Keywords

Customization Model, Perceived Value, Perceived Value Hierarchy, China.

Introduction

Since January 2020, COVID-19 has ravaged the world and the global tourism industry is in a state of almost complete shutdown (Lew et al., 2020). To this day, tourism is still restricted in many countries and regions of the world due to the tremendous impact of the pandemic. The tourism-related service industry has entered an unprecedented period of depression. As one of the sectors most affected by COVID-19, many studies have shown that it disrupted tourism demand and economic development (Miao et al., 2021), but also provided new opportunities for tourism practitioners to address innovative reforms in the tourism industry (Zhang et al., 2021).

COVID-19 exacerbates travelers' fears and risks, and due to increased perceptions of risk, travelers' needs change accordingly Karl et al. (2020); Neuburger & Egger (2020) but there is limited research examining changes in traveler behavior, such as choosing alternative destinations and supporting new types of travel that are relatively less risky. Travel customization services can undoubtedly respond to the changing needs of travelers by incorporating expectations such as safety, comfort, etc. into travel details. Since perceived value is considered an important determinant of travel behavior and future intentions, Yi et al. (2014) understanding the value perceptions of tourists in a customized model has an important role for managers who are competing in this market segment after the epidemic (Eid & El-Gohary, 2015).

Customization enables companies to meet the heterogeneous needs of customers, thus becoming the first choice for the differentiation and low-cost strategies of tourism companies (Wu, 2004). Given the severe setbacks suffered by small businesses during the epidemic period, the customization model is likely to be the focal model for strategic choices during the tourism recovery period (El-Adly, 2019). Past research has demonstrated that perceived value, satisfaction, and service quality are all key influences on customer loyalty (Petrick, 2004). No research to date has examined the structure of perceived value within the framework of the customization model and has not specifically explored the perceived value of tourists in this model (Brouder et al., 2020). This study therefore fills the knowledge void in this area of research prior to COVID-19 by examining the hierarchical relationships between various factors in the visitor value perception system and their outcomes in a customized business model, and provides suggestions for corresponding market recovery after the pandemic (Gilbert & Wong 2003).

This study divides tourist value perception into demand and result levels, and examines the impact of both on final tourist satisfaction and behavioral tendencies (Castellanos-Verdugo et al., 2016). The study advances the theoretical development of the customization model in the tourism industry. The findings provide practical implications for stakeholders in the tourism industry (Hong, 2012). It helps tourism companies to understand the transmission of visitor value perceptions in a customization business model and the proportions at which business resources and strategic focus can be adjusted to achieve optimal results (Overstreet, 1993). Secondly to help improve the product, service, marketing and management development of tourism companies offering customized trip after the pandemic. The specific research objectives are as follows: First, to examine how the perceived demand level of tourists in the customization business model affects the perceived result level. Second, to examine how the result level affects tourists' satisfaction and behavioral tendencies (Chang et al., 2010). Last, to examine what factors in each level have a significant impact on the other levels and what factors do not play a significant role in the value transfer process (Peacock et al., 2017).

Literature Review

Customization and Perceived Value in Tourism

In tourism service process, customers engage in service design and delivery (Chathoth et al., 2016). The intangibility Botterill & Crompton (1996); Jayanti & Ghosh (1996) and experiential character Inkson & Minnaert (2018) of tourism products prevent customers from conducting presales quality inspections of travel products; thus, they bear more risk at the time of purchase. Being a producer can bring more perceived value to customers (Dong, 2015). Enterprises that can provide customized services are more competitive than those that offer standardized products (Anderson et al., 1997). Providing personalized services have a significant influence on purchase intention Zhang et al. (2012) while it can increase customer loyalty to the company Zhou et al. (2007); Zhou et al. (2013) and customer satisfaction with online shopping (Chang & Chen, 2009). According to Woodruff (1997), customer perceived value can be used to describe product attributes, features, and product usage outcomes. It originated from discovering a product's extra benefits after purchasing and using the product, thereby establishing an emotional bond with the supplier. In the case of oversupply, customer value theory can increase the competitive advantage of tourism companies Overstreet (1993) and as a typical service-oriented field, the application of the theory also increases tourist loyalty (Cronin et al., 2000; Ryu et al., 2008). In consumer behavior research, customer value or perceived value can replace customer perceived value Gallarza & Saura (2006) which serves as the main measure of customer satisfaction and loyalty and also influences customer behavior and repurchase intentions. (Parasuraman & Grewal, 2000). Providing tourists with perceived value that is better than their competitors can promote them to purchase the products and services of the tourism company (Phau et al., 2014). Perceived value, which has various definitions, with two major ideas Döring (2008). The first one focuses on the functional value of quality and money. which takes the experience of the consumer as the judge stander of value (Eid & El-Gohary, 2015). The other idea underline the importance of affective factors especially pleasure and hedonic Duman & Mattila (2005); Prebensen et al. (2013) and the symbolic value derived from the social level on this basis (Chen & Hu, 2010).

Therefore, most studies combinate a wider point that consider the perceived value as a multidimensional system that composed of functional, emotional and social value (Rasoolimanesh et al., 2016). Travel companies that meet customer expectations can experience long-term profits while enjoying competitive advantages (O' Cass & Sok, 2013). Jin et al. (2012) empirically showed that offering travel packages with downgrades and upgrades for tourists with different needs can increase the attractiveness of travel agencies. According to Kramer (2007) under the same conditions, customers can actively participate in the production process of products and services, which will make such products and services more in line with customer preferences and improve customer satisfaction (Sánchez-Cañizares et al., 2021). Although customers may have different emphases on distinct aspects of customization, leading to differences in purchase intentions Pappas et al. (2014) therefore it is particularly important to combine internal resources of the enterprise with the different needs of consumer groups to effectively configure (Pallant et al., 2020). In the development research process of tourism enterprises, the perspective of tourists' is undoubtedly a mirror that enterprises can use to check their products, services, and even management omissions. Therefore, we combine the customization model with a framework of travelers' perceived value to analyze which specific factors in this model lead to high value ratings by travelers (Sanchez et al., 2006).

