Old and New System Design Online Website Customer Satisfaction Literature Review
Int J Environ Res Public Health. 2020 January; 17(one): 174.
Assessing the Effects of Information Arrangement Quality and Relationship Quality on Continuance Intention in E-Tourism
Ni Wayan Masri
1College of Management, National Kaohsiung University of Science and Technology No. 1, Academy Rd., Yanchao Dist., Kaohsiung City 824, Taiwan; moc.liamg@1akillamadnana
Jun-Jer You lot
2Department of Artificial Intelligence CTBC Business concern School No. 600, Sec. 3, Taijiang Blvd., Annan District, Tainan 709, Taiwan; wt.ude.cbtc@rejnujuoy
Athapol Ruangkanjanases
threeChulalongkorn Business organization School, Chulalongkorn University, Bangkok 10330, Thailand
Shih-Chih Chen
ivDepartment of Information Direction, National Kaohsiung University of Science and Applied science No. ane, University Rd., Yanchao Dist., Kaohsiung City 824, Taiwan; wt.ude.tsukn@nehccs
Received 2019 Nov ane; Accepted 2019 Dec 22.
Abstract
The advance of electronic commerce has resulted in successful eastward-travel services. Through the development of eastward-travel information, consumers can programme their trip without time and space limitations. This study proposes a model regarding the formation of the relationship quality (customer satisfaction and trust), information arrangement quality, perceived value, and customers' intention to continue in the e-tourism environs. The report is based on 351 e-travel users in Taiwan. The result shows that customer satisfaction has a positive consequence on continuance intention. Data system quality has a positive relationship with customer satisfaction, trust, and client continuance intention. Furthermore, the perceived value has an upshot on client satisfaction and trust. However, the perceived value is partially related to customer constancy intention through customer satisfaction. The managerial implications of this study are discussed.
Keywords: e-tourism, information system quality, perceived value, human relationship quality, continuance intention
1. Introduction
The success of electronic commerce (EC) is dependent on the internet infrastructure online services [1]. A new model of advice via email, net, eastward-travel, spider web services, and social media has increased in customer service, and the role of traditional communications such as the telephone has decreased [2]. The high-tech environments enable transactions to take place through virtual channels, no longer requiring the concrete presence between customers and service providers. The trend is away from confront-to-face contact and toward online services [two,3].
A focus on developing online consumers is primal to business organization models in electronic commerce [4]. Travel agents and managers must learn how to maintain customer relationship quality and continuance intention, and they must understand the influence of antecedent factors in the e-tourism surroundings. Specifically, due east-tourism has been apace rising in contest around the globe, and therefore many emerging agents have switched from business concern-to-business (B2B), business-to-consumer (B2C) and Business-to-Business organization-Consumer (B2BC) in order to sustain their existing customers.
Although the central role of human relationship quality related to customer constancy intention has been previously studied, many critical issues withal crave research, including the germination of relationship quality [5] and customer continuance purchasing beliefs to sustain existing customer loyalty in the east-tourism environment. It is articulate that some critical factor needs to be developed to enhance customers' constancy intention in the east-tourism environment. Previous studies confirmed that customer loyalty was found to be straight influenced by customer satisfaction [six,7].
In the present written report, we are focused on how the relationship quality (customer satisfaction and trust) is influenced by the information system quality and the customer's perceived value in the eastward-tourism environment. The study contributes to the due east-tourism literature by extending previous studies and presenting a new concept on human relationship quality and information organization quality in the e-tourism context. The new construct of human relationship quality consists of satisfaction and trust. The three components of data system quality—the information system, system quality, and service quality—are examined as a single construct to enhance the sustainable e-tourism environs. In Department two, nosotros nowadays the literature review regarding the germination of relationship quality, information system quality, hypotheses, and a summary of our hypotheses in Tabular array i. The research methodology is in Section 3, our findings are in Section 4, and discussions and implications are in Department v.
Table one
Relationship hypotheses.
| Hypotheses | Part | |
|---|---|---|
| H1 | Sat has a positive relationship on customer CI | SAT->CI |
| H2 | TR has a positive relationship on client CI | TR->CI |
| H3a | ISQ has a positive relationship on customer SAT | ISQ->SAT |
| H3b | ISQ has a positive relationship on customer TR | ISQ->TR |
| H3c | ISQ has a positive relationship on customer PV | ISQ->PV |
| H3d | ISQ has a positive relationship on customer CI | ISQ->CI |
| H4a | PV has a positive relationship on customer Sat | PV->Sabbatum |
| H4b | PV has a positive relationship on customer TR | PV->TR |
| H4c | PV has a positive relationship on customer CI | PV->CI |
two. Theoretical and Hypotheses Development
2.1. Relationship Quality
Previous studies take widely investigated relationship quality from unlike angles [5,viii]. Relationship quality is recognized equally a key to developing customer loyalty [7,ix,10], also as a number of dissimilar constructs related to satisfaction [8] and trust [6,seven]. Withal, dissimilar authors have presented combinations of different constructs to indicate human relationship quality. Two singled-out dimensions of relationship quality (e.thou., data sharing and advice quality) take been found to influence long-term customer satisfaction. Further, a recent written report establish that relationship quality consisted of customer satisfaction, service quality influence, customers' repurchase intentions, and subjective well-beingness [11]. The study suggests that relationship quality is a central event for long-term success in direction and business relationships [12]. Relationship quality is the factor that enhances profitability for both parties [13]. Therefore, relationship quality can be posited as an antecedent for customer continuance intentions [11]. Studies accept proposed 2 dimensions of relationship quality (satisfaction and trust) as an antecedent of customer continuance intentions in the e-tourism context. Data system quality and customer perceived value are considered as the antecedents of relationship quality. Moreover, human relationship quality affects customer satisfaction and trust, influencing the customer's constancy to buy the production or service in the e-tourism surroundings. We define human relationship quality equally the customers' satisfaction and trust relationship toward the information system quality and the perceived product value and service. We define customer satisfaction equally the customer perceived value of the information system quality that is provided past an e-tourism provider. We ascertain customer trust as a customer's subjective belief that an eastward-travel bureau tin can serve their needs and expectations.
