User Acceptance of Biometric Identification at Airports

Empirical Study

Bachelorarbeit , 2021 , 76 Seiten , Note: 1,2

BWL - Allgemeines

In this bachelor thesis, the focus is on investigating the factors that impact user acceptance of biometric identification at airports and assessing the extent of their influence. Drawing from existing literature, several factors such as the number of flights taken annually, gender, interest in new technologies, importance placed on data privacy, and fear of infection during the COVID-19 pandemic are identified and transformed into testable hypotheses. Through a quantitative survey, a total of 307 individuals are interviewed to empirically examine these factors.

TABLE OF CONTENTS

List of Abbreviations

List of Figures

List of Tables

List of Symbols

Abstract

1 Introduction
1.1 Problem Statement
1.2 Thesis Structure

2 Basics ofBiometric Identification
2.1 Definitions and Requirements
2.2 Historical Development
2.3 Types ofBiometrics
2.4 Biometric Identification Process
2.5 Data Privacy Issues

3 Biometric Identification at Airports
3.1 AirportTouchpoints
3.2 Biometric Implementation Programs
3.2.1 Biometric Path: Emirates
3.2.2 Biometric Boarding: Lufthansa Group & Star Alliance
3.2.3 Biometric Terminal: Delta Airlines
3.2.4 OneID:IATA

4 User Acceptance of Technology
4.1 Relevance and Measuring Instruments
4.2 Unified Theory of Acceptance and Use ofTechnology
4.3 User Acceptance ofBiometric Technology at Airports

5 EmpiricalResearch
5.1 Research Approach
5.2 Survey Structure and Question Types
5.3 Statistical Approach
5.4 Presentation of the Results
5.4.1 Demographic Information
5.4.2 H1: NumberofFlightsPerYear
5.4.3 H2:Gender
5.4.4 H3: Interest in New Technological Devices
5.4.5 H4: Importance ofData Privacy
5.4.6 H5: COVID-19
5.4.7 Open Questions
5.5 Discussion of the Results
5.6 Limitations and Further Research

6 Conclusion

Bibliography

Appendix

List of Abbreviations

Abbildung in dieser Leseprobe nicht enthalten

List of Figures

Figure 1: Biometric Process

Figure 2: Airport Passenger Process

Figure 3: Biometric Boarding

Figure 4: UTAUT

Figure 5: Independent and Dependent Variables

Figure 6: Distribution ofRespondents' Gender

Figure 7: Distribution ofRespondents' Age

Figure 8: Number ofFlights per Year

Figure 9: Influence of Gender on the Acceptance ofBiometric Identification

Figure 10: Interest in New Technological Devices

Figure 11: Importance ofData Privacy

Figure 12: Acceptance ofBiometric Identification (COVID-19 related)

Figure 13: Reasons Not to Accept Biometric Identification

Figure 14: Reasons Not to Accept Biometric Identification (COVID-19 related)

List of Tables

Table 1: Regression: Number ofFlights per Year

Table 2: Influence of Gender on the Acceptance ofBiometric Identification

Table 3: Regression: Interest in New Technological Devices

Table 4: Regression: Importance ofData Privacy

Table 5: Evaluation ofHypotheses

List of Symbols

Abbildung in dieser Leseprobe nicht enthalten

Abstract

The aim of this bachelor thesis is to identify the factors that influence the user acceptance of biometric identification at airports and to examine to what extent these factors influ­ence the user acceptance. For this purpose, the possible factors: Number of flights per year, gender, interest in new technologies, importance of data privacy and fear of infec­tion caused by the COVID-19 pandemic are derived from the literature and formulated into hypotheses. To test these factors empirically, 307 people are questioned in a quanti­tative survey. The results indicate that the factors: Number of flights per year, interest in new technological devices and the COVID-19 pandemic have a positive effect on user acceptance of biometric identification technology at airports. Furthermore, the results show that the factor importance of data privacy has a negative impact on the acceptance. Regarding the factor gender, it is found that men show a lower acceptance towards the technology, but only with a small difference compared to women. The bachelor thesis is especially interesting for airport operators and airlines who are planning to introduce bi­ometric identification at airports.

