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Article

Older Travelers’ E-Loyalty: The Roles of Service Convenience and Social Presence in Travel Websites

by
Yahua Bi
and
Insin Kim
*
Department of Tourism and Convention, Pusan National University, Busan 46241, Korea
*
Author to whom correspondence should be addressed.
Sustainability 2020, 12(1), 410; https://doi.org/10.3390/su12010410
Submission received: 1 December 2019 / Revised: 22 December 2019 / Accepted: 1 January 2020 / Published: 4 January 2020
(This article belongs to the Special Issue Influencing Factors of Traveler Loyalty for Destination, Company, and Brand)
Browse Figure
Versions Notes

Abstract

:
The research aims to examine what service convenience factors drive customer satisfaction in travel websites from the perspective of older travelers, and if older travelers’ satisfaction enhances e-loyalty. Additionally, drawing on socioemotional selectivity theory, this study argues that the social presence in travel websites plays a significant moderating role in increasing older travelers’ satisfaction. To empirically verify the conceptual model, an online survey was conducted targeting older travelers aged over 50 in the USA who have purchased products via travel websites. The data from 308 older travelers were analyzed, and the results revealed four dimensions of service convenience positively influence satisfaction. Unexpectedly, access convenience and transaction convenience do not influence older travelers’ satisfaction. The older travelers’ satisfaction with travel websites has a positive impact on e-loyalty. Additionally, social presence amplifies the effect of post-purchase convenience on satisfaction. The current research makes a significant contribution to understanding older travelers’ perceptions and behaviors for using e-commerce service in the field of tourism and provides practitioners with effective ways to attract older travelers for sustainable management of travel websites.

1. Introduction

In most Western countries, the older generation is growing rapidly [1]. In particular, according to data from the United States Census Bureau [2], individuals aged 50 and over accounted for 35.08% of the total United States population in 2017, and this has been continuously growing since 2010 (32.20%), emerging as a major market for the tourism industry. U.S. Department of Transportation [3] indicated that 80.30% of people aged 50 and older traveled.
Meanwhile, since older adults in recent years confront the circumstances of Internet-based services, they are increasingly eager to use the Internet [4]. According to a report by the Pew Research Center [5], 72% of those aged 50 to 64 have ever purchased products online and 59% of those aged 65 years and older usually shop online. That is, a growing number of older adults are moving towards Internet-based lifestyles [6], and older travelers’ online shopping has been mainstreamed these days. However, despite the desire of older travelers to search for travel information and purchase travel products via the Internet, older adults have been interrupted in using information technology due to a variety of barriers in online environments [4,6,7]. According to Gitlow [4], a lack of computer knowledge and difficulty in navigating are the main barriers preventing older adults from going online [6]. Compared with younger adults, older adults confront more risk and traditional barriers while online shopping [7]. Thus, it is necessary to examine service convenience from the older travelers’ perspective to improve older travelers’ technological acceptance and have favorable attitudes towards the Internet [8], ultimately contributing to sustainable e-commerce in the travel context.
Since e-loyalty leads to improving transaction intention for products in the websites [9], positive word-of-mouth [10], and continuous purchase intention online [11], researchers have identified various driving forces to increase e-loyalty, especially in the era of e-commerce [12]. In particular, in travelers’ e-commerce, although satisfaction has been widely known as the main component to enhance their e-loyalty e.g., [13], travel websites’ service convenience factors maximizing older travelers’ satisfaction has been undiscovered. Therefore, it is essential to identify crucial factors of service convenience optimized for older travelers.
Since Copeland [14] initially proposed the convenience theory, scholars have suggested that there are distinctive and unique convenience dimensions in the service industry [15,16,17,18,19]. Although researchers have conducted extensive studies on online convenience, they mainly focused on younger adults or general users [20,21]. For example, Colwell et al. [22] developed a multiple-item scale and five dimensions of service convenience in the mobile and Internet usage context. Duarte et al. [23] identified critical dimensions of online convenience in inducing customer intention to shop online from the perspective of younger adults. In other words, scholars have ignored the demands of older travelers for online convenience even though older consumers are becoming a significant market in the travel industry and seniors also confront the circumstances of Internet-based services. Therefore, the current study targeted older travelers who purchase travel products and services via travel websites.
According to the socioemotional selectivity theory, older individuals are willing to behave by emotional motivations rather than cognitive challenges due to the viewpoint of a limited lifetime [24]. Several previous studies applying this theory asserted that older individuals are more likely to spend time on leisure, be responsive to emotional stimuli, and experience social interactions through the Internet or TV [25,26,27,28]. Thus, it is critical to examine the function of social presence in amplifying their satisfaction while older travelers use the Internet.
The purposes of the research are to identify important service convenience factors of travel websites in enhancing satisfaction from the perspective of older travelers, to test the effect of older travelers’ satisfaction on e-loyalty, and to investigate whether social presence strengthens the effect of service convenience on older travelers’ satisfaction.

