Risk Perceptions Using Urban and Advanced Air Mobility (UAM/AAM) by Applying a Mixed Method Approach

Abstract

From a mobility rationale, advanced air mobility (AAM) and/or urban air mobility (UAM) claims a reduction in travel time with integration into intermodal transportation networks and a reduction in ground traffic congestion due to the current modal shift to air, ultimately contributing to more sustainable transportation. Starting in 2025, South Korea is planning to operate air taxis between International Airport and Seoul downtown. This study applied a mixed-method approach to identify barriers to the use of air taxis by investigating consumers’ risk perception of air taxis. A focus group interview yielded a scale with 18 items across five dimensions. Next, through exploratory factor analysis, the 18 items were reduced to 10 items across two dimensions: safety risk (6 items) and cyber risk (4 items). The findings of this study will offer practical guidelines for creating marketing tools and designing strategic management planning for air taxis. The risk perception using air taxis will assist with creating a more strategic and efficient business model that destination management organizations, developers, and policymakers can utilize.

1. Introduction

Due to urbanization worldwide, population density, traffic congestion, and air pollution have become problems that cannot be overlooked. Advanced air mobility (AAM) encompasses the ability for consumers to access on-demand air mobility, package delivery, and emergency management via multimodal transportation network [1]. AAM can serve a variety of built environments including use cases of up to a 50-mile (80 km) radius in rural and urban areas and intraregional cases of up to a few hundred miles [2]. Often referred to as on-demand air mobility, urban air mobility (UAM), or rural air mobility [3], many areas try to construct a digitalized and automated system for urban air traffic management for the efficient and safe integration of AAM vehicles into built environments [4]. By shifting ground transportation into the air to reduce travel times and ease traffic congestion, UAM travel will ultimately contribute to more sustainable transportation [5]. UAM is evolving as an air transportation alternative for logistics delivery drones and passenger-carrying air taxis operating from small towns to high-traffic routes in large cities such as the airport to downtown route [6].

In line with this trend, in Korea, the Ministry of Land, Infrastructure, and Transport announced the ‘Korean-style K-UAM Roadmap for 2020′, proposing to commercialize air taxis to resolve ground traffic congestion in large cities. Manned and unmanned, vertical take-off and landing, electric powered air taxis are proposed for us to address environmental sustainability [7]. The drone mobile industry including these air taxis is one of the main keywords of the 4th industrial revolution along with big data, the Internet of Things (IoT), artificial intelligence (AI), and blockchain technology [8]. Expected to catalyze huge changes in the future, air taxi services are predicted to become commercialized in Korea by 2025. The United States already announced a shared-based air taxi service plan as the next growth direction in 2016, centering on Uber, which has become a global unicorn company by introducing the concept of a shared taxi [9].

NASA [6] conducted a report on 1700 people in five U.S. cities, 55% of respondents said they would be willing to use an air taxi, and 50% said they would be comfortable using an air taxi. However, only 36–37% answered that they would feel safe and secure flying in an air taxi, expressing willingness, safety, fear, and concern that might be caused by a lack of personal experience with the air taxi technology [6]. In addition, the results of a survey conducted by Kim et al. [10] for outbound travelers residing in the metropolitan area, 79.9% of respondents reported a willingness to use an air taxi. The reasons for not using an air taxi included safety issues, price, convenience of existing transportation, and unfamiliarity with air taxis. In addition, JoongAng Ilbo [11] reported that 20% of consumers answered that they would never ride an air taxi in 2025. In addition, 73.5% of respondents who intend to use an air taxi and 65% of non-users raised concerns about safety as the most concerning part when using an air taxi.

