A Study on the Customer Attitudes toward the Airport IT Service: Focusing on Handling Process and Acceptance Intention

  • ABSTRACT

    Purpose : In the aviation industry, we will investigate the impact of users’ acceptance of technology on their usage behavior and find out the factors that affect their acceptance of technology. We will expand the prior study to find out the impact of the self-service technology of Incheon Airport. Research design, data and methodology : Within the last six months, the survey was conducted on people using self-service technology at Incheon International Airport from July to August 2019. Part 307 of the valid questionnaires were used for this final analysis. The collected data were used to perform frequency, factor, reliability, and multiple regression analyses using the SPSS statistical package. Results : Individual aspects of external variables, service aspects and system aspects have been shown to affect usefulness and perceived ease of use. Also, perceived ease-of-use and usefulness have effects on users' intention to accept technology. Conclusions : The perceived easement and perceived usefulness of Incheon International Airport has been shown to affect self-service users. Increasing the user's self-efficiency and increasing the user's expectations for benefits, convenience, rapid processing, and minimal effort will have a positive meaningful effect on the intention of accepting the technology.


  • KEYWORD

    Customer Attitude , Airport , IT Service , Handling Process , Acceptance Intention

  • 1. Introduction

    The aviation industry is a dynamic transport industry, and air transport plays an important role in promoting globalization by facilitating the flow of people, goods and information (IATA, 2019). Due to defects in high-speed 5G and smart device technologies, each field of society is making rapid progress. In particular, technology-based self-service, which interacts with passengers in new ways, is rapidly being introduced in the aviation industry sector as the application of technology to services increases.

    In particular, the airport is the first gateway for passengers to begin their journey, and since the infrastructure of the airport has a significant meaningful impact on the perception of the passenger experience, self-service technologies for saving passenger time, reducing space strategy, and cost are widely implemented in the aviation industry. The airport's new information technology was divided into self-service technology and airport support technology, which said that ticket issuance, boarding and baggage processes could improve throughput as a major application area (Bogicevic et al., 2017; Kim & Park, 2019), reducing costs and improving consumer services, as well as creating an image that leads the service's leading position (Byun, 2018; Chen & Shang, 2018).

    Incheon Airport's 2nd Passenger Terminal, which opened recently, is a state-of-the-art airport, and aims to drastically reduce the time required for passengers to and from the country and implement world-class smart airports by expanding self-service, such as self-check-in and automatic baggage claim.

    As a result of creating and extending the "self-service zone" in the center, the waiting space of the 2nd Passenger Terminal at Incheon International Airport is three times larger than the 2nd Terminal, the utilization rate of the airport increased from 23% and 2.7% in 17 years, respectively, by self-checking and 115 by self-backing. Immigration time is also reduced by more than 30 percent(Kim & Park, 2017; Rajasekhara & Satagopam, 2018).

    Therefore, we will examine the variables that affect the acceptance intention of self-service users for simplified procedures, enhanced security, and efficient work, and see how perceived usefulness and ease of use affect the acceptance intention of the technology in this study. In doing so, we would like to draw a suggestion that contributes to the airport's self IT service technology operation policy to encourage passengers to use the airport's self-service technology.

    2. Literature Reviews

    What factors users of information technology embrace is one of the most important meaningful research areas in recent years. Theoretical basis (Im et al., 2017; Gu & Lee, 2019) for studying these skills is based on three models: Technology Acceptance Model (TAM), Theory of Planned Behavior (TPB) and Theory of Reasoned Action (TRA).

    As such, TAM is a model that explains the factors that users embrace information technology. Currently, IT services are widely used and the scope of end users is expanding (Lee et al., 2016; Jin & Lee, 2018). Also, it is possible to use digital products traded on the Internet only with basic knowledge to handle information technology such as the Internet and computers. Therefore, the use of TAM, which looks at computers and the Internet as information technology, and explains what factors influence the acceptance of information technology, was deemed appropriate, so TAM was introduced as a research model.