2. Literature Review

2.1. Service Convenience

Service convenience is defined as “the speed and ease of shopping” [20] (p. 194). Copeland [14] originally presented the concept of service convenience, meaning that customers can find products in an easy-to-access store and purchase products with minimal effort. In other words, service convenience allows customers to complete consumption in a short time with insignificant manpower [29]. Convenience products should not require too much effort and time to compare and purchase [30] and pose low risks to customers [31]. Since service convenience reduces customers’ time and energy expenditure [15], a number of scholars have examined the convenience in various fields, such as online stores [21], art museums [32], and commercial banks [33]. In the tourism field, although Chang et al. [34] addressed convenience as a key factor driving customer satisfaction in the restaurant industry, identifying crucial factors of online customer convenience still remains an important issue for the tourism industry in the circumstance that the number of traditional agents is decreasing due to technological advances.
When using online services, customers cannot communicate directly with employees. Due to an unclear path, customers would feel difficulties in browsing a website and getting information [35], suggesting the importance of investigating online convenience. Website convenience refers to “the extent to which a customer feels that the website is simple, intuitive, and user friendly” [36] (p. 4). Website convenience can reduce the time spent by customers in the purchasing process [37]. Website convenience, the degree of “easy to use” in the transaction process [38], is the basic determinant of system use [39] and affects people’s choices and actions at various stages of the information search process [40].
Researchers have suggested that convenience should be considered as a multidimensional construction [15,16,19,41]. Yale and Venkatesh [19] (p. 405) divided product convenience into six classes: “time utilization, handiness, appropriateness, portability, accessibility, and avoidance of unpleasantness.” In a study on the retail industry, Seiders, Berry and Gresham [16] suggested four types of convenience, namely, access, search, possession, and transaction. In each stage of the consumer purchase process, Berry, Seiders and Grewal [15] (p. 6) proposed five types of convenience: “decision, access, transaction, benefit, and post-benefit”. Seiders, Voss, Godfrey and Grewal [17] empirically developed and verified these five dimensions. Later, Lai, Ulhas and Lin [42] modified five dimensions based on the background of online shopping [15,17]. Drawing from the classification of convenience from Berry, Seiders and Grewal [15], Seiders, Voss, Grewal and Godfrey [18], and Seiders, Voss, Godfrey and Grewal [17], Jiang, Yang and Jun [20] (p. 197) developed online shopping convenience dimensions: “access, search, evaluation, transaction, possession, and post-purchase convenience.”
Access convenience: Customers always want to open the shopping site anytime, anywhere for consumption. Access convenience reflects the fact that customers can easily get initial service delivery [15], minimizing physical labor related to initiating exchanges [17]. Good access convenience greatly increases the customer’s initial interest in using a website. Access convenience is one of the crucial system qualities valued by online purchasers [43].
Search convenience: Websites should ensure that customers can quickly search for products and services. Search convenience reflects how easily a customer is able to find the service or product they need on a website and includes website design, navigation, and product information selection and availability [44]. Since search convenience allows customers to compare prices or items with simple clicks, it is a crucial factor in promoting online shopping, leading to saving search costs for customers [45]. While online shopping, if insufficient input knowledge in searching for products is provided to customers, they would be reluctant to continue consumption behavior [46]. In the online hotel context, Kim and Kim [47] found that search convenience is a key predictor of willingness to book hotels, and they highlighted that online hotel agents should enhance information search convenience.
Evaluation convenience: Consumers can easily understand product attributes and evaluate through various information on the website, such as text, pictures and so on [20]. According to a survey related to online shopping in the United States [48], about half of Americans (46%) believe that customers’ evaluations help them to have confidence in purchasing products. Websites, such as booking, even allow customers to post product-related experience text and product images. Enough information can help users identify different products and services in the same category. If a travel website can provide customers with detailed product information, such as travel routes, travel options, meals and time required, then consumers can better understand travel products and make judgments. This evaluation convenience can be very effective in saving consumers’ time and effort during the purchase process [20].
Transaction convenience: Transaction convenience means that customers can easily and flexibly use various payment methods to complete online payments. An inconvenient transaction process can cause consumers to abandon the purchase. According to Rajamma et al. [49], the complication of filling an order, inflexibility in common information selection, technical failure at the checkout stage [49], and inconvenient payment method can affect a transaction. In the bricks-and-mortar shopping context, consumers generally dislike waiting too long for payment [50]. Online customers may give up their shopping when the transaction process is too long, confusing or complicated [51].
Possession convenience: Seiders, Berry and Gresham [16] (p. 85) indicated that possession convenience is “the speed and ease with which consumers can obtain desired products”. In the online shopping context, the lack of ability to see, touch, and try products and services [52], makes possession convenience more crucial compared with offline shopping. As such, is essential to keep the products and services ordered by customers reserved correctly. For travel websites, it is even more important to ensure that customers receive confirmations and itineraries after purchase. The price on the website should be the same as on the order. Duarte, e Silva and Ferreira [23] found that possession convenience has become the most key driver for online shopping, which is the main reason for consumers to shop online. Possession convenience reflects the ease that consumers get accurate online ordering products or services [20].
Post-purchase convenience: After the customer purchases, the website needs to provide after-sales service (e.g. refund) and subsequent security (e.g. the protection of the customer’s personal information). Post-purchase convenience reflects the ease of the time and effort spent reconnecting with the company after the purchase [15]. Post-purchase convenience is associated with consumer demand for product repair, maintenance, cancel or refund [15]. After the customer purchases products or services, the website should ensure that the customer’s personal information is not abused and the consumer feels safe about the transaction. The existing study demonstrated that providing post-purchase conveniences, such as a timely return service and complaint support, can enhance customers’ repurchase intention [53].

