E-Loyalty and E-marketing: A matter of E-Trust

1. Introduction

E-loyalty and e-marketing are two of the most important aspects of any successful online business. In order for customers to remain loyal to a business, they must trust the company and its products. Trust in digital context is known as e-trust, where customer avail goods and services digitally or through internet (Taddeo, M. (2009), it is essential for any business to succeed in the digital age. Previous satisfaction and loyalty surveys were mainly conducted in offline consumer environments. Hence, it is discovered by the researchers that it is necessary for interactive and personalized marketing to offer more and more opportunities (Burke, R. R. 2002). Hence the main focus of this study is on e-loyalty and how automatically it generates the e-trust. Lack of trust is a major obstacle to the adoption of e-commerce (Chang, Cheung, & Tang, 2013). On the other side, trust is found to be a key factor in the global spread of Information and communication technologies (ICTs) (Kirs & Bagchi, 2012). Indeed, e-marketing has globalized, making cross-border purchases by consumers simple and convenient, and opening up markets for online retailers on both sides of the Atlantic.

Culture is the backbone of this study. Previous literature emphasize the need for more study of trust's dimensions and the influence of culture on trust (Gefen, Benbasat, and Pavlou (2008), therefore culture and e-trust are interrelated. Nonetheless, there is a surprising lack of actual study validating their connection, especially in digital context (e-marketing) (Gefen & Heart, 2006), trust, trustworthiness (including ability, integrity, and benevolence), and inclination to trust are so frequently used synonymously and combined in the research, we also focus on the dimensionality of these and related categories in the present study. In short if there would be no trust then the consumers avoid to buy goods and services online, and their focus would be changed from online to physical which affect the whole market. Culture also took part in trust depending on the specific area, for example in some countries people do not prefer to buy online because of the e-trust they prefer to buy physical it happens mostly in Asian countries. According to Luhmann (1979), a person decides whether or not to trust a brand based on three factors: past experiences, expectations, and the level of risk involved. The familiarity of both the trustor and the trustee with the system is crucial. It's the thing that sets the trustor at ease with their decision to trust. So the e-trust build by designing the good strategies as per the digital market requirement. E-trust is also affected by e-loyalty and e-marketing (Wilis & Nurwulandari, 2020). Discussing the E-loyalty and E-marketing phenomenon is the important in this era because all the digital marketing is depending on it. Researchers have also been looking into ways to build up online loyalty among clients in recent years (Chou, Chen, & Lin, 2015). Previous research has shown that e-satisfaction and e-trust are two of the most important aspects in creating e-loyalty (Chou, Chen, & Lin, 2015). There are other factors affecting e-trust (Juwaini, 2022), these factots could be quality, price, marketing tactics etc. But here researcher were not specifically mentioned about culture, which is the focus of the study.

As per the previous literature, there are two problems that has to define: (1) why consumer still face e-trust issue while designing different strategies according to the market? (2) Which factor involved with e-trust so that consumer are still hesitated by trusting an online brand? Apart from all marketing strategies and purchasing again and again by showing e-loyalty, consumer still affected by culture and the trends in the particular society they are living in. (3) This study also explaining the consequences of e-loyalty and e-trust. (4) It also explaining the importance of e-loyalty, e-marketing, e-trust and culture in both national and international perspective.

Further studies are needed for e-loyalty, e-marketing, e-trust (Shafiee, Haghighizade & Rahimzadeh, 2016) and culture is the suitable factor to analyze the digital marketing in a better way. Previous studies defined commitment of e-loyalty and how consumer to consistently revisit the website and repeatedly buy the goods and services from that particular website (Cyr, 2008) but they did not define why this happened, this happened due to the e-trust they built. If consumer is loyal then he/she will purchase goods and services repeatedly, but some other factors also change the mind set of consumer such as culture, which is not discussed in this perspective. Of course e-loyalty and e-marketing generated e-trust but culture has the power to change the consumer mentality against e-trust, which is the focus of the current study. Therefore, it is a pressing need to address the knowledge gap around the connections between e-marketing, e-trust, and e-loyalty with the effect of culture as a mediator. On the basis of literature review and prior studies on e-loyalty, e-marketing, e-trust and culture; the present study is focused on closing above mentioned key gaps and concluded the following research questions:

• What is the relationship of E-loyalty and e-trust? Either this relationship is positive or negative?
• What is the relationship of E-marketing and e-trust? Either this relationship is positive or negative?
• Either Culture mediates the relationship between E-Loyalty and E-trust?
• Culture mediates the relationship between E-Marketing and E-trust?
• Culture affected E-trust in both positive and negative way.

