Megawati
Simanjuntak
Department
of Family and Consumer Sciences,
Faculty
of Human Ecology, IPB University, Indonesia
E-mail: mega_juntak@apps.ipb.ac.id
Ujang
Sumarwan
Department
of Family and Consumer Sciences,
Faculty
of Human Ecology, IPB University, Indonesia
Email
: usumarwan@gmail.com
Ariel
Diesto Situmorang
School
of Business, IPB University, Indonesia
Email
: ariel@situmorang.web.id
Submission: 1/15/2019
Accept: 9/19/2019
ABSTRACT
The study aimed to analyze the effect of the marketing mix (product, price,
location, promotion, service, human resources, and physical evidence) and brand
image of premixed mortar customer loyalty. A total of 100 questionnaire surveys have been
distributed to customers in greater Jakarta area who became a decision-maker in
a high rise building project. Based on the analysis of the effect of the marketing
mix and brand image on premixed mortar loyalty, it can be concluded that
product, price, process, and brand image significantly affects loyalty. The
variable that has the most significant effect is the price, followed by the
product, process and brand image.
1.
INTRODUCTION
Services construction is one of the
strategic sectors to support national development. According to Dipohusodo (1996), a construction project is a project on
building infrastructure, which generally covered the work of civil engineering
and architecture. Services according to Kotler (2011), are every action offered
by one party to another party, which is intangible and does not result in
ownership of something.
An increase in the
services sector construction is also affecting demand goods consumed at the
project, namely the cement industry. Cement is one
of the commodities that encourages the development of construction services: the development, especially construction, in proportion to the needs of cement that
consumed every year. The data compiled by Indonesia Cement Association proved that the national cement consumption is
increasing every year, the latest data show there was a rise in cement
consumption in 2016 of 1 million tons, resulted in a total of 62 million tons on cement consumption.
The growth of cement
production also affects the increase in premixed mortar production. The
prospect of the premixed mortar cement industry has increased significantly
over the years. In 2011 record, premixed mortar there is only ten companies
that produced premixed mortar; however, in 2016, there are 104 companies produce
the premixed mortar. This indicates that business in the field of industrial
materials building is exciting and promising. The data obtained from factory
production capacity per year
shows only five
companies that could be classified as a large scale (>250,000 tons/year) and
the rest are local players.
The number of newcomers proved how this industry is very interesting to develop. These new companies generally rely on prices that are relatively cheaper than big players but override the quality of products and services. Consumers who have a good impression on a product will make the product into consideration for the next project. With this approach, companies apply mix marketing to obtain a distinct impression and responses from the customers as part of the company strategy to improve company performance. Mix marketing applied seven variables (7P), including covering, product, price, place, promotion, process, people, and physical evidence (BOOMS; BITNER, 1981). Rahman et al., (2019) found that marketing mix significantly and positively influenced on loyalty.
The company also has to observe the brand image that
flourished in the market. Consumer positive attitudes toward the brand will affect consumer’s loyalty (SUMARWAN, 2014). Simanjuntak et al., (2019) also found that emotion as attitude also influence on the repurchase intention. So the brand image is a variable that essential to provide a view for the company. The
7P marketing mix strategy and brand image that is carried out are expected to
provide outcomes as input for the company in the future.
Based on the problem mentioned above, this study aimed to analyze the effect of the
marketing mix (product, price, location, promotion, service, human resources,
and physical evidence) and brand image of premixed mortar customer loyalty. The paper consists of the following
section: literature review, research methodology, result and discussion and conclusion.
2.
LITERATURE REVIEW
2.1.
Premixed Mortar
Cement is an adhesive
used in building materials such as stone, adobe, red bricks, or light brick.
Cement will become adhesive when mixed with water.
Along with the time, technology enables consumers to be more practical, consistent and maintain
homogeneity products, thus resulted in a product called premixed mortar
(instant cement). Premixed mortar is cement ready-made
whose component in the form of are generally cement, sand, filler, and various
kinds of additive that adapted to its function. Mortar is part of structural
building elements and has functions in making foundations or walls (KURNIADI;
HERUMANTA, 2016).
The advantages of using
premixed mortar (ARIF; ABDILLAH, 2011) are consistency, convenience,
quality, material efficiency, and energy efficiency. Premixed
mortar has a standard condensed, which is useful in determining mortar strength
according to its function and usefulness, so it is expected that the mortar
that withstands the compressive forces due to the load working on it is not
destroyed (MULYONO, 2003). An excellent premixed mortar
according to Tjokrodimuljo (1996) should have a
cheap, durable, easy to apply (stirred, lifted, fitted and flattened), adheres
well with bricks/stone or other media, quick-dry and hardened, resistant to
water seepage, and no cracks arise after installation.
2.2.
Marketing Mix
According to Sumarwan et al. (2009), there are three levels of marketing
mix interaction, i.e., consistency
is a logical fit
between two or more elements of the marketing mix, integration is a harmonious
relationship to each marketing mix variables, and last is leverage is a right
and related approach to support any marketing mix variables. According to
Kotler (2011), the marketing mix is a systematically developed strategy through
tactical marketing, pricing, place, and promotion (4P). Products, prices,
places, and promotions are the factors that cause the business to succeed or
fail (NUSEIR; MADANAT, 2015). The company integrates these four variables to produce the
desired response in a targeted market.
