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Article

Antecedents and Consequences of the Ease of Use and Usefulness of Fast Food Kiosks Using the Technology Acceptance Model

by
Joonho Moon
1,
Jimin Shim
2 and
Won Seok Lee
2,*
1
Department of Tourism Administration, Kangwon National University, Chuncheon 24341, Korea
2
Department of Tourism and Recreation, Kyonggi University, Seoul 03746, Korea
*
Author to whom correspondence should be addressed.
Systems 2022, 10(5), 129; https://doi.org/10.3390/systems10050129
Submission received: 23 July 2022 / Revised: 20 August 2022 / Accepted: 23 August 2022 / Published: 24 August 2022
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Abstract

:
The aim of this study is to investigate whether kiosk users’ characteristics can be explained by the technology acceptance model (TAM). Additionally, the goal of this research is to closely examine antecedents relevant to usefulness and ease of use. For the purposes of this study, the determinants of usefulness, degree of non-contact, time-saving efficiency, order accuracy, and ease of use were examined as important factors of kiosk design. The ease of use antecedents mainly consisted of payment and navigability. This study also attested to the relationships among a variety of TAM attributes: ease of use, usefulness, attitude, and intention to use. A survey was used to collect the majority of the data. Amazon Mechanical Turk was used for the recruitment of survey participants, and the number of valid observations was 346. A structural equation model was employed to test the study’s research hypotheses. It was found that time saving, order accuracy, and ease of use are positively associated with the level of usefulness. Ease of use is positively influenced by navigability, and attitude is positively determined by both ease of use and usefulness. Additionally, intention to use is positively impacted by both attitude and usefulness.

1. Introduction

Fast food kiosks have been widely used in fast food restaurants, as they provide buyers with an improved service experience, mainly through swifter orders, fewer crowds, and reliable service quality without human interaction [1,2]. Forbes [1] reported that 65 percent of fast food kiosk users prefer fast food stores that offer kiosk order technology. Given the market’s trends, it is worthwhile to understand why fast food kiosks have become increasingly popular in the market. Despite such importance in the market, previous research lacks empirical studies of fast food kiosk users’ characteristics. For instance, Ketimin and Shami [3] examined usefulness and ease of use as the main attributes to identify fast food kiosk users. Park et al. [4] researched how to improve user experience using the quality function development method. Lee [5] and Hamid [6] also implemented research to understand fast food kiosk user behaviors through user-related attributes: non-contact payment systems and waiting times. However, previous studies have limited research on fast food kiosk users’ motivation. To bridge this research gap, the purpose of this research is to explore fast food kiosk users’ characteristics.
The technology acceptance model (TAM) is the theoretical foundation of this research study to account for kiosk user behaviors; the TAM argues that ease of use, usefulness, attitude, and intention to use are the main attributes of technology users’ behaviors [7,8,9]. Many other studies have demonstrated the explanatory power of the TAM in various technology settings: mobile payment systems, hotel mobile applications, hotel kiosks, and online travel review systems [8,9,10,11]. Overall, they suggest that the TAM could be a powerful framework to account for different user behavior patterns when using technologies. However, the TAM model’s accountability has been insufficiently demonstrated in the area of fast food kiosk service. This explanatory power provided by the TAM leads us to adopt the model as the theoretical underpinning of this work.
The extant literature has demonstrated that the benefits of using fast food kiosk systems mainly stem from greater order accuracy and lower waiting times [6,12,13,14,15]. Additionally, Insider [16] and Moon et al. [17] presented the argument that coronavirus (COVID-19) changed food consumption patterns greatly, which caused an increase in the value of greater non-contact services, as kiosks have been strongly regarded as a solution to reduce human interactions in restaurant service. However, Insider [16] and Ooi and Tan [18] also noted that the complexity of the payment system may be a downside of kiosk technology usage, and the UX Collective [19] and Naqvi et al. [20] showed that the difficulty in searching for necessary information could present barriers to commercial kiosk usage from the perspective of consumers. All things considered, this research designates non-contact, time saving, order accuracy, easy payment, and navigability as the major antecedents of the TAM’s main variables: ease of use and usefulness. In sum, this study demonstrates the explanatory power of the TAM and identifies the antecedents of ease of use and usefulness. Such efforts are likely to expand the area of the TAM by inspecting possible determinants of its main variables (e.g., ease of use and usefulness).
The results may offer a source of empirical evidence for whether the attributes substantially impact fast food kiosk users’ appraisal of usage satisfaction. This study sheds light on the literature by demonstrating the usage of the TAM in the domain of fast food kiosk research. Additionally, revealing the influential antecedents of usefulness and ease of use could serve as another academic contribution of this research, as it could present an opportunity to understand fast food kiosk users’ characteristics in a more in-depth manner. Moreover, this research could also help the management of fast food kiosk technology service providers to develop better long-term service for users, which could eventually result in increased overall competitiveness within the market.