2. Theoretical Background

Previous research has shown that e-trust is significant contributors to e-loyalty among customers (Chou, Chen & Lin 2015). Customers are more likely to make purchases from an online retailer in which they have a high level of perceived e-trust (Connolly, & Bannister, 2007), E-trust creates a safe environment in which consumers feel more comfortable being honest (Cho& Fiorito, 2009) and prefer to buy products again and again on the same website (Liu, et al., 2005), which shows higher loyalty to the particular brand or website. If a consumer has e-trust then uncertainty decreases and rebuying possibility increase (Doong, Wang, & Shih, 2008) which shows e-loyalty to that specific brand. Several researches done in an online setting have indeed revealed a beneficial connection between e-trust and e-loyalty (Harris & Goode, 2004; Kassim & Abdullah, 2008).

The emergence of loyalty notion comes back to early decade of 1940. The market share (behavioral loyalty) and brand preferences (attitude loyalty) are two distinct ideas represented in this framework (Rundle-Thiele, 2001). In this domain, numerous scholars have provided a variety of definitions. Some academics think that loyalty is demonstrated by repeated purchases of consumer (Jacoby, 1978), and examining a customer's purchasing patterns entails examining their level of loyalty (Kuehn, 1962). Others think the behavioral and attitudinal components work well together to evaluate loyalty (Dick & Basu, 1994). Richard Oliver has provided the most thorough definition, and in his opinion, loyalty is defined as a strong commitment to continue purchasing the same goods or services in the future, despite rivals' marketing efforts (Oliver, 1999). E-loyalty is defined as customers' propensity to make repeat purchases based on their positive impressions of a brand over time (Keller, 1993), and repeat purchase showed e-trust and e-loyalty direct and positive relationship. Here it is approved that E-loyalty and E-trust has positive relationship with each other. If a consumer trust any website or brand and prefer to purchase repeatedly it shows the E-loyalty with that particular brand.

H1. 

E-Loyalty has positive effect on E-trust; E-trust positively affected by E-Loyalty

In order to effectively communicate with its clients, the lodging sector has embraced the Internet (Diaz and Koutra, 2013; Law et al., 2010). A website is undoubtedly a helpful tool for businesses to advertise their goods and services and attract and keep clients (Akincilar and Dagdeviren, 2014). According to McMullan and Gilmore (2008), returning guests have an impact on the hotel's bottom line and are crucial to the spread of good word of mouth (WOM), which shows the trust and loyalty of the customers. E-loyalty increased comprises on e-marketing effectiveness (which represented the e-trust), sufficient sales and growth in customer attraction (Sharma & Sheth, 2004), which represented the positive relation of E-marketing and E-trust).

Loyal clients are the foundation of a successful business, and the Internet and e-marketing provide a low-cost means of cultivating these ties (Chang, & Chen, 2008) and loyal customers are those who has trust on that particular brand. Previous studies demonstrated the significance of trust in e-business (e-marketing) and showed how trust mitigates client apprehension and encourages site visits and purchases (Wu et al. 2008) represented that e-marketing and e-trust has a positive and significant relationship. Accordingly, it may be argued that content on websites is an effective way of developing customers' e-trust (Rahimnia & Hassanzadeh, 2013), which showed the connection of e-marketing and e- trust. E-commerce has a strong influenced on customers’ buying intentions to trust e-marketing (Corbitt et al. 2003) so that, e-trust is created by e-marketing. E-trust has a significant, positive impact on e-marketing (Corbitt et al. 2003). It has been shown that consumers are more willing to shop online if they have greater e-marketing techniques and a higher level of trust in e-commerce (Rahimnia & Hassanzadeh, 2013). Customers are attracted to and remain loyal to online businesses that they trust. Hence proved that the e-marketing has a positive effect on e-trust and e-trust significantly making the relation stronger with e-marketing.

H2. 