2.2. Customer Satisfaction

Online customer satisfaction refers to the customers’ experience of contentment with a given travel e-commerce environment [54]. Since customer satisfaction can be the best indicator of future purchase intentions and loyalty [55,56,57,58,59,60], it is essential to satisfy customers for the companies’ achievement of good economic returns [61,62,63].
In the aspect of customer satisfaction, service convenience plays a role in reducing customers’ cost in time and effort in the process of receiving services, thereby increasing satisfaction [22]. In particular, online convenience is a vital factor affecting online customer satisfaction [64]. Empirical studies have also demonstrated evidence that service convenience significantly influences satisfaction [19,33]. For example, Colwell, Aung, Kanetkar and Holden [22] developed a service convenience scale and examined the effect of service convenience using multiple items on overall satisfaction targeting students. They found that service convenience was a significant antecedent of satisfaction with Internet use [22]. Mpinganjira [21] identified service convenience dimensions in the context of online stores and verified that an online store’s service convenience influenced service satisfaction with a sample consisting of 127 online consumers: 88.8% were aged between 18 and 49, while 10.2% were more than 50 years old.
Though a large number of studies regarding service convenience have been conducted, previous studies have asserted that convenience is more important among older customers [26,65]. In addition, as individuals are older, they are more likely to rely on the Internet [25] and TV home shopping [26] due to physical immobility. Lim and Kim [26] suggested that TV shopping companies can satisfy older customers with limited shopping mobility by adding convenience benefits [26].
Additionally, according to innovation resistance theory, changes generate conflict between existing culture and innovation, thus the conflict causes users to resist innovation [66]. In particular, as using the innovative product is not compatible with users’ work and habits, consumers tend to resist accepting innovation. A number of researchers have identified that older consumers are more likely to resist to accept technology usage than young people [7,67,68], perceiving a lack of convenience. Although previous studies found service convenience is a significant predictor leading to customer satisfaction, it is essential to identify crucial factors of online travel service convenience generating older travelers’ overall satisfaction with travel websites. Thus, the following hypotheses were established.
Hypothesis 1 (H1).
Access convenience positively influences older travelers’ satisfaction.
Hypothesis 2 (H2).
Search convenience positively influences older travelers’ satisfaction.
Hypothesis 3 (H3).
Evaluation convenience positively influences older travelers’ satisfaction.
Hypothesis 4 (H4).
Transaction convenience positively influences older travelers’ satisfaction.
Hypothesis 5 (H5).
Possession convenience positively influences older travelers’ satisfaction.
Hypothesis 6 (H6).
Post-purchase convenience positively influences older travelers’ satisfaction.

