JIMMY SIKACHELELA FINAL RESEARCH REPORT

EXAMINING THE KEY DETERMINANT FACTOR FOR TRANSPORT

DEMAND BY MSMEs IN DIFFERENT BUSINESS SECTORS

IN ZAMBIA

Bachelor of Commerce (Economics) Thesis

A Dissertation by

JIMMY SIKACHELELA

Submitted to the School of Social sciences Studies

In partial fulfillment of the requirements for the degree of Bachelor of Commerce

(Economies)

MULUNGUSHI UNIVERSITY

6th MAY, 2014

CHAPTER ONE

INTRODUCTION

Mobility is an essential part of human life especially in cities. Transport demand, mainly

results from rapid urbanization, population growth, modern life styles, economic conditions

and is one of the most commonly used transport modes that provide the mobility required in

our time according to Cihat (2012:1211).In the last 20 years and/or more, transport demand

has risen rapidly in local, nationwide, and worldwide agenda and it’s not only influenced by

the measure of elasticity but also on the quality of people’s lives. This increase is credited to

the dominant function that transport plays in everyday life due to the escalating amounts of

energy used and to the economical impacts of transport on local, national and the global

economy.

When a business or an entity engages in economic activities that may contribute to the

economy regardless of it being a sole proprietorship, corporation, partnership or any legal

business, it may be referred to as medium-sized enterprise or micro, small, medium

enterprises (MSMEs).

The terms “small” and “medium” in reference to a size of business or entity may vary within

the sectors. A broad general definition can be taken for MSMEs, some countries have a very

precise definition on how the types of enterprises can be called as “MSME”. MSMEs Country

Indicator (2010) defined MSMEs as follows: micro enterprises: 1 to 9 employees; small: 10 to

49 employees; and medium: 50 to 249 employees. On the other hand, the Small Enterprises

Development (SED) Act of 1996 defines MSMEs as follows: An enterprise is defined as an

undertaking engaged in the manufacture or provisions of services or any undertaking carrying

out business in the field of manufacturing, construction, trading, and services but does not

include mining or recovery of minerals. Micro: - an enterprise whose total investment

excluding land and buildings does not exceed 50 thousand Zambian Kwacha; annual turnover

that does not exceed 20 thousand Zambian Kwacha and employing up to 10 persons. Small-

an enterprise whose total investment excluding land and buildings does not exceed 50

thousand Zambian Kwacha, in case of manufacturing and processing enterprise and 10

thousand Zambian Kwacha in case of a trading and service enterprise; an annual turnover that

does not exceed 80 thousand Zambian Kwacha and employing up to 30 people. Transport is a

service rarely in demand for its own characteristics. Demand for transport, especially road

freight facilities is usually derived from some other function. An MSME producing food

(bread or buns) or sale merchandize sees transport as a means of moving its products from

factory or warehouse to the retail store. As demand for products, raw material and

merchandize increases so the demand for transport facilities will increase. MSMEs in different

business sectors intend to have different types of preference (characteristics of goods involved

or standard of services) when it comes to demand for transport because of the nature of

trading or business they are involved in.

1.1 BACKGROUND

The Zambian government had no policy on the private sector development in particular the

MSMEs as they followed a central planned economic system after attaining independence in

1964. The UNIP government had no special legal framework promoting the MSMEs since the

economy was receiving more revenue from the high copper prices hence ignoring MSME

sector. The country depended much on mining industry and only the public sector was visible

by the government. Sadly, the copper prices dropped in 1970s. With decreasing revenues in

the copper industry, the Zambian government had to find alternative ways of sustaining its

economy therefore, after 1981, it begun to initiate policies targeted at promoting MSMEs and

hence came up with the Small Industries Development Act of 1981 succeeded by the Small

Enterprises Development (SED) Act of 1996. Both policies had a negligible impact on the

development of SMEs as they were just merely public pronouncements with little effort to

implement them.

In the past, Zambians were not very enterprising due to the public sector led economic growth

model which excluded citizenry from participating in business activities with the threat of

nationalization of their business. Zambian citizenry depended entirely on formal service as a

way of earning income and living.

However, after the 1990s, when Zambia adopted the free market economy system that was

perpetuated by the World Bank (IBRD) and the International Monetary Fund (IMF) and

during this period, the Zambian economy experienced the most severe economic recession. As

a result, this lead to the privatization of the Zambia economy which left inefficient among

local producers thus becoming uncompetitive, hence it became essential that they restructure

in order to remain in business and retrenchment of employees was one of the methods used

while other firms had to shut-down operations completely. The opening up of domestic

markets was attached with privatization of the state owned mines and companies (and firms).

The Gross Domestic Product declined and poverty levels increased drastically (70%) placing

Zambia among the poorest countries in the world. The MSMEs formation was unavoidable

since most Zambians were now out of formal employment and they had to find other ways of

surviving.

1.2 SIGNIFICANCE OF TRANSPORT IN ZAMBIA

Being a landlocked country with the main economic centers lying at least 1400km from the

nearest seaport, Zambia is highly dependent on the efficiency and costs of cross-border

transport services. Transport costs can contribute as much as 17% to import costs (Mackellar

et al. 2000), which is more than three times the amount in most developed countries but

comparable with most landlocked countries.

Zambia’s main trading partner is South Africa, accounting for 1.8 million tonnes per year

(44% of the estimated total freight traffic in 2005). The DRC and Zimbabwe account for

about 9% and 8% respectively of total trade. Zambia’s international trade outside the SADC

region accounts for about 36% of total trade (www.sarpn.org,30th April, 2014).

The main products transported by road within Zambia are: mining products (ores,

concentrates, metals, sulphur, sulphuric acid, coal), agricultural products (sugar, tobacco,

cotton), fuels (diesel and petrol), and food (bulk grain).

According to data from the Zambian Revenue Authority, the total volume of Zambian

regional and international trade is 3.9 million tonnes in 2005, made up of 2.3 million of

imports and 1.6 million of exports.

Road transport is the dominant mode in Zambia and is expected to remain so. Current modal

share of about 71% of Zambia’s trade (in volume) is carried by road, 24% by rail and about

5% accounts for oil imports by pipeline from Dares-Salaam (TAZAMA pipeline).High value

mining and agricultural goods (cobalt and fresh / frozen products) are generally transported by

air freight except for copper cathodes (about USD 250,000 per load), which are exported by

road to Gauteng, where they are containerized in order to be exported through

Durban(Raballand etal 2008:4).

Poverty is said to be highest in most of the Zambian rural areas because of the lack of access

to market for agricultural produce as well as productive inputs. This has been worsened by the

poor transport systems that exist in rural areas. Therefore, if the poverty situation in rural

areas is to be addressed, the issue of transport has to be of paramount importance. In order to

improve rural travel and transport, the following measures have been proposed

(www.sarpn.org,30th April, 2014):

• Establish an institutional framework for the development and management of rural

transport and travel in the country.

