Abstract
Purpose
This study aims to examine the impact of website design, reliability and perceived ease of use as an engagement motivational factors on customer e-trust and e-retention in online shopping.
Design/methodology/approach
By using deductive approach, quantitative methods and purposive sampling technique, this study has collected the data from 295 young online customers to enhance an understanding of website design, reliability and perceived ease of use in an online shopping context.
Findings
The findings revealed interesting insights where reliability is the most significant predictor of customer e-trust in online shopping, followed by perceived ease of use and website design. In addition, a significant mediating effect of e-trust is found between customer e-retention, website design, reliability and perceived ease of use.
Research limitations/implications
Future research is recommended to predict the antecedents of online engagement motivational factors with value co-creation and co-creation experience in online shopping context.
Originality/value
This study offers fresh insights about driving elements and impediments of online customer retention. Customer engagement comprising of website design, reliability and perceived ease of use appear to influence the online customer retention through direct and indirect effect.
Keywords
Citation
Saoula, O., Shamim, A., Mohd Suki, N., Ahmad, M.J., Abid, M.F., Patwary, A.K. and Abbasi, A.Z. (2023), "Building e-trust and e-retention in online shopping: the role of website design, reliability and perceived ease of use", Spanish Journal of Marketing - ESIC, Vol. 27 No. 2, pp. 178-201. https://doi.org/10.1108/SJME-07-2022-0159
Publisher
:Emerald Publishing Limited
Copyright © 2023, Oussama Saoula, Amjad Shamim, Norazah Mohd Suki, Munawar Javed Ahmad, Muhammad Farrukh Abid, Ataul Karim Patwary and Amir Zaib Abbasi.
License
Published in Spanish Journal of Marketing - ESIC. Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode
1. Introduction
Recent marketing research has shown that focusing on customer engagement (CE) can result in enhanced market share, a competitive advantage, higher profits, increased consumer value and stronger customer relationships characterized by increased attachment, loyalty, trust, commitment and satisfaction (Ijaz et al., 2016; Kumar and Lata, 2021; Wagner et al., 2020). Customers who are actively involved in the company’s marketing process are more likely to make purchases and refer friends and family to the business by providing positive feedback on existing and proposed products and services (Pansari and Kumar, 2017).
CE plays an important role in online mediums of interaction (Japutra et al., 2022). These interactions are a result of both emotional and utilitarian drivers (Siddique et al., 2021). The recent debate in the CE literature advocates that positive interaction with customers on online platforms may lead to favorable outcomes for the service providers (Kang et al., 2021). These favorable outcomes may arise in the form of customer loyalty (Zaid and Patwayati, 2021), customer repurchase intention (Majeed et al., 2022) and customer e-retention (Arora et al., 2021). CE is relying on several factors which may include positive interaction with the website, creative and convenient website design, the reliability of the service provider and the convenience to use the website (Sukendia and Harianto, 2021). These factors are important to engage customers toward online purchases and posting positive reviews about the webstore (Busalim and Ghabban, 2021).
Moreover, one of the major concerns of e-commerce companies is customer e-retention. This is imperative because customer e-retention has a strong influence on the company’s profitability (Giao et al., 2020; Javed et al., 2018). As argued by Ali et al. (2010), the cost of acquiring a new customer is seven times greater than that of maintaining an old one. Purani et al. (2019) also agreed that customer acquisition for online shops is more challenging than for traditional outlets. Furthermore, scholarly thoughts on the concept of e-retention argue that it varies from situation to situation. Some scholarly insights have defined the concept in terms of loyalty (Ahmad and Al-Hawari, 2014, Al-Hawari, 2015, in Al-hawari and Mouakket, 2010), whereas others have associated it with the repurchase intentions of the customers (Zhou et al., 2009; Wen et al., 2011).
In addition, many of the extant studies recognize CE by integrating other factors to determine customer retention in the online retail market. Most studies focused on consumer value creation (Vakulenko et al., 2018; Wijaya et al., 2020), e-commerce strategy (Sambhanthan and Good, 2016; Tang and Yang, 2020) and website quality (Giao et al., 2020; Ramadhanti and Slamet, 2020). Though CE has been widely discussed in the literature through different factors yet, the integrative formulation of website design, its reliability and ease of use as a predictor of developing CE with online webstores has not yet been studied. We integrate these variables due to the following reasons.
First, as reported by Chung et al. (2018), to determine the nature of CE with websites, it is necessary to consider website design as a significant strategic customer touchpoint through which retailers can sell items and engage customers. Second, according to Lăzăroiu et al. (2020), customers are motivated to interact with a company’s website when they believe the website to be a reliable resource for locating and assessing products, as well as for submitting and reading evaluations of those products and services. As perceived reliability encourages customers to submit their online reviews on a social platform, Ventre and Kolbe (2020) further bolster the case by pointing out that this opinion favorably affects the level of trust that other buyers have in their purchase decision. Third, perceived ease of use has been identified as the most crucial and vitally studied variable in the context of online buying, according to a large body of research. Due to the shopping website’s user-friendliness, customers find it simple to navigate and choose their items. However, websites that make it difficult for users to find and buy what they are looking for tend to see fewer visitors and fewer sales.
Furthermore, the role of e-trust as a mediator to predict the nexus between the abovementioned factors and customer e-retention further extends the line of discussion in the online engagement and e-retention prospect. Those customers who are more engaged with the webstore because of its convenience, reliability and creative design may likely develop a strong level of trust with the e-service provider (Tran and Vu, 2019). These online actions may likely develop an influential relationship of the customers with the webstores, service brands and online organizations. This relationship which is an outcome of different emotional and utilitarian factors helps the e-service providers in e-customer retention. Customer retention and developing the loyalty of customers are the most challenging aspects of online shopping due to the presence of many competitors (Choi, 2020). However, the researchers did not concentrate on incorporating an integrated view of these success factors in online retail into a systematic research model. Thus, further empirical research on these aspects is necessary.
The present study has taken in point the case of loyalty which emerges from the trust provided by the online service provider which will gauge the customer repurchase intention (e-retention) in an online shopping context. Thus, defining the concept of e-retention as the extent to which customers indicate certain behaviors over and over to online shopping in specific situations through cognitive disposition and positive attitude. Hence, this study will treat e-retention in the context of online repurchase intentions.
Addressing these gaps, this study aims to examine the impact of website design, reliability and perceived ease of use as an engagement motivational factor on customer e-trust and e-retention in online shopping. E-commerce companies must identify the ways of retaining customers on a long-term basis, as this leads to more profits and revenues (Lee et al., 2009). This has been further buttressed by Lee et al. (2009) who stated that customers who are satisfied with a website’s services not only repurchase from the same website but also become loyal. Thus, the concept of customer loyalty is important for retaining customers (Auf et al., 2018; Rodríguez et al., 2020). The customers who trust service providers are also the retained customers most of the time (Soyeun et al., 2020) of the customers.
Theoretically, the present study is extending the line of discussion in the following ways. First, the present study has empirically investigated the important roles of website design, reliability and perceived ease of use as underlying factors of online CE which not only helps in developing strong customer e-trust during online shopping, but it will channelize in retaining existing customers. Second, we have empirically investigated the mediating role of e-trust between factors of CE and customer e-retention. Third, this study has provided practical insights for the practitioners to enable e-trust which is a response to online CE motivational factors that proved to be a prominent factor in enhancing e-retention among consumers.
2. Literature review
2.1 Theoretical background and concept development
Uses and gratification (U&G) theory forms the well-rooted explanation for the motivations customers develop to use media-enabled channels (Maslowska et al., 2016). These motivations include both emotional and utilitarian factors, i.e. online information, hedonic entertainment, online social interaction and personal identity (Maslowska et al., 2016). The literature (Malthouse and Peck, 2011) further elaborates on developing different ways of engagement using U&G theory. CE is relying on different motivational factors consumers are seeking before interacting with online webstores (Busalim et al., 2019). The massive usage of online e-commerce platforms, mobile marketing and social media marketing has made it compulsory for e-commerce webstore service providers to understand the motivational factors for interacting and engaging online customers (Busalim and Ghabban, 2021). A similar study (Larivière et al., 2013) has extended the U&G theoretical axioms by adding convenience and monetary motivation in the context of mobile marketing. Furthermore, Muntinga et al. (2011) added remuneration and empowerment to extend the theoretical discussion on U&G theory. The present study has further added website design (creativity), reliability of the webstore/service provider and its perceived ease of using the website as the underlying dimensions of CE which will help the service providers for better and positive interaction with their customers.
