How Are Travel E-Commerce Platforms Becoming Sustainable? A Discrete Choice Experiment Based on the Technology Acceptance Preferences of Elderly Tourists

Abstract

The technology acceptance preferences of elderly tourists is one of the important factors influencing their continuous use of tourism e-commerce platforms and promoting the sustainable development of tourism e-commerce platforms. The current tourism market continues to expand within the elderly population. Further, the internet has become the primary channel for tourists’ online consumption in the digital age. This study aims to explore the technology acceptance preferences of elderly tourists for tourism e-commerce platforms, considering active aging and its influence by constructing two adaptation to aging scenarios for tourism e-commerce platforms composed of technology acceptance attributes. Using experimental data from 94 elderly tourists in Nanjing, a mixed logit regression analysis was conducted to explore the characteristics and personalized differences in the respondents’ technology acceptance preferences while using tourism e-commerce platforms. The study found that information access, information understanding, information protection policy and privacy protection technology have a significant positive impact on the consumption preference of elderly tourists. Among them, in the scenario without adaptation to aging, the order of the variables which influence the consumption preferences of elderly tourists online is information access, privacy protection policy, information understanding and privacy protection technology, which reflects the current demand of elderly tourists for easy access to effective information and strong privacy protection. In the context of adaptation to aging, the order is privacy protection policy, information understanding, information access and privacy protection technology, which shows that in the context of improved information access and understanding, elderly people pay more attention to the privacy protection provided by the platform. Moreover, there is individual heterogeneity in elderly tourists’ preferences for the technology acceptance of tourism e-commerce platforms. With the aging population and the digital processes, exploring the influencing factors of elderly tourists’ internet technology acceptance preferences is helpful in promoting the sustainable development of tourism e-commerce platforms in the era of active aging, bridging the digital divide and providing decision support for the practice of an active aging strategy.

1. Introduction

The number of people over the age of 60 in China reached 297 million at the end of 2023, making China the country with the largest elderly population in the world and with the world’s largest market for elderly tourists, according to the National Bulletin on the Development of Aging Undertakings. According to the 53rd statistical report on the development of the Internet in China, in 2023, online travel bookings in China exceeded 454 million, making it becoming the most important travel booking channel for tourists. However, the research shows that people aged 60 years old and above have the lowest Internet usage rate, and technological advancements have brought challenges to society, particularly for the elderly population [1,2]. As individuals age and their cognitive abilities deteriorate, their ability to obtain information, understand content and identify privacy risks declines significantly, which seriously hinders their acceptance of travel service platforms [1]. Tourism e-commerce platforms (or online travel agents, OTA) refer to enterprises that provide tourism products and services through the Internet. Users can book hotels, airline tickets and vacations through these platforms [3]. This is a new form of business in the tourism industry which has emerged in the Internet era. To actively cope with the aging population, travel e-commerce platforms, such as Ctrip and Feizhu, have launched age-appropriate pages for elderly tourists in an attempt to lower the technology acceptance barriers for elderly tourists on the Internet. However, there remains a lack of accurate measurements and assessment of elderly tourists’ experiences of the age-appropriate transformation of travel e-commerce platforms. It has also failed to systematically explore what factors affect the effect of the age-appropriate transformation of the tourism e-commerce platform. Therefore, the conclusions of the existing research cannot fully reveal the influence mechanism of elderly tourists’ Internet technology acceptance preference. Thus, it is difficult to effectively guide the tourism e-commerce platform to implement adaptation to aging and upgrades to effectively improve and protect the digital and intelligent experiences of elderly tourists.

Currently, online reservation platforms are faced with the coexistence of rapid macro-growth and a micro-service lag [4,5]. Although Ctrip, Feizhu and Qunar have all launched age-appropriate APP pages for elderly tourists, adaptations still remain restricted to the level of enlarging fonts and simplifying operations, thereby failing to improve and ensure the digital and intelligent experience of elderly tourists according to the level of technology acceptance of elderly tourists. Many scholars have conducted extensive studies on the Internet use behaviors of elderly tourists, and found that factors such as individual characteristics, technical facilities, psychological state and social environment significantly affect the online bookings, online comments and other Internet behaviors of elderly tourists [6,7,8]. However, there remains a lack of accurate assessment of elderly tourists’ preferences for technology acceptance on tourism e-commerce service platforms. There is still no systematic research on the factors that affect the aging adaptation of the tourism e-commerce service platforms. Consequently, the existing research conclusions cannot fully reveal the influence mechanism of elderly tourists’ Internet technology acceptance preference behavior, and nor can they effectively guide the tourism e-commerce platforms to implement adaptation to aging and upgrades.

