E-commerce websites, consumer order fulfillment and after-sales service satisfaction: The
customer is always right, even after the shopping cart check-out!
By Mark Anthony Camilleri
, University of Malta, Malta and University of Edinburgh, Scotland.
Suggested citation: Camilleri, M.A. (2021). E-commerce websites, consumer order fulfillment and after-sales service
satisfaction: The customer is always right, even after the shopping cart check-out, Journal of Strategy and
Management, 15(3), 377-396. https://doi.org/10.1108/JSMA-02-2021-0045
Purpose: This research identifies the critical factors of online service delivery of electronic commerce (e-
commerce) websites, including website attractiveness, website functionality, website security and
consumer fulfillment during an unprecedented Coronavirus (COVID-19) pandemic.
Design/methodology/approach: A structured questionnaire was used to gather data from 430 online
respondents, who were members in popular social media groups. The survey instrument relied on valid and
reliable measures relating to electronic service quality (e-SERVQUAL), to better understand the
participants’ satisfaction with shopping websites as well as their loyal behaviors and word-of mouth
Findings: The findings reported that consumers valued the e-commerce websites’ features and their
consumer order fulfillment capabilities. These factors increase the consumers’ satisfaction with online
shopping experiences, generate repeat business as well as positive reviews in social media.
Originality: This contribution posits that e-commerce websites’ ought to be appealing, functional and offer
secure transactions. More importantly, it suggests that online merchants should consistently deliver a
personalized service in all stages of an online purchase, including after the delivery of the ordered products.
Research implications / limitations: This study addresses a knowledge gap in academia. To date, little
research has focused on the consumer order fulfillment aspect of e-commerce transactions and on the after-
sales services of online businesses.
Keywords: electronic service quality, consumer fulfillment, website functionality, consumer satisfaction,
consumer loyalty, word-of-mouth.
Department of Corporate Communication, Faculty of Media and Knowledge Sciences, University of Malta, Malta. Email:
E-commerce has grown at an exponential rate during the unprecedented outbreak of the
COVID-19 (Barnes, 2020; Sheth, 2020). Many companies, including small businesses have
recognized the potential of selling their products through the Internet. COVID-19 has accelerated
the shift towards a more digital world (Sheth, 2020). It led to the expansion of e-commerce
transactions, ranging from luxury goods and services to everyday necessities. E-commerce has
increased across different product categories during the pandemic. More online users are using
digital and mobile technologies to search about products or services
They may be intrigued to
finalize their online transactions and make a purchase, if they perceive that the service quality of
the online business would meet and exceed their expectations
(Flanagin, Metzger, Pure, Markov
and Hartsell, 2014; Rajamma, Paswan and Ganesh, 2007).
WEF (2020) reported that there was a significant increase in online purchases relating to
grocery items, information and communications technologies or electronics, gardening or do-it-
yourself, pharmaceuticals, education, furniture or household as well as cosmetics or personal care
products, among other items. Several consumers from advanced and developing countries, have
also increased the frequency of their online purchases (UNCTAD, 2020). COVID-19 has shifted
consumer demand from brick-and-mortar retail to e-commerce (Barnes, 2020). The pandemic’s
preventative measures have led individuals to follow social distancing procedures and to limit their
physical interactions with other persons, to curb the spread of the contagion (Camilleri, 2021). In
a similar vein, consumers were encouraged to avoid crowded stores and to utilize the internet to
procure everyday items (OECD, 2020).
E-commerce is different from traditional shopping. Online websites can feature a wide
array of products. They are easily accessible, functional and convenient without the restrictions of
time and space (Barrera and Carrión, 2014; Chang and Wang, 2011). Typically, online users can
easily compare the attributes, features and prices of different products through their personal
computers or mobile devices. They can access a wide range of alternative products with more
competitive prices in various websites. Thus, user-friendly and responsive e-commerce websites
and online marketplaces can capture the attention of their visitors and entice them to make a
purchase. Eventually, they may re-visit these websites, if they were satisfied with their levels of
service quality (Li, Peng, Jiang and Law, 2017). Hence, e-commerce websites and online
marketplaces are expected to deliver a personalized customer service to online users (Tong, Luo
& Xu, 2020).
Many direct-to-consumer merchants are increasingly using public cloud platforms like
Amazon Personalize and PinPoint, among others, to differentiate themselves through immersive
omnichannel online experiences, to win new customers (Shopify, 2021). They are relying on the
expertise of ecommerce giants and on their machine learning capabilities to provide personalized
recommendations, to help their customers discover products, deals and promotions. Online
marketplace technologies are supporting merchants to delivering unique consumer experiences,
during and after the sales transactions (Amazon, 2021). Online merchants can minimize their
consumers’ complaints if they respond to their queries in a timely manner (Santouridis, Trivellas
and Tsimonis, 2012). For instance, they are providing more information about shipping and
delivery options of products before consumers lay down their credit card details. The automated
shipping and consumer fulfillment are becoming a competitive differentiator as consumers are
interested in brands that offer fast, reliable, and sustainable shipping options (Nguyen, de Leeuw
and Dullaert, 2018).
