Aviation Market Analysis: Forecasting Techniques for Passenger Demand

This essay critically discusses the merits of three forecasting techniques used in global aviation to predict passenger demand within a dynamic and turbulent environment. It highlights the importance of passenger demand factors, such as inflight services and customer service, and how they influence demand. The essay also explores how past events, like the COVID-19 pandemic, have impacted airline business and the shift towards online booking. Furthermore, it details various forecasting techniques, including qualitative forecasting, quantitative forecasting, time series analysis, and econometric methods, evaluating their effectiveness in predicting passenger demand and addressing uncertainties in the aviation industry. The essay references Arena Aviation Capital as an example, emphasizing the importance of adapting to changing environments and implementing strategies like digital marketing to enhance business growth. Desklib offers a range of study tools and resources for students.

Aviation Forecast

Table of Contents
INTRODUCTION...........................................................................................................................3
Importance of the different passenger demand factor within global aviation as how they have
influenced demand in future as well as past...........................................................................3
Illustrate about three forecasting techniques used global aviation to predict passenger demand
across through global regions. ..............................................................................................5
CONCLUSION................................................................................................................................8
REFERENCE...................................................................................................................................9

INTRODUCTION
Aviation Management usually deals with study of better airlines, airports and business
which is related towards the aerospace industry. Aviation industry also use to forecast about its
resources and services. It also helps to make short term decisions such as making strategy how to
execute or control aviation and airline service during high weather condition. According to this
decision making its positive outcomes enhance for longer period of time. Further more, Aviation
makes work study which encourage to the candidates regarding with operate airline activities. It
also provides better scope and other related work which generate outcomes effectively. In this
report, the information is related with Aviation base for make more elaborate to consider
company Arena Aviation. This company is determines on the complete life cycle of acquiring
and leasing commercial aviation assets. Further in following report, topics are concentrate on
Aviation industry forecast, in which it use to both enable short term decision such as weather to
expect adverse weather condition. To elaborate about importance of passenger factors to better
create global aviation and how it influence demand in future, given dynamic and turbulent
environment that the aviation through industry faces. Highlight about three forecasting
techniques which is used in global aviation to better predict passenger (Goswami and et.al,
2020). There is consider Arena Aviation Capital company as example which is UK based
company effectively.
Importance of the different passenger demand factor within global aviation as how they have
influenced demand in future as well as past.
Aviation provides the only rapid worldwide transportation network that makes it
necessarily towards for global business. It generates economic growth, creates job and facilities
international trade and tourism. Airlines or Aviation passenger are similar and they have ability
to generate a good relationship with them for long term period. To maintain the relationship with
them Aviation team enhance to provide better airlines services that makes the passenger travel
experience more satisfactory. They enhance to provide more food services as passenger brings
their own food or somehow not due to aviation rules and regulations. Further more, for passenger
perspective they have make their contribution towards better economic development. It has not
only increased where world trade activity by enabling faster and easier movement for passenger
and goods. Apart from it, they generate high rate of employability for millions of people and also
make sure about resources that plays an important role in aviation for longer period of time