Hierarchy of Perceived Value

In the specific measurement system for customer value, scholars tend to adopt a concept of value composed of multiple dimensions. Sheth et al. (1991) collated 650 related studies and built a five-value influence model from the enterprise perspective. They argued that consumers' choice behavior was determined by multiple values, explicitly divided into functional, social, emotional, epistemic, and conditional value. Flint et al. (1997) divided customer value into actual perceived value and expected value. The research of Roig et al. (2006) believes that perceived value is composed of six dimensions: functional value of the establishment, the personnel; the service; functional value price; emotional value; and social value. Most research of customer value from the perspective of exchange value argued that the core of perceived value is ultimately the trade-offs between perceived gains and losses. In the empirical research, divided the driving factors of customer value into three categories: product-related characteristics (e.g., consistency, characteristics, range, and flexibility of products), service-related characteristics (e.g., supply reliability, business agility, extensibility, technical support, rapid response, product innovation, and technical information), and item-related characteristics (e.g., image, personal relationships, company reliability, public relations, and upstream integration).

In addition to influencing factors, there are many sources of customer value in tourist areas. Most studies tend to apply multidimensional value analysis. Current academic research focuses on exploring and measuring the scale development of the customer value components of different tourism enterprises, tourist attractions, tourist destinations, tourist markets, and tourist products (Sweeney & Soutar 2001; Yoo & Park 2007). Petrick (2004) compiled the Tourist Perceived Value Scale (SERV-PERVAL). Through empirical testing of the first and repeat tourists participating in cruise ship travel, a measurement framework was established, which consists of five dimensions: quality, emotional response, monetary price, behavioral price, and reputation. Studying the perceived value of the group travel of university students, Gallarza & Saura (2006) proposed a measurement system of eight dimensions: efficiency, service quality, social value, entertainment, aesthetics, the perceived monetary cost, perceived risk, and the time and effort spent. Table 1 lists the main results of research on the dimensions of perceived value in the tourism field. Owing to the complexity of the products and services of tourism enterprises, the dimensions of tourists' perceived value are more complex than those of ordinary products and services. Most previous studies on tourists' perceived value located all measurements at the same level. We contend that tourists' perceived value is a progressive system with different levels composed of multiple dimensions (Solvoll et al., 2015).

Table 1 The Dimensions Of Customer Value In Tourism Research
Authors	Background	Value dimension	Items	Composite reliability
Otto and Ritchie (1996)	Service experience in tourism	Hedonic	11	0.919
		Peace of mind	5	0.838
		Involvement	5	0.759
		Recognition	2	0.756
Petrick (2004)	Cruise customers (SERV-PERVAL)	Emotional response	5	0.96
		Quality	4	0.93
		Reputation	5	0.94
		Monetary price	6	0.94
		Behavioral price	5	0.96
Gallarza and Saura (2006)	Group travel of university students	Efficiency	5	0.64
		Service quality	9	0.94
		Social value	5	0.69
		Play	4	0.84
		Aesthetics	4	0.81
		Perceived monetary cost	4	0.78
		Perceived risk	8	0.78
		Time and effort spent	7	0.80
Sánchez et al. (2006)	Tourism package GLOVAL	Functional value of the travel agency	4	0.84
		Functional value of the contact personnel of the travel agency	4	0.89
		Functional value of the tourism product	4	0.90
		Functional value price	3	0.78
		Emotional value	5	0.81
		Social value	4	0.89
Huang and Huang (2007)	TOUR-PERVAL	Perceived quality of tourism resources	7	0.796
		Perceived quality of the tourism reception system	6	0.770
		Perceived quality of tourism activities	5	0.785
		Emotional value of pleasure	3	0.848
		Emotional value of novelty	4	0.678
		Social value	3	0.807
		Perceived cost	3	0.757
		Perceived nonmonetary costs	4	0.644
Williams and Soutar (2009)	Adventure tourism	Functional value	4	0.87
		Value for the money	4	0.92
		Emotional value	4	0.88
		Social value	4	0.94
		Novelty value	4	0.87
Sui, Li, and Cheng (2009)	Cultural heritage tourism	Value of quality	3	0.75
		Value of efficiency	3	0.82
		Value of the service	4	0.82
		Cost value	6	0.70
		Social value	2	0.70
		Hedonic value	5	0.73
Zhang, Hong, and Zhang (2012) Hong, Zhang(2012)	Tourism destinations	Service	5	0.87
		Landscape/environment	3	0.72
		Tourism infrastructure	3	0.74
		Activity	2	0.76
		Cost	3	0.77
El-Adly (2019)	Hotels	Self-gratification	4	0.861
		Aesthetics	4	0.829
		Price	4	0/809
		Prestige	4	0.867
		Transaction	3	0/815
		Hedonic	4	0/904
		Quality	4	0.862

After being processed by enterprises, tourism products and services and the attributes of products and services in the customization model obtain value added and distinguish themselves from products directly purchased by tourists. By selecting and consuming such customized products and services, tourists can minimize unexpected outcomes or costs, improve their individual perceived value, and satisfy their travel needs (Sui et al., 2009).

Currently, constructing and expanding the perceived value model, exploring other dimensions beyond the known dimensions, and making the measurement method scientific still attract attention. In this study, by drawing on the dimensions of Petrick (2004); Gallarza & Saura (2006); Sánchez et al. (2006) we propose two levels and seven dimensions for measurement given the characteristics of small tourism enterprises. Tourists’ perceived value is divided into the demand level and the result level. The value perception at the demand level includes four dimensions, namely, enterprise functions (EFs), personnel functions (PFs), travel value (TV), and monetary and nonmonetary value (MNM). The value perception at the result level includes three dimensions, which are hedonic value (HV), SV, and cost value (CV). The final behavioral outcomes are tourist satisfaction (TSA) and behavioral tendency (BT). This study posits the corresponding hypotheses below shows in Figure 1.

H1: The demand level of perceived value has a positive effect on the result level.

H2: The result level of perceived value has a positive effect on tourist behavior.

H3: The result level of perceived value mediates the relationship between the demand level and tourist behaviour.

Methodology

Measurements

The questionnaire consisted of 24 items. We measured nine constructs designed by multiple-item scales adapted from previous studies. All items were measured on a 5-point Likert scale that ranged from strongly disagree (1) to strongly agree (5). EFs were assessed using three items adapted from Sánchez et al. (2006); Huang & Huang (2007). Two items were adapted from previous study Sánchez et al. (2006) to measure PFs. To assess TV, we followed Sánchez et al. (2006); 58. Sui et al. (2009) and defined it as a dimension measured by four items. Three items of MNM were adapted from (Petrick, 2004; Hongmei et al., 2012). To measure HV, two items were adopted from prior research on entertainment and aesthetic experience by (Zhang & Jia 2008; Hongmei et al., 2012). To measure SV, we borrowed or adapted three items from Gallarza & Saura (2006); Sánchez et al. (2006); Sui et al. (2009). Finally, in conceptualizing CV, three items were adapted from (Hongmei et al., 2012). The questionnaire also contained demographic information, which we measured using categorical scales. The measurement items in the questionnaire all utilized a five-point Likert scale: 1-strongly disagree, 3-neutral and 5-strongly agree. The degree shows how much respondents rate the item on the scale.

