Syntax Literate: Jurnal Ilmiah Indonesia p–ISSN: 2541-0849 e-ISSN: 2548-1398
Vol. 9, No. 12, Desember 2024
POWERING UP USER LOYALTY: EXPLORING
MULTIDIMENSIONAL PLATFORM VALUE AND SERVICE QUALITY IN THE PLN MOBILE
ELECTRICITY SERVICE APPLICATION PLATFORM
Fristyan
Pradipta1*, Daniel Tumpal H
Aruan2
Universitas Indonesia, Indonesia1,2
Email: [email protected]1*
Abstract
The objective of this research is to explore how digital
interactive platforms can assist companies in cultivating brand loyalty for
their platforms. This study employs a quantitative approach, collecting a total
of 310 questionnaires from PLN Mobile users, a platform operated by the largest
electricity company in Indonesia. Respondents were selected using
non-probability random sampling, and Structural Equation Modeling was employed
as the analysis tool. The findings reveal that among the three multidimensional
platform values (functional, cost, and contextual) only functional platform
value lacks significant influence on perceived value. Additionally, within the
context of PLN Mobile application users, service quality demonstrates a
positive and significant direct influence on perceived value, platform brand
image, and platform brand loyalty. Furthermore, perceived value exhibits a
significant direct influence on continuance intention and platform brand image,
although it does not significantly influence platform brand loyalty directly in
this context. This research offers a new theoretical framework and managerial
insights for value creation in digital interactive platforms. It contributes to
the body of knowledge by demonstrating the relationships between various
factors influencing brand loyalty in the context of digital platforms. The
implications of the research findings on management and business practices are
significant. Companies can utilize the insights provided by this research to
enhance their digital platform offerings, improve customer satisfaction, and
ultimately foster brand loyalty. Additionally, policymakers can use these
findings to shape regulations and policies that promote innovation and
competitiveness in the digital platform in service industry.
Keywords: Continuance Intention,
Multidimensional Platform Value, Perceived Value, Platform Brand Image, Service
Quality, Platform Brand Loyalty
Introduction
In 2023, Indonesia reached 78.19 percent internet
penetration, encompassing 215,626,156 people out of a total population of
275,773,901 people (APJII, 2023). As digital information and
communication technology continues to reshape the economy, many academics and
practitioners concur that platform, as a category of digital creative products,
play a pivotal role for companies, including traditional ones, in establishing
distinct competitive advantages (He & Zhang, 2022).
Platforms are becoming increasingly popular, and
businesses of all sizes, ranging from startups to established companies, are
seeking to integrate digital platforms into their business models (Kapoor et al., 2021; Pandey & Rupnawar, 2022). With the significant trend
of companies digitizing their services through platforms, PT. PLN (Persero)
Indonesian state-owned company, and as one of the market share leaders of
electricity providers, has undergone a transformation by digitizing its services
through an interactive mobile application platform, known as PLN Mobile. Since
its launch in 2020, user growth has nearly doubled in just one year, going from
18 million users in 2021 to 35 million users in 2022 (PLN, 2022).
Apart from PLN carrying out transformations in its
core services, such as electrical installations, electricity bills, and outage
management, PLN Mobile application also functions as a “super-app” that caters
to various electricity-related needs. These include services such as ICONET, an
internet provider owned by a PLN subsidiary, ListriQU,
a home electrical installation service owned by other subsidiaries, and
services supporting electric vehicle usage, as well as offerings beyond the
electricity domain, such as marketplace services. Through its mobile
application, PLN has introduced additional features that extend beyond the
scope of their primary business operations. This positions as a super app make
PLN Mobile had the potential to became the main engine of the PLN services
digitalized transformation as a whole.
From a practical standpoint, this makes it intriguing
to conduct a more in-depth study on the impact of platform multi-functionality
from its value and services quality on perceived value, brand image, usage
intensity, and platform loyalty. Numerous studies have examined the various
types of value that digital interactive platforms deliver and their
interrelationships. Value generated by a platform often leads to perceived
value, which directly influences usage loyalty among customers and the
intensity of their platform use (Maroufkhani et al., 2022). Additionally, research has
categorized the created value into primary aspects like functional value, cost
value, and contextual value. These aspects contribute to expanding a product's
market share when offered through a platform, establishing connections through
brand engagement and loyalty across the region (He & Zhang, 2022).
Beyond value creation, quality also plays a
significant role in shaping customer brand loyalty (Omoregie et al., 2019). A platform's service quality
can also exert an influence on brand loyalty through trust (Shankar & Jebarajakirthy, 2019) and brand image (Omoregie et al., 2019). Conversely, the role of
perceived quality in relation to brand loyalty within the digital services
context holds a significant antecedent influence on a company's offerings (Garcia et al., 2020). Marketing research developed
the SERVQUAL service quality construct to measure consumer perceptions of
service quality (Parasuraman et al., 1985). However, recently only a
small number of studies have included service quality to measure the success of
technology implementation (van Dat, 2020).
The value creation dimension sees service quality as
an important antecedent that has a direct influence in building brand image,
perceived value and also brand loyalty (Chen & Liu, 2017). Perceptions of low quality
and/or image generally stem from exposure to negative information (e.g.,
advertising, third-party evaluation ratings, word-of-mouth communications)
and/or personal experiences (Homer, 2008). The importance of quality of
a service is an important aspect in value creation where it is expected to be
able to increase brand image, intention to use and the ability of a platform to
increase the loyalty of its users.