This data prompts further studies concerning consumers’ perceptions toward using air taxis. Consumers’ perceived risks have a significant impact on their purchasing behavior, using products, and the execution and cancellation of actions [12]. Recently, the development of vertical take-off and landing, smart airports, and the expansion of the drone industry to passenger transportation are being promoted as important new services or innovations [10]. Prior research found factors influencing the intention to use air taxis derived from customer experience and technology acceptance literature, such as prior knowledge, attitudes, perceived risks, behavioral intentions, and willingness to pay [13,14,15]. Particularly, the psychological barrier of social and public acceptance is a significant determinant in deciding whether this vision will come to reality [16]. Also, when considering user acceptance for the development of new technology, technology adoption, the process of accepting, integrating, and using new technology, can be facilitated by acknowledging and highlighting the factors affecting user acceptance [17]. Therefore, it is necessary to find a way to reduce or solve the risk perception by providing the optimal service in response to the risk perception of consumers who want to use the air taxi.

The purpose of this research is to develop and validate measurement scales for risk perceptions using air taxis. This study adopted a mixed-methods sequential explanatory design to integrate the phases by using the qualitative results focus group interviews (FIG) to develop a scale to measure the risk perceptions using air taxis and to shape the quantitative portion by specifying research questions and variables. As most of the research on air taxis has been focused on the technology, research on the consumers’ perceptions on risks using air taxis is minimal [1,2,3,4]. By applying a mixed method approach, this study analyzed qualitative data from FIG to explore the perception of risk as a consumer and whether it acts as a barrier to using an air taxi as a practical means of urban air transportation in the future. In addition, an exploratory factor analysis (EFA) was used to determine the dimensions of the perceived risk. The academic and practical implications of the air taxi business model were also derived.

2. Theoretical Background

2.1. Air Taxis

As shown in Figure 1, electric air taxis, also called e-VTOL (electric Vertical Takeoff Landing), because of their vertical take-off and landing capabilities, are being considered for carrying people from one point to another [18]. Uber of the United States, well-known as a ride-sharing service platform company, has initiated an air taxi aircraft development competition by developing an aircraft for urban air taxi service and presented an air taxi business model to the market [7]. Uber plans to commercialize air taxis starting 2023 and operate in Dallas and Los Angeles. According to Uber’s plan, 400 to 1000 air taxis per hour will operate at one vertical take-off and landing site (Vertiport) [19].

There is also active discussion about the commercialization of air taxis in Korea. Korea is planning to operate air taxis and connect the Vertiports between International Airport and Seoul downtown (Figure 2). The Ministry of Land, Infrastructure and Transport operates ‘The K-UAM Concept of Operation 1.0’ and ‘The Korean Urban Air Traffic (K-UAM) Grand Challenge’ to revitalize air taxis and establish a business model. In these models, the development stage of the air taxi business is divided into four stages: preparation (2020–2024), initial (2025–2029), growth (2030–2035), and maturity (2036–). In the preparation period (2020–2024), drone-related issues and tasks are discovered, laws/systems are rearranged, and private tests/verifications are carried out. In the early stage (2025–2029), the commercialization of some routes of air taxis connecting the inner and outer hubs (Vertiports) in the metropolitan area is achieved using fixed flight corridors. The pilot is on board the air taxi, but operation and traffic management are performed automatically. During the growth period (2030–2035), the route using the fixed flight corridor connecting the Vertiports in the metropolitan area will be expanded. The operation is automatically performed by the ground control platform (GCP) and the captain is only a monitoring agent. Minimal intervention is allowed to monitor on the ground and intervene in emergencies. In the maturity stage (2036–), the use of air taxis will become common nationwide through the expansion of the intercity movement, and the operation of air taxis will be fully automated. Autonomous driving is the basis for everything from the AI system to the setting of flight routes and the operation of air taxis.

Recently, new technologies such as air taxis are having a great impact on the development of the tourism industry. This ICT (Information and Communications Technology) technology development provides new tourism services, creates new demand, and expands the market [20]. Several logistics companies and air taxi companies are working to launch an air taxi service using UAM, which is predicted to be launched soon (Figure 3) [21]; however, there are very few empirical studies on air taxis in the tourism field. For instance, Rajendran and Shulman [22] predicted the number of taxis to meet the demand of New York City through a study of air taxi network operation. Within this study, the necessity of a smartphone application for using air taxis, the connection of air taxis with existing land taxis, and the establishment of 2 Vertiports and 16 Vertistops for New York City were suggested. Garrow, Ilbeigi, and Chen [23] measured the demand for on-demand air taxi services through focus group interviews. This study estimated high-income earners as early adopters of air taxis and classified them into potential consumers for airport transfers, potential consumers for inter-city transfers, and commuter users. In a study on the development of drone use in the tourism industry, Lee [24] presented a field of leisure using a boarding drone to enjoy water sports or flying in the sky as a development direction. In addition, a drone taxi pilot project was proposed in the special tourist zone.