• Improve the planning, management, and financing of rural road transport as well as

upgrading the road infrastructure such as community roads, paths, tracks, trails, and

footbridges through community participation.

• Facilitate the rural communities with the establishment of sustainable approaches to

the construction and maintenance of rural transport infrastructure.

• Facilitate the introduction and promotion of appropriate motorized and non-motorized

means of transport aimed at improved mobility in rural areas.

• Encourage the development of industries for the design, manufacture, repair, and

maintenance of intermediate motorized and non-motorized means of transport for rural

areas. And ensure that gender issues and the interests of the differently able persons

are considered in rural travel and transport.

1.3 NATURE OF TRANSPORT IN ZAMBIA

The road network is the backbone of the Zambian transport system reaching to remote areas

where other modes cannot. Zambia has a gazette road network of approximately 37,000 km of

which 6,476 km are bituminous and surfaced to Class 1 standard. The gravel and earth roads

account for 8,478 km and 21,967 km respectively. In addition there are about 30,000 km of

ungazetted community road network comprising tracks, trails and footpaths. A large part of

the main road network was constructed between 1965 and 1975. Over the years the country’s

road infrastructure has been eroded through lack of maintenance. The main problems have

been institutional and financial which relate to (WB 2002):

• Inadequate and erratic flow of funding.

• The inadequacy of the institutional framework within which roads were managed

• Poor terms and conditions of employment.

• Lack of clearly defined responsibilities among road management actors.

• Lack of managerial accountability.

According to ZDA (2013), the Zambian economy is forecast to grow between 7.5 and 8

percent annually over the next five years. To sustain this growth, Zambia needs to upgrade its

transportation infrastructure. Zambia, being a landlocked country lies in the center of the

Southern African Region and to this effect heavily relies on her neighbors for vital routes to

various import and export destinations. Transport infrastructure covers: roads and bridges,

railways, airports and aerodromes and maritime and inland waterways. The state of transport

infrastructure, however, remains inadequate to sustain and match the desired levels of growth

due to weak structural and management capacity resulting in over commitments, high cost of

construction and low investment.

Airports

There are four international airports; five secondary airfields and five airstrips serving the

international and domestic flights. Airports with paved runways are 8, of which 1 airport over

3,047m is, 3 are between 2,438m to 3,047m and between 914m to 1,523m respectively.

Airports with unpaved runways are 80,of which 1 is between 2,438m to 3,047m,5 are between

1,524m to 2,437m,53 are between 914m to 1,523m and 21 are under 914m (ZDA 2013:5).

The Kenneth Kaunda International Airport is Zambia’s main airport connecting the country

with the rest of the world. This is complimented by three airports at Ndola (Simon Mwansa

Kampwepwe, Livingstone (Harry Mwanga Nkumbula) and Mfuwe, as well as secondary

airfields at Chipata, Kitwe, Kasama, Mongu, Solwezi and Mansa.

RDA (2013:5) states that, Zambia has no national airline but is served by a number of airlines

that connect to international routes via Johannesburg, Cape Town, Addis Ababa, Nairobi,

London, Amsterdam, Dubai and Dar-Es-Salaam. Proflight Zambia is a privately run airline

with proposed regional flights to Johannesburg and Congo DRC and local flights to various

destinations within the country. The country recently adapted an “open sky policy” and is

currently promoting the establishment of an air cargo hub for the Southern African region.

Roads

According to RDA (2013), the Government of Zambia has recently embarked on the Link

Zambia 8,000 project (Accelerated National Roads Construction Programme) aimed at

rehabilitating and constructing the road network. The aim is to construct an efficient road

network and international highways linking Zambia to South Africa, Zimbabwe,

Mozambique, Malawi, Tanzania, the Democratic Republic of Congo and Namibia. This

project also aims at contributing to the reduction of road user costs and transit times across

Zambia. In 2001, the Zambian roadways had a total of 91,440 km, of which 20,117 km were

paved and 71,323 km were unpaved.

Railways

The Government intends to expand its railway network in the country to develop the surface

transport sector. The development of rail routes linking important exit points is not only vital

for facilitating smooth access to the outside world but also for the overall boosting of trade in

the sub-region and making Zambia a competitive country for doing business with a total of

2,157 km of railways.

The Zambian railways generally operate well below their original design capacity, yet they

cannot increase their volumes because of poor track condition, lack of locomotive and wagon

availability and low operating capital.

According to ZDA (2013:6-7), rail network remains the dominant mode of transportation for

goods on the local and international routes. However, the infrastructure requires urgent

rehabilitation and new developments. The main railway lines are Zambia Railways which is

owned by Government and the TARARA line which links Zambia with Tanzania, is jointly

owned by the Zambian and Tanzanian governments. The recent opening of the Chipata-

Mchinji railway link provides connectivity into the Malawi railway network and further

connects Zambia to the northern Mozambique railway network and opens up new and exciting

opportunities for the private sector in Zambia, Malawi, and Mozambique. Government is

seeking private sector participation in the development and rehabilitation of the railway

infrastructure (RDA 2013).

• Chingola to Jimbe (Border with Angolan) - The railway line involves linking the

existing line in Chingola through Solwezi to the border town of Jimbe to enhance the

transportation of freight and passenger traffic and other products using Lobito Bay

port in Angola.

• Kafue (Zambia) – Zawi in Zimbabwe: The railway line will link Zambia Railway line

to Ziwa Zimbabwe to the Beira Port as the shortest route to the port of Baira in

Mozambique.

• TAZARA Nseluka – Mpulungu port: The railway lines involves linking Mpulungu

Port to TAZARA line at Nseluka to facilitate the imports and exports from the Great

Lakes region to the sea ports on the Indian Ocean.

• Extension of the Mchinji/Chipata Railway line to TAZARA: The railway line involves

linking the Chipata–Mchinji line through Petauke District to the port of Nacala in

Mozambique.

• Railway link with Zambia and Namibia (Livingstone –Sesheke): The construction of

this line involves the partial rehabilitation of the Mulobezi line and feasibility studies

for construction of a spur between Livingstone and Katima Mulilo via Kazungula and

connect to the Namibian Railway System at (Border) as part of the Walvis Bay –

Livingstone – Lusaka – Ndola – Lubumbashi Corridor.

Waterways, Ports, and Pipelines

Zambia has 2,250km of waterways which includes; Lake Tanganyika, Kafue river, Zambezi

river, and Luapula river to mention but a few. There are 771 km of pipelines in Zambia (e.g.

Tazama Pipeline) and Mpulungu been the only port of Zambia (RDA 2013).

1.4 THE STATEMENT OF THE PROBLEM Over the last two decades, Zambia has experienced rapid changes and socio-economic

transformations. These socio-economic changes are affecting and causing worry mainly to

isolated, minor and rural areas of Zambia. However, the changes in economic and social

culture structure of Zambia have brought about an increase in the demand for transport. With

an increase in demand for transport in Zambia, MSMEs keep searching for the best alternative

mode of transport to move their goods from one place to another. This is however, dependent

on the attributes or characteristic of particular mode involved .It is therefore essential to find

out the key determinant factor from a wide range of factors that determine the demand for

transport of MSMEs, and a particular mode of transport being used.