Recently, the perspective of continuance intention, or
the intention to use smart technology (such as smart devices and mobile
applications), has evolved into the study of consumer behavior, encompassing
how consumers behave when utilizing smart devices or mobile applications in
their daily lives (Nikhashemi et al., 2021). In the expanding economic
wave of the 'new technology lifestyle,' the concept of usage intention pertains
to an individual's willingness to assess and embrace the idea that technology
usage can be useful, helpful, and can facilitate daily needs (Chou et al., 2020). Several studies indicate
that usage intention has an influence on the relationship between reputation
and brand image regarding perceived value and the reputation of a platform (Huang, 2022). Furthermore, usage intention
also plays a crucial role as a variable mediating perceived value's impact on
customer loyalty (Maroufkhani et al., 2022). Therefore, in this study,
the role of usage intention appears to be integral in enhancing platform brand
loyalty.
This research endeavors to demonstrate that PLN, as
one of the largest state-owned companies in Indonesia with a long-established
history, is capable of digitally transforming its services through its Super
Apps mobile platform. Specifically, this study addresses the following
questions: 1. Does the multi-dimensional platform value which is functional,
cost and contextual value and service quality of the PLN Mobile positively
impact the platform perceived value? 2. Does the perceived value of the PLN Mobile
positively impact continuance intention, platform brand image and loyalty? 3.
Does the service quality of the PLN Mobile platform positively impact the
platform brand image and loyalty? 4. Does PLN Mobile's perceived value
positively mediate the influence of service quality on platform brand image and
brand loyalty? 5. Does continuance intention positively mediate the influence
of perceived value and platform brand image on platform brand loyalty? And 6.
Does platform brand image positively mediate the influence of perceived value
and service quality on platform brand loyalty?
By investigating these six issues, the study's
innovative contributions include the following: Firstly, this study aims to
determine the extent of the influence value and quality has on platform brand
image and loyalty, as well as the role that each multidimensional function in
creating value (functional, cost, and contextual value) plays in this process.
Secondly, this study also seeks to substantiate previous theories highlighting
the significant role of perceived value as a mediating variable between service
quality on platform brand image and loyalty. Third, this study endeavors to
establish that platform brand image and continuance intention also actively
contribute to the enhancement of platform brand loyalty.
The relevant findings could provide traditional
businesses with valuable strategic insights for leveraging digitalized
interactive platforms and associated platform products to drive business model
transformation. This conceptual section is followed by hypotheses related to
multi-dimensional platform value, service quality, platform brand image,
continuance intention, and platform brand loyalty. Subsequently, the research
presents methodologies and analysis findings, concluding with a discussion of
our results, their theoretical and practical implications, the study's
limitations, and prospects for future research.
Hypotheses Development
Classification of digitalized interactive platform
value
The types of value creation in the context of digital interactive
platforms are divided into functional, cost, contextual, and overall platform
values (He &
Zhang, 2022). This overall value will later serve as a
benchmark for evaluating the usefulness of a product or service based on the
perceived value of the product or service(Ortiz et
al., 2016). In the context of its existence, such
value creation can be considered a dimension of a platform, and from the
perspective of the logic of change, these values are important antecedents to
drive platform value creation (i.e., digital interactive platforms can create,
maintain, and expand platform value by strengthening these three value
dimensions) (He &
Zhang, 2022).
The importance of functional value as a predictor of perceived
value is defined as the perceived usefulness of product and service attributes,
emphasizing its role in shaping customer perceptions (Roig et
al., 2006). The interaction between benefits and
costs is proven to have a significant influence on the perceived value of
digital services, further emphasizing the importance of cost as a predictor of
perceived value (Park &
Kim, 2013). Additionally, contextual value, which
involves the integration of contextual offers such as timeliness and spatial
relevance, is an important part of perceived value (Le &
Wang, 2021).
In recent years, successful digital interactive platforms have
effectively integrated functional, cost, and contextual values, which is a
fundamental way for them to create competitive differentiation and gain a
competitive advantage (Wade et
al., 2016). This study aims to prove the influence
of these values in the PLN Mobile application so that the following research
hypothesis is obtained:
H1a: Functional value has a positive effect on perceived value.
H1b: Cost value has a positive effect on perceived value.
H1c: Contextual value has a positive effect on perceived value.
Service Quality, Perceived Value and Platform Brand
Loyalty
Various studies emphasize the significance of service quality in
influencing different dimensions of perceived value for customers (Chen &
Liu, 2017; van Dat, 2020). Service quality features, which measure
tangibility, empathy, reliability, and responsiveness, are positively
correlated with consumer perceived value (Ryu. et
al., 2011). Since value is the ratio of quality to
price, a positive relationship is expected between quality and the value of a
brand's product (Yang &
Wang, 2010). This suggests that when customers
perceive high service quality, they are inclined to assign greater value to the
service they receive, highlighting the importance of service quality in shaping
customer perceptions and influencing perceived value (Zeithmal,
2001).
The ultimate objective of the marketing team is to retain existing
customers, attract new ones, convert them into loyal and repeat customers, and
build and maintain that loyalty (Maroufkhani
et al., 2022). With loyalty, changes in pricing
dynamics have no impact on consumer behavior (Aaker,
1991). The positive promotion of services is also a key advantage in
increasing application usage within the context of brand loyalty platforms.