two.2. Relationship Quality and Continuance Intention in East-Tourism
According to the expectation disconfirmation model, a customer'due south continuance intention is influenced by service quality and customer satisfaction [14]. In an eastward-commerce B2C model, information technology has been shown that client satisfaction influences consumers' constancy intentions as the effect of cerebral, melancholia, and conative loyalty [15]. Furthermore, relationship quality has a positive influence on repurchase intention in B2B e-commerce [16]. Satisfaction and trust accept been examined as a single entity, where the relationship quality was considered every bit a second-order construct [16]. The nowadays study shows that human relationship quality consists of satisfaction and trust, which can predict a customer'southward continuance to buy the product or service in the e-tourism surround. Customer satisfaction and trust are examined as split entities to fit the avant-garde engineering science available. For instance, many customers may be satisfied with the information on a website, but this does non hateful that the customer volition trust the product or service provided. Based on the to a higher place literature, our report hypotheses are:
Hypothesis1(H1).
Client satisfaction has a positive effect on constancy intention.
Hypothesistwo(H2).
Customer trust has a positive issue on continuance intention.
two.three. Information System Quality
The information system was proposed in [17]. The study introduced the model, which posits 3 major dimensions: system quality, data quality, and user satisfaction in the context of organizations. Ten years after, in an update to the original Information System literature, the authors added service quality to the information system model to evaluate the information system through vii factors: information quality, organisation quality, service quality, data utilise, use, user satisfaction, and net benefits [eighteen]. This develops a dissimilar definition regarding the information organization [19]. The system quality consists of response time, organization reliability, and system availability, which have a positive impact on the perceived ease of use and usefulness of website [18,20].
Service quality is divers as the user's perceptions regarding the service performance [21]. Service quality measures the discrepancy between what the customer feels and needs and what is offered accordingly to fulfill the customer's expectations [twenty,22]. For example, service quality on multi communication mechanisms enables the user to accept their complaints responded to in a timely style.
Information organisation success has been measured in 4 dimensions: abyss, accuracy, format, and currency [23]. For information quality, the user-perceived effectiveness of system quality measurements take included accuracy, relevance, adequacy, and included quality, timeliness, and sequencing [24]. Other studies have also shown that the information organisation quality has a significant relationship with perceived usefulness [nineteen]. However, the numbers of previous studies take developed the data system quality in an east-commerce environment. This written report adopts the model from the study in [18], as shown in Effigy one. We conceptualize three dimensions of system quality, information quality, and service quality every bit information system quality to adopt the advanced technology in the e-tourism environment. The information system quality is defined equally products or services that fit client needs and expectations to complete their transaction in the east-tourism environment. The products or services include itinerary services, reliable data, instant information, accurate performance, and specific information with easy access at anytime and anyplace past the customer. For instant, low-cost travel, travel agencies provide interconnected systems, such equally TripAdvisor, ezfly.com, or skyscanner.com.tw.
Relationship quality research model. Annotation: H = hypothesis.
The value that a service involves is not only by the provider but also through the opportunity for customer satisfaction and a trust relationship. The data system quality accommodates the swift customer mindset that has changed from traditional to online 24-h services. The travel agency reduces the time and travel expense, which benefits both parties. Our model has shown that customer trust and satisfaction are influenced by the information system quality and perceived value. The information system quality enhances the mindset of the customer relationship through a single entity of the production and service in an e-travel environment. Perceived value is dependent on the consumer'southward perceptions of what is received and what is given [25]. The customer'southward perceived value influences the customer satisfaction and trust regarding the product or service in the due east-tourism surround. Based on the studies above, nosotros propose the following hypotheses:
Hypothesis3(H3).
Information system quality has an issue on customer (a) satisfaction, (b) trust, (c) perceived value, and (d) continuance intention.
2.4. Perceived Value
The concept of value has constantly emerged from the different studies related to consumer behavior [25,26]. Prior studies suggested that perceived value is a better predictor of repurchase intentions than satisfaction, commitment, or trust [26]. Furthermore, the perceived value of the product and service could attract new consumers and result in benefits to the vendor [half-dozen,27,28]. Our model has shown that customer satisfaction and trust relationships are influenced by the customer's perceived production and service value. The client's perceived value influences the client'due south constancy intention. Based on this literature, nosotros suggest the following hypothesis:
Hypothesis4(H4).
Perceived value has a positive result on customer (a) satisfaction, (b) trust, and (c) continuance intention.
3. Enquiry Methodology
3.one. Subjects: Instrument Development and Measurement
The survey report was designed based on the previous study on the data system success and IT development in an e-commerce environment, looking at service quality, system quality, perceived quality, trust, satisfaction, and continuance of use. We developed and reworded the survey items to fit the present study. All the items in the questionnaire were modified from English, translated to Chinese, and then translated back to English language. The initial version of the survey written report was pretested by two Ph.D. students and 1 professor who is an expert in the field of questionnaire design for east-commerce studies. Afterwards obtaining feedback from the experts, we modified the questionnaires for the final measurements of the model.
The constructs are measured using 5-point Likert scales, ranging from one–5, with 1 indicating "strongly disagrees" and 5 indicating "strongly agrees". Data system quality was adopted from [14,18], with vii items. Perceived value, with five items, was modified from [26,28], and three items were taken for further data analysis. Customer trust, with iv items, was modified from [six,29]. Satisfaction, with four items, was modified from [half dozen]. Continuance intention was adapted from [30] with 5 items, and iii items were taken for further information assay, as the loading value was lower than the effective value.
iii.two. Survey Collection
The questionnaire was targeted to online travel users such every bit students, information technology users, manufacturers, and customers in finance, public service, and medical fields, who have experience ownership domestic or international travel itineraries such every bit air tickets, reservations, and car rentals, besides as experience booking hotels and other services in east-travel (e.k., Ezfly, Eztravel, Skyscanner, tripadvisor). We chose websites that were the almost popular and where the systematic system tin easily be accessed by personal computer (PC) and cell phones, with flexible times and affordable prices for immature or elderly people. The information were nerveless over 2 months in Taiwan. For more data regarding the survey items, refer to Appendix A. To maximize the respondents' awareness on this survey, we contacted the respondents by email or sent the questionnaire on personal Facebook chat, Line conversation, grouping Facebook, or Line chat. We distributed 450 questionnaires, and 376 were returned, with a response charge per unit of 83.5%. Later information sterilization, 25 respondents were dropped due to incomplete responses on the survey. The concluding sample employed in our study was 351 responses (93.iv% of the full responses). We employed IBM SPSS twenty (Armonk, NY, USA) for descriptive analysis to assess the frequency, and the percent range of populations is shown in Tabular array two.