1.5 GENERAL RESEARCH OBJECTIVES • To identify the key determinant factors for transport demand by MSMEs in their

different business sectors (Agricultural and Livestock, Trading, Service, Food

Processing and Non-Food Processing).

SPECIFIC OBJECTIVES

• To examine and identify which MSMEs by sector (agriculture & livestock, trading,

service, food processing and non-food manufacturing) demands more of transport.

• To determine what kind of transport mode is demanded mostly and what determinant

factors are attributed to.

• To determine the impact of transport on MSMEs growth with respect to effective

demand.

• Find out the period of existence of MSMEs by business sector.

1.6 FORMULATION OF HYPOTHESIS • It was hypothesized that, there is positive relationship between the number of trips

travelled and the determinant factors (speed of transport, characteristics of goods

involved and standard of services) for transport.

1.7 SIGNIFICANCE OF THE STUDY The significance of this study is to identify and evaluate the determinant of transport and the

impact it has on the MSMEs growth. This study is also aimed to be of benefit to MSMEs,

Government, policy makers and the community at large in finding remedies to develop the

Zambian economy. The research done was a partial fulfillment for the award of a Degree in

Bachelor of Commerce degree at Mulungushi University. The study was also intended to

contribute to the already existing body of knowledge which might be of help for future

researchers.

1.8 SCOPE AND LIMITATION OF THE STUDY

1.8.1 Scope of the study The study focused on MSMEs (agriculture & livestock, trading, service, food processing and

non-food manufacturing) that had been existence for the past period of 10 years from 2004 to

2014.

1.8.2 Limitation of the study The following were the challenges faced by the researcher during data collection and these

were; Firstly resistance on the part of the MSMEs Managers/owner to give clear information,

secondly the period of the study was too short as a result, alot of information was compressed

within a limited time. Lastly secondary information was not readily available and limited time

and resources could not allow further findings.

CHAPTER TWO

LITERATURE REVIEW

2.1 INTRODUCTION The following chapter reviews what other scholars have written on determinant factors for

transport demand by MSMEs. This will help to broaden the scope knowledge of what others

have written about this topic.

2.2 THEORETICAL LITERATURE REVIEW Travel demand modeling: definitions and purpose

Mohammad and etal (2011:3) states that people travel in order to participate in some land-

based activity, making the demand for travel a derived demand. Travel demand forecasting

predicts the number, type, origin and destination, and distribution of “trips” on a

transportation network as a function of land use patterns. A “trip” is defined as travel between

two points for one purpose, for instance, between home and work, or home and school, or

work and shopping. Therefore, more than one mode can be used for the same trip (e.g., walk

or dropped off at a bus stop). Usually, travel demand is expressed in terms of vehicles

(vehicle-trips); however, it can also be defined in terms of individuals (person-trips) or goods

(truck-trips). According to Wee and Kees (2003:201), travel demand has been defined as the

sum total of realized needs of travel, expressed as the actual number of trips or trip kilometers.

The theoretical foundation for the relation between travel and spatial structure can be found in

the theory of utilitarian travel demand. This theory postulates that the demand for travel does

not derive its utility from the trip itself. Rather, it comes from the need to reach the locations

where activities take place, such as the dwelling, the work place, and services and facilities.

Travel demand forecasting tools allow practitioners to measure and evaluate the impact of

changes to the transportation network and surrounding land uses on the traffic volumes, travel

paths, and travel modes. Using travel demand modeling tools, planners, engineers, and

economists make informed transportation infrastructure planning decisions.

Mohammad and etal (2011:30) states the most commonly used methodology for travel

demand modeling is the four step process that considers generation, distribution, mode choice,

and route assignment of trips. Trip distribution has been chosen by the researcher as it

provides relevant measures and analysis that are needed for the research. The gravity trip

distribution model, evaluates the number of trips produced from a zone which depends on the

magnitude of activities at the destination zone, the trip length by purpose, trip length

frequency distribution by purpose and the space (distance) separation between the two zones.

The following equation describes the trip distribution equation:

Tij=Pi*∑��∗��∗��

��∗��∗��

��

Where,

Tij=Number of trips from zonei to zonej

Pi = Number of trip productions in zonei

A j = Number of trip attractions in zonej

Fij = Friction factor relating to spatial separation between zonei to zonej

K ij = Trip distribution adjustment factor between zonei to zonej

The model holds that households/firms will increase the number of trips from one zone(town)

to another due to increased good quality of service(suppliers),reduced time travel(due to

speed) and income. The model shows that, there is a positive relationship between transport

demand (trip travel) and quality of service, income, time travel, price charged and etc.

2.3 EMPIRICAL LITERATURE REVIEW Several studies have been carried out on matatus (Kenya) as a mode of transport. The studies

have mainly concentrated in the city of Nairobi. For instance, Alila and Pedersen (2001:70)

cited in (Situma 1977, Barwell 1979, Nairobi City Council 1980, Kapila 1994) states that they

all focused on Nairobi city. Situma (1977) looked at the origin of matatus and their

destinations: types of vehicles used, their carrying capacity, roadworthiness, average number

of trips, ridership and fare structure. The analysis based on Nairobi City Council surveys of

1971 indicate that the Matatu mode of transport played an important role in the public sector

in Nairobi. This finding is still quite valid in the 199Os. For example although matatus make

an important contribution to public transport in Kenya, a number of passengers are dissatisfied

with the services provided. For instance, Matatu drivers are often accused of over speeding,

carrying passengers beyond capacity, playing very loud music and generally of being reckless

drivers. The other workers associated with 'matatus like conductors, 'manambas' are often

accused of being rude to the passengers. The author's personal experience as a passenger in

the matatus to some extent agrees with the accusations. Despite the accusations, very few

studies have been carried out to establish the quality of services provided by matatus to

passengers.

Aduwa (1990) looked at the Matatu system's general role, its efficiency and quality of service

offered by matatus in Nairobi. A very strong functional relationship was established between

the distribution of Matatu services and population distribution. The other factors that

accounted for distribution was distance covered per trip, profitability levels and income levels

of the population. In ranking commuter (public) transport model choice, the matatus were

preferred because of their availability (frequency), comfort and speed. Little concern was

shown for reliability, cost and safety while travelling. This study is quite pertinent to the

present study. While road traffic accidents are threatening the safety of every traveler, it is

interesting to note that the travelers themselves do not give safety priority while travelling.

Bresson et al (2004) explored the economic and structural determinants of the demand for

public transport based on a panel data analysis of annual time series from 1975 to 1995 for 62

urban areas in France. Three economic determinants were considered – vehicle-kilometers,

income and price. Public transport was found to be an ‘inferior good’ as the estimated income

elasticity was negative. By synthesizing the structural determinants (including population

ageing, urban sprawl and growing car ownership) in a single indicator, there was an

interesting discovery that the ‘income effect’ was in fact mainly a ‘motorization effect’. It was

concluded that the downward trend in public transport patronage was mainly due to increasing

car ownership. It was also observed that the use of public transport was quite sensitive to the

service level and its price.

