Heliyon 6 (2020) e05710
Contents lists available at ScienceDirect
Heliyon
journal homepage: www.cell.com/heliyon
Research article
Does quality stimulate customer satisfaction where perceived value
mediates and the usage of social media moderates?
Md. Uzir Hossain Uzir a, *, Ishraq Jerin a, Hussam Al Halbusi b, Abu Bakar Abdul Hamid a, **,
Ahmad Shaharudin Abdul Latiff a
a
b
Putra Business School (PBS), Universiti Putra Malaysia (UPM), 43400, Seri Kembangan, Selangor, Malaysia
Department of Management, College of Economics and Political Science, Sultan Qaboos University, P.O. Box 20, Al Khoud 123, Oman
A R T I C L E I N F O
A B S T R A C T
Keywords:
Customer satisfaction
Social media usage
Customer perceived value
Quality of service
SEM-AMOS
Electronic home appliances
Moderated mediation
Bangladesh
Tourism
Information science
Business
Technology management
Management
Marketing
Consumer attitude
Research and development
Psychology
Customer is considered as the king in the world of business. The issue of customer satisfaction in electronics home
appliances has received greater attention from academics and practitioners. In other words, customer satisfaction
is a vital consideration in marketing. With the development of technology, new and innovative electronic home
appliances are available in the market. Customers purchase and use the costly electronic home appliances where
the satisfaction issue is an important concern. In Bangladesh, working families find the electronic home appliance
very necessary. Companies offer state-of- the-art appliances for customers' household works. Therefore, the study
intends to investigate the effect of product quality (PQ), quality of service (SQ) and perceived value on customer
satisfaction (CS). In addition, this study also seeks this relationship shaped by customer's perceived value (CPV) as
a key mechanism and interacted by social media usage. A total of 300 households were selected on a judgmental
basis from Dhaka city in Bangladesh using a structured questionnaire. Collected data were CB-SEM (AMOS-v24)
and SPSS. The findings showed PQ and SQ have positive effects on CS; SQ affects, but PQ does not affect CPV. CPV
has a mixing mediating effect on SQ and CS relationship and PQ and CS relationship. Importantly, the positive
impact of PQ, SQ and CPV is greater on customers who exhibit higher social media use. The conceptual framework
was buttressed by EDT theory. The study contributed to contextual and theoretical knowledge in regards to home
appliances. The practicing managers can collect an insight of customer satisfaction for their business.
1. Introduction
Marshall, the famous and pioneer retailer, introduced the motto
“Right or wrong, the customer is always right”. This motto indicates
customer satisfaction. On the other hand, the concept caveat emptor (let
the buyer beware) ignored customer attitude and their importance
earlier stage in marketing (Jackson, 2017; McBain, 1944). Gradually
some scholars identify the importance of customers. Fazal and Kanwal
(2017) mentioned that customers are the nucleus of every successful
company. Customer satisfaction is an aspect of psychological attitude or
mood of customers, and a firm necessarily focuses this emotional state
(Feng et al., 2019; O’Dwyer and Gilmore, 2018). Due to technological
development, human life has become faster (McArthur, 2016), social
needs and wants change, and the nature of their satisfaction alters.
Similarly, marketing environment has changed (Kotler, 2017) and
businesses are facing a tough challenge to ensure customer value
(Shamsudin et al., 2018b) and their satisfaction (Hassan and Shamsudin,
2019).
Electronic appliances, especially home appliances like air conditioner, coffee maker, crockeries, dishwasher, fan, fridge, geyser, iron,
kitchen accessories, lighting bulbs, micro oven, oven, pressure cooker,
rice cooker, sewing machine, television, washing machine, water heater,
etc. have made human lives easier (McArthur, 2016). These home appliances or consumer durables last for a long period, and additional
service or replacement are required (Lobo, 2016). One report from Statista (2020a) shows that total revenue for electronics home appliances in
2020 globally would be US$121.16 billion with user penetration of
13.60%. This report also forecasted that with the growth rate of 6.10%,
the projected market volume will be US$153.51 billion in 2024 and new
user penetration of 23.90%. Every user will spend an average amount to
* Corresponding author.
** Corresponding author.
E-mail addresses: mduzir.phd_mkt18@grad.putrabs.edu.my (Md.U.H. Uzir), abu.bakar@putrabs.edu.my (A.B.A. Hamid).
https://doi.org/10.1016/j.heliyon.2020.e05710
Received 24 December 2019; Received in revised form 6 June 2020; Accepted 9 December 2020
2405-8440/© 2020 Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
Md.U.H. Uzir et al.
Heliyon 6 (2020) e05710
groups to purchase same or similar products from the same brand (Belwal
and Amireh, 2018; Ghazzawi and Alharbi, 2019; Herhausen et al., 2019)
and contribute to higher sales and business profit (Razak and Shamsudin,
2019; Uddin, 2013). According to Morra et al. (2018), social media
generates an impact on their reviews about the brand, on their satisfaction level, and their perception. Before purchasing electronics items, a
customer considers the reviews by others, word of mouth, family and
friend’s recommendations and suggestions. By the grace of social media,
customer can easily find valuable opinion, advice and reviews. In
contrast, social media, in the absence of systematic effort, leads the
spread of misinformation (Webb et al., 2016) and can cause chaos in
society (Lukasik et al., 2019). On average, a person shares a good experience with nine others. In comparison, s/he shares a poor experience
with 16 people (American Express Survey); unhappy consumers share
their poor experience with 11 people (The Sydney Entrepreneur Centre),
and a dissatisfied customer tells 9–15 people, and 13% customers share
more than 20 persons (While House Office of Consumers Affairs). In
social media, this trend increases. In many events related shopping,
women are the decision-makers or purchasers. Due to their interaction in
social media regarding purchasing these electronics home appliances,
they count others’ observation, experiences and recommendation.
The home electronics market has been digitalized, and everincreasing and customer interaction in social media has been
enhanced. Begum and Zami (2018) stated that some risks prevail in logistic support, price and after-sale services. A report shows that in some
cases, customers complaints are not entertained as promised. Product
quality of household items is found lower, and after-sale services
(repairing, replacement, or servicing) sometimes are dilly-dallying. As a
result, customers are found unhappy and dissatisfied with appliances and
companies. Beside, HofstedeInsights (2020) illustrates that Bangladeshi
society upholds rigid codes of belief and behaviour (Uncertainty Avoidance Index-UAI) and in long term orientation index (LTOI). In this
emerging market in Bangladesh, therefore, customer satisfaction needs to
be improved, and customer complaints need to be quickly entertained.
Academicians or market researchers did not emphasize this crucial issue
very much. To best of their knowledge, the authors of this research could
not find much relevant literature. According to Lobo (2016), very few
literature is available on customer satisfaction on physical product like
electronic home appliances. Thus, this study focuses on this important
issue to fill up the literature gap which will also implicate in the present
market growth. Consequently, the research gap of this study has been
conceptualized in the following questions: i) whether the perceived
quality of electronics home appliances satisfy the customers and users in
Bangladesh where high demand for these home appliances exist; ii)
whether customer perceived value (cost-benefit comparison) strengthens
the perceived quality and satisfaction relationship; and iii) whether the
role of social media usage (the information used, shared, or commented)
fluctuates the perceived quality and satisfaction relationship because
customers are using social media rampantly and are being influenced by
the information therein while buying and using electronics home
appliances.
The authors examined the relationship of customer satisfaction with
its antecedents such as product quality, quality of installation service and
after-sale service, their value about the brand and product, and how
social media affects the buying decisions based on the recommendation
of family members, friends and other customers’ reviews and comments
therein. Gerdt et al. (2019); Hirata (2019); Kim et al. (2019) illustrated
the significance of customer satisfaction as a vital role in a business organization. A quality product, better customer service, and image of the
company satisfy the customer (Shamsudin et al., 2019a). Previous studies
demonstrate that customer satisfaction influences a business firm, that is,
a happy and delighted customer will repurchase and repeated purchase
with a bulk amount (Gerdt et al., 2019). The satisfied customer even is
ready to pay more (Shamsudin et al., 2019b) and is ready to advertise to
have more customers by suggesting company’s products (Shamsudin et
al., 2015b). A satisfied customer invites their family members, friends
US$119.99. The Chinese users will spend the most amount compared to
the other global users. Another report has forecasted that global home
appliances will increase at 8.00% compound annual growth rate in 2025
(ReportLinker, 2020). Similarly, MarketWatch (2020) reported on
August 13, 2020, that global home appliance market would grow to US$
837.00 billion in 2024 at a compound annual growth rate of 5.30 from
US$ 615.00 billion in 2020. The top major global brand of home appliances are Haier, Whirlpool, Electrolux, GREE Electronics, BSH Bosch &
Siemens.
Similarly, the Bangladeshi household appliance market has been
expanding rapidly to meet the increasing demand. In Bangladesh, which
is the 8th lar-gest population in the world, the annual expenditure is
above USD 130.00 billion with a growth rate of 6% per annum. According to a study, BGD (2015) assumed that the middle and affluent
class would be around 34 million by 2025 who would use those appliances for a long time (Begum and Zami, 2018). The national poverty line
dropped from 14.8% in 2016 to 9.2% in 2019 (ADB, 2020), which indicates an increase in consumers’ purchasing capacity. Home electronic
appliances are mostly purchased and used by this large group of people.
According to a report of DataBD (2020), electronic market size is of US$
1.37 billion in Bangladesh (particularly, television: USD 414.22 million,
refrigerators: USD 549.11 million, air conditioner: USD 164.57 million
and other appliances: USD 251.41 million). Among various electronic
categories, refrigerator occupies 40%, and television covers 30% market
size. In the television product category, local brands such as Rangs,
Walton, Vision, Singer, MyOne are occupying the market. In contrast,
international brands such as Sony, Samsung, Panasonic, Toshiba, Phillips, LG, Sanyo are meeting the customers’ needs. Similarly, Walton,
MyOne, Minister brands are providing refrigerators goods as a local
brand, wherein Samsung, Whirlpool, Kelvinator, LG, Hitachi, Hier, etc.
are competing with local brands. Butterfly and Walton (local brands) and
General, LG, Daikin, GREE, Carrier, Whirlpool, etc. (foreign) meet AC
demand. Besides, other home appliances are getting available at customers’ doorsteps by both local brands like Walton, Electra, Singer, Ecoþ
and international brands (Miyako, Sebec, Panasonic, Sharp, SteamFast,
etc.) (DataBD, 2020).
