Principles of Marketing Research 3

Omari Mbura

118

Open Access article distributed in terms of the

Creative Commons Attribution License [CC BY 4.0] (http://creativecommons.org/licenses/by/4.0)

SALIENT ATTRIBUTES ON THE CHOICE OF AN AIRLINE SERVICE

PROVIDER: A CASE OF DOMESTIC AIRLINES IN TANZANIA

Omari K. Mbura 1

ABSTRACT

This paper reports the findings of a study which assessed the attributes influencing

customers’ choice of airline on domestic routes. Its independent variables were service

quality, price, image and airline schedules. A structured questionnaire was administered with

120 airline passengers at Julius Nyerere International Airport (JNIA). Quantitative data have

been analysed with the help of the Statistical Package for Social Sciences (SPSS) version 22

and presented as descriptive statistics. Moreover, the study carried out regression analyses to

ascertain the strength of the relationship between the four constructs and the choice of an

airline service provider in the domestic market. The study found that airline schedules, price

and airline image significantly influenced the customers’ choice of an airline. Service quality

attributes, on the other hand, did not seem to have significant bearing on airline choice.

Thus, the paper recommends that airline firms should focus on providing convenient

schedules in their service provision. Moreover, fares should be set at considerably fair rates

as the majority of the clients are price-sensitive. Furthermore, there is a need to foster good

and positive airline image.

Key Words: Service quality, Airline Schedule, Price, Airline Images, Airline Service Provider

INTRODUCTION

Technological advancements have resulted in significant developments in the airline industry

which across the world serves as not only a reliable means of transportation but also acts as

an enabler in achieving economic growth and development. In fact, air transport facilitates

the integration into the global economy and provides vital connectivity on a national,

regional, and international scale. According to IATA annual Review (2017) Aviation brings

people together, transports vital medicines to patients in need, and facilitates the exchange of

experiences and ideas. It also creates significant employment hence contributing to making a

living through created income. According to Fraissard (2004), air transport creates 3.9

million jobs all over the world. Large improvements in aircraft technology coupled with the

rise of Low-Cost Carriers (LCCs), also known as budget airlines, accounts for more than half

of total capacity, hence allowing many people to fly for the first time (Fernandez, 2017).

The USA Air Commerce Act states the power to establish airways, certify aircrafts and

enforce air traffic regulations. The first commercial airlines were Pan American, Western Air

Express and Ford Transport Service. Later on, other modern day airlines emerged as major

players (Harris, 2010). In 1938, the Civil Aeronautics Board (CAB) was established, which in

turn led to the regulation of the airline industry (Gilliland, 1971). The board was responsible

for controlling airline routes and regulating prices for passenger fares. Essentially, the CAB‘s

1 Department of Marketing, University of Dar es Salaam Business School, P.O. Box 35046, Dar es Salaam,

Tanzania

Business Management Review 22(2), pp. 118-136 ISSN 0856-2253 (eISSN 2546-213X) ©July-October, 2019

UDBS. All rights of reproduction in any form are reserved

Omari Mbura

119

role was to protect the industry from itself through government intervention. NewMyer

(1990) reveals that this protection covered various CAB actions which limited competition

among airlines through pricing controls, and route controls in addition to limiting the

formation of new, large airline companies. During this time, few airlines were operating, with

the majority being low fares; nevertheless, the quality of service was the main focus (Harris,

2010). The board determined whether competition in a particular area is necessary to assure

the sound development of an appropriate system. In exercising this discretion, the Board was

duty-bound to protect the industry against the evils of unrestrained competition, on the one

hand, and the adverse consequences of monopolistic control, on the other. Competition

invites comparison on the equipment, cost, personnel, organisation, methods of operation,

solicitation and handling of traffic, all of which tend to ensure the development of an air

transportation system (Gilliland, 1971)

The overly regulated airline market in the US opened up to the private companies after the

introduction of the De-regulation Act in 1978. The De-regulation Act minimised entry

barriers, hence paving the way for the introduction of several commercial airlines introduced,

and opening of new routes directly connecting cities. Moreover, government intervention was

minimal. In the meantime, the fares were determined by the airline companies following the

De-regulation Act. Overall, De-regulation resulted in increased competition which led

airlines to compete based on pricing and total collapse of some of the major full carriers such

as Pan American and Trans World Airline which had hitherto dominated the sky (NewMyer,

1990; Harris, 2010).

Owing to the nature of the airline market structure which is oligopolistic, few companies do

dominate a limited market. Customers are hypersensitive to fare, causing airlines to operate

close to the break-even seat factor. On average, 80% of airline companies use flexible pricing

whereby most of the seats are on discount basis to fill the aircraft because empty seats are

perishable (Malik, 2016). The competition that started in 1978 continues to exist to the

present in most of the countries around the world.

Tanzania on its part acquired its first airline in 1977, a year before the liberalisation of the

airline market across the world. Tanzania is one of the fastest growing regions in the

continent in terms of international traffic with an average growth rate of 6-7% compared to

the global average of 5.8% and 7.9% in the Middle East and Asia Pacific, respectively. In

Europe, Latin America and North America are projected to record lower international

passenger growth rate of 5.0, 5.8% and 4.9%, respectively (www.ippmedia.com).

Air Transport in Tanzania

Before 1977, air transport was not the major form of transportation for the majority of the

people in Tanzania (Skwirk, 2014). Indeed, people travelled mostly by land followed by

water-based transport (ibid.). In fact, most of the people found air transport to be too

expensive for them to afford, regardless of the time saved when it is used as an option

(Mbura, 2017). This reality is in line with the truism that the majority of the Tanzanians are

poor, many of whom live on less than a dollar per day. Inevitably, the majority of Tanzanians

were unable to pay for the expensive flights. This scenario necessitated the introduction of

low-cost carriers (LCCs) in 2012 (Timanywa, 2017). In Tanzania, Fastjet was the first airline

to apply the LCC business model. Initially, it operated domestic flights before expanding its

services to other Sub-Saharan African countries.