2.2. Risk Perceptions

Bauer [25] initially proposed the following concept of perceived risk, “Consumer behavior involves risk in the sense that any action of a consumer will produce consequences which he cannot anticipate with anything approximating certainty, and some of which at least are likely to be unpleasant” (p. 24). This refers to the cognitive probability that people will be exposed to threats or risks [22]. Risk perception can be divided into individual and social-level of perceived risk. Individual-level risk perception refers to the perceived vulnerability of an individual to the possibility of risk exposure, and the severity of the risk felt by the individual. On the other hand, social-level risk perception refers to the perceived vulnerability to the possibility that other people will be exposed to risks and the presence of risks to society [12].

Several previous studies have investigated risk perceptions in consumers’ purchasing behavior. For instance, Savas [26] classified risk perceptions into seven dimensions of financial risk, physical risk, performance risk, social risk, psychological risk, time risk, and privacy risk. According to Savas [26], financial risk is the potential loss of money associated with a purchase. Physical risk is the perception that a product or service will harm its audience. Performance risk refers to the potential failure after the consumer purchases a product or service. Social risk refers to the potential loss of good evaluations such as praise, respect, and friendship from others by using the product or service. Psychological risk refers to the agitation that arises from emotions such as potential regret, disappointment, worry, and frustration that the recipient obtains from using the product or service. Privacy risk means potential loss of control of personal information. Furthermore, Stone and Gronhaug [27] classified risk perception into financial, performance, social risk, physical, psychological, and temporal risk, time and future loss risk. These risk perception studies have been important in identifying areas for improvement in marketing, services, and production.

In NASA research report titled “The Potential Societal Barriers of Urban Air Mobility”, Shaheen, Cohen and Farrar [6] investigated the social perceptions of air taxis and what risks act as barriers to using air taxis via focus group interviews. The result of this study showed five factors (i.e., performance risk, psychological risk, privacy risk, physical risk, efficacy risk) on 17 items (see

Table 1. The potential societal barriers of UAM.

Perceived Risks	Shaheen, Cohen and Farrar [6]
Performance risk	- Inconvenience required connections to/from vertiport - Restrictions on landing
Psychological risk	- Inconvenience due to fly with strangers in a piloted aircraft - Safety accidents due to the absence or reduction of flight attendant - Aircraft windows would make passengers feel too exposed
Privacy risk	- Low-level flight could be unsafe or visually undesirable - Sharing personal information - Sharing weight information
Physical risk	- Inconvenience caused by frequent stops such as buses (frequent take-off and landing) - Safety issues due to flying at low altitude - Greater safety risks associated with accidents than with ground transportation - Potentially noisy in urban areas - Inconvenience caused by a small aircraft size
Efficacy risk	- Expensive fees - Demand would exceed available supply leading to high costs, long waits, or both

).

3. Research Methods

3.1. Focus Group Interview

The focus group interview (FGI) technique used in this study followed the FGI interview procedure proposed by Morgan [28]. FGI is a qualitative analysis method that draws conclusions by collecting data created through the interaction of people who are familiar with the research topic or have a similar background. FGI conducts interviews with a small group on a specific topic, generally consisting of a minimum of 4 to a maximum of 12 research participants with similar backgrounds [29]. FGI can improve data quality by excluding false or extreme views through mutual checks among interviewees [30]. The procedure was carried out according to the five steps: Step 1: Prepare research plan and questionnaire, Step 2: Recruit participants, Step 3: Conduct interview, Step 4: Data Analysis, and Step 5: Draw results.