We conducted pre-testing before the questionnaires were officially distributed. 100 surveies was sent and returned 83 copies, excluding 2 incomplete questionnaires, resulting in a valid response rate of 81%. After analyzing the sample data from the participants, we further revised the structure of the questionnaire by removing duplicate items and rewording some items in the TSA and BT to ensure that respondents understood the questions (Lew et al., 2008).

Data Collection

We get information from a directory of custom travel agencies in China published on the dingzhiyou.org website. This is a self-organized business alliance of travel agencies and related companies in the custom tour industry, which is a non-governmental organization (NGO). The custom tour agency directory provided by the website was published on July 13, 2017, and contains information on 578 companies, including specific information such as type of service, agency location, agency profile, destinations in the area of specialized knowledge, and number of customization expert OCass & Sok (2013).

Based on this information, we first excluded 33 agencies that only provide services for peers. Based on the sifting of agencies specializing in destinations, we found that Southeast Asia, Europe, North America, Japan and Korea were the keywords of most travel agencies. Considering that some agencies only focus on single destinations, such as Africa, North and South Poles, according to the Statista Research Department 2021 report "Chinese tourism in Europe - statistics & facts" shows that about 28% of Chinese outbound tourists visited Europe in 2019, making Europe the second most important destination for Chinese tourists after Asia. We then set the final destination keyword to Europe and excluded 224 agencies that did not include Europe as their service provider, and finally sent an email to the eligible agencies requesting help, explaining our research and the structure of the questionnaire in the email and asking for their willingness to send the questionnaire to their clients Ulaga (2001).

We ended up with 82 companies that responded positively and assisted us in sending questionnaires to their customers. Since an excessively long time span is not conducive to reflecting the true feelings of tourists, we chose to send questionnaires to tourists who had participated in their customized travel services during 2019. Before the questionnaire was formally distributed, we conducted a small pilot survey to reword some of the items in the TSA and BT to ensure that respondents understood them. A total of 550 formal questionnaires were collected, in which 14 were incomplete and 68 missed important data. The effective rate was 85.09%. Finally, we coded 468 questionnaires for data analysis.

Results

Respondent’s Profile

Respondents were primarily female tourists (59.2%), most of them were aged 21–30 (31.8%) and 41–50 (29.5%). Less than half of all respondents (49.8%) visited Europe more than two times. Of the tourists, 20.9% visited Europe for the first time; 29.3%, second. In the customization model, 41.7% of the travelers were in groups of 1–5 people, 28.2%, 6–10. Majority of the respondents hired tour guides (74.1%) and used a chartered bus during the whole journey (62%). The most frequent travel time for these respondents was 9–12 days (26.9%), followed by 17–20 days (19.9%) and 5–8 days (19.2%). More than half of all respondents (80.5%) visited less than four countries on this trip, and most of them (28%) visited only one country.

The Dimension of Tourist's Perceived Value under Customization Models

This study used SPSS 23.0 and Amos 23.0 for exploratory and confirmatory factor analysis to assess the reliability and validity of all constructs. First, reliability analysis uses Cronbach's Alpha reliability coefficients to check the consistency of the survey questionnaire variables on each measurement item. Hair et al. (2010) believe that for a variable to have excellent reliability, the Cronbach's Alpha coefficient must be higher than 0.7. The results of the reliability analysis are provided in Table 2. All scales have reliability coefficients ranging from 0.866 to 0.909, which exceed the cut-off level of 0.70 set for basic research. Besides, models fit the data at the acceptable range (CMIN/DF<3; RMR<0.08; GFI>0.8; AGFI>0.8; NFI>0.9; CFI>0.9; IFI>0.9; RMSEA<0.08) indicating that variables in this questionnaire have good convergent validity.

Table 2 Cronbach's Alpha Reliability Coefficients And Goodness-Of-Fit Analysis (N=468)
Factor	Cronbah's Alpha	CMIN/DF	RMR	GFI	AGFI	NFI	CFI	RMSEA
Enterprise Functions	0.892	2.329	0.045	0.975	0.953	0.977	0.987	0.053
Personnel Functions	0.871	2.753	0.044	0.985	0.962	0.987	0.991	0.061
Travel Value	0.909	1.268	0.037	0.978	0.966	0.981	0.996	0.024
Monetary and Nonmonetary Value	0.905	2.744	0.041	0.964	0.938	0.970	0.981	0.061
Hedonic Value	0.879	2.246	0.035	0.987	0.966	0.989	0.994	0.052
Social Value	0.891	2.684	0.043	0.971	0,946	0,974	0.983	0.060
Cost Value	0.872	2.718	0.035	0.985	0.961	0.986	0.991	0.061
Tourist Satisfaction	0,892	1.290	0.028	0.982	0.970	0.983	0.996	0.025
Behavioral  B Tendency	0.866	2.892	0.040	0.984	0.958	0.985	0.990	0.063

As shown in Table 3, all factor loadings and CRs are ranging from 0.847 to 0.887, indicating that all variables have good convergence validity. As AVE greater than their corresponding squared inter-construct correlations means the discriminant validity of the model (Fornell & Larcker, 1981), these constructs in this model meet the requirements for discriminant validity shows in Table 4.

