determinants of passenger brand preference decision …
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Marketing Management Thesis and Dissertations
2021-08-20
DETERMINANTS OF PASSENGER
BRAND PREFERENCE DECISION (A
CASE OF LONG-DISTANCE PUBLIC
TRANSPORT SERVICE IN BAHIR DAR
CITY STATION).
AHMED MOHAMMED
http://ir.bdu.edu.et/handle/123456789/12526
Downloaded from DSpace Repository, DSpace Institution's institutional repository
BAHIR DAR UNIVERSITY
COLLEGE OF BUSINESS AND ECONOMICS
DEPARTMENT OF MARKETING MANAGEMENT
DETERMINANTS OF PASSENGER BRAND PREFERENCE DECISION (A
CASE OF LONG-DISTANCE PUBLIC TRANSPORT SERVICE IN BAHIR
DAR CITY STATION).
BY:
AHMED MOHAMMED
JUNE, 2021
BAHIR DAR, ETHIOPIA
BAHIR DAR UNIVERSITY
COLLEGE OF BUSINESS AND ECONOMICS
DEPARTMENT OF MARKETING MANAGEMENT
DETERMINANTS OF PASSENGER BRAND PREFERENCE DECISION
(A CASE OF LONG-DISTANCE PUBLIC TRANSPORT SERVICE IN BA-
HIR DAR CITY STATION).
BY:
AHMED MOHAMMED
A THESIS SUBMITTED TO THE DEPARTMENT OF MARKETING MANAGEMENT,
COLLEGE OF BUSINESS AND ECONOMICS, BAHIR DAR UNIVERSITY IN PAR-
TIAL FULFILLMENT OF THE REQUIREMENT FOR THE DEGREE OF MASTER OF
ART IN MARKETING MANAGEMENT.
ADVISOR:
GASHAW M. (PhD)
©2021 AHMED MOHAMMED
JUNE, 2021
BAHIR DAR, ETHIOPIA
Declaration
I, Ahmed Mohammed, declare that this thesis entitled “The determinants of passengers‟ brand
preference decision a case of long-distance public transport service in Bahir Dar City station” is
my original work and has not been conducted for degree requirement in this and any other uni-
versity, and all the sources used to support this particular study have been accordingly acknowl-
edged.
---------------------------------
Signature
-----------------------------------
Name of the student
------------------------------------
Date of submission
Statement of Certification
This is to certify that this thesis entitled “the determinants of passengers brand preference deci-
sion a case of long-distance public transport service in Bahir Dar City station ”, is submitted in
partial fulfillment of the requirements for the degree of Master of Arts in Marketing Manage-
ment to the College of Business and Economics, Bahir Dar University, done by Ahmed Mo-
hammed is a genuine work carried by him under our guidance. (Gashaw M. (PhD).
Advisor: Gashaw M. (PhD)
Signature _________________
Date _____________________
BAHIR DAR UNIVERSITY
COLLEGE OF BUSINESS AND ECONOMICS
DEPARTMENT OF MARKETING MANAGEMENT
Approval Sheet
As members of the board of examiners, we examined this thesis entitled “ the determinants of
passenger brand preference decision a case of long-distance public transport service in Bahir
Dar City station ” prepared by Ahmed Mohammed. We hereby certify that the thesis is accepted
for fulfilling the requirements for the award of the degree of Master of Art in Marketing Man-
agement.
______________________ ________________ _________________
Internal Examiner‟s Name Signature Date
______________________ _______________ __________________
External Examiner‟s Name Signature Date
______________________ ______________ __________________
Chair Person‟s Name Signature Date
I
Acknowledgment
The greatest debt of gratitude is owed to my advisor Dr. Gashaw M. for His countless and con-
structive comments, suggestions, and guidance starting from the proposal work up to its comple-
tion of thesis work. My heartfelt gratitude was to the department head of Marketing Management
Mr. Elias S. for his great support and advice and statistician Dr. Awoke S. for his great support
during data analysis. And I owe a great deal of gratitude to Woldia University for its educational
sponsorship and financial supporter. My sincere gratitude goes to all my friends namely: Tilahun
Shewangezaw,Yohanis mekonnen, Oumer Mohammed, Mandefro Tagele, Tsadiku Setegn,
Melese Eniyew, Kasim Werkicho, Yemisrach Getie, Sara Mohammed, Belete Debasu, Wend-
imunegn Asrat, Seid Mohammed, Shambel Abate, and Yetnayet Mulat. Also, I would like to ex-
press my deepest gratitude to all passengers who are agreed and involved to fill the question-
naire.
Last but not the least, I would like to thank my family for their support and encouragement while
doing this paper.
THANK YOU ALL
II
LIST OF ACRONYMS
CSA: Central Statistical Authority
DF: Degree of Freedom
EFTA: Ethiopia Federal Transport Authority
ERA: Ethiopia Road Authority
FMCG: Fast Moving Consumer Good
GDP: Gross Domestic Products
GOF: Goodness of fit
LDBT: Long Distance Bus Transport
OLR: Ordinal Logistic Regression
OR: Odds Ratio
PBPD: Passenger Brand Preference Decision
POM: Proportion Odds Model
SAS/STAT: Statistical Analysis Software
SBPLC: Selam Bus Private Limited Company
SPSS: Software Package for Social Science
VIF: Variance Inflation Factors
III
Table of Contents
Acknowledgment ............................................................................................................................. I
LIST OF ACRONYMS .................................................................................................................. II
Table of Contents .......................................................................................................................... III
List of tables ................................................................................................................................. VII
List of figures ............................................................................................................................. VIII
ABSTRACT .................................................................................................................................. IX
Chapter One .................................................................................................................................... 1
1. Introduction ............................................................................................................................. 1
1.1. Background of the study .................................................................................................. 1
1.2. Statement of the problem ................................................................................................. 3
1.3. Specific research question ................................................................................................ 5
1.4. Objectives of the study ..................................................................................................... 5
1.4.1. The general objective of the study ............................................................................ 5
1.4.2. The specific objective of the study ........................................................................... 6
1.5. Significance of the study .................................................................................................. 6
1.6. Scope of the study ............................................................................................................ 7
1.7. Variable Definitions, Measurements, and Expected sign ................................................ 7
1.8. Organization of the paper ................................................................................................. 9
Chapter Two.................................................................................................................................. 11
2. Review of Related literature .................................................................................................. 11
2.1. Introduction .................................................................................................................... 11
2.2. Theoretical Literature Review ........................................................................................ 11
2.2.1. The concept of branding ......................................................................................... 11
2.2.2. Classification of Brands .......................................................................................... 12
IV
2.2.3. Brand Preference ..................................................................................................... 13
2.2.4. Types of Preferences ............................................................................................... 14
2.2.5. Theories of Brand Preference ................................................................................. 15
2.2.6. The natures of long-distance transport service ....................................................... 17
2.3. Determinants of Passengers‟ brand Preferences ............................................................ 18
2.3.1. Price ........................................................................................................................ 18
2.3.2. Availability of facilities .......................................................................................... 19
2.3.3. Brand Name Awareness .......................................................................................... 20
2.3.4. Brand attributes (Safety measure, customer care, and comfort) ............................. 21
2.3.5. Perceived service quality ........................................................................................ 21
2.3.6. Employee service .................................................................................................... 22
2.4. Empirical literature review ............................................................................................. 23
2.5. Conceptual Framework .................................................................................................. 26
Chapter three ................................................................................................................................. 27
3. Methodology of the study ...................................................................................................... 27
3.1. Introduction .................................................................................................................... 27
3.2. Description of the study area .......................................................................................... 27
3.3. Research paradigm ......................................................................................................... 28
3.4. Research approach.......................................................................................................... 28
3.5. Research design .............................................................................................................. 29
3.6. Target Population ........................................................................................................... 29
3.7. Source of Data and Collection technique ....................................................................... 30
3.7.1. Source of Data......................................................................................................... 30
3.7.2. Method of Data collection and instruments ............................................................ 31
3.8. Sample Size and Sampling Techniques ......................................................................... 32
V
3.8.1. Sample size ............................................................................................................. 32
3.8.2. Sampling Technique ............................................................................................... 32
3.9. Method of Data Analysis................................................................................................ 33
3.10. Model Specification .................................................................................................... 34
3.10.1. Logistic regression .................................................................................................. 34
3.10.2. Testing of Parallel Lines ......................................................................................... 37
3.10.3. Odds ratio (OR)....................................................................................................... 38
3.11. Ethical Consideration ................................................................................................. 38
3.12. Reliability and validity analysis ................................................................................. 39
3.12.1. Reliability Analysis ................................................................................................. 39
3.12.2. Validity Analysis .................................................................................................... 40
CHAPTER FOUR ......................................................................................................................... 41
4. DATA PRESENTATION, ANALYSIS, AND INTERPRETATION ................................ 41
4.1. Introduction .................................................................................................................... 41
4.2. Response Rate of sample respondents ........................................................................... 41
4.3. Demographic profile of the respondents ........................................................................ 41
4.4. Descriptive statistical analysis of the study.................................................................... 45
4.5. Inferential statistical analysis of the study ..................................................................... 51
4.6. Chi-square Test & Association measures....................................................................... 51
4.7. Regression analysis of the study .................................................................................... 53
4.7.1. Model Fitting Information ...................................................................................... 53
4.7.2. The goodness of fit test ........................................................................................... 55
4.7.3. Pseudo R-Square ..................................................................................................... 56
4.7.4. Test of Parallel Lines .............................................................................................. 56
4.7.5. Multicollinearity Test.............................................................................................. 57
VI
4.7.6. Ordered logistic regression parameter estimates .................................................... 59
4.7.7. Ordinal Logistic Regression: Odds Ratio Analysis ................................................ 66
CHAPTER FIVE .......................................................................................................................... 75
5. SUMMARY, CONCLUSION, AND RECOMMENDATION ............................................. 75
5.1. INTRODUCTION .......................................................................................................... 75
5.2. Summary of major findings............................................................................................ 75
5.3. Conclusions .................................................................................................................... 78
5.4. Recommendations .......................................................................................................... 78
5.5. Suggestions for Further Research Direction .................................................................. 80
Reference ...................................................................................................................................... 81
APPENDICES 1.1፡ QUESTIONNAIRE (ENGLISH VERSION) ............................................... 87
APPENDICES 1.2: QUESTIONNAIRE (AMHARIC VERSION) ............................................. 92
VII
List of tables
TABLE 1-1: VARIABLE DEFINITION, MEASUREMENT AND EXPECTED SIGN ...................................... 7
TABLE 3-1: CONSTRUCT VARIABLES RELIABILITY ......................................................................... 39
TABLE 4-1: GENDER FREQUENCY OF THE PASSENGERS: ................................................................. 42
TABLE 4-2: AGE CATEGORIES OF THE PASSENGERS ........................................................................ 42
TABLE 4-3: LEVEL OF EDUCATION ................................................................................................. 42
TABLE 4-4: THE FREQUENCY OF TRAVELING PREFERRED BUS BRAND............................................. 43
TABLE 4-5: INCOME LEVEL OF PASSENGERS ................................................................................... 44
TABLE 4-6: PRICE * PASSENGER BRAND PREFERENCE ................................................................... 45
TABLE 4-7: AVAILABILITY OF FACILITIES * PASSENGER BRAND PREFERENCE .............................. 46
TABLE 4-8: BRAND NAME AWARENESS * PASSENGER BRAND PREFERENCE .................................. 47
TABLE 4-9: BRAND ATTRIBUTES * PASSENGER BRAND PREFERENCE ............................................ 47
TABLE 4-10: PERCEIVED SERVICE QUALITY * PASSENGER BRAND ................................................ 48
TABLE 4-11: PERCEIVED SERVICE QUALITY * PASSENGER BRAND PREFERENCE ........................... 49
TABLE 4-12: DESCRIPTIVE STATISTICS FOR FACTOR AND OUTCOME VARIABLES ............................ 50
TABLE 4-13: INTERPRETATION OF ASSOCIATION OF VARIABLES .................................................... 51
TABLE 4-14: CHI-SQUARE TEST STATISTICS ................................................................................... 52
TABLE 4-15: MODEL FITTING INFORMATION: ................................................................................. 53
TABLE 4-16: GOODNESS OF FIT TEST STATISTICS ........................................................................... 55
TABLE 4-17: PSEUDO R-SQUARE ................................................................................................... 56
TABLE 4-18: PARALLEL LINE TEST OF PARAMETERS ...................................................................... 57
TABLE 4-19: MULTICOLLINEARITY TEST COEFFICIENTS ................................................................. 58
TABLE 4-20: TEST OF PARAMETER ESTIMATES ............................................................................... 59
TABLE 4-21: ODDS RATIO ANALYSIS .............................................................................................. 66
TABLE 4-22: TEST OF HYPOTHESIS ................................................................................................. 74
VIII
List of figures
FIGURE 2-1: CONCEPTUAL FRAMEWORK ....................................................................................... 26
FIGURE 3-1: PROVIDERS OF LONG -DISTANCE TRANSPORT SERVICE IN BAHIR DAR CITY STATION .. 27
FIGURE 4-1: BAR GRAPH INDICATION FOR OUTCOME VARIABLE MEASUREMENTS .......................... 44
IX
ABSTRACT
The purpose of this study was to examine the determinants of passenger brand preference deci-
sion in case of long-distance public transport service in Bahir Dar City station.Specifically, the
study sought to address the influence of price, availability of a facility, brand name awareness,
brand attributes (comfort, customer care, and safety measures), perceived service quality, and
employee service on passengers' brand preference decisions. The study used a positivism para-
digm with a deductive research approach and an explanatory research design to investigate the
significance level and the direction of its determinant. In this study, non-probability sampling
(convenience sampling) was used to select the sample respondents. The primary source of data
was used.This Primary data were gathered from a survey questionnaire, 385 questionnaires
were distributed and 366 were returned and analyzed with the use of both descriptive and infer-
ential statistics on SPSS Software version 23. And the reliability of the instrument was tested by
using Cronbach’s Alpha coefficient and further data analysis was performed with the help of
STATA/SE 14. From the spearman’s rho correlation test of association, it was founded that
brand name awareness, brand attributes, and employee service have statistically substantial/
strong and positive association, and price and perceived service quality have a statistically mod-
erate and positive association, and also the remaining availability of facilities have a statistically
weak and positive association with the response/predicted variable. It was analyzed by the ordi-
nal logistic regression model. In accordance, the finding of this study showed that except the
availability of facility which was insignificant or did not have an effect based on the finding of
the regression model, all other predictors/independent/ variables (price, brand name awareness,
brand attributes (comfort, customer care/ safety measures), perceived service quality and em-
ployee service) have a strong positive effect on passengers brand preference decision a case of
long-distance public transport service in Bahir Dar City station. To survive the present competi-
tive pressure and to take the bus as the preferred brand in the industry, the Road transport firms
should be required to manage and give more attention to the price charged, increase the level of
awareness, creation of comfort, customer care, and safety measures, provide a better quality of
service, and improve employees hospitality of service.
Keywords: Brand, Brand preference, Price, Brand attribute, Employee service, Brand name
awareness, Perceived service quality, Availability of facilities
1
Chapter One
1. Introduction
This chapter presents the background of the study, statement of the problem, objectives of the
study, specific research questions, significance of the study, scope of the study, variable defini-
tions, measurements, and expected signs, and organization of the paper.
1.1. Background of the study
Transport is one of the complex services which contributes a greater share to the country‟s eco-
nomic development.Everybody travels whether it is work, play, and shop or do business. over the
years there has been an ever-growing demand and need for public road transport over other
means of transportation for efficiency and the optimization in the balance of mobility of people
and cargo in the world at large. Providing service transportation that is adequate and appropriate
is the challenge encountered in almost all cities in the world. Cities will always have a new prob-
lem, which arises due to transportation system. In general, large cities in developing countries
are highly dependent on road transport. Increasing the number of residents and the use of motor
vehicles has caused social and economic problems for cities that are dependent on road transport
highways. Similarly, other problems will occur such as increased travel time and frequency of
accidents resulting from chronic road congestion, as well as environmental problems such as air
pollution, vibration, and extravagance of fuel consumption (Wijaya, 2009). Ethiopian transport
was started in 1942, when fascist Italy was driven out of Ethiopia, by accumulating vehicles and
spare parts used by the invader. In 1960 the government implemented a rule that the transport
operators governed to offer the transport service on regulated tariff to serve the people at a rea-
sonable price (Berhan, Beshah, & Kitaw, 2013).
According to (Moore & Reid, 2008), “A brand is a name, term, sign, symbol, design, or a com-
bination of these elements that is intended to identify the goods or services of a seller and differ-
entiate them from competitors.” A brand shows the meaning and direction of any product and
identifies the product with due to time and space. Brand may have several components including
brand name, brand image, logo, design, packaging, and promotion. As global brands have be-
come ubiquitous with clear, recognizable, standardized platforms worldwide based. Brand man-
2
agement argues that the global standardization of branding activities leads to consistent and well-
defined brand meaning and image across markets (Huang & Sarigöllü, 2014).
Branding began sometime around 1500 BC when the ancient Greeks marked their cattle, a prac-
tice that still exists in the livestock industry. However, branding initiatives relevant to an institu-
tional enterprise began in 1931, when Procter & Gamble started placing labels on its products to
help consumers differentiate one product from another. Shortly after the Second World War,
Ford and General Motors started in heated advertising battles, which continue today, as a means
of educating their audiences about the distinctive qualities of their respective products (Cas-
anoves-Boix & Kuster-Boluda, 2017).
The functions of brands have changed over the years. Brands are no longer treated just as differ-
entiation tools but have nowadays become vital for a firm's success. In addition to the tangible
assets of a firm, the intangible assets also generate its market value. Brands being intangible as-
sets are essential for a firm's existence. This emerging importance of brands emphasizes the need
to effectively manage the brand to maximize the profit as well as the value of the Firm (Bauer,
Donnevert, Hammerschmidt, & Maier, 2008).
Liberalization and globalization together with the ever-growing consumption culture made mar-
keting an unpredictable and competitive venture this further strengthen by the emerging of new
brands and the colony of giant global brands over domestic brands (Kachiga, 2008). The arbi-
trary marketing experience of people throughout the world indicates the fact that consumers
seem to have particular brand preferences irrespective of price and quality similarities (Kachiga,
2008).
Brand preference is closely related to brand choice that can facilitate consumer decision-making
and activate brand purchase. Knowing the pattern of consumer preferences across the population
is a critical input for designing and developing innovative marketing strategies. It also uncovers
the heterogeneity of consumer choices leading to efficient market segmentation strategies. How-
ever, forecasting consumer‟s preferences between brands is not an easy task. Most of the early
models focused on brand attributes in preference construction (R. Ebrahim, Ghoneim, Irani, &
Fan, 2016). Brand preference can be defined as the subjective, conscious, and behavioral tenden-
cies which influence a consumer‟s predisposition toward a brand. Understanding the brand pref-
3
erence of consumers‟ will dictate the most suitable and successful marketing strategies (Mohan
Raj, 2016). Brand choice or brand behaviors are the words that are used interchangeably for
brand preference which means that to identify the consumer choice among different brands. Con-
sumer brand preference is linked with brand loyalty, which means repurchase again and again
over a long time (Ghose & Lowengart, 2013). For consumers, brands reflect their experience and
knowledge; simplifying the processing of information accumulated over time about the company
and its products or brands. In addition, brands reflect consumer‟ experiences and knowledge;
thus, simplify the processing of information accumulated over time about the company and its
products or brands. Consequently, brands act as signals for products of high quality and low per-
ceived risk, thus, enable the consumers to capture both cognitive and non-cognitive values ex-
pressed in the positive feelings or self-expression experienced(R. S. Ebrahim, 2013).
Therefore this study aims to examine the determinants of passengers‟ brand preference decision
of long-distance public transport service in Bahir Dar City station. This study is inspired by the
academic demand of underscoring factors affecting passengers‟ brand preference decision in
public bus transport service.
1.2. Statement of the problem
Transport plays an important role in the development of the country. The demand for public
transport services in Ethiopia is growing from time to time with the growth of the population and
economy. The growth of business opportunities in the Ethiopia road Transport Industry has led
to the entrance of new, modern operators into the system. It is evident that in growing countries
of Africa, the number of vehicles continues to increase yearly as congestion increases and the
best thing to do will not be to build or widening the transport substructures- roads, airports but to
seek a balance and ensure optimum utility for the passengers and make available for them those
values that would attract them to public transportation. Building of terminals at strategic areas
within the towns/cities, employee service, awareness level, quality of service, creation of comfort
time utilization, cost-effectiveness, and safety could to a very large extent influence the passen-
gers on the choice of mode and means of transport to take/make. The road transport companies
in Ethiopia were mainly touting structured with little or no attention paid to safety, comfort, em-
ployee attitude towards passengers‟‟ availability, quality of service, and travel time/speed of the
4
bus. However, the availability of many travelers‟ in transport and long-distance road transporta-
tion has redefined the nature and pattern of competition in the transport sector (Mammo, 2010).
Now a day, companies compete in a global market that is undergoing difficulties in creating
long-lasting competitive advantages to ensure their survival. While traditional marketers
focus on consumer rationality and define the brand as a bundle of attributes, experiential
marketers focus on experience (Brakus, Schmitt, & Zarantonello, 2009) This is outlined in brand
marketing proposing consumer„s experiential responses to brand-related stimuli (Schmitt, 1999).
A few years ago, there were few long-distance public bus brands in Ethiopia namely Selam and
Sky Bus. Currently, there are several different names of public bus brands in Ethiopia including
Odda, Gada, Lima limo, Abay, Golden, Zemen, Dream liner, Africa, Air, Ethio, Yegna, Habe-
sha, and Walia Bus. Thus, increasing the number of buses and the availability of such different
brands in the market show the sign of competition in the bus companies and create brand prefer-
ence challenge among passengers. Most of the time the decision in brand selection the passen-
gers into doubts due to considering faith of management, safety, reliability, awareness lev-
el,charged price, hospitality of service, comfortability, and its determinant of passengers‟ brand
preferences.