Although there are many empirical studies that have explored the service quality of retail
websites (Wu, Shen and Chang, 2015; Ariff, Yun, Zakuan and Ismail, 2013; Büyüközkan and
Çifçi, 2012; Akinci, Atilgan-Inan and Aksoy, 2010; Ladhari, 2009; Parasuraman, Zeithaml and
Malhotra, 2005; Santos, 2003; Zeithaml, Parasuraman and Malhotra, 2000), for the time being,
little research has focused on the consumer fulfillment aspect of e-commerce transactions, during
an extraordinary crisis like COVID-19. Therefore, this contribution builds on relevant theoretical
underpinnings that are grounded in the service-dominant logic (SDL). Its empirical research
addresses a gap in academic knowledge by investigating the effects of website attractiveness,
website functionality, website security and consumer order fulfillment on consumer satisfaction,
loyalty behaviors and word-of-mouth activities during an unprecedented pandemic situation.
The data was collected from 430 online users who were members of two popular social
media groups. A structured questionnaire was used to investigate their perceptions and attitudes
about online shopping experiences during COVID-19. This study’s objectives are threefold:
Firstly, it presents a critical review of the literature that is focused on the service quality of e-
commerce websites. Secondly, it puts forward a theoretical model that consists of measures that
were tried and tested in academia. This research reveals the validity and reliability of the proposed
research model. Thirdly, it identifies the implications of this contribution to academia and
This article is structured as follows: The following section sheds light on the conceptual
framework and formulates the hypotheses of this research. Hence, the methodology section
clarifies how the data was captured and analyzed. The results section provides an interpretation of
the findings. In conclusion, this contribution puts forward its theoretical as well as its practical
implications. It identifies its research limitations and outlines future research avenues to academia.
2. The Conceptual framework
The consumers’ re-purchase intentions construct is usually considered as the likelihood
that consumers will continue buying products from the same merchant or website (Nguyen et al.,
2018; Zeithaml, Berry and Parasuraman, 1996). The consumer loyalty in an electronic service
environment (i.e. e-loyalty) prompts online users to revisit e-commerce websites and to repeat
their purchase behaviors (Cyr, Hassanein, Head and Ivanov, 2007). Their loyalty towards
particular online marketplaces (or towards online vendors) is one of the major factors that increases
their profitability. Online consumers tend to be less loyal than consumers who purchase products
and services through brick-and-mortar settings (Rajamma et al., 2007). In anonymous and
automated shopping contexts, online users can quickly compare competing products and services
with minimal efforts (Srinivasan, Anderson and Ponnavolu, 2002). Consumers who utilize an e-
commerce website’s services are likely to find alternative sites that can also satisfy their shopping
requirements (Anderson and Srinivasan, 2003).
Consumer satisfaction is one of the fundamental concepts in the marketing literature. This
notion epitomizes the consumers’ state of fulfillment and evidences their positive or negative
feelings about the product or service they received (Evanschitzky, Iyer, Hesse and Ahlert, 2014;
Oliver, 2014; Collier and Bienstock, 2006). It is often described as a subjective judgement that is
driven from the consumers' personal feelings of pleasure or disappointment, as they compare the
purchased products’ performance (or outcome) with their expectations (Oliver, 2014; Walker,
1995). In an online context, the consumers’ satisfaction from e-commerce websites (i.e. e-
satisfaction) represents their contentment with respect to previous purchase experiences through
specific websites (Anderson and Srinivasan, 2003). The e-commerce websites most important
goals are to deliver long term value to online customers to trigger loyal behaviors. Many studies
reported that the quality of the mentioned websites and the consumers’ satisfaction levels with
respect to their prior purchase experiences can have a significant effect on their loyalty toward
electronic shopping services (Rodríguez, Villarreal, Valiño and Blozis, 2020; Nguyen et al., 2018).
The consumers’ e-satisfaction has a significant and positive impact on their e-loyalty (Castañeda,
Rodríguez and Luque, 2009). This argumentation leads to the first hypothesis:
H1: The consumers’ e-satisfaction has a positive and significant effect on their e-loyalty.
Prospective consumers are increasingly evaluating and appraising different products,
services as well as the service performance of online businesses, e-commerce websites or
marketplaces before committing themselves to making a purchase (Kemény, Simon, Nagy and
Szucs, 2016; Hennig-Thurau, Gwinner, Walsh and Gremler, 2004). Electronic word-of-mouth (e-
WOM) communications have often been described as the consumers’ positive or negative
statements, relating to their knowledge and experience about a product or service provider (Guo,
Barnes and Jia, 2017; Rossmann, Ranjan and Sugathan, 2016). Their experience is usually
disseminated to a multitude of online and mobile users through social media and consumer review
websites (Troise and Camilleri, 2021; Camilleri, 2019). The consumers’ testimonials and
recommendations can help prospective customers to make up their mind with their purchase
decisions (Park and Lee, 2009).
