Home Interview Survey Research Articles

PERUBAHAN PERILAKU MANDATORY ACTIVITY DAN ONLINE SHOPPING ACTIVITY AKIBAT PANDEMI COVID-19

<p class="Keywords"><em><span lang="EN-GB">Teleworking activities, which have been developing since 1970 and initially aimed at employee efficiency, proved applicable during the COVID-19 pandemic. Supported by the advances of internet-based information technology, teleworking activities could be carried out optimally, leading to the emergence of various new innovations. One such innovation is app-based online shopping, which facilitates users in ordering ready-to-eat meals or groceries, known as food delivery. The COVID-19 pandemic, which spread to all countries globally, also impacted individual behaviors in activities and travel, especially with government advisories to implement lockdowns to reduce the spread of the Coronavirus. This study was conducted to examine individual behaviors in carrying out online activities in the Surakarta Agglomeration Area. Data was collected through a home interview survey from March to June 2021, involving 402 respondents. Online activities, particularly for shopping and ordering food, were hypothesized to have high value during COVID-19, leading to a comprehensive dependency on online activities, especially shopping. The research results, however, contradicted the initial hypothesis. 88.8% of individuals stated that they "never" shopped online or did grocery shopping online, with the remaining 11.2% engaging in online shopping. This discrepancy is suspected to occur because, although online shopping is easy to conduct, it requires adequate financial strength to support it.</span></em></p>

Overweight/obesity relationship with travel patterns, socioeconomic characteristics, and built environment

IntroductionOverweight and obesity are significant health issues in the modern era and correlate with daily activities, including travelling. This study focuses on understanding the relationship between overweight/obesity and travel patterns and built environment for individuals belonging to different socioeconomic groups for developing countries, where limited research is witnessed from a transportation perspective on such health parameters. MethodThe data was collected using a face-to-face home interview survey in Navi Mumbai city in Maharashtra. The sample size used for the analysis is 4253 respondents. A logistic regression model is developed to assess the impact of travel patterns, socioeconomic factors, and built environment around an individual on the likelihood of getting overweight/obese. ResultsThe results indicate that commuting by private modes is associated with increased chances of getting overweight/obese. In contrast, a negative association is observed in the chances of getting overweight/obese if commuting by active mode. The study provides quantitative support on the relationship between commuting vehicle preferences and their chances of getting overweight/obese. The interaction of walk score and population density suggests that the probability of getting overweight/obese reduces at higher values of walk score as the population density increases. The odds ratio helps understand the impact of different travel modes and their risk on the likelihood of being overweight/obese within a specific age category. ConclusionThe highest risk is observed for car/cab users compared to other modes in all age categories. The study highlights the importance of sustainable transportation modes (walking and public transport) on overweight/obesity—a crucial physical wellbeing parameter. Improving walkability measures such as walk score coupled with appropriate population density and efficient public transport system can be effective public health intervention and overweight/obesity preventative strategies.

The Guidelines of Housing Management Service for Disabled Households

The purpose of this study was to analyze existing guidelines related to housing for the disabled and housing management, and to identify the status of housing management for the disabled at home. In addition, it was intended to suggest a system for constructing the guideline for housing management services of a housing model for disabled households. The research method was as follows. 1. Analyzed the existing guidelines 2. A home visit survey and interview survey were conducted for 40 people with disabilities at home. 3. A survey was conducted on 11 experts. The data were analyzed using the SPSS statistical program. The results were as follows.: 1) Through analysis of the existing guidelines, it was derived that it is necessary to develop the guidelines for housing management services for disabled who wants to live independently. 2) In the case of people with disabilities at home, maintenance and replacement of facilities was the most common (55%) among housing management activities. 3) The final derived housing management service guideline consisted of 6 areas, 17 detailed areas, and 35 required detailed items. The six areas were A. guideline outline, B. housing management plan and operation, C. exclusive space management, etc., D. common space management and community programs, E. housing management service support organization, and F. housing management service using the housing management service app.