Table 3 Means And Reliability Of The Demand Level
Technical Functions (CR = 0.888, AVE = 0.727)	Factor loading	Mean	SD
Clear functions and enough information on website	0.826	3.278	1.286
Completed technical support	0.802	3.447	1.187
Completed facilities and equipment to provide services	0.925	3.318	1.213
Department Functions (CR = 0.847, AVE = 0.648)
Complete departments	0.81	3.650	1.125
Adequate staff	0.816	3.731	1.171
Good marketing strategies	0.789	3.731	1.081
Cooperative Functions (CR = 0.868, AVE = 0.686)
Good strategic alliance between the tourism company and upstream resource Party	0.863	3.654	1.243
Rich upstream resources and peer resources	0.811	3.729	1.082
Fixed destination suppliers, wholesalers, distributors, and has complete cooperation network	0.81	3.701	1.212
Professional Quality (CR = 0.872, AVE = 0.696)
Has relevant knowledge reserves and experience	0.818	3.588	1.208
Highly efficient and can deal with emergencies in the travelling	0.753	3.665	1.162
Kind and thoughtful	0.923	3.566	1.181
Interpersonal Intelligence (CR = 0.882, AVE = 0.714)
Don’t have the burden to telling the real idea	0.783	3.671	1.183
Have a closer relationship	0.836	3.720	1.182
Can maintain a long-term good interpersonal relationship	0.911	3.677	1.202
Product Quality (CR = 0.838, AVE = 0.634)
High quality (such as restaurants, hotels and buses).	0.805	3.635	1.191
Arranges are of high quality and safe.	0.833	3.756	1.165
The schedule is coherent and reasonable	0.748	3.887	1.142
Product Feature (CR = 0.887, AVE = 0.725)
The tourist attractions and experience are attractive and special	0.809	3.494	1.222
Services and products are hard to replace	0.809	3.541	1.178
The tourism product portfolio is more unique	0.931	3.571	1.218
Service Attitude (CR = 0.863, AVE = 0.678)
Listens patiently	0.879	3.622	1.217
Responds positively	0.785	3.594	1.146
Patiently listen suggestions and opinions at the end of the trip	0.803	3.551	1.152
Service Efficiency (CR = 0.847, AVE = 0.649)
Respond quickly	0.87	3.579	1.171
Quickly provide solutions and corresponding assistance	0.784	3.622	1.165
Quickly deal with refund, feedback	0.758	3.654	1.217
Price Reasonableness (CR = 0.862, AVE = 0.676)
Price advantage	0.813	3.592	1.204
Charges reasonable fees for temporarily increased	0.776	3.680	1.174
The charges of the tourism company are equal to the value of the services	0.875	3.600	1.196
Price-Performance Ratio (CR = 0.886, AVE = 0.723)
Tourist routes and products are cost-effective.	0.832	3.641	1.222
Services cost-effective.	0.792	3.688	1.182
The overall economic investment has even exceeded the expected experience return	0.922	3.639	1.182
Nonmonetary Input (CR = 0.887, AVE = 0.664)
Time spent on trip preparation is within acceptable range	0.786	3.641	1.135
Time spent on communication and emergencies handling is within acceptable range.	0.781	3.780	1.138
Energy and physical strength spent are within the acceptable range	0.823	3.887	1.034
Energy and physical strength spent within the acceptable range.	0.866	3.795	1.128

Test of the Hierarchical Relationships between the Dimensions of Tourist's Perceived Value in Customization Models

Based on the "demand-result" chain, tourists' perceived value can be divided into three levels. This study used a structural equation model to examine the hypothesized structural model shows in Table 5.

Table 4 Means And Reliability Of The Perceived Value Results
Entertainment Experience (CR = 0.876, AVE = 0.702)	Factor loading	Mean	SD
Relaxing	0.805	3.534	1.147
Full of fun	0.797	3.447	1.143
No additional pressure during the customization process	0.907	3.449	1.176
Aesthetic Experience (CR = 0.877, AVE = 0.705)
Natural aesthetic experience.	0.785	3.383	1.173
Cultural aesthetic experience.	0.816	3.502	1.136
Meet the aesthetic expectations	0.912	3.402	1.126
Knowledge Acquisition (CR = 0.856, AVE = 0.664)
Informative and entertaining into the destination’s history, art, nature	0.828	3.660	1.195
Enrich experience of participating in the local area and the cultural customs	0.788	3.671	1.135
Enriched travel experience	0.828	3.637	1.154
Personal Reputation (CR = 0.864, AVE = 0.681)
Can get higher recognition	0.833	3.588	1.057
Can improve others’ impression and enhance personal reputation	0.743	3.372	1.073
Can get more respect and preferential treatment when I travel.	0.892	3.474	1.084
Social Interaction (CR = 0.882, AVE = 0.714)
Broaden social interaction scope.	0.838	3.511	1.102
Enhance social skills.	0.79	3.590	1.098
Can participate and integrate into the social life of the destination	0.903	3.545	1.069
Monetary Cost Value (CR = 0.866, AVE = 0.684)
The travel cost matches the products and services	0.77	3.329	1.152
Worthy of the money	0.8	3.526	1.119
Economical	0.905	3.438	1.151
Non-Monetary Cost Value (CR = 0.876, AVE = 0.703)
Process is reasonable	0.795	3.374	1.142
Energy and physical effort invested in is worthwhile.	0.794	3.318	1.053
No need for extra time and energy to deal with unexpected problems during the trip	0.92	3.242	1.089

The main objectives of this study are to validate the hierarchical structure for the tourist perceived value constructs of a customization model and to examine the relationship among these factors. The results of the correlation analysis (Table 5) and hypothesis testing (Table 6) based on structural equation modeling show that in the hierarchy of tourists’ perceived value demand, EFs, PFs, and MNM have significant positive effects on the HV, SV, and CV of the perceived value result level. However, TV does not have a significant positive effect on SV (β= 0.105, p>0.05); thus, the corresponding hypothesis is not established.

Table 5 Correlation Analysis Results
	EFs	PFs	TV	MNM	PV	SV	CV	TSA	BT
EFs	1
PFs	0.312**	1
TV	0.331**	0.306**	1
MNM	0.377**	0.335**	0.328**	1
HV	0.457**	0.426**	0.389**	0.431**	1
SV	0.419**	0.361**	0.345**	0.426**	0.408**	1
CV	0.441**	0.421**	0.433**	0.447**	0.397**	0.356**	1
TSA	0.426**	0.314**	0.281**	0.309**	0.552**	0.486**	0.494**	1
BT	0.392**	0.390**	0.349**	0.365**	0.564**	0.547**	0.563**	0.512**	1

The main objectives of this study are to validate the hierarchical structure for the tourist perceived value constructs of a customization model and to examine the relationship among these factors. The results of the correlation analysis (Table 5) and hypothesis testing (Table 6) based on structural equation modeling show that in the hierarchy of tourists’ perceived value demand, EFs, PFs, and MNM have significant positive effects on the HV, SV, and CV of the perceived value result level. However, TV does not have a significant positive effect on SV (β = 0.105, p>0.05); thus, the corresponding hypothesis is not established shows in Figure 2.