CE is defined as “the establishment of a deeper, more meaningful bond between the organization and the customer” (Khan et al., 2016). Respectively, CE is also relying on self-efficacy (Maslowska et al., 2016). For instance, consumers use online platforms as a medium of purchasing and interacting with different services offered at the webstore (Shamim et al., 2021). Therefore, the risk of minimum challenge a consumer is expecting from the online webstore shall exhibit more engagement behavior as compared to those having less self-efficacy and more risk associated with the online webstores. Thus, the fit between the regulatory orientation and the goal accomplishment (purchase/repurchase intention) are important as it will enhance the online engagement ties between the service provider and its customers.
Therefore, the present study extends the line of discussion by investigating the mitigating factors of CE which will enhance the e-trust with the webstore. The firm level of trust will contribute to developing a long-term e-retention with their customers. Furthermore, the mediating role of trust is important because despite having reliability, convenience and attractive design, customers shall only carry forward their relationship with the service provider if they are having a strong level of trust in the e-service provider. Table 1 explains the recent insights from the literature on technology adoption, technology innovation and CE.
2.2 Hypotheses development
2.2.1 Website design, customer e-trust and customer e-retention.
Website design refers to the process of creating websites incorporating the aspects of Web page layout, content production and graphic design (Zhou et al., 2009) which helps in developing positive interaction with the webstore. These multiple interactions help online firms to develop a strong level of trust among the customers. The quality of website design is a crucial factor in enhancing customer trust and retention in e-commerce (Basha et al., 2020; Cho and Park, 2001). Research works by Giao et al. (2020) and Jiyoung et al. (2009) argued that website design significantly affects customer loyalty, trust, satisfaction and quality assessment of website retailers. In a similar vein, purchase intention is positively impacted by website design (Wardhani, 2020).
Customer e-retention refers to the customer’s intention to purchase products or services from the same online channel/store again (ThakreemBanua, 2021). Customer retention in e-commerce is described as the customer’s willingness to buy a product from the same retailer through online channels (Wen et al., 2011). The willingness to purchase from the online platform is relying on different factors one of which is website design (Nam et al., 2021). The attractive and creative website design helps the customers to engage with the store positively. Customers nowadays look for more catchy and appealing website designs which helps them to explore more in terms of hedonic and utilitarian value outcomes (Chaouali and Souiden, 2022). Customer e-retention contributes to a firm’s profits by saving the cost of attracting new customers; further, long-term customers purchase more, spread positive word of mouth, take less time to make a purchase and are less sensitive to product prices (Capponi et al., 2020).
In addition to the findings of the previous research, (Chakraborty et al., 2022), it can be argued that there are a variety of subjective elements that contribute to website design quality that can have an impact on customer perceptions of the brand. Not only that but both Giao et al. (2020) and Albayrak et al. (2020) indicate that the information shown on a website may influence users’ levels of pleasure, which in turn can have substantial repurchases.
Based on the above discussion, the following hypotheses are proposed:
Website design positively influences customer e-retention in online shopping.
Website design has a positive effect on customer e-trust in online shopping.
2.2.2 Reliability, customer e-trust and customer e-retention.
Reliability is described as the provision of the promised service/product in the given time frame with exact details displayed on the website, and as per customer expectations (Kim and Lee, 2002). Companies are trying to build e-trust and customer e-retention by providing reliable services (Zhu et al., 2002). These reliable services are in other words developing positive CE with the webstores. Furthermore, calling and emailing customers are effective methods to reduce the uncertainty among customers regarding online shopping (Madad et al., 2017). These methods are catered to develop positive engagement ties with the customers which results in developing a high level of trust among the customers. The reliability of a product or service is associated with the aspect of trust derived from accurate delivery and fulfilment of the terms and conditions of purchase (Alkhateeb, 2020; Wen et al., 2011).
Furthermore, Ratnawati and Lestari (2018) claimed that a high degree of reliability in terms of favorable brand image would increase the likelihood of the choice of a brand for their consumer trust in the brand, hence, generating greater customer loyalty and decreasing market competition. Multiple studies, like those by Marliawati and Cahyaningdyah (2020) and Adiwidjaja (2017), corroborate this assertion by demonstrating the favorable impact of a positive brand image on customer loyalty. Indeed, trust is a major element that concerns customers during online shopping (Basha et al., 2020; Kim and Lee, 2002). Thus, it is postulated that:
Reliability positively influences customer e-retention in online shopping.
Reliability has a positive effect on customer e-trust in online shopping.
2.2.3 Perceived ease of use, customer e-trust and customer e-retention.
PEOU is the extent to which a customer finds a website and its interface easy to access and use (Moslehpour et al., 2018). Past scholars have reported that perceived ease of use is considered as a crucial element for retaining customers (Vatolkina et al., 2020; Wen et al., 2011; Flavián et al., 2006). Online shopping and visits to a website are increased if customers find the website easy to use (Koufaris, 2002). In addition, perceived ease of use has a positive impact on repurchasing (Alkhateeb, 2020; Basha et al., 2020). Customers’ perceived ease of shopping on a Web-based store can increase their e-trust and e-retention concerning future purchase transactions (Escobar-Rodriguez and Monge-Lozano, 2012; Silitonga et al., 2020). Customers avoid using a technology-enabled platform that is difficult to comprehend. Instead, they will look for alternatives that provide the same activities but are easier to learn (Wilson et al., 2021).
Recent studies, for instance, Daud et al. (2018) and Balci (2021), discovered that perceived ease of use and perceived usefulness both had a substantial influence on influencing customers’ repurchase intentions via trust within the e-commerce industry. Furthermore, Maryanto and Kaihatu (2021) discovered that perceived usefulness and perceived ease-of-use both positively and significantly increase consumer loyalty through trust. Similarly, Mulyaningsih (2022) noted that perceived ease-of-use and usefulness strongly influenced customers’ levels of trust in a system or technology, which in turn influenced and impacted the creation of loyalty in the consumers’ perceptions.
Therefore, it is hypothesized that:
Perceived ease of use positively influences customer e-retention in online shopping.
Perceived ease of use has a positive effect on customer e-trust in online shopping.
2.2.4 Mediating role of e-trust.
Trust refers to the expectation of one party concerning the motives of the other party (Casalo et al., 2008). E-trust among customers is a crucial part of e-commerce transactions (Raman, 2020). Past studies have found that trust plays a mediating role while measuring purchase intention (Dang et al., 2020; Irshad et al., 2020). Likewise, Pavlou and Chai (2002) and Rauyruen and Miller (2007) noted the significant role of trust as a mediator in determining customer repurchase intention, which in turn enhances customer satisfaction. E-trust positively influences consumer behavior as consumers will not engage in e-commerce transactions if they do not trust the store (Marriott et al., 2017; Shilpa and Rathi, 2020; Silitonga et al., 2020).
In recent studies, for instance, Boateng (2018) and Nguyen and Khoa (2019), trust has a more substantial impact on influencing consumer loyalty than satisfaction does. These results were supported by different studies (Al-Adwan et al., 2020; Aslam et al., 2020), who found that trust had a favorable effect on consumer loyalty. Researchers Bulut and Karabulut (2018), Riquelme et al. (2019) and (Wilis and Nurwulandari, 2020) all came to the same conclusion: trust increases consumer loyalty. As with the concept of satisfaction, the connection between trust and loyalty has become one of the most talked-about and popular topics in market research. This is because it will always be interesting to fully understand how consumers’ trust in a company could eventually affect their loyalty to that company which can be achieved by the customer retention.
Given this understanding, the following hypotheses are posited:
E-trust positively influences customer e-retention in online shopping.
E-trust mediates the relationship between website design and customer e-retention in online shopping.
E-trust mediates the relationship between reliability and customer e-retention in online shopping.
E-trust mediates the relationship between perceived ease of use and customer e-retention in online shopping.
Based on the aforesaid literature, the proposed research framework is illustrated in Figure 1.
3. Methodology
3.1 Study design
The study design was based on positivist research philosophy. The nature of the study was cross-sectional as the data was collected at one point in time and from multiple respondents. The research approach was deductive. Data was collected from public higher education institutions in Malaysia. The higher learning institutions were selected because of the maximum likelihood of the chance for respondents to meet the study criteria. Furthermore, we have designed an exclusion criterion where only those respondents who have been involved in online shopping will be asked for the data collection. We have designed an initial question that we further standardized as only those respondents who have been involved in online shopping behavior were asked to fill out the questionnaire. We have used a purposive sampling technique to extract the potential sample from the pool of the population.