As per the researcher's knowledge concerned , few researchers tried to find out the factors that
affect customer brand preference. Some of them are explained as follows. Research conducted
by (Lema & Negash, 2018) showed that quality of products, brand image, brand availability,
packaging, price, and advertisements have significant and positive effects on consumer brand
preferences of bottled water brands. The research conducted by (MENTESNOT, 2018) studied
that price, advertisement, emotional benefits, and quality of service have significant and positive
effects on consumer brand preferences of beer industries in selected hotels of Addis Ababa but
reference group is negatively affected. The other study was conducted by (Hunde, 2019) factor
affecting consumer brand preference for dairy products. The result showed that price, quality of
the products, brand name awareness, brand availability, and advertisement have significant and
positive effects on consumer brand preferences.
Even though the above researchers had reviewed good points on consumer brand preference re-
garding different service sectors, they did not study long-distance public bus transport service
5
related to passengers brand preferences, the previous researchers ignored the important variables
which affect consumers brand preference such as employee service, brand attributes (comfort,
customer care, and safety measures) and availability of facilities. To fill the above-mentioned
gap, the researcher was studied the effect of variables like price, availability of facilities, brand
name awareness, brand attributes (safety measure, customer care, and comfort), employee ser-
vice, and perceived service quality to examine the determinants of passengers brand preference
decision in case of long-distance public transport service providers in Bahir Dar city Bus. Hence
after investigation, the study tried to provide possible recommendations for long-distance public
transport service providers in Bahir Dar City station to be effective and competent.
1.3. Specific research question
Specifically, the researcher wants to answer the following questions:
1. To what extent does price influence the passengers‟ brand preference decisions?
2. To what level does brand name awareness influence passengers‟ brand preference deci-
sions?
3. Does the availability of facilities significantly influence their passengers‟ brand prefer-
ence decisions?
4. Do brand attributes (safety measure, customer care, and comfort) significantly influence
the passengers‟ brand preference decisions?
5. Does employee service significantly influence the degree of the passengers‟ brand prefer-
ence decisions?
6. Does perceived service quality significantly influence the passengers‟ brand preference
decisions?
1.4. Objectives of the study
1.4.1. General objective of the study
The main objective of the study was to examine the determinants of passengers' brand prefer-
ences decision in the case of long-distance public transport service in Bahir Dar city station and
at the same time, the study attempted to recognize the passengers' preference level of a specific
brand and also to give some research-based policy insight and measure concern on brand prefer-
ence.
6
1.4.2. Specific objectives of the study
1. To determine the effect of price on passengers' brand preference decision.
2. To examine the effect of brand awareness on passengers' brand preference decisions.
3. To analyze the effect of availability of facilities on passengers' brand preference decision.
4. To know the effect of brand attributes (safety measure, customer care, and comfort) on pas-
sengers' brand preference decisions.
5. To assess the effect of perceived service quality on passengers' brand preference decision.
6. To examine the effect of employee service on passengers' brand preference decisions.
1.5. Significance of the study
“All progress is born of inquiry and doubt is often better than overconfidence, for it leads to in-
quiry and inquiry leads into invention” is a famous Hudson Maxim in the context of which the
significance of the research can be assumed (C.R. Kothari, 2004).
The researcher believes that the result of this study will have a different benefit to different
stakeholders like a marketer, transport providers, communities, government, and other related
stakeholders thus it will present a significant help to marketers because the findings of the study
will assist marketers to look at the determinants of brand preference among their passengers‟
which in turn help in evaluating and reshaping their marketing strategies, and the study will serve
as an input for policy decisions to the public bus service sector by the government or policy
makers and the study will contribute by being a reference for other researchers who want to con-
duct further studies on the concept of passengers' brand preferences in the context of Ethiopia.
Moreover, it will spark some high lights about the most prominent contributors of passengers‟
based brand preference and the challenges it faces and the study will help the professional when
they want to implement a new marketing strategy in the country and assist the newly created
brand on marketing strategy implementation and this study will open pave for future researchers
who will undertake related studies also it will have some importance in narrowing the unfilled
gap in the existing literature.
In general, efficient transportation services are not only significant to public transport of cross
country buses but a crucial factor to the entire transport industry in particular and the economic
development of the country in general.
7
1.6. Scope of the study
This study was delimited conceptually, geographically, and methodologically.
Geographically, the study has covered passengers‟ brand preference decisions in the long-
distance public transport service in Bahir Dar City station. Conceptually; despite there was being
other market activities that influence passengers‟ brand preference decisions the focus of this
study focused on predictor variables such as price, brand name awareness, availability of facili-
ties, brand attributes, employee service, and perceived quality and the predicted variable is pas-
sengers‟ brand preference decision (PBPD) and this study was carried out between Dec, 23,2020
G.C up to June 24, 2021, G.C. Methodologically, the research design of the study was explanato-
ry and adopted a positivist research paradigm.
1.7. Variable Definitions, Measurements, and Expected sign
Table 1-1: Variable definition, Measurement, and Expected sign
No,
Variable
Concepts
Measurements and
no.of items
Ex-
pected
Sign
effect
1.
Price/ Affordability
The ability of the passengers‟
to pay for their transit. that
may be negotiated and speci-
fied in a contract between the
transportation provider and
that person buying the ticket.
1-5 Likert scale
Stronglydisagreeto
strongly agree,
4 items
(+)
2.
Availability of
facilities
It enables passengers to plan
their journeys, especially for
prospective passengers, and
provides various facilities like
food and water, cleanness,
proper window ventilation, set-
ting belt e.t.c
1-5 Likert scale
Strongly disagree to
stronglyagree
5 items
(+)
3.
Brand name
awareness
It is the awareness of the brand
in the mind of the customer
1-5 Likert scale
Strongly disagree to
8
and the aggregate of beliefs,
ideas, and impressions that a
customer holds regarding the
brand.
strongly agree
5 items
(+)
4
Brand Attributes
It is the connection between
brand characteristics and cus-
tomer perception that appeared
differences; the basic elements
are comfort, customer care,
and safety measures.
Comfort: - Service elements
that make journeys relaxing,
enjoyable, or productive, e.g.
through station facilities, seat-
ing and personal space, ride
comfort, vehicle condition, at-
mosphere, and complimentary
services such as onboard Wi-
Fi.
Safety/ security measures: -
The extents of the service free
from danger and injuries of
passengers/commuters and
Customer care: - Customer
interface, staff behavior and
attitudes, and ticketing options.
1-5 Likert scale
Strongly disagree to
strongly agree
5 items
(+)
9
5.
Perceived Service
Quality
Perceived service quality refers
to the level of quality as per-
ceived by the passengers dur-
ing their movements. Howev-
er, the way passengers per-
ceive service quality depends
on service quality dimensions:-
Reliable: - the consistencies of
the service delivery to the pas-
sengers.
Responsiveness: - the service
providers active and voluntary
to help their customers and
provide prompt service. This
dimension demands that the
service provider should be
more flexible in solving their
customers‟ problems and re-
quests.
Tangibles: - service provider
enhances their image and con-
veys quality service to custom-
ers.
Assurance: - refers to employ-
ee knowledge and courtesy and
the ability of the firm and its
employees to inspire trust and
confidence.
Empathy: - refers to afford
more facilities for the current
or potential customers and en-
hance the service capacity
through personalized or cus-
tomized service.
1-5 Likert scale
Strongly disagree to
strongly agree
7 items
(+)
Source: Researcher’s survey; 2021
10
1.8. Organization of the paper
The study was organized into five chapters. The first chapter presented the background of the
study, statement of the problem, specific research questions, and objectives, the significance of
the study, the scope of the study, and variable definitions, measurements, and expected signs.
The second chapter discussed the theoretical backgrounds, empirical analysis, and conceptual
framework of the study, and the third chapter is organized as the description of the study area,
research paradigm, research approach, research design, type of data, target population, sample
size and sampling technique, data collection instruments, method of data analysis, model specifi-
cation, ethical consideration, validity, and reliability also the fourth chapter elaborated the analy-
sis and results of the study and the final chapter comprised four sections such as a summary of
findings, conclusions, recommendations, and future research directions.
11
Chapter Two
2. Review of Related literature
2.1. Introduction
This chapter discusses the theoretical and practical aspects of passengers‟ brand preference for
long-distance public transport service around the globe, Africa, Ethiopia, and more specifically
Bahir Dar City, and also the hypothesis and conceptual framework of the study was drawn.
2.2. Theoretical Literature Review
2.2.1. The concept of branding
The term “brand” “originates from the Old Norse ‟brand meaning ‟to burn. The use term evolved
in Middle English to the practice of “marking permanently with a hot iron,” a practice used for
the marking of cattle and livestock. Historically, the concept of the brand was first used by the
ancient Egyptian brick-makers who drew symbols on bricks for identification (Farquhar, Han, &
Ijiri, 1991). Other countries' use of brands was found in Greek and Roman times; at this time,
due to illiteracy shopkeepers identified their shops using symbols. Moreover, in the middle ages,
craftsman marked their goods with stamps as a trademark by which to differentiate their skills.
The next milestone of brand evolved in North America with the growth of cattle farming as a
kind of legal protection, proof of ownership, and quality signals (de Chernatony & McDonald,
2003).
A brand is a name, term, sign, symbol, or design, or a combination of them intended to identify
the goods or services of one seller from among a group of sellers and to differentiate them from
those of the competitors. Thus, a brand identifies the seller or manufacturer. Under trademark
law, the seller is granted exclusive rights to the use of the brand name in perpetuity. This differs
from other assets such as patents and copyrights that have expiration dates. If a company treats a
brand only as a name, it misses the point of branding. The challenge in branding is to develop a
deep set of meanings for the brand. Perhaps the most distinctive skill of professional marketers is
their ability to create, maintain, protect, and enhance brands (Kotler, Asplund, Rein, & Haider,
1999). But a brand is more than the product it identifies “because it can have dimensions that dif-
ferentiate it in some way from other products designed to satisfy the same need. These differ-
12
ences may be rational and tangible related to product performance of the brand or more symbol-
ic, emotional, and intangible related to what the brand represents” (Kotler & Keller, 2012).
All the definitions above have common explanations. Which adds value, can identify and differ-
entiate a product/service from one to another. Moreover, a brand will be meaningful when con-
sumers able to create a mental association in their mind. (de Chernatony & McDonald, 2003)
offer a definition that incorporates many scholars' views. „A successful brand is an identifiable
product, service, person or place, augmented in such a way that the buyer or user perceives rele-
vant, unique added values which match their needs most closely. Furthermore, its success results
from being able to sustain those added values in the face of competition.
2.2.2. Classification of Brands
According to (Kotler & Keller, 2016) brand is classified into family, individual, national, private,
and umbrella brands.
A. Family Brand: A single brand name for all the products of a company and which are being
similar in quality.
B. Individual Brand: Brand name is given for each variety of products and each product of the
same producer will carry its brand used for dissimilarity.
C. National Brand: The same brand used on the national level manufacturers brands are com-
monly termed as national level.
D. Private Brand: Large wholesalers and retailers operation over the regional or national market
and placing their brand on the products that they market. These brands offered by wholesal-
ers and retailers are usually called private Brands.
E. Umbrella Brand: All products having the name of the company or manufacturer is called the
umbrella brand
Even though marketers try to evolve effective commercial centers that is why because there
exist many bus services in the market, the passengers have likely recognize them. So that in
this competitive market bus brand can be a strategic solution to passengers‟ recognize, recall
and select one bus than others.
13
2.2.3. Brand Preference
The word preference means the desirability, likeness, or choice of an alternative. Preferences are
above all behavioral tendencies (Zajonc & Markus, 1982). Brand preference is the consumer‟s
predispositions toward a brand that varies depending on the salient beliefs that are activated at a
given time; the consumer sadness toward a certain brand; the extent to which a consumer favors
one brand over another (Davis, 2014). It is a measure of brand loyalty in which the consumer
chooses a particular brand in presence of competing brands, but will accept substitutes if that
brand is not available (Baek & King, 2011). Again, (Davis, 2014) disclosed that brand preference
reflects a desire to use a particular company's product(s) or service(s) even when there are equal-
ly-priced and equally-available alternatives. Brand preference is noted to be a desire to seek out a
specific product or service even when it requires paying more or expending more effort to obtain
it. It is important to companies because it provides an indicator of their customers‟ loyalty, the
success of their marketing tactics, and the strength of their respective brands, and gives a com-
petitive edge to the brand and the producer (firm). For this study this definition for brand prefer-
ence is adopted: “the biased behavioural tendencies reflecting the consumers‟ predisposition to-
ward a brand”.
As pointed out by (G. Agu & Ogbuji, 2008), brand preference is driven by new and engaging
media that catch people on the run. To ensure that a brand is preferred to others, identifying the
target market, managing the legalities, securing celebrity endorsement among others have been
advocated by (G. Agu & Ogbuji, 2008). (Fournier, 1998) once pointed out that a brand is simply
a collection of perceptions that are held in the minds of the consumers and have no objective ex-
istence at all other than through the activities of the managers that administer it. The stronger the
brand position is in the consumer‟s mind, according to (Marginson, 2011) the more essential
source of differentiation it becomes, and this a fundamental competitive advantage. According to
(Isik & Yasar, 2015) brand preference is regarded as a key step in consumer decision making,
involving elements of choice. In establishing brand preference, consumers compare and rank dif-
ferent brands by focusing on their uniqueness. Brand preference is “the extent to which the cus-
tomer favors the designed service provided by his or her present company, in comparison to the
designated service provided by other companies in his or her consideration set,” with a consider-
ation set referring to brands that a consumer would consider buying soon (X. Jin & Weber,
2013).
14
2.2.4. Types of Preferences
The target audience might like the product but not prefer it to others. In this case, the communi-
cator must try to build customer preference by promoting quality, value, performance, and other
features. The communicator can check the campaign‟s success by measuring audience preference
after the campaign. The following are the types of preference (Kotler & Keller, 2016).
A. Homogeneous Preferences
B. Diffused Preferences
C. Clustered Preferences
D. Heterogeneous Preferences
A. Homogeneous Preferences:
A market is where the entire customer has roughly the same preference. The market shows
no natural segments. We would predict that existing brands would be similar and cluster
around the middle of the scale in both sweetness and creaminess (Kotler & Keller, 2016).
B. Diffused Preferences:
At the other extreme, customer preferences may be scattered throughout the space, indicating
that customer varies greatly in their preferences. The first brand to enter the market is likely
to position in the center to appeal to the most people. A brand in the center minimizes the
sum of total customer dissatisfaction. A second competitor could locate next to the first brand
and fight for market share or it could locate in a corner to attract a customer group that was
not satisfied with the center brand. If several brands are in the market, they are likely to posi-
tion throughout the space and show a real difference to match customer preference differ-
ences (Kotler & Keller, 2016).
C. Clustered Preferences
The market might reveal distinct preference clusters called natural Market Segments.
The first firm in this market has three options. It might position in the center hoping to appeal
to all groups. It might position in the largest market segment. It might develop several
brands, each positioned in a different segment if the first firm developed only one brand and
competitors would enter and introduce brands in the other segments (Kotler & Keller, 2016).
D. Heterogeneous Preferences
Customer preference heterogeneity may be the most important reason for segmenting in cus-
tomer preference. Taste and preferences differ among people. Some people are highly con-
15
cerned about the appearance of a product, whereas others are more concerned about func-
tionality. As preference heterogeneity increases the case for segmentation increases in
strength moreover; the greater the variability the large the number of profitable segments
present in a market (Kotler & Keller, 2016).
2.2.5. Theories of Brand Preference
Brand preferences represent consumer dispositions to favor a particular brand (Overby & Lee,
2006). It refers to the behavioral tendencies reflecting the extent to which consumers favor one
brand over another (R. Ebrahim et al., 2016). Brand preference is close to reality in terms of re-
flecting consumer evaluation of brands. In the marketplace, consumers often face situations of
selecting from several options (Dhar, Nowlis, & Sherman, 1999).
Consumer preferences for brands reflect three responses: cognitive, affective, and conative or
behavioral (Grimm, 2005). The cognitive components encompass the utilitarian beliefs of brand
elements (Zajonc & Markus, 1982). The affective responses refer to the degree of liking or fa-
voring that reflects consumer feelings towards the brand (Zajonc & Markus, 1982). The conative
or behavioral tendencies are denoted by (Zajonc & Markus, 1982) as the consumers predicted or
approached act towards the object. It is the revealed preference exhibited in consumers' choices
(Hsee, Yang, Gu, & Chen, 2009). (Chernev, Hamilton, & Gal, 2011) assumes that the association
of behavioral outcomes, such as willingness to pay and brand preference. These are assumed to
be associated with behavioral tendencies (Chernev et al., 2011). For most companies, their single
biggest asset is their brand. Since the road industry in Ethiopia has firms with different categories
of offering (brands); for instance, the shuttle services, the coach services, the mini-bus services,
etc., it becomes imperative to understand the key drivers of preference amongst passengers, es-
pecially given the competitive nature of the road transport industry in Ethiopia.
Passenger selection decisions are the behavioral outcome that precedes differentiation between
several alternatives and subsequent outcomes of consumer preferences (Dhar et al., 1999). Pref-
erences facilitate consumers‟ choices by enhancing their intentions towards the favored brand.
The actual passenger selection decision is likely to correspond to intentions; the mechanism of
intention formation provides evidence of persistent passenger preferences (Van Kerckhove,
Geuens, & Vermeir, 2012). The consistency between passenger preferences and choices adds to
16
the predictive validity of preference statement over attitude (Bither & Wright, 1977; Cobb-
Walgren, Ruble, & Donthu, 1995) report that attributes are a poor indicator of marketplace be-
havior. (Carpenter, Glazer, & Nakamoto, 1994) reported that the difficulty of altering consumer
preferences once they are developed, even if consumers discover the irrelevance of differentiat-
ing attributes to the brand. The bias position consumers constitute toward a certain brand, created
from comparative judgment between alternatives, reflects the brand strength (Biel, 1997). Thus,
changes in passenger brand preferences are reflected in the brand performance and market shares
(Sriram, Chintagunta, & Neelamegham, 2006). In addition, brand preference combines the de-
sired attributes and consumer perceptions; thus, it offers an indirect and unobtrusive way to as-
sess salient attributes (Sriram et al., 2006). Therefore, uncovering passenger brand preferences
are considered critical input to design successful brand strategy, brand positioning, and gives in-
sights into product development (Alamro & Rowley, 2011; Iglesias, Singh, Casabayó, Alamro,
& Rowley, 2011). Consequently, understanding brand preferences contribute to building strong
brands able to build a long-term relationship with consumers. Additionally, identifying patterns
of consumer preference across the population and uncovering consumer heterogeneity is vital for
designing and developing innovative marketing strategies (Russell & Kamakura, 1997), and effi-
cient market segmentation strategies (Horsky, Misra, & Nelson, 2006). Marketers need to know
how consumers trade-off between different brands before making their choices. Since the brand
preference has a direct influence on passenger brand selection and then segmenting the market
based on brand preference is more interpretable and managerially useful than using the desired
brand attributes (O'Connor & Sullivan, 1995).
Despite the importance of brand preferences, it is still guided by the expectancy-value theory and
the economic theory. This traditional view explains brand preferences as a utility function de-
rived from consumer„s beliefs of brand attributes. Thus, it provides a narrow focus (Hartmann,
Ibáñez, & Sainz, 2005). It is argued that this view focuses on the origins of rationality rather than
the preferences„ origin (Dhar et al., 1999). Moreover, these models are criticized for ignoring
other evaluative responses and the irrationality of consumers, such as the emotional experiences
(Allen, Machleit, Kleine, & Notani, 2005). In a
ddition to consumer„s beliefs on brand functional attributes, their beliefs on the brand symbolic
attributes such as the brand personality and image have been demonstrated to influence their
17
preferences (J. L. Aaker, 1997). However, the brand preference is still based on consumers cog-
nitive information processing constituting their brand knowledge structure. This perspective has
been criticized by the experiential view proposed by (Holbrook & Hirschman, 1982).
2.2.6. The natures of long-distance transport service
Transport has an important role to play in the economic growth and social development of Ethi-
opia. Land transportation in general, among other modes, and road transport, in particular, is the
most widely used transport sector all over the world. It also provides a base for local, national,
regional, and international flow of goods and passengers. (Tadesse, 2006) states that the road
transport sector plays a significant role in the national economy of developing countries through
direct contribution to GDP and employment. Indirectly it also provides the services that are in-
dispensable for the development of other economic sectors. Road transportation plays a vital role
in the distribution of essential goods and services from place to place (Kassa, 2015).
In Africa, road transport is the dominant mode of motorized transport that accounts for 80% of
the goods traffic and 90% of the passenger traffic in the continent. Three modal systems of
transport exist in the country (road, air, and rail). Nonetheless, studies that were conducted in the
country, ERA (2005) and EFTA (2011), note that about 99.31% of all passengers use road
transport for their mobility, 0.65% use airlines, and 0.04% use railway transport. This indicates
that the mobility of the society is highly dependent on the road transport industry rather than oth-
er modes (ERA, 2005). And the Ethiopian Federal Transport Authority EFTA (2011) reports that
the sector is facing certain challenges because the entire population of the nation relies on road
transport much more than on other alternative modes. There is also the prevalence of poor quali-
ty services in the sector. As a result of this report, it can be noted that the existing road passenger
transportation of the nation is not satisfactory. This implies that it is important to maximize ser-
vice satisfaction in the industry.
(Authority, 2011) EFTA (2011) report indicates that there is a slight growth in the passenger
transport industry, particularly in the medium commercial passenger transport (about 15.7%).
The maximum growth (74.7%) is registered in the small commercial passenger road transport
sector such as the minibusses, while long-distance buses show a slight increase (9.6%). The re-
port further indicates that in 2010, the total number of passenger transport vehicles that rigorous-
18
ly served society was 13,684. Of these, about 7.75% were long-distance buses with 44 and more
seats and the rest 12,623 (about 92.25%) were buses with 24-44 seats. This indicates that the
growth of cross-country commercial passenger transport is relatively small in terms of quantity.
