This study presents a competitiveness analysis of five strategic container ports in West Africa using the DEA model Windows I-C method. This method takes into account the different changes in these ports efficiency and performance using a window length of 3 over the years 2005 to 2016. The model is used to provide a ranking of the efficient strategic ports in the region. Efficient ports promote trade growth by empowering a country’s imports and exports. The ranking and competitiveness of a port are evaluated based on its efficiency compared to others in its group. From the one output and the sev en input variables selected, the results reveal the port of Tema to be the most competitive in the West Africa with 95% production average efficiency score, then followed respectively by Lagos, Abidjan, Lomé and Cotonou port.
The international trade at the present time, is commonplace and goods are rarely consumed where they are produced. About 90% of international trade is done by sea [
These developing countries’ ports unproductiveness, assessed by global standard, find their origin in inadequate investments and facilities, triggering congestion, long delays and dwell time, thus affecting port competitiveness in terms of import and export prices. In the case of the five West Africa selected ports, they are of high importance as they have international status with much considerable annual container throughput. They are also better positioned in servicing the markets of same landlocked countries namely Burkina Faso, Mali, and Niger. This creates a tense competition in the regional port sector.
This paper therefore aims to examine the relative efficiency and port competitiveness of following strategic sea ports in West Africa, the port of Abidjan, the port of Tema, the port of Cotonou, the port of Lagos and the port of Lomé. These sea gateways are strategic in the sense that they are counted among the regional leading ports and, added to the fact that they compete for the same markets.
The remainder of this study is organized in the following way. Section 2, presents the research theoretical basis on the topic of ports competitiveness. Section 3, introduces the data source and the methodology adopted, then Section 4 presents and discusses the empirical results of the five studied strategic West African container ports. The paper concludes the study in Section 5.
A careful literature review has disclosed numerous aspects that occupies port research involving port competition [
Generally, the competitive position of a container port is determined by its level of differentiation from other competing ports. The port must offer a level of service demanded by port users for specific trade route or within a specific geographic region that outweighs that of its competitors. A situation may exist whereby a particular port may be solely in the position to provide access to a particular hinterland market thereby giving it total monopoly in the market. On the other hand, a situation may also exist whereby many ports within a region may be able to provide access to a common hinterland market thereby creating fierce competition. Port services are thus provided on competitive basis. Due to the competitive nature of the evolving port sector through improvements, etc. [
Emphasizing on both second levels of port competition as individually identified by authors [
The study covers a period of 12 years from 2005 to 2016. The paper selected the 5 strategic countries container ports in the West African region. These container ports are identified as Decision Making Units (DMUs), and are shown in
S/N | Country | Ports Name |
---|---|---|
1 | Cote d’Ivoire | Port of Abidjan |
2 | Benin | Port of Cotonou |
3 | Nigeria | Port of Lagos |
4 | Togo | Port of Lomé |
5 | Ghana | Port of Téma |
Source: Processed by the Author.
Variables | Measurement | |
---|---|---|
Inputs | Quay Length | Total quay length in meters (m) |
Terminal Area | Total size of terminal in hectare (Ha) | |
Quayside Cranes | Total number of quayside cranes | |
Yard Gantry Cranes | Total number of Gantry Cranes | |
Reach Stackers | Total number of Reach Stackers | |
Draught | Depth of Container Terminals (m) | |
Container Throughput Limit | Port Terminal Handling Capacity (TEU) | |
Outputs | Container Throughput | Annual Cargo Throughput (TEU) |
Source: Processed by the Author.
for this study. They practically possess similar operational measures.
The competitive analysis of these ports, is carried out using the DEA Window I-C method. The DEA efficiency ratings can be a useful tool for port managers and for researchers, providing a deeper insight into ports performances [
The research therefore intends to assess the operational efficiencies of the selected DMUs. Seven input variables and one output variable are selected, and the standard container size or TEU is used with regards to the output variable (see
The inputs variables data listed in
The linear programming technique is used to find the set of coefficients (u’s and
v’s) that will give the highest possible efficiency ratio of outputs to inputs for the service unit being evaluated [
DMUj = service unit number j
j = number of decision making units (DMU) being compared in the DEA analysis.