3.2 Sampling procedures
As part of quantitative research, a self-administered questionnaire was provided to 300 young e-shoppers, who were selected via the purposive sampling technique. The participants were the students of a public higher learning institution in northern Malaysia who are frequent customers of online stores. Each questionnaire was directly handed to the participating consumers in a sealed envelope with a pencil. To reduce participation referrals, the researchers explained the study’s purpose and the survey were only distributed to those who showed a willingness to participate and spend a minimum of 10–15 min to complete it. Direct distribution of questionnaires minimizes bias and confirms the anonymity and confidentiality of the respondents.
A total of 295 responses were completed and used for data analysis. This sample size was considered adequate based on Hair et al.’s (2014) suggestion that a tolerable sample size should be more than 100 cases. As shown in Table 2, 46% of the respondents were female and 54% were male; 52.88% of them were local students and 47.12% were international students, while most of the participants were pursuing their bachelor’s degrees. Sixty-five percent of respondents had shopped online from six to ten times while 70% of the e-shoppers were internet users for the past five years.
3.3 Questionnaire development
A two-section questionnaire was prepared, encompassing the demographic characteristics of the respondents and perceptions of online customers. Section A collected information on the participants’ gender, nationality, education, online shopping experience and internet usage experience. Section B recorded the perceptions of online customers regarding e-trust, website design, reliability, perceived ease of use and customer e-retention. The construct of website design was evaluated using the four items adapted from Zhou et al. (2009), and reliability was measured using the four items developed by Kim and Lee (2002). Four items were adapted from Escobar-Rodriguez and Monge-Lozano (2012) to measure the perceived ease of use, whereas e-trust was tested using the five items developed by Gefen et al. (2003). Finally, customer e-retention was examined using the three items adapted from Wen et al. (2011).
4. Data analysis
4.1 Partial least square structural equation modeling
The partial least square structural equation modeling (PLS-SEM) approach was performed via a two-stage assessment:
the measurement model; and
the structural model.
The first was performed to conduct a psychometric analysis of the construct measures in terms of their validity and reliability, whereas the latter was executed to check the strength of the hypothesized relationships.
4.2 Outliers and common method bias
First, multivariate outliers with a significance level of more than 0.001 were identified and deleted as Lynch (2013) recommended. Given the single source of the data, both procedural and statistical remedies were applied to avoid potential common method variance (Podsakoff et al., 2012). The variables’ measurements were placed randomly (Podsakoff et al., 2012). Furthermore, a shorter version of the behavioral intention measurement ensured no overlapping between constructs (e.g. Patwary et al., 2022). Harman’s single-factor test was also applied, indicating that a single factor explained only 16.54% of the total variance of 63.23%. Because this value was less than 50%, it can be established that the data did not have a common method variance (Podsakoff and Organ, 1986).
4.3 Measurement model assessment
In the measurement model, reliability, convergent validity and discriminatory validity of the constructs were assessed. Cronbach’s alpha and composite reliability (CR) were used to evaluate the internal consistency reliability. As shown in Table 3 that is explaining the measurement model, the values for both measures exceeded the threshold value of 0.70, inferring adequate reliability (Hair et al., 2018). Meanwhile, convergent validity was measured to determine whether the loadings of measuring items were above 0.60, and the average variance extracted (AVE) value surpassed 0.50. In the present study, both requirements were met (i.e. item loadings range between 0.736 and 0.880 and AVE ranges between 0.557 and 0.757). Thus, these results confirmed the convergent validity of the construct measures used (Bagozzi and Yi, 1988; Hair et al., 2018).
Discriminant validity was evaluated by verifying whether the square root of AVE was higher than the interconstruct correlation coefficients and whether the heterotrait–monotrait (HTMT) ratios were less than 0.85, as suggested by Henseler et al. (2015). Table 4 reports that the correlation coefficients varied between 0.282 and 0.843, and the square root of the AVE exceeded these (Fornell and Larcker, 1981). These results establish discriminant validity.
4.4 Structural model assessment
The structural model was assessed by calculating the coefficient of determination (R2) and the path coefficients via a bootstrapping procedure of 5,000 resamples. Table 5 and Figure 2 show that website design had an insignificant impact on customer e-retention in online shopping (β1 = 0.004, t-value = 0.102, p > 0.05); hence, H1a was not supported. Besides, website design had a noteworthy relationship with e-trust in online shopping (β2 = 0.093, t-value = 2.045, p < 0.05), signifying that H1b was supported.
In addition, reliability positively impacted customer e-retention in online shopping (β3 = 0.265, t-value = 5.761, p < 0.05), thereby supporting H2a. Likewise, reliability also positively influenced customer e-trust in online shopping (β4 = 0.402, t-value = 7.262, p < 0.05), which indicates that H2b was accepted. Further inspection of the linkages between perceived ease of use and customer e-retention in online shopping produced significant results whereby β5 = 0.326, with t-value = 5.771 at p < 0.05. Therefore, H3a was supported. Likewise, perceived ease of use also had a positive association with online trust (β6 = 0.384, t-value = 6.846, p < 0.05), supporting H3b as expected. Moreover, H4, which posited that e-trust positively influences customer e-retention in online shopping was also supported (β7 = 0. 348, t-value = 6.599, p < 0.05).
The R2 of the present study was tolerable (i.e. e-trust = 0.532 and e-retention = 0.664) as it exceeded 0.10, a threshold set by Falk and Miller (1992) and Hair et al. (2010). Besides, the results of Stone–Geisser’s (Q2) value by using a blindfolding procedure for e-trust (Q2 = 0.363) and e-retention (Q2 = 0.501) were above 0, signifying that the current research model is satisfactory and has a high predictive relevance (Hair et al., 2014).
4.5 Mediating effect of e-trust
The path analysis of the indirect effects of website design, reliability and perceived ease of use on customer e-retention in online shopping that are mediated through e-trust is presented in Table 6. The analysis was performed using a bootstrapping method in the PLS-SEM approach. Contrary to the expectations, the indirect effect of website design on customer e-retention through e-trust in online shopping was insignificant (p > 0.05). Thus, it can be conjectured that e-trust does not mediate the association between website design and customer e-retention. Hence, H5a was not supported as website design has neither a direct nor an indirect effect on customer e-retention in online shopping through e-trust. Table 6 presents the mediation results.
An examination of the indirect effect of reliability on customer e-retention through e-trust in online shopping yielded a significant relationship (p < 0.05). Therefore, it can be deduced that e-trust mediates the association between reliability and customer e-retention in online shopping. Consequently, H5b was supported. To be specific, reliability has direct significant effects on e-retention, and when the association between them is mediated through e-trust, the indirect effect is also significant, resulting in a full mediation.
Next, H5c was tested to inspect whether e-trust mediates the association between perceived ease of use and customer e-retention while shopping online. The indirect effect of perceived ease of use on customer e-retention through e-trust was significant. Thus, it can be concluded that e-trust mediates the association between perceived ease of use and customer e-retention. Thus, H10 was supported. The direct association between perceived ease of use and e-retention is significant, and when it is mediated through e-trust, the indirect effect is also significant, resulting in a full mediation.
5. Discussion, implications and agenda for future research
5.1 Discussion of findings
The discussion is as follows: first, the findings revealed that website design does not have a noteworthy relationship with customer e-retention in an e-commerce setting. The results explain that e-retention is based on the level of trust which is gauged by the engagement ties with the webstores. The regulatory engagement theory which advocates that the strength of engagement increases when an individual overcomes certain challenges are in line with the findings of this study. Customers first engage with the webstore through multiple interactions (Shamim et al., 2021). These interactions will develop trust with the service provider which will in the next stage enhance the chances of customer retention (Kumar et al., 2021). The findings of the study reveal significant insights where website design positively develops e-trust among the customers and enhances the chances of customer e-retention in the online shopping context. Hence, the findings do not support H3a but support H2a. The result signifies those customers highly acknowledge the online shopping websites’ navigability and how they can contact or communicate with them. These results support the findings of prior studies that having an attractive web design enhances e-trust and increases e-retention among customers (Fimberg and Sousa, 2020; Masele and Matama, 2020; McKnight et al., 2002; Rahimnia and Hassanzadeh, 2013).
