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JOURNAL OF RESEARCH IN NATIONAL DEVELOPMENT VOLUME 6 NO 2, DECEMBER, 2008

JOURNEY TO WORK PATTERN IN THE NIGER DELTA: AN EMPIRICAL ANALYSIS OF WARRI AND ENVIRONS
Dr. Augustus Atubi
Department of Geography and Regional Planning, Delta State University, Abraka

Abstract
This research work seeks to identify how journeys to work in Warri and environs are related to space in the residential and also to define how the traffic of workers from Warri to other areas within the environs are related to some underlying factors (i.e. the work trips, time taken to do these trips and cost of the trips). Moreover, eight (8) of the areas (residential) in Warri metropolis are also used for the work. From the study, the number of work trips from these residential areas in the metropolitan Warri area decrease with distance and the interior on the metropolis is the major attractor of these trips. This area is served with many types of transit systems which include private bus services, taxes, boats, motorbikes, etc. It was observed that 82% of the variation in journey to work pattern  in the study area can be attributed to the measures of spatial separation (i.e. travel time, travel cost and travel distance). Based on the findings, recommendations were proffered.

Keywords:  Work ; journey ; pattern ; Warri 

 


Introduction
Throughout the country in both large and small communities, traffic congestion is getting worse and thus, causes inconvenience to intra-city work trip makers. Subsequently, the result of this traffic congestion has increased cost and loss of work hours.

The Texas Transportation Institute studied 68 cities in the United States of America and observed that congestion cost in these cities amounted to 92 billion dollars. Similarly, in Britain, drivers lose about 1.5 billion man-hours a year to traffic congestion.

According to Ogunsanya (2002) in Nigeria, many cities experience alarming traffic problems. These problems range from road congestion which has reached crisis level in large cities, to the absence of or very poor system of public transport in smaller but fast growing towns. The issue of journey to work is one that is common in both developed and developing countries. In Warri metropolis, the increasing intensity of land use has given rise to an increased traffic flow constituted by large number of workers and their automobiles.

Pooley and Turnbull (2001) examined changing attitudes to different modes based on a survey of 1834 individuals. They demonstrate that in general, the reasons why men and women choose one mode of transport have been consistent overtime. To the policy makers, their papers suggests that once a particular mode of transport becomes established people are often reluctant to change.

Adidjaja et al. (1999) analysed change in journey to work patterns in the tri-state metropolitan regions (New York, New Jersey, and Connecticut). Between 1980 and 1990, journey to work in these regions increased by 13 percent from 1960 to 1990. The regions indicates that trips by drive alone mode increased by 35 percent, while nationally, trips by drive alone increased by 35 percent. They believe that possible reason is a combination of facts including an increased in the number of dual income families, increase participation of women in labour force and decentralized development patterns.

Kingham et. al.(2001) examined commuters perception of their mode choice during journey to work based on surveys administered at two large companies in U.K. The result of the survey indicate that 97% and 88% of staff at the respective companies travel to work by car, while only 2% and 7% of respondents cycled to work. Although only 0% and 3% currently use public transport for the journey to work, they express their willingness to shift to public transport if services are improved.

De Palma and Rochat (2000), investigate the mode choice for trips in the city of Geneva by means of a nested logic approach. They focus on the joint nature of

the decision of how many cars to own in the household and the precision to use the car for the trip to work. Their findings suggest that travel time and travel cost play a key role in mode split choice between car and transit.
Kim et. al. (2003) estimate a multinomial profit model of work trip mode choice in Seol, Korea, using a simulation based method. They estimate direct and cross elasticity with respect to travel cost and the value of time. Their findings suggest that whereas travel demands are insensitive to cost, travel demands are sensitive to travel time change. According to Myers et. al. (2002), use of public transportation was found to increase the travel time across racial ethnic groups between cities.

Blumenberg and Waller (2003) studied some cities with transit service and noticed that transit travel time on average, far exceed auto travel time because of walking to and from stops, waits at vehicle stops along the way.
In Nigeria, various authors and researchers have written much on transportation system and also journey to work pattern. They focused their attention mainly on the relationship between road network and traffic congestion (Atubi et. al., 2004a; Atubi et. al., 2004b).