In this changing twenty-first-century business environment, the need
for research on product quality, customer attitude, innovation has poised
an inevitable strategy of a business organization to meet and satisfy the
multiple role holding consumers (Lau et al., 2019; Moghavvemi et al.,
2018; Quang et al., 2018). Besides, customers’ interaction in technology
and social media have made this challenge more challenging (Hamzah
and Shamsudin, 2020). This competition enables companies to offer
better products at a reasonable price (Balakrishnan et al., 2013).
A report indicates that the number of social media is increasing with
its users in Bangladesh. The recent data shows around 40.70 million users
as of March 2020. Among them, a total of 37.91 million (93.28%) are
using Facebook; messenger users are 11.28 million (27.52%), and 1.35
(3.31%) million are YouTube users. Similarly, Pinterest users (0.51 mil.,
1.24%), Twitter (0.10 mil., 0.98%), Instagram (2.28mil., 5.6%), Reddit
(0.05 mil., 0.11%), Tumblr (0.04 mil.,0.1%), LinkedIn (a professional
social media) (3.33 mil., 8.18%), VKontakte (0.04 mil.,0.09%) and others
(0.98 mil., 0.24%) are using social media (NapoleonCat, 2020). Thus,
social media is a large platform for interacting with each other. According to a newspaper report, 94% of total users have access to social
media through mobile phone devices (Report, 2018). This report also
stated that female users are around 24% of total users. Social media like
Facebook, WhatsApp, Instagram, Pinterest affect customer references,
usage experience, and recommendation on customer behaviour. In views
of Schwartz-Chassidim et al. (2020), people use Facebook as a social
media and social network for sharing messages, comments and
recommendation.
Consumers-interchangeably used as customers (Shamsudin et al.,
2018b) as a human being are accustomed to what others do (Feng et al.,
2019; Gligor et al., 2019; Hamzah et al., 2016). A loyal customer influences others such as family members, friends, relatives, and peer
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(1999); Ruyter and Bloemer (1999); Mittal and Kamakura (2001) and
Szymanski and Henard (2001). Over the period, the customer satisfaction
concept has received attention. Many researchers, academics, and
scholars have addressed customer satisfaction to cope with the characteristics of customers in present time. Among them, Ulaga and Eggert
(2006); Fornell et al. (2010); Kaura et al. (2015); Ayo et al. (2016);
Cheung and To (2016); Kant and Jaiswal (2017); Mannan et al. (2017);
Marinkovic and Kalinic (2017); Oh and Kim (2017); Sampaio et al.
(2017); Tandon et al. (2017); Keshavarz and Jamshidi (2018); Moorthy
et al. (2018); Thielemann et al. (2018) and Tseng (2019) are remarkable
in recent years.
and peer groups. But a dissatisfied customer shares their dissatisfaction
or discomfort in social media (Hassan and Shamsudin, 2019; Shamsudin
et al., 2015a, 2015b). Zhang et al. (2019) warned that this negative
message in social media might cause a risk for the organization of losing
prospective customers.
This study underpinned the expectancy disconfirmation theory (EDT)
developed by Oliver (1980) to investigate customer satisfaction. This
theory explains that customers compare the actual experience of using
products and services with expectations about those products. If the
actual experience is below the expectations, they will be dissatisfied.
Instead, if the actual experience supersedes the expectation, customers
will be delighted (Skogland and Siguaw, 2004). This net difference is
either satisfaction, dissatisfaction or neutral (Yi, 1990). Customer satisfaction depends on this comparison outcome.
Consequently, this current study tries to cover the gaps in the theories, literature, as well as in the practical and industrial issues by
initiating-how customer satisfaction interacts the effect of social media
usage in the context of electronics household items (Lobo, 2016) in
Bangladesh. Understanding the customers’ perception and its determinants will assist brand managers, marketing managers, retail
showroom businesses in creating and upholding an appropriate
competitive strategy.
The current study tried to maintain the flow of the review of literature, development of research hypotheses and conceptual framework,
research methodology, data analysis, results, and discussions; finally,
conclusion, contribution, implications, limitations and future directions
for the study in the following sections respectively.
2.2. Product quality (PQ)
According to Tseng (2019), customer satisfaction is very vital to the
success of a company; it is also crucial to identify those influential factors.
Research on customer satisfaction has not ended yet, and researchers and
scholars are making a relentless effort to examine the effect of antecedents and consequence of customer satisfaction. Researchers still are
suggesting to conduct more research on this area (Evanschitzky et al.,
2012).
The product provides consumers with functional benefits (Hankinson
and Cowking, 1996) by which a customer fill their needs. The features
and characteristics of a product or service reflect product quality.
Therefore, product quality means “fitness for use” or ‘conformance to
requirement” (Russell and Taylor, 2006). Besides, the International Organization for Standardization (ISO) defines product quality “as the
ability to satisfy the customer and market” (Lakhal and Pasin, 2008).
However, the term quality has eight dimensions: performance, features,
reliability, conformance, durability, serviceability, aesthetics and
perceived quality (Garvin, 1984). Some scholars have defined product
quality in two ways-perceived and objective, and in this study, perceived
product quality was adopted.
Product quality concept was used in different research fields. Previously, Aaker (1991); (1996); Cronin and Taylor (1992); Parasuraman et
al. (1996); Rao and Monroe (1989); Sweeney et al. (1999); Taylor and
Baker (1994) and Zeithaml (1988) used this construct in their works.
Later on, Brunsø et al. (2005) and Russell and Taylor (2006) also tested
product quality for customer satisfaction. Over the time, the quality of a
physical product was prioritized in the research of Calantone and Knight
(2000); Cho and Pucik (2005); Forker et al. (1996); Martínez-Costa et al.
(2009); Molina-Castillo et al. (2013); Morgan and Vorhies (2001) and
Prajogo and Sohal (2004). Very recently, Kotler and Armstrong (2018);
Lin et al. (2018) and G€
ok et al. (2019) also studied product quality.
2.1. Customer satisfaction (CS)
2.3. Quality of service (SQ)
Satisfaction also refers to the “perceived discrepancy between prior
expectation and perceived performance after consumption; performance
differs from expectation, dissatisfaction occurs” (Oliver, 1980). Kondou
(1999) defines “customer satisfaction as a person’s subjective evaluation
of his or her situation results in a positive emotional response.” Consumer
satisfaction is a “condition in which consumer expectations would be met
by a product” (Kotler and Armstrong, 1999). Customer satisfaction is a
psychological response of customers to their positive evaluative consumption outcome (real experience) about their expectations (perception) (Shukla, 2004). According to Chitty et al. (2007), customer
satisfaction is a psychological assessment and a constructive comparison
between the sacrifice they make by paying (cost) for availing services and
products and benefits they receive from the moment of purchase to
product life cycle or end of consuming. If real experience (interest) is
higher than the perceived expectation (cost/sacrifice), customers become
satisfied. Otherwise, they are dissatisfied (Oliver, 1980).
Satisfaction is a trade-off of pre and post-consumption or usage of a
product (Shamsudin et al., 2018a). Customer satisfaction is thus essential
to meeting the various needs of customers and firms (Yi and Nataraajan,
2018). The pursuit of customer satisfaction has become a strategic
imperative for most firms that need to sustain and remain competitive (Yi
and Nataraajan, 2018).
Realizing this importance of customer satisfaction, many scholars
attempted to conceptualise and formulate this constructs like- Fornell
and Wernerfelt (1988); Anderson and Sullivan (1993); Halstead et al.
(1994); Fornell et al. (1996); Oliver (1997); Kotler (1997); Boshoff
This study used quality of service to mean the service that a company
provides during the purchase and installation of a product (electronic
items) and after-sale service (warrantee, replacement, cashback, etc.).
With an after-sale service, a company can maintain a long term customer
relationship (Shaharudin et al., 2010). As electronic items need some
assistance to be associated with for functioning and maintenance (Bei
and Chiao, 2006), this study denotes the quality of service as that service
for operation and maintaining of the physical products such as installation, repairing and after-sale service. Hu et al. (2009) emphasised on
quality of service from customer views and remarked quality of service as
an uncompromised core factor of service promise. Like the service industry, physical product-based companies have to assure the quality of
service. The “after-sales service” of tangible goods refers to “operative
activities” (Gaiardelli et al., 2007). After-sale service is a term that is
mostly and widely used while an electronic item is on sale. To customers,
after-sale service means some services that are to be received after purchasing products (Vitasek, 2005). These services refer to “field service”
when those services are in customer’s sites or customer houses (Simmons, 2001). “After-sales support” is also known as “technical support”
(Agnihothri et al., 2002) or even just “services”, are discussed in the
previous studies (Goffin and New, 2001). Lele and Karmarkar (1983)
mentioned that “after-sales services” are termed as “product support
activities” which means those supports activities are related to ‘product-centric transaction’. In literature, these support activities are
“customer support” elements that indicate all activities assuring this
product is available to consumers “over its useful lifespan for trouble-free
2. Literature
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Heliyon 6 (2020) e05710
inspires the company to serve its customers need in a better way . According to Philip et al. (2016), the role of social network as well as media
has become increasingly significant . In their opinion, reviews and recommendations on a product as well as service play an influential role in
customer’s decision-making process in the current digital age .
