Understanding Online Store Service Quality Antecedents and Their Impact on Customer Satisfaction and Behavioral Intentions in Iran
محورهای موضوعی : Marketing
Seyed Mojtaba Moussavi Neghabi
1
,
مرتضی انوشه
2
,
Masoud Qorbankhani
3
1 - Assistant Professor of University of Gonabad
2 - استادیار گروه مدیریت، دانشکده علوم اجتماعی، دانشگاه بین المللی امام خمینی(ره)،
3 - Alborz Institute of Higher Education
کلید واژه: Online Store, Service Quality, Customer Satisfaction, behavioral intention,
چکیده مقاله :
The proliferation of online stores in Iran has surged in recent years, yet a notable proportion of these ventures falter shortly after inception. Among the myriad challenges confronting Iranian online retailers, the discontinuity in customer purchases stands out prominently. To address this issue, this study delves into the influence of online store service quality antecedents, specifically perceived risk, service convenience, and website design, on both customer satisfaction and behavioral intentions. Data collection entailed administering a questionnaire, and the research model underwent scrutiny via structural equation modeling (SEM). Results indicate a significant positive association between website design and the quality of online store services. Moreover, service convenience and the quality of online store services emerged as robust determinants of customer satisfaction. Satisfaction, in turn, exhibited a substantial positive impact on customer behavioral intentions. Conversely, perceived risk exerted a negative and significant influence on the quality of online store services. Notably, the effects of service convenience on service quality and the impact of service quality on customer behavioral intentions were statistically insignificant at the 95% confidence level. However, the mediating variable of satisfaction significantly mediated the relationship between online store service quality and customer behavioral intentions.
The proliferation of online stores in Iran has surged in recent years, yet a notable proportion of these ventures falter shortly after inception. Among the myriad challenges confronting Iranian online retailers, the discontinuity in customer purchases stands out prominently. To address this issue, this study delves into the influence of online store service quality antecedents, specifically perceived risk, service convenience, and website design, on both customer satisfaction and behavioral intentions. Data collection entailed administering a questionnaire, and the research model underwent scrutiny via structural equation modeling (SEM). Results indicate a significant positive association between website design and the quality of online store services. Moreover, service convenience and the quality of online store services emerged as robust determinants of customer satisfaction. Satisfaction, in turn, exhibited a substantial positive impact on customer behavioral intentions. Conversely, perceived risk exerted a negative and significant influence on the quality of online store services. Notably, the effects of service convenience on service quality and the impact of service quality on customer behavioral intentions were statistically insignificant at the 95% confidence level. However, the mediating variable of satisfaction significantly mediated the relationship between online store service quality and customer behavioral intentions.
Agrawal, S., & Agrawal, B. (2019). Customer delight: An antecedent of brand loyalty in online shopping. International Journal of Marketing and Technology, 9(8), 21-32.
Ahmad, A., Rahman, O., & Khan, M. N. (2016). Consumer's perception of website service quality: An empirical study. Journal of Internet Commerce, 15(2), 125-141.
Akbari, M. S. A., Manouchehri, F., & Sadeghi, H. (2018). Analysis of the use of online stores to Supply of rural products. spatial planing, 8(1), 89-110.
Al-dweeri, R. M., Obeidat, Z. M., Al-dwiry, M. A., Alshurideh, M. T., & Alhorani, A. M. (2017). The impact of e-service quality and e-loyalty on online shopping: moderating effect of e-satisfaction and e-trust. International Journal of Marketing Studies, 9(2), 92.
Al-Qeisi, K., Dennis, C., Alamanos, E., & Jayawardhena, C. (2014). Website design quality and usage behavior: Unified Theory of Acceptance and Use of Technology. Journal of Business Research, 67(11), 2282-2290.
Alcántara-Pilar, J. M., Blanco-Encomienda, F. J., Armenski, T., & Del Barrio-García, S. (2018). The antecedent role of online satisfaction, perceived risk online, and perceived website usability on the affect towards travel destinations. Journal of Destination Marketing & Management, 9, 20-35.
Alkhouli, S. (2017). The effect of banks website service quality and e-satisfaction on e-loyalty: An empirical study on swedish banks. International Journal of Business and Management, 13(1), 1-12.
Ariffin, S. K., Mohan, T., & Goh, Y.-N. (2018). Influence of consumers’ perceived risk on consumers’ online purchase intention. Journal of Research in Interactive Marketing.
Beikzad, J., Molavi, Z., & Esgandari, K. (2011). Relationship between the Quality of Electronic Services and Student's Electronic Satisfaction in Islamic Azad University of Bonab. Information and Communication Technology in Educational Sciences, 1(3), 67-92.
Biswas, K. M., Nusari, M., & Ghosh, A. (2019). The Influence of Website Service Quality on Customer Satisfaction Towards Online Shopping: The Mediating Role of Confirmation of Expectation. International Journal of Management Science and Business Administration, 5(6), 7-14.
Biucky, S. T., & Harandi, S. R. (2017). The effects of perceived risk on social commerce adoption based on TAM Model. " International Journal of Electronic Commerce Studies", 8(2), 173-196.
Blut, M. (2016). E-service quality: development of a hierarchical model. Journal of Retailing, 92(4), 500-517.
Blut, M., Chowdhry, N., Mittal, V., & Brock, C. (2015). E-service quality: A meta-analytic review. Journal of Retailing, 91(4), 679-700.
Bonnin, G. (2020). The roles of perceived risk, attractiveness of the online store and familiarity with AR in the influence of AR on patronage intention. Journal of Retailing and Consumer Services, 52, 101938.
Cangur, S., & Ercan, I. (2015). Comparison of model fit indices used in structural equation modeling under multivariate normality. Journal of Modern Applied Statistical Methods, 14(1), 14.
Chang, S.-H., Chih, W.-H., Liou, D.-K., & Hwang, L.-R. (2014). The influence of web aesthetics on customers’ PAD. Computers in Human Behavior, 36, 168-178.
Coker, B. (2013). Antecedents to website satisfaction, loyalty, and word-of-mouth. JISTEM-Journal of Information Systems and Technology Management, 10(2), 209-218.
Collier, J. E., & Bienstock, C. C. (2015). A conceptual framework for measuring e-service quality. In Creating and Delivering Value in Marketing (pp. 158-162). Springer.
Dedeke, A. N. (2016). Travel web-site design: Information task-fit, service quality and purchase intention. Tourism Management, 54, 541-554.
Dianat, I., Adeli, P., Jafarabadi, M. A., & Karimi, M. A. (2019). User-centred web design, usability and user satisfaction: The case of online banking websites in Iran. Applied ergonomics, 81, 102892.
Duarte, P., e Silva, S. C., & Ferreira, M. B. (2018). How convenient is it? Delivering online shopping convenience to enhance customer satisfaction and encourage e-WOM. Journal of Retailing and Consumer Services, 44, 161-169.
El-Haddadeh, R., Weerakkody, V., & Al-Shafi, S. (2013). The complexities of electronic services implementation and institutionalisation in the public sector. Information & Management, 50(4), 135-143.
Emami, L., & Namamian, F. (2018). Identify Factors Affecting the Development of Electronic Banking (using the Delphi technique). Journal of Development Evolution Management, 31(31), 131-140.
Faisal, C. N., Gonzalez-Rodriguez, M., Fernandez-Lanvin, D., & de Andres-Suarez, J. (2016). Web design attributes in building user trust, satisfaction, and loyalty for a high uncertainty avoidance culture. IEEE Transactions on Human-Machine Systems, 47(6), 847-859.
