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which shows that the customers of the pharmacy don’t have much expectations on the product quality which include the product variety and
product durability. It was concluded that in this study, product quality did not matter, nor did it have no positive and significant impact on
customer satisfaction with Muhibbah Jaya Pharmacy.
H3: Facilities have a positive and significant impact on customer satisfaction with pharmacy.
The facilities have a positive and significant impact on customer satisfaction with pharmacy. Accept this proposed hypothesis by referring
to the significant value (p-value) in the regression analysis. This hypothesis was accepted with p-value at 0.041 (p<0.05). The finding is
consistent with Hui et al. (2013) which stated facilities play an important role in customer satisfaction. The previous research of Harisman
el al. (2021) also found that the facility significantly and positively affects customer satisfaction at pharmacy. As a result, it may be stated
that the facility must exist in the organization before a subscription can be given. The facilities' interior and external design, as well as their
cleanliness, must be maintained, particularly in terms of what the client feels immediately. Nawangwulan et al. (2012) findings show that
building conditions and facilities have a significant impact on consumer satisfaction. The findings are also in line with previous research by
Azhar et al. (2019) and Faeni & Faeni (2018) which found the facility is positive and significant impact on customer satisfaction. Thus, this
means the facilities have a positive and significant impact on customer satisfaction with Muhibbah Jaya Pharmacy. During peak periods,
customers may have to wait in line at the pharmacy to purchase medications. As a result, customers appear to be more satisfied with a
pharmacy that has a pleasant waiting area (Do and Foulon, 2018). In this dimension, three items are examined, namely store layout,
cleanliness and atmosphere, and product display. In the customer satisfaction level analysis, facilities get 89.3% score which is a high
satisfaction level. Muhibbah Jaya Pharmacy may maintain or improve the facilities as when the facilities improve, it will improve the
customer satisfaction with the pharmacy.
H4: Reliability has a positive and significant impact on customer satisfaction with pharmacy.
The research findings show that reliability has a positive and significant impact on customer satisfaction with pharmacy. The results from
regression analysis show the hypothesis is accepted by having a p-value at 0.000 (p<0.05). This result is in line with previous research from
Barusman (2019), Janahi and Mubarak (2017), and Minh et al. (2015). In contrast, this research finding is inconsistent with Munusamy et al
(2010), which responded that reliability has no significant impact on customer satisfaction. However, dimensions of reliability include
honouring promises, providing accurate and timely service, and ensuring a safe and secure stay (Minh et al., 2015). Research from Fauziah
et al. (2019) found that reliability is the important dimension in determining the customer satisfaction of a pharmacy. Customers of a
pharmacy will certainly expect the pharmacy to deliver the service at the promised time. In this research, the reliability dimension is evaluated
by the accuracy of receipt, correct product price and reservation promise. Customers of Muhibbah Jaya Pharmacy give a high satisfaction
level to this dimension with 88.8%. The analysis shows the pharmacy has achieved their customer expectation on reliability. To conclude
this, the reliability has a positive and significant impact on customer satisfaction with Muhibbah Jaya Pharmacy. The pharmacy may maintain
and can have an improvement in order to increase higher customer satisfaction.
H5: Process has a positive and significant impact on customer satisfaction with pharmacy.
The fifth hypothesis is accepted in this study. Process factor has a positive and significant impact on customer satisfaction with pharmacy.
This hypothesis was accepted with p-value at 0.032 (p<0.05). The finding is consistent with previous research from Chan and Wong (2006),
Khatab at al. (2019) and Ortiz (2020), where the process has a positive and significant impact on customer satisfaction. Keshavarz and
Jamshidi (2018) supported that process quality has a significant relationship with customer satisfaction. The items investigated under this
dimension are the operation time and transaction process at counters. Customers frequently wish to purchase medications at any time, thus
a pharmacy that is open throughout business hours has an impact on customer satisfaction (Do and Foulon, 2018). By referring to the customer
satisfaction level analysis, the process dimension has the highest score of all dimensions at 94%. The results show the customers of Muhibbah
Jaya Pharmacy have a high satisfaction level to their operation time and transaction process. Pharmacy can maintain or improve service
processes to achieve higher levels of customer satisfaction since the process has a significant impact on customer satisfaction. Improvements
to processes are vital since they will lower total prescription fulfilment time, enhance consumer satisfaction, and improve the pharmacy's
organisation and structure (Ortiz, 2020). In conclusion, the process dimension has the highest level of customer satisfaction and has a positive
and significant impact on customer satisfaction with pharmacy.
H6: Value for money has a positive and significant impact on customer satisfaction with pharmacy.
The research found that the value for money has a positive and significant impact on customer satisfaction with pharmacy. The result shown
at multiple regression analysis obtained the significant value (p-value) of value for money is 0.000 (p < 0.05). Therefore, this hypothesis is
accepted: Value for money has a positive and significant impact on customer satisfaction with Muhibbah Jaya Pharmacy. The result is
inconsistent with previous research from Sriratanavit (2015) and Harisman el al. (2021) which proved that drug price does not significantly
affect customer satisfaction at the pharmacy. However, the research outcome is consistent with the previous from Indriana (2021), Guhl et
al. (2019) and Celil Cakici et al. (2019), which showed the customer value has a positive impact on customer satisfaction. The element under
value for money in this research is the competitive price and the frequency of promotions or discounts. With a beta value of 0.385, value for
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903 Tam & Adaviah (2022)
money is the highest predictor of customer satisfaction. Consumer satisfaction is influenced by pricing; if the price is acceptable and
equivalent to the product or service supplied, the customer will be satisfied. Customer satisfaction will drop if customers believe the prices
paid are not equivalent to the services they obtain (Indriana, 2021). Similarly, if the company's pricing is significantly more than its
competitors' without any distinct benefits over the services supplied, the consumer would be dissatisfied. In the customer satisfaction level
analysis, value for money had the least score with 78.8%. The results show the customers of Muhibbah Jaya Pharmacy had the least
satisfaction on value for money. Drugs are sold on the open market, with merchants and market forces determining drug costs. Customers
typically study and compare medicine costs at many pharmacies before asking for the lowest price at the pharmacy they have visited
previously. Customers have additional options from different retail pharmacies, as well as branded and generic medicines. Most people visit
many pharmacies to compare pricing and select the one that gives the best deal on the medicine they want. To conclude, value for money
has a positive and significant impact on customer satisfaction with pharmacy and also the highest predictor of customer satisfaction.
Pharmacy should focus on their pricing strategy, try to provide product value to customers and offer more promotion events to enhance
customer satisfaction.
H7: Service quality has a positive and significant impact on customer satisfaction with pharmacy.
The research findings show that the service quality has a positive and significant impact on customer satisfaction with pharmacy. This
hypothesis was accepted with p-value at 0.000 (p<0.05). The result is consistent with the previous research conducted by Anwar et al. (2019),
Harisman el al. (2021), and DAM et al. (2021). Ruzaihan, et al (2020) findings showed that service quality has a significant positive impact
on customer satisfaction on pharmaceutical stores. According to Parasuraman et al. (1988), service quality is defined as a customer's total
quality rating of a service provider based on a comparison of the customer's expectations with the perceived quality they get. The
characteristics that most affected satisfaction, according to Mahmoud and Mahmoud (2016), were pharmacy location, service quality, and
pharmacists' ability to read medication instructions. When it comes to service quality, the majority of aspects are connected to customer
satisfaction, which means that if service quality or performance does not satisfy the expectations of the customer, people will think about
and make judgments based on that quality (Anwar & Balcioglu, 2016). The items investigated under this dimension are the friendliness of
staff, employee knowledge, performance of staff, availability of staff to offer help. Based on the customer satisfaction level analysis, the
service quality is in high satisfaction level with a score of 89.9%. Customers want staff to be able to deal with them, offer clear and intelligible
drug information, and be knowledgeable enough to deliver correct service (Fauziah et al, 2019). Improving service quality means improving
product utilization and increasing satisfaction (Abdullah et al. 2017). As a result, when it comes to improving services, community
pharmacists should evaluate staff performance, and pharmacy employees should obtain adequate training and enhanced communication
skills. In conclusion, service quality has a positive and significant impact on customer satisfaction with pharmacy. Training programs can be
offered to employees due to the impact on customer satisfaction.
5.3 RESEARCH IMPLICATION
This study has investigated the factors that have positive and significant impacts on customer satisfaction for pharmacy. The research
findings found that the 5 dimensions which include facilities, reliability, process, value for money, and service quality have positive and
significant impact on customer satisfaction. In contrast, dimensions of additional services and product quality have no positive and significant
impact on customer satisfaction. Muhibbah Jaya Pharmacy should pay attention to dimension value of money due to the dimension being
the highest predictor of customer satisfaction and with least satisfaction among all dimensions. Pharmacy should focus on their pricing
strategy and develop prices that are more acceptable to customers. Another recommendation is that the pharmacy can train employees to
demonstrate and deliver product value to customers, and try to offer more promotion events to enhance customer satisfaction.
This study adds to the existing literature and helps marketers understand customer satisfaction, as well as providing pharmacies
recommendations and directions for improvement in order to boost customer satisfaction and retention. Therefore, if pharmacies take
customer perspectives into account and focus on relevant service elements, they may increase customer satisfaction and loyalty. To improve
effectiveness, personal interaction appears to be the most important factor for proper resolution. The location of the pharmacy should also
be easily accessible and convenient for customers. As a result, marketers and company owners should keep an eye on how to satisfy
consumers and boost customer satisfaction in order to increase customer retention and profit. High satisfaction will give customers a good
image of the company and create good word of mouth. If not, low satisfaction allows customers to spread their unpleasant buying experience,
which can lead to other consumers shunning the brand.
5.4 LIMITATION OF STUDY AND RECOMMENDATIONS
The study has various limitations that might be addressed in the future. The study was conducted in only one pharmacy which is
Muhibbah Jaya Pharmacy and the questionnaire was only distributed to the customers of the Muhibbah Jaya Pharmacy. The respondents
were limited to consumers near the Muhibbah Jaya Pharmacy area. Future research could expand the range of respondents by including more
pharmacies and other locations. There are limitations to conducting academic research in rural areas, and most target respondents are not
concerned with the purpose and significance of the research. Researchers can use simpler questions or simpler methods to create
questionnaires that allow respondents to understand what the questionnaire means.
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904 Tam & Adaviah (2022)
Moreover, there are limitations to conducting an investigation, especially during the Covid-19 pandemic. With offline surveys, most
targeted respondents are reluctant to conduct in-person surveys during this pandemic. Regarding the method of the online survey, as a
limitation of connecting the target respondents online, the researchers asked the pharmacy owner for a membership list to distribute the
survey through the customer WhatsApp number. This resulted in a high level of satisfaction for most respondents as most respondents were
members of the pharmacy. For future research, it should reduce the loyal consumer or high satisfaction-based respondents to answer the
customer satisfaction survey. Due to constraints in distributing the survey, the study had a small number of respondents, only 155 respondents.
Future research needs to increase the number and variety of respondents. These will improve the accuracy of the data, and lead to better results
and analysis.
Finally, the quantitative method used in this study also has limitations. Future researchers can engage in two-way communication with
respondents through qualitative research such as interviews, where researchers can clearly explain research areas and gain deeper insights
from respondents.
■ 6.0 APPRECIATION
Here I am very grateful to my parents, advisor and friends for their guidance, encouragement and help throughout the research process.
Additionally, I would like to sincerely thank the pharmacy owner for her generosity in supporting the survey by providing each respondent
with membership points. It is difficult to conduct an offline survey especially during the pandemic period. I would also like to thank each of
the respondents for their willingness to take the time and effort to answer my questionnaire. Their generous participation allowed me to
successfully complete this dissertation.
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FYP PRESENTATION
JANUARY 2022
AHIBS UTM
EFFECT OF REFERENCE PRICE TOWARD CUSTOMER PURCHASE INTENTION ON FROZEN FOOD: A
CASE STUDY AT RESTAURANT VEGETARIAN S.I. JIN WEI
TAN YI TING, DR ADAVIAH MAS’OD
Azman Hashim International Business School, Universiti Teknologi Malaysia, Johor Bahru
*Corresponding author: [email protected] & [email protected]
Abstrak
Penularan wabak Covid-19 telah menyebabkan harga makanan meningkat melebihi kadar inflasi
purata. Oleh itu, harga yang sanggup dibayar oleh pelanggan terhadap sesuatu barang atau
perkhidmatan akan bergantung kepada kepenggunaan. Harga rujukan merupakan harga yang dijangka
dan perlu dibayar oleh pelanggan. Harga rujukan terdiri daripada dalaman (berasaskan ingatan) atau
luaran (berasaskan rangsangan). Pelanggan akan bertindak sensitif terhadap harga rujukan adalah
disebabkan harga rujukan boleh mengubah persepsi mereka terhadap nilai. Jadi, kajian ini dijalankan
adalah untuk mengkaji kesan harga rujukan termasuklah harga lepas, kadar lawatan, ciri-ciri
pelanggan, persekitaran dan kategori produk terhadap niat pembelian para pelanggan. Kaedah
kuantitatif dijalankan dengan mengedarkan 170 soal selidik secara talian melalui Borang
Google.Responden yang diisasarkan adalah individu yang pernah membeli makanan sejuk beku di
Restaurant Vegetarian S.I. Jin Wei dengan menggunakan teknik persampelan bertujuan. SPSS
computer software akan digunakan untuk menganalisi data yang dikumpul daripada soal selidik.Hasil
kajian menunjukkan harga lepas, bilangan lawatan, ciri-ciri pelanggan dan kategori produk akan
mempengaruhi niat pembelian para pelanggan. Selain itu, kesan persekitaran tidak akan
mempengaruhi niat pembelian para pelanggan. Sebagai kesimpulan, penemuan diperolehi daripada
kajian diharapkan untuk memberi pandangan serta garis panduan kepada usahawan mengenai kesan
harga rujukan terhadap niat pembelian para pelanggan.
Kata Kunci: Harga rujukan, Niat pembelian pelanggan
Abstract
With the start of Covid-19 pandemic, food prices increased faster than average inflation globally.
Therefore, the price willing to pay by the customers for products/services depends on utility. Reference
price defined as the price assumption needed to pay by customers which can be appeared in terms of
internal (memory-based) or external (stimulus-based). Customers act sensitively as the reference
pricing can change their perception of its value. Hence, researcher aims to examine the effect of
reference price including price history, store visit history, customer characteristics, store environment
and product category on customer purchase intention. Quantitative method was adopted by
distributing 170 sets of online questionnaires through Google Form. Target respondents were chosen
from the individuals with the buying experience on frozen food at Restaurant Vegetarian S.I. Jin Wei
by using the purposive sampling technique. SPSS computer software was used for data analysis.
Findings illustrated that price history, store visit history, customer characteristics and product
category have influenced the customer purchase intention positively and significantly. In contrast,
store environment will not significantly influence customer purchase
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intention. To conclude, findings are expected to provide insights and guidance to the entrepreneurs on
the effect of reference price in order to enhance customer purchase intention.
Keywords: Reference price, Customer purchase intention
1.0 INTRODUCTION
Price is one of the most flexible elements in the marketing mix (Kemmer & Boden, 2013) for
Restaurant Vegetarian S.I Jin Wei in selling their products to the final customers as well as retailers. It
is a charge that must be paid by the customer in order to receive a product or service. Addition to that,
price is one of the marketing variables which is the easiest part to change and copy by other
competitors. Customers will seek particular products or services to satisfy their needs and wants. Thus,
customers will judge the value based on how much they are willing to spend and the price they are
willing to pay to satisfy their needs and wants. Generally, customers are not willing to pay higher and
want to pay as little as possible. Before making a purchase decision, customers will set their own
price expectations towards certain products or services. Price expectations are always used as the
reference points to compare the price. It is human nature to compare, judge the value based on the
comparisons. Most of the customers will consider purchasing something if the price of the products or
services matched with their perceived value.