The contradiction between the growing travel demands of elderly tourists and the expanding digital divide has become a key factor restricting their tourism decision-making and tourism experience [9,10]. Accelerating the tourism e-commerce platforms’ adaptation to the aging population is important for the development of the silver tourism market. The technology acceptance model is widely used to detect users’ acceptance of emerging technologies, and demonstrates strong predictive ability [11,12]. A large number of researchers have paid attention to the research on online tourism platform user behavior. Most of the research activities have been analyzed through the platform technical indicators, and the technology acceptance model is one of the widely used models [9,10,13]. As a digitally vulnerable group, elderly people have serious technical anxiety and low self-efficacy. It is urgent to study their preferences for the technology acceptance of tourism e-commerce platforms. However, there is a lack of online travel booking research for the elderly population, so this paper innovatively opens up a new research perspective on the elderly population and broadens the technology acceptance model to the field of travel e-commerce, taking Nanjing as a case study, constructing research variables from three dimensions: perceived ease of use (information acquisition); perceived usefulness (information understanding); and perceived risk (privacy protection policy, privacy protection technology and privacy settings). Then, it employs discrete choice experimental methods to explore different scenarios of adaptation to aging and non-adaptation to aging. The influence of various combinations of attributes on elderly tourists’ preferences for Internet technology acceptance and the heterogeneity analysis based on individual characteristics will reveal elderly tourists’ acceptance of technology for the age-appropriate transformation of tourism e-commerce platforms. This influence mechanism will enrich the theoretical research on elderly tourists’ preferences for Internet tourism technology acceptance in the age of digital intelligence. The study also aims to provide practical guidance for the age-appropriate transformation of tourism e-commerce platforms in the background context of aging populations.

2. Literature Review and Model Construction

2.1. Technology Acceptance Model

The technology acceptance model contains four key variables: perceived usefulness, perceived ease of use, usage attitude and behavioral intention [13]. It is widely used to detect users’ acceptance of emerging technologies, and demonstrates strong predictive ability [11,12]. While conducting research on the elderly population, some researchers found that perceived usefulness and perceived ease of use are the two most critical influencing factors when studying the influences on elderly people, and perceived ease of use and perceived usefulness have become emerging as the key factors affecting the acceptance of digital technologies by the elderly population [14,15,16,17]. Hence, according to the characteristics of the tourism e-commerce platform and the elderly population, information acquisition and information understanding are, respectively, included in the perceived usefulness and perceived ease of use. In recent years, the frequent phenomenon of tourism e-commerce platforms forcibly demanding users’ rights and the excessive collection of personal information have caused people to have many doubts and worries when they are asked to authorize privacy policy consent. Therefore, scholars have incorporated perceived risk factors to expand the technology acceptance model, and highlighted that the perceived risks of the Internet for elderly people have a negative impact on their behavioral intentions [18,19]. Especially for elderly tourists, the risks of unsafe payment transactions, personal privacy disclosure and information abuse have seriously hindered the willingness of elderly tourists to accept tourism e-commerce platforms [5]. The privacy threat model for elderly people classifies the harmful activities that may lead to privacy risks for elderly people, and classifies the strategies for alleviating the privacy risk of elderly people into passive strategies and active strategies [6]. Some elderly people actively set their own privacy protections, while others do not adopt any privacy protection strategies, or passively accept the privacy protection provided by the platform in terms of policies and technologies. Hence, this study subdivides perceived risk into privacy protection technology, privacy protection policy and privacy settings.

In summary, combining the particularity of the research context and the research objective of this study based on the technology acceptance model, the factors affecting the elderly tourists’ acceptance preference for the network technology of the tourism e-commerce platform are divided into information acquisition; information understanding; privacy protection policy; privacy protection technology and privacy settings, and included in age-appropriate and non-age-appropriate transformation scenarios. Then, a theoretical model for this study is constructed.

2.2. Information Acquisition

Information acquisition refers to the degree of matching between the information provided by the tourism e-commerce platform and the conditions of elderly tourists; that is, whether they can clearly understand the interface content and select the desired products, including clear sight and hearing [20]. Increasing age causes memory, reactions and other physical functions to diminish commensurately. Therefore, the use of apps by elderly people could lead to less efficient information acquisition, resulting in a lack of confidence in their own access to new technologies, information literacy and the physiological function of their abilities, directly affecting their perception of the usefulness of the system and ease of access to information [20]. Technical support can appropriately relieve technical anxiety among elderly people, enhance their confidence and enthusiasm about Internet use and improve their perceived accessibility to information [21]. For example, sound can compensate for visual interaction effects and improve the availability of age-appropriate products. Therefore, this study proposes the following hypothesis:

Hypothesis 1. 

Elderly tourists prefer e-commerce tourism platforms that provide easy access to information.

2.3. Information Understanding

With the rapid development of modern science and technology, the app interface and function design are becoming increasingly complex, meeting the diversified needs of the younger generation while forgetting the requirements of elderly people. The highly professional presentation of information hinders complete understanding, and most older people are used to judging the acquired information based on their own experience and subjective consciousness, lacking the ability of scientific identification [22]. Consequently, it is difficult to understand and distinguish between the various functions of an app, leading to restricted understanding and cognition [23]. Other research revealed that the greater the knowledge, experience and ability of individuals, the stronger their perception and understanding of information [24]. However, owing to the deterioration of psychological and physiological skills in various aspects, elderly people are vulnerable in the network environment. They lack the ability to understand and discriminate information published by media networks and can easily become disseminators and victims of rumors. If the cognition of intelligent products does not match that of elderly users, cognitive friction may arise, hindering their acquisition and understanding of information [25]. However, the content of privacy policies in apps cannot be correctly understood by ordinary users because of their professionalism and complexity [26]. Therefore, this study proposes the following hypothesis:

Hypothesis 2. 