    The individual aspect of the information technology sector was said to be the voluntary will of individuals to test new information technology, and the individual aspect would affect their intention to use new technology (Agarwal and Prasad, 1997). Agarwal and Karahana (2000) said that personal aspects are considered to be important determinants of cognitive immersion and have a meaningful impact on perceived usefulness and ease of use, with five individual aspects. Therefore, this study defined the individual aspect as 'the degree of voluntary will of individuals to test new information technology'.

    Rayport (1995) defined testability to the extent that innovation could be tried on a limited basis. In this study, it was defined as 'providing service use opportunities and degree of symbolism of functional testing'.

    The characteristics of the system were similar in meaning to the performance and speed of the system used by Davis et al. (1989). That is, the system aspect is the extent to which users can use the system reliably and efficiently. In this study, system aspects are defined as 'system stability and speed'.

    Perceived ease-of-use took advantage of the key concepts presented in Davis et al. (1989)'s technology acceptance model. Perceived convenience is defined as 'the extent that users believe that using a particular system will reduce users' efforts.'

    Perceived usefulness of IT service has been used in its entirety the core concepts presented in the technology acceptance model. Perceived usefulness of IT service is defined as 'the extent to that users believe it will improve job performance for users using a particular system.'

    Davis et al. (1989) found that acceptance was 'intentional strength to use a specific information system'. Acceptance was a major factor in determining actual behavior, making actual behavior predictable from the intent to use. This study defined 'intentional or probability of using a service'.

    3. Data and Research Methodology

       3.1. Research Model

    In this study, a research model based on prior research was proposed as shown in Figure2. We would like to explore how external variables affect perceived usefulness of IT service and perceived ease of use. And we also want to examine how perceived ease-of-use and perceived usefulness affect technology acceptance intent through empirical analysis.

       3.2. Research Hypothesis

    3.2.1. The Influence of External Variables on Perceived Ease and Perceived Usefulness

    In situations where IT services are not mandatory, a higher degree of use of IT technology to enable users to use technology can make the system easier for users (Lee, 2011; Kim & Park, 2017; Byun, 2018; Chen & Shang, 2018; Kim & Park, 2019). In other words, the use of an related information system by users is dependent on information systems. It has been shown that users of information systems have a positive impact on the use and acceptance of technology by participating in the system development process.

    In this study, external variables are composed of individual variables, service variables, and system variables to verify how they affect perceived ease of use and usefulness. To this end, the following research theories were established:

     

    H1: External Variables will have impact on the perceived ease of use.

    H1-1: Personal aspect will have impact on the perceived ease of use.

    H1-2: Service aspect will have impact on the perceived ease of use.

    H1-3: System aspect will have impact on the perceived ease of use.

    H2: External Variables will have significant impact on the perceived IT service usefulness.

    H2-1: Personal aspect will have significant impact on the perceived IT service usefulness.

    H2-2: Service aspect will have significant impact on the perceived IT service usefulness.

    H2-3: System aspect will have significant impact on the perceived IT service usefulness.

     

    3.2.2. The Influence of Perceived Ease and Perceived Usefulness on Technical Acceptance Intention

    Many prior studies have demonstrated a causal relationship that perceived ease-of-use influences the intent to use (Davis et al, 1989; Adam et al., 1992; Bharadwaj, 2000, Lee, 2011)

    Perceived values are recognized as one of the major contributors variables to behavior (Park et al., 2012). Many studies have been conducted on the effects of perceived value of users on post-intelligence and behavior patterns. Zeithaml (1998) regarded perceived value as similar to perceived product value concepts, and said perceived value is the utility that is derived from the use of an information system.

    Acceptance means the willingness, frequency of use, and time of use by technical users (Davis & Bagozi, 1989; Venkatesh & Bala, 2008; Kim & Park, 2017). This will verify the impact of perceived usefulness on technology acceptance intent.

     

    H3: Perceived ease of use on IT service will have a significantly positive influence on the technology acceptance intention.

    H4: Perceived usefulness on IT service will have a significantly positive influence on the technology acceptance intention.

     

    4. Results

       4.2. The Demographic Characteristics of a Sample

    Questionnaires were collected using random sampling method to verify the proposed hypothesis. The investigation period lasted for two months until July-August 2019. A total of 310, of which 307 were used for the analysis, excluding those with missing values. The demographic characteristics of the 307 samples are shown in Table 1.