1 Introduction

1.1 Problem Statement

Biometric identification is increasingly being tested and implemented at airports world­wide. In 2021, Statista published a study in which it reported responses from 263 airport executives worldwide regarding the new technologies they would like to test at their air­ports within the next three years. At 83%, biometric identification was among the top two technologies to be tested (Statista 2021, p. 3). Airport processes are expected to be more efficient through the implementation of biometrics by reducing operational costs, increas­ing security and providing passengers a pleasant and smooth travel process (Negri/Bo­rille/Falcao 2019, p. 1).

Since the beginning of the CO VID-19 (Corona Virus Disease 2019) pandemic, the inter­est and demand in biometric identification at airports has increased significantly. The pandemic has posed serious challenges for airports and airlines. Apart from reduced air traffic, airports have had to work out solutions to make airport processes more hygienic. To minimize the risk of contracting the virus, airports around the world have introduced new protective measures, which include biometric identification, as it offers a non-contact experience and therefore a more hygienic alternative compared to conventional identifi­cation processes (Serrano/Kazda 2020, p. 1-2, 9).

An important aspect of the introduction of new technologies is to find out whether they are practical and will be accepted by users (Alturas 2021, p. 13). Investigating user ac­ceptance in advance can have a positive impact on successful and sustainable implemen­tation (Negri/Borille/Falcao 2019, p. 1). Since the acceptance of biometric identification at airports has not yet been explored sufficiently in the literature, this thesis investigates the following research question:

Whichfactors are relevantfor the user acceptance of biometric identification at airports and to what extent do thesefactors influence the user acceptance?

The research question is examined in this thesis with the help of a quantitative survey. For better readability, the generic masculine is used in this thesis, referring to both gen­ders equally. Furthermore, a comma is used for the decimal separator and a period for the thousand’s separator.

1.2 Thesis Structure

The thesis is essentially divided into two parts, the theoretical and the empirical part (in­cluding the discussion of results). The theoretical part focuses on three topics. Firstly, biometric identification in general is discussed. The following chapters explain the mean­ing of biometric identification, the different types of biometric identification, how bio­metric processes work and the challenges that arise when using this form of identification.

Since the focus of this thesis is on the application of this technology at the airport, the second part of the literature review indicates which passenger processes can be replaced by biometric identification and describes which biometric programs already exist at air­ports worldwide. The third theoretical part starts with exploring general acceptance of the technology. A theoretical model is presented that can be applied to measure user ac­ceptance of technology. Afterwards, it explores the acceptance of biometric technology at airports. Based on the findings of this chapter, the hypotheses for the empirical part are derived.

The main focus of this thesis is on the empirical part. At the beginning of the empirical part, the research design of this work is described and the data analysis as well as the statistical methods used are explained. In the context of the research question and the previously derived hypotheses, a survey is conducted. The results of this survey are pre­sented, analyzed and discussed in the empirical part. Based on the results, the hypotheses are evaluated and the research question is answered. Finally, the limitations of the thesis as well as further research approaches are presented.

2 Basics of Biometric Identification

2.1 Definitions and Requirements

Biometric identification can be defined as “[...] the process of automatically recognizing an individual using their unique characteristics” (Igweze 2020, p. 11). The notion bio­metric is composed of two Greek words, bio and metric. The former can be translated to life, whereas the latter means to measure. The two words combined describe the general idea of biometric identification, meaning that biological traits are measured in order to identify an individual (Sharif et al. 2019, p. 15).

The use of biometric technology for identification purposes has become increasingly pop­ular (Sinha/Oo 2019, p. 1). The reason behind this development is that biometric technol­ogy offers various benefits over other identification methods, such as higher security and reliability (Abiodun 2020, p. 2).