(McKeown, 2021). The importance of Aviation which consider by passenger demand are
Inflight Services: It turns out about to willing to pay more for flight fares on which passenger
expects some extra or can say complimentary services. They provide more food services as
passenger brings their own food or somehow not due to aviation rules and regulations. However,
as food is also limited due to lack of cooking facilities on aviation. There are some of other
services are indulged like entertainment which is also key prevails better travel experiences. The
value of passengers are entertainment system as key a good level of experiences and also willing
to pay with for extra hospitality services which can get the customer effectively. Customer
service and reputation: It is not just food and films that turn passenger’s heads and open their
wallets. . The competency of Airlines as well as Aviation they use to generate long term loyalty
and relationship through delivering a smooth and professional services. For example: Arena
aviation company use to take care about their major resources which is needful to generate for
passenger at the time of providing services like complementary food and beverages and others.
By considering future demand of passenger in aviation and airline services aspects that if
customer is reliable to pay more or they have high purchasing power so they can easily approach
air travel services. The Aviation service influence of demand about airline travel within the past
and how they could influence demand in future.
. In previously, many peoples were only travel through bus transportation or trains which takes
more time consumingBut as of now, trends has been changes air travel enters and generate
flexible level of services where now people can travel national and international in less consume
time (Badulescu, Hameri and Cheikhrouhou, 2021). Through technology and resources raise
their benchmark it also increase prices of Air travel where now people who having buying power
can easily afford it. In recent example, in Covid situation arise where airline business get drastic
impact, previously people use to book their tickets through offline. Now the trend changes where
people can easily book their ticket through online and other Airline online websites. By this
felxibile online air ticket more flexibilie for customers which is why it increase the demand of
booking tickets . But due to having Pandemic situation it creates drastic change as passengers
are not able to travel where it generate effective way of travel services to attain properly services
attained.

The dynamic strategy implies to understand about of bringing new business style which
can boost the growth of company. Through implementation of the dynamic strategy in aviation
or airlines business is to make change in service practises just like in Covid situation when
people are faces high level challenges in regarding with economic crises which impact on airline
business. The turbulent environment exists when changes are unexpected and unpredictable.
. e. As the main key environment issues can raise pressure for changes and the speed through
which it organisation which must be able to respond on act. In atmospheric turbulence which is
having major hazardous in the aviation and cause injuries to passenger crew through better
understanding that airlines business need to make sure about security resources like first aid kit
etc. Some of strategy and change that determine through the impact of changes which aviation or
airline business has been made. Due to not having proper resources in any drastic environment
crises then it would create more complexity for passenger at the time of travelling. For example:
The company Arena Aviation (https://www.arena-aviationcapital.com/) they enhance their health
care kit resources where passenger safety can make concerned by their arena team along with
that proper sanitised of proper airline infrastructure where passenger can feel safe. Mentoring
programs are regarded as structure one to on relationship among organisation. It is a well
functioning program that is required for strategic planning & organisation for connecting people,
enhancing knowledge and further setting of goals (Le Bris, Nguyen and Tagoe, 2020). In
present report there is design of a mentoring programs by application. Further more, Aviation
business can approach new plan for their business of airline service that would generate better
business outcomes. Such as, Digital marketing is a marketing tool that is based on marketers
with constant innovative ideas for enhance of present market share. Paid digital marketing
strategy is a broad term that is related with digital advertising and pay for every user click.
Another is paid search adverting that is that is google, Bing and yahoo that is allowing business
organisations to target their potential customers who are actively searching for a product or
services.. Aviation business can approach for Digital marketing practise which is related with
opportunities where individual organisation can work towards digital impact on business It can
help to boost the airline business which would get to attained more opportunities like new
customer In perspective of Arena Aviation their marketing team uses digital marketing practises
for promote and create awareness within public for airline quality service and job opportunities
through online.

