generation model based on input-output data. The GOODE model and its extension bring together national input-output data, truck survey data, a global searching method, and a GIS platform for data manipulation. This paper presents the GOODE model structure, a prototypical numerical example, a benchmarking exercise with an existing O-D estimation model, and a real-world application of the GOODE-commodity model for a case study of commodity movements in Ontario. Avenues for future research are also addressed.Key words: origin-destination (O-D) matrix estimation, truck transportation modelling, input-output, Ontario, genetic algorithm.

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Bundas, Andrei. "DIASPORA NETWORKS AND THE CONSUMPTION OF NOSTALGIC PRODUCTS AMONG ROMANIAN MIGRANTS IN GERMANY." Oradea Journal of Business and Economics 3, no. 2 (2018): 86–99. http://dx.doi.org/10.47535/1991ojbe054.

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Statistics show that cross-national immigration represents one of the fastest growing global trends. Researchers have revealed that immigration is a transnational process with immigrants maintaining ties across the sending and receiving locations, and acting as a bridge between their countries of destination and origin. Research has also revealed the economic link created by the diaspora between the countries of origin and destination with two main components: the remittances sent to families and the consumption of home origin goods, also defined by scholars as ethnic products, nostalgic products or nostalgia products. During the period 2010-2015, the Romanian diaspora had the world's second fastest average annual growth rate. In the same period, Germany became one of the premier destinations for Romanian migration. An empirical study was organized in Germany in the period June – August 2017. The study is based on a regional survey of 124 subjects belonging to the Romanian community in Germany in four Bavarian cities. Four hypotheses have been advanced with the purpose of evaluating the level of demand for home origin products among Romanian migrants, the sources of supply, the level of expenditures and the motivational factors. The findings show that Romanian migrants in Germany manifest an important interest in and demand for home origin country goods; they spend 420 EUR yearly on ethnic products and their consumption motivation is strongly related to the products' special tastes and characteristics. Most of the products are obtained through local ethnic stores. The study’s results also reveal important similarities between the nostalgic product consumption habits of Romanian migrants in Germany and those of South American migrants in the U.S. The study’s findings are relevant for both the literature and for the Romanian companies, especially the ones active in the food and drink sector.

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Altintas, Volkan, Ercan Sirakaya-Turk, and Serkan Bertan. "Destination images of visitors attending to travel expo in key markets of Turkey." Tourism and hospitality management 16, no. 2 (2010): 229–41. http://dx.doi.org/10.20867/thm.16.2.8.

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The objective of the current study was to assess how the origin, education levels, gender, ages and income of expo visitors affected their perceptions of Turkey and what could be done to improve visitors’ perception of Turkey. Data were collected in three expos held in three countries via self-reported survey instruments. Survey instrument included scale items which probed people’s perceptions and images of Turkey along with other relevant variables. There were 264 Germans participants, 332 Dubains, and 94 Russians. Profiles of markets were analyzed using t-tests. The result of this study showed that demographic characteristics of participants affected their perceptions of the destination differently.

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Jones, Lee K., Nathan H. Gartner, Michael Shubov, Chronis Stamatiadis, and David Einstein. "Modeling Origin-Destination Uncertainty Using Network Sensor and Survey Data and New Approaches to Robust Control." Transportation Research Procedia 23 (2017): 887–900. http://dx.doi.org/10.1016/j.trpro.2017.05.049.

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Ji, Yuxiong, Rabi G. Mishalani, and Mark R. McCord. "Transit passenger origin–destination flow estimation: Efficiently combining onboard survey and large automatic passenger count datasets." Transportation Research Part C: Emerging Technologies 58 (September 2015): 178–92. http://dx.doi.org/10.1016/j.trc.2015.04.021.

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Jones, Lee K., Nathan H. Gartner, Mikhail Shubov, Chronis Stamatiadis, and David Einstein. "Modeling origin-destination uncertainty using network sensor and survey data and new approaches to robust control." Transportation Research Part C: Emerging Technologies 94 (September 2018): 121–32. http://dx.doi.org/10.1016/j.trc.2017.09.007.

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Li, Haojie, Dongyu Wu, Daniel J. Graham, and N. N. Sze. "Comparison of exposure in pedestrian crash analyses: A study based on zonal origin-destination survey data." Safety Science 131 (November 2020): 104926. http://dx.doi.org/10.1016/j.ssci.2020.104926.

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Watling, David P., and Michael J. Maher. "A statistical procedure for estimating a mean origin-destination matrix from a partial registration plate survey." Transportation Research Part B: Methodological 26, no. 3 (1992): 171–93. http://dx.doi.org/10.1016/0191-2615(92)90023-p.

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Montazer, Shirin, and Blair Wheaton. "Economic Conditions in Countries of Origin and Trajectories in Distress after Migration to Canada." Society and Mental Health 7, no. 1 (2016): 1–20. http://dx.doi.org/10.1177/2156869316671372.