Second, reliability uncovered positive and significant influence on e-trust and e-retention of customers in online shopping. This indicated that error-free transactions, as well as adequate security assurance, increase the reliability of online stores which enhances the positive engagement ties (Vásquez, 2020), as online customers see low risks in terms of delivery, payment, information breaches, etc. with online retailers compared to traditional retailers. Online customers may, therefore, tend to deal with online retailers, whom they perceive as reliable. Thus, H1a and H4 were reinforced as expected. These results are consistent with the results of previous studies, which also found that positive perceptions of customers regarding the reliability of the online seller led to online retention (Basha et al., 2020; Jiyoung et al., 2009).
Third, the findings have provided a significant relationship between perceived ease of use and e-retention in online shopping. Convenience is another motivation for the customers as advocated by U&G theory which engages the customers positively to stay with the webstore for a long time (Hicks et al., 2012; Huang and Zhou, 2018). This long-term engagement tie is again based on the level of trust with the service provider which is accessed by spending time with the webstore through multiple interactions (Li et al., 2020). Hence, H3b was supported. Likewise, H2b, which posits that this factor affects customer e-trust in online shopping, is also supported. The possible reason for this could be that interacting with online stores is frequently pleasurable and does not involve much mental effort. Customers do not need to consult the user manual often when shopping at an online store. This ease of online shopping contributes to the enhancement of customers’ e-retention and e-trust. The results echo the findings of past studies that perceived ease of use is a significant contributor to customer e-trust and e-retention in online shopping (Basha et al., 2020; Jiyoung et al., 2009; Vatolkina et al., 2020).
Fourth, our findings support H1b are in line with the previous studies (Shilpa and Rathi, 2020; Silitonga et al., 2020). Customers feel that their transactions with the website and online stores are safe and that the platforms are trustworthy and protect their privacy. They also believe that online stores would provide them with good services.
Finally, the mediation effect of e-trust on the relationship of website design, reliability and perceived ease of use with customer e-retention in online shopping is further explored in H5c, H5b and H5a, respectively. H5c, which states that e-trust mediates the association between website design and customer e-retention in online shopping, was not supported. A possible explanation for this insignificant result could be that, although the website’s design influences customer e-trust, it is not considered a vital factor in influencing customer e-retention in online shopping, particularly in the Malaysian setting.
For H5b, findings have revealed that e-trust mediates the association between reliability and customer e-retention in online shopping. The possible rationale for this significant result could be that the reliability of the products or services in online stores is associated with the aspect of trust derived from the accurate delivery and fulfillment of the terms and conditions related to a purchase (Hsu et al., 2017), and trust is a major element that customers are concerned with during online shopping (Alkhateeb, 2020; Basha et al., 2020). Therefore, online retailers continuously try to build customer e-trust and e-retention by providing reliable online shopping services. Likewise, the findings infer that e-trust significantly played a role in mediating the relationship between perceived ease of use and customer e-retention, thereby supporting H5a. The possible reason behind this could be that when customers find online shopping easy, their trust increases, making them more likely to engage in repeat purchases at the store and eventually resulting in increased e-retention (Silitonga et al., 2020).
5.2 Theoretical implications
Theoretically, this study contributes to the body of knowledge in the following ways. First, we have conceptualized the website design, reliability and perceived ease of use as an engagement motivational factor. CE primarily is relying on different motivational factors consumers are seeking before interacting with online webstores (Busalim et al., 2019). The positive integration of these antecedents significantly engages the customers with the webstores. We argue that reliability and perceived ease of use are most important for CE with the webstores. Second, we argued that positive engagement with the webstores significantly develops an e-trust among the customers which will help to capture customers’ e-retention in an online context. This study has conceptualized e-trust and e-retention as engagement outcomes. Therefore, we delineate an understanding of engagement outcomes that resides in e-trust and e-retention. The case in this point entails that the convenient, reliable and attractive design of the website eliminates several challenges customers encounter while interacting with the online services at the webstore. These challenges eliminate the risk of shifting from the webstore. The long-term interaction with the webstore/service provider develops a certain level of trust among the customers which will help the service providers to retain their customers for a long time (Rana et al., 2021). Finally, we have explored the role of e-trust as a mediator between consumer engagement and e-retention characteristics. Customers’ e-trust plays an eminent role to build a strong relationship between the webstores and online customers. This study has proposed that e-trust is one of the important contributors that mediates a relationship of engagement motivational factors and engagement motivational outcomes. Customers despite having an attractive webstore and ease of operating a webstore will avoid to shop if there is less or no element of trust between two parties.
5.3 Practical implications
This study has provided several implications which are as follows. First, based on the empirical insights we advise the online shoppers to enhance the website reliability and incorporate attractive and unique features with ease of usability. Customers are most attracted to the webstore which is providing these three features. These features will help the online webstore managers to create a high level of motivation among the customers to engage with the webstore. Second, we have proposed that e-trust is an important mediator that allows the managers to enhance customer e-retention with the webstore. Trust is an important foundation for developing a strong relationship between firms and customers (Abid et al., 2023). Customers’ level of trust in the webstore is a significant predictor of persons’ expectations in monetary exchanges. Credibility and reliability in honoring legal and informal responsibilities may increase customer loyalty. The results suggest that e-commerce sites may use the perception of reliability to their advantage. We advise company heads to increase customer trust by capitalizing on existing connections to prove credibility. Consumers will have a positive impression of the seller’s reliability if their expectations are met. Companies operating in the digital era need to consider the benefits their customers receive against the costs of providing such products/services.
5.4 Limitations and future recommendation
The limitations and future research directions are as follows. Because the study has used the self-rated survey questionnaire for data collection, which affirms that there may be some sort of response bias among respondents even though the required tests are also performed to identify the such issue. Second, it is suggested that future studies must consider the different data collection approaches such as they can use supervisor and employee ratings, or they can have interviews for data collection. Third, future research studies should consider the role of customers’ self-construal and value co-creation to enhance value-in-experience in the online webstore engagement context (Shamim et al., 2023; Abid et al., 2022). Fourth, future research should investigate the CE, e-trust and e-retention using neuro devices such as EEG as a different analytical lens (Siddique et al., 2023). Besides, future research may consider other mediators such as customer e-security and e-satisfaction, which might provide a deeper understanding of online customer retention. Because website design revealed a significant positive effect on e-trust, future studies should evaluate the influence of different dimensions of website design including product display, color, text and background on online customer retention.