2. Literature Review and Theoretical Foundations

2.1. Fast Food Kiosk

A fast food kiosk refers to a device for food service; consumers can order food by themselves using the kiosks at fast food restaurants [21,22]. Prior works have noted that fast food kiosks enable customers to minimize mistakes in ordering because they do not require verbal communication [3,5]. Moreover, consumers are likely to reduce contact with employees by using the kiosk system, which has improved the service experience of customers during COVID-19 by minimizing contact between consumers and service staff [4,21]. Because the fast food industry faces heavy competition, fast food businesses have eagerly adopted the system, as it builds competitive advantage by replacing human service staff [23,24]. Moreover, fast food system manufacturers dedicate their resources to offering easier systems because difficult systems for handling have difficulty surviving in competitive markets [4,22].

2.2. Technology Acceptance Model (TAM)

The technology acceptance model (TAM) is a commonly adopted theoretical framework that is used to analyze and understand users’ behaviors toward a certain technology type. The TAM documents the associations among ease of use, usefulness, attitude, and intention to use [7,25]. Many studies have been performed with the TAM to understand user behavior [8,10]. In the TAM, ease of use positively impacts both usefulness and attitude, as any difficulty in controlling a certain technology becomes a cost from the users’ perspective. Huang et al. [9] presented the accountability of the TAM within the area of hotel mobile application services. Go et al. [26] attested to the explanatory power of the TAM within robot systems that have been used in the hospitality and tourism domains, and the study also demonstrated the accountability of the TAM for user behaviors. Assaker [8] explored and validated how the TAM is broadly applicable for user-generated content in online travel review systems. Kim and Qu [10] employed the TAM as their theoretical underpinning to understand the experience of hotel kiosk users.
Usefulness is likely to be determined by the attributes that produce and influence a technology’s utility to users. First, the domain of fast food kiosks could become more non-contact. Because of the current COVID-19 pandemic, individuals value safety more, and minimizing human interaction can lower the likelihood of infection [17,27,28,29]. This trend encourages customers to use those instruments that prioritize non-contact with service employees [28,29,30,31], and fast food kiosks could become such a method for non-contact consumption. In fact, numerous studies have found a positive effect of non-contact systems on favorable consumer behavior. More specifically, Lee and Lee [27] alleged that non-contact methods provide a new service strategy to increase competitive advantage by increasing the utility for users. Bae and Chang [30] emphasized non-contact characteristics within the service domain for the purpose of risk minimization in product consumption. Moon et al. [17] revealed the positive effects of non-contact airline services and how this caused a positive client reaction. Given the review of the literature, we propose the following research hypothesis:
H1. 
Non-contact positively affects usefulness.
The next factor of this study is time saving, which could become one of the main merits of fast food consumption, as fast food specifically allows customers to save time by shortening the time spent cooking, waiting, and eating [32,33,34]. It can thus be further inferred that saving time is an essential factor that customers prioritize when choosing to consume fast food. A vast body of literature has documented that time saving brings about positive consumer behavior outcomes. For instance, Abroud et al. [35] showed that e-financing system users’ main motivation centered upon saving time because time is a resource from the perspective of service users. Flett et al. [36] and Yang and Yoo [37] contended that individuals adopt technology for the purpose of saving their time because time is a resource that ultimately enhances their productivity. Wei et al. [38] demonstrated that Chinese clothing shoppers used online clothing shopping systems because they were able to save time by using the technology. It can be inferred that time saving could provide users with utility in consumption. Therefore, this research proposes the following hypothesis:
H2. 
Time saving positively affects usefulness.
According to Kimes [39], order accuracy determines the overall impression of customers within the restaurant industry, as inaccurate service delivery is recognized as a service failure. Along a similar vein, Collier and Bienstock [40] stated that inaccurate product delivery within the restaurant business is considered a serious service failure. Utama et al. [41] documented that the merit of kiosks in the food service industry is that they enhance the accuracy of ordering by offering greater visual information about the products for sale. Although few studies have inspected the association between order accuracy and customer reaction types, it could be inferred by the reverse aspect that service failure, such as inexact order delivery, would cause negative consumer appraisal [29,42,43]. Given the review of the literature, this research hypothesizes the following:
H3. 
Order accuracy positively affects usefulness.
The extant literature suggests that difficulty with using technology discourages users, so scholars have proposed that offering an uncomplicated system for consumers to handle at the main purchasing stage, such as during the time of payment, plays a particularly significant role for the survival of technology in the context of commercialization [11,44,45]. Indeed, numerous studies have displayed that the easy payment system is the main function of ease of use within various domains, including mobile payment [11,46] and the e-wallet system [47]. Ooi and Tan [18] have also argued that providing an easy payment system is imperative within the area of smartphone credit card technology because complexity in a payment system could discourage customers from choosing a certain product or service. Ozturk [48] also claimed that an easy payment system is the core attribute in the area of hospitality service purchasing. Hence, this study proposes the following research hypothesis:
H4. 
Easy payment positively affects ease of use.
The next attribute to determine the ease of use is navigability, which refers to the overall design of information technology when consumers are searching for desired information [49,50]. Shephard and Pookulangara [51] stated that navigability is the most fundamental element within the domain of museum service technology. Kimiagari and Malafe [52] also demonstrated that navigability is a core element for positive user appraisal in online purchasing, because offering information is the main function of technology. Zhao et al. [53] performed a meta-analysis and asserted that navigability is an important element for technology users, as it generally allows users to easily access necessary information, because effort can be regarded as a sort of searching cost from the perspective of consumers. Naqvi et al. [20] demonstrated a positive association between navigability and ease of use within the area of a web-based transaction system. Based on the review of the literature, we propose the following research hypothesis:
H5. 
Navigability positively affects ease of use.
The TAM is composed of four main elements: ease of use, usefulness, attitude, and intention to use [9,54,55]. Ease of use refers primarily to how easy the system is to control, usefulness stands for how the technology enhances the overall service experience, attitude refers to the degree to which users like a certain technology, and intention to use denotes how likely technology users are to select the system for their product purchase [54,55,56,57]. Scholars have also posited relationships among these variables. Overall, ease of use exerts positive impacts on both usefulness and attitude, as the complexity of controlling the system presents an obstacle and is costly from the viewpoint of users [9,26,56]. Usefulness exerts a positive effect on both attitude and intention to use, as recognized helpfulness makes users appraise the technology more positively [9,10,26]. Next, a positive attitude increases the probability of users’ intention to use in accordance with the TAM [7,56,58]. With respect to the literature review of studies analyzing the TAM, this research proposes the following hypotheses:
H6. 
Ease of use positively affects usefulness.
H7. 
Usefulness positively affects attitude.
H8. 
Usefulness positively affects intention to use.
H9. 
Ease of use positively affects attitude.
H10. 
Attitude positively affects intention to use.