Reference pricing is one of the ways that framing a price can change customer perception of its
value. Reference price is defined as the amount or value expected by customers to pay against the
actual price of the product (Bruno, Hai & Dutta, 2012; Kopalle, Kannan, Boldt & Arora, 2012; Kumar
1998; Rajendran & Tellis 1994). There is an assumption that customers only rely on reference prices
instead of the absolute price of the products or services (Kopalle, Kannan, Boldt & Arora, 2012; Thaler,
1985). Sometimes, reference prices also can come from the subconscious level and even the price of
unrelated products in relation to affect customer perceived value towards the products and services.
Reference prices can come from the internal part as well as the external part (Mayhew & Winer, 1992)
A majority of researchers have assumed that internal reference price is based on memory for prices
encountered by customers on previous observations, stored in customers’ memory, recalled and
reevaluated as occasion demand. Past experiences come out with a reasonable expectation on how
much a product or service should cost. However, some customers may have little experience with
certain products, especially in services where intangibility and heterogeneity make it difficult for the
customer to judge the appropriate price. External reference price is formed at the point of purchase and
it doesn’t relate to customers’ past information in memory. External reference price can be influenced
by the choice of environment and its product category. Some consumers may be sensitive to the drivers
other than price, but it’s true that price is one of the major variables that might influence customers'
purchase decisions. This is because price information influences the perceived cost and perceived value
of the products or services (Abrate et al., 2019; Bornemann and Homburg, 2011). Normally, customers
will make their product choice by comparing the actual price of the product with the internal and
external reference price.
1.1 PROBLEM STATEMENT
The World Health Organization (WHO) declared the outbreak of coronavirus disease 2019 (Covid-19)
as pandemic on March 11, 2020. Keep the pandemic under control and restrain the spread of the virus
becoming the top international priority (Huang et al., 2020; Paules, Marston, & Fauci, 2020; Wang,
Wang, et al., 2020). Covid-19 pandemic has changed our lives. Many countries around the world
adopted unprecedented enforcement to restrict the public and stop the community from spreading.
Today’s companies have to confront an overwhelming, competitive and challenging environment. In
response to the Covid-19 pandemic, the Malaysian government enforced a
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Movement Control Order (MCO). During MCO, a series of enforcement measures carried out by the
government included closing all government and private premises except for those essential services
and announced travel bans on foreigners entering Malaysia and on Malaysians leaving the country,
even the restriction of movement within the country. All of these business sectors such as the primary
sector, secondary sector and tertiary sector have been threatened by this pandemic.
On the other hand, due to the Covid-19 pandemic, there was widespread panic among people.
Supply disruptions and the higher demand from customers stockpiling food, toilet paper, mask and
hand sanitizer cause the price of these essential products to increase substantially. It is unavoidable that
Restaurant Vegetarian S.I Jin Wei also faced the disruption of its raw material supply such as oil, raw
mushrooms and fried chicken powder. Raw material shortage will definitely affect the manufacturing.
The impacts from such disturbances may bring to high lead time, increase production cost, lower
production level and even increase the product selling price. Furthermore, the Consumer Price Index
(CPI) of food has increased faster than overall CPI in all regions of the world. Globally, food prices
increase faster than average inflation with the start of a pandemic. Therefore, the price of a customer
willing to pay for products and services depends on its utility. The total utility is defined as the
aggregate amount of satisfaction gained by customers through the consumption of products or services.
Total utility is associated with acquisition utility and transaction utility in consumption choice.
Acquisition utility can be obtained by acquiring the product’s need satisfying attributes at a given price.
Meanwhile, transaction utility is the payoff of customers derived from realization that the purchase
price is less than their reference price. Under stockout situations in which consumers "have to" buy the
product, they derive both acquisition utility and transaction utility from the purchase. When they have
the option to wait (non-stockout), however, the emphasis placed on the acquisition utility will be lower,
because they don't need to buy the product right away. In other words, the consumer's transaction utility
under stockout conditions will be less than under non-stockout conditions.
2.0 LITERATURE REVIEW
Literature review consists of frozen food, reference price and customer purchase intention.
2.1.1 FROZEN FOOD
Frozen food and ready to cook food markets have been rapidly expanding and show significant growth
in the market share. It comes from foods related to fish, meat, vegetables, seafood as well as snacks.
Frozen snacks based products can refer to both fish and meat based snacks or vegetable based snacks
including chicken nuggets, meatball, fish ball, fish cakes and spring roll (Arifeen, 2012). According to
the NFRA, consumers nowadays have changed their perception regarding frozen food. Due to the
busy and hectic lifestyle, people are lacking time to prepare their food by themselves. That’s why
consumers’ eating habits are different compared to previous times and they realized the value and
convenience of frozen food for every meal occasion. Food preparation decisions are totally influenced
by the homemaker's time. The factors such as individuals’ time, energy in acquisition, consumption
and disposal must align with the conveniences and food consumption method. People appreciated the
time saving advantages of frozen processed food.
Increasing the use of frozen food trends supported by the dietary consumption which has
transformed from home-cooked to the use of frozen food brings to the growth of the frozen food
industry (Euromonitor International, 2014). Restaurant Vegetarian S.I Jin Wei also took this
opportunity by investing in the frozen food industry and launched their own brand’ frozen vegetable
snacks based products such as Crispy Oyster Mushroom and Mushroom Chop. The brand name is
“Sweet Igloo”. The ingredients for these products are fully free of animal products, no egg and no milk
as it could be consumed by vegetarians and vegans too. Besides, the manufacturer only adopts the high
quality and fresh raw mushrooms even the fast freeze technology in order to ensure
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freshness of the products. Thus, the products are safe to be consumed. Crispy Oyster Mushroom is
the most popular product that everyone loves. Till now, Restaurant Vegetarian S.I Jin Wei is able to
sell its frozen foods in 11 states within Malaysia and Singapore through agents.
2.1.2 REFERENCE PRICE
Price perception of customers always being influenced by reference prices. Reference prices do usually
come from competing products, thus it is important to enhance customers' perception on the product.
The product will become more superior and more expensive. The theoretical foundation of reference
price is Kahneman’s and Tversky’s (1979) prospect theory and it includes reference dependence, loss
aversion and sensitivity decrement in the theory. Previous research (Kalyanaram and Winer, 1995)
identified that the reference price comes from the product price of the last purchase. Furthermore,
customers will always use the reference price to make their choice of bands. Customers’ choice
presents loss aversion while under the influence of reference price. It shows that these characteristics
are aligned with the basic characteristics of prospect theory.
Besides, there are many researchers that have presented that (Hardie et al., 1993; Mazumdar et al.,
2005; Briesch et al., 1997) reference price can be divided in 2 parts named as internal reference price
and external reference price. Internal reference price is based on the past memory and past purchase
experience whereas the external reference price is triggered by external environmental price
incentives. There is a question that arises on which reference price acts significant in customer
purchasing. In the study of Hardie et al. (1993), it portrays that the external reference price acts more
significant than internal reference price. In contrast, Briesch and other researchers (1997) draw an
opposite opinion from their study. Addition to that, according to Mazumdar’s and Papatla’s (2000),
they identified that both internal and external reference prices have an impact and it will vary based on
different market segments. For example, there are certain customers who tend to be more sensitive to
internal reference prices while others may be more sensitive to external reference prices.
The most commonly cited explanation for reference price is based on Helson’s (1947, 1964)
adaptation-level theory, which asserts that judgments are proportional to deviations from a comparison
standard. The context of the adaptation level is quite sensitive presented by the mean of stimuli within
a contextual set (Helson 1964; Wedell 1995). According to Helson’s theory, it explains that there is a
significant relationship between past experiences and an individual's judgement on the present day.
Customers will take into account several criteria such as the reference points of previous judgments,
mean of similar stimuli depending on the recency and salience. Thus, customers’ past experiences and
encounters related to stimuli will be the key drivers to determine the adaptation level. From the view
of Monroe, 1990, customers will use the reference price to weigh average product prices from the
relevant category.
2.1.3 PURCHASE INTENTION
Purchase intention represents consumers’ preference or precedence to purchase a product or service.
Addition to that, purchase intention also describes customers' evaluation towards a product or service
to decide their willingness on whether to buy or not buy (Younus et al., 2015). Purchase intention is a
process related to consumers’ decision making which requires researchers to study about the reason
why customers will purchase certain products or services according to the brand which they are more
favorable. Purchase intention takes place when customers decide to buy a certain product or service
in a particular condition (Mirabi et al., 2015).
2.2 HYPOTHESIS DEVELOPMENT
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There There are 5 hypotheses proposed in this study to identify the relationship between price history,
store visit history, customer characteristics on internal reference price and store environment, product
category on external reference price toward customer purchase intention.
2.2.1 INTERNAL REFERENCE PRICE
2.2.1.1 Price History
Wenzel and Martin’s (2011) research identified that price expectation and customer purchase intention
are significantly influenced by trend, range and variance of past price. Price history involves the last
price paid or “price image” that might influence how the customers act to the price change. For internal
reference price customers, they will remember the past price and use that information to monitor the
pricing environment and make the purchase decision based on their adaption-level. There is the direct
relationship between changes in the environment and customers’ behavior. This study predicts price
history may influence internal reference price. Thus, this study posits:
H1: Price history will positively and significantly influence customer purchase intention.
2.2.1.2 Store Visit History
Effect of repetition takes place on the frequent visit to a particular store. Repetition tends to increase
consumers’ confidence in price knowledge and price information. Bell and Bucklin (1996) suggested
that consumers’ familiarity interacts with store visits on a given trip or the store visit history of the
consumer. The interactions of reference price effects are shown by the generally higher effects on the
purchase probability more familiar than unfamiliar stores. Moreover, frequent buyers are more
confident than infrequent buyers about their estimates of regular prices (Urbany and Dickson 1991),
and they take less time than infrequent buyers to evaluate price (Dickson and Sawyer 1990). Repetition
leads to greater confidence and has also found empirical support in the psychology literature (Dewhurst
and Anderson 1999; Koriat 1993; Zaragoza and Mitchell 1996; also see Menon And Raghubir 2003).
Internal reference price is a malleable construct that is sensitive to phenomenological experiences, thus
it will be affected by this repetition-induced confidence. This study predicts store visit history may
influence internal reference price. Thus, this study posits:
H2: Store visit history will positively and significantly influence customer purchase intention.
2.2.1.3 Customer Characteristics
Through Moon, Russell and Duvvuri’s research (2006), consumers who have brand knowledge can
access an associative network memory model held in the consumer’s mind, which contains information
linked to the deep memory about the brand and its meaning. This knowledge is conceptualized
according to terms of two components: brand awareness and brand image. The higher the levels of
brand awareness and brand image the higher the probability of brand choice and greater consumer
loyalty. Brand loyalty is formed when favorable beliefs and attitudes for the brand are demonstrated
in repeat buying behavior (Keller, 1993). This study predicts customer characteristics may influence
internal reference price. Thus, this study posits:
H3: Customer characteristics will positively and significantly influence customer purchase
intention.
2.2.2 EXTERNAL REFERENCE PRICE
2.2.2.1 Store Environment
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Store environment is the most obvious structure that is related to customers’ brand choice whereas
other product prices displayed in store will be the reference price (Rajendran and Tellis, 1994).
Reference price not just consists of the past prices but also product purchase frequency, store
characteristics, and price trends (Briesch, Krishnamurthi & Mazumdar, 1997). In-store atmosphere is
determined by the physical characteristics of a retail store or space utilization in creating an eye-
catching image to attract customers’ attention and additional human senses such as sound and smell.
A “pleasant” atmosphere triggered a customer buying mood in order to spend more money. This study
predicts the store environment may influence external reference prices. Thus, this study posits:
H4: Store environment will positively and significantly influence customer purchase intention.
2.2.1.2 Product Category
A product able to bring both utilitarian and hedonic benefits (Hirschman and Holbrook, 1982). One
of the sources of hedonic benefits came from the pleasure gained by individuals on the good taste of
food. In contrast, utilitarian benefits (in this case, food) are linked to instrumental functionality such
as low price, low calorie content or high nutritional value. The products mostly seek to provide
consumers with a combination of hedonic and utilitarian benefits. Customers tend to compare the price
information of the brand they buy usually with the nutrition level, ingredients and way to serve before
any consumers’ decision making process. If the customers don’t have any past price information or
past experience, they are likely to use price information from other brands or product categories to
form price expectations for a particular product (Jacobson and Obermiller, 1990). With the speed of
changing human life, frozen food has become the more favourable choices among the individuals. This
study predicts that the product category may influence external reference prices. Thus, this study posits:
H5: Product category will positively and significantly influence customer purchase intention.
2.3 RESEARCH FRAMEWORK MODEL
Figure 1 shows the relationship between price history, store visit history, customer characteristics on
internal reference price and store environment, product category on external reference price toward
customer purchase intention.
Figure 1: Research Framework
3.0 RESEARCH METHODOLOGY
The research methodology consists of research design, population and sampling, sampling technique
and research instrument.
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3.1 RESEARCH DESIGN
Research design includes sources related, methods and techniques used for data collection, data
measurement and data analysis in achieving the research objectives (Akhtar, 2016). Researcher
adopted conclusive research design with descriptive research by using a cross-sectional approach in
this study. The independent variable in this study consists of price history, store visit history, customer
characteristics on internal reference price, store environment and product category on external
reference price. Meanwhile, customer purchase intention is the dependent variable of this study.
3.2 POPULATION AND SAMPLING
Population represents the individuals where the researchers would like to study (Marczyk, DeMatteo,
Festinger, 2005). On the other hand, sample size is considered as the subset of the population to
stand for the population of a study. In this study, the population is the individuals who have the
buying experience at Restaurant Vegetarian S.I. Jin Wei. This study only targeted the respondents
that have bought the frozen foods. Hatcher (2014) sets a minimum subject-to-item ratio of at least
5:1. Tabachnick and Fidell (2013) also presented a subject-to-item ratio method for determining
sample size requirement by considering the number of independent variables. In this study,
researcher wishes to use a minimum subject-to-item ratio to determine the sample size. The total
items in demographic profile (8 items), independent variables (18 items) and dependent variables (4
items). The calculation of the sample size as below:
Demographic = (8 x 5)
= 40
Dependent Variables = (4 x 5)
= 20
Independent Variables = (4 x 5) + (3 x 5) + (4 x 5) + (4 x 5) + (3 x 5)
= 20 + 15 + 20 + 20 + 15
= 90
Total Number of Sample Size = 40 + 20 + 90
= 150 respondents
3.3 SAMPLING TECHNIQUE
Sampling technique is the method used in picking samples from a population and concluding the
population (Helen Barratt, Saran Shantikumar, 2017). In general, sampling technique consists of 2
types such as probability sampling and non-probability sampling methods (Burns & Veeck, 2020).
Probability sampling is a sampling method that offers an equal opportunity for all individuals in the
population to be selected as a research sample (Marczyk, DeMatteo, Festinger, 2005) whereas non-
probability sampling is a sampling method that does not provide an equal opportunity for all
individuals in the population to be selected as a sample (Taherdoost, 2016). In this research, researcher
employs non-probability sampling through purposive sampling techniques to determine the sample.
Purposive sampling is defined as the samples chosen from the population based on judgement of
researchers where the sample selected will definitely make the contribution to this study. This study
targeted the individuals who have the buying experience on frozen foods at Restaurant Vegetarian S.I.
Jin Wei.
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3.4 RESEARCH INSTRUMENT
Research can appear in 2 categories such as quantitative research or qualitative research. Quantitative
research involves formal, systematic measurement and statistical analyses to obtain findings of a study.
On the other hand, most of the qualitative researchers agreed with the observation of (Snider, 2010)
that qualitative research can be conducted through interviews and observations which does not analyze
the findings through formal statistical analyses. Thus, researcher employs the quantitative method via
survey methods by using the questionnaires. The questionnaire in this study consists of Part A which
involves 8 questions related to respondents’ demographic profile whereas Part B consists of 22
questions related to the effect of reference price toward customer purchase intention. The five-points
Likert scale was applied in Part B, so that the respondents can answer the questions based on their level
of agreement. It will be distributed to the targeted respondents by using the google form.