Table 2
Demographics of the respondents.
| Demographic Respondents (N = 351) | |||||
|---|---|---|---|---|---|
| Characteristics | Frequency | Percent (%) | Characteristics | Frequency | Percent (%) |
| Gender | Occupation | ||||
| Male Female | 143 208 | 40.7 59.3 | Student Technology Manufacturing Finance Service Medical | 52 38 75 56 93 37 | 14.8 10.8 21.4 16.0 26.5 ten.5 |
| Age | Monthly Income | ||||
| ≤20 21–thirty 31–forty 41–l 51–60 >60 | 29 89 56 66 78 33 | 8.three 25.iv sixteen.0 18.8 22.2 9.4 | ≥thou$ 1001–2000$ 2001–3000$ 3001–4000$ <4000 | 45 169 49 half dozen 82 | 12.eight 48.one 14.0 1.vii 23.4 |
| Instruction | Travel service | ||||
| ≥Senior high school University/college Graduate higher up | lxx 155 126 | nineteen.9 44.two 35.9 | hkexpress ezfly eztravel TripAdvisor Others | 70 70 103 85 23 | nineteen.ix 19.9 29.3 24.2 6.half dozen |
| Instruments | |||||
| PC Smartphone | 114 237 | 32.5 67.5 | |||
The majority of respondents used the online travel service itinerary for their travels, which showed that 59.iii% were female and 40.vii% were male. The participants were generally from the historic period groups of 21–30 years old and 51–60 years old. The participants generally work in manufacturing and public service from unlike sectors. The highest monthly income was 1001–2000 USD. The participants searched for information using a smartphone 67.five% of the fourth dimension. Further, eztravel (29.3%) and TripAdvisor (24.2%) were the most popular due east-travel service websites for finding information and booking itineraries. The information samples were sufficient to identify the customers' behavior and to accommodate further study on the information system quality.
4. Information Assay Results
4.1. Measurement Model Assay
The measurement model and structural model was assessed with partial least squares (PLS) using Smarts-PLS 3.2.viii [31]. Beginning, PLS is not every bit restrictive on the sample size as that designed in the structural equation model. The constructs in this written report are all cogitating. Therefore, a PLS modeling approach was chosen in this written report.
Second, for the data assay, we started with the PLS algorithm that tin obtain at convergence, satisfying fixed-betoken equations which include measurement reliability and model validity.
The third, the bootstrap procedure [32] was used to test the significance of diverse results such as path coefficients, Cronbach's alpha, and R two values. As in bootstrapping, subsamples are randomly drawn observations from the original set of data. This process was repeated until a large number of random subsamples were created, which in the case of our written report was 2000 subsamples. The estimations from the bootstrap subsamples were used to derive standard errors for the PLS-SEM results. With this data, t-values, p-values, and conviction intervals were calculated to assess the significance of model studies.
4, confirmatory factor analysis was conducted to assess the item loadings, discriminant validity, and internal consistency of the model. Item loading and internal consistencies greater than 0.seventy were considered acceptable [33,34]. Moreover, to assess convergent and discriminant validity, first, the indicators loaded should exist stronger than corresponding ones on the other constructs. Second, the square root of the average variance extracted (AVE) should be greater than the internal-constructs correlations shown in Appendix B, (cross-factor loading) which confirms the presence of a valid discriminant. Furthermore, in Table iii, the Cronbach'south alpha values range from 0.91 to 0.98, and the AVE ranges from 0.79 to 0.96, indicating acceptability [33]. These results demonstrate that all the measurements take an adequate acceptability level.
Tabular array 3
Construct reliability and discriminant validity.
| Constructs | Items | Cronbach'south Blastoff | Composite Reliability | AVE | CI | ISQ | PV | Saturday | TR |
|---|---|---|---|---|---|---|---|---|---|
| Continuance Intention | CI | 0.98 | 0.99 | 0.96 | 0.98 | ||||
| Information system Quality | ISQ | 0.97 | 0.98 | 0.87 | 0.78 | 0.93 | |||
| Perceived Value | PV | 0.95 | 0.97 | 0.91 | 0.67 | 0.66 | 0.96 | ||
| Satisfaction | Sabbatum | 0.91 | 0.94 | 0.79 | 0.72 | 0.70 | 0.86 | 0.89 | |
| Trust | TR | 0.92 | 0.94 | 0.fourscore | 0.lxx | 0.70 | 0.78 | 0.83 | 0.ninety |
5, an exploratory factor analysis was conducted to determine the relationship factors in the Smart-PLS algorithms. The exploratory cistron assay results are shown in Table 4. Standard gene loading and the t-value on the measurements were significant at the level of 0.01–0.02. Table 5 shows all the items of latent variables correlations on their intended factors to make up one's mind if the survey study is adequate for further assay.