Illustrate about three forecasting techniques used global aviation to predict passenger demand
across through global regions.
Forecasting is form of technique that uses historical data to inputs to make informed
estimates that are predictive in determining the direction regarding with future trends. As any for
of business utilise forecasting process to determine how to allocate their budgets or plan for
better anticipated expenses for an upcoming period of time (Butyrkin and et.al, 2020). .
There are different techniques which are explained in context of Aviation company are: -
1) Straight line method: It is one of the simplest and easy to follow forecasting method, as
financial analysts use historical figure trends that helps to predict future revenue growth.
2) Qualitative Model: The forecasting model which is used when they are trying for predict
business important prediction over short term period of time. The business experts are consultant
and their opinion form which is crucial inputs in coming up within forecasting sales or values.
3) Quantitative model with having human components which involved in forecasting that can
potentially add human basis or errors in process, the quantitative method solely relies on
historical data and understand about pattern to know future. According to this model when it is
dearth of historical data and there that needed to forecasting no only for the short term but
medium or even long term (Abd-Elmajed, 2020).
4) Time Series: The data is focuses on the pattern found in historical data and uses statistical
method to better understand how time effects the target variable. Therefore, the concept such as
analytics of seasonality, trend, cyclicity which scrutinise historical base data in future better
manner. According to this method emphasis about how to use statistics and better method.
5) Econometric method: According time series analysis which is used of discipline of statistics,
by using of this method assorted mathematically exhaustive techniques through business
forecasting. While analysing of time series analysis is used for more general business
environment where the it also used for analyse the economic policies.
There are three major forecasting which would used to mapping better aviation business
growth within effective manner that get to attained more growth such as:
Three Techniques of Forecasting
in Aviation
Merit about techniques
Qualitative forecasting This technique used in Aviation for mapping future
prediction which uses expert judgement instead of

numerical analysis. To implementation of this technique
would help to predict about uncertainty factor in any
situation. It helps to overcome from problem like hiring
of extra staff, facing crises as financial and weather.
These one which apply knowledge of business, market
product base consumer which make judgement call or to
make long term forecast. Some of the advantages of
Qualitative forecasting in Aviation business which is
having ability of predict changes in sales pattern. For
predict better customer behaviour that based on their
effective travel experiences . Management of Aviation
can use of techniques and also use of past researcher
record (Camitz and Johansen, 2021). The flexibility
forecasting of management the flexibility which is
necessary to use of non numerical data such as intuition
and judgement of better experienced manager, sales
professionals and industry experts. From this practise, It
will improve the quality of forecast because of
quantitative data can not capture defect or issues. By
using of modern technology can help to predict more
defective factors. A It also implies new software
application will not have histrocial data which is having
better kind of predict future sales (Huiting and et.al,
2020). As in perspective of Aviation company which
may have the resources to conduct focus group and field
test design of airlines planes. This forecasting can help to
boost customer demand by providing proper authentic
data related with Aviation or airline services. The data
could be related to airline travelling status where
customer or passenger can easily track and book tickets.
Quantitative forecasting According to this forecasting technique in aviation

business for generating more flexibility and appear in
more better aspect. The main advantages of utilising
quantitative techniques which is based on availability for
hard and complex data. It ensures forecasting which
prevails results are as objectives as possible, as having
importance is placed or numerical information and better
quantify past performance rather than opinions better
industry experts or customer. Through the staffs of
aviation can also contribute their efficiency which would
generate more positive outcomes. The benefit of using
this technique is for making better business in aviation by
mapping past data in perspective of sales and demand of
product and services get to better engaged effectively
(Moon and Kim, 2020). Aviation business can easily
make their data influence through better modern forecast
which can easily simplify about modern forecast to
complete analysis and historical data. For automating
quantitative techniques in business forecasting will
ensure maximum flexibility, accessibility and complete
level of accuracy as each complex level of forecasting
technology for long term reliability. On the basis of
Quantitative technique applies in Aviation business to
make sure the services can creates flexible as well as
customer get essential resources like quality of food and
beverages, security essentials, health kits etc. For
example in recent situation of COVID-19 all aviation and
airline services implies changes in their service polices as
well as sanitizing their air base systems. All these
practises are counted as Quantitative forecasting that
enhance customer satisfaction along with their demand.
Time Series This is structure of techniques that enhance for major