Concerning the number and types of buses by levels, in 2010 only 23 buses worked as level one,
381 as level two and 657 as level three. Level three comprises only about 61.9% of all buses in
the nation (EFTA, 2011). This puts the adequacy of the service provision into question.
Again, concerning the passengers transported, the CSA (2009) reports passenger and freight
transport activities in the nation. It indicates that from 2004 to 2008, the growth rate of transport-
ed passengers by medium and large passenger road transport has risen from 4.1% to 6.7%
(SBPLC, 2009). In terms of vehicle spread in the country, Ethiopia holds more than 75% of ve-
hicles in the country, which is about 400,000; about 130,000 vehicles in 2004 were located in
Ethiopia.
2.3. Determinants of Passengers’ brand Preferences
There are different reasons to choose one brand than others. So many important elements might
have a strong influence on long-distance public transport services.
"The most situations facing every business are to identify the factors determining preferences for
the brands with supporting reasons which affect consumer preference".(Dhar & Simonson,
2003)), further, (Wilson & Schooler, 1991) found that "subjects who had analyzed their reasons
for liking different brands of jams subsequently expressed preferences that corresponded less
well to those of experts than the preferences of subjects who did not analyze the reasons for their
attitudes".
2.3.1. Price
In the road transport industry, the fare and other service charges represent the price paid by pas-
sengers‟. Some road transport passengers‟ may be price sensitive; demanding economic pricing,
while others may be innovators who value good quality services at any cost. (Davidson et al.,
2007). (Macdonald & Sharp, 2000) stated that price can be used as a reason for brand preference
in two ways; either by going for the lowest price to escape financial risk or the highest price to
achieve product quality.
19
(Foster & Cadogan, 2000) argued that price is probably the most important consideration for the
passengers‟.And to (Peter & Donnelly, 2007) the price of products and services often influences,
whether passengers will securing them at all and if so, which competitive offering is selected.
For some offerings, higher prices may not deter purchase because passengers believe that the
products or services are high quality or more prestigious. However, many of today‟s quality-
conscious passengers may buy products based on price than other attributes. Therefore, a better
understanding of how consumers use price information in choosing among alternative brands
within frequently bought product categories helps to evaluate it and knowing the intensity as
compared to other factors or reasons.
H1: The price has a statistically positive and significant effect on passenger brand pref-
erence decisions.
2.3.2. Availability of facilities
Consistency of resources and availability of different facilities are vital for preference of brand.
According to (Chen & Chang, 2008) convenience of facilities has a significant impact on c pas-
sengers‟ brand preference. Details of routes operated, points at which vehicles may load and un-
load passengers, places served along each route, final destinations of routes, and service opera-
tion time-tables which include departure times from terminals, times at major intermediate stops,
and arrival times at the destination are important information that should be made available to
passengers (Ranawana & Hewage, 2015). In other words, easy access to brands is vital when
preferring the service. Certainly, distribution channels and location are important to brand acces-
sibility.
Moreover, (de Chernatony & McDonald, 2003) states that passengers are not motivated to search
out low involvement brands, manufacturers should ensure wide availability. Any out-of-stock
situations would probably result in passengers switching to an alternative brand. Within the con-
text of passengers‟ decision making, especially when evaluating potential alternative brands dur-
ing the pre-purchase stages, the evoked set refers to the specific brands passengers consider
when making an obtaining within a specific product category (Lin & Chang, 2003).
Furthermore, once passengers‟ are inside a store, little evaluation is made of competing brands,
therefore locating a brand at eye level or very close to the checkout counter is an important fa-
cilitator of brand selection (de Chernatony & McDonald, 2003). Products that are convenient to
20
buy in a variety of stores increase the chance of consumers finding and buying them. When the
passengers are seeking low-involvement products they are unlikely to engage in extensive
search, therefore readily available is important (Peter & Donnelly, 2007).
H2: Availability of facilities has a statistically significant positive effect on passenger
brand preference decision.
2.3.3. Brand Name Awareness
Several researchers have found brand name awareness to be an important element that plays a
vital role in consumers' preferences of brands. (Lin & Chang, 2003) established in their study
that brand awareness has the most powerful influence on consumers' purchase decisions. Nota-
bly, consumers with high brand awareness do not always spend a great deal of time or cognitive
effort in making purchase decisions. They often try to minimize decision-making by using heu-
ristics such as I buy the brand I have heard of or choose the brand I know or purchase only famil-
iar, well-established brands (Ailawadi & Keller, 2004).
According to (Ailawadi & Keller, 2004) brand awareness includes both brand recognition and
brand recall performance. Brand recognition is the ability of consumers to recognize prior
knowledge of a brand when they are asked questions about that brand or when they are shown a
specific brand. While the brand recall is the potential of consumers to retrieve a brand from
memory when given the service, needs to be satisfied by that category or buying scenario as a
signal.
Brand awareness will increase the likelihood of a brand to be a member of the consideration set,
the handful of brands that receive serious consideration for purchase. A brand that has some level
of brand awareness is far more likely to be considered and therefore chosen than brands, which
the consumer is unaware of (Sundar & Pandey, 2012).
According to (Ailawadi & Keller, 2004), brand awareness can be created by the increasing famil-
iarity of the brand through repeated exposure, although this is generally more effective for brand
recognition than for brand recall. That is the more a consumer experiences the brand by seeing it
hearing it or thinking about it, the more likely is that the brand will become strongly registered in
memory. The source of awareness can be a wide range of communication options such as adver-
21
tising and promotion, sponsorship and event marketing, publicity and public relation, point of
sale displays, and outdoor advertising. However, as (Sundar & Pandey, 2012) explain, other un-
controllable factors such as word of mouth can help to maintain and enhance brand awareness.
Furthermore, (Gylling & Lindberg-Repo, 2006) state that being aware of the brand leads to brand
familiarity which in turn results in a level of comfort with the brand. A familiar brand is more
likely to be selected than an unfamiliar brand because often the familiar brand is viewed as relia-
ble and acceptable quality compared to the unknown brand. The familiar brand is likely to be in a
consumer's evoked set (consideration set), whereas the unfamiliar brand is not.
H3: Brand name awareness has a statistically significant positive effect on passenger
brand preference decision.
2.3.4. Brand attributes (Safety measure, customer care, and comfort)
The factors like customer care, security features, safety features, and driving comfort were the
prominent factors that influenced the brand preferences. Trustworthiness and customer feeling or
association towards a brand are the most dominant factors influencing brand preference (Mohan
Raj, Sasikumar, & Sriram, 2013).
Good seats with available space to move easily, good heating and ventilation systems, a high
proportion of seated to standing passengers, low step heights (to facilitate the access by disabled
passengers), good maintenance standards so that the interiors of buses are in a good state of re-
pair and good standards of cleanliness, low level of crowding, smoothly driven buses particularly
where standing passengers are carried, good protection and resting facilities for waiting for pas-
sengers at bus stops and stations, good discipline at bus stops and onboarding the vehicle so that
passengers are being protected from jostling or losing their places in a queue are highly required
by passengers and determine their level of comfort and satisfaction (Anjulo & Gebeyehu, 2019).
H4: Brand attributes (safety measure, customer care, and comfort) have a statistically
significant positive effect on passenger brand preference decision.
2.3.5. Perceived service quality
Quality has no specific meaning unless related to a specific function and/or object. Passengers
always compare the quality of alternatives concerning price within a category (B. Jin & Suh,
2005). According to (Swanson & Davis, 2003) perceived service quality is directly related to the
22
reputation of the firm that manufactures the product. Perceived quality is also regarded as the
degree to which a product provides key consumer requirements and how reliably these require-
ments are delivered. Whereas (D. A. Aaker & Jacobson, 1994) said that perceived quality is not
the actual quality of the product, rather, it is 'the consumer's judgment about a product's overall
excellence or superiority. Product quality is conformance to requirements (Tsiotsou, 2006) en-
compassing the features and characteristics of a product that satisfy stated needs. The common
element of the business definitions is that the quality of a product or service refers to the percep-
tion of the degree to which the product or service meets the consumer's expectations.
Literature and studies found out that perceived quality is the major factor that enables consumers
to prefer one brand over another. Quality is important for affecting brand preference. Because it
is the portions of personal risk that, a consumer takes on the decision-making process and in
evaluating the purchase of a product (Hoyer, Chandy, Dorotic, Krafft, & Singh, 2010). Moreover
(Bornmark, Goransson, & Svensson, 2005) found out that perceived quality help consumers to
reduce the risk; the consumers trust the brand and know what they will get. (Sarwade &
Ambedkar, 2011), (Vikkraman & Dineshkumar, 2012) and (Jain & Sharma, 2012)found quality
as a major determinant of brand preference.
H5: perceived service quality has statistically positive and significant effects on passen-
ger brand preference decision.
2.3.6. Employee service
Those people who are involved in delivering service for passengers. They are directly, or indi-
rectly, involved in the transport company. Transport employees can be personnel including oper-
ators, drivers, ticket sellers, and others. (Ivy* & Naude, 2004) stated that people are not a highly
influential element in the context of prospective customers. Disagreement was raised by
(Amofah, Gyamfi, & Tutu, 2016) who argued that services depend on the people who deliver
them, as they directly involve in the customer experience of the service. (Budd, 2004) also stated
that it takes happy employees to make a customer happy. (Amofah et al., 2016) supported that
customer satisfaction largely rest on the quality of service provider encounter. Receiving cus-
tomers with smiling faces, friendliness, politeness, understanding customers' problems, and oth-
ers have a positive effect on customer choice (Mahmood & Khan, 2014). Their argument was in
23
support of (Jones & Dent, 1994) who found that a smiling face has a valuable effect on customer
choice. There‟s no use in creating a great brand, innovative product, or amazing social media
presence if you don‟t have the right people behind you. It‟s integral to the survival of your busi-
ness that you make sure that all of your employees, no matter how behind-the-scenes or custom-
er-facing they are, have fair training and a considerable understanding of their role and the im-
pact that it has within transport company.Employing and retaining the right people is imperative
in both the long and short term success of Transport Company.Haring unqualified workers and
insufficient employee training can both lead to poor customer‟s service. Competent people must
be employed and educated thoroughly in the firm‟s customer‟s service philosophy.They must
knowwhat their responsibilities are and what actions they empowered to take in order to satisfy
the customers.Workers must thoroughly understand what management expects of them so that
customers can be treated accordingly. It is crucial that these employees understand the critical
role they play in providing customer satisfaction and receive the training necessary to carry out
their tasks.
H6: Employee services have a statistically significant positive effect on passenger brand
preference decision.
2.4. Empirical literature review
This part involved prior researches that were done within brand preference in the past. It argued
the rationale of the researches, which have related concepts with the research question of this
study finding, methodologies, implications, and recommendations for researchers and practition-
ers has been explained.
Preferences are a crucial feature of everyday decision-making. They are a vital element in many
reasoning tools. Preferences are often used in collective decision making when multiple agents
need to choose one out of a set of possible decisions; each agent expresses its preferences over
the possible decisions, and a centralized system aggregates such preferences to determine the
willing decision (Rossi, Venable, & Walsh, 2011)
According to (Chimboza & Mut, 2007) investigate the determinants of brand preference in the
context of the dairy product market in Zimbabwe using a sample of 90 survey respondents. Us-
ing exploratory factor analysis, the researchers identified four factors as key determinants of
dairy product choice namely promotion, price and availability of a product, attractive packaging,
24
and product quality. Of these, the promotion of dairy products was the most important determi-
nant of brand choice.
According to (Vikkraman & Dineshkumar, 2012) conducted a study on consumers' brand Prefer-
ence towards FMCG (Dental Care) Products, in India, by using a quantitative research technique
(survey on 200 consumers as a sample). Through descriptive analysis, the researchers found out
that consumers give more preference towards the quality of the product followed by the price,
design, sales, and service.
According to (Jain & Sharma, 2012) the study on brand awareness and consumer preference for
FMCG products in rural market of Garhwal region in India. As per the study brand quality,
Price, easy availability, family liking, were found to be the most important variables for brand
preference. (Usha, 2007) employ a randomly selected sample size of 180 respondents in Kolar
District, in India, to study the buying behavior of consumers towards instant food products. As
per the study, customers considered the best quality and ready availability for preferring a partic-
ular brand of product or service.
According to (A. G. Agu, Ikenna, & Ben, 2017) the study was conducted on determinants of pas-
senger preference for long-distance shuttle services in Nigeria using a sample of 217 passengers‟.
This study was found that product, place, people, physical evidence, and process variables are
significant drivers of passenger preference for road transport operators, while price and promo-
tion variables are weak drivers. This study provides insight into the key service factors that drive
road transport customers‟ patronage and loyalty.
According to (Lema & Negash, 2018) the study was conducted on identifying determinant fac-
tors of consumers' brand choice on bottled water products in Ethiopia using a sample of 400 bot-
tled water consumers‟.The study was adopted a descriptive and explanatory research design with
a cross-sectional survey strategy. This study was found that packaging, product quality, price,
brand name, brand availability, brand image, and advertisement were significantly associated
with consumers' brand choice for bottled water products. However, the influences of brand im-
age, brand name, packaging, and price on consumers' brand choice decisions were more contrib-
uting than others.
25
According to (MENTESNOT, 2018) to the study was conducted on assessing the factors affect-
ing consumers‟ brand preference of beer products in selected hotels operating in Addis Ababa
city by using a quantitative research technique (survey of 200 consumers as a sample). A de-
scriptive and explanatory type of research design was employed as the main research design for
this study. Though the finding indicated that among the determinant factors of beer brand prefer-
ence the most important determinants of beer preference were quality, emotional benefit, and
advertisement, followed by the price of the beer. There is a significant and positive relationship
between the brand preference of beer products and its determinants quality, price, emotional
benefit, and advertisement but the reference group is negative affects the brand preference of
beer products.
According to (Hunde, 2019) the study was investigated factors affecting consumer brand prefer-
ence for dairy products using a sample of 382 consumers' the Council housing units. The result
showed that price, quality of the products, brand name awareness, brand availability, and adver-
tisement have significant and positive effects on consumer brand preferences. Both descriptive
and ANOVA, two-tailed t-test, and multiple regression were employed.
26
2.5. Conceptual Framework
Many studies are focusing on the determinants of brand preference. But no extensive and ex-
haustive study has focused on the determinant of passenger brand preference concerning cross
country public bus transport service. Hence the present study attempts to fill this gap in the exist-
ing literature by shedding light on the factors determining the preference of bus brands by the
passenger in Bahir Dar City Station.
Figure 2-1: Conceptual Framework
Independent variable Dependent variable
Source: - Conceptual model adapted and modified from (Kotler, Wong, Saunders,
& Armstrong, 2007; Ranawana & Hewage, 2015).
Passenger Brand
Preference Decision
Price
Availability of facilities
Availability
Brand Name Awarenes
Brand Attributes
Employee Service
Perceived Service quali-
ty
27
Chapter three
3. Methodology of the study
3.1. Introduction
This chapter presented the methodology part of the research. It included the description of the
study area, research paradigm, research approach, research design, target population, type of data
and data collection technique, sample size and sampling technique and instruments, method of
data analysis, model specification, ethical considerations, and validity and reliability.
3.2. Description of the study area
Bahir Dar city is connected through road transportation service to another city around the coun-
try. The city is a home to various long-distance trans port bus services such as Abay, Africa,
Dream liner, Ethio, Golden, Habesha, Walia, Yegna, and Zemen buses are available for passen-
gers.
Figure 3-1: providers of long-distance transport service in Bahir Dar city station
ABAY BUS
ZEMEN BUS
ETHIO BUS
YEGNA BUS
DREAM LINER
BUS
GOLDEN BUS
HABASHA BUS
WALIA BUS
AFRICA BUS
28
3.3. Research paradigm
The paradigm means a shared belief system that influences the kind of knowledge the researcher
seeks and how it can be interpreted (Morgan, 2007). A collection of common beliefs and agree-
ments exchanged/ shared between scientists about how problems can be understood and ad-
dressed are called research paradigm as cited in (Krauss, 2005). Positivism (also known as logi-
cal positivism) holds that the scientific method is the only way to establish truth and objective
reality. It holds that the methods, techniques, and procedures used in the natural sciences offer
the best framework for investigating the social world. The term „positivism‟ was used to reflect a
strict empirical approach in which claims about knowledge are based directly on experience; it
emphasizes facts and the causes of behavior. Positivism typically applies the scientific method to
the study of human action. Positivist believed that there is a single reality which could be meas-
ured and known and they committed to value neutrality, statically measurement, quantifiable el-
ements, and observable events to establish causal laws. Positivism today is viewed as being ob-
jectivist (Bogdan & Biklen, 2003). Therefore for this study, the study was used the positivism
paradigm because of its emphasis on the occurrence of the events and their causes and effect, and
the study is neutral from the variables being studies.
3.4. Research approach
For any research process, the researchers refer to two broad categories of reasoning called deduc-
tive and inductive reasoning. A deductive approach starts its work from more general to detail
specific and sometimes informally it is called a "top-down" approach. In this method, the conclu-
sion is logically based on the available facts. It starts with theory continued with hypothesis and
observation and finally, confirmation would take. On the other hand, Inductive reasoning works
with moving from specific observations to broader generalizations and theories. Informally,
sometimes we call the bottom-up approach. In this approach, conclusions are made based on
premises and it involves uncertainty (Burney, 2008). In inductive, arguments can be based on
experience or observation while in deductive, arguments are based on laws, rules, or other wide-
ly accepted principles. (Creswell, Hanson, Clark Plano, & Morales, 2007) defined that a deduc-
tive researcher “works from the „top-down, i.e. start from theory to hypotheses to data to add to
or contradict the theory. But, an inductive researcher is someone who works from the “bottom-
up, by using the participants‟ view to build broader themes and generate a theory and intercon-
necting the themes. The first philosopher of science, Aristotle, seized that induction was neces-
29
sary to develop valid theories and thus logically preceded deduction, it is important for testing and
further refining theories (Harriman, 2010).
The study built a deductive (quantitative) research approach because it tests the validity of as-
sumptions (or theories/hypotheses) in hand and as the study starts with theory from different lit-
erature, and designed to test this theory, and it is analyzed quantitatively, so deductive research
approach was appropriate. As mentioned earlier, the main characteristics of deductive research
approaches are an explanation of the interrelation of concepts and variables and also it enables to
measure facts quantitatively (Saunders, Lewis, & Thornhill, 2007).
3.5. Research design
Research design means a blueprint or procedures for collecting, analyzing, interpreting, and re-
porting data during the research process (Creswell et al., 2007). It is also referred to as the over-
all plan to connect conceptual research problems with achievable empirical research. Research
design sets out data requirement procedure, the methods applied for collecting and analyzing this
data, and show how all this procedure going to answer the basic research question (Owen, 2014).
The three forms of research design are explanatory, exploratory, and descriptive.
Descriptive type of research design sets out to explain and account for the descriptive infor-
mation. The descriptive study asks “what” kind of questions; while the explanatory study asks
the “why and how” type of questions (Owen, 2014). This type of research design would build on
exploratory research design and goes on to identify actual reasons a phenomenon occurs. It fo-
cuses on the causes or reasons behind the problem occur and provides evidence to support or re-
but an explanation or prediction. It is investigated to find out and report some relationships
among different variables under study. The main emphasis of explanatory research design is
studying a problem or situation to explain the relationship between variables or to test whether
one event causes another (Creswell et al., 2007).
Therefore, this study employed explanatory research designs with survey methods as the study
aims to explain the determinants of passenger brand preference decisions. The explanatory re-
search design was used to investigate the determinants of passenger brand preference decisions.
3.6. Target Population
All the items under consideration in any field of inquiry constitute a population. (Sekaran &
Bougie, 2016) defines a population as “the entire group of people, events, or thing of interest that
30
the researcher wishes to investigate”. The research population refers to the targets that the re-
searcher plans to use for an investigation (Freeman, Robson, Bates, & Sierra, 2008) or it may
also be referred to as a researcher‟s target population (Robertson, 2009).
The population for this study is infinite. The passengers availing of the long-distance public
transport service from Bahir Dar City Bus cannot be ascertained.
The passengers/commuters prefer/choose long-distance public transport service in Bahir Dar
City station maybe girls and boys, men and women, rich and poor. Data was gathered at the
place of contact with the target user and for information availability and basic educational back-
ground at least.
3.7. Source of Data and Collection technique
3.7.1. Source of Data
Data collection means a process by which information on the variable of interest was collected
and measured in an established systematic fashion which enables to answer stated research ques-
tions, testing the derived hypothesis, and evaluating the outcomes. An accurate data collection
procedure is important for maintaining the research integrity regardless of the field of study/
preference to define data (quantitative or qualitative) (Punch, 2013).
For statistical analysis, data collection plays an essential role. The two main data gathering
methods in research are primary and secondary data sources. Primary data is data that is collect-
ed for the first time by the researcher. Or it is factual/original information and is collected for the
aim of getting a solution for the problem at hand. Primary data cannot be published yet and it is
reliable, authentic, and more objective than secondary data. It can‟t be changed by human beings
due to that its validity is greater than that of secondary data. The sources of primary data are sur-
veys, experiments, observation, questionnaires, and interviews (Ajayi, 2017).
On the other hand, secondary data is data that is already collected or produced by other individu-
als and it is the analysis and interpretation of the primary data. Secondary data can be collected
through different sources like books, journals internal records, government publications, web-
sites, etc (Ajayi, 2017).
Therefore, this study was based on primary data. That is why because it was important for the
investigator to collect specific data for the problem under investigation and there is no doubt
31
about the quality of the data collected. In which the researcher was prepared the questionnaires
that were distributed to passengers of long-distance public transport service in Bahir Dar City
Bus.