Population Synthesis for a City in a Developing Country

Activity-based approach in transportation studies increased the demand for detailed disaggregate data. To overcome the tedious and costly data collection, synthesized data are widely used in activity based modeling practices in developed countries. In the case of developing economies, time, resource and monetary constraints hinder the development of new generation travel demand models. Population synthesis practices are the need of the hour in developing countries. Through this study, the authors proposed a method for population synthesis for a medium sized city, in a developing country. Details from 9901 households, collected through home-interview survey in 2011 formed the database for this work. The proposed synthesis procedure makes use of Monte Carlo process along with logit modeling technique to simulate population attributes using the survey data. The procedure is developed as a Visual Basic Application in spreadsheet platform. By adopting this method, various household level and person level attributes are simulated. Comparison of observed data from survey and simulated data showed consistent results and low differences. It is expected that this study will assist the planning authorities to better understand the city′s population characteristics.

Updating of a Travel Demand Model Based on Fuel Consumption Data

Traditional methods like Home Interview Survey (HIS) used for estimation of travel demand in an urban area are not only costly and time-consuming, but also suffer from problems like sample bias, significant no-response rate, and data coding errors. In addition, such data collection processes still need to be updated on a continuous basis. Due to the above issues, there is a need for the use of more accurate secondary big data sources for the estimation of travel demand, such as mobile call records, mobile/GPS navigation data, travel smart card, and fuel smart card data.Development of travel demand forecasting models (TDFM)s based on up-to-date variables can help decision-makers achieve efficient solutions to the sudden transport problems, highlighting the need for new tools and methods that are comparatively cheaper, yet more accurate and more efficient. Nevertheless, the validity assessment of combined revealed and stated preference (RP and SP) data for analysis purposes often becomes a complicated task.This study tries to offer an improved and efficient alternative to the conventional and tedious data instruments, like HIS, for the development of a TDFM, where the big data collected through the fuel smart cards (7.5 million records of refueling data), as well as water and electricity consumption data, are used for examining travel demand patterns in the city of Shiraz in Iran. Coupled with other information technologies, smart fuel card data can provide an alternative replacement to the conventional time-consuming transport planning surveys. The large dataset of all the 64 fuel stations, amounting to 7.5 million refueling records for 61 days, was analyzed in this study, and valuable information was obtained that correlated well with traffic parameters for the city.

Modelling cellphone trace travel mode with neural networks using transit smartcard and home interview survey data

This study proposes a framework to impute travel mode for trips identified from cellphone traces by developing a deep neural network model. In our framework, we use the trips from a home interview survey and transit smartcard data, for which the travel mode is known, to create a set of artificial pseudo-cellphone traces. The generated artificial pseudo-cellphone traces with known mode are then used to train a deep neural network classifier. We further apply the trained model to infer travel modes for the cellphone traces from cellular network data. The empirical case study region is Montevideo, Uruguay, where high-quality data are available for all three types of data used in the analysis: a large dataset of cellphone traces, a large dataset of public transit smartcard transactions, and a small household travel survey. The results can be used to create an enhanced representation of origin-destination trip-making in the region by time of day and travel mode.

Ecological relationship between social capital and cognitive decline in Japan: A preliminary study for dementia-friendly communities.

