By Ndubuisi,
KE; Ndikom, OB; Nze, I; Nwokedi, TC (2024).
|
Greener
Journal of Business and Management Studies Vol. 12(1),
pp. 30-37, 2024 ISSN:
2276-7827 Copyright
©2024, Creative Commons Attribution 4.0 International. |
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Performance
Evaluation of Public and Private Marine Terminals in Nigeria under Fuel
Subsidy Regimes.
Kenneth Ezebunwa Ndubuisi 1; Obed
B. Ndikom 2; Ibeawuchi Nze 3; Theophilus Chinonyerem
Nwokedi 4
1. Department of Maritime Management Technology, Federal University of
Technology Owerri, Imo State, Nigeria.
2. Department of Maritime Management Technology, Federal University of
Technology Owerri, Imo State, Nigeria.
3. Department of Maritime Management Technology, Federal University of
Technology Owerri, Imo State, Nigeria.
4.
Department of Maritime Management Technology,
Federal University of Technology Owerri, Imo State, Nigeria.
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ARTICLE INFO |
ABSTRACT |
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Article No.: 022324027 Type: Research |
Fuel scarcity has remained persistent in
the Nigeria polity even as a net exporter of petroleum. This challenge has
been subjected to various policy reforms by different administration to curb
the menace in Nigeria as both privately and publicly managed marine terminal
operators are constantly retooling to mitigate fuel scarcity and implement
the fuel subsidy reforms of government. The aim of this study is to evaluate
and compare the relative performance of 3 publicly and 3 privately managed
marine terminals in the execution of RPEA and DSDP reforms of government
over the period of 2012 to 2020. Data Envelopmental analysis model was
adopted to analyse their relative efficiencies over time. The result
revealed that the 3 publicly managed maritime terminals were efficient once
respectively under OPA/RPEA (Jonathan’s tenure) while the publicly-managed
maritime terminals were efficient both during OPA/RPEA (Jonathan’s tenure)
and DSDP (Buhari’s tenure). The study shows that the privately managed
marine terminals performed more efficiently in the process of fuel
availability in Nigeria. |
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Accepted: 29/02/2024 Published: 13/03/2024 |
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*Corresponding
Author Kenneth Ezebunwa
Ndubuisi E-mail: kennambrose@ yahoo.com |
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Keywords: |
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The policy implementation exercise of the Nigeria
government is often adjudged cumbersome and subject to bureaucratic nuances. This
has made the operational efficiency of such policies implementation by
government agencies subject to serious questioning. The administration and
policy direction of the petroleum and energy sectors in Nigeria have been piloted
by successive governments without cogent improvement in the area of mitigating
the challenge of perennial fuel scarcity and fuel price hike in Nigeria. The
fuel subsidy scheme has remained a hot conduit of corruption since the 1970s.
It has remained a lucrative scheme for successive administrations because of
its socio political and economic importance to the country.
However, the
argument amongst the professionals concerning the efficient implementation of
government policies is said to be best left in the hands of the private sector
but subject to monitoring and regulation by the public sector. Since the advent
of the fuel subsidy regimes, it is observed that both private and public sector
petroleum marketing firms are involved in the supply and distribution of petrol
in Nigeria. Petroleum industry is a capital intensive, highly volatile and
competitive industry that operates with the objective of continuous improvement
of the supply chain for the purposes of sales and profit maximisation.
The policy reforms
and strong control of the petroleum sector have compelled the operators to
efficiently strive in the implementation of these government policies since the
industry is subject to price fluctuations.
In this study, there is the need to
empirically establish the performance of publicly managed marine terminals and
the privately managed marine terminals in the implementation of the fuel supply
and distribution drive of government under the fuel subsidy reforms in Nigeria.
Hence, the study
tends to evaluate and compare the relative performance of 3 publicly-managed marine
terminals and 3 privately-managed marine terminal within the same geographical
location to ascertain how efficiently they have implemented the supply and
distribution of petrol in Nigeria.