The introduction of LCC airlines has allowed a considerable number of Tanzanians

passengers to shift from land and water transport to air transport as the fares for travelling

Omari Mbura

120

have been considerably fair and in some few cases they have competed with land transport

fares. This trend culminated in increased airline passengers in the Tanzania market. Table 1

shows the trend of the growth of the airline passengers over years:

Table 1: Passengers Traffic Records for Government Airports in Tanzania

Year No of Passengers Average No per month Average No per day

1999 1,269,397 105,783 3,526

2000 1,381,400 115,117 3,837

2001 1,418,872 118,239 3,941

2002 1,561,608 130,134 4,338

2003 1,732,395 144,366 4,812

2004 2,200,064 183,339 6,111

2005 2,458,082 204,840 6,828

2006 2,766,956 230,580 7,686

2007 3,177,258 264,772 8,826

2008 3,212,414 267,701 8,923

2009 2,966,829 247,236 8,241

2010 3,228,908 269,076 8,969

2011 3,877,949 323,162 10,772

2012 4,359,418 363,285 12,109

2013 4,954,074 412,840 13,761

2014 5,193,265 432,772 14,426

2015 5,114,835 426,236 14,208

2016 7,135,903 594,659 19,822

Source: Tanzania Airport Authority (2016)

As Table 1 illustrates, the number of passengers travelling on domestic routes increased from

an average of 3,526 passengers per day in 1999 to 19,822 passengers per day in 2016.

According to Tanzania Invests (2016), the number of air passengers in Tanzania increased by

62% in the past five years from 2.1 million in 2010 to 3.5 million in 2015. Such an increase

marks a shift of passengers to air transport, meaning that the demand for using air transport

service is increasing. In fact, this increase in the average number of passengers in 2012

Omari Mbura

121

coincides with the introduction of FastJet Tanzania. This first LCC in Tanzania motivated

certain travel segments to use air transport. ForwadKeys—a Spanish company—conducted

analysis in 2016 on international air travel to East Africa and found Tanzania to be one of the

top ten Africa air travel destinations. Specifically, ForwadKeys ranks Tanzania 8th with a 3%

share of the total international air arrivals to Africa. South Africa ranks 1st with 13% share,

followed by Egypt with 9%, Morocco (8%), Mauritius (5%), Kenya (4%), Algeria (4%), and

Tunisia (4%). Ethiopia (3%) is at the same level with Tanzania but above Nigeria (2%).

Other countries in Africa account for 45 percent (Tanzania Invests, 2016). The growth of

economic activities at least in the mining and tourism sectors has been associated to

accounting for this growth (Ibid). Despite the LCC being introduced, the number of

Tanzanians using air transport taking advantage of the model is not in proportion to the entire

Tanzania population of about 54.5 million, with the majority using land transportation.

The first commercial airline to operate local routes in Tanzania was Air Tanzania, a national

carrier, which was established in 1977. This was followed by Coastal Aviation (1987)

operating routes along the coastal regions. Later on, other airlines emerged such as

PrecisionAir (1991), Zan Air (1992), Air Excell famous by the name Tinga Tinga, Regional

Air (1997), Tropical Air (1999), Sky Aviation (2006) and FastJet (2012). The current study

focuses on three major airlines—Air Tanzania, PrecisionAir and FastJet to ascertain the

factors influencing the choice of airline to use in Tanzania‘s domestic market.

Market share for the selected Airlines

Market share represents the percentage of an industry, or market’s total sales, a particular

company earns over a specified period. The statistic in Table 2 represents the market share of

leading airlines in the Tanzania Domestic market for the selected airlines:

Table 2: Market share of the Tanzania Airline Industry

Domestic Air Operators (% Market Share)

Airline Company 2009 2010 2011 2012 2013 2015 2016

Precision Air Services PLC 48.4 57.8 58.58 62.7 48.33 21.4 23.3

Coastal Travel Limited 12.9 16.5 21.8 8.57 8.05 5.6 6.9

Zan Air 5.5 6.9 4.2 4.8 4.03 5.6 6.9

Auric Air Services 1 1.9 2 - - 8 8.3

Air Tanzania Company

Limited 19.2 6.7 0.4 - - 3 2.5

FastJet Airline - - - 5.94 19.45 46.8 42.6

Others 13 10.2 12.8 17.99 20.14 13.1 12.6

Source: Tanzania Civil Aviation Authority (2017)

Context of the paper

Air transport is generally the safest and fastest way to travel to the desired destinations

(Laurel, 2015). On daily basis, there are about 93,000 scheduled commercial aircraft flights

Omari Mbura

122

across the world (Becker, 2014). Despite the good reasons for using air transport, the number

of people using air transport particularly in Tanzania and elsewhere is not significantly

growing mainly because of stiff competition in the market (Harris, 2010) coupled with low

demand for air transport service. Both internal and external airline operators compete among

themselves and with other means of transport. Tanzania has more than 70 airlines offering

domestic services across the country as well as services within the East Africa region and

outside the region (Timanywa, 2017). The airline sector that starved of competition for more

than 30 years now has multiple players vying for business. This can only result in a faster,

more efficient and effective travel experience for business travellers.

One of the major sources of competition in this industry is the liberalisation of market access

and the De-regulation Act of 1978 in the US which reduced the entry barriers in the industry.

According to the International Air Transport Association (IATA), about 1,300 new airlines

have been established over the last 40 years (Cederholm, 2014). Competition tends to

increase when new airlines enter the market or when the existing airlines expand their

services to new markets. Mondliwa (2015) claims that in the airline industry the bargaining

power of customers is relatively high since most airlines are forced to cut costs by aggressive

competitors. Ismael (2015) re-affirms that the bargaining power of customers in the airline

industry is relatively high because airlines are highly vulnerable to any price reduction

measures introduced by their competitors due to the lack of brand loyalty associated with the

airline industry. Therefore, customers enjoy high bargaining power because switching to

another airline is simple and is not associated with additional expenses (Winsen, 2016).

In this regard, Malik (2016) argues that, this situation prompts most of the airlines to operate

at break-even or less. The persistence of the problem might cause collapse of the airline

business. As such, Airline companies need to address the problem in different ways. The

management in the airline companies can adopt the marketing mix elements model to create

desired response in the target market (Isoraite, 2016). These elements which are often in form

of product, price, place and promotion decisions (Kotler and Armstrong, 2012) can be

controlled to meet consumers‘ needs and achieve company‘s goals by stimulating the demand

for air transport.