Hensher (2008) analyzed the direct elasticities associated with public transport demand with

respect to changes in three factors: fares, in-vehicle time and headway, based on information

from 319 studies. The major influences identified were: time of day (peak, all day versus off-

peak), data paradigm (especially combined stated preference/revealed preference versus

revealed preference), whether an average fare or class of tickets was included, the unit of

analysis (trips versus vehicle-kilometers), specific trip purposes, country and specific-mode

(i.e. bus and train).

Greer (2008) carried out a spatial analysis of cross-sectional data on bus ridership by

commuters to work and other related statistics for the Auckland region collected during the

2006 Census. The results from a regression analysis indicated that the following four factors

had a positive effect on commuter bus ridership:

• The total number of commuters from the area unit

• The distance from the centre of the area unit to the nearest rail or ferry terminal

• The population density of the area unit

• The combined morning and evening peak-hour bus service frequency within the area

unit.

On the other hand, the following three factors were found to have a negative influence on

commuter bus ridership:

• The average number of cars available to a household within the area unit

• The distance from the centre of the area unit to the city centre

• Median household income within the area unit.

Bureau of Industry Economics (1992b) reviewed international performance indicators for

road, which included customer orientated determinants, stating that these typically cover areas

like price, timeliness and other aspects of service quality. In a survey of Australian road

freight transport providers and users, the determinants stated in order of priority were:

• Price (road freight priced in a number of ways/km adopted to allow comparison).

• On-time delivery (as a percentage).

• Care of goods (loss and damage rates and claims paid as percentages).

• Availability of equipment to meet user needs.

• Timely and acceptable response to queries.

• Invoice accuracy.

• Shipment tracing.

Liability coverage and claims procedures were judged to be less important, which was

attributed as being possibly due to low loss and damage rates in the industry. It was noted that

suitability of electronic data interchange capability had not yet become a key factor of

concern.

CHAPTER THREE

METHODOLOGY The main purpose of this chapter was to demonstrate the methodology used to select

participants, the tools and approaches used to collect the data, the sample size and how it was

selected.This study was on determinant factors for transport demand by MSMEs.

3.1 RESEARCH DESIGN The research uses both qualitative and quantitative approaches. Qualitative data was be

collected by reviewing literature, asking question and conducting consultations with MSMEs

of Kabwe town while quantitative data was be collected by computation of cross-section data

using Regression, MS-EXCEL and SPSS.

3.2 DESCRIPTION OF RESEARCH AREA (KABWE) Kabwe, formally known as Broken Hill is the provincial headquarter of central province

which is one among 10 other provinces in Zambia. Kabwe is a one largest town in Zambia

located about 140 Km north of the Capital City Lusaka and 26km along great north road from

Mulungushi University. Kabwe is geographically located in the central part of Zambia and its

holds the headquarters of Zambia Railways and Prison Service. At 2010 census population,

Kabwe has a population of 202, 914, with a 16% share of the central province population

(1,267,803). The major economic activity of Kabwe town was mining and Manufacturing

before the closure of the major industries such as the Zambia-China Mulungushi Textile,

Kabwe Tannery and Kabwe Mine. At present, Kabwe’s increasing economic activity has been

agriculture, tertiary service and though some mining and manufacturing are still in operations

such as Zalco, Kifco, and San Hae.

3.3 MODEL SPECIFICATION

In order to produce an observed study we need to establish a functional relationship for total

trips traveled as a proxy for transport demand. As a result of this research, the functional

model measurement will be represented mathematically as follows:

TP= f (SS, GP, CGI, ST, µ)………………………….….. (a)

Where;

TP = Trips Traveled

SS - Standard of Service

GP – Good Price

CGI- Characteristics of Goods Involved

ST- Speed of Transport

µ- error term

In order to understand the relationship and significance of the variables above in the

objectives of this research and also applying to the testing of the hypothesis through the

transport economics theory of trip distribution and the econometric model can be expressed as

followed from (a) above:

TP =β0 + β1SS + β2GP + β3CGI + β4ST + µ……………………… (b)

Where;

TP = Trip Traveled

SS = Standard of Service

GP = Good Price

CGI = Characteristics of Goods Involved

ST = Speed of Transport

µ= error term

β0= Constant term and

β1= the coefficient of the independent variable (SS) which β1 > 0

β2= the coefficient of the independent variable (GP) which β2 > 0

β3= the coefficient of the independent variable (CGI) which β3 > 0

β4 = the coefficient of the independent variable (ST) which β4 > 0

3.4 IDENTIFICATION OF VARIABLES

• The independent variables are Standard of Service, Good Price, Speed of Transport,

and Characteristics of Goods.

• The dependent variable is the trips travelled in a month.

3.5 POPULATION The target population was five different types of MSMEs business sectors namely agriculture

and livestock, food processing, manufacturing, trading and service sectors.

3.6 SAMPLE SIZE The sample size was 40 but only managed to 36 respondents which consisted of the following.

- Agriculture and Livestock 8

- Food processing 5

- Non-Food processing 6

- Servicing 7

- Trading 10

3.7 SAMPLING PROCEDURES

The sample procedure which was used to select the respondents was on random sampling.

3.8 RESEARCH INSTRUMENTS

Data was collected using self-administered questionnaires which were designed with most

questions closed ended and few questions open ended.

3.9 DATA COLLECTION The study was confined to the period ranging from February 2014 to first week of May 2014

of data collection, analysis and evaluation (three months).

Date was collected using both the primary and secondary data. Primary data was collected

using questionnaires on management representatives/owners of MSMEs and the Secondary

data was collected using the reports on MSMEs, internet and the commercial banks reports.

3.4.0 DATA PROCESSING The data collected using questionnaires was subjected to verification for consistency, standard

editing, uniformity and accuracy before been coded. Data processing was done through the

use of simple and cross tabulations which was analyzed by using statistical package SPSS

version 16.0 and there-after was exported to and analyzed using a MS-EXCEL.

3.4.1 DATA ANALYSIS The data was analysed using both qualitative and quantitative approaches. The qualitative

approach gives an explanatory measure of research whilst the quantitative approach provides a

mathematical evaluation for the research. A proxy for transport demand was used to analyze

the findings.

3.4.2 ETHICAL ISSUES Issues of confidentiality and privacy were dealt with(personal and business details of

respondents were not published). Information was provided to the respondents prior to the

start of the interviews to the effect that the information provided is for academic purposes.

CHAPTER FOUR

DATA ANALYSIS AND DISCUSSION

4.1 INTRODUCTION This section contains the data collected. This chapter will include the respondents’ mode of

transport used, business sectors, speed of transport, characteristics, employment creation,

price/other forms of transport, and quality or quantity of the product and etc. The data will be

presented in form of tables, charts and where tables or charts cannot be easily applied,

interpretation, description, analysis and a short explanation will follow for each and every

table or chart.