       4.3. Feasibility and Reliability Analysis

    In this study, the validity of measurement tools was verified through exploratory factor analysis and correlation analysis, and internal consistency was assessed based on the Cronbach's α factor to assess whether reliability of measurement tools was ensured. First, the results of the factor analysis of external variables are shown in Table 2.

    The analysis results showed that there were three sub-factors, identical to the theoretical structure of the preceding study. Therefore, they were named 'personal side', 'service side' and 'system side' in the same way as the preceding study. The factorial values of all items were shown to be above 0.6 and above, and the Cronbach's α coefficients for all constitutive concepts were high above 0.7, ensuring the reliability of the measurement items that selected in this study.

    The results of the factor analysis for perceived ease are shown in Table 3. The analysis results showed a single factor, identical to the theoretical structure of the preceding study. Therefore, it was named 'recognized ease of use' in the same way like in the preceding study. The factorial values of all items were all higher than 0.8 and higher, and the Cronbach's α of the concept of composition was also higher than 0.8 to ensure the reliability of the measurement items selected in this study.

    The results of the factor analysis of perceived usefulness are shown in Table 4. The analysis results showed a single factor, identical to the theoretical structure of the preceding study. Therefore, it was named 'recognized ease of use' in the same way as in the preceding study. The factorial values of all items were all higher than 0.8 and higher, and the Cronbach's α coefficient of the concept of composition was also higher than 0.8 to ensure the reliability of the measurement items selected in this study.

    The results of the exploratory factor analysis of the intended use are shown in Table 5. The analysis results showed a single factor, identical to the theoretical structure of the preceding study. Therefore, it was named 'recognized ease of use' in the same method as in the prior study. The factorial values of all items were all higher than 0.8 and higher, and the Cronbach's α coefficient of the concept of composition was also higher than 0.8 to ensure the reliability of the measurement items that selected in this study.

    The results of the correlation analysis for this study are shown in Table 6. The relationship between all potential variables is found to be below the absolute value of 0.7 and there is no problem with multiple coherence. The directionality of the relationship between each concept was assessed to be consistent with the direction established in this study, indicating a positive relationship.

       4.4. Hypothesis Test

    4.4.1. Effect of External Variables on Perceived ease of use

    Multiple regression analyses of the effects of external variables on perceived ease-of-use are shown in Table 7. The independent variable's ability to describe perceived ease-of-use was high at 53.8%, and F=119.814(p=.000) was found to be statistically significant. But, the influence of the individual aspects, the service aspects and the system aspects, which are specifically sub-components of external factors, on perceived ease-of-use are 0.167(t=3.342, p=.001), 0.134(t=3.090, p=.002), 0.567(t=10.051, p=.000) showed that the individual aspects, the service aspects and the system aspects, which are sub-components of external factors, have a significant influence on perceived ease-of-use. Therefore, H1-1, H1-2 and H1-3 were adopted.

    4.4.2. Effect of External Variables on Perceived Usefulness

    Multiple regression analyses of the effects of external variables H2 on perceived usefulness were shown in Table 8. The independent variable's ability to describe perceived usefulness was high at 43.0% and high at F=77.964(p=.000), indicating that it was statistically significant. But, the effects of the individual aspects, the service aspects and the system aspects, which are specifically sub-components of external factors, on perceived usefulness are 0.255(t=3.984, p=.000), 0.078(t=1.406, p=.161), 0.580 (t=8.021, p=.000) showed that among the subcomponents of external factors, the personal and system aspects have a significant impact on perceived usefulness, and the service aspects have no significant impact on perceived usefulness. Therefore, H2-1, H2-3 was adopted and H2-2 was rejected.

    4.4.3. Effect of Perceived Ease of Use on Technical Acceptance

    A simple regression analysis of the effects of perceived ease-of-use H3 on technology acceptance intent was found in Table 9. The perceived ease-of-use of technology acceptance was shown to be high at 43.0% and F=230.447(p=.000) was found to be statistically significant. On the other hand, the influence of recognized ease-of-use on technical acceptance is 0.749(t=15.180, p=.000) indicates that perceived ease of use has an effect on the technical acceptability. Therefore, H3 was adopted.