4.0 DATA ANALYSIS
Data analysis is a process of evaluating data collected by using analytical and statistical tools to obtain
useful outcomes for decision making. The statistical techniques will be used for data analysis including
pilot test, descriptive analysis, normality test, reliability test and multiple regression. All of these
quantitative data collected will transfer to SPSS software version 26.0 to obtain the findings.
4.1. (PRE-TEST) PILOT TEST
As mentioned by the study of Whitehead et al., (2015), the pilot test can reduce early problems or
errors as it could help researcher to refine and clarify the questionnaire. The respondents were given
questionnaires by Google Form and researcher will request the respondents to note the problems or
difficulties facing while completing this questionnaire. Based on the pilot test result, the questionnaire
will be re-modified. Browne (1995) also mentioned that at least 30 or more participants must be used
to conduct the pilot test. Thus, researcher will distribute 30 sets of questionnaires to the customers at
Restaurant Vegetarian S.I Jin Wei during semester break. Therefore, the result shows in Table 4.1 that
the overall range of Cronbach’s Alpha is located between the value of 0.617 to 0.937 which are
categorized as accepted reliability value and very good level of reliability value.
Table 4.1 Reliability for Pilot Test
Variable Construct Cronbach’s Alpha No. Of Item
IV 1 Price History 0.781 4
IV 2 Store Visit History 0.742 3
IV 3 Customer Characteristics 0.936 4
IV 4 Store Environment 0.852 4
IV 5 Product Category 0.617 3
DV Customer Purchase Intention 0.937 4
4.2 PROFILE OF RESPONDENTS
Table 4.2 displays the frequency and percentage of respondents’ demographic. In this study, the
questionnaire consists of 8 questions under demographic profile such as gender, age, ethnicity, monthly
income, type of frozen foods, buying frequency and price range on the last purchase as well as expected
price range in the next future.
In this research, there were 96 (56.50%) female respondents who participated in answering
the questionnaire followed by male with 74 (43.50%) respondents. Next, the majority of the
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respondents were in the age between 19 - 28 years old with 79 (46.50%) while the age of 29 - 38 years
old contributed to 35 (20.60%) respondents and followed by 34 (20%) respondents were in the age of
39 - 48 years old. In addition, there were 17 (10%) respondents from the age range within 49 years old
and above, followed by only 5 (2.90%) respondents who were at 18 years old and below.
Moreover, data collected indicated that the highest involvement was from Chinese respondents
with 106 (62.40%), followed by Indian respondents with 40 (23.50%) and Malay
respondents with 24 (14.1%).
Then, most of the respondents with the total of 69 (40.60%) respondents achieved RM 2000
and below for their monthly income while there were 36 (21.20%) respondents recorded the monthly
income of RM 3001 - RM 4000. Followed by RM 2001 - RM 3000 with 30 (17.60%) respondents,
RM 4001 - RM 5000 with 21 (12.40%) respondents and only 14 (8.20%) respondents earn RM 5001
and above for monthly income.
In term of the kind of frozen food often bought by respondents, majority with a total of 53
(31.20%) respondents usually bought frozen ready meals, followed by frozen snack-based products
with 41 (24.20%) respondents, frozen meat and poultry with 33 (19.40%) respondents and frozen dim
sum with 26 (15.30%) respondents. Data collected highlighted that there were only 17 (10%)
respondents who often bought the frozen fish.
Besides, most of the respondents preferred to buy the frozen food once by month with 92
(54.10%) respondents, followed by once per week 70 (41.20%) respondents, only 3 respondents
(1.80%) bought the frozen food everyday and others as only once, twice per month and sometimes
respectively.
In addition, there were 80 (47.10%) respondents mentioned that the price range of frozen
food on their last time purchase were RM 11 - RM 20, while RM 10 and below consists of 34 (20%)
respondents and 30 (17.60%) respondents spent within RM 21 - RM 30 for their last time purchase on
frozen food. Subsequently, the number of respondents who did their purchase at the price range of
RM 41 and above and RM 31 - RM 40 were 17 (10%) respondents and 9 (5.30%) respondents during
the last time.
Furthermore, respondents assumed that the price range of frozen food in the next 3 months will
increase contributed to majority of respondents with 82 (48.20%), followed by 81 (47.60%)
respondents expected that the the price range will be remain the same and only 7 (4.10%) respondents
think that the future price range of frozen food will be decrease.
Table 4.2: Profile of Respondents
Demographic Variables Frequency Percentage
(F) (%)
Gender Female 96 56.50
Male 74 43.50
Age 18 year old and below 5 2.90
19 - 28 years old 79 46.50
29 - 38 years old 35 20.60
39 - 48 years old 34 20
49 years old and above 17 10
Ethnicity Malay 24 14.10
Chinese 106 62.40
Indian 40 23.50
Others: 0 0
Monthly Income RM 2000 and below 69 40.60
RM 2001 - RM 3000 30 17.60
RM 3001 - RM 4000 36 21.20
RM 4001 - RM 5000 21 12.40
RM 5001 and above 14 8.2
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What kind of frozen Frozen ready meals 53 31.20
food do you often buy at Frozen meat and poultry 33 19.40
Restaurant Vegetarian Frozen fish 17 10
S.I. Jin Wei? Frozen dim sum 26 15.30
Frozen snack-based products 41 24.10
How often do you buy Everyday 3 1.80
the frozen foods at Once per week 70 41.20
Restaurant Vegetarian Once per month 92 54.10
S.I. Jin Wei? Others: 5 2.90
The price range of RM 10 and below 34 20
frozen food at the last RM 11 - RM 20 80 47.10
time you bought? RM 21 - RM 30 30 17.60
RM 31 - RM 40 9 5.30
RM 41 and above 17 10
The price range of I expect it will increase 82 48.20
frozen food you I expect it will decrease 7 4.10
expected in the next 3 I expect it will remain the same 81 47.60
months? Others: 0 0
4.2 DESCRIPTIVE ANALYSIS
Descriptive analysis, beginning stage of statistical analysis in SPSS software. It can help to explain the
main characteristics of the respondents' data set. Respondents’ demographic profile data such as
gender, age, ethnicity, monthly income, type of frozen foods, buying frequency and price range on
the last purchase as well as expected price range in the next future can be analyzed by using descriptive
analysis methods. The results of summary data will be presented in either table format, chart format or
histogram format for an easy explanation (Mellinger, 2016).
4.3 NORMALITY TEST
Score measurement for each variable can be done through normality test (Sekaran, Bougie 2010).
These scores should be normally distributed on the dependent variable scores expected in order to
minimize redundancy. The normality test also includes the measurement of skewness and kurtosis and
it is measured by SPSS technique. Hair et al. (2010 highlighted that the data can be considered normally
distributed if the p-value of each item is between -2 to +2 for Skewness test and is between
-7 to +7 for Kurtosis test. Therefore, it can be concluded that the data sets in this study were
normally distributed.
Table 4.4 Normality Test
Descriptive Analysis
Variable Skewness Kurtosis
N Statistic Std Statistic Std
Error Error
Price History 170 -1.102 .186 1.460 .370
Store Visit History 170 -.936 .186 1.046 .370
Customer Characteristics 170 -1.374 .186 2.360 .370
Store Environment 170 -.734 .186 .763 .370
Product Category 170 -.984 .186 .831 .370
Customer Purchase Intention 170 -1.325 .186 1.580 .370
4.4 RELIABILITY TEST
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Reliability tests can ensure the item for each variable has a consistent scale of measurement. In this
study, reliability of the independent variables and dependent variable will be measured through
Cronbach’s Alpha. If the value of Cronbach’s Alpha is higher, it presented that the variable is higher
reliability. A general accepted rule mentioned in previous study of Ursachi, Horodnic & Zait (2015)
that the reliability values of 0.6 to 0.7 are acceptable and 0.8 and above is a very good level. However,
the value of Cronbach’s alpha at 0.7 or more is considered as an acceptable reliability coefficient
(Nunally, 1978). On the other hand, Keith (2016) suggested that the value of Cronbach’s Alpha within
0.45 to 0.98 was considered acceptable, followed by 0.61 to 0.65 as moderate, 0.67 to
0.87 as reasonable, 0.71 to 0.91 as good, 0.73 to 0.95 as high, 0.84 to 0.90 as reliable and 0.93 to
0.94 as excellent. Table 4.5 illustrates the value of Cronbach’s Alpha for reliability test of all the
variables. Hence, all the variables is acceptable and reliable in this study.
Table 4.5: Reliability Test
Construct of IV/DV No. of Items Cronbach’s
Alpha
Price History 4 0.789
Store Visit History 3 0.720
Customer Characteristics 4 0.917
Store Environment 4 0.885
Product Category 3 0.580
Customer Purchase Intention 4 0.897
4.6 MULTIPLE REGRESSIONS
Multiple regression is used to explore the relationship between one continuous dependent variable and
a number of independent variables. In this study, multiple regression is significant to provide the
findings dependent variable (customer purchase intention) and independent variables (price history,
store visit history, customer characteristics, store environment and product category). The main null
hypothesis (H0) of a multiple regression is that there is no relationship between the X variables and
the Y variables whereas the alternative hypothesis (H1) of a multiple regression is that there is the
relationship between the X variables and the Y variables. Therefore, multiple regression may
determine the overall fit of the model and the relative contribution of each independent variable to the
total variance explained.
Standardized regression coefficients through beta were used to identify the direct effects of each
independent variable toward the dependent variable. Beta coefficients can be positive or negative
and it can help to determine the amount of change in the dependent variable which associated with
every one unit change in the independent variable.In this study, the p-value of independent variables
included price history at 0.004, store visit history at 0.031, both customer characteristics and product
category at 0.000 were less than 0.05, therefore all of these independent variables were significantly
influence customer purchase intention. On the other hand, for independent variables of store
environment with p-value more than 0.05 which was 0.406 determined that it was not significantly
related to customer purchase intention.
Table 4.6: Coefficients of Relationship between Independent Variables toward Dependent
Variable
Model Unstandardized Standardized t Sig
Coefficients Coefficients
B Std. Error Beta
1 (Constant) .505 .231 2.187 .030
PH .144 .049 .175 2.950 .004
VH .158 .073 .162 2.173 .031
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CC .321 .068 .345 4.705 .000
SE .057 .069 .054 .834 .406
PC .241 .061 .238 3.950 .000
a. Dependent Variable: Customer Purchase Intention
4.6 DISCUSSION OF FINDINGS
All the findings obtain from various data analysis methods include descriptive analysis, normality test,
reliability test as well as multiple regression will be discussed in this section.
4.6.1 PRICE HISTORY
Since the p-value for price history is less than 0.05 at 0.04 (as shown at Table 4.7.1), thus it shows that
the positive relationship as price history will positively and significantly influence customer purchase
intention. The result is supported by Wenzel and Martin’s (2011) research. As mentioned in Wenzel
and Martin’s (2011) research, past price’s trend, range and variance will influence customer purchase
intention as pricing patterns observed by consumers over time tends to vary (increase, decrease, remain
same) but consumers will automatically create their own price expectation based on the situation.
They will have their own forecasting rules for the price of particular products or services. Customer
purchase intention is always being influenced by their price expectation. Customer purchase
intentions vary based on the kind of price expectation that exists in consumers’ minds. For example, if
consumers encounter the promotion for discounted price frequently in certain shops, they might adjust
to the lower price and may be adverse to paying the normal price during the promotion campaign. As
consumers come along with its past price memories, thus they will develop their own decision rules
which may alter their purchase intention in either way, buying or not buying for their current purchase.
Due to the increase of raw material cost, manufacturers have increased the product selling price which
might affect consumer buying intention if they realize the changes of the price compared to past price.
Therefore, price history will significantly influence customer purchase intention as proposed in this
study.
Table 4.7.1: Summary of Hypothesis Testing - Price History
Independent Variable Hypothesis Result
Price History H1: Price history will p-value = 0.04 < 0.05
positively and significantly Accepted
influence customer purchase
intention.
4.6.2 STORE VISIT HISTORY
As the p-value of store visit history is less than 0.05 at 0.0031 (as shown at Table 4.7.2). Hence, the
result shows that this independent variable will influence the dependent variable positively and
significantly. High visiting frequency to familiar stores will definitely increase consumers’ knowledge
or familiarity with the products and expertise, especially the interactions of reference price effects
(Bell and Bucklin, 1999). As stated by Urbany and Dickson (1991), usually inexperienced/infrequent
buyers tend to rely on the observed price as an indicator for the quality of the products compared to
those consumers who have the knowledge of the product. This might affect their price estimation. This
is because not all of the products with high price could be categorized as high quality. The price range
for the frozen foods manufactured by Restaurant Vegetarian S.I. Jin
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Wei was RM 10 to RM 20 with Malaysian Certified. Hence, consumers will be influenced by
familiarity towards the store as well as affected their purchase intention.
Table 4.7.2: Summary of Hypothesis Testing - Store Visit History
Independent Variable Hypothesis Result
Store Visit History H2: Store visit history will p-value = 0.031 < 0.05
positively and significantly Accepted
influence customer purchase
intention.
4.6.1 CUSTOMER CHARACTERISTICS
Individuals will scan their memory for cues depending on its knowledge level while ongoing the
judgement process in evaluating level of product class knowledge (Park, Mothersbaugh & Feick,
1994). In this study, the p-value of customer characteristics at 0.000 less than 0.05 (as shown at Table
4.7.3) thus there is a positive relationship between customer characteristics and customer purchase
intention. Consumers come along with brand knowledge to represent their understanding and recall of
a brand or product which is agreed by Moon, Russell and Duvvuri’s research (2006). Consumers are
aware of the frozen food produced by Restaurant Vegetarian S.I. Jin Wei and it is recognized by the
consumers for its freshness, delicious, high quality as well as reasonable price compared to other
competitors. Manufacturer only use the raw material (mushroom) sent directly from the farm in order
for them to control the quality of the raw material easily. Besides, manufacturer put a “Bear wearing
as Chef” as their logo to catch consumers’ eyes to buy these products. Hence, consumers with brand
knowledge tend to increase their confidence in making purchase decisions.
Table 4.7.3: Summary of Hypothesis Testing - Customer Characteristics
Independent Variable Hypothesis Result
Customer H3: Customer characteristics will p-value = 0.000 < 0.05
Characteristics positively and significantly influence Accepted
customer purchase intention.
4.6.2 STORE ENVIRONMENT
Since the p-value of store environment is more than 0.05 at 0.406 (as shown at Table 4.7.4) thus it
shows that store environment will not positively and significantly influence customer purchase
intention. This result illustrates that the store environment is not a significant factor in affecting
customer purchase intention. However, some previous studies emphasized that the store environment
will influence customer purchase intention significantly as other product prices displayed in store will
be the reference price which is related to customers' brand choice. On the other hand, some actions can
be taken by sellers while setting the price by putting its products next to more expensive ones to show
that both products belong to the same class (Kotler Marketing). However, a strong brand with unique
and high recognition tends to distinguish it from other brands and will not be easily influenced by its
competitors (Smith et al., 2017). In this case, frozen foods manufactured by Restaurant Vegetarian S.I.
Jin Wei is outperforming and recognized by customers compared to other frozen food brands, thus
there is not direct alternatives bring to lower price sensitivity and higher customer purchase intention.
To specify, if a brand is good, has a high reputation and strong enough,
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920 Tan Yi Ting & Dr Adaviah (2022)
other product price display in store will not be the reference price to it. Hence, store environment will
not influence customer purchase intention significantly.
Table 4.7.4: Summary of Hypothesis Testing - Store Environment
Independent Variable Hypothesis Result
Store Environment H4: Store environment will p-value = 0.406 > 0.05
positively and significantly Rejected
influence customer purchase
intention.
4.6.3 PRODUCT CATEGORY
According to Hirschman and Holbrook (1982), products bring either utilitarian, hedonic benefits or
both. Thus, consumers will match his/her needs (benefits pursued by consumers) with the product price
before making a purchase decision. In this study, the result illustrates the positive relationship between
product category and customer purchase intention as p-value 0.000 < 0.05 (as shown at Table
4.7.5). Besides, inexperienced buyers are likely to use price information from other brands or product
categories to form price expectations for a particular product as mentioned by Jacobson and Obermiller
(1990). Consumers can make comparisons between brands/products on ingredients, price, taste,
freshness and come out with a good decision which could maximize their needs and wants as well as
happiness. Moreover, consumers with a lot of prior buying experience in a particular product category
tend to act differently with inexperienced consumers. Therefore, product category in significantly
influence customer purchase intention.