Generally, delivering quality service (which is an important Product decision attribute) is an

essential strategy for attaining business success and ensuring survival (Ramseook-

Munhurrun, Lukea-Bhiwajee and Naidoo, 2010). In fact, quality service has a direct

relationship with the image of the airline company. In consequence, managers in the service

sector are under pressure to demonstrate that their service is customer centric, no matter their

financial and resource constraints (ibid.). In this regard, Geraldine and David (2013) urge

managers in airline companies to improve the quality of their service to boost their respective

airline‘s image, which also determines the passengers‘ choice and decision of repeat

patronage.

According to Kotler and Armstrong (2010) advertisement is an effective way of

communicating a company‘s product/service via text, sound and colour. Advertising helps to

form a long-term sustainable image of the product in addition to stimulating sales. Mohapatra

(2016) opines that the use of promo-tools such as discounts and good online or offline

advertising tends persuades customers to choose certain airlines over others.

Scheduling on the other hand determines where and when the airline will fly. Efficient

schedules, which match the supply and demand, are key to airline profitability (Jacobs et al.,

2012). Profitable solutions need anticipation of the market conditions, cost of capital, fuel,

Omari Mbura

123

labour, and competition level. Scheduling issues such as route availability, punctuality,

timing and frequency can be addressed with large-scale combinatorial optimisation

techniques. Implicitly, more experts in managing constraints and use of technology for

optimisation are required (Gervet, 1991).

Price is the determinant of choice of air transport in a highly price sensitive market (Ukpere,

et al., 2012). Many businesses charge a competitive fare as a technique applied for

influencing positive demand. One major effort aimed to reduce competition and stimulate

demand for air transport was the introduction of LCCs, which provides the lowest price for

consumers by undercutting the price levels of Legacy Carriers (Hameed, 2011). This strategy

currently seems largely inadequate as other airlines now offer the same advantage to the

customers, provided clients made early bookings. As a result, the same cut-throat competitive

environment experienced earlier by the airline companies remained the norm. It is against this

backdrop that the paper seeks to determine the attributes influencing customers‘ choice of an

airline.

Objective and structure of the paper

The paper assesses the influence of airline service quality, price, image and schedule-based

factors on the choice of airline for different domestic destinations in Tanzania. The study was

conducted with passengers at the Julius Nyerere International Airport in Dar es Salaam, the

largest international airport in Tanzania. It begins by presenting the theoretical basis of the

paper, before reviewing empirical literature and establishing the research gap. Then the paper

presents the conceptual framework, hypotheses, the methods, the results and analyses, and,

finally, the discussion of the findings prior to concluding and making the recommendations of

the study.

THEORETICAL BASES OF THE PAPER

The paper has adopted four theories: the Customer Matrix Model, Theory of Reasoned

Action, EKB Model and Gap Analysis Model as they complement each other in adequately

explaining the variables under study.

Customer Matrix Model

Bowman and Faulkner (2012) came up with a model which extends from the three Porter‘s

generic strategies of focus, differentiation and cost leadership. They configured an

alternative to Porter‘s Model called the Strategy Clock. The model considers different

combination of value and price. These are termed as Perceived User Value (PUV) and

Perceived Price (PP). The low-cost strategy (Cost leadership) is position 1-2 on the clock,

differentiation is position 4, and a hybrid strategy is position 3. The hybrid strategy may be

appropriate in certain scenarios and environments and lead to different results. Customers‘

needs manifested through value and pricing do generally differ. This implies that it is

important to take into account different combinations of the quality of service offered and

attach the corresponding price for each category of the service. It should then be possible to

identify different market segments with different levels of readiness for the value and price in

the airline industry. Thus, airline companies in Tanzania should stimulate demand which

can, consequently, influence choice through all possible strategies by having a sufficient

number of least cost carriers and legacy carriers with differentiated price points as Figure 1

illustrates:

Omari Mbura

124

Figure 1: Bowman Strategic Clock

Source: Bowman and Faulkner (1997)

Theory of Reasoned Action

Fishbein et al. (1967) developed the Theory of Reasoned Action. The theory posits that,

consumers act on a behaviour based on their intention to create or receive a particular

outcome. Consumer only takes a specific action when there is an equally specific result

expected. From the time the consumer decides to act to the time the action is completed, the

consumer retains the ability to change his or her mind and decide on a different course of

action.

Siringoringo and Noversyah (2015) applied Theory of Reasoned Action to explain consumer

behaviour in the use of Islamic banking in Jakarta. The study established that, pre-existing

attitude influenced purchase intention and, finally, the choice of using Islamic banking.

Implicitly, air passengers would initially choose only certain airline services based on the pre-

existing knowledge and the repeated service purchase behaviour would happen when the

expectations is met during the clients‘ first experience. Therefore, airlines should make sure

that first time fliers get good experience by providing quality service, charging a competitive

and fair price, ensuring punctuality and route availability for areas with a high demand.

Engel, Kollet, Blackwell (EKB) Model

SueLin and TAN (2010) developed EKB Model (which extends from the Theory of

Reasoned Action) to interpret how customers reach decisions when purchasing a service or

product. The model consists of five sequential steps for information processing before

reaching a consumption decision. First is need or problem recognition followed by a search

for alternative solutions which involves obtaining relevant information from internal and

external sources. Information is also obtainable from various advertisements exposed to

customers. The third stage involves the evaluation of alternatives that is subjected to the

consumer‘s personal criterion in deducing the preference. Then, the consumer moves into the

fourth stage where the buying of the selected alternative takes place. The final step involves

post-purchase evaluation.

Omari Mbura

125

This theory attest to how the relevant information companies expose customers when trying

to create image to the public through advertisement facilitate the making of comparison and,

ultimately, reach a decision. In this regard, provision of sufficient information through

different communication channels such as adverts and websites can simplify the airline

customer search process. In other words, this theory help to explain why provision of good

services can ensure customer satisfaction and positive post-purchase evaluation and, hence

give the airline firm a competitive edge.

