THE UNIVERSITY OF DANANG UNIVERSITY OF ECONOMICS TRAN THI THU DUNG THE RESEARCH ON TRAVELERS'''' CONTINUANCE INTENTION TO USE MOBILE TOURISM APPS THE CASE OF ONLINE TRAVEL AGENCIES'''' APPS ON MOBILE DEVICE[.]
THE UNIVERSITY OF DANANG UNIVERSITY OF ECONOMICS TRAN THI THU DUNG THE RESEARCH ON TRAVELERS' CONTINUANCE INTENTION TO USE MOBILE TOURISM APPS: THE CASE OF ONLINE TRAVEL AGENCIES' APPS ON MOBILE DEVICES SUMMARY OF DOCTORAL THESIS DA NANG - 2023 THE UNIVERSITY OF DANANG UNIVERSITY OF ECONOMICS TRAN THI THU DUNG THE RESEARCH ON TRAVELERS' CONTINUANCE INTENTION TO USE MOBILE TOURISM APPS: THE CASE OF ONLINE TRAVEL AGENCIES' APPS ON MOBILE DEVICES MAJOR: BUSINESS ADMINISTRATION CODE: 934.01.01 SUMMARY OF DOCTORAL THESIS Supervisor: ASSOC.PROF.DR LE VAN HUY DA NANG - 2023 INTRODUCTION Research background The urgency of the research topic Nowadays, mobile apps are widely adopted because they have provided a great number of benefits From a business perspective, mobile apps are valuable tools to reach potential customers and trigger travelers’ needs (Liang et al., 2017) For travelers, these apps allow searching for information, accommodation, transportation, and booking services at any time (Liu et al., 2020) The applications contribute to enhancing travelers’ experiences by providing them with a wide range of functions, quick response with high reliability, and high context adaptability (Kirova & Vo Thanh, 2019) Mobile tourism apps are one of the mobile technologies of interest to researchers because they have a strong impact on travelers’ behavior (Tan et al., 2017b); and its importance to tourism businesses (Lamsfus et al., 2015) In fact, mobile apps are often associated with smart destinations (Lamsfus et al., 2015), therefore, they are effective tools to promote the destinations (Fernández-Cavia et al., 2017) and create destination attachment (Kuo et al., 2019; Zhang et al., 2021) Moreover, mobile tourism apps have a significant role in enhancing perceived destination image (Kirova & Vo Thanh, 2019; Zhang et al., 2021) For online travel agencies (OTA), the mobile app is one of the key components (Kustiwi, 2018) However, only nearly half of tourism apps are retained on mobile devices after first use (Linton, & Kwortnik, 2015) Meanwhile, the initial technology acceptance is only for a successful adoption of a new technology (Bhattacherjee et al., 2008), long-term viability and ultimate success depend on users’ continuance intention to use (Bhattacherjee, 2001; Fong et al., 2017) The majority of existing studies focus on the technology acceptance or adoption (Kirova & Vo Thanh, 2019) This leaves a scarcity of research on post-adoption behavioral intention (Jeong & Shin, 2020; Liebana-Cabanillas et al., 2020) Research on post-adoption behavioral intention is critical because it related to user satisfaction, and leading to users’ continuance intention to use or not in the future (Bhattacherjee, 2001a) On the other hand, the mobile app usability (MAU) is the key to successful development of mobile apps (Hussain & Omar, 2020); and positively influences the continuance intention to use the app (Hoehle & Venkatesh, 2015; Tan et al., 2020) In the tourism context, it is necessary to improve the MAU to ensure that travelers’ expectations for tourism apps can be achieved However, the existing research models on the MAU are still inconsistent and have not enabled specific improvements and developments regarding the apps’ design and interface (Tan et al., 2020) Furthermore, although the relationship between MAU and continuance intention to use has been established in some studies, there are few studies focusing on the mechanisms underlying this relationship (Ozturk et al., 2016; Tarute et al., 2017) Scholars have suggested that further research to understand the dynamics of the relationship is crucial (Hoehle & Venkatesh, 2015; Ozturk et al., 2016; Tarute et al., 2017) Meanwhile, satisfaction and perceived usefulness were considered as determinants of behavioral intention at the postadoption stage (Bhattacherjee, 2001; Liu et al., 2020) In