The
Influence of Service Quality, Word of Mouth Price on Restaurant D'cost Kemang
South Jakarta Purchasing Decision
Nalam Efendi1, Resti Hardini2, Kumba Digdowiseiso3, Khatijah Omar4
Faculty
of Economics and Business, Universitas Nasional, Indonesia1,2,3
Email: [email protected]1, [email protected]2, [email protected]3
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ABSTRACT |
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Quality of Service,
Price, Word Of Mouth (WOM), Purchasing Decision. |
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This study aims to analyze the magnitude of the influence of Service
Quality, Price, and Word Of Mouth (WOM) on the Purchasing Decision of
Restaurant D'cost Kemang South Jakarta. This study used primary data by
distributing questionnaires as many as 100 respondents. Data were analyzed
using descriptive and inferential analysis. In the implementation of the
study using primary data obtained through the distribution of questionnaires
and processed with SPSS 17.0. The results showed that the variables of Service
Quality, Price, and Word Of Mouth (WOM) had a positive and real influence on
Purchasing Decisions of 0.906 which was classified as strong. While the
coefficient of determination obtained R Square of 0.538 or 53.8% variation in
the dependent variable, namely purchasing decisions can be explained by a
combination of independent variables, namely, Service Quality, Price, and
Word Of Mouth (WOM). While the remaining 4.62% can be explained or explained
by other factors that the author did not study. Through regression values KP
= 3.931 + 0.353 KP + 0.210 H + 0.285 WOM can be predicted regarding the ups
and downs or size of employee performance. |
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INTRODUCTION
The business world is
experiencing increasingly fierce competition which is balanced with the
development of increasingly sophisticated technological tools that make it
easier for every company to improve its business performance to achieve a goal.
In an ever-evolving and fast-changing environment, companies cannot maintain an
attitude of attracting customers or expanding new markets
When consumers decide to buy a
product, consumers can form an intention to buy the brand they like the most
and have certain reasons for choosing a product, for example being satisfied
with the quality of service offered by the product
In addition to the quality of
service, the price factor is also an important thing that consumers consider
for purchasing decisions. The definition of price according to Kotler and
Armstrong
A company can position itself by
providing superior value to its chosen target market, offering lower prices
than competitors, or providing greater benefits by looking higher. Companies
will gain a competitive advantage with the needs and desires of buyers who vary
in prices, which can be a guide for marketing strategy design
Word Of Mouth (WOM), according
to Kotler and Keller (2009: 204), is a communication process in the form of
providing recommendations both individually and in groups for a product or
service that aims to provide personal information. Of all promotional media,
Word Of Mouth (WOM) is a promotional activity whose level of control by
marketers is very low but has a very extraordinary impact on the company's
product or brand
The most valuable customers are
not the customers who buy the most, but customers who do a lot of Word Of Mouth
(WOM) activities and can bring other customers to buy in our company,
regardless of the number of purchases that these customers make themselves.
This research aims to
investigate and analyze the factors influencing consumer purchasing decisions,
specifically focusing on the strategies employed by Restaurant D'Cost, a food
company established in 2006 in Kemang, South Jakarta. By exploring the company's
approach to service quality, pricing, and Word Of Mouth (WOM) promotion, the
research seeks to provide valuable insights for enhancing business performance
and market share in a competitive environment.
METHODS
This study focuses on consumer
purchasing decisions at D'Cost Kemang Restaurant, South Jakarta, with variables
considered including service quality, price, and Word Of Mouth (WOM). Data for
this study was obtained through questionnaires distributed to consumers of
D'Cost Kemang Restaurant. The type of data used is primary data, which is
obtained through direct field surveys to respondents observed using
questionnaires.
The population of this study is
customers of D'Cost Kemang Restaurant, South Jakarta. Population is defined as
a generalized region consisting of objects or subjects that have certain
qualities and characteristics that the researcher wants to research. To narrow
the scope of research, researchers use samples taken through the Probability
Sampling technique, with a special technique, namely simple random sampling.
Probability sampling provides equal opportunities for each element of the
population to be selected as a member of the sample, while simple random
sampling is done randomly regardless of the strata in the population. Thus,
this study will provide a deeper understanding of the factors that influence
consumer purchasing decisions at D'Cost Kemang Restaurant, South Jakarta.
The sampling technique is based on accidental
sampling, that is, anyone who happens to meet the researcher can be used as a
sample, if it is considered that the person who happens to meet is suitable as
a data source, with specified limits. The sample used for the measurement of
this questionnaire is D'Cost restaurant consumers who have just made a purchase
transaction on the basis of their own purchase decisions.
According to Ferdinand (2006: 208), if
the population number is unknown, the alternative formula that can be used is:
n = ( Z2α
) [P x Q]
...........................................( 1 )d2
where:
Za
= Z table with a certain
significant level of 1.96 out of a significant level of 95%.