3. Method

3.1. Research Model and Data Collection Methods

Figure 1 presents the research model, in which there are nine attributes. The antecedents of usefulness include non-contact, time saving, order accuracy, and ease of use. Ease of use is influenced by easy payment and navigability, and the determinants of attitude are ease of use and usefulness. Lastly, intention to use is affected by attitude and usefulness. Ten research hypotheses are proposed in the scope of this research project, and the directions of all relationships are positive.
This study used Amazon Mechanical Turk (https://www.mturk.com) (accessed on 1 February 2022) to recruit respondents by offering financial compensation. The sampling becomes simple random sampling because all Amazon Mechanical Turk panels had the same likelihood of participation [59]. The survey was conducted in a self-reported manner. Amazon Mechanical Turk has been commonly chosen in many studies as a data collection instrument, as the data quality is assured to maintain sound statistical inferences [60,61,62,63]. Given this assurance, this study was based on data obtained through Amazon Mechanical Turk, and the period of data collection was between 1–3 February 2022, with a total of 390 collected observations. Over the course of the survey, participants were asked whether they had experience using kiosks in fast food systems and were offered binary options (yes or no). Then, this research eliminated 44 observations, mainly the survey participants who had no experience with kiosk usage. Consequently, the number of valid observations for statistical analysis was 346.