Given, the unique
petrol supply system as practiced in Nigeria, the marine terminals and ports
have enjoyed a pride of place in the supply and distribution of petrol in
Nigeria. The pride of place is as a result of the gross infrastructural decays
of the standard fuel distribution networks hence causing the overburdening of
nodes of transportation system such as vessels, marine terminals /ports, tank
farms, Bulk Road Vehicles, etc. which have led to huge patronage and its
associated costs such as transactional costs, delays, externalities costs etc. which
finally translates to the cost of petrol in Nigeria. For instance, the
patronage of foreign long range and medium range vessels for the transportation
of petroleum, patronage of tank farms, liquid bulk jetties and Bulk Road
Vehicles remains good examples for pollution. The husbandry of poorly
maintained and usage of poor-quality equipment and crafts in the distribution
of petrol, basically because of poor enforcement of standards on the
transportation system is the order of the day as the demand for transportation
system and its attendant revenue generation is so huge that maintenance culture
as stipulated by the international organizations is ill executed or not
executed at all due to transactional profits and poor regulatory enforcement in
Nigeria.
The petrol price
hike and the perennial fuel scarcity have elicited public outcry on the
authenticity of the payment of fuel subsidy claims, while also querying the
effect of marine terminal operator’s contributions to the persistent fuel
scarcity and price hike in Nigeria.
The study is geared
towards empirically exposing the better performing group of marine terminals
saddled with the supply and distribution of petrol from the Niger delta region
of Nigeria. Hence the evaluation of the relative efficiency of 6 marine
terminals comprising 3 privately managed and 3 publicly managed, operational in
the Niger delta region of Nigeria.
The concept of Performance
is fundamental to every business, for the sake of measurement of internal
performance or progress and also to monitor the performance of the competitors
and also business regulators. Performance internal interest is also to measure
achievements against set goals and objectives. Seaports are complex businesses
with huge investments as inputs resources with expected benefits as output
resources which should be proven to give return on investment for purposes of
sustainable development. To evaluate the benefits after such investment in seaports
is termed performance measurement. However, the evaluation of these systems –
marine terminal operations compels stakeholders and policy makers to take
decisions to increase productivity or efficiency. This has led to academic
interest in seaport performance measures.
Hence, this paper will assess the relative efficiencies of the six
marine terminals from 2012 to 2020 using the Data Envelopment Analysis (DEA).
The result of this research will aid the policy makers, investors and port
operators on the different ways to improve system efficiency while also
increasing system patronage as individual elements or as a total system. This article
is categorized into 4 sections: section 1 is the Introduction, Review of
Literature, section 2 is Methodology and Data Presentation, section 3 Results
and Discussion of Findings and section 4 is Conclusions and Recommendation.
Background
Information
Maritime transportation as a major channel of international trade has
been subjected to deliberate efforts to improving the efficiency of the sector.
The maritime industry is a vital and strategic sector in every country’s
economy. According to UNCTAD (2009), international sea borne trade, from 1980
to 2008 witnessed an increase of over 120%.
According to Umang et al. (2011), this increase was possible due to the
steady growth in world population, rapid industrialization, and the depletion
of local resources, road congestion, increase in the need for better living
standard and elimination of trade barriers. He also claimed that since the
beginning of the decade, dry bulk, liquid bulk and containerized cargo have
registered an impressive tonnage increase of 52%, 48% and 154% respectively. In
this period of high globalized production and consumption driven by increase in
world population with limited available resources, there is a growing need for
efficient and productive supply chain management which cannot be, without the
high efficiency of seaports-marine terminals that serves as the interface
between the marine and hinterland leagues.
The fluidity of movement of goods and services within region aids
increase in socio-economic development of such region. This is made possible
based on the performance of the seaports. According to Emeghara and Ndikom
(2012) they reiterated that ship and port relationship is like that of a
master/servant relationship. A port is
likened to be an enterprise established to provide quality service to her
masters/customers to survive economically. This is because shippers as well as
ship owners demand efficient service from port operators for continual
patronage. Nigeria is endowed with marine domain with estuaries hosting
harbors, ports and jetties. However, it is vital to note that the deliberate
distribution of vessel traffic in accordance to final consumer’s location
reduces acute traffic congestions in some ports. Considerably, the importance
of ports in the economic life of any nation cannot be over emphasized. According to former Managing Director NPA Hadiza Bala
Usman in her opening remark in NPA as reported in (NPA handbook 2018/2019), she
posits that the critical role of the port in national economic and social
development derives from its significance as the cheapest mode of moving large
cargoes from one point to the other. This assertion is not for liquid bulk that
is actually supposed to enjoy the cheapest and fastest transportation mode of
pipeline transportation in the deliveries of petroleum products. The lack of
the functionality of the pipeline transport in Nigeria have led to the increase
in demand for port services by vessels which includes tanker vessels, BRVs,
etc. hence, this condition has made these ports and marine terminals operate as
cartels with little or no competition within the Nigerian geographical space. The
lack of tangible, convincing and concerted effort of the Nigerian government to
repair the pipelines, the refineries and mitigate the fuel scarcity and price
hike have also emboldened the grip of the petrol supply chain operators on
Nigerian without recurse to ameliorating the price hike of the product.