P
= The expected proportion of the
population has certain characteristics, the variation of the population is
expressed in the form of proportions, and the proportion is divided in 2 parts
by a total of 100% or 1.
Q
= The expected proportion of the
population has no particular characteristics.
D
= Tolerable error rate
(expressed in 10%).
So;
n = (1.962) [0.5 x
0.5]
0,12
The data collection technique
used in this study was by questionnaire. A questionnaire according to Sugiyono
(2012: 136) is a data collection technique carried out by giving a set of
questions or written statements to respondents to answer. The questionnaire in
this study is a data collection by distributing a list of questions or
statements to consumers where the list of questions or statements is in the
form of close-ended questions, statements that accompany alternative answers
that have been determined by the principle of weighting scores according to the
Likert scale. Likert scale is used to measure attitudes, opinions, and
perceptions of a person or group of people about social phenomena (Sugiyono,
2014: 94).
RESULTS
Validity Test
The
validity test is used to measure the validity or absence of a questionnaire
(Ghozali, 2011: 53). A questionnaire is valid if the statements on the
questionnaire are capable of expressing something that the questionnaire will
measure. The high and low validity of measuring instruments shows the extent to
which the collected data does not deviate from the description of the variable.
In making decisions to test the validity of the indicators are:
a) If r count (positive) > r table then the item or
variable is valid
b) If r count (negative) < r table then the item or
variable is invalid
Reliability Test
Reliability test is a tool for
measuring a questionnaire that has indicators of variables or constructs. A
questionnaire is considered reliable or reliable if a person's answers to
statements are consistent or stable over time (Ghozali, 2011: 47). This
reliability test uses the Cronbach Alpha (α) statistical test. According to
Ghozali (2011: 48) decision making of a construct or variable is said to be
reliable as follows:
a) If
Cronbach Alpha (α) > 0.60 then the questionnaire used is reliable.
b) If
Cronbach Alpha (α) < 0.60 then the questionnaire used is not reliable.
Classical
Assumption Test
Normality
Test
The normality test aims to find out
whether the regression model, bound variables and independent variables have a
normal distribution or not because a good regression model has a normal or
near-normal data distribution (Ghozali, 2011: 160). According to Ghozali (2011:
32) to detection normality can be done with the Kolmogorov-Smirnov test.
According to Ghozali (2011: 34) decision-making is carried out with the
following criteria:
a) If
sig. 2-tailed> 0.05, then the data is distributed normally.
b) If
sig. 2- tailed < 0.05, then the data is not normally distributed.
Multicollinearity
Test
This multicollinearity test aims to
test whether the regression model found a correlation between independent
variables (Ghozali, 2011: 105). A good regression model does not have
correlation between independent variables. If independent variables correlate
with each other, then these variables are not orthogonal. Orthogonal variables
are independent variables whose correlation value between independent variables
is equal to zero (Ghozali, 2011: 105). In
this study to detect the presence or absence of multicollinearity of the
regression model, namely:
a) If the tolerance value > 0.1 and the VIF value
< 10, then there is no multicollinearity between independent variables in
the regression model.
b) If the tolerance value < 0.1 and the VIF value
> 10, then there is multicollinearity between independent variables in the
regression model.
Heteroscedasticity Test
The
heteroscedasticity test aims to test whether in a regression model there is an
inequality of variance from residual from one observation to another (Ghozali,
2011: 107). If the variance from the residual or one observation to another is
fixed, then it is called homoscedasticity. If variance is different then it is
called heteroscedasticity. A good regression model is one in which
homokedasticity or heteroscedasticity does not occur (Ghozali, 2011: 108). One
way to detect heteroscedasticity is to look at the plot graph between the
predicted value of the dependent variable ZPRED and the residual value
SRESID.
Autocorrelation Test
According
to Ghozali (2011: 110), the autocorrelation test aims to test whether in the
linear resonance model, there is a correlation between confounding errors in
period t with confounding errors in period t-1 (previous). If correlation
occurs, then there is an autocorrelation problem, a good regression model is a regression
that is free from autocorrelation (Ghozali, 2011: 110). To test whether
autocorrelation occurs or not, the Durib-Watson test criteria are used as
follows:
a) DU
< DW < 4 – DU, then no autocorrelation occurs.
b) DW
< DL or DW > 4 – DL, then autocorrelation occurs.
c) dl
< dw < du or 4 – du < dw < 4 –dl, meaning there is no certainty.
