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An empirical study of Russian container terminals’ handling capacity on the basis of production frontier approach
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Introduction 7
CHAPTER 1. RESEARCH CONTEXT 10
1.1 Container Ports and Terminals 10
1.1.1 Overview of container market 10
1.1.2 Container ports and terminals functionality and operations 12
1.1.3 Approaches to capacity measurement 16
1.2 Performance Analysis: approaches on measuring efficiency 18
1.2.1 Main approaches on measuring economic performance 18
1.2.2 Approaches on measuring efficiency 20
1.2.3 Alternative production frontier models 23
1.3 Summary of Chapter 1 24
CHAPTER 2. THEORETICAL BACKGROUND 26
2.1 Analysis of the previous studies about efficiency measurement in ports 26
2.1.1 Study scope in existing literature 26
2.1.2 Analysis of model specification in the existing literature 34
2.1.3 Function form 36
2.2 Summary of Chapter 2 37
CHAPTER 3. METHODOLOGY OF THE RESEARCH 38
3.1 Research design 38
3.2 Stochastic frontier analysis framework 41
3.3 Empirical model specification 45
3.4 Summary of Chapter 3 47
CHAPTER 4. EMPIRICAL RESEARCH 48
4.1 Data description 48
4.2 Cause and effect analysis 52
4.3 Construction of production frontier model 59
4.4 Modeling of handling capacity 63
4.5 Discussion of results 64
4.5.1 Academic contribution 64
4.5.2 Managerial implication 65
4.5.3 Limitations and further research 66
Conclusion 67
Reference 69
Appendix 73
CHAPTER 1. RESEARCH CONTEXT 10
1.1 Container Ports and Terminals 10
1.1.1 Overview of container market 10
1.1.2 Container ports and terminals functionality and operations 12
1.1.3 Approaches to capacity measurement 16
1.2 Performance Analysis: approaches on measuring efficiency 18
1.2.1 Main approaches on measuring economic performance 18
1.2.2 Approaches on measuring efficiency 20
1.2.3 Alternative production frontier models 23
1.3 Summary of Chapter 1 24
CHAPTER 2. THEORETICAL BACKGROUND 26
2.1 Analysis of the previous studies about efficiency measurement in ports 26
2.1.1 Study scope in existing literature 26
2.1.2 Analysis of model specification in the existing literature 34
2.1.3 Function form 36
2.2 Summary of Chapter 2 37
CHAPTER 3. METHODOLOGY OF THE RESEARCH 38
3.1 Research design 38
3.2 Stochastic frontier analysis framework 41
3.3 Empirical model specification 45
3.4 Summary of Chapter 3 47
CHAPTER 4. EMPIRICAL RESEARCH 48
4.1 Data description 48
4.2 Cause and effect analysis 52
4.3 Construction of production frontier model 59
4.4 Modeling of handling capacity 63
4.5 Discussion of results 64
4.5.1 Academic contribution 64
4.5.2 Managerial implication 65
4.5.3 Limitations and further research 66
Conclusion 67
Reference 69
Appendix 73
Relevance of the study
More than 90% of world trade is carried by sea transport. Therefore, ports are the strategic infrastructure facilities and the basis of international trade, they plays a key role in international logistics chains and acts as trade facilitators in the regions and countries.
During the last decades the containerized trade volumes experienced a sharp rise from 224 million TEU in 2000 to 793 million TEU in 2018 because of the ability to containerize different type of goods. It led to the establishment of new container terminals on the main trade routes and as a consequence, increase in the fierce competition for customers with neighborhood terminals.
Aware of that facts, the port authorities showed great interest in effective port management. Thus, they are constantly looking for strategies to meet growing needs through the rational utilization of their current resources. Port efficiency is an indicator of an appropriate port development and right management decisions, and therefore monitoring and comparing one port with other ports in terms of their efficiency has become an integral part of competitive analysis in many countries.
If the container terminals could properly conduct the evaluation of their performance in terms of the track of operational efficiency change in their activities, it would generate valuable information for terminal management for their further steps in the strategy development or in resource utilization.