Table 4
Weight and loading.
| Constructs | Items | Outer Loading | Outer Weights | Standard Difference | T Statistics |
|---|---|---|---|---|---|
| Continuance Intention | CI1 | 0.98 | 0.34 | 0.01 | 171.44 |
| CI2 | 0.98 | 0.34 | 0.01 | 161.33 | |
| CI3 | 0.98 | 0.33 | 0.01 | 137.83 | |
| Information system Quality | ISQ1 | 0.95 | 0.16 | 0.01 | 97.28 |
| ISQ2 | 0.94 | 0.xvi | 0.02 | 62.09 | |
| ISQ3 | 0.92 | 0.15 | 0.02 | 49.69 | |
| ISQ4 | 0.92 | 0.15 | 0.01 | 67.88 | |
| ISQ5 | 0.93 | 0.15 | 0.02 | 61.26 | |
| ISQ6 | 0.94 | 0.15 | 0.01 | 101.48 | |
| ISQ7 | 0.xc | 0.14 | 0.02 | 54.xl | |
| Perceived Value | PV3 | 0.95 | 0.34 | 0.01 | 102.x |
| PV4 | 0.96 | 0.35 | 0.01 | 134.48 | |
| PV5 | 0.96 | 0.35 | 0.01 | 93.05 | |
| Satisfaction | SAT1 | 0.89 | 0.31 | 0.01 | 63.35 |
| SAT2 | 0.xc | 0.27 | 0.02 | 59.68 | |
| SAT3 | 0.85 | 0.24 | 0.02 | 38.83 | |
| SAT4 | 0.91 | 0.31 | 0.01 | 62.48 | |
| Trust | TR1 | 0.87 | 0.31 | 0.02 | 57.57 |
| TR2 | 0.88 | 0.27 | 0.02 | 52.50 | |
| TR3 | 0.91 | 0.26 | 0.02 | 55.83 | |
| TR4 | 0.92 | 0.28 | 0.01 | 69.56 |
Table 5
Latent variable correlations.
| Constructs | Items | CI | ISQ | PV | Sat | TR |
|---|---|---|---|---|---|---|
| Continuance Intention | CI | 1.00 | 0.78 | 0.67 | 0.72 | 0.70 |
| Information Arrangement Quality | ISQ | 0.78 | i.00 | 0.66 | 0.70 | 0.70 |
| Perceived Value | PV | 0.67 | 0.66 | i.00 | 0.86 | 0.78 |
| Satisfaction | Sat | 0.72 | 0.lxx | 0.86 | 1.00 | 0.83 |
| Trust | TR | 0.70 | 0.70 | 0.78 | 0.83 | i.00 |
four.2. The Results of Structural Model
The results of the Smart-PLS function coefficients and significance values are shown in Figure ii. Table 6 shows the summary of our hypotheses testing. Seven of the nine hypotheses have positive and pregnant relationships. Customer satisfaction has a positive and significant effect on continuance intention, which supports H1, Sabbatum–CI (β = 0.20, t = 2.59, ** p < 0.01). However, the influence of customer trust has no significant relationship with constancy intention. Thus, H2 is not supported, trust–continuance intention (TR–CI) (β = 0.13, t = i.89, p < 0.05). The testing (H3a, H3b, H3c, and H3d) showed that data system quality has a positive and pregnant effect on client satisfaction, trust, perceived value, and customer continuance intention. Thus, H3a, data organization quality–satisfaction (ISQ–SAT) (β = 0.12, t = 2.99, *** p < 0.001), H3b, ISQ–TR (β = 0.33, t = v.82 *** p < 0.001), H3c, ISQ–perceived value (PV) (β = 0.67, t = 17.0 *** p < 0.001), and H3d, ISQ–CI (β = 0.50, t = seven.50, *** p < 0.001) were supported. Consequently, the (H3a, H4b), client perceived value has a positive and pregnant effect on customer satisfaction and customer trust. Thus, H4a and H4b were supported (PV–SAT, β = 0.50, t = 8.thirty, *** p < 0.001, and PV–TR, β = 0.56, t = 10.one, *** p < 0.001). Still, perceived value does not have a pregnant influence on customer continuance intention, so H4c, PV–CI (β = 0.07, t = 0.97, p < 0.05) is not supported. The model besides explains 67% of the variance of client constancy intention, 81% of the variance of customer satisfaction, 67% of the variance of a client trust relationship, and 44% of the variance of client perceived value of the product or service on an east-tourism aqueduct.
The results of the human relationship quality model. Note: ** p < 0.01 = t > ii.58; *** p < 0.001 = t > 3.29; with a two-tailed exam. ns = non supported.
Tabular array 6
Summary the results of the hypotheses.
| Hypotheses | Path Coefficients | t-Value | Results | |
|---|---|---|---|---|
| H1 | Saturday has a positive effect on customer CI | 0.20 | ii.59 | Supported |
| H2 | TR has a positive outcome on customer CI | 0.13ns | 1.88 | Not supported |
| H3a | ISQ has a positive effect on customer Sat | 0.12 | 2.99 | Supported |
| H3b | ISQ has a positive effect on client TR | 0.33 | 5.82 | Supported |
| H3c | ISQ has a positive effect on customer PV | 0.67 | 17.0 | Supported |
| H3d | ISQ has a positive effect on customer CI | 0.50 | 7.50 | Supported |
| H4a | PV has a positive effect on customer Saturday | 0.50 | eight.30 | Supported |
| H4b | PV has a positive effect on customer TR | 0.56 | 10.i | Supported |
| H4c | PV has a positive effect on customer CI | 0.07ns | 0.97 | Not supported |
4.3. Mediation Furnishings
To solve the problem in the hypotheses (H2, H4c), this study performed mediating furnishings following certain steps [35,36]. First, the written report tested the significant indirect effect of the product paths "a" and "b") using the Sobel test [37].
The results showed that perceived value has a positive and significant event on continuance intention through the mediator of customer satisfaction, PV–Saturday–CI, with a Sobel-test statistic (z = three.10, ** p < 0.01). Consequently, customer trust has a positive and pregnant result on customer continuance intention through customer satisfaction, TR–SAT–CI, with a Sobel-examination statistic (z = ii.31, * p < 0.05). 2nd, the study likewise accesses the variance-deemed-for (VAF) ratio past accounting result (indirect effects/total furnishings = VAF). Thereby, we can determine the extent to which the dependent variable is directly explained by the independent variable and how much of the target construct variance is explained by the indirect human relationship via the mediator variable [38,39]. If the VAF ratio is less than twenty%, it shows a non-significant mediating effect; when the ratio is 20%–80%, it shows partial mediating effects, and when it is larger than fourscore%, information technology is assumed to have a fully mediating effect.
The test results showed that client perceived value has a partially mediating relationship on constancy intention through the mediator client satisfaction (PV–SAT–CI), with a variance-accounted-for (VAF) ratio of 75%. Furthermore, customer trust has a partially mediating relationship on customer constancy intention through the mediator of customer satisfaction (TR–SAT–CI) with a variance-accounted-for (VAF) ratio of 35%. The summary of mediating effects is shown in Table 7.