Table 4.7.5: Summary of Hypothesis Testing - Product Category
Independent Variable Hypothesis Result
Product Category H5: Product category will p-value = 0.000 < 0.05
positively and significantly Accepted
influence customer purchase
intention.
5.0 RESEARCH IMPLICATIONS, LIMITATIONS AND RECOMMENDATIONS
5.1 RESEARCH IMPLICATIONS
The purpose of the study highlighted the effect of reference price on frozen food toward customer
purchase intention through the development of the frozen food industry. Increasing the use of frozen
food trends supported by the dietary consumption which has transformed from home-cooked to the use
of frozen food brings to the growth of the frozen food industry over time. Thus, the findings of this
study will provide the information to the existing business owner, marketers, entrepreneurs as well as
future researchers. Researcher identified that the effect of reference price includes price history, store
visit history, customer characteristics and product category are the most important elements which will
influence customer purchase intention on frozen foods. Therefore, it is significant for existing business
owner to understand and learn about how these effects influence customer purchase intention and make
improvements in the future. Marketers should develop a new marketing plan by taking into account
variables suggested in this study in order to make the comparison between current business and how
it would be in the future. In addition, existing business owner should cooperate with marketers in
building customer relationships as well as improving public awareness towards the products through
advertising and promotion. On the other
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921 Tan Yi Ting & Dr Adaviah (2022)
hand, findings from this study can be the reference point for potential entrepreneurs to estimate
customer demand on frozen foods.
5.1 LIMITATIONS AND RECOMMENDATATIONS TO FUTURE RESEARCH
There are some limitations discovered by researcher while running this research which can provide
suggestions to future research. Although there are a total 150 respondents for the sample size (n=150)
determined by subject-to-item ratio of 5:1, researcher find out that it still couldn’t represent the
whole population of the customers at Restaurant Vegetarian S.I. Jin Wei in this study. On the other
hand, purposive sampling method used in this study which is totally based on judgement of
researcher tend to lead to the bias on the sample selection. Therefore, researcher would like to
suggest for future research to increase the sample size based on desired accuracy with confidence
level of 95% and 99% from the population size whereas other sampling methods through probability
sampling methods. Under probability sampling methods, it consists of simple random, stratified
random, cluster sampling and systematic sampling are encouraged to use in future research to
increase data accuracy.
In addition, findings show that there is a hypothesis proposed (H4) not supported in this study, thus
further investigation on the relationship between store environment and customer purchase intention
suggested to future research in order to find out the reasons for inconsistent findings.
Since the language used in the questionnaire is only in the English version, it might influence the
answer provided by targeted respondents, especially elderly as they cannot understand the questions
given clearly. Hence, future research could adopt the 3 languages questionnaire to improve the results’
consistency.
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FINAL YEAR PROJECT
AHIBS UTM SKUDAI JAN 2022
FACTORS INFLUENCING CUSTOMER SATISFACTION AT DAILY HAPPY OTAK
OTAK
TEE KELLY, DR MAZILAH BINTI ABDULLAH
Azman Hashim International Business School, Universiti Teknologi Malaysia, Johor Bahru
*Corresponding author: [email protected], [email protected]
Abstract
In the food industry, the relationship between four independent variables (quality of food, quality of service, quality of setting, price and value) and overall
customer satisfaction is close. Overall, customers satisfaction is important for a company because of this link to customer loyalty towards the company and
also the company's sales and reputation. Therefore, many companies pay attention to customer satisfaction and find ways to solve the problem of dissatisfaction
and manage customer satisfaction for building reputation and positive world-of-mouth. The research objective is to examine the influence of independent
variables on customers' overall satisfaction. Thus, Daily Happy Otak Otak can know customer satisfaction towards their company to improve their weakness
and plan for the future. This study uses questionnaires by distributing questionnaires to Daily Happy Otak Otak. The sampling method used in this study was
quantitative, and the sample size is 137 respondents based on purposive sampling. The result showed that food quality, service, price, and value significantly
influence customers' overall satisfaction. Therefore, these variables are the company's need to focus and improve to increase customer satisfaction.
Keywords: Quality of food, Price and Value, Quality of Setting, Quality of Service, Customer Satisfaction
■ 1.0 INTRODUCTION
Food plays an important role in our lives, which is why the methods of growing, processing and transporting it are valued to us to understand
it and try to improve it. The food industry consists of compound activities related to the availability, consumption, and catering of food and
services worldwide.
Today's food industry has become highly competitive and quite growing rapidly. In the global market, Malagie et al., (1998) stated that world
food exports totalled 290 billion U.S. dollars in 1989, 30% over 1981. Countries with industrialised market economies account for 67% of
exports. There has been substantial growth because of increased demand for food and drinks. This also means that the world's food production
will continue to increase. The rapid development of technology in the food industry is partly driven by population pressure, uneven
distribution of agricultural resources, and the need to keep food fresh for better distribution. Rapid economic development and enormous
marketing pressure allow the industry to continuously deliver new, different and attractive products. In order for the population's needs to be
met, the industry not only needs to produce enough food to satisfy the huge population, but it also needs to adhere to strict hygiene controls,
in this way to ensure and maintain the quality required for community health.
Therefore, the rapid development in the food industry also affects the economy of the global market. According the The Business Research
Company website (2020), the global food market value in 2019 is close to $5,943.6 billion and has grown at a compound annual growth rate
(CAGR) of 5.7% since 2015. In addition, according to the business research company's website, the global food market is expected to grow
from $5,383.8 billion in 2020 to $619.615 billion in 2021, with a compound annual growth rate (CAGR) of 6.1%. This shows that the
food industry has greatly contributed to the global economy.
According to Food & Beverage Industry Report Malaysia 2020, Malaysia's food industry is the major contributor to the national accounts
because it is a rapidly growing market in this industry. Its 2018 revenue was around 22.12 billion euros, an annual growth rate of 7.6%.
Referring to the same report, Malaysia is a diverse food industry that offers processed foods in a variety of Asian-preferred dietary tastes,
but also many recipes of Western. The industry is dominated by small and medium enterprises (SMEs). Besides, the food distribution market
is highly fragmented because there are many substitute products and participants in the market. Distribution channels include hawkers,
convenience stores, market stalls, supermarkets, hypermarkets, and shopping centres. In addition, e-commerce platforms are platforms of
online shopping. Online shopping platforms are becoming more and more popular, especially in COVID-19.
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925 Kelly & Mazilah (2021)
Because Because of the huge number of similar products and competitors in the food market, consumers' preferences and satisfaction
significantly influence the food industry and food companies. Therefore, this study is aimed to research customer satisfaction towards the
company so that it can help the company understand their customer satisfaction and give them a chance to improve it.
■ 1.1 BACKGROUND OF THE PROBLEM
Today's food industry customers will not sacrifice bad service for deliciousness. (Ryu, K. et al., 2012). In this market with many competitors,
it can be believed that the main point to get profit depends on providing high-quality services to satisfy customers (Han and Ryu, 2007).
Customers usually use the product, setting, and company services to evaluate the company's service quality (Ryu and Han, 2010; Namkung
and Jang, 2008). Price and value are also important factors that affect customer satisfaction (Garg & Kumar, 2017). The right combination
of these important attributes can improve customer satisfaction (Ryu, K. et al., 2012).
Customer satisfaction was important to a business or organization. This is because customer satisfaction is a factor that most influences an
organization's sales and names. Customer satisfaction cannot guarantee that customers will be loyal to the company, but if customers are
dissatisfied, it should make customers switch to other competitors (Davis & Heineke, 1998). This means if customers are dissatisfied with
the level of service they receive in the company, they will not visit and come again in the future. Conversely, if customers are very satisfied
with the company's service experience, they will continue to come again. Through word-of-mouth interactions with other potential customers,
the customer's experience in the service company may increase exponentially: if customers are satisfied with the services of the company,
they will influence other customers' expectations towards this company; if customers are dissatisfied with the company's service, they will
"spread" and influence expectations of others. Therefore, although a higher level of customer satisfaction is not necessary for a company, a
lower level of customer satisfaction will make the company face the problem of decreased sales and customers' shifting behaviour. This
means customer satisfaction is what companies need to manage and follow closely.
Managing customer satisfaction well can bring more benefits to a company. Customer satisfaction is directly related to business sales (Baker
and Crompton, 2000). If customer satisfaction is high towards the company, customers will purchase again and again. Therefore, customer
satisfaction is significant towards sales and names of an organisation. If companies can know which factors are most significant to impact
customer satisfaction, they can find a good way to manage the main factors of success and improve the failure aspects (Hwang, J., & Zhao,
J., 2010). Therefore, this survey is aimed to find out customer satisfaction towards Daily Happy Otak Otak so that more understanding about
real customer perception and satisfaction towards this company. Besides, this survey can help the company know what aspect is most
complained about by customers or certain aspects that customers most care about.
According to an interview with Xie Shun Loong – the current owner of Daily Happy Otak Otak on April 2, 2021, Daily Happy Otak Otak
was organized by Ang Bee Heong in 1981 at Parit Jawa. In the beginning, Ang Bee Heong found a Nyonya friend to learn how to do otak
otak. She learned how to do otak otak due to the need to sell otak otak to burden her big family's living expenses. Ang Bee Heong sold otak
otak at her home, not a shop. Due to her otak otak being very delicious, her otak otak became a famous food in Parit Jawa. Besides, people
who ate her otak otak will praise her otak otak and recommend it to their family and friends. Therefore, more and more people gradually
know her otak otak, so more and more people came to buy her otak otak. When Ang Bee Heong saw that her business was getting
better, she registered with the government as a Suruhanjaya Syarikat Malaysia (SSM) in 2006.
Now, her business was succeeded by her eldest grandson – Xie Shun Loong. Xie wanted to make his family business achieve greater
achievements in his hands; he commissioned experts to manufacture Otak Otak machines from more than ten years ago to maximise their
quantity of product to meet high demand. At the same time, they also can make sure their product's quality is good. Xie also collaborates
with the tourism industry so that Daily Happy Otak Otak becomes more famous to the whole of Malaysia and also internationally. To prove
this, Daily Happy Otak Otak has become a tourist attraction and has been interviewed by many T.V. stations from national and also
international. This brought some customers to Daily Happy Otak Otak and made sales increase. Daily Happy Otak Otak is also a wholesale
business that sells otak otak to other businesses. Daily Happy Otak Otak has wholesale otak otak to Melaka, Batu Pahat, Seremban, Johor
Bahru and even exports to Singapore. Even though otak-otak is considered not a staple food, Xie's effort to introduce this to tourists and
maintain sales during Covid-19 attracted the researcher to choose the company, It is a unique situation, and the researcher would love to
explore more.
The reason for choosing this company to do research is that Daily Happy Otak Otak is the only company that sells traditional food – Otak
Otak at Parit Jawa. The company is historical and known as a tourist attraction at Parit Jawa. A food company that became a famous tourist
attraction needs a good product and good reputation. However, this company never does a customer satisfaction survey. Therefore, there are
doubts about the level of customer satisfaction in this company, how their customers' real perception and satisfaction towards this company.
Therefore, this study was started from doing a preliminary study to confirm there are problems with customers satisfaction towards Daily
Happy Otak Otak. The study was done by distributing Google Form in Whatsapp to 30 company's customers, asking them their satisfaction
and expectation towards this company. Another way of doing a preliminary study is by observing their customer's comments on their official
Facebook website. Through both ways, customer satisfaction problems can be found in detail with aspects that customers comment and reason
in Fishbone Diagram. In the diagram, the problem of customer satisfaction that Daily Happy Otak Otak faces can be divided into four aspects:
quality of food, service, setting, and price. After this, the framework similar to this Fishbone Diagram has been found and adapted to be
this research framework (Figure 3).
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Based on the preliminary study conducted on May 28, C2021, distributed to 30 customers of Daily Happy Otak Otak over WhatsApp,
using a Google Form, the researcher concluded the major themes of the verbatim analysis below Fishbone Diagram (Figure 1).
Figure 1: Fishbone Diagram
The theme was the basis for the variables chosen in this research. Based on this Fishbone Diagram, the researcher can understand the aspects
of customer satisfaction towards Daily Happy Otak Otak. In the quality of food, customers complain that the company's product has foreign
matter inside the product and bad product's serving temperature. For the quality of service, this aspect is the most complaint by customers.
The complaint includes forgetting orders, slow service speed, bad staff's attitude, and poor handling of problems. A few customers were
dissatisfied with the price of the product a bit high and no offer on buying more. The quality of the company's setting is also complained
about by customers in the waiting environment and cleanness. Through the preliminary study, the problem of customer satisfaction can be
established by dividing them into several variables. Besides, the company's strengths and weaknesses also through preliminary study to know
and SWOT analysis as the below diagram. (Figure 2)
Figure 2: SWOT Analysis of Daily Happy Otak Otak
1.2 RESEARCH QUESTIONS
This study listed four main research questions:
i. Does the quality of food influences customer' overall satisfaction？
ii. Does quality of service influences customers' overall satisfaction?
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iii. Does the quality of setting influences customers' overall satisfaction?
iv. Does price and value influences customers' overall satisfaction?
1.3 RESEARCH OBJECTIVES
There have four objectives in the study:
i. To examine the influence of quality of food on customers' overall satisfaction.
ii. To examine the influence of quality of service on customers' overall satisfaction.
iii. To examine the influence of quality of setting on customers' overall satisfaction.
iv. To examine the influence of price and value on customers' overall satisfaction.
■ 2.0 LITERATURE REVIEW
2.1 CUSTOMER SATISFACTION
The amazing experience customers have when acquiring or consuming a product will make customer satisfaction reviews (Oliver, 1981).
Besides, customer satisfaction is the customer's overall measurement standard after purchasing products or services (Fornell, 1992). It is
based on the overall attitude of experience creation and comparing before and after the customer accepts the product. In addition, customer
satisfaction is a person's happiness or disappointment after they compare his product expectations with his perceived product performance
(Kotler, 1997). Customers based on their past consumption experience towards company product or services to make an overall evaluation
and customer satisfaction. Good quality of service will make it easier for customers to be satisfied with this company (Lin, 2007). Customers
are very satisfied when the actual results of service provided by the company exceed the expectations of customers towards the company's
service; on the contrary, the customer will be dissatisfied with the company (Joewono and Kubota, 2007).
Customer satisfaction is "customers' perception of whether the reward is appropriate to the service that they experience" (Howard
& Seth, 1969). Customer satisfaction may be a key business requirement, significantly affecting customers' willingness to shop back (He
and Song, 2009). Customer satisfaction can predict loyalty customers and potential customers (Barber et al., 2011). This also will bring
profits to companies (Brunner et al., 2008). Improving customer satisfaction can reduce customer complaints and increase customer
satisfaction (Fornell and Wernerfelt, 1988). Therefore, customer satisfaction is very important to the company.
2.2 DEFINITION OF EACH VARIABLE
2.2.1 QUALITY OF FOOD
According to M. McWilliams (2000), quality of food is a food quality characteristic acceptable to customers. The taste, freshness,
nutritional aspects and serving size are all classified as food quality measurements. Quality of food includes many components such as taste,
presentation of dishes, food temperature, freshness, and health choice (Namkung & Jang, 2007). Customers rate the quality of their food
subjectively. Therefore there will be different perceptions and levels of satisfaction from person to person (Ophuis and Van Trijp, 1995).
Freshness and health have become bigger concerns for consumers' diets of late. Quality of food is highly valued as the main product of
foodservice operations. As a result, customers rate their satisfaction with its food based on temperature, flavour and texture. (Serhan & Serhan,
2019). The quality of food is thought to influence customers' willingness to revisit a company.