Building community social capital is important for socially inclusive societies, leading to dementia-friendly communities. However, quantitative evidence is currently lacking regarding the effectiveness of dementia-friendly communities, including the association with community social capital. The current study examined the ecological relationship between social capital and the proportion of people with cognitive decline. Data were obtained from population-based, cross-sectional surveys (mail-in questionnaire survey and home-interview survey) of community-dwelling older adults aged ≥65 years, living in 17 district areas in Machida City, Tokyo, Japan. Social capital included social networks (neighborly ties) and social support (emotional support and instrumental support). Cognitive function was assessed using the Mini-Mental State Examination, Japanese version (with a cut-off of 23/24). The proportions of people with high social capital and cognitive decline (Mini-Mental State Examination, Japanese version ≤23) were calculated for residential districts and used in the analysis. The district-level social capital indicators were positively and moderately correlated with the proportion of people with cognitive decline. After adjusting for the aging rate, educational level and population density of the district, an ordinal logistic regression analysis showed that higher proportions of people with strong neighborly ties and people with strong instrumental support were significantly associated with a higher proportion of people with cognitive decline. This trend was stronger among women than men. People can continue to live in communities with high social capital, even if they are experiencing cognitive decline. Although this study was preliminary, it provided empirical evidence for the benefits of promoting dementia-friendly communities. Geriatr Gerontol Int 2019; 19: 950-955.

ANALISIS BIAYA OPERASIONAL KENDARAAN, ABILITY TO PAY DAN WILLINGNESS TO PAY UNTUK PENENTUAN TARIF BUS TRANS KOETARADJA KORIDOR III

The Government of Aceh through the Department of Transportation develop the transportation system, especially in the means of transportation one of them improve the urban transport system with the mass transit system that is Trans Koetaradja of 6 (six) corridors. Trans Koetaradja transportation is carefully planned so that it has the same direction and destination point and is bound to a predetermined schedule by using transportation cost concept which regulates fare setting so as to provide services for mutual interest, safe, fast, convenient and cheap. This research is conducted to determine the fare of Trans Koetaradja based on vehicle operational cost (VOC), Ability To Pay and Willingness To Pay from its passenger. Primary data were obtained from interviews and field surveys using state preference method in public and student respondents around Corridor III. Sampling was conducted in stratified random sampling to household (home interview survey) with total sample amounted to 110 samples. Data analysis was done by using 3 (three) method of DEPHUB method to calculate VOC, Household Budget Method to get Ability To Pay (ATP) value and perception method to get Willingness To Pay (WTP) value. The results of this study obtained the fare for corridor III based on VOC was Rp. 5,900.00, the general public ATP was Rp. 5,400.00 and student/college student was Rp. 5,200.00, public WTP was Rp. 3.000.00, and student/college student was Rp. 2,800.00

MODEL BANGKITAN PERGERAKAN RUMAH TANGGA BAGI PENGGUNA SEPEDA MOTOR BERDASARKAN LOKASI TUJUAN PERJALANAN DI KOTA BANDA ACEH

Population growth in banda Aceh city is increasing every year resulting in increased community movement. Community movement in Banda Aceh city dominated by motorcycle users, there are several factors that influence the Trip generation of Household in Banda Aceh city. One of which is the characteristic of trip behaviour which is the location of the choosen destination of the community. This research aims to know the variables of socio-economic characteristics, demography, and trip behavior in 4 sub-districts that are jaya Baru sub-dsitrict, banda raya, Lueng bata, and Kuta raja sub-dsitrict in Banda Aceh city, obtained trip generation model of motorcycle users on the household base don selection of destination location travel, what factors that affect the trip generation and analyzing the probability and error rate from the selection of each generation. This method is done by using home interview survey method. Sampling of household population to be studied by using stratified random sampling method. Method use to obtained model and probability also the relationship of variables that influenced in this research is by binomial logistic regression analysis model then processed with the help of SPSS v20 software program. From this research obtained 2 models which are the trip generation model based on destination location of trip to other places with the most influential variables are job status and last education. The generation probability is ≤ 3 movements of 77% and generation probability greater than 3 with movement of 23%. The second model is the trip generation model is based on the destination location of trip to office/school with the most influential variables are number of family members who attened school and number of family members, the probability of trip generation is. ≤ 5 movements of 81% and probability of trip generation greater than 5 movements of 19%. Both of two models also meets the specifications error value which si below 10%..