Table 7
Results of mediating effects.
| Indirect Effect | IV-MD | MD-DV | C | c' | AB | Full Result | Sobel | VAF% | Type |
|---|---|---|---|---|---|---|---|---|---|
| PV-SAT-CI | 0.l *** | 0.20 ** | 0.20 *** | 0.67 *** | 0.21 *** | 0.28 *** | 3.x ** | 75% | Partial |
| TR-SAT-CI | 0.36 *** | 0.20 ** | 0.28 *** | 0.70 *** | 0.07 ** | 0.20 *** | 2.31 * | 35% | Partial |
5. Discussion
5.i. Theoretical Implication
Several implications are obtained from this written report. Commencement, this study extends the previously study [18], and the findings support the research on information system quality by examining information quality, system quality, and service quality as a single entity.
Second, the prior study on customer relationship quality examined this quality as a single entity and showed a positive and significant issue on continuance intention [7]. In this written report, human relationship quality was examined as two split entities (client satisfaction and customer trust). Customer satisfaction had a positive and significant effect on the continued employ of the products or service in the east-tourism environs. Customers showed a continuance of trust in the products or service when the customer was satisfied with the product or service. The information organization quality proved long-term usage investment on client constancy intention, which differs from the existing studies [18] and supports [30,40] client relationship quality in the e-tourism surround.
Third, the customer-perceived value has a positive event on client satisfaction and trust. Withal, perceived value has no significant human relationship on customer continuous intention. Furthermore, perceived value has a partial influence on customer constancy intention through customer satisfaction. This means that without sufficient customer satisfaction, customers may not tend to purchase in the future or will be unable to retain long-term success in eastward-tourism. The travel agencies take to build existing customers through customer human relationship quality, in particular, building client satisfaction and trusting relationships.
The findings stated that the customer's relationship qualities (e.chiliad., trust and satisfaction) are the primary issues affecting the standing usage intention in regard to information system quality. Providing a new model, such as a ane-desk-bound data service and improved relationship quality (customer satisfaction and trust) could enhance the impact of information system quality on the e-tourism environment.
Fourth, the study establish that the majority of respondents who employ the online travel service for their travels were 59.iii% female and 40.7% male. The hateful gender show a like do good from the information organization quality in eastward-tourism. Moreover, results besides showed that the participants from ages 21–xxx and 51–sixty years former who worked in manufacturing and the public service from unlike sectors were more expected to continue to purchase the products or service.
Furthermore, the customers with income from 1001–2000 USD more ofttimes used the information and booking and were the well-nigh familiar with the websites Eztravel 29.3% and TripAdvisor 24.2%. Yet, virtually customers used a smartphone equally their preferred tool for booking travel plans. We conclude that these feature customer behaviors are shown to provide continuance success in the data arrangement applications in this e-commerce environment, which is different from the findings of previous studies [eighteen].
v.2. Practical Implication
The practical implications for information system quality, perceived value, relationship quality, and customer'south continuance intention offer important implications for travel agencies and managers in e-tourism. To better IS quality in the eastward-tourism environment, the travel agency and manager has to upgrade the operational procedure infrastructure and delivery service transaction to lucifer existent-time customer expectations. Furthermore, they crave software and hardware with an advanced data system that can prevent technical difficulties and transactions overloading [xxx].
Managers and practitioners can use these results as guidelines to develop websites, operations, and provide advance support to customers. The measurement of information system quality can enhance products and services to help managers and organizations provide better products and services in the e-tourism environment. In addition, these results may apply a particularly powerful benchmark against competitors' websites that can affect long-term development activities on eastward-tourism. Our findings non only support a viewpoint on information organization quality development, merely also on building client relationship quality through the application of customer satisfaction and trust provided by the due east-tourism provider. Service providers can provide an incentive program such as purchasing a parcel program for client travel planning. Furthermore, the study besides demonstrated the positive and pregnant influence of perceived value on customers' constancy intention through customer satisfaction, which enhances long-term client success in adopting a new programme such as a package information service. This may propose that enhancing information organization quality is non only to satisfying for the customers but also helps to build customer trust relationships in an e-tourism environment.
6. Conclusions and Future Study
This study has important implications for the researcher and practitioner. The study concludes that customer relationship quality (satisfaction) has positive furnishings on client constancy intentions. However, client trust as well has a partial human relationship on continuance intention through customer satisfaction. In addition, information system quality has a pregnant relationship with customer satisfaction, trust, perceived value, and continuance intention. Furthermore, the customer-perceived value is also significantly related to customer satisfaction and trust, only it is partially related to customer continuance intention through the customer satisfaction relationship.
However, present, east-tourism companies have profoundly invested in training programs and advertising campaigns to transform information organisation quality for the users. This written report provided more comprehensive findings on the information system and examined iii dimensions (information quality, organization quality, and service quality) in a single entity every bit information system quality, but it also separately examined the relationship quality that consists of customer satisfaction and trust in the e-tourism environment. We attempted to integrate perceived value and customer relationship quality with the model on customer constancy intention. Some interesting findings that were not discussed in previous studies are also covered in the current study. A large sample in this study is from the manufacturing and services sector, which is due to the customer trust and satisfaction in due east-tourism. This study also provides meaningful implications on east-tourism continuance intention behavior.
A limitation in this study is using cocky-report instruments, every bit this may have the potential for a common method bias in measuring the study variables [41]. Hence, nosotros diminished the probability of common biases by segregating the instruments and motivating the participants in the study. Furthermore, study data were collected in Taiwan. The travel forum members accept similar culture and convenience traits. More research beyond countries and cultures will exist required in club to generalize the findings. Finally, time to come studies also have the possibility to investigate different factors that tin can be integrated into the model.