Traditional identification methods include the use of a PIN (Personal Identification Num­ber), password, token, or card. A common major disadvantage of these methods is infor­mation and identity theft (Labati/Piuri/Scotti 2012, p. 3). Furthermore, PINs and pass­words must be remembered and changed after a certain amount of time, whereas biomet­rics are generally unalterable and only need to be registered once (Igweze 2020, p. 11). Unlike conventional methods, biometric identification cannot be performed in the ab­sence of the subject person, as he must be present during the process. Thus, identity theft is more difficult (Jaswal/Nigam/Nath 2019, p. 582). Consequently, biometrics can be seen as a highly effective approach to verify a person’s identity (Sharif et al. 2019, p. 15).

The terms biometric identification and biometric verification are frequently used in the literature. The aim of identification is to find out who the person is. It involves comparing the biometric feature with all the reference features stored in the biometric system. Veri­fication, on the other hand, involves comparing the biometric recognition features with a single biometric reference already stored in the biometric system. This verifies whether the person is who he claims to be (Morton 2012, p. 34).

Biometric systems at airports are often required to perform both processes (Matema IPS GmbH 2021). To simplify readability, the term identification is used for both processes in the following text.

According to Ashok, Shivashankar and Mudiraj (2010, p. 2402), a biometric feature may be used for the purpose of identification if it fulfills the following requirements:

1. Universality: Each individual has biometric characteristics.
2. Uniqueness: The characteristics are unique to each person.
3. Permanence: The characteristic must not change with time.
4. Collectability: The characteristic must be able to be detected by the system for measurements.
5. Acceptability: Users must agree to have their biometric characteristics measured.

2.2 Historical Development

The roots of biometrics reach as far back as six centuries. The initial use of biometrics started in the 14th century in China. During this time, the feet or palms of children were stamped on paper to distinguish newborns by their biometric characteristics (Abiodun 2020, p. 9).

Throughout the 19th century, biometrics were used as a method by police agencies to identify criminals (Sinha/Oo 2019, p. 3). In the beginning of the 1920’s, the United States (U.S.) established a department within the Federal Bureau of Investigation (FBI) to look further into fingerprint recognition. Within the following years, the FBI was able to create a database in which biometric information of criminals, such as fingerprints, could be stored (Asha/Chellappan 2012, p. 35). Between 1970 and 1990, research was expanded to other biometric alternatives, such as face, palm, or iris recognition (Asha/Chellappan 2012, p. 35). Furthermore, the first automated fingerprint systems were introduced in the U.S. (Roberts 2003,p. 96).

One of the main consequences of the terror attack on September 11 in New York was the increasing concern about national security. Not just the U.S. but countries all over the world were worried about their safety (Abiodun 2020, p. 9).

As a result, the importance of efficient security systems increased significantly which contributed to a higher demand for biometric identification technology (Roberts 2003, p. 95).

In the 21st century, biometric technology improved even further, hence more industries began to use biometric identification to enhance security. Especially banks, healthcare providers and governments use this form of identification technology (Roberts 2003, p. 96).

The outbreak of the coronavirus in 2020 and the resulting global pandemic accelerated the need for the implementation of contactless technologies (Serrano/Kazda 2020, p. 9). Biometric identification types that are non-intrusive, such as facial recognition, fall into this category and are therefore particularly in high demand (Libby/Ehrenfeld 2021, p. 39).

2.3 Types of Biometrics

There are different types of biometrics. For this work, the types fingerprints, face and iris are relevant as they are commonly used for biometric identification at airports. In the following sections, the three types are described.

Fingerprint

Fingerprint is the most widely used form of biometric technology (Igweze 2020, p. 15). The reason why fingerprint technology is commonly implemented is because of its low cost, its user-friendliness and its high speed (Abiodun 2020, pp. 12-13).

Since fingerprint technology requires the customer to place his finger on the device, the condition of the skin plays an important role during the verification process. Fingers that are wounded or grimed are not verifiable. Furthermore, aged skin can lead to complica­tions in the scanning process, which limits the user group of the technology (Igweze 2020, pp. 15-16).