With the benefit of a user-generated-content platform, as the studies
demonstrate, customers check the product reviews, feedback from customers and recommendations and make a buying decision. Facebook,
Facebook Messenger, Imo, Instagram, LinkedIn, Pinterest, QQ, QZone,
Skype, Tik Tok, Viber, WeChat, WhatsApp, and YouTube are popular
social media networking platforms. Over 2,603 million people in the
world actively use Facebook as on April 2020 (Statista, 2020b). In
Bangladesh, Facebook, FB Messenger, WhatsApp, Imo, YouTube, LinkedIn, Viber, Skype are very popular and widely used. The study indicates
the extent the respondents trust social media for the information, comments, reviews that are posted and shared leading to their buying decision . The more the people use social media and trust the shared
information, the more it has an impact on their buying decision and vice
versa. On the basis of the critical role of social media and its usage, Hu
and Kettinger (2008) researchers to work with social media.
The authors of this study formulated the conceptual framework based
on an extensive literature review and the objective of this study.
use” (Loomba, 1998). Furthermore, the term “after-sales services” is
brought in the perspective of two considerations in the literature.
Rigopoulou et al. (2008) illustrated these services are “the transport
or delivery to clients, the installation, the product-related training, the
hotline and advice by the help desk, any repairing service and even the
recycling process”. Koyuncu et al. (2014); Shi et al. (2014); Dhar (2015);
Kaura et al. (2015); Lai (2015); Zameer et al. (2015); Ayo et al. (2016);
Pizam et al. (2016); Kant and Jaiswal (2017); Oh and Kim (2017) and
Keshavarz and Jamshidi (2018) worked on service quality in their
respective fields in very recent times.
2.4. Customer perceived value (CPV)
Zeithaml (1988) defines perceived value as “the consumer’s overall
assessment of the utility of a product (or service) based on perceptions of
what is received and what is given”. Another scholar, Bettman et al.
(1998), meant customer perceived value as “value customers perceive
they receive or experience by using a service”. Similarly, Lovelock (2000)
defined perceived value as a “trade-off between perceived benefits and
perceived costs”. Vandermerwe (2003) stated the practical view of
perceived value as a ratio of value a customer receives consuming a
product and the value s/he expects before consuming it. Perceived value
is the state of fulfilment of what they expect from an electronics household product or its associated service and what they ultimately gain
(Uddin, 2013).
Perceived value is considered as a vital factor in marketing and for
marketers (Keshavarz and Jamshidi, 2018; Oh and Kim, 2017; Thielemann et al., 2018; Zameer et al., 2015). Some scholars find customer
perceived value as a stable factor to forecast customer’s buying behaviour (Anderson and Sullivan, 1993; Carroll et al., 2002; Chen and
Dubinsky, 2003; van Riel and Pura, 2005). Zeleti et al. (2016); Sabiote-Ortiz et al. (2016); Joung et al. (2016) and Walls (2013) conducted
their research on the perceived value. Similarly, other researchers like
Wu et al. (2011); Howat and Assaker (2013); Kim et al. (2013); Tung
(2013) (Chen and Lin, 2015); Hanna et al. (2011); Ramseook-Munhurrun
et al. (2015); Moorthy et al. (2018); Keshavarz and Jamshidi (2018) and
Oh and Kim (2017); Thielemann et al. (2018); Zameer et al. (2015) used
perceived value in their studies.
2.6. Hypotheses development
2.6.1. Product quality and customer satisfaction
Customers purchase and use physical products to meet their requirements. Therefore, a firm need to realize the basic idea of customer
requirements (Gerdt et al., 2019; Zhang et al., 2019). Companies that
offer products (attractive feature, size, colour and functional quality,
serviceability, and so on) can enhance competitiveness and obtain higher
customer value (Kafetzopoulos et al., 2015) (Prakash et al., 2017). Santouridis and Trivellas (2010) opine that a satisfied consumer is highly
possible to stick to existing products whereas a dissatisfied consumer
tends to switch to competitors’ products. Uddin (2013), in his study on
electronics household appliances in Bangladesh, discloses that perceived
product quality positively affects satisfaction, as it is a psychological
issue. He also added that customer-oriented and product-selling firms
practice quality and persuade consumer satisfaction. Lin et al. (2018) and
G€
ok et al. (2019) found that product quality is a strong antecedent of
ok et al. (2019) stated that contrast theory excustomer satisfaction. G€
plains the clarification of the product evaluation process and the quality
of the product that customer magnifies the gap between the product
received and the product expected. If the actual performance of the
product fails to meet expectations, the customer will evaluate the product
less favourably (Anderson, 1973; Korgaonkar and Moschis, 1982).
Quality of products is considered as a driver of customer satisfaction
(Ehsani and Ehsani, 2015) and the improved insights of this quality
motivate consumer contentment (Uddin, 2013). It is a logical expectation
that a customer will be satisfied with the quality of a product of a
particular brand (Ayo et al., 2016). Hamzah and Shamsudin (2020)
found a significant relationship between product quality and customer
satisfaction. Thus, managers of electronics company can focus on
developing quality and safe products that fulfil the customers’ needs with
satisfaction. The quality of a tangible product is strongly associated with
the satisfaction of the customer (Ryu and Han (2010); Jakpar et al.
(2012); Vera (2015); and Beneke et al. (2013). Based on past studies, the
following has been formulated:
2.5. Social media (SM) and its usage
With the support of social media, customers are well-connected with
the whole world with a finger-tap (Hamzah and Shamsudin, 2020). Many
scholars define social media from their point of view and application.
Generally, social media refers to a website and applications by which users
can create, view, share and interact content in virtual social media.
Kietzmann et al. (2011) depicted social media as “interactive
computer-mediated technologies that facilitate creation and sharing of
information, ideas, career interests and other forms of expression via
virtual communities and networks”. In view of Mangold and Faulds
(2009), there is a significant transformation in media, especially in
traditional networking in the last ten years. Supporting them, Coulter et al.
(2012) noted that conventional networking has been replaced by a system
facilitating modern technology. Leung et al. (2019) brought the exact
utility of social media. They stated that it is a track of information superhighway, and users can share any information-in text, voice, image, video
and other people can read and get information from it at their convenient
time. Rao (2019) states that social media in the form of online websites
that allow individuals to communicate and establish social networks such
as Facebook and web-based videos like those viewed on YouTube.
Mirmehdi et al. (2017) pointed out the prominence of social media in
the social networking system and remarked how social media influence in
the daily decision. In view of Khan and Khan (2012), social media helps get
various news and information about products, service; customers read
this news, provide reviews, and feedback regarding purchased products .
Regarding the role of social media, Sashi (2012) opines that social media
H1. Product quality positively and significantly affects customer
satisfaction
2.6.2. Quality of service and customer satisfaction
In marketing research, service quality receives more attention
considering the intangible aspect (Bei and Chiao, 2006). But tangible
products require some sorts of services associated with them. The
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Md.U.H. Uzir et al.
Heliyon 6 (2020) e05710
Lin (2015) who worked on social media and blowing, Kim et al. (2013)
on mobile user engagement, and Unyathanakorn and Rompho (2014) on
commercial banking. They found that customer perceived value has a
positive impact on customer satisfaction. One of the past studies by
Uddin and Akhter (2012) in Bangladesh demonstrated that customers’
perceived value has a significant direct effect on the satisfaction of the
customer in mobile phone services. Similarly, according to Uddin (2013),
customer perceived value has a positive effect on the users of electronics
products in Bangladesh. After reviewing the previous literature, the
Hypothesis proposed is as follows:
concept of a product-service continuum indicates service and only product
as the two extreme bipolar (Rathmell, 1966), that is, the support of
services is required to some extent for most of electronics products. This
support service is associated with satisfaction. For this reason, customer
satisfaction is an outcome of perceived quality (Ayo et al., 2016). Kondasani and Panda (2015); Ali and Raza (2015); Hu et al. (2009) were
applauded for exploring the relationship between these two constructs.
The quality of service, namely after-sale service, is very vital in the case of
electronics appliances. With an after-sale service, a company can maintain a long term customer relationship (Shaharudin et al., 2010). As has
been argued, service for the tangible product is the intangible value
offered to customers (Alteren and Tudoran (2016); O’Dwyer and Gilmore
(2018); and Gligor et al. (2019). Chinomona et al. (2013) conducted a
study in the retail industry in South Africa and found that service quality
and customer satisfaction are positively and significantly related.
Another study conducted by Kondasani and Panda (2015) in India
illustrated that customer satisfaction and service quality are positively
associated with each other.
Similarly, the study done by Minh et al. (2015) implies that service
quality plays an essential role as a driver for higher customer satisfaction
level in hotel service in Vietnam. Likewise, some authors worked on the
physical product to find significance in this relationship. Like, Cronin and
Taylor (1992) showed that customer services in four services industries
such as banking, laundry, pest control and processed food have positive
effects on customer satisfaction. And Gilbert et al. (2007) also finds this
relationship significant in restaurant business where fifty percent service
and fifty percent physical products (like food, water and so on). As
electronics home appliances require some associated service after selling
the products, after-sale service is very significant for customers and users
satisfaction (Ehsani and Ehsani, 2015). In his study of electronics home
appliances in Bangladesh, Uddin (2013) shows that customer service
plays an influential role in determining customer satisfaction.
Past studies showed evidence that perceptions of service quality influences satisfaction different industries and in different country contexts
(Beigi et al., 2016; Chen, 2008; Olorunniwo et al., 2006; Tsai et al.,
2007). Thus, the authors proposed the following Hypothesis:
H3. Customer perceived value positively and significantly affects
customer satisfaction.