Elderly tourists prefer easy-to-understand e-commerce tourism platforms.

2.4. Privacy Protection Policy, Privacy Protection Technology and Privacy Settings

Privacy protection policy refers to the liability and obligation of the app operator to protect the legitimate rights and interests of personal information, as well as the disclaimer of information disclosure not caused by the reasons associated with the app, formulated in the process of collecting, sharing and using personal information [27]. For example, the travel e-commerce app requires access to users’ phone numbers, reservation records, etc. The privacy policy of the app should explain why it is necessary to access this information and how to analyze data to help users improve their travel experience, explaining how data are encrypted and stored in the cloud and how users delete or export their own data. It should also outline the circumstances under which anonymous data will be shared with partners. When users perceive that the privacy policy of a website is clear and easy to understand, they are more likely to have privacy perception and control, lowering their perceived privacy risk [28]. Most of the time, users are unaware of the use of personal private information and passively provide “consent” in the policy column to hand over private data [29]. When service providers have fair procedures to protect private information, users are more likely to disclose personal information to them [28].

Privacy protection technology refers to the protective measures adopted by app providers to prevent users’ information from being improperly obtained [30], including encryption technology for setting keys, identity authentication technology such as fingerprint and face recognition and controlling access to sensitive information. Nowadays, users are paying more attention to the privacy of their personal information; mobile service providers have noticed this demand and have provided more privacy protection technologies [31]. The higher the level of privacy protection technology, the higher the user’s privacy perception and control [32]. Effective privacy protection technology positively affects the perceived control of personal privacy information, reducing the degree of perceived risk [33].

The above privacy protection policies and technologies are passive privacy security management measures, while privacy settings—that is, a series of configurations or options used in personal applications to control and manage visibility and access to personal information—are proactive protection measures. Users make their own decisions regarding which information to publicize or protect and who can access it. This includes the ability to view, modify and delete personal information; and manage notifications and marketing information. Research has shown that privacy settings improve users’ perceived privacy controls [34]. Some elderly people are out of touch with the information age and are unable to navigate registration management and privacy settings, which not only reduces their sense of control but also undermines their confidence in using emerging technologies [35]. Therefore, they need social support to help them complete privacy-related settings [20]. Therefore, the following hypotheses are proposed:

Hypothesis 3. 

Elderly tourists prefer tourism e-commerce platforms with clearer privacy policies.

Hypothesis 4. 

Elderly tourists prefer tourism e-commerce platforms with effective privacy protection technologies.

Hypothesis 5. 

Elderly tourists prefer tourism e-commerce platforms with auxiliary privacy setting functions.

3. Materials and Methods

3.1. Research Methods

This study employed a discrete choice experimental model to analyze the technology acceptance preference mechanism of elderly tourists on a tourism e-commerce platform. The discrete choice experiment (DCE) is based on the stochastic utility theory [36], which assumes that decision-makers always pursue the option that maximizes utility when making choices, and was further extended by McFadden [37,38]. The discrete choice experiment is a multi-factor variable analysis method used to measure and quantify the behavior of decision makers, weighing options and making the optimal choice under multiple attributes and levels. It can comprehensively analyze the preferences of decision-makers regarding the characteristics of goods or services. It is primarily used to explain choice scenarios involving a limited, mutually exclusive set of options. Over the years, modeling methods, data collection, estimation algorithms, prediction methods and other aspects of discrete choice models have been further developed and improved, in terms of breadth and depth, by many scholars [39,40,41,42], gradually becoming one of the most powerful tools for studying individual choice behavior. With the increasing complexity of research problems and increasingly sophisticated model settings, a series of relatively complete theoretical systems have been constructed for discrete choice models, which have been widely used in various fields, such as tourism [43]. The specific research ideas are presented in Figure 1.

3.2. Construction of the Hybrid Logit Model

A traditional logit model assumes homogeneous individual preferences. However, research proves that individual preferences for commodities are heterogeneous [44]. The mixed logit model (MXL) assumes that individual preferences are heterogeneous and continuously distributed, allows for random errors, has high flexibility and has been widely used in selection experiments in recent years [37]. Based on this, a mixed logit model was used to analyze data from discrete selection experiments. In the mixed logit model presented in this paper, the linear expression of the deterministic term V$nit$ is:

$$Vnit=IAni\ast \beta 1+ICni\ast \beta 2+PPni\ast \beta 3+PTni\ast \beta 4+PSni\ast \beta 5+\epsilon$$

where $IA,IC,PP,PT,PS$ respectively represent information acquisition, information understanding, privacy protection policy, privacy protection technology and privacy settings, and β1–β5 are the coefficients of each attribute variable, respectively. The attribute level assignment and description can be seen in

Table 1. Attribute level assignment and description table.