The advances in Web 2.0 coupled with the increased growth of social media networks have
inevitably led to more interactions from consumers, who may be intrigued to share their opinions
about their service encounters or on the products they used, with other individuals (Capriotti, Zeler
and Camilleri, 2021; Wu et al., 2015; Huang, Zhang, Liu and Liang, 2014). The e-WOM publicity
that is featured in social networking sites (SNSs) can transmit mixed brand messages to millions
of online users. Hence, the consumers’ satisfaction (or dissatisfaction) with products and services
can lead them to publish their recommendations or referrals (Rather and Camilleri, 2019). On the
other hand, their dissatisfaction with previous purchase may encourage them to voice their
negative experiences with other online users. Hence, in this case, the consumers’ intention is to
tarnish the image and reputation of the online seller or marketplace (Chu and Kim, 2011). This
leads to the following hypothesis:
H2: The consumers’ e-satisfaction has a positive and significant effect on their e-WOM.
The consumers’ satisfaction and loyalty toward an online business or marketplace is
dependent on the consistent delivery of electronic service (e-service) quality (Barrutia, Paredes
and Echebarria, 2016; Wu et al., 2015). There are several academic commentators that have
attempted to define and conceptualize the notion of e-service quality. Zeithaml, Parasuraman and
Malhotra (2002) suggested that e‐service quality is “the extent to which a website facilitates
efficient and effective shopping, purchasing, and delivery of products and services”. Santos (2003)
maintained that service quality in e-commerce involves “the consumers´ overall evaluation and
judgement of the excellence and quality of service offerings in the virtual marketplace”. Many
researchers strived in their endeavors to identify the factors that affect the consumers’ perceptions
about the service quality of websites (Büyüközkan and Çifçi, 2012).
e-Service quality is a comprehensive construct that covers both pre‐web and post‐website
service aspects. Lee and Lin (2005) argued that the consumers’ perceptions about e‐service quality
in online shopping are influenced by: website design (degree of user friendliness), reliability
(trustworthiness and security), responsiveness (courteous customer service and helpfulness), and
personalization (differentiating services to satisfy specific individual needs).
Many researchers explored the respondents’ perceptions and experience with online
retailing, price comparison sites, travel search engines, and electronic banking, among other e-
commerce websites. Several studies relied on the following measuring scales to evaluate the
service quality of websites: electronic service quality (e-SQ or e-SERVQUAL) (Wu et al., 2015;
Ariff et al., 2013; Büyüközkan and Çifçi, 2012; Ho and Lin, 2010; Ladhari, 2009; Fassnacht and
Koese, 2006; Parasuraman et al., 2005; Santos, 2003; Zeithaml et al., 2000), electronic retail
quality (eTailQ) (Wolfinbarger and Gilly, 2003).
Others developed transaction process-based approaches for capturing service quality
(eTransQual) (Bauer, Falk, and Hammerschmidt, 2006), or identified key quality factors in web
site designs (KQFs) (Cox and Dale, 2002); and developed theoretical models that are closely
related to e-SQ, including net quality (NETQual) (Bressolles and Nantel, 2008); perceived e-
service quality (PeSQ) (Cristobal, Flavian, and Guinaliu, 2007), site quality (SITEQUAL) (Yoo
and Donthu, 2001), Website Quality (webQual) (Loiacono, Watson and Goodhue, 2007; Barnes
and Vidgen, 2002) and WebQualTM (Loiacono, Watson, and Dale, 2002), among others. Figure
1 presents a list of key elements for the delivery of service quality of e-commerce websites and
electronic marketplaces, that will be explored in this empirical research.
Service Quality Factors of e-Commerce Websites and Online Marketplaces
Figure 1. Key elements for the effective delivery of service quality of e-commerce websites and online marketplaces
Ease of use
The e-service quality features, including website attractiveness, website functionality,
website security and consumer fulfillment are significant antecedents of e-satisfaction, e-loyalty
and e-WOM (Rossmann et al., 2016; Ladhari, 2009; Cristobal et al., 2007; Parasuraman et al.,
2005; Santos, 2003; Zeithaml et al., 2000).
2.3 Website attractiveness
Many researchers maintained that website designs and their presentation are important
dimensions of e-service quality (Li et al., 2017; Wakefield, Wakefield, Baker and Wang, 2011;
Yoo and Donthu, 2001). The structure, layout and organization of the web sites’ content can
capture the online and/or mobile users’ attention. Alternatively, they may lure them to visit other
competitors’ sites (King, Schilhavy, Chowa and Chin, 2016). Attractive website designs provide
easily accessible information, use large, legible fonts and may feature appropriate colors that are
coordinated with the company’s logo and corporate image. Their calls to action may usually
include high-contrast buttons, as well as clear information to enhance the online visitors’
experiences, and can facilitate their purchase transactions (Flanagin et al., 2014). Conversely, a
complicated funnel could prevent prospective customers from finalizing online transactions.
The aesthetics of attractive website designs can play a critical role in improving the
browsing experience of online visitors (Li and Yeh, 2010; Ranganathan and Ganapathy, 2002).