2.6.4. Product quality and customer perceived value
Extant literature demonstrates that product quality as predictors of
customers’ perceived value (Bolton and Drew, 1991; Chen and Hu, 2010;
Lai, 2015; Zeithaml, 1988). Studies by Ryu and Jang (2008) appear to be
the only empirical evidence indicating that food quality significantly
affected perceived value. Hanzaee and Yazad (2010); Razak et al. (2016)
mentioned the apparent effect of product quality on customer perceived
value. According to a study conducted by Yang et al. (2016) on product
features, like its functionality and usefulness, perceived product quality
has a direct effect on customers’ perceived value. Only the customer can
evaluate whether or not a product or service provides value for their
money and the concept of customer perceived value is perceived to be
very subjective and personal (Liu and Jang, 2009; Parasuraman et al.,
1985). In the case of Bangladeshi electronics home appliances market,
product quality is considered a successful predictor of customer
perceived value (Uddin, 2013). Additionally, Sweeney et al. (1997)
regarded customers’ perceived value as an outcome of perceived product
quality. Based on these studies, the following Hypothesis is proposed:
H4. Product quality positively and significantly affects customers’
perceived value.
2.6.5. Quality of service and customers’ perceived value
Service quality serves as a predictor of customer perceived value
(Bolton and Drew, 1991; Chen and Hu, 2010; Lai et al., 2009; Zeithaml,
1988). In line with earlier findings, Agarwal and Teas (2002); Butz and
Goodstein (1996) found the perceived quality to have a significant influence on perceived value. In other words, the better the service quality
is, the higher the customers’ perceived value obtained (Howat and
Assaker, 2013; Tam, 2004; Yu and Yuan, 2019). Another critical view is
that perceived value also believed as a trigger of customer satisfaction.
There are cogent empirical pieces of evidence to buttress the idea that
quality of service is positively related to perceived value (Brady and
Robertson, 1999; Ravald and Gr€
onroos, 1996; Teas and Agarwal, 2000).
Similarly Eggert and Ulaga (2002); Lai (2015); Oh (1999); Thielemann et
al. (2018) highlighted that the quality of service’s features (tangibles,
empathy, reliability, and responsiveness) are associated with consumers’
perceived value. Liu and Jang (2009); Parasuraman et al. (1985) viewed
customer value as subjective and personal. Meanwhile, Sweeney et al.
(1997), regarded customers’ perceived value as an outcome of perceived
service quality. Based on these studies, the study proposed the following
Hypothesis:
H2. Quality of service positively and significantly affects the relationship with customer satisfaction.
2.6.3. Customer perceived value and customer satisfaction
Customers are rapturous and want to get ensured for the value for
their money (Campbell and Stanley (2015); Chicu et al. (2019); Hirata
(2019); and Rita et al. (2019). Delivering superior customer value and
the resulting customer satisfaction are crucial to the competitive edge of a
firm (Murali et al., 2016). In their study, McDougall and Levesque (2000)
similarly discuss the significance of customer perceived value on
customer satisfaction. According to them, perceived value is a strong
predictor of satisfaction. In view of Zeithaml (1988), when a customer
considers his benefits much more than the expenditure, he gets satisfied.
Therefore, perceived value is determinant of satisfaction (Uddin, 2013).
Aligned with the intuition, Fornell et al. (1996) and Hu et al. (2009)
supported that perceived value has a positive influence on customer
satisfaction. However, there is a debate on whether customer perceived
value has a direct or indirect effect on customers’ satisfaction (Ravald
and Gr€
onroos, 1996). Fazal and Kanwal (2017) conducted a study on
mobile phone users in Pakistan. They showed that customer perceived
value has a positive and significant impact on user satisfaction of the
mobile phone.
The effect of customer perceived value on satisfaction can be wellperceived by digging more in-depth in the literature. A significant
number of previous studies reflect that customer value affects satisfaction
(Chen, 2008; Tsai et al., 2007). Hu et al. (2009) explored the relationship
between perceived value and customer satisfaction, and accordingly to
their findings, superior customer value ensures higher customer satisfaction. Some studies on this relationship were conducted by Chen and
H5. Quality of service positively and significantly affects customer’
perceived value.
2.6.6. Mediating effect of perceived value
Value is the function of consumer evaluation; thus, it is subjective
where the cost and benefit must be favourable (Itani et al., 2019; Peng et
al., 2019). Therefore, the marketing literature focused the concept of
customer value, putting it at the centre and as one of the core strategies
when serving consumers (Fang et al., 2016; Prebensen and Xie, 2017).
Nonetheless, companies are well-aware that their consumers are highly
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Heliyon 6 (2020) e05710
asking for social validation of their decision from both their online and
offline social networks, which is often out of sight of the actual retailer or
brand (Hall et al., 2017; Nunan and Di Domenico, 2019). The empirical
evidence indicated that rapid and continued growth in shopper’s marketing
requires precise communication strategies to drive performance (Hall et
al., 2017). Through the use of smartphones and other devices, people
have more access to information than ever before. Consumers can get
detailed knowledge about products instantly nowadays. The concern of
the current study, therefore, is to demonstrate-the extent the users and
customers of electronics home appliances trust and apply the information
in their product selection, buying decision and recommending others.
Therefore, the usage of social media comes handy for developing
moderating hypotheses:
empowered and will only purchase value-added products which are
capable of providing a highly satisfying experience (Yang et al., 2016).
However, the value is assessed based on the perception of the individual
customers, as the same offering might be perceived to hold different
value levels among customers (El-Adly, 2019). Also, Slater and Narver
(2000) have explained that value is maximized when the benefits from
the firm’s offerings are more than the related costs (e.g., price, search,
time, and psychic cost). Thus, firms should deliver more value to customers by providing them more benefits and fewer expenses; failing to do
so will lead firms to lose the probability of gaining a competitive
advantage. As a result, customers may search for new alternatives (Itani
et al., 2019; Marbach et al., 2016). Thus, we predict that product quality
and quality of service shape the customers’ perceived value; such that these
customers perceive values that invite and reinforce customers’ satisfaction (Chen and Lin, 2019).
A significant indirect association exists between service quality and
behavioural intention through perceived value and customer satisfaction
(Cronin et al. (2000); Kim et al. (2013); Oh (1999). Again, the findings of
Keshavarz and Jamshidi (2018) reflect the mediating role of perceived
value in the relationship between quality and satisfaction. Similarly,
Edward and Sahadev (2011) investigated the significant mediating effect
of perceived value in mobile service providers in India. According to Oh
and Kim (2017), a total of 21 percent of studies focused on customer
perceived value in the last 15 years, e.g. from 2000- 2015. Malik (2012)
had research involving the mediating role of perceived value and found
customer perceived value as a partial mediator in the relationship between perceived service quality and customer satisfaction. Also, Lukito
and Yustini (2019) discovered a partial mediating role of customers’
perceived value. Therefore, the following hypotheses are proposed in line
with the above literature:
H8a. Social media usage moderates the relationship between product
quality and customer’ satisfaction, such as the relationship is stronger
when the usage of social media is high than low.
H8b. Social media usage moderates the relationship between quality of
service and customer’ satisfaction, such as the relationship is stronger
when the usage of social media is high than low.
H8c. Social media usage moderates the relationship between customer
perceived value and customer’ satisfaction, such as the relationship is
stronger when the usage of social media is high than low.
2.7. Theoretical assessment
The study underpinned two theories to support the conceptual
framework and met the assumptions of those with the objective of the
study.
H6. Customer perceived value mediates the relationship between PQ
and customer satisfaction.
2.7.1. Expectation disconfirmation theory (EDT)
Expectation Disconfirmation Theory, introduced by Oliver (1977)
and developed in (1980), is a cognitive theory or assumption that entails
the post-purchase or post-adoption satisfaction. It is a function of expectations, perceived performance, and disconfirmation of beliefs.
Satisfaction is conceptualized in several ways in the literature to date
(Hair et al., 2010), and confirmation–disconfirmation approach
(Veloutsou, 2015). Skogland and Siguaw (2004) prescribe three types of
satisfaction, such as natural feeling, satisfaction (confirmation) and
dissatisfaction (disconfirmation). The natural feeling exists if customers
receive actual performance similar to the standard they expect. If actual
performance is better than the natural feeling (standard), it confirms
satisfaction. On the other hand, if actual performance fails to meet natural feeling, unfortunately it leads dissatisfaction.
According to this theory, a customer assesses his/her satisfaction
levels by comparing their expectation with the experience received
from the product quality, quality of service and their post evaluative
behaviour and customer satisfaction. Past studies indicate the different
effects of performance, expectations and disconfirmation (Yi and
Nataraajan, 2018). being developed and tested in western countries,
satisfaction theories are gradually extending to developing counties in
a different context,. An Asian country well-known as Bangladesh with
a large population, increased market size, and a different culture, is a
choice of this study to utilize this theory. In a different context, it is
required to test the application of customer satisfaction theories (Yi
and Nataraajan, 2018). According to the expectancy disconfirmation
theory, as the scholars opine, customers expect a benefit or utility
from the product that before buying any product, customers expect a
benefit or utility from the product. They use or consume the products,
_measure the prior expectation from product and the performance and
at the end compare the expectation with the actual performance they
receive. This comparison confirm satisfaction or dissatisfaction. In case
of buying and using electronics home appliances, the customers
compare their expectation before buying with actual benefits they
receive during and the post usage.
H7. Customer perceived value mediates the relationship between SQ
and customer satisfaction.
2.6.7. Social media usage and its moderating role with customer satisfaction
According to Sashi (2012), social media plays a part to build a
buyer-seller relationship. Lang (2010) stated that people spend more than
one-third of their working day using social media. Only Facebook has
more than 2.40 billion active users (Statista, 2020b). However, like
Facebook, users are involved in spending their time on all other social
media. These platforms are interactive as concerned with views, comments, and recommendations about the usage of products, including
additional issues of life. Laroche et al. (2012) conducted a study using
CB-SEM on social media effect in their model. They found that brand
communities established on social media have a positive impact on their
community (i.e., shared consciousness, shared rituals and traditions, and
obligations to society), which have positive effects on value creation
practices (i.e., social networking, community engagements, impressions
management, and brand usage). Social media and its popularity as a
unique element, have opened a new horizon for marketing practices
(Hanna et al., 2011). Even social media affects “consumer behaviour
through information acquisition to post-purchase behaviour such as
dissatisfaction statements or behaviours” (Mangold and Faulds, 2009).