The study will
attempt to appraise the relative performance of 6 marine terminals for refined
petroleum, comprising of 3 government managed and 3 privately managed marine
terminals in Nigeria subject to the fuel subsidy reforms under the
administrations of former presidents Goodluck Jonathan and Muhammadu Buhari.
According
to Adetayo Olaniyi Adeniran (2018), fuel is a major factor amongst other factor
that affects or influences the costs of transportation and its rate in Nigeria
which also translates to the cost of goods and services.
The
policy factor of government on the fuel consumption through fuel subsidy
reforms is also a veritable factor that could impact transport system’s
economic performance. The execution of these reforms was for the purposes of
providing consistent fuel to the low-income earners in all nooks and crannies
of Nigeria. This policy has strategically made the port a key custodian of the
distribution process of petrol in Nigeria because they oversee the husbandry of
all vessels calling into Nigerian ports while also generating revenue through
port charges to government from this exercise. Adetayo Olaniyi Adeniran (2018),
further buttresses the assertion that fuel subsidy is a factor that affect
transportation costs and its rates which serves as a derived demand for ports
services. According to Adeniran and Yusuf 2016) the port is one of the
important elements in transportation system amongst other elements such as
infrastructure, vehicles, terminals and operations. The marine terminals/ports
as a node of interest in the execution of the distribution of the subsidized
fuel in this study cannot be over emphasized. The port factor is a very vital
cost factor that influences the cost of goods and services in Nigeria.
According
to Jean, Claude and Brian (2006), transportation costs are monetary measures of
both fixed and variable costs of the transport provider expended in the
provisions of transportation services to a person or organization.
They
went further to explain transportation rate as the price paid by the transport
user for the transportation services rendered to such individual or firm. This
is actually the price paid for the conveyance of passenger and or goods to an
agreed destination at a particular time. These rates are actually influenced by
transportation cost as influenced by location/geography, type of product
conveyed, economies of scale or carrying capacity of the craft in use, fuel for
equipment or transport modes, infrastructure conditions, and trade imbalance.
Therefore, fuel subsidy is actually supposed to impact on the costs and fares
for transportation of which the port and marine terminals are part of the
system. (Adetayo Olaniyi Adeniran 2018)
There is
availability of Port performance and operational efficiency studies on ports
vis -a-viz marine terminal operations and there are also researches that
measure efficiency of ports or marine terminal operations using Data Envelopmental
Analysis DEA (Chansu Lim, Jongsu Lee (2020); Brooks, M.R., Schelinck, T. and
Pallis, A.A. (2011); Magdiel A. Agüero-Tobar, Marcela
C. González-Araya, Rosa G. González-Ramírez (2022) Snezana Radukic, Milan Veselinovic, and Ivana Marjanovic (2023)). For the
Nigerian seaport efficiency evaluation, extensive studies have been conducted
using DEA and other analytical models Nze, Obiageli N. et. al (2021); Kenneth
E. Ndubuisi and Nwoloziri Chinyeaka Nwokodi (2020); Geraldine Okeudo (2015);
Nwanosike, F., Tipi, N.S. and Warnock- Smith, D. (2012), Donatus E.
Onwuegbuchunam et al (2020); Ugboma Ogochukwu and Oyesiku Kayode (2021) etc.
However this study
is centered in the evaluation of marine terminals performance in Nigeria
subject to fuel subsidy reforms. It is geared towards unveiling the performance
contribution of the marine terminal operators in the supply and distribution of
petrol thereby striving to ameliorate fuel scarcity challenge. It will reveal
the comparative performances of the publicly managed marine terminals and the
privately managed marine terminals during the fuel subsidy reform periods under
consideration.