3.7.2. Method of Data collection and instruments
In research, there were different methods and instruments for gathering data. It might be from
primary data which was collected through questionnaires, interviews, and observation. Second-
ary data is data that is initially collected by someone else. Secondary data would be collected
through books, magazines, journals, reports, and different company documents. The researcher
would use primary data which is collected through self-administered questionnaires with close-
ended questions. A questionnaire means a data-gathering instrument from respondents which
consists of a series of questions. A questionnaire is important than others because it is cheap and
could not require much effort from the questioner and also have standardized answers which
make it simple to collect the required data. It is one of the primary sources of data and an obser-
vational technique that has a series of questions presented for the respondent in a written form
and individual respondents expected to answer in writing. In the questionnaire, the respondents
are given a list of written questions which he/ she responds the answer by ticking the one he/ she
considers appropriate (Ajayi, 2017).
For this study, the data was gathered by distributing a survey questionnaire for sampled respond-
ents, and for this study quantitative methodology is involving a close-ended questionnaire would
be used to measure gathered data. the researcher was used a five-point Likert scale to investigate
the determinant of passengers' brand preference decision in a case of long-distance public
transport service in Bahir Dar City. The reason why the researcher selected a questionnaire for
the data gathering instrument is its simplest way to answer the questionnaires by respondents.
The designed questionnaires was pretested by using Cronbach„s Alpha reliability measurement
scales. Therefore the data collection instruments (questionnaire) were adopted based on previous
researcher's prepared questionnaires (Anjulo & Gebeyehu, 2019; Arif, Ahmed, & Aslam, 2015;
Lakshika & Malkanthie, 2017).In addition to the prior researcher, the questionnaire was also
adopted based on the nature of the country or surrounding environment.
And the researcher divided the questionnaire into two sections. Section one was concerned with
the demographical background of the respondents. Section two addressed the questions related to
32
the independent variable (price, brand name awareness, availability of facilities, brand attributes
(comfort, customer care & safety measures), employee service, and perceived service quality),
and the dependent variable (passenger brand preference).
3.8. Sample Size and Sampling Techniques
3.8.1. Sample size
Determining sample size is a very important issue because samples that are too large may waste
time, resources, and money. While samples that are too small may lead to inaccurate results. Pas-
sengers of cross country bus transport service in Bahir Dar city are vast in number. Therefore,
to gather the information needed for the research on the given time and resource the resulting
sample in this study will determine as follows.
According to G.Cochran (1963) cited by (Israel, 1992) for the population that is large to yield a
representative sample for proportions which is valid; where n is a sample size, Z is the Abscissa
of the normal curve that cuts off an area “α” at the tails, the tails are (1- α) equals the desired
confidence level i.e. 95%. “e” denotes the desired level of precision, “p” is the estimated proba-
bility of attribute that is present in the population. “q” is 1-p. The value for Z is found in the sta-
tistical tables, which contain the area under the normal curve.
3.8.2. Sampling Technique
The sampling technique is a definite plan for obtaining a sample from a given population. It re-
fers to the technique or the procedure the researcher would adopt in selecting items for the sam-
ple. As a priori, the researcher must decide the number of samples or sample size that he or she is
going to use for the study. The sampling process is to choose the sampling frame, which is the
list of elements from which a sample may be drawn: also called the working population
(Chakravanti Rajagopalachari Kothari, 2004).
33
According to Saunders, there are generally two types of sampling, namely probability sampling
and non-probability sampling (Saunders et al., 2007).In the probability sampling method, the
sample is chosen in a way that each member of the population has a known chance of being se-
lected. There are three main types of probability sampling methods, namely random sampling,
systematic sampling, and stratified sampling (Saunders et al., 2007).
In non-probability sampling, the sample is chosen in a way that the chance of each member of
the population to be selected cannot be determined. According to Saunders, there are four main
types of non-probability sampling, namely convenience sampling, judgment sampling, quota
sampling, and snowball sampling (Saunders et al., 2007).
The study has employeed a non-probability sampling method which is convenience sampling.
Convenience sampling is also called accidental or opportunity sampling where a sample is drawn
from that part of the population that is close to hand, readily available, or convenient (Bhattach-
erjee, 2012). The study was used convenience sampling as the total population is infinite and the
member of the target population that meet certain practical criteria, such as easy accessibility,
availability at a given time, or the willingness to participate is included in the study. The tech-
nique is useful where the target population is defined in terms of a very broad category. For in-
stance, the passenger‟s/commuters may be girls and boys, men and women, rich and poor.
3.9. Method of Data Analysis
After the data has been collected by the researcher, the data were carefully reviewed and checked
for completeness & consistencies then it was edited, coded, and all kinds of data management
has been conducted to make it easier for the analysis and after the data has been entered, and
analyzed via descriptive and inferential statistics using SPSS version 23 software package and
with the helping of STATA version 14. The intention behind using this software as a tool was to
increase the credibility and truthfulness of the research. The term data analysis refers to the com-
putation of certain measures along with searching for patterns of relationships that exist among
data groups. Thus, "in the process of analysis, relationships or differences supporting or conflict-
ing with original or new hypotheses should be subjected to statistical tests of significance to de-
termine with what validity data can be said to indicate any conclusions” (C.R. Kothari, 2004).
The data was analyzed by using both descriptive and inferential statistics. Descriptive statistics
refers to a measurement unit that describes the feature of data in the study and its main aim is
briefly summarizing the sample and the measurements done in particular research. With the sup-
34
port of different graphics analyses, descriptive statistics is the main element of major quantitative
data analysis and it presents several quantitative analyses of variables in the simplest way. It
helps to summarize and present data by frequencies, percentages, means, and standard deviations
and also helps to decide the normality of the distribution of variables. In descriptive statistics,
data be described, presented, summarized, and organized by a numerical calculation or by graphs
or tables. Therefore, the researcher was used descriptive statistics to analyze data in addition to
inferential statistics. Inferential statistics would design to infer the cause and effect relationship
between the variables. Inferential statistics applies a complex mathematical calculation and it
builds an assumption‟ and prediction, allows concluding trends about a population based on the
sample. It is also important for making inferences from the data to more general condi-
tions(Michael & Finkelstein, 1980).
To test the association of the variable under study, i.e the relationship between independent vari-
ables (price, brand name awareness, availability of facilities, brand attributes (comfort, customer
care & safety measures), employee service and perceived service quality) and the dependent var-
iable (passenger brand preference), the spearman‟s rho chi-square test association was applied.
The researcher applied logistic regression specifically ordinal logistic regression analysis to ex-
amine the determinant of passengers‟ brand preference decision and association/correlation anal-
ysis was used in this study to determine the relationship between variables by taking independent
variables (price, brand name awareness, availability of facilities, brand attributes (comfort, cus-
tomer care & safety measures), employee service and perceived service quality) and the depend-
ent variable (passenger brand preference).
3.10. Model Specification
3.10.1. Logistic regression
Regression is a statistical procedure that attempts to predict the values of a given variable,
(termed the dependent, outcome, or response variable) based on the values of one or more
variables (called independent variables, predictors, or covariates) (Gujarati, 2004) and to do that
there are methods of regression such as Multiple linear, Logit, Tobit, and Probit regression which
are useful tools to analyze the relationship between multiple explanatory variables. These meth-
ods also permit researchers to estimate the magnitude of the effect of the explanatory variables
on the outcome variable. In the regression, if the response /dependent variable is continuous
35
researcher can use the usual multiple or linear regression model while if the response/dependent
variable is categorical, ranked, discrete, taking on two or more possible values the appropriate
regression model is a logistic regression model. This model was developed by (McCullagh,
2018). Logistic regression would use as a regression model when the researcher tries to model
the categorical dependent variable as a function of one or more independent variables. This re-
gression model is classified according to the type of categories of the response variable: Binary
logistic regression model, Multinomial logistic regression model, and Ordinal logistic regression
models (Hosmer & Lemeshow, 2000). The binary logistic regression model is used to model the
dichotomous response variable, whereas the multinomial logistic regression is a simple extension
of the binary logistic regression model where the response variable has more than two categories
that are nominal but not naturally ordered. Ordinal logistic regression models are used to model
the relationship between independent variables and an ordinal response variable or when the re-
sponse variable category has ordered/ranked.
Therefore, this study employed an ordinal logistic regression model because the response
/dependent/ variable (passenger band preference) has more than two categories with having order
or rank. And also used for explaining the relationship between an ordered categorical response
(dependent) variable and one or more predictor (independent) variables.
Mostly, in a survey research responses were Likert scale-like strongly disagree, disagree, up to
strongly agree and these are ordinal scales in that there is a clear ranking among the categories
(As cited in Masresha, 2014).
Assumptions of ordinal logistic regression
The response/dependent variable should be measured at the ordinal level.
there must be no multicollinearity
The ordinal independent variable must be either categorical or continuous.
Categories are ordered/ranked based on name identification,and each independent varia-
ble has an identical effect at each cumulative split of the ordinal dependent variable
(Reddy & Alemayehu, 2015).
On the contrary, it doesn't assume linearity of the relationship between the dependent and inde-
pendent variables, normality of the error distribution, and homoscedasticity of the errors (H.-A.
Park, 2013)
36
To meet the setup objective in this study, an ordinal logistic regression model and tests related to
the model are used. It is natural to consider methods for more categorical responses which have
more than two possible values. The procedure of the ordinal logistic regression model empowers
one to select the predictive model for ordered dependent variables. As it is known the structure
of the questionnaire in this study was the Likert scale which is an ordered form. Therefore, an
ordinal logistic regression model was found to be an appropriate model for this study to explain
the cause and effect relationship between predictors (independent) variables and dependent (pre-
dicted) variables.
The proportional odds model considers the probability of that event and all events that are or-
dered before it. When response categories are ordered, logits can directly incorporate the order-
ing. The cumulative probabilities are the probability that the response Y falls in the category I or
below, for each possible ith
cumulative probability is/are:
ipppiYpr ...)(
21 .
Each logit has its term but the same coefficient. This means that independent variables having
the same effect on different logit functions which is an assumption we have to check. And it was
a reason for saying the model also called the proportional odds model. The proportional odds
model assumes that the cumulative logits can be represented as parallel linear functions of inde-
pendent variables. That is, for each cumulative logit the parameters of the models are the same,
except for the intercept(A. Adejumo & A. Adetunji, 2013).
Let‟s Y takes as categorical response variable with ordered categories and assume pr (Y= 1) is
p1, pr (Y= 2) is p2…….p (Y= i) is pi for i= 1 ….., c Cumulative probability reflect the ordering,
with 1)(....)2()1( iYprYprYpr and let the cumulative probability of the first c-1
of Y is pr (Y≤ i) =πi, i = 1 ….c-1, then the odds of the first c-1 cumulative likelihoods are
Odds (pr (Y≤ i)) = --------------------------------------- (1)
The proportional Odds model the log odds of the first c-1 cumulative probability as:
= log --------------------------------------- (2)
And the relationship between the cumulative logits of Y is:
---------------------------------- (3)
37
Consider a collection of P independent variables denoted by the vector Χ = (X1, X2….. XP)
The relationship between the predictor and response variables is not a linear function in logistic
regression; instead, the logistic regression function is used, which is the logit transformation .
----------------------------------------------- (4)
Then the logit or log-odds of having pr (Y≤ i) = πi is modeled as a linear function of the inde-
pendent variables as:
---
--------------------------------------------------------------------------------------- (5)
Yi = brand preference for each category
i= the y-intercept
Ui = residual value or error terms
B1----B6 = the population slope coefficient of each x value
X1= price
X2= brand name awareness
X3= Availability of facilities
X4= brand attributes (comfort, customer
care & safety measures)
X5= employee service
X6= perceived service quality
3.10.2. Testing of Parallel Lines
One of the assumptions of ordinal regression is that the regression coefficients are alike for all
categories (Agresti, 2002). If the assumption of parallelism is rejected, it is better to consider us-
ing (1) multinomial regression (2) partial proportional model, (3) separate binary logistic regres-
sion, which estimates separate coefficients for each category. The assumption that all logit sur-
faces are parallel must be tested. The test of parallel lines helps to determine whether it is rea-
sonable to assume that the values of the location parameters are constant across categories of the
response (Harrell Jr, 2015). Bender and Benner (2000) said to use ordinal regression model it
needed to ensure the assumption of parallel lines since the model does not assume normality and
38
constant variance and proportional odds model would only be valid if the parallel lines assump-
tion is ensured, for that matter this assumption has been tested and ensured.
3.10.3. Odds ratio (OR)
The odds ratio is a value that measures the strength of the effect of each independent variable in
the model on the log odds of the dependent variable (Bender & Benner, 2000; Rahman, 2011).
The odds of some event happening are defined as the ratio of the number of occurrences to the
number of non-occurrences and it is often used to compare proportions across groups. That is,
the odds and OR of the event where P1 is the success of the first category and p2 is the success
of the second category but we can have more categories though the following function OR is for
only two categories, thus is given by:
And
The odds of the response are multiplied by every unit increment of P. That is, the odds at
level P + 1 equal the odds at P multiplied by . If the odds less than one indicate the occurrence
is less likely than non-occurrence and if the odds greater than one indicate the occurrence is more
likely than non-occurrence (H. Park, 2013). The problem of non-normality and heteroscedasticity
lead to the model estimation method to be maximum likelihood after natural logarithm transfor-
mation of the odds ratio of the response because in logistic the relationship between the response
with the set of explanatory variables is not linear hence the procedures used in the linear regres-
sion is extended to logistic regression (AO Adejumo & AA Adetunji, 2013).
3.11. Ethical Consideration
For any research process, participants can be harmed in different ways whether physically or
mentally. The researcher‟s responsibility is to make sure that there is no harm comes to the par-
ticipants in any way (Bell, Bryman, & Harley, 2018). According to (Saunders, Lewis, & Thorn-
hill, 2011) Ethics refers to the appropriateness of your behavior about the rights of those who
became the subject of your work, or are affected by it. All the research participants included in
this study would be appropriately informed about the purpose of the research and their willing-
ness and consent are secured before the beginning of distributing the questionnaire. Regarding
39
the right to privacy of the respondents, the study maintains all participants have been briefed
about the research and joined with their full consent and the confidentiality of the identity of
each participant.
3.12. Reliability and validity analysis
3.12.1. Reliability Analysis
Reliability refers to a measure of the degree to which research instruments yield consistent re-
sults. On the other hand, it is the extent to which results are consistent over time and an accurate
representation of the total population under study and if the result of the study could be repro-
duced under similar methodology then the research instrument considered being reliable or relia-
ble analysis is concerned with the internal consistency of the research instrument (Thatcher,
2010). Therefore for this study, Cronbach„s alpha would be used to examine the internal con-
sistency of variables in the research instrument. Cronbach„s alpha is a coefficient of reliability
used to measure the internal consistency of the scale; it is represented as a number between 0 and
1. The scale with coefficient alpha between 0.6 and 0.7 indicates fair reliability, a Cronbach„s
alpha score of 0.7 or above is considered acceptable to determine reliability.
Cronbach’s basic equation for Alpha
Where n = number of questions
Vi = variance of scores on each question
V test = total variance of overall scores on the entire test obtained values for the variables
Table 3-1: Construct variables reliability
Variables N of items Alpha value
Price 4 .894
Availability of facility 5 .911
Brand name awareness 5 .905
40
Brand attributes 5 .900
Perceived service quality 7 .897
Employee service 6 .862
Passenger brand preference 5 .927
All over item together 37 .879
Source: Researcher’s survey; 2021
3.12.2. Validity Analysis
Validity determines whether the research truly measures that which it was intended to measure
how truth full the research results are. In other words, does the research instrument allows you
to; hit the bull‟s eye; of your research objective (Golafshani, 2003). According to Fraenkel and
Wallen (1996) cited by bin Darusalam and Hussin (2016), validity is defined as appropriateness,
truthfulness, meaningfulness, and usefulness instrument that allows data to be inference. If a test
has poor validity then it does not measure the content and competencies it ought to assess how
well a set of scale items matches the relevant content domain of the construct that is trying to
measure defines the validity of the content. To ensure the content validity of this research, a rep-
resentative sample of respondents will be taken. Moreover, the appropriateness of the questions
can be verified by the advisor, instructors, and academic friends.
The researcher was adopted based on standardized questions from previous studies (Anjulo &
Gebeyehu, 2019; Arif et al., 2015; Lakshika & Malkanthie, 2017), and the researcher devising
question was included and also based on the nature of country environments but it has been cus-
tomized to context of the study purpose. The customization was done through; first, the drafted
questionnaire was appraised by professionals who are experienced in conduct survey question-
naires such as instructors and graduate students. After receiving comments from the experts
some comments in the questionnaire are reworded to make it familiar with and it was tested with
20 passengers/commuters.
41
CHAPTER FOUR
4. DATA PRESENTATION, ANALYSIS, AND INTER-
PRETATION
4.1. Introduction
This chapter presented the data analysis, presentation, and interpretation of findings.
The main objective of the study was to investigate the determinants of passenger brand prefer-
ence decisions. Under this chapter demographic characteristics of the respondent, frequency of
conceptual variable, chi-square test, the test of ordinal logistic regression assumptions, parameter
estimate (β), and odds ratio result (OR) with its interpretation in connection with hypothesis
statements are presented and discussed.
Finally, this chapter has also presented the result of ordered logistic regressions to make predic-
tions on the determinant of passenger brand preference (Price (Pr), availability of facilities
(AoF), brand name awareness (BNAW), brand attributes (BATT), perceived service quality
(PSQ) and employee service (ES), passenger brand preference (PBP) using.
4.2. Response Rate of sample respondents
A total of 385 questionnaires were distributed to passengers /commuters of the public bus
transport service in Bahir Dar city station. From this, 366 questionnaires were properly filled and
returned or obtained valid and used for analysis purposes with a response rate of 366/385 (95%).
The remaining 19/385 (5%) questionnaires were not collected due to refusal to give a response
for the questionnaires.
4.3. Demographic profile of the respondents
This study sought the general characteristics of the respondents. The demographic profile of
sample respondents is presented and analyzed below by using descriptive statistics. The purpose
of assessing and analyzing gender and age is to decide the sample respondents.
On the other hand, the need for analyzing and presenting frequency of passenger, educational
level, and income level per month is to determine whether the respondents are more frequently
used the preferred bus brand, more educated, more capable to pay a reasonable price, and give a
better response than other else
42
Table 4-1: Gender frequency of the passengers:
The following table indicates that 169 (45.8%) of respondents were female while 200 (54.2%) of
respondents are male. This entails that comparatively, male passengers/commuters are relatively
more than female passengers to prefer specific bus brands in Bahir Dar city station.
Gender Freq. Percent Cum.
F 150 41 41
M 216 59 100
Total 366 100
Source: Researcher’s survey; 2021
Table 4-2: Age categories of the passengers
With regarding age, 18(4.9 %) of the respondents are below 20 years, 162 (44.3 %) are in the
range of 21-30 years, 107 (29.2 %) are in the range of 31-40 years, 70 (19.1 %) are in the range
of 41-50 years and 9 (2.5 %) were above 50 years as indicated in (Table 4.2). The result revealed
that the majority of the passengers range in age of 21-30 years
Age Freq. Percent Cum.
Below 20 18 4.9 4.9
21-30 162 44.3 49.2
31-40 107 29.2 78.4
41-50 70 19.1 97.5
Above 50 9 2.5 100
Total 366 100
Source: Researcher’s survey; 2021
Table 4-3: Level of education completed
As shown in table 4.3, the highest educational level attained by most of the respondents was
first degree which represents 132 ( 36.1%) out of the respondents and followed by college di-
ploma holders which account for 103(28.1%). On the other hand masters and above respondents
account for 62(16.9%), while secondary school was 53(14.5%) and primary school 16(4.4%).
43
Based on the below data collected from respondents, it is possible to conclude that most of the
respondents have an ability for understanding the objectives of the study or they were able to un-
derstand the questions designed and asked passenger of the public bus transport service in Bahir
Dar city station and this provides the greatest contribution for the quality of the study.
Level of education Freq. percent Cum.
primary school (1-8) 16 4.4 4.4
secondary school(9-12) 53 14.5 18.9
Diploma(12+4) 103 28.1 47.0
BA/BSC degree 132 36.1 83.1
masters and above 62 16.9 100
Total 366 100
Source: Researcher’s survey; 2021
Table 4-4: The frequency of traveling the preferred bus brand
Table 4.4 showed the frequency of traveling with public transport. From the total respondents, 3
(.8%) of the respondents are traveling weekly, 83 (22.7%) are traveling once a month, 256 (69.9
%) are traveling once a year & above 4(6.6%) are traveling without a concerned specified period.
From this, it can be understood that travels availing the public transport from Bahir Dar city sta-
tion/terminal is a mix of all commuters who are traveling at different intervals of time with the
majority of passengers at once a year and above (69.9 %).
Traveling preferred bus brand Freq. Percent Cum.
Weekly 3 .8 .8
Monthly 83 22.7 23.5
once a year and above 256 69.9 93.4
Randomization 24 6.6 100
Total 366 100
Source: Researcher’s survey; 2021
44
Table 4-5: Income level per month of passengers
As indicated the following in table, from the total respondents, 33(9.0%) of the respondents are
in the range of less than 1000, 13(3.6%) are in the range of 1001-2500, 91 (24.9%) are in the
range of 2501-5000, 17 (4.6%) are in the range of 5001 - 7500, 146(39.9%) are in the range of
7501-10000, and 66(18%) are above10000 birr. From this result, it can be understood that the
majority of respondents (39.9%) range in income level of Br 7500-10,000 birr. As a result of
this, the majority of the respondents prefer /select the preferred bus brand that has capable to pay
the rate of payments.