In consumers’ buying decision process, there are influences and
motivation from the family members, colleagues, peers and neighbours,
media personalities, traditional and digital media (promotions and
advertisement) as well as the internet (Hayan and Samaan (2015). Villarroel et al. (2019) did extensive text mining from social media and
analysed those online data. They unearthed that online text message (in
Facebook and Twitter) contains emotion and information, and the
satisfied customers share their experience and recommend electronics
products to their known persons (Uddin, 2013). Particularity, shoppers
undertake various activities before they make their final purchase decision. This effort may include seeking content from different retailers and
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Heliyon 6 (2020) e05710
the prior studies to measure customer perceived value (CPV) (Aaker,
1996; Parasuraman et al., 1985; Schechter, 1984; Sekaran and Bougie,
2009; Walls, 2013). To measure social media usage 4-items were
slightly adapted from the earlier studies (Brito, 2011; Freidman, 2011;
Mangold and Faulds, 2009). Finally, we measured customer satisfaction (CS) with five items taken from previous researches (Faullant et
al., 2008; Parasuraman et al., 1985; Schechter, 1984; Sekaran and
Bougie, 2009; Walls, 2013; Zeithaml, 1988).
4. Data analysis and results
Covariance-based structural equation modelling (CB-SEM) was
employed to test the conceptual model of this study. CB-SEM carries
some advantages. It is a parameter estimation where maximum likelihood (ML) method was used (Hair et al., 2017b). The data were analyzed
with CB-SEM technique and using AMOS software (v.24). Two analytical
steps were considered, such as the measurement model and the structural
model. Measurement model encompasses reliability, validity and overall
model fitness of the constructs and the structural model deals with hypotheses testing.
Figure 1. Conceptual framework.
Based on the literature and insights of the EDT theory, the study
developed the following framework (see Figure 1).
3. Methodology
The study was based_on household members (both male and female)
in Dhaka, the capital city of Bangladesh. The quantitative method was
adopted in this study, where a total of 300 respondents participated
based on the judgmental sampling technique. A judgmental sampling,
also known as purposive sampling, refers to the sampling method that
chooses the units to be judged as the most representative of the population (Saunders et al., 2016). The researcher imposes a subjective
experience and condition (criteria) to select samples from the intended
population (Saunders et al., 2016). The quality of samples selected by
using this approach depends on the accuracy of subjective interpretations which constitutes a typical sample (Valliant and Dever,
2018). We employed this technique following the goal of this research is
to achieve theory generalization, as the complete sampling frame is not
available in the given context (Memon et al., 2017; Hulland et al.,
2018). The questionnaire was shared in Facebook messenger group,
WhatsApp group, the LinkedIn group with a request to fill those out.
Some questionnaire was also distributed through known email addresses. The reason for using electronic surveys (i) to minimize effort
and cost (ii) to approach the largest respondents compared to the
self-administered survey because in the technological era, all individuals
are attached to mobile phone or computer device. Thus, that supported
the researchers to approach the targeted respondents of the current
study. Prior to that, a standardized and structured questionnaire was
developed from the literature. The data collection period was between
March to June 2019. The questionnaire with cover letter stated the
purpose of the survey assuring the confidentiality and sought the consent of respondents. In addtion, researchers conducted studies involving
human participants per institutional committee’s ethical standards
(Putra Business School Research Ethical Committee headed by Prof. Dr.
Zulkornain Yusop, Reference Number: PBS/PhD/PBS18123252 dated
March 15, 2019) and the 1964 Helsinki declaration and its later
amendments or comparable ethical standards.
4.1. Demographic information
Table 1 presents the demographic information. Among surveyed 300
respondents in this study, 144 (48%) were male, and 156 (52%) were
female, 198 (66%) respondents belonged to 31–40 years. A total of 273
(91%) was married, and 24 (8%) unmarried. Respondents were from
diverse occupations such as students (21; 7%), jobseekers (33; 11%), selfemployed (18; 6%), government employees (72; 24%), private service
(90; 30%) and homemakers (66; 22%).
4.2. Exploratory and preliminary data analysis
Exploratory data analysis (EDA) were processed with the aid of the SPSS
software. EDA includes missing data, data outliers, data normality, mean,
median, standard deviation, correlation, linearity, multicollinearity, and
homoscedasticity for determination of reliability, validity, measurement
and structural models. For path coefficient analysis, covariance-based
structural equation modeling (CB-SEM) was utilized. Abdollahi and Talib
(2015); Kline (2010) stated some advantages while using SEM, especially
CB-SEM. Hair et al. (2017a) supported the adoption of the maximum
likelihood method for parameter estimation. In the measurement model,
model fitness was checked, and in the structural model, the proposed hypotheses were tested. SPSS output showed no missing data in the dataset. It
was possible for the authors’ vigilance and persuasion to respondents.
Extreme and unexpected data in the dataset were checked through univariate and multivariate outlier analysis (Kline, 2015). Cook’s distance and
Leverage values for outliers showed that three cases contained absolute
values and accordingly were deleted. Data normality is one of the very vital
issues in multiple regression (Sun et al., 2015), especially in SEM (Hair et
al., 2016). Traditionally, the skewness and kurtosis statistics were also
checked, and the Skewness-Kurtosis values were within acceptable range
1.96 (Byrne, 2013; Hair et al., 2017a). Besides, the Shapiro-Wilks test
showed that data distribution was normal.
Multicollinearity is a threat to multiple regression, including SEM
(Hair et al., 2016). The correlation coefficient among the independent
variables was not highly correlated. The result from coefficient collinearity diagnosis showed that the variance inflation factor (VIF) was
below 1.70 (highest is 1.63 for customer perceived value). Therefore,
data were derived from the normal distribution, and there was no evidence of multicollinearity. The scattered residual plots showed that the
residuals were_scattered randomly around the zero lines and had no
triangular-shaped pattern. It also proved that there was no sufficient
evidence heteroscedasticity of the error terms (Hair et al., 2010).
3.1. Variables measurement
All the instruments were taken from a reliable source. Before the
main data collection phase, the questionnaire was checked by academic experts to ensure content validity. Therefore, the variables were
measured by self-report on multi-item scales derived from previous
studies. All the measures were assessed by seven-point Likert-type as
‘1’ representing ‘strongly disagree’ and ‘7’ representing ‘strongly
agree’. All the items have been presented in Table 3. To measure
product quality (PQ), four indicators were adapted from Parasuraman
and Grewal (2000). We measured quality of service (SQ) with 4-items
adapted from (Rigopoulou et al., 2008). Four items were taken from
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Table 1. Demographic information.
Characteristics
Gender
Age Category
Marital Status
No
%
Characteristics
Male
144
48%
Occupation
Female
156
52%
No.
%
Students
21
7%
Job seekers
33
11%
Less than 26
12
4%
Self-employed
18
6%
26–30
21
7%
Govt. Service
72
24%
30%
31–35
87
29%
Private Service
90
36–40
111
37%
Homemakers
66
22%
41–45
42
14%
Facebook
90
97%
Social Media Usage
(Multiple response)
46–50
15
5%
FB Messenger
230
77%
More than 50
12
4%
YouTube
156
52%
Married
273
91%
WhatsApp
68
23%
Unmarried
24
8%
Twitter
24
8%
Single (widowed,
divorced, separated)
3
1%
LinkedIn
45
15%
Imo
87
29%
Viber
50
17%
and MSV test were done. Diagonal value is higher than the corresponding
value of the respective row and column values (values are bold shown in
Table 4). It indicates that the construct’s correlation is higher than the
correlation with other constructs. Similarly, maximum shared variance
(MSV) is lower than AVE, but higher than average shared variance (ASV)
(Table 4). Thus, the measurement variables are unique and discriminant
from each other.
4.3. Common method variance or common method bias test
Common method bias exists if principal constructs are significantly
and highly correlated (r > 0.90) (Bagozzi et al., 1991). The correlation
matrix reveals that variables are not highly correlated. Therefore, there is
no initial evidence of possible CMV in this current research. Nitzl (2016)
asserted that the overall correlation between items might be inflated and
shows a significant relationship between constructs while at the same
time reduces the discriminant validity between constructs. The correlation among all the constructs was found less than 0.90.
The present study also applied Harman’s single-factor test (Podsakoff
and Organ, 1986) to check for CMV. This test is conducted using principal
component analysis (PCA) as suggested by (Tehseen et al., 2017). The
unrotated principal axis factoring analysis reveals that a single factor
explains 37.258% variance (Table 2), which is less than 50% (Al Halbusi
et al., 2020; Kumar, 2012; Uzir et al., 2019, 2020). Hence, this suggests
that common method bias in this study is non-existent and not a major
concern and unlikely to inflate relationships between variables.
Table 5 indicated that CMN/DF was 1.672, which is lower than the
threshold value (5.00). GFI (0.923) is an acceptable level, and CFI
(0.981) is very good.
The indicators of the badness of the model were acceptable level as
RMR and RMSEA were 0.023 (<0.05) and 0.047 (<0.08) respectively
which were less than the threshold (Hair et al., 2017b). The overall results demonstrated the measurement model fitted good and was eligible
for the structural model (Figure 2).
4.4. Measures of reliability, validity and measurement model
4.6. Path coefficient and structural model
Measurement model has some properties such as reliability and validity for measuring each construct to be measured through SEM-AMOS.