Attribute Variable	Attribute Level	Attribute Description	Source
Information acquisition	Easy/Difficult	Whether to take certain measures, such as adjusting the size of the word, voice retrieval, etc., to match the conditions of elderly tourists	Zhang X; Wen D; Lei J [45]
Information understanding	Easy/Difficult	Whether to take certain measures such as: sensory compensation (voice explanation, vibration and beeps), one-to-one customer service to improve the comprehensibility and readability of information	Leicht; Jens and Heisel; Maritta [24]
Privacy protection policy	Clarity/Ambiguity	Whether the privacy policy is simple and easy for elderly people to understand	D. Harrison McKnight; Vivek Choudhury; Charles Kacmar [46]
Privacy protection technology	Valid/Invalid	Whether the privacy protection technology provided can effectively protect the rights and interests of elderly people	Pramod, D [47]
Privacy settings	Assisted/Unassisted	Whether to provide privacy assistance settings to older users	Liu Z, Wang X [34]

.

3.3. Research Scenario and Questionnaire Design

Since every choice is made by consumers under a certain decision-making background, according to the constructive choice view, consumers’ choices and decisions are highly dependent on the scenario (such as market economy, technology, natural disasters and major changes in the political system) [45,48], and consequently, the relative preference and value measurement of tourism e-commerce platforms may be different. Therefore, it is necessary to clarify the decision-making situation of experimental designs and further test the role of situational factors in individual choice. Adaptation to aging is one of the important factors that affect elderly tourists’ choice of digital technologies [46,47]. But at present, only a few tourism platform studies have taken situational factors into account. This hinders the aging transformation of tourism e-commerce platforms. Therefore, this study is divided into two scenarios, i.e., adaptation to aging and without adaptation to aging, in order to promote the adaptation to aging of tourism e-commerce platforms and improve the utilization rate of elderly tourists.

A questionnaire survey was used to collect data. The questionnaire was divided into two main parts. The first part included demographic characteristics, including age, gender and education level. The second part comprised the declarative selection experiment, which was divided into two scenarios: a tourism e-commerce platform without age-appropriate transformation, and a tourism e-commerce platform after age-appropriate transformation. Each scenario contained a five-point Likert scale related to attribute evaluation after using the app, with scores from one to five, respectively, representing the range from “very unimportant” to “very important”. Respondents selected the corresponding scores according to their real feelings, and in the four choice sets, they chose the corresponding options according to their preferences. This study included five attributes, each with two levels, in the discrete choice model questionnaire. If the attribute levels were fully combined, 32 attribute combinations of 2 × 2 × 2 × 2 × 2 could be generated, but these lacked the conditions required to conduct the selection experiment. To ensure the scientific validity and feasibility of the selection experiment, this study implemented an orthogonal experimental design using the %choicEff macro. First, the %MktRuns macro program was used to output the recommended size of the choice set. The results show that running eight times is sufficient to saturate the design (i.e., eight choice sets). Then, the %MktEx macro program was used to generate an orthogonal design as the candidate set. Next, the %choicEff macro program randomly constructed an initial design from the candidate set and replaced each scheme in the initial design with the candidate set until the design efficiency stabilized at the maximum value, and then output the optimal design (see

Table 2. Questionnaire selection set example.

Attribute	Option A	Option B
Information acquisition	Easy	Difficult
Information understanding	Easy	Difficult
Privacy protection policy	Obscure	Clear
Privacy protection technology	Invalid	Valid
Privacy setting	Assisted	Unassisted
Your choice is

for examples of selection experiments). Each selection consisted of two different combinations of e-commerce tourism platform options with different attribute levels. This scheme enabled the questionnaire to more accurately simulate the choice situation of elderly tourists. In the two suitable aging situations, respondents were required to make a total of 16 choices; an example of the choice set is shown in the table. The specific questionnaire can be seen in Appendix A.

In order to test the rationality of the experimental design, a pre-experiment was conducted on the Internet and around the school for the elderly before the formal survey. In the interview, elderly people generally reflected that in the process of using the tourism e-commerce platform, the difficulty of information understanding, access and privacy disclosure risks, such as payment, were the key determinants of whether they would continue to use the platform, which was consistent with the research questionnaire designed in this paper. And most elderly people could understand the rich and clear content of the questionnaire design and fill it in smoothly. Considering that the survey group consisted of elderly tourists, the research team visited the Nanjing Xuanwu Lake scenic spot, the main destination of the most significantly represented elderly tourists, to conduct the survey from 30 September to 3 October 2024. Elderly tourists with online booking experience were investigated by the convenience sampling method. A total of 101 questionnaires were received, and 94 valid responses were obtained after excluding invalid and missing ones. The efficacy rate was 93%. Due to the limited resources of the respondents in this survey, and based on the sample size calculation formula proposed by Johnson and Orne [49], which is the most widely used formula at present, $N\ge 500{\displaystyle \frac{L^{max}}{JS}}$ (where $L^{max}$ represents the maximum number of levels of attributes, $J$ represents the number of options for each selection and $S$ represents the number of selection sets to be completed by the respondents), it was calculated that the minimum sample size in this paper should be 31, indicating that the number of samples collected met the required conditions. Most respondents were aged 50–65 years, lived in cities or towns and had a general understanding of age-appropriate tourism e-commerce platforms. The descriptive statistics of the samples are shown in

Table 3. Sample descriptive statistics.

