The impact of socioeconomic characteristics and land use patterns on household vehicle ownership and energy consumption in an urban area with insufficient public transport service – A case study of metro Manila

Rith, Monorom; Fillone, Alexis M.; Biona, Jose Bienvenido M.

doi:10.1016/j.jtrangeo.2019.102484

Cited by 23 publications

(14 citation statements)

References 18 publications

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“…On the other side, households in the urban areas may own fewer cars if the public transit networks are well-developed. Previous studies found that people incline to have fewer cars if they are living in a high-density built environment [16,37].…”

Section: Datamentioning

confidence: 99%

“…The literature indicated that the car ownership level is positively related to household income [34,35]. Rith et al [16] pointed out that, as compared with the other socio-economic attributes, household income is found as the main factor of household car ownership. House ownership status is measured by a dummy variable, valued at 1 if the house is owner occupied and 0 otherwise.…”

Section: Datamentioning

confidence: 99%

“…Numerous studies have proven that socio-demographic factors have significant effects on household car ownership. Rith et al [16] and Ao et al [17] found that household characteristics influenced household car ownership. Rith et al [16] evidenced that household income was the main factor of household vehicle ownership in Manila.…”

Section: Introductionmentioning

confidence: 99%

“…Rith et al [16] and Ao et al [17] found that household characteristics influenced household car ownership. Rith et al [16] evidenced that household income was the main factor of household vehicle ownership in Manila. Households inclined to acquire more vehicles owing to more working adults and older and well-educated household heads in families.…”

Section: Introductionmentioning

confidence: 99%

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Generational Differences in Household Car Ownership

Huang¹,

Chao²

2021

J. sustain. dev. energy water environ. syst.

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The stagnation of car demand had been observed in many countries. A similar phenomenon had emerged in Taiwan. From the perspective of socio-demographic characteristics, this study employs quantile regression for count data to investigate generational differences in household car ownership in Taiwan. The results show that the socio-demographic characteristics affected household car ownership. Due to the seniority effects, households in the later life-cycle stages and households with a higher proportion of elderly members would reduce car demand. But, households with the middle-aged heads owned more cars due to their better economic ability. The income effects are greater for higher income households. Household car ownership varied across generations, which was related to the income effects, the life course, and household structure. Hence, the demographic changes and generational differences in travel preferences should be considered in urban transportation planning. Seamless transportation and senior-friendly facilities would be important for transportation demand management.

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Section: Datamentioning

confidence: 99%

Section: Datamentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Generational Differences in Household Car Ownership

Huang¹,

Chao²

2021

J. sustain. dev. energy water environ. syst.

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“…Similarly, a good transport facility leads to less demand of automobiles. Improvement of public transport and reduction in distance to the nearest railway station leads to less dependence on private vehicles (Rith et al , 2019). A well-planned metro network leads to decrease in private vehicle ownership by 2% ∼ 3% (Mulalic et al , 2016).…”

Section: Literature Reviewmentioning

confidence: 99%

Analysis of demand risks for the Indian automotive sector in globally competitive environment

Kumar

Jain

Kain

et al. 2020

IJOA

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Purpose The purpose of this study is to understand the different types of risks affecting the demand for the automotive sector in India. The study is further trying to illustrate an approach for analyzing the relative intensities of these risks in the present uncertain business environment. Design/methodology/approach Risk on the overall demand is assessed by a combined Bayesian – multi-criteria decision-making approach. Data related to the different factors, affecting their product demand is collected from major automobile firms. Then, weights for these factors are evaluated by applying the analytic hierarchy process approach. Further, these weights are used in the Bayesian analysis network to evaluate the risk intensity for different subgroups, namely, political, economic, social, technological and environmental. Findings From the literature and experts’ opinion, total 16 risk factors have been finalized and these are further grouped into 5 categories i.e. political, economic, social, technological and environmental. It is observed that the demand for organizations functioning in the automotive sector is more vulnerable to economic risk as compared to other risks considered in the study. Practical implications Managers and decision makers of associated organizations can use the proposed framework to assess the demand risks so as to pre-evaluate their demand corresponding to future changes. Factors can be added or removed and importance could be assigned to different risk factors according to the prevailing business environment for an organization or sector. This will also help the organizations to conduct a more effective risk management in an uncertain business environment. Originality/value The study will help in better understanding of the various demand risks prevalent in the Indian auto sector. The methodology used, provides a novel approach for assessing the macroeconomic demand risks and can be used by the firms working in the automotive sector. The proposed methodology could be used for assessing supply chain risk or any other business initiative risk. The suggested approach will help managers in devising flexible management techniques so as to mitigate the risk.

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