Managerial problem
Due to the change in the demand for certain type of cargo, there are a decrease in the throughput flow in ports which are dependent on non-container cargo. Therefore, the management faces the tough long-term challenge to increase the throughput flow in these ports with falling demand on the main cargo of the port. One of the possible solution is to re-profiling the port into container terminal, since there is a long-term trend of containerization of goods, and there is also a lack of container handling capacity at current ports in Russia in a short term. Therefore, the relevant task of this study is to define what infrastructure characteristics a terminal should possess in order to be re-profiled.
Research gap
Although many studies have already analyzed the technical efficiency of container terminals using different set of variables and on the various geographical scope, most of them were focused on the general performance analysis of container terminals and horizontal comparison of estimated efficiency scores among selected observations. In addition to that, examined articles are ended up with the identification of the drivers which impact the technical efficiency and no further research was made. After thorough analysis of academic papers, no study has been found that identified the infrastructure variables which influence the handling capacity of the terminal. Therefore, this research is aimed at filling this gap by proposing the infrastructure characteristics which impact the handling capacity of the container terminal. Moreover, the decision support tool for the authorities of container terminals will be proposed which defines the parameters of terminal’s infrastructure characteristics needed for the reaching certain empirical capacity of the terminal.
More than 90% of world trade is carried by sea transport. Therefore, ports are the strategic infrastructure facilities and the basis of international trade, they plays a key role in international logistics chains and acts as trade facilitators in the regions and countries.
During the last decades the containerized trade volumes experienced a sharp rise from 224 million TEU in 2000 to 793 million TEU in 2018 because of the ability to containerize different type of goods. It led to the establishment of new container terminals on the main trade routes and as a consequence, increase in the fierce competition for customers with neighborhood terminals.
Aware of that facts, the port authorities showed great interest in effective port management. Thus, they are constantly looking for strategies to meet growing needs through the rational utilization of their current resources. Port efficiency is an indicator of an appropriate port development and right management decisions, and therefore monitoring and comparing one port with other ports in terms of their efficiency has become an integral part of competitive analysis in many countries.
If the container terminals could properly conduct the evaluation of their performance in terms of the track of operational efficiency change in their activities, it would generate valuable information for terminal management for their further steps in the strategy development or in resource utilization.
Managerial problem
Due to the change in the demand for certain type of cargo, there are a decrease in the throughput flow in ports which are dependent on non-container cargo. Therefore, the management faces the tough long-term challenge to increase the throughput flow in these ports with falling demand on the main cargo of the port. One of the possible solution is to re-profiling the port into container terminal, since there is a long-term trend of containerization of goods, and there is also a lack of container handling capacity at current ports in Russia in a short term. Therefore, the relevant task of this study is to define what infrastructure characteristics a terminal should possess in order to be re-profiled.
Research gap
Although many studies have already analyzed the technical efficiency of container terminals using different set of variables and on the various geographical scope, most of them were focused on the general performance analysis of container terminals and horizontal comparison of estimated efficiency scores among selected observations. In addition to that, examined articles are ended up with the identification of the drivers which impact the technical efficiency and no further research was made. After thorough analysis of academic papers, no study has been found that identified the infrastructure variables which influence the handling capacity of the terminal. Therefore, this research is aimed at filling this gap by proposing the infrastructure characteristics which impact the handling capacity of the container terminal. Moreover, the decision support tool for the authorities of container terminals will be proposed which defines the parameters of terminal’s infrastructure characteristics needed for the reaching certain empirical capacity of the terminal.
Due to the shifts in the demand on the cargo transportation: decrease in non-container cargo and increase in container cargo, container terminals increased their role in the international logistics chains and act as trade facilitators in the regions and countries. However, there is also a lack of container handling capacity at current ports in Russia in a short term. Therefore, terminal managers of non-container ports started to re-profile ports into container terminals, since there is a long-term trend of containerization of goods. Thus, the hot topic for the management is to define what infrastructure characteristics a terminal should possess in order to be re-profiled.
The study was aimed to make a design and application of analytical models for measuring an impact of the infrastructural variables on the container terminals handling capacity. The goal of the master thesis filled out the research gap - the absence of studies on infrastructure variables which influence the handling capacity of the terminal. For this purpose the list of objectives was met on the rolling basis of this work.