3.2. Depiction of Measurement Items

This research mainly implemented the Likert five-point scale (1 = strongly disagree, 5 = strongly agree) except when measuring attitude, which is also measured by a five-point scale (e.g., 1 = negative, 5 = positive). To measure non-contact [17,30] and navigability [20,51,52], this study reviewed information from the extant literature and modified it for the purposes of the current study. Additionally, the factors of time saving, order accuracy, and easy payment were measured by consulting with three hospitality and tourism experts working within the field of academia. For the measurement of the TAM attributes (i.e., usefulness, ease of use, attitude, and intention to use), this research referenced a host of previous studies and selected the items suitable for this current study’s research goals [8,9,10,26,56]. Nine constructs were produced: non-contact, time saving, order accuracy, easy payment, navigability, usefulness, ease of use, attitude, and intention to use, and four items were used to build each construct. Table 1 presents and describes the measurement items.

3.3. Data Analysis

To start, a frequency analysis was carried out to attain the demographic profile of the survey participants. A confirmatory factor analysis, a correlation matrix, and a structural equation model were executed to ensure the validity of the measurements and to test the proposed hypotheses. Factor loadings (threshold: 0.5), average variance extraction (threshold 0.5), and construct reliability (threshold: 0.7) were checked for convergent validity (Fornell and Larcker, 1981; Hoyle, 1995; Hair et al., 2010). This study also followed the rule whereby the square root of the average variance extracted is greater than that of the correlation coefficient to appraise discriminant validity [59,64,65]. To test the hypotheses, this study carried out a path analysis using a p value of 0.05 as the criterion. Next, multiple indices were all assessed to examine the overall goodness-of-fit of the structural equation model, such as Q (CMIN/degree of freedom) < 3; RMR (root mean square residual) and RMSEA (root mean square error of approximation) < 0.05; and GFI (goodness-of-fit index), NFI (normed fit index), RFI (relative fit index), IFI (incremental fit index), TLI (Tucker–Lewis index), and CFI (comparative fit index) > 0.8 [59,64,65]. Moreover, previous literature has demonstrated that more than 300 observations are adequate to ensure statistical power in a structural equation model analysis [59,66].

4. Results

4.1. Descriptive Statistics

Table 2 presents the demographic information, with the number of valid observations measuring 346. Among survey participants, the proportion of males was 60.4 percent, and the proportion of employed people was 85.5 percent. In terms of average age, 102 individuals were in their 20 s or younger, 13 were in their 30 s, 58 were in their 40 s, 33 were in their 50 s, and 20 were older than 60. Table 2 also presents the information on the survey participants’ monthly household income (less than USD 2000: 70, USD 2000–4000: 97, USD 4000–6000: 75, USD 6000–8000: 69, and more than USD 8000: 65) and weekly kiosk usage frequency (less than 1 time: 111, 1–2 times: 148, 3–5 times: 57, and more than 5 times: 30).

4.2. Confirmatory Factor Analysis and the Correlation Matrix

Table 3 exhibits the mean and standard deviations of the measurement items, which also describes the mean value range of the study variables: non-contact (4.07–4.15), time saving (3.80–4.03), order accuracy (3.98–4.04), easy payment (4.02–4.18), navigability (4.00–4.16), ease of use (4.18–4.24), usefulness (3.93–4.04), attitude (4.08–4.18), and intention to use (3.96–4.08). Additionally, Table 3 shows the results of the confirmatory factor analysis. The average variance extracted, factor loading, and construct reliability values are all greater than the cutoff value. The results of the confirmatory factor analysis are substantial based on the goodness-of-fit indices (χ2 = 1313.727, df = 574, Q(χ2/df) = 2.289, RMR = 0.042, GFI = 0.830, NFI = 0.895, RFI = 0.884, IFI = 0.938, TLI = 0.931, CFI = 0.937, and RMSEA = 0.061). The overall values of CR and loading indicate convergent validity.
Table 4 illustrates the correlation matrix, and overall, the diagonal values are greater than the correlation coefficients, which implies that the discriminant validity of the measurement model can be ensured. Intention to use positively correlates with non-contact (r = 0.648), time saving (r = 0.800), order accuracy (r = 0.691), easy payment (r = 0.722), and navigability (r = 0.826). Additionally, attitude positively correlates with non-contact (r = 0.655), time saving (r = 0.817), order accuracy, (r = 0.699), easy payment (r = 0.761), and navigability (r = 0.811). Plus, certain correlation coefficients are between 0.8 and 0.9, which suggests that the model is likely to be undermined multi-collinearity. The overall discriminant validity of this work could be acceptable, even though certain items could not meet the criteria. It is marked as bold in Table 4.