4.1.1 THE DESCRIPTION OF THE POPULATION

4.1.1.1 THE PROPORTION OF RESPONDENTS BY BUSINESS SECTORS.

Table 1(one)

The findings revealed that the majority of respondents were in the trading sector with 10

respondents representing 27.8% of the total sample of 36, followed by the agriculture and

livestock sector with 8 respondents representing 22%, then the service sector with 7

respondents representing 19.4%, non-food processing sector with 6 respondents representing

16.7% and lastly the food processing sectors with 5 respondents representing 13.9%. This

0

5

10

15

20

25

30

Services Non-Food

Processing

Trading food

Processing

Agricultural

and Livestock

Frequency

Percent

Valid Percent

revealed to the researcher that more MSMEs are involved in tr

agriculture sector, followed by service sector,

processing sectors in Kabwe.

4.1.1.2 PERIOD OF EXISTENCE OF THE COMPANIES/BU

TO THE BUSINESS SECTOR

Table 2(two)

The table shows that most MSMEs

total of 17 respondents out of the sample of 36

existence between 5 to 10 years, having the total of 7

in existence between 1 to 3years with a total of 4

This revealed that 2 respondents in agriculture had be

four had been in existence for more than ten years, in food processing sector one

had been in existence for less than one years and four

years, for trading sector one

respondent existence between 3

years and the other 4 respondents

respondents had been in existen

existence for than 10 years and

less than one years, four respondent between 5 and 10, and two

years in existence.

0

0.5

1

1.5

2

2.5

3

3.5

4

less then 1

year

1-3 years

revealed to the researcher that more MSMEs are involved in trading sector seconded by

sector, followed by service sector, non-food processing and lastly th

4.1.1.2 PERIOD OF EXISTENCE OF THE COMPANIES/BUSINESSES IN RESPECT

SECTOR

The table shows that most MSMEs respondents had been in existence above

pondents out of the sample of 36, followed by the ones which had

existence between 5 to 10 years, having the total of 7 respondents and the least were the

ween 1 to 3years with a total of 4 respondents.

respondents in agriculture had been in existence for less than one year and

in existence for more than ten years, in food processing sector one

ce for less than one years and four had been in existence for more t

years, for trading sector one respondents had been in existence between 1

respondent existence between 3-5 years, three respondents had been existence between 5

respondents for more than 10 years. Non food processing

respondents had been in existence for less than one year, 4 respondents had been between

for than 10 years and , lastly service, only 1 respondent had been in existence for

pondent between 5 and 10, and two respondents for more than 10

3-5 years 5-10 years Above 10

years

Agricultural and Livestock

food Processing

Trading

Non

Services

ading sector seconded by

and lastly the food

SINESSES IN RESPECT

respondents had been in existence above10 years giving a

, followed by the ones which had been in

respondents and the least were the ones

en in existence for less than one year and

in existence for more than ten years, in food processing sector one respondents

had been in existence for more than 10

had been in existence between 1-3 years, two

respondents had been existence between 5-10

for more than 10 years. Non food processing sector 2

had been between in

, only 1 respondent had been in existence for

respondents for more than 10

Agricultural and Livestock

food Processing

Trading

Non-Food Processing

Services

4.1.1.3 MSMEs THAT HAD OR DID NOT HAVE THEIR OWN TRANSPORT

CARRIERS

Table 3(Three)

The table above shows the MSMEs with the total sample of 36 respondents. The majority

respondents, that is, 22 respondents representing 61.1% had their own transport carriers and

only 14 respondents representing 38.9% did not have their own transport carriers. This

revealed that most MSMEs needed transport carriers for their business operation because

more than 60% used their carriers for business activities. From the sample, the majority

respondents who had their own transport carriers belonged to trading sector consisting of 9

respondents representing 25% and the least coming from service sector having 1 respondent

representing 2.8%.The majority respondents who did not have their own transport carriers

belonged to service sector consisting of 6 respondents representing 16.7% and the least

coming from trading having 1 respondent representing 2.8%.This shows that MSMEs in

trading sector had their own transport as means of transporting goods from point of buying

and where they sale their merchandize as to reduce the cost of transport.

0

5

10

15

20

25

30

Count % of

Total

Count % of

Total

Count % of

Total

Count % of

Total

Count % of

Total

Agricultural and

Livestock

food Processing Trading Non-Food

Processing

Services

No

Yes

4.1.1.4 THE PROPORTION

Table 4(Four)

The table above, shows 36 respondents of which the majority respondents

trips in a month were from trading

sector consisting of 8 MSMEs, and thirdly was the service sector consisting of 7 MSMEs.The

fourth sector was the non-food processing consisting of 6 MSMEs and lastly was the

processing sector consisting

MSMEs in trading sector traveled a lot as compared to any business sector because of the

nature and characteristics of goods they transact. The second sector that travels more in a

month is agricultural and livestock, followed by services, then non

buyers goes to the processing plant and buy directly them, as a result they only travel on few

situation when they been asked to deliver)

their products within Kabwe town (thus no need to travel out

to the researcher that transport was highly demanded in trading sector as it had a highest

rating on the number of trips travelled in a month.

ON OF TRIP TRAVELED BY BUSINESS SECTOR

he table above, shows 36 respondents of which the majority respondents

ere from trading sector consisting of 10 MSMEs, followed by agriculture


food processing consisting of 6 MSMEs and lastly was the

of 5 MSMEs.From the data above, it shows that more of the



tural and livestock, followed by services, then non-food processing (mainly


situation when they been asked to deliver), and lastly is food processing as they buy

Kabwe town (thus no need to travel out-side Kabwe town).


rating on the number of trips travelled in a month.

BY BUSINESS SECTOR.

he table above, shows 36 respondents of which the majority respondents who traveled many

consisting of 10 MSMEs, followed by agriculture


food processing consisting of 6 MSMEs and lastly was the food

From the data above, it shows that more of the



food processing (mainly


, and lastly is food processing as they buy most of

side Kabwe town).This revealed


4.1.1.5 THE PROPORTION OF RESPONDENTS BY MODE OF TRANSPORT USED.

Table/Chart 5(Five)

The entire five different business sectors in the sample size chose road transport (100%) with

the reasons being; it is faster and convenient as compared to rail, reliability and its frequency

(availability of different suppliers), prices are reasonable and they can be negotiated

depending on the situation prevailing (e.g. in rail and air transport, prices are not easily

negotiated), it is easier to travel in the mode as the goods are been transport from the point of

the sale and where they will traded.

4.1.1.6 THE PROPORTION OF RESPONDENTS BY PREFERENCE WHEN

CHOOSING MODE OF TRANSPORT.