Attribute	Variable Attribute	Number	Proportion
Gender	Male	40	42.55%
	Female	54	57.44%
Age	50–55 years old	31	32.97%
	56–60 years old	14	14.89%
	61–65 years old	25	26.59%
	66–70 years old	10	10.63%
	Age 71 and older	14	14.89%
Career before retirement	Civil servants and enterprises and institutions	17	18.08%
	Enterprise	23	24.46%
	Military	4	4.25%
	Self-employed	25	26.59%
	Farmer	11	11.70%
	Others	14	14.89%
Average monthly earnings	CNY 2000 and below	9	9.57%
	CNY 2001–4000	31	32.97%
	CNY 4001–6000	26	27.65%
	CNY 6001–8000	15	15.95%
	CNY 8000 and above	13	13.82%
Permanent residence	Cities and towns	72	76.59%
	Countryside	22	23.40%

.

4. Research Results

Because the discrete selection experiment used a long-form format and the paper questionnaire was entered in a wide form, the wide data needed to be converted into long data before the analysis. After the conversion, Stata software (version 16.0) was used to perform a fitting analysis of the discrete choice model for the data of elderly users’ technical acceptance preferences for e-commerce platforms.

4.1. Preference Analysis in Different Situations

4.1.1. Elderly Tourists’ Preference for Attributes of Tourism E-Commerce Platforms

Stata 17.0 software was used to fit the mixed logit model, with a total of 1488 selected data points from 94 valid questionnaires. The estimated results are presented in

Table 4. Mixed logit model parameter estimation results (scenario without aging modification).

Attribute	Coefficient	SE	Z-Score
Information acquisition	1.756 ***	0.230	7.62
Information understanding	0.698 *	0.378	1.84
Privacy protection policy	0.796 ***	0.231	3.44
Privacy protection technology	0.110 *	0.317	0.35
Privacy setting	−0.166	0.320	−0.52
N	1488
AIC	1581.430
BIC	1661.169
Log likelihood	−775.71514
LR Chi2 (6)	78.72
Prob > Chi2	0.0000

Note: * and *** indicate that the estimated results are statistically significant at 10% and 1%, respectively.

and

Table 5. Mixed logit model parameter estimation results (adaptation to aging scenario).

	Coefficient	SE	Z-Score
Information acquisition	0.940 ***	0.236	−3.98
Information understanding	1.779 ***	0.240	7.40
Privacy protection policy	1.819 ***	0.217	8.37
Privacy protection technology	0.284 ***	0.220	1.29
Privacy setting	0.726	0.218	3.33
N	1488
AIC	1476.786
BIC	1561.669
Log likelihood	−722.3932
LR Chi2 (6)	129.61
Prob > Chi2	0.0000

Note: *** indicate that the estimated results are statistically significant at 1%, respectively.

. From the model estimate, the log likelihood was −775.71514 and −722.3932 and the LR Chi22(6) was 78.72 and 129.61, respectively, and the Prob > Chi of the result of the invalid hypothesis test of the model was 0.0000. This indicated that the overall fitting degree of the model was good, its validity was high and the model setting was reasonable.

In the non-age-appropriate modification scenario, the regression coefficients of all variables, except privacy settings, passed the significance test and were positive, indicating that elderly tourists showed positive preferences for the four attributes, information acquisition; information understanding; privacy protection policy and privacy protection technology, which were conducive to improving their utility levels. The coefficients were ranked from largest to smallest as follows: information access (β = 1.756) > privacy policy (β = 0.796) > information understanding (β = 0.698) > privacy technology (β = 0.110). The greater the absolute value of the coefficient, the greater the marginal utility that elderly tourists could obtain from this attribute. This reflects the degree of influence of each attribute on the final choice decisions of elderly users. The analysis results show that, compared with other groups of users, the audiovisual, cognitive, expressive and operational abilities of elderly users constantly weaken, and they are more likely to be unable to predict privacy risks due to a lack of judgment ability [50]. Therefore, they pay more attention to whether the information presented by the platform can be accessed normally and correctly understood, and whether its privacy protection is clear and effective. This also reflects that current travel e-commerce platforms, which have not been adapted for aging, generally include problems such as small size, unclear fonts, complex interfaces and unsatisfactory audio–visual interaction effects.

In the context of age-appropriate transformation, information acquisition and understanding, as well as privacy protection policy and technology, were all significantly positive. This indicates that, in this context, elderly tourists demonstrate a positive preference for these four attributes, and the improvement in each attribute level increases the possibility of their acceptance of network technology, which also confirms Hypotheses 1–4 (

Table 6. Research result.