θ = efficiency rating of the decision making unit being evaluated by DEA
yij= amount of output r used by service unit j
xij = amount of input r used by service unit j
i = number of inputs used by the DMUs
r = number of outputs generated by the DMUs
ur = coefficient or weight assigned by DEA to output r
vi = coefficient or weight assigned by DEA to input i
The function is subject to the constraint that when the same set of u and v coefficients is applied to all other service units being compared, no service unit (DMUs) will be more than efficient than 1. Scholars [
D M U j = u 1 y 1 j + u 2 y 2 j + ⋯ + u r y r j v 1 x 1 j + v 2 x 2 j + ⋯ + v i x i j = ∑ r = 1 s u r y r j ∑ i = 1 m v i x i j ≤ 1 , j = 1 , ⋯ , n (1)
u r , ⋯ , u s > 0 and v i , ⋯ , v m ≥ 0 ; r = 1 , ⋯ , s ; i = 1 , ⋯ , m
To solve the fractional mathematical programming problem, Equation (1) has been transformed into a linear programming model written below:
max ∑ r = 1 S u r y r o S .t . ∑ r = 1 S u r y r j − ∑ i = 1 m v i x i j ≤ 0 , j = 1 , ⋯ , n ∑ i = 1 m v i x i 0 = 1 u r , v i ≥ 0 (2)
As earlier mentioned, the DEA model Windows I-C gives an efficiency value close to one, which can be expressed in percentage in order to provide accordingly a ranking among the competitive ports by highlighting the most efficient ones.
The characteristics of the variables used to estimate the relative competitiveness of the selected ports are presented in
Based on the graph in
Statistics | Inputs | Output | ||||||
---|---|---|---|---|---|---|---|---|
Quay Length (m) | Terminal Area (Ha) | Quayside Cranes | Yard Gantry Cranes | Reach Stackers | Draught (m) | Annual Container Throughput Limit (TEU) | Container Throughput (TEU) | |
Max | 1752 | 42 | 14 | 16 | 23 | 14.5 | 2,000,000 | 1,335,470 |
Min | 575 | 14 | 6 | 10 | 14 | 11.5 | 700,000 | 333,000 |
Mean | 1027.4 | 25.4 | 9.4 | 13 | 17 | 12.5 | 1,280,000 | 824,214.6 |
St. Dev. | 435.080 | 11.092 | 3.072 | 2 | 3.162 | 1.265 | 444,522.215 | 324,729.291 |
Source: Processed by the Author.
noticeable sharp decrease of throughput from 2008 to 2009 of about 25%, and 2012 to 2013 of about 38%. 2012 marks its highest throughput with 1.62 Million TEUs throughout the study period. All other 4 ports showed less variation throughout the study period, with the Port of Lomé marking a sharp throughput growth of 138% from 2014 to 2015. This upsurge is explained by the Lomé Container Terminal (LCT), a terminal dedicated to container transhipment, which entered officially into operation in 2014. The ports of Abidjan, Cotonou and Lomé saw a reduction of throughput from 2015 to 2016 contrary to the other two ports of the study. The port of Tema saw a constant increase in term of throughput over time.
From the analysis in
2005 | 2006 | 2007 | 2008 | 2009 | 2010 | 2011 | 2012 | 2013 | 2014 | 2015 | 2016 | Average | C-Average | |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Port of Abidjan | 1 | 0.7143 | 0.6610 | 0.7917 | ||||||||||
0.7774 | 0.7194 | 1 | 0.8322 | |||||||||||
0.7194 | 1 | 0.9354 | 0.8849 | |||||||||||
0.9252 | 0.8654 | 0.7964 | 0.8623 | |||||||||||
0.6908 | 0.6357 | 0.6186 | 0.6484 | |||||||||||
0.6357 | 0.6186 | 0.5367 | 0.5970 | |||||||||||
0.6186 | 0.5367 | 0.6308 | 0.5954 | |||||||||||
0.6695 | 0.7869 | 0.8271 | 0.7612 | |||||||||||
0.9515 | 1 | 1 | 0.9838 | |||||||||||
0.9567 | 1 | 0.8440 | 0.9336 | 0.7891 | ||||||||||
Port of Cotonou | 0.5009 | 0.4599 | 0.5169 | 0.4926 | ||||||||||
0.4553 | 0.5118 | 0.6074 | 0.5248 | |||||||||||
0.5046 | 0.5989 | 0.8433 | 0.6489 | |||||||||||
0.5335 | 0.7512 | 0.8722 | 0.7190 | |||||||||||
0.5857 | 0.6800 | 0.7188 | 0.6615 | |||||||||||
0.6800 | 0.7188 | 0.4563 | 0.6184 | |||||||||||
0.7188 | 0.4554 | 0.5079 | 0.5607 | |||||||||||
0.6219 | 0.6936 | 0.7290 | 0.6815 | |||||||||||
0.7263 | 0.7633 | 0.8830 | 0.7909 | |||||||||||
0.7230 | 0.8364 | 0.5899 | 0.7164 | 0.6415 | ||||||||||
Port of Lagos | 0.9629 | 0.9684 | 1 | 0.9771 | ||||||||||
0.9236 | 0.9537 | 1 | 0.9591 | |||||||||||
0.9537 | 1 | 0.7503 | 0.9013 | |||||||||||
0.8398 | 0.6300 | 1 | 0.8233 | |||||||||||
0.5029 | 0.7983 | 1 | 0.7671 | |||||||||||
0.7983 | 1 | 1 | 0.9328 | |||||||||||
1 | 1 | 0.6228 | 0.8743 | |||||||||||
1 | 0.6228 | 0.6545 | 0.7591 | |||||||||||
0.8742 | 0.9188 | 1 | 0.9310 | |||||||||||