Information:
du =
upper bound of Durbin-Watson (DW) values in the DW table
dl =
lower bound of Durbin-Watson values in the DW table
Model Due Diligence
Test F
This test is used
to determine the effect of the independent variable together on the dependent
variable. To determine the significance or not of the influence of the
independent variable together on the dependent variable, a probability of 5% (α
= 0.05) is used. Basis of decision making:
1). If the F count is at sig ≤ 0.05, then H
0 is rejected. ( regression model
valid)
2). If the F count is at sig ≥ 0.05, then H
0 is accepted. ( regression model
invalid)
Coefficient of Determination (R2)
The coefficient of
determination (R2) essentially measures how far a model is able to explain from
variations in dependent variables (Ghozali, 2011: 97). A coefficient of
determination (R2) of 0% means that the independent variable cannot explain the
dependent variable at all. If the coefficient of determination is closer to
100%, it can be done that the independent variable is more able to explain the
dependent variable.
Hypothesis Testing (T-Test)
This test is used
to determine the significance of the influence of the independent variable on
the dependent variable individually and considers the other dependent constant.
The significance of this effect can be estimated by comparing calculated T values
at a significance of ≤ 0.05. The basis for decision-making is as follows:
1.
If the T count
is at a significance of ≤ 0.05, then H0 is rejected, meaning that
Service Quality, Price and Word Of Mouth partially have a positive and
significant effect on Purchasing Decisions at D'Cost Kemang restaurant in South
Jakarta.
2. If the T count is at a significance of > 0.05
then H0 accepted means that Service Quality, Price and Word Of Mouth partially
do not have a positive and significant effect on Purchasing Decisions at D'Cost
Kemang restaurant South Jakarta.
CONCLUSION
Based on the research results regarding the
influence of Service Quality, Price, and Word of Mouth on Purchasing Decisions
at D'Cost Kemang Restaurant, it can be concluded as follows: First, Service
Quality has a positive and significant influence on Purchasing Decisions at the
restaurant. The quality of service in the purchasing source is influenced by
several factors, one of which is the quality of service provided by D'Cost
Kemang restaurant in South Jakarta. Second, Price positively and significantly
influences Purchasing Decisions at D'Cost Kemang restaurant in South Jakarta.
In determining purchasing decisions, information about prices is crucial, where
consumer perceptions about a product's price can be used to standardise product
quality based on the product's price value. Third, Word of Mouth positively and
significantly influences Purchasing Decisions at D'Cost Kemang restaurant in
South Jakarta. Word of Mouth (WOM) is related to purchasing decisions. In this
case, when individuals or other personal sources we already know to share
positive information about a product, the greater the consumer's desire to buy
the product, benefiting the producing company.
This article is a
part of joint research and publication between Faculty of Economics and
Business, National University, Jakarta and Faculty of Business, Economics, and
Social Development, Universiti Malaysia Terengganu.
REFERENCES
Agag, G., Shehawy, Y. M.,
Almoraish, A., Eid, R., Chaib Lababdi, H., Gherissi Labben, T., & Abdo, S.
S. (2024). Understanding the relationship between marketing analytics,
customer agility, and customer satisfaction: A longitudinal perspective. Journal
of Retailing and Consumer Services, 77, 103663.
https://doi.org/10.1016/J.JRETCONSER.2023.103663
Ariyanto, A. (2019). The Influence
of Price and Service Quality on Customer Satisfaction at PT Sarana Estate. Jurnal
Administrare: Jurnal Pemikiran Ilmiah Dan Pendidikan Administrasi Perkantoran,
6(2), 217–228.
Benaglia, M. F., Ho, M. H. C.,
& Tsai, T. (2023). Drivers of customer satisfaction with restaurants
during COVID-19. A survey of young adults in Taiwan and Indonesia. Asia
Pacific Management Review. https://doi.org/10.1016/J.APMRV.2023.08.001
Boubker, O., & Naoui, K.
(2022). Factors affecting airline brand love, passengers’ loyalty, and
positive word-of-mouth. A case study of Royal Air Maroc. Case Studies on
Transport Policy, 10(2), 1388–1400.
https://doi.org/10.1016/J.CSTP.2022.05.006
Çavdar, B., & Erkip, N. (2023).
Word-of-Mouth on Action: Analysis of Optimal Shipment Policy When Customers
are Resentful. Omega (United Kingdom), 118.
https://doi.org/10.1016/J.OMEGA.2023.102865
El-Manstrly, D., Ali, F., &
Line, N. (2021). Severe service failures and online vindictive word of mouth:
The effect of coping strategies. International Journal of Hospitality
Management, 95. https://doi.org/10.1016/J.IJHM.2021.102911
Fetra, R., & Pradiani, T.
(2023). The Influence of Price, Facilities, and Service Quality on Re-Staying
Interest. ADI Journal on Recent Innovation, 4(2), 184–193.