Numerous prior studies establish a direct link between value and loyalty (Maroufkhani
et al., 2022), both directly and indirectly (He &
Zhang, 2022).
In the digitalized service concept, service quality aspects such
as reliability, privacy, and security directly impact brand loyalty (Shankar
& Jebarajakirthy, 2019). Other research also underscores
satisfaction as a mediating variable, playing a positive role between perceived
service quality and brand loyalty (Boubker
& Naoui, 2022). This study aims to explore the
contextual relationship between perceived value and service quality in the
mobile platform realm and its influence on brand loyalty, leading to the
formulation of the following hypothesis:
H2: Service Quality has a positive effect on perceived value.
H3: Perceived value has a positive effect on platform brand loyalty.
H4: Service Quality has a positive effect on platform brand loyalty.
Service Quality, Perceived Value and Platform Brand
Image
Value creation enhances the company's image (Pitt et
al., 2020). Additionally, various studies indicate
that the ability to convey perceived value affects brand image. This suggests
that the higher the perceived value in society, the stronger the societal brand
image (Wijaya et
al., 2020). PT. PLN (Persero) stands out as a
dominant electricity supply company in this sector, holding over 90% of the
national market share as a state-owned entity. Therefore, this study aims to
assess the extent to which the perceived value derived from the digitalization
of services through PLN Mobile influences the Brand Image Platform.
Furthermore, product quality significantly shapes a company's
brand image. Poor product quality can have a detrimental impact on the
company's image, but with timely corrections, it can lead to a positive brand
image (Widiani et
al., 2022). Numerous previous studies affirm that
service quality affects brand image (Chen &
Liu, 2017; Dam & Dam, 2021; Fajariah et al., 2016; Widiani et al., 2022;
Wijaya et al., 2020). In the context of the mobile platform,
empirical evidence indicates that online service quality influences brand image
(Garcia et
al., 2020; Mariano et al., 2022). This study aims to explore the impact of
the relevance of value and quality on brand image, resulting in the following
hypothesis:
H5: Perceived value has a positive effect on platform brand image.
H6: Service Quality has a positive effect on platform brand image.
Perceived Value, Platform Brand Image and
Continuance Intention
Perceived value has been demonstrated to exert a significant
influence on continuance intention in various research contexts, particularly
concerning its use on mobile platforms. For instance, within the realm of
mobile shopping applications, it was observed that perceived value strongly and
positively affects consumer continuance intention (Dobre et
al., 2023). Additionally, in the context of social
commerce, perceived value is recognized as crucial for the continuance
intention of a service and serves as the primary determinant of purchasing
intention (Murillo-Zegarra
et al., 2020). The consistent findings from these
studies underscore the importance of perceived value as a determinant of
continuance intention in the context of diverse digital services.
Furthermore, brand image also exerts a positive influence on
continuance intention. Across various service sectors, there exists empirical
evidence justifying the significant impact of brand image on repurchase
intention (Ayutthaya,
2013; Prabowo et al., 2020; Ratasuk, 2021). Moreover, within various types of
digital services, brand image significantly influences purchase intention,
demonstrating its impact on consumer decision-making and continuance intention (Jaya &
Prianthara, 2020; Tam et al., 2022). Thus, this study formulates the
following research hypothesis:
H7: Perceived value has a positive effect on continuance intention.
H8: Platform brand image has a positive effect on continuance
intention.
Platform Brand Image, Continuance Intention and
Platform Brand Loyalty
The substantial influence of continuance intention on brand
loyalty has been substantiated in various types of research across diverse
service and industrial sectors. In the service sector, spanning from
conventional to digital, several studies highlight the crucial role of
continuance intention as a variable influencing brand loyalty (Hew et
al., 2016; Sadli et al., 2022). Additionally, in the mobile platform
sector, several studies related to the impact of continuance intention on brand
loyalty also validate a significant correlation between the two (Al Amin et
al., 2023).
Furthermore, brand image also exerts a positive influence on brand
loyalty, as several studies emphasize its positive impact on customer loyalty,
reinforcing the significance of brand image in fostering brand loyalty (Fitriani
& Paramita, 2022; Rahmatulloh et al., 2019). Users or consumers tend to favor a
strong and impressive brand image, leading to a positive orientation towards
customer satisfaction and loyalty, thus strengthening the influence of brand
image on brand loyalty (Dam &
Dam, 2021). The decision to digitize services
through PLN Mobile must be complemented by the value and quality of the
resulting platform. Continuance intention and Platform Brand Image are deemed
integral components in establishing the Brand Loyalty Platform on PLN Mobile,
resulting in the formulation of the following research hypothesis:
H9: Continuance intention has a positive effect on platform brand
loyalty.
H10: Platform brand image has a positive effect on platform brand
loyalty.
The mediating role of Perceived Value
Several studies have established the mediating role that perceived
value plays in the relationship between Service Quality and Brand Loyalty. Chen
& Liu (2020) elucidated the significant mediating role of perceived value
in various variable relationship constructs within the aviation services
sector. Additionally, specific research indicates that perceived value acts as
a mediator in the relationship between service quality and complete customer
loyalty (Hasby et al., 2023). As a result, this study
posits the following research hypothesis:
H11: Perceived value mediates the relationship between Service
Quality and Platform Brand Loyalty
The mediating role of Platform Brand Image
In several research analysis results, we have also identified the
role of brand image as a mediating variable in the relationship between Service
Quality and Brand Loyalty. Chen & Liu (2020) explained the significant
mediating role of brand image in various variable relationship constructs
within the aviation service sector. Additionally, there is research stating
that brand image plays a significant role in mediating the relationship between
service quality and customer loyalty (R. S. Pratiwi et al., 2021).