Another drawback is the fact that it is a contact-based technology, which means that cus­tomers repeatedly touch the same surface. Therefore, concerns regarding the hygienic conditions arise (Abiodun 2020, p. 13; Asha/Chellappan 2012, p. 40).

Throughout the COVID-19 pandemic, the importance of hygiene has significantly in­creased. People fear that they might infect themselves with the virus when touching a surface that has been touched by many other people. In a study conducted by the World Travel & Tourism Council (WTTC), it was found that consumers prefer contactless bio­metric technology due to the COVID-19 pandemic (WTTC 2020, pp. 19-21).

Face

Facial identification is the most well-known type of biometrics. This type of identification is used by humans on a daily basis, without any technology involved, when identifying other people by their face. Due to its familiarity and widespread use, it is the most ac­cepted method (Ashok/Shivashankar/Mudiraj 2010, p. 2403).

Facial identification and verification have been implemented in many different industries. There are many possible applications, both for personal use and institutions. Governments use this type for border control purposes. Furthermore, it for instance serves as a surveil­lance tool to identify criminals (Joshi/Gupta 2016, p. 58).

Nowadays, facial identification is integrated in most smartphones. It can be used, for ex­ample, to unlock the smartphone using the face instead of a PIN. Studies have shown that consumers unlock their phones on average 50 times per day (Ellavarason et al. 2020, p. 27).

In contrast to fingerprint identification , facial recognition can be performed without any physical contact between the user and the device. As a result, this type of biometrics can be used for surveillance purposes, where there is a distance between the person and the camera. Furthermore, it presents a more hygienic experience to the user since there is no risk of infection due to physical touch (Joshi/Gupta 2016, pp. 54-55). This has been a critical advantage since the outbreak of the COVID-19 pandemic (WTTC 2020, pp. 19­21).

The process of identifying a person via his face is rather complex, especially when the person moves and or does not directly face the camera. In addition, it can be challenging for the camera to identify a face when the background is not neutral and the lighting conditions are insufficient (Igweze 2020, p. 13). Another disadvantage is that facial iden­tification systems have difficulties to differentiate between a live face and an artificial face, video or printed photograph which facilitates identity theft (Piccolotto/Maller 2014, p.31).

Iris

“Iris recognition is a technique that uses patterns of color and shape in the iris to confirm a person’s identity” (Piccolotto/Maller 2014, p. 30). When looking at the eye from the front, the iris can be identified as the colored part with a round shape (Igweze 2020, p. 18).

According to Abioudun (2020, p. 11), iris is the type of biometric identification that has the highest accuracy rate. The difficulty of forging an iris is one of the main reasons why this biometric method is considered highly secure. Generally, it is possible to change the iris by surgery however it is relatively simple to recognize an artificial iris (Igweze 2020, p. 18).

An advantage of using iris recognition is related to the speed of the process. The compar­ison of the image of the iris with the ones stored in the database can be performed under one minute (Abiodun 2020, p. 11). Similar to facial identification, the iris identification process is non-intrusive (Asha/Chellappan 2012, p. 42).

One feature of the iris stands out as being distinctly unique. Contrary to fingerprint and face recognition, irises do not change over time. Thus, one stored image of a person’s iris is enough to recognize this person through their entire lifetime. Both the face and finger­print change with age. Therefore, multiple images are required (Feit 2018, p. 31).

A drawback is the high cost of the identification technology (Igweze 2020, p. 11). Fur­thermore, the process of scanning the iris is highly dependent on sufficient lighting con­ditions. If there is insufficient light shining into the eye, the system cannot detect the iris (Piccolotto/Maller 2014, p. 31). However, the light is often perceived as unpleasant by customers (Abiodun 2020, pp. 11-12).

2.4 Biometric Identification Process

The process of biometric identification is divided into five steps (see Fig. 1). In the first step, which is referred to as “Image Acquisition”, a biometric sample is taken from the user in form of an image. This biometric sample can for instance be the image of a per­son’s face, finger, or iris. Requirements such as the format and size of the image must be met to use the sample for the next process steps. These adjustments are made in the “Re­processing Stage” (Sinha/Oo 2019, p. 1-2).