Assumed Serial Number	Hypotheses	Hypotheses Result
Hypothesis 1	Elderly tourists prefer e-commerce tourism platforms that provide easy access to information.	Confirmed
Hypothesis 2	Elderly tourists prefer easy-to-understand e-commerce tourism platforms.	Confirmed
Hypothesis 3	Elderly tourists prefer tourism e-commerce platforms with clearer privacy policies.	Confirmed
Hypothesis 4	Elderly tourists prefer tourism e-commerce platforms with effective privacy protection technologies.	Confirmed
Hypothesis 5	Elderly tourists prefer tourism e-commerce platforms with auxiliary privacy setting functions.	Unconfirmed

). This conclusion reveals the current phenomenon that elderly tourists are sensitive to privacy and security due to the decline in their physical function, and they are more cautious about the cognition and attitude of emerging Internet technologies, deepening the application of CPM theory and role theory in the field of tourism. The coefficients in descending order are as follows: privacy protection policy (β = 1.819) > information understanding (β = 1.779) > information access (β = 0.940) > privacy protection technology (β = 0.284). The current age-appropriate e-commerce platform has basically achieved a simple interface, bold font display, enlarged size and clear and easy-to-understand explanations. However, some platforms have ignored improvements in privacy protection. Therefore, compared with the situation without age-appropriate transformation, elderly tourists value clear and effective privacy protection policy content in this scenario. The privacy settings were not significant in either scenario, and thus, Hypothesis 5 is not supported. The reason for this may be that at present, many tourism e-commerce platforms, such as Ctrip and Feizhu, have set up privacy protection functions and the process is cumbersome. In addition, studies have indicated that elderly people in China currently lack initiative in online privacy protection and an awareness of the risks of privacy disclosure [51]. This makes many elderly tourists vulnerable and unfairly treated, so it is important to strengthen the operability of privacy settings. However, the design of privacy settings on most platforms is not user-friendly. Even with the auxiliary function of privacy settings, elderly people need to read a large amount of indicative information and carry out multi-step operations, which conflicts with their needs. There are communication barriers between the platform and elderly tourists, which are the key problems to be urgently solved, both in theory and in reality.

4.1.2. Heterogeneity Analysis of Different Individual Characteristic Preferences

In the two scenarios, cross-terms of the demographic characteristic variables of elderly tourists and product attributes were introduced, and the mixed logit model was used for regression (

Table 7. Analysis results of interaction terms (scenario without aging modification).

Interaction Term	Coefficient	SE	Z-Score
Gender
Gender_IA	−0.830 ***	0.309	−2.69
Gender_IU	0.338	0.273	1.24
Gender_PP	0.145	0.272	0.53
Gender_PT	0.480	0.328	1.46
Gender_PS	−0.333	0.329	−1.01
Age
Age_IA	0.405 ***	0.106	3.82
Age_IU	0.176 *	0.095	1.85
Age_PP	0.032	0.095	0.34
Age_PT	0.189 *	0.113	1.66
Age_PS	0.161	0.109	1.47
Education
Education_IA	−0.119	0.176	−0.68
Education_IU	0.192	0.157	1.22
Education_PP	−0.153	0.157	−0.98
Education_PT	−0.046	0.191	−0.24
Education_PS	0.079	0.188	0.42
Career
Career_IA	0.257	0.103	2.51
Career_IU	0.020	0.091	0.22
Career_PP	0.015	0.091	0.16
Career_PT	0.217	0.110	1.97
Career_PS	0.255	0.107	2.38
Average monthly earnings
Average monthly earnings_IA	0.193	0.160	1.21
Average monthly earnings_IU	−0.080	0.143	−0.56
Average monthly earnings_PP	0.183	0.143	1.28
Average monthly earnings_PT	0.146	0.173	0.85
Average monthly earnings_PS	0.040	0.169	0.24
N	1488
AIC	1423.337
BIC	1502.108
Log likelihood	−696.66869
LR Chi2 (25)	66.13
Prob > Chi2	0.0000

Note: * and *** indicate that the estimated results are statistically significant at 10% and 1%, respectively.

and

Table 8. Analysis results of interaction terms (adaptation to aging scenario).

	Coefficient	SE	Z-Score
Gender
Gender_IA	−0.200	0.287	−0.70
Gender_IU	0.121	0.261	0.46
Gender_PP	−0.101	0.260	−0.39
Gender_PT	0.060	0.321	0.19
Gender_PS	0.114	0.312	0.36
Age
Age_IA	0.273 ***	0.100	−2.73
Age_IU	0.017	0.092	0.19
Age_PP	0.090	0.091	0.99
Age_PT	−0.101	0.111	−0.91
Age_PS	0.040	0.108	0.37
Education
Education_IA	0.105	0.176	0.59
Education_IU	−0.193	0.161	−1.20
Education_PP	0.123	0.160	0.77
Education_PT	−0.145	0.197	−0.74
Education_PS	−0.006	0.191	−0.03
Career
Career_IA	0.041	0.095	0.43
Career_IU	0.025	0.087	0.29
Career_PP	−0.191	0.086	−2.22
Career_PT	−0.065	0.107	−0.61
Career_PS	−0.075	0.105	−0.72
Average monthly earnings
Average monthly earnings_IA	−0.253 *	0.153	−1.66
Average monthly earnings_IU	0.038	0.139	0.27
Average monthly earnings_PP	−0.296 **	0.139	−2.14
Average monthly earnings_PT	−0.092	0.171	−0.54
Average monthly earnings_PS	−0.084 *	0.168	−0.50
N	1488
AIC	1536.019
BIC	1747.794
Log likelihood	−728.00945
LR Chi2 (25)	35.78
Prob > Chi2	0.0451

Note: *, ** and *** indicate that the estimated results are statistically significant at 10%, 5% and 1%, respectively.