Gefen, D., Karahanna, E., & Straub, D. W. (2003). Trust and TAM in online shopping: An integrated model. MIS quarterly, 27(1), 51-90.
Gera, R., Mittal, S., Batra, D. K., & Prasad, B. (2017). Evaluating the effects of service quality, customer satisfaction, and service value on behavioral intentions with life insurance customers in India. International Journal of Service Science, Management, Engineering, and Technology (IJSSMET), 8(3), 1-20.
Gharibi, H., Dehdashtishahrokh, Z., & Hoseinimehr, M. (2020). The Impact of Brand Image and Brand Strength on the Desire to Buy Customers From Online Stores (Case Study: Bamilo Store). Commercial Surveys, 17(99), 52-76.
Gounaris, S., Dimitriadis, S., & Stathakopoulos, V. (2010). An examination of the effects of service quality and satisfaction on customers' behavioral intentions in e‐shopping. Journal of services marketing.
Habeeb, S., & Sudhakar, K. F. (2019). Analyzing Causality Among the Service Quality, Customer Satisfaction and Behavioral Intention Variables with Respect to E-Shopping: An Empirical Take. International Journal of Online Marketing (IJOM), 9(1), 38-59.
Hasan, B. (2016). Perceived irritation in online shopping: The impact of website design characteristics. Computers in Human Behavior, 54, 224-230.
Hsu, S.-H., & Luan, P. M. (2017). The Perception Risk of Online Shopping Impacted on the Consumer’s Attitude and Purchase Intention in Hanoi, Vietnam. Journal of Business & Economic Policy, 4(4), 19-29.
Hult, G. T. M., Sharma, P. N., Morgeson III, F. V., & Zhang, Y. (2019). Antecedents and consequences of customer satisfaction: do they differ across online and offline purchases? Journal of Retailing, 95(1), 10-23.
Hume, M., & Mort, G. S. (2010). The consequence of appraisal emotion, service quality, perceived value and customer satisfaction on repurchase intent in the performing arts. Journal of services marketing.
Imankhan, N. (2018). E-Business and Startup's Performance. Quarterly Journal of Economic Modelling, 12(1), 83-105.
Jeon, M. M., & Jeong, M. (2017). Customers’ perceived website service quality and its effects on e-loyalty. International Journal of Contemporary Hospitality Management.
Jin, N., Lee, S., & Lee, H. (2015). The effect of experience quality on perceived value, satisfaction, image and behavioral intention of water park patrons: New versus repeat visitors. International Journal of Tourism Research, 17(1), 82-95.
Kant, R., & Jaiswal, D. (2017). The impact of perceived service quality dimensions on customer satisfaction. International Journal of Bank Marketing.
Khademi, A., & Farazandeh, H. (2019). The study of effective factors on customer relationship quality in creating brand value and intention to online purchase (A study of eshop customers in Tehran). Journal of Marketing Management, 14(44), 41-59.
Khan, M. A., & Khan, S. (2018). Service Convenience and Post-Purchase Behaviour of Online Buyers: An Empirical Study. Journal of Service Science Research, 10(2), 167-188.
Kourtesopoulou, A., Theodorou, S.-D., Kriemadis, A., & Papaioannou, A. (2019). The Impact of Online Travel Agencies Web Service Quality on Customer Satisfaction and Purchase Intentions. In Smart Tourism as a Driver for Culture and Sustainability (pp. 343-356). Springer.
Lee, F.-H., & Wu, W.-Y. (2011). Moderating effects of technology acceptance perspectives on e-service quality formation: Evidence from airline websites in Taiwan. Expert Systems with Applications, 38(6), 7766-7773. https://doi.org/https://doi.org/10.1016/j.eswa.2010.12.131
Lee, G. G., & Lin, H. F. (2005). Customer perceptions of e‐service quality in online shopping. International Journal of Retail & Distribution Management.
Martin, J., Mortimer, G., & Andrews, L. (2015). Re-examining online customer experience to include purchase frequency and perceived risk. Journal of Retailing and Consumer Services, 25, 81-95.
Mofokeng, T. E. (2021). The impact of online shopping attributes on customer satisfaction and loyalty: Moderating effects of e-commerce experience. Cogent Business & Management, 8(1), 1968206. https://doi.org/10.1080/23311975.2021.1968206
Mpinganjira, M. (2015). Online store service convenience, customer satisfaction and behavioural intentions: a focus on utilitarian oriented shoppers. Journal of Economics and Behavioral Studies, 7(1), 36-49.
Olorunniwo, F., Hsu, M. K., & Udo, G. J. (2006). Service quality, customer satisfaction, and behavioral intentions in the service factory. Journal of services marketing.
Park, J. Y., & Thangam, D. (2019). What Makes Customers Repurchase Grocery Products from Online Stores in Korea. International Journal of E-Business Research (IJEBR), 15(4), 24-39.
Pereira, H. G., de Fátima Salgueiro, M., & Rita, P. (2017). Online determinants of e-customer satisfaction: application to website purchases in tourism. Service Business, 11(2), 375-403.
Phuong, N. N. D., & Dai Trang, T. T. (2018). Repurchase intention: The effect of service quality, system quality, information quality, and customer satisfaction as mediating role: a PLS approach of m-commerce ride hailing service in Vietnam. Marketing and Branding Research, 5(2), 78.
Qalati, S. A., Vela, E. G., Li, W., Dakhan, S. A., Hong Thuy, T. T., & Merani, S. H. (2021). Effects of perceived service quality, website quality, and reputation on purchase intention: The mediating and moderating roles of trust and perceived risk in online shopping. Cogent Business & Management, 8(1), 1869363.
Retno, I. D., Budi, S., & Agustina, S. (2019). ANALYSIS OF THE RELATIONSHIP BETWEEN E-SERVICE QUALITY, CUSTOMER SATISFACTION, AND CONSUMER BEHAVIORAL INTENTIONS: A CASE STUDY OF ONLINE-BASED AGRIBUSINESS COMPANIES IN MALANG CITY. Russian Journal of Agricultural and Socio-Economic Sciences, 85(1).
Rita, P., Oliveira, T., & Farisa, A. (2019). The impact of e-service quality and customer satisfaction on customer behavior in online shopping. Heliyon, 5(10), e02690. https://doi.org/https://doi.org/10.1016/j.heliyon.2019.e02690
Ro, H. (2014). Complaint, patience, and neglect: responses to a dissatisfying service experience. Service Business, 8(2), 197-216.
Roy, S. K., Lassar, W. M., & Shekhar, V. (2016). Convenience and satisfaction: mediation of fairness and quality. The Service Industries Journal, 36(5-6), 239-260.
Sahadev, S., & Purani, K. (2008). Modelling the consequences of e‐service quality. Marketing Intelligence & Planning.
Saleem, M. A., Zahra, S., & Yaseen, A. (2017). Impact of service quality and trust on repurchase intentions–the case of Pakistan airline industry. Asia Pacific Journal of Marketing and Logistics.
Santos, J. (2003). E‐service quality: a model of virtual service quality dimensions. Managing Service Quality: An International Journal.
SastryT, D., & Rao, B. M. (2017). Consumer perception about the influence of online retail service quality on e-satisfaction, moderated by purchase volume and perceived value. Journal of Business and Retail Management Research, 12(1).