Figures
Valuable insights from the past literature
| Reference and methods | Key findings | Theoretical foundation |
|---|---|---|
| Amin et al. (2014); quantitative methods – structural equation modeling (SEM) – 302 valid responses | There is a positive relationship between PEOU, PU and mobile users’ satisfaction. PU is positively related to trust and mobile users’ satisfaction. Moreover, trust positively influences mobile users’ satisfaction | The technology acceptance model and trust theory |
| Castaneda et al. (2007) Quantitative method using structural equation modeling (SEM) |
The user’s experience of the website played a moderating role. For less experienced users, perceived ease of use was found to be a more important factor in deciding to revisit the website, whereas perceived usefulness had more effect on more experienced users | The technology acceptance model and trust theory |
| Ozturk et al. (2016) – Quantitative; SEM; 396 valid responses | Convenience, compatibility and perceived ease of use (PEOU) had a significant impact on the users’ loyalty intentions toward MHB technology. In addition, compatibility significantly influenced PEOU and convenience and PEOU had a significant impact on loyalty and convenience | The technology acceptance model |
| Mbama et al. (2018) – qualitative-thematic analysis | The attributes affecting DB experience are as follows: service quality, functional quality, perceived value, service customization, service speed, employee–customer engagement, brand trust, DB innovation, perceived usability and perceived risk. They affect customer experience, satisfaction and loyalty and financial performance | Digital marketing theory |
| Quantitative – structural equation modelling – 598 valid responses | Results reveal that the key website attributes, namely, website interactivity, website aesthetics, customization, ease of use and telepresence positively affect CE. The results also delineate positive associations between CE, customer trust and customer retention | The technology acceptance model (TAM) and the theory of planned behavior (TPB) |
| Islam et al. (2019) Field experiments – 295 valid responses |
The results showed website interactivity enhances customer perceptions of usefulness and ease of using retail websites | The technology acceptance model (TAM) |
| Molinillo et al. (2021) Quantitative-SEM |
The results showed that information and service quality are key antecedents of perceived value, whereas rewards and recognition and customization are nonsignificant | The technology acceptance model (TAM) and the theory of planned behavior (TPB) |
DB = Digital banking
Source: Authors’ own work based on the past literature cited in the table
Demographic characteristics of respondents
| Variable | Cases (%) |
|---|---|
| Gender | |
| Male | 135 (45.76) |
| Female | 160 (54.24) |
| Age | |
| 19–24 | 105 (35.59) |
| 25–34 | 135 (45.76) |
| 35–44 | 55 (18.6) |
| Education | |
| Bachelor’s degree | 127 (43.05) |
| Master’s degree | 121 (41.01) |
| PhD | 47 (15.94) |
| Nationality | |
| International | 139 (47.12) |
| Local | 156 (52.88) |
| Online shopping experience | |
| 1–2 times | 39 (13.22) |
| 3–5 times | 65 (22.03) |
| 6–10 times | 191 (64.75) |
| Internet usage experience | |
| 1–2 years | 30 (10.17) |
| 3–4 years | 58 (19.66) |
| 5–6 years | 122 (41.35) |
| 7–10 years | 85 (28.82) |
Construct reliability, Cronbach’s alpha, CR and AVE of latent variables
| Loadings | |
|---|---|
| Website design (WD) Adapted from Zhou et al. (2009) – α = 0.737, CR = 0.834, AVE = 0.557 | |
| Overall, online shopping websites work very well, technically | 0.736 |
| Visually, online shopping websites resemble other websites I think highly of | 0.758 |
| The online shopping websites are simple to navigate | 0.742 |
| The online shopping websites clearly show how I can contact or communicate with it | 0.748 |
| Reliability adapted from Kim and Lee (2002) – α = 0.873, CR = 0.913, AVE = 0.725 | |
| The online stores deliver on its undertaking to do certain things by a certain time | 0.848 |
| The online stores show a sincere interest in solving customer problems | 0.838 |
| Transactions with the online stores are error free | 0.855 |
| The online stores have adequate security | 0.863 |
| Perceived ease of use (PEU) Adapted from Escobar-Rodriguez and Monge-Lozano (2012) – α = 0.880, CR = 0.917, AVE = 0.735 | |
| I don’t make mistakes when using the online stores | 0.837 |
| Interacting with online stores is often pleasant | 0.879 |
| I do not need to consult the user manual often when using an online store | 0.858 |
| They are interacting with online stores, which does not require a lot of mental effort | 0.856 |
| Online trust (ET) adapted from Gefen et al. (2003) – α = 0.886, CR = 0.917, AVE = 0.688 | |
| I feel safe in my transactions with the website/online stores | 0.852 |
| I believe online stores can protect my privacy | 0.848 |
| I select online stores, which I believe are honest | 0.842 |
| I feel that online stores would provide me with good service | 0.859 |
| I feel that online stores are trustworthy | 0.740 |
| E-retention (ER) adopted from Wen et al. (2011) – α = 0.839, CR = 0.903, AVE = 0.757 | |
| I intend to continue using online shopping rather than discontinue its use | 0.884 |
| My intention is to continue using online shopping rather than use traditional shopping | 0.846 |
| If I could, I would like to continue shopping online as much as possible | 0.880 |
Discriminant validity (HTMT)
| Variables | 1 | 2 | 3 | 4 | 5 |
|---|---|---|---|---|---|
| (1) E-trust | |||||
| (2) E-retention | 0.843 | ||||
| (3) Perceived ease of use | 0.726 | 0.824 | |||
| (4) Reliability | 0.734 | 0.799 | 0.674 | ||
| (5) Website design | 0.350 | 0.318 | 0.337 | 0.282 |
Relationships with e-retention and e-trust
| Relationship | Beta | SE | t-values | Result | |
|---|---|---|---|---|---|
| H1a | Website design ---> E-retention | 0.004 | 0.036 | 0.102 | Not supported |
| H1b | Website design ---> E-trust | 0.093* | 0.045 | 2.045 | Supported |
| H2a | Reliability ---> E-retention | 0.265* | 0.046 | 5.761 | Supported |
| H2b | Reliability ---> E-trust | 0.402* | 0.055 | 7.262 | Supported |
| H3a | Perceived ease of use ---> E-retention | 0.326* | 0.057 | 5.771 | Supported |
| H3b | Perceived ease of use ---> E-trust | 0.384* | 0.056 | 6.846 | Supported |
| H4 | E-trust ---> E-retention | 0.348* | 0.053 | 6.599 | Supported |
*p < 0.05
Mediation results
| Relationship | Beta | S.E. | t-values | Result | |
|---|---|---|---|---|---|
| H5a | Website design ---> E-trust ---> E-retention | 0.032 | 0.018 | 1.810 | Not supported |
| H5b | Reliability ---> E-trust ---> E-retention | 0.140* | 0.029 | 4.779 | Supported |
| H5c | Perceived ease of use ---> E-trust ---> E-retention | 0.134* | 0.027 | 4.977 | Supported |
*p < 0.05
References
Abid, M.F., Shamim, A., Khan, Z. and Khan, I. (2022), “Value creation or value destruction: conceptualizing the experiential nature of value‐in‐use”, Journal of Consumer Behaviour, Vol. 21 No. 3, pp. 583-601.
Abid, M.F., Siddique, J., Gulzar, A., Shamim, A., Dar, I.B. and Zafar, A. (2023), “Integrating the commitment-trust theory to gauge customers loyalty in riding services”, Journal of Promotion Management, Vol. 29 No. 3, pp. 1-33.
Adiwidjaja, A.J. (2017), “Pengaruh brand image dan brand trust terhadap keputusan pembelian sepatu converse”, Agora, Vol. 5 No. 2, pp. 1-9.
Al-Adwan, A.S., Kokash, H., Adwan, A.A., Alhorani, A. and Yaseen, H. (2020), “Building customer loyalty in online shopping: the role of online trust, online satisfaction and electronic word of mouth”, International Journal of Electronic Marketing and Retailing, Vol. 11 No. 3, pp. 278-306.
Ahmad, A. and Al-Hawari, M. (2014), “Does customer sociability matter? Differences in e-quality, e-satisfaction, and e-loyalty between introvert and extravert online banking users”, Journal of Services Marketing, Vol. 28 No. 7, pp. 538-546.
Al-Hawari, M.A. (2015), “How the personality of retail bank customers interferes with the relationship between service quality and loyalty”, International Journal of Bank Marketing, Vol. 33 No. 1, pp. 41-57.
Al-hawari, M.A. and Mouakket, S. (2010), “The influence of technology acceptance model (TAM) factors on students’e-satisfaction and e-retention within the context of UAE e-learning”, Education, Business and Society: Contemporary Middle Eastern Issues, Vol. 3 No. 4, pp. 299-314.
Albayrak, T., Karasakal, S., Kocabulut, Ö. and Dursun, A. (2020), “Customer loyalty towards travel agency websites: the role of trust and hedonic value”, Journal of Quality Assurance in Hospitality and Tourism, Vol. 21 No. 1, pp. 50-77.
Ali, J.F., Ali, I., Ur Rehman, K., Yilmaz, A.K., Safwan, N. and Afzal, H. (2010), “Determinants of consumer retention in cellular industry of Pakistan”, African Journal of Business Management, Vol. 4 No. 12, pp. 2402-2408.
Alkhateeb, M.A. (2020), “Impact of e-services quality on e-loyalty in Paltel e-satisfaction as a mediating variable”, International Journal of Web Portals, Vol. 12 No. 2, pp. 81-101.
Amin, M., Rezaei, S. and Abolghasemi, M. (2014), “User satisfaction with mobile websites: the impact of perceived usefulness (PU), perceived ease of use (PEOU) and trust”, Nankai Business Review International.
Arghashi, V. and Yuksel, C.A. (2022), “Interactivity, inspiration, and perceived usefulness! How retailers’ AR-apps improve consumer engagement through flow”, Journal of Retailing and Consumer Services, Vol. 64, p. 102756.
Arora, L., Singh, P., Bhatt, V. and Sharma, B. (2021), “Understanding and managing customer engagement through social customer relationship management”, Journal of Decision Systems, Vol. 30 Nos 2/3, pp. 215-234.
Aslam, W., Hussain, A., Farhat, K. and Arif, I. (2020), “Underlying factors influencing consumers’ trust and loyalty in e-commerce”, Business Perspectives and Research, Vol. 8 No. 2, pp. 186-204.
Auf, M.A.A., Meddour, H., Saoula, O. and Majid, A.H.A. (2018), “Consumer buying behaviour: the roles of price, motivation, perceived culture importance, and religious orientation”, Journal of Business and Retail Management Research, Vol. 12 No. 4, pp. 186-195.