E-Marketing has positive effect on E-trust; E-trust positively affected by E-Marketing.

It is evaluated the role of culture in the establishment of e-loyalty intentions (Gracia, Arino, & Blasco, 2015), some culture allows the customers to create the e-loyalty and they making purchasing repeatedly then e-trust automatically generated. E-loyalty development process changes among cultures, even across comparable civilizations (Gracia et al., 2015). Consumers in a collectivist and high uncertainty-avoidant culture were hypothesized to be more likely to form trust through a transference process (i.e. the truster draws on proof sources from which trust is transferred to a target) than those in an individualistic and low uncertainty-avoidant culture (Doney et al. 1998). People in high-collectivist and low-risk-taking cultures are more likely to transmit trust because they compare the recipient to the provider (Jin et al. 2008), so that customers are relying on previous experiences and reputation which is created by e-marketing through e-trust which become the root of e-loyalty. Users' perspectives on the e-commerce, such as their level of loyalty, are influenced by cultural norms (Chau et al. 2002) which explained e-loyalty and e-trust depend on the cultural norm of that particular region. For example in China people has more e-trust and e-loyalty than Pakistan or India because their trust built by the previous experience.

H3. 

Culture mediates the relationship between E-Loyalty and E-trust

Therefore, this study combines the findings of previous studies on e-trust with the idea of culture to inquire into the factors that shape customers' perceptions of an e-marketing reliability (Hallikainen & Laukkanen, 2018) which explains the customers’ set of mind are also changing because of the culture and tradition prevailing in that specific region or country. Theoretical investigations imply a connection between national cultures and trust (Doney, Cannon & Mullen, 1998; Hofstede, 1984) Nonetheless, there is surprisingly little actual study verifying their connection, especially in e-marketing (Gefen & Heart, 2006; Huang, Ba, & Lu, 2014; Hwang & Lee, 2012; Jarvenpaa, Tractinsky, & Saarinen, 1999; Yoon, 2009). Some studies inquired into how different cultures affect people's propensity to trust each other (An, & Kim, 2008; Chen, Wu, & Chung, 2008; Park, Gunn, & Han, 2012; Teo, & Liu, 2007), by investigating how various characteristics and dimensions of national culture have an effect on trust (An, & Kim, 2008; Capece et al., 2013; Huang, Ba, & Lu, 2014; Hwang & Lee, 2012; Chen, Wu, & Chung, 2008) culture may effect trust differently in various countries (Gefen & Heart, 2006), it is argued that cultural values effect how consumers from Eastern and Western origins establish trust in e-marketing. In some countries like USA have more trust on e-marketing as compare to Pakistan or Bangladesh. It is studied that trust development among virtual community members in China, Hong Kong and Taiwan, and discover no significant variations in trust development across the nations, but indicate that overall Chinese exhibit a greater trust tendency (Chen, Wu, & Chung, 2008) so It is proved that trust on e-marketing vary from country to country according to their culture. Individuals not only have diverse attitudes and experiences with e-marketing inside and across national cultures, but they also have different degrees of trust in general. Therefore culture mediates the relationship between E-marketing and E-trust.

H4. 

Culture mediates the relationship between E-Marketing and E-trust

Gefen, Benbasat, and Pavlou (2008) included the dimensionality of trust and the influence of culture on trust as research issues that need additional exploration in their research agenda for trust in the digital world. Empirical research validating the connection between national culture and trust is surprisingly scarce, especially in the world of the internet (Huang et al., 2014; Gefen & Heart, 2006; Yoon, 2009), but according to Hofstede, (1984) despite theoretical evidence to the contrary. Current study is also focused on the relationship of culture and trust which is still under observation of many researcher (Tong & Mitra, 2009; Denner et. al., 2019; Hoppes & Holley, 2014). Theoretical studies imply a connection between national cultures and trust (Doney, Cannon, & Mullen, 1998) which showed that still have a need to explore the phenomenon of E-trust and Culture. This study also explaining all the relationship of E-trust and culture in an advance way and contributed in literature. Mostly studies focused on trust but not interested to discuss the trust in digital form which is e-trust. People also follow the trends of e trust (Bauman, A., & Bachmann, R. (2017) that trend is called culture, which convinced the consumer to follow that culture either to trust in digital world or not (e-marketing). If one bad case found then more online consumer affected (Koh, Hu & Clemons, 2010), they believe on what they see in their environment (Trudel, 2019). So we hypothesized:

H5. 