Appendix A
Tabular array A1
Survey particular.
| Office 1: Demographic | |||||
| Gender | 1□ Male 2 □ Female person | ||||
| Historic period | 1□≥ twenty 2□ 21–30 3□31–40 4□ 41–50 five□ 51–60 vi□ < lx | ||||
| Education | 1□ ≥Senior high school 2 □ University/college 3 □ Graduate in a higher place | ||||
| Occupation | one.□ Student ii□ Engineering science 3□ Manufacturing iv□ Finance five□ Service half-dozen □ Medical | ||||
| Monthly Income | 1□≥yard$ 2□1001-2000$ 3□2001–3000$ 4□3001-4000$ 5□ < 4000 | ||||
| Travel service | one□ hkexpress 2□ ezfly 3□ eztravel 4□ heaven scanner 5□ TripAdvisor six□ Others | ||||
| Instrument | i□ PC ii □ Smart phone | ||||
| Strongly disagree | Disagree | Neutral | Disagree | Strongly hold | |
| Part 2(ISQ): This section to know; How do the data system quality and the website system provided service the on customer online travel. | |||||
| Information Organisation quality [fourteen,eighteen,42] | |||||
| 1. Online travel provider provided the customer with a consummate data itinerary | □ | □ | □ | □ | □ |
| 2. Online travel provider provided travelers a consummate reliable information | □ | □ | □ | □ | □ |
| three. Online travel provider provided travelers with instantaneous data | □ | □ | □ | □ | □ |
| iv. Online travel provider provided travelers accurately operators | □ | □ | □ | □ | □ |
| 5. Online travel provider provided the data what I need | □ | □ | □ | □ | □ |
| 6. Online travel provider provided the customer with information on specific websites | □ | □ | □ | □ | □ |
| 7. Online travel provider provided appropriate information | □ | □ | □ | □ | □ |
| Part 3(PV): This department to know; How do you feel well-nigh the value of service and product provided by online travel agency [26,28,43] | |||||
| 1. Online travel agency tin save more fourth dimension and travel expenses. | □ | □ | □ | □ | □ |
| 2. Online travel agency allows me quickly complete of my travel itinerary | □ | □ | □ | □ | □ |
| 3. Online travel agency, it is helpful to me. | □ | □ | □ | □ | □ |
| 4. Although information technology takes some time to compare travel itineraries on the Internet, information technology is worthwhile to do so. | □ | □ | □ | □ | □ |
| 5. In short, online travel agency provided more benefit and fast processing the information. | □ | □ | □ | □ | □ |
| Part iv: This department to know; 1. How practice yous trust the service and the products provided by travel agency [6,25,29]. | |||||
| i. I think the visitor that provides online travel website and information is reliable. | □ | □ | □ | □ | □ |
| two. I recall the services provided by online travel operators are trustworthy. | □ | □ | □ | □ | □ |
| three. Online travel operators should able to perform services and promised to users | □ | □ | □ | □ | □ |
| four. I believe that online travel provider has the ability to protect user | □ | □ | □ | □ | □ |
| 2. How do you satisfies with the online service provided by travel agency [half dozen,44] | |||||
| ane. I am satisfied with the travel planning provided past the online travel agency. | □ | □ | □ | □ | □ |
| 2. I am satisfied with the information provided online on website. | □ | □ | □ | □ | □ |
| three. I am sure that the online travel website is such a convenience service | □ | □ | □ | □ | □ |
| iv. The product or service provided by online travel bureau are generally quite assisting | □ | □ | □ | □ | □ |
| Role 5 (CI) [9,40]: This section, To know well-nigh how your future planning on e-tourism | |||||
| 1. The overall experience of using online travel websites is enjoyable. | □ | □ | □ | □ | □ |
| 2. I am willing to use the services provided by online travel bureau | □ | □ | □ | □ | □ |
| 3. I will use the travel website to plan my travel itinerary in the future. | □ | □ | □ | □ | □ |
| 4. I would similar to introduce the travel itinerary to my friends | □ | □ | □ | □ | □ |
| 5. I am willing to continue to buy product or service itinerary provided past the online travel provider. | □ | □ | □ | □ | □ |
Appendix B
Tabular array A2
The Issue of cantankerous loading.
| Cross Loadings | ||||||
|---|---|---|---|---|---|---|
| Constructs | Items | CI | ISQ | PV | Sabbatum | TR |
| Continuance Intention | CI1 | 0.98 | 0.76 | 0.68 | 0.71 | 0.70 |
| CI2 | 0.98 | 0.77 | 0.66 | 0.71 | 0.69 | |
| CI3 | 0.98 | 0.75 | 0.64 | 0.69 | 0.67 | |
| Data system Quality | ISQ1 | 0.76 | 0.95 | 0.66 | 0.68 | 0.67 |
| ISQ2 | 0.76 | 0.94 | 0.66 | 0.69 | 0.69 | |
| ISQ3 | 0.72 | 0.92 | 0.59 | 0.63 | 0.62 | |
| ISQ4 | 0.lxx | 0.92 | 0.61 | 0.64 | 0.65 | |
| ISQ5 | 0.71 | 0.93 | 0.62 | 0.66 | 0.66 | |
| ISQ6 | 0.73 | 0.94 | 0.61 | 0.66 | 0.66 | |
| ISQ7 | 0.68 | 0.90 | 0.58 | 0.61 | 0.60 | |
| Perceived Value | PV3 | 0.threescore | 0.63 | 0.95 | 0.80 | 0.76 |
| PV4 | 0.66 | 0.64 | 0.96 | 0.82 | 0.75 | |
| PV5 | 0.66 | 0.64 | 0.96 | 0.84 | 0.72 | |
| Satisfaction | SAT1 | 0.seventy | 0.66 | 0.87 | 0.89 | 0.73 |
| SAT2 | 0.58 | 0.threescore | 0.72 | 0.90 | 0.72 | |
| SAT3 | 0.51 | 0.53 | 0.63 | 0.85 | 0.70 | |
| SAT4 | 0.71 | 0.68 | 0.80 | 0.91 | 0.78 | |
| Trust | TR1 | 0.69 | 0.71 | 0.76 | 0.83 | 0.87 |
| TR2 | 0.59 | 0.59 | 0.66 | 0.73 | 0.88 | |
| TR3 | 0.58 | 0.55 | 0.66 | 0.68 | 0.91 | |
| TR4 | 0.63 | 0.63 | 0.69 | 0.71 | 0.92 | |
Author Contributions
Funding conquering, Writing—original draft, A.R.; Resources, C.-I.P.; Supervision, S.-C.C.; Writing—original draft, Data drove, Data analysis, N.Due west.M.; Writing—review and editing, J.-J.Y. All authors take read and agreed to the published version of the manuscript.