2.3. The Moderating Role of Social Presence

Socioemotional selectivity theory posits that as people get older, they increasingly put the value on emotionally meaningful aspects to lead to a meaningful life, such as emotional social relationships and social interconnections [69]. According to the socioemotional selectivity theory, older individuals are willing to behave by emotional motivations rather than cognitive challenges due to the viewpoint of the limited lifetime [24]. Several previous studies applying this theory asserted that older individuals are more likely to spend time on leisure, be responsive to emotional stimuli, and experience social interactions through the Internet or TV [25,26,27,28]. Thus, while older individuals use the Internet, a feeling of human interaction, that is, social presence, is needed along with the convenience of technology.
Social presence refers to “the degree of salience of the other person in the interaction and the consequent salience of the interpersonal relationships…” [70] (p. 65). Social presence, described as the feeling or sense of warmth and sociability within a website, has desirable consequences in an online context [71]. In other words, social presence is a crucial element to evaluate online service. Dash and Saji [72] provided evidence that the social presence embedded in the offline shopping context can reduce the perceived risk in the online shopping process.
In the existing service literature, social presence has been highlighted as a key precursor influencing users’ satisfaction in a variety of online contexts, such as in a mobile instant messaging environment [73], digital service encounters [74], and e-commerce [75]. Additionally, social presence has been used as an antecedent enhancing customers’ perception of usefulness, enjoyment [76], trust [77], and e-loyalty [78] in the online shopping context.
However, several existing studies have suggested social presence should be investigated as the moderating function in an online context. Since online shopping customers tend to pursue utilitarian value, social presence goes beyond psychological effects on customer satisfaction in an online context. Thus, since social presence constitutes a boundary condition, it is examined as a moderator, not a precursor. Several scholars have identified that social presence has a moderating effect. For example, Chung et al. [79] empirically verified the moderating effect of social presence in the context of social media for travel information. The results of data analysis from 527 users who conducted user-generated content on social media revealed that social presence significantly moderated relationships not only between argument quality and perceived usefulness but also between source credibility and social relationships.
Robert and Dennis [80] also noted that when customers use social media with a high social presence, they perceive usefulness more by paying their attention than customers with a low social presence. That is, when older travelers perceive high human warmth in the travel websites they visit to search for or purchase travel products/services, the effect of each service convenience (access, search, evaluation, transaction, possession, and post-purchase convenience) on satisfaction with online consumption would strengthen. Based on the existing literature and empirical studies, this study suggests the following hypotheses.
Hypothesis 7a (H7a).
Social presence moderates the effect of access convenience on satisfaction.
Hypothesis 7b (H7b).
Social presence moderates the effect of search convenience on satisfaction.
Hypothesis 7c (H7c).
Social presence moderates the effect of evaluation convenience on satisfaction.
Hypothesis 7d (H7d).
Social presence moderates the effect of transaction convenience on satisfaction.
Hypothesis 7e (H7e).
Social presence moderates the effect of possession convenience on satisfaction.
Hypothesis 7f (H7f).
Social presence moderates the effect of post-purchase convenience on satisfaction.

2.4. E-Loyalty

As a non-random behavior [81], e-loyalty can be defined as positive customer attitudes towards using the website as a consumer environment, which can result in continued reuse or purchase [54]. Given that customer loyalty leads to company’s success [82,83,84], since e-loyalty is an essential consequence of website services [85], maintaining and improving e-loyalty has become an important consideration for marketing researchers and practitioners [12,86,87], especially in the era of e-commerce [12].
As such, researchers have come up with various driving forces to increase e-loyalty, such as e-customer satisfaction from online determinants (website image, online routine, online knowledge) [88], attitude on online travel websites from the perspectives of seniors [27], e-trust from website design (navigation design, visual design, and information design) [89], and convenience (easy to navigate and user-friendly) [90]. Through these studies [27,88,89,90], it is fundamental to promote customers’ e-loyalty in the survival and development of websites [91]. That is, e-loyalty leads to improving transaction intention for products in the websites [9], positive word-of-mouth [10], and continuous purchase intention online [11].
In the tourism context, various studies have investigated the relationship between customer satisfaction and e-loyalty and have demonstrated that customer satisfaction is a key factor in positively affecting e-loyalty e.g., [88,91,92]. In particular, if consumers are satisfied with websites they are using, they continue to consume on the websites [81]. Compared with offline consumption, online consumers can see many competitive options at the same time, and leave the website easily [91]. That is, when customers are not satisfied with websites, they can find other alternatives and even choose competitors [54]. So the impact of customer satisfaction on e-loyalty is even stronger in the online environment than the offline environment. Based on the aforementioned literature, the following hypothesis is suggested.
Hypothesis 8 (H8).
Older travelers’ satisfaction positively influences e-loyalty.
Figure 1 illustrates the conceptual model hypothesized in this study.