The impact of perceived value on brand image has been demonstrated
in various research analysis results, showing a significant coefficient
relationship (Ayutthaya, 2013; Chen & Liu, 2017; Wijaya et al., 2020). On
the other hand, the influence of brand image on brand loyalty has also been
noted in various research studies (Abdullah, 2015; Dam & Dam, 2021; Hasby et al., 2023). Based on various empirical research
findings, this study formulates the following research hypothesis:
H12: Platform brand image mediates the
relationship between Service Quality and Platform Brand Loyalty
H13: Platform brand image mediates the
relationship between Perceived Value and Platform Brand Loyalty
The mediating role of Continuance Intention
Specifically, in his research, Nguyen (2020) asserted that
perceived value and social commerce continuity intention are crucial variables
with a positive impact on brand loyalty. Additionally, this study proposes the
existence of a mediating role for social commerce continuance intention in the
relationship between perceived value and brand loyalty. The reference to this
study is pertinent because it directly addresses the mediating role of
continuance intention between perceived value and brand loyalty.
The impact of brand image on continuity has been highlighted in
various empirical study results, revealing a positive and significant effect on
the relationship between variable constructs (Prabowo et al., 2020; Ratasuk, 2021; Savitri et al., 2021; Tam et al., 2022).
Furthermore, the influence of continuance intention on brand loyalty has also
been asserted in various research studies (Chalomba
& Duh, 2019; Hew et al., 2016; Maroufkhani et
al., 2022). Therefore, based on various empirical research findings, this study
formulates the following research hypothesis:
H14: Continuance Intention mediates the
relationship between Perceived Value and Platform Brand Loyalty
H15: Continuance Intention mediates the
relationship between Platform Brand Image and Platform Brand Loyalty
Figure 1. The
Conceptual Research Model
Research Method
This research is aimed to capture the current
condition of apps offered by traditional firms, which are used on mobile
devices as digitalized interactive platforms. First, the PLN Mobile app was
selected as the research object. As the largest electricity company in
Indonesia, PLN has a large-scale and diverse consumer group. This study applied
a quantitative research method. Quantitative research is a deductive research
method that uses measurement and sampling techniques for data collection (Hair et al., 2019).
Because the criteria for selecting respondents were
established before the data collecting stage, the samples were selected using a
purposive sampling technique (Sekaran & Bougie, 2016). The samples selected in this
study were PLN Mobile application users who had used the application for at
least the past 6 months and were at least 17 years old. The questionnaire was
distributed online using Google Forms as a method of data collection, which was
distributed through personal connections, social media and Instagram ads.
In this study, there are eight variables of interest,
namely, functional platform value, cost platform value, contextual platform
value, perceived value, service quality, platform brand image, continuance
intention and platform brand loyalty (Table 1). The measure of functional, cost
and contextual platform value was adapted from He & Zhang (2022) and comprises ten items. The
measure of perceived value and service quality was modified form Chen & Liu (2017) and comprises eight items.
The measure of platform brand image were adapted from Dam & Dam (2021) and Widiani et al., (2022). The measure of continuance
intention was modified from a previous study conducted in the PLN Mobile
context, comprising three items (Maroufkhani et al., 2022; Nikhashemi et al., 2021). The measure of platform
brand loyalty in PLN Mobile from He & Zhang (2022) and Maroufkhani et al., (2022) that consist three items.
To make sure the respondents would fully grasp the
questions, the questionnaire was translated into Indonesian. The items used
were operationalized using a six-point Likert scale ranging from “highly
disagree” to “highly agree”. This study makes use of Smart PLS 3.2.9 software
and the partial least squares structural equation modeling (PLS-SEM)
methodology. PLS-SEM is preferred because of its reliable outcomes and
adaptability to different data assumptions, such as the lack of a normal
distribution requirement (Hair et al., 2019). Along with hypothesis
testing, the study includes evaluating the measurement model, which shows how
measured variables represent constructs, and the structural model, which
illustrates the links between constructs (Hair et al., 2019).