Stiakakis, E., & Georgiadis, C. K. (2009). E‐service quality: comparing the perceptions of providers and customers. Managing Service Quality: An International Journal.
Suhaily, L., & Soelasih, Y. (2017). What Effects Repurchase Intention of Online Shopping. International Business Research, 10(12), 113-122.
Suhartanto, D., Helmi Ali, M., Tan, K. H., Sjahroeddin, F., & Kusdibyo, L. (2019). Loyalty toward online food delivery service: the role of e-service quality and food quality. Journal of foodservice business research, 22(1), 81-97.
Tandon, U., Kiran, R., & Sah, A. N. (2017). Customer satisfaction as mediator between website service quality and repurchase intention: An emerging economy case. Service Science, 9(2), 106-120.
Tandon, U., Kiran, R., & Sah, A. N. (2018). The influence of website functionality, drivers and perceived risk on customer satisfaction in online shopping: an emerging economy case. Information Systems and e-Business Management, 16(1), 57-91.
Tran, V. D., & Nguyen, T. D. (2022). The impact of security, individuality, reputation, and consumer attitudes on purchase intention of online shopping: The evidence in Vietnam. Cogent Psychology, 9(1), 2035530. https://doi.org/10.1080/23311908.2022.2035530
Tsao, W.-C., Hsieh, M.-T., & Lin, T. M. (2016). Intensifying online loyalty! The power of website quality and the perceived value of consumer/seller relationship. Industrial Management & Data Systems.
Udo, G. J., Bagchi, K. K., & Kirs, P. J. (2010). An assessment of customers’e-service quality perception, satisfaction and intention. International Journal of Information Management, 30(6), 481-492.
Vasić, N., Kilibarda, M., & Kaurin, T. (2019). The influence of online shopping determinants on customer satisfaction in the Serbian market. Journal of theoretical and applied electronic commerce research, 14(2), 0-0.
Vásquez, F., & Vera-Martínez, y. J. (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, 15(3), 20-35.
Wali, A. F., & Opara, B. (2012). E-Service quality experience and customer loyalty: an emphasis of the Nigeria airline operators. European Journal of Business and Social Sciences, 1(9), 118-125.
Wu, L.-Y., Chen, K.-Y., Chen, P.-Y., & Cheng, S.-L. (2014). Perceived value, transaction cost, and repurchase-intention in online shopping: A relational exchange perspective. Journal of Business Research, 67(1), 2768-2776.
Yang, H., Yu, J., Zo, H., & Choi, M. (2016). User acceptance of wearable devices: An extended perspective of perceived value. Telematics and Informatics, 33(2), 256-269.
Yang, S.-K., & Shim, J.-H. (2018). The effects of service qualities on customer satisfaction, trust, and behavioral intention in smartphone shopping malls. International Journal of Industrial Distribution & Business, 9(12), 31-43.
Yang, Z., & Fang, X. (2004). Online service quality dimensions and their relationships with satisfaction. International journal of service industry management.
Yeh, Y.-S., & Li, Y.-M. (2014). Design-to-lure in the e-shopping environment: A landscape preference approach. Information & Management, 51(8), 995-1004.
Yeo, V. C. S., Goh, S.-K., & Rezaei, S. (2017). Consumer experiences, attitude and behavioral intention toward online food delivery (OFD) services. Journal of Retailing and Consumer Services, 35, 150-162.
Yulisetiarini, D., Subagio, A., Paramu, H., & Irawan, B. (2017). Customer repurchase intention and satisfaction in online shopping. International Business Management, 11(1), 215-221.
Zeglat, D., Shrafat, F., & Al-Smadi, Z. (2016). The Impact of the E-Service Quality (E-SQ) of Online Databases on Users’ Behavioural Intentions: A Perspective of Postgraduate Students. International Review of Management and Marketing, 6(1S), 1-10.
Zhang, X., & Prybutok, V. R. (2005). A consumer perspective of e-service quality. IEEE transactions on Engineering Management, 52(4), 461-477.
Zhou, R., Wang, X., Shi, Y., Zhang, R., Zhang, L., & Guo, H. (2019). Measuring e-service quality and its importance to customer satisfaction and loyalty: an empirical study in a telecom setting. Electronic Commerce Research, 19(3), 477-499.
Online ISSN: 2538-1571, Print ISSN: 2322-2301
10(4), 2024, pp. 67-80
DOI: 10.30495/SJSM.2024.1105489
RESEARCH ARTICLE Open Access
Understanding Online Store Service Quality Antecedents and Their Impact on Customer Satisfaction and Behavioral Intentions in Iran
Abstract
The proliferation of online stores in Iran surged in recent years, yet a notable proportion of these ventures faltered shortly after inception. Among the myriad challenges confronting Iranian online retailers, the discontinuity in customer purchases stood out prominently. To address this issue, this study delved into the influence of online store service quality antecedents, specifically perceived risk, service convenience, and website design, on both customer satisfaction and behavioral intentions. The statistical population of this study included customers of selected online stores who had made at least one purchase in the last three months. The sampling method used was stratified sampling. Data collection entailed administering a questionnaire, and the research model underwent scrutiny via structural equation modeling (SEM). Cronbach's alpha coefficient was utilized to evaluate the reliability of the questionnaire, while the average extracted variance (AVE) was employed to measure the validity. The results indicated a significant positive association between website design and the quality of online store services. Moreover, service convenience and the quality of online store services emerged as robust determinants of customer satisfaction. Satisfaction, in turn, exhibited a substantial positive impact on customer behavioral intentions. Conversely, perceived risk exerted a negative and significant influence on the quality of online store services. Notably, the effects of service convenience on service quality and the impact of service quality on customer behavioral intentions were statistically insignificant at the 95% confidence level. However, the mediating variable of satisfaction significantly mediated the relationship between online store service quality and customer behavioral intentions.
Keywords: Online Store, Service Quality, Customer Satisfaction, behavioral intention
3. Department of Management, Alborz Institute of Higher Education, Qazvin, Iran.
Introduction
To satisfy customers, online stores must provide high-quality services (Rita et al., 2019) so that satisfied customers buy again and introduce and recommend the store to others. In other words, online stores today must provide high-quality services to their customers to survive, keep their current customers satisfied, and attract new customers (Hult et al., 2019). Electronic services differ significantly from traditional services. Electronic services mean providing services on electronic networks such as the Internet, including services provided by service companies and manufacturing companies (Paiola et al., 2021). Online store services also differ significantly from physical stores, and various factors affect the quality of online store services (Blut, 2016). For example, how to provide information, how to send goods to customers, how to get money from customers, guarantees, and after-sales service all affect the quality of online store services (Al-dweeri et al., 2017). Website design is a critical component that can enhance the user experience and facilitate easy navigation, ultimately leading to higher customer satisfaction (Zadegan et al., 2023). Service convenience, which includes factors like the ease of finding products, simple checkout processes, and efficient customer support, also plays a vital role in shaping customer perceptions (Rane et al., 2023). On the other hand, perceived risk, which encompasses concerns about security, privacy, and the reliability of online transactions, can negatively impact customer trust and satisfaction (Jin & Lim, 2021).