Funding
This research received no external funding.
Conflicts of Interest
The authors declare no conflict of involvement.
References
1. Ponte E.B., Carvajal-Trujillo E., Escobar-Rodríguez T. Influence of trust and perceived value on the intention to buy travel online: Integrating the effects of balls on trust antecedents. Tour. Manag. 2015;47:286–302. doi: x.1016/j.tourman.2014.10.009. [CrossRef] [Google Scholar]
2. Chen S.-C., Li S.-H. Consumer adoption of e-service: Integrating technology readiness with the theory of planned behavior. Afr. J. Bus. Manag. 2010;4:3556–3563. [Google Scholar]
three. Breidbach C.F., Kolb D.G., Srinivasan A. Connectivity in service systems: Does technology-enablement impact the ability of a service system to co-create value? J. Serv. Res. 2013;sixteen:428–441. doi: 10.1177/1094670512470869. [CrossRef] [Google Scholar]
4. Li X., Wang Y., Yu Y. Nowadays and future hotel website marketing activities: Modify propensity assay. Int. J. Hosp. Manag. 2015;47:131–139. doi: ten.1016/j.ijhm.2015.02.007. [CrossRef] [Google Scholar]
5. Wu H.-C., Cheng C.-C. Relationships between technology attachment, experiential relationship quality, experiential risk and experiential sharing intentions in a smart hotel. J. Hosp. Bout. Manag. 2018;37:42–58. doi: ten.1016/j.jhtm.2018.09.003. [CrossRef] [Google Scholar]
vi. Su L., Hsu M.K., Swanson S. The effect of tourist relationship perception on destination loyalty at a world heritage site in Red china: The mediating role of overall destination satisfaction and trust. J. Hosp. Tour. Res. 2017;41:180–210. doi: 10.1177/1096348014525630. [CrossRef] [Google Scholar]
vii. Setó-Pamies D. Customer loyalty to service providers: Examining the role of service quality, client satisfaction and trust. Total Qual. Manag. Coach. Excell. 2012;23:1257–1271. doi: 10.1080/14783363.2012.669551. [CrossRef] [Google Scholar]
8. Williams P., Ashill North.J., Naumann E. Relationship quality and satisfaction: Customer-perceived success factors for on-time projects. Int. J. Proj. Manag. 2015;33:1836–1850. doi: 10.1016/j.ijproman.2015.07.009. [CrossRef] [Google Scholar]
9. Ou W.-M., Shih C.G., Chen C.Y. Relationships among customer loyalty programs, service quality, human relationship quality and loyalty: An empirical study. Chin. Manag. Stud. 2011;five:194–206. doi: x.1108/17506141111142825. [CrossRef] [Google Scholar]
x. Liu C.-T., Guo Y.Thousand., Lee C.-H. The effects of relationship quality and switching barriers on customer loyalty. Int. J. Inf. Manag. 2011;31:71–79. doi: 10.1016/j.ijinfomgt.2010.05.008. [CrossRef] [Google Scholar]
11. Su L., Swanson S.R., Chen X. The effects of perceived service quality on repurchase intentions and subjective well-being of Chinese tourists: The mediating role of relationship quality. Tour. Manag. 2016;52:82–95. doi: 10.1016/j.tourman.2015.06.012. [CrossRef] [Google Scholar]
12. Gounaris Due south., Tzempelikos N. Relational key business relationship management: Building key account management effectiveness through structural reformations and human relationship direction skills. Ind. Marker. Manag. 2014;43:1110–1123. doi: 10.1016/j.indmarman.2014.06.001. [CrossRef] [Google Scholar]
13. Casidy R., Nyadzayo One thousand. Drivers and outcomes of relationship quality with professional service firms: An SME owner-manager perspective. Ind. Marking. Manag. 2017;78:27–42. doi: 10.1016/j.indmarman.2017.09.011. [CrossRef] [Google Scholar]
xiv. Bhattacherjee A. Understanding information systems continuance: An expectation-confirmation model. MIS Q. 2001;25:351–370. doi: 10.2307/3250921. [CrossRef] [Google Scholar]
15. Yuksel A., Yuksel F., Bilim Y. Destination zipper: Effects on customer satisfaction and cognitive, affective and conative loyalty. Tour. Manag. 2010;31:274–284. doi: 10.1016/j.tourman.2009.03.007. [CrossRef] [Google Scholar]
16. Zhang Y., Fang Y., Wei K.Yard. Repurchase intention in B2C east-commerce—A human relationship quality perspective. Inf. Manag. 2011;48:192–200. doi: 10.1016/j.im.2011.05.003. [CrossRef] [Google Scholar]
17. DeLone Due west.H., McLean Due east.R. Information systems success: The quest for the dependent variable. Inf. Syst. Res. 1992;3:60–95. doi: ten.1287/isre.iii.ane.60. [CrossRef] [Google Scholar]
xviii. Delone W.H., McLean Eastward.R. The DeLone and McLean model of information systems success: A ten-year update. J. Manag. Inf. Syst. 2003;19:nine–thirty. [Google Scholar]
19. Chung N., Koo C. The employ of social media in travel information search. Telemat. Inf. 2015;32:215–229. doi: 10.1016/j.tele.2014.08.005. [CrossRef] [Google Scholar]
20. Dedeke A.North. Travel web-site design: Data task-fit, service quality and purchase intention. Tour. Manag. 2016;54:541–554. doi: 10.1016/j.tourman.2016.01.001. [CrossRef] [Google Scholar]
21. Wang K. Determinants of mobile value-added service continuance: The mediating role of service feel. Inf. Manag. 2015;52:261–274. doi: 10.1016/j.im.2014.11.005. [CrossRef] [Google Scholar]
22. Walsh G., Hennig-Thurau T., Sassenberg K. Does relationship quality matter in e-services? A comparison of online and offline retailing. J. Retail. Consum. Serv. 2010;17:130–142. doi: 10.1016/j.jretconser.2009.11.003. [CrossRef] [Google Scholar]