Empirical studies

Several studies have been conducted on the airline industry. A Kaimkhani‘s (2012) study in

Pakistan found boarding and clearance time and ease of e-ticketing to have significant impact

on customer preference and positively lead to purchasing intention of the services the airline

companies in the market. Similarly, Buaphiban‘s (2015) study conducted in Thailand found

that subjective norms, perceived behavioural control, airline reputation, price, and service

quality had a positive impact on u intentions whereas behavioural intentions positively

influenced buying behaviour. Moreover, the Low-Cost Carrier (LCC) passengers were found

not only to be after low price, but more significantly factors such as service quality, airline

reputation, and social acceptability—subjective norms—played a significant role in the

choice of LCCs over Full Service Carriers (FSCs). Neverteless, Kamarulzaman, Ekiz, and Sai

(2011) in Malaysia came up with different findings for either FSCs or LCCs. The study found

safety and service quality to exert a significant positive effect on choice decision in Full

Service Airline whereas price, strategic alliance and loyalty programme exerted significant

positive effects on the choice decision for Low Cost Carriers.

OAG (2000), an air travel intelligence company based in the United Kingdom carried out a

survey on factors influencing passenger choices of airlines. The survey established that 3,000

business air travellers around the world (including the US, Europe, Singapore, and Australia)

singled out convenient schedules, reputation for safety, frequent flier programmes, on-board

comfort, leg-room and efficient check-in procedures as the highly featured factors when

business passengers chose an airline. Such travellers were not concerned about obtaining the

cheapest fare.

Fourie and Lubbe (2006) in South Africa focused on business air travellers and factors they

consider in selecting either full-service or low-cost carriers. Results indicate that, for both

business travellers using LCCs and those using FSCs, the three most important service factors

were seat comfort, the schedule/frequency of trips and the price of the air ticket, whilst in-

flight entertainment was regarded as the least important. Ukpere et al. (2012) study in

Nigeria found that gender, age, marital status, income, comfort, on-board services, frequency,

crew behaviour, ticket fare and power of monopoly were significant influencing variables. A

study by Onomo (2016) on factors behind airline customer loyalty in Kenya revealed that

perceived value, quality, customer satisfaction and corporate image impact on customer

loyalty. Similarly, Kising'u‘s (2010) study on the factors influencing the passengers‘ choice

of airline in Kenya airways found that social factors such as influence from friends or

celebrities, personal factors such as ticket fare and customer service, psychological factors

such as safety records do have a bearing on the choice of airline. On the other hand, cultural

factors such as attachment to a national flag carrier did not influence their choice. Study

conducted by Namukasa (2012) in Uganda examined the pre-flight (back office operations),

the in-flight and the post-flight service quality effect on passenger satisfaction. The study also

ascertained whether satisfaction affects passenger loyalty. The findings show that there was a

strong relationship between the proposed variables and customer satisfaction.

Omari Mbura

126

In Tanzania Naji‘s (2016) study found that, poor compensation, poor technical support, poor

direct communication, and poor complaint handling strongly affected customer satisfaction.

The implication of this study on the customer choice of airline is that, customers who go for

airlines with high ability of service recovery in case of emergency would become loyal to one

airline.

Research gap

Different literatures related to the study around the world and Tanzania in particular have

been presented. These other studies did not consider service quality, price, image and

scheduling-based factors constructs as influencing customers‘ choice of an airline, which is

the focus of the current study. Moreover, it is not logical to generalise the results from

studies conducted in different contexts to a particularised situation because different markets

have different needs, characteristics, policies and even challenges.

Conceptual framework for the study

The conceptual framework informing the study has four independent variables namely

service quality, price, image and schedule-based factors that presumably influence the choice

of an airline in the domestic market. The variables have been developed following an

extensive review of literature related to the study.

Figure 2: Conceptual Framework

Independent Variables Dependent variable

Hypotheses formulation

Delivering quality service is considered an essential strategy for success and survival in

today‘s competitive environment (Parasuraman et al., 1985, 1988; Zaithaml, 1996). Good

customer service at the airport and customer service by phone by cabin crew, IFE availability

(audio only, overhead TV etc.), seat comfort, how an emergency is handled, how customers

who miss a flight are treated and the ability of a customer to change reservation ideally have

H1: Service Quality IFE Seat comfort Customer service Emergence handling Ability to change reservation

Choice of Airline On Domestic Routes

H2: Price Fare Levels Fare Conditions Frequent Flier Price

H3: Image Promotion and advertisements Frequent Flier Programmes Branding

H4: Scheduled Based Factors Route Availability Punctuality Timing Frequency

Omari Mbura

127

direct influence on the customer selection process of an airline. As service quality affects the

customer decision, the first hypothesis to be tested which relates with service quality is thus

presented:

(a) H1: Quality of service offered has a significant influence on customer choice

of airline.

The most important considerations for a consumer in deciding on their purchases are their

overall income, which account for their budgetary constraints (Boundless, 2016). Price is an

important factor to consider, especially in a price-sensitive market such as Tanzania. In fact,

the pricing factor has become a dominant variable in a short-haul markets or routes. In

consequence, low cost airlines have had a major impact on this industry nowadays (Doganis,

2010). Thus, we come to our second hypothesis which states:

(b) H2: Price has significant influence on customers when choosing an airline.

Moreover, good advertising, whether online or offline, influences consumer purchases

(Mohapatra, 2016). Marketers are highly concerned about knowing how the brand names

influence the customer purchase decision (Alamgir, Nasir, Shamsuddoha and Nedelea, 2010).

FFPs have become an influential factor in airline choice, especially for business travellers and

leisure passengers. Its main goal is to sell more seats (Doganis, 2010). The third hypothesis is

thus deduced based on the positive impact of airline image:

(c) H3: Airline Company‘s image has significant influence on the customers‘

choice of an airline.

Schedule-based features consist of a number of frequencies of operation, the timing which

consist of departure and arrival times, points served or route availability. Different markets

have different scheduling requirements. Schedule-based features constitute core elements of

schedule airline product on short-haul routes and business travellers consider them to be the

most important (Doganis, 2010). As such, we hypothesise as thusly:

(d) H4: Schedule-based factors have significant influence on the customers‘

choice of airline.

METHODS

Research paradigm and design

The study has adopted a positivistic paradigm because it is quantitative in nature. It partially

adopts interpretivistic paradigm because qualitative data also serve to complement

quantitative data in the analysis. Our population of interest in this study is limited to all

domestic air travellers from three domestic operators in Tanzania, namely PrecisionAir,

FastJet and Air Tanzania Company Ltd. These are leading airline companies by market share

on domestic routes in Tanzania. Statistics shows that the Julius Nyerere International Airport

(JNIA) has had an average of 6,800 air travellers per day for four years back from 2013

(TAA, 2016).