Activity-travel patterns of workers and students: a study from Calicut city, India

Travel behaviour studies in activity-based perspective treat travel as a result of individual’s desire to participate in different activities. This approach is more significant in the context of developing countries, as the transportation problems are more severe here. Since, commuters contribute to a major share in the travel, understanding their travel behaviour is essential. This paper aims to explore the travel behaviour of commuters in Calicut city, Kerala State, India and thereby model their activity-travel patterns. Household, personal and activity-travel information from 12920 working people and 9684 students formed the database for this study. The data collection was performed by means of home-interview survey by face-to-face interview technique. From preliminary analysis, several simple and complex tours were identified for the study area. Working people’s work participation and students’ education activity participation decision are modelled as mandatory activity participation choice in a binary logit modelling framework. Results of this mandatory activity participation model revealed that male workers are more likely to engage in work compared to females. Presence of elderly persons is found to negatively influence the work participation decisions of workers. This may be due to the fact that, work activity may be partially or completely replaced with the medical requirements of the elderly. The chances for work activity participation increase with increase in number of two-wheelers at home. In the case of students, as the education level increases, they are found to be less likely to participate in education activities. Students are observed to follow simple activity-travel pattern. Complex tours are found to be performed by males, compared to females. Activity-travel pattern of the study group are predicted using the developed models. The percentages correctly predicted indicate reasonably good predictability for the models. These kind of studies are expected to help the town planners to better understand city’s travel behaviour and thus to formulate well-organised travel demand management policies.

PROPOSAL OF A GEOSTATISTICAL PROCEDURE FOR TRANSPORTATION PLANNING FIELD

Abstract: The main objective of this study is to estimate variables related to transportation planning, in particular transit trip production, by proposing a geostatistical procedure. The procedure combines the semivariogram deconvolution and Kriging with External Drift (KED). The method consists of initially assuming a disaggregated systematic sample from aggregate data. Subsequently, KED was applied to estimate the primary variable, considering the population as a secondary input. This research assesses two types of information related to the city of Salvador (Bahia, Brazil): an origin-destination dataset based on a home-interview survey carried out in 1995 and the 2010 census data. Besides standing out for the application of Geostatistics in the field of transportation planning, this paper introduces the concepts of semivariogram deconvolution applied to aggregated travel data. Thus far these aspects have not been explored in the research area. In this way, this paper mainly presents three contributions: 1) estimating urban travel data in unsampled spatial locations; 2) obtaining the values of the variable of interest deriving out of other variables; and 3) introducing a simple semivariogram deconvolution procedure, considering that disaggregated data are not available to maintain the confidentiality of individual data.

Modeling of Discretionary Activities of Non-Workers in a City in India

This paper concentrates on the decision of non-workers to participate in shopping and recreation in Calicut city, a major urban center in Kerala, in India. The non-workers in the present study comprise of homemakers and the retirees. Activity and travel details collected using home interview survey formed the data base for the study. Multinomial logit models are used for analyzing the participation behaviour of non-workers in these activities. Age, travel mode, availability of household vehicles, presence of school going children, day of the week and time of day are some of the variables influencing these choices. The outcome confirms the previous findings on factors affecting non-work participation behaviour of non-workers in these activities. These models have wide applicability in determining the travel behaviour of non-workers and can serve as a major input to travel demand forecast.

DEVELOPMENT OF MODE CHOICE MODELS USING MULTINOMIAL LOGIT APPROACH IN HYDERABAD CITY

Modesplitis the process of separating person trips by mode of travel.Choice of particular mode of a commuter affects efficiency of travel within the trip performed. This paper initially explains on factors influencing mode choice behavior in metropolitan city, Hyderabad. Multinomial logistic regression model was used for evaluation of influencing factors in mode choice behavior. A stretch of 10 km from Bachupally to Mallampet in Hyderabad city of Telangana State was considered for the study. The socio economic data was collected by performing home interview survey on sample basis. Factors like age, income, travel time and travel cost are considered in generating the model. It is observed from the results that preference to public transport is more compared to all other modes of travel. Increase in travel time and travel cost per distance travelled increases in cost of operation which is primary cause for commuters to switch from personalized transport to public transport facility. The model developed for mode choice is significant at 95% having a R 2 of 0.875.This model will certainly facilitate transport planners in identification of mode choice by the commuters in the locality and to formulate effective transport policies for improvement of transportation facility within the city.