3. Method

3.1. Measurement Items

The measurement items were derived from previous studies that have empirically examined consumer behaviors and have been found to be reliable and valid. Twenty items were used to measure the six sub-dimensions of service convenience based on the studies ouf Jiang, Yang and Jun [20] and Lai, Ulhas and Lin [42]: three items for access convenience, four for search convenience, three for evaluation convenience, three for transaction convenience, four for possession convenience, and three for post-purchase convenience. The study of Jiang, Yang and Jun [20] focused on service convenience rather than price in the e-commerce context and the researchers developed rigorous measurement items of service convenience through interviews. The items Jiang, Yang and Jun [20] developed were appropriate to measure older travelers’ service convenience in e-commerce and we adopted and somewhat revised measurement items to fit the context of travel websites. Four items asking whether the travel website was satisfactory were drawn from Kim et al. [93] and Kuo et al. [94]. Four items measuring e-loyalty were derived from Anderson and Srinivasan [54]. Social presence was measured with five items adopted from Cyr, Hassanein, Head and Ivanov [78] and Gefen and Straub [71], with sample items such as “There is a sense of human contact on the travel website.” A five-point Likert-scale, from 1 (strongly disagree) to 5 (strongly agree), was used in rating all items.

3.2. Data Collection and Sample

The web-based survey was conducted by relying on a survey research company with a large number of panels in the U.S. The research company sent emails to invite 1000 older travelers who often travel because it was necessary to collect approximately 300 responses to empirically test the research model. To select the proper sample for the current study, two questions were asked at the beginning of the questionnaire, which screened out unqualified participants. Based on recommendations in previous North American research, (Roberts and Zhou [95], Szmigin and Carrigan [96], and Zhou and Chen [97]) the criterion for older adults was determined to be more than 50 years old. That is, the specific subjects targeted in this study were individuals aged over 50 who had purchased online travel products or services in the last three months. Of the 1000 invitations by convenient sampling, 884 individuals responded to participate in the survey, but only 315 people were older travelers who bought products or services via travel websites. The valid 308 cases after excluding problematic answers were used in our further analyses.
A profile of the sample is presented in Table 1. There were slightly more females (54.9%) than males (45.1%), and the annual income of the respondents was somewhat equally distributed: Under $20,000, 30%, $20,000–less than $40,000, 73%, $40,000–less than $60,000, 71%, $60,000–less than $80,000, 83%, $80,000–less than $100,000, 36%, and over $100,000, 15%. Regarding ethnicity, the largest proportion of the sample (85.1%) was Caucasian, and more than two-thirds of the respondents (68%) held higher than a college degree. The sample was predominantly retired (44.2%) or semi-retired (31.5%) people. The mean age of the participants was 60.1 years old.

4. Results

4.1. Measurement Model Validation

Prior to testing the hypothesized relationships, the validity and reliability of the multidimensional constructs were estimated with confirmatory factor analysis (CFA) based on the recommendation of Hair et al. [98]. Overall, the model fit indices met the acceptable criterion: χ2 = 698.023, df = 322, comparative fit index (CFI) = 0.951, root mean square error of approximation (RMSEA) = 0.062, incremental fit index (IFI) = 0.952, and Tucker-Lewis index (TLI) = 0.943.
Convergent validity was assessed by checking whether (1) each standardized factor loading for the corresponding construct is higher than 0.5 and (2) the average variance extracted (AVE) value for each construct exceeded the cut-off value of 0.5 [99]. As Table 2 and Table 3 show, the factor loadings indicated substantially high values ranging from 0.681 to 0.929, and the AVE values ranged from 0.621 to 0.787. Discriminant validity was evaluated by confirming that the AVE values of constructs were higher than squared correlations for each construct. As shown in Table 3, most were satisfactory. Though some of the squared correlations indicated higher AVE values of the corresponding construct, Bagozzi and Yi [100] suggested that a chi-square difference test between a free model and a combined model for pairs of constructs should be conducted to estimate whether these concepts are different from each other. The results of the chi-square difference test showed that each construct was significantly different, indicating ∆χ2 = 83.758 (search convenience–evaluation convenience), ∆χ2 = 114.433 (transaction convenience–possession convenience), and ∆χ2 = 141.565 (satisfaction–e-loyalty) > χ20.05 = 14.067 (df = 7). Thus, discriminant validity was confirmed.

