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Article

An Analysis of Factors Influencing the Intention to Use “Untact” Services by Service Type

by
Hyunsuk Liu
1,
Changjun Lee
2,
Keungoui Kim
3,
Junmin Lee
4,
Ahram Moon
5,
Daeho Lee
1 and
Myeongjun Park
6,*
1
Department of Interaction Science, Sungkyunkwan University, Seoul 03063, Republic of Korea
2
Department of Media & Social Informatics, Hanyang University, Ansan 15588, Republic of Korea
3
School of Applied Artificial Intelligence, Handong Global University, Pohang 37554, Republic of Korea
4
Department of Public Policy and Management, Pusan National University, Busan 46241, Republic of Korea
5
Center for AI & Social Policy, Korea Information Society Development Institute, Gwacheon 427710, Republic of Korea
6
Strategic Business Division, Korea Institute of Robotics & Technology Convergence, Pohang 37666, Republic of Korea
*
Author to whom correspondence should be addressed.
Sustainability 2023, 15(4), 2870; https://doi.org/10.3390/su15042870
Submission received: 14 January 2023 / Revised: 25 January 2023 / Accepted: 2 February 2023 / Published: 5 February 2023
(This article belongs to the Special Issue Impact of COVID-19 on Education)
Browse Figure
Versions Notes

Abstract

:
Since COVID-19, social distancing has become common, and the demand for untact services has increased rapidly, resulting in an economic phenomenon centered on untact worldwide. Due to social distancing, the untact service area is expanding not only to shopping but also to online learning, home training, and telemedicine, and untact services are expected to expand to more diverse areas in the future. This study investigates four types of untact services: online lectures, online meetings related to work and study, online seminars, and online performances, and the effects of concerns about untact services on the intention of use have been examined using a path analysis model. As a result of the analysis, the perceived usefulness had a positive effect on the user’s continuous intention to use untact services. However, depending on the type of untact service, it can be confirmed that the factors that affect the intention to continue using the service differ from each other. Practitioners can use the results of this study when designing untact services in the future.

1. Introduction

An “untact” service is defined as a series of services in which a service provider and a consumer exchange information on a product, select, and purchase without face-to-face communication [1]. In particular, based on the characteristics of digital technologies such as remoteness, unmannedness, automation, and the transcendence of time and space, it can be understood as a concept that encompasses the process of the digitalization of existing “physical behavior” and “services” or applied technologies, as well as the services provided through them [2]. Since COVID-19, social distancing has become common, and the demand for untact services has increased rapidly, resulting in an economic phenomenon centered on untact worldwide [3]. There are two key keywords for the untact economy: “online” for consumers and “remote work” for companies. Due to social distancing, the online service area has expanded not only to shopping but also to online classes, home training, and telemedicine [4,5]. As the face-to-face economy shrank, the untact economy replaced this position, and it is a time when it is steadily expanding due to the prolonged COVID-19 [6]. The COVID-19 incident, which no one expected, is widely predicted to serve as a steppingstone for the growth of the ICT industry, and changes that have been pushed by many companies but have not been realized are now taking place in earnest. It is time for the government and related companies to increase investment in untact infrastructure and services.
Major forms of untact services include online-to-offline (O2O) services using virtual spaces, mobile commerce, delivery applications, and kiosks and unmanned stores where information and communication technology is implemented offline. O2O service, which means online and offline connection service, is becoming a new business model by connecting mobile information such as marketing, payment, and coupon provisions, as mobile devices have been increasingly used recently [6]. Unmanned stores have emerged as an alternative to ease the labor shortages caused by population decline and to improve the weakening of profitability due to rising labor costs. The trend of unmanned stores has jumped over the small scale such as ATMs, and an order payment machine is expected to begin in earnest in the future [7]. In addition, the use of kiosks has been rapidly increasing recently, and they are using the unmanned order payment system very well, mainly in coffee shops and fast-food industries [8]. Previously, the introduction of untact services was an option, but now, untact services are considered essential.
Despite the high proportion of untact services in the Korean economy, many studies on untact services have not been conducted. According to Park et al. [9], anonymity due to avatars in video conferencing motivates people to participate more in discussions. According to Lee et al. [10], untact counseling with artificial intelligence chatbots reduces the burden on the client. Because users have different purposes of use for each service in particular, an analysis of which factors cause users to use the untact service will provide many practical implications.
Therefore, this study classifies untact services into four types: online lectures, online meetings related to work and studies, online seminars, and online performances (live sports viewing, concerts, musicals, exhibitions, etc.), and it examines the effect of the factors of concern for untact services on the intention to use and derives implications. According to the results, the perceived usefulness had a positive effect on the user’s continuous intention to use all the untact services, whereas the factors that affect the intention to continue differ by the type of untact service; in the online lecture model, perceived usefulness was affected by the difficulty in comparing with other students and the difficulty in communicating and conducting off-hours meetings. In the online meeting model, concerns about poor seminars in the online seminar model and concerns about presence in the online performance model affected the perceived usefulness. Practitioners can use the results of this study when designing untact services in the future.