In this study, two FGI sessions were conducted with six members each. To recruit FGI participants, researchers contacted an FGI specialized agency and 58 interviewees were recommended from 25 May to 27 May 2022. Among them, 12 people who agreed to the FGI while meeting the selection criteria (those who have heard of drone taxi, AAM/UAM, and air taxi) were selected, and six people each were selected as participants in two focus groups. The first two FGIs took place for Group 1 on 14 June 2022 and Group 2 on 16 June 2022 as non-face-to-face using ZOOM sessions during COVID-19. Due to the nature of being online, there were concerns that the intimacy between each other would decrease compared to the offline face-to-face FGI. Therefore, to increase the intimacy between the participants themselves, and between the host and the participants, before the FGI, the facilitator set the stage by greeting the participants and leading an icebreaker to have the participants introduce themselves. The FGI allowed the participants to speak freely about the moderator’s questions, and the moderator induced the participants to take turns answering the questions comfortably so that other participants could either empathize or oppose them.

Considering air taxis are not yet a reality, before starting the FGI, a 100-s video clip was presented to participants to explain a brief video describing the concept [6]. Based on the YouTube video of Korea Airports Corporation (source: https://www.youtube.com/watch?v=lgCOXkToVgM (accessed on 1 June 2022)), this was edited and provided for the study purpose and to enhance the understanding of air taxis of FGI participants. Figure 4 and Figure 5 show screenshots from scenes included in the video.

The first FGI lasted 150 min and the second FGI lasted about 140 min. Based on the literature review [6], the structure for conducting the FGI includes: (1) welcome (10 min), (2) overview of the topic (10 min), (3) ground rules (10 min), (4) perception of air taxi use (20 min), (5) advantages and disadvantages of air taxis (20 min), (6) security and safety (20–30 min), (7) privacy (20 min), (8) concerns as a non-user (20 min), and (9) closing (10 min) [31,32]. In addition, the FGI was recorded via Zoom the interview contents were requested to Daglo (https://daglo.ai/ (accessed on 20 June 2022)) and converted into text through STT (Sound to text) conversion work. The textual draft was revised three times compared to the audio of the recorded Zoom video, and the Zoom recorded video and text were provided to a third party not related to this study for verification review.

FGI participants were Korean adult men and women, between the ages of 25 and 55, who had heard related words and contents such as drone taxi, air taxi, or UAM. Regarding gender, age, and educational background, respondents were distributed evenly by the group (see

Table 2. Respondents’ Profile.

Focus Group	ID	Gender	Age	Education Level	Occupation	Marital Status
Group 1	G101	M	25	Undergraduate	College student	Single
	G102	F	35	Undergraduate	Cabin crew	Single
	G103	F	42	Graduate	Professor	Married
	G104	M	46	Undergraduate	Self-employed	Married
	G105	F	51	Graduate	Government officer	Married
	G106	F	33	Undergraduate	Office worker	Single
Group 2	G201	F	44	College	Cabin crew	Married
	G202	M	48	Graduate	Researcher	Married
	G203	M	47	Undergraduate	Cabin crew	Married
	G204	F	55	Undergraduate	Homemaker	Married
	G205	F	29	Undergraduate	Nurse	Single
	G206	M	33	Graduate	Freelancer	Single

).

In order to derive the themes related to the risk perception of consumers using air taxis, the same data were analyzed by multiple individuals including three experts in the tourism field. The three experienced experts were identified based on skills in the types of qualitative research, years of work experience, and recent publications in the tourism field [33]. The data analysis was compared and checked by three qualitative tourism researchers who were not involved in this study. Invited were three Ph.D. professionals who have studied and published qualitative tourism research for more than 10 years. To avoid distortion of the study, the researcher and three experts independently performed analysis coding. Coding for data analysis proceeded in three stages. In the first stage, meaningful words, phrases, and expressions were derived using open coding [34]. In the second stage, axial coding was applied to classify the categorization task and its sub-elements. By applying the selective coding method in step 3, selections from among the various categories derived in step 2 were limited to risk areas related to the subject of this study. After the coding work was completed, the researcher and three experts had a meeting to compare and collect the analyzed data. During the meeting, themes, subthemes, and coding results were confirmed based on the agreement of the four people.