2.2.2 QUALITY OF SERVICE
The quality of service compares customers' expectations towards the company's service and customers' perceptions of the actual
performance of service (Naik, Gantasala, and Prabhakar, 2010). Many studies have found that service quality is important than food quality
in terms of customers' satisfaction towards service. Abo-Baker (2004) describes the quality of service as the company's ability to meet
customers, satisfy customers' wishes and needs, and exceed their expectations within the scope of determining service specifications,
characteristics, and requirements. Zeithaml (1988) defines the quality of services as judging customers' overall performance towards the
product. The quality of service is differences among expectations and perceptions of customers towards services provided by the company
(Parasuraman et al., 1988). Similarly, service quality is a perceived attribute of the services experience that customers perceive when the
company provides the services (Zeithaml et al., 1990).
2.2.3 QUALITY OF SETTING
Company services usually involve environmental and operational aspects (Kwun, 2011). Customer expectations and insights vary
by consumption location. It is worth mentioning that this setting is considered a dimension that can further influence customers' insights into
the organisation of food company services. Setting components can also include various decoration and music environments (Andaleeb and
Caskey, 2007).
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2.2.4 PRICE AND VALUE
Price fairness refers to judging whether the result of achieving a result is accepted by customers (Bolton and Shankar, 2003).
Likewise, customers' prices for a product can be a measurement tool for the quality level a company offers (Soriano, 2003). Price is a key
factor influencing the company's brand image (Campbell, 1999). Therefore, if the price unfairness or not acceptable to customers will make
the company has negative word-of-mouth, and customers will purchase products from other competitors. Thus, the most important factor in
encouraging customers to visit the company again is getting a good value that matches the product's price or service (Yuksel and Yüksel,
2002).
2.3 HYPOTHESIS DEVELOPMENT
2.3.1 QUALITY OF FOOD
There is a significant relationship between customer satisfaction towards the quality of food and customers' willingness to buy the
product again from a company (Oh, 2000). Today's customers expect companies' food to have a high quality of freshness (Chamhuri and
Batt, 2015). The key factors of customers visiting a company are quality of food because quality of food is the core attribute of a food
company (Sulek and Hensley, 2004). Similarly, Vangvanitchyakorn (2000) pointed out food quality as the most important aspect for
customers' overall evaluation of companies. Furthermore, the quality of food is the main factor affecting customers' overall satisfaction
and behavioural intentions (Gagić et al., 2013). The important factors of customers' evaluation of food companies are based on food
quality (Susskind and Chan, 2000). Based on the explanation given above, the following research hypotheses are proposed:
H 1 : Quality of food has a significant positive influence on customers' overall satisfaction.
2.3.2 QUALITY OF SERVICE
The quality of service means evaluating service quality by comparing customers' expectations of the company's service with the
customer's insight and experience of the experience of service (Parasuraman, Zeithhaml, and Berry, 1994). Yuksel and Yusel (2002)
believe that service quality greatly influences the market level of customer satisfaction. According to Inkumsah (2011), customer
satisfaction was influenced by the company's service quality level to customers. Garg (2014) pointed out that the services affect
customers' organisation perceptions. Küçükaltan (2017) claimed that even if it is the same service, customers will have different
judgments and satisfaction because they have different views on the service. If the company's service cannot exceed the customer's
expectations, the customer's satisfaction towards quality of service is low; if the service exceeds their expectations, then perceived quality
of service is high (Akbaba and Kilinc, 2001). Based on the explanation given above, the following research hypotheses are proposed:
H 2 : Quality of service has a significant positive influence on customers' overall satisfaction.
2.3.3 QUALITY OF SETTING
Several studies have shown that comfort, environment, cleanliness, business hours, and days greatly influence customer satisfaction
and customers' willingness to revisit (Liang and Zhang, 2009). Various scholars (Flegal et al., 2010; Norhati and Fadzil, 2013; Raman
and Chinniah, 2011) have determined the relationship between food information and quality and the food distribution environment.
Based on the explanation given above, the following research hypotheses are proposed:
H 3 : Quality of setting has a significant positive influence on customers' overall satisfaction.
2.3.4 PRICE AND VALUE
The price and value can greatly affect customers satisfaction (Martin-Consuegra et al., 2007). Soriano (2003) concluded that
customers' expectations towards quality depend on the price of products and services. When price rises, the expectations towards the
quality of products and services also increase. He also concluded the price (value) of food and service as the key to increasing customer
satisfaction. In the same study, they showed that food prices are as important as other determinants of satisfaction. If the prices are unfair
can make to bad results, such as increased customer complaints, high dissatisfaction towards the company, reputation decreased, and
customers not or less to coming back again (Rothenberger, 2015). Based on the explanation given above, the following research
hypotheses are proposed:
H 4 : Price and Value has a significant positive influence on customers' overall satisfaction.
2.4 RESEARCH FRAMEWORK MODEL
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Figure 3: A research framework for the customer satisfaction towards Daily Happy Otak Otak
Figure 3 shows this study's research framework. The function tests the relationships between dependent variables and independent variables
for customers' overall satisfaction towards Daily Happy Otak Otak. The framework of the variables in Figure 3 was adapted from Serhan &
Serhan (2019), who highlighted the food attribute towards the customers' overall satisfaction.
■ 3.0 RESEARCH METHODOLOGY
3.1 RESEARCH DESIGN
The descriptive quantitative was used in this study. This study uses survey methods in collecting data from prospective respondents.
This research focuses on B to C customers even though Daily Happy Otak Otak also had B to B customers. This is because B to B customers
are less than B to C customers, and they are very busy, so they are hard to interview them. Therefore, the questionnaire was distributed among
B to C customers through the Daily Happy Otak Otak company Whatsapp.
3.2 POPULATION AND SAMPLING
This research aims to examine the influence of four independent variables' influence on customers' overall satisfaction. Therefore,
the population of this study focuses on respondents of customers of Daily Happy Otak Otak that are located at Parit Jawa, Malaysia. Due to
respondents focusing on customers of Daily Happy Otak Otak, thus, people who are not the customers of Daily Happy Otak Otak cannot
be respondents of this research. Therefore, purposive sampling was used in this research. Questionnaires were distributed to the respondents
using Daily Happy Otak Otak's Whatsapp. According to the table of statistical power analysis (Cohen, 1992), the sample size in four
independent variables with a medium population was required to collect 118 results from 118 respondents. The result was measured for
examining the influence of four independent variables on customers' overall satisfaction towards Daily Happy Otak Otak by multiple
regression.
3.3 RESEARCH INSTRUMENT
The questionnaire design was adapted from a questionnaire in a previous study (Serhan & Serhan, 2019). The most suitable
quantitative approach for this study is Likert scale questions. There are six sections in the questionnaire: Section A, B, C, D, E, and F. Section
A consists of three questions about the respondent's information. Section B consists of four questions about independent variables (quality
of food). Section C contained four questions that asked about the quality of service.
Meanwhile, Section D contains three independent variables (quality of setting) questions. Next, Section E consists of two questions
about the price and value of the product Daily Happy Otak Otak. The last section has five questions about customers' overall satisfaction
towards Daily Happy Otak Otak in four independent variables. To ensure the questionnaire design is eligible, thus pre-testing, pilot testing
and expert review were previously conducted for validation in this study. Applying the Likert scale in this section, respondents were requested
to tick the answer follows five-levels such as 'strongly disagree', 'disagree', 'neutral', 'agree', and 'strongly agree' while the B, C, D, E section
using 'strongly satisfied', 'satisfied', 'neutral', 'dissatisfied', and 'strongly dissatisfied' to answer their satisfaction towards four variables of
Daily Happy Otak Otak. Likert scale can determine the level of customer satisfaction towards each question contained with that five levels.
■ 4.0 DATA ANALYSIS
This study has collected 137 respondents. It exceeds the number required of Cohen Table, 118 respondents. According to Rohieszan (2021),
a 10% more than the sample size is acceptable. The result and analyses about demographic, normality test, univariable and
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multivariable analysis, multicollinearity analysis, and multiple regression analysis were stated in this chapter. Besides, the reliability test was
used in a pilot study that collected 30 respondents.
4.1 RELIABILITY TEST
The reliability test aims to make sure the questionnaire's results are reliable and consistent (Sürücü & MASLAKÇI, 2020). According to
Hair et al. (2010), the cronbach alpha score in the reliability test must exceed 0.7 to prove the questionnaire is reliable and consistent. The
reliability test was used in a pilot study that collected 30 respondents and its result at the table below showed all variables exceed 0.7. This
means questions of all variables can be acceptable.
TABLE 4.1 Reliability Test
Variables Cronbach's Alpha
Quality of Food 0.817
Quality of Service 0.779
Quality of Setting 0.863
Price and Value 0.884
Overall Customer Satisfaction 0.828
4.2 RESPONDENTS’ DEMOGRAPHIC
The information of respondents such as gender, race, age, the average number of visits to Daily Happy Otak Otak, and once average
expenditure in Daily Happy Otak Otak are shown in Table 4.2.
TABLE 4.2: Demographic
Profile of Respondents Frequency Percent (%)
Gender
Female 93 67.9
Male 44 32.1
Race
Malay 3 2.2
Chinese 133 97.1
Indian 1 0.7
Age
Under 20 years old 12 8.8
21 - 30 years old 47 34.3
31- 40 years old 23 16.8
41 - 50 years old 21 15.3
51 years old and above 34 24.8
Average Number of Visits to Daily Happy Otak Otak
Once/three months 47 34.3
Once/month 66 48.2
Once/week 20 14.6
Twice/week 4 2.9
Once Average Expenditure in Daily Happy Otak Otak
Less than RM20 22 16.1
RM21 - RM30 45 32.8
RM31 - RM40 31 22.6
RM41 - RM50 18 13.1
More than RM50 21 15.3
4.3 NORMALITY TEST
In the normality test, skewness and kurtosis were shown that all variables in this study were normally distributed. This is because the result
of data is between 2 and -2 (Garson, 2012), that shown in Table 4.3.
TABLE 4.3: Results of Normality Test
Variables Items N Skewness Kurtosis
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Quality of Food QF1 137 -0.929 1.897
QF2 137 -0.324 -1.361
QF3 137 -0.376 -1.346
QF4 137 -0.665 -0.906
Quality of Service QS1 137 0.201 -1.298
QS2 137 -0.202 -1.101
QS3 137 -0.311 -0.937
QS4 137 -0.261 -1.227
Quality of Setting QFS1 137 -0.531 -0.906
QFS2 137 -0.445 -0.92
QFS3 137 -0.203 -1.079
QFS4 137 -0.52 -0.338
Price and Value PV1 137 -0.976 0.551
PV2 137 -0.896 1.023
PV3 137 -1.052 1.164
Customers’ Overall OS1 137 -0.335 -0.848
Satisfaction OS2 137 0.073 -1.311
OS3 137 0.04 -1.416
OS4 137 -0.649 -0.994
OS5 137 -0.476 -1.204
4.1 UNIVARIABLE AND MULTIVARIABLE ANALYSIS
After doing the normality test, the univariate outlier and multivariate outlier were be tested in this study. The standardised z score value
needs between 4 and -4 to prove there is no univariate outlier in this study (Coakes & Steed, 2003; Hair et al., 2010). In this study, there have
been no values exceeding 4 and -4. After this, the multivariate outlier is tested to make sure the maximum value of Mahalanobis Distance
(D ) that showed in Table 4.4 is less than the 18.467 (four variables) (Hair et al., 2010). This result proves there was no extreme value in this
2
study. Therefore, univariate outlier and multivariate outlier were tested, and the result showed no extreme values in this study.
TABLE 4.4: Mahalanobis Distance (D )
2
Std.
Mahal. Minimum Maximum Mean Deviation N
Distance 0.321 13.326 3.971 2.814 137
4.2 MULTICOLLINEARITY ANALYSIS
In multicollinearity, two or more predictors of multiple regression models must be highly correlated. According to Garson (2012), the
applicable rules of the tolerance value should be greater than 0.2 and based on the findings of Pallant (2015), the value of VIF should be less
than 10. Thus, there are no multicollinearity problems in this study because Table 4.5 showed the value of tolerance of all variables exceeded
0.2, and the value of VIF is below 10.
TABLE 4.5: Multicollinearity Analysis
Collinearity Statistics
Model Tolerance VIF
Quality of Food 0.602 1.661
Quality of Service 0.305 3.275
Quality of Setting 0.333 3.005
Price and Value 0.745 1.342
a Dependent Variable: Customers’ Overall Satisfaction >0.2 <10
4.3 MULTIPLE REGRESSION ANALYSIS
2
Table 4.6 shows that the value of R square was 0.478 in the multiple regression analysis. This means 47.8% of the variation in
customers' overall satisfaction can be explained by the quality of food, service, setting, price, and value. The ANOVA table implies value F
(4, 137) = 30.255, the significant influence value was below 0.05 (ρ=0.000). Therefore, it is not greater than α (0.001). The result of Table
4.4 proves this study's variable has a significant effect on the dependent variable that named customers' overall satisfaction.
The output of coefficients that showed in Table 4.8 indicated H1, H2, and H4 resulted that quality of food, quality of service, price
and value positively influence customers' overall satisfaction towards Daily Happy Otak Otak. At the same time, Hypothesis 3 stated
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that the quality of setting was not positively influenced customers' overall satisfaction towards Daily Happy Otak Otak. Based on the table,
quality of food, quality of service, price and value were positively significant to customers' overall satisfaction towards Daily Happy Otak
Otak, which were p=0 (p<0.001), p=0.007 (p<0.05), p=0.007 (p<0.05). The standardised beta values for the three variables were positive
(β=0.429, β=0.314, β=2.735), supporting Hypothesis 1, Hypothesis 2, and Hypothesis 4. Furthermore, Hypothesis 3 predicts that quality of
setting cannot significantly affect customers' overall satisfaction with Daily Happy Otak Otak, and the ρ values are bigger than 0.05, which
were (ρ=0.255). The standardised betas for quality of setting (β= -0.125). The beta value of the quality of the setting (β=-0.125) was negative,
indicating that the quality of the setting was high, the customers' overall satisfaction with Daily Happy Otak Otak was also low or not respond.
This means that the quality of the setting cannot significantly affect overall customers' overall satisfaction. After that, H3 cannot be accepted
in this study.
TABLE 4.6: Model Summary of Multiple Regression Analysis
R Adjusted R Std. Error of the
Model R Square Square Estimate
1 .692a 0.478 0.462 0.60477
a Predictors: (Constant), PV_AVG, QS_AVG, QF_AVG, QFS_AVG
TABLE 4.7: ANOVA
ANOVA
Model Sum of Squares df Mean Square F Sig.
1 Regression 44.263 4 11.066 30.255 .000b
Residual 48.279 132 0.366
Total 92.541 136
a Dependent Variable: OS_AVG
b Predictors: (Constant), PV_AVG, QS_AVG, QF_AVG, QFS_AVG
TABLE 4.8: Multiple Regression Analysis
Unstandardized Standardized
Model t Sig.
Coefficients Coefficients
B Std. Error Beta
1 (Constant) -0.15 0.342 -0.437 0.663
Quality of Food 0.49 0.093 0.429 5.291 0
Quality of 0.298 0.108 0.314 2.756 0.007
Service
Quality of Setting -0.123 0.108 0.125 -1.144 0.255
Price and Value 0.227 0.083 0.199 2.735 0.007
4.5 SUMMARY OF HYPOTHESES
As shown in Table 4.9, this study proposes four hypotheses. This means that quality of food, price and value, and quality of service were
positively supported, while the quality of setting does not support this study to significantly influence customers' overall satisfaction with
Daily Happy Otak Otak.
TABLE 4.9 Hypothesis Testing
Hypothesis Testing
H1. Food quality has a significant positive influence on Supported
customers' overall satisfaction.
H2. Quality of service has a significant positive influence on Supported
customers' overall satisfaction.
H3. Quality of setting has a significant positive influence on Not supported
customers' overall satisfaction.
H4. Price and Value has a significant positive influence on Supported
customers' overall satisfaction.