Table 6(Six)

The above table reveals that 64 %( 23 of 36 MSMEs) of business sector sample valued safety

as the most important factor when choosing the mode of transport to use (trade having 30% of

23 MSMEs, service 26%, agricultural and livestock 22%, non-food processing13% and food-

processing 9%).The frequency of transport was the second best factor enterprises considered

(10 from 36 MSMEs) representing 28 % of the business sector sample and having the highest

in food and non-food processing having, thirdly was comfort having the highest rating in both

agricultural &livestock and service sector and lastly was reliability which was only

considered by MSMEs which were in trading sector. This meant that, the business sector

valued safety as the vital factor when choosing which mode of transport to use.

0

5

10

15

20

25

Agricultural

and Livestock

food

Processing

Trading Non-Food

Processing

Services Total

Safety

Reliability

Frequency

Comfort

4.1.1.7 THE PROPORTION OF RESPONDENTS BY PREFERENCE WHEN

MAKING A JOURNEY.

Table 7(Seven)

The data above shows that, 33.33 %( highest)

quantity of the product as the most important factor when business/enterprise is making a trip

representing a majority from trading

services both representing 22.22% of the sample

high quality of services than any other sector because of the nature of goods and commodities

they usually buy and income is mostly in considered in non

deals with high cost goods that nee

business travel (incurred expenses are paid

transport is highly considered in the service sector with a percentage of 13.89% and it shows

that MSMEs that are involved in service sector are only interest in time taken to travel to their

respective destinations and come

business sector selected showing only 8.33% of the total sample

MSMEs considers among the business sector viewed it as one of the most influencing factor

PORTION OF RESPONDENTS BY PREFERENCE WHEN

The data above shows that, 33.33 %( highest) from 36 respondents considers


representing a majority from trading sector. The second factors are income and quality of

services both representing 22.22% of the sample size. The agricultural and livestock considers

services than any other sector because of the nature of goods and commodities

they usually buy and income is mostly in considered in non-food manufacturing sector as it

deals with high cost goods that need to be properly apportioned before making an order or

expenses are paid the end of the month).Price of other forms of


re involved in service sector are only interest in time taken to travel to their

respective destinations and come back. Speed of transport is considered to be the least in the

showing only 8.33% of the total sample size; this means

MSMEs considers among the business sector viewed it as one of the most influencing factor

PORTION OF RESPONDENTS BY PREFERENCE WHEN

considers quality or


second factors are income and quality of

gricultural and livestock considers

services than any other sector because of the nature of goods and commodities

food manufacturing sector as it

d to be properly apportioned before making an order or

Price of other forms of


re involved in service sector are only interest in time taken to travel to their

d to be the least in the

this means neither of

MSMEs considers among the business sector viewed it as one of the most influencing factor.

4.1.1.8 THE PROPORTION OF RESPONDENTS

RELLATIONSHIP BETWEEN

EMPLOYMENT CREATION

Table 8(Eight)

The growth of MSMEs leads to jobs creation in the economy and less unemployment leads to

economic growth. From the sample size of 36 MSMEs ,28% (trading sector),22%(agricultural

and livestock),19%(services),17%(non

that effective demand of transport can lead to employment

highest percentage of job creation

sector. The following reasons gi

employment creation. When more trips are made, more vehicles are needed and hence more

drivers, co-drivers and conductors will be employed and effective demand for road transport

leads to road damages(number of trips increa

construction and maintenance and thus creating employment. When there is high effective

demand for transport, more mechanics will be needed for the maintenance of automobile

because wear and tear will be high

create employment.

HE PROPORTION OF RESPONDENTS ON HOW THEY VIEW THE

RELLATIONSHIP BETWEEN EFFECTIVE TRANSPORT DE

EMPLOYMENT CREATION.



and livestock),19%(services),17%(non-food processing),and 14%(food processing)

that effective demand of transport can lead to employment creation. Trading sector shows the

of job creation as it demands more of transport than any other business

s given by are how effective demand for transport can lead to

. When more trips are made, more vehicles are needed and hence more

drivers and conductors will be employed and effective demand for road transport

leads to road damages(number of trips increases) which in turn lead to road rehabilitation,



will be high due to number trips taken, distance covered and thus it

ON HOW THEY VIEW THE

TRANSPORT DEMAND AND



food processing),and 14%(food processing),all agreed

creation. Trading sector shows the

than any other business

demand for transport can lead to

. When more trips are made, more vehicles are needed and hence more

drivers and conductors will be employed and effective demand for road transport

ses) which in turn lead to road rehabilitation,



due to number trips taken, distance covered and thus it

4.2 Challenges Faced by MSMEs

The following are some of the challenges faced by the MSMEs in Kabwe town according to

the study and these are as following;

Cost of wages and salaries have increased on MSMEs that have their own freight or transport

carriers. This showed that most MSMEs had difficulties to meet the minimum wage

demanded by the government and hence they had difficulties to employ many drivers to meet

their workforce.

Road traffic congestion between Kabwe and Lusaka road had brought concern on Kabwe

MSMEs due to its increased road accidents and delays made because of congestion as it is a

major trade route used by Kabwe MSMEs.The cost of energy had increased especially

electricity which had made an increment on expenses in incurred and MSMEs in food

processing and production sector felt the impact, thus reduced its profit which would have

been used for expansion.

Lack of high technology automobile center for the servicing of vehicles especially the

automatic vehicles, light and heavy trucks. There are few or no automobile center for spare

part and skilled workforce for vehicles such as trucks, automatic and heavy duty trucks. This

had made MSMEs either to hire expert from other towns (Lusaka or Copperbelt) or toll the

vehicles (trucks) to Lusaka to be work on by experts. This had brought inconveniences and

increased operation cost on MSMEs. The other factor was poor road network within and

which increased the cost of operation (depreciation) on vehicles.

4.3.1 Regression Analysis In order to produce a proxy, we need to establish a functional relationship for total trips

traveled. As a result of this research, the functional model measurement will be represented

mathematically as follows:

TP= f (SS, GP, CGI, ST, µ)………………………….….. (a)

Where;

TP = Trips Traveled

SS - Standard of Service

GP – Good Price

CGI- Characteristics of Goods Involved

ST- Speed of Transport

µ- error term

In order to understand the relationship and significance of the variables above in the

objectives of this research and also applying to the testing of the hypothesis through the

transport economics theory of trip distribution and the econometric model can be expressed as

followed from (a) above:

TP =β0 + β1SS + β2GP + β3CGI + β4ST + µ……………………… (b)

µ= error term

β0= Constant term and

β1= the coefficient of the independent variable (SS) which β1 > 0

β2= the coefficient of the independent variable (GP) which β2 > 0

β3= the coefficient of the independent variable (CGI) which β3 > 0

β4 = the coefficient of the independent variable (ST) which β4 > 0

4.3.2 Results and Discussion of the model This section discusses the regression of the total trips traveled (TP) against the Standard of

Services(SS),Good Price(GP),Characteristics of Good Involved(CGI),and Speed of

Transport(ST) . The results of the model are described in the tables below:

4.3.3 One to Two Trips in Month

ANOVA Column1 Column2 Column3 Column4 Column5

Df SS MS F

Significance

F

Regression 4 0.86594203 0.216485507 1.363766049 0.269102377

Residual 32 6.77294686 0.211654589

Total 36 7.63888889

Column1 Coefficients

Standard

Error t Stat P-value

Lower

95%

Upper

95%

Intercept 1 0.46006 2.173633 0.03724228 0.063 1.9

Standard of service -0.65217 0.46995 -1.38774 0.17480461 -1.61 0.3

Good price 0 0 65535 #NUM! 0 0

Characteristics of goods

involved -0.77778 0.48495 -1.60385 0.11857369 -1.77 0.2

Speed of transport -1 0.53123 -1.88242 0.06889897 -2.08 0.1

The coefficient of determination, R 2, tells us that only 11.33 percent of the variation in data

values was explained by the regression line and 87 percent of the variables in the model are

not explained. The R2 is less than 0.2 as a result the fitted regression line is not of good fit and

it means that a very few MSMEs were affected by standard of services,price,characteristics of

goods involved and the speed of transport when making one to two trips in a month. They

were affected by other factors other than these mentioned above.

Regression Statistics Column1

Multiple R 0.336689299

R Square 0.113359684

Adjusted R Square -0.001012846

Standard Error 0.460059332

Observations 36

4.3.4 Three to Four Trips in Month



R Square 0.171497585

Adjusted R Square 0.062575483


Observations 36


Df SS MS F Significance F

Regression 4 1.371980676 0.342995169 2.207968902 0.091116931

Residual 32 6.628019324 0.207125604

Total 36 8


Standard

Error t Stat P-value Lower 95% Upper 95%

Intercept 1.443E-15 0.45511054 3.17031E-15 1 -0.92702983 0.92702983

Standard of

service 0.4782609 0.464898984 1.028741483 0.311314708

-

0.468707367 1.425229106

Good price 0 0 65535 #NUM! 0 0

Characteristics

of goods

involved 0.1111111 0.479728631 0.231612424 0.818313765 -0.86606413 1.088286352

Speed of

transport -1.41E-15 0.525516386 -2.6834E-15 1

-

1.070441844 1.070441844

4.3.5 Coefficient of Variation R-Squared (R2)

The coefficient of variation for this econometric model was found to be 0.1714975. This

implies that 17 percent of the disparity on total trips traveled was attributed to the variation on

standard of service, good price, characteristics of goods involved and speed of transport and

the remaining 83 percent of the variables in the model are not explained. The R2 is less than

0.2 as a result the fitted regression line is not of good fit. This shows that only a few of

MSMEs who traveled between three to four trips in a month were affected by standard of

services,price,characteristics of goods involved and the speed of transport and 83 percent of

the MSMEs were not affected.

4.1.3.5 Five trip and above in month



R Square 0.361349426

Adjusted R Square 0.270225934


Observations 36


df SS MS F

Significance

F

Regression 4 3.001207729 0.750301932 6.035215543 0.001034137

Residual 32 5.304347826 0.16576087

Total 36 8.305555556


Standard

Error t Stat P-value Lower 95% Upper 95%

Intercept 5.55E-16 0.40713741 1.363E-15 1

-

0.829311759 0.829312

Standard of service(SS) 0.173913 0.41589405 0.4181667 0.67862

-

0.673235418 1.021062

Good price(GP) 0 0 65535 #NUM! 0 0

Characteristics of goods

involved(CGI) 0.666667 0.42916051 1.5534203 0.13016

-

0.207504683 1.540838

Speed of transport(ST) 1 0.47012179 2.1271084 0.04122 0.042393265 1.957607

4.3.7 INTERPRETATION OF RESULTS 4.3.7.1 CONSTANT INTERPRETATION

The intercept value of 5.55112 was found, mechanically interpreted, means that if the values

of SS,GP,CGI, and ST rate were fixed at zero, the mean trip travel in a month would increase

by 6 trips in a month. This implies that, the number of trips will still increase by 6 when

standard of service, speed of transport and characteristics of good involved are held constant.

4.3.7.2 COEFFICIENTS INTERPRETATION:

4.3.7.2a Standard of service

0.173913 is the partial regression coefficient of SS and tells us that with the influence of GP,

CGI, and ST held constant, as SS increases, number of trips traveled in a month will increase

by 0.173913. The coefficient was positive and statistically significantly with t-test value of

0.4181667 at 0.05 level of significance. This means that, if standard of service increases by 1

percent, the number of trips increases by 17 percent

4.3.7.2b Characteristics of Good Involved

In the model, the partial regression coefficient of CGI was found to be 0.66667 which implies

that for every increase in characteristics of goods involved, the total trip travels rate increases

by 0.66667. The coefficient was positive and statistically significantly with t-test value of

1.5534203 at 0.05 level of significance. This economically means that, if there are new

transport vessels that can accommodate different characteristics of goods involved then the

number of trips will increase by 67 percent.

4.3.7.2c Good Price

The partial coefficient of GP was found to be 0(zero) and tells us that holding the influence of

SS, CGI, and ST coefficient, constant, the number of trips to be traveled in a month was still

be 0(zero) at 0.05 level of significance.Economically, it implies that the number of trips will

still increase even if price increases at any percentage rate as demand for transport is elastic.

4.3.7.2d Speed of Transport

The partial regression coefficient was found to as 1. This implies that as the total number of

trips in a month increase by 100%. This implies that there is a positive relationship between

trips in a month and speed of transport. The coefficient was found to be positive and

statistically significantly with t-value of 2.1271084 at 0.05 level of significance. This implies

that, the number of trips will increase by 100 percent when there is a 1 percent increase in

speed of transport vessels.

4.3.7.3a Coefficient of Variation R-Squared (R2)

The coefficient of variation for this econometric model was found to be 0.361349426. This

implies that 36 percent of the disparity on total trips traveled was attributed to the variation on

standard of service, good price, characteristics of goods involved and speed of transport and

the remaining 64 percent of the variables in the model are not explained. The R2 is greater

than 0.2 as a result the fitted regression line is of good fit.

4.3.7.3b F-test and its significance:

The F-test shows that the relation of the disparity in the regression to the ratio of the variation

of the residual or errors was found as 6.03521. This value found was greater than the tabulated

F-value of 0.0010 at 0.05 level of significance. This implies that the econometric model was

significant correct.

4.3.7.3c Proving the hypothesis

The findings of this study accept the null hypothesis and rejected the alternative hypothesis

which stated that determinant factors of transport with reference to the standard of services,

speed of transport and characteristics of goods involved have a positive impact on MSMEs

number of trips to be traveled. From the regression model, it showed that speed of transport

was a major determinant factor of transport demand by MSMEs as it was more elastic than

any other determinant factors (good price, standard of services and characteristics of goods

involved).It was found that MSMEs who had more trips in a month had R2 greater than 20%

as compared to those who had less trip. Thus determinant factors had a positive influence on

transport demanded by MSMEs.