Data for this study were all secondary data gotten
from the individual marine terminals, government agencies like NPA, NMDPRA, etc
under study in Nigeria. In this study the marine terminals names were all
codenamed. The dataset covers the period of 9 years. The data were collated and
analysed for the benefit using DEA.
Data Envelopment
Analysis (DEA)
Data Envelopment
Analysis (DEA) is increasingly one of the popular tools to measure performance
for transit firms with multiple variables. DEA reduces complex and
multi-objective problem of performance measurement to a single number. Here,
DEA is applied in a transit system -the marine terminal which is major supply
chain infrastructure.
Data Envelopment
Analysis is a non-parametric model for measuring the efficiency of
Decision-Making Units (DMU) with multiple inputs and or multiple outputs.
Charnes et al., (1978) first introduced the DEA as a multi-factor productivity
analysis module for measuring the relative efficiencies of DMUs. The DEA
analysis shows how inputs and output have to be changed in order to maximize
the efficiency levels of the target DMU. DEA is used in this study because of
its suitability in analyzing supply chain performance of marine terminal
operations and their improvement. The proposed model involves the following
problem of linear programming.
Input-oriented Primal (BCCp-I)
Min Zo=Ө-є.1μ s+- є.1μ
s-
Ө, λ, s+, s-,
s.t. Yλ - s+
ӨXo - Xλ-s+
1μ λ≥1
λ, s+, s-≥ 0
Input-Oriented BCC Dual (BCCd-I)
Max Wo = μTҮo + ụo
μ,v
s.t. VTXo = 1
μTY - VTX + ụo 1μ ≤ 0
- μT
≤ - є.1μ
- VT≤
- є.1μ
DEA as developed by Charnes et al., (1978) explain
that suppose we have a set of n peers DMUs which produces multiple output
vector Y by using observed multiple input vector X respectively.
Where,
X= input vector used in the DMUs.
Y= output vector produced by DMUs.
Є=is a constant non- Archimedean
(infinitesimal of the order of 10-6) that ensures no input or output is given a
zero weight
s+ and s- are the slack vectors for output and input
respectively
Ө=represents the proportional reduction of the
input in relation to the amount of the projected input. The optimal value of
λ forms a composite unit outperforming the DMU under analysis and
providing targets for this DMU to identify sources of its inefficiency. This
model is known as input-oriented BCC, the initial being in recognition of its
formulators ( Banker et al 1984)
Then the production possibility set will be defined
as follows in relation to this study:
Thus:
F = {(Y, X)/X
can produce Y}
(As cited by Po- Kyung and Prabir De 2004)
Where in this study:
n = B-Terminal,
POTerminal, NCTerminal, NoWTerminal, WTerminal and ROTerminal.
Y= Official
Pump Price, Daily Swap Import, Number of Supply Vendors, Port Channel Approach
draft, Port/Jetty Draft, Berth Distance from FWB, Ship Max Length Overall,
Shore Tank Capacity, Annual Subsidy Payment.
X= Berth Rent, Bulk Road Vehicle Traffic, Cargo
Dues, Cargo Throughput, Environmental Protection Levy, Fire Coverage, Ship
Dues, Ship GRT, Ship Traffic, Value Added Tax,
They were collated from the boarding team records,
terminal records, and shipping agents’ records. These parameters include vessel
calls, cargo throughputs, BRVs calls, cargo dues, ship dues, environmental
protection levy, fire coverage, GRT- Ship size, VAT, Berth rent, etc. all
associated with ship- cargo marine terminal operations as supervised by NPA.
Other secondary data gotten from relevant literature were official petrol pump
price, annual subsidy payment, number of supply vendors (oil exporters), and
Direct swap imports (quantity consumed) as cited in price gap approach -(Koplow
2009; Foo, N., H. H. Lean, and R. Salim. 2020), International Energy Agency
(IEA), International Institute for Sustainable Development (IISD), PWC reports.