2. Literature Review and Research Model

According to Deloitte’s analysis of the untact economy [11], untact services began to be activated with the spread of COVID-19, and the home consumption market in the Asia-Pacific region will be 2316 billion in consumer goods, 299 billion in entertainment, 192 billion in education, 101 billion in health, 96 billion in food and beverage, and 20 billion in financial services, respectively. This study focuses on the entertainment and education markets, excluding consumer goods, and divides untact services into (1) online lectures, (2) online meetings related to work and studies, (3) online seminars, and (4) online live sports viewing, concerts, and musicals and analyzes how users’ concerns about untact services affect the continuous use of the service.

2.1. Online Lectures

Due to the spread of COVID-19, most universities across the country have adopted untact online education methods using video and video conferencing programs, and the educational environment that requires active interaction between instructors and learners has reached a turning point [12]. It is true that there are many concerns that online lectures will reduce learners’ learning outcomes due to the sudden transition to online lectures, but according to the results of Canning [13], online lectures have a significant effect on enhancing learners’ expertise. However, learning through online lectures does not always have a positive effect on learning outcomes, and various preceding factors work in order for online lectures to lead to learning outcomes.
First of all, regarding online education, it was also found that the quality of education had a great influence on the performance of education in relation to offline education. According to Almaiah et al. [14], the service quality, information quality, and system quality are the most important factors affecting mobile learning usability among learners during COVID-19, and Brown [15] stated that the quality of educational services provided by instructors affects learner satisfaction and that learner satisfaction significantly affects learner loyalty. In addition, in the study of Harasim [16], the content quality of online education was an important factor in learner satisfaction. Specifically, Harasim [16] presented the content structure, the interest in content development, the importance of data, the screen composition of the system, and the interaction with the system as influencing factors of online education.
In addition, some scholars analyzed the important elements of online lectures from the perspective of learners. First, looking at previous studies related to remote lectures and focusing on learner factors, it can be found that educational outcomes such as learning satisfaction or academic achievement can be significantly changed by self-directedness [17,18,19]. Keller’s ARCS learning motivation is also a learning motivation related to the design of class materials, which is the theory that learner satisfaction increases when learning materials raise learners’ attention and develop confidence to perform successfully [20].
In a study on the effectiveness of real-time remote/online lectures, the educational environment, stable technical support, and the use of various technical tools appear to have a significant effect on learner satisfaction [21]. It can be confirmed through existing studies that various factors affect online lectures.

2.2. Online Meeting

All social life and economic activities that were conducted face-to-face were converted to untact situations, and video conferencing services began to be actively used. However, as online video conferencing systems such as “Zoom” became commonplace throughout society, the number of people complaining of mental and physical fatigue began to surge, creating new terms such as “Zoom fatigue” and “Zoom burnout”. In particular, “Zoom fatigue” is a new term that has occurred with the start of full-working-from-home since the start of the COVID-19 pandemic in March 2020, meaning that video conference participants feel excessively drained after working through a video conference program.
According to this phenomenon, research on video conferencing fatigue has recently begun to proceed quickly abroad. In a previous study, the concept of video conferencing fatigue was defined as “the degree of exhaustion and exhaustion due to participation in video conferencing”, and a study was conducted to reveal the cause of Zoom fatigue, a representative video conferencing service [22]. In addition, the fact that the user’s own face keeps shining like a mirror on the zoom screen, receiving too much attention at once, and the fact that communication is difficult due to the lack of various body languages have been revealed as the main causes of Zoom fatigue in video conferencing [23]. Sitting and staring at one place during the video conference time can reduce the user’s cognitive judgment ability [23], and technical problems such as internet disconnection or computer specifications can interfere with conversations between users. As a solution to this phenomenon, alternatives such as reducing the size of the Zoom screen and turning off self-reflecting video features and voice were proposed [23], and ways to reduce fatigue through video conferencing with muting and highly cohesive groups were also proposed [22].

2.3. Online Seminars

Online seminars refer to events in digital spaces, including virtual events, virtual exhibitions, conferences, webinars, and virtual learning environments. The definition of online seminars or online events presented by the Virtual Edge Institute (VEI) is live seminars using virtual platforms customized to enterprises and customers or in virtual spaces. PCMA has expanded its definition of online events by adding technical examples such as digital conferencing, webcasting, virtual events, virtual exhibitions, conferences, and learning environments [24]. An online event is a large-scale, multi-session online event in which webinars are mainly conducted. The basic definition of an online convention is an event in which participants interact in a virtual space, not in a physical location. Online seminars can create a similar feeling to offline events in physical spaces, and networking between participants can also occur actively [25]. In addition, if an exhibition in the traditional sense is a temporary and time-sensitive market [26], the online exhibition is continuous and has the characteristic of being held 24 h a day [27,28].
In particular, the paradigm shift for online seminars brought by COVID-19 presents new standards for future seminar forms, suggesting the possibility that traditional seminar paradigms can be expanded beyond geographical limitations. Using a combination of augmented reality and virtual reality platforms, participants’ needs for untact interactions can also be supplemented [29].
In order for online seminars to be selected by users, various factors must be considered. First, user-friendliness should be the most important criterion for choosing a solution, and participants do not have the level of technical knowledge that event officials have, so every step of the online convention experience should be intuitive and provide adequate explanations [30]. Looking at previous studies on tourism and convention experiences, it was found that the experience of participating in tourism and conventions had a significant effect on tourism and convention satisfaction, perceived value, the achievement of the purpose of the visit, and the intention to revisit [31]. Moreover, participants’ active participation (engagement) in convention events is one of the most important elements of all events and has significance beyond the provision of content [32]. Finally, Worldspan also stressed that the time difference of participants should be considered in online seminars [33].