Monthly income level Freq. Percent Cum.
less than Br 1000 33 9.0 9.0
Br1001-2500 13 3.6 12.6
Br 2501-5000 91 24.9 37.4
Br 5001-7500 17 4.6 42.1
Br 7500-10,000 146 39.9 82.0
Above Br 10,000 66 18.0 100
Total 366
100
Source: Researcher’s survey; 2021
Figure 4-1: Bar graph indication for outcome variable measurements
As conveyed in the following bar graph, the majority of the respondents (66.12%) were agreed
with the measurements of passenger brand preference decision as they acquired the better quality
of service, affordable charged payments, have awareness and knowledge, and creating comforta-
ble about specific bus brand and some of the respondents (20.22%) were moderately agreed with
the measurements of passenger brand preference decision as they got a moderate quality of ser-
vice, affordable charged payments, have awareness and knowledge, and creating comfortable
about specific bus brand but the remaining respondents (13.7%) were not agreed with the meas-
urements of passenger brand preference decision, as they did not provide quality service, not af-
fordable charged payments, have not awareness and knowledge, and not creating comfortable
about specific bus brand.
45
Source: Researcher’s survey; 2021
4.4. Descriptive statistical analysis of the study
In this section, the collected data was entered and reported using SPSS version 23 and
Stata/SE14. The frequency of each variable response concerning respondents‟ category is ana-
lyzed and presented. In this study, the researcher designs different sort of questions in line with
the study variable and collect data with the help of those designed questions. Then the collected
data was transformed/ computed into a mean value concerning each predictor and outcome vari-
ables. This mean value was computed by summing up the result of each question in line with
each variable and divided by the number of questions in each factor and outcome variable. And
the frequency and percentage of that computed mean value of the variable were summarized in
the following table.
Table 4-6: Price * Passenger Brand Preference
As indicated in the following table 4.7, most of the respondents 120 (32.78 %) agreed that they
pay a reasonable price from the preferred bus brand in a good manner followed by 112 (30.60 %)
respondents who strongly agreed to the reasonable price payment in the bus station. Unfortunate-
ly 101 (27.59 %) they were moderate on reasonable price in the bus station. The remaining 18
(4.93%) and 15 (4.09 %) of respondents strongly disagree and disagree respectively on the rea-
sonable price for the preferred bus brand in Bahir Dar station. This shows that most of the pas-
sengers (63.38%) of respondents have a positive attitude about reasonably priced for preferred
bus brands.
46
Passenger Brand Preference Total
strongly
disagree
disagree moderate Agree strongly
agree
Price strongly
diaagree
4 5 0 9 0 18
disagree 0 1 3 7 4 15
moderate 12 2 21 42 24 101
agree 8 3 27 51 31 120
strongly
agree
11 4 23 43 31 112
Total 35 15 74 152 90 366
Source: Researcher’s survey; 2021
Table 4-7: Availability of facilities * Passenger Brand Preference
As shown below in table 4.8, most of the respondents responded106 (28.96%) respondents who
did not agree (disagree) with the facility from the preferred bus service in Bahir Dar city station.
96 (26.66%) responded that they were getting with the moderate facility of service from the pre-
ferred bus brand, 63 (17.21%) respondents were strongly agreed with the better facility of bus
service, and 56 (16.79 %) of respondents agree with the facility of service from the preferred bus
service and also the remaining 45(12.29 %) respondents did not get the available service from
the preferred bus service in Bahir Dar station. This shows that the majority of respondents
(40.58%) of respondents have a negative attitude about the facility of the preferred bus service.
Passenger Brand Preference Total
strongly
disagree
disagree moderate agree strongly
agree
Availability
of facilities
strongly
diaagree 10 5 15 12 3 45
disagree 2 7 13 51 33 106
moderate 8 7 35 40 6 96
agree 9 1 10 23 13 56
47
strongly
agree 1 1 20 26 15 63
Total 35 15 74 152 90 366
Source: Researcher’s survey; 2021
Table 4-8: Brand name awareness * Passenger Brand Preference
As indicated in the following table 4.9, most of the respondents 153 (41.81%) agreed that they
were capable to know the brand name of the preferred bus brand, 108 (30.51%) respondents they
were strongly agreed with the well-known brand name, 90 (25.59%) the respondents were mod-
erate on the well-known brand name. The remaining 12(1.59%) and 3 (.8%) of respondents
strongly disagree and disagree respectively on the well-known brand name from the preferred
bus brand in Bahir Dar City station. This shows that (72.32%) majority of the respondents have
enough/adequate knowledge and information to know/understand well-known bus brands.
Passenger Brand Preference Total
strongly dis-
agree
disagree moderate agree strongly
agree
Brand name
awareness
strongly
disagree 5 0 5 2 0 12
disagree 0 0 1 1 1 3
moderate 3 6 22 26 33 90
agree 7 6 33 69 38 153
strongly
agree 20 3 13 54 18 108
Total 35 15 74 152 90 366
Source: Researcher’s survey; 2021
Table 4-9: Brand Attributes * Passenger Brand Preference
As indicated in the following table 4.10, most of the respondents 205 (56.02%) they agree that
they were acquired comfortable service, customer care, and safety measures from the preferred
rd brand, 61 (16.7%) respondents strongly agreed about comfort, safety measures, and concern
customer care, 12(3.645%) the respondents were moderate on comfortable service, customer care
and safety measures of the passengers. The remaining 83(22.67%) and 5(1.455%) of respondents
disagree and strongly disagree respectively were not comfortable with service, customer care,
and safety measures of the passengers for preferred bus brand in Bahir Dar City station. This in-
48
dicated that 266(72.7%) majority of the respondents have acquired comfortable bus service, con-
cern on customer care, and related to safety measures from the preferred brand.
Passenger Brand Preference Total
strongly
disagree
Disagree Moderate agree strongly
agree
Brand At-
tributes
strongly
disagree
11 5 18 35 14 5
disagree 19 9 38 88 51 83
moderate 4 0 2 4 2 12
agree 1 1 1 1 1 205
strongly
agree
0 0 15 24 22 61
Total 35 15 74 152 90 366
Source: Researcher’s survey; 2021
Table 4-10: Perceived service quality * Passenger Brand preference
According to the following table 4.11, most of the respondents 159 (48.36%) agreed that they
were gain prompt quality, reliable and responsive from the preferred brand, 159(43.44%) re-
spondents who were moderate quality of transport service, 24 (6.56%) the respondents were
strongly agreed by acquiring a better quality of transport service. But the remaining 6 (1.64%) of
respondents strongly disagree on the quality of transport service from the preferred bus brand.
This shows that almost all passengers 183(54.92%) of respondents were certainly acquired the
best quality of transport service from the preferred bus brand.
Passenger Brand Preference Total
strongly
disagree
disagree moderate agree strongly
agree
Perceived ser-
vice quality
strongly
disagree
1 0 2 3 0 6
moderate 22 9 33 58 37 159
agree 12 6 30 86 43 177
strongly 0 0 9 5 10 24
49
agree
Total 35 15 74 152 90 366
Source: Researcher’s survey; 2021
Table 4-11: Employee service * Passenger Brand Preference
According to the following table 4.12, most of the respondents 181 (49.45%) agreed that the
driver, ticketer, and other related stakeholders have a positive attitude toward the passengers,
148(40.43%) respondents who have moderate employee hospitality, 31 (8.45%) the respondents
were strongly agreed by acquiring a better quality of transport service. But the remaining 6
(1.67%) of respondents strongly disagree on employee hospitality bus transport service for the
preferred bus brand. This shows that almost all passengers 212(57.9%) of respondents were cer-
tainly acquired better employee service for the preferred bus brand
Passenger Brand Preference Total
strongly
disagree
disagree moderate agree strongly
agree
Employee
service
strongly
disagree
1 0 2 3 0 6
moderate 18 10 29 72 19 148
agree 15 5 43 73 45 181
strongly
agree
1 0 0 4 26 31
Total 35 15 74 152 90 366
Source: Researcher’s survey; 2021
On the other hand, the above computed and summarized output of descriptive statistics of the
variable under study was more explained by using the mean and standard deviation of the varia-
bles. Standard deviation means a measurement unit that deals with how much the mean of the
variable represents the data well (Field, 2009). The standard deviation value which is smaller or
relative to the mean itself shows that the data were closer to the mean. That means a smaller
standard deviation value would more acceptable. While larger standard deviation explains that
the data would be far from the mean. As mentioned earlier, the researcher used a five-point Lik-
50
ert scale rating to construct a range that is used to measure the attitude of respondents for each
predictor and outcome variable. And according to (Alhakimi & Alhariryb, 2014) the Likert scale
response has been put on an interval of the mean based on the following formula;
Max-Min / n1 which means 5-1 / 5 = 0.80
Based on the above formula, the mean of each item ranging from 1- 5 lies on the following inter-
val:
Mean interval Respondents Perception/ attitude
1. 1.00-1.80 Strongly Disagree
2. 1.81-2.60 Disagree
3. 2.61-3.40 Neutral
4. 3.41-4.20 Agree
5. 4.21-5.0 Strongly Agree
So, the following descriptive statistics table of both predictor and outcome variables was put for
more explanation in a short and precise way.
Table 4-12: Descriptive statistics for factor and outcome variables
So based on this interval of mean, the following table is constructed & interpreted
Descriptive Statistics
N Min. Max. Mean Std. Deviation
Price 366 1 5 3.80 1.073
Availability of facilities 366 1 5 3.17 1.081
Brand Name Awareness 366 1 5 3.93 .954
Brand Attributes 366 1 5 3.81 .843
Perceived service quality 366 1 5 3.58 .689
Employee service 366 1 5 3.63 .708
Passenger Brand Preference 366 1 5 3.67 1.171
Source: Researcher’s survey; 2021
51
From table 4.13 above, the mean value of price, brand name awareness, perceived service quali-
ty, employee service, and passenger brand preference shows that the attitude of respondents to-
ward the question falls on the mean range of agreement by the approximate value of 3.80, 3.93,
3.81, 3.63 and 3.67 respectively. Thus it shows that respondents were agreed on the idea request-
ed concerning each variable. On the other hand, the mean value of the availability of facility falls
the range of moderate by the approximate value of 3.17 which shows that respondents were
moderate on the idea requested about availability of facilities of public bus transport service in
Bahir Dar city station.
4.5. Inferential statistical analysis of the study
In this section, an association of variables, ordinal logistic regression coefficient, odds ratio, and
final model summary would be reported and interpreted by using SPSS and Stata/14 software.
4.6. Chi-square Test & Association measures
At this point, the relationship between the independent variable (price, brand name awareness,
availability of facilities, brand attributes (comfort, customer care & safety measures), employee
service and perceived service quality) and passenger brand preference Bahir Dar city cross coun-
try bus station had been tested using chi-squares test and Spearman‟s rho correlation test was
chosen because the variable under study was categorical/ ordinal. Spearman‟s rho correlation
coefficient (rho correlation value) and sig level is a standardized measure of the strength and di-
rection of a relationship between two variables. To measure the strength and direction of associa-
tion there is four chi-square association measurement for ordinal response variable where the
choice is depending on some criteria by the researcher those are Gamma, Somers' d., Kendall's
tau-b, and Kendall's tau-c are a measure of association between two ordinal variables that range
between -1 and 1. According to Alwadaei (2010), as cited in (Bekele, Shigutu, & Tensay, 2014),
Correlation or association analysis was conducted to show the strength of the association be-
tween the variables involved, and its correlation value interpretation would be depicted in the
following table.
Table 4-13: Interpretation of association of variables
Correlation/ association value Description
52
0.70-1.00 Very strong association
0.50-0.69 Substantial association
0.30-0.49 Moderate association
0.10-0.29 weak association
Source: As cited in (Bekele et al., 2014)
Table 4-14: Chi-square test statistics
Variable Likelihood
ratio
df Ordinal by ordinal Ken-
dall's tau-b
Value
Spearman rho
correlation coef-
ficient
p-value (2
tailed at
0.05)
Pr 37.680 16 0.360 0.428 0.037
AoF 16.388 12 0.137 0.126 0.182
BNA 74.654 12 0.504 0.602 0.000
BATT 76.385 16 0.526 0.630 0.000
PSQ 47.008 12 0.333 0.488 0.002
ES 72.054 12 0.444 0.587 0.000
Source: Researcher’s survey; 2021
Gamma and Somers' d. is similar both calculate symmetric version of statistic but Somers'd dif-
fer only the inclusion of the number of pairs not tied on the independent variable, while Kendall's
tau-b and Kendall's tau-c are a nonparametric measure of association for ordinal variables, where
the first take ties into account but not the later.
Ordinal by ordinal Kendall's tau-b value and Spearman rho correlation coefficient is a nonpara-
metric measure of association for ordinal, Therefore, for this study, non-parametric measures i.e
Ordinal by ordinal Kendall's tau-b value and the Spearman rho correlation coefficient were better
choices to measure the direction and magnitude of associations/correlation that is why because
the variables under study are tie among the respondent's response, ranked /ordered, do not as-
sume normality.
Based on the Ordinal by ordinal Kendall's tau-b value and Spearman rank-correlation coefficient,
price, brand name awareness, brand attributes, perceived service quality, and employee service
has a statistically significant positive association with passenger brand preference. Brand attrib-
53
utes, brand name awareness, and employee service has Substantial / higher association but the
statistics show that availability of facility has no association with passenger brand preference be-
cause it's Kendall's tau-b value (p-value) shows insignificant where p-value > alpha i.e. 0.182 >
0.05). As the Spearman rho- correlation coefficient and Ordinal by ordinal Kendall's tau-b value
indicated in the above table 4,14 price and perceived service quality has a moderate level of as-
sociation/ correlation with passenger brand preference while Availability of facility has a weak
association/correlation with passenger brand preference.
4.7. Regression analysis of the study
Regression analysis is conducted to know how much the independent variable explains or pre-
dicts the dependent variable. Like that of other regression models, ordinal logistic regression analy-
sis should be tested and ensured unless the result can not be valid, those assumptions such as a test of
model fitting information, the goodness of fit tests, a test of parallel lines, and multi co-linearity
tests required. So, before doing an ordinal logistic regression model, those OLR model related
tests would be checked as follows;
4.7.1. Model Fitting Information
Model fitting information explains whether the final selected model is fitted with the data ob-
served or not. The general rule is that the significance value must be less than 5%.
To be the model is fitted, there must be a difference between the baseline model and the final
model, where the baseline model is a model without any independent variable whereas the final
model is with all possible independent variables If the p-value is less than the alpha, the null hy-
pothesis needs to be accepted if not reject Ho. The hypothesis is:-
Ho: There is a significant difference between the baseline model and the final model.
Ha: There is no significant difference between the baseline model and the final model.
Table 4-15: Model fitting information:
Model -2 Log Like-
lihood
Chi-Square Df Sig.
Intercept Only 883.941
54
Final 763.377 120.565 21 .000
Link function: Logit.
Source: Researcher’s survey; 2021
The ordinal logistic model says that the model is a better fit to the data if it establishes an im-
provement over the intercept-only model also known as the null model. An intercept-only model
serves as a good baseline because it doesn‟t have any predictors. Test of intercept only model
(i.e., the constant in Table 4.14), merely describes whether an intercept included or not within the
model. The final model is the model with many predictors and is used to conclude whether the
model is fit for the data observed or not.
The SPSS version 23 outputs of table 4.14 above show that the significance values are less than
0.05 i.e. there is a significant difference between the baseline model and the final model. This
shows that the final selected model was fitted with the data observed. For this data, the sig value
(p value= 0.000) less than 5% tells that the final alternative model excluding intercept would be
applied to the data. As a rule, to accept the fitted model, the significance value must be less than
5% i.e p-value < 0.05. So, from the above table, it is possible to conclude that the p-value of the
final model is less than5% which is 0.000 which indicates the model is fit for the data.
-2 Log-likelihood is a comparison test of two models, which is that the first model is the simpler,
restricted model with the likelihood of L1and the second model was more complex, a full model
with the likelihood of L2 (Benoit, 2012). So, in this way the second model is the same as the first
model with some extra parameters. H0: says that the more complex model is no better than the
simpler one; then L1and L2 will be similar, i.e. the difference between them will be small. Then
it is possible to test the more restricted model (null model) in our case the intercept only model
with final model: So, -2 log-likelihood of Model 1, without parameters =883.941 and-2 log-
likelihood of Model 2, with parameters = 763.377. Differences in -2 log-likelihoods are equal to
chi-square test value 120.565 or 883.941-763.377= 120.565, Difference in degrees of freedom =
21 So, the p-value for 120.565 on X2
distribution with 21 degrees of freedom < 0.001, then re-
ject the null model (intercept only model) and accepting the final model with keeping parameters
in the model. Thus from the above table, it was possible to conclude that an intercept-only model
is a model without parameters and it was compared with the alternative model what we call the
final model with parameters. Then the null model is rejected and the final model is accepted with
parameters. So the statistically significant chi-square statistic (p<0.05) indicates that the Final
55
model gives a significant improvement over the baseline intercept the only model and we can
conclude the model is fitted.
4.7.2. The goodness of fit test
The goodness of fit refers to whether the data collected /observed data is fitted or not with the
fitted model which is discussed in the model fitting information above. If the sig value is less
than 0.05 we reject the null hypothesis. To say that the observed data is having the goodness of
fit with a fitted model the p-value must be greater than the alpha value or the 0.05. Based on this
rule the observed data of this study is highly fitted with a fitted model both in deviance and Pear-
son method of goodness-of-fit test because the p-value is 0.939 and 0.358 for each respectively
both works to measure of goodness of fit. But deviance is a widely used measure of GOF( good-
ness of fit) and more appropriate ordinal data and by definition, it is a likelihood ratio (LR) sta-
tistic for comparing one‟s current model to the saturated model. Thus, the use of the chi-square
distribution to test for the significance of the deviance appears justified because the LR statistic
has an approximate chi-square distribution under Ho when comparing full vs. reduced (nonsatu-
rated) models that are fitted using ML(maximum likelihood) estimation (Klein, 2010).
The hypothesis is:-
Ho: The observed data have the goodness of fit with the fitted model.
Ha: The observed data have no goodness of fit with the fitted model.
Table 4-16: Goodness of fit test statistics
Chi-Square Df Sig.
Pearson 1071.900 944 .358
Deviance 663.728 944 .939
a. Link function: Logit.
b. Accept the Ho if p-value > alpha value 0.05 0.939 > 0.05. & 0.358 > 0.05: So failed to reject
Ho.
Source: Researcher’s survey; 2021
The above table 4.15 indicates that the deviance (0.939) and Pearson (0.358) are greater than the
p-value of 5%. So the researcher fails to reject the null hypothesis. Thus it is possible to conclude
that the goodness of fit of the observed data to the fitted model is satisfied.
56
4.7.3. Pseudo R-Square
Pseudo R-Square is the proportion of the variance explained by the independent variable on the
dependent variable in the regression model i.e. how much proportion of variance explaining the
dependent variable. In an ordinal logistic regression model, it is impossible to compute the same
R-Square statistic as in linear regression. What constitutes a “good” R2 value depends upon the
nature of the outcome and the explanatory variables. Various R-square statistics can be used to
measure the strength of the association between the dependent variable and the predictor varia-
bles. The pseudo-R-square indicates the proportion of variance explained by the independent
variable to the dependent variable in the regression model. The common statistics used in the or-
dinal logistic regression are Nagelkerke, Cox and Snell, and McFadden. Most statisticians and
researchers recommend using the Nagelkerke R-square result is better and the best measure to
use is the model with the largest R-square. So for this study, the researcher used the Nagelkerke
R-square result for it has the highest score and most recommended (AO Adejumo & AA Adetun-
ji, 2013). So that the power of predictor variables (price, availability of facility, brand name
awareness, brand attributes, perceived service quality, and employee service) to explain the de-
pendent variable (passenger brand preference) is 68.4% which is moderately high, this is just as
we would expect because numerous factors affect the passenger brand preference so the other
31.6 % can be explained by other unobserved variables in this study.
Table 4-17: Pseudo R-Square
Cox and Snell .572
Nagelkerke .684
McFadden .436
Link function: Logit.
Source: Researcher’s survey; 2021
4.7.4. Test of Parallel Lines
The test of a parallel line is related to proportion odds. If the significance value less than 5%, we
reject the null hypothesis otherwise we accept it. One of the assumptions of ordinal regression is
that the regression coefficients are the same for all categories. If the assumption of parallelism is
rejected, it is better to consider using multinomial regression, which estimates separate coeffi-
57
cients for each category. If the null hypothesis is rejected at a specific level of significance i.e at
5%, this implies that it is possible that the link function selected is incorrect for the data or that
the relationships between the independent variables and logits are not statistically same for all
logit so it requires more than one model (AO Adejumo & AA Adetunji, 2013).
The hypothesis is:
Ho: The location parameters (slope coefficients) are the same across response categories.
Ha: The location parameters (slope coefficients) are not the same across response categories
Table 4-18: Parallel line test of parameters
Model -2 Log Likelihood Chi-Square df
Null Hypothesis 763.377
General 655.381b 107.996
c 0.764
Link function: Logit
The null hypothesis states that the location parameters (slope coefficients) are the same across
response categories.
Source: Researcher’s survey; 2021
One of the assumptions to undertake ordinal logistic regression was that the relationship between
each paired outcome group should be the same. This is what is commonly known as the test of
parallel lines because the null hypothesis states that the slope coefficients in the model are the
same across response categories and its line in the same slope was parallel. If we don‟t have able
to reject the null hypothesis, we conclude that the assumptions would fulfill.
The above table 4.16 indicates that the parallel line test for a general model with the chi-square
value 107.996 and p-value= 0.764 which is greater than the 5% level of significance, fails to
reject the null hypothesis. Due to that, there is no enough evidence to reject the null hypothesis
for the general model. For that matter, the proportional odds assumption appears to have held for
the general model. So, from the above table, it is possible to conclude that the location parame-
ters (the slope coefficient) are the same across response categories.