To reduce the potential bias induced in focus group data collection, analysis, and interpretation, following Krueger and Casey [31], the FGI process attempted to enhance a systematic, sequential, provable, and continuous approach. For instance, we tried to establish neutrality focusing on the research findings are entirely a function of the informants and the research conditions and not guided by other biases, motives, and views [31]. The moderator makes sure not to unintentionally influence or sway the participants’ opinions. According to Krueger and Casey [31], randomization reduces the selection bias in a random sample of sufficient size. This study consisted of a random sample of six people each in two focus groups.

In this present study, peer review by experienced experts helped the researchers ensure that their biases, data analysis, and interpretations do not affect study findings and conclusions made from the data. A total of 251 sentences, 848 words, and phrases were determined to be meaningful sentences based on the responses of the FGI participants. Finally, 18 items were derived by combining and compressing sentences and words with the same meaning. The researcher used the TAGUETTE program (https://app.taguette.org/ (accessed on 25 June 2022)), a qualitative research analysis program, to derive themes and subthemes through coding. The TAGUETTE program is an open source-based free software for qualitative data analysis.

3.2. Online Panel Survey

The online panel survey further validated the scale to measure the risk perception of UAM. To refine the measurement scale, an online survey was distributed to 250 potential participants, and 225 questionnaires were obtained (response rate: 90%). However, 222 responses were used for the data analysis as 3 questionnaires were removed due to missing values, outliers, and inappropriate responses. This survey to determine the scale was conducted at an online survey company from 1 July to 5 July 2022 among Korean adults over 19 years old. The respondents were asked to watch an introduction to the air taxi for a virtual UAM process (https://youtu.be/IipX7-P-LNM (accessed on 1 July to 5 July 2022)). Only respondents who watched the video before the survey could participate in the online panel survey.

As presented in

Table 3. Sociodemographic Characteristics by Age Group.

Variable	Characteristic	Frequency	Percentage (%)
Gender	Male	131	59.0
	Female	91	41.0
Age	20 s	7	3.2
	30 s	21	9.5
	40 s	44	19.8
	50 s	88	39.6
	Over 60 s	62	27.9
Occupation	Business people/ Self-employed	20	9.0
	Professionals	61	27.5
	Government employee	13	5.9
	Agriculture, forestry, and fisheries	1	0.5
	Technitionas	8	3.6
	Sales/Service	11	5.0
	Tourism sector	8	3.6
	Student	4	1.8
	Homemaker	9	4.1
	Office worker	54	24.3
	Others (retired, unemployed)	33	14.9
Monthly Household Income (Korean Won)	Less than 1 million	19	8.6
	1–1.99 million	30	13.5
	2–2.99 million	30	13.5
	3–3.99 million	32	14.4
	4–4.99 million	35	15.8
	5–5.99 million	22	9.9
	6–6.99 million	13	5.9
	7–7.99 million	41	18.5
	Over 8 million	19	8.6
Marital Status	Single	190	85.6
	Married	29	13.1
	Other	3	1.4
Education	Highschool	7	3.2
	Undergraduate	103	46.4
	Graduate	112	50.5

Notes: United States Dollar is equivalent to 1380 Korean Won (KRW).

, descriptive analysis was performed on a total of 222 valid samples to identify the demographic characteristics of the EFA analysis sample for selecting the risk perception scale of UAM. Regarding gender, there were more males than females with 131 (59.0%) and 91 (41.0%) females. By age, 88 people (39.6%) were in their 50 s, followed by those in their 60 s (27.9%), 40 s (19.8%), 30 s (9.5%), and 20 s (3.2%). Most had a college degree or higher (96.8%). More than half were office workers and professionals (51.8%). The average monthly income of this group was less than 6 million Korean won (65.8%), and 18.5% of the respondents were high-income earners with more than 8 million Korean won.

4. Results

4.1. Focus Group Interviews

As shown in

Table 4. Perceived Risks Reported by FGI Interviewees.