2.4. Online Performance

As the untact environment spreads in the aftermath of COVID-19, online performances are emerging as a trend. It can be said that the success of online performances depends on how similarly users will feel the presence provided by online performances. First of all, presence refers to the degree to which a virtual object is experienced as a real object in the real world [34,35,36,37]; the higher the degree to which consumers perceive the experience implemented through online performances as realistic, and the lower the degree to which they perceive it as a technology-mediated experience, the higher the perception of presence [38]. Accordingly, the sense of presence is understood to have the potential to influence the overall decision-making process of consumers [39]. According to existing studies, presence has a positive effect on perceived usefulness and perceived enjoyment [40] and is reported as an important predictor of user satisfaction [34].
Many online performances are choosing the live streaming method for a greater presence. Live streaming is a real-time video rather than a pre-production or recording method, and it is defined as a service that is produced and transmitted through streaming technology. Live streaming has the characteristic of the concurrency of communication, in which everything happens in real time through a mobile device or PC [41]. Viewers respond to streamers’ words and actions through text-based chat windows and share and communicate information through comments between viewers, and live streaming serves as a “third place”—a virtual space where communities are formed [42].
In order for online performances to be selected by users, the quality of online performances is also important. There are various approaches to service quality, but it is generally understood as an overall assessment, from the user’s point of view, of a particular service in consumer research [43], which affects consumer loyalty and intentions to purchase [44].

2.5. Research Model and Methodology

Alsyouf et al. [45] used a context-driven model comprising the major pandemic characteristics that lead to various patterns of technology acceptance, and Alrawad et al. [46] used the psychometric paradigm to assess whether people perceived the risks of various work activities. The research model used in this paper is shown in Figure 1, based on the previous literature provided in Section 2.1, Section 2.2, Section 2.3 and Section 2.4. For analysis, this study analyzed users’ experiences of using untact services online, and users who have not used each service or have not used it for the past year, along with users with a very low frequency of use (less than once a month), were excluded from the analysis.
In order to prove the relationship between the variables shown in Figure 1 above, path analysis was used in this study. Path analysis is a statistical method used to model the relationships between multiple variables. It is based on path equation models and allows for the prediction and analysis of cause-and-effect relationships in a system. In path analysis, linearity and independence assumptions are made, and each variable’s relationship to others is modeled using regression analysis. This allows for the use of linear models to predict and analyze the path of the system.
All of the variables used in Figure 1 were collected through questionnaire questions. The questionnaire items actually used to measure variables are shown in Table 1. The level of consent for the question was investigated in four stages, and the respondents chose one of “not at all”, “disagree”, “yes”, and “strongly agree”.

3. Results

3.1. Questionnaire Questions and Data

The model analysis of this study utilizes the “2021 Intelligent Information Society User Survey” conducted by KISDI (Korea Information Society Development Institute) to analyze general users’ perceptions and behaviors regarding intelligent information technology and services [47]. The survey sample selected 1200 households in 17 cities and provinces nationwide through the two-stage probability–proportional system extraction method based on the 2019 Population and Housing Survey by Statistics Korea and surveyed 15-year-old male and female households. However, for the main purpose of this survey, it was conducted on household members who were found to be smartphone-holders among male and female household members aged 15 or older and who use the internet more than once a day. Therefore, there were 2341 final respondents of this survey.
The 2021 Intelligent Information Society User Survey was collected from 7 October to 23 November in 2021 through a face-to-face survey in which a surveyor visited households and surveyed respondents, and the socioeconomic characteristics of the 2341 final respondents are shown in Table 2.
In this study, the questionnaire items of the surveyed items are mainly used to analyze the usage behavior for online-based untact services. When asked about their experience in using online untact services over the past year, they responded in the order of “online conversations with family members or acquaintances” (35.0%), “online lectures (classes)” (12.5%), “online sports viewing, concerts, musicals, exhibitions” (9.3%), and “online seminars” (9.0%).
The mean and standard deviation of the variables used in this study are shown in Table 3. The number in the table means the average value for each variable, and the number in parentheses is the result of calculating the standard deviation.

3.2. Model Fit and Path Equation Analysis Results

Using the measured variables, a path equation model was performed to examine the effect of users’ concerns about untact services on the intention to continue using untact services. Before looking at the analysis results of the path equation model in earnest, the results of the suitability of the model are shown in Table 4. In this study, GFI, NFI, TLI, and CFI were examined, and all four indicators exceeded 0.9, indicating that all models were suitable for analysis.