Gazi, Md. A. I., Mamun, A. Al,
Masud, A. Al, Senathirajah, A. R. bin S., & Rahman, T. (2024). The
relationship between CRM, knowledge management, organization commitment,
customer profitability and customer loyalty in telecommunication industry: The
mediating role of customer satisfaction and the moderating role of brand
image. Journal of Open Innovation: Technology, Market, and Complexity, 10(1),
100227. https://doi.org/10.1016/J.JOITMC.2024.100227
Hameed, I., Akram, U., Khan, Y.,
Khan, N. R., & Hameed, I. (2024). Exploring consumer mobile payment
innovations: An investigation into the relationship between coping theory
factors, individual motivations, social influence and word of mouth. Journal
of Retailing and Consumer Services, 77, 103687.
https://doi.org/10.1016/J.JRETCONSER.2023.103687
Kartikasari, A., & Albari, A.
(2019). The influence of product quality, service quality and price on
customer satisfaction and loyalty. Asian Journal of Entrepreneurship and
Family Business, 3(1), 49–64.
Kester S. Ong, A., German, J. D.,
Dangaran, P. C., Jethro B. Paz, J., & Roniel G. Macatangay, R. (2024).
Service quality and customer satisfaction analysis among motorcycle taxi
transportation in the Philippines through SERVQUAL dimensions and social
exchange theory. Case Studies on Transport Policy, 15, 101139.
https://doi.org/10.1016/J.CSTP.2023.101139
Kola Olayiwola, R., Tuomi, V.,
Strid, J., & Nahan-Suomela, R. (2024). Impact of Total quality management
on cleaning companies in Finland: A Focus on organisational performance and
customer satisfaction. Cleaner Logistics and Supply Chain, 10,
100139. https://doi.org/10.1016/J.CLSCN.2024.100139
Kotler, P., & Amstrong, G.
(2010). Pemasaran. Jakarta: Erlangga.
Li, Y., Wu, R., & Wang, S.
(2024). Mitigating the influence of preference-oriented negative electronic
word-of-mouth: Investigating the role of consumers’ cognition regarding
preference heterogeneity. Electronic Commerce Research and Applications,
64, 101360. https://doi.org/10.1016/J.ELERAP.2024.101360
Li, Z., Zhao, X., & Ou, G.
(2023). Understanding customer satisfaction in curated subscription services:
Moderating roles of subscription time and information disclosure. Information
and Management, 60(6). https://doi.org/10.1016/J.IM.2023.103834
Nilashi, M., Abumalloh, R. A.,
Ahmadi, H., Samad, S., Alrizq, M., Abosaq, H., & Alghamdi, A. (2023). The
nexus between quality of customer relationship management systems and
customers’ satisfaction: Evidence from online customers’ reviews. Heliyon,
9(11). https://doi.org/10.1016/J.HELIYON.2023.E21828
Prasilowati, S. L., Suyanto, S.,
Safitri, J., & Wardani, M. K. (2021). The impact of service quality on
customer satisfaction: The role of price. The Journal of Asian Finance,
Economics and Business, 8(1), 451–455.
Rezaee Vessal, S., De Giovanni, P.,
& Hassanzadeh, A. (2022). Technology and service investments in the
presence of feature fatigue and word-of-mouth. European Journal of
Operational Research, 301(3), 923–941.
https://doi.org/10.1016/J.EJOR.2021.11.035
Rivero, D. M., Suson, R., Arnejo,
A., Atibing, N. M., Aro, J. L., Wenceslao, C., Burdeos, A., Yamagishi, K.,
& Ocampo, L. (2023). Service recovery and innovation on customer
satisfaction amidst massive typhoon-induced disruptions: The mediating role of
SERVQUAL. International Journal of Disaster Risk Reduction, 99.
https://doi.org/10.1016/J.IJDRR.2023.104130
Sakas, D. P., Reklitis, D. P.,
Terzi, M. C., & Glaveli, N. (2023). Growth of digital brand name through
customer satisfaction with big data analytics in the hospitality sector after
the COVID-19 crisis. International Journal of Information Management Data
Insights, 3(2). https://doi.org/10.1016/J.JJIMEI.2023.100190
Shamim, A., Abid, M. F., &
Ahmad, F. (2024). S–O–R based experiential framework for measuring in-store
customer satisfaction in non-fuel retailing. Journal of Retailing and
Consumer Services, 77.
https://doi.org/10.1016/J.JRETCONSER.2023.103672
Wicaksono, T., Nugroho, A. D.,
Lakner, Z., Dunay, A., & Illés, C. B. (2021). Word of mouth, digital
media, and open innovation at the agricultural smes. Journal of Open
Innovation: Technology, Market, and Complexity, 7(1).
https://doi.org/10.3390/JOITMC7010091
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Copyright holder: Nalam Efendi, Resti Hardini, Kumba
Digdowiseiso (2024) |
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First publication rights: International Journal of
Social Service and Research (IJSSR) |
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This article is licensed under:
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