The appearance of corporate websites is usually the first determinant that is noticed by online and
mobile users. Of course, individuals will have different preferences. They may hold varying
attitudes and perceptions on what they consider as key elements that can increase the websites’
appeal. For instance, they may favor one color or image, over another. A specific color may be
alluring to a person, yet it may be considered inappropriate for other individuals. Website
developers may utilize certain colors to engage with online users. They may use vivid, eye‐
catching varieties, pleasant tones or complementary hues and shades. In addition, they may include
good-quality graphics, images, animations and/or multimedia features, including Java applets,
moving objects, and zooming effects, to improve their visual appeal. Generally, too many or too
little images, as well as the use of small text and images are not appropriate to captivate the
attention of the users of mobile technologies, including tablets and smartphone technologies.
Several studies reported different findings on the effects of attractive website designs on
online consumers’ behaviors. For instance, Parasuraman (2000) found that a web site’s appearance
entices online users to continue browsing through its content, and to revisit it again, whether the
actual product is appealing or not. Other researchers reported that the websites’ designs have a
positive effect on their customers’ satisfaction (Li et al., 2017; Tsang, Lai and Law, 2010;
Wolfinbarger and Gilly, 2003). This leads to the following hypothesis:
H3: Website attractiveness has a positive and significant effect on the consumers’ e-satisfaction.
2.4 Website functionality
The website’s functionality is related to its instrumental utility, technical capability and
efficiency in terms of offering relevant information about products. Online users will usually
perceive the functionality of a website if they are in a position to check out its content, with
minimal efforts (Cristobal et al., 2007; Collier and Bienstock, 2006). Hence, e-commerce websites
ought to be useful and easy to use, to satisfy their consumers’ needs for information. Online users
should find it simple and straightforward to access and to find their way through shopping web
sites. They expect to find what they need, without difficulty, and to maneuver effortlessly and
quickly, back and forth, through e-commerce pages. Prospective consumers have to be in a position
to clearly understand the ecommerce websites’ content, including their terms and conditions.
These websites ought to be reliable, concise, accurate, timely and complete (Filieri, 2015).
Their technical functionality relies on the accuracy of e-commerce services. For example,
the shopping websites’ inventory systems should always feature correct product information of all
items that are readily available in stock. Typically, online users would assess the variety and range
of products that are available in the e-commerce websites. Many online marketplaces provide
comparative information on a wide range of products during the shopping journeys of their
visitors. They also present clear pricing information in their check-out process, including the costs
of delivery (Mauri, Sainaghi and Viglia, 2019). E-commerce websites and marketplaces can offer
flexible payment methods and shipping options. In this day and age, they should provide clear
information on their returning policies. They may direct online users to frequently answered
questions, use chatbots or offer a webchat facility, if they require the assistance of customer service
(Adam, Wessel and Benlian, 2020; Nordheim, Følstad and Bjørkli, 2019).
The online users’ perceptions about the website’s functionality as well as their e-
satisfaction would probably be influenced by the breadth and depth of products that are featured
in the retailers’ websites (Nguyen et al., 2018). Hence, the website’s functionality is considered to
be one of the most important dimensions that increases the customers’ satisfaction (Adam et al.,
2020; Tsang et al., 2010). This leads to the following hypothesis:
H4: Website functionality has a positive and significant effect on the consumers’ e-satisfaction.
2.5 Website security
The website security has been defined as the degree to which online users believe that the
web page is safe and that their personal information is protected (Parasuraman et al., 2005; Santos,
2003). Consumers ought to be convinced that they are dealing with a trustworthy shopping
website. They have to be assured that the data they are sharing with the online merchants or
marketplaces, including their credit card details, cannot be accessed and used by others for
fraudulent purposes (Okazaki, Hairong and Morikazu 2009; Chang, Wang and Yang, 2009).
Online users have to feel confident that e-commerce website offer secure and safe transactions in
the virtual context (Neuburger, Beck and Egger, 2018; Cristobal et al. 2007). Thus, the notion of
website security is frequently associated with website privacy in an online service environment
(Wolfinbarger and Gilly, 2002). The absence of privacy in a website is one of the main concerns
of online users and may deter them from shopping online (Barrera and Carrión, 2014; Cristobal et
The website’s security is a vital e-service quality dimension (Parasuraman et al., 2005;
Santos, 2003). Online businesses and marketplaces are entrusted with their consumers’ personal
information. It is their responsibility to protect their consumers’ data. They may use SSL
certificates to prove that their transactions are safe and secure. This way, online users will be
reassured that ecommerce websites are trustworthy. as they are safeguarding their online details.
Previous research confirmed that consumer privacy was found to have a significant effect on
overall perceptions about e-service quality as well as on e-customer satisfaction (Barrera and
Carrión, 2014). This leads to the following hypothesis:
H5: Website security has a positive and significant effect on the consumers’ e-satisfaction.
2.6 Consumer fulfillment
Secure web sites ensure that the consumers’ personal information remain secure. However,
before providing their personal account and payment details, consumers have to choose their
desired products, add them to their shopping cart or proceed to check-out, if they are readily
available in stock (Chang et al., 2009). Nguyen et al. (2018) argued that the e-commerce websites’
failure to live up to the consumers’ order-fulfilment promises can be detrimental to their online
sales. They pointed out that out-of-stocks are negatively correlated with the consumers’ loyalty to
a business. Retailers face a trade-off between offering a wide range of product categories in their
website whilst incurring higher inventory costs, to satisfy their customers (Nguyen et al., 2018).