However, today 4P is
evolving into 7P to respond to the nature of the service to the consumer. The concept of 7P's in the marketing
mixrequired to plan viable strategies in order to fulfill the customer need
profitably in a stiff marketplace (LOVELOCK, 2011). Each variable will interact with
each other so that mutual support and sustainability can be achieved. Lovelock and Wright (2007) say that in the
service process, three additional elements of 4P development are considered to
have a role, i.e., the process is a method of operation or a series of specific
actions required in a sequence that has been applied. Second is the person
(human resources), i.e., the employees involved in the
interaction. Third is physical evidence of visual cues that provide evidence of
the quality that the service provided.
2.3.
Customer Loyalty
Subagyo
(2010) argues that consumer loyalty is the purchase of a brand consistently by
customers. Sumarwan (2014) states that brand loyalty
is defined as a consumer's positive attitude towards a brand; consumers have a
strong desire to buy the same brand in the present and future. Real loyalty
cannot be formed if the customer does not or has not made the purchase process
first. Brand loyalty will lead to the emergence of brand commitment, namely the
emotional and psychological closeness of a consumer to a product (SUMARWAN, 2014). One way to sustain consumers is to maintain good relationships
with consumers, as customers with long-term loyalty will not easily switch to
other brands, while customers with short-term loyalty defect more quickly when
faced with a better alternative (LIU et al., 2011).
Therefore, companies
are competing to retain existing customers, and even to entertain consumers so
as not to move to other products. The theory by Griffin (2005) explained that
there are four loyal customer variables include:
a) Make a purchase regularly
b) Buying between product lines or
services
c) Not affected by the competition of
other similar products
d) Recommend to others
2.4.
Product
Product by Kotler
(2011) is everything that can be offered to the market to get attention,
bought, used, or consumed that can satisfy the wants or needs. Conceptually the
product is a personal understanding of the producer of something that can be
offered as an attempt to achieve organizational goals through the fulfillment of
consumer needs and activities, under the competence and capacity of the
organization and the purchasing power of the market.
· H1: The product has a significant
effect on loyalty.
2.5.
Price
The definition of the price
according to Kotler (2011), is the amount of money charged to a product or
service. More broadly, the price is the total value that consumers exchange for
a profit from ownership of a product or service. The price according to Sumarwan (2014), is an amount of money that is worth spending
on many goods or services. Arokiasamy (2012) suspect that
the marketing mix and consumer perceptions influence the variable forming of
consumer loyalty.
· H2: Price has a significant effect
on loyalty.
2.6.
Place
Kotler (2011) stated
that the non-strategic location of the consumer allows the possibility of a
smaller interest in the products offered. Location is a consumer that decides to
make transactions and buy something they want. Utomo
and Nurmalina (2011), concluded customer satisfaction
and loyalty to be formed from service quality.
· H3: Location has a significant
effect on loyalty.
2.7.
Promotion
Promotion can be
interpreted as communication because, through effective communication, there is
a beneficial interaction (KOTLER, 2011). Promotions by companies vary according
to company strategy.
H4: Promotion has a significant effect on loyalty.
2.8.
Process
A service is a set of
methods or operating procedures that require measurements and steps to be taken
jointly at work. Kotler (2011) says the process/service is a set of methods or
operating procedures that require measurements and stages to be done jointly at
work. The process of one of the activities is done by providing services to
someone.
·
H5:
Process has a significant effect on loyalty.
2.9.
People
Ahmady
(2012) said that the relationship between seller and buyer is not based only on
the transactional aspect but also on the social aspect that helps the
interaction happened. This aspect will lead to another goal, which is a convenience
between two sides. Nasuka (2016) study revealed that
there is a significant indirect relationship between salespeople and consumer
loyalty, mediating by consumer satisfaction. This means that that sales
attitude has a positive and significant relation to customer satisfaction.
·
H6:
People vea significant effect on loyalty.
2.10.
Physical Evidence
Booms and Bitner (1981) said that physical evidence as a visual sign
or physical aspects that affect the quality of service. The appearance of the company's
physical facilities, infrastructure, and the circumstances of the surrounding
environment are clear evidence of the services provided by the service
provider. Physical evidence may include physical facilities (buildings,
warehouses, and so on), equipment and equipment used (technology), and the
appearance of employees. Zeithalm et al. (2006) state
that physical evidence communicates to consumers where and how service
organizations play a role in creating service experience in satisfying
consumers and in enhancing consumer perceptions about service quality.
·
H7:
Physical evidence has a significant effect on loyalty.
2.11.
Brand Image
Imagery cannot be
described physically because it is only in the minds of society/perception.