3.2.1. Online Lecture Model

Users were found to consider how useful online lectures are in taking lectures online as a very important factor. Based on the standardization coefficient, the standardization coefficient of the usefulness of online lectures is 0.568, which is the highest compared to other services (online meeting 0.486, online seminar 0.442, and online performance 0.331). In the online lecture model, we analyzed the effects of seven factors on perceived usefulness: concerns about poor classes, decrease in concentration, Q&A restrictions, class uniformity, concerns about fragmentary classes, difficulty comparing with other students, and the lack of instructor bonding. The factors other than difficulty comparing with other students did not appear to have a statistically significant effect on perceived usefulness. On the other hand, the difficulty of comparing one’s own status with other students had a statistically significant negative effect on the perceived usefulness of online lectures. Factors that can affect the quality of classes or learning performance, such as poor class performance, decreased concentration during class, or difficulty in asking questions, do not have a statistically significant effect on the perceived usefulness of online lectures. On the other hand, it is a very interesting result that only concerns about the comparison with other students, which are not actually related to the quality of online lectures or learning outcomes, have a statistically significant effect.
Looking at the existing literature on motivation for learning, the motivation for learning can be divided into intrinsic and extrinsic motivation. According to self-determination theory, motivation can be distinguished according to the reasons or goals that provoke behavior [48]. Intrinsic motivation refers to motivation that arises because people are intrinsically interested in the work or because the work is fun, and extrinsic motivation refers to the motivation to carry out work in order to obtain a reward or positive result [48]. In Korea, the extrinsic motivation is stronger than the intrinsic motivation of learning. If you have a strong extrinsic motivation, it may be more important to see how much learning you have achieved compared to other students, that is, what your grades are, rather than how much you achieved in your study or how interesting you find studying. Therefore, the analysis result of this online lecture model can be seen as a result of reflecting the characteristics of Korea, with strong extrinsic motivation, rather than the characteristics of online lectures. The empirical results of the online lecture model are shown in Table 5 below.

3.2.2. Online Meeting Model

In the online meeting model, difficulty in communicating and off-hours meeting were found to be statistically significant factors affecting perceived usefulness. However, among the two factors, the difficulty in communicating factor had a negative effect on perceived usefulness, while the off-hours meeting factor had a positive effect on the perceived usefulness. As mentioned earlier, the factor of off-hours meeting was measured through the question, “I’m concerned that my break time will be interrupted because the meeting is held outside the set hours.” In fact, as meetings are conducted online, the need for an offline meeting space is eliminated, and, as travel time to the meeting space is also eliminated, calling a meeting is much easier compared to calling an offline meeting. Thus, online meetings have also made it easier to meet outside of work hours on weekdays or on weekends, which may increase concerns about interrupting breaks. However, in this study, what we wanted to measure through perceived usefulness as a dependent variable was whether online meetings were more useful than offline meetings. Therefore, it can be analyzed that the concern that online meetings removed the time limit had a positive effect on the usefulness of online meetings.
Among the remaining factors, decrease in concentration, difficulty in conveying emotions, difficulty in preparing a meeting, etc. did not appear to have a statistically significant effect on perceived usefulness, but it was found that difficulty in communicating had a negative effect on perceived usefulness. In fact, online meetings are mostly conducted through the delivery of video information and are services that use very high network bandwidth. Therefore, when the bandwidth of the internet connection is insufficient, or when many users use the online meeting service at the same time, there are often difficulties in communicating, such as video stops or delays. Therefore, operators providing online meeting services will need to improve their services so that users’ intentions can be better communicated in the future. The empirical results of the online meeting model are shown in Table 6 below.

3.2.3. Online Seminar Model

In the online seminar model, a seminar refers to events such as conferences, discussions, symposiums, etc. At events like this, participants can be divided into hosts, presenters, debaters, and audiences. However, in this study, the respondents assumed the role of the audience and answered the questionnaire. Therefore, in the above online meeting model, the respondent is not only a listener to other people’s remarks during the meeting but also a speaker who speaks their opinion. On the other hand, in this online seminar model, the respondent’s role as a listener is more important than that of a speaker, and it was found that factors different from the results of the previous online meeting model affect perceived usefulness.
As can be seen in Table 7, factors related to the respondents themselves, such as a decrease in concentration and concerns about conveying intent, did not have a statistically useful effect on the perceived usefulness of the online seminar. Additionally, the effect of factors related to information delivery, such as a decline in presence and concerns about difficulties in networking, on perceived usefulness was also not statistically significant. On the other hand, only concerns about poor seminars had a significant negative effect on the perceived usefulness of online seminars.