■ 5.0 DISCUSSION & RECOMMENDATION
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The first hypothesis of this study is that the quality of food greatly influences customer satisfaction. It was the same with the results
of Abdullah et al. (2018) that concluded there is a highly positive correlation within consumers' satisfaction and food quality because most
customers support the utilitarian value's food quality. In other words, customers who visit this company must pay for the food it sells. If the
food quality does not fulfil customers, customers must be dissatisfied with the company. On the contrary, if the quality of the food fulfils
customers, customers will naturally have a good impression and satisfy the company, and they will visit again. Therefore, it could be seen that
food quality is the key to overall customer's satisfaction.
For the second hypothesis, quality of service also be found out that stated it has a significant positive effect on customer's overall
satisfaction towards Daily Happy Otak Otak. Referring to Cristo et al. (2017), they concluded the service quality could significantly impact
overall customer satisfaction. If service quality is good, it will increase the customers' satisfaction; on the contrary, if the service is poor, it
will make customers dissatisfied with this company. This means service quality is a key to improving and increasing the customers' overall
satisfaction. Therefore, service quality plays an important role in customers' overall satisfaction.
In this study, hypothesis 3 that the quality of setting does not significantly affect the customer's overall satisfaction with Daily
Happy Otak Otak. This is also the same as a previous study's result. According to Ali et al. (2009), they found out that setting cannot greatly
affect customer satisfaction. This is because the setting quality cannot play as a predictor to influence customers' overall satisfaction. This
means customers care more about the quality of product or service than the quality of setting, so they will not focus on whether the company's
setting is good or bad. If the quality of the setting is relatively poor, customers will feel dissatisfied a bit only. The company's setting is low
but has a high quality of products; customers also will come again for their products. Therefore, whether the quality of the setting is good or
bad cannot greatly affect customers' overall satisfaction towards Daily Happy Otak Otak.
The last hypothesis is price and value. Price and value are also factors that the company needs to improve customers' overall
satisfaction. Price and value become the main factors influencing customer satisfaction (Hanaysha, 2016). Customers will compare the price
of the product within different brands to judge perceived value and conclude satisfaction. Most customers are sensitive to products' prices
and compare them with other competitors, especially in this food industry. Conclusion: Many competitors also sold Otak Otak, making
customers have many choices. Therefore, this makes customers sensitive to the price and the value that products bring to them. Customers
will compare the value that products brings to them and the price of products. The price must match its value so that customers can satisfy
the price, products and satisfy the company. If the quality of food does not match its prices, customers will be dissatisfied with this product
then shift to another competitor. From this, it can be seen that the relationship between price and value is the variable that companies need
to focus on customer satisfaction because price and value are the keys to improving their customers' overall satisfaction.
5.1 Managerial Implications
In this study, the researcher found that the quality of food, service, price, and value can greatly influence customers' overall
satisfaction. Quality of food is a key to increasing and maintaining customer satisfaction. Thus, the company needs to train their employees
to be more professional in the manufacturing process. Besides, the company needs to ensure the freshness, taste and serving temperature of
products before selling to customers.
Service is the same important dimension as food quality for the quality of service. If the service quality is poor, this will decrease
customers' overall satisfaction. Therefore, the company must train their employees to be polite, friendly, high speed of service, and have
the knowledge or ability to solve problems.
Last is the price and value; the price should be reasonable and match the product's quality. The company is advised that it cannot
increase price without increasing product quality. This will decrease the customers' overall satisfaction. Furthermore, the price staying with
competitive pricing is the best because customers sometimes make comparisons with competitors' prices.
5.2 Limitations and Recommendations
In this research, it is inevitable to encounter several limitations. First, the company does not have a customer database. Although the company
has its own official Facebook, just a few people will follow and comment on their Facebook. Therefore, this questionnaire needs to be
distributed through owners of the company to their customers who have Whatsapp in their company. Second, the questionnaire must also be
tailored to the company's customers in large fonts and three languages because most customers are relatively older and cannot recognise
other languages. Third, this research focuses on B to C customers even though Daily Happy Otak Otak also had B to B customers. This is
because B to B customers are less than B to C customers, and they are very busy, so they are hard to interview them. Based on these
limitations, future research can try to research B to B customers and B to C customers together to be more accurate to know the real customer
satisfaction of the company. Besides, future research can try to find different variables or features to research customer satisfaction. Thus,
there will find a deeper result in customers satisfaction.
5.3 Conclusion
This study examines the quality of food, quality of service, price, and value that can significantly influence customers' overall satisfaction
towards Daily Happy Otak Otak. Conclusion: there can be concluded that these variables are what the company needs to focus on and
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improve to increase their customer's satisfaction. The other variables, namely the quality of the setting, proved that it could not significantly
influence customer satisfaction. It means whether the quality of the setting is good or bad, customers will be satisfied overall with the
company.
■ 6.0 ACKNOWLEDGEMENT
The researchers expressed their appreciation and sincere gratitude to Dr Mazilah Binti Abdullah, the thesis supervisor, who provided
suggestions and valuable support during this research preparation. Besides,the researcher also thanks to the Dr. Noor Hazarina Hashim and
Prof Dr Rohaizat Baharun, experts in the field of marketing, for conducting the expert validity in this study. Moreover, the researchers are
also eager to thank parents and friends for their continued support. In addition, the researcher thanks Daily Happy Otak Otak for giving
support in distributing the questionnaire and thanks to customers of the company give cooperating in answering the questionnaire.
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FYP PROPOSAL
AHIBS UTM SKUDAI JAN 2022
THE IMPACT OF BRAND EQUITY ON REPURCHASE INTENTION TOWARD
HERMS C ENTERPRISE
TEO KAR QING, DR. ADAVIAH MAS'OD
Azman Hashim International Business School, Universiti Teknologi Malaysia, Johor Bahru
*Corresponding author: [email protected]
Abstract
The evolution of web2.0 enables people to interact and generate content in video, photo, audio, text, etc., which change the way companies communicate to
their customers. Instagram has made it incredibly easy for the business to market and advertise the products. In recent years, the activewear business is
expanding as it is a new trend that attracted the eye of people in Malaysia. Since activewear has become a popular trend in Malaysia, a number of domestic
companies start activewear businesses in Malaysia, yet the industries face intense competition in the market due to there has a different brand of activewear
in the market. The purpose of this research examines the effect of e-WOM and brand equity on customers' repurchase intention toward HERMS C Enterprise.
Literature reviews were conducted before analyzing the research topic in order to have a better understanding of how social media dimensions create e-WOM
and have future knowledge on e-WOM and brand equity influence customers' repurchase intention of activewear brands on Instagram. A set of online
questionnaire had distributed to 140 respondents via Instagram. 9 outliers in the questionnaire and had eliminated from this research. Results generated by
using Smart PLS and SPSS software. This study also provides an overview on the respondents' demographics. Theoretical and practical ramifications of the
findings in this study have been addressed.
Keywords: e-WOM, Brand Equity, Repurchase Intention, Activewear, Instagram
■ 1.0 INTRODUCTION
HERMS C Enterprise is an activewear brand company in Malaysia. This company was founded by Hermione Goh and the business is entirely
conducted through the Internet, where HERMS C Enterprise utilizes social media to promote and sell its brand to the public. It has a wide
range of product lines such as sports bras, tops and t-shirt, bottoms and leggings, combat sets, loungewear, swimwear, and accessories in
order to satisfy customers and enhance customers' shopping experiences. In Malaysia, the activewear market is in a unique situation since it
is still growing. Activewear has been a popular trend among teenagers and young adults because it associates them with a more comfortable
and relaxed lifestyle and better mobility. This has encouraged international companies such as Adidas and Nike to expand their businesses
in Asia, especially Malaysia, because the region has high potential to provide them with a greater sales revenue volume. Malaysia is a
multicultural country with more than 30 million residents, including Malays, Chinese, Indians, and other ethnic groups living side by side
(Khaliq & Selim, 2013). Therefore, the activewear business has a lot of potential in the marketplace because of the growing popularity of
athletic activities in Malaysia.
As the outbreak of Covid-19, Malaysian have to work from home, and for students, the class would be conducted online throughout the year.
The usage of the Internet and social media had increased dramatically. According to Digital 2021: Malaysia had achieved 28 million social
media users in 2021. In order to get in the current trend, companies started to build a strong relationship with the Internet users and provide
all information regarding their brand to the public. Many businesses are increasingly utilizing social media to promote their brands and
sustain a positive relationship with their consumers (Saravanakumar & Lakshmi, 2012). As there are various competitors, the brand needs to
catch customers' repurchase intention to compete in the market.
■ 1.1 PROBLEM STATEMENT
Since activewear has become a popular trend in Malaysia, a number of domestic companies start activewear businesses in Malaysia, yet the
industries face intense competition in the market due to there has a different brand of activewear in the market. Branding aims to attract
customers' attention to particular brands in order to identify the brand and retrieve information from memory about it (Leighton, 2012).
International brands with strong brand equity, such as Nike and Adidas, expanded their businesses, and the market became more competitive
in Malaysia. This has affected the clothing industry to face large-scale competitiveness, especially in activewear brands. The international
activewear business is very competitive and one of the most heavily brand-named apparel industry divisions (Tong and Hawley, 2009). As
a result of the increased competition in the market, customers' buying behaviours and decision-making processes have evolved. The company
needs to elevate its brand, but it also needs to build strong positive brand equity in the market. Therefore, brand equity is essential for every
company to succeed in the marketplace.
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HERMS C Enterprise fails to develop and manage substantial brand equity on social media. HERMS C Enterprise has its brand, yet it
could not compete with the competitors in the market. The company spends around RM20,000 on social media advertising. However, it does
not work where the company still faces low brand equity in the social media market and fails to attract customers' repurchase intention
toward the brand. When HERMS C Enterprise launches a new product on social media, the success rate of the new product might be low due
to its lack of brand trust and credibility to convenience customers repurchase on the new product. Apart from that, HERMS C Enterprise
faces difficulty attracting customers to repurchase its products as low brand equity will influence the choice of customers where the customers
would choose the brand with strong brand equity. The impact of brand equity on customer retention, retention, and profit margin primarily
looked at the relationship between the brand's value and the consumer's lifetime value (Stahl, Heitmann, Lehmann, and Neslin, 2012).
However, there has been limited research on this issue. In addition, there is still insufficient research study on customers' repurchase intention
toward activewear brands on social media platforms which influence by e-WOM and brand equity. Therefore, this research will focus on the
factors that influence customers' repurchase intention toward activewear brands and the importance of brand equity on social media platforms.
1.2 RESEARCH QUESTIONS
This study listed four main research questions:
RQ1: Does user-generated social media communication positively affect the electronic word-of-mouth communication (e-WOM) of HERMS
C Enterprise?
RQ2: Does firm-generated social media communication positively affect the electronic word-of-mouth communication (e-WOM) of HERMS
C Enterprise?
RQ3: Does electronic word-of-mouth communication (e-WOM) positively affect brand equity of HERMS C Enterprise?
RQ4: Does brand equity positively affect customers' repurchase intention toward HERMS C Enterprise?
1.3 RESEARCH OBJECTIVES
This study listed four main objectives:
RO1: To identify the significant relationship between user-generated social media communication and electronic word-of-mouth
communication (e-WOM).
RO2: To identify the significant relationship between firm-generated social media communication and electronic word-of-mouth
communication (e-WOM).
RO3: To identify the effect of electronic word-of-mouth communication (e-WOM) on brand equity of HERMS C Enterprise.
RO4: To identify the effect of brand equity on customers' repurchase intention toward HERMS C Enterprise.
■ 2.0 LITERATURE REVIEW
2.1 INSTAGRAM AS SOCIAL MEDIA COMMUNICATION TOOL
Social media users can broadcast their ideas and opinions throughout the world with a single click on social media. The message
may be addressed specifically to someone, but it is difficult to determine who the author is (Bertot, Jaeger, P.T., et al., 2012). All the social
media users may share their thoughts and openly express themselves on social media. Therefore, various brands extend their businesses via
social media to reach out to more users about their brands. Marketers may reach out to customers in their social communities and develop
more intimate relations with the users via social media (Kelly, Kerr, & Drennan, 2010). People and businesses are connected through the
Internet and social media, including Instagram, and interactions with less dependent on time and place. In order to build and sustain brand
equity, the social media marketing strategy needs to be unique to attract Instagram users' attention. Instagram have made it incredibly easy
for the business to market and advertise the products. According to a survey reported in BBC News (2012), a significant percentage of the
world's top businesses use Instagram as part of their marketing strategies.
2.2 DEFINITION OF BRAND EQUITY
Brand equity is a combination of assets and liabilities associated with a business, its name and symbols that contribute to or detract
from the value supplied by a service or product to a company and its consumers (David A. Aaker, 1991, p.15). Brand equity refers to the
value that a company gains from its product with a distinctive name compared to its competitors (Liao & Cheng, 2014). According to Goi
& Goi (2011), an organization that undergoes a rebranding revolution generally wants to increase its brand equity. Improved levels of brand
equity are frequently translated into higher cash flows and enhanced competitiveness (Baalbaki & Guzmán, 2016). Brand equity
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adds extra value to a company where the business able to improve the efficiency of marketing strategy on Instagram. The brand equitys'
elements enable a company to gain a competitive edge over its competitors.
Brand equity considers a variety of factors, including brand awareness, brand associations, brand loyalty, and perceived quality.
Figure 2.1 shows four dimensions of brand equity. Brand awareness is the ability of a consumer to identify or recognize the brand sufficient
detail to make a buying decision (Kotler and Keller, 2016). Brand associations are described as a brand’s assets and liability that are connected
to the consumer's memory (Aaker, 1991). Brand loyalty indicates customer willingness to stick with a certain brand when the brand changes
in price, product characteristics, distribution programs or communication (Aakar, 1991). While perceived quality refer to customers'
perceptions regarding the quality or general performance of a product (Zeithaml et al., 2012).
Figure 2.1: Dimensions of Brand Equity
2.3 THE IMPACT OF LOW BRAND EQUITY
Brand equity is essential for all business, no matter online or offline business. When a company fails to build and sustain brand equity for its
business, it will lead to low credibility toward the brand. People might think the brand is new and worry about trying it off, as they do not
realize its brand. When a brand has a low level of brand awareness, it is not very likely that customers would consider it. Companies cannot
generate sales revenue unless they enter the consideration sets of the potential customers. Low brand equity stems from a lack of awareness
as well as negative associations (Herschell Newman, 2015). Hence, there is a negative impact on the business when the business has low
brand equity in the competitive market.
2.4 HYPOTHESIS DEVELOPMENT
2.4.1 USER-GENERATED SOCIAL MEDIA COMMUNICATION
User-generated social media communication, generally known as User-Generated Content (UGC), is defined as "the total of all
ways in which individuals utilize social media, widely utilized to characterize the different types of contents that can publicly accessible
and created content by the end-users" (Kaplan & Haenlein, 2010). McNally et al. (2012) define the form of User-Generated Content
(UGC) as multimedia productions, audio, individual texts, photos, and videos. According to Gonzalez (2010), whereas social media
gives endless opportunities for communication, it is individuals, not technology, who act as the influencers. User-Generated Content
(UGC) provides social value for businesses due to it helps to define the brand. The utilization of the user-generated content and Web
2.0 technology has transformed marketing, and the popularity of social media platforms has soared to greater levels (Habibi, Laroche,
and Richard, 2014). Therefore, user-generated social media communication has become an essential element for eWOM communication
(Kucukemiroglu & Kara, 2015). Hence, this able to hypothesize as below:
H1: User-generated social media communication has a positive effect on electronic word of mouth (e-WOM).
01
H : User-generated social media communication has a negative effect on electronic word of mouth (e-WOM).
2.4.2 FIRM-GENERATED SOCIAL MEDIA COMMUNICATION
Firm-generated content is described as marketing communications conducted by a firm on its official social media sites that aid
in the development of one-on-one connections with customers due to the interactive aspect of the medium (Baker, Donthu, & Kumar,
2016). Marketers choose to promote a positive image of their business, and the companies have total control over their social media
profiles, where they will constantly post positive communication material (Bruhn et al., 2012). Content marketing is a marketing approach
that uses the development and distribution of information to draw consumers' attention, position the firm, develop trust, and ultimately,
fidelity through the construction of community relationships by news and articles, statistics, photo, video research, etc. (Maciá, 2013).
