Productivity and convergence in Norwegian container seaports: An SFA-based Malmquist productivity index approach

Odeck, James; Schøyen, Halvor

doi:10.1016/j.tra.2020.05.001

Cited by 18 publications

(13 citation statements)

References 48 publications

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“…In this case the previous researcher that specifically discusses about efficiency are Iyer & Nanyam (2021), Kutin et al (2017), Munim (2020), Mustafa et al (2021), andZarbi et al (2019). Then the discussion specifically for productivity is carried out by Odeck and Schøyen (2020) and Song & Cui (2014). Furthermore, the analysis of efficiency can be analyzed more deeply/specifically.…”

Section: Previous Researchmentioning

confidence: 99%

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Technical Efficiency Analysis of Container Terminals in Tanjung Perak, Surabaya, East Java

Afiatno

Joyoutomo

2022

JDE

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Container Terminals in Tanjung Perak Port is a trading center in the Eastern Indonesia Region (KTI) with a total throughput of 3.6 million TEUs in 2020. The utility/level of use of terminal facilities, consisting of the pier/berth occupancy ratio (BOR), has reached 60%. The field/yard occupancy ratio (YOR) is 65%, while the maximum utility is 70% (UNCTAD). It is necessary to explore the technical efficiency of each container terminal using the stochastic frontier analysis (SFA) because it can also capture the inefficiency effects. This study is built from the analysis of production factors in the period of 2009-2020, where the variables used are capital (k) using company asset data, labor variable (l) using data on the number of human resources, energy variable (e) using energy cost data (fuel oil/fuel, electricity, and water). The inefficiency variables are port draught (d) and loading and unloading productivity (p). The container terminal in Tanjung Perak has a relatively high technical efficiency value of 0.94. This shows that the terminal operation is quite optimum and is approaching the maximum point. The overall average elasticity is 2.01, which can be categorized as an increasing return to scale. The elasticity of assets has the most significant proportion, so it can be concluded that the port is capital intensive. Next, it’s found that the higher productivity 1% increase in loading and unloading productivity, the more inefficiency with a relatively minimal value of 0.11%. Finally, an increase of 1% in depth will increase efficiency by 10.89%.

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Section: Previous Researchmentioning

confidence: 99%

“…Furthermore, Odeck and Schøyen (2020) analyzed the efficiency of container terminals based on the delivery of logistics services in the hinterland. Continuing Pérez et al (2020) examines whether port specialization and size can have an impact on port efficiency.…”

Section: Previous Researchmentioning

confidence: 99%

Technical Efficiency Analysis of Container Terminals in Tanjung Perak, Surabaya, East Java

Afiatno

Joyoutomo

2022

JDE

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“…To overcome the shortcomings of the first two methods, Aigner et al considered the effect of relative technical efficiency on TFP and proposed the stochastic frontier analysis in 1977 [19]. Thereafter, a large number of scholars have started to use this method to study the growth of TFP [20][21][22]. The SFA takes the influence of relative technical efficiency on TFP into account, which can avoid the interference of random disturbance terms to a certain extent.…”

Section: Literature Reviewmentioning

confidence: 99%

Has the Economic Structure Optimization in China’s Supply-Side Structural Reform Improved the Inclusive Green Total Factor Productivity?

Wang

Min

et al. 2021

Sustainability

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One of the goals of China’s supply-side structural reform is to improve total factor productivity (TFP). Considering the problems of environmental deterioration and income disparity faced by China, this paper first incorporates environmental pollution and income disparity as undesirable outputs into the TFP analysis framework, and extends the concept of inclusive green TFP (henceforth IGTFP).We measure and analyze the IGTFP in China’s provinces from 1995 to 2017 using the Malmquist–Luenberger index, and then examine, for the first time, the impacts of economic structural optimization in the supply-side structural reform on the IGTFP. The results are shown as follows. First, China’s national IGTFP index is significantly smaller than the traditional TFP index. That is, the traditional TFP without the constraints of environmental pollution and income disparity overestimates China’s real TFP. Second, there are significant regional differences in China’s IGTFP, the average annual growth rate of IGTFP shows a gradual downward trend from east to west. This would further exacerbate the regional imbalance in China’s economic development. Third, among the structural factors in economic structure optimization, industrial structure and energy structure are negatively correlated with the IGTFP, while factor structure, labor structure and urban–rural structure are all positively correlated with the IGTFP. These results imply that the economic structure optimization driven by supply-side structural reform will improve China’s IGTFP.

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“…International authors to be considered are [22][23][24][25][26][27][28][29][30][31]. Work [22] addresses the impact of intelligent capital (IC) on operational efficiency for Indian financial sector companies.…”

Section: Literature Review and Problem Statementmentioning

confidence: 99%

“…The study results show that all components of IC have a significant impact on the efficiency of a firm. Paper [23] examines the efficiency, performance, and convergence of Norwegian seaports. The authors included other seaports in other Scandinavian countries and the UK in the dataset.…”

Section: Literature Review and Problem Statementmentioning

confidence: 99%

Advancing the multifactor model of Stochastic Frontier Analysis

Mitsel

Alimkhanova

Grigoryeva

2021

EEJET

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The concept of efficiency is important in economic science; at present, its role in every sector of the economy is growing. Evaluating an enterprise’s efficiency makes it possible to implement a correct and profitable strategy of resource allocation, which shows its potential level Given an annual increase in the number of bankrupt enterprises, the issue of estimating the efficiency of enterprises is relevant for both their owners and managers, as well as for creditors. There are various methods and models for estimating the performance of enterprises. This work has assessed the efficiency of enterprises in the industrial sector over the period of 2017‒2018. Stochastic Frontier Analysis is based on the stochastic model of production function. The classic SFA method is based on the production function of the company, which relates the volume of output to the volume of resources consumed. At the same time, the SFA model uses several inputs (volumes of resources consumed) and only one output parameter ‒ the volume of production. In order to achieve more precise results, a given model has been modified. The model allows several key financial indicators to be taken into consideration as outputs at the same time, based on which the financial activities of the studied economic entities are assessed. The result of the work involving open sources has revealed how the efficiency of different enterprises in the same industry changes over several years. It is shown that the modified Stochastic Frontier Analysis model could be used to assess financial stability and predict bankruptcy.

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Productivity and convergence in Norwegian container seaports: An SFA-based Malmquist productivity index approach

Cited by 18 publications

References 48 publications

Technical Efficiency Analysis of Container Terminals in Tanjung Perak, Surabaya, East Java

Technical Efficiency Analysis of Container Terminals in Tanjung Perak, Surabaya, East Java

Has the Economic Structure Optimization in China’s Supply-Side Structural Reform Improved the Inclusive Green Total Factor Productivity?

Advancing the multifactor model of Stochastic Frontier Analysis

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