Afterwards, biometric features must be filtered from the image. The features which were filtered in the last step are now secured as a template and stored in a database (Sinha/Oo 2019, p. 2). The steps from “Image Acquisition” up to “Representation Feature and Tem­plate Database” are also summarized as the biometric enrolment phase. Without the en­rolment, a biometric system cannot be used for identification purposes (Abiodun 2020, p. 10).

The next two steps are referred to as the testing stage. During template matching, the generated template is compared with all templates stored in the database. Once the tem­plate can be matched, a person is identified. A person is verified when the live template and the stored template match (Sinha/Oo 2019, p. 2).

Abbildung in dieser Leseprobe nicht enthalten

Figure 1: BiometricProcess (derivedfrom: Sinha/Oo 2019,p. 2)

2.5 Data Privacy Issues

Biometric identification is considered efficient and highly secure. The security of bio­metric identification can only be guaranteed if the data is adequately protected. Customer acceptance of biometric identification is therefore highly dependent on how much the customer perceives his or her data to be at risk. Customers fear that their data will be misappropriated by institutions and used for purposes contrary to their consent. However, most customers are concerned about identity theft (Labati/Piuri/Scotti 2012, p. 4-7).

In case of identity theft, there is a significant difference between traditional identification methods and biometric identification. A stolen password or PIN can be easily changed or replaced. Biometric data on the other hand cannot be replaced since it is unique, as de­scribed in chapter 2.1. Consequently, it is difficult to identify a person with stolen bio­metric data (Labati/Piuri/Scotti 2012, p. 4-7).

Fraudsters can therefore often impersonate the stolen identity for a long period of time (Labati/Piuri/Scotti 2012, p. 4-7). The influence of data privacy on the acceptance of biometric identification will be further examined in the empirical part of the thesis.

3 Biometric Identification at Airports

3.1 Airport Touchpoints

To understand how biometric identification systems can be incorporated at the airport it is crucial to get to know the customer’s journey at the airport, including the touchpoints that the passenger encounters. The four relevant airport touchpoints will be highlighted by describing a passenger’s departure process at the airport.

The passenger enters the airport through the terminal’s entrance (Brause et al. 2020, p. 4). In the terminal, check-in counters, baggage drop-off, restaurants and shops can be found. This area is open to public, which implies that any person can enter without having to pass through a security process (Flughafen Koln/Bonn Gmbh 2021a).

The first touchpoint that a departing passenger encounters is the check-in counter and baggage drop-off. At this touchpoint, the passenger is checked-in to his flight and drops off his checked-in luggage item. Nowadays, customers also have the option to check-in to their flight in advance from home, which means that they only need to visit the check­in counter if they need to drop off their checked baggage. Customers can bypass the check-in counter and directly move to the next touchpoint in case they only travel with carry-on luggage (Brause et al. 2020, p. 4).

The second touchpoint is the security check which takes place at the security touchpoint. It is the second touchpoint and acts as a transition zone between the public area and the sterile area, which is the area where passengers wait for the boarding of their flight (Price/Forrest 2016, p. 273). During the security check, the passenger must place his per­sonal belongings into his hand-luggage and place the hand luggage into a bin, that passes an x-ray check. The passenger himself is also screened by walking through a body scan­ner. Before entering the body scanner, metals such as belts and outerwear are obliged to be taken off (Flughafen Koln/Bonn Gmbh 2021b).

If no complications arise during the screening process, the passenger can enter the sterile area. In this area duty free shops, restaurants and boarding gates are located. Passengers spend their interim in this area (Price/Forrest 2016, p. 273).

Whether the passenger must go through passport control depends on where the passenger is coming from and which destination has been booked for the flight. Passengers traveling within the Schengen Area can directly proceed to the boarding touchpoint. Except for five countries, all European countries belong to the Schengen Area. Passengers traveling out­side the Schengen Area must present their passport for passport control. When it is time for boarding the aircraft, the passenger moves to the next touchpoint, which is the respec­tive departure boarding gate. The boarding process usually terminates 20 minutes before the flight’s departure time (Brause et al. 2020, p. 4; European Commission 2021).