Table 6 Path Coefficients
Path			Standardized	Unstandardized	S.E.	C.R.	P	Result
			estimates	estimates
CV	<---	EFs	0.274	0.301	0.077	3.933	***	Supported
CV	<---	PFs	0.254	0.298	0.08	3.718	***	Supported
CV	<---	TV	0.219	0.243	0.068	3.591	***	Supported
CV	<---	MNM	0.201	0.196	0.066	2.952	0.003	Supported
HV	<---	EFs	0.318	0.331	0.074	4.484	***	Supported
HV	<---	MNM	0.176	0.162	0.062	2.599	0.009	Supported
HV	<---	TV	0.13	0.137	0.063	2.179	0.029	Supported
HV	<---	PFs	0.299	0.333	0.077	4.295	***	Supported
SV	<---	PFs	0.192	0.209	0.075	2.791	0.005	Supported
SV	<---	MNM	0.234	0.21	0.063	3.331	***	Supported
SV	<---	TV	0.105	0.107	0.063	1.709	0.087	Not supported
SV	<---	EFs	0.302	0.307	0.073	4.177	***	Supported
TSA	<---	HV	0.414	0.441	0.072	6.137	***	Supported
TSA	<---	SV	0.288	0.315	0.066	4.747	***	Supported
TSA	<---	CV	0.279	0.282	0.066	4.239	***	Supported
BT	<---	HV	0.364	0.378	0.069	5.488	***	Supported
BT	<---	SV	0.355	0.378	0.066	5.715	***	Supported
BT	<---	CV	0.387	0.381	0.067	5.671	***	Supported

The three dimensions of the perceived value result level (i.e., HV, SV, and CV) significantly affect the two dimensions of the result level (i.e., TSA and BT) shows in Table 6.

Discussion

Theoretical Implications

Although tourist value perceptions have been studied for more than a decade, customer value perception models have been constructed mainly around destinations, tourism products and services. The model adopted by tourism firms, as the subject of value transfer, has rarely been studied in isolation, but has been split into other, more subtle branches such as individual employees Liang & Wu (2022) employee work environment Hartline & Jones (1996), and organizational values (Cheng et al., 2013). In addition, most studies tend to locate various factors in tourists' perceived value at the same level, arguing that these factors have a similar impact on tourists' ultimate satisfaction and behavior.

Tourism products and services differ among companies with distinct business models. As a customer-oriented model, customization can bring personalized products and services to customers. This study focuses on testing whether an enterprise’s operation mode, the service method of the staff, and the service experience during customized travel ultimately affect the attitudes and loyalty of tourists.

First, we divide the tourist perceived value system into a demand level and a result level. Our empirical data show that EFs and PFs can affect the result level, including CV, SV, and HV. Nevertheless, TV, which contains products and services, cannot affect tourists' SV.

We believe that this result can be explained by two aspects: first, in a customization model, the most basic needs of customers are to enjoy tailor-made itinerary details that meet their expectations and, to some extent, to save on time and energy costs. The purpose of a customized tour is not to obtain knowledge or even to expand one’s social interaction. Hence, SV itself is not within the scope of the travel purpose, which is different from the measurement results of the perception model established by (Williams & Souter 2009; Huang & Huang 2007).

Second, when stratifying the dimensions of tourists' perceived value, SV may not be assigned to the result level but should be located at the demand level. From the perspective of customization, for some tourists who like culture, history, or art, whether tourism products and the route design are related to their needs directly affects their perception of SV. Tourists who do not have such needs will pay more attention to advantages other than the perceived increase in SV. Kim et al. (2019) showed that social value does not affect loyalty, but brand value has a positive impact on user perceived value. This study believes that different types of customization have different effects on the branding of tourism companies. We include the brand value in the social value, which corroborates that the products and services do affect social value. However, whether the brand's influence on the perceived value of tourists is mainly derived from the company itself or from the destination experience remains to be explored.

Under a customization model, tourists directly perceive the division of labor and specialization of the personnel of tourism enterprises, and these factors directly affect their' perceptions. In the past, tourism enterprises focused on product development and destination experience upgrading, ignoring their own upgrading and connection with tourist.

In the future, after the COVID-19 pandemic, tourists will be more cautious about their travel choices. Customization models have great potential though skill and precision are required. They enable customers to participate in itinerary design with tourism companies, choose the travel content they are interested in, and save on time and energy costs. The considerable development potential also necessitates enterprises to innovate to address the existing defects in customization models. Current customization models still meet the basic needs of tourists. More social, aesthetic, and cultural richness are needed.

Management Implications

Customization model is a business field with huge potential and rapid growth in the tourism market, studies on how to bring more value to tourists and transform it into corporate benefits under this model are few. This study provides an advanced level system of tourists’ perceived value under the framework of the customization model and the influence relationship of each perceived value factor on satisfaction and repurchase intention. This research also provides a new perspective for tourism companies to explore more services and product innovations to help maximize tourists’ experience of tourism products, corporate services, and destination-related activities.

Tourism service design combined with tourist value is a successful marketing strategy (Phau et al., 2014). This research provides the following practical suggestions for tourism companies that adopt customized services. First, the company should improve the website functions and product information while emphasizing its customization features. Tourists value the role of companies in the customization process. Therefore companies to consider primary ticketing, hotel, transportation, and accommodation and focus on the development of destination-related experiences so that tourists can gain a sense of social integration by experiencing the local cultural life. At present, tourists can obtain destination information from various channels and establish their psychological expectations. However, this fragmented information can be customized and combined with the specific needs of tourists, which has extremely high requirements for the professionalization of the customizer. Recommending far-fetched experience package to tourists is not advisable. How to closely contact the destination and grasp timely information is the key to successfully realizing the customized model.

Secondly, when developing certain tourism behaviors, attitudes can be the decisive factor Han & Kim (2010) and positively impact the perceived value of tourists. The degree of satisfaction of tourists at different stages will affect their attitude. The communication, service attitude, and knowledge storage of corporate staff before the trip affect tourists’ perception of the value of the route. Therefore, targeted delivery of destinations such as cultural customs, historical site information or emphasis on the comfort and pleasure of the itinerary can guide tourists. The return visit can also lead tourists to have a positive attitude.

Furthermore, many studies have shown that tourist satisfaction is closely related to the expected product performance Chang et al. (2010) the well-being gained by experiencing tourism services or products will increase the behavior intentions of tourists(Kim & Hall, 2019). Nevertheless, Dolnicar et al. (2015) put forward a scenario hypothesis: when a family travels to an old place, the degree of surprise does not affect satisfaction. Another situation is that tourists are delighted with the spectacular cultural scene of the destination, but they will not return because they seek more cultural features of different regions. Different tourism situations will lead to varying expectations of product quality. Previous studies have pointed out that subjective well-being plays a positive role in the context of the tourism industry. For users with different emotional needs, market segmentation strategies should be formulated based on the motivation of psychological needs (Kim et al., 2017). According to the difference in customer perception of value, providing more personalized and even thematic services can not only improve the functional level of value perception, but also enhance the emotional and experience value (Zhao et al., 2020).