The e-commerce websites should provide wide product assortment, fulfill their orders correctly,
deliver items as quickly as possible and have to be as responsive as possible to consumer enquiries,
within a reasonable timeframe (Santos, 2003). They have to facilitate the fast completion of an
online transaction and should strive to minimize their consumers’ efforts. Their ongoing provision
of customer service is a key element for achieving good results in an online shop (Cristobal et al.
2007; Zeithaml et al., 2002).
Consumers are increasingly expecting a personalized service and a fast response to their
complaints (Tong et al., 2020). Very often, online users are provided with different delivery
options as well as with specific information including shipping dates, timeslots, estimated delivery
times, et cetera, prior to checking out and placing their orders. However, prospective customers
may respond in different ways to an online retailer’s customized services. They may either decide
to purchase more products. Alternatively, they could abandon their shopping cart. It they opt to
order their chosen items; they may be informed about their prospective delivery dates. Very often,
they can also trace and track their locations. The online sellers’ inadequate communications and/or
handling of contingent issues including the provision of shipping information, service breakdowns,
delays, lost orders, returns and/or refund requests may lead consumers to switch to competitor e-
commerce websites that deliver on their promises (Santouridis, Trivellas, and Reklitis, 2009;
Bauer et al., 2006; Collier and Bienstock, 2006). Most probably, they will also engage in negative
word-of-mouth publicity with other individuals. This leads to the following hypotheses:
H6: Consumer fulfillment has a positive and significant effect on e-consumer satisfaction.
H7: Consumer fulfillment has a positive and significant effect on e-consumer loyalty.
H7a: Consumer satisfaction mediates the relationship between consumer fulfillment and e-
H8: Consumer fulfillment has a positive and significant effect on e-WOM.
H8a: Consumer satisfaction mediates the relationship between consumer fulfillment and e-WOM.
Figure 2 sheds light on the research model and of the formulated hypotheses.
Figure 2. A research model representing the service quality of online shopping websites
3.1 Survey administration
The empirical data was collected through an online survey questionnaire that was
disseminated through two popular social media groups. These groups had more than 170,000
members. Their groups’ subscribers were kindly requested to take part in an academic research
that sought to explore their online shopping experiences during COVID-19. The survey
questionnaire complied with the European General Data Protection Regulation (GDPR) according
to EU 2016/679
The targeted research participants were reassured that there was no way that they
can identified. They were informed that only aggregate data was being analyzed in this study.
The respondents were expected to indicate the extent of their agreement with the survey’s
measuring items, in a five-point Likert scale. The responses ranged from 1 = “strongly disagree”
to 5 = “strongly agree”, whilst 3 signaled an indecision. In the latter part of the questionnaire, the
participants indicated their gender and age categories. They also revealed their favorite ecommerce
The survey instrument and its items were presented in a such a way to reduce the
plausibility of common method and self-selection biases. It considered the effects of the chosen
participants’ response styles, the proximity of related or unrelated constructs, and the items’
wording were simple and straightforward, according to MacKenzie and Podsakoff’s (2012)
recommendations. The survey questionnaire was pilot tested with a small group of experienced
colleagues, to identify any possible weaknesses.
3.2 The measures
The questionnaire’s measuring items were adapted from different academic sources. They
were drawn from key theoretical underpinnings relating to electronic service quality literature. The
study explored the participants’ perceptions about website attractiveness (3 items), website
functionality (3 items), website security (2 items), consumer fulfillment (3 items), consumer
satisfaction (2 items), consumer loyalty (2 items) and electronic word-of-mouth (2 items). The
measures that were used in this research are illustrated in Table 1.
Table 1. The survey questionnaire’s constructs and their corresponding items
Website Attractiveness WA1 My favorite online shopping website is visually appealing.
(King et al., 2016; Wolfinbarger
and Gilly, 2003).
WA2 I feel comfortable purchasing products through my favorite online
WA3 I enjoy purchasing products through my favorite online shopping
Website Functionality WF1 My favorite online shopping website offers a good selection of
(Kwon and Kim, 2012; Okazaki et
WF2 My favorite online shopping website provides clear information and
is well organized.
WF3 It is quick and easy to complete a transaction in my favorite online
Website Security SEC1 My favorite online shopping website offers secure online
(Chang et al., 2009; Cho, 2006;
Parasuraman et al., 2005).
SEC2 I feel safe in my transactions when I use my favorite online shopping
F1 The products I purchase from my favorite online shopping website
are always delivered on time.
(Bauer et al., 2006; Parasuraman
et al., 2005; Wolfinbarger and
Gilly, 2003; Srinivasan et al.,
F2 The return policies laid out in my favorite online shopping website
F3 My favorite online shopping website takes good care of its
SAT1 I am satisfied with the service I receive from my favorite online
(Walsh and Beatty, 2007;
Maxham and Netemeyer, 2002;
SAT2 I am satisfied with the quality of my favorite online shopping
Consumer Loyalty LOY1 I try to use my favorite online shopping website whenever I need to
make a purchase.