Non probabilistic convenience sampling was employed to gather data from a sample of 120

passengers. Tabachnic and Fidel‘s (1996) rule of the thumb was used to determine the

sample. Accordingly, to select sample that enables the use of strong statistical analysis, the

sample size should be N>104+M where M is the number of independent variables and N is

the number of cases. For our case, we have 4 independent variables, hence making 180

passengers as the minimum sample that can be chosen using this approach. Generally, a large

Omari Mbura

128

sample increases statistical power (Hair, 2006); therefore, a sample of 120 was selected for

such a purpose.

Passengers were approached both at the waiting space at JNIA before entering for check-in

and at the JNIA sales offices while making ticket reservations. Self-administered structured

questionnaires were used to collect data from passengers in a 5-day period. Only domestic

passengers were selected from the entire population. This was achieved by the pre-screening

question in the questionnaires.

On the other hand, purposive sampling was employed to get 3 marketing managers of the

three largest airlines under research namely PrecisionAir, FastJet and Air Tanzania Company

Ltd who served as key informants. These provided in-depth information on the nature of the

study (Crossman, 2017). Purposive sampling helps to reach target sample quickly with the

assurance that the sample chosen shall respond and provide relevant information. This

method helped researcher to save time and money.

Reliability and Validity Tests

The Cronbach‘s alpha test was employed to measure the internal consistency (reliability) of

the study variables. All the variables met the minimum acceptable Cronbach‘s alpha of 0.70

(Tavakol and Dennick, 2011). For validity, the study focused on content validity, which is

particularly the most recommended (Taherdoos, 2016). In this regard, exhaustive literature

reviews to extract the related items was done followed by pre-testing of the questionnaires

with 5 passengers not included in the final sample. The pre-testing helped to identify a few

unclear questions, which were corrected accordingly before the instrument was rechecked by

two experts prior to final application in the field (ibid.)

FINDINGS AND ANALYSIS

This study examined the attributes influencing the choice of airline among domestic travellers

in Tanzania. The following are the mean, standard deviations and inferential statistics and

discussion of the study:

Mean and Standard Deviations of the Study Variables

The mean and standard deviations were computed for all the study variables. The results are

as summarised in Table 3.

Table 3: Mean and Standard Deviations of the Study Variables

N Mean Std. Deviation

Service Quality 120 2.8403 .7150

Price 120 4.2146 .68622

Airline Image Attributes 120 3.7167 .85847

Schedule-based Factors 120 4.2958 .65704

The results in Table 3 show that all the study variables but for service quality had high mean

scores (4.21 for price, 3.72 for airline image, and 4.30 for schedule-based factors). This

means price, airline image and schedule-based factors have a significant influence on the

choice of airline on the domestic routes. The schedule-based factor is the most influencing

factor followed by pricing as their highest mean indicate. However, the mean of service

quality was 2.84, which is less than the neutral score (that is 3) hence indicating that service

Omari Mbura

129

quality had no significant bearing on the choice of airline on domestic routes. On the other

hand, the standard deviations for all the variables are moderately small (less than 3), which

signals that there was minimum dispersion of opinions among the respondents (Mbura, 2007)

Results on Inferential Statistics

Under this section, the paper presents the results stemming from the correlation and

regression analyses as per research objectives. These analyses were preceded by a test on the

model fitness.

Model Fitness

The fitness of the model was assessed using the R square and F statistics as indicated in table

4.

Table 4: Model Summary

Model R R Square

Adjusted R

Square

Std. Error of

the Estimate F sig

1 .879 .773 .765 .27442 97.882 .000

Dependent Variable: Choice of Airline on Domestic Routes

Predictors: (Constant), Schedule Based Factors, Service Quality, Airline

Image Attributes, Price

The results in Table 4 show that the overall model was good and statistically significant at

5% level of significance. The coefficient of determination was high (R 2 =0.773), implying that

77.3% of the variation in choice of airline on domestic routes as the explanatory variables

(Price, Airline image, service quality and Schedule-based factors) affirm. The remaining

22.7% is explained by other variables not included in this study.

Correlation Analysis

Running the correlations for the pairs of independent variables was useful in checking for

multicollinearity among the independent variables. The findings on correlation analysis are

presented in Table 5.

Table 5: Correlation Matrix for Study Variables

Choice of Airline

on Domestic Routes

Service

Quality

Price Airline Image

Attributes

Schedule Based

Factors

Choice of

Airline on

Domestic

Routes

Pearson

Correlation

1 .135 .405 *

*

.639 **

.552 **

Sig. .234 .000 .000 .000

Service

Quality

Pearson

Correlation

.135 1 .015 .033 .106

Sig .234 .875 .813 .124

Price Pearson

Correlation

.405 **

.015 1 .103 .280 **

Sig. .000 .875 .263 .002

Omari Mbura

130

Airline

Image

Attributes

Pearson

Correlation

.639 **

.033 .103 1 .255 **

Sig. .000 .813 .263 .005

Schedule

Based

Factors

Pearson

Correlation

.552 **

.106 .280 *

*

.255 **

1

Sig. .000 .124 .002 .005

**. Correlation is significant at the 0.05 level

The results in Table 5 show that all the independent variables except service quality at least

moderately correlated with each other. In particular, Price and Airline Image had strong

correlations with Scheduled-based factors (r=.208 and r=.255, respectively). These results

show that there was multicolinearity problem to be solved through multiple linear regression

analysis which provides the Variance Inflation Factor (VIF).

Multiple Linear Regression Analysis

Multiple linear regression analysis was performed to identify the statistically significant

variables in explaining the choice of an airline on domestic routes. The results are presented

in Table 6:

Table 6: Results of Multiple Linear Regressions

Model

Unstandardised

Coefficients

Standardised

Coefficients t Sig. VIF

B Std.

Error Beta

1

(Constant) 1.470 .471

3.119 .002

Service quality -.094 .075 -.092 -1.245 .216 1.034

Price .324 .065 .329 4.985 .000 1.088

Airline Image

Attributes .200 .073 .209 2.729 .007 1.072

Schedule-based

Factors .523 .072 .557 7.282 .000 1.188

a. Dependent Variable: Choice of Airline on Domestic Routes

The findings in Table 6 show that all the factors have VIF value of less than 5. This implies

that the multicollinearity problem has been sorted out by linear regression analysis.