4.2. Structural Model Testing

In order to empirically test the causal relationships hypothesized in the current study, the structural model was analyzed. The overall fit of the structural model was satisfactory (χ2 = 709.968, χ2/df = 2.165, df = 328, CFI = 0.951, IFI = 0.952, TLI = 0.943, RMSEA = 0.062). Hypotheses 1, 2, 3, 4, 5 and 6 to assess the effects of convenience sub-dimensions on older travelers’ satisfaction with travel websites were tested. The regression paths from search convenience (β = 0.215, t = 2.115), evaluation convenience (β = 0.235, t = 2.877), possession convenience (β = 0.218, t = 2.073) and post-purchase convenience (β = 0.145, t = 2.170) to satisfaction were positive and significant. Therefore, hypotheses 2, 3, 5 and 6 were supported. However, the impacts of access convenience (β = 0.067, t = 1.251) and transaction convenience (β = 0.098, t = 1.035) on satisfaction were not significant, indicating that hypotheses 1 and 4 were not supported. In addition, hypothesis 8 was assessed. The link between satisfaction and e-loyalty was positively significant (β = 0.901, t = 18.574, p <0.05). The result provides support for hypothesis 8. Table 4 shows the results of the structural model test.

4.3. Moderating Effect

The moderating effect of social presence on the relationship between convenience and satisfaction was assessed (H7a–H7e). The path coefficient between convenience and satisfaction was compared between high- and low-perceived social presence groups. The sum of five items for social presence was used as the moderator score. To assess the differential effects of social presence for these two subgroups, a chi-square difference test was conducted [101]. The results of the chi-square difference test showed that the moderating effect of social presence on the effects of five sub-dimensions (access convenience, search convenience, evaluation convenience, transaction convenience, and possession convenience) out of six on older travelers’ satisfaction were insignificant at the 0.05 level, indicating that H7a–H7e were not supported. However, the chi-square difference between the unconstrained and constrained models of the link from post-purchase convenience to satisfaction was significant at the 0.05 level (∆χ2 = 4.722 > χ20.05 (1) = 3.84, df = 1), indicating significant differences in the effect of post-purchase convenience on older travelers’ satisfaction, providing support for H7f.
For the high-perceived social presence group, the path coefficient between post-purchase convenience and older travelers’ satisfaction was 0.402 (p < 0.01), whereas, for the low-perceived social presence group, it was 0.013 (p > 0.01). That is, there was a significant difference in the effect of post-purchase convenience on older travelers’ satisfaction by the perceived social presence levels. In sum, social presence is more effective in enhancing the effect of post-purchase convenience on the satisfaction of older travelers with travel websites.