Understanding these factors is essential for the success and sustainability of online stores in Iran, a rapidly growing segment of the retail market. This study investigates the effect of online store service quality antecedents—perceived risk, service convenience, and website design—on customer satisfaction and behavioral intentions. Specifically, the research aims to answer the following question: How do perceived risk, service convenience, and website design influence the quality of online store services, and in turn, how do these factors affect customer satisfaction and behavioral intentions, with satisfaction serving as a mediator? By addressing this question, the research seeks to provide valuable insights that can help online retailers improve customer retention rates, increase profitability, and foster long-term growth. This study not only contributes to the academic literature on e-commerce and service quality but also offers practical implications for online store managers and policymakers striving to enhance the online shopping experience and ensure the sustainability of online retail businesses in Iran.
Literature Review
Some experts define service quality as the consumer's comprehensive judgment of service performance compared to similar services (Park et al., 2023). In another definition, the quality of a service is determined by the degree to which the service performance matches the customer's expectations. The quality of e-services is the customer's understanding, judgment, and overall assessment of the virtual marketplace service quality. Many researchers have proposed various features and dimensions to measure the quality of electronic services. The main features of e-service quality are delivery speed, ease of use, reliability, enjoyment, and control (Nandankar et al., 2023). The quality of a website's e-services reflects the ease, efficiency, and effectiveness of product search, product purchases, and product delivery processes (Gupta et al., 2024).
Because all e-services interactions are through websites, some authors have emphasized the importance of web service quality as a prerequisite for customer satisfaction (Abesh Loui Aghdam et al., 2023; Vasić et al., 2019). The quality of website services is essential because the initial perception of customers is formed from the website's value. However, it also makes it possible to continue their current and future searches on the website. Research shows that the quality of e-services has a significant impact on the perceived value of customers, which in turn has a significant impact on customer satisfaction, repurchasing, word of mouth, and ultimately their online loyalty (Uzir et al., 2021).
Table (1) presents the results of some studies related to the present research area.
Table 1.
Research Background
Source | Research title | Results |
(Qalati et al., 2021) | Effects of perceived service quality, website quality, and reputation on purchase intention: The mediating and moderating roles of trust and perceived risk in online shopping | The study findings indicate that perceived risk moderates the relationship between trust in online shopping and purchase intention. When perceived risk is high, the relationship between trust and purchase intention becomes stronger. Trust also mediates the relationship between perceived service quality, website quality, reputation, and online purchase intention. Increasing trust can reduce the impact of perceived risk on purchase intention and foster stronger customer-company relationships. |
(Zhou et al., 2019) | Measuring e-service quality and its importance to customer satisfaction and loyalty: An empirical study in a telecom setting | The study confirmed the positive relationship between e-service quality, customer satisfaction, and loyalty. In addition, the quality of electronic services is recognized as the main predictor of customer satisfaction and loyalty. Customer satisfaction emerged as the strongest predictor of customer loyalty. |
(Vásquez & Vera-Martínez, 2020) | From e-quality and brand perceptions to repurchase: a model to explain purchase behavior in a web-store | In contrast to previous research, the findings of this study suggest product brand perception and store brand perception as a predictor of customer trust and behavioral intentions in an online store. |
(Habeeb & Sudhakar, 2019) | Analyzing Causality Among the Service Quality, Customer Satisfaction, and Behavioral Intention Variables Concerning E-Shopping: An Empirical Take | Research shows that the quality of e-services has a positive effect on e-satisfaction, which in turn affects consumer behavioral intentions, such as word of mouth, web browsing, and repurchasing. |
(Jeon & Jeong, 2017) | Customers’ perceived website service quality and its effects on e-loyalty | The findings of this study confirm that loyalty changes from cognitive (perceived service quality of the website) to emotional (customer satisfaction) to results (intention to return) and finally to the stage of action (customer loyalty). The perceived service quality of the website is a prerequisite for customer satisfaction, which leads to repurchasing intention. |
(Biswas et al., 2019) | The Influence of Website Service Quality on Customer Satisfaction Towards Online Shopping: The Mediating Role of Confirmation of Expectation | The results of the study showed that the quality of website services has a significant and positive relationship with customer satisfaction and, in turn, their satisfaction with online shopping. |
(Wali & Opara, 2012) | E-Service quality experience and customer loyalty: emphasis of the Nigeria airline operators | There is a positive correlation between website design and customer repurchase. Also, the credibility of the company's online services affects the repetition of consumer purchases. |
The present study examines the prerequisites and consequences of website services quality of online stores in Iran, which is, therefore, different from other research in which the quality of service is only used as an independent or dependent variable.
Conceptual Framework
The conceptual model of the present study is shown in Figure 1.
Figure 1. Conceptual model of research
Antecedents of online store service quality
Perceived risk: The customer's concern about the possible loss caused by online shopping is called perceived risk. Potential risks of online shopping include privacy, security, and credit card theft (Torki Biucky et al., 2017). Security and reputation of online store positively affect cognitive trust, whereas it negatively affects perceived risk (Tran & Nguyen, 2022). Online shopping risks include abusing customer information, sending the wrong shipment, sending poor-quality products, and not providing after-sales service (Das & Kunja, 2024). To evaluate the credibility of the online store and the quality of the product, the customer only has access to the information and content provided on the store's website, and unlike physical stores, it is not possible to evaluate the seller's credit and product quality closely; as a result, the perceived risk of the customer is greater than the physical store (Alcántara-Pilar et al., 2018). Risk perceived by e-customers has been identified as one of the significant barriers to online shopping. As a result, online stores are trying to reassure customers about the security of the process and reduce their perceived risk (Udo et al., 2010). The results of several studies show that perceived risk has a significant impact on customer perception of the quality of e-services as well as satisfaction (Akbari et al., 2023; Alcántara-Pilar et al., 2018).
Hypothesis 1: Perceived risk significantly impacts online store service quality.
Hypothesis 2: Perceived risk has a significant effect on customer satisfaction.
Website Design: Website design can be defined as the presentation and layout of website information and the work process (Al-Qeisi et al., 2014). This structure includes dimensions such as the quality of information, the appropriateness of the information, types of media, presentation mode, size and type of images or videos, and how the website purchase process is performed (Hasan, 2016). Also, a combination of photos, graphics, and audio and video files can be used to enhance the website design quality. Findings from some studies suggest that website design can effectively influence customer behavior, leading to behavioral intentions and continued use of the website's services (Nazari Ghazvini et al., 2023; Rita et al., 2019).
Hypothesis 3: Website design significantly impacts online store service quality.
The convenience of Internet Services: One of the most important benefits of online shopping for customers is the convenience of online shopping in terms of access at any time, the availability of information, no need to spend much time, no geographical barriers, and anonymity (Mombeuil & Uhde, 2021). Some studies show that customers often cite the convenience of online shopping as a primary reason to shop online (Duarte et al., 2018). Customer satisfaction is effectively affected by the convenience of the online marketplace. Some researchers have also found that the convenience of Internet services significantly impacts the perceived quality of services (Jebarajakirthy & Shankar, 2021).
Hypothesis 4: The convenience of Internet services significantly impacts the service quality of online stores.
Hypothesis 5: Convenience of Internet services significantly impacts customer satisfaction.
Consequences of online store service quality
Customer Satisfaction: Customer satisfaction is a sign of confidence that service will likely lead to a positive feeling (Udo et al., 2010). Customer satisfaction of online store is influenced by product delivery, perceived security, information quality, and product variety (Mofokeng, 2021). So, Customer satisfaction results from customer experience during the buying process and plays a key role in influencing future customer behaviors, such as repurchasing and loyalty. One of the essential criteria for the success of online stores is customer satisfaction. A satisfied customer will likely buy again and recommend the store to others (Meilatinova, 2021), while a dissatisfied customer leaves the online store with or without a complaint. The findings of the study show that the quality of online store services, directly and indirectly, has a positive effect on satisfaction as well as behavioral intentions, i.e., intention to repurchase, word of mouth (WOM), and revisit the store site (Gholipour Soleimani & Einolahzadeh, 2018).
