Developer behavior in local infrastructure provision in Indonesia: Implications for policy

Maryati, Sri; Humaira, An Nisaa’ Siti; Afriana, Anita; Roekmi, Raden Ajeng Koesoemo; Suhartini, Ninik

doi:10.1016/j.jup.2021.101183

Cited by 5 publications

(3 citation statements)

References 24 publications

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“…Governments in both developed and developing countries have used PPPs as leverage when attempting to attract private sector investment in infrastructure projects (Jayasena et al, 2022). However, infrastructure provision in developing countries, including Indonesia, has not been as fulsome as in the developed world (Maryati et al, 2021). Part of the reason for this difference is purported to be the need for governmental capacity to overcome various constraints, particularly those related to credibility issues, governance weaknesses and issues related to opaqueness in the establishment of risk bearing frameworks (Bashar et al, 2021).…”

Section: Ppps In Infrastructure Developmentmentioning

confidence: 99%

Evidence on optimal risk allocation models for Indonesian geothermal projects under PPP contracts

2023

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Section: Ppps In Infrastructure Developmentmentioning

confidence: 99%

Evidence on optimal risk allocation models for Indonesian geothermal projects under PPP contracts

2023

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“…The increase in railroad construction was caused by the large number of residents who urbanized to Banjarbaru (Maryati et al, 2021). In 2015, the original population was 227,500 in 2014 to 234,371 in 2015, around 6,871 people who experienced an increase (Erlina & Suherty, 2019).…”

Section: Introductionmentioning

confidence: 99%

Modeling of Land Cover Changes in Banjarbaru City South Kalimantan Province

Saputra,

Fatchurohman

et al. 2024

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Urban areas often experience land cover changes. Banjarbaru is one of several cities in Indonesia that has experienced land changes. The relocation of the administrative center of Banjarmasin City to Banjarbaru City led to the development of settlements. One spatial analysis carried out to examine the phenomenon of land change is remote sensing techniques. The method that can be used is the Land Change Modeler from MOLUSCE in QGIS. This model uses the CAM (Cellular Automata Markov) method to identify land cover change and predict land cover distribution. CAM can understand and predict land change patterns by considering land use, vegetation, and cell spatial interactions. This modeling is based on land cover data for 2015 and 2020 and several supporting parameters such as DEM data and distance to roads. Based on the modeling results from 2015 and 2020, Banjarbaru City experienced a change in built-up land, with most of it occurring in the center of Banjarbaru City. Based on the Markov Chain method by looking at land changes in the previous year, the development of built-up land increased by about 8% of the Banjarbaru City area of 32917.41 hectares. Based on the prediction results, the development of built-up land is centered in the middle of Banjarbaru City, such as North and South Banjarbaru Districts, due to the development of residential development.Keywords: Land Cover, Land Change Modeller, Cellular Automata, Markov Chain

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“…According to The Global Competitiveness Report 2019 issued by the World Economic Forum in 2019, Indonesia achieved a score of 67,7 points and is ranked 72nd out of 141 countries in terms of infrastructure development (Schwab, 2019). The provision of infrastructure in Indonesia is considered not to meet the expected conditions (Maryati et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

The Effect of Infrastructure Development on Economic Growth

Ma'rifah

2022

jef

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The development gap between The Western Indonesia (TWI) and The Eastern Indonesia (TEI) is still quite visible, this gap can be seen from infrastructure development consisting of the Special Allocation Fund (DAK), Long Road Infrastructure (IPJ) and Construction Workforce (TKK). This study aims to determine the effect of infrastructure development on economic growth. The data used is secondary data using panel data regression analysis. This study uses a combination of data between time series data, namely 2015-2019 and cross section data consisting of 34 provinces in Indonesia. The dependent variable used is economic growth, while the independent variables in this study are the Special Allocation Fund (DAK), Long Road Infrastructure (IPJ), Construction Workers (TKK) and the dummy variable, namely the difference between KBI and KTI. The results of the study indicate that DAK has a positive but not significant effect on economic growth. Meanwhile, IPJ and TKK have a positive and significant impact on economic growth. There is also a difference between KBI and KTI that the economic growth is greater in KBI. Kesenjangan pembangunan Kawasan Barat Indonesia (KBI) dan Kawasan Timur Indonesia (KTI) masih cukup terlihat. Kesenjangan tersebut dapat dilihat dari pembangunan infrastruktur yang terdiri dari Dana Alokasi Khusus (DAK), Infrastruktur Panjang Jalan (IPJ) dan Tenaga Kerja Konstruksi (TKK). Data yang digunakan yaitu data sekunder dengan menggunakan analisis regresi data panel. Penelitian ini menggunakan gabungan data antara data time series tahun 2015-2019 dan data cross section dari 34 provinsi di Indonesia. Variabel dependen yang digunakan adalah pertumbuhan ekonomi, sedangkan variabel independen dalam penelitian ini adalah Dana Alokasi Khusus (DAK), Infrastruktur Panjang Jalan (IPJ), Tenaga Kerja Konstruksi (TKK) dan variabel dummy yaitu perbedaan KBI dan KTI. Hasil dari penelitian menunjukkan bahwa DAK memiliki pengaruh positif tetapi tidak signifikan terhadap pertumbuhan ekonomi. Sementara IPJ dan TKK memiliki pengaruh positif dan signifikan terhadap pertumbuhan ekonomi. Terdapat juga perbedaan antara KBI dan KTI lebih besar pertumbuhan ekonominya di KBI.

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Developer behavior in local infrastructure provision in Indonesia: Implications for policy

Cited by 5 publications

References 24 publications

Evidence on optimal risk allocation models for Indonesian geothermal projects under PPP contracts

Evidence on optimal risk allocation models for Indonesian geothermal projects under PPP contracts

Modeling of Land Cover Changes in Banjarbaru City South Kalimantan Province

The Effect of Infrastructure Development on Economic Growth

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