Culture affected E-trust in both positive and negative way.

Figure 1. Theoretical Framework.

Figure 1. Theoretical Framework.

Hypothesis

H1. 

E-Loyalty has positive effect on E-trust; E-trust positively affected by E-Loyalty.

H2. 

E-Marketing has positive effect on E-trust; E-trust positively affected by E-Marketing.

H3. 

Culture mediates the relationship between E-Loyalty and E-trust and created causes and effects the E-trust.

H4. 

Culture mediates the relationship between E-Marketing and E-trust and created causes and effects the E-trust.

H5. 

Culture affected E-trust in both positive and negative way.

3. Methodology

In order to create effective marketing tactics that cater to the kind and degree of customer E-loyalty and e-marketing with the effect of culture, participants were offered a gift certificate as a reward for taking part. This study offers useful guidelines for hotel industry in hospitality sector that shed light on the e-loyalty formation process of anticipations on the part of potential consumers. This research shows that the methods through which customers establish E-loyalty to hotels in physical and virtual settings are same. The results showed that e-loyalty and e-marketing created e-trust (Shafiee, Haghighizade & Rahimzadeh, 2016) while culture of different regions/areas also affect the e-trust (Miao et. al., 2022). It seems that men, in comparison to women, are more attuned to the ways in which the design and features of a hotel's website affect their stay to increase client happiness with the website's services (Tzavlopoulos et. al., 2019) and the likelihood of repeat visits, which in turn increases customer loyalty. Current study also discuss all these circumstances but at one page which included e-loyalty, e-marketing, e-trust and culture simultaneously. We have translated all the questionnaires English into Chinese language for better understanding and to avoid inconvenience of respondents. Table 1 showing the descriptive statistics of demographic information of the respondents.

419 valid replies generated in total which are in suitable condition to use for this study. 25.5% (107) were female, while 74.5% (312) who were taking part in present study. 28.4% (119) were between the ages of 25-30 years, 43.2% (181) were between the age 31-36 years and 28.4% (119) of the respondents were over the age of 36. Higher-educated respondents dominated the sample, with 73% (306) having earned master degrees from an accredited university, 15% (65) are those who had doctorate degree.

Measurement

Cyr, D., Kindra, G. S., & Dash, S. (2008) provided the basis for the items used to assess the components in the conceptual framework. The offline fulfillment factor was also addressed by adding some more questions. E-loyalty was measured by adapting Oliver (1999); Pedersen and Nysveen (2004) and Hinson et al. (2016). E-trust was measured by using the five-point likert scale adapted from the study of Garbarino and Johnson (1999). E-Marketing was adapted by Davis (1989), El-Gohary (2010) and Phillips, Calantone and Lee (1994). Culture and gender measurement was adapted by House, R. J., Hanges, P. J., Javidan, M., Dorfman, P. W., & Gupta, V (2004). Five point Likert scale was used to measure all the measurement items ranging from 1 to 5 (strongly disagree to strongly agree). Researchers can improve the quality of their findings and the efficacy of their study by using a well-thought-out research design (Wiersma, 2009.

4. Results

The nature and strength of hypothesized correlations may be determined through quantitative research, making it the method of choice (de Vaus, 2001). Quantitative research designs, as stated by Chase, Teel, Thornton- Chase, and Manfredo (2016), provide reliable and valid findings, therefore current study also based on quantitative data. In this study, the measurement models were first evaluated using Smart PLS 4, built-in statistical tools, specifically the composite reliability (CR), average variance extracted (AVE), and Cronbach's alpha (CA) measures. The theoretical model was then tested for variance inflation factor (VIF), R2, and coefficient of determination (R2). The study concluded by using SEM to test the hypothesized connections.

Cronbach's alpha measures internal consistency on a standard scale from 0 to 1 (Table 2). A greater number of elements agree with each other. When the Cronbach's alpha for a series of questions is high, it means that the participants' responses were generally reliable (Brown, 2002). Table 2 showed the Cronbach's alpha of culture is 0.888 which indicated 88% response rate is reliable, E-marketing has 0.894 which indicated 89% and so on.