23. Rana N.P., Dwivedi Y.K., Williams M.D. Investigating success of an e-government initiative: Validation of an integrated IS success model. Inf. Syst. Front. 2015;17:127–142. doi: 10.1007/s10796-014-9504-7. [CrossRef] [Google Scholar]
24. Hosseini South., Barker K., Ramirez-Marquez J.E. A review of definitions and measures of system resilience. Reliab. Eng. Syst. Saf. 2016;145:47–61. doi: 10.1016/j.ress.2015.08.006. [CrossRef] [Google Scholar]
25. Kuo Y.-F., Wu C.-Chiliad., Deng W.-J. The relationships among service quality, perceived value, customer satisfaction, and mail service-buy intention in mobile value-added services. Comput. Hum. Behav. 2009;25:887–896. doi: 10.1016/j.chb.2009.03.003. [CrossRef] [Google Scholar]
26. Gallarza One thousand.M., Saura I.Yard. Value dimensions, perceived value, satisfaction and loyalty: An investigation of university students' travel behaviour. Tour. Manag. 2006;27:437–452. doi: 10.1016/j.tourman.2004.12.002. [CrossRef] [Google Scholar]
27. Su L., Swanson S.R., Chen X. The bear upon of perceived service fairness and quality on the behavioral intentions of chinese hotel guests: The mediating part of consumption emotions. J. Travel Bout. Mark. 2016;33(Suppl. 1):88–102. doi: 10.1080/10548408.2015.1008668. [CrossRef] [Google Scholar]
28. Lai T.Fifty. Service quality and perceived value's impact on satisfaction, intention and usage of curt message service (SMS) Inf. Syst. Front. 2004;half dozen:353–368. doi: 10.1023/B:ISFI.0000046377.32617.3d. [CrossRef] [Google Scholar]
29. Wang 50., Law R., Guillet B.D. Affect of hotel website quality on online booking intentions: eTrust as a mediator. Int. J. Hosp. Manag. 2015;47:108–115. doi: 10.1016/j.ijhm.2015.03.012. [CrossRef] [Google Scholar]
xxx. Hadji B., Degoulet P. Information organization terminate-user satisfaction and continuance intention: A unified modeling approach. J. Biomed. Informat. 2016;61:185–193. doi: 10.1016/j.jbi.2016.03.021. [PubMed] [CrossRef] [Google Scholar]
31. Ringle C.Thousand., Wende Due south., Becker J.-M. SmartPLS three. Boenningstedt: SmartPLS GmbH. [(accessed on 30 July 2015)]; Bachelor online: http://world wide web.smartpls.com.
32. Hair J., Hollingsworth C.L., Randolph A.B. An updated and expanded cess of PLS-SEM in information systems enquiry. Ind. Manag. Data Syst. 2017;117:442–458. doi: 10.1108/IMDS-04-2016-0130. [CrossRef] [Google Scholar]
33. MacKenzie S.B., Podsakoff P.M., Podsakoff N.P. Construct measurement and validation procedures in MIS and behavioral research: Integrating new and existing techniques. MIS Q. 2011;35:293–334. doi: x.2307/23044045. [CrossRef] [Google Scholar]
34. Fornell C., Larcker D.F. Structural equation models with unobservable variables and measurement error: Algebra and statistics. J. Marker. Res. 1981;1:382–388. doi: x.1177/002224378101800313. [CrossRef] [Google Scholar]
35. Hair F.J., Jr., Sarstedt G., Hopkins 50. Fractional to the lowest degree squares structural equation modeling (PLS-SEM) An emerging tool in business research. Eur. Bus. Rev. 2014;26:106–121. doi: 10.1108/EBR-10-2013-0128. [CrossRef] [Google Scholar]
36. Nitzl C., Roldan J.Fifty., Cepeda M. Mediation analysis in partial least squares path modeling: Helping researchers discuss more sophisticated models. Ind. Manag. Data Syst. 2016;116:1849–1864. doi: x.1108/IMDS-07-2015-0302. [CrossRef] [Google Scholar]
38. Baron R.M., Kenny D.A. The moderator–mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. J. Pers. Soc. Psychol. 1986;51:1173. doi: 10.1037/0022-3514.51.6.1173. [PubMed] [CrossRef] [Google Scholar]
39. Carrión G.C., Nitzl C., Roldán J.Fifty. Partial Least Squares Path Modeling. Springer; Berlin/Heidelberg, Germany: 2017. Mediation analyses in partial least squares structural equation modeling: Guidelines and empirical examples; pp. 173–195. [Google Scholar]
40. Kim J., Hong South., Min J. Antecedents of application service continuance: A synthesis of satisfaction and trust. Expert Syst. Appl. 2011;38:9530–9542. doi: 10.1016/j.eswa.2011.01.142. [CrossRef] [Google Scholar]
41. Jeyaraj A., Rottman J.W., Lacity G.C. A review of the predictors, linkages, and biases in IT innovation adoption enquiry. J. Inf. Technol. 2006;21:1–23. doi: 10.1057/palgrave.jit.2000056. [CrossRef] [Google Scholar]
42. Kettinger W.J., Lee C.C. Businesslike perspectives on the measurement of information systems service quality. MIS Q. 1997;21:223–240. doi: 10.2307/249421. [CrossRef] [Google Scholar]
43. Moliner M.A., Sánchez J., Rodríguez R.M., Callarisa Fifty. Relationship quality with a travel agency: The influence of the postpurchase perceived value of a tourism package. Bout. Hosp. Res. 2007;7:194–211. doi: 10.1057/palgrave.thr.6050052. [CrossRef] [Google Scholar]
44. Liao C., Chen J.-L., Yen D.C. Theory of planning behavior (TPB) and customer satisfaction in the continued utilize of e-service: An integrated model. Comput. Hum. Behav. 2007;23:2804–2822. doi: ten.1016/j.chb.2006.05.006. [CrossRef] [Google Scholar]
Articles from International Periodical of Environmental Research and Public Health are provided here courtesy of Multidisciplinary Digital Publishing Institute (MDPI)
Source: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6982020/
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