(Srinivasan et al., 2002;
Zeithaml, et al., 1996).
LOY2 I will continue purchasing products from my favorite retail website.
WOM1 I recommend shopping through my favorite online shopping
website to anyone who seeks my advice.
(Srinivasan et al., 2002; Zeithaml
et al., 1996).
WOM2 I encourage my friends to do business with my favorite online
3.3 The profile of the survey participants
After two weeks, there were 436 responses to the survey. The electronic questionnaires
were carefully examined and crosschecked to determine if they had incomplete responses. There
were six questionnaires that were not included in the analysis as they had missing values. Hence,
the research sample of this study consisted of 430 valid responses. The frequency table reported
that there were three hundred thirty-five females (n=335) and ninety-five males (n=95) who
participated in this study. The respondents were classified into five age groups (18-28; 29-39; 40-
50; 51-61 and over 62 years of age). Most of the research participants were between 29 and 39
years of age (n=152), followed by those between 40 and 50 years of age (n=97).
4. Data analysis
4.1 The descriptive statistics
Generally, the respondents suggested that they agreed with the survey items as there were
high mean scores above the midpoint (3). The highest scores were reported for SEC1 (M=4.407),
WA2 (M=4.337) and SEC2 (M=4.302). Whilst WOM2 reported the lowest mean score (M=3.756).
The SD indicated that there were small variances in the participants’ responses, thereby indicating
a very narrow spread around the mean. The values of the SD varied from 0.641 (for SAT2) to
0.962 (for LOY1).
4.2 Confirmatory composite analysis
A structural equation modelling partial least squares (SEM-PLS 3.3), confirmatory
composite analysis (CCA) was utilized to evaluate the measurement quality of the proposed
research model (Ringle, Wende and Becker, 2014). Its PLS algorithm revealed the results of the
reflective measurement model (Hair, Howard, Nitzl, 2020). Most of the standardized loadings
reported values that were higher than the recommended threshold of 0.7 (Hair et al., 2020), except
Table 2 sheds light on the outer loadings. It also indicates the results of the reliability and
validity of this model. The CR values were between 0.808 and 0.972. The values of average
variance extracted (AVE) confirmed convergent validity as each construct explained more than 50
per cent of the variance of its items. In other words, the values for AVE were higher than 0.5.
There was evidence of discriminant validity as the square root value of AVE was greater than the
correlation values among the latent variables (Fornell and Larcker, 1981). This study also
examined heterotrait-monotrait (HTMT) ratio of the correlations to re-confirm the presence of
discriminant validity. There was evidence of discriminant validity where the figures were lower
than 0.9 threshold (Henseler, Ringle and Sarstedt, 2015).
Table 2. An assessment of the composite reliability, convergent validity and discriminant validities
Construct Items Outer Loadings
CR AVE 1 2 3 4 5 6 7
1 Consumer Fulfillment
0.946 0.659 0.806 0.4 0.663 CF2 0.8 0.647 0.808
2 Consumer Loyalty LOY1 0.947 0.868 0.876 0.938
0.56 0.94 0.779 0.552 0.542 0.335 0.782
3 Consumer Satisfaction SAT1 0.908 0.802 0.804 0.91 0.835
0.914 0.768 0.895 0.576 0.744
4 Website Attractiveness
0.847 0.857 0.907
0.516 0.48 0.638 0.875
0.926 0.697 0.579 WA2 0.904
5 Website Functionality
0.796 0.796 0.88 0.711
0.716 0.763 0.843 0.703 0.494 WF2 0.858
6 Website Security SEC1 0.972 0.942 0.942 0.972
0.502 0.628 0.609 0.972 0.408
7 Word-of-Mouth WOM1
0.926 0.816 0.82 0.915
0.604 0.492 0.401 0.36 0.919
Note: The Fornell-Larcker criterion was used to calculate the discriminant validity. The levels of square root of AVE for each construct were greater than the correlation involving
the other constructs in the same column. The shaded area features the results of Heterotrait-Monotrait Ratio (HTMT).
4.3 Structural model assessment
The results indicated that there were no collinearity issues as the variance inflation factors
(VIFs) were lower than the recommended threshold of 3.3 (Hair et al., 2020). The PLS algorithm
revealed the model’s predictive power, in terms of the coefficient of determination (R
) of the
endogenous latent variables. A bootstrapping procedure was used to explore the statistical
significance and relevance of the path coefficients. It indicated that the relationships’ t-statistic
were well above ±1.96. These values were significant for a two-tailed test at the 5% level (Hair,
Ringle and Sarstedt, 2011). Table 3 reveals the results of the hypotheses of this study. It tabulates
the findings of the standardized beta coefficients (original sample), the confidence intervals, t-
values and the significance values (p). Table 4 summarizes the results of the mediation analysis.