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This paper re-examines the study of immigrant mental health by arguing that the level of economic development of origin country alters both initial mental health status and subsequent trajectories of distress over time. Using five waves of longitudinal survey data from the National Population Health Survey of adults living in three metropolitan cities in Canada ( N = 2,887), results show an increase in distress with time, but mainly among immigrants from lower gross national product (GNP) origin countries and only for the first 5 years postarrival, followed by a decline among all immigrants, irrespective of origin-country GNP. Increases in chronic stress exposure fully explain the initial increase in distress among immigrants from less developed countries of origin. Results call into question the generalizability of the “immigrant health paradox” to all immigrant groups and point to the importance of macro-level social and economic factors, and the matching of conditions at origin and destination, in the migration process.

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Matiza, Tafadzwa, and Elmarie Slabbert. "Understanding the Country Image-Travel Motivation Nexus in Emerging Tourism Typologies for South Africa." Polish Journal of Sport and Tourism 27, no. 3 (2020): 28–33. http://dx.doi.org/10.2478/pjst-2020-0017.

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Abstract Introduction. This paper explores the influence of country image on the evaluation of a destination’s attributes from the perspective of inbound tourists to South Africa - within the context of both business and medical tourism. Material and methods. Data were generated from a self-administered questionnaire distributed as part of a survey of inbound tourists visiting South Africa’s Table Mountain. Factor analysis and multiple regression were employed to determine the factors and establish their relationship, respectively. Results. The results suggest that South Africa’s image as a country influences tourist’s perception of the country and its destination attributes. More intriguingly, the results show that South Africa’s image is subject to both stereotypes and the country-of-origin effect. Conclusion. The paper concludes that country image is a significant heuristic cue in the appraisal of the destination attributes that motivate inbound tourist travel behaviour. More so, it is aspects such as the ability to manage its affairs, nationally branded exports and the availability of international business-related opportunities that may be most influential to South Africa’s perceived image in tourist decision-making.

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Malamassam, Meirina Ayumi. "Youth Migration in Indonesia: Decision to Move and to Choose of Destination Areas." Indonesian Journal of Geography 48, no. 1 (2016): 62. http://dx.doi.org/10.22146/ijg.12469.

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Using intercensal population survey data, this paper examines migration behavior of youth in Indonesia aged 15 to 24 years old. Logistic regressions are employed to understand factors influencing youth’s decision to migrate as well as their choice of destination areas. The study findings suggest that migration preferences are determined by both the individual characteristics as well as the development level in both areas of origin and destination. It is also shown that education plays an important role in youth migration in Indonesia, not only in improving individual’s capacity to migrate, but also in prompting migration to big cities. In addition, youth migrants tend to move to areas with similar characteristics or similar cultural background to their areas of origin. For most of young people, migration is considered as an attempt for gaining upward social mobility, thus the prevalence of youth migration to less developed areas is low.

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Sondakh, Eduard, Saptono Kusdanu Waskito, and Sari Armiati. "SEBARAN PASIEN SAAT PANDEMI COVID-19 DI JAWA BARAT MENGGUNAKAN METODE ORIGIN DESTINATION." Jurnal Logistik Bisnis 11, no. 1 (2021): 1–6. http://dx.doi.org/10.46369/logistik.v11i1.1373.

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Wabah COVID-19, diumumkan secara resmi ada di Indonesia di awal bulan Maret 2020. Sejak saat itu pemerintah pusat melalui Badan Nasional Penanggulangan Bencana (BNPB) sebagai Gugus Tugas Percepatan Penanganan COVID-19 memberikan informasi terkini secara periodik. BNPB juga bekerja sama dengan pemerintah daerah dan pemerintah kota baik dalam penyaluran informasi maupun dalam penyaluran bantuan alat pelindung diri (APD). Pemerintah Provinsi Jawa Barat Bandung pun telah memiliki pusat informasi dan koordinasi COVID-19 melalui pikobar.jabarprov.go.id. Namun demikian muncul permasalahan, beberapa rumah sakit rujukan yang terus ditambah sejalan bertambahnya pasien Covid19 baik di kota maupun kabupaten di Jawa Barat, belum menunjukan apakah kapasitas tersebut memadai sesuai jumlah pasien yang dirujuk atau tidak. Untuk itu dalam penelitian ini dibuat analisis sebaran pasien Covid19 menggunakan metode Origin Destination menggunakan data pasien di bulan Agustus 2020. Tahap kegiatan penelitian yang dilakukan melalui 3 tahapan yaitu survey pencarian data rumah sakit rujukan beserta jumlah kapasitasnya, data pasien positif yang harus dirawat di Jawa Barat dan pemetaan matrik Origin Destination (OD). Kegunaan hasil dari penelitian ini adalah berupa kajian pemenuhan kebutuhan layanan kesehatan terhadap pasien Covid19 di Jawa Barat dan dapat dijadikan dasar pengembangan perancangan sistem pelayanan rumah sakit rujukan terhadap pasien Covid19.