With individual CFA and model fitness indices of the measurement
model, the strength of the relationship path was checked through the
structural model. Table 3 showed the measurement elements. For item
reliability, the results reveal no serious problems as most of the items
exceed the recommended 0.707 level (Hair et al., 2017b). To evaluate the
constructs’ internal consistency, we used composite reliability; it ranged
from 0.889 to 0.963, higher than the cut-offs value 0.70 (Hair et al.,
2017b). In support of convergent validity, the average variance extracted
(AVE) for the constructs ranged from 0.668 to 0.902, above the threshold
0.50 (Hair et al., 2017b). In the case of discriminant validity,
cross-loading, the square-root of AVE (Fornell and Larcker ratio), ASV
The structural model (path coefficient) describes the association and
effect of independent variables on the dependent variable. SEM method,
especially the maximum likelihood method, can test complex models
rigorously and find integrating multiple associations among multi-item
variables, and moderating and mediating effects (Berraies et al., 2017).
The β of path coefficient shows the direct impact of latent predictor
variable on predicted variables (Figure 3).
Table 6 shows that product quality (β ¼ 0.190, CR ¼ 3.247, p <
0.001) has a positive and significant effect on customer satisfaction
which supports the first Hypothesis. Similarly, quality of service (β ¼
0.214, CR ¼ 3.597, p < 0.001) has a significant and positive relationship
on customer satisfaction (Hypothesis 2). Customer perceived value (β ¼
0.224, CR ¼ 3.704, p < 0.001) also has a positive relationship with
4.5. Model fit assessment
Table 2. Common method variance test via single factor.
Factor
Initial Eigenvalues
Extraction Sums of Squared Loadings
Total
% of Variance
Cumulative %
Total
% of Variance
Cumulative %
1
25.335
37.258
37.258
24.724
36.359
36.359
2
8.115
11.933
49.191
3
4.610
6.779
55.970
Extraction Method: Principal Axis Factoring.
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Heliyon 6 (2020) e05710
Table 3. Measurement model, item loadings, construct reliability and convergent validity.
Constructs
Coding
Items Description
Loading
Product Quality
PQ1
The brand has an excellent functional quality.
0.954
PQ2
The brand offers very durable products.
0.920
PQ3
Products of the brand are reliable.
0.922
PQ4
The brand offers products with excellent features.
0.926
Quality of Service
Customer Perceived value
Social Media Usage
Customer satisfaction
SQ1
Reliability in delivery times.
0.937
SQ2
Quality of the product packaging when delivered.
0.947
SQ3
Kindness and friendliness of the personnel.
0.950
SQ4
Flawless of the installation.
0.964
CPV1
I think the price of the product is equivalent to its quality.
0.925
CPV2
The brand provides high-quality customer services.
0.906
CPV3
I feel relaxed in buying this product.
0.909
CPV4
I feel trust, safe and confident in buying the product from this company.
0.640
SM1
Social media have made, more convenient access to brand information.
0.767
SM2
Social media help us compare various brands.
0.838
SM3
I think I am getting benefits from social media in choosing a brand.
0.801
SM4
I think the usage of social media has any positive effects on selecting a brand.
0.898
CS1
The brand meets my expectations.
0.830
CS2
I am satisfied with my decision to buy this brand.
0.753
CS3
The brand is the only one that I buy and use.
0.838
CS4
I would recommend the product or service to others
0.846
CS5
I am satisfying delighted with this brand.
Dropped
CA
CR
AVE
0.963
0.866
0.973
0.902
0.913
0.728
0.896
0.685
0.889
0.668
0.963
0.973
0.904
0.893
0.887
Notes: CR ¼ Composite Reliability, AVE ¼ Average Variance Extracted.
Table 4. Discriminant validity.
1. CustSat
AVE
MSV
ASV
1
0.668
0.228
0.105
0.818
2
3
4
2. ProdQual
0.866
0.047
0.016
0.216
0.931
3. ServQual
0.902
0.073
0.034
0.270
0.087
0.950
4. CustPerVal
0.728
0.072
0.041
0.269
0.032
0.180
0.853
5. SocMed
0.685
0.228
0.080
0.477
0.090
0.158
0.240
5
0.827
Table 5. Overall model fit.
Construct
CMIN/DF
GFI
CFI
NFI
RMR
RMSEA
PClose
Indicator Value
1.672
0.923
0.981
0.954
0.023
0.047
0.656
indirect effect (Hayes, 2009; Williams and MacKinnon, 2008). From
Table 7, it was found that product quality (0.217, 95 per cent CI) has a
significant direct effect on customer satisfaction but has an
customer satisfaction (Hypothesis 3). The relationship between product
quality and customer perceived value was not significant (β ¼ 0.017, CR
¼ 0.277, p < 0.782) which implies that the fourth hypothesis has been
supported. On the other hand, the quality of service has a positive relationship with customer perceived value (β ¼ 0.179, CR ¼ 2.99, p <
0.001) (Hypothesis 5).
4.7. Mediating role of customers’ perceived value
By using the bootstrapping method, it was possible to ascertain the
mediating effect (indirect) of the customers’ perceived value in the
relationship between independent variables (product quality and
quality of service) and dependent variable (customer satisfaction).
Preacher and Hayes (2008) initially suggested this bootstrapping
technique as a tool for investigating the indirect effects of different
variables. It is also relevant in obtaining accurate results while
calculating the confidence intervals (CIs) of indirect relationships, as
suggested by Baron and Kenny (1986). In this study, 5000 subsample
bootstrapping in bias-corrected confidence interval at 95% provide the
following results (Table 7) as bootstrapping is a powerful tool to test
Figure 2. Measurement model.
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Heliyon 6 (2020) e05710
Figure 3. Structural model.
Table 6. Result of hypotheses testing.
Hypotheses & Path
B
Beta (β)
Standard Error
Critical Ratio
P-value
Result
H1: P Q → CS
0.155
0.190
0.048
3.247
0.001
Supported
H2: SQ → CS
0.090
0.214
0.025
3.597
***
Supported
H3: CPV → CS
0.122
0.224
0.033
3.704
***
Supported
H4: PQ → CPV
0.025
0.017
0.089
0.277
0.782
Rejected
H5: SQ → CPV
0.137
0.179
0.046
2.99
0.003
Supported
B ¼ unstandardized regression weights, Beta (β) ¼ standardized regression weights and ***p < 0.001.
Table 7. Mediating effect (indirect effect) of customer perceived value.
Hypotheses
Direct
Mediation
Indirect
Mediation type
PQ →
CS
0.217***
0.190***
0.004(NS)
Lower band: -0.024
Upper band: 0.054
No mediation
SQ →
CS
0.271***
0.214***
0.040***
Lower band: 0.012
Upper band: 0.095
Partial mediation
***P < .0.001.
Figure 4. Direct model: PQ-CPV-CS.
10
Md.U.H. Uzir et al.
Heliyon 6 (2020) e05710
Figure 5. Mediating model: PQ-CPV-CS.
Figure 6. Direct model: SQ-CPV-CS.
Figure 7. Mediating model: SQ-CPV-CS.
Figures 4, 5, 6, and 7 showed the mediation of customer perceived
value.
insignificant indirect impact on customer satisfaction (0.004). Hence,
customer perceived value has no mediation effect on the relationship
between product quality and customer satisfaction (Hypothesis 6).
Furthermore, the quality of service has both a significant direct effect (0.271) and indirect effect 0.040) on customer satisfaction. Hence,
customer perceived value has a partial mediating role in the relationship
between quality of service and customer satisfaction (Hypothesis 7).
4.8. Moderating effect of social media usage
Social media usage has been utilized as the moderator in this study
and was categorized into three levels: low usage, mid usage, and high
11
Md.U.H. Uzir et al.
Heliyon 6 (2020) e05710
0.05). The effect of quality of service on customer satisfaction was significant at both low level (β ¼ 0.270, p < 0.001) and high level (β ¼
0.238, p < 0.001) but insignificant at mid-level (β ¼ 0.131, p > 0.05).
The effect of customer perceived value on customer satisfaction was
significant at both low level (β ¼ 0.262, p < 0.001) and high level (β ¼
-0.081, p < 0.001) but insignificant at mid-level (β ¼ 0.118, p > 0.05).
usage. These levels are the extent to which a customer has faith on the
information available in social media. Before testing the moderation effect, the study checked the measurement invariance of the composite
model.
4.8.1. Measurement invariance of composite model (MI-COM)
Eberl (2010), while describing measurement invariance states that
“….. the loading and weights of the constructs’ measurement model must
not differ significantly within the model” (p. 504). Hair et al. (2017)
signified measurement invariance composite model (MI-COM) and
mentioned that “… variations in the structural model relationships between latent variables could stem from the different meaning the groups’
respondents attribute to the phenomena being measured, rather than the
true differences in the structural relationships”. In this study, the usage of
social media was grouped into low, medium and high. According to
Henseler et al. (2016), the first step of MI-COM is configuration invariance. Configuration invariance is achieved if the factor loadings of items
are invariance in the measurement model. The study found that regression weights of items with constructs were significant; CFI and TLI were
higher than 0.90, and RMSEA was less than 0.08. In the second
step-parameter invariance, unconstraint model, measurement weights,
structural covariance and measurement residuals were checked. Unconstraint model’s Chi-square was insignificant. Model one showed that
invariance between groups (CFI, TLI) was higher than 0.90, and RMSEA
was 0.70. Model 2 (structural covariance and correlation) and model 3
(measurement residuals) showed that invariance was significant.
Considering the factor invariance, parameter invariance, and their significance, the study found that this measurement model was invariant.
Therefore, moderating effect could be checked.
4.9. Mediated (perceived value) moderating (social media usage) effect on
PQ → CS and SQ → CS
According to the findings demonstrated in Table 11, perceived value
does not mediate the relationship between product quality and customer
satisfaction at a different level of using social media. Similarly, the
perceived value does not mediate the relationship quality of service and
customer satisfaction (Table 12).
5. Discussions
The main objective of this study was to investigate the relationships
among product quality, quality of service and customer satisfaction, and
how customers’ perceived value mediates and social media usage moderates these relationships. The results showed that product quality has a
positive and significant relationship with customer satisfaction (Hypothesis 1). This finding is consistent with a similar study conducted by
Uddin (2013) on electronics household markets in Bangladesh.