3.2.4. Online Performance Model

“Performance” in the online performance model means sports games, concerts, musicals, exhibitions, etc. Like the previous lectures and meetings, these services have mainly been carried out offline in the past. However, the difference between the performance and the previous lectures, meetings, and seminars is that if lectures, meetings, and seminars have a strong business nature whose main purpose is to transmit information, then performance is more of a hobby than a job. Therefore, people go to the theater to feel the heat of the field and interact with the performers, rather than just to enjoy the music and watch the sporting event.
The results of this study also seem to reflect this point, and, as can be seen in Table 8, it was found that the concern that the presence might decrease had a statistically significant effect on the perceived usefulness of the online performance, while the effect of the other variables was not statistically significant. As with all previous models, the perceived usefulness was found to be significant at the 99% level in the intention to use the service continuously. The empirical results of the online performance model are shown in Table 8 below.

4. Discussion and Conclusion

4.1. Discussion

In this study, untact services were classified into four services: (1) online lectures (class), (2) online meetings (conference, discussion, symposiums, etc.), and (4) online live sports viewing, concerts, and musicals. The purpose of this study was to analyze which factors of concern for each classification affect the intention to use the service continuously. This study investigated four types of non-face-to-face services and examined the effects of concerns about untact services on the intention to use them. As a result of the analysis, it was found that perceived usefulness had a positive effect on users’ continuous intention to use non-face-to-face services. However, it can be confirmed that the factors affecting the intention to continue using the service are different depending on the type of untact service.
First of all, in the online lecture model, it was found that perceived usefulness had a positive effect on the intention to use continuously, and only difficulty comparing with other students was found to have an effect on perceived usefulness. In existing studies related to online learning, self-efficacy, subjective norms, and perceived entertainment were mainly used as variables that affect perceived usefulness. For example, studies by Al-Azwei et al. [49], Al-Mushasha [50], Chow et al. [51], Lee et al. [52], and Nagy [53] found that the greater the student’s self-efficacy in online learning, the greater the student’s perceived usefulness. In addition, Agudo-Peregrina et al. [54], Farahat [55], and Mohadam and Bairamzadeh [56] analyzed the effect of subjective norms in online learning, and it was found to have a positive effect on perceived usefulness. Similarly, perceived enjoyment in e-learning also had the effect of developing perceived usefulness (Chen et al. [57], Lin et al. [58], and Zare & Yazdanparast [59]), but there were no papers dealing with difficulties in e-learning, as in this study. However, there were papers that analyzed computer anxiety, but what is interesting is that computer anxiety had a significant effect on the study of employees (Park et al. [60], Purnomo & Lee [61]), while the study of students (Liu [62], Saade & Kira [63]) had no significant effect. From the results of this study, it can be seen that, when using online electrical services, students value the difficulties they feel compared to other students more than the difficulties they have.
In the online meeting model, differential communication had a negative effect on perceived usefulness, and off-hours meetings had a positive effect on perceived usefulness. Online meetings did not receive much attention before the COVID-19 pandemic began. Rini and Khasanah [64] analyzed the factors affecting the use of online meeting applications during the COVID-19 pandemic, and as a result of the analysis, personal innovation, negative word of mouth, perceived phase of use, and perceived risk were found to have an effect. Alturki and Aldraiweesh [65] attempted to analyze the factors affecting perceived usefulness that were analyzed as key factors in this study, and as a result of the analysis, subjective norms, self-efficacy, perceived enjoyment, task technology fit, information quality, and perceived ease of use affected the perceived usefulness of Google Meet. In addition, in the studies by Djojo et al. [66] and Purwanto and Tannady [67], the perceived phase of use was found to have a positive effect on the perceived usefulness of online meeting services. However, the existing studies did not link the characteristics of online meetings themselves with usefulness, as in this study, and the analysis of this study showed that difficulty in communicating and off-hours meetings affect perceived usefulness.
Next, in the online seminar model, it was found that perceived usefulness influenced the intention to use continuously, and the concerns about poor seminars influenced perceived usefulness. The main factor affecting the intention to use of online seminar services in the previous literature is the perceived ease of use (Bailey et al. [68], Djojo et al. [66], and Lee et al. [69]). Moreover, according to Lee et al. [69], in addition to the perceived ease of use, self-efficacy, academic engagement, interactivity, and social presence have a significant effect on the perceived usefulness of online seminars. Park et al. [70] proved that institutional support and voluntariness have an effect on the perceived usefulness of teleconferencing systems, while anxiety does not. The result of the study by Park et al. [70] indicating that anxiety does not affect perceived usefulness is contrary to this study’s result indicating that concerns about poor sensitivity affect perceived usefulness. It seems that different results came out because it was concerned about the seminar becoming poor rather than the technology itself in this study, while anxiety means “the extent to which independents feel unconvincing when using or considering a certificate technology” in the study by Park et al. [70]
Finally, in the online performance model, it was found that only concerns of presence influenced the perceived usefulness of online performance. According to Choi [71], presence has a positive effect on perceived usefulness in online concerts, and presence has a positive effect on engagement in online exhibitions, according to Resta et al. [72]. According to Chang et al. [73], the perceived usefulness of watching sports games online affects the behavior intention, and perceived usefulness is influenced by the social presence of watching sports games online. The results of this study, which showed that concerns about presence affect the perceived usefulness of online performances, support the results of these existing studies.