Kotler and Armstrong (2001) argue that brand image is a set of consumer beliefs
about a particular brand. An image is a company asset because it has an impact
on consumer perception. When consumers believe in a specific brand, it will
cause a perception of the product’s brand. Schiffman
and Kanuk (2007) define perception as an individual
process for selecting, processing, and interpreting the stimulus into a
particular picture. Therefore, perception is the view of a person seeing the
reality that occurs around him.
·
H8:
Brand image has a significant effect on loyalty.
3.
RESEARCH METHODOLOGY
3.1.
Data
The research activities were
conducted in Jabodetabek. Data collection was conducted by a direct survey to the respondents who have used the
product of premixed
mortar as 100 respondents. The
selection in the Jabodetabek area as a place of research is based on the
highest growth rate of development compared to other big cities.
3.2.
Variables
Exogenous
latent variables in this study were the product (X1), price (X2), place (X3),
promotion (X4), process (X5), people (X6), physical evidence (X7), brand image
(X8), the endogenous latent variable was loyalty (Y1). Measurement scale used
is a Likert scale with 5 (five) points, one state strongly disagrees, and five
states strongly agree.
Table 1: Likert scale score
No |
Answer |
Score |
1 |
Strongly agree |
5 |
2 |
Agree |
4 |
3 |
Neutral |
3 |
4 |
Disagree |
2 |
5 |
Strongly disagree |
1 |
The research conducted using the 7P
marketing mix and brand image as an exogenous variable. The eight exogenous and
one endogenous variable are:
1. Products (X1). This variable has
seven indicators, namely:
(X1.1): famous products
(X1.2): diverse products
(X1.3): the product is easy to apply
(X1.4): the resulting product is qualified
(X1.5): consistency of quality between each
product
(X1.6): the product is environmentally
resistant
(X1.7): the product is well packed
2. Price (X2). This variable has three
indicators, namely:
(X2.1): price according to product quality
(X2.2): price competes with other brands
(X2.3): acceptable terms of payment
3. Place (X3). This variable has three
indicators, namely:
(X3.1): large production capacity
(X3.2): factory location close to the
center of development
(X3.3): ease of delivery if the
product needs undertones
4. Promotion (X4). This variable has
five indicators, namely:
(X4.1): the product catalog is
informative and easy to understand
(X4.2): interesting product samples
(X4.3): testimony from the previous
project
(X4.4): conducting periodic field
supervision
(X4.5): hold periodic gatherings
5. Process (X5). This variable has six
indicators, namely:
(X5.1): customer service procession
responded quickly
(X5.2): the training service
procession responded well
(X5.3): the mock-up service
procession responded well
(X5.4): the supervision service procession
responded well
(X5.5): a fast procession from the
stage of order to delivery of product material
(X5.6): delivery of product materials
on time
6. People (X6). This variable has six
indicators, namely:
(X6.1): friendly sales team attitude
towards consumers
(X6.2): a well-dressed
and standard-looking sales team
(X6.3): follow-up by the sales team regularly
(X6.4): a trustworthy sales team
(X6.5): team sales can be contacted
at any time
(X6.6): the explanation of the
technician team is easy to understand
7. Physical evidence (X7). This variable
has four indicators, namely:
(X7.1): delivery of products under
operational standards
(X7.2): there is a project support
letter
(X7.3): there are technical data in
each product variation
(X7.4): the driver is willing to wait
for the loading queue
8.
Brand
Image (X8). This variable has three indicators, namely:
(X8.1): the brand is easy to remember
(X8.2): the brand is familiar
(X8.3): the brand has a distinctive
feature in each product
9.
Loyalty
(Y1). This variable has four indicators, namely:
(Y1.1): make purchases regularly
(Y1.2): buy the inter-product line
from offered
(Y1.3): not affected by the
competition of other similar products
(Y1.4): recommending the brand to
others
3.3.
Structural Equation Modeling
The tool used in the research is a
questionnaire, a set of computers, software SmartPLS 2.0. Data are processed by using PLS
(Partial Least Square), PLS is one of the alternative method of SEM (Structural
Equation Modeling) which can be used to overcome problems in the relationship.
The purpose of the PLS is to predict the effect of variable X on Y and explain
the theoretical relationships between the two variables (TALBOT, 1997).
PLS has the assumption of free
research data distribution, meaning that the research data does not refer to
one particular distribution (GHOZALI, 2008). PLS is an alternative method with a variance-based or
component-oriented approach to model prediction, whereas covariance-based SEM
methods are oriented toward modeling analysis and require a robust theoretical
basis of a relationship model.
4.
RESULT AND DISCUSSION
4.1.
Outer model evaluation
Evaluation
of the measurement model is performed on each latent variable by testing the
validity and reliability of the construct. The size of a valid indicator if it
has a loading factor (λ) with latent variables to be measured > 0.50
(IGBARIA et al., 1997) and has a value of t-value > 1.96. According to Hartono (2008), if the value of the t-value is
higher than t-table, then the hypothesis is accepted (t-value > 1.96), which means the
influence of variables on the dependent variable is significant. Based on the
loading factor and t-value obtained and can be seen in Table 2.