4.7.5. Multicollinearity Test
As Gujarati (2003) pointed out multicollinearity refers to a situation where it becomes difficult to
identify the separate effect of independent variables on the dependent variable because there ex-
58
ists a strong relationship among them, in other words, it is a situation where explanatory varia-
bles are highly correlated. Multicollinearity in the regression model suggests substantial correla-
tions among independent variables and this phenomenon introduces a problem because the esti-
mates of the parameters become inefficient and entail large standard errors, which makes the co-
efficient values and signs unreliable. In addition, multiple independent variables with high corre-
lation add no additional information to the model. It also conceals the real impact of each varia-
ble on the dependent variable (Gujarati, 2004). Therefore, checking the co-linearity problem with
the assumption of tolerance and VIF (Variance Inflation Factor) statistics is important before re-
gressing. Daoud (2017) suggested that a tolerance value less than 0.1 almost certainly indicates a
serious co-linearity problem, also Liu (2010) also suggested that for a VIF value greater than 10,
there is also a serious co-linearity problem. So in this study, the SPSS multicollinearity test
shows there is no multicollinearity problem for it is fulfilled the standard, where there are no VIF
more than 10 and tolerance value less than 0.1.
Table 4-19: Multicollinearity test coefficients
Independent variables Collinearity Statistics
Tolerance VIF
Price .968 1.034
Availability of facilities .916 1.092
Brand Name Awareness .918 1.089
Brand Attributes .836 1.197
Perceived service quality .793 1.260
Employee service .821 1.218
Source: Researcher’s survey; 2021
The above table 4.19 shows that the VIF value of each variable was below 10 which is the max-
imum expected value to say co-linearity happen or not. The VIF value of all predictor variables
was too small. Thus, the multi-co-linearity result of this study as indicated in table 4.17 above
confirmed that there is no problem of multi-co-linearity since the value indicates between one
and ten. Therefore, to conclude that all the assumptions, as well as related tests, were fit for re-
gression analysis and the result of all facilitates the model to functionalize. Thus there was no
59
hindrance factor to do regression analysis. So, an ordinal logistic regression analysis was con-
ducted as well.
4.7.6. Ordered logistic regression parameter estimates
The logistic regression model can be classified as multinomial, ordinal, and binary. In this study,
an Ordinal logistic regression model was used. The ordinal logistic regression procedure em-
powers one to select the predictive model for ordered dependent variables. It describes the rela-
tionship between an ordered response variable and a set of independent variables. The independ-
ent variables may be continuous or discrete (or any type). In this study, the researcher was used
ordinal logistic regression analysis to know whether the predicted variable influence the response
(dependent) variable or not. So, in these studies, the ordinal logistic regression model has be-
come the statistical model of choice. The estimates (β) are ordinal regression coefficient of predictor
variable and is the y-intercept of the model for each category in OLR and The Wald statistic is
used to assess the contribution of individual predictors or the significance of individual coefficients in a
given model (Bewick, 2005) and it is the square of the ratio of the coefficient to its standard error.
The significance of the Wald statistic at sig < 0.05 indicates the importance of the predictor vari-
ables in the model, the hypothesis of Wald Ho is βgj = 0 whereas the alternative βgj ≠ 0 and the
higher values of the Wald statistic shows that the corresponding predictor variable is significant
which means rejecting the null hypothesis.
Table 4-20: Test of parameter estimates
Estimate
Std.
Error
Wald Df Sig. 95% Confidence Interval
Lower
Bound
Upper
Bound
Threshold [PBP = 1] -20.007 .751 64.007 1 .000 -21.478 -18.535
[PBP = 2] -15.522 .743 55.256 1 .000 -16.978 -14.065
[PBP = 3] -12.152 .730 32.381 1 .000 -13.583 -10.721
[PBP = 4] -9.962 .708 7.672 1 .006 -11.349 -8.574
Location [Pr=1] -4.092 .492 4.924 1 .026** -5.056 -3.127
[Pr=2] -3.115 .539 .940 1 .002** -4.171 -2.058
[Pr=3] -2.522 .271 .381 1 .001** -3.053 -1.991
[Pr=4] -1.260 .261 .996 1 .318 -1.772 .748
[Pr=5] 0a . . 0 . . .
[AOF=1] -3.743 1.49 6.290 1 .203 -6.669 818
60
[AOF=2] -2.887 .320 7.699 1 .345 .261 1.514
[AOF=3] -1.144 .303 .226 1 .635 -.737 .449
[AOF=4] -1.055 .365 .023 1 .881 -.661 .771
[AOF=5] 0a . . 0 . . .
[BNAW=1] -2.557 .663 .705 1 .001** -3.856 -1.257
[BNAW=3] -1.628 .290 4.687 1 .030** -2.196 -1.059
[BNAW=4] -.074 .251 .086 1 .770 -1.232 .248
[BNAW=5] 0a . . 0 . . .
[BAtt=1] -3.456 1.064 .183 1 .669 -5.541 1.370
[BAtt=2] -2-630 .859 5.411 1 .020** -4.313 -.946
[BAtt=3] -1.702 .340 7.800 1 .005** -2.368 -1.035
[BAtt=4] -.951 .299 5.502 1 .019** -1.537 -.365
[BAtt=5] 0a . . 0 . . .
[PSQ=1] -2.086 1.418 8.302 1 .004** -4.865 -.693
[PSQ=3] -1.402 .443 .827 1 .002** -2.270 -.533
[PSQ=4] -.765 .449 .625 1 .014** -1.675 -.085
[PSQ=5] 0a . . 0 . . .
[ES=1] 0a . . 0 . . .
[ES=3] -3.270 .537 37.13 1 .000** -4.321 -2.218
[ES=4] -2 .174 .528 36.087 1 .000** -3.208 -1.139
[ES=5] 0a . . 0 . . .
a. This parameter is set to zero because it is redundant.
b. It is significant if p-value < alpha value (0.05)
c. It is significant if the Wald value greater than the standard error
d. Estimates are the ordered log-odds (logit) regression coefficient (β)
Source: Researcher’s survey; 2021
4.7.6.1. Discussion and Interpretation for coefficient (β)
In ordinal logistic regression, the log-likelihood ratio is used to interpret the coefficient.
Log-likelihood; is the probability of whether the dependent variables perceived value was pre-
dicted by the independent variables' perceived value. This likelihood function is important for
estimating the probability of observing data, given unknown parameters of (α and β). Similar to
other probabilities the likelihood varies from 0 to 1. The log-likelihood function is a logarithm
function and it is easier to work. In the process of comparing different models, log-likelihood
will be used for inference testing. The log-likelihood varies from 0 to -∞ (it is negative because
the natural log of any number less than 1 is negative).
61
An ordered logistic regression coefficient is used to show whether the factor (independent varia-
ble) influences the outcome variable positively or negatively. To interpret the result of logistic
regression, first, the researchers need to know the coefficients to understand their association be-
tween the variable under study. So, in simple terms, the coefficient table (table 4.17) was used to
identify whether the factor variable influences the outcome or dependent variable negatively or
positively. From the above table 4.17, it is possible to conclude that price with a significance
value across categories (p-value = 0.026, 0.002, and 0.001) has statistically a positive and signif-
icant effect on passenger brand preference decision of long-distance public transport service in
Bahir dar City station. In addition, brand name awareness with significance value a cross (value
=0.01 and 0.03) has statistically a positive and significant effect on passenger brand preference
decision of long-distance public transport service in Bahir dar City station. Brand attribute with a
significance value across category (p-value across category = 0.02, 0.005 and 0.019) has a posi-
tive and significant effect on passenger brand preference decision of long-distance public
transport service in Bahir dar City station. Perceived service quality with a significance value
across categories (p-value = 0.004, 0.002, and 0.019) has statistically a positive and significant
effect on passenger brand preference decision of long-distance public transport service in Bahir
dar City station. The same to that employee service with a significance value across category (p-
value =0.000 and 0.000) has statistically a positive and significant effect on passenger brand
preference of public bus transport service in Bahir dar City station. But, the p-value or signifi-
cance value of the availability of facility was beyond 5% which is 0.203, 0.345, 0.635, and 0.881
across category respectively, and has no association with passenger brand preference decision of
long-distance public transport service in Bahir dar City station at the beginning in the chi-square
test and was not a statistically significant determinant as ordinal logistic regression coefficient
and odds ratio results presented. The coefficient of the parameter presented in the above table are
comprehended using reference categories denoted by 0a, for each significant independent varia-
ble along with its categories is discussed in the following way:
Price charged /Affordability/from passengers’
Passengers who feel the price charged unreasonable at all has less brand preference by 4.092
times of the brand preference by passengers feel the price charged who has reasonable charged
means passengers who feel the price charged has reasonable for brand preference makes 4.092
62
times greater brand preference than who feel the unreasonable price charged and responded
strongly disagree.
Passengers who reveal the price charged unreasonably have less brand preference by 3.115 times
of the brand preference by passengers reveals price charged who has reasonable charged means
passengers who reveal price charged has reasonable for brand preference makes 3.115 times
greater brand preference than who reveals unreasonable price charged and responded disagree.
Passengers who tell the price charged moderately reasonable has moderate brand preference by
1.522 times of the brand preference by passengers tell price charged who has reasonable price
charged means passengers who tell price charged has reasonable for brand preference makes
1.522 times greater brand preference than who tell moderately reasonable price charged and re-
sponded moderately.
In general, coefficients of parameter disclose the passengers charged unreasonable/ unfair price
means less preferred/chosen/ the bus brand. While the passengers charged fairly/ reasonable
price means highly preferred the bus brand.
Awareness level of passengers’ about the brand name
Passengers who have lower awareness level about the preferred brand have less brand preference
by 2.557 times greater brand preference by passengers who have higher awareness level means
passengers who have higher awareness level for brand preference creates 2.557 times greater
brand preference than those who have lower awareness level about the preferred brand and re-
sponded strongly disagree and passengers who have moderate awareness level about the pre-
ferred brand have a moderate brand preference by 1.628 times of the brand preference by pas-
sengers who have higher awareness level means passengers who have higher awareness level for
brand preference creates 1.628 times greater brand preference than who have moderate aware-
ness level about the preferred brand and responded moderately.
Generally, the above table 4.17 indicates the passenger's awareness level increased from lower
level to moderate level, the ability to prefer/choice/ the bus brand also upgraded or the passen-
ger's awareness level is high, the capacity to prefer/choice the brand also better and vice versa.
63
Brand attributes (comfort, customer care, and safety /security measures)
Passengers who considered the preferred bus brand has not clean/comfort/, safety measures, and
customer care has less preferred the brand by 2.630 times of brand preference by passengers who
have best considered the preferred bus brand has clean/comfort/, safety measures, customer care
means passengers who have best considered the preferred bus brand has clean/comfort/, safety
measures and customer care for brand preference makes 2.630 times greater brand preference
than who passengers who considered the preferred bus brand has not clean/comfort/, safety
measures, and customer care and responded disagree.
Passengers who considered the preferred bus brand has moderately clean/comfort/, safety
measures, and customer care has moderately preferred brand by 1.702 times of brand preference
by passengers who have best considered the preferred bus brand has clean/comfort/, safety
measures and customer care means passengers who have best considered the preferred bus brand
has clean/comfort/, safety measures, and customer care for brand preference makes 1.702 times
greater brand preference than who passengers who considered the preferred bus brand has mod-
erately clean/comfort/, safety measures, and customer care and responded moderately.
Passengers who considered the preferred bus brand has clean/comfort/, safety measures, and cus-
tomer care has more preferred brand by 0.951 times of brand preference by passengers who have
best considered the preferred bus brand has clean/comfort/, safety measures, customer care
means passengers who have best considered the preferred bus brand has clean/comfort/, safety
measures, and customer care for brand preference makes 0.951 times greater brand preference
than who passengers who considered the preferred bus brand has clean/comfort/, safety
measures, and customer care and responded agree.
In general, estimate (β) specifies very low and low brand attributes (no cleanness/comfort of the
bus, no protect the passengers from any kind s of threat like bandits/theft, and no concern the
customer care at the bus station/stop), less chosen the bus brand. While good brand attributes
(cleanness/comfort of the bus, protect the passenger from any kind of threats/ problem like ban-
dits/theft and concern the customer care (arrange minibus and baggage for passengers up to reach
its destination/ around the bus stop and source/ bus station/), highly preferred the bus brand.
64
Perceived service quality
Passengers who acquire the lower quality of service have less brand preference by 2.086 times
greater brand preference by passengers who acquire a higher quality of service means passengers
who acquire a higher quality of service for brand preference produces 2.086 times greater brand
preference than those who acquire the lower quality of service and responded strongly disagree.
Passengers who obtain the moderate quality of service have moderate brand preference by 1.402
times greater brand preference by passengers who obtain a higher quality of service means pas-
sengers who obtain a higher quality of service for brand preference produces 1.402 times greater
brand preference than those who obtain the moderate quality of service and responded moderate-
ly.
Passengers who gain a good quality of service have good brand preference by 0.765 times great-
er brand preference by passengers who gain a higher quality of service means passengers who
gain a higher quality of service for brand preference produces 0.765 times greater brand prefer-
ence than those who gain a good quality of service and responded agree.
In general, the estimate (β) discloses low quality of service (not reliable, not promptness and not
responsiveness for transportation service), less preferred the bus brand while the high quality of
service (more reliable, promptness and responsiveness for transportation services), highly pre-
ferred the bus brand than ever.
Employee’s delivery of service
Passengers who acquire moderate employee service (driver/co-driver, ticket seller, and other re-
lated stakeholders) for the preferred brand by 3.270 times greater brand preference by passengers
who acquire excellent employee service means passengers who acquire excellent employee ser-
vice for brand preference makes 3.270 times greater brand preference than who acquire moderate
employee service and responded moderately and passengers who obtain good employee service
(driver/co-driver, ticket seller and other related stakeholders) for the preferred brand by 2.174
times greater brand preference by passengers who obtain excellent employee service means pas-
sengers who obtain excellent employee service for brand preference makes 2.174 times greater
brand preference than who obtain good employee service and responded agree.
65
In general, the above parameter estimates show service provider employees like driver/co-driver,
ticket seller, and another related stakeholder gives/deliver better service to the passenger, the
ability to chosen/preferred the bus brand becomes better and vice versa.
Based on the above parameter estimate table 4.18, the following logit equations devel-
oped for significant outcome variable categories.
(1=lower level of passenger brand preference, 2 = low level of passenger brand preference, 3 =
moderate level of passenger brand preference and 4= agreed with level of passenger brand pref-
erence ) under this study were :
Equation 1
Log ( )
= -20.0007- 4.092 Pr (SD) -3.115 Pr (D) - 2.522 Pr (M) - 2.557 BNAW (SD)-1.628 BNAW (M)
- 2.630 BAtt (D) - 1.702 BAtt (M) -.951 BAtt (A) – 2.086 PSQ (SD) - 1.402 PSQ (M) -.765 PSQ
(A) – 3.270 ES (M)- 2.174 ES (A).
Equation 2
= -15.522 - 4.092 Pr (SD) -3.115 Pr (D) - 2.522 Pr (M) - 2.557 BNAW (SD)-1.628 BNAW (M) -
2.630 BAtt (D) - 1.702 BAtt (M) -.951 BAtt (A) – 2.086 PSQ (SD) - 1.402 PSQ (M) -.765 PSQ
(A) – 3.270 ES (M) - 2.174 ES (A).
Equation 3
=-12.152- 4.092 Pr (SD) -3.115 Pr (D) - 2.522 Pr (M) - 2.557 BNAW (SD)-1.628 BNAW (M) -
2.630 BAtt (D) - 1.702 BAtt (M) -.951 BAtt (A) – 2.086 PSQ (SD) - 1.402 PSQ (M) -.765 PSQ
(A) – 3.270 ES (M) - 2.174 ES (A).
Equation 4
=-9.962 - 4.092 Pr (SD) -3.115 Pr (D) - 2.522 Pr (M) - 2.557 BNAW (SD)-1.628 BNAW (M) -
2.630 BAtt (D) - 1.702 BAtt (M) -.951 BAtt (A) – 2.086 PSQ (SD) - 1.402 PSQ (M) -.765 PSQ
(A) – 3.270 ES (M) - 2.174 ES (A).
66
Where:-
SD, D, N, A, SA represents strongly disagree, Disagree, Neutral, Agree, and Strongly
Agree respectively. And,
The abbreviation in the bracket i.e Pr, BNAW, BAtt, PSQ and ES indicates the price,
brand name awareness, brand attributes, perceived service quality, and employee service
respectively.
-20.007, -15.522, -12.152, and -9.962 indicates the labeled intercept (cut point) for each catego-
ry. And, the remaining values from the equation above are the slope/ coefficient of the variable
under study for each category.
4.7.7. Ordinal Logistic Regression: Odds Ratio Analysis
The most popular model in ordinal logistics is the proportional odds model. The odds ratios of
the predictors can be calculated by exponential estimate (Exp (B).
Odds ratio means the exponential of coefficient, and mostly it is recommended in an ordinal lo-
gistic regression model to interpret the result of the model.
The odds ratio (OR) is a comparative measure of two odds relatively different. The odds ratios of
the predictors can be calculated by exponential estimate ( ) which measures the strength of the
effect of each independent variable in the model on the log odds of the dependent variable (H.-A.
Park, 2013). The test statistics like, , P-value, Wald, CI, and standard error way of interpreta-
tions are similar to that of the parameter estimate. but odds ratio analysis is the most important
way for interpretation than parameter estimate.
Table 4-21: Odds ratio analysis
Exp(β) Std.
Error
Wald D
f
Sig. 95% Confidence Interval
Lower Bound Upper Bound
Threshold [PBP = 1] 2.04677593E-9 .751 64.00 1 .000 8.91937464E-9 4.69684464E-10
[PBP = 2] 2.81501848E-7 .743 55.25 1 .000 7.78637687E-7 4.23084080E-8
[PBP = 3] 0.0000052778 .730 32.38 1 .000 1.430794722 1.4308052778
[PBP = 4] 0.0000471583 .708 7.672 1 .006 1.3876328417 1.3877271583
Location [Pr=1] .016 .492 4.924 1 .026** .94832 .98032
[Pr=2] .044 .539 .940 1 .002** 1.01244 1.100044
[Pr=3] .119 .271 .381 1 .001** .41216 .65016
67
[Pr=4] .283 .261 .996 1 .318 .22856 .79456
[Pr=5] 1 . . 0 . . .
[AOF=1] .024 1.49 6.290 1 .203 2.90228 2.95028
[AOF=2] .056 .320 7.699 1 .345 .5712 .6832
[AOF=3] .318 .303 .226 1 .635 .27588 .91188
[AOF=4] .348 .365 .023 1 .881 .3674 1.0634
[AOF=5] 1 . . 0 . . .
[BNAW=1] .077 .663 .705 1 .001** 1.37648 1.22248
[BNAW=3] .196 .290 4.687 1 .030** .7644 .3724
[BNAW=4] .928 .251 .086 1 .770 1.41996 .43604
[BNAW=5] 1 . . 0 . . .
[BAtt=1] .032 1.06 .183 1 .669 2.11744 2.05344
[BAtt=2] .072 .859 5.411 1 .020** 1.75564 1.61164
[BAtt=3] .182 .340 7.800 1 .000** .8484 .4844
[BAtt=4] .386 .299 5.502 1 .019** .97204 .200040
[BAtt=5] 1 . . 0 . . .
[PSQ=1] .124 1.42 8.302 1 .004** 2.90328 2.65528
[PSQ=3] .246 .443 .827 1 .002** 1.11428 .62228
[PSQ=4] .465 .449 .625 1 .014** 1.34504 .41504
[PSQ=5] 1 . . 0 . . .
[ES=1] 1 . . 0 . . .
[ES=3] .038 .537 37.13 1 .000** 1.09052 1.01452
[ES=4] .113 .528 36.08 1 .000** 1.14788 .92188
[ES=5] 1 . . 0 . . .
Link function: Logit.
a. This parameter is set to zero because it is redundant.
b. It is significant if p-value < alpha value (0.05)
c. It is significant if the Wald value greater than the standard error
d. Odds ratios are the exponential of ordered log-odds (logit) regression coefficient (eβ
)
Source: Researcher’s survey; 2021
4.7.7.1. Discussion and Interpretation for odds ratio results (eβ)
According to the above odds ratio table 4.18, the following discussion and interpretation are giv-
en along with the hypothesis of the study and the decision to reject and accept is depend on the
alpha value, chi-square test result, and the odds ratio result value but the direction of odds ratio
68
interpretation is something different where it can be understood by, odds ratio result with great-
er than one means the variable or categories positively affects the dependent variable and with
an odds ratio less than one refers to the variable or categories are negatively affect dependent
variables. The interpretation was made only for a statistically significant variable.
H1:- Price has a statistically significant positive effect on passenger brand preference deci-
sion of long-distance public transport service in Bahir Dar city station.
Literature indicates that price and passenger brand preference has a direct association and direct
positive significant effect on passenger brand preference.
Based on the output of the ordinal logistic regression model table 4.18 indicates with the (odds
ratio = 0.016, 0.044, and 0.119 and the p-value 0.026, 0.002, and 0.001) respectively significant-
ly determines brand preference at 5% level of significance.
Passengers who feel the price charged from the preferred bus brand is not reasonable at all (who
responded strongly disagree) decreased the log odds of brand preference by 0.016 times of the
log odds of brand preference by passengers feels price charged is reasonable from the preferred
brand being other variables held constant.
Passengers who feel the price charged from the preferred bus brand is not reasonable (who re-
sponded disagree) decreased the log odds of brand preference by 0.044 times of the log odds of
brand preference by passengers feels price charged is reasonable for the preferred brand being
other variable remain constant.
Passengers who feel the price charged from the preferred bus brand is moderately reasonable
(who responded moderately) decreased the log odds of brand preference by 0.119 times of the
log odds of brand preference by passengers feels price charged is reasonable for the preferred
brand being other variable held constant.
In general, the odds ratio and parameter estimate result indicate that as the passengers charged a
reasonable price for his/her preferred bus brand, the capacity to choose the bus brand to become
better. i.e unreasonable charged price means less preferred the brand and reasonably charged
price means best preferred the brand and has moderately associated as the Spearman rho correla-
tion coefficient value (0.428%) and Kendall's tau-b value (0.360%) in chi-square test result
showed in table 4.14.