Lekan (1999), looked at the causes of traffic congestion in Lagos State and traced the causes in the metropolis to complete disregard of traffic rules and regulations, impatient driving and pedestrian abuse of roadways. Adedimila (1977), studied the ways to improve traffic flow in Lagos metropolitan area, he emphasized the extension of rail-lines to the Lagos Island and construction of more dual carriage ways. Meanwhile, Onokala (1976), in her own journey to work in Edmonton, Canada has investigated the relationship between residential locations on place of work in Edmonton. She also noticed that parking cost at destination is not a strong deterrent to worktrip making to major employment centers in the city. She added that

a transit system adequate to deal with worktrips will have more than enough capacity to deal with shopping, business, social and recreational trips.

Car ownership modeling has received considerable attention in the travel demand analysis literature because of the important role it plays in the overall transportation and land use planning process. It is now well recognized that car ownership is one of the key determinants of the activity – travel behaviour of individuals and households.

Finally, although mode characteristics are less relevant in this part of the analysis, the author decided to keep the variable “travel time” in the set of explanatory variables to represent the notion of distance in a broader sense. Not only this variable closely related to the physical distance from home to work but it also encompasses the performance of the network.

Study Area
The Warri metropolis lies between latitude 5º30'N to 5º55'N of the equator and longitude 5º25'E of the Greenwich meridian. It is bounded on the south by Burutu and Bomadi, in the east by Aladja and Ughelli, in the north by Okpe Local Government and in the west by Escravos and Forcados with an area of about 12,160 sqkm. Warri as a settlement is nearly bisected by the Warri/Sapele road from south to north. This road extends from the other side of the Nigerian Ports Authority to the Enerhen junction. Warri urban therefore, extends to both the east, and west of the road. The east of the road, Warri urban is bordered by the Warri River while to the west of the road, Warri urban is bordered by Okumagba layout. And the areas referred to as the environs of Warri urban are the suburbs. Some are within Warri for example, Ekurede-urhobo and Ogunu, while others are within other local government areas for example Effurun and Enerhen (see figs. 1 and 2).

Map

map2

Methodology
Different studies have adopted different criteria in the attempt to analyse available data related to journey to work pattern. The earliest studies relied upon simple measures of density and access to route. However, the analysis for this work relied on some statistical techniques as related to available data. Below are some of these techniques:

i.          The gravity model was used to determine relationship or the interaction between places of the residence in the study area – Warri and Environs. However, the two basic factors considered here are population and distance between the residential zones. This is in line with finding out how distance affects the volume of work trips. Algebraically, the model is written as


                        ad   ……………..…………………… Equation (I)
Where;
            Tij is volume of traffic between centres i and j
            Pi is population at centre i
            Pj is distance between i and j
            K is a gravitational constant
            adis distance decay symbol

  1. Also, the simple correlation statistic was used to find out the relationship or degree of association existing between the measures of
  1. spatial separation (i.e. travel time, travel cost, and travel distance) and the volume of work journeys into Warri. The correlation technique is algebraically represented as;

 

                        r  =              n∑XY –  (∑X)( ∑Y)             i     
ada                                 √n∑X2 – (∑X)2  x √n∑Y2 – (∑Y)2   ………… Equation (ii)


iii.        The multiple correlation is used to complete the combined effects of these measures of spatial separation on work trip. The multiple correlation coefficient technique is written as;


                        fadf            ………………….Equation (iii)
dafd         adWhere ;
            R is multiple correlation
            1.23 is variable 1 with variables 2 and 3fad
            r is bi-variate correlations
r12 is simple correlation between variables 1 and 2
R2 is the square of determinationadf


Results and Discussions
For the interest of this research work, Warri metropolis was divided into six (6) major residential zones using the 2005 census data in Nigeria (see Table 1). The value of interaction (expected), Tij between each of the 6 zones and Warri is then calculated with the aid of respective populations of (2005)


Table 1: The Gravity Model Calculation


S/N

Residential  Zone

PiPj

dij

Dij

Tij

Pj/2005

1
2
3
4
5
6

Okumagba Avenue
Airport Road
Okere Road
Enerhen Road
Ajamimogha
Ugborikoko

687951000
591116685
427,710950
559429245
2088571950
413118050

2.3
4
3
16
20
13

5.29
16
9
256
400
169

130,0474,48
36,944792,08
47523438,89
2185270,488
5221304875
2444485,05

19,800
17,013
12,310
16,101
60,110
11,890

Source: Field survey
To get the expected interaction for Okumagba Avenue for instance,

            ad  This procedure applies to all the 6 zones.