Table 3 indicated the Mediation Analysis Results. Preacher and Hayes (2004) rule, for the mediation H3 and H4 so that can measure the mediation assessment of culture in the relationship of E-loyalty/E-marketing and E-trust. Through bootstrapping, for E-trust and E-loyalty (β=0.072, P<0.01, t=2.297)) and E-marketing and E-loyalty (β=0.701, t=3.843, p<0.01) positive effect were found. Boot confidence interval (CI; for E-trust, lower limit (LL) =0.069, upper limit (UL) = 0.32; for E-marketing and E-trust LL=0.037, UL=0.67) are advised to avoid include a leading or trailing zero (see Table 3). Both of the proposed mediation hypotheses are supported by the data in this study. This shows a complementary total effect and indirect mediating role of Culture between E-loyalty & E-Trust, as well as E-marketing & E-Trust. Hence H3 and H4 for mediation hypothesis supported. All the other hypothesis H1, H2 and H5 shown in Table 5.

A series of confirmatory factor analyses (CFAs) were performed to check for uni-dimensionality and discriminatory validity of the suggested factors and indicators (Table 4). Each construct's factor loadings and composite reliabilities are provide (Table 4). All factor loadings are significantly higher than 0.5, demonstrating convergent validity as suggested by Hair et al. (2019). The levels of reliability achieved are far higher than those advocated by Nunnally (1978). PLS-SEM efficiently deal with smaller sample or normatively stated constructs (Becker, Ringle & Sarstedt 2018; Hair et al. 2019). According to Bagozzi and Yi 1988; Nunnally 1978) Table 4 showed the threshold of 0.70 for composite reliability standards was met. The AVE (average variance extracted) is >0.5, also analyzed the value of VIF which also met the criteria. In Structural equation results, it showed how E-loyalty and E-marketing created E-trust (Shafiee, Haghighizade & Rahimzadeh, 2016) while culture is also affected the E-trust. It is suggestive that where E-loyalty contain positive attitude (Li, Aham-Anyanwu, Tevrizci, & Luo, 2015), and have a significant impact in promoting E-trust, and developed positive relationship between customer and brand. According to Bagozzi and Yi (1988) and Hair et al. (2011) Composite reliability (CR) values 0.7 is sufficient or higher than 0.7 (Khan et al., 2017). Table 4 presented the composite reliability (CR) values at its range, which support the study findings. Researchers also suggested the proposed validity threshold at least 0.50 which should be acceptable. (Table 4) shows that the AVE in this analysis varied from 0.612 to 0.698, which supported the current study.

Table 4. Confirmatory factor Analysis (CFA).

Variables	Items	Loadings	Cronbach's alpha	Composite reliability	Average Variance Extracted (AVE)	Composite reliability (rho_a)	Variance Inflation Factor (VIF)
E-Loyalty			0.89	0.891	0.645	0.891
	EL 1	0.792					2.042
	EL 2	0.746					1.93
	EL 3	0.863					2.317
	EL 4	0.719					1.927
	EL 5	0.792					2.204
	EL 6	0.774					2.041
E-Marketing			0.894	0.895	0.612	0.895
	EM 1	0.839					2.166
	EM 2	0.794					1.863
	EM 3	0.860					2.098
	EM 4	0.837					2.02
	EM 5	0.812					2.008
	EM 6	0.773					1.915
	EM 7	0.701					1.747
Culture			0.888	0.888	0.64	0.888
	CUL 1	0.698					1.927
	CUL 2	0.782					2.17
	CUL 3	0.733					1.957
	CUL 4	0.798					2.085
	CUL 5	0.742					1.947
	CUL 6	0.778					2.079
E-Trust			0.892	0.892	0.698	0.892
	ET 1	0.702					2.042
	ET 2	0.783					2.447
	ET 3	0.711					2.143
	ET 4	0.711					2.226
	ET 5	0.716					2.249

Table 4. Confirmatory factor Analysis (CFA).