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Saeedimoghaddam, M., and C. Kim. "MODELING A SPATIO-TEMPORAL INDIVIDUAL TRAVEL BEHAVIOR USING GEOTAGGED SOCIAL NETWORK DATA: A CASE STUDY OF GREATER CINCINNATI." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences IV-4/W2 (October 20, 2017): 207–14. http://dx.doi.org/10.5194/isprs-annals-iv-4-w2-207-2017.

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Understanding individual travel behavior is vital in travel demand management as well as in urban and transportation planning. New data sources including mobile phone data and location-based social media (LBSM) data allow us to understand mobility behavior on an unprecedented level of details. Recent studies of trip purpose prediction tend to use machine learning (ML) methods, since they generally produce high levels of predictive accuracy. Few studies used LSBM as a large data source to extend its potential in predicting individual travel destination using ML techniques. In the presented research, we created a spatio-temporal probabilistic model based on an ensemble ML framework named “Random Forests” utilizing the travel extracted from geotagged Tweets in 419 census tracts of Greater Cincinnati area for predicting the tract ID of an individual’s travel destination at any time using the information of its origin. We evaluated the model accuracy using the travels extracted from the Tweets themselves as well as the travels from household travel survey. The Tweets and survey based travels that start from same tract in the south western parts of the study area is more likely to select same destination compare to the other parts. Also, both Tweets and survey based travels were affected by the attraction points in the downtown of Cincinnati and the tracts in the north eastern part of the area. Finally, both evaluations show that the model predictions are acceptable, but it cannot predict destination using inputs from other data sources as precise as the Tweets based data.

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Cools, Mario, Elke Moons, and Geert Wets. "Assessing the Quality of Origin–Destination Matrices Derived from Activity Travel Surveys." Transportation Research Record: Journal of the Transportation Research Board 2183, no. 1 (2010): 49–59. http://dx.doi.org/10.3141/2183-06.

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Pronello, Cristina, Davide Longhi, and Jean-Baptiste Gaborieau. "Smart Card Data Mining to Analyze Mobility Patterns in Suburban Areas." Sustainability 10, no. 10 (2018): 3489. http://dx.doi.org/10.3390/su10103489.

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This paper aims to define an algorithm capable of building the origin-destination matrix from check-in data collected in the extra-urban area of Torino, Italy, where thousands of people commute every day, using smart cards to validate their travel documents while boarding. To this end, the methodological approach relied on a survey over three months to record smart-card validations. Peak and off-peak periods have been defined according to validation frequency. Then, the origin-destination matrix has been estimated using the time interval between two validations to outline the different legs of the journey. Finally, transport demand has been matched with existing bus services, showing which areas were not adequately covered by public transport. The results of this research could assist public transport operators and local authorities in the design of a more suitable transport supply and mobility services in accordance with user needs. Indeed, tailoring public transport to user needs attracts both more customers and latent demand, reducing reliance on cars and making transport more sustainable.

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Docquier, Frédéric, Giovanni Peri, and Ilse Ruyssen. "The Cross-country Determinants of Potential and Actual Migration." International Migration Review 48, no. 1_suppl (2014): 37–99. http://dx.doi.org/10.1111/imre.12137.

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In this study, we use cross-country bilateral data to quantify a two-step process of international migration and its aggregate determinants. We first analyze which country-specific factors affect the probability that individuals join the pool of potential (aspiring) migrants. Then, we consider the bilateral and destination country factors that affect the frequency at which potential migrants turn into actual migrants. Using information on potential migrants from World Gallup surveys and on actual migrants from national censuses for 138 origin countries and 30 major destinations between 2000 and 2010, we analyze economic, policy, cultural, and network determinants of each step. We find that the size of the network of previous migrants and the average income per person at destination are crucial determinants of the size of the pool of potential migrants. Economic growth in the destination country, on the other hand, is the main economic generator of migration opportunities for a given pool of potential migrants. We also find that college-educated exhibit greater actual emigration rates mainly because of better chances in realizing their immigration potentials, rather than because of higher willingness to migrate.

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Greve, Henrich R. "Interorganizational Learning and Heterogeneous Social Structure." Organization Studies 26, no. 7 (2005): 1025–47. http://dx.doi.org/10.1177/0170840605053539.

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Organizations can learn from the innovations made or adopted by other organizations. I present a framework for interorganizational learning that allows study of how learning is affected by the characteristics of the origin and destination organizations and their relationship. I survey recent findings within this framework and develop new propositions on the population-level consequences of interorganizational learning from innovations. I identify areas of work that have received insufficient attention and make new proposals for research.

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Bonilla-Escobar, FJ, and MI Gutierrez-Martínez. "Proposal for a road safety indicator based on origin-destination survey: the problem of indicators in developing countries." Injury Prevention 18, Suppl 1 (2012): A205.3—A206. http://dx.doi.org/10.1136/injuryprev-2012-040590u.7.

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