It can be deduced that traffic flow in any zone is neither sequal with the size of the zone nor with the total length of roads in that zone. Zone 9, the second largest zone offer zone 1 with 0.52km2 and 0.86km2 in area respectively has network density than the largest zone 1 which attracts 10,689 or 11.35% of the total traffic in all the zones with one of the smallest zones (see Table 2).


Table 2: Traffic Volume Analysis Via the Road Network Density of Each of the Ten (10) Traffic Zones in Warri and Environs.


Traffic Zones

Area of Zone (Km2)

Total length of Road in the zone

Road Network Density in each zone

Average volume of traffic in each zone

Percentage of total area

Percentage of road length

Percentage of total traffic vol.

1
2
3
4
5
6
7
8
9
10

0.86
1.28
2.54
0.80
0.66
1.80
2.64
1.10
0.52
0.62

0.40
0.74
1.06
0.43
0.16
0.50
1.02
0.94
0.08
0.18

0.47
0.58
0.42
0.54
0.24
0.28
0.39
0.85
0.15
0.29

10689
1115
9605
9463
9597
9072
6310
8155
10352
9810

6.71
9.98
19.81
6.24
5.15
14.04
20.59
8.58
4.06
4.84

 

7.17
13.26
18.99
7.71
2.87
8.96
18.28
16.84
1.44
3.22

11.35
11.80
10.20
10.05
10.19
9.63
6.70
8.66
10.99
10.43

Total

12.82

5.58

4.21

94,168

100

100

100

Total area of zones = 12.82km2
Total road length in all zones = 5.58
Source: Field survey

 

Total volume of traffic trough zone = 94,168
The road network density in each zone is given by:
Total length in a zone
Area of the zone
Therefore, the network density for zone 1 is
            =   fsd
            =   0.47


This was calculated for all the ten (10) zones.
From field observations, it has been shown that even if the road network density increased in any zone without sequel optimization of land use and rate of employment, escalation for traffic on its road goes on. It also follows that no matter the size of the zone, if the rate of traffic flow is not checked, probably by decentralization of land use, congestion stays put on these roads. This congestion again, has been traced to the areas of inadequate and network density, land use pattern and employment densities of the zones.

Having said this much, it was observed that the degree of association between the volume of trip generated and the travel distance using the correlation statistics was -0.80 which carries a negative value indicating an inverse relationship between two variables tested. What this result implies is that so long as travel distance increases the volume of worktrips equally reduces.

Time was also taken to check for the significance of the correlation coefficient between the volume of worktrips generated in relation to travel cost. It was also observed that an inverse relationship was recorded accounting for a value of -0.79. The argument here is that both volume of worktrips in these residential zones and the transportation cost to work places will continue to go in opposite directions indicating that as long as transport cost increases, there will always be a decrease on the number of work trips with respect to such residential

zones as the case may be. Again where travel cost of individual worktrip is allowed to influence the travel distance, it was seen that the direction of influences is positive, with a magnitude of 0.94 and coefficient determination (r2) of 88.36%. In other words, travel cost explains 88.34% of the decisions made by work tripmakers into Warri metropolis, leaving only 11.64% to be explained by other factors.

However, when the combined influence of these variables on work journeys into Warri and environs is sought for, the multiple correlation revealed that the multiple effect of the variables R is 0.82 (See Appendix A). In other words, they can together only define 82% of the behaviour of working journeys into Warri metropolis. This means that only 18% is left undefined and is thus under the determination of other factors which may include trip-makers economic status’, some may find other means of getting to work in Warri and environs etc.