Table 3. Testing of the Hypotheses
Path Coefficient Original Confidence t-
value p Outcome
e-Satisfaction -> e-Loyalty 0.511 [0.417, 0.609] 10.22
e-Satisfaction -> e-WOM 0.486 [0.393, 0.596] 9.785
Website Attractiveness -> e-Satisfaction 0.117 [0.032, 0.211] 2.536
Website Functionality -> e-Satisfaction 0.323 [0.229, 0.427] 6.261
Website Security -> e-Satisfaction 0.1 [0.013, 0.235] 1.805
Consumer Fulfillment -> e-Satisfaction 0.411 [0.331, 0.492] 9.924
Consumer Fulfillment -> e-Loyalty 0.205 [0.100, 0.311] 3.865
Consumer Fulfillment -> e-WOM 0.171 [0.012, 0.275] 2.7
Note: Critical values are t < 1.96; *** p < 0.01; ** p < 0.05.
Table 4. The mediation analysis
Direct Indirect p Total Confidence t-value p Outcome
Effect Effect 1 Effect Intervals
H7 Consumer Fulfillment -> e-Loyalty 0.205 0.000
Consumer Fulfillment -> e-Satisfaction -> e-
0.21 0.000 [0.159,
H7 Consumer Fulfillment -> e-WOM 0.171 0.007
Consumer Fulfillment -> e- Satisfaction -> e-
WOM 0.2 0.000 [0.147,0.263] 6.693 0.000
Note: *** p < 0.001
SmartPLS 3.3 illustrates the results of the PLS algorithm as it features the direct,
indirect and total effects among the constructs. Figure 3 depicts the explanatory power of this
research model. It sheds light on the total effects, outer loadings and on the coefficients of
determination (R squared) values of the constructs.
Figure 3. A graphical illustration of the results
The findings from this research model revealed that the constructs that were used in this
study predicted 64.1% of e-satisfaction, 44.9% of e-loyalty and 38% of e-WOM.
H1: This study reported that there was a positive and highly significant effect between e-
consumer satisfaction and e-loyalty, where β=0.511, t=10.22, and p<0.001. H2 indicated that e-
satisfaction was also a very significant antecedent of e-WOM, where β=0.486, t=9.785, and
p<0.001. H3 revealed that the websites’ attractiveness was a significant antecedent of e-
satisfaction, where β=0.117, t=2.536, and p<0.05.
H4: The websites’ functionality was a very significant precursor of e-satisfaction, where
β = 0.323, t=6.261 and p<0.001. H5 was not supported. Website security had a negligible effect
on e-satisfaction, as β = 0.1, t=1.805 and p<0.1. H6: There was a very significant relationship
between consumer fulfillment and e-satisfaction, where β = 0.441, t=9.924 and p<0.001. Similarly,
the results from H7 have shown that consumer fulfillment was a very significant antecedent of e-
loyalty, where β=0.205, t=3.865 and p<0.001. H8: The consumer fulfillment was also found to be
a direct antecedent of e-WOM, where β = 0.171, t=2.7 and p<0.05. In addition, the mediation
analysis revealed that e-satisfaction partially mediated the consumer fulfillment -> e-loyalty as
well as consumer fulfillment -> e-WOM causal paths.
5. Discussion and conclusions
5.1 Theoretical implications
This research confirmed that the consumers’ satisfaction with e-commerce websites has a
significant effect on their loyalty as well as on their electronic word-of-mouth publicity. This is an
important finding, considering that there are several shopping websites and online marketplaces
where consumers can find identical or alternative products (Guo et al., 2017; Barrutia et al., 2016;
Anderson and Srinivasan, 2003).
In this case, the respondents suggested that e-commerce websites delivered good value to
them and that they triggered their loyal behaviors. The research participants indicated that they
were satisfied with the quality of the shopping websites and with their electronic services. Other
research also reported similar results. Rodríguez et al. (2020) found that the service quality of
online vendors as well as the consumers’ satisfaction from their electronic shopping experiences
may lead to repeat purchases from e-commerce websites. This study showed that the customers
were intrigued to share their positive or negative experiences with products and/or services with
other online users. Hence, they were willing to cocreate online content for the benefit of
prospective consumers (Devereux and Gallarza, 2019; Kemény, 2016; Hennig-Thurau et al.,
Many customers are increasingly voicing their opinions and recommendations through
qualitative reviews and/or quantitative ratings to support other individuals in their purchase
decisions (Guo et al., 2017; Wu et al., 2015; Huang et al., 2014; Park and Lee, 2009). They may
either encourage or discourage others from shopping from a particular vendor and/or website. This
research confirmed that the online users’ satisfaction levels with the service quality of the e-
commerce website relied on different factors, including website attractiveness, functionality and
security as well as on consumer order fulfillment, during and after a purchase.