Bagozzi, R.P. and Yi, Y. (1988), “On the evaluation of structural equation models”, Journal of the Academy of Marketing Science, Vol. 16 No. 1, pp. 74-94.
Balci, G. (2021), “Digitalization in container shipping: do perception and satisfaction regarding digital products in a non-technology industry affect overall customer loyalty?”, Technological Forecasting and Social Change, Vol. 172, p. 121016.
Basha, A.M., Rajaiah, M., Penchalaiah, P., Kamal, C.R. and Rao, B.N. (2020), “Machine learning-structural equation modeling algorithm: the moderating role of loyalty on customer retention towards online shopping”, International Journal of Emerging Trends in Engineering Research, Vol. 8 No. 5, pp. 1578-1585.
Boateng, S.L. (2018), “Online relationship marketing and customer loyalty: a signaling theory perspective”, International Journal of Bank Marketing, Vol. 37 No. 1, pp. 226-240.
Bulut, Z.A. and Karabulut, A.N. (2018), “Examining the role of two aspects of eWOM in online repurchase intention: an integrated trust–loyalty perspective”, Journal of Consumer Behaviour, Vol. 17 No. 4, pp. 407-417.
Busalim, A.H. and Ghabban, F. (2021), “Customer engagement behaviour on social commerce platforms: an empirical study”, Technology in Society, Vol. 64, p. 101437.
Busalim, A.H., Hussin, A.R.C. and Iahad, N.A. (2019), “Factors influencing customer engagement in social commerce websites: a systematic literature review”, Journal of Theoretical and Applied Electronic Commerce Research, Vol. 14 No. 2, pp. 1-14.
Capponi, G., Corrocher, N. and Zirulia, L. (2020), “Personalized pricing for customer retention: theory and evidence from mobile communication”, Telecommunications Policy, Vol. 45 No. 1, p. 102069.
Casalo, L.V., Flavián, C. and Guinalíu, M. (2008), “Fundaments of trust management in the development of virtual communities”, Management Research News, Vol. 31 No. 5, pp. 324-338.
Casaló, L.V., Flavián, C. and Guinalíu, M. (2011), “The generation of trust in the online services and product distribution: the case of Spanish electronic commerce”, Journal of Electronic Commerce Research, Vol. 12 No. 3, p. 199.
Castaneda, J.A., Munoz-Leiva, F. and Luque, T. (2007), “Web acceptance model (WAM): moderating effects of user experience”, Information and Management, Vol. 44 No. 4, pp. 384-396.
Chakraborty, D., Banerjee, J., Mehta, P. and Singh, N.P. (2022), “The impact of website design on online customer buying satisfaction and loyalty to e-tailers: an exploratory study of e-tailers in India”, Information Resources Management Journal), Vol. 35 No. 1, pp. 1-18.
Chaouali, W. and Souiden, N. (2022), “Design aesthetics in predominantly-utilitarian versus predominantly-hedonic services: the ‘what is beautiful is good’ and ‘Ulysses’ effects”, Journal of Marketing Theory and Practice, pp. 1-14.
Cho, N. and Park, S. (2001), “Development of electronic commerce user‐consumer satisfaction index (ECUSI) for internet shopping”, Industrial Management and Data Systems, Vol. 101 No. 8, pp. 400-406.
Choi, Y. (2020), “A study of antecedents of switching cost and customer retention in social commerce”, International Journal of E-Business Research, Vol. 16 No. 4, pp. 51-64.
Chung, S., Kramer, T. and Wong, E.M. (2018), “Do touch interface users feel more engaged? The impact of input device type on online shoppers’ engagement, affect, and purchase decisions”, Psychology and Marketing, Vol. 35 No. 11, pp. 795-806.
Dang, V.T., Nguyen, N. and Pervan, S. (2020), “Retailer corporate social responsibility and consumer citizenship behavior: the mediating roles of perceived consumer effectiveness and consumer trust”, Journal of Retailing and Consumer Services, Vol. 55, p. 102082.
Daud, A., Farida, N., Andriansah, A. and Razak, M. (2018), “Impact of customer trust toward loyalty: the mediating role of perceived usefulness and satisfaction”, Journal of Business and Retail Management Research), Vol. 13 No. 2, pp. 235-242.
Eng, T.-Y. (2008), “E-customer service capability and value creation”, The Service Industries Journal, Vol. 28 No. 9, pp. 1293-1306.
Escobar-Rodriguez, T. and Monge-Lozano, P. (2012), “The acceptance of moodle technology by business administration students”, Computers and Education, Vol. 58 No. 4, pp. 1085-1093.
Falk, R.F. and Miller, N.B. (1992), A Primer for Soft Modeling, University of Akron Press, Akron.
Fimberg, K. and Sousa, S. (2020), “The impact of website design on users’ trust”, Paper presented at the proceedings of the 11th Nordic Conference on Human-Computer Interaction: Shaping Experiences, Shaping Society, pp. 1-5.
Flavián, C., Guinalíu, M. and Gurrea, R. (2006), “The role played by perceived usability, satisfaction and consumer trust on website loyalty”, Information and Management, Vol. 43 No. 1, pp. 1-14.
Fornell, C. and Larcker, D.F. (1981), “Structural equation models with unobservable variables and measurement error: algebra and statistics”, Journal of Marketing Research, Vol. 18 No. 3, pp. 382-388.
Gefen, D., Karahanna, E. and Straub, D.W. (2003), “Trust and TAM in online shopping: an integrated model”, MIS Quarterly, Vol. 27 No. 1, pp. 51-90.
Giao, H., Vuong, B. and Quan, T. (2020), “The influence of website quality on consumer’s e-loyalty through the mediating role of e-trust and e-satisfaction: an evidence from online shopping in Vietnam”, Uncertain Supply Chain Management, Vol. 8 No. 2, pp. 351-370.
Hair, J.F., Anderson, R., Babin, B. and Black, W. (2010), Multivariate Data Analysis, Pearson, Upper Saddle River, NJ.
Hair, J.F., Black, W.C., Babin, B.J. and Anderson, R.E. (2014), Multivariate Data Analysis: Pearson New International Edition, Pearson, Upper Saddle River, NJ.
Hair, J.F., Page, M. and Brunsveld, N. (2019), Essentials of Business Research Methods, Routledge, New York, NY.
Hair, J.F., Sarstedt, M., Ringle, C.M. and Gudergan, S.P. (2018), Advanced Issues in Partial Least Squares Structural Equation Modeling, Sage, Thousand Oaks, CA.
Henseler, J., Ringle, C.M. and Sarstedt, M. (2015), “A new criterion for assessing discriminant validity in variance-based structural equation modeling”, Journal of the Academy of Marketing Science, Vol. 43 No. 1, pp. 115-135.
Hicks, A., Comp, S., Horovitz, J., Hovarter, M., Miki, M. and Bevan, J.L. (2012), “Why people use yelp. com: an exploration of uses and gratifications”, Computers in Human Behavior, Vol. 28 No. 6, pp. 2274-2279.
Higgins, E.T. and Scholer, A.A. (2009), “Engaging the consumer: the science and art of the value creation process”, Journal of Consumer Psychology, Vol. 19 No. 2, pp. 100-114.
Huang, J. and Zhou, L. (2018), “Timing of web personalization in mobile shopping: a perspective from uses and gratifications theory”, Computers in Human Behavior, Vol. 88, pp. 103-113.
Ijaz, M.F. and Rhee, J. (2018), “Constituents and consequences of online-shopping in sustainable e-business: an experimental study of online-shopping malls”, Sustainability, Vol. 10 No. 10, p. 3756.
Ijaz, M.F., Tao, W., Rhee, J., Kang, Y.-S. and Alfian, G. (2016), “Efficient digital signage-based online store layout: an experimental study”, Sustainability, Vol. 8 No. 6, p. 511.
Irshad, M., Ahmad, M.S. and Malik, O.F. (2020), “Understanding consumers’ trust in social media marketing environment”, International Journal of Retail and Distribution Management, Vol. 48 No. 11, pp. 1195-1212.
Islam, J.U., Shahid, S., Rasool, A., Rahman, Z., Khan, I. and Rather, R.A. (2020), “Impact of website attributes on customer engagement in banking: a solicitation of stimulus-organism-response theory”, International Journal of Bank Marketing, Vol. 38 No. 6, pp. 1279-1303, doi: 10.1108/IJBM-12-2019-0460.