Table 2: Validity test of the premixed mortar measurement model
Relation |
Loading Factor |
T-Value |
X1.1 à Product X1 |
0.538 |
3.149* |
X1.2 à Product X1 |
0.848 |
26.966* |
X1.3 à Product X1 |
0.644 |
6.272* |
X1.4 à Product X1 |
0.885 |
43.898* |
X1.5 à Product X1 |
0.830 |
19.882* |
X1.6 à Product X1 |
0.830 |
20.199* |
X1.7 à Product X1 |
0.862 |
36.484* |
X2.1 à Price X2 |
0.928 |
64.247* |
X2.2 à Price X2 |
0.860 |
38.191* |
X2.3 à Price X2 |
0.884 |
25.761* |
X3.1 à Price X3 |
0.977 |
7.095* |
X3.2 à Price X3 |
0.936 |
7.715* |
X3.3 à Price X3 |
0.965 |
6.939* |
X4.1 à Promotion X4 |
0.876 |
4.383* |
X4.2 à Promotion X4 |
0.919 |
5.47* |
X4.3 à Promotion X4 |
0.887 |
4.633* |
X4.4 à Promotion X4 |
0.722 |
3.669* |
X4.5 à Promotion X4 |
0.893 |
4.634* |
X5.1 à Process X5 |
0.832 |
32.805* |
X5.2 à Process X5 |
0.820 |
29.444* |
X5.3 à Process X5 |
0.851 |
27.11* |
X5.4 à Process X5 |
0.811 |
17.801* |
X5.5 à Process X5 |
0.841 |
24.597* |
X5.6 à Process X5 |
0.815 |
18.232* |
X6.1 à People X6 |
0.850 |
3.595* |
X6.2 à People X6 |
0.772 |
3.139* |
X6.3 à People X6 |
0.791 |
3.007* |
X6.4 à People X6 |
0.616 |
2.072* |
X6.5 à People X6 |
0.889 |
3.526* |
X6.6 à People X6 |
0.920 |
3.877* |
X7.1 à Physical Evidence X7 |
0.844 |
3.825* |
X7.2 à Physical Evidence X7 |
0.902 |
3.345* |
X7.3 à Physical Evidence X7 |
0.976 |
3.402* |
X7.4 à Physical Evidence X7 |
0.878 |
3.599* |
X8.1 à Brand Image X8 |
0.591 |
2.031* |
X8.2 à Brand Image X8 |
0.763 |
8.077* |
X8.3 à Brand Image X8 |
0.908 |
31.881* |
Y1.1 à Loyalty Y1 |
0.717 |
14.137* |
Y1.2 à Loyalty Y1 |
0.905 |
34.352* |
Y1.3 à Loyalty Y1 |
0.869 |
35.602* |
Y1.4 à Loyalty Y1 |
0.900 |
48.410* |
Note: loading factor score > 0.5; T-Value >
1.96 = valid
Based
on the results of the loading factor and t-value obtained and can be seen in
the table above, it can be concluded that all loading factor from the
relationship of indicator variable with latent variable has loading factor >
0.5 and has a value of t-value > 1.96. This indicates that all the indicator
variables are valid to measure the latent construct.
The
results of SEM measurement analysis indicate that for the product, the highest indicator of contribution is
X1.4, which is 0.885 of loading factor and
t-value 43.898. Whereas for the
price, the highest contribution
is X3.1, namely 0.977 of loading factor with
a t-value of 7.095. On promotion, the highest contribution is X4.2 which is
0.919 of loading factor with
t-value 5.47. In the process, the highest contribution is X5.3 which is 0.851 of loading factor with
t-value 27.11. The highest contribution to people is X6.6, which is 0.920 of the loading factor with a
t-value of 3.877. At the most substantial evidence, the physical contribution
is X7.3 namely 0.976 of loading factor with
t-value 3.402. In the highest brand image, the contribution is X4.2, which is
0.908 of the loading factor with
a t-value 31.881. Finally, the highest contribution to loyalty is Y1.2, which
is 0.905 of the loading factor with
t-value 34.352. The indicators with the highest factor loading values indicate
the highest causality relationship from the indicator
to the construct.
Another
method that can be used to measure the validity of a construct is to look at
the value of AVE in each latent variable. The AVE value for each latent
variable has a value > 0.5 is highly recommended. Based on Table 3, the AVE
value of the product, price, location, promotion, process, people, physical
evidence, brand image, and loyalty indicate that more than 0.5 indicates that
each variable is a valid indicator to measure its latent construct.
Furthermore, a variable is said to be quite consistent if the variable has a value of composite reliability > 0.7. Table 3 shows that all values of composite reliability > 0.7; therefore it can be concluded that the indicators used in this study have good reliability or able to measure the construct. The evaluation of the measurement model shows that the overall model fit with the data so that the results of this study can be declared valid and reliable.