5. Discussion and Implications

Although more and more travelers are shopping online with the development and popularity of the Internet, one of the major reasons older travelers could not do online shopping is its inconvenience [4]. Therefore, the current study attempted to identify the important dimensions of service convenience enhancing the satisfaction of older travelers, further leading to e-loyalty. Additionally, the study verified that social presence amplifies which paths from online travel service convenience to older travelers’ online shopping satisfaction. The current study is unique because a service convenience model for older travelers was generated via an empirical study in the travel websites, contributing to sustainable e-commerce in the travel context.
First, for older travelers, four of six service convenience dimensions in travel websites, namely, search, evaluation, possession, and post-purchase convenience, were found to enhance the elderly’s satisfaction with online travel shopping. Specifically, evaluation convenience is the most important dimension affecting older travelers’ satisfaction. It can be interpreted that older travelers want easy-to-understand information with detailed descriptions and pictures regarding travel products and services in travel websites because of the limitation in getting sufficient information (e.g., limited external mobility) [26]. Therefore, travel websites should provide sufficient product information such as travel routes, travel options, meals and time spent in travel sites by using entertaining tools such as pictures, animation, music, and video. Surprisingly, access convenience and transaction convenience had no effects on older travelers’ satisfaction. In spite of unexpected findings, it is explicable in the older travelers’ online context. According to a report related to technology adoption among older Internet users in the United States [6], 34% of older internet users said they have no confidence in using electronic devices to conduct online tasks, and 48% of old internet users said they need help from others when using new electronic devices. In addition, access convenience involves the time and effort that customers spend before reaching a travel website [102]. Perhaps older travelers may still have barriers to access online while younger adults can be online anytime and anywhere they want for travel shopping through technology tools such as mobile devices. Additionally, they may receive help from other people in the transaction process when online travel shopping.
Second, the findings of the study stress the role of social presence as a moderator of the relationship between service convenience and customer satisfaction, indicating that social presence strengthens the effect of post-purchase convenience on older travelers’ satisfaction. The result implies that older travelers may have a certain anxiety about potential problems in post-purchase (e.g., refund, cancellation or exchange) through online travel shopping, and they may need more human interaction rather than technology in this process. Therefore, online travel companies should offer a feeling of warmth to older travelers in the online post-purchase process by assigning service providers and offering online learning for older travelers, recognizing policies for refund, cancellation or exchange and preventing them from paying a penalty unnecessarily. However, the results indicate that social presence was insignificant in moderating the effects of the other five conveniences on satisfaction. As one of the reasons, since access convenience is the initial process of e-commerce, online social presence might not influence the relationship between access convenience and satisfaction. If travel websites would like to strengthen the effect of access convenience through social warmth for older travelers, they should design ways to educate older travelers offline regarding how to access them easily.
Finally, the results highlight that satisfaction with using travel websites is an important antecedent for greatly improving e-loyalty among older travelers under the context of travel websites. This is widely underpinned by previous extensive studies [88,91,92,103]. This study corroborated previous research reported that customers who perceive greater satisfaction tended to express stronger e-loyalty and it also expanded the existing research in the online travel context for older travelers. That is, in this study, we identified older travelers’ e-loyalty, repurchasing travel products or reusing travel website services continuously, is driven by satisfaction, and the older travelers’ satisfaction is maximized by enhancing critical service conveniences of travel websites. Maintaining existing older travelers and promoting future consumption are the most important goals for online travel companies. When online travel companies targeting older travelers develop travel products or services, they should consider providing a convenient shopping environment for older travelers. This will not only improve online travel companies’ performance but will also encourage older travelers to enjoy online shopping and continue to consume in the online environment.
Theoretically, although previous research has been limited in highlighting convenience as a driving force for online shopping by older adults e.g., [7], this study sheds new light on specific convenience factors in driving older travelers’ satisfaction, contributing to tourism literature. In addition, the online service convenience model is differentiated in that it introduced a necessary concept of older travelers, the feeling of warmth and sociability [71] like human interactions (social presence), in a limited environment that uses information and communications technology tools. This research contributes to extending psychological knowledge in understanding older people by applying the socioemotional selectivity theory [24,69] to tourism literature. This study also offers effective suggestions to online travel companies to develop advanced technology that induces a sense of warmth, like human interactions.
Despite the significant implications of this study, certain limitations exist. Although the study examined older travelers’ attitudes and behavior in travel websites by targeting older adults by their actual age, socioemotional selectivity theory emphasizes that individuals’ limited time should be considered [24,69]. In this respect, future research is needed to examine older travelers’ distinctive behaviors online according to psychological age rather than actual age. Additionally, as Menor-Campos et al. [104] argued, since tourists have different motivations, it is necessary to identify differences regarding using tourism products depending on the socio-demographic profile and characteristics of their trip across tourists’ clusters in a future study.

Author Contributions

Y.B. and I.K. designed the research model, analyzed the data, and wrote the paper together. All authors have 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 interest.