addition, confirmation is also a factor affecting users' perceived usefulness, satisfaction, and continuance intention to use technology; however, most studies consider this factor as the aggregate level (Bhattacherjee, 2001b) This factor should be considered in specific aspects However, to the best of our knowledge, there has been no research on the role of two variables (perceived usefulness and satisfaction) in the relationship between Confirmation of MAU and continuance intention to use Research on this topic is critical as it helps better capture mobile apps attributes that may enhance positive travelers’ experiences (Chea & Luo, 2008), thereby initiates continuance intention to use as well as enables to promote the destinations (Kuo et al , 2019; Zhang et al , 2021) To fill in the above research gaps, it is necessary to conduct “The research on travelers' continuance intention to use mobile tourism apps: The case of online travel agencies' apps on mobile devices” Research questions: Four research questions were proposed Research objectives The main objective of the thesis is to extend the previous research of Bhattacherjee (2001b) and Hoehle & Venkatesh (2015b) into the context of mobile tourism application to examine the impact of confirmation of mobile tourism app usability, travelers’ perceived usefulness, and satisfaction on travelers’ continuance intention to use the Online Travel Agencies’ apps Object and scope of the research Object of the research: the impact of mobile tourism app usability on travelers’ perceived usefulness, travelers’ satisfaction and continuance intention to use OTAs’ app Participants are Vietnamese domestic travelers who have used an online travel agencies’ apps for travel purposes Data collection was conducted through an online survey from 7/2020 to 5/2021 Research methods: Quantitative and qualitative methods were applied for this study New contribution of the research - This study extended the concept “confirmation” out of the information system boundary by putting it in the context of tourism and specifying the constituting dimensions - The thesis researched the relationship between the dimensions of confirmation of mobile tourism app usability and travelers' continuance intention to use tourism app according to the process of consumer behavior: cognitive - affective - behavioral intention The cognitive component was enriched by combining the two research concepts - This study examined the mediation and serial mediation role of perceived usefulness and satisfaction in the relationship between confirmation of mobile tourism app usability and continuance intention to use This helped to broaden understanding of the affective component of the behavioral process - The study offered practical implications for app developers, tourism providers, and policymakers, especially OTAs, to encourage travelers' continuance intention to use mobile tourism apps Structure of the thesis The thesis consists of five chapters: Chapter Literature review; Chapter Research model building; Chapter Research Methodology; Chapter Research results; Chapter Discussing the research results and implications CHAPTER LITERATURE REVIEW Chapter introduction 1.1 Continuance intention to use 1.1.1 The concept of continuance intention to use technology Continuance intention to use is users’ intention to continue using an information system after its initial acceptance (Bhattacherjee, 2001b) 1.1.2 The role of continuance intention to use technology This is a predictor and determinant of users’ behavior in using technology (Kim et al., 2013; Bhattacherjee, 2001a) The ultimate success of new technology depends on users' continuance intention to use; and user discontinuation may lead to many business consequences, such as financial impact (Bhattacherjee, 2001b) 1.2 Mobile tourism app 1.2.1 The concept of mobile tourism app Mobile tourism apps are the apps that are downloaded, installed, and used by travelers on mobile devices for travel purposes (Tan et al., 2017a) 1.2.2 The role of mobile tourism app - In terms of travelers, the apps support