prediction of events through a sequence of time. It is
majorly predict future events through analysing for
trending past and assumption which would similar
through better historical data. There are certain
advantages of time series which would help to Aviation
business provide flexible growth effectively. The
advantages of better time series analysis for identify
patterns where memories went fragile and most effective
cases through form of time series analysis which is
having simple base plot of bar line chart which represent
about simple prediction of situation with no longer of
doubts. Another benefit of time related series analysis
creates the better opportunity to clean up data. Similarly
aviation business will also get used to this time series
techniques which help to predict uncertainty which
identified gaps in the data for fill up missing value
effective (Leiming, 2020). The another benefit of Time
series is to future forecasting which help to predict the
future useful of glimpse of better forecasting comes
down to looking at past behaviour and seeking of pattern
into future (Acharya and Bhattarai, 2021). This
forecasting technique would help to connect passenger
demand by providing them proper arrival and departure
schedule of airlines. To generate more relevant
information updates by airline services to customer
regarding with policies, price and offers as per specific
time accordingly.

CONCLUSION
From above report of Aviation Forecast is summarised about define different passenger
which is having better demand factor in global aviation. It discussed about how aviation and
airline services execute or control. It also analysed that technology plays an important role in
Aviation business by help to manage resources effectively. There are some of factor which
determined on environmental which helps to predict hazardous situation. For explained the
situation of COVID-19 on which airlines faces issues of decreasing profit in competitive market.
In detail analysation of three forecast technique like Qualitative, Quantitative and Time series to
implement aviation business growth within better manner. All these main techniques described
in role of aviation business more productive manner. Each technique comprise how their
forecasting influence make aviation services generate quality like provide proper time track of
airlien schedule, food and beverages along with health base resources to provide satisfaction to
customer.

REFERENCE
Books & Journal
Abd-Elmajed, A.S., 2020. A Microcontrooller-Based Weather Prediction System using the
Sliding Window Algorithm (Doctoral dissertation, Sudan University of Science and
Technology).
Acharya, R. and Bhattarai, N., 2021. Analysis of Greenhouse Gas Emission From Aircrafts and
Ground Service Equipment at Tribhuvan International Airport of Nepal. Journal of
Advanced College of Engineering and Management, 6, pp.111-122.
Badulescu, Y., Hameri, A.P. and Cheikhrouhou, N., 2021. Evaluating demand forecasting
models using multi-criteria decision-making approach. Journal of advances in
management research.
Butyrkin, A.Y., and et.al, 2020, September. Models for predicting passenger traffic in rail and air
transport. In IOP Conference Series: Materials Science and Engineering (Vol. 918, No.
1, p. 012057). IOP Publishing.
Camitz, A. and Johansen, M., 2021. Creating a Forecasting Model for a Volatile Environment.
Goswami, S., and et.al, 2020. Adaptive neuro‐fuzzy inference system to estimate the
predictability of visibility during fog over Delhi, India. Meteorological Applications,
27(2), p.e1900.
Hanuliaková, R. and Jarošová, M., 2021. Meteorological radiolocator as a tool to improve
meteorological information for aviation.
Huiting, H.A.N., and et.al, 2020, December. Research on Forecast of Passenger Flow of High
Speed Railway in Competitive Market Based on XGBoost Model. In 2020 13th
International Symposium on Computational Intelligence and Design (ISCID) (pp. 110-
113). IEEE.
Langford, J.S., 2020. Electrified aircraft propulsion. The Bridge, 50(2).
Le Bris, G., Nguyen, L.G. and Tagoe, B., 2020. The Future of Airports: A Vision of 2040 and
2070: Topic No. 11: Human Resources and Education.
Leiming, M., 2020. Development of Artificial Intelligence Technology in Weather Forecast.
Advances in Earth Science, 35(6), pp.551-560.
McKeown, P., 2021, April. Industrial and aviation contamination–Looking upstream to prevent
PFAS from impacting municipal wastewater. In 2021 Emerging Contaminants in the
Environment Conference (ECEC21).
Moon, S.H. and Kim, Y.H., 2020. Forecasting lightning around the Korean Peninsula by
postprocessing ECMWF data using SVMs and undersampling. Atmospheric Research,
243, p.105026.
Morozova, N.S. and Andreeva, E.G., 2020. Improving the accuracy the forecasting volumes of
electric grid construction in energy systems based on economic and statistical dynamic
models. In Journal of Physics: Conference Series (Vol. 1441, No. 1, p. 012024). IOP
Publishing.
Olaganathan, R., 2021. Impact of COVID-19 on airline industry and strategic plan for its
recovery with special reference to data analytics technology. Global Journal of
Engineering and Technology Advances, 7(1), p.33.