This research extends the behavioral intention of tourists to the perceived value at the demand and result levels and reflects the gradual relationship between them and the final satisfaction. We provide a reference structure for tourism companies, which can specifically deepen the degree of customization according to the actual needs of tourists. Tourism companies can then understand the different priorities in customers’ travel demand hierarchy and expectations of tourists on all aspects of the value perception result level to adjust the details of customized products. Ultimately, they will realize the maximum value transmission of tourism products and services (Kim et al., 2019).

This provides a reference for small businesses to combine limited resources to maximize benefits after COVID-19, while tourism policy makers can also support through policy to allow companies providing customized services to better explore the potential resources of the destination. For example, encouraging enterprises to develop thematic travel itineraries for different target markets, customized marketing and the development of new niche tourism programs will achieve a rapid recovery of destination tourism while stimulating effective competition among enterprises.

Conclusion

Many of the structures of the tourism service process related to tourist perception and satisfaction are intangible structures that are difficult to measure. The results of this study conceptualise multidimensional perceived value transmissions, concretising tourist value perceptions into a needs dimension (pragmatism) and a results dimension (psychological needs and socialisation). The study explores for the first time the hierarchical relationship between tourist perception levels, satisfaction, and behavioural intentions in the context of customization. The study emphasises the impact that a tourism company's services and products can have on tourist satisfaction through value transfer at different levels of perception. Specifically tourists are more likely to generate greater satisfaction if their needs level is satisfied, and the mediating role of the tourist perceived outcome level in the relationship between the three dimensions of needs level, satisfaction and behavioural intentions is found, highlighting the importance of research that specifically delineates the direct and indirect effects between the perceived value levels in the areas of tourist satisfaction and behavioural intentions. This study adapts and extends the existing customer perceived value dimensions to apply to a range of value analyses in a customized model.

The limitation of this research is that customization, as a rapidly developing new model, is widely adopted by Chinese tourists. However, given differences in culture, customs, and religions, whether the research results can apply to other countries must be treated cautiously. Researchers can also adjust or decrease the factors of tourists’ perceived value at the demand and result levels for specific situations in the future. For example, customized routes for festivals, festival elements (e.g., weather, atmosphere, customs, etc.) and social elements (e.g., safety, travel convenience, etc.) can be incorporated into tourists’ perceived value demand level.

Finally, a growing number of scholars incorporate perceived risk into the research on perceived value, satisfaction, and behavior tendency. After going through the COVID-19 pandemic, the public’s first consideration for a while is a destination’s safety. Whether the customized model can coordinate the perceived risk remains to be explored. Over time, customized companies are also prone to homogeneity. How to make this model sustainable and competitive is also worthy of attention by scholars.

Acknowledgement

The author would like to thank the support of the National Social Science Fund of China (20BGL159).

References

Anderson, E.W., Fornell, C., & Rust, R.T. (1997). Customer satisfaction, productivity, and profitability: Differences between goods and services. Marketing science,16(2), 129-145.

 Indexed at, Google Scholar, Cross Ref

Botterill, T.D., & Crompton, J.L. (1996). Two case studies exploring the nature of the tourist's experience. Journal of Leisure Research,28(1), 57.

Indexed at, Google Scholar

Brouder, P., Teoh, S., Salazar, N.B., Mostafanezhad, M., Pung, J.M., Lapointe, D., & Clausen, H.B. (2020).  Reflections and discussions: tourism matters in the new normal post COVID-19. Tourism Geographies, 22(3), 735-746.

Indexed at, Google Scholar, Cross Ref

Castellanos-Verdugo, M., Vega-Vázquez, M., Oviedo-García, M.Á., & Orgaz-Agüera, F. (2016). The relevance of psychological factors in the ecotourist experience satisfaction through ecotourist site perceived value. Journal of Cleaner Production, 124, 226-235.

Indexed at, Google Scholar, Cross Ref

Chathoth, P. K., Ungson, G. R., Harrington, R. J., & Chan, E. S. (2016). Co-creation and higher order customer engagement in hospitality and tourism services: A critical review. International Journal of Contemporary Hospitality Management, 28(2), 10357

Indexed at, Google Scholar, Cross Ref

Chang, H.H., & Chen, S.W. (2009). Consumer perception of interface quality, security, and loyalty in electronic commerce.  Information and Management, 46(7), 411-417.

Indexed at, Google Scholar, Cross Ref

Chang, R.C., Kivela, J., & Mak, A.H. (2010). Food preferences of Chinese tourists. Annals of Tourism Research, 37(4), 989-1011.

Indexed at, Google Scholar, Cross Ref

Chen, P.T., & Hu, H.H. (2010). The effect of relational benefits on perceived value in relation to customer loyalty: An empirical study in the Australian coffee outlets industry. International Journal of Hospitality Management, 29(3), 405-41.

Indexed at, Google Scholar, Cross Ref

Cheng, P.Y., Yang, J.T., Wan, C.S., & Chu, M.C. (2013). Ethical contexts and employee job responses in the hotel industry: The roles of work values and perceived organizational support. International Journal of Hospitality Management, 34, 108-115.

Indexed at, Google Scholar, Cross Ref

Cronin Jr, J.J., Brady, M.K., & Hult, G.T.M. (2000). Assessing the effects of quality, value, and customer satisfaction on consumer behavioral intentions in service environments. Journal of Retailing, 76(2), 193-218.

Indexed at, Google Scholar, Cross Ref

Dolnicar, S., Coltman, T., & Sharma, R. (2015). Do satisfied tourists really intend to come back? Three concerns with empirical studies of the link between satisfaction and behavioral intention. Journal of Travel Research, 54(2), 152-178.

Indexed at, Google Scholar, Cross Ref

Dong, B. (2015). How a customer participates matters: “I am producing” versus “I am designing”. Journal of services marketing. 29(6/7), 498-510.

Indexed at, Google Scholar, Cross Ref

Döring, S. (2008). Personalization of the search process in tourism (Doctoral dissertation, Dissertation, Universität Augsburg).

Indexed at, Google Scholar

Duman, T., & Mattila, A.S. (2005). The role of affective factors on perceived cruise vacation value. Tourism Management, 26(3), 311-323.

Indexed at, Google Scholar, Cross Ref

Eid, R., and El-Gohary, H. (2015), Muslim tourist perceived value in the hospitality and tourism industry, Journal of Travel Research, 54(6), 774-787.