Hypothesis 6: The online store service quality significantly impacts customer satisfaction.
Behavioral Intentions: Behavioral intentions can be expressed through intent to repurchase, word of mouth (WOM), loyalty, complaint behavior, and price sensitivity (Lin et al., 2022). High quality of service (understood by the customer) often leads to desirable behavioral intentions, while low quality of service leads to undesirable behavioral intentions (Hossain et al., 2023). Customer experiences are related to behavioral intentions, so the more positive the customer experience, the more likely he or she is to want to use the service again (Barari et al., 2020).
Hypothesis 7: The online store service quality significantly affects behavioral intentions.
Hypothesis 8: Customer satisfaction has a significant effect on behavioral Intentions.
Methodology
The present study is a descriptive survey study regarding the data collection method. A questionnaire was used to collect research data. Cronbach's alpha coefficient evaluates the reliability of the questionnaire, and the average extracted variance (AVE) was used to measure the validity of the questionnaire. The research model has been tested using structural equation modeling (SEM). In this study, SEM was conducted using LISREL (Linear Structural Relations). LISREL allows for the simultaneous estimation of multiple relationships, providing a robust framework to assess both the direct and indirect effects of various antecedents on customer satisfaction and behavioral intentions.
The statistical population of this study includes customers who have purchased from the online stores under study at least once in the last three months. This timeframe ensures that respondents have recent and relevant shopping experiences, allowing them to accurately recall and evaluate the content of the website and the quality of online store services. Given the widespread and continuous nature of online shopping, the number of potential customers is extremely large. Therefore, the statistical population can be considered infinite. This assumption helps in applying statistical methods that are designed for large populations, ensuring the reliability and generalizability of the findings. Selecting people with online shopping experiences in the past three months is crucial. It ensures that participants can remember and provide detailed information necessary to answer questions related to website content, service quality, and their overall shopping experience. This approach enhances the validity of the data collected, as recent shoppers are more likely to provide accurate and relevant responses. In the present study, a stratified sampling method was used. In this way, first, the list of buyers of each online store in the last quarter was received, and then, in proportion to the number of buyers of each site, electronic questionnaires were sent to users randomly. Finally, 251 questionnaires were collected, of which 245 were used for analysis. Table (2) shows some of the demographic characteristics of the research sample.
Table 2.
Demographic characteristics of the statistical sample
Variable | Dimensions | Number | Percent |
Sexuality | Female | 57 | 27.23 |
Male | 188 | 73.76 | |
Total | 245 | 100 | |
Age | 20 years and less | 13 | 31.5 |
Between 21 and 30 years | 160 | 31.65 | |
Between 31 and 40 years | 55 | 45.22 | |
Between 41 and 50 years | 12 | 9.4 | |
51 years and older | 5 | 04.2 | |
Total | 245 | 100 | |
The number of online purchases in the last three months | 1 time | 123 | 2.50 |
2 times | 49 | 20 | |
3 times | 23 | 39.9 | |
4 times and more | 50 | 41.20 | |
Total | 245 | 100 |
Questionnaire and its Validity and Reliability
The primary tool used in this study to collect data was the Standard Questionnaire, which included 27 questions. Based on previous research, a seven-point Likert scale questionnaire was developed for measuring the construct components. The questionnaire was sent by email to the respondents. Cronbach's alpha coefficient was used to evaluate the reliability of the questionnaire. The questionnaire has acceptable reliability since Cronbach's alpha coefficient calculated for all questionnaire dimensions is more than 0.7. The average variance extract was used to evaluate the validity of the questionnaire. The average extracted variance above 0.5 indicates the appropriate validity of the questionnaire. Table (3) presents the validity and reliability of the questionnaire.
Table 3.
Resources, validity, and reliability of the questionnaire
AVE | Cronbach's Alpha | Number of questions | Source | Constructs |
0.538 | 0.807 | 4 | (Al-dweeri et al., 2017) | online store Services Quality |
0.728 | 0.895 | 3 | (Alkhouli, 2017) | Satisfaction |
0.723 | 0.902 | 4 | (Yeo et al., 2017) | Behavioral Intentions |
0.580 | 0.904 | 6 | (Kamalul Ariffin et al., 2018) (Bonnin, 2020) | Perceived risk |
0.506 | 0.871 | 7 | (Rita et al., 2019) (Dianat et al., 2019) | Website Design |
0.523 | 0.764 | 3 | (Khan & Khan, 2018) | The convenience of Internet service |
Model fit test
Confirmatory factor analysis was used to determine the model's fitness, shown in table (4). A value less than 3 is acceptable for the Ratio of Chi-Square to degree of freedom, and values greater than 0.9 are desirable for GFI, CFI, NFI, and NNFI, while a value less than 0.1 for RMSEA is acceptable. The indices presented in Table 4 show that the research model is quite acceptable.
Table 4.
Model Fit indices
Index name | Value indicator | Limit | Results |
1.53 | Less than 3 | Acceptable | |
GFI | 0.98 | Above 0.9 | Acceptable |
RMSEA | 0.047 | Less than 0.9 | Acceptable |
CFI | 0.97 | Above 0.9 | Acceptable |
NFI | 0.94 | Above 0.9 | Acceptable |
NNFI | 0.91 | Above 0.9 | Acceptable |
Research findings
The correlation coefficients between the research variables are shown in Table (5), all of which were confirmed at 95% confidence level. Due to the significance of the relationship between the research variables, the research hypotheses were tested.
Table 5.
The correlation coefficient among research variables
| (1) | (2) | (3) | (4) | (5) | (6) |
1) Perceived risk | 1 |
|
|
|
|
|
2) Website Design | -0.333 | 1 |
|
|
|
|
3) Convenience of Internet service | -0.048 | 0.321 | 1 |
|
|
|
4) online store Services Quality | -0.406 | 0.792 | 0.301 | 1 |
|
|
5) Satisfaction | -0.442 | 0.638 | 0.366 | 0.743 | 1 |
|
6) Behavioral Intentions | -0.446 | 0.549 | 0.418 | 0.665 | 0.820 | 1 |
The test results of 8 research hypotheses based on the modeling of structural equations are shown in Figure (2).
Figure 2. Research model in a significant mode (T-value)
As shown in Figure (2), the first, second, third, fifth, sixth, and eighth hypotheses have been confirmed according to the value of t-statistics. Therefore, perceived risk and website design significantly impact the quality of online store services. Perceived risk, Convenience of internet service, and quality of online store service also significantly impact satisfaction. Satisfaction also has a significant effect on behavioral intent. However, the effect of the Convenience of internet service on the quality of online store services and the impact of the quality of online store services on behavioral intentions is not significant at the 95% confidence level.
Figure 3. The research model in the Estimating path coefficients
Considering the number of path coefficients shown in the relationships between the research variables in Figure (3), it can be concluded that the effect of web design on the quality of online store services, the effect of internet service convenience, and the online store services quality on satisfaction; also, the effect of satisfaction on behavioral intentions is positive. However, the impact of perceived risk on the quality of online store services and satisfaction is negative.
Table 6.