Customers' attitudes and behavior are heavily influenced by the content provided by a company (Kumar et al., 2015). Compared to earlier
forms of firm-created communication, social media interactions have been a mass phenomenon with a broad demographic appeal
(Kaplan & Haenlein, 2010). The number of followers may be boosted by posting exciting content (Lipsman,
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Mudd, Rich, & Bruich, 2012). Therefore, it's critical to figure out which types of content get the most attention and which messages get
the best results to figure out what items to advertise and what kind of promotions are much more attractive, the idea is that the content
creates a relationship with the business (Santana et al., 2012). According to Tsimonis and Dimiatris (2014), constructive firm- generated
content on social media helps businesses to develop positive eWOM. The following hypothesis is presented as a result of the above
reasons:
H2: Firm-generated social media communication has a positive effect on electronic word of mouth (e-WOM).
H : Firm-generated social media communication has a negative effect on electronic word of mouth (e-WOM).
02
2.4.3 ELECTRONIC WORD OF MOUTH (E-WOM)
Traditional word of mouth was revolutionized by the development of the Internet and the expansion of social media, which brought
it to electronic level and converted it into electronic word of mouth (e-WOM) (Mishra & S M, 2016). The term electronic word of mouth
(e-WOM) refers to the process of conveying and collecting information, as well as service and product recommendations, through various
media channels (Abrantes et al.,2013), when the communicator and recipient are separated in location and time (Steffes & Burgee, 2009).
Today, eWOM is the most prevalent method of gathering brand information that may be utilized to influence customer product
assessments (Kudeshia & Kumar, 2017). People throughout the world actively express their views, making an effect on problems that
interest them (Kucukemiroglu & Kara, 2015). Customers create content regarding brands, products, services, and experiences, which
they could share with other consumers (Kim et al., 2015). Online reviews aid people in their purchasing decision process while also
increasing the company's revenue (Kudeshia & Kumar, 2017). According to Lin & Xu (2017), these reviews influenced almost 50% of
buying decisions made in stores. Therefore, this can be hypothesized the e-WOM has a direct association with brand equity.
H3: Electronic word of mouth (e-WOM) has a positive and direct impact on brand equity.
03
H : Electronic word of mouth (e-WOM) has a negative and direct impact on brand equity.
2.4.4 REPURCHASE INTENTION
Repurchase intention has been identified as the possibility of buying the brand items again (Chen et al., 2016). Repurchase intention
is defined by Fang et al. (2017) as customers' predisposition to buy items from the same producer over a lengthy period of time. According
to Wu et al. (2014), repurchase also known as retention, which is frequently regarded one of the most essential elements in marketing
concept. Businesses should be concerned about their customers' repurchase intentions, especially if they want to expand service and
product sales. Its in accordance with Lin & Lekhawipat (2014) who stated that repurchase intention could encompass not just desire to
buy the product again, but also desire to promote it to family and friends. Customer repurchase intention is strongly influenced by brand
awareness, which is essential and vital constraint in brand-related investigations (Kapferer, 2008). Pather,
P. (2017) indicated that repurchase intention had been influenced by brand association. According to Chaudhuri (2002), customer
repurchase intention would be high when customers’ perceived quality increase. Loyalty is an important factor in achieving lengthy
profitability, customer repurchase intention, and competitiveness (Nguyen and Liem, 2013). Thus, the following hypothesis is presented
as a result of the above reasons:
H4: Brand equity has a positive and direct impact on repurchase intention.
04
H : Brand equity has a negative and direct impact on repurchase intention.
2.5 RESEARCH FRAMEWORK MODEL
Figure 1: Conceptual Framework
Figure 1 is a conceptual framework that is applied in this research. In order to investigate the effect of e-WOM and brand equity on repurchase
intention, the research model was created and using identified components from a comprehensive literature study. The dimension used in
this study was modified from Mersid and Sumeja research (2019), who studied the influence of social media content on
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consumer purchase intention: mediation effect of brand equity. Mersid and Sumeja focus on the impact of social media communication on
consumer purchase intention. This research would focus on the impact of e-WOM and brand equity on repurchase intention toward Herms
C Enterprise.
■ 3.0 RESEARCH METHODOLOGY
3.1 RESEARCH DESIGN
Conclusive research design will be adopted in this study which including descriptive research. Descriptive research is procedures
and methods for describing certain characteristics of a group of individuals (Gill & Johnson, 2010). This method includes collecting data,
organizing, and summarizing data. The design gathers data and tests the hypothesis as well as answers the questions about the present state
of the research issue. The benefit of adopting this method in this study is that it can illustrate the influence of e-WOM and brand equity on
customers' repurchase intention in various ways.
Furthermore, this research would be focused on the quantitative research method as a set of questionnaire would be distributed to
respondents to answer. The questionnaire would be created using google form and distribute to Instagram customers of HERMS C Enterprise
in order to collect data from the users. As Covid-19 pandemic, the questionnaire would be distributed through social media platform, which
is Instagram.
3.2 POPULATION
The population is defined as the entirety of items or individuals who have common, specified characteristics and are relevant to the
study's findings (Denise F. Polit & Cheryl Tatano Beck, 2010). As the research background emphasizes social media users in Malaysia, a
population is a group of persons or aspects of interest that have knowledge obtained by the researcher. The followers on Instagram of HERMS
C Enterprise had reached 6000 followers. Therefore, the targeted population for this research is Herms C Enterprise's customers on Instagram
who have experience with HERMS in Malaysia.
3.3 SAMPLE
This research proposes to use sample-to-item ratio to determine the sample size for this research depending on the number of items.
A sample-to-item ratio of 5:1 should be the least number of respondents requested in the surveys (Suhr, 2016). Tabachnick and Fidell (2013)
presented a five-to-one ratio method for determining sample size requirement while considering the number of independent variables. The
sample size may be determined as below:
Independent Variables = (IV1 items × 5) + (IV2 item × 5) + (IV3 items × 5)
= (6 x 5) + (4 x 5) + (4 x 5)
= 30 + 20 + 20
= 70
Mediator Variable = (MV items x 5)
= (5 x 5)
= 25
Dependent Variable = (DV items x 5)
= (3 x 5)
= 15
Minimum number of respondents = 70 + 25 + 15
= 110 respondents
3.4 SAMPLING TECHNIQUE
This study used convenience sampling, which involves the targeted population of Instagram users who meet the required criteria,
such as availability at a specific time or willingness to participate, in the study. The sample must be characterized by the fact that it accurately
represents the population due to the sample's data is used to generalize or draw conclusions about the population (Lau, Phang, & Zainudin,
2012). This study adopts convenience sampling approach because it is easy to identify respondents' repurchase intention impacted by
Instagram e-WOM and brand equity of HERMS C Enterprise. It is affordable, accessible and the subjects are readily accessible (Ilker Etikan,
Sulaiman Abubakar Musa, Rukayya Sunusi Alkassim, 2016).
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3.5 DATA COLLECTION METHOD
Regardless of the topic of study, data collecting is at the core of this research. Any research project begins with a set of questions
that must be addressed (Dr. Huma Parveen & Nayeem Showkat, 2017). This study's data collection method is questionnaires distributed to
Instagram followers of HERMS C Enterprise. Rupesh (2010) claims that questionnaires are highly cost effective compared with interviews.
Therefore, the researcher would request the founder of HERMS C Enterprise to post a set of online questionnaire in the Google Form on its
Instagram page for its customers who are familiar and unfamiliar with its brand.
3.5.1 PRIMARY DATA
Questionnaires were used to collect primary data, which were organized based on the research questions listed in chapter
one. There have four sections in the questionnaires. There are both open and closed-ended questions in the questionnaires, which
provide the advantage of being easier for respondents to evaluate. According to Michael R Hyman & Jeremy J. Sierra (2016), it is
easier to respond to closed-ended questions regarding attitudes and behaviours. The questionnaire would involve a 5-point Likert
scale of 1-5. The purpose of collecting primary data is to study the effect of e-WOM and brand equity to repurchase intention
toward HERMS C Enterprise. However, primary data would not be sufficient to support this research. Therefore, secondary data
is needed in this research as well.
3.5.1 SECONDARY DATA
Secondary data is information that has been gathered and collated by someone and is available to the general public (Dr.
Huma Parveen & Nayeem Showkat, 2017). The secondary data of this research is from the Internet, which are Science Direct,
Google Sholar, academic articles, e-book and articles. Moreover, there have a variety of statistical results conducted by the previous
researchers would also be collected as secondary data to support this research. Hence, secondary data is essential to help the
researcher develops research questions, formulate the research designs, answer research questions, and provide insight into the
study.
3.6 RESEARCH MEASURE AND INSTRUMENT
Primary data would be collected via online questionnaires, which provide the researcher with first-hand data and trustworthy
information for this research. A structured questionnaire was utilized in the study as the data collection method. The questionnaire was
divided into four sections: personal information (age, gender, nationality, race and income levels), the brand equity of HERMS C Enterprise,
e-WOM (user-generated and firm-generated social media communication) and lastly is repurchase intention toward HERMS C Enterprise.
The questionnaire represents a set of questions designed to gather information from specific respondents (Malhotra, 2009).
Furthermore, the questionnaires would be designed as multiple-choice questions and open-ended questions. All components in this
study were measured using five-point Likert ratings that ranged from "Strongly disagree" to "Strongly Agree". Table 3.1 shows the five-
point Likert rating for measuring the effect of e–WOM and brand equity on the customers' repurchase intention toward HERMS C Enterprise.
STRONGLY DISAGREE DISAGREE NEUTRAL AGREE STRONGLY AGREE
1 2 3 4 5
Table 3.1: Five-point Likert Scale's Table
Adapted from: Zainudin Awang, Asyraf Afthanorhan & Mustafa Mamat (2016).
3.6.1 QUESTIONNAIRE DEVELOPMENT
A set of questionnaire was constructed based on the objectives of the research. By referring to the previous study,
researchers can get an understanding of the questionnaire's creation. Table 3.2 indicates the list of the questionnaire.
Variable Items Citation
Mediating 5 Uslu et al., 2013
Patria Laksamana, 2018; Devkant Kala & D.S. Chaubey, 2018; Schivinski &
Independent 14 Dabrowski, 2013
Dependent 3 Mirza & Almana, 2013; Devkant Kala & D.S. Chaubey, 2018
Table 3.2: Questionnaire Development
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3.7 DATA ANALYSIS
Data analysis is a set of techniques for detecting patterns, identifying facts, developing explanations, and testing hypotheses
(Malhotra, 2009). Quantitative research seeks insight through a less organized and more flexible method, whereas qualitative research
generates insights that are not reached by statistical techniques or other quantification methods (Hoepfl, 2015). The data for this study is
processed and analyzed using the Statistical Package for Social Sciences (SPSS) software for descriptive analysis, normality testing and
demographic data analysis. In contrast, Smart Partial Least Squares software will be used to test hypotheses and evaluate the connection
between independent (e-WOM and brand equity) and dependent variables (repurchase intention) in this research. Table 3.3 shows the variety
of methods apply in the study, while Table 3.3 shows the summary analysis planning and rule of thumbs of each analysis.
Statistical Measure Objective
Pilot test To determine the clarity of the questionnaire of this research. In effect, pilots are a risk-
mitigation method for reducing the chances of a bigger project failing.
Descriptive Analysis To analyse data from respondents' demographic backgrounds and the influences of e-
WOM and brand equity on Instagram customers' repurchase intention toward HERMS C
Enterprise.
Normality Test To ensure the data was taken from a normally distributed population.
Reliability Test To determine the reliability or consistency of findings across duration.
Path Coefficient Analysis To measure the level of relationships in two continuous variables.
Multiple Regression Analysis To find correlations between two or more variables with cause-and-effect relationships
and to make subject predictions utilizing the relationship.
Table 3.3: The Summary Analysis Planning and Rule Of Thumbs of Each Analysis.
RO Data Collected Analysis Rules of Thumb
Demographic Profile of Respondents Frequency Percentages
Descriptive Statistics Skewness and Kurtosis Skewness is between-2 and 2 and the Kurtosis is between -7
• Normality test and 7 (Anderson et al., 2013).
• Reliability Cronbach's Alpha Test scores must be larger than 0.7 (Hair et al., 2010).
1-4 Inferential Statistics Multiple Regression P-value < 0.05 (Hossain et al., 2013)
Table 3.4: The Summary Analysis Planning and Rule Of Thumbs of Each Analysis.
■ 4.0 DATA ANALYSIS
4.1 RESPONSE RATE
In this research, the minimum sample size is 120 respondents. 140 of respondents have been answered the questionnaire completely
through the Google Form. However, there has 9 outliers in the questionnaire. Therefore, the 9 outliers been eliminated from this research
and left 131 set of questionnaires accepted to be used in the data analysis. Table 4.1 shows that 131 out of 140 questionnaires are usable data,
representing a response rate of 93.57%. The response rate has to be at least 50% (Mugenda and Mugenda, 2003). According to Jack &
Fincham (2008), researchers should aim for response rates of around 60% for most studies. Hence, the response rate is acceptable in this
research.
Data Number of Questionnaire Percentage (%)
Minimum Sample Size 120 -
Collected Questionnaire 140 -
Outliers 9 6.43
Usable data 131 93.57
Table 4.1 Response Rate of the Research
4.2 DESCRIPTIVE ANALYSIS
4.2.1 RESPONDENTS’ DEMOGRAPHIC
This section summarized the demographics of the respondents in this study as shown in Table 4.2, which include age,
gender, nationality, race, region and level income. The majority of respondents are 20 – 25 years old where it consists of 62
respondents (47.3%), following with the others age group. The least group age in this research is 36 – 40 years old with just 1
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respondents (0.8%), meanwhile there are no respondents who are in the age group of 41 years old and above. In term of gender,
there has 115 female (87.8%) and 16 male (12.2%) participated in this research. All of the respondents are Malaysian. The highest
involvement in this study is Chinese respondents with 106 respondents (80.9%) while Malay and Indians recorded 19 respondents
(14.5%) and 6 respondents (4.6%) respectively. The most of the respondents’ religion are Buddha where it has 88 respondents
(61.2%), following by Islam, Christian and Hinduism. Lastly, the majority of respondents’ income level are RM2501 – RM3500
with 37 respondents (28.2%) and it follows by RM1500 and below with 34 respondents (26%).
Demographic Categories Frequency Percentage (%)
19 years old and below 10 7.6
20-25 years old 62 47.3
26-30 years old 46 35.1
Age
31-35 years old 12 9.2
36-40 years old 1 0.8
41 years old and above - -
Female 115 87.8
Gender
Male 16 12.2
Malaysian 131 100
Nationality
Non-Malaysian - -
Malay 19 14.5
Chinese 106 80.9
Race Indians 6 4.6
Others - -
Islam 20 15.3
Hindu 6 4.6
Religion Buddha 88 61.2
Christian 17 13
Others - -
RM1500 and below 34 26
RM1501 – RM2500 27 20.6
Income Level RM2501 – RM3500 37 28.2
RM3501 – RM4500 24 18.3
RM4501 and above 9 6.9
Table 4.2: Respondent Profile Analysis
4.1.1 DESCRIPTIVE ANALYSIS
The descriptive analysis for each variable is shown in Table 4.3. Mean and standard deviation are the finding of
descriptive analysis. According to Andrade (2020), the mean indicates the average value, whereas the standard deviation indicates
the average spread of values around the mean. Repurchase intention has the highest mean and standard deviation with 3.9466 and
0.66257 respectively.
Descriptive Analysis
Variable N Mean Std. Deviation
Statistic Statistic Statistic
Brand Equity 131 3.7969 0.65397
e-WOM 131 3.9097 0.51068
User Generated Social Media Communication 131 3.7939 0.51280
Firm Generated Social Media Communication 131 3.7481 0.56797
Repurchase Intention 131 3.9466 0.66257
Table 4.3: Descriptive Analysis
4.2 NORMALITY TEST
The skewness and kurtosis of the data distribution were used to determine the normality. The data to be ordinary if the skewness
was between -2 and 2 and the kurtosis was between -7 and 7 (Hair et al., 2010; Byrne, 2010). Based on the Table 4.4, each variable's skewness
value is in the range of -2 to +2. In addition, the values of kurtosis for each variable also in the range of -7 to 7. This indicates that the
research items are regularly distributed, allowing for further analysis of the data.