Indexed at, Google Scholar, Cross Ref

El-Adly, M.I. (2019). Modelling the relationship between hotel perceived value, customer satisfaction, and customer loyalty. Journal of Retailing and Consumer Services, 50, 322-332.

Indexed at, Google Scholar, Cross Ref

Flint, D.J., Woodruff, R.B., & Gardial, S.F. (1997). Customer value change in industrial marketing relationships: a call for new strategies and research. Industrial Marketing Management, 26(2), 163-175.

Indexed at, Google Scholar, Cross Ref

Fornell, C., & Larcker, D.F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39-50.

Indexed at, Google Scholar, Cross Ref

Gallarza, M.G., & Saura, I.G. (2006). Value dimensions, perceived value, satisfaction and loyalty: an investigation of university students’ travel behaviour. Tourism Management, 27(3), 437-452.

Indexed at, Google Scholar, Cross Ref

Gilbert, D., & Wong, R. K. (2003). Passenger expectations and airline services: a Hong Kong based study. Tourism Management, 24(5), 519-532.

Indexed at, Google Scholar, Cross Ref

Hair, J.F., Black, W.C., Babin, B.J., & Anderson, R.E. (2010). Multivariate Data Analysis : A global perspective (7th ed.).

Han, H., & Kim, Y. (2010). An investigation of green hotel customers’ decision formation: Developing an extended model of the theory of planned behavior. International Journal of Hospitality Management, 29(4), 659-668.

Indexed at, Google Scholar, Cross Ref

Hartline, M. D., & Jones, K. C. (1996). Employee performance cues in a hotel service environment: Influence on perceived service quality, value, and word-of-mouth intentions. Journal of Business Research, 35(3), 207-215.

Indexed at, Google Scholar, Cross Ref

Hong, Z.H.A.N.G. (2012). Analysis of the characters and applications of" Tailor-made Tour. Tourism Research.

Hongmei, Z., Juan, H., & Wenjing, Z. (2012). The hierarchy relationship model of tourists perceived value on tourism destination. Human Geography, 27(4), 125-130.

Huang, Y., & Huang, F. (2007). Tourists’ perceived value model and its measurement: An empirical study. Tourism Tribune, 22(8), 42-47.

Inkson, C., & Minnaert, L. (2018). Tourism management: an introduction. Sage.

Jayanti, R. K., & Ghosh, A. K. (1996). Service value determination: An integrative perspective. Journal of Hospitality & Leisure Marketing, 3(4), 5-25.

Indexed at, Google Scholar, Cross Ref

Jin, L., He, Y., & Song, H. (2012). Service customization: To upgrade or to downgrade? An investigation of how option framing affects tourists’ choice of package-tour services. Tourism Management, 33(2), 266-275.

Indexed at, Google Scholar, Cross Ref

Karl, M., Muskat, B., & Ritchie, B. W. (2020). Which travel risks are more salient for destination choice? An examination of the tourist’s decision-making process. Journal of Destination Marketing & Management, 18, 100487. 

Indexed at, Google Scholar, Cross Ref 

Kim, M. J., & Hall, C. M. (2019). A hedonic motivation model in virtual reality tourism: Comparing visitors and non-visitors. International Journal of Information Management, 46, 236-249.

Indexed at, Google Scholar, Cross Ref

Kim, S., Ham, S., Moon, H., Chua, B. L., & Han, H. (2019). Experience, brand prestige, perceived value (functional, hedonic, social, and financial), and loyalty among GROCERANT customers. International Journal of Hospitality Management, 77, 169-177.

Indexed at, Google Scholar, Cross Ref

Kramer, T. (2007). The effect of measurement task transparency on preference construction and evaluations of personalized recommendations. Journal of Marketing Research, 44(2), 224-233.

Indexed at, Google Scholar, Cross Ref 

Lew, A.A., Cheer, J.M., Haywood, M., Brouder, P., & Salazar, N.B. (2020). Visions of travel and tourism after the global COVID-19 transformation of 2020. Tourism Geographies, 22(3), 455-466.

Indexed at, Google Scholar, Cross Ref

Lew, A.A., and Hall, C.M., and Williams, A.M., Ed.s. (2008),A companion to tourism, John Wiley & Sons, New York, NY.

Liang, L., & Wu, G. (2022). Effects of COVID-19 on customer service experience: Can employees wearing facemasks enhance customer-perceived service quality? Journal of Hospitality and Tourism Management, 50, 10-20. 

Indexed at, Google Scholar, Cross Ref

Miao, L., Im, J., Fu, X., Kim, H., & Zhang, Y. E. (2021). Proximal and distal post-COVID travel behavior. Annals of Tourism Research, 88, 103159.

Indexed at, Google Scholar, Cross Ref

Moral-Cuadra, S., Orgaz-Agüera, F., & Cañero-Morales, P.M. (2019). Attitude towards border tourism and its relationship with visitor satisfaction and loyalty. Geo Journal of Tourism and Geosites, 25(2), 609-622.

Indexed at, Google Scholar, Cross Ref

Neuburger, L., & Egger, R. (2021). Travel risk perception and travel behaviour during the COVID-19 pandemic 2020: A case study of the DACH region. Current Issues in Tourism, 24(7), 1003-1016. 

Indexed at, Google Scholar, Cross Ref

O'Cass, A., & Sok, P. (2013). Exploring innovation driven value creation in B2B service firms: The roles of the manager, employees, and customers in value creation. Journal of Business Research, 66(8), 1074-1084.

Indexed at, Google Scholar, Cross Ref

Otto, J.E., & Ritchie, J.B. (1996). The service experience in tourism. Tourism Management, 17(3), 165-174.

Indexed at, Google Scholar, Cross Ref

Overstreet Jr, G.A. (1993). Creating a value in Oversupplied Markets: The Case of Charlotesville, Vinia, Hotels. Cornell Hotel and Restaurant Administration Quarterly, 34(5), 68-96.

Indexed at, Google Scholar, Cross Ref

Pallant, J., Sands, S., & Karpen, I. (2020). Product customization: A profile of consumer demand. Journal of Retailing and Consumer Services, 54, 102030.

Indexed at, Google Scholar, Cross Ref 

Pappas, I.O., Kourouthanassis, P.E., Giannakos, M.N., & Chrissikopoulos, V. (2014). Shiny happy people buying: the role of emotions on personalized e-shopping. Electronic Markets, 24(3), 193-206.