69
According to (Dharmaraj & Sivasubramanian, 2011) finding shows that having a reasonable
charged price has significantly influenced consumer‟s brand preferences. (Radhamani & Anja-
naRaju, 2016) the finding showed that the price of a brand plays a fundamental role in the con-
sumer‟s brand preference. If a brand is priced too high then a consumer will avoid it. The price
of a brand is an indication of the quality of the brand as well. Other studies finding by (R.
Ebrahim et al., 2016), the price of service positively affects the consumer brand preference in
hospitality marketing. The result of the current studies is consistent with this study's results.
Therefore, the finding above it is possible to reject the null hypothesis. Price has a statistically
significant positive effect on passenger brand preference. So, Accept the H1.
H2:- Brand name awareness has a statistically significant positive effect on passenger brand
preference decision of long-distance public transport service in Bahir Dar city station.
Literature shows that brand name awareness and passenger brand preference have a direct asso-
ciation and direct significance positive effect on passenger brand preference decision. Based on
the output of the ordinal logistic regression model table 4.18 indicates with the (odds ratio =
0.077 and 0.196 and the p-value 0.001 and 0.030) respectively significantly determines brand
preference at a 5% level of significance.
Passengers who have lower brand awareness levels for the preferred bus brand (who responded
disagree) decreased the log odds of brand preference by 0.077 times of the log odds of brand
preference by passengers have best brand awareness level about brand preference being other
variable held constant.
and the passengers who have a moderate awareness level for the preferred brand (who respond-
ed moderately) decreased the log odds of brand preference by 0.196 times of the log odds of
brand preference by passengers have best awareness level about brand preference being other
variable held constant.
The odds ratio and parameter estimate result showed that when the passenger's level of aware-
ness is increased, the power of choice preferred bus brand also increased. i.e low awareness
means less preferred bus brand, moderate awareness level means moderately agree to choose the
preferred bus brand and high awareness level means best preferred the bus brand and has strong-
ly associated as the Spearman rank correlation coefficient value (0.602%) and Kendall's tau-b
value (0.504%) in chi-square test result showed in table 4.14.
70
(Lema & Wodaje, 2018), the finding revealed that brand name awareness has a significant posi-
tive relationship with consumers‟ choice for lead them to lose their customers. According to
(Ogbuji, Anyanwu, & Onah, 2011), the finding indicates that brand name awareness has a signif-
icant effect on consumer purchase for regulated bottled water. The result of the current studies is
consistent with this study's results. Therefore, the finding above it is possible to reject the null
hypothesis. Brand name awareness has a statistically significant positive effect on passenger
brand preference. So, accept the alternative one.
H3:-Brand attributes have a statistically significant positive effect on passenger brand prefer-
ence decision of long-distance public transport service in Bahir Dar city station.
Different literature shows that brand attributes (comfort, customer care/ safety measures) and
passenger brand preference decision have a direct association/direct significance positive effect
on passenger brand preference. Based on the output of the ordinal logistic regression model table
4.18 indicates with the (odds ratio = 0.072, 0.182, and 0.386 and the p-value 0.020, 0.005, and
0.019) respectively significantly determines brand preference at a 5% level of significance.
Passengers who consider the preferred bus brand has not clean/comfort/, safety measures, cus-
tomer care from any dangers (who responded disagree) decreased the log odds of brand prefer-
ence by 0.072 times of the log odds of brand preference by passengers who have best consider
the preferred bus brand has clean/comfort/, safety measures, and customer care from any dangers
about brand preference being other variable held constant.
Passengers who consider the preferred bus brand has moderately clean/comfort/, safety
measures, and customer care from any dangers (who responded moderately) decreased the log
odds of brand preference by 0.182 times of the log odds of brand preference by passengers have
best consider the preferred bus brand has clean/comfort/, safety measures, and customer care
from any dangers about brand preference being other variable held constant.
Passengers who consider the preferred bus brand has clean/comfort/, safety measures, customer
care from any dangers (who responded agree) decreased the log odds of brand preference by
0.386 times of the log odds of brand preference by passengers have best consider the preferred
bus brand has clean/comfort/, safety measures, and customer care from any dangers about brand
preference being other variable held constant.
71
In general, the odds ratio and parameter estimate result conveyed that the bus service is comfort-
able, protects passengers from any kinds of threat/ safety measures or concern customer care at
the bus station areas, the passengers can choose the bus brand than ever. low and very low brand
attributes mean less choice the bus brand service due to no comfort, customer care and safety
measures whereas moderate and high brand attributes means prefer/choice the bus brand service
like comfort, customer care/ safety measures and has strongly associated as the Spearman rho
correlation coefficient value (0.630%) and Kendall's tau-b value (0.526%) in chi-square test re-
sult showed in table 4.14.
Similar studies conducted by (Anjulo & Gebeyehu, 2019) the finding conveyed that, transport
comfort, safety from accident and customer care is significantly determined passenger preference
and (Profillidis & Botzoris, 2012) also asserts that the safety, the level of comfort and cleanliness
had a big weight to determine the level of customer preference. The result of the current studies
is consistent with this study's results. Therefore, the finding above it is possible to reject the null
hypothesis. Brand attributes has statistically significant positive effect on passenger brand pref-
erence decision. So, accept alternative one.
H4:-Perceived service quality has a statistically significant positive effect on passenger brand
preference decision of long-distance public transport service in Bahir Dar City station.
Many kinds of literature indicate that perceived service quality and passenger brand preference
decision has a direct association/direct significance positive effect on passenger brand preference
decision. Based on the output of the ordinal logistic regression model table 4.18 indicates with
the (odds ratio = 0.124, 0.246, and 0.465 and the p-value 0.04, 0.002, and 0.014) respectively
significantly determines brand preference at 5% level of significance.
Passengers who obtain the lower quality of service for the preferred bus brand (who responded
strongly disagree) decreased the log odds of brand preference by 0.124 times of the log odds of
brand preference by passengers who obtain the best quality of service about brand preference
being other things remain constant.
Passengers who get moderate quality of service from the preferred bus brand (who responded
moderately) decreased the log odds of brand preference by 0.246 times of the log odds of brand
preference by passengers who get the best quality of service about brand preference being other
things remain constant.
72
Passengers who acquire a good quality of service from the preferred bus brand (who responded
agree) decreased the log odds of brand preference by 0.465 times of the log odds of brand pref-
erence by passengers who acquire the best quality of service about brand preference being other
variable held constant.
The odds ratio and parameter coefficients result indicate that as the bus service is reliable, re-
sponsible, and tangible, the passengers can choose the bus brand over another bus brand. Low
quality of service means less preferred the bus brand while the moderate and high quality of ser-
vice means moderately and highly choice the bus brand and has moderately associated as the
Spearman rho correlation coefficient value (0.488%) and Kendall's tau-b value (0.333%) in chi-
square test result showed in table 4.14.
Similar studies conducted by (Ul Zia & Sohail, 2016) the finding showed that there were statisti-
cally significant effects on quality with brand preference and the finding is similar to the results
of the study by (Hunde, 2019) the finding disclosed that quality has a statistically significant im-
pact on consumer preference and (Calantone & Knight, 2000), the finding conveyed that, service
quality is a significant effect on the performance of a product, and the interaction of a product
meeting or exceeding consumer expectations based on its performance is how quality is evaluat-
ed. The result of the current studies is consistent with this study's results. Therefore, based on the
finding above it is possible to reject the null hypothesis. Perceived service quality has a statisti-
cally significant positive effect on passenger brand preference decision. So, accept an alternative
one.
H5:-Employee service has a statistically significant positive effect on passenger brand prefer-
ence decision of long-distance public transport service in Bahir Dar City station.
Literature shows that employee service and passenger brand preference decision has a direct as-
sociation/ direct significance positive effect on passenger brand preference decision.
Based on the output of the ordinal logistic regression model table 4.18 indicates with the (odds
ratio = 0.038 and 0.113 and the p-value 0.000 and 0.000) respectively significantly determines
brand preference at a 5% level of significance.
Passenger‟s who gain moderate hospitality/employee service for the preferred bus brand (who
responded moderately) decreased the log odds of brand preference by 0.038 times of the log
odds of brand preference by passengers who gain excellent hospitality /employee service about
73
brand preference and passengers‟ who obtain good hospitality/employee service for the preferred
bus brand (who responded agree) decreased the log odds of brand preference by 0.113 times of
the log odds of brand preference by passengers who obtain excellent hospitality/employee ser-
vice about brand preference being other variable held constant.
The odds ratio and parameter estimate/coefficient result indicate that as the driver/co-driver,
Ticket seller, and other related stakeholders give better hospitality service to its passengers, the
level of preferring the bus brand becomes better. Moderate and high hospitality service means
moderately and best choice the bus brand than competing bus brand and hypothesis has strongly
associated as the Spearman rho correlation coefficient value (0.587%) and Kendall's tau-b value
(0.444%) in chi-square test result showed in table 4.14.
(G. Agu & Ogbuji, 2008) the result revealed that the road transport employees are positively de-
termined customers‟preference decisions. They organized road transporters have such employees
as front line staff; customer service officers, operations managers, waybill officers, security per-
sonnel, porters/ lodgers, as well as offline staff, accounts officers, auditors, etc., how these peo-
ple relate to customers tells whether there will be repeat patronage, positive word-of-mouth, and
recommendation. Other studies ' findings showed that employees with smiling faces, friendli-
ness, politeness, understanding customers' problems, and others have a positive effect on cus-
tomer choice (Mahmood & Khan, 2014). The result of the current studies is consistent with this
study's results. Therefore, based on the finding above it is possible to reject the null. Employee
services have a statistically significant positive effect on passenger brand preference decisions.
So, accept an alternative one.
Decision summary of the hypothesis
According to the ordinal regression coefficient and odds ratio results of the current study H1, H3,
H4, H5, and H6 fail to reject while H2 fails to accept. The decision of acceptance and rejection of
the hypothesis depends on the alpha value, in which a 5% significance level is used to identify
association strength and significance of variables to the factors of passenger brand preference.
74
Table 4-22: Test of hypothesis
No
Hypothesis statement
Signinificance
Decision
H1 Price has a statistically significant positive effect
on passenger brand preference decision of long-
distance public transport service in Bahir Dar
City station.
Significant
Failed to
reject
H2 Brand name awareness has a statistically signifi-
cant positive effect on passenger brand preference
the decision of long-distance public transport ser-
vice in Bahir Dar City station.
Significant
Failed to
reject
H3 Brand attributes have a statistically significant
positive effect on passenger brand preference de-
cision of long-distance public transport service in
Bahir Dar City station.
Significant
Failed to
reject
H4 Perceived service quality has a statistically signif-
icant positive effect on passenger brand prefer-
ence decision of long-distance public transport
service in Bahir Dar City station.
Significant
Failed to
reject
H5 Employee service has a statistically significant
positive effect on passenger brand preference de-
cision of long-distance public transport service in
Bahir Dar City station.
Significant
Failed to
reject
75
CHAPTER FIVE
5. SUMMARY, CONCLUSION, AND RECOMMENDA-
TION
5.1. INTRODUCTION
This chapter presented a summary, conclusions, and recommendations based on the findings of
the study. Accordingly, this chapter is organized into four subsections: Section 5.2 presented a
summary of major findings, section 5.3 presented the conclusion of the study, and 5.4 presents
the recommendations and 5.5 presented‟ further research directions.
5.2. Summary of major findings
The main objective of this study was to investigate the determinants of passenger brand prefer-
ence decision of long-distance public transport service in Bahir Dar City station through the total
distributed survey questionnaire (385), 95% were returned by the passengers in Bahir Dar City
station and then after the necessary data management located it was analyzed using ordinal lo-
gistic regression by running STATA version 14 and SPSS version 23 software package. So the
results of both descriptive and inferential statistics are generalized as follows.
This study revealed that: -
150(41%) of the passengers were female while 216(59%) were male passengers. As in-
ferred from descriptive statistics revealed that relatively male passengers were more than
females to prefer brand than ever.
From passengers‟ age categories, 4.9% of passengers below 20 years, 44.3% were from
21- 30 years, 29.2% of respondents‟ age group was from 31- 40 years, and 19.1% of pas-
sengers‟ age group was from 41- 50 years. And the remaining 2.5% of passengers were
from above 50 years old. As inferred from descriptive statistics shown that majority of
passengers were adults in age-level categories.
From the educational level of passengers, 4.4% of passengers were in primary school
completed, 14.5% were secondary school completed, 28.1 were having a diploma holder,
36.1% were BA/MSC holder and the remaining 16.9 were master and above holders. As
inferred from descriptive statistics displayed that the majority of passengers who use
long-distance public transport service were BA/MSC degree holders; from this, it is pos-
76
sible to see that they have enough knowledge/skill to compare one bus brand overall fa-
cilities with other bus brands.
From the passengers traveling frequency, .8% were traveling weekly period, 22.7% were
traveling monthly, 69.9% were traveling once a year and above and the remaining 6.6%
passengers were travel randomization. As inferred from descriptive statistics disclose that
the majority of passengers were traveling one year and above.
From the income level of the passengers, 9% of the passenger's income level have below
Br1000, 3.6% of the passenger's income level have from Br 1000-2500, 24, 9% of the
passenger's income level have from Br 2501-5000, 4.6% of the passenger's income level
have from Br 5001-7500, 39.9% of the passenger's income level have from Br 7501-
10000 and the remaining 18% of the passenger's income level have above Br 10000. As
inferred from descriptive statistics conveys that majority of the passenger's income level
have from Br 7501 - 10000; from this, it is possible to decide that they can pay a reason-
able price for the preferred bus brand.
About 64% of the respondents‟ respondents strongly agree and agree that they charged a
reasonable price/fair rate of payment from the preferred bus brand service.
Around 72% of the respondents strongly agree and agree that they have adequate
knowledge and skills about the preferred bus brand name.
Approximately 79% of the respondents strongly agree and agree that they get com-
fort/cleanness, protect the passenger from any problems or dangers, and concerned cus-
tomer care from the preferred bus brand service.
Approximately 58% of the respondents strongly agree and agree that they acquire a better
quality of service (responsiveness, courtesy, reliability, promptness, and tangible) from
the preferred bus brand service.
Around 55% of the respondents strongly agree and agree that they receive better employ-
ee hospitality (driver/co-driver, ticket seller, and other related stakeholders have a har-
monize relationship among passengers regarding the preferred bus brand service.
The influence of all independent variables together such as (price, availability of facility
brand name awareness, brand attributes, perceived service quality, and employee service)
to explain the dependent variable (passengers brand preference decision) is 68.4% as
Nagelkerke R-square result showed.
77
The passengers who feel unreasonable charged to reasonable charged price about the pre-
ferred brand decrease the log odds /logit/of brand preference by 0.016, 0.044, and 0.119
times of the log odds of brand preference by the passengers who feel reasonable charged
price about preferred bus brand respectively being other variable held constant and was
statistically significant.
The passengers who have a low and moderate level of awareness about chosen brand de-
crease the log odds of the brand preference by the 0.077 and 0.196 times of log odds of
brand preference by the passengers who have a high level of awareness about the pre-
ferred brand being other variable held constant respectively and was statistically signifi-
cant.
The passengers who consider low, moderate, and better brand attributes about cho-
sen/preferred brand decrease the log odds of the brand preference by the 0.072,0.182 and
0.386 times of log odds of brand preference by the passengers who have high brand at-
tributes respectively being other variable held constant and was statistically significant.
Passengers who feel lowest, low and moderate quality of service ( reliable, responsive-
ness and promptness about brand preference decrease the log odds of the brand prefer-
ence by the 0.124,0.246 and 0.465 times of log odds of the brand preference by the pas-
sengers who feels the high quality of service respectively being other variable remain
constant and was statistically significant.
Passengers who think moderate and better employees‟ service (Bus owner, Driver, Ticket
cuter) and other related stakeholders about brand preference decrease the log odds of the
brand preference by the 0.038 and 0.113 times of log odds of the brand preference by the
passengers who thinks better employee service respectively being other variable held
constant and was statistically significant.
The correlation test of the variable under study shows that price, availability of the facili-
ty, brand name awareness, brand attributes, perceived service quality, and employee ser-
vice have an association with passenger brand preference with the p-value of less than
5%.
The finding of this study indicates except the availability of facilities, all the variables
such as price, brand name awareness, brand attributes (comfort, safety measures, and cus-
tomer care), perceived service quality and employee service have statically significant
78
positive effects on passenger brand preference of cross country public bus transport ser-
vice in Bahir Dar City Bus.
5.3. Conclusions
This study was attempted to investigate the determinants of passenger brand preference decision
of long-distance public transport service in Bahir Dar City Bus.
In this study, ordinal logistic regression models were applied when our outcome is represented
by an ordinal variable. This shows how to evaluate the ordinal Proportional odds model and how
this can allow us too directly to evaluate the consistency in Odds ratios across an ordinal out-
come. Where the Proportional odds assumption is justified ordinal regression models could be a
powerful means of summarizing relationships that utilize all the information present in the ordi-
nal outcome. And the result shows that the study was the best fit with the regression model.
The existing study indicated that Price, Brand name awareness, Brand attributes (comfort, safety
measures, and customer care), Perceived service quality, and Employee service are significant
determinants for passengers brand preference decision but unfortunately, the availability of facil-
ity is not a statistically significant factor that determines passengers‟ brand preference decision
of long-distance public bus transport service in Bahir Dar City Bus with 95% confidence interval
or p-value of less than 0.05, even though the availability of facility is somewhat good but it does
not help this to prefer/choice specific bus brand. Therefore, Price, Brand name awareness, Brand
attributes (comfort, safety measures, and customer care), Perceived service quality, and Employ-
ee service are responsible factors for brand preference decision of long-distance public transport
service Bahir Dar city Station but it doesn't mean availability of facility are not important factors
slightly it is not a major factor which determines brand preference.
5.4. Recommendations
Based on the findings of the study and the conclusions of the result, the following
recommendations were forwarded:-
Brand attributes have a statistically significant effect on passenger brand preference deci-
sions. The study result showed that low brand attributes have less preferred bus brands.
Thus, The Ethiopian federal transport authority in cooperation with the service provider
should construct/build/ bus station/terminals areas for each bus brand (in Amharic
MENEHARIA) just like short distance transport service. In addition, the service provid-
79
er should assign/arrange/ additional transport services like Minibus/Bajaj/ as they reached
a particular source and destination to safe the passengers from theft/bandits, and also the
concerned body should hire enough security personnel at the bus station.
Price has a statistically significant positive effect on passenger's brand preference deci-
sions. The finding disclosed that unaffordable price has less preferred bus brand. Hence,
the service provider company should adjust their price to make their service affordable
for the passengers. But in doing that they should certain their decision will not affect the
profitability of the companies.
Brand name awareness has statistically significant positive effects on passenger brand
preference decisions. The finding revealed that a low awareness level about a specific bus
brand has less preferred bus brand. Therefore, to deliver better brand awareness by the
passengers, the concerned body should implement appropriate promotion strategies
Advertizing (like Radio, TV, Newspaper, and Magazine) to give awareness about the
clear picture of the logo/symbol/of the specific brand, informing any relevant infor-
mation, knowledge, and experience about a specific brand.
Perceived service quality has a statistically significant effect on passenger brand prefer-
ence decisions. The finding indicated that low quality of service has less preferred bus
brand. Consequently, to create a better quality of service, the service provider should de-
liver prompt service, truthful, and responsible for the quality of service-related problems.
Brand attributes (comfort) have a statistically significant positive effect on passenger de-
cisions. The finding disclosed that some bus services are not neat, clean and in good con-
dition. Thus, to be comfortable bus service, the concerned bodies should focus on the
bus's neat, clean, and sitting arrangements and special facilities installed and also allo-
cate/donate/ for road construction as they ensure comfort and security.
Employee service has a statistically significant effect on passenger brand preference deci-
sions. The result showed that moderate and good employee hospitality of service. Hence,
to ensure better hospitality of service, the service provider should treat them friendly,
courteous, and show a willingness to help the passengers and provide prompt services
and explain the announcement of delays of the buses, the service provider should give
training and improve awareness of drivers/co-driver, ticket seller, and other related stake-
holders to bring attitudinal change.
80
5.5. Suggestions for Further Research Direction
The future researchers need to give much attention to passengers‟ brand preference that is over-
looked and empirically available. This study to investigate the passenger's brand preference deci-
sion was only included six major determinant factors and explained by 68.4%. This indicates
there should be some other predictors that are not included in this study. So, the future researcher
should focus on more factors that affect passenger brand preference decision such as Reference
group, Word of mouth , Ethnocentric feeling ,and Past experiance which can influence passenger
brand preference decision. In addition to this, future researchers should be including mediated
variable passenger satisfaction and moderation variable price by analyzing the Structural
Equation Model used AMOS software to help SPSS software to find out the effect of the interac-
tion among variables. Moreover, future research should be conducted in other regional City sta-
tions.
81
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87
APPENDICES 1.1፡ QUESTIONNAIRE (ENGLISH VERSION)
BAHIR DAR UNIVERSITY
COLLEGE OF BUSINESS AND ECONOMICS
DEPARTMENT OF MARKETING MANAGEMENT
A questionnaire is to be filled by passengers of the cross country public bus transport ser-
vice in Bahir Dar City station.
Dear all respected passengers’:
My name is Ahmed Mohammed. I am a post-graduate student at Bahir Dar University, College
of Business and Economics, Marketing Management. At this time; I am conducting a research
thesis on the Determinants of passengers' brand preference decision in case of long-distance
public bus transport service in Bahir Dar City for the fulfillment of the requirement of an M.A
degree in Marketing Management.
This questionnaire is prepared by the researcher to collect data from the respondents to examine
the Determinants of passengers' brand preference decision in a case of long-distance public
bus transport service in Bahir Dar City. I would greatly appreciate it if you take the time to an-
swer a few questions. It will take about 7-10 minutes. Its main purpose is to collect necessary da-
ta for investigating the study only for academic purposes and your response will be confidential
or not affect you in any case. As a result, the outcome of this study will highly depend upon your
response. Therefore, you are kindly requested to fill the questionnaire as per the instruction care-
fully and responsibly.