4.2. Implications

As a result of the analysis, the results of this study have the following practical implications.
First, as in the results of previous studies, perceived usefulness had a positive effect on users’ continuous intention to use untact services. This is analyzed because the services selected in this study were practical services such as online lectures. In other words, it can be seen that the characteristics of the corresponding service have a greater effect on the perceived usefulness effect, rather than depending on whether it is a face-to-face service or an untact service.
Second, the factors affecting the intention to continue using the service differed depending on the service. Concerns that it would be difficult to compare with other students in the online teaching model negatively affected the intention to continue using the online lecture service, and concerns that communication would be difficult in the online meeting model negatively affected the intention to continue using the online meeting service. On the other hand, in the online seminar model, concerns that seminars may become poor, and in the online performance model, concerns about a decrease in presence, were found to have a negative effect. In other words, although people have various concerns about untact services, the concerns that decrease their perceived usefulness and eventually reduce the intention to use them should eventually consider the nature of the service.
Third, although people have various concerns about untact services, these concerns have not often reduced the intention to use untact services. Looking at the results of the analysis, among the seven to eight factors in all services, only one factor for each service had a statistically significant negative effect on the perceived ease of use. The year 2021, when these survey data were collected, was a time when untact services were common, as the government took measures to prevent social distancing due to COVID-19. Therefore, people tended to think that there are no other alternatives at the same time as they became accustomed to using untact services for the stabilization of COVID-19, even if they were uncomfortable. Therefore, it is considered that there were not many cases in which actual concerns had a statistically significant effect on the perceived ease of use or the intention to continue using these services. In addition, this study provides managerial implications. As emphasized by First and Davis [74], users’ perceived usefulness has a significant effect on the purchase intention of the product, and, as can be seen from the results of this study, perceived usefulness has a significant effect on the intention to continuously use the untact services as well. In the era of untact, therefore, managers need to provide a service that allows users to avoid contact with others so that users do not become infected, but they must also take care of the usefulness of the product itself. Second, existing studies have suggested product diversity [75], relative advantage [76,77], compatibility and accessibility [77,78,79], etc. as factors affecting perceived usefulness. However, as can be seen from the results of this study, in the case of untact services, it can be seen that variables (e.g., difficulty comparing with other students (online lecture), difficulty in communicating (online meeting), concerns about poor quality (online seminar), concerns about presence (online performance)) different from the existing ones affect perceived usefulness, and, in particular, it can be seen that the factors affecting perceived usefulness are different depending on the service. Therefore, managers should consider what factors to prepare according to the service provided to increase the usefulness of the service.

4.3. Limitations and Future Works

This study has limitations in the following areas. First, although data were collected from a large number of respondents, data were collected only in South Korea, not in several countries. Therefore, future research may provide broader implications if data from various countries are collected and compared. Second, this study conducted a survey in a unique situation of COVID-19. Therefore, it is not known whether the same results will come out even after the COVID-19 situation is over, and it is expected that the results after COVID-19 and the results of this study can be compared in future studies. Third, as the results of this study show, even for untact services, there were differences in factors affecting the intention to use depending on the type of service. Therefore, it will be necessary to analyze more untact services in the future. Fourth, the variables in this study consist of only one observed variable. If more observed variables can be used to measure variables in a follow-up study, the reliability of the model can be increased. Fifth, only perceived usefulness was used as a mediator in this study, but there will be many more variables that affect the intention of continuous use. Therefore, it is expected that a richer implication can be derived when more diverse mediators are used.

Author Contributions

Methodology, D.L.; Investigation, M.P.; Writing—original draft, H.L., C.L., K.K., J.L., A.M., M.P. and D.L. All authors have read and agreed to the published version of the manuscript.

Funding

This research was supported by the Ministry of Education of the Republic of Korea and the NRF (Nos. 2020S1A5A8045556, 2020R1F1A1048202).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Conflicts of Interest

The authors declare no conflict of interest.