The websites’ designs and layouts can capture their visitors’ attention and may possibly
improve the online consumers’ experiences during their purchase transactions. The e-commerce
websites’ appearance and their functionality may entice online users to continue browsing through
their content and to revisit them again, in the future (Tsang et al., 2010). Online users would be
satisfied if the e-commerce websites are informative, useful and easy to use. They utilize shopping
websites to access relevant content on the attributes and features of products, including consumer
reviews (Mellinas and Reino, 2019). Therefore, the technical functionality of these websites’
inventory systems should feature accurate and timely information on the availability of items as
well as on their prices and costs of delivery. In this day and age, they should provide approximate
shipping dates, estimated delivery times, et cetera. The online sellers should also establish clear
information on their returning policies. They may direct online users and past consumers to
frequently answered questions, and/or to chatbots. Alternatively, they may offer webchat facilities
to engage with their valued customers, in real time (Adam et al., 2020; Nordheim et al., 2019).
Although there are many studies that have explored the service quality of e-commerce
websites during a purchase transaction, only a few of them have focused on consumer fulfillment
(and on their after-sales services). The findings from this research reported that timely deliveries,
and the provision of personalized services have a highly significant effect on consumer satisfaction
and loyalty. Nguyen et al. (2018) contended that service providers ought to meet and exceed their
customers’ expectations in different stages of their order fulfilment in online retailing contexts.
The authors contended that online sellers ought to deliver the ordered items as expeditiously as
possible, to improve their service quality. Other authors, including Santos (2003) and Parasuraman
et al. (2005), among others, argued that online retailers should respond to consumer enquiries, in
a timely manner. This way, they can increase consumer satisfaction, minimize complaints and
reduce the likelihood of negative criticism (and damaging e-WOM) in review websites and social
5.2 Implications to practitioners
The outbreak of COVID-19 and its preventative measures have led several businesses and
consumers to change their shopping behaviors. Many individuals have inevitably reduced their
human-to-human interactions in physical service environments and were increasingly relying on
the adoption of digital media and mobile devices, including smart phones and tablets for their
shopping requirements (Camilleri and Falzon, 2020). Consumers as well as businesses are
benefiting of faster connections as the loading speeds of these devices is one of the critical
determining factors as to whether visitors may (or may not) be willing to browse through e-
commerce websites or apps, to proceed to check out, and to lay down their credit cards.
Advances in technological capabilities have improved the consumers’ online shopping
experiences. More businesses are benefiting from the expertise of online marketplaces to deliver
personalized services to their customers. For instance, Amazon provides product recommendations
to its visitors, that are based on their previous searches (Shopify, 2021). Ecommerce giants utilize
machine learning technologies to segment consumers by geographical location, age and gender,
buying habits, total expenditure, and more (Camilleri, 2018). They capture data from online users,
including their browsing and purchase histories. They distinguish between profitable, loyal
customers, price-sensitive customers, and identify those who are likely to abandon their shopping
Prospective consumers will usually compare a wide variety of products and their
corresponding prices, in different virtual marketplaces, before making their purchase decision.
They will probably check out the consumer reviews to confirm the reputation and trustworthiness
of online merchants. At times, they will not be in a position to confirm the legitimacy of certain
websites and to determine if it is safe to disclose their payment details to anonymous vendors. A
few websites may require consumers to join their mailing list. They may expect them to provide
their email addresses, that they may share with third parties. As a result, consumers could receive
unwanted ads and scams in their inboxes. Moreover, they may experience phishing and spoofing.
Therefore, shopping web pages should use SSL certificates to prove that their transactions are safe
and secure. Furthermore, e-commerce websites ought to feature accurate, timely and reliable
content. They have to be as transparent as possible with online users. They should clarify their
terms and conditions as well as their refund policies.
The smallest thing that’s out of place in their e-commerce pages could rapidly erode the
customers’ trust in their products and services. Online users cannot inspect (or try) their chosen
products until they receive them. They may experience delays in the delivery of their shopping
items, particularly, if they get lost, detoured or delivered in the wrong address. Once they receive
the product they ordered, they may decide to return it, if for some reason they are not satisfied by
its quality. In this case, they could (or could not) be reimbursed for incurring shipping and
packaging costs. Shopping websites are increasingly offering synchronous communications
facilities to enhance their personalized services through web chat facilities that enable
instantaneous conversations with online users. This development has significantly improved the
consumers’ perceptions about the service quality of e-commerce websites and their satisfaction
levels. They also increased the chances of their repeat purchases.
In sum, this contribution suggests that online businesses and marketplaces should identify
the critical success factors that are differentiating e-commerce websites from one another. The
most popular online marketplaces are capable of attracting repeat consumers through a consistent
delivery of personalized customer service, thereby increasing their sales potential and growth
5.3 Limitations and future research
This research has used the constructs that were tried and tested in academia to identify
significant antecedents of consumer satisfaction, loyalty and e-WOM. The findings reported that
the websites’ functionality as well as the consumers’ fulfillment during and after the sales
transactions, were the most significant antecedents of consumer satisfaction of e-commerce
website during COVID-19. Therefore, this contribution puts forward research avenues to
academia. In future, researchers can replicate this study to validate this contribution’s conceptual
model, in different contexts.
Other methodologies and sampling frames can be used to capture and analyze the data.
Perhaps, inductive studies may investigate the online users’ in-depth opinions and beliefs on their
shopping experiences. Interpretative studies can reveal important insights on what can be improved
in e-commerce websites’ content and/or in the provision of their online services.
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