Variables	Items	Loadings	Cronbach's alpha	Composite reliability	Average Variance Extracted (AVE)	Composite reliability (rho_a)	Variance Inflation Factor (VIF)
E-Loyalty			0.89	0.891	0.645	0.891
	EL 1	0.792					2.042
	EL 2	0.746					1.93
	EL 3	0.863					2.317
	EL 4	0.719					1.927
	EL 5	0.792					2.204
	EL 6	0.774					2.041
E-Marketing			0.894	0.895	0.612	0.895
	EM 1	0.839					2.166
	EM 2	0.794					1.863
	EM 3	0.860					2.098
	EM 4	0.837					2.02
	EM 5	0.812					2.008
	EM 6	0.773					1.915
	EM 7	0.701					1.747
Culture			0.888	0.888	0.64	0.888
	CUL 1	0.698					1.927
	CUL 2	0.782					2.17
	CUL 3	0.733					1.957
	CUL 4	0.798					2.085
	CUL 5	0.742					1.947
	CUL 6	0.778					2.079
E-Trust			0.892	0.892	0.698	0.892
	ET 1	0.702					2.042
	ET 2	0.783					2.447
	ET 3	0.711					2.143
	ET 4	0.711					2.226
	ET 5	0.716					2.249

Table 5. Hypothesis construct.

Hypothesis	Relationship	β	t-value	p-value	Decision
H1	EL->ET	0.286	2.369	0.000	Supported
H2	EM->ET	0.722	4.697	0.000	Supported
H3	EL->CL->ET	0.272	2.297	0.000	Supported
H4	EM->CL->ET	0.701	3.843	0.000	Supported
H5	CL->ET	0.193	4.603	0.000	Supported

Note: **p-value <0.1, EL: E-Loyalty; ET: E-trust; EM: E-marketing; CL: Culture;.

Table 5. Hypothesis construct.

Hypothesis	Relationship	β	t-value	p-value	Decision
H1	EL->ET	0.286	2.369	0.000	Supported
H2	EM->ET	0.722	4.697	0.000	Supported
H3	EL->CL->ET	0.272	2.297	0.000	Supported
H4	EM->CL->ET	0.701	3.843	0.000	Supported
H5	CL->ET	0.193	4.603	0.000	Supported

Note: **p-value <0.1, EL: E-Loyalty; ET: E-trust; EM: E-marketing; CL: Culture;.

For H1 (β=0.286, t=2.369, p<0.01), proved that E-Loyalty has positive effect on E-trust (shown in Table 5) if customer is prefer to purchase again and again same online services which showing his/her e-loyalty (Valvi & Fragkos, 2012; Audrain-Pontevia, N’Goala & Poncin, 2013) which further build e-trust. H2 (β=0.722, t=4.697, p<0.01) e-trust is also built by e-marketing (Yousaf et. al., 2018; Rahimnia & Hassanzadeh, 2013). If any brand market their brands with best marketing strategies the consumer definitely impressed by those marketing tactics. For H5 (β=0.193, t=4.603, p<0.01) shows the Culture affected E-trust, consumer trust level affect as per the trends (Culture) revealing in that particular society (Akour et. al., 2022; Posey et. al., 2010; Bansal & Gefen, 2010). Culture as a mediator also play vital role in relation with E-loyalty and E-trust/E-marketing and E-trust. It suggests that while E-loyalty directly impact culture, they do not activate efficiently in E-trust but at the same time culture change the mind set of customers to trust a brand. As per the additional contribution, this study is conducted in hotel Industry of China through online survey.

5. Discussion

The current study has some real-world consequences because it was conducted in the hospitality sector (Hotel Industry) including different hotels located in different cities of China, which is widely recognized as one of the world's most important economic sectors (Jauhari & Sanjeev, 2012) and has practical implications. The hotel industry is among the world's most dynamic and rapidly expanding markets (De Grosbois, 2012) and becomes largest industry in future (Gu, Ryan & Yu, 2012). Customer are more concern about the goods and services which they have seen online and compare them physically (Smith & Brynjolfsson, 2001; Butler & Peppard, 1998) it also happened in current study when asked from consumer about their experience for hotel industry, they are more concern about services they are showing on their websites or web pages (Zhou, Lu, & Wang, 2009). In this study customers are also concerned about their cultural trends. For example, in some areas digital marketing does not work as good rather than other areas. Customer mind set is dependent on the particular area where he/she is living (Keller, 2013; Gupta & Govindarajan, 2002; Saaksjarvi & Pol, 2007).