AB TEMPORAL TRIP GENERATION MODELLING FOR PRIMARY ACTIVITIES: A CASE STUDY OF FAST GROWING METROPOLITAN CITY

Transportation planning for any city evolves on the basis of complex interplay between urban activity, transport and land use system to result in varied travel patterns. Travel pattern can be defined at micro level to include individual journey departure and arrival time, journey duration and distances to make way for temporal trip generation and distribution from specific area. Trip generation is the first step of four stages of travel forecasting analysis mostly followed all over the world. Traditionally, it is focused on the prediction of aggregate trip generation by a household rather than the choice of individual activity participation. However, spatial and temporal activity domains are equally important in forecasting process and strategic urban transportation planning. The present paper attempts to develop Activity Based (AB) Temporal Trip Generation Models (ABTGM) for primary activities to cover work and educational trips considering fast growing Surat city of Gujarat, India as study area. Home interview surveys are carried to provide household and socioeconomic characteristics and the activity travel diary information to focus on the activity based tours rather the trips.

Transportation Demand Management: A Park and Ride System to Reduce Congestion in Palembang City Indonesia

Park and Ride is one of Transport Demand Management (TDM) scheme, which is very popular in some congested city with wide parking area at the border line or outskirt area. Palembang is capital city of South Sumatera Province, which has three Terminals in the border area with surrounding kabupaten (district). Right now the Terminal is not functioned appropriately because many public transport vehicles are loading and unloading passengers outside the Terminal, or on the street nearby the Terminal. On the other hand, the city centre itself has been crowded of private vehicles (car and motor cycle). The current on street parking system has been no longer adequate. According to Cities Development Initiatives for Asia (CDIA) study 2011, about 1382 cars and 1431 motorcycles need a place to park in the city centre. The aims of this paper are to present the characteristics of trips surrounding the Terminal and to know their potential of accepting Park and Ride system, and to plan the program and policy regarding Park and Ride in Palembang. The Data was collected by doing Home Interview survey in Palembang, with 4000 sample of Households (Buchari, 2011). Method of Analysis is descriptive Analysis, Cross tabulation, matrices analysis and multimodal analysis. The data from previous study was used to analyze the interconnection Terminal location with trips from surrounding areas. The results showed the potential shifting from private vehicle user to park and ride user.

Study of Work-Travel Related Behavior Using Principal Component Analysis

The main objective of this study is to analyze work travel-related behavior through a set of variables relative to socio-economic class, urban environment and travel characteristics. The Principal Component Analysis was applied in a sample consisting of workers of the S?o Paulo Metropolitan Area, based on the origin-destination home interview survey, carried out in 1997, in order to: 1) examine the interdependence between travel patterns and a set of socioeconomic and urban environment variables; 2) determine if the original database can be synthetized on components. The results enabled to observe relations between the individual’s socio-economic class and car usage, characteristics of urban environment and destination choices, as well as age and non-motorized travel mode choice. It is then concluded that the database can be adequately summarized in three components for subsequent analysis: 1) urban environment; 2) socio-economic class; and 3) family structure.

MODEL DISTRIBUSI PERJALANAN PENDUDUK UNTUK PENENTUAN KORIDOR ‘LRT’ DI PULAU BATAM

In consequence of the increasing of regional economic activities in Pulau Batam, a reliable transportation system is required. Decreasing road network performance as a result of increasing traffic volume needs a strategic planning to anticipate the worsening condition in the future. One of the solutions is by providing mass transit system which is expected to attract private car users. Therefore, determination of potential corridor of mass transit system need to be identified so that the system provide better accessibility. Trip pattern in Pulau Batam must be known by developing trip distribution model. The trip distribution model is calibrated using origin-destination (O-D) data that is based on home interview survey. The validated model will be used to forecast and simulate travel demand onto transport network. Result of model calibration process shows mean trip length difference between model and survey is equal 0.141 %. From simulation of trip assignment is obtained that potential corridor for mass transit system using LRT is Batu Ampar – Batu Aji via Muka Kuning. Passenger forecast in the year 2030 is 193,990 passenger/day (2 directions).