many functions for travel purposes (Wang et al., 2016); and allow service ratings based on their experience (Banerjee & Chua, 2016) - In terms of tourism business, the apps help to easily reach potential customers (Brown & Chalmers, 2003); and to increase travelers' satisfaction and engagement with tourism services and destinations (Buhalis & O’Connor, 2005; Wang et al., 2012b) 1.2.3 Classification of mobile tourism app: Kennedy-Eden & Gretzel (2012) classifies mobile tourism apps into seven categories according to functionality 1.2.4 Online Travel Agencies’ App (OTA) is an intermediary that sells travel services through online channels such as Web sites, Web apps, mobile apps; and all transactions are conducted online (Wang & Xiang, 2012) Mobile tourism apps are one of the important dimensions of OTA (Kustiwi, 2018), and some popular mobile apps of OTAs such as Booking.com, Agoda, Traveloka, Airbnb, 1.3 Introduction to research theory on behavioral intention to use technology In the study of behavioral intention, popular theories are often applied, such as The Cognitive-Affective-Behavioral intention Theory (Lavidge & Steiner, 1961), Theory of Reasoned Action TRA (Ajzen & Fishbein, 1980), Theory of Planned Behavior TPB (Ajzen, 1985), Technology Acceptance Model TAM (Davis, 1998), Expectation Confirmation Model ECM (Bhattacherjee (2001b), Unified Theory of Acceptance and Use of Technology UTAUT (Venkatesh et al., 2003), UsabilityContinuance Intention to Use Model Fits - UCMF (Hoehle & Venkatesh, 2015b) 1.4 Review of studies related to the research topic Currently, studies related to continuance intention to use mobile tourism apps are focused on the relationship between MAU, confirmation, perceived usefulness, satisfaction, continuance intention to use, etc However, few systematic studies have focused on the impact of mobile tourism app usability dimensions on continuance intention to use these apps through the mediating role of perceived usefulness and satisfaction In Vietnam, there is no research focused on this topic 1.5 Mobile tourism app usability 1.5.1 The concept of MAU MAU refers to the extent to which a particular user can use an app with efficiency and performance in a specific context (Hoehle & Venkatesh, 2015b) 1.5.2 The role and theoretical models of MAU This is an important quality aspect that evaluates the ease of use of the user interface (Baharuddin et al., 2013); and is the key to successful mobile app development (Hussain & Omar, 2020) There are many research models of MAU developed by Coursaris & Kim (2011), Hornbæk & Law (2007), and Zahra et al., (2017) However, these models have not provided all the aspects that could help guide the improvement and development of app design and interface (Zahra et al., 2017) While the biggest challenge of mobile apps is the interface and its content and design (Zahra et al., 2017) Chapter summary CHAPTER RESEARCH MODEL BUILDING Chapter introduction 2.1 Background theory used in the study 2.1.1 Cognitive-Affective-Behavioral Intention Theory (CAB) 2.1.2 Expectation - Confirmation Model (ECM) 2.1.3 Usability - Continuance Intention to Use Model Fits (UCMF) 2.2 Proposed research model The research model is based on three fundamental theories, including the cognitive - affective - behavioral intention theory, the ECM model, and the UCMF model The built-in facility is the limitations of each model Figure 2.1 Research model Cognitive Affective Behavioral intention Perceived usefulness Confirmation of mobile app usability - App design - App utility - Interface graphics - Interface structure - Interface input - Interface output - App dependability Satisfaction with apps’ usage Continuance intention to use mobile tourism app 2.3 Definition of the research concepts 2.3.1 The dimensions of confirmation of mobile tourism app usability Confirmation of mobile tourism app usability as the travelers’ positive perception when evaluating the congruence between their expectations about the extent to which a mobile tourism app can be used to help them achieve their purposes accurately and