Figure two displays a simplified passenger airport journey that can be applied to small- and medium sized airports and is based on the passenger departure process at Cologne Bonn Airport (Brause et al. 2020, p. 4-5).

Abbildung in dieser Leseprobe nicht enthalten

Figure 2:AirportPassenger Process (derivedfrom: Brause et al. 2020,p. 5)

3.2 Biometric Implementation Programs

The use of biometric identification has already been tested and implemented at several airports around the world. Especially since the outbreak of the COVID-19 pandemic, there has been an increased search for contactless solutions that can replace traditional processes at airports (Serrano/Kazda 2020, p. 9). In the following chapters, four examples ofbiometric implementation at airports are described.

3.2.1 Biometric Path: Emirates

As a consequence of the COVID-19 pandemic, The Emirates Group (Emirates) intro­duced a contactless biometric path at Dubai International Airport (DXB) in October 2020. The biometric path enables passengers to move through the airport without showing travel documents and touching a single surface at touchpoints (Emirates 2020). Eligible users are Emirates’ First Class and Business Class customers departing from or travelling through DXB (Emirates 2021).

The biometric type used for this program is a combination of face and iris recognition. To use the biometric path, passengers must register at the selected check-in desks. The touchpoints included in the biometric path are selected check-in counters, passport con­trol, Emirates’ lounge located in concourse B and selected boarding gates. Hence, three out of four touchpoints, displayed in figure two, are replaced by biometric identification technology (Emirates 2020; Brause et al. 2020, p. 5). The passport control touchpoint is replaced by a smart tunnel, which is a biometric identification technology that scans the passenger’s iris while walking through it. It is the first of its kind to be launched at an airport worldwide (Emirates 2018).

3.2.2 Biometric Boarding: Lufthansa Group & Star Alliance

In November 2020, the airlines Deutsche Lufthansa AG (Lufthansa) and Swiss Interna­tional Air Lines (SWISS), which are part of the global aviation group Lufthansa Group, launched a biometric boarding program in collaboration with Star Alliance (Lufthansa 2020). Star Alliance is a global airline alliance (Star Alliance Services GmbH 2021).

This biometric program allows selected passengers to perform the boarding process via facial identification. As can be seen in figure 3, the face scanner recognizes customers, even if they are wearing masks (due to the COVID-19 pandemic). In order to use this program, passengers must be over the age of 18, customers of Lufthansa or SWISS and be members of the airlines’ Frequent Flyer Program (FFP) “Miles&More” (Lufthansa 2021).

Currently, the service is available for selected flights from Frankfurt Airport and Mu­nich Airport (Lufthansa 2020). Eligible passengers can enroll for the program via the Star Alliance App. The following information must be provided to use biometric board­ing at the airport: Frequent Flyer Number, photo of the passenger, photo of the passen­ger’s passport and the consent that the airport and airline can use the data provided for identification purposes during boarding. One day after completing the registration, cus­tomers can use the biometric gates at the respective airports (Lufthansa 2021).

Abbildung in dieser Leseprobe nicht enthalten

Figure 3: BiometricBoarding (Lufthansa, 2020)

3.2.3 Biometric Terminal: Delta Airlines

In 2018, Delta Airlines (Delta), together with two U.S. public authorites and Hartsfield- Jackson Atlanta International Airport (ATL) opened the first biometric terminal in the U.S. at ATL. Customers ofDelta and four other airlines flying out of Terminal F at ATL can use facial identification technology from curb to the boarding gate. The biometric technology is placed throughout the terminal at all relevant airport touchpoints. Passen­gers who prefer to continue using their physical passport instead of having their face scanned can do so as well. Passengers register by verifying their passport and scanning their face via self-service kiosks at the airport, or at check-in desks (Delta 2018).

According to Delta (2018), the adoption rate of biometric boarding amounted to 98%. Furthermore, when boarding a wide-body aircraft, biometric boarding saved an average total of nine minutes compared to the traditional process.