Trip generation production model for North zone of Fallujah city

Fallujah is one of Iraqi cities which need a comprehensive transport plan for its increased urban development and have increasing in umber of moving vehicles, caused an increasing in population with changes in the standard of living and daily trips especially at the central area, which causes jamming in transportation network. For the purpose of study, the study area in the north sector of Fallujah city is considered as one sector consists of (10) zones containing about (11954) dwelling units. Home interview survey was made of random sample which represent 5% of the study area population, and data collected through this zone. Data was related to socioeconomic characteristics of the population. The collected information solve by using the method multi – linear regression by a package(SPSS). The total persons trips per dwelling unit and various purposes were investigated. A trip production model in Fallujah city, through find relationship between socioeconomic characteristics (car ownership, family income, employee, family no., population, family size, time and cost of trip, distance to the center and area of household unit). It was found that the number of families is the most influential variable to trip production model.

Motorized Vehicle Purchase in Surat, India

As India's economy grows, so does its rate of car ownership. Motorized two-wheelers had been the prevalent mode of personal transport in the country. With improving economic conditions, more households are buying and using cars, and large cars are being introduced in a market that consisted primarily of small cars. This study assessed the trends in the future composition of motorized vehicles in the Indian city of Surat by analyzing a cross section of consumer purchases across used and new motorized vehicles, namely, two-wheelers and different size categories of cars. The findings have potential use in informing policies on infrastructure development and in controlling the negative externalities of car use. Data were obtained through home interview surveys of Surat residents who had recently purchased a motorized vehicle. To explain the vehicle choices of these residents, different observed attributes of the vehicles and their owners were considered. It was hypothesized that latent attributes (e.g., careful spender behavior, perception of status, and negative image of nonmotorized and public modes) may play an important role in the choice of personal vehicles, which are prohibitively expensive in India. To test this hypothesis, latent attributes were obtained as explanatory variables through factor analysis of responses to Likert scale questions pertaining to such attitudes and incorporated into the model. An integrated choice and latent variable model was used for this analysis. The results indicate that while household size does affect the size of vehicle purchased, small vehicles, in addition to lower fuel costs and larger engines, are generally preferred. The results further indicate that observed variables are more significant than latent ones in explaining vehicle choice.

An exploratory analysis of relationships between socioeconomic, land use, activity participation variables and travel patterns

This paper aims to find relations between the socioeconomic characteristics, activity participation, land use patterns and travel behavior of the residents in the São Paulo Metropolitan Area (SPMA) by using Exploratory Multivariate Data Analysis (EMDA) techniques. The variables influencing travel pattern choices are investigated using: (a) Cluster Analysis (CA), grouping and characterizing the Traffic Zones (TZ), proposing the independent variable called Origin Cluster and, (b) Decision Tree (DT) to find a priori unknown relations among socioeconomic characteristics, land use attributes of the origin TZ and destination choices. The analysis was based on the origin–destination home-interview survey carried out in SPMA in 1997. The DT application revealed the variables of greatest influence on the travel pattern choice. The most important independent variable considered by DT is car ownership, followed by the Use of Transportation “credits” for Transit tariff, and, finally, activity participation variables and Origin Cluster. With these results, it was possible to analyze the influence of a family income, car ownership, position of the individual in the family, use of transportation “credits” for transit tariff (mainly for travel mode sequence choice), activities participation (activity sequence choice) and Origin Cluster (destination/travel distance choice).