At the beginning the concept of container terminal handling capacity was operationalized. In this research we consider handling capacity as the real maximum throughput which can be handled in the terminal accounting for existing practices of serving vessels under realistic operating conditions. Therefore, terminal authorities needs to know real throughput that is lower than the nominal capacity in order to manage terminal’s development.
For the modeling of container terminals handling capacity 17 major container terminals in Russia were taken. Then the sound database was collected. The panel data includes infrastructure characteristics of terminals from the period of 2012-2019.
In this study we provided the causality model of relationship between throughput of the container terminals and their infrastructure variables. For this purpose the infrastructure quality index was proposed that was treated as parameter since the infrastructure characteristics do not change. It comprises normalized data of berth depth, length of the quay, number of cranes and storage area. Such model specification helps to achieve reliable quality of the model.
Then the empirical container handling capacity and technical efficiency rates for selected container terminals were estimated by constructing production frontier with the help of Stochastic Frontier Analysis. These projections are the evidence of current terminals performance. Moreover, on the basis of empirical handling capacities the causal model of relation between technical efficiency of the terminals and the infrastructure variables was constructed. Having reliable model with the good fit we can make forecasts of empirical container terminal handling capacity according to infrastructure characteristics.
As a result of the study, the obtained model can be used as a tool supporting the managerial decisions. For example, there is the evidence that more and more ports are re-profiled to the container terminals due to the containerization tendency and the rising demand for container transportation. For this purpose the management needs to know the potential container terminal handling capacity obtained from the current infrastructure characteristics and the potential level of its utilization in order to make decision about the change of specialization.
Regarding further research, the study can be extended by other factors influencing the container terminal handling capacity such as personnel, services and other qualitative characteristics. Moreover, the scope of the model can be broaden: it can be used for handling capacity projections in non-container terminals and ports or for other related industries such as railway and air transportations.
The study was aimed to make a design and application of analytical models for measuring an impact of the infrastructural variables on the container terminals handling capacity. The goal of the master thesis filled out the research gap - the absence of studies on infrastructure variables which influence the handling capacity of the terminal. For this purpose the list of objectives was met on the rolling basis of this work.
At the beginning the concept of container terminal handling capacity was operationalized. In this research we consider handling capacity as the real maximum throughput which can be handled in the terminal accounting for existing practices of serving vessels under realistic operating conditions. Therefore, terminal authorities needs to know real throughput that is lower than the nominal capacity in order to manage terminal’s development.
For the modeling of container terminals handling capacity 17 major container terminals in Russia were taken. Then the sound database was collected. The panel data includes infrastructure characteristics of terminals from the period of 2012-2019.
In this study we provided the causality model of relationship between throughput of the container terminals and their infrastructure variables. For this purpose the infrastructure quality index was proposed that was treated as parameter since the infrastructure characteristics do not change. It comprises normalized data of berth depth, length of the quay, number of cranes and storage area. Such model specification helps to achieve reliable quality of the model.
Then the empirical container handling capacity and technical efficiency rates for selected container terminals were estimated by constructing production frontier with the help of Stochastic Frontier Analysis. These projections are the evidence of current terminals performance. Moreover, on the basis of empirical handling capacities the causal model of relation between technical efficiency of the terminals and the infrastructure variables was constructed. Having reliable model with the good fit we can make forecasts of empirical container terminal handling capacity according to infrastructure characteristics.
As a result of the study, the obtained model can be used as a tool supporting the managerial decisions. For example, there is the evidence that more and more ports are re-profiled to the container terminals due to the containerization tendency and the rising demand for container transportation. For this purpose the management needs to know the potential container terminal handling capacity obtained from the current infrastructure characteristics and the potential level of its utilization in order to make decision about the change of specialization.
Regarding further research, the study can be extended by other factors influencing the container terminal handling capacity such as personnel, services and other qualitative characteristics. Moreover, the scope of the model can be broaden: it can be used for handling capacity projections in non-container terminals and ports or for other related industries such as railway and air transportations.