Defined government sources in Nigeria and various websites disclosed some
specific information regarding official petrol pump prices, and number of
supply vendors, annual subsidy payment and daily swap import (quantity
consumed). Other parameters adopted for this study were suggested from literature
reviews of materials on data envelopmental analysis applications in port
efficiency studies, NPA Tariff yearbook and the world port tariff- port pricing
UNCTAD 1975
According to Cooper
et al (2004), the performance of a DMU is efficient if and only if it is not
possible to improve any input or output without worsening any other input or
output, while the performance of a DMU is inefficient if and only if it is
possible to improve some input or output without worsening some other input and
output. (Pareto-Koopmans Definition of Efficiency)
Hence, DEA model is
a linear programming model applied on the input-output variables to empirically
or quantitatively estimate the technical and scale efficiency of the refined
petroleum oil terminal jetties. These will determine the level of inefficiency
plus the input/output slack that would have been needed to perfect or improve
the systems efficiency.
The research has a
restricted study population because of the nature of the industry studied and
also the scope of the study. The study population is basically the boarding
team of tanker vessels which consists of Cargo inspectors, Shipping agents,
Department of Petroleum Resources (DPR) staff, Petroleum Product Pricing
Regulatory Agency (PPPRA) staff, Nigerian Ports Authority (NPA)Traffic and
marketing department staff, Terminal Loading master, Company Shipping manager
and Supply and Distribution manager.
The data analysis
is applied to the six (6) selected marine terminal operators in the Niger Delta
region of Nigeria namely: B-Terminal, POTerminal, NCTerminal, NoWTerminal, WTerminal
and ROTerminal. These marine terminals were selected basically because they
have been in cargo operations under different subsidy regimes and governments.
These terminals have been in cargo operations on or before 2012 and are still
operational till date. The selected terminals are operational in 3 out of the 4
Nigerian ports authority pilotage districts of Nigeria.
Table 1. Technical Efficiencies result of the selected Marine Terminals from
2012-2020 using DEA under Output
Oriented Model
|
DMU Name |
TEvrs |
RTS |
Inputs Slack |
||||||||
|
NSV |
DSI |
OPP |
JD |
PCA |
PDF |
STC |
MLOA |
ASP |
|||
|
BJ2012 |
0.77 |
DRS |
1.6 |
67165.2 |
20.2 |
1.7 |
2.6 |
11.3 |
29289100.3 |
43.0 |
2.0 |
|
BJ2013 |
1.00 |
CRS |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
|
BJ2014 |
0.97 |
IRC |
0.2 |
8234.5 |
2.2 |
0.2 |
0.3 |
1.2 |
3142342.0 |
4.6 |
0.2 |
|
BJ2015 |
0.60 |
DRS |
1.2 |
178470.3 |
34.8 |
2.9 |
4.5 |
19.4 |
50501835.4 |
74.1 |
1.4 |
|
BJ2016 |
0.53 |
DRS |
12.6 |
199400.3 |
67.6 |
3.4 |
5.1 |
22.4 |
58138228.4 |
85.3 |
0.4 |
|
BJ2017 |
1.00 |
CRS |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
|
BJ2018 |
0.52 |
DRS |
16.2 |
210615.6 |
69.1 |
3.4 |
5.2 |
22.9 |
59463171.3 |
87.2 |
1.9 |
|
BJ2019 |
0.69 |
DRS |
11.2 |
152810.2 |
58.1 |
2.2 |
3.4 |
15.0 |
38996288.5 |
57.2 |
1.6 |
|
BJ2020 |
1.00 |
CRS |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
|
PJ2012 |
1.00 |
CRS |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
|
PJ2013 |