efficiently, and its actual performance (adapted from Bhattacherjee, 2001; Lee et al., 2009; Hoehle & Venkatesh, 2015b) According to Hoehle & Venkatesh (2015) and Tan et al., (2020), MAU is a multidimensional concept, reflected in main dimensions: - App design (TKUD) is the degree to which users perceive that the app is designed well (Hoehle & Venkatesh, 2015), demonstrated through the ability to preserve the data that is entered by the user (Tan et al., 2009); the ability of the app launches quickly and allows users to instantly start using it, and the information to be displayed effectively works well independent of how the user holds the mobile device (Wobbrock et al., 2008); integrated branding effectively (Hoehle & Venkatesh, 2015) - App utility (TIUD) is the degree to which users perceive that the app serves its purpose well (Hoehle & Venkatesh, 2015b); demonstrated by the app focusing on the content that is most relevant to its users and emphasizing the main function (Venkatesh & Ramesh, 2006); easy to find information and navigate (Wells et al., 2005) - User interface structure (CTGD) is the degree to which users perceive that the app is structured effectively (Hoehle & Venkatesh, 2015b); that is, the app arranges and organizes information effectively in structuring from top-to-bottom (Hong et al., 2004; Wells et al., 2011) - User interface graphic (DHGD) is the degree to which a user perceives the apps’ interface graphics to be effectively designed (Hoehle & Venkatesh, 2015b); expressed through a combination of icons and actual images (Hong et al., 2004; Hess et al., 2005a); 10 aesthetically appealing graphics (Hess et al., 2005b; Wells et al., 2005) - User interface input (GDDV) is the degree to which a user perceives that the app allows for easy input of data (Hoehle & Venkatesh, 2015b) - User interface output (GDDR) is the degree to which users perceive that the app presents information effectively (Hoehle & Venkatesh, 2015b); technical terms are easy to understand and familiar to users (Hess et al., 2005b); contains standard elements that create familiarity (Jokela et al., 2006) - App dependability (DOOD) is the degree users perceive that the app can operate dependably from start to end of an app’s usage cycle (adapted from Tan et al., 2020) 2.3.2 Perceived usefulness is the user’s perceived functional benefits gained from mobile tourism apps use (adapted from Bhattacherjee, 2001b) 2.3.3 Satisfaction is the user’s overall evaluation of prior mobile tourism apps use experience (adapted from Bhattacherjee, 2001b) 2.4 Research hypothesis According to ECM, confirmation tends to heighten users' perceived usefulness of the technology (Bhattacherjee, 2001a) Confirmation positively affects users' perceived usefulness of mobile tourism apps (Garima & Sajeevan, 2019; Liu et al., 2020b) Islam et al (2017) and Brown et al (2008) recommend research on the confirmation variable in aspect-specific since expectations are formed from many individual dimensions and within the specific research context Therefore, we hypothesis 11 that: H1a,b,c,d,e,f,g: The confirmation of (a)TKUD, (b)TIUD, (c)DHGD, (d)CTGD, (e)GDDV, (f)GDDR, and (g)DOOD is positively associated with travelers’ perceived usefulness The higher users' confirmation, the higher users' satisfaction level (Lin et al., 2005b) Confirmation is positively related to satisfaction with using technology in general and mobile apps in particular (Liao et al., 2009; Lin et al., 2005; Thong et al., 2006; Bhattacherjee, 2001b Lin et al., 2005b) Thus, we propose that H2a,b,c,d,e,f,g: The confirmation of (a)TKUD, (b)TIUD, (c)DHGD, (d)CTGD, (e)GDDV, (f)GDDR, and (g)DOOD is positively associated with travelers’ satisfaction with apps’ usage A user who finds a particular technology useful is more likely to be satisfied with the technology's usage (Lee, 2010) Bhattacherjee (2001a) demonstrated perceived usefulness as one of the main determinants of continuance intention to use technology H3: Travelers’ perceived usefulness of mobile tourism app is positively associated with their satisfaction with