Japutra, A., Molinillo, S., Utami, A.F., Ekaputra, I.A.J.T. and Informatics (2022), “Exploring the effect of relative advantage and challenge on customer engagement behavior with mobile commerce applications”, Telematics and Informatics, Vol. 72, p. 101841.
Javed, A.M., Ahmad, N. and Zakaria, N. (2018), “An integrated framework on service recovery performance: the mediating role of organizational commitment”, Pakistan Journal of Humanities and Social Sciences, Vol. 6 No. 2, pp. 263-279.
Jiyoung, K., Jin, B. and Swinney, J.L. (2009), “The role of etail quality, e-satisfaction and e-trust in online loyalty development process”, Journal of Retailing and Consumer Services, Vol. 16 No. 4, pp. 239-247.
Kang, K., Lu, J., Guo, L. and Li, W.J.I.J.O.I.M. (2021), “The dynamic effect of interactivity on customer engagement behavior through tie strength: evidence from live streaming commerce platforms”, International Journal of Information Management, Vol. 56, p. 102251.
Khan, I., Rahman, Z. and Fatma, M. (2016), “The role of customer brand engagement and brand experience in online banking”, International Journal of Bank Marketing, Vol. 34 No. 7, pp. 1025-1041.
Kim, J. and Lee, J. (2002), “Critical design factors for successful e-commerce systems”, Behaviour and Information Technology, Vol. 21 No. 3, pp. 185-199.
Koufaris, M. (2002), “Applying the technology acceptance model and flow theory to online consumer behavior”, Information Systems Research, Vol. 13 No. 2, pp. 205-223.
Kumar, A. and Lata, S. (2021), “The system quality and customer satisfaction with website quality as mediator in online purchasing: a developing country perspectives”, Journal of Operations and Strategic Planning, Vol. 4 No. 1, pp. 7-26.
Kumar, M.R., Venkatesh, J. and Rahman, A. (2021), “Data mining and machine learning in retail business: developing efficiencies for better customer retention”, Journal of Ambient Intelligence and Humanized Computing, 1-13.
Larivière, B., Joosten, H., Malthouse, E.C., Van Birgelen, M., Aksoy, P., Kunz, W.H. and Huang, M.H. (2013), “Value fusion: the blending of consumer and firm value in the distinct context of mobile technologies and social media”, Journal of Service Management, Vol. 24 No. 3, pp. 268-293.
Lăzăroiu, G., Neguriţă, O., Grecu, I., Grecu, G. and Mitran, P.C. (2020), “Consumers’ decision-making process on social commerce platforms: online trust, perceived risk, and purchase intentions”, Frontiers in Psychology, Vol. 11, p. 890.
Lee, H., Choi, S.Y. and Kang, Y.S. (2009), “Formation of e-satisfaction and repurchase intention: moderating roles of computer self-efficacy and computer anxiety”, Expert Systems with Applications, Vol. 36 No. 4, pp. 7848-7859.
Li, M.-W., Teng, H.-Y. and Chen, C.-Y. (2020), “Unlocking the customer engagement-brand loyalty relationship in tourism social media: the roles of brand attachment and customer trust”, Journal of Hospitality and Tourism Management, Vol. 44, pp. 184-192.
McKnight, D.H., Choudhury, V. and Kacmar, C. (2002), “Developing and validating trust measures for e-Commerce: an integrative typology”, Information Systems Research, Vol. 13 No. 3, pp. 334-359.
Madad, A., Asmi, F., Rahman, M.M., Malik, N. and Ahmad, M.S. (2017), “Evaluation of e-service quality through customer satisfaction (a case study of FBR E-Taxation)”, Open Journal of Social Sciences, Vol. 05 No. 9, pp. 175-195.
Majeed, M., Asare, C., Fatawu, A. and Abubakari, A. (2022), “An analysis of the effects of customer satisfaction and engagement on social media on repurchase intention in the hospitality industry”, Cogent Business and Management, Vol. 9 No. 1, p. 2028331.
Malthouse, E.C. and Peck, A. (2011), Medill on Media Engagement, Hampton Press, Newburyport, MA.
Marliawati, A. and Cahyaningdyah, D. (2020), “Impacts the brand of experience and brand image on brand loyalty: mediators brand of trust”, Management Analysis Journal, Vol. 9 No. 2, pp. 140-151.
Marriott, H.R., Williams, M.D. and Dwivedi, Y.K. (2017), “Risk, privacy and security concerns in digital retail”, The Marketing Review, Vol. 17 No. 3, pp. 337-365.
Maryanto, R.H. and Kaihatu, T.S. (2021), “Customer loyalty as an impact of perceived usefulness to grab users, mediated by customer satisfaction and moderated by perceived ease of use”, Binus Business Review, Vol. 12 No. 1, pp. 31-39.
Masele, J.J. and Matama, R. (2020), “Individual consumers' trust in B2C automobile e‐commerce in tanzania: assessment of the influence of web design and consumer personality”, The Electronic Journal of Information Systems in Developing Countries, Vol. 86 No. 1, p. e12115.
Maslowska, E., Malthouse, E.C. and Collinger, T. (2016), “The customer engagement ecosystem”, Journal of Marketing Management, Vol. 32 Nos 5/6, pp. 469-501.
Mbama, C.I., Ezepue, P., Alboul, L. and Beer, M. (2018), “Digital banking, customer experience and financial performance: UK bank managers’ perceptions”, Journal of Research in Interactive Marketing, Vol. 12 No. 4, pp. 432-451, doi: 10.1108/JRIM-01-2018-0026.
Molinillo, S., Aguilar-Illescas, R., Anaya-Sánchez, R. and Liébana-Cabanillas, F. (2021), “Social commerce website design, perceived value and loyalty behavior intentions: the moderating roles of gender, age and frequency of use”, Journal of Retailing and Consumer Services, Vol. 63, p. 102404.
Moslehpour, M., Pham, V., Wong, W.-K. and Bilgiçli, İ. (2018), “e-Purchase intention of Taiwanese consumers: sustainable mediation of perceived usefulness and perceived ease of use”, Sustainability, Vol. 10 No. 1, p. 234.
Mulyaningsih, S. (2022), “The effect of perceived usefulness, perceived ease of use in digital banking services toward customer loyalty with user’s trust as mediator”, universitas bakrie.
Muntinga, D.G., Moorman, M. and Smit, E.G. (2011), “Introducing COBRAs: exploring motivations for brand-related social media use”, International Journal of Advertising, Vol. 30 No. 1, pp. 13-46.
Nam, C., Cho, K. and Kim, Y.D. (2021), “Cross-cultural examination of apparel online purchase intention: SOR paradigm”, Journal of Global Fashion Marketing, Vol. 12 No. 1, pp. 62-76.
Nguyen, M.H. and Khoa, B.T. (2019), “Customer electronic loyalty towards online business: the role of online trust, perceived mental benefits and hedonic value”, Journal of Distribution Science, Vol. 17 No. 12, pp. 81-93.
Ozturk, A.B., Bilgihan, A., Nusair, K. and Okumus, F. (2016), “What keeps the mobile hotel booking users loyal? Investigating the roles of self-efficacy, compatibility, perceived ease of use, and perceived convenience”, International Journal of Information Management, Vol. 36 No. 6, pp. 1350-1359.
Pansari, A. and Kumar, V. (2017), “Customer engagement: the construct, antecedents, and consequences”, Journal of the Academy of Marketing Science, Vol. 45 No. 3, pp. 294-311.
Patwary, A.K., Rasoolimanesh, S.M., Rabiul, M.K., Aziz, R.C. and Hanafiah, M.H. (2022), “Linking environmental knowledge, environmental responsibility, altruism, and intention toward green hotels through ecocentric and anthropocentric attitudes”, International Journal of Contemporary Hospitality Management, Vol. 34 No. 12, pp. 4653-4673.
Pavlou, P.A. and Chai, L. (2002), “What drives electronic commerce across cultures? Across-cultural empirical investigation of the theory of planned behavior”, Electron. Commerce Res, Vol. 3 No. 4, pp. 240-253.
Podsakoff, P.M., MacKenzie, S.B. and Podsakoff, N.P. (2012), “Sources of method bias in social science research and recommendations on how to control it”, Annual Review of Psychology, Vol. 63, pp. 539-569.
Podsakoff, P.M. and Organ, D.W. (1986), “Self-reports in organizational research: problems and prospects”, Journal of Management, Vol. 12 No. 4, pp. 531-544.
Purani, K., Kumar, D.S. and Sahadev, S. (2019), “e-Loyalty among millennials: personal characteristics and social influences”, Journal of Retailing and Consumer Services, Vol. 48, pp. 215-223.