88
Instruction:
Please don‟t write your name
Give appropriate answers by putting “√” mark in the boxes
In case of any question or problem please contact me via phone No, and E-mail address.
Mob number: - 09-19-39-35-45 & 09-36-44-60-99
E-mail address: - [email protected]/[email protected]
In advance, I thank you so much for your support!!
Part I: General Information
Instruction: For each of the following statements, please put a (√) mark
1. Gender:-Male Female
2. Age categories of the passengers
Below 20 21-30 31-40 41-50 Above 50
3. Level of education completed
Primary School (1-8)
Secondary School (9-12)
Diploma (12+1-4)
BA/BSC degree
Mastersandbove
4. The frequency of traveling from the preferred bus brand
Weekly
Monthly
Once a year and above
If any specify it
5. Income level per month of the passengers
Less than Br 1000
Br 2501- 5000
Br 7500- 10,000
Br 1001- 2500
Br 5001-7500
Above Br 10,000
6. Which bus brand you prefer to travel
Abay Bus
AirBus
Africa Bus
Dream liner Bus
Yegna Bus
Golden Bus
Habesha Bus
Walya Bus
ZemenBus
Part II: - Underlying factors affect of passenger brand preference decision of cross country
public transport service
Dear respected respondents!
89
Please look at carefully the numbers on the Likert five-point scale. Then indicate the scales how
you agree or disagree with the following statements on passengers ‟brand preference for public
bus transport service by putting a “√” mark in one of the numbers given for the five scales
against each statement below.
Note 1 = Strongly Disagree, means you strongly disagree with the idea requested
2 = Disagree, means you disagree with the idea requested
3 = Moderate, which means somewhat agree with the idea requested
4 = Agree, means you agree with the idea requested
5 = Strongly Agree, means you strongly agree with the idea requested
Strongly Agree Agree Moderate agreement Disagree Strongly Disagree
5 4 3 2 1
1. Price
S. No Measuring statements about price 5 4 3 2 1
1 My preferred bus brand is approximately fairly charged.
2 My preferred bus brand is very economical.
3 My preferred bus brand uses by considering the amount of payment.
4 My preferred bus brand uses if it is competitively priced.
2. Availability of facilities
S. No Measuring statements about the availability of facilities 5 4 3 2 1
1 There are adequate physical facilities like toilets, showers, drink-
ing water, etc.
2 There are cafeteria and food joints for the facility of passengers‟
around the bus station.
3 There are bus shelters, seating arrangements, parking spaces for
waiting passengers.
4 The station has proper lighting facilities for the passengers dur-
ing the night.
5 There is service facility of minibus or baggage from my house to
the bus station
3. Brand name Awareness
S. No Measuring statements about brand name awareness 5 4 3 2 1
1 I have adequate knowledge and information about the preferred
bus brand.
2 The feature of the preferred bus brand comes to my mind imme-
90
diately as I think about the bus brand.
3 I can recognize quickly the preferred bus brand among other
competing bus brands.
4 I feel more secure when its service with a well-known brand.
5 I know the logo/symbol of my preferred bus brand.
4. Brand Attributes (comfort, customer care, and safety measures
S. No Measuring statements about brand attributes(comfort, cus-
tomer care, and safety measures
5 4 3 2 1
1 The buses are always neat and clean.
2 The seating arrangement in the bus is comfortable.
3 My preferred bus brand has enough windows placed with glasses
for proper ventilation for the passengers.
4 There are security employees for the safety of the passengers at
the bus station.
5 My preferred bus brand is always running at safe and carries the
passengers as per the specified capacity.
5. Perceived service quality
S. No Measuring statements about the perceived service quality 5 4 3 2 1
1 My preferred bus brand has a prompt service quality.
2 My preferred bus brand has been perceived as better service
quality.
3 My preferred bus brand has an acceptable service quality stand-
ard.
4 My preferred bus brand has a comfortable quality.
5 My preferred bus brand has visually appealing facilities associ-
ated with the services.
6 My preferred bus brand has kept passengers informed about
when the service is executed.
7 My preferred bus brand has trustworthy in handling passenger‟s
complaints and problems.
6. Employee service
S. No Measuring statements about employee service 5 4 3 2 1
1 Employees in the bus station (driver, operator, and ticket) are
friendly, courteous, and show a willingness to help the passen-
gers‟.
2 Employees in the bus station provide prompt service and explain
the announcement of delays of the bus.
3 Employees in the bus station have the knowledge and experience
91
to perform their activities accurately and dependably.
4 Employees in the bus stations are caring, inspiring trust and con-
fidence in delivering service.
5 The ticket seller is volunteers to return the money when the pas-
senger late and absent from their journey.
6 The bus service providers are good management systems to gov-
ern operators, passengers, drivers, ticket sellers, and other relat-
ed stakeholders.
Part III: - Measurements of passenger brand preference decision
Strongly Agree Agree Moderate Disagree Strongly Disagree
5 4 3 2 1
S. No Measuring statements about the passengers’ brand prefer-
ence decision
5 4 3 2 1
1. I frequently prefer the best quality brand.
2. I frequently prefer a reasonable rate of payments.
3. I frequently prefer a comfortable bus service
4. I frequently prefer the brand I know very well.
5. I frequently prefer bus brand which harmonizes the relationship
between passengers and employees in the bus service.
Any comments on unmentioned issues
---------------------------------------------------------------------------------------------------------------------
---------------------------------------------------------------------------------------------------------------------
-------------------------.
Thank you again for your kind co-operation!
92
APPENDICES 1.2: QUESTIONNAIRE (AMHARIC
VERSION)
ባህር ዳር ዩኒቨርሲቲ
ቢዝነስና እና ኢኮኖሚክስ ኮሌጅ
ማርኬቲንግ ማኔጅመንት ትምህርት ክፌሌ
ይህ መጠይቅ በባህር ዳር ከተማ በአውቶቡስ ማረፉያ/ማቆሚያ ውስጥ በአገር አቋራጭ የህዝብ አውቶቡስ ትራንስፖርት
አገሌግልት ተሳፊሪዎች የሚሞሊ ነው ፡፡
ውድ የተከበራችሁ የትራንስፖርት አገሌግልት ተጠቃሚዎች ሁለ፡-
እኔ አህመድ ሙሐመድ እባሊሇሁ፡፡ በባህር ዳር ዩኒቨርስቲ ፣ ቢዝነስ እና ኢኮኖሚክስ ኮላጅ ፣ የማርኬቲንግ ማኔጅመንት
ሁሇተኛ ዲግሪ /ድህረ ምረቃ/ ተማሪ ነኝ፡፡ ስሰሆነም በባህር ዳር ከተማ በአገር አቋራጭ የህዝብ ማመሊሇሻ አውቶቡስ
ትራንስፖርት አገሌግልት ሊይ የምርምር እና ጥናታዊ ፅሑፌ እያካሄድኩ እገኛሇሁ፡፡
ይህ መጠይቅ በባህር ዳር ከተማ የሀገር አቋራጭ የህዝብ አውቶቡስ ትራንስፖርት አገሌግልት ጉዳይ ተሳፊሪዎች ሰሇ ምርት
መሇያ/ብራድ / ምርጫ ውሳኔን ሇማጥናት የተሇያዩ መረጃ ሇመሰብሰብ በተማሪው ተዘጋጅቷሌ፡፡ ሇእነዚህ ጥያቄዎች መሌስ
ሇመስጠት ከ7-10 ደቂቃዎች ያህሌ ሉወስዱ ይችሊለ፤ ሇዚህም ጊዜዎን ስሇሠጡኝ በጣም አመሰግናሇሁ፡፡ የጥናቱ ዋና
ዓሊማው ሇትምህርት /ሇአካዳሚክ/ አገሌግልት ብቻ ነው፡፡ በመሆኑም የእርስዎ ምሊሽ ሚስጢሩ የተጠበቀ ወይም
በማንኛውም ሁኔታ ሊይ ምንም አይነት ተጽዕኖ የሇዉም፡፡ የዚህ ጥናት ውጤት በእርስዎ ምሊሽ ሊይ የተመረተ ይሆናሌ።
ስሇሆነም መጠይቁን እንዲሞለሌኝ በአክብሮት/በትህትና እጠይቃሇሁ፡፡
መመሪያ
እባክዎን ስምዎን አይፃፈ
ሇጥያቄዎቹ ተገቢውን መሌስ በሳጥኖቹ ውስጥ የ “√” ምሌክት ያስቀምጡሌን፡፡
93
በዚህ መጠይቅ ሊይ ማንኛውም አይነት ጥያቄ ወይም ችግር ካሇ እባክዎን በስሌክ ቁጥር ወይም በኢሜሌ አድራሻ
ያነጋግሩኝ
የስሌክ ቁጥር:- 09-19-39-35-45 & 09-36-44-60-99
የኢሜሌ አድራሻ ፡ - [email protected]/[email protected]
መጠይቁን ስሇሞለሌኝ በቅድሚያ አመሰግናሇሁ !
ክፌሌ አንድ :- አጠቃሊይ መረጃ
መመሪያ - ሇሚከተለት ሇእያንዳንዱ መሌሶቻቹሁ እባክዎን የ (√ ) ምሌክት ያስገቡ
1. ፆታ:- ወንድ ሴት
2. የተሳፊሪው የዕድሜ ደረጃ
ከ20 አመት በታች
21-30
31-40
41-50
ከ 50 ዓመት በሊይ
3. የትምህርት ደረጃ
የመጀመሪያ ደረጃ ትምህርት ቤት (1-8)
ሁሇተኛ ደረጃ ትምህርት ቤት (9-12)
ዲፕልማ (10 + 1-4)
ቢኤ /ቢኤሲ ዲግሪ
ማስተርስ ዲግሪ እና በሊይ
4.የመረጡትን የአውቶቡስ ምርት መሇያ በየ ስንት ጊዜው ይጓዛለ
በየ ሳምንቱ
በየ ወሩ
በ አመት አንድ ጊዜ
ላሊ ካሇ
5. የተሳፊሪዎች የወር ገቢ መጠን ፡-
ከብር 1000 በታች
ከብር 1001- 2500
ከብር 2501- 5000
ከብር 5001- 7500
ከብር 7501-10000
ከብር 10,000 በሊይ
6. ሇመጓዝ ሲያስቡ የትኛውን የአውቶብስ ምርት ስም ይመርጣለ
አባይ አውቶቢስ
ኤር አውቶቢስ
አፌሪካ አውቶቢስ
ጎሌደን አውቶቢስ
ድሪም ሊይነር አውቶቢስ
ሀበሻ አውቶቢስ
ዋሉያ አውቶቢስ
ዘመን አውቶቢስ
የኛ አውቶቢስ
94
ክፌሌ ሁሇት : - የአገር አቋራጭ የህዝብ ትራንስፖርት አገሌግልት ተጠቃሚዎች የምርት መሇያ/ ብራንድ/
ምርጫ ውሳኔን ሇመሇካት ስሇሚረዱ ወሳኝ ሁኔታዋች መጠይቅ
ውድ የተከበራችሁ ምሊሽ ሰጪዎቼ !
እባክዎን የአምስት ሚዛን ቁጥሮችን በጥንቃቄ ይመሌከቱ ፡፡ ከዚያ በተጠቀሰው ቁጥር ውስጥ የ “√” ምሌክት በማስቀመጥ
በሕዝብ አውቶቡስ ትራንስፖርት አገሌግልት ሊይ በተሳፊሪዎች ምርጫ ሊይ በሚከተለት መግሇጫዎች ሊይ እንዴት
እንደሚስማሙ ወይም እንደማይስማሙ ያሳዩ ፡፡ ከዚህ በታች ያለት እያንዳንዱ መግሇጫዎች ሊይ አምስቱ ሚዛኖች ፡፡
ማሳሰቢያ 1 = በጣም አሌስማማም ማሇት በተጠየቀው ሀሳብ ሙለ በሙለ አሌስማሙም ማሇት ነው።
2 = አሌስማማም ማሇት በተጠየቀው ሀሳብ አሌስማማም ማሇት ነው።
3 = በመጠኑ ማሇት በተሰጠው ሀሳብ መጠኑ እስማማሇሁ ማሇት ነው።
4 = እስማማሇሁ ማሇት በተጠየቀው ሀሳብ እስማማሇሁ ማሇት ነው።
5 = በጣም እስማማሇሁ ማሇት በተጠየቀው ሀሳብ ሙለ በሙለ እስማማሇሁ ማሇት ነው።
በጣም እስማማሇሁ እስማማሇሁ በመጠኑ እስማማሇሁ አሌስማማም በጣም አሌስማማም 5 4 3 2 1
1. ዋጋ
ተ.ቁ መመዘኛ ስሇ ዋጋ 5 4 3 2 1 1 እኔ የመረጥኩት አውቶቡስ ምርት መሇያ/ብራድ/ ተመጣጣኝ የሆነ ዋጋ
ያስከፌሊለ።
2 እኔ የመረጥኩት አውቶቡስ ምርት መሇያ/ብራድ/ ምርጫ በጣም ገንዘብ ቆጣቢ ነው
3 እኔ የመረጥኩት አውቶቡስ ምርት መሇያ/ብራድ/ የክፌያው መጠን እኔን ከግምት ውስጥ በማስገባት ነው።
4 እኔ የመረጥኩት አውቶቡስ ምርት መሇያ/ብራድ/ ከላልች አውቶቡስ የሚያስከፌለት ዋጋ ጋር ተቀራራቢ ነው።
95
2. አውቶቡሱ የሚሰጣቸው አቅርቦቶች
3. የምርት መሇያ/ብራድ/ ግንዛቤ
ተ.ቁ መመዘኛ ስሇ ምርት መሇያ/ብራድ/ ግንዛቤ
5 4 3 2 1
1 የመረጥኩትአውቶቡስ የምርትመሇያ/ብራድ/በቂ እውቀትና ተገቢ የሆነ መረጃ አሇኝ ፡፡
2 የመረጥኩት አውቶቡስ መሇያ ባህሪ ወዳውኑ ወደ አእምሮዬ ይመጣሌ ፡፡
3 ከላልች ተወዳዳሪ አውቶቡሶች ሲታይ እኔ የመረጥኩት አውቶቡስ የምርቱ መሇያ ምን እንደሆነ አውቃሇሁ ፡፡
4 ታዋቂ ምርት ስም አገሌግልት የሚሰጡት ይበሇጥ ሇደህንነታችን የተረጋገጠ ነው ፡፡ 5 የመረጥኩት አውቶብስ ምርት ምሌክቱ / አርማው ምን እንደሆነ አውቃሇሁ ፡፡
4. የምርቱ መሇያ ባህሪዎች (ምቾት ፣ ሇተሳፊሪዎች እንክብካቤ የሚሰጥ እና ጥንቃቄ የሚወስዱ)
ተ.ቁ መመዘኛ ስሇ ምርቱ መሇያ ባህሪዎች( ምቾት ፣ ሇተሳፊሪዎች እንክብካቤ የሚሰጥ እና ጥንቃቄ የሚወስዱ)
5 4 3 2 1
1 አውቶቢሱ ሁሌ ጊዜ በጥሩ ሁኔታ ሊይ ያሇ እና ንፁህ ነው ፡፡
2 አውቶቡሱ ውስጥ ያለ ወንበሮቸ ምቹ ናቸው። 3 የመረጥኩት አውቶቡስ ምርት መሇያ ሇተሳፊሪዋች በቂ የሆነ አየር ማስወጫ እና
ማስገቢያ መስኮቶች አለት ፡፡
4 በአውቶቢሱ መቆሚያ አከባቢ ሇተሳፊሪዎች ደህንነት ሲባሌ የደህንነት ሰራተኞች አለ ፡፡
5 እኔ የመረጥኩት አውቶቡስ ምርት መሇያ ሁሌጊዜ ደህንነቱ የተጠበቀ እና ተሳፊሪዎችን በወንበር ቁጥር ብቻ ይይዛለ።
5. ጥራቱን የጠበቀ አገሌግልት
ተ. ቁ መመዘኛ ስሇ አውቶቢሱ የሚሰጣቸው አቅርቦት 5 4 3 2 1 1 እንደ ሽንት ቤት ፣ ሻወር ፣ የመጠጥ ውሃ ያለ በቂ የሆኑ አቅርቦቶች አለት ፡፡ 2 አውቶቡሱ የሚቆመው/ የሚያርፇው/ ሇተሳፊሪዎች ጥራቱን የጠበቀ ምግብ አሇበት
አከባቢ ነው ፡፡
3 የአውቶቡሱ ወንበር ሌብሶች ፣ የመቀመጫ ሁኔታው፣የተሳፊሪዎች የማቆሚያ ቦታ አሇው፡፡
4 አውቶቡሱ መነሻ ቦታ ሇተሳፊሪዎች ላሉት መብራት አሇው ፡፡ 5 ከቤቴ እስከ አውቶቡስ ጣቢያ ድረስ አነስተኛ አውቶቡስ አገሌግልት ይሰጣለ፡፡
ተ.ቁ መመዘኛ ስሇ ጥራቱን የጠበቀ አገሌግልት መግሇጫ 5 4 3 2 1 1 እኔ የመረጥኩት አውቶቡስ ምርት መሇያ ጥራቱን የጠበቀ ፇጣን አገሌግልት
ይሰጣሌ።
2 እኔ የመረጥኩት አውቶቡስ ምርት መሇያ ጥራቱ የተሻሇ የአገሌግልት እንደሆነ አቃሇሁ።
96
6. የትራንስፖርት ሰራተኞች የሚሰጡት አገሌግልት/መስተንግዶ/
ተ.ቁ መመዘኛ ስሇ ሰራተኞቹ የሚሰጡት አገሌግልት/ መስተንግዶ/ 5 4 3 2 1 1 በአውቶቡስ ጣቢያ ያለ ሰራተኞች ሁለ ማሇትም (ሹፋሩ ፣ ኦፕሬተር እና ቲኬት)
ተግባቢ ፣ መሌካም ስብእና ያሊቸው እና ተሳፊሪዎችን ሇመርዳት ፇቃደኞ ናቸው ፡፡
2 በአውቶቡስ ጣቢያ ውስጥ ያለ ሰራተኞች ፇጣን የሆነ አገሌግልት የሚሰጡ ሲሆን እና አውቶቡሱ ባገጣሚ ቢዘገይ ሇተሳፊሪዎች መሌእክት ያደርሳለ ፡፡
3 በአውቶቡስ ጣብያ ውስጥ ያለ ሰራተኞች ስራቸውን በትክክሌ እና በተገቢው መንገድ ሇማከናወን በቂ ዕውቀት እና ሌምድ አሊቸው ፡፡
4 በአውቶቡስ ጣብያ ውስጥ ያለ ሰራተኞች ጠንቃቃ ፣ አገሌግልት ሇመስጠት እምነት የተጣሇባቸው እና የምንተማመንባቸው ሰራተኞች ናቸው ፡፡
5 የአገሌግልት ትኬት ተቀባዩ ተሳፊሪው በችግር ምክኒያት ቢከር እና ዘግይቶ ቢመታ ብሩን ሇመመሇስ ፇቃደኛ ናቸው።
6 የአውቶቡስ አገሌግልት ሰጭ ሰራተኞች ማሇትም ኦፕሬተር ፣ ተሳፊሪዎች ፣ቲኬት ፣ ሹፋሩ እንዲሁም ላልች ባሇድርሻ አካሊትን የሚያስተዳድሩበት ትክክሇኛ አመራር ስርዓት አሊቸው ፡፡
ክፌሌ ሶስት :- የተሳፊሪዎች የምርት መሇያ/ብራንድ/ ምርጫ ውሳኔን ሇመሇካት
በጣም እስማማሇሁ እስማማሇሁ በመጠኑ እስማማሇሁ አሌስማማም በጣም አሌስማማም
5 4 3 2 1
ያሌተጠቀሰ ሀሳብ ወይም አስተያየት ካሇወት
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3 እኔ የመረጥኩት አውቶቡስ ምርት መሇያ ተቀባይነት ያሇው የአገሌግልት ጥራት ደረጃ አሇው።
4 እኔ የመረጥኩት አውቶቡስ ምቹ ጥራት አሇው። 5 እኔ የመረጥኩት አውቶቡስ ምርት መሇያ ከአገሌግልቱ ጋር የተያያዙ የተሇያዩ
ማራኪ የሆኑ አገሌግልቶች አለት።
6 እኔ የመረጥኩት አውቶቡስ ምርት መሇያ አገሌግልቱን የሚሰጥበት የሰአት ገደብ ተደንግጓሌ።
7 እኔ የመረጥኩት አውቶቡስ ምርት መሇያ የተሳፊሪዎችን ቅሬታ እና አሇመግባባት ችግሮችን በተገቢው መንገድ ይፇታለ።
ተ.ቁ መመዘኛ ስሇ ተሳፊሪዎች የምርት ምርጫ ውሳኔ 5 4 3 2 1 1 ብዙ ጊዜ የምርት ጥራት ያሇውን የአውቶቡስ አይነትእመርጣሇሁ፡፡ 2 ብዙ ጊዜ ምክንያታዊ ዋጋ የሚያሰወከፌለ የአውቶቡስ ምርት እመርጣሇሁ፡፡
3 ብዙ ጊዜ ምቾት ያሇው የአውቶቡስ ምርትአይነት እመርጣሇሁ ፡፡
4 ብዙ ጊዜ የማቀውን የአውቶቡስ ምርት ያሇውን /ብራንድ/አይነት እመርጣሇሁ፡፡ 5 ብዙ ጊዜ የምመርጠው አውቶቡስ የትራንስፖርት ሰራተኞች እና ተሳፊችዎቸ
መሌካም የሆነ መስተንግዶ ያሊቸውን ነው ፡፡
97
ስሇ ትብብርዎ እንደገና ከሌብ አመሰግናሇሁ!