Table 3: Score of AVE, Composite Reliability and r square of
laten variable
Laten
Variables |
AVE |
Composite Reliability |
R Square |
Product |
0.618 |
0.917 |
- |
Price |
0.794 |
0.920 |
- |
Place |
0.92 |
0.972 |
- |
Promotion |
0.744 |
0.935 |
- |
Process |
0.686 |
0.929 |
- |
People |
0.66 |
0.920 |
- |
Physical
evidence |
0.812 |
0.945 |
- |
Brand image |
0.585 |
0.804 |
- |
Loyalty |
0.725 |
0.913 |
0.836 |
4.2.
Indicator Contribution toward
Variables
4.2.1. Indicator Contribution toward
Product
The
loading factor value means the contribution of the indicator to the variable. The
indicator which has the least value is well-known product indicator with a 0.538
loading factor, indicating that this indicator provides the least relative
contribution rate to product variables (Table 4). Quality
product indicator with loading factor 0.885 is the most contributing indicators
of the product. Consumers prioritize the quality of products produced and see
goods based on the quality offered.
Table 4:
Indicator contribution to product variable
Indicators |
Loading Factor |
t-value |
Famous |
0.538 |
3.149* |
Diverse |
0.848 |
26.966* |
Easy
application |
0.644 |
6.272* |
Quality |
0.885 |
43.898* |
Consistent |
0.830 |
19.882* |
Resistent |
0.830 |
20.199* |
Well
packed |
0.862 |
36.484* |
Note: loading
factor > 0.5 = valid, t-value >
1.96 = significant
4.2.2. Indicator Contribution toward Price
Based
on the result of the study note that the price indicator, according to quality,
competitive prices, and acceptable payment process, is an indicator that
contributes significantly to the price variable (Table 5). The
indicator that has the least value is price competing with a 0.860 loading
factor, indicating that the indicator provides the least relative contribution
rate to the price variable. The price indicator corresponds to the product
quality with the loading factor value of 0.928 is the greatest contribution.
This indicates that the quality of the product is proportional to the price
offered. Consumers will continue to use the product when the price offered
matches the quality provided.
Table 5: Indicator contribution to price variable
Indicators |
Loading Factor |
t-value |
According to quality |
0.928 |
64.247* |
Compete |
0.860 |
38.191* |
Payment |
0.884 |
25.761* |
Note: loading
factor > 0.5 = valid, t-value >
1.96 = significant
4.2.3. Indicator Contribution toward Place
The
results of the PLS calculation indicate that the indicator of production
capacity, the location of the plant near the center of development, as well as
the ease of delivery if the need for undertonase is an indicator that
contributes to the location variable (Table 6). The
indicator which has the least value is the factory indicator near the
development center, with the loading factor 0.936. The indicator of production
capacity at the factory with the loading factor value of 0.977 is the most
contributing indicator. The higher the production capacity, the more products
are produced, so the product can be ready to send without waiting for the
production queue. With large production, companies can issue guarantees to
projects with extensive needs.
Table 6: Indicator contribution to place variable
Indicators |
Loading Factor |
t-value |
Production
capacity |
0.977 |
7.095* |
Factory
near the center |
0.936 |
7.715* |
Undertonase |
0.965 |
6.939* |
Note: loading
factor > 0.5 = valid, t-value >
1.96 = significant
4.2.4. Indicator Contribution toward
Promotion
Based
on the results of PLS show an informative product catalog, interesting product
samples, there is testimony / reference from the previous project, the
procurement of periodic supervision, and held a periodic gathering is an
indicator that contributes to the promotional variable (Table 7).
The indicator which has the least value is an informative product catalog
indicator with a loading factor of 0.876. The promotional variable is
represented by product samples that contribute the most with a loading factor
value of 0.919. It is known that the samples of the products provided are
interesting and informative. Especially in one sample consists of many products
displayed, making it easier for consumers to see and assess the products
listed. Great product samples can also convince consumers to use the product.
Table 7: Indicator contribution to promotion variable
Indicators |
Loading Factor |
t-value |
Catalog |
0.876 |
4.383* |
Product
sample |
0.919 |
5.470* |
Project
testimony |
0.887 |
4.633* |
Periodic
supervision |
0.722 |
3.669* |
Gathering
|
0.893 |
4.634* |
Note: loading
factor > 0.5 = valid, t-value >
1.96 = significant
4.2.5. Indicator Contribution toward
Process
Based
on the results of the calculation of the PLS shows customer service, training, mock-up,
supervision, the fast procession from the stage of order to the delivery of
product materials, and delivery of materials on time products are indicators
that contribute to service variable (Table 8). The
indicator which has the least value is the indicator of supervision service
with the loading factor of 0.811. The mock-up process, with the loading factor
value of 0.851, becomes the most influential indicator. A mock-up is a function
of providing an example of how the application and see the results of the
products that have been installed in the project, usually combined with other
products. This is seen from the better mock up service provided by the company,
the higher the loyalty generated by consumers.