3.2.4 OneID:IATA

One ID is a project created by the IATA (International Air Transport Association) pro­moting a document-free travel process at airports around the globe. As described in the previous chapters, individual stakeholders have already implemented biometric pro­cesses, but there is lack of coordination between them. As a result, passengers often have to go through the same processes and provide their biometric data to various stakeholders (IATA 2019a).

Through the One ID project, IATA aims to strengthen collaboration among stakeholders to avoid unnecessary processes and promote faster implementation of biometric pro­grams. IATA works together with experts from the industry to develop a framework and standards for One ID. The biometric type suggested for this project is facial, iris and fin­gerprint identification (IATA 2019a).

The initial ideas for the project were developed in 2016. IATA is planning pilot projects at different airports and aims to completely replace the physical passport with biometrics by 2030. Furthermore, IATA plans to enable biometric processing between airports from different countries (IATA 2017).

4 User Acceptance ofTechnology

4.1 Relevance and Measuring Instruments

To follow the empirical study about user acceptance of biometric identification in the next chapter, it is important to understand the general framework of user acceptance of tech­nology. The following subchapters provide an insight in what user acceptance of technol­ogy is and how it can be measured. One of the models used for measuring will be de­scribed in detail, as the model is discussed in the context of the quantitative survey in the empirical part of the thesis.

“User acceptance can be defined as the demonstrable willingness within a user group to employ information technology for the tasks it is designed to support” (Seuwou/Ban- issi/Ubakanma 2016, p. 231). Nowadays, people use technology on a daily basis. Thus, it plays a vital role in our society and has a significant effect on humans’ everyday life (Seuwou/Banissi/Ubakanma 2016, p. 230).

The interaction between humans and technology is complex and requires extensive re­search. Various factors, either of psychological or social nature must be considered to gain a better understanding of the interaction between technology and its potential user (Seuwou/Banissi/Ubakanma 2016, p. 231). To serve as a tool for this complex topic, re­searchers created several models and theories, which are applied by researchers around the world (Alturas 2021, p. 13). For the sake of simplicity and easier reading, both ac­ceptance theories and acceptance models will be referred to as acceptance models in the following text.

By applying user acceptance models, the acceptance and intention of users towards using technology can be predicted to a certain extent. This can be particularly useful when de­veloping and testing new technologies (Alturas 2021, p. 13). Each model is unique and has its own advantages and disadvantages. When comparing the acceptance models, it can be observed that each model has a similar structure but examines different variables, thus has an individual approach to the topic (Seuwou/Banissi/Ubakanma 2016 p. 231).

4.2 Unified Theory of Acceptance and Use ofTechnology

One of the most common used acceptance models is the Unified Theory of Acceptance and Use ofTechnology (UTAUT), which was firstly introduced by Venkatesh et al. in 2003. The UTAUT is formulated based on eight of the most popular theoretical ac­ceptance models, such as the technology acceptance model or the theory of planned be­havior (Venkatesh et al. 2003, pp. 425-426). Venkatesh et al. observed, that there was a high degree of similarity between these eight models and therefore aimed to unify these models into one single model, which resulted in the UTAUT. An advantage that has re­sulted from the invention of the model is that organizations planning to implement a new technology are able to apply the unified model, instead of choosing one of the eight indi­vidual models (Williams/Rana/Dwivedi 2011, p. 38).

The UTAUT is composed of the four independent variables: Performance Expectancy, Effort Expectancy, Social Influence and Facilitating conditions. Furthermore, it includes the dependent variables: Behavioral Intention and Use Behavior and the four moderators: Gender, Age, Experience and Voluntariness (Venkatesh et al. 2003, p. 447). In the fol­lowing paragraph, the variables ofUTAUT are further explained:

Performance Expectancy:“[...] is defined as the degree to which an individual believes that using the system will help him or her to attain gains in job performance” (Venkatesh et al. 2003, p. 447).

Effort Expectancy:“[...] is defined as the degree of ease associated with the use of the system” (Venkatesh et al. 2003, p. 450).