Results summary
Hypothesis | Independent V. | Dependent V. | Path coefficient | T-value | Conclusion |
|---|---|---|---|---|---|
H1 | Perceived risk | online store service quality | -0.15 | -2.96 | supported |
H2 | Perceived risk | customer satisfaction | -0.20 | -3.64 | supported |
H3 | Website design | online store service quality | 0.85 | 8.16 | supported |
H4 | Convenience of Internet services | online store service quality | 0.05 | 1.02 | Not supported |
H5 | Convenience of Internet services | customer satisfaction | 0.21 | 3.99 | supported |
H6 | online store service quality | customer satisfaction | 0.66 | 7.17 | supported |
H7 | online store service quality | behavioral Intentions | -0.08 | -0.81 | Not supported |
H8 | customer satisfaction | behavioral Intentions | 0.98 | 9.06 | supported |
Conclusions and Discussion
With the advancement of technology and the growth of competition, the distribution of products has also undergone a fundamental change. Today, online stores play an important role in selling products in all regions and countries. The most critical issue in this competitive market is the quality of services. Due to the increasing number of online stores, only those online stores can achieve appropriate profitability, which provides high-quality services to satisfy customers and turn them into loyal customers (Suhartanto et al., 2019). Therefore, the present study has examined the antecedents and consequences of online store service quality. In this regard, a questionnaire was distributed among 245 customers of online stores, and data were collected.
Based on the results of the data analysis, six hypotheses were confirmed, and two hypotheses were rejected. Website design has a positive and significant impact on the quality of online store services. Also, the Convenience of internet service and the quality of online store services have a positive and significant effect on customer satisfaction. Satisfaction also has a positive and significant effect on customer behavioral intentions. The impact of perceived risk on the quality of online store services and satisfaction was negative and significant. Nevertheless, the impact of internet service Convenience on the quality of online store services and the impact of the quality of online store services on behavioral intentions was not significant at 95% confidence.
Website design and perceived risk had a significant impact on the quality of online store services, so the impact of perceived risk on the quality of online store services was negative, and the impact of website design on the quality of online store services was positive. Therefore, to increase the quality of online store services, we should reduce the perceived risk and improve website design. Also, because of the negative impact of perceived risk and positive impact of internet service convenience on satisfaction, perceptual risk should be reduced, and convenience of internet service should be increased to enhance customer satisfaction. Finally, since satisfaction has a positive effect on the intention to buy, to increase the buying intention, customer satisfaction should be increased. However, the increase in satisfaction also depends on the factors affecting it.
The results of previous studies are contradictory regarding the impact of perceived risk on the quality of e-services. In a group of studies, the impact of perceived risk on the quality of e-services has been confirmed (Ahmad et al., 2016; Rita et al., 2019). In some studies, the hypothesis of the impact of perceived risk on e-services quality has not been confirmed (Blut et al., 2015). This discrepancy in the impact of perceived risk on the quality of e-services is probably due to differences in the community under study. Customers have sufficient confidence in online stores in developed countries where specific security standards govern online store operations. However, there have been occasional reports of customer information theft or other criminal activity in countries like Iran, where there are no strict regulatory mechanisms for online store activity. So, one of the Iranian customer's concerns is online shopping risk; therefore, online stores should take special measures to reduce customers' perceived risk. The findings of the present study regarding the positive effect of website design on the quality of e-services, the positive effect of the quality of e-services on customer satisfaction, and the positive effect of satisfaction on customer behavioral intentions are consistent with previous studies (Rita et al., 2019; Vásquez & Vera-Martínez, 2020).
While the hypothesis of the impact of Internet services convenience on the quality of e-services has been confirmed in several previous studies (Shi et al., 2018; Udo et al., 2010), in the present study, the relationship was not significant at the of %95 confidence level. This hypothesis may have been rejected because convenience is more related to the user's expertise and skills than the e-services' quality. Of course, website design is involved in the perceived convenience of internet service, but not so much as to make the impact of perceived convenience on the quality of e-services meaningful. Another hypothesis that was not confirmed in the present study was the effect of e-service quality on behavioral intentions. Although this hypothesis has been proven in many studies (Purnamasari & Suryandari, 2023; Retno et al., 2019), in this research has been rejected. The reason may be related to other factors affecting the customer's buying intention. This means that other factors, such as product price, are more important for customers with high price sensitivity; therefore, the customer pays more attention to these factors than the e-service quality when purchasing. Also, due to the demographic characteristics of the statistical sample, more than fifty percent of the respondents have bought from online stores only once in the last three months, so it could be said that a significant number of online customers in Iran only buy online to get online shopping experience and do not seriously intend to make regular purchases from online stores.
Given the above, online stores should strengthen the website design and convenience of access but weaken the perceived risk. To facilitate convenience of access, online store managers should design their websites so that the customer can go to the desired location (for example, to find a specific type of product) without any hassle. Of course, while maintaining the beautiful appearance of the website, the website should be designed in such a way that visitors can browse it easily despite the slow internet speed in Iran. For example, the website may offer similar products when a customer searches for a product. To reduce customer's perceived risk, the website should be designed to increase customer confidence in the store. For example, an online store can reduce the customer's perceived risk by posting that their money will be refunded if there are any problems with the purchase process. Alternatively, the trust of new customers can be gained by posting positive experiences from previous customers. It should be noted that although such content is necessary for e-businesses, exposing it to customers can dramatically affect their confidence.
Regarding the results of the present study, paying attention to the following items can be helpful in future research. First, the conceptual model of this research has been tested among customers of all kinds of online stores. Therefore, it is recommended that in future research, this model be considered in a specific group of online stores, for example, online bookstores or clothing stores. Second, in this study, a questionnaire was used to measure all variables, including variables related to the consequence of the quality of online store services, but the consequences can also be observed. The results of the observational study can be more valuable and valid.
