Identification of key determinants of travel satisfaction for developing policy instrument to improve quality of life: An analysis of commuting in Delhi

Majumdar, B. C.; Jayakumar, Malavika; Sahu, Prasanta K.; Potoglou, Dimitris

doi:10.1016/j.tranpol.2021.06.012

Cited by 35 publications

(14 citation statements)

References 43 publications

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“…Champahom et al (2022) used the combination of multiple correspondence analysis and OLR approaches to analyze the factors affecting the severity of motorcycle accidents on Thailand's arterial roads. Majumdar et al (2021) employed OLR to identify the key determinants influencing travel satisfaction. It was found that gender, age, accessibility, level of congestion, availability and existing condition of sidewalks, bus stop safety, and security are significant predictors of travel satisfaction.…”

Section: Literature Reviewmentioning

confidence: 99%

“…This modelling technique is based on the cumulative probabilities of the predictor variables (Champahom et al, 2022). The ordered logit model for perceived safety can be represented as in equation 1 (Majumdar et al, 2021). Where X = a vector of variables determining perceived safety, β = a vector of parameters, and ε = a random disturbance assumed to be logistically distributed with mean = 0 and variance = 1 (Majumdar et al, 2021;Champahom et al, 2022).…”

Section: W_shl Dmentioning

confidence: 99%

“…The ordered logit model for perceived safety can be represented as in equation 1 (Majumdar et al, 2021). Where X = a vector of variables determining perceived safety, β = a vector of parameters, and ε = a random disturbance assumed to be logistically distributed with mean = 0 and variance = 1 (Majumdar et al, 2021;Champahom et al, 2022). The error term in ordered logistic regression is assumed to follow a logistic distribution (Rasca & Saeed, 2022).…”

Section: W_shl Dmentioning

confidence: 99%

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Identification of key determinants of personal safety perception at bus stops using proportional odds logistic regression

Sethulakshmi¹

2023

European Transport/Trasporti Europei

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Complex vehicle-pedestrian interaction near the bus stop affects the safety perception of users, but the subjective nature of perceived safety and the lack of specific measurement techniques makes its estimation further laborious. This paper identifies factors influencing safety perceptions of bus users by employing Ordered Logistic Regression analysis. The study focussed on five dimensions; bus stops' design and surrounding facilities, traffic characteristics, and travellers' individual, travel and accident characteristics. The results demonstrated that increased vehicular flow, absence of footpath, crossing facility and safety barrier would scale down the perceived safety. Furthermore, the respondent's age, education, frequency of travelling by bus, familiarity with the bus stop, and previous accident experience are significant predictors of perceived safety. Results concluded that females perceived less safe, and no effects can be attributed to the household vehicles and income. Regarding road shoulder width, 1-2 meters is the most preferred width from the travellers' safety perspective.

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Section: Literature Reviewmentioning

confidence: 99%

Section: W_shl Dmentioning

confidence: 99%

Section: W_shl Dmentioning

confidence: 99%

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Identification of key determinants of personal safety perception at bus stops using proportional odds logistic regression

Sethulakshmi¹

2023

European Transport/Trasporti Europei

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“…The policies and plans implemented by local governments in terms of infrastructure and municipal services as UEM affect how individuals view and judge governments (Samsurijan et al 2022). Their actions, as a policy tool, can affect the QOL of individuals and lead to their satisfaction (Majumdar et al 2021). Public facilities and services around a community are vital for the livelihood and harmony of residents as the basic unit of living conditions (Li et al 2021).…”

Section: Urban Infrastructure and Facilities (Urban Services)mentioning

confidence: 99%

Environmental social science and urban environment management: A review of pathways link- ing policies and planning to citizens living by the river

Mousazadeh

2022

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Urban environment management (UEM) and environmental social science (ESS) are two interconnected approaches that show significant potential for creating more sustainable and liveable cities. Their research has, however, been mainly disjointed, which may be because planning and policy have placed more emphasis on UEM than ESS at the same time. This research examined ESS in terms of the quality of life (QOL) criteria and sense of place (SOP) of citizens living by the river with the UEM intervention in the form of policies and programmes. The effects of fieldwork in the form of specialised and spatial interviews are presented in this research, which is usually ignored in the literature review of this type of analysis. The study aims to fill the current gap in this field in three European capitals by providing a reflective methodological account of fieldwork and the ‘elite interviewing’ approach. This paper produces a distinct form of the localisation of the research and sampling techniques and is as new, interactive and developing as possible. The results of the present study are underpinned by the conceptual model of research, which supports the main aim of this analysis and tries to examine the components of research in a new perspective. The findings high- lighted that maintaining and strengthening ESS for citizens living next to rivers require innovative UEM, which uses urban creativity in the field of goals, urban settlements, strategies and management solutions to provide the base for increasing the liveability of the city and improving the quality of urban life.

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“…How to improve commuting satisfaction is a common concern for city managers, planners, and researchers in related fields. The factors affecting commuting satisfaction mainly include the commuting time [8,9], commuting mode [10][11][12][13], built environment [14,15], service level [16,17], and perceived attitude [18,19]. For the commuting mode, there are a few reasons why walking or cycling are associated with higher satisfaction, such as moderate commuting times and lower commuting costs [20], more exposure to green space [21], increased social interaction, and the promotion of physical and mental health [22].…”

Section: Introductionmentioning

confidence: 99%

Exploring the Group Difference in the Nonlinear Relationship between Commuting Satisfaction and Commuting Time

Yang

2022

Sustainability

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Analyzing commuting-time satisfaction could help to improve the subjective well-being of society. This study aimed to explore the nonlinear relationship between commuting satisfaction and commuting times in different groups and its influencing factors. An empirical study was conducted in Kunming, China. Firstly, applying a random forest algorithm revealed that there was a nonlinear relationship between commuting satisfaction and commuting time. Secondly, the k-means clustering algorithm was used to divide the respondents into three types of commuter: short-duration-tolerant (group 1), medium-duration-tolerant (group 2), and long-duration-tolerant (group 3). It was found that the commuting-time satisfaction of these three clustered groups had different threshold effects. Specifically, the commuting satisfaction of group 1 showed a nonlinear downward trend, which decreased significantly at 12 and 28 min, respectively; the commuting satisfaction of group 2 rapidly decreased at 35 min; the commuting satisfaction of group 3 first increased in the range of 20–30 min, decreased significantly after 45 min, and decreased sharply above 70 min. These time thresholds were consistent with the ideal commuting times (ICTs) and tolerance thresholds of the commuting times (TTCTs) of the three clustered groups, which indicates that the ICT and TTCT had significant effects on commuting satisfaction. Lastly, the results of the multinominal logistic model showed that variables such as the commuting mode, job–housing distance, income, and educational background had significant effects on the three clustered groups. The policy implications of the study are that commuting circles should be planned with the TTCT as a constraint boundary and ICT as the optimal goal; in addition, different strategies should be adopted for different commuting groups to improve commuting satisfaction.

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Identification of key determinants of travel satisfaction for developing policy instrument to improve quality of life: An analysis of commuting in Delhi

Cited by 35 publications

References 43 publications

Identification of key determinants of personal safety perception at bus stops using proportional odds logistic regression

Identification of key determinants of personal safety perception at bus stops using proportional odds logistic regression

Environmental social science and urban environment management: A review of pathways link- ing policies and planning to citizens living by the river

Exploring the Group Difference in the Nonlinear Relationship between Commuting Satisfaction and Commuting Time

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