4.3. Results of Hypothesis Testing

Figure 2 describes the results of the hypothesis testing. The goodness-of-fit indices implied that the results of the structural equation modeling were acceptable overall (χ2 = 1312.419, df = 574, Q(χ2/df) = 2.286, RMR = 0.042, GFI = 0.829, NFI = 0.893, RFI = 0.883, IFI = 0.937, TLI = 0.931, CFI = 0.937, and RMSEA = 0.061). Regarding the coefficients, usefulness is positively determined by time saving (β = 0.437, p < 0.05), order accuracy (β = 0.086, p < 0.05), and ease of use (β = 0.493, p < 0.05). Ease of use is in turn positively impacted by navigability (β = 0.665, p < 0.05). Attitude is positively affected by ease of use (β = 0.175, p < 0.05) and usefulness (β = 0.848, p < 0.05), while intention to use is positively associated with usefulness (β = 0.822, p < 0.05) and attitude (β = 0.254, p < 0.05). Certain correlation coefficients are greater than 0.8 concerning the multi-collinearity problem in the path coefficient. However, all coefficients are less than 1, which implies that multi-collinearity is less likely to undermine the estimation for the coefficient. In sum, all hypotheses other than H1 and H4 are supported by the results of the analysis.

5. Discussion

This research inspected kiosk users by using the TAM, and the results of testing indicate that kiosk users perceived increased usefulness when saving time, minimizing errors in order processing, and controlling the kiosk without difficulty. Regarding magnitude, ease of use exerted the strongest effect on usefulness when compared to other attributes. Additionally, time saving was more influential on usefulness than order accuracy, and it can be inferred that fast food kiosk users value saving time the most, as the main point of fast food is to save time. However, non-contact methods appeared to be a nonsignificant attribute when determining the degree of usefulness. This could be explained by the very nature of a fast food business, which is a limited service restaurant. Namely, interactions with employees might not be the most crucial aspect from the perspective of fast food consumers, as the business model already provides few interactions with service employees. In terms of ease of use, the results suggest that navigability was identified as the most essential element. However, ease of payment exerted a nonsignificant effect on ease of use. As a result, it is possible that customers of the food service industry have already become used to the kiosk easy payment system in various domains, such as in food courts and within food delivery service apps; therefore, customers in the food service industry may not perceive any further difficulty for payment systems. That is, fast food kiosk users may in fact take easy payment systems for granted. Thus, offering an easy payment system may not be crucial to build further competitive advantage in the market. Next, kiosk users’ positive attitudes were established by offering usefulness and a system that was easy to control. Lastly, the intention to use the kiosk is elevated by usefulness and a positive attitude. In terms of the intention to use and attitude, the magnitude of usefulness exerted the strongest impact among the attributes, including ease of use and attitude.

6. Conclusions

6.1. Theoretical and Practical Implications

This study contributes to the literature in multiple ways. First, this research noted the determinants of usefulness and ease of use by inspecting the opinions and behavioral patterns of fast food kiosk users. This study proposed five attributes as antecedents of the TAM, and it is found that three attributes (e.g., time saving, order accuracy, and navigability) out of the five significantly accounted for the psychological mechanisms of fast food kiosk users. This study also contributes to the literature by demonstrating the accountability of the TAM for kiosk user behaviors, mainly by uncovering the significant linkages among four attributes, i.e., ease of use, usefulness, attitude, and intention to use. These results could then be used to externally validate the findings of prior studies, mainly through the reporting of significant relationships among the four attributes: ease of use, usefulness, attitude, and intention to use [8,9,10,26,56].
This study has practical implications. First, fast food kiosk management companies might be able to focus more closely on the fast food kiosk system when strategizing how to save users’ time, increase order accuracy, and offer better navigability and a more straightforward system to control. Such an effort may play a significant role in attaining a higher utility of fast food kiosks for users, which would result in attaining a greater market share. To achieve more efficient resource allocation, managers could use the results of this research to set their priorities accordingly. In terms of usefulness, offering an easier and more detailed system might be of foremost importance, and providing systems that enable fast food kiosk users to save time may become the second most crucial area for budgeting. In addition, fast food kiosk service managers could contemplate how to best provide an easier system (ease of use) and to enhance working efficiency related to the users’ service experience (usefulness), as this is associated with usefulness, attitude, and intention to use. Next, fast food kiosk providers may need to further consider how to build positive attitudes toward their businesses. More positive attitudes could be formed through better brand marketing and the implementation of corporate social responsibility for their core stakeholders. Lastly, fast food kiosk providers can use this research to allot resources in a more efficient manner, which could be achieved by concentrating more closely on enhancing the usefulness of the system, as usefulness is a more powerful attribute for intention to use than attitude is.