0.7955 | 0.8658 | 1 | 0.8871 | 0.8812 | ||||||||||
Port of Lome | 0.5947 | 0.6275 | 0.6914 | 0.6379 | ||||||||||
0.6188 | 0.6818 | 0.8487 | 0.7164 | |||||||||||
0.6711 | 0.8353 | 1 | 0.8355 | |||||||||||
0.7417 | 0.8879 | 0.8513 | 0.8270 | |||||||||||
0.6941 | 0.6655 | 0.6907 | 0.6834 | |||||||||||
0.6655 | 0.6907 | 0.4504 | 0.6022 |
0.6907 | 0.4504 | 0.4863 | 0.5425 | |||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
0.6463 | 0.6978 | 0.8531 | 0.7324 | |||||||||||
0.7154 | 0.7644 | 1 | 0.8266 | |||||||||||
0.7644 | 1 | 0.9072 | 0.8905 | 0.7294 | ||||||||||
Port of Tema | 0.8614 | 0.9284 | 1 | 0.9299 | ||||||||||
0.9192 | 0.9901 | 1 | 0.9698 | |||||||||||
0.9762 | 0.9860 | 1 | 0.9874 | |||||||||||
0.8783 | 0.8908 | 1 | 0.9230 | |||||||||||
0.6945 | 0.7797 | 1 | 0.8247 | |||||||||||
0.7797 | 1 | 1 | 0.9266 | |||||||||||
1 | 0.9789 | 1 | 0.9930 | |||||||||||
0.9789 | 1 | 0.9902 | 0.9897 | |||||||||||
0.9826 | 0.9730 | 1 | 0.9852 | |||||||||||
0.9004 | 0.9254 | 1 | 0.9420 | 0.9471 | ||||||||||
Average | 0.7840 | 0.7393 | 0.7701 | 0.8530 | 0.7815 | 0.7759 | 0.8056 | 0.7188 | 0.7533 | 0.8409 | 0.9511 | 0.8682 |
Source: Processed by the Author.
88% and 79% respectively. However, the port of Lomé despite its advantages in terms of quay length, quayside cranes, reach stackers and draught, scored a lower average efficiency of 73%; and bringing up the rear, the port of Cotonou which showed the lowest performance with an average efficiency score of 64%.
The port of Lagos remains the second largest after the Port of Lomé, in term of size and the first in term of throughput with over 1 million TEU’s. Nevertheless, the analysis denotes throughout time the port of Tema (95%) as the most efficient port among the selected DMUs (see
Ports play a critical role in economies of many nations, and the countries in the West African region are not excluded. The five selected West African ports of this study are of high importance as they have an international status with much considerable container throughput. They are also servicing markets of same landlocked countries namely Burkina Faso, Mali, and Niger. Hence, leading to a fierce port competitiveness in the region. For the purpose of the competitiveness study, this research involved the use of a model and methodology to attain rigorous and reliable results. In this regard, the Data Envelopment Analysis (DEA) model was used to evaluate the efficiency and competitiveness of these five strategic ports’ region.
The West African port landscape has evolved rapidly since the turn of the
century despite a slow start in adjusting to the requirements of modern shipping liners and containerized trade. Out of the twelve West Africa ports, the present study measured the relative efficiency and competitiveness of five major commercial ports (Abidjan, Cotonou, Lagos, Lomé and Tema). The selection of these ports was in relation to their proximity to the Port of Lomé.
For the purpose of the competitiveness comparative study between these strategic West African ports, the research made use of the Data Envelopment Analysis (DEA), a technique used in port sector. Seven inputs variables were used, annual container throughput limit, draught, reach stackers, yard gantry cranes, quayside cranes, terminal area and quay length, with one output variable container throughput. Based on the DEA model results, the study showed the port of Tema to be the most efficient despite being the smallest port among the ports under study. It was followed by Lagos the first in the region in term of throughput, then the port of Abidjan. The port of Lomé came in the fourth position despite being the largest in terms of size among the studied ports, while the port of Cotonou occupied the last position.
The author declares no conflicts of interest regarding the publication of this paper.
Kalgora, B. (2019) Strategic Container Ports Competitiveness Analysis in West Africa Using Data Envelopment Analysis (DEA) Model. Open Journal of Business and Management, 7, 680-692. https://doi.org/10.4236/ojbm.2019.72046
Source: Port Management Association of West & Central Africa (2017).
Appendix 2: Container Throughput for Selected Countries Ports from Year 2005-2016Source: Container Port traffic, World Bank, (2017).