Riba, E.M., 2021. Exploring advanced forecasting methods with applications in aviation
(Doctoral dissertation).
Zheng, X., Liu, C.M. and Wei, P., 2020. Air transportation direct share analysis and forecast.
Journal of Advanced Transportation, 2020.
Gössling, S. and Humpe, A., 2020. The global scale, distribution and growth of aviation:
Implications for climate change. Global Environmental Change, 65, p.102194.
Hon, K.K., Ng, C.W. and Chan, P.W., 2020. Machine learning based multi-index prediction of
aviation turbulence over the Asia-Pacific. Machine Learning with Applications, 2,
p.100008.
Zhang, K., Jiang, Y., Liu, D. and Song, H., 2020, November. Spatio-Temporal Data Mining for
Aviation Delay Prediction. In 2020 IEEE 39th International Performance Computing
and Communications Conference (IPCCC) (pp. 1-7). IEEE.
Ershov, M.A., Klimov, N.A., Burov, N.O., Abdellatief, T.M. and Kapustin, V.M., 2021. Creation
a novel promising technique for producing an unleaded aviation gasoline 100UL. Fuel,
284, p.118928.
Varotsos, C., Krapivin, V., Mkrtchyan, F. and Zhou, X., 2021. On the effects of aviation on
carbon-methane cycles and climate change during the period 2015-2100. Atmospheric
Pollution Research, 12(1), pp.184-194.
Gao, Y., Hao, Y., Wang, S. and Wu, H., 2021. The dynamics between voluntary safety reporting
and commercial aviation accidents. Safety Science, 141, p.105351.
Andriyanov, N. and Andriyanov, D., 2021, May. Intelligent Processing of Voice Messages in
Civil Aviation: Message Recognition and the Emotional State of the Speaker Analysis.
In 2021 International Siberian Conference on Control and Communications (SIBCON)
(pp. 1-5). IEEE.
Valdés, R.M.A., Comendador, V.F.G. and Campos, L.M.B., 2021. How Much Can Carbon
Taxes Contribute to Aviation Decarbonization by 2050. Sustainability, 13(3), p.1086.
Gudmundsson, S.V., Cattaneo, M. and Redondi, R., 2021. Forecasting temporal world recovery
in air transport markets in the presence of large economic shocks: The case of COVID-
19. Journal of Air Transport Management, 91, p.102007.
Verma, S. and Kumar, P., 2021, February. A Comparative Overview of Accident Forecasting
Approaches for Aviation Safety. In Journal of Physics: Conference Series (Vol. 1767,
No. 1, p. 012015). IOP Publishing.
Morris, M.T., Carley, J.R., Colón, E., Gibbs, A., De Pondeca, M.S. and Levine, S., 2020. A
quality assessment of the Real-Time Mesoscale Analysis (RTMA) for aviation.
Weather and Forecasting, 35(3), pp.977-996.
Devezas, T., 2020. Trends in aviation: rebound effect and the struggle composites x aluminum.
Technological Forecasting and Social Change, 160, p.120241.
Basart, S., Votsis, A., Rautio, T., Chouta, K., Barnaba, F., Di Tomaso, E., Mona, L., Mytilinaios,
M., Formenti, P., Werner, E. and Pérez García-Pando, C., 2021, April. Operating in
risky sand and dust storm environments in Northern Africa, the Middle East and
Europe: a portfolio of aviation climate services. In EGU General Assembly Conference
Abstracts (pp. EGU21-14490).