Table 8: Indicator contribution to a process variable
Indicators |
Loading Factor |
t-value |
Customer
Service |
0.832 |
32.805* |
Training |
0.820 |
29.444* |
Mock up |
0.851 |
27.110* |
Supervision |
0.811 |
17.801* |
Fast
order |
0.841 |
24.597* |
Material
delivery |
0.815 |
18.232* |
Note: loading
factor > 0.5 = valid, t-value >
1.96 = significant
4.2.6. Indicator Contribution toward People
Based
on the results of the calculation of the PLS shows a friendly sales attitude,
sales look neat, follow up by the sales team regularly, the sales team can be trusted, the
sales team can be contacted at any time, and explanation technician team is
easy to understand are indicators that contribute to people variables (Table 9). The indicator which has the least value
is a reliable sales indicator with a loading factor of 0.616. An explanation by
a technician with a value of 0.920 loading factor becomes the most influential.
This happens because the project requires information not only technical data
products but also requires field data. Explanation of the technician to
strengthen the written data. At the time of mock-up activities, a technician
team doing the explanation of the start application, constraints, and the
strength of the product. Technician explanation can also influence purchasing
decisions because it can affect consumers in selecting products.
Table 9:
Indicator contribution to people variable
Indicators |
Loading Factor |
t-value |
Friendly
sales |
0.850 |
3.595* |
Neat
sales |
0.772 |
3.139* |
Follow
up periodic |
0.791 |
3.007* |
Sales
can be trusted |
0.616 |
2.072* |
Sales are
easy to contact |
0.889 |
3.526* |
Technician
explanation |
0.920 |
3.877* |
Note: loading
factor > 0.5 = valid, t-value >
1.96 = significant
4.2.7. Indicator Contribution toward
Physical Evidence
PLS
shows the delivery of products in accordance with operational
standards, there is a letter supporting the project, there is technical data in
each product, and the driver is willing to wait for the loading queue are an
indicator that contributes to the physical evidence variable (Table 10). The indicator which has the smallest
value is the product delivery indicator in accordance with the operational
standard with the loading factor value of 0.844. The availability of technical product data with the loading factor
value of 0.976 is the indicator that most contribute to the physical. Physical
evidence on products that tohave technical
data means that the consumer realizes that a good product is a product that has
complete data either in the specification, method of application, or chemical
data product.
Table 10: Indicator contribution to physical evidence
variable
Indicators |
Loading Factor |
t-value |
Delivery product |
0.844 |
3.825* |
Supporting letter |
0.902 |
3.345* |
Technical data |
0.976 |
3.402* |
Queue of loading |
0.878 |
3.599* |
Note: loading
factor > 0.5 = valid, t-value >
1.96 = significant
4.2.8. Indicator Contribution toward Brand
Image
Based
on the results of PLS calculations show the brand is easy to
remember, familiar brand and brand have characteristics that are indicators
that contribute to brand image variable (Table 11). The
indicator which has the least value is the brand indicator is easy to remember
with the loading factor value of 0.591. The brand indicator characterizes each
product as the indicator that most contributes to the brand image with the
loading factor of 0.908. This is because product characteristics that other brands
do not have can be a product advantage to increase consumer loyalty. Easy to
stick to the basic media and long dry when the application is a part of the product
which has characteristics.
Table 11: Indicator contribution to brand image
variable
Indicators |
Loading Factor |
t-value |
Easy to
remember |
0.591 |
2.031* |
Known
brand |
0.763 |
8.077* |
Have
characteristics |
0.908 |
31.881* |
Note: loading
factor > 0.5 = valid, t-value >
1.96 = significant
4.2.9. Indicator Contribution toward
Loyalty
Based
on the results of PLS calculations showing regular purchases,
purchasing each product variant, not being affected by other similar product
variants, and recommending products to others are indicators that contribute to
loyalty variables (Table 12). The
indicator which has the least value is a regular purchase indicator with a
loading factor value of 0.717. The purchasing indicator for each product line
with a loading factor of 0.905 is the most contributing to loyalty. This is
because consumers who buy each product indicate greater loyalty level. For
example, any use of the work area of wall or floor system, it has several products that can facilitate
these areas, buying each product line means that consumers buy all the products
that are part of the area.
Table 12: Indicator contribution to loyalty variable
Indicators |
Loading Factor |
t-value |
Regular
purchases |
0.717 |
14.137* |
Buy
each product line |
0.905 |
34.352* |
Not
affected by similar products |
0.869 |
35.602* |
Recommend
products |
0.900 |
48.410* |
Note: loading
factor > 0.5 = valid, t-value >
1.96 = significant
The
structural model can be evaluated by looking at the R-square value of
endogenous latent variables. Table 13 shows that the R-square value of loyalty variable is 0.836, meaning that
the loyalty can be explained by product, price, place, promotion, process,
people, physical evidence, and brand image of 83.6%, the remaining 16.4% is
other variables outside the model. If the Goodness of Fit value > 0.36, then
the model validation is good (COHEN,
1988). A value of 0.78 over 0.36 indicates that model validation is good.
Table 13: Goodness of Fit score
Variables |
Communality |
R-Square |
Product |
0.618 |
- |
Price |
0.794 |
- |
Place |
0.92 |
- |
Promotion |
0.744 |
- |
Process |
0.686 |
- |
People |
0.66 |
- |
Physical
Evidence |
0.812 |
- |
Brand Image |
0.585 |
- |
Loyalty |
0.725 |
0.836 |
4.4.