References
Abesh Loui Aghdam, S., Soltanpanah, H., Mahdieh, O., Shakeri, R., & Habibi, F. (2023). Presenting a Systemic Model for the Effectiveness of Marketing Communication Activities in Social Networks. Journal of System Management, 9(2), 153-167. https://doi.org/https://doi.org/10.30495/jsm.2023.1972982.1715
Agrawal, S., & Agrawal, B. (2019). Customer delight: An antecedent of brand loyalty in online shopping. International Journal of Marketing and Technology, 9(8), 21-32. https://doi.org/https://doi.org/10.5958/2249-877x.2019.00035.3
Ahmad, A., Rahman, O., & Khan, M. N. (2016). Consumer's Perception of Website Service Quality: An Empirical Study. Journal of Internet Commerce, 15(2), 125-141. https://doi.org/https://doi.org/10.1080/15332861.2016.1144442
Akbari, M., Vashan, M. M., & Hakimpour, H. (2023). Designing a Systemic Model for Promoting the Adoption of Virtual Banking in Iran's Banking Industry. Journal of System Management, 9, 2. https://doi.org/https://doi.org/10.30495/jsm.2023.1972732.1710
Al-dweeri, R. M., Obeidat, Z. M., Al-Dwiry, M., Alshurideh, M. T., & Alhorani, A. (2017). The Impact of E-Service Quality and E-Loyalty on Online Shopping: Moderating Effect of E-Satisfaction and E-Trust. International Journal of Marketing Studies, 9, 92-103. https://doi.org/https://doi.org/10.5539/IJMS.V9N2P92
Al-Qeisi, K., Dennis, C., Alamanos, E., & Jayawardhena, C. (2014). Website design quality and usage behavior: Unified Theory of Acceptance and Use of Technology. Journal of Business Research, 67(11), 2282-2290. https://doi.org/https://doi.org/10.1016/j.jbusres.2014.06.016
Alcántara-Pilar, J. M., Blanco-Encomienda, F. J., Armenski, T., & Del Barrio-García, S. (2018). The antecedent role of online satisfaction, perceived risk online, and perceived website usability on the affect towards travel destinations. Journal of Destination Marketing & Management, 9, 20-35. https://doi.org/https://doi.org/10.1016/j.jdmm.2017.09.005
Alkhouli, S. (2017). The Effect of Banks Website Service Quality and E-satisfaction on E-loyalty: An Empirical Study on Swedish Banks. International Journal of Business and Management, 13(1), 1-1. https://doi.org/https://doi.org/10.5539/ijbm.v13n1p1
Barari, M., Ross, M., & Surachartkumtonkun, J. (2020). Negative and positive customer shopping experience in an online context. Journal of Retailing and Consumer Services, 53, 101985. https://doi.org/https://doi.org/10.1016/j.jretconser.2019.101985
Biswas, K. M., Nusari, M., & Ghosh, A. (2019). The influence of website service quality on customer satisfaction towards online shopping: The mediating role of confirmation of expectation. International Journal of Management Science and Business Administration, 5(6), 7-14. https://doi.org/https://doi.org/10.18775/ijmsba.1849-5664-5419.2014.56.1001
Blut, M. (2016). E-Service Quality: Development of a Hierarchical Model. Journal of Retailing, 92(4), 500-517. https://doi.org/https://doi.org/10.1016/j.jretai.2016.09.002
Blut, M., Chowdhry, N., Mittal, V., & Brock, C. (2015). E-Service Quality: A Meta-Analytic Review. Journal of Retailing, 91(4), 679-700. https://doi.org/https://doi.org/10.1016/j.jretai.2015.05.004
Bonnin, G. (2020). The roles of perceived risk, attractiveness of the online store and familiarity with AR in the influence of AR on patronage intention. Journal of Retailing and Consumer Services, 52, 101938. https://doi.org/https://doi.org/10.1016/j.jretconser.2019.101938
Darvish, A., Lotfizadeh, F., Hiedarzadeh, K., & Mohtaram, R. (2023). Identifying the Effective Factors of Oral Electronic Marketing on Brand Equity. Journal of System Management, 9(1), 15-36. https://doi.org/https://doi.org/10.30495/jsm.2022.1966066.1680
Das, L., & Kunja, S. R. (2024). Why do consumers return products? A qualitative exploration of online product return behaviour of young consumers. Journal of Retailing and Consumer Services, 78, 103770. https://doi.org/https://doi.org/10.1016/j.jretconser.2024.103770
Dianat, I., Adeli, P., Asgari Jafarabadi, M., & Karimi, M. A. (2019). User-centred web design, usability and user satisfaction: The case of online banking websites in Iran. Applied Ergonomics, 81, 102892. https://doi.org/https://doi.org/10.1016/j.apergo.2019.102892
Duarte, P., Costa e Silva, S., & Ferreira, M. B. (2018). How convenient is it? Delivering online shopping convenience to enhance customer satisfaction and encourage e-WOM. Journal of Retailing and Consumer Services, 44, 161-169. https://doi.org/https://doi.org/10.1016/j.jretconser.2018.06.007
Emami, L., & Namamian, F. (2018). Identify Factors Affecting the Development of Electronic Banking (using the Delphi technique). Journal of Development Evolution Management, 31(31), 131-140.
Gharibi, H., Dehdashtishahrokh, Z., & Hoseinimehr, M. (2020). The impact of brand image and brand strength on the desire to buy customers from online stores (Case study: Bamilo store). Commercial Surveys, 17(99), 52-76. https://doi.org/https://dorl.net/dor/20.1001.1.26767562.1398.17.99.3.7
Gholipour Soleimani, A., & Einolahzadeh, H. (2018). The influence of service quality on revisit intention: The mediating role of WOM and satisfaction (Case study: Guilan travel agencies). Cogent Social Sciences, 4(1), 1560651. https://doi.org/10.1080/23311886.2018.1560651
Gupta, P., Sachan, A., & Mishra, V. (2024). Perceived service process in e-service delivery system: B2C online retailers performance ranking by TOPSIS. International Journal of Services Technology and Management, 29(1), 1-17. https://doi.org/https://doi.org/10.1504/IJSTM.2024.138237
Habeeb, S., & Sudhakar, K. F. (2019). Analyzing Causality Among the Service Quality, Customer Satisfaction and Behavioral Intention Variables with Respect to E-Shopping: An Empirical Take. International Journal of Online Marketing (IJOM), 9(1), 38-59.
Hasan, B. (2016). Perceived irritation in online shopping: The impact of website design characteristics. Computers in Human Behavior, 54, 224-230. https://doi.org/https://doi.org/10.1016/j.chb.2015.07.056
Hossain, M. A., Jahan, N., & Kim, M. (2023). A multidimensional and hierarchical model of banking services and behavioral intentions of customers. International Journal of Emerging Markets, 18(4), 845-867. https://doi.org/10.1108/IJOEM-07-2020-0831
Hult, G. T. M., Sharma, P. N., Morgeson, F. V., & Zhang, Y. (2019). Antecedents and Consequences of Customer Satisfaction: Do They Differ Across Online and Offline Purchases? Journal of Retailing, 95(1), 10-23. https://doi.org/https://doi.org/10.1016/j.jretai.2018.10.003
Imankhan, N. (2018). E-Business and Startup's Performance. Quarterly Journal of Economic Modelling, 12(1), 83-105.
Jebarajakirthy, C., & Shankar, A. (2021). Impact of online convenience on mobile banking adoption intention: A moderated mediation approach. Journal of Retailing and Consumer Services, 58, 102323. https://doi.org/https://doi.org/10.1016/j.jretconser.2020.102323
Jeon, M. M., & Jeong, M. (2017). Customers’ perceived website service quality and its effects on e-loyalty. International Journal of Contemporary Hospitality Management, 29(1), 438-457. https://doi.org/https://doi.org/10.1108/IJCHM-02-2015-0054
Jin, Z., & Lim, C.-K. (2021). Structural relationships among service quality, systemic characteristics, customer trust, perceived risk, customer satisfaction and intention of continuous use in mobile payment service. Journal of System and Management Sciences, 11(2), 48-64. https://doi.org/https://doi.org/10.33168/jsms.2021.0204
Kamalul Ariffin, S., Mohan, T., & Goh, Y.-N. (2018). Influence of consumers’ perceived risk on consumers’ online purchase intention. Journal of Research in Interactive Marketing, 12(3), 309-327. https://doi.org/https://doi.org/10.1108/JRIM-11-2017-0100
Khademi, A., & Farazandeh, H. (2019). The study of effective factors on customer relationship quality in creating brand value and intention to online purchase (A study of eshop customers in Tehran). Journal of Marketing Management, 14(44), 41-59.