Table 1. Measurement of items
|
Construct |
Code |
Indicator |
|
Functional Platform
Value; |
FU1 |
The PLN Mobile
application can effectively meet daily electricity needs. |
|
FU2 |
The PLN Mobile
application helps complete tasks related to electricity needs, electrical
support and others, according to the features offered. |
|
|
FU3 |
The PLN Mobile
application allows me to make better decisions. |
|
|
Cost Platform Value; |
CO1 |
The PLN Mobile
application helps me to save more costs. (Where I don't need to come to the
PLN office to take care of all kinds of electrical needs) |
|
|
CO2 |
The PLN Mobile
application provides cheaper service products. (Such as administration fees
for new installations, token purchases, electricity payments, etc.) |
|
Cost Platform Value; |
CO3 |
The PLN Mobile
application provides other economic benefits. (Such as promos, discounts,
prize draws etc.) |
|
CO4 |
All types of service
transactions on the PLN Mobile Application provide more effective and
efficient services. |
|
|
Contextual Platform
Value; |
CN1 |
The PLN Mobile
application provides important information. |
|
CN2 |
The PLN Mobile
application provides interesting information. |
|
|
CN3 |
The PLN Mobile
application provides correct information. |
|
|
Perceived Value; |
OV1 |
The PLN Mobile
application provides all types of services and products to meet my various
possible requests. |
|
OV2 |
The PLN Mobile
application provides real-time information that supports me in making the
right decisions. |
|
|
OV3 |
The PLN Mobile
application has an active communication pattern (such as complaint
notifications and regular application tracking notifications). |
|
|
Service Quality; |
PQ1 |
The PLN Mobile
application has good service quality. |
|
PQ2 |
The possibility of the
PLN Mobile Application functioning properly is very high |
|
|
PQ3 |
The possibility of the
PLN Mobile Application being reliable is very high |
|
|
PQ4 |
The interface or
display for using the PLN Mobile Application is easy to understand and not
confusing. |
|
|
PQ5 |
Updating the PLN
Mobile Application is always appropriate and on target |
|
|
Platform Brand Image; |
BI1 |
I have a positive
opinion of the services provided by PLN Mobile. |
|
BI2 |
The PLN Mobile
application is able to represent the information and services provided by PT
PLN (Persero). |
|
|
BI3 |
The services provided
by the PLN Mobile Application produce satisfactory output |
|
|
BI4 |
The PLN Mobile
application increases my trust in PT PLN (Persero) services. |
|
|
Continuance Intention;
(Maroufkhani et al., 2022) |
UI1 |
I intend to always use
the PLN Mobile Application service on an ongoing basis. |
|
UI2 |
I would like to get
more information about the PLN Mobile application |
|
|
UI3 |
I prefer to use the
PLN Mobile Application rather than other alternative types of service. |
|
|
Platform Brand
Loyalty; |
BL1 |
I would like to
recommend the PLN Mobile Application to others. |
|
BL2 |
I feel the PLN Mobile
Application is the best solution to answer the need for the services offered. |
|
|
BL3 |
I would like to give
the PLN Mobile Application a positive review of the services provided. |
Result and Discussion
Respondent Profile
The criteria for
respondents in this study were being over 17 years old when filling out the
questionnaire and having used the PLN Mobile mobile
app within the last 6 months. Of the 310 respondents in the study, 47.42% were
men, and 52.58% were women. The majority of respondents were in the age range
of 27–31 years (129;41.61%), working as entrepreneur (99;31.94%), with the
highest level of education being a Bachelor's Degree (137;44.19%) (Table 2).
Table
2. Demographics of respondent
|
Profile |
Category |
Frequency |
Percentages |
|
Gender |
Males |
147 |
47.42% |
|
Females |
163 |
52.58% |
|
|
Ages |
17-21 years old |
13 |
4.19% |
|
22-26 years old |
56 |
18.06% |
|
|
27-31 years old |
129 |
41.61% |
|
|
32-36 years old |
63 |
20.32% |
|
|
36-41 years old |
32 |
10.32% |
|
|
>42 years old |
17 |
5.48% |
|
|
Occupations |
Student |
23 |
7.42% |
|
Civil Servant or
stated owned employee |
70 |
22.58% |
|
|
Private sector
employee |
72 |
23.23% |
|
|
Entrepreneur |
99 |
31.94% |
|
|
Housewife |
36 |
11.61% |
|
|
Professional (Doctor,
Accountant etc) |
4 |
1.29% |
|
|
Others |
6 |
1.94% |
|
|
Education |
High school or below |
131 |
42.26% |
|
Associate’s degree |
30 |
9.68% |
|
|
Bachelor’s degree |
137 |
44.19% |
|
|
Master’s degree |
11 |
3.55% |
|
|
Doctoral degree |
1 |
0.32% |
Measurement Model Evaluation
The author is expected to interpret the results and then connect
them with previous research (accompanied by scientific discussions and
arguments that support). The discussion should be able to align with the
main purpose of research in the Introduction. Writers may include tables
or graphics on the results and discussions.
Through indicator loadings, construct reliability, convergent
validity, and discriminant validity, the measurement model clarifies how the
measured variables represent a construct (Hair et
al., 2019). Although a value of 0.5 is still
considered acceptable, ideal acceptable indicator values should have outer
loadings above 0.707 (Chin,
1998; Hair et al., 2019) or 0.708 (Hair et
al., 2019). According to Hair et
al., (2019) and Chin (1998), the average threshold for the Average
Variance Extracted (AVE) is 0.5. All indicator variables and latent variables
satisfy the requirements for appropriate outer loadings and AVE, as shown in
Table 4. Table 4 also suggests that every variable in the model passes the
reliability test, obtaining Composite Reliability scores above 0.70 and
Cronbach's Alpha above 0.70 (Hair et
al., 2019).
The degree to which a construct actually varies from another is
then investigated using discriminant validity (Hair et
al., 2019). The HTMT test is advised for assessing
discriminant validity using PLS-SEM (Hair et
al., 2019). The minimum HTMT value is less than 0.9,
and ideally less than 0.85. It is possible to conclude that every variable in
this study satisfies the HTMT test based on the test results (Hair et
al., 2019), which are displayed in Table 5. The Fornell-Larcker test was also performed; it is also shown
in Table 5; all variables in this study satisfy the test's acceptance criteria,
which state that a latent variable's (diagonal value) square root of AVE must
be greater than its correlation with other factors (Chin,
1998; Hair et al., 2019).