Perceived Risks	Items
Performance risk	Risk1	I am concerned about air taxis do not operate a set route.
	Risk2	I am concerned about air taxis being small and unstable.
	Risk3	I am concerned about the inconvenience of using the app to use air taxis.
	Risk4	I am concerned about the technical reliability of air taxis.
Psychological risk	Risk5	I am concerned about air taxis do not have security staff.
	Risk6	I am concerned about riding the air taxi with someone I don’t know.
	Risk7	I am concerned about the operation error of air taxis.
Privacy risk	Risk8	I am concerned about the leakage of personal information
	Risk9	I am concerned about sharing weight for using air taxis.
	Risk10	I am concerned about the privacy of people living around the route if air taxis operate between buildings.
	Risk11	I am concerned about providing biometric information to use air taxis.
	Risk12	I am concerned about providing facial recognition to use air taxis.
Physical risk	Risk13	I am concerned about being fall or injured using air taxis
	Risk14	I am concerned about the noise from the operation of air taxis.
	Risk15	I am concerned about inconvenience caused by a small aircraft size of air taxis.
Efficacy risk	Risk16	I am concerned about inconvenience caused by access time to Vertiport
	Risk17	I am concerned about inconvenience caused by accessibility (location) to Vertiport
	Risk18	I am concerned about expensive fees of using air taxis.

, analysis of FGI data led to the identification of 18 items of perceived risks using air taxis. From the inductive qualitative approach, five themes evolved: performance risk (i.e., driving route, use of the app, stability, the performance of air taxis), psychological risk (i.e., security staff, riding with strangers, trust), privacy risk (i.e., weight information, surrounding privacy, biometric and facial recognition), physical risk (i.e., fall or injury, driving noise, the small size of aircraft), and efficacy risk (expensive fees, access time/location).

Statements show examples of participants’ responses to air taxi risk perception. Quotes about perceived risks using air taxis reflected and concretely exemplified their perceptions of risks of air taxis in terms of driving route, use of the app, stability, technical reliability, and performance risk. Many respondents’ perceived risks were related to the stability and the performance of air taxis:

“Can a machine completely replace a human and completely guarantee stability? I doubt it, but in fact, this next-generation means of transportation will come out”.

(G203)

“I don’t even ride a regular airplane because of fear, but if the aircraft is small, I think there will be more stability problems”.

(G101)

Participants shared their concerns about their psychological risk regarding security staff and riding with strangers. They perceived risks regarding safety accidents due to the absence or reduction of security staff: “I have fear of such a new technology about flying in the sky can perform well without having security staff” (G103). This perceived risk is echoed by another, sharing her flight attendant experience: “Air taxis have such advantages as speed, so the flight time is short, and nothing dangerous will happen during the short time. However, from the point of view of an airline flight attendant, I think the role of security staff is necessary in case a dangerous situation occurs” (G201). Inconvenience due to flying with strangers in a piloted aircraft was communicated: “I am worried about what will happen with people because I think I am riding with a stranger. Even if I pay extra, I don’t think I will ride with a stranger.” (G202)

Some respondents perceived physical risks such as falls or injury, driving noise, the small size of the aircraft: “Since air taxis are not yet a generalized means of transportation, is it technically safe, I am not sure about falls or other injuries like that…” (G105)

Statements from the FGI reflected concerns regarding privacy leaks. G204 shared the perceived risks that low-level flight could be unsafe and visually undesirable. Interviewees also shared concerns about sharing weight information for aircraft weight and balance, biometric and facial recognition information, cybersecurity, and cyberterrorism. The participant shared that not only is privacy being invaded as air taxi windows can make them feel too exposed, but also people on the ground can see into the aircraft:

“It doesn’t fly high enough in the sky like an airplane, but it flies between buildings. Then I am worried about invasion of privacy, I might look inside the building, and people will see me as well”.

(G204)

Few respondents expressed concerns regarding the efficacy of using air taxis in terms of expensive fees and inconvenience caused by access time to Vertiport and by accessibility (location) to Vertiport. They were unsure if air taxi is an efficient system for air passenger transportation as they would need access to a Vertiport location (a vertical take-off and landing site), know which times to board, and consider the costs of a possible expensive fare. Also, a concern was that air taxis need might need connection with existing public transportation such as subways, buses, and taxis.