Conversely, the results are also identical to the outcome of various researches over the period. The corresponding results were found by Hill
and Alexander (2016), Ryu and Han (2010), Ryu and Jang (2008) as well
as Santouridis and Trivellas (2010). Later on, Beneke et al. (2013); Jakpar et al. (2012); Kafetzopoulos et al. (2015); Vera (2015); Verhoef and
Lemon (2013); Wang et al. (2012) and Prakash et al. (2017) also
confirmed equivalent findings that product quality is positively related to
customer satisfaction.
Product quality is the functionality and conformance of the product
that serve the purchasers and users satisfactorily. People purchase electronics home appliances of their favourite brand for their convenience. In
Bangladesh, customers focus on product durability, usability, design,
colour shape and physical outlook. Products should be convenience, and fit
and easy to use. Customers first expect the electronics appliances to be fit
for usage (Russell and Taylor, 2006) and meet their requirements (Crosby
and Stephens, 1987). If the home appliances meet the daily requirement
of the customers and make the life easy and comfortable, customers will
be delighted and satisfied to that brand (Gerdt et al., 2019; Zhang et al.,
2019). G€
ok et al. (2019) in their recent research that quality of physical
products satisfies the users. The electronics home appliances TV, fridge,
washing machine, fan, lights, oven, air conditioners, etc. have some risks,
for example, electric shock, blast, short-circuit, etc.; sometimes these risks
harm users. The safety of electronics home appliance is a considerable
issue to customers. Herrington and Weaven (2009), as well as Feigenbaum (1991) argued on product quality control and production
quality for product safety, which ensure customer satisfaction. Therefore,
product quality, such as functionality has a significant influence on
customer satisfaction. This finding has been supported by the
expectancy-disconfirmation theory (EDT) by comparing the customer
perception of product quality and their expectations (Oliver, 1980).
The study has also found the quality of service has a positive and significant relationship with customer satisfaction (Hypothesis 2). The
findings indicated that installation service, demonstration of using electronic items, pre-cautions regarding possible dangers, after-sale service,
warranty, repairing service, and home service are very vital to customers.
The findings of the study suggested that quality of service, like other
intangible pure services, are the influential factor in customer satisfaction. Chen (2008) and Hu et al. (2009) spoke about similar outcomes in
4.8.2. The categorical moderating effect of social media usage
This section tests the moderating effect of social media in the three
hypotheses 6a, 6b, and 6c. earlier mentioned. Social media usage
construct was categorized into three multi-group- low, medium, and
high. The result showed (Table 8) that social media moderate the relationship as unconstrained model (Chi-Square: 2.627, CFI: 0.919, IFI:
0.920, RMSEA: 0.074) and is better than measurement residuals (ChiSquare: 3.372, CFI: 0.848, IFI: 0.848, RMSEA: 0.089) as well as statistically significant (p ¼ 0.000) (Hair et al., 2017b).
For the moderator (multi-group) variables, social media has been
categorized into three groups based on the mean. The category calculation was done by deducting lower scale point (1) from the upper scale
point (5), and the difference has been divided into 3 (e.g. three categories). Here interval is 1.33 (5-1 ¼ 4, 4/3 ¼ 1.33). Classification for low
level is 1 þ 1.33 ¼ 2.33 and below, mid-level ¼ 1.33 þ 2.33 ¼ 3.66 and
below; and high level above 3.66. The path was moderated by the level of
social media where β of three categories (low, mid and high level) gives
different significance or all paths are either negatively significant or
positively significant (Table 9).
Social media does not affect those who use these media less. In regard
to medium usage of social media, users are affected much. Medium users
get various information from the reviews, recommendations, and feedbacks shared in these media. Low-level users and high-level users
cognitively ignore comments.
Social media usage construct was categorised into three multi-groupslow, medium, and high (Table 10). The findings showed that social
media moderate the relationship as unconstrained model (Chi-Square:
2.627, CFI: 0.919, IFI: 0.920, RMSEA: 0.074) is better than measurement
residuals (Chi-Square: 3.372, CFI: 0.848, IFI: 0.848, RMSEA: 0.089) and
statistically significant (p ¼ 0.000) (Hair et al., 2010).
From Table 10, the effect of product quality on customer satisfaction
is significant at a low level ((β ¼ 0.395, p < 0.001) but insignificant at
both mid-level ((β ¼ -0.054, p > 0.05) and high level (β ¼ 0.037, p >
12
Md.U.H. Uzir et al.
Heliyon 6 (2020) e05710
Table 8. Moderation effect of social media usage.
Hypothesis
Table 11. Mediated (Perceived Value) moderated (Social Media Usage) effect on
PQ > CS.
Beta and p-Value
Combined Model
Low
Medium
High
PQ→CS
0.190***
0.395***
-0.054
0.037
SQ→CS
0.215***
0.270***
0.131
0.238***
CPV→CS
0.223***
0.262***
0.118
-0.081***
Level
Relationship
Parameter
Comments
Low
Direct
0.121***
No Mediation
Mediation
0.123***
Indirect
0.004 (NS)
Lower Band: -0.006
Upper Band: 0.039
Note: *** indicates significant.
Mid
Table 9. Moderating effect of social media usage.
Hypothesis
Direct
0.126***
Mediation
0.118***
Indirect
0.004 (NS)
Lower Band: -0.007
Upper Band: 0.034
Beta and p-Value
Combined Model
Low
Medium
High
High
PQ→CS
0.190***
0.395***
-0.054
0.037
SQ→CS
0.215***
0.270***
0.131
0.238***
CPV→CS
0.223***
0.262***
0.118
-0.081***
Direct
0.166***
Mediation
0.149***
Indirect
0.005 (NS)
Lower Band: -0.009
Upper Band: 0.036
No Mediation
No Mediation
*** Significant (p < 0.001).
them more benefits than expenditure, the customers become happy The
customers assess how much benefits they are getting using this electronic
over paying such amount.
The fourth Hypothesis was regarding a significant relationship between product quality and perceived value, and it was insignificant statistically (hypothesis 4). This finding is rare that product quality does not
affect value perception. It is due to the perception of Bangladeshi customers like electronics products will meet their needs as usual. Product
quality, its functionality, durability and usefulness are common characteristics. They pay money and hope that product will function properly.
Therefore, their value perception is not affected. The fifth hypothesis,
which was the relationship between service quality and perceived value,
was significant. This finding is consistent with the result of Lai (2015);
Thielemann et al. (2018). Customers in Bangladesh prioritize services such
as installation, delivery, after-sales service, etc. to form a value about
those services and products. Higher services generate a psychological
attachment in the customers that is the spending is worthy. This positive
feeling regarding the electronics home appliances service creates a strong
perception about service.
The study found that customer perceived value does not mediate the
relationship between product quality and customer satisfaction (Hypothesis 6). In customers’ beliefs, electronics products are liberally
similar in quality, functionality, and features. Meeting the customers’
needs independently are sufficient as far as product and its functional
quality are concerned. If the utility and household electronics appliances
are safe, convenient to use, durable, and are of fashionable features (like
their studies. The findings of the current study also match with the study
findings by Ali and Raza (2015); Beigi et al. (2016); Chinomona et al.
(2013); Kondasani and Panda (2015). Mostly, this significant finding
corresponds to the result of Uddin (2013) in electronics home appliances
in Bangladesh.
Bangladeshi customers expect the sales personnel to demonstrate how
to use, to guide regarding the utility and installation process of the
electronic items at home. Moreover, customers expect to receive the
after-sale service, repairing service and replacement in case of malfunctioning. As technical supports, electronic equipment or products have
some guidelines to be followed for security purpose or these items to be
assembled, or fixed at home. A quick, smooth and passionate support and
service in setting, installation and repairing matter a lot. If these services
are useful, customers are likely to be highly satisfied. Therefore, quality
(timely, quick and practical) of service ensures customer satisfaction.
According to expectancy disconfirmation theory, customer satisfaction
comes from service quality. If the service of sale personnel meets the
requirements of customers, it will ultimately ensure satisfaction leading
to next purchase.
In the third Hypothesis, customers’ perceived value was found to
have a positive and significant effect on customer satisfaction. Collaboratively, the study_ results of Chen (2008); Frank and Enkawa (2007); Hu
et al. (2009); Uddin and Akhter (2012) and Uddin (2013) affirmed that
customers’ perceived value influences customer satisfaction significantly.
Several recent findings also reflect that customer perceived value is
essential for customer satisfaction (Chen and Lin, 2015; Ramseook-Munhurrun et al., 2015; Unyathanakorn and Rompho, 2014). Customer
satisfaction depends, most unlikely on product quality and quality of
service, and the perception of a customer. If electronics home appliances
are purposeful for the customers, they will be happy and delighted.
Customers compare the expectation before the usage of an electronic
item such as television, fridge, washing machine, etc. to their actual
experience during and post usage of those items. Practically, it means
that customers assume that their spending is worthy and also_they win in
this purchase. Similar to EDT theory, if purchasing and using of electronic
items ensure comfort like the customer that this purchase or usage offer
Table 12. Mediated (Perceived Value) moderated (Social Media) effect on SQ >
CS.
Level
Relationship
Parameter
Comments
Low
Direct
0.181***
No Mediation
Mediation
0.175***
Indirect
0.016 (NS)
Lower Band: -0.001
Upper Band: 0.062
Mid
Direct
0.204***
Mediation
0.177***
Indirect
0.004 (NS)
Lower Band: -0.001
Upper Band: 0.064
Table 10. Usage of social media.
Usage of Social Media
Frequency
Percentage
Low
92
30.70
Medium
96
32.00
High
114
37.30
High
13
Direct
0.2466***
Mediation
0.202***
Indirect
0.019 (NS)
Lower Band: 0.000
Upper Band: 0.070
No Mediation
No Mediation
Md.U.H. Uzir et al.