They follow the norm and trends of that particular areas/countries so they prefer to make decision on their cultural trends and norms (Forssbaeck & Oxelheim, 2014; Arraras et. al., 2013; Gabriel & Lang, 2006) hence, the current study also target the main concern which is cultural trends. This is proved by the findings as per the Figure 2 and Table 5.

Table 5 stated all the proposed hypothesis results. All the hypothesis supported as per the obtained results. H1 concluded that both E-loyalty and E-trust has positive relationship which is proved by the stated results. E-loyalty and E-trust interrelated with each other (Ghane, Fathian & Gholamian, 2011) this study also showed their interrelation by values (β=0.286, t=2.369, p < .001), which showed the 28% (0.286) positive significant effect is generated by e-loyalty towards e-trust. Figure 2 also presented all numeric values to show the positive and significant values. Hence, proved that if a customer purchased repeatedly the same goods or services then e-trust is created. H2 explained that also has positive relationship between E-Marketing and E-trust which shows higher significant positive relationship which is 0.722. Table 5 showing the values (β=0.722, t=4.697, p < .001) positive significant effect is generated by e-Marketing and e-trust. Figure 2 also justified the presented values to show the significance of the results. Therefore, it is proved that if design e-marketing strategies in an appropriate way then customer attracted more and which directly help to build e-trust. In the Figure 2 and Table 5 showed 72% (β =0.722) impact is created by the e-marketing techniques which was practically significant for any business. H3 supported by the mediation results which shown in Table 3/Table 5 for E-Loyalty to E-trust (H3: β=0.272, t=2.297, p < .001), results showed that 27% mediation will be supported when culture mediated the relationship between e-loyalty to e-trust. Findings also showed that if a customer purchased repeatedly the same goods or services then e-trust is created but at the same time it is also affected by culture and trends prevailing in that region/country. For H4, E-marketing to E-trust relationship mediated by the cultural trends prevailing in that particular area. Values showed (H4: β=0.701, t=3.843, p < .001), culture mediated the relationship between E-marketing and E-trust which showed and proved by the analysis (see Table 3). E-marketing and e-trust has 70% mediation due to culture which support the H4. It also explained how culture affect the e-trust in a high and significant way. H5: Culture and E-trust direct effect which is (β=0.193, t=4.603, p < .001) which supported the hypothesis (see Table 5), culture effect the e-trust by 19%. Findings showed that 19% are those customers who were made decisions on the base of cultural trends revealing in that specific area. So the main focus of the current study is on Hospitality sector especial hotel industry which shows E-loyalty and E-marketing at its best. That's why it's so important for the marketing sector of an economy to foster an immersive setting by taking a marketing-minded view on the value of experiences. This research aimed to develop a theoretical framework for analyzing how cultural factors influence e-loyalty, e-marketing and e-trust. Managers in the field of marketing can, however, strengthen and facilitate e-trust through the implementation of systems of experiential marketing.

6. Conclusion

Therefore we proved that E-Loyalty and E-marketing significantly valuable by promoting the e-trust in customer. E-loyalty and E-marketing are the backbone of any brand, and become the cause to generate E-trust practices. Cultural trends also created hurdles while making trust in hotel industry. It is suggested that E-loyalty and E-marketing can support the businesses/brands to become stronger in getting customers’ e-trust to enhance the brand value and get fruitful outcomes. But there is a need to focus on cultural trends which not only effect the mindset of customer but also make this trend stronger in specific areas, which might affect the digital market in future.

7. Limitations and Future Directions

Although the present research boosting the results but still have notable limitations. First, data was collected virtually with different time lags and multiple sources. But results would be differed if it is conducted by cross sectional or experimental design. Secondly this research is conducted in Hospitality sector and targeted hotel industry of China but if choose any other sector and region then it could be changed. The future directions are recommended in several other categories such as banking, educational, high-tech, manufacturing industries and development sectors etc. as well as in other countries and culture to enhance the model abstraction. Thirdly, current study focused on E-loyalty, E-marketing, culture and E-trust, it is observed that if customer satisfaction and e-satisfaction which also affected by Culture. Lastly, other research design could be used for better recognition.