6.2. Limitations

This study has a few limitations, as the scope of this research was constrained to the study of fast food kiosks. The kiosk system is used in various areas, such as at transportation service stations and in food courts. It could also be useful to investigate the characteristics of users in different domains of the food service business, such as casual dining restaurants and cafés. Future studies may consider other areas for the implementation of this research. Additionally, this study was limited to determining the main effects of using the TAM, and future research is likely to understand the moderating effects of using the TAM. Such efforts may further extend the literature through a more nuanced understanding of user characteristics. Moreover, this study had a high percentage of male survey participants, which is likely to lead to biased results. Future research thus needs to consider collecting data that balances gender. Additionally, Al-Emran and Granić [67] claimed that the TAM could be an outdated framework. Given this argument, future research might consider other theoretical underpinnings to determine user behaviors for fast food kiosks.

Author Contributions

Formal analysis, J.S.; Supervision, W.S.L.; Writing–original draft, J.M. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

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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Systems 10 00129 g001 550
Figure 1. Research model.
Figure 1. Research model.
Systems 10 00129 g001
Systems 10 00129 g002 550
Figure 2. Results of hypothesis testing.
Figure 2. Results of hypothesis testing.
Systems 10 00129 g002
Table
Table 1. Illustration of measurement items.
Table 1. Illustration of measurement items.
ConstructCodeItem
Non-contactNC1The self-service kiosk at the fast food restaurant helped non-contact consumption.
NC2The self-service kiosk at the fast food restaurant enabled consumption without employee contact.
NC3The self-service kiosk at the fast food restaurant enabled me to consume without employee contact.
NC4The self-service kiosk at the fast food restaurant was a tool for non-contact consumption.
Time savingTS1The self-service kiosk at the fast food restaurant was good for saving time.
TS2I could save time by using the self-service kiosk at a fast food restaurant.
TS3The self-service kiosk at the fast food restaurant reduced the waiting time for food.
TS4The time spent obtaining food was decreased by using the self-service kiosk at fast food restaurant.
Order accuracyOA1The self-service kiosk at the fast food restaurant made my order more precisely.
OA2I could make a more accurate order by using the self-service kiosk at the fast food restaurant.
OA3The self-service kiosk at the fast food restaurant enhanced the accuracy of the food order.
OA4The self-service kiosk at the fast food restaurant minimized the error in making a food order.
Easy paymentEP1It was easy to pay at the self-service kiosk at the fast food restaurant.
EP2The self-service kiosk at the fast food restaurant had a payment system that was not difficult.
EP3Payment at the self-service kiosk at the fast food restaurant was uncomplicated.
EP4I could pay effortlessly at the self-service kiosk at the fast food restaurant.
Navigability NA1It was easy to navigate the self-service kiosk at the fast food restaurant.
NA2It was simple to find the menu at the self-service kiosk at the fast food restaurant.
NA3It was effortless to find the product information at the self-service kiosk at the fast food restaurant.
NA4The self-service kiosk at the fast food restaurant was easy to navigate.
Ease of useEU1The self-service kiosk was easy to use.
EU2It was straightforward to use the self-service kiosk.
EU3The self-service kiosk was a simple system to use.
EU4For me, it was straightforward to control the self-service kiosk.
UsefulnessUF1Using the self-service kiosk allowed me to obtain the food speedily at the fast food restaurant.