Moreover, airline image, price and schedule-based factors were statistically significant in

inducing the choice of airline on domestic routes as indicated by their respective significance

values which were less than 0.05 (0.000, 0.007 and 0.000 for price, airline image and

scheduled based factors, respectively). Service quality had no significant influence on the

choice of airline on domestic routes because its significance value is 0.216, which is greater

than 0.05. Furthermore, price, airline image and schedule-based factors had a positive effect

on the choice of airline on domestic routes as indicated by their coefficients which are all

positive (0.324, 0.200, and 0.523 for price, airline image and scheduled-based factors

respectively). Thus, the results of multiple regressions analysis indicate that the clients‘

Omari Mbura

131

choices of airline on domestic routes are influenced by the price, airline image and schedule-

based factors.

DISCUSSION OF FINDINGS

Service Quality and Choice of Airline

The study results presented in table 5 reveal that there is no significant relationship between

service quality and choice of airline on domestic route as the level of significance of 0.216 is

greater than 0.05 and the negative coefficient which is -0.092. This finding on service quality

attributes and airline choice is contrary to the finding by Namukasa (2013) in Uganda whose

study underscore the importance of service quality as manifested by customer satisfaction

with pre-flight, in-flight and post-flight services. In addition, Ukpere (2012) has reported that

customers will choose airlines with comfortable seats, good on-board services with good

customer service (crew behaviour). Furthermore, a study by Onomo (2016) in Kenya

revealed that perceived value, quality, customer satisfaction and corporate image have a

positive impact on customer loyalty. All these studies were done by people outside Tanzania.

This implies that service quality attributes (seat comfort, in-flight entertainment, customer

service) considered in this study do not seem to be of much concern in the Tanzania local air

market.

Due to competitive pressure, airlines offer in-flight entertainment to match with what their

competitors are doing (Doganis, 2010). However, surveys repeatedly show that in-flight

entertainment is way down on the list of factors that influence the customer choice of an

airline. After all, most of the domestic routes are short-haul and, therefore, customers do not

spend more time travelling. The Tanzania market, in this regard, seems to be more

preoccupied with price, airline schedules and airline image. Therefore, marketing managers

in Tanzania should focus more on these attributes to attract more airline passengers. One

airline company marketing manager acknowledged the importance of quality service along

with other proven influencing factors thusly:

The majority of air travellers are sensitive to time. Our good airline

schedules avail business travellers and other time-sensitive travellers to

prefer our airlines. Moreover, we rely on making sure that our customers

get better services as we know that they can be a source of creating good

public image, which eventually influences customer choices. Things such

as seat comfort, IFE are minor issues in short-haul routes; however, the

seat should fairly and considerably be comfortable.

Price and the choice of Airline

The assessment of the influence of price on the choice of airline, whose results have been

presented in table 6, reveals that price has a significant value of 0.000 which is less than

0.005 and a positive standardised coefficient of 0.329.This suggests that price has a positive

significant influence on the choice of an airline. This result is consistent with the finding from

the study conducted by Kamarulzaman et al (2011) which also found price to be the main

determinant factor of the clients‘ choice of an airline in a highly price-sensitive domestic

market. The price attributes deployed in that study include variation of levels of price,

discounted frequent flier price, and fairly tickets fare conditions. Similarly, Buaphiban (2015)

and Kaimkhan (2012) found that the price to influence customer choice of an airline. This

implies that the price should be competitive and attractive enough to lure other potential

travellers to use air transport. In this regard, one of the airline company marketing managers

argued against over-reliance on price to attract and retain customers:

Omari Mbura

132

Price should be looked at carefully considering that the majority of the

customers are budget conscious who seek lower prices. This can

evidently be justified by the big shift of customers in case of small change

in price.

Image and the choice of Airline

As table 6 illustrates, there exists significant relationship between airline company image and

choice of an airline. Corollary to these findings, Onomo (2016) found that image influences

customer choice. Doganis (2009), on the other hand, argues that creating image through

promotion, branding and frequent flier programme are important techniques airlines should

use to influence customer choice. An airline‘s image manifested attributes such as the

popularity of brand, frequent flier loyalty programmes, and promotion and advertisement.

This finding concurs with those by Khraim (2013) who studied the airline image and service

quality effects on travelling customers‘ behavioural intentions in Jordan. The main results of

his study revealed that a significant effect of airline image was observed on customers‘

behavioural intentions at the level of (α ≤ 0.05) as well as a significant effect of service

quality on customers‘ behavioural intentions at the level of (α ≤ 0.05). Kotler and Armstrong

(2010) concur that a good company image creates a long-term sustainability of the product..

Overall, image-related attributes manifested in terms of frequency of operations, route

availability to a destination, punctuality of the airline in terms of arrival and departure time

and proper programming of the airline schedule. A marketing manager from one airline

Company augmented the findings by indicating how newness of Aircraft creates positive

image in the thoughts of the customer:

An airline company should make sure that they create a good image in

the eyes of the public as this variable plays a significant role in

influencing airline choice. New product can sometimes create an image

and influence customer choice. The coming of Bombardier, a popular

brand of aircraft manufacturer, for example has drawn the attention of

many Tanzanians who now seem to show interest in travelling aboard

these Bombardiers.

Schedule-based factors and the choice of Airline

The significant relationship between schedule-based factors and choice of airline vividly

emerged in table 6. This finding is in line with a survey conducted by SAS (1980), which

found that the majority of the respondents indicated that arrival and departure times are

significant factors when choosing an airline. A study conducted by American air travel

intelligence company OAG (2000) came up with similar results. Moreover, Foure and Lube

(2006) insist on the contribution of schedule-based factors such as frequency on airline

selection. In fact, Brueckner and Flores-Fillol (2006) contend that convenient airline

schedules are of paramount concern to air passengers. Attributes that were used for

determining schedule-based factors include an airline having at least two (morning and

evening flights) frequency of operation per day, which is good for business competition on

the domestic market, route availability to a destination, punctuality of the airline and a well-

programmed airline schedules. In this regard, a marketing manager from one airline

Company augmented the findings by saying:

Most of the air passengers are sophisticated. They demand too much on

time performance. Delays, cancellations of flight and inconsistent

Omari Mbura

133

departure times are the issues that customers cannot tolerate, especially

business and customers travelling for official purposes.