Table
3. Demographics of respondent
|
Variable |
Indicator |
Mean |
SD |
Loading |
AVE |
CR |
CA |
|
Functional Platform Value |
FU1 |
4.997 |
1.021 |
0.868 |
0.774 |
0.912 |
0.855 |
|
FU2 |
5.052 |
0.939 |
0.894 |
||||
|
FU3 |
4.784 |
1.054 |
0.878 |
||||
|
Cost Platform Value |
CO1 |
5.11 |
1.11 |
0.800 |
0.692 |
0.9 |
0.851 |
|
CO2 |
4.684 |
1.225 |
0.865 |
||||
|
CO3 |
4.661 |
1.272 |
0.800 |
||||
|
CO4 |
4.942 |
1.058 |
0.860 |
||||
|
Contextual Platform Value |
CN1 |
5.029 |
1.011 |
0.905 |
0.779 |
0.914 |
0.858 |
|
CN2 |
4.735 |
1.069 |
0.880 |
||||
|
CN3 |
5.106 |
0.925 |
0.863 |
||||
|
Perceived Value |
OV1 |
4.671 |
1.057 |
0.828 |
0.724 |
0.887 |
0.808 |
|
OV2 |
4.658 |
1.074 |
0.891 |
||||
|
OV3 |
4.826 |
1.096 |
0.831 |
||||
|
Service Quality |
PQ1 |
4.961 |
1.006 |
0.848 |
0.682 |
0.915 |
0.883 |
|
PQ2 |
4.981 |
0.943 |
0.829 |
||||
|
PQ3 |
4.919 |
1.011 |
0.838 |
||||
|
PQ4 |
4.848 |
1.074 |
0.784 |
||||
|
PQ5 |
4.59 |
1.027 |
0.829 |
||||
|
Platform Brand Image |
BI1 |
4.955 |
0.897 |
0.855 |
0.726 |
0.914 |
0.874 |
|
BI2 |
5.006 |
0.884 |
0.864 |
||||
|
BI3 |
4.819 |
0.916 |
0.829 |
||||
|
BI4 |
5.006 |
0.964 |
0.860 |
||||
|
Continuance Intention |
UI1 |
5.026 |
0.993 |
0.901 |
0.747 |
0.899 |
0.831 |
|
UI2 |
4.997 |
0.932 |
0.859 |
||||
|
UI3 |
4.713 |
1.092 |
0.831 |
||||
|
Platform Brand Loyalty |
BL1 |
5.042 |
1.063 |
0.889 |
0.785 |
0.916 |
0.863 |
|
BL2 |
4.923 |
0.954 |
0.880 |
||||
|
BL3 |
5.116 |
0.919 |
0.889 |
Note:
SD—Standard Deviation; AVE—Average Variance Extracted; CR—Composite Reliability
CA— Cronbach's Alpha.
Table
4. Measurement Model Evaluation 2: Discriminant Validity
|
Fornell and Lacker Criterion |
||||||||
|
Variable |
BI |
BL |
CN |
CO |
FU |
PV |
SQ |
CI |
|
|
|
|
|
|
|
|
|
|
|
BI |
0.852 |
|||||||
|
BL |
0.765 |
0.886 |
||||||
|
CN |
0.702 |
0.63 |
0.883 |
|||||
|
CO |
0.676 |
0.639 |
0.723 |
0.832 |
||||
|
FU |
0.681 |
0.631 |
0.685 |
0.692 |
0.88 |
|||
|
PV |
0.681 |
0.637 |
0.743 |
0.691 |
0.653 |
0.851 |
||
|
SQ |
0.759 |
0.734 |
0.74 |
0.725 |
0.717 |
0.756 |
0.826 |
|
|
CI |
0.731 |
0.764 |
0.653 |
0.657 |
0.64 |
0.635 |
0.707 |
0.864 |
|
HTMT
Ratio Approach |
||||||||
|
Variable |
BI |
BL |
CN |
CO |
FU |
PV |
SQ |
CI |
|
BI |
|
|
|
|
|
|
|
|
|
BL |
0.88 |
|||||||
|
CN |
0.811 |
0.733 |
||||||
|
CO |
0.78 |
0.744 |
0.842 |
|||||
|
FU |
0.787 |
0.735 |
0.798 |
0.807 |
||||
|
PV |
0.811 |
0.764 |
0.892 |
0.831 |
0.782 |
|||
|
SQ |
0.863 |
0.84 |
0.849 |
0.831 |
0.823 |
0.892 |
||
|
CI |
0.851 |
0.898 |
0.773 |
0.778 |
0.756 |
0.771 |
0.821 |
|
Note:
BI = Platform Brand Image; BL = Platform Brand Loyalty; CN = Contextual
Platform Value; CO = Cost Platform Value; FU = Functional Platform Value; PV =
Perceived Value; SQ = Service Quality; CI = Continuance Intention
Structural Model Evaluation
After the
measurement model's validity and reliability were proven, the structural model
was evaluated (Hair et al., 2019). When
collinearity was evaluated by looking at inner VIF values, all of the values
were found to be below 3.3, which indicates that common method bias was not
present (Kock, 2015). The structural
model was then assessed by utilizing coefficients of determination (R²),
cross-validated redundancy (Q²), and path coefficients or hypothesis testing to
determine the interrelatedness of the constructs.