0.51 |
DRS |
3.4 |
143226.4 |
41.9 |
4.5 |
5.4 |
23.4 |
427080867.6 |
89.1 |
4.0 |
|
PJ2014 |
0.78 |
DRS |
1.5 |
71849.4 |
18.9 |
2.0 |
2.4 |
10.5 |
192680086.5 |
40.2 |
1.6 |
|
PJ2015 |
0.66 |
DRS |
1.0 |
151906.5 |
29.6 |
3.2 |
3.8 |
16.5 |
302073548.1 |
63.0 |
1.2 |
|
PJ2016 |
0.31 |
DRS |
18.5 |
293561.3 |
99.5 |
6.3 |
7.5 |
32.9 |
601491945.8 |
125.5 |
0.6 |
|
PJ2017 |
0.22 |
DRS |
30.3 |
303637.0 |
112.6 |
7.1 |
8.5 |
37.3 |
681008852.1 |
142.1 |
0.4 |
|
PJ2018 |
0.63 |
DRS |
12.4 |
161671.9 |
53.0 |
3.4 |
4.0 |
17.6 |
320765027.0 |
66.9 |
1.4 |
|
PJ2019 |
0.53 |
DRS |
16.9 |
229234.0 |
87.2 |
4.3 |
5.2 |
22.5 |
411097673.3 |
85.8 |
2.4 |
|
PJ2020 |
0.47 |
DRS |
18.6 |
266059.5 |
99.0 |
4.9 |
5.9 |
25.5 |
466581107.2 |
97.4 |
0.5 |
|
NWJ2012 |
0.60 |
DRS |
2.8 |
113240.6 |
34.0 |
2.8 |
2.5 |
19.8 |
17094951.1 |
73.6 |
3.4 |
|
NWJ2013 |
0.78 |
DRS |
1.6 |
65187.8 |
19.1 |
1.6 |
1.4 |
11.1 |
9575525.4 |
41.2 |
1.8 |
|
NWJ2014 |
1.00 |
CRS |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
|
NWJ2015 |
1.00 |
CRS |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
|
NWJ2016 |
1.00 |
CRS |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
|
NWJ2017 |
1.00 |
CRS |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
|
NWJ2018 |
0.75 |
DRS |
8.5 |
110663.7 |
36.3 |
1.8 |
1.6 |
12.5 |
10815996.5 |
46.6 |
1.0 |
|
NWJ2019 |
0.83 |
DRS |
6.3 |
85401.9 |
32.5 |
1.2 |
1.1 |
8.7 |
7544704.2 |
32.5 |
0.9 |
|
NWJ2020 |
1.00 |
CRS |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
|
NJ2012 |
0.58 |
DRS |
3.0 |
121271.7 |
36.4 |
2.8 |
2.7 |
21.2 |
22246829.7 |
65.7 |
3.6 |
|
NJ2013 |
0.40 |
DRS |
4.2 |
175036.4 |
51.2 |
3.9 |
3.8 |
29.8 |
31244077.8 |
92.3 |
4.9 |
|
NJ2014 |
1.00 |
CRS |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
|
NJ2015 |
0.44 |
DRS |
1.7 |
246249.1 |
48.0 |
3.6 |
3.6 |
27.9 |
29313184.8 |
86.6 |
1.9 |
Table 1 cont:
Technical Efficiencies of the
selected Marine Terminals from 2012-2020 DEA under Output Oriented Constant Return to Scale Model
|
DMU Name |
TEvrs |
RTS |
Input Slacks |
||||||||
|
NSV |
DSI |
OPP |
JD |
PCA |
PDF |
STC |
MLOA |
ASP |
|||
|
NJ2016 |
0.21 |
DRS |
21.4 |
338984.9 |
114.8 |
5.1 |
5.1 |
39.6 |
41577990.4 |
122.8 |
0.7 |
|
NJ2017 |
0.20 |
DRS |
31.1 |
311421.6 |
115.5 |
5.2 |
5.1 |
39.8 |
41811796.9 |
123.5 |
0.4 |
|
NJ2018 |
0.26 |
DRS |
25.3 |
329181.4 |
108.0 |
4.8 |
4.8 |
37.2 |
39096682.4 |
115.4 |
2.9 |
|
NJ2019 |
0.37 |
DRS |
22.8 |
309770.0 |
117.8 |
4.1 |
4.1 |
31.7 |
33255030.9 |
98.2 |
3.2 |
|
NJ2020 |
0.29 |
DRS |
24.9 |
355949.2 |
132.4 |
4.6 |
4.6 |
35.6 |
37367013.7 |
110.3 |
0.7 |
|
RJ2012 |
1.00 |
CRS |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
|
RJ2013 |
1.00 |
CRS |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
|
RJ2014 |
0.96 |
IRS |
0.3 |
12661.0 |
3.3 |
0.3 |
0.2 |
2.0 |
1897607.9 |
7.1 |
0.3 |
|
RJ2015 |
1.00 |
CRS |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
|
RJ2016 |
1.00 |
CRS |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
|
RJ2017 |
1.00 |
CRS |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
|
RJ2018 |
0.73 |
DRS |
9.1 |
118302.9 |
38.8 |
1.8 |
1.6 |
13.9 |
13118108.5 |
49.0 |
1.0 |
|
RJ2019 |
0.77 |
DRS |
8.2 |
111705.6 |
42.5 |
1.5 |
1.3 |
11.9 |
11196033.1 |
41.8 |
1.2 |
|
RJ2020 |
0.84 |
DRS |
5.5 |
79270.3 |
29.5 |
1.1 |
0.9 |
8.2 |
7769305.5 |
29.0 |
0.2 |
|
WJ2012 |
0.41 |
DRS |
4.1 |