Khan, M. A., & Khan, S. (2018). Service convenience and post-purchase behaviour of online buyers: An empirical study. Journal of Service Science Research, 10, 167-188. https://doi.org/https://doi.org/10.1007/s12927-018-0006-x
Lin, T. T., Yeh, Y.-Q., & Hsu, S.-Y. (2022). Analysis of the Effects of Perceived Value, Price Sensitivity, Word-of-Mouth, and Customer Satisfaction on Repurchase Intentions of Safety Shoes under the Consideration of Sustainability. Sustainability, 14(24), 16546. https://doi.org/https://doi.org/10.3390/su142416546
Meilatinova, N. (2021). Social commerce: Factors affecting customer repurchase and word-of-mouth intentions. International Journal of Information Management, 57, 102300. https://doi.org/https://doi.org/10.1016/j.ijinfomgt.2020.102300
Mofokeng, T. E. (2021). The impact of online shopping attributes on customer satisfaction and loyalty: Moderating effects of e-commerce experience. Cogent Business & Management, 8(1), 1968206. https://doi.org/10.1080/23311975.2021.1968206
Mombeuil, C., & Uhde, H. (2021). Relative convenience, relative advantage, perceived security, perceived privacy, and continuous use intention of China’s WeChat Pay: A mixed-method two-phase design study. Journal of Retailing and Consumer Services, 59, 102384. https://doi.org/https://doi.org/10.1016/j.jretconser.2020.102384
Nandankar, S., Sachan, A., Mukherjee, A., & Adhikari, A. (2023). Electronic service quality (e-SQ) measurement: a cross-functional review. International Journal of Quality & Reliability Management, 40(1), 148-168. https://doi.org/https://doi.org/10.1108/IJQRM-05-2021-0153
Nazari Ghazvini, S., Vakil Alroaia, Y., & Baharon, R. B. (2023). The Study of Electroencephalography in Neuromarketing Research, Consumer Behavior and Performance Method: A Systematic Analysis. Journal of System Management, 9(4), 185-204. https://doi.org/https://doi.org/10.30495/jsm.2023.1983505.1805
Paiola, M., Schiavone, F., Grandinetti, R., & Chen, J. (2021). Digital servitization and sustainability through networking: Some evidences from IoT-based business models. Journal of Business Research, 132, 507-516. https://doi.org/https://doi.org/10.1016/j.jbusres.2021.04.047
Park, J. Y., & Thangam, D. (2019). What Makes Customers Repurchase Grocery Products from Online Stores in Korea. International Journal of E-Business Research (IJEBR), 15(4), 24-39.
Park, S.-J., Yi, Y., & Lee, Y.-R. (2023). Assessment of six alternative models of service quality. Total Quality Management & Business Excellence, 34(3-4), 364-396. https://doi.org/https://doi.org/10.1080/14783363.2022.2056440
Purnamasari, I., & Suryandari, R. T. (2023). Effect of E-Service Quality on E-Repurchase Intention in Indonesia Online Shopping: E-Satisfaction and E-Trust as Mediation Variables. European Journal of Business and Management Research, 8(1), 155-161. https://doi.org/https://doi.org/10.24018/ejbmr.2023.8.1.1766
Qalati, S. A., Vela, E. G., Li, W., Dakhan, S. A., Hong Thuy, T. T., & Merani, S. H. (2021). Effects of perceived service quality, website quality, and reputation on purchase intention: The mediating and moderating roles of trust and perceived risk in online shopping. Cogent Business & Management, 8(1), 1869363. https://doi.org/https://doi.org/10.1080/23311975.2020.1869363
Rane, N. L., Achari, A., & Choudhary, S. P. (2023). Enhancing customer loyalty through quality of service: Effective strategies to improve customer satisfaction, experience, relationship, and engagement. International Research Journal of Modernization in Engineering Technology and Science, 5(5), 427-452. https://doi.org/https://doi.org/10.56726/irjmets38104
Retno, I. D., Budi, S., & Agustina, S. (2019). ANALYSIS OF THE RELATIONSHIP BETWEEN E-SERVICE QUALITY, CUSTOMER SATISFACTION, AND CONSUMER BEHAVIORAL INTENTIONS: A CASE STUDY OF ONLINE-BASED AGRIBUSINESS COMPANIES IN MALANG CITY. Russian Journal of Agricultural and Socio-Economic Sciences, 85(1).
Rita, P., Oliveira, T., & Farisa, A. (2019). The impact of e-service quality and customer satisfaction on customer behavior in online shopping. Heliyon, 5(10), e02690. https://doi.org/https://doi.org/10.1016/j.heliyon.2019.e02690
Safari Ali Akbari, M., Manouchehri, F., & Sadeghi, H. (2018). Analysis of the use of online stores to Supply of rural products. Spatial Planning, 8(1), 89-110. https://doi.org/https://doi.org/10.22108/sppl.2018.107407.1122
Suhartanto, D., Helmi Ali, M., Tan, K. H., Sjahroeddin, F., & Kusdibyo, L. (2019). Loyalty toward online food delivery service: the role of e-service quality and food quality. Journal of Foodservice Business Research, 22(1), 81-97. https://doi.org/https://doi.org/10.1080/15378020.2018.1546076
Torki Biucky, S., Abdolvand, N., & Rajaee Harandi, S. (2017). The effects of perceived risk on social commerce adoption based on TAM model. International Journal of Electronic Commerce Studies. https://doi.org/https://doi.org/10.7903/ijecs.1538
Tran, V. D., & Nguyen, T. D. (2022). The impact of security, individuality, reputation, and consumer attitudes on purchase intention of online shopping: The evidence in Vietnam. Cogent Psychology, 9(1), 2035530. https://doi.org/10.1080/23311908.2022.2035530
Udo, G. J., Bagchi, K. K., & Kirs, P. J. (2010). An assessment of customers’e-service quality perception, satisfaction and intention. International Journal of Information Management, 30(6), 481-492.
Uzir, M. U. H., Al Halbusi, H., Thurasamy, R., Thiam Hock, R. L., Aljaberi, M. A., Hasan, N., & Hamid, M. (2021). The effects of service quality, perceived value and trust in home delivery service personnel on customer satisfaction: Evidence from a developing country. Journal of Retailing and Consumer Services, 63, 102721. https://doi.org/https://doi.org/10.1016/j.jretconser.2021.102721
Vasić, N., Kilibarda, M., & Kaurin, T. (2019). The influence of online shopping determinants on customer satisfaction in the Serbian market. Journal of theoretical and applied electronic commerce research, 14(2), 0-0.
Vásquez, F., & Vera-Martínez, y. J. (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, 15(3), 20-36. https://doi.org/https://doi.org/10.4067/S0718-18762020000300103
Wali, A. F., & Opara, B. (2012). E-Service quality experience and customer loyalty: an emphasis of the Nigeria airline operators. European Journal of Business and Social Sciences, 1(9), 118-125.
Yeo, V. C. S., Goh, S.-K., & Rezaei, S. (2017). Consumer experiences, attitude and behavioral intention toward online food delivery (OFD) services. Journal of Retailing and Consumer Services, 35, 150-162. https://doi.org/https://doi.org/10.1016/j.jretconser.2016.12.013
Zadegan, H., Aghaei, M., Esfidani, M. R., Hasangholipour, T., & Ansari, M. (2023). Designing and Explaining the Digital Marketing Model with the Approach of Customer Experience Management (CEM). Journal of System Management, 9(3), 61-76. https://doi.org/10.30495/jsm.2023.1973844.1721
Zhou, R., Wang, X., Shi, Y., Zhang, R., Zhang, L., & Guo, H. (2019). Measuring e-service quality and its importance to customer satisfaction and loyalty: an empirical study in a telecom setting. Electronic Commerce Research, 19, 477-499. https://doi.org/https://doi.org/10.1007/s10660-018-9301-3