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Sustainability 15 02870 g001 550
Figure 1. (a) Online Lecture model; (b) Online Meeting model; (c) Online Seminar model; (d) Online Performance model.
Figure 1. (a) Online Lecture model; (b) Online Meeting model; (c) Online Seminar model; (d) Online Performance model.
Sustainability 15 02870 g001
Table
Table 1. Variable Descriptions.
Table 1. Variable Descriptions.
Online Lecture Model Variable Description
Concerns about poor classesI’m concerned that the contents of the class will become poor.
Decrease in
concentration		I’m concerned that the concentration of the class will decrease.
Q&A restrictionsI’m concerned that opportunities for questions and answers will be limited due to difficulties in communication with instructors (teachers).
Class uniformityI’m concerned that the content and format of the class will be uniform.
Concerns about fragmentary classesI’m concerned that the class will only follow the progress.
Difficulty
comparing with other students		I’m concerned that I can’t make sure I’m following the class well because I can’t compare with other students.
Lack of
instructor bonding		I’m concerned that I may not be able to build bonds with instructors (professors) and students.
Online Meeting Model Variable Description
Concerns about poor meetingsI’m concerned that the meeting will go haywire.
Decrease in
concentration		I’m concerned that the concentration of the participants on the meeting will decrease.
Difficulty in
communicating		I’m concerned about whether conversations and communication can be facilitated.
Difficulty in
conveying emotions		I’m concerned that misunderstandings will occur due to difficulties in conveying emotions and nuances.
Difficulty in
preparing for a meeting		I’m concerned that additional efforts such as the preparation of materials for online meetings will occur.
Increased meeting timeI’m concerned that the meeting will take longer.
Off-hours meetingI’m concerned that my break time will be interrupted because the meeting is held outside the set hours.
Online Seminar Model Variable Description
Concerns about poor seminarsI’m concerned that the seminar will become poor.
Decrease in
concentration		I’m concerned that the concentration on the seminar will decrease.
Decline in presenceI’m concerned that I may not be able to properly feel the atmosphere of the scene.
Concerns about difficulties in
networking		I’m concerned that there will be difficulties in networking with other attendees who participated in the seminar.
Concern about the delivery of
intentions		I’m concerned that the original intention of the seminar may not be conveyed due to the formality of the seminar.
One-way information transferI’m concerned that there will be only one-sided information transfers.
Off-hours seminarI’m concerned that my break time will be interrupted because the seminar is held outside the set hours.
Online Performance Model Variables Description
Concerns about poor performanceI’m concerned that the content provided will become poor.
Decrease in
concentration		I’m concerned that the concentration of the audience will decrease.
Concerns of
presence		I’m concerned that I may not be able to properly feel the atmosphere of the scene.
Concerns about networkingI’m concerned that I will not be able to interact or communicate with other audiences.
Concerns about content qualityI’m concerned that the difference in sound and video equipment that individuals own will affect the quality of content that can be enjoyed.
Concerns about information leakageI’m concerned that content will be leaked through abnormal channels.
Table
Table 2. Characteristics of 2021 Intelligent Information Society User Survey Respondents.
Table 2. Characteristics of 2021 Intelligent Information Society User Survey Respondents.
Number of CasesRatio
(%)		 Number of CasesRatio
(%)
Total2341 100.0Marital StatusUnmarried44619.1
GenderMale1125 48.1Married162769.5
Female1216 51.9Bereavement/divorce268 11.4
By Age15 to 19 years622.6By monthly average household incomeLess than 1 million won42 3.5
20 to 29 years24510.5Over 1 million won to less than 2 million won91 7.6
30 to 39 years41017.5Over 2 million won to less than 3 million won171 14.3
40 to 49 years41717.8Over 3 million won to less than 4 million won267 22.4
50 to 59 years63227.0Over 4 million won to less than 5 million won211 17.7
Over 60 years57524.6Over 5 million won to less than 6 million won235 19.7
By
educational
background		Below elementary school graduation582.5Over 6 million won to less than 7 million won111 9.3
Middle school graduation1436.1Over 7 million won66 5.5
High school graduation102843.9Number of household membersSingle246 20.6
Above university graduation111247.5Two persons445 37.3
OccupationProfessional management145 6.2Three persons303 25.4
Office work509 21.7Over four persons200 16.8
Sales of services696 29.7Regional scaleMetropolis1367 58.4
Agriculture/Fishing98 4.2Small- and
medium-sized cities		709 30.3
Skill labor287 12.3Township area265 11.3
Student156 6.7By RegionSeoul/Incheon/
Gyung-gi		758 32.4
Housewives376 16.1Daejeon/Sejong/
Chung-cheong		397 17.0
Jobless/Other743.2Gwangju/Jeolla/Jeju380 16.2
Household owner statusA householder1194 51.0Daegu/Geongbuk/
Gangwon		377 16.1
A member of the household1147 49.0Busan/Ulsan/
Geongnam		429 18.3
Table
Table 3. Mean and standard deviation for each variable.
Table 3. Mean and standard deviation for each variable.
Online LectureOnline Meeting
Concerns about poor classes3.579
(0.808)		Concerns about poor meetings3.608