In the PLS-SEM model R-Square (R²), measures the prediction
strength within the sample; a value of 1 denotes a perfect association, and 0
denotes no relationship (Hair et
al., 2019). Overall, all the predictor variables
tested in the study are in the moderate category above 0.5. Furthermore,
acceptable predictive accuracy on endogenous constructs is demonstrated by the
cross-validated redundancy method with Q² values above zero (Hair et
al., 2019). Blindfolding techniques are used to
calculate Q², a measure of the PLS-SEM model's predictive strength, on subset
data. The study's model's acceptable predictive accuracy is confirmed by the
results, which show that all endogenous variables have Q² values greater than
zero (Hair et
al., 2019).
The next step is to assess the importance and size of structural
path coefficients. Using bootstrapping with 5,000 sub-samples, path
coefficients were evaluated for their magnitude and importance in the
structural path relationships (Hair et
al., 2019). If a P Value in a hypothesis test is
less than (<) 0.05, it is accepted. Based on the hypothesis testing results
in Table 5, it can be seen that 14 hypotheses were accepted, and 3 hypotheses
were rejected. Regarding the results
show that functional platform value had a positive influence toward perceived
value but the result of the p values < 0.05. Therefore, hypotheses H1a was
not supported this shows that the relationship between functional platform
values and the overall platform value is complex and varied. It is highly
dependent on the context of the services offered within the entire ecosystem
and the service process. This complexity makes the significance of the direct
influence on perceived value very small.
On the contrary, regarding the impact of contextual on perceived
value (H1b), was significant with p Values < 0.05. The result indicates that
digital interactive platforms create cost value for users by providing lower
prices or other economic benefits through advantages in scale or efficiency.
The 1c hypotheses, which examined the impact of contextual on perceived value,
were accepted that the p Values < 0.05. The results show that digital
interactive platforms can increase the level of contextualization and
personalization through instructions or features that have relevance to each
user (He &
Zhang, 2022). Therefore, contextual value can serve as
a signal of high-quality experiences and positive psychological states.
Table
5. Structural Model Evaluation
|
Hypothesis |
Path |
VIF |
β |
T statistics |
P Values |
Supported |
|
H1a |
FU -> PV |
2.478 |
0.075 |
1.183 |
0.118 |
No |
|
H1b |
CO -> PV |
2.696 |
0.148 |
1.998 |
0.023 |
Yes |
|
H1c |
CN -> PV |
2.769 |
0.32 |
5.353 |
0.000 |
Yes |
|
H2 |
SQ -> PV |
2.956 |
0.358 |
5.501 |
0.000 |
Yes |
|
H3 |
PV -> BL |
2.531 |
0.03 |
0.557 |
0.289 |
No |
|
H4 |
SQ -> BL |
3.349 |
0.216 |
3.241 |
0.001 |
Yes |
|
H5 |
PV -> BI |
2.331 |
0.251 |
4.055 |
0.000 |
Yes |
|
H6 |
SQ -> BI |
2.331 |
0.569 |
9.315 |
0.000 |
Yes |
|
H7 |
PV -> CI |
1.866 |
0.255 |
4.109 |
0.000 |
Yes |
|
H8 |
BI -> CI |
1.866 |
0.557 |
9.316 |
0.000 |
Yes |
|
H9 |
CI -> BL |
2.475 |
0.358 |
7.316 |
0.000 |
Yes |
|
H10 |
BI -> BL |
2.968 |
0.320 |
5.915 |
0.000 |
Yes |
|
H11 |
SQ -> PV -> BL |
0.011 |
0.528 |
0.299 |
No |
|
|
H12 |
SQ -> BI -> BL |
0.182 |
5.034 |
0.000 |
Yes |
|
|
H13 |
PV -> BI -> BL |
0.080 |
3.351 |
0.000 |
Yes |
|
|
H14 |
PV -> CI -> BL |
0.091 |
3.654 |
0.000 |
Yes |
|
|
H15 |
BI -> CI -> BL |
|
0.200 |
5.852 |
0.000 |
Yes |
Note:
BI = Platform Brand Image; BL = Platform Brand Loyalty; CN = Contextual
Platform Value; CO = Cost Platform Value; FU = Functional Platform Value; PV =
Perceived Value; SQ = Service Quality; CI = Continuance Intention; VIF—variance
inflation factor; β—path coefficient.
The effect of service quality toward perceived value (H2) was
found to have a significant impact with p values <0,05. This shows the
customers' subjective assessment of the quality of a brand or product can
evaluate the value provided to them. Similar to the impact of service quality
on perceived value, the impact of service quality on platform brand loyalty
(H4) is also significant with a p value < 0,05. This indicate that the role
of quality can be linked directly to loyalty.
In contrast, the impact of perceived value on platform brand
loyalty (H3) was positive, but the p-value result was > 0.05. Therefore,
hypothesis H3 was not supported, indicating that there are other variables that
should be considered when assessing the significance of a platform's value in
relation to loyalty. This also affects the role of perceived value as a
mediating variable in the relationship between service quality and platform
brand loyalty (H11), as the p-value is > 0.05. Consequently, the H11 hypothesis
was not supported either. This suggests that the characteristics of perceived
value do not play a mediating role between service quality and brand loyalty
for PLN Mobile application users. Some studies assert that there is no
significant influence between perceived value and loyalty (Pratiwi et
al., 2021), and this impact may vary across
different service sectors, explaining the absence of a mediating role for this
variable in our research.