Hypothesis Test
The
most influential variable to loyalty is the price with the coefficient loading
factor of 0.431 and the t-value of 3.608 (Table 14). Then
followed by a product with a loading factor of 0.279 and t-value of 2.596, then
process with loading factor of 0.181 and t-value of 2.013, then brand image
with a large 0.146 and t-value of 2.067. This becomes one of the notes that
project work requires support from suppliers not only products but also
services provided after the goods are delivered. In the structural equation
model of premixed mortar, physical evidence, promotion, human resources, and
location do not affect premixed mortar loyalty as seen from the t-value value
of < 1.96 each.
Table 14: Results of hypothesis
Relationship |
Beta Coef |
T-value |
Conclusion |
Product à
Loyalty |
0.279 |
2.596 |
Accept
H1 |
Price à
Loyalty |
0.431 |
3.608 |
Accept
H2 |
Place à
Loyalty |
0.072 |
1.631 |
Reject
H3 |
Promotion à
Loyalty |
-0.023 |
0.571 |
Reject
H4 |
Process à
Loyalty |
0.181 |
2.013 |
Accept
H5 |
People à
Loyalty |
-0.001 |
0.015 |
Reject
H6 |
Physical
Evidence à Loyalty |
0.028 |
0.698 |
Reject
H7 |
Brand Image à
Loyalty |
0.146 |
2.067 |
Accept
H8 |
Note: T-value > 1.96 is significant
4.4.1. The Relationships between Product
and Loyalty
From the data obtained shows that
product variables between the two brands have significant results. This means
that product variables have a significant effect on consumer loyalty. This
result is in accordance with the research of Nuseir and Madanat (2015) which
states that the product affects loyalty.
Product variables (4.53) have a high value. This is based on good products
being the main choice in supporting the sustainability of the project. It prioritizes well-known products, products that are diverse, easy to
apply, consistent quality, and packaging. From the results obtained, the higher
the value of the product will increase loyalty. For product-oriented consumers,
the better the use of these products, the higher the intensity of purchases on
the products offered.
4.4.2. The Relationships between Price and
Loyalty
Based on the results of the
analysis, the relationship between price and loyalty variables on both brands
has significant value. This is based on not only the product which is the
reason consumers choose and use the brand but also the price. The value of the
price loading factor is the highest compared to other variables. These results
interpret the price variable to be the most important in instant cement
consumer loyalty.
This result is comparable with the
research conducted by Arokiasamy (2012), namely of the five variables tested in
the marketing mix and consumer perceptions of brand loyalty, there are four
variables that show significant results, one of which is price. The price is
the variable that has the most significant effect on loyalty. The price
variable is built by competitive prices and payment terms that can be received.
The price corresponds to quality becomes an
advantage.
The more the price is in accordance
with the product offered, the higher the purchase and use of the product.
Selang (2013), in his research also stated partially that product variables and
prices have a significant effect on consumer loyalty. Therefore, it is closely
related between product variables and prices given.
4.4.3. The Relationships between Location
and Loyalty
The results of the study showed that
the relationship between location variables and loyalty in both brands did not
have a significant value. Large production capacity, close to development, and
products easily sent if the undertonase does not affect consumer loyalty. This
is not in line with the research conducted by Utomo
and Nurmalina (2011), which states that one of the factors that influence
consumer loyalty is the ease of reaching the location (outlet). This difference
can be seen from the location, namely where the transaction is at the outlet,
while this research is located on a project where consumers are not too
influenced by the location of the factory and do not need to go to the store to
transact.
4.4.4. The Relationships between Promotion
and Loyalty
Promotion variables become one of
the variables that are not significant. Informative catalogs, interesting
samples, testimonials from previous projects, periodic supervision and
gathering do not affect consumer loyalty. This result is not comparable to what
has been done by Pourdehghan (2015), in his research that one of the positive
effects on loyalty is promotional activities. This is based on the products
sold to the project prioritizing the product, price and reference aspects of
the previous project. So it is infrequent that there is a product promotion for
activities on the project. Therefore, the promotion variable does not affect
the consumer loyalty of instant cement.
4.4.5. The Relationships between Service
and Loyalty
The results of the research show
that the relationshipbetween service and loyalty has significant results. The
response was given by customer service, response during training, mock-up,
supervision, a fast procession from order to delivery, and material coming on
time influencing consumer loyalty. This result is consistent with the research
conducted by Ivanauskienė and Volungėnaitė (2014) which states
that service variables have a positive impact on consumer loyalty. This can be
seen from the needs of a project. Activities in the field are not only about
products, but also services or services provided. The needs of the project are
different from the needs of end-users in general. In one project, it takes a
relatively long time to complete.
Therefore, services must always be
prepared to support the project development process. This indicates that the
project activities are not only about the product but also the service
activities provided become one of the loyalty points that occur. Projects that
are done have a relatively long time with more
than one until two years of processing
time. If there is no good service to consumers, the product can have a negative
impact on consumer loyalty for instant cement.