Heliyon 6 (2020) e05710
relationships. The purchasers and users of electronics items in
Bangladesh were the target population of the study. Findings of the study
indicated that product quality and quality of service of electronic home
appliance items ensure the customer satisfaction. Though perceived value
does not mediate the product quality-satisfaction relationship but mediates quality of service-satisfaction relationship partially. Moreover,
perceived value does not mediate these relationships at various levels of
social media usage. Since social media is popular in all walks of life,
online survey method was used in this study. Moreover, social media is a
moderating variable in this study, therefore the authors tried their best to
utilize technology. The main objective was to explore the relationship of
product quality, service quality, and perceived value on customer satisfaction in connection with social media. The findings of this study are
very consistent with the previous findings.
Additionally, the impact of social media has also been diagnosed.
Various levels of involvement in social media have a substantial impact
on customer satisfaction.
in colour, shape, etc.), the product ensures the customer satisfaction.
Bangladeshi customers first look into the product, its functionality and
durability satisfaction.
On the other hand, it mediates the relationship between quality of
service and customer satisfaction (Hypothesis 7). Service quality is a
subjective judgement, and perceived value is also a psychological state of
customers. If customers perceive that service is enough with proper delivery and installation of the electronic items, as well as services are
worthy compared to their spending, these will ultimately ensure
customer satisfaction and customer perceived value will enhance the
relationship. Customers consider how smooth service is provided in case
of installation, repairing guidelines, and after-sale service. Another issue
is that many companies do not exchange sold items, or replace malfunctioned items. So, customers are very concerned while purchasing or
using an electronic item. As a result, customer perceived value has an
indirect effect on the quality of service and customer satisfaction.
The moderating role of social media usage refers to the impact, for
example, how various levels of customer involvement in social media
affect customer satisfaction with product quality and services. The study
found the moderating effect of social media. The usage level of social
media affects the relationships between independent variables and
customer satisfaction (Hypotheses 8a, 8b, and 8c). In regard to product
and customer relationship (Hypothesis 8a), this relationship is significant
for low-level users but insignificant for the mid-level and high-level users.
Here, low level users believe in the information, reviews, comments, and
recommendations of product quality. Low involved-customers in Bangladesh
consider that social media is a trusted source of information. On the other
hand, the customers who are highly involved in social media do not
consider the message information, comments, recommendations; rather,
they care about the quality of products. As regard to the relationship with
the quality of service (hypothesis 8b), social media usage affects the
relationship. For low and high level users of social media, this relationship between service quality and customer satisfaction is significant but
insignificant for mid-level users. The message information, comments,
recommendations regarding service quality of electronics home appliances are viable for lower and higher level customers; the information
(found in the social media is not considerable for mid level users as regard to ensuring satisfaction with service.Similarly, low and high level
users consider that the news, comments and reviews posted in the social
media develop the feeling such as their investment to purchase the
electronic home appliances is fruitful and satisfactory. But midlevel users
are ignorant. Finally, the indirect relationships of customer perceived value
between product quality and customer satisfaction and between the quality of
service and customer satisfaction at various level of social media usage were
insignificant. The findings showed that these two indirect (mediating role)
relationships of customer perceived value are insignificant with various
level of customer involvement in social media. As a result, customers are
indifferent in assuming perceived value though thy are involved in social
media.
Usage of modern technology, especially social media, customer
choice, preference and usage pattern of the product has been changed
and shifted from traditional behaviour. Facebook, FB messenger, WhatsApp are mainly used in Bangladesh. Various companies have targeted
these social media for a communication and advertisement platform.
These companies are spending a significant amount of money for an
advertisement of products and services. With one feature, i.e. sponsored
advertisement (spending money for advertising their products and service) companies are targeting their audience quickly. Therefore, accessibility has increased. The level of social media usage has a moderating
effect on customer satisfaction.
6.1. Implications
This type of study is first in Bangladesh. To the best of the authors’
knowledge, there is hardly any study as regard to examine customer
satisfaction in electronics home appliances. The findings of the study can
assist the managers and decision-makers involved in national and
multinational companies focusing on customer satisfaction; the components are product quality, service quality, and customer perceived value.
They may concentrate on product quality, ensuring the quality of service
as well as providing more benefits in comparison to price or cost of the
product.
6.1.1. Managerial implications
Customer and the brand of electronics home products require a successful relationship. This successful relationship lasts long once both
parties attain their respective objectives. The study found the quality of
electronics home appliances has a significant and positive relationship on
customers satisfaction. The brand managers, the company, showroom
owners, retailers, and other concerned authority may focus on developing and improving the quality. Customer assessment program, loyalty
program, customer interview, and random customer selection for focus
group discussion may produce some insights regarding product development. Based on the information collected from the customers and users of
electronics household items, the company can offer new products with new
features, shapes, models and colours. Household items not only meet the
requirement but also indicate the status, choice, and taste of a family.
Electronics products sometimes can be some causes of dangers due to
blast, short-circuit, firing, etc. Therefore, product safety is also a concern
of the customers. The company and brand (especially local companies
and local brands) can form a customer panel and expert panel to address
these developments and difficulties. According to their opinions, new
products can be introduced in the market. This initiative may increase
the satisfaction of customers and users of electronics home appliances.
Similarly, the quality of after-sale service has a significant impact on
satisfaction. The electronics home appliance needs some services during
and post-selling stages. Delivery service is essential in regard to large
home appliances such as fridge, air conditioners, large TV, etc. The
company can arrange instant delivery service so that sooner the customer
purchases an item, it can be delivered. Customers usually do not want to
wait after purchasing (paying bills). The prompt service may delight the
customers.
Similarly, the installation service is also significant issue. Technicians
should be ready to move with the product or immediately after the delivery of the product at the customer’s point. Smooth technical installation services, instruction on usage may increase the image of the
company, ensuring customer satisfaction. Company and showroom
owners can ensure the availability of technical team for these mentioned
services (expert team with carrying van).
6. Conclusion and recommendations
The study attempted to examine the relationship between product
quality, service quality with customer satisfaction, and how customers’
perceived value mediates and social media moderates these
14
Md.U.H. Uzir et al.
Heliyon 6 (2020) e05710
marketing research. b. Only product quality, quality of service, customers’ perceived value and social media are not sufficient to explain
customer satisfaction of electronics home appliances. Some other variables such as price, brand image, customer experiences, brand knowledge, verbal recommendation, and country of origin might lead to a
better understanding. Similarly, the different associations can be integrated into the research model. Judgmental sampling technique is not
proper technique to select the appropriate respondents. Other sampling
techniques may even be tried for better output. The intercept sampling
method can be appropriate in this regard to collect data from respondents
at a particular time, particular day of the week.
Once their perception of this comparison between expectation and
benefit is positive there is a strong possibility to be loyal to the brand. In
relation to electronics home appliances, this comparison and perception
exist to a large extent. Therefore, with continuous product development,
the company should a strategy to judge customer perception. Management can offer assessment program for the customers, can form online
customer group or community or can arrange or set compliant boxes in
showrooms, display centers or provide an e-mail address to put their
opinions, comments, assessments or recommendations, etc. Management
can offer assessment program for the customers, can form online
customer group or community, can arrange or set compliant boxes in
showrooms, display centers or provide an e-mail address to put their
opinions, comments, assessments or recommendations The practicing
managers can select some customers and select some customers and
consider their own opinions as well as their friends and family members
on regular basis. Marketing managers consider the marketing research
data of customer satisfaction, trust, and related information that reflect
the brand’s components. The practicing managers should consider these
issues in their daily, monthly and yearly plan.
As social media and its usage strengthen the customer brand and
customer relationship, the companies can focus on social media. They
may launch company’s online account (e.g., Facebook, Twitter, LinkedIn) wherein they can share company, brand and product information.
They may maintain a cat’s eye on social media. Any false propaganda and
news should be under company consideration and necessary actions
should be taken to resolve those issues. Press news, social media advertisement can be fruitful in this regard.
6.2.1. Future directions
Prospective researchers on this type of study can focus on other
constructs such as price, brand image, customer experiences, brand
knowledge, word of mouth, and country of origin. Further research can
also be done on a specific home appliance such only tv, or fridge, or
washing machine or air conditioners.
Declarations
Author contribution statement
MD U.H. Uzir: Conceived and designed the experiments; Performed
the experiments; Analyzed and interpreted the data; Contributed reagents, materials, analysis tools or data; Wrote the paper.
I. Jerin: Conceived and designed the experiments.
H. Al Halbusi: Performed the experiments; Analyzed and interpreted
the data.
A.B.A. Hamid: Conceived and designed the experiments; Wrote the
paper.
A.S.A. Latiff: Contributed reagents, materials, analysis tools or data;
Wrote the paper.
6.1.2. Theoretical implications
Many researchers might want to replicate the study in other countries
and cultural contexts, for example, a large population in a developing
country. This study findings can contribute in several ways to the current
body of knowledge in the context of slow-moving consumer durables.
The findings may also add contribution by supporting the assumption
that is expectation disconfirmation theory (EDT). The constructs-product
quality and quality of service considering the indirect effect of customer
perceived and interaction effect of usage level of social media can
contribute to the literature of electronics home appliances, brand loyalty
and customer satisfaction. This study is possibly the first one on electronics home appliances where customer satisfaction was examined with
social media usage in the Bangladeshi context. It added a knowledgeview in EDT theory in this context such way: use of second-generation
statistical tools (SEM-AMOS). Investigating the usage of social in this
context, especially, in physical products context is a milestone. Previously, service quality and its five or six dimensions were used; the authors
of the current study used quality of service in the form of delivery service;
besides installation service and other after-sale service were brought into
this model. Social media usage and its moderation in mediating relationship are also a contributing aspects for the literature. The findings
generalize many developing countries where the population is large as
well as income and education level are not that high.
Funding statement
This research did not receive any specific grant from funding agencies
in the public, commercial, or not-for-profit sectors.
Data availability statement
Data will be made available on request.
Declaration of interests statement
The authors declare no conflict of interest.
Additional information
No additional information is available for this paper.
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