CONCLUSION, IMPLICATION AND RECOMMENDATION

The regression analysis has generally shown that all the factors except service quality

attributes have a significant influence on customer choice of airline. The following provides

the implication and recommendation:

Most of the air passengers in Tanzania are people who are time sensitive. Airline companies

should, thus, guaranteed timely and on-schedule flight services. Tanzanian airline companies

should also prioritise on route diversification to make sure that different destinations are

reachable by flights. The current 29 airports in Tanzania need to be enhanced to allow

accessibility by different models of aircraft.

Despite the presence of legacy and hybrid model of airline operations, managers from

different airline companies in Tanzania should set fares with a customer-oriented mindset to

make air transport affordable to the majority of middle-income groups. This may suggest the

introduction of more LCCs and few hybrid and legacy airlines to accommodate corporate

customers and a few high-end users.

As the study findings show that airline company image plays a significant role in the

selection of airline, airlines in Tanzania should to create and enhance a good image in the

minds of the consumer. Doing so could significantly influence the customers‘ airline choices.

REFERENCES

Air Tanzania History (2016). Retrieved from airtanzania:

http://www.airtanzania.co.tz/pages/air-tanzania-history?mid=172

Alamgir, M., Nasir, T., Shamsuddoha, M., & Nedelea, A. (2010). Influence of name on

consumer decision-making process.

Becker, K. (2014). 10 Reasons why flying is still the best way to travel. Retrieved on Sept 07,

2017, from https://www.flightnetwork.com/blog/10-reasons-flying-still-best-way-

travel/

Boundless. (2016). Impact of income on consumer choices. Retrieved June 13, 2017, from

boundless:https://www.boundless.com/economics/textbooks/boundless-economics-

textbook/consumer-choice-and-utility-5/theory-of-consumer-choice-53/impact-of-

income-on-consumer-choices-204-12331/

Bowman, C. and Faulkner, D. (2012). How Does Strategic Choice Affect Business Results?,

53.

Bowman, C., and Faulkner, D. (1997). Competitive and corporate strategy. London: Irwin

Buaphiban, T. (2015). Determination of factors that influence passengers‘ airline selection:

A study of low cost in Thailand. Florida, Thailand.

Cederholm, T. (2014). Low-entry barriers intensify competition in airline industry. Retrieved

July 10, 2017, from marketrealist: http://marketrealist.com/2014/12/low-entry-

barriers-intensify-competition-airline-industry/

Crossman, A. (2017). A review of software tools for quantitative data analysis. Retrieved

July 20, 2017, from thoughtco: https://www.thoughtco.com/quantitative-

analysis-software-review-3026539

Crossman, A. (2017). Understanding purposive sampling. Retrieved July 20, 2017, from

thoughtco: https://www.thoughtco.com/purposive-sampling-3026727

Dhanalakshmi, U., Rajini, R., & Kanimozhi, S. (2010). Developing service quality using gap

model: A critical study. Journal of Business and Management, 48-49. Retrieved

Omari Mbura

134

July 30, 2017, from http://www.iosrjournals.org/iosr- jbm/papers/ncibppte-

volume-1/1027.pdf

Doganis, R. (2010). Flying of course. In: R. Doganis (ed), Flying Of Course. New York:

Routledge.

Geraldine, O. and David, C. (2013). Effects of airline service quality on airline image and

passengers‘ loyalty: Findings from Arik Air Nigeria passengers. Journal of

Hospitality and Management Tourism, 4(2), 19-28. doi:DOI:

10.5897/JHMT2013.0089

Gervet, C. (1991). Large Scale Combinatorial Optimization A Methodological

Viewpoint. Retrieved Sep 09, 2017, from

http://eclipseclp.org/reports/chic2_meth_carmen.pdf

Gillilland W. (1971) Role of the civil aeronautics board in the development of the domestic

air carrier route system, 47Notre Dame L.Rev.32 (1971)

Fraissard M. P (2004) Presentation to the MIT Department of Aeronautics and Astronautics,

The World Bank

Fernandez, T. (2017) Low-cost airlines have democratized travel. It’s time airports did

their part. Retrieved June 13, 2017, from World Economic Forum:

https://www.weforum.org/agenda/2017/04/low-cost-airlines-have-democratized-

travel-it-s-time-airports-did-their-part/

Fishbein, M., Ajzen, I., Morris, J., Marzano, M., Dandy, N., O‘Brien, L. & Ajzen, F. (1967).

Theories and models of behaviour.

Hameed, M. (2011). Low cost airlines: A brief history, the current state and the future.

Retrieved from aviationKnowledge:

http://aviationknowledge.wikidot.com/aviation:low-cost-airlines:a-brief-history-the-

current-state

Harris, A. (2010). The history of airline industry. Retrieved June 9, 2017, from USA

Khraim, H, S. (2013), Airline image and service quality effects on travelling customers‘

behavioural intentions in Jordan. European Journal of Business and Management, 5

(22)

IATA. (2016). Demand for air travel in 2015 surges to strongest result in five years,

Press Release No.: 4. (A. De Juniac, Editor) Retrieved from http://www.iata.org:

http://www.iata.org/pressroom/pr/Pages/2016-02-04-01.aspx

IATA (2017) IATA Annua review 2017. Retrievable on on 4 th

February 2014 from

https://www.iata.org/publications/Documents/iata-annual-review-2017.pdf

Isoraite, M ―Marketing Mix theoretical aspects‖ International Journal of Research –

Granthaalayah, Vol. 4, No. 6(2016): 25-37.

Jacobs, T. L., Garrow, L. A., Lohatepanont, M., Frank, K. S., Coldren, G. M., &Purnomo, H.

(2012). Airline planning and schedule development. In: Barnhart, Cynthia, Smith,

Barry, Barnhart, Cynthia, Smith, & Barry (Eds.), Quantitative Problem Solving

Methods in the Airline Industry (pp. 36-37). Retrieved Sep 09, 2017, from

www.springer.com/cda/content/document/cda.../9781461416074c2.pdf?SGWID

Kaimkhani, S. (2012). Factors affecting consumer preferences in airline industry. Far East

Journal of Psychology and Business, 7, 63.