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Variable Skewness Kurtosis
Statistic Std. Error Statistic Std. Error
Brand Equity -0.171 0.212 -0.224 0.420
e-WOM 0.162 0.212 -0.369 0.420
User Generated Social Media 0.134 0.212 -0.166 0.420
Communication
Firm Generated Social Media -0.010 0.212 0.104 0.420
Communication
Repurchase Intention -0.264 0.212 0.089 0.420
Table 4.4: Skewness and Kurtosis Normality
4.3 VALIDITY ANALYSIS
4.3.1 CONSTRUCT VALIDITY
According to Mohajan (2017), construct validity is particularly essential for empirical measurements and testing of
hypotheses in theory creation. To determine the construct validity, researchers conducted a study in which they examined whether
the test's variables aligned with theoretical predictions (Sekaran & Bougie, 2010). Convergent and discriminant validity are the
two categories of construct validity. These two categories are aimed to ensure that the instruments are compatible with the concept
of speculation. For the best results, the loading value should be more than 0.5, as stated by Hair et al. (2010).
4.3.2 CONVERGENT VALIDITY
Convergent validity is being used to examine the extent to which numerous items evaluate the same idea (Ramayah et
al., 2011). It refers to the degree toward which results on one measure have a high, moderate, or low correlation with values on
another test that assesses the same construct. The loading value should be more than 0.5 to have the best results (Hair et al., 2010).
Based on Table 4.5, the result shows that all values are more than 0.5. It demonstrates the close connection between items that
measure the same construct and all items that fall into one component. Thus, the convergent validity was fulfilled.
BE E F R U
BE1 0.866
BE2 0.899
BE3 0.898
BE4 0.723
BE5 0.829
E1 0.82
E2 0.811
E3 0.791
E4 0.606
E5 0.547
E6 0.651
F1 0.942
F2 0.919
F3 0.949
F4 0.853
R1 0.879
R2 0.914
R3 0.908
U1 0.661
U2 0.899
U3 0.896
U4 0.8
Table 4.5: Result of Convergent Validity Test
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4.2.2 DISCRIMINANT VALIDITY
Discriminant validity refers to the degree whereby the constructs genuinely differ empirically from each other. It also
assesses the extent to which the overlapping constructs differ from one another (Hair et al., 2014). Based on the Table 4.6, all of
the values in the same construct are greater than those in other constructs. Hence, the discriminant validity is established.
BE E F R U
BE 0.846
E 0.702 0.713
F 0.525 0.575 0.917
R 0.726 0.596 0.484 0.901
U 0.527 0.629 0.863 0.508 0.82
Table 4.6: Discriminant Validity Assessment
4.3 RELIABILITY ANALYSIS
This research employs a reliability analysis. Reliability is a term that refers to a tool that enables researchers to determine the
quality of a questionnaire and prevent producing biased results. It is mandatory to evaluate the reliability of the scales and variables employed.
In terms of Cronbach’s Alpha, 0.9 and above is good, while 0.6 is consider acceptable, yet 0.5 and below is consider poor (George & Mallery,
2003; Bhatnagar et al., 2014). Based on Table 4.7, all values of Cronbach’s Alpha are consider acceptable as they are in the range from 0.811
to 0.936.
According to Hair et al. (2014), composite reliability values between 0.60 and 0.70 are acceptable, but in a more advanced stage,
the value has to be greater than 0.70 to be considered reliable. Table 4.7 shows that the composite reliability results are acceptable and
consider reliable where the values are greater than 0.7.
Barclay et al. (1995) stipulate that the AVE analysis have to be larger than 0.5. Based on Table 4.7, all the value of AVE are greater
than 0.5 where the values are in the range of 0.508 to 0.84. This indicates that all the dimensions are valid and acceptable for determining
the AVE value. As a result, the data are reliable and acceptable for use.
Average Variance
Cronbach's Alpha rho_A Composite Reliability
Extracted (AVE)
BE 0.899 0.903 0.926 0.715
E 0.811 0.852 0.858 0.508
F 0.936 0.939 0.955 0.84
R 0.884 0.889 0.928 0.811
U 0.83 0.827 0.89 0.672
Table 4.7: Reliability Analysis Result
4.4 HYPOTHESIS TESTING
Hypothesis testing is a statistical technique for evaluating a statement or hypothesis about a population parameter using data from
a sample. The results of the analysis are provided in Table 4.8 and Figure 4.1. The P-value should be smaller than 0.05 in this study. A P-
value of 0.05 indicates a degree of confidence greater than 95%. Additionally, the T-value has to be 1.645 or greater to support the hypothesis.
Table 4.8 summarizes the structural model framework's output from Smart-PLS. Based on the table below, H1, H3 and H4 are supported
and accepted, while H2 is not supported.
Original Sample Sample Standard T Statistics P Values
Hypothesis Path Deviation (|O/STDEV|) Decision
(O) Mean (M) (STDEV) (>1.645) (<0.05)
H1 U -> E 0.519 0.529 0.136 3.808 0.000 Supported
Not
H2 F -> E 0.127 0.121 0.144 0.885 0.377
Supported
H3 E -> BE 0.702 0.706 0.039 17.866 0.000 Supported
H4 BE -> R 0.726 0.726 0.044 16.412 0.000 Supported
Table 4.8: Path Coefficient and Hypotheses Testing
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Figure 4.1: Structural Framework
4.5 MULTIPLE REGRESSION
According to Moore et al. (2006), multiple regression is a statistical approach for analyzing the connection between a dependent
variable and independent variables. Hair et al. (2011) and Hair et al. (2013) proposed that R² values of 0.75 considered substantial, 0.50
considered moderate, and 0.25 considered weak for endogenous latent variables as a basic rule of thumb in academic research on marketing
concerns. Based on Table 4.9, the highest R² is 0.527 which is repurchase intention while the lowest R² is e-WOM with 0.4. Hence, the R²
of this research is acceptable as all the R² values are in the range of 0.50 which considered moderate.
R Square R Square Adjusted
BE 0.493 0.489
E 0.4 0.39
R 0.527 0.523
Table 4.9: R-Square
■ 5.0 DISCUSSION AND CONCLUSION
5.1 HYPOTHESIS DISCUSSION
The data and findings will be used to discuss the hypothesis and determine the significance of the relationship between user
generated social media communication, firm-generated social media communication, electronic word of mouth (e-WOM), brand equity and
repurchase intention toward HERMS C Enterprise.
H1: User-generated social media communication has a positive effect on electronic word of mouth (e-WOM).
01
H : User-generated social media communication has a negative effect on electronic word of mouth (e-WOM).
Based on the Table 4.8, the hypothesis testing results showed that the beta value and P-value (β= 0.519, t-value= 3.808, p-value=
0.000). This indicates that the relationship between user-generated social media communication and e-WOM are supported. Thus, user-
generated social media communication has a positive effect on e-WOM. The null hypothesis rejected. According to Abubakar et al. (2017),
customers rely on the e-WOM of other customers to help shape their purchasing decisions when it comes to a certain brand. Consumers'
feedback and opinions are collected through user-generated social media communication which can be used to improve relationship with
customers and new product development (Gu, Tang & Whinston, 2013). Regfeldt & Pallin (2021) believe that e-WOM would not exist
without user-generated social media communication as they are inextricably linked. Therefore, HERMS C Enterprise have to encourage
customers to share their opinion and feedback regarding the brand in order to improve it e-WOM on social media.
H2: Firm-generated social media communication has a positive effect on electronic word of mouth (e-WOM).
02
H : Firm-generated social media communication has a negative effect on electronic word of mouth (e-WOM).
The hypothesis testing results showed in Table 4.8 indicates that firm-generated social media communication and electronic word
of mouth (e-WOM) are not supported where beta value and P-value (β= 0.127, t-value= 0.885, p-value= 0.337). Therefore, firm- generated
social media communication has a negative effect on electronic word of mouth (e-WOM). The null hypothesis accepted. A similar factor
contributing to decreased trust in firm-generated content is when advertising fails to represent reality with its picture-perfect appearance
(Goh et al., 2013). This is a result, as consumers' understanding that marketers have an incentive to inflate product advantages in order to
make appealing advertising that results in sales. Due to customers' belief that marketers promote product benefits to the point that the
advertising is not perceived as trustworthy or authentic, users in both circumstances have a low level of trust in firm-generated content in
social media. As a result, past research has shown that firm-generated content in social media has a lower impact on consumers' trust (Goh
et al., 2013). In this study, the content to generated by HERMS C Enterprise might not being trusted by users as customers
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nowadays will trust another customer review more than what firm has claimed in the social media. Thus, HERMS should create more
interesting and accurate information regarding the products and services. The products reality need to align with its picture-perfect appearance
in the social media in order to increase the trustworthiness.
H3: Electronic word of mouth (e-WOM) has a positive and direct impact on brand equity.
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H : Electronic word of mouth (e-WOM) has a negative and direct impact on brand equity.
According to the result on Table 4.8, H3 is supported and accepted with the P-value is 0.000 and the T-value is 17.866. The result
showed that β value is 0.702 where it indicates that e-WOM has a significant relationship with brand equity. Therefore, electronic word of
mouth (e-WOM) has a positive and direct impact on brand equity. The null hypothesis rejected. According to Babic et al. (2015), eWOM is
one of the most important changes in modern consumer behaviour, transforming consumers into informed decision makers. In this study, the
customers more inclined to change their mind about the brand after reading a positive or negative review on HERMS C Enterprise on social
media. Furthermore, people would like to go for the brand suggested by friends on Instagram rather than a brand they do not recommend as
they are swayed by the opinions of others when it comes to making decisions. In terms of the subordinate brand equity aspects, e-WOM
positivity has a high impact on the consumer perception of brand, while also having a considerable impact on brand awareness, brand
associations, brand loyalty, and perceived quality. According to Murtiasih, Sucherly, & Siringoringo (2013), word- of-mouth can influence
several forms of brand perceptions, and this in turn can significantly influence brand equity. Hence, e-WOM of HERMS need to be improved
to increase and sustain it brand equity on social media.
H4: Brand equity has a positive and direct impact on repurchase intention.
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H : Brand equity has a negative and direct impact on repurchase intention.
The hypothesis testing results shows that the beta value and P-value (β= 0.726, t-value= 16.412, p-value= 0.000). This indicates
that there has a positive relationship between brand equity and repurchase intention are supported. Thus, the null hypothesis rejected.
Repurchase intention is positively influenced by brand equity (Lee, 2017). Firms need face intense competition if they expect to maintain a
following of loyal customers. Increasingly, companies recognize the brand as a competitive advantage and a valuable organizational asset.
In this study, HERMS customers are willing to repurchase HERMS products in the future as provides high-quality of products. Perceived
quality is one of the main elements in brand equity in order to increase the repurchase intention of customers. Once customers feel that the
company provides high quality of products, they will repurchase again and even will recommend the brand to others. Furthermore, the
followers of HERMS are aware of the brand and easily recognize the brand among the other activewear brands in social media. Brand
awareness and brand association also important to encourage customers to repurchase it brand. Customer repurchase decisions influenced
by brand awareness, where brand awareness fosters a sense of familiarity that drives purchasing decisions. While brand association appears
to have a beneficial effect on the recall of a brand and it would encourage customers to repurchase on the brand. According to Yee and Sidek
(2008), customers who are loyal to a certain brand are more likely to make well-informed purchases without conducting any further research.
Customers are more likely to stay loyal to a particular brand if they feel a sense of ownership and pride in it, especially in an increasingly
competitive market. Brand equity have a favorable and significant effect on repurchase intention (Pitaloka & Gumanti, 2019). Hence, all the
dimensions of brand equity have positively effect on repurchase intention toward a brand.
5.2 MANAGERIAL IMPLICATIONS
The outcomes of this study provide a framework for evaluating the impact of e-WOM and brand equity on repurchase intention
toward HERSM C Enterprise from a practical standpoint. Additionally, this study aims to educate marketers regarding the important of e-
WOM and brand equity when they use social media in order to increase and encourage customer to repurchase toward the brand. E-WOM
significantly influences brand equity characteristics, including customers' perceptions of brand quality and their brand choice, according to
this study. When users post negative comments about a brand online, other people's perception of that brand affects, which in turn reduces
their desire to buy from that brand. Because of this, marketers must pay attention on consumer feedback on social media platforms. E- WOM
has a significant impact on how customers evaluate a product and also can persuade them to make a purchase based on that evaluation
(Kudeshia & Kumar, 2017). Management should always be aware of this type of information and devise solutions to mitigate the negative
content. In addition, HERMS can actively encourage e-WOM by initiating consumer word-of-mouth communication. In order to encourage
positive e-WOM, HERMS need to develop an environment that encourages customers to assist other customers, or online brand communities,
in which brand representatives and voluntary customers offer information and support to customers in need (Kumar et al., 2010). In addition,
marketers may take into account the interactive aspects of social media, such as building a strong connection between the brand and its
existing customers through social media interactions. HERMS can encourages user generated content about its brand by offering a special
giveaway for customers who had follow its social media pages and share the particular promotion post on their personal profile and friends.
Apart from that, HERMS should develop and post more interesting and accurate information regarding the products and services. The
products reality need to align with its picture-perfect appearance in the social media in order to increase the trustworthiness. In order to
maintain customers loyal, marketers may require a good and interesting loyalty program for their current customers. Repurchase intention
not only is influenced by the present use of the brand, but also by the brand equity dimensions, which in turn influences repurchase intention.
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5.3 THEORETICAL IMPLICATIONS
Four supporting hypotheses were developed and tested in order to answer the study problem. Many publications and theories in
the field of marketing, particularly social media communication, have combined the effects of e-WOM and brand equity to evaluate the
impact on customer repurchase intention. Researcher developed a conceptual framework based on the hypotheses to illustrate the various
ways in which consumers' repurchase intentions can be influenced.
5.4 LIMITATION AND RECOMMENDATION OF THE RESEARCH
There are several limitations and recommendations that should be taken into account for future research in order to enhance the
quality. First, the research just focused on the customers of HERMS C Enterprise who are have experience with HERMS on Instagram in
Malaysia for the preliminary stages of investigation. Therefore, the results can only be interpreted in terms of this particular population.
Future research can broader geographical diversity in order to generalize the data patterns on a global scale. Furthermore, survey
questionnaire method was used in this study. Closed-ended questionnaires constrained the opinion of the respondents. For future research,
a variety of other methodologies, such as focus groups and interviews, also can be employed to gain a better understanding of the topic.
Despite the fact that construct attribute variables were utilized to investigate consumers' repurchase intention, several potential aspects such
as perceived ease of use, reliability and perceived usefulness were overlooked. Those aspects will have a broader impact on customers’
repurchase intention. In order to boost the level of study, future studies should investigate these probable factors.
5.5 CONCLUSION
This research studied about the effect on brand equity on customer’s purchase intention, involved firm-generated social media
communication and firm-generated social media communication which under electronic word-of-mouth (e-WOM). Four objectives and
hypotheses would be proposed and developed conceptual framework in this research. 140 of respondents have been answered the
questionnaire completely through the Google Form. However, there has 9 outliers in the questionnaire. Therefore, the 9 outliers been
eliminated from this research and left 131 set of questionnaires accepted to investigate the relationship between the independent variables
and dependent variable. All the data would be examined by using Smart PLS and SPSS software. The finding results show the user- generated
social media communication has a positive impact on e-WOM. However, the relationship between firm-generated social media
communication and e-WOM are not supported, where these attributes need to be improved and give more attention toward the attributes. On
the other hand, e-WOM has a positive effect on brand equity and brand equity also has a direct positive impact on repurchase intention
toward HERMS C Enterprise. Future study on repurchase intention could be accomplished by introducing other aspects into the conceptual
model. Lastly, three of the four hypotheses has been fulfilled and research questions and objectives were addressed in this study.
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