). From the estimated results of the model, the log likelihood was −1855.0617, LR Chi² (35) was 640.38, and the Prob > Chi of the test result of the invalid hypothesis of the model was 0.000. This indicates that the model had a better overall fitting degree.

In the scenario without age-appropriate modification, gender and age influenced the attribute preference of tourism souvenirs among the cross-terms of attributes and individual characteristic variables. However, the interaction terms of education level, average monthly income, occupation and the attributes of tourism e-commerce platforms were not significant, which is similar to the situation in the overall age-appropriate modification scenario. This indicates that education level and occupation are not the sources of heterogeneity in Internet technology acceptance attribute preference, and that there is no significant difference in Internet technology acceptance preference among elderly tourists with different education levels and occupations. The specific manifestations are as follows.

The interaction effect between gender and information acquisition was significantly negative, and that between gender and privacy settings was negative and insignificant. This indicates that for platforms that are not suitable for aging transformation, men prefer platforms with rich interfaces, complete functions and independent privacy settings according to their own needs, whereas women value the simplicity of information acquisition and the auxiliary functions of privacy settings.

The effects of age, information acquisition, information understanding and privacy protection technology were significantly positive, indicating that older adult tourists are more inclined to choose tourism e-commerce platforms with high perceived ease of use, high perceived usefulness and effective privacy protection technology. Some researchers have also proven that older people tend to choose easily accessible tourism information [21].

The average monthly income of elderly tourists in the adaptation to the aging scenario had a significant positive effect on information acquisition, privacy protection technology and privacy settings. This may be because older individuals with money and leisure pursue spiritual abundance, travel relatively frequently and use tourism e-commerce platforms more often. They are more inclined to use tourism e-commerce platforms with convenient information acquisition, guaranteed privacy and specific privacy settings according to their needs to ensure the security of personal information and payment accounts.

5. Discussion and Conclusions

5.1. Theoretical Discussion

Starting from the difference in preferences for Internet technology acceptance in two situations, this study conducted an offline survey of elderly tourists. Based on the discrete choice experiment method and hybrid logit model, it explored elderly tourists’ preferences for Internet technology acceptance in tourism e-commerce platforms in different situations and further analyzed individual heterogeneity according to the individual characteristics of elderly users. The main conclusions are as follows.

Information acquisition, information understanding, privacy protection policy and privacy protection technology have significant positive effects on elderly tourists’ Internet technology acceptance preferences, regardless of whether the tourism e-commerce platform is retrofitted for aging. Hypotheses 1–4 were verified. This finding further demonstrates the applicability of the technology acceptance model to elderly tourists, indicating that perceived ease of use, usefulness and risk are key variables affecting elderly tourists’ acceptance of Internet technology. However, the influence of privacy settings on elderly tourists’ Internet technology acceptance preferences was not significant in either scenario. Privacy settings refer to elderly tourists’ initiatives to protect themselves against the potential risks of tourism e-commerce platforms. Considering the current digital literacy of the elderly population in China and the specific design of privacy settings on tourism e-commerce platforms, it can be observed that elderly tourists have relatively weak awareness of privacy disclosure risk and privacy protection initiatives, and their digital literacy is relatively low. Additionally, although most tourism e-commerce platforms provide privacy settings during adaptation, the operation process is too complicated, resulting in elderly tourists often giving up or directly ignoring the implementation of effective privacy protection behaviors in real life. This study reveals the shortcomings of current tourism e-commerce platforms in their adaptation to aging, filling the gap in existing literature, which mostly focuses on the technical acceptance of intelligent information by elderly users [52].

The influence mechanism of age-appropriate tourism e-commerce platforms on elderly tourists’ technology acceptance preferences significantly differs from that of general tourism e-commerce platforms. In the absence of age-appropriate transformation, the order of the degree of influence of various attributes of tourism e-commerce platforms on the technology acceptance preference of elderly tourists, from high to low, is as follows: information acquisition, privacy protection policy, information understanding and privacy protection technology. Elderly tourists focus more on how to obtain information about unmodified tourism e-commerce platforms, which verifies the research conclusions of some researchers [53]. However, compared with other groups concerned about understanding information, elderly people are concerned about privacy protection policies, indicating that they attach importance to privacy risk disclosure. After the age-appropriate transformation, the degree of influence of various attributes of tourism e-commerce platforms on elderly tourists’ technology acceptance preferences changed from high to low as follows: privacy protection policy, information understanding, information access and privacy protection technology. After the aging transformation, tourism e-commerce platforms place more emphasis on the protection of the privacy of elderly tourists, so that the latter pay more attention to personal privacy, which is a significant protection for them, echoing laws and regulations and reflecting society’s love and care for digitally vulnerable groups.