Social Influence:“[...] is defined as the degree to which an individual perceives that important others believe he or she should use the new system” (Venkatesh et al. 2003, p. 451).

Facilitating Conditions:“[...] are defined as the degree to which an individual believes that an organizational and technical infrastructure exists to support use of the system” (Venkatesh et al. 2003, p. 453).

Behavioral Intention:This variable measures the intention to use the technological sys­tem (Venkatesh et al. 2003, p. 456-457).

Use Behavior:This variable describes the actual use of the technology (Venkatesh et al. 2003, p. 456-457).

The independent variables influence the “Behavioral Intention”, except for the independ­ent variable “Facilitating Conditions”, which has a direct influence on “Use Behavior”. The moderators influence the relationship between the independent variables and the de­pendent variables. According to Venkatesh et al. (2003), the moderators may have both positive and negative influences on the variables. The moderator “Gender” may have an impact on “Performance Expectancy”, “Effort Expectancy” and “Social Influence”.

“Age” may impact all independent variables. User “Experience” may affect “Effort Ex­pectancy”, “Social Influence” and “Facilitating Conditions”. The moderator “Voluntari­ness ofUse” influences the variable “Social Influence” (Venkatesh et al. 2003).

Figure four displays the interconnection between the variables and moderators.

Abbildung in dieser Leseprobe nicht enthalten

Figure 4: UTAUT (Venkatesh etal. 2003,p. 447)

4.3 User Acceptance of Biometric Technology at Airports

To be able to investigate the research question in more detail, five hypotheses are formed to determine which factors influence customer acceptance of biometric identification at airports. The hypotheses are formed based on the findings from the literature review.

In 2019, IATA conducted a global passenger survey. The survey addresses the travel be­havior of air travelers and provides insight into what passenger’s value when traveling and which factors influence their satisfaction. One finding of the study was that people who fly more than ten times a year are biometric supporters, meaning that they are more willing to use biometric identification at airports (IATA 2019b). In addition, Lufthansa and SWISS currently offer their biometric program solely to members of their FFP (Lufthansa 2021).

This leads to the following hypothesis:

Hl: The morefrequently people fly per year, the higher their acceptance of using bio­metric identification at airports.

Another finding of the same study is that men are biometric supporters and therefore show a higher acceptance towards biometric identification at airports than women (IATA 2019b). This results in the following hypothesis:

H2: Men show a higher acceptance towards biometric identification at airports than women.

In 2019, an article was published in the Journal of Air Transport Management examining the acceptance of biometric check-in at three Brazilian airports. This technology had not been deployed at the time. In 2018, a study was conducted at the following Brazilian airports: Guarulhos International Airport, Congonhas Airport and Viracopos International Airport. A total of 760 passengers participated in the study. Based on the discrete choice model, the collected data was analyzed. Moreover, the collected data were classified into categories, such as demographic characteristics or reason for travel. The results showed that 82,94% of respondents would accept the technology (Negri/Borille/Falcao 2019, pp. 1-11).

It was found, that the older the passengers, the lower their acceptance of the new technol­ogy. This result was explained by the fact that younger people come into contact with technology more often in their everyday lives and are therefore more accustomed to it than older people. Since older people interact with technology less often, they are more cautious when new technologies are introduced and are less willing to accept them. In this study, the interest in new technology was not directly examined, but served as an explanation for the difference in satisfaction between age groups (Negri/Borille/Falcao 2019, pp. 4-9).

[...]

• Hochschule: Hochschule Worms
• Note: 1,2
• Autor: Sophia Ritter (Autor:in)
• Erscheinungsjahr: 2021
• Seiten: 76
• Katalognummer: V1372232
• ISBN (PDF): 9783346907912
• ISBN (Buch): 9783346907929
• Sprache: Englisch
• Schlagworte: Biometric Identification, Aviation, Airports, User Acceptance, UTAUT, User Acceptance of Technology, Biometrics, Flughafen, Biometrische Authentifizierung, Technologieakzeptanz