Indexed at, Google Scholar, Cross Ref   

Parasuraman, A., & Grewal, D. (2000). The impact of technology on the quality-value-loyalty chain: a research agenda.  Journal of the Academy of Marketing Science, 28(1), 168-174.

Indexed at, Google Scholar, Cross Ref

Peacock, S., Reddy, A., Leveille, S. G., Walker, J., Payne, T. H., Oster, N. V., & Elmore, J. G. (2017). Patient portals and personal health information online: perception, access, and use by US adults. Journal of the American Medical Informatics Association, 24(e1), e173-e177.

Indexed at, Google Scholar, Cross Ref

Petrick, J. F. (2004). The roles of quality, value, and satisfaction in predicting cruise passengers’ behavioral intentions. Journal of Travel Research, 42(4), 397-407.

Indexed at, Google Scholar, Cross Ref 

Phau, I., Quintal, V., & Shanka, T. (2014). Examining a consumption values theory approach of young tourists toward destination choice intentions. International Journal of Culture, Tourism and Hospitality Research.8, ( 2)

Indexed at, Google Scholar, Cross Ref

Prebensen, N.K., Woo, E., Chen, J.S., & Uysal, M. (2013). Motivation and involvement as antecedents of the perceived value of the destination experience. Journal of Travel Research, 52(2), 253-264.

Indexed at, Google Scholar, Cross Ref 

Rasoolimanesh, S.M., Dahalan, N., & Jaafar, M. (2016). Tourists' perceived value and satisfaction in a community-based homestay in the Lenggong Valley World Heritage Site. Journal of Hospitality and Tourism Management, 26, 72-81.

Indexed at, Google Scholar, Cross Ref

Roig, J.C.F., Garcia, J.S., Tena, M.A.M., & Monzonis, J.L. (2006). Customer perceived value in banking services. International Journal of Bank Marketing.24 (5).

Indexed at, Google Scholar, Cross Ref 

Ryu, K., Han, H., & Kim, T.H. (2008).The relationships among overall quick-casual restaurant image, perceived value, customer satisfaction, and behavioral intentions. International Journal of Hospitality Management, 27(3), 459-469. 

Indexed at, Google Scholar, Cross Ref

Sánchez-Cañizares, S. M., Cabeza-Ramírez, L. J., Muñoz-Fernández, G., & Fuentes-García, F. J. (2021). Impact of the perceived risk from Covid-19 on intention to travel. Current Issues in Tourism, 24(7), 970-984. 

Indexed at, Google Scholar, Cross Ref

Sanchez, J., Callarisa, L., Rodriguez, R. M., & Moliner, M.A. (2006). Perceived value of the purchase of a tourism product. Tourism Management,27(3), 394-409.

Indexed at, Google Scholar, Cross Ref

Sweeney, J.C., & Soutar, G.N. (2001). Consumer perceived value: The development of a multiple item scale. Journal of Retailing. 77(2), 203-220. `

Indexed at, Google Scholar, Cross Ref

Sheth, J.N., Newman, B.I., & Gross, B.L. (1991). Why we buy what we buy: A theory of consumptionvalues. Journal of Business Research,22(2), 159-170.

Indexed at, Google Scholar, Cross Ref

Solvoll, S., Alsos, G.A., & Bulanova, O. (2015). Tourism entrepreneurship–review and future directions. Scandinavian Journal of Hospitality and Tourism,15(1), 120-137. 

Indexed at, Google Scholar, Cross Ref

Sui L., Li Y., and Cheng W. (2009), A study on the difference of customer perceived value of Chinese cultural heritage tourism and western. Tourism Science, 23(6), 14-20.

Ulaga, W. (2001). Customer value in business markets: an agenda for inquiry. Industrial Marketing Management, 30(4), 315-319. 

Indexed at, Google Scholar, Cross Ref

Williams, P., & Soutar, G.N. (2009). Value, satisfaction and behavioral intentions in an adventure tourism context. Annals of Tourism Research,36(3), 413-438.

Indexed at, Google Scholar, Cross Ref   

Woodruff, R.B. (1997). Customer value: the next source for competitive advantage. Journal of the Academy of Marketing Science,25(2), 139-153.

Indexed at, Google Scholar, Cross Ref

Wu, J.J. (2004). Influence of market orientation and strategy on travel industry performance: an empirical study of e-commerce in Taiwan. Tourism Management,25(3), 357-365.

Indexed at, Google Scholar, Cross Ref

Yi, S., Day, J., & Cai, L.A. (2014). Exploring tourist perceived value: An investigation of Asian cruise tourists' travel experience. Journal of Quality Assurance in Hospitality Tourism,15(1), 63-77.

Indexed at, Google Scholar, Cross Ref 

Yoo, D.K., & Park, J.A. (2007). Perceived service quality: Analyzing relationships among employees, customers, and financial performance. International Journal of Quality & Reliability Management, 4(9).  

Google Scholar, Cross Ref

Zhao, Y., Chau, K. Y., Shen, H., Duan, X., & Huang, S. (2020). The influence of tourists’ perceived value and demographic characteristics on the homestay industry: A study based on social stratification theory. Journal of Hospitality and Tourism Management,45, 479-485.

Indexed at, Google Scholar, Cross Ref

Zhang, H., Song, H., Wen, L., & Liu, C. (2021). Forecasting tourism recovery amid COVID-19. Annals  of Tourism Research,87, 103149.

Indexed at, Google Scholar, Cross Ref

Zhang, H., Hong, J., & Zhang, W., (2012). The Hierarchy relationship model of tourists perceived value on tourism destination.  Human Geography, 27(4), 125-130.

Zhang, T., and Jia, S.H. (2008), A Study on the Dimensions and Measurement of Consumers' Perceived Values during Festivals. Tourism Tribune,12(5), 4-78.

Zhou, L., Dai, L., & Zhang, D. (2007). Online shopping acceptance model-A critical survey of consumer factors in online shopping. Journal of Electronic Commerce Research,8(1).

Indexed at, Google Scholar

Zhou, F., Ji, Y., & Jiao, R. J. (2013). Affective and cognitive design for mass personalization: status and prospect. Journal of Intelligent Manufacturing, 24(5), 1047-1069.

Indexed at, Google Scholar, Cross Ref

Received: 11-Apr-2022, Manuscript No. AEJ-22-11763; Editor assigned: 12-Apr-2022, PreQC No. AEJ-22-11763(PQ); Reviewed: 18-Apr-2022, QC No. AEJ-22-11763; Revised: 22-Apr-2022, Manuscript No. AEJ-22-11763(R); Published: 25-Apr-2022