4.4.6. The Relationship between Human
Resource and Loyalty
Research shows that the human resource variable does not have a significant value on
loyalty in both brands. The hospitality of the sales, tidiness, periodic
follow-up, trust in sales, easy contact, and an easy-to-understand explanation
of the technician team turned out to have no effect on customer loyalty.
Project work is slightly different
from store transactions, if the human resource variable
store becomes one of the influential ones, according to research conducted by
Ferrinawati and Pantja (2004) as well as
Arthur et al., (2019) about consumer loyalty in the perspective of human
resources, it turns out that the results obtained are reliable seller roles can
affect loyalty through satisfaction and consumer confidence that results from
employee performance. Loyalty can be created if the consumer is satisfied with
a product.
4.4.7. The Relationship between Physical
Evidence and Loyalty
The results obtained are that the
physical evidence variable is not significant, meaning that it does not
significantly affect loyalty. Basically the business carried out on this
project is not too concerned with physical evidence. This situation occurs
because this work is done by the way the product is sent to the project, and
the consumer needs to use it. Product shipments according to standard with good
pallet, letter of support, technical data, and a driver willing to wait for the
loading queue is not the reason for consumers to be loyal to the product.
This is not in line with the
research conducted by Tjan (2015), which states that one physical evidence
variable from 7P has a significant impact on customer loyalty. The difference
was clarified due to differences in the target market, where he researched a
shopping center and the opposite of the project.
4.4.8. Relationship between Brand Image and
Loyalty
Brand image is the last variable
that has significant results on both brands. Products are easy to remember,
familiar, and have characteristics that affect consumer loyalty. This result is
in line with the research conducted by Anwar et al. (2011) which states that brand
image and brand trust have a positive impact on brand loyalty. Consumer actions
towards a brand are determined by the brand's image. It is not easy to form a
brand image, but if it is formed it will be difficult to change it back.
The image that is formed must be
clear and robust and have an advantage
compared to its competitors. The stronger the brand image, the higher the
possibility of loyalty to the product. The brand
applies not only the function but also emotional bonds. It
carries
out a customer insight strategy wherein sellers and buyers not only educate
good products but also add emotional bonds that are channeled to consumers.
4.5.
Managerial implication
Based
on the results of the research note that the price becomes a very influential
variable in the loyalty of premixed mortar, followed by product, brand image,
and service. As for the project work, the price becomes the most important
thing to progress in the negotiation phase of the tender. The more a
manufacturer supports the price, then the consumer's chances of using the more
significant product will be followed by loyalty to the product. Product is not
less important if the price is competitive but not followed by a good product,
then it is in vain (Table 15).
Table 15: Managerial implications
No |
Analysis Results |
Managerial
Implications |
1 |
Price |
Price: always critical in responding to the
consumer. Open in the price negotiation process and share information about
project needs and scale. Segmentation: loyal customers with big
purchases get special prices Target: consumers with large project needs,
get more intense service Positioning: retaining a good name and good
relationship to consumers, whether the project is running or not. |
2 |
Product |
Manufacturers maintain consistent product
quality, reduce consumer complaints on projects by minimizing product
problems, production defects, packaging defects, or application errors. |
3 |
Brand Image |
Manufacturers keep the company's good name
and maintain good relationships with consumers. Holding a gathering, presentation of a new
product, and refreshment of the product into an agenda that must be done
manufacturer. Holding an event marketing becomes one part
in strengthening producer ties with consumers. |
4 |
Process |
Serving consumers and responding quickly in
response to consumer desires into customer satisfaction. Be available at any time if needed. |
The brand image becomes another
influential variable because project work often mirrors the previous projects.
The better brand is when workmanship, undamaged, and the services provided are
good, the more loyal consumers are towards the brand, and will be considered
when the consumer is working on the next project. The service variable becomes
one of the indicators that affect loyalty.
Companies
engaged in the premixed mortar, not only associated with the product, but also
process or service. Because the company is engaged in products and services.
Marketed products must be balanced with good service in order to synergize with
each other. Good product but not parallel with good service, then the result is
not maximal and vice versa.
For
that, it is necessary to determine the appropriate managerial implications for
the company in determining the strategy in achieving the company's sales
targets. The managerial implications used are Segmentations, Targeting, Positioning (STP). From the
segmentation can be determined based on the consumers who have bought and used
the product, the extensive project needs can affect the consumer entry in the
criteria of the upper, middle, or lower segment. In terms of targets, consumers
with large project needs will always benefit from price and service.
Moreover,
always have a target to every consumer in a year, if the consumer reaches the
target, then there is a bonus that can be given in accordance with the initial
agreement of the contract. In terms of positioning, it should always be able to
create a good image for every consumer in order to keep the name and good
relationship between both parties. Managerial implications can be arranged
based on the following variables.
5.
CONCLUSION
Based on the analysis of the effect of the marketing mix and brand image on premixed mortar loyalty, it can be concluded that product, price, process, and brand image significantly affects loyalty. The variable that has the greatest effect is the price, followed by the product, process and brand image.
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