City Logistics and Clustering: Impacts of Using HDI and Taxes

Castro, Rodrigo Barros; Merchán, Daniel; Lima, Orlando Fontes; Winkenbach, Matthias

doi:10.1002/9781119425526.ch8

“…The application of K-Means cluster analysis has been carried out in various studies. Among them, Castro et al (2018) which identifies logistics and city categorization by HDI and taxes in São Paulo; Pejić Bach et al (2018) examine the economic cost impact of violence on 119 countries worldwide; and Sharkh & Gough (2010), who grouped a large number of developing countries based on their level of welfare and stability.…”

Section: Literature Reviewmentioning

confidence: 99%

Classifying regencies and cities on human development index dimensions: Application of K-Means cluster analysis

Nurhasanah

2023

Jambi University

0

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The Human Development Index (HDI) is a measurement that analyzes a region's development in improving human development. The government's development plan aims to create a successful and peaceful life. The unbalanced development in every regency and city in Indonesia is a typical issue during the development process. It may also be shown that the HDI level changes across regencies and cities in Indonesia. This research aims to identify Indonesian regencies and cities based on HDI indices. K-Means clustering algorithm is the clustering method adopted. The results of the analysis formed 4 clusters. The first cluster consisted of 20 regencies with a low average HDI indicator. The second cluster consisted of 148 regencies and cities with an average HDI indicator is medium. The third cluster consisted of 88 regencies and cities with an average HDI indicator. The fourth cluster consists of 258 regencies and cities with high HDI indicators.

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“…The application of K-Means cluster analysis has been carried out in various studies. Among them, Castro et al (2018) which identifies logistics and city categorization by HDI and taxes in São Paulo; Pejić Bach et al (2018) examine the economic cost impact of violence on 119 countries worldwide; and Sharkh & Gough (2010), who grouped a large number of developing countries based on their level of welfare and stability.…”

Section: Literature Reviewmentioning

confidence: 99%

Classifying regencies and cities on human development index dimensions: Application of K-Means cluster analysis

Nurhasanah

¹

,

Salwa

²

,

Ornila

³

et al. 2021

View full text Add to dashboard Cite

The Human Development Index (HDI) is a measurement that analyzes a region's development in improving human development. The government's development plan aims to create a successful and peaceful life. The unbalanced development in every regency and city in Indonesia is a typical issue during the development process. It may also be shown that the HDI level changes across regencies and cities in Indonesia. This research aims to identify Indonesian regencies and cities based on HDI indices. K-Means clustering algorithm is the clustering method adopted. The results of the analysis formed 4 clusters. The first cluster consisted of 20 regencies with a low average HDI indicator. The second cluster consisted of 148 regencies and cities with an average HDI indicator is medium. The third cluster consisted of 88 regencies and cities with an average HDI indicator. The fourth cluster consists of 258 regencies and cities with high HDI indicators.

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Transport Service Provider Perception of Barriers and Urban Freight Policies in Brazil

Oliveira

¹

,

Nascimento

²

,

Sousa

³

et al. 2019

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The aim of this paper is to analyze the perceptions of the transport service providers on the barriers in urban freight transport and the restrictions imposed on freight vehicles, identifying which urban freight transport policies can improve this activity in Brazil. Principal component analysis allowed us to identify which are barriers in urban cargo transport and the restrictions imposed on freight vehicles. In addition, we evaluated freight policies that can improve the activity using probabilistic preference. We obtained the database from a web-based survey of transport service providers in Brazil. The results indicate that the urban freight vehicle restriction is related to congestion and availability of loading and unloading areas. The freight vehicle restriction is a result of the lack of information and data. The theft of cargo significantly impacts urban freight transport. Transport service provider company perceptions indicate an urban mobility plan as the most-required freight policy to improve freight mobility. To reduce the barriers to urban freight planning, an understanding of the problem involving the stakeholders is needed. To do so, the challenge is to change the culture in the transportation planning process by integrating various actors to create an urban logistics plan that generates opportunities for the city.

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City Logistics and Clustering: Impacts of Using HDI and Taxes

Cited by 3 publications

References 5 publications

Classifying regencies and cities on human development index dimensions: Application of K-Means cluster analysis

Classifying regencies and cities on human development index dimensions: Application of K-Means cluster analysis

Classifying regencies and cities on human development index dimensions: Application of K-Means cluster analysis

Transport Service Provider Perception of Barriers and Urban Freight Policies in Brazil

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