apps’ usage H4: Travelers’ perceived usefulness of mobile tourism app is positively associated with continuance intention to use the app User satisfaction plays an important role in predicting future usage behavior intention (Sayyah Gilani et al., 2017); specifically have a significant effect on continuance intention to use from different points of view (Lin & Wang, 2006) H5: Travelers’ satisfaction with mobile tourism app usage is positively associated with continuance intention to use 12 According to ECM, perceived usefulness has an indirect effect on continuance intention to use through satisfaction, and that confirmation is positively associated with satisfaction via perceived usefulness (Bhattacherjee, 2001a) The mediating role of perceived usefulness and satisfaction in the relationship between confirmation and continuance intention to use technology, in general, has been mentioned in previous studies Filieri et al (2020), Garima & Sajeevan (2019), Liu et al (2020b) H6a,b,c,d,e,f,g: Travelers’ satisfaction with mobile tourism app usage mediates the relationships between confirmation of (a)TKUD, (b)TIUD, (c)DHGD, (d)CTGD, (e)GDDV, (f)GDDR, and (g)DOOD and continuance intention to use H7: Travelers’ satisfaction with mobile tourism app usage mediates the relationship between perceived usefulness and continuance intention to use H8a,b,c,d,e,f,g: Travelers’ perceived usefulness mediates the relationships between confirmation of (a)TKUD, (b)TIUD, (c)DHGD, (d)CTGD, (e)GDDV, (f)GDDR, and (g)DOOD and continuance intention to use Chapter summary CHAPTER RESEARCH METHODOLOGY Chapter introduction 3.1 Research paradigms: Positivistic paradigm was used in this study 3.2 Methodologies: The study used quantitative as the main method The research process had three main steps: Literature review → Pilot study → Main study 13 The study was based on the eight-step process of measuring the scale of Churchill (1979) Qualitative research included a review of related studies combined with in-deep interviews to form a draft scale Quantitative research included pilot study and main study The pilot study used Cronbach's Alpha, EFA to test the reliability of the scale; refine items; complete the scale and official questionnaire The main study included two parts: (1) scales were evaluated by Cronbach's alpha coefficients, EFA, CFA to confirm convergent validity, discriminant validity, composite reliability of scales; (2) the structural equation modeling method (SEM) was used to test hypotheses specified; Bootstrap method for verifying the sustainability of estimates in the model; Multigroup analysis method to test differentiation of the model according to individual characteristics This study used the 7point Likert scale to measure the research concepts 3.3 Scale of research concepts 3.3.1 Confirmation of mobile tourism app usability Adapted the scale from Hoehle et al (2015); Hoehle & Venkatesh (2015); Bhattacherjee (2001), Tan et al (2020b) and in-deep interviews results, conceptual scales included: Confirmation of TKUD: 07 items; TIUD: 06 items; ĐOOĐ: 05 items; DHGD: 04 items; CTGD: 05 items; GDDV: 05 items; and GDDR: 05 items 3.3.2 Perceived usefulness: Nine items were adapted from Choi (2018) 3.3.3 Satisfaction: Four items were adapted from Patterson & Spreng (1997); Bhattacherjee (2001) 14 3.3.4 Continuance intention to use: Four items were adapted from Patterson & Spreng (1997); Bhattacherjee (2001) 3.4 Pilot study 3.4.1 Questionnaire design 3.4.2 Data collection and data analysis method The study used an online survey Data were analyzed using SPSS 24.0 software 3.4.3 Pilot study results: The results from the second Cronbach's alpha confirmed that MAU concept includes dimensions There were items deleted due to the total corrected item-total correlation less than 0.3 3.4.4 Adjust the scale: The remaining 47 observed variables were used in the official questionnaire 3.5 Preliminary quantitative research 3.5.1 Data collection: Online survey 3.5.2 Sample size: Based on Bollen's (1989) sample size calculation, 478 valid responses were included in the