Kamarulzaman, Y., Ekiz, E. H., & Sai, B. T. (2011). Factors determining the choice of full

service airlines. Hong Kong, Malaysia.

Kising'u, B. M. (2010). An investigation of the factors influencing passenger choice of

airline in Kenya. Kenya.

Kotler, P. and Amstrong G. (2012). Principles of marketing. Pearson Education ltd, England.

Kotler, P., & Armystrong, G. (2010). Principles of marketing (3rd ed.). Pearson Education.

Omari Mbura

135

Retrieved from

https://www.theseus.fi/bitstream/handle/10024/80777/Frolova_Svetlana.pdf

Laurel. (2015). Top-reasons-for-flying. Retrieved sept 07, 2017, from airlinetravelguide:

http://www.airlinetravelersguide.com/Top-Reasons-for- Flying.html

Ismael, Z. (2015). ‗SAA to get R6.5bn bailout‘. iafrica.com.

Malik, M. A. (2016). What is the airline industry's market structure like? Retrieved June 13,

2017, from Quora: https://www.quora.com/What-is-the-airline-industrys-market-

structure-like

Maslen, R. (2013). Fastjet prepares for international launch from Tanzania. Retrieved

Sep 07, 2017, from http://www.routesonline.com/news/29/breaking-

news/204068/fastjet- prepares-for-international-launch-from-tanzania/

Mbura, O. K. (2007). The role of entrepreneurail network in the acquisition of

marketing information resources. In: O. K. Mbura. University of Dar es Salaam.

Mbura, O.K. (2017) Introduction to business. A Tanzanian Context. DD Group of

Companies, Dar es Salaam, Tanzania.

Mohapatra, P. (2016). Does advertising influence our choices as consumers? If yes, what

effect does it have on our lifestyle? Retrieved June 12, 2017, from

Quora:https://www.quora.com/Does-advertising-influence-our-choices-as-consumers-

If-yes-what-effect-does-it-have-on-our-lifestyle

Mondliwa, P. (2015). Muted battle for the region‘s skies: competition in the airline industry.

Quarterly Review. Available from:

http://www.competition.org.za/review/2015/5/25/muted-

battle-for-the-regions-skies-competition-in-the-airline-industry. [Accessed February

4th 2019].

Naji, L. S. (2016). Investigating the effect of service recovery strategied on customer's

satisfaction. MBA Dissertation, University of Dar es Salaam, Marketing: Dar es

Salaam.

Namukasa, J. (2013).The influence of airline service quality on passenger satisfaction and

loyalty: The case of Uganda airline industry. The TQM Journal, 25 (5), 520-532.

Emerald Group Publishing Company.

NewMyer D. A (1990). The impact of deregulation on airports: An international perspective.

Journal of Aviation /Aerospace Education & Research, 1(1), Art. 11

Onomo, O. S. (2016). Factors contributing towards airline customer loyalty in Kenya. United

States International University-Africa, Kenya. Retrieved from

http://erepo.usiu.ac.ke/bitstream/handle/11732/2590/Factors%20Contributing%20To

wards%20Airline%20Customer%20Loyalty%20in%20Kenya%20A%20Case%20Stu

dy%20Of%20Kenya%20Airways%20%28Kq%29.pdf?sequence=1&isAllowed=y

Precision Air History. (1994). Retrieved from precisionairtz:

https://www.precisionairtz.com/about-us/history

Psucd8. (2011). What is validity and why is it important in research. Retrieved July 02, 2017,

from psucd8.wordpress: https://psucd8.wordpress.com/2011/11/20/why-is-validity-

important-in-research/

Ramseook-Munhurrun, P., Lukea-Bhiwajee, S. D., & Naidoo, P. (2010). Service Quality in

The Public Service. International Journal of Management and Marketing Research,

3(1), 37. Retrieved from

http://observgo.uquebec.ca/observgo/fichiers/95792_PSP%201.pdf

SueLin, C., & TAN. (2010). Understanding of consumer purchase behavoir in the Japanese

personal grooming sector, 2911.

TAA. (2017). Traffic statistics up to 2016. Retrieved from http://www.taa.go.tz:

http://www.taa.go.tz/index.php/download/statisticts/23-traffic-statistics-up-to-2016

Omari Mbura

136

Tanzania Invests. (2016). Tanzania among top 10 African air travel destinations in 2016.

Retrieved July 27, 2017, from tanzania invest:

http://www.tanzaniainvest.com/transport/air-travel-2016

Timanywa M. (2017) Assessment of factors influencing passengers‘ choice of low cost

carrier, a case of fastjet in Tanzania. A PhD submitted in partial fulfillment of the

requirements for the degree of master of arts in monitoring and evaluation of the Open

University of Tanzania

Taherdoost, H.(2016) Validity and Reliability of the Research Instrument; How to Test the

Validation of a Questionnaire/Survey in a Research. Vol. 5, No. 3, 2016, Page: 28-36,

ISSN: 2296-1747

Tavakol M. and Dennick, R (2011) Making sense of Cronbach‘s alpha. International Journal

of Medical Education, 2, 53-5.

Ukpere, W. I., Stephens, M. S., Ikeogu, C. C., Ibe, C. C., Akpan, E. O., & Ibe, C. (2012).

Determinants of airline choice-making: The Nigerian perspective. African Journal of

Business Management, 6, 5442-5455.

USA Today: http://traveltips.usatoday.com/history-airline-industry-100074.html The History

of airline Industry. Retrieved on 3 rd

February 2019

Winsen, S. (2016). New airline entrants struggle to combat market distrust. Available from:

http://www.tourismupdate.co.za/article/117041/moving-conflict-over-UBC-into-the-

Courts. [Accessed 4 th

February 2019].

Www.ippmedia.com The Guardian (8 January 2018) Accessed on 20 th

January 2018

Wyse, S. E. (2012). 4 main benefits of survey research. Retrieved July 20, 2017, from

snapsurveys: https://www.snapsurveys.com/blog/4-main-benefits-survey-research

Copyright of Business Management Review (BMR) is the property of University of Dar es Salaam, Business School and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use.