In particular, the risk perception found in this study was similar to the past study by Shaheen et al. [6], having consistent items such as access convenience, passengers traveling with others, security personnel, personal information, surrounding privacy, weight information, biometric information, facial recognition information, falls, operating noise, cabin narrowness, and usage fees. Additional new items in this study are noteworthy such as travel route, aircraft size, app use, safety, reliability, and operation method. The additional items appear because UAM is scheduled for commercial operation in 2025 and customers have practical use in mind. Also, air taxi as a future transportation method is not a proven transportation method and unlike the existing transportation methods, appears to be a risk perception.

4.2. Exploratory Factor Analysis

A sample of 222 respondents was used to perform the EFA to sustain the validity and reconfirm the dimensionality of the scale of the perceived risk using air taxis. The KMO measure of sampling adequacy was 0.881, and Bartlett’s test of Sphericity was 984.151 (p < 0.001) (

Table 5. Exploratory Factor Analysis of Perceived Risks using Air Taxis.

Factors	Items	Factor Loading	Commonalities	Eigen Value	Variance Explained	Cronbach’s α
Safety risk	Risk7	0.839	0.786	5.180	3.512	0.875
	Risk13	0.764	0.658
	Risk5	0.727	0.583
	Risk2	0.714	0.542
	Risk4	0.705	0.637
	Risk6	0.608	0.401
Cyber risk	Risk11	0.915	0.869	1.243	2.911	0.851
	Risk12	0.863	0.804
	Risk8	0.692	0.611
	Risk10	0.660	0.532

KMO = 0.881, Bartlett’s test of Sphericity (Χ² = 984.151, df = 45, p < 0.001), Total variance explained = 64.227%.

). 18 risk perceptions using air taxi items were factor analyzed to reconfirm the dimensionality of the scale. A principal component analysis (PCA) with a varimax rotation extracted the factors and Kaiser’s (1974) criteria of eigenvalues over 1.0 were retained. Items with commonalities and loadings over 0.4 were included in the final factor structure. Cronbach’s alphas within each dimension were then used to estimate a factor’s internal consistency.

As a result of the EFA, risk perception using air taxis items was classified into two factors. The first factor, safety risk, included six items regarding perceived psychological safety risks of UAM performance. This included general perceived performance risks using air taxis in prior tourism research. With an eigenvalue of 5.180, this factor explained 35.12% of the total variance with a reliability coefficient 0.875.

The second factor, cyber risk, included four items regarding cyber data leak risks. Particularly consumer information such as biometric information, facial recognition, and other personal information emerged as a risk perception in this study. With an eigenvalue of 1.243, this factor explained 29.11% of the total variance with a reliability coefficient 0.851.

For the remaining 8 items, four items (Risk1 Risk3, Risk9, and Risk16) were deleted as their factor loadings were less than 0.4. Also, four items (Risk14, Risk15, Risk17, and Risk18) were removed that had high loadings on more than two factors.

5. Discussion and Conclusions

This study explored risk perceptions using air taxis predicted to operate from airports to downtown Seoul starting in 2025. The results of this study will now be compared to the findings of previous work. The findings of the current study are consistent with those of Shaheen et al. [6] common 13 factors were shared, such as safety issues due to flying at low altitude, potential accidents, weight information, privacy information, high cost, small aircraft size, noise, inconvenience required to/from vertiport, concern about a set route, piloted aircraft and flight attendant, that were emerged among the 18 items of risks perceptions using air taxis from the mixed-method approach. The results of this study did not show three particular user concerns such as impracticality for short-distance travel, demand would exceed available supply leading to high costs, long waits, or both, and aircraft windows would make passengers feel too exposed. However, the findings of this study revealed five new factors such as application use for air taxis, size of air taxi aircraft, technical stability of air taxi aircraft, operation of air taxi aircraft, and technical trust in air taxis. As our results indicate that the 18 items of perception of risks using UAM emerging from the mixed-method approach were classified into two dimensions: safety risk (six items) and cyber risk (four items). The prevalent perceived risk factors were perceived safety risks of UAM performance. Distinct from the generally perceived risk factors, individuals were concerned about cyber data leaks involving consumer information such as biometric information, facial recognition, and other personal information.