The choice preferences of elderly tourists are heterogeneous, and their choice of tourism e-commerce platform is affected by individual characteristics such as gender, age and average monthly income. In the context of non-age-appropriate transformation, gender and age have interactive effects on information acquisition, with age also having interactive effects on information understanding and privacy protection technologies. Specifically, the older elderly tourists are, the more inclined they are to choose platforms with easier information acquisition and understanding and more effective privacy protection technology. This finding is consistent with the current common Internet needs of elderly people. Compared to women, men are more likely to accept e-commerce platforms with complex interfaces and rich information. Existing studies on elderly users’ needs for intelligent network systems tend to ignore the heterogeneity of elderly users; different values, health conditions and experiences may significantly affect the requirements for intelligent systems [54]. This finding complements the research on elderly tourists’ technology acceptance preferences. In the adaptation to aging scenario, there is an interactive effect between age and information access, and average monthly income has an interactive effect on information access, privacy protection policies and privacy settings. Specifically, older tourists with higher average monthly incomes are more willing to accept a platform with rich information, are less afraid of privacy disclosure and can independently use complex privacy settings. From this, it can be interpreted that wealthy and independent older adults more frequently have a rewarding travel experience using tourism e-commerce platforms; being skilled in relevant operations, they can establish a trusted connection with the platform [55]. This is consistent with the current phenomenon of elderly travel and the strong momentum towards digitalization in our country.

In both scenarios, all factors except for privacy setting attributes—elderly tourists’ preferences for information acquisition, information understanding, privacy protection policy and privacy protection technology—are significant, with positive coefficients. This indicates that these attributes have a greater positive impact on elderly tourists’ technology acceptance decisions, supporting Hypotheses 1–4. The reasons for the lack of significant privacy settings in the two scenarios may be as follows: (1) The complexity of privacy settings does not match the digital literacy of elderly tourists, exceeding their cognitive ability and resulting in difficulties in understanding and operational errors, leading them to abandon the privacy settings. (2) Although elderly tourism e-commerce platforms can only provide auxiliary measures for privacy settings, the guidance fails to meet the needs of older adults. The guidance process and operation guide are too complicated, and elderly users fail to receive timely operational feedback and support, reducing their self-efficacy. Additionally, because privacy settings are proactive protection measures in the perceived risk dimension, the current situation in China also leads to elderly people often suffering from internet fraud and similar problems.

5.2. Practical Implications

Based on the research conclusions, to improve the experience and sense of acquisition of e-commerce platforms for elderly users and enhance the practicability and pertinence of the platform, the following suggestions are proposed:

The physical functions of elderly people and the strength of their perceptions should be fully considered. For instance, travel e-commerce platforms like Ctrip should create an elderly mode, in which they increase the bold display of text; add picture guidance, voice explanations and other auxiliary functions; avoid using vague and lengthy descriptions; refrain from using jargon in the field of privacy protection and retain only necessary content in the interface, to reduce the learning threshold for elderly people.

Secondly, privacy concerns should be eased and platforms should build trust. Tourism e-commerce platforms should follow the example of applications like himarket and display corresponding security marks within the software, such as privacy shields and SSL certificates, and emphasize data security measures, such as encryption algorithms and anonymization processing. This would help older adult users to feel that their information is fully protected, and regular security notifications should be sent to users so that they know where their information is going in a timely manner.

Thirdly, platforms should create an atmosphere that is suitable for the aging population, and enhance the sense of integration among elderly people. This would involve encouraging communities, volunteer organizations and other social forces to participate in the creation of a digitally friendly atmosphere for elderly people, such as building dedicated social platforms for their communication, establishing community interest groups to learn about the use of electronic products and providing appropriate guidance and support. This would strengthen digital literacy education for elderly people, who could improve their understanding and application of digital technologies through community courses and online lectures. Government departments should strengthen the popularization and application of digital technologies in elderly communities, promote the construction of smart communities and enable elderly people to easily use digital technologies in their daily lives.

Finally, the acceptability of technology in tourism e-commerce platforms should be improved for elderly tourists. In the next few years, the government should actively introduce policies for adaptation to aging, and the information and communication industry should hold aging-friendly digital technology activities in various regions. Through rich forms such as fairs and cultural activities, a more friendly, convenient and secure digital environment should be created for elderly people to address their concerns about the usability, ease of use, security, privacy and control of intelligent systems. Bridging the digital divide among elderly people will promote the realization of active aging policies [56,57,58,59].

5.3. Research Prospects

From the perspective of research methods, previous studies have mostly used single- or multi-factor statistical methods to explore the impact of different factors on the satisfaction and behavior of tourism e-commerce platforms, but the relative importance of each factor is often difficult to quantify. This study established an evaluation method for elderly tourists’ Internet technology acceptance preferences that combined a questionnaire survey and a discrete choice experiment. Guided by the stated preferences, selection experiments are at the core, and empirical and experimental methods are combined to measure the preferences of various attributes of tourism e-commerce platforms, providing a new perspective and direction for service providers of tourism e-commerce platforms to adapt to the transformation associated with the aging population. However, this study has some limitations that should be explored in future research. From a methodological perspective, this study focuses on discrete choice experiments. Although real-choice scenarios were presented to respondents as much as possible during the experimental design and data collection process to reduce understanding and answer bias, some elderly respondents may still have comprehension biases and fill in errors. Future studies can further conduct one-to-one explanatory selection experiments and combine them with other experimental methods to measure the physiological and psychological changes in elderly people when using age-adapted travel e-commerce platforms more accurately. From a data perspective, future research could expand the sample selection range, consider differences in results caused by varying tourism scenes and conduct comparative analyses to enhance the universality of the research conclusions.