Rahimnia, F. and Hassanzadeh, J.F. (2013), “The impact of website content dimension and e-trust on e-marketing effectiveness: the case of Iranian commercial saffron corporations”, Information and Management, Vol. 50 No. 5, pp. 240-247.
Ramadhanti, A. and Slamet, A.S. (2020), “Developing e-commerce success model by measuring website quality of Indonesian MSMEs”, Paper Presented at the 5th Sriwijaya Economics, Accounting, and Business Conference (SEABC 2019), Vol. 142, pp. 16-23, available at: www.atlantis-press.com/proceedings/seabc-19/125940858
Raman, P. (2020), “Online shopping characteristics and their influence on female buying behavior: an extension of the theory of planned behavior”, Journal of Electronic Commerce in Organizations, Vol. 18 No. 4, pp. 1-29.
Rana, J., Gaur, L., Singh, G., Awan, U. and Rasheed, M.I. (2021), “Reinforcing customer journey through artificial intelligence: a review and research agenda”, International Journal of Emerging Markets, Vol. 17 No. 7, pp. 1738-1758.
Ratnawati, A. and Lestari, A.A. (2018), “Peran brand trust dalam memediasi brand experience, brand personality dan brand community terhadap brand loyalty”, Jurnal Ekonomi Dan Bisnis, Vol. 19 No. 2, pp. 185-202.
Rauyruen, P. and Miller, K. (2007), “Relationship quality as a predictor of B2B customer loyalty”, Journal of Business Research, Vol. 60 No. 1, pp. 21-31.
Riquelme, I.P., Román, S., Cuestas, P.J. and Iacobucci, D. (2019), “The dark side of good reputation and loyalty in online retailing: when trust leads to retaliation through price unfairness”, Journal of Interactive Marketing, Vol. 47, pp. 35-52.
Rodríguez, P.G., Villarreal, R., Valiño, P.C. and Blozis, S. (2020), “A PLS-SEM approach to understanding E-SQ, e-satisfaction and e-loyalty for fashion e-retailers in Spain”, Journal of Retailing and Consumer Services, Vol. 57, p. 102201.
Sambhanthan, A. and Good, A. (2016), “Strategic advantage in web tourism promotion: an e-commerce strategy for developing countries”, International Business: Concepts, Methodologies, Tools, and Applications, IGI Global, Hershey, pp. 597-618.
Shamim, A., Ahn, J., Khan, I., Shah, M. and Abid, M.F. (2023), “Make every interaction count-assessing the role of customers’ self-construal on value co-creation at service encounters”, The International Review of Retail, Distribution and Consumer Research, Vol. 33 No. 2, pp. 1-24, doi: 10.1080/09593969.2022.2109714.
Shamim, A., Siddique, J., Noor, U. and Hassan, R.J. (2021), “Co-creative service design for online businesses in post-COVID-19”, Journal of Islamic Marketing, Vol. 14 No. 1, pp. 128-145.
Shilpa, S.K. and Rathi, R. (2020), “Empirical investigation of internet banking usage – a factor analytical approach”, Journal of Advanced Research in Dynamical and Control Systems, Vol. 12 No. 4, pp. 754-763.
Siddique, J., Shamim, A., Nawaz, M. and Abid, M.F. (2023), “The hope and hype of neuromarketing: a bibliometric analysis”, Journal of Contemporary Marketing Science, Vol. 6 No. 1, pp. 1-21.
Siddique, J., Shamim, A., Nawaz, M., Faye, I. and Rehman, M. (2021), “Co-creation or co-destruction: a perspective of online customer engagement valence”, Frontiers in Psychology, Vol. 11, p. 591753.
Silitonga, K., Fakhrorazi, A. and Ikhsan, R. (2020), “Drivers of buyer retention in e-commerce: the role of transaction characteristics and trust”, Management Science Letters, Vol. 10 No. 15, pp. 3485-3494.
Soyeun, L., Han, H., Radic, A. and Tariq, B. (2020), “Corporate social responsibility (CSR) as a customer satisfaction and retention strategy in the chain restaurant sector”, Journal of Hospitality and Tourism Management, Vol. 45, pp. 348-358.
Sukendia, J. and Harianto, N. (2021), “The impact of e-service quality on customer engagement, customer experience and customer loyalty in B2C e-commerce”, Turkish Journal of Computer and Mathematics Education, Vol. 12 No. 3, pp. 3170-3184.
Tang, R. and Yang, L. (2020), “Financing strategy in fresh product supply chains under e-commerce environment”, Electronic Commerce Research and Applications, Vol. 39, p. 100911.
ThakreemBanua, M. (2021), “A study on customer loyalty and customer retention in online shopping”.
Tran, V.-D. and Vu, Q.H. (2019), “Inspecting the relationship among e-service quality, e-trust, e-customer satisfaction and behavioral intentions of online shopping customers”, Global Business Finance Review, Vol. 24 No. 3, pp. 29-42.
Vakulenko, Y., Hellström, D. and Hjort, K. (2018), “What's in the parcel locker? Exploring customer value in e-commerce last mile delivery”, Journal of Business Research, Vol. 88, pp. 421-427.
Vásquez, F. (2020), “From e-quality and brand perceptions to repurchase: a model to explain purchase behaviour in a web-store”, Journal of Theoretical and Applied Electronic Commerce Research, Vol. 15 No. 3, pp. 20-36.
Vatolkina, N., Gorbashko, E., Kamynina, N. and Fedotkina, O. (2020), “E-service quality from attributes to outcomes: the similarity and difference between digital and hybrid services”, Journal of Open Innovation: Technology, Market, Complexity, Vol. 6 No. 4, p. 143.
Ventre, I. and Kolbe, D. (2020), “The impact of perceived usefulness of online reviews, trust and perceived risk on online purchase intention in emerging markets: a Mexican perspective”, Journal of International Consumer Marketing, Vol. 32 No. 4, pp. 287-299.
Wagner, G., Schramm-Klein, H. and Steinmann, S. (2020), “Online retailing across e-channels and e-channel touchpoints: empirical studies of consumer behavior in the multichannel e-commerce environment”, Journal of Business Research, Vol. 107, pp. 256-270.
Wang, L., Law, R., Guillet, B.D., Hung, K. and Fong, D.K.C. (2015), “Impact of hotel website quality on online booking intentions: eTrust as a mediator”, International Journal of Hospitality Management, Vol. 47, pp. 108-115.
Wardhani, A. (2020), “Identifying consumer review through web design and online advertisement in online shop”, International Journal of Data and Network Science, Vol. 4 No. 3, pp. 289-296.
Wen, C., Prybutok, V.R. and Xu, C. (2011), “An integrated model for customer online repurchase intention”, Journal of Computer Information Systems, Vol. 52 No. 1, pp. 14-23.
Wijaya, A.P., Bernarto, I. and Purwanto, A. (2020), “How to achieve value creation in digital world? The influence of IT response on value creation and customer satisfaction”, International Journal of Advanced Science and Technology, Vol. 29 No. 3, pp. 6705-6715.
Wilis, R.A. and Nurwulandari, A. (2020), “The effect of e-service quality, e-trust, price and brand image towards e-satisfaction and its impact on e-loyalty of Traveloka’s customer”, Jurnal Ilmiah MEA (Manajemen, Ekonomi, and Akuntansi), Vol. 4 No. 3, pp. 1061-1099.
Wilson, N., Keni, K. and Tan, P.H.P. (2021), “The role of perceived usefulness and perceived ease-of-use toward satisfaction and trust which influence computer consumers’ loyalty in China”, Gadjah Mada International Journal of Business, Vol. 23 No. 3, pp. 262-294.
Zaid, S Patwayati. (2021), “Impact of customer experience and customer engagement on satisfaction and loyalty: a case study in Indonesia”, The Journal of Asian Finance, Economics and Business, Vol. 8 No. 4, pp. 983-992.
Zhou, T., Lu, Y. and Wang, B. (2009), “The relative importance of website design quality and service quality in determining consumers’ online repurchase behavior”, Information Systems Management, Vol. 26 No. 4, pp. 327-337.
Zhu, F.X., Wymer, W. and Chen, I. (2002), “IT‐based services and service quality in consumer banking”, International Journal of Service Industry Management, Vol. 13 No. 1, pp. 69-90.
Acknowledgements
Declaration of conflict of interest: The authors declare no conflict of interest concerning the research, authorship and or publication of this article.