168594.2 |
50.7 |
5.9 |
3.5 |
30.6 |
110435815.1 |
107.8 |
5.0 |
|
WJ2013 |
0.12 |
DRS |
6.1 |
258101.5 |
75.5 |
8.8 |
5.2 |
45.6 |
164508513.7 |
160.6 |
7.3 |
|
WJ2014 |
0.32 |
DRS |
4.8 |
223915.9 |
58.9 |
6.8 |
4.0 |
35.6 |
128353958.1 |
125.3 |
5.0 |
|
WJ2015 |
0.59 |
DRS |
1.2 |
181549.9 |
35.4 |
4.1 |
2.4 |
21.4 |
77169007.4 |
75.3 |
1.4 |
|
WJ2016 |
1.00 |
CRS |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
|
WJ2017 |
0.05 |
DRS |
37.0 |
370449.5 |
137.4 |
9.5 |
5.6 |
49.3 |
177597824.8 |
173.4 |
0.4 |
|
WJ2018 |
0.13 |
DRS |
29.7 |
385834.5 |
126.6 |
8.7 |
5.2 |
45.4 |
163630469.8 |
159.7 |
3.4 |
|
WJ2019 |
0.22 |
DRS |
28.1 |
381454.0 |
145.1 |
7.8 |
4.6 |
40.6 |
146224050.3 |
142.8 |
4.0 |
|
WJ2020 |
0.28 |
DRS |
25.2 |
360374.9 |
134.0 |
7.2 |
4.3 |
37.5 |
135086972.8 |
131.9 |
0.7 |
Table 1 shows the DEA under Output
Oriented Constant Return to Scale Model results on the technical efficiencies of the selected Marine Terminals for
the years under consideration.
The result
discloses that there is constant return to scale in 2012 for POTerminal, in
2014 for NCTerminal and in 2016 for WTerminals. It also showed constant return
to scale in 2013, 2017 and 2020 for BTerminals. The result further revealed
constant return to scale for NoWTerminal in 2014, 2015, 2016, 2017 and 2020.
RTerminal, in 2012, 2013, 2015, 2016 and 2017.
The
study is on the Performance Evaluation
of Public and Private Marine Terminals in Nigeria under
fuel subsidy regimes. In executing this study, data were gotten from NPA,
NMDPRA, etc. DEA was adopted in the analysis of the data. It was empirically
inferred that there was a total of 16 efficiencies within the 9 years under
review.
A closer look
however, shows that each of the 3 publicly managed terminals was efficient ones
during the study period under review. This was mainly during the RPEA reform
time of the administration of former President Goodluck Jonathan. A more
cursory look at the result, further disclosed that the 3 privately managed
marine terminals had more efficient performances than the publicly managed
marine terminals within the same years under consideration. The privately
managed marine terminals had a total of 13 efficient performances which covered
the periods of RPEA and DSDP reforms of both Jonathan and Buhari
administrations as against 3 efficient performances by the 3 publicly managed
marine terminals.
This result goes to
show that the privately managed marine terminal operators implemented
government fuel subsidy reforms more efficiently than the publicly managed
marine terminal operators. In other words, the effort to distribute petrol to
the populace to avert fuel scarcity was more efficiently executed by the
privately managed marine terminal operators than the publicly managed marine
terminal operators during the fuel subsidy reforms,
It is therefore
recommended that the government collaborates with the marine terminal operators
/ practitioners in policy formulation, execution and ICT integration in the
product supply chain to further avert fuel scarcity challenges.
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|
Cite this Article: Ndubuisi, KE; Ndikom, OB; Nze, I; Nwokedi, TC (2024).
Performance Evaluation of Public and Private Marine Terminals in Nigeria
under Fuel Subsidy Regimes. Greener Journal of Business and Management
Studies, 12(1): 30-37. |