4.3.7.3d Justification of Model

In literature, transport demand is influenced to a certain degree by the determinant factors.

The model shows that, there is a positive relationship between transport demand (trip travel)

and quality of service, income, time travel, price charged and etc. In this context, regression

model was being used as proxy of MSMEs travel demand model. The researcher found that,

the results obtained had a correlation with the previous studies carried by other authors in

literature review.

CONCLUSION AND RECOMMENDATION

5.1 Conclusion

From this research, most MSMEs who considered speed of transport as a main determining

factor could travel five trips and above in a month because of the reduced time taken.

Therefore a price charged on transport had no effect on the number of trips to be traveled in a

month as MSMEs were influenced by other factor such as their income, the importance of the

business trip and the distance to be covered because MSMEs still travelled even if price

charge on transport was increasing. If the speed of transport increase across the board, then

trips made in a month increases, causing an increase in demand for transport. Using the

number of trip traveled, shows that transport was highly demanded in trading sector with the

highest percentage rating as shown in tables 4.1.1.4 and least demanded in food processing.

Determinant factors (standard of service, characteristics of good involved, good price and

speed of transport) of transport encourage the number of trips to make in an economy. The

number of trips can change rapidly in response to changes in standard of service, price,

characteristics of goods involved and the speed of transport. The majority of enterprise in the

private sector especially the Kabwe MSMEs needs high speed of transport vessels, followed

by well manufactured transport vessel to accommodate the different characteristics of goods

to be involved and lastly high standard of service increased from transport operators to run

their businesses.

The research study identified three factors that determine the number of trips to be made and

these factors include; standard of service, characteristics of goods involved and the speed of

transport and encouraged MSMEs to demand more of transport modes in order to expand.

Furthermore the growth of MSMEs leads to jobs creation in the economy and less

unemployment lead to economic growth. In addition road transport in general despite the

determinant factors was used by the MSMEs in their transportation. Not only that road

transport had been found to have a positive impact on the MSMEs growth but also led the

MSMEs to demand more of transport

5.2 RECOMMENDATIONS There is need for other researchers to examine the transport providers on the standard of

services they provide, conditions, the price they charge and how it comes to effect on

MSMEs, and other related issues but time and resources could not allow.

The researcher makes recommendation for future research to be done on MSMEs and even to

other business sectors and different industries. The future researcher should also include other

determinant factor and also do a research on transport supply as to examine what determinant

factors makes transport providers to supply more of transport vessels (different transport

mode).

Government should set up business incubators that will incubate individual or groups of

individuals to operate enterprises. For it had showed that MSMEs demands more of transport

which in return would lead to more of employment creation (table 8). This would thus lead to

reduction in unemployment rate as a result it will bring promotion and development of

MSMEs. These bodies may also provide, managerial skills, accounting skills and transport

and logistics support for start up.

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EXAMINING THE KEY DETERMINANT FACTORS FOR TRANSPORT DEMAND

BY MSMEs IN DIFFERENT BUSINESS SECTORS (AGRICULTURAL AND

LIVESTOCK, TRANDING, SERVICES, FOOD PROCESSING AND NON-FOOD

MANUFACTURING)

APPENDIX

1. Name.............................................................................................................

2. Sex Male [ ] Female [ ]

3. Age Range:

16-25 26-35 36-45 46-55 56-65 Above 65

4. Highest formal education:

None primary Basic High

School

Certificate/Dip Degree Master & Above

SECTION 2: BUSINESS CHARACTERISTICS

1. Name of the

business....................................................................................................................

2. Contacts: Telephone..................................,Email................................................

3. In which sector does the business falls in? (Multiple answers is possible)

Agriculture

& livestock

Food

processing

Trading Non-food

manufacturing

Services Other Specify

4. Where does the business along the value chain?

Primary

producer

Primary

Supplier

Processor/Manufacturer Wholesale Retailer None

5. For how long have you been doing this business?

Less than a year 1-3 years ago 3-5 years ago 5-10 years ago Above 10 years

SECTION 3: QUESTION FROM SUBJECT AREAS OF RESEARCH

1. (a) Does the business have its own freight or transportation carriers? No [ ]

Yes [ ] and if yes

specify...........................................................................................................................................

(b) What is the main reasons for a business to have its transportation carrier?(if (a) was "yes")

.......................................................................................................................................................

.......................................................................................................................................................

3. Is the business registered with any association?

No [ ] Yes [ ] and if yes please

specify...........................................................................................................................................

4. How many times have you been on a business journey or a trip for the business in one

month?

One Twice Three times Four Five Above five times

5. How long does the journey takes?

Overnight 2-5days 6-10 days Above 10 day

Specify the distance if possible...................................................................................Kilometers

6. (a) How do you travel to your respective destination?

Private car Hired vehicles Public transport Coaches Other

(b) When coming from respective destinations, do you usually travel in the same mode of

transport where the goods/commodities are? Yes [ ] No[ ] And if so, why?

Ans.................................................................................................................................................

7. How affordable are the travelling fares/freight charges? Ans......................................

8. (a) Do you experience any problem during the travelling to the same destination?

Yes

(Specify)...............................................................................................................................

No [ ]

(b) What solution do you suggest to these problems?

.......................................................................................................................................................

9. Rearrange in chronological order of preference when choosing a specific mode of

transport? Ans...............................................................................................................................

[Standard of services-1] [Quality-6] [Speed-4] [Good price-4] [Characteristics of goods

involved-3]

10. Rearrange following in chronological order of preference when you are about to make a

journey (starting with the top priority things).e.g. 12345

[Quality or quantity of the product-1] [Price/other forms of transport-2] [Income-3] [Speed

of transport-4] [Quality of service-

5].Ans...........................................................................................................................................

11. How are the goods/commodities transported from the point of origin to their destination?

Road [ ] Railway [ ] Air [ ] other [ ]

12. What is the major reason for choosing the mode of transport in question 11?

.......................................................................................................................................................

.......................................................................................................................................................

13. What factors are needed to improve the transportation services in order to enhance the

MSMEs growth and stability?

a)..................................................................................................................................................

b)....................................................................................................................................................

c)....................................................................................................................................................

14. Does effective demand for transport lead to employment creation?

Yes [ ]

Specify…………………………………………………………………………………………

…………………………………………………………………………………………………

No[ ]

Specify………………….………………………………………………………………………

….………………………………………………………………………………………………

15. For long did it take in the past year for your business to acquire specific mode of transport

when it has been demanded for?

Ans………………………………………………………………………………………………

16. How long does it take now for the same transport to be provided when it has been

demanded for?

Ans……………………………………………………………………………………………

17. What are the key factor that has lead into this disparity (question 19 and 20)?

A)…………………………………………………………………………………………...

B)……………………………………………………………………………………………

C)……………………………………………………………………………………………

Documents

JIMMY SIKACHELELA FINAL RESEARCH REPORT