UF2Using the self-service kiosk enabled me to attain the product more quickly at the fast food restaurant.
UF3Using the self-service kiosk improved my product purchasing experience at the fast food restaurant.
UF4Using the self-service kiosk enhanced the effectiveness of buying goods at the fast food restaurant.
AttitudeAT1The self-service kiosk at fast food restaurant is (Negative–Positive)
AT2The self-service kiosk at fast food restaurant is (Unattractive–Attractive)
AT3The self-service kiosk at fast food restaurant is (Unfavorable–Favorable)
AT4The self-service kiosk at fast food restaurant is (Bad–Good)
Intention to useIU1I intend to use the self-service kiosk at fast food restaurants.
IU2I am going to use the self-service kiosk at fast food restaurants.
IU3The self-service kiosk will be chosen for my shopping at fast food restaurants.
IU4I will use the self-service kiosk at fast food restaurants.
Table
Table 2. Profile of survey participants (N = 346).
Table 2. Profile of survey participants (N = 346).
ItemFrequencyPercentage
Male20960.4
Female13739.6
20 s or younger10229.5
30 s13338.4
40 s5816.8
50 s339.5
Older than 60205.8
Unemployed5014.5
Employed29685.5
Monthly household income
Less than USD 20007020.2
USD 2000~USD 39999728
USD 4000~USD 59997521.7
USD 6000~USD 79996911.3
More than USD 80006518.8
Weekly kiosk using frequency
Less than 1 time11132.1
1~2 times14842.8
3~5 times5716.5
More than 5 times308.7
Table
Table 3. Illustration of measurement items.
Table 3. Illustration of measurement items.
Construct
(AVE)		CodeMeanSDLoadingCR
Non-contact
(0.673)		NC14.150.980.7230.673
NC24.070.970.881
NC34.0910.859
NC44.090.970.809
Time saving
(0.697)		TS14.031.060.870.697
TS24.021.060.864
TS33.891.130.807
TS43.81.10.795
Order accuracy
(0.668)		OA13.981.040.8010.668
OA24.041.020.827
OA34.0110.841
OA44.011.020.799
Easy payment
(0.706)		EP14.180.970.8440.706
EP24.121.020.825
EP34.021.070.827
EP44.11.030.865
Navigability
(0.702)		NA14.041.010.8870.702
NA24.160.940.814
NA340.990.796
NA44.0410.85
Ease of use
(0.728)		EU14.240.810.880.728
EU24.220.860.823
EU34.210.90.866
EU44.180.890.843
Usefulness
(0.679)		UF14.0410.820.679
UF24.021.010.793
UF33.931.040.839
UF43.980.990.844
Attitude
(0.794)		AT14.140.960.9070.794
AT24.080.990.845
AT34.160.990.903
AT44.180.960.908
Intention to use
(0.779)		IU14.051.060.8760.779
IU24.081.030.901
IU33.961.060.865
IU44.081.020.888
Note: AVE denotes the average value extracted, CR stands for construct reliability, and SD denotes standard deviation. χ2 = 1313.727 df = 574 Q(χ2/df) = 2.289 RMR = 0.042 GFI = 0.830 NFI = 0.895 RFI = 0.884 IFI = 0.938 TLI = 0.931 CFI = 0.937 RMSEA = 0.061.
Table
Table 4. Correlation matrix.
Table 4. Correlation matrix.
123456789
1.Non-contact0.820
2.Time saving0.686 *0.835
3.Order accuracy0.588 *0.687 *0.817
4.Easy payment0.676 *0.693 *0.626 *0.840
5.Navigability0.646 *0.729 *0.724 *0.859 *0.838
6.Usefulness0.687 *0.882 *0.709 *0.745 *0.776 *0.824
7.Ease of use0.605 *0.696 *0.631 *0.713 *0.823 *0.830 *0.853
8.Attitude0.655 *0.817 *0.699 *0.761 *0.811 *0.877 *0.815 *0.891
9.Intention to use0.648 *0.800 *0.691 *0.722 *0.826 *0.908 *0.870 *0.886 *0.883
Note: * p < 0.05, Diagonal is square root of AVE.
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Moon, J.; Shim, J.; Lee, W.S. Antecedents and Consequences of the Ease of Use and Usefulness of Fast Food Kiosks Using the Technology Acceptance Model. Systems 2022, 10, 129. https://doi.org/10.3390/systems10050129

AMA Style

Moon J, Shim J, Lee WS. Antecedents and Consequences of the Ease of Use and Usefulness of Fast Food Kiosks Using the Technology Acceptance Model. Systems. 2022; 10(5):129. https://doi.org/10.3390/systems10050129

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Moon, Joonho, Jimin Shim, and Won Seok Lee. 2022. "Antecedents and Consequences of the Ease of Use and Usefulness of Fast Food Kiosks Using the Technology Acceptance Model" Systems 10, no. 5: 129. https://doi.org/10.3390/systems10050129

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