(0.750)
Decrease in concentration3.733
(0.915)		Decrease in concentration3.796
(0.932)
Q&A restrictions3.730
(0.913)		Difficulty in communicating3.720
(0.883)
Class uniformity3.620
(0.907)		Difficulty in conveying emotions3.653
(0.843)
Concerns about fragmentary classes3.635
(0.856)		Difficulty in preparing for a meeting3.638
(0.793)
Difficulty comparing with
other students		3.622
(0.852)		Increased meeting time3.569
(0.905)
Lack of instructor bonding3.615
(0.795)		Off-hours meeting3.585
(0.852)
Perceived usefulness3.673
(0.987)		Perceived usefulness3.667
(0.877)
Intention to use continuously3.637
(0.913)		Intention to use continuously3.701
(0.854)
Online seminarOnline performance
Concerns about poor seminars3.744
(1.088)		Concerns about poor performance3.719
(0.952)
Decrease in concentration3.832
(1.189)		Decrease in concentration3.840
(1.105)
Decline in presence3.908
(1.158)		Concerns about presence3.931
(1.034)
Concerns about difficulties
in networking		3.864
(1.138)		Concerns about networking3.826
(0.983)
Concern about the delivery of intentions3.810
(1.176)		Concerns about content quality3.823
(1.039)
One-way information transfer3.769
(1.112)		Concerns about information leakage3.785
(1.017)
Off-hours seminar3.828
(1.113)		Perceived usefulness3.701
(1.020)
Perceived usefulness3.791
(1.139)		Intention to use continuously3.729
(0.924)
Intention to use continuously3.788
(0.985)
Table
Table 4. Model Fit Analysis Results.
Table 4. Model Fit Analysis Results.
Online
Lecture Model		Online
Meeting Model		Online
Seminar Model		Online Performance Model
GFI0.9950.9830.9960.994
NFI0.9940.975 0.996 0.993
TLI0.9920.900 10.0060.988
CFI0.9990.98110.0000.997
Table
Table 5. Online Lecture Model.
Table 5. Online Lecture Model.
Online Lectures (Classes)Non-Standardization CoefficientStandardization CoefficientC.R.
Perceived usefulness ← Concerns about poor classes−0.014−0.012−0.184
Perceived usefulness ← Decrease in concentration−0.008−0.008−0.124
Perceived usefulness ← Q&A restrictions0.0950.0881.341
Perceived usefulness ← Class uniformity−0.078−0.073−1.142
Perceived usefulness ← Concerns about fragmentary classes0.1020.0901.376
Perceived usefulness ← Difficulty comparing with other students−0.145 *−0.126 *−1.883
Perceived usefulness ← Lack of instructor bonding0.0930.0761.272
Intention to use continuously ← perceived usefulness0.531 ***0.568 ***14.401
Note: *** Significant at 1% level, * Significant at 10% level.
Table
Table 6. Online Meeting Model.
Table 6. Online Meeting Model.
Online Meetings Related to Work and StudiesNon-Standardization CoefficientStandardization CoefficientC.R.
Perceived usefulness ← concerns about poor meetings−0.031−0.026−0.0384
Perceived usefulness ← decrease in concentration0.0060.0060.097
Perceived usefulness ← difficulty in communicating−0.111 *−0.112 *−1.679
Perceived usefulness ← difficulty in conveying emotions0.0320.0310.488
Recognized usefulness ← difficulty in preparing for a meeting−0.015−0.014−0.197
Perceived usefulness ← increased meeting time0.0920.0951.373
Perceived usefulness ← off-hours meeting0.216 ***0.210 ***2.928
Intention to use continuously ← perceived usefulness0.474 ***0.486 ***10.801
Note: *** Significant at 1% level, * Significant at 10% level.
Table
Table 7. Online Seminar Model.
Table 7. Online Seminar Model.
Online Seminar (Conference, etc.)Non-Standardization CoefficientStandardization
Coefficient		C.R.
Perceived usefulness ← concerns about poor seminars−0.218 **−0.208 **−2.010
Perceived usefulness ← decrease in concentration0.0640.0660.693
Perceived usefulness ← decline in presence0.0340.0350.362
Perceived usefulness ← concerns about difficulties in networking0.0310.0310.329
Perceived usefulness ← concern about the delivery of intentions0.1090.1131.183
Perceived usefulness ← one-way information transfer0.0210.0210.197
Perceived usefulness ← off-hours seminar0.1400.1361.483
Intention to use continuously ← perceived usefulness0.382 ***0.442 ***8.128
Note: *** Significant at 1% level, ** Significant at 5% level.
Table
Table 8. Online Performance Model.
Table 8. Online Performance Model.
Online PerformanceNon-Standardization CoefficientStandardization CoefficientC.R.
Perceived usefulness ← concerns about poor performance−0.015−0.013−0.163
Perceived usefulness ← decrease in concentration0.0460.0440.582
Perceived usefulness ← concerns of presence−0.154 *−0.137 *−1.768
Perceived usefulness ← concerns about networking0.1000.0861.122
Perceived usefulness ← concerns about content quality0.0560.0510.666
Perceived usefulness ← concerns about information leakage0.1220.1101.432
Intention to use continuously ← perceived usefulness0.295 ***0.331 ***6.602
Note: *** Significant at 1% level, * Significant at 10% level.
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Liu, H.; Lee, C.; Kim, K.; Lee, J.; Moon, A.; Lee, D.; Park, M. An Analysis of Factors Influencing the Intention to Use “Untact” Services by Service Type. Sustainability 2023, 15, 2870. https://doi.org/10.3390/su15042870

AMA Style

Liu H, Lee C, Kim K, Lee J, Moon A, Lee D, Park M. An Analysis of Factors Influencing the Intention to Use “Untact” Services by Service Type. Sustainability. 2023; 15(4):2870. https://doi.org/10.3390/su15042870

Chicago/Turabian Style

Liu, Hyunsuk, Changjun Lee, Keungoui Kim, Junmin Lee, Ahram Moon, Daeho Lee, and Myeongjun Park. 2023. "An Analysis of Factors Influencing the Intention to Use “Untact” Services by Service Type" Sustainability 15, no. 4: 2870. https://doi.org/10.3390/su15042870

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