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Sustainability 12 00410 g001 550
Figure 1. Hypothesized conceptual model.
Figure 1. Hypothesized conceptual model.
Sustainability 12 00410 g001
Table
Table 1. Profile of respondents (n = 308).
Table 1. Profile of respondents (n = 308).
CharacteristicsCategoriesFrequency (N)Percentage (%)
GenderMale13945.1
Female16954.9
Income level
(Annual income)		Under $20,000309.7
$20,000–less than $40,0007323.7
$40,000–less than $60,0007123.1
$60,000–less than $80,0008326.9
$80,000–less than $100,0003611.7
Over $100,000154.9
EthnicityCaucasian26285.1
Hispanic/Latino103.2
Asian227.1
Other82.6
Level of EducationSome high school41.3
High school graduate9330.2
College or university graduate15550.3
Post-graduate5618.2
Current employmentEmployed72.3
Retired13644.2
Semi-retired9731.5
Homemaker175.5
Other5116.5
Mean age = 60.1 years old
Table
Table 2. Confirmatory factor analysis: Items and factor loadings.
Table 2. Confirmatory factor analysis: Items and factor loadings.
ItemsLoadings
Service Convenience
Access convenienceI can shop anytime I want on the travel website.0.871
The travel website is always accessible.0.828
I can order travel products and services wherever I am.0.839
Search convenienceThe travel website is user-friendly for making purchases.0.870
The travel website is easy to understand and navigate.0.810
I am able to find the desired travel products and services quickly.0.816
The travel product and service classification are intuitive and easy to follow.0.794
Evaluation convenienceThe website provides product specifics such as travel routes, tourism options, meals and the time required.0.808
The website provides sufficient information so that I can identify different travel products and services within the same category.0.861
The website uses both text and graphics to provide in-depth travel product and service information.0.686
Transaction convenienceOnline payment is simple and convenient.0.904
Payment methods are flexible.0.800
I am able to complete my purchase without difficulty.0.926
Possession conveniencePurchased travel products and services are reserved correctly.0.853
I received a confirmation message after reserving all the travel products and services.0.840
I received my e-ticket itinerary receipt.0.856
The prices of reserved travel products and services are identical to those on the order form.0.869
Post-purchase convenienceIt takes little effort to change or refund some unwanted travel products and services.0.681
The website does not misuse my personal information.0.910
I feel safe in my transactions.0.899
Satisfaction
Overall, I was satisfied with the travel website.0.879
The travel website information content met my needs.0.916
I was satisfied with the offerings on the travel website.0.845
I was satisfied with online buying on the travel website compared to offline buying.0.762
E-loyalty
If I were to buy tourism products/services again, I would likely buy them from the travel website.0.886
I am likely to return to this travel website for my next purchase.0.929
I am likely to make another purchase from this travel website in the next year.0.836
I intend to continue using this travel website rather than discontinue its use.0.896
Note: All factor loadings were significant at p < 0.001.
Table
Table 3. Descriptive statistics and associated measures.
Table 3. Descriptive statistics and associated measures.
ConstructAVE12345678
1Access convenience0.7160.936 a0.632 b0.5610.6240.6150.4490.5880.550
2Search convenience0.6770.399 c0.9400.8220.7410.7740.7420.7960.718
3Evaluation convenience0.6210.3140.6750.8940.6610.6630.6550.7510.678
4Transaction convenience0.7710.3890.5490.4360.9320.8790.7010.7340.705
5Possession convenience0.7300.3780.5990.4390.7720.9440.7420.7570.743
6Post-purchase convenience0.7000.2010.5500.4290.4910.5500.8860.7020.692
7Satisfaction0.7260.3450.6330.5640.5380.5730.4920.9450.890
8E-loyalty0.7870.3020.5150.4590.4970.5520.4780.7920.950
Goodness-of-fit indices: χ2 (322) = 698.023, p < 0.001, χ2/df = 2.168
CFI = 0.951, IFI = 0.952, TL I = 0.943, RMSEA = 0.062
Note: AVE = Average variance extracted. GFI = Goodness-of-fit index. CFI = Comparative fit index. IFI = Incremental fit index. TLI = Tucker-Lewis index. RMSEA = Root mean square error of approximation. a Composite reliability is indicated along the diagonal. b Correlations are above the diagonal. c Squared correlations are below the diagonal.
Table
Table 4. Standardized parameter estimates for the structural model.
Table 4. Standardized parameter estimates for the structural model.
Paths Standardized Estimatet-ValueSupport
H1 Access convenience→Satisfaction0.0671.251No
H2 Search convenience→Satisfaction0.2152.115Yes
H3 Evaluation convenience→Satisfaction0.2352.877Yes
H4 Transaction convenience→Satisfaction0.0981.035No
H5 Possession convenience→Satisfaction0.2182.073Yes
H6 Post-purchase convenience→Satisfaction0.1452.170Yes
H8 Satisfaction→E-loyalty0.90118.574Yes

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MDPI and ACS Style

Bi, Y.; Kim, I. Older Travelers’ E-Loyalty: The Roles of Service Convenience and Social Presence in Travel Websites. Sustainability 2020, 12, 410. https://doi.org/10.3390/su12010410

AMA Style

Bi Y, Kim I. Older Travelers’ E-Loyalty: The Roles of Service Convenience and Social Presence in Travel Websites. Sustainability. 2020; 12(1):410. https://doi.org/10.3390/su12010410

Chicago/Turabian Style

Bi, Yahua, and Insin Kim. 2020. "Older Travelers’ E-Loyalty: The Roles of Service Convenience and Social Presence in Travel Websites" Sustainability 12, no. 1: 410. https://doi.org/10.3390/su12010410

APA Style

Bi, Y., & Kim, I. (2020). Older Travelers’ E-Loyalty: The Roles of Service Convenience and Social Presence in Travel Websites. Sustainability, 12(1), 410. https://doi.org/10.3390/su12010410

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