analysis 3.5.3 Data analysis method: Data were analyzed using SPSS 24.0; AMOS 24.0 Chapter summary CHAPTER RESEARCH RESULTS Chapter introduction 4.1 Sample profile Our sample size was Vietnamese domestic travelers who have used online travel agencies’ apps for travel purposes Data collection conducted from 09/2021 to 05/2021 through online survey and voreceived 478 valid questionnaires 4.2 Descriptive statistical analysis results 15 4.2.1 The results of descriptive statistical analysis results in the confirmation of mobile tourism app usability 4.2.2 The results of descriptive statistical analysis results in perceived usefulness, satisfaction, and continuance intention to use mobile tourism app 4.3 Preliminary evaluation of the scales 4.3.1 Exploratory factor analysis results (EFA) The EFA results showed that the coefficient KMO = 0.880 > 0.5: factor analysis was appropriate for the research data Sig value =0.00050% satisfactory, showing that these factors explained 60.084% of the variability of the data 4.3.2 Testing reliability of the scale by Cronbach’s alpha The scale reliability value of 10 factors was from 0.7 to 0.9, which indicates that the scale had high intrinsic consistency (L.V.Huy & T.T.T Anh, 2012) The correlation coefficient of the total variables of the observed variables were higher than 0.3, ensuring the requirements for the scale 4.3.3 Confirmation factor analysis results (CFA): TIUD5 and TIUD4 were deleted at the second and third times, respectively, to AVE > 0.5 The third CFA result indicated that the scale of the confirmation of MTU had the requirements of adequate reliability, convergent validity, and discriminant validity 4.4 Testing research model and hypothesis 4.4.1 Research model testing result: The SEM results demonstrated that the research model achieved compatibility with data 16 Figure 4.3 Structural model testing (SEM) 4.4.2 Hypothesis testing results Table 4.10 Results of hypothesis testing Hypothesis Relationship Decision Coefficient β β Coefficient Coefficient Standardized Pvalue H1a TKUD→NTHI 0,054 0,059 0,290 Rejected H1b TIUD→NTHI 0,187 0,182 0,000 Supported H1c DHGD→NTHI 0,178 0,198 0,000 Supported H1d CTUD→NTHI 0,162 0,185 0,000 Supported H1e GDDV→NTHI 0,107 0,125 0,017 Supported H1f GDDR→NTHI 0,090 0,113 0,023 Supported H1g DOOD→NTHI 0,264 0,250 0,000 Supported H2a TKUD→SHAL 0,201 0,242 0,000 Supported H2b TIUD→SHAL 0,113 0,121 0,023 Rejected H2c DHGD→SHAL 0,028 0,035 0,540 Supported H2d CTUD→SHAL 0,090 0,113 0,033 Supported H2e GDDV→SHAL 0,093 0,120 0,023 Supported H2f GDDR→SHAL 0,125 0,175 0,000 Supported H2g DOOD→SHAL 0,144 0,151 0,005 Supported H3 NTHI→SHAL 0,140 0,019 Supported 0,126 17 Hypothesis Relationship Decision Coefficient β β Coefficient Coefficient Standardized Pvalue H4 NTHI→TTSD 0,323 0,278 0,000 Supported H5 SHAL→TTSD 0,385 0,300 0,000 Supported The findings confirmed that out of the 07 dimensions of MAU, 06 dimensions directly affected perceived usefulness and satisfaction More specifically, confirmation of app dependability had the most influence on perceived usefulness (β=0,174) Confirmation of app design had the strongest influence on the satisfaction (β=0.225) In terms of continuance intention to use, both satisfaction and perceived usefulness had a significant impact (p-value < 0.05) However, satisfaction has a stronger impact than perceived usefulness (β=0.39) 4.4.3 Model estimation testing results To evaluate the reliability of the estimated coefficients, the Bootstrap method with 1000 repeated samples was used The results showed that the bias and standard deviation of the bias were very small Thus, the estimates in the model were reliable 4.4.4 Mediating effects testing results Satisfaction mediated the links between TKUD, TIUD, CTGD, and GDDV and continuance intention to use (Supported H6a,b,d,e with p-value 0,05; and H6f, g were rejected because of the confidence intervals (CI) containing the zero value (Hayes & Preacher, 2014) Satisfaction mediated the relationship between perceived usefulness and continuance intention to use, H7 was supported with p-value = 0,022