    4.4.4. Effect of Perceived Usefulness on the Acceptance Intention of Technology

    A simple regression analysis of the effects of perceived usefulness of H4 on technical acceptability is shown in Table 10. The independent variable's recognized usefulness of IT service for technical acceptability was high at 59.0%, and F=439.474(p=.000) was found to be statistically significant. On the other hand, the meaningful influence of perceived usefulness on technical acceptability is 0.760(t=20.964, p=.000) indicates that perceived usefulness has a significant effect on the technical acceptability. Therefore, H4 was adopted.

    5. Conclusions

    This study used TAM on the premise that the airport's IT service was one of information technology. It began with the assumption that individuals will try to use the IT service at Incheon International Airport depending on their belief or attitude to embrace the technology. The analysis analyzed which attributes would increase the acceptance of IT service technology by airport users. Also, the company wanted to check the characteristics of the product, users, and external variables..

    An Empirical Analysis One consequence is as follows :

    Personal side system and the perceived ease and shown to have significant impact to perceived significance. The perceived ease and perceived significance of the airport's IT services have been shown to increase the acceptance of technology.

    Based on the results of the overall empirical analysis, the existing TAM studies influence the acceptance of technology in the external environment variables, which differ from the fact that the research model is initiated based on personal aspects of the external environment variables. This is fundamentally different from previous studies.

    The previous study sought to determine whether environmental variables affect the acceptance of technology by means of independent variables and perceived ease-of-use and perceived usefulness.

    However, in this study, the external environmental variable, the personal aspect, is set as the primary independent variable, placing the system side and the service side as parameters when the causal relationship is started. Perceived ease-of-use and usability are set as secondary independent variables.

    The reason for this is that unlike conventional TAMs, the characteristics of the subjects were strong, and differences were seen in terms of the systems and services to which the airport IT services were provided. In other words, it is meaningful that new factors have been validated by presenting a new study model.

    There are several implications for this study. First, it provided criteria for comparing IT services, which were used as comparison means for physical products to date, by classifying them according to their attributes. Second, it provided a shift from a marketing perspective to an acceptance of information technology in an academic approach to airport IT services. Third, airport IT services indicate the importance of personal commitment to how actively users want to leverage the new technology. This is particularly significant in the reality that airport IT services are not yet widely available. In other words, for the expansion of airport IT services, the acceptance of the technology increases when the usefulness and ease of use of the customers is identified. The results of these empirical analyses are judged to be widely applicable to various convergence industries, as well as to the airport service sector.

    However, this study has the following several limitations: First, the variables derived through prior research are the factors that were derived from past research on the acceptance factors of the information system. Future research will require elicitation and verification of influential factors in deriving awareness, utilization and effectiveness of airport IT technologies and services. The survey targets for empirical analysis are also temporary and limited. Further research could suggest more effective implications if the study is conducted on a variety of subjects.

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  • [Figure 1:] 
  • [Figure 2:] 
  • [Table 1:] Demographic Characteristics
    Demographic Characteristics
  • [Table 2:] Exploration Factor Analysis of External Variables
    Exploration Factor Analysis of External Variables
  • [Table 3:] Exploration Factor Analysis of Perceptual Ease of Use
    Exploration Factor Analysis of Perceptual Ease of Use
  • [Table 4:] Exploration Factor Analysis of Usefulness
    Exploration Factor Analysis of Usefulness
  • [Table 5:] Exploration Factors of Technical Acceptance
    Exploration Factors of Technical Acceptance
  • [Table 6:] Correlation Analysis
    Correlation Analysis
  • [Table 7:] Effect of External Variables on Perceived Ease of Use
    Effect of External Variables on Perceived Ease of Use
  • [Table 8:] Effect of External Variables on Perceived Usefulness
    Effect of External Variables on Perceived Usefulness
  • [Table 9:] Effect of Perceived Ease of Use on Technical Acceptance
    Effect of Perceived Ease of Use on Technical Acceptance
  • [Table 10:] Effect of Perceive Usefulness on the Acceptance Intention of Technology
    Effect of Perceive Usefulness on the Acceptance Intention of Technology