The most important theoretical contributions of this study’s results are developing a scale to measure risk perceptions using air taxis and identifying two dimensions of the perceived risk. This is essential because most research on air taxis has been focused on its technology, so current measures are hard to figure out the consumers’ perceptions on the risks using air taxis. This research utilized a mixed-methods sequential explanatory design to combine the phases. The qualitative results (FIG) were used to develop a scale to measure the risk perceptions using air taxis, and the quantitative part was shaped by defining the research questions and variables. Due to the potential technological advancement for air taxis and limited literature on this topic, determining measurement scales for air taxis provides a timely addition to the existing scholarship f urban air transportation, including developing new scales using mixed methods and applying new scales.

In addition, this finding has important theoretical implications for extending our understanding of risk perception of air taxis. These results are consistent with other studies showing that perceived risk was found to play an important role in the performance risk (travel route, aircraft size, app use, stability, access convenience) [35], psychological risk (safety personnel, traveling with others, operation method, trust), and privacy risk (personal information, weight information, surrounding privacy, biometric information, facial information), play a role in perceived risks [26,27].

Since respondents watched a video because air taxi is not yet commercialized, people extended their risk perceptions of psychological and personal concerns to social risks they produced based on a technology that was not yet commercialized. For example, respondents were reluctant to ride with strangers, so they would ride alone despite incurring additional costs. Also, since it is a means of transportation that no one has ever experienced, people expressed doubts about the technical stability and reliability, with the biggest concern being falling while driving. There were also concerns about the small aircraft size of the air taxis.

Practically, authorities and planners could use these results to focus the potential UAM technology implementation in urban development toward the vital target of sustainable mobility [4], emphasizing sustainable urban development in terms of more diversity in use, relatively short distances, and less urban populated area [7]. The findings will provide practical guidelines for destination management organizations, developers, and policy-makers for air taxi marketing tools and risk management planning. Implementing the tourism perspective on risk perception factors acting as barriers to air taxis will assist in establishing a more strategic approach to creating effective and efficient business models. As customers’ risk perceptions of air taxis are important, the result of this study can be applied with the operation of air taxis in the future. Thus, the perception of safety-related risks perceived by consumers means that technological support must precede the operation of air taxis to relieve users’ anxiety. To use the air taxi, the travel time to the vertical take-off and landing site and the method of transportation should also be designed to arrive in a convenient and short time by linking basic public transportation.

Limitations of a study on future transportation methods that have not been experienced before, include that it may not be possible to find specific risk items that may appear in actual operation. However, for future development, it can be seen that this study provides meaningful research that can be compared and analyzed with the recognition of risks appearing in the actual operation process. Second, as a limitation of qualitative interviews, it is possible to draw conclusions biased toward some participants [36,37]. In order to control the bias of each group, FGI was performed with two groups, but it cannot be considered to be completely controlled.

Considering that the majority of respondents in this study surveyed focused on highly educated men over their 40 s, age may affect the use of technology. Therefore, caution should be taken when attempting to generalize these results to other populations. Future research should include additional testing of the scale on other samples to refine the measurement scale and increase the scale’s generalizability. Also, looking at the risk perception of air taxis from a tourism perspective could minimize user inconvenience and anxiety in the actual operation of air taxis. For example, as a solution to the inconvenience of traveling with strangers, it could be made possible to use it alone at an additional cost when making a reservation. Or for concerns about the use of biometrics (already in use at domestic airports) and facial recognition due to the development of security screening technology (already used when entering the United States), developing education that these efforts are expected to reduce the preparation time for boarding, thereby providing faster service would be useful. Finally, further studies could include access to Vertiport (a vertical take-off and landing site) or the boarding of air taxis requiring a comprehensive fare in connection with existing public transportation such as subways, buses, and taxis.