Policy Implications and Conclusions
From the findings of this research work, it is however recommended that landuse pattern in Warri and environs should be centrally located and distributed (i.e. places of central activities should be properly located so as to redistribute traffic flow. Similarly, some of the activities within the central employment zones should be segregated so as to re-direct traffic away from the major routes and centres. Also, some of the major routes should be expanded so as to reduce traffic congestion and possible road traffic accidents on these routes (see Atubi and Onokala, 2005).
It is also recommended that for further studies of the  pattern and intensity of journey to work in other Nigeria cities should be undertaken in order to find out more about the phenomenon of journey to work in Nigeria. In other to do this, there is need for a lot of improvement in volume of traffic and employment statistics collected for Nigerian cities and made available to researchers. This will encourage the comparison of the results of the analysis of data for the different cities in the country.

 

References
Adedimila, A.S. (1977): Towards Improving Traffic Flow in Lagos Transport “Transport in Lagos” “Transport in Nigerian National Development, proceedings of a Conference held at the University of Ibadan” July 4th to 9th.

Adidjaja, C. (1999) “Analysis and Comparison between 1980 and 1990 Journey to work data”. New York Metropolis Transportation Council.
 
Atubi, A.O. and Onokala, P.C. (2004a): The Effects of Road Network Characteristics on Traffic Flow in South-Western Nigeria. A case of Lagos Mainland. Pecop Journal of Environmental Design and Management in the Tropics. Vol. 1, No.1 pp.39-51

Atubi, A.O. and Onokala, P.C. (2004b) “The Accessibility of Centres to the Road Networks: The Case of Lagos Island, Lagos, Nigeria, International Journal of Ecology and Environmental Dynamics. Vol.2, pp. 140 – 151.

Atubi, A.O. and Onokala, P.C. (2005) “The Effects of Traffic Congestion on Road Accidents in the Niger-Delta: The Case of Warri Metropolis, ” Journal of Nigerian Academic Forum Vol.9, No.5.
 
Blumenberg, E.M. and Waller, C. (2003) “The Long Journey to Work: A Federal Transportation Policy for Working Families” Brookings Institute Series on Transportation Reform. July 2003: 1 – 19.

De Palma, A. and Rochat, D. (2000) “Mode Choices for Trips to Work in General: An empirical Analysis  Journal of Transport Geography Vol.8. pp. 43 – 51.

Kim, Y.T. and Heo, E. (2003) Bayesian Estimation of Multinomial probit models of work trip choice”. Transportation 30: 351 – 365.

Kingham, S.J.; Dickson, S. and Copsey, C. (2001) “Travelling to Work: will people move out of their cars”, Transport Policy, 8: 151 – 160.

Lekan, E. (1999) “Socio-demographics, activity participation and travel Behaviour,  Transportation Research 33 (1): 1 – 18.

Myers, K. and Mauch, M. (2002) “Public Transportation and Work-trip length” Traffic quarterly,  44 (6) 508 – 515.

Ogunsanya, A.A. (2002) “Issues and Problems in Nigerian Transport System”, The Trainer. Journal of the Nigerian Institute of Transport Technology,  Vol. 1, No. 1, pp. 4 – 10.

Onokala, P. C. (1976) “Journey to Work Patterns in Edmonton, Canada”. Unpublished M.Sc. Thesis, University of Alberta, Canada.

 

Pooley, C. and Turnbull, J. (2001) “Modal Choice and Modal Change: The Journey to Work in Britain since 1890”,  Journal of Transport Geography  8(1) 11 – 24.


APPENDIX  A
Analysis via multiple correlation technique. This is given as
R = 1 – R21.234  =  [1 – r212][1 – r213.2][1 – r214.23]
From the above equation we look for r213.2 given as

sfdf= –  df
sd= –  a
fa= –  d
dfsdfdf= –  fd
dfda= –  f
daf= 0.035
adf= 0.0012
Therefore we look for d which is given as
fd d
f fd
d ff
fd dfdf
f d
df 0.08
d e

fff e
df wet
d f
f s
d –0.23
f –0.05
Then rg dfgf
gr d

ad sfg
ad 0.2
dgw 0.04
Therefore we calculate the value of sf which is given as
sfs sfds
f f
f ssfsf
sfsf
s
sfsf
Therefore we introduce the first equation
f
Therefore
sf
f
ffsfs
sf
s
ffsf