The hypotheses H5 and hypotheses H6 was supported in both result
with a p value < 0.05, showing that both perceived value and service quality
had significant impact of platform brand image. The value generated from the
mobile platform is proven to be able to generate an overall brand image, same
with the quality perception on costumers. The hypotheses H7 and hypotheses H8
was also supported in both result with a p value < 0.05, showing that both
perceived value and platform brand image had significant impact on continuance
intention. In various service contexts, perceived value can generate the user's
intention to continue using the service continuously, the same as the platform
brand image of all the services offered on the platform itself.
The next hypotheses H9, which examined the impact of continuance
intention on platform brand loyalty, was supported with p value < 0,05. This
indicate that PLN Mobile respondents' desire to use the application again in
the future has a significant relationship to the loyalty they feel in the brand
platform on the application. The last direct hypothesis H10, also had a
significant impact on platform brand image on platform brand loyalty with p
value < 0,05. This indicated that the characteristics of the Platform Brand
Image have a positive and significant effect on the Platform Brand Loyalty of
PLN Mobile application users.
Based on the several hypotheses above, the following are the
results of the mediation hypothesis that complement the measurement outcomes in
the structural model. In hypothesis H12, where platform brand image mediates
the influence of service quality on platform brand loyalty, the p-value is
<0.05, indicating a significant value, and the hypothesis is accepted.
Therefore, in the context of PLN Mobile, brand image can partially mediate the
role of service quality on application loyalty due to the significance between
service quality and platform brand image in relation to platform brand loyalty.
Furthermore, hypotheses H13 and H14 show a p-value <0.05,
proving that platform brand image and continuance intention can significantly
mediate the influence of perceived value on platform brand loyalty. These two
variables can fully mediate the role of perceived value on platform brand
loyalty because the direct influence between perceived value and platform brand
loyalty is not significant in this research. In the final hypothesis H15,
continuance intention has a significant mediating influence on the relationship
between platform brand image and platform brand loyalty, with a p-value
<0.05. This shows that continuance intention can partially mediate the role
of platform brand image on application loyalty due to the significance between
platform brand image and platform brand loyalty.
The summary of hypothesis testing results can be seen in Figure 2.
Figure 2. Structural
Model
Discussion
This study examines the impact of three multidimensional of
platform value creation and service quality on perceived value, platform brand
image, continuance intention and platform brand loyalty. The result shows that
cost, contextual platform value and service quality have a significant impact
on perceived values but not with functional values. Another result shows that
perceived value has no direct influence on platform brand loyalty. Therefore,
perceived value cannot become the only mediating factor that creating
significant impact between service quality on platform brand loyalty.
However, another several factor that had been studied in this
study shows that platform brand image and continuance intention had significant
influences on loyalty. Therefore, these two variables can become mediating
variable in this study that creating significant impact of perceived value on
platform brand loyalty. Based on the overall findings of the study above, this
study theoretically contributes to the current research about value creations
and service quality creating digitized services effectiveness by providing
empirical evidence. By considering the perceived value of users, services
offered via mobile platforms can become more effective and significantly
increase the intension too use and platform brand loyalty. Apart from that,
value and quality have also been proven to be able to improve the overall image
of the digitization of services offered on the mobile platform so that this can
empirically increase the desire and loyalty of mobile platform users.
The analysis and hypothesis testing reveal several key findings.
First, among the three multidimensional platform values—functional, cost, and
contextual—only functional platform value lacks a significant influence on
perceived value. Cost and contextual values, on the other hand, directly impact
perceived value. Second, in the context of PLN Mobile application users, there
is a positive and significant direct influence between service quality and
perceived value, platform brand image, and platform brand loyalty.
Third, although perceived value has a positive and significant
direct influence on continuance intention and platform brand image, it does not
directly impact platform brand loyalty for users of the PLN Mobile application.
Fourth, perceived value partially mediates the influence of service quality on
platform brand image but does not mediate the influence of service quality on
platform brand loyalty. Fifth, continuance intention partially mediates the
influence of platform brand image on platform brand loyalty, and it fully
mediates the influence of perceived value on platform brand loyalty. Lastly,
platform brand image fully mediates the influence of perceived value on
platform brand loyalty and partially mediates the relationship between service
quality and brand loyalty on the platform.
The increasing use of the internet and mobile platforms requires
companies, particularly in customer service sectors, to enhance user engagement
and customer loyalty through the digitalization of services. The rapidly
evolving landscape of information technology has disrupted traditional service
sectors in various large Indonesian companies. This study identifies practical
implications for fostering loyalty in the evolving digital service landscape,
emphasizing the need for value and quality that can stimulate increased usage
and enhance overall user perception of the application.
Furthermore, among the variables perceived value and platform
brand image, which are variables that influence continuance intention, platform
brand image is the variable that has the greatest influence value. Where the
BI2 indicator is a representation of the Company's overall services that can be
provided by the application, therefore it is important for the Company to be
able to translate the types of services offered as a whole into digital
application channels so that this can increase the intensity of use of the
application itself.
On the other hand, the four latent variables that influence
platform brand loyalty in this research model show that the continuance
intention variable is the variable that has the greatest influence value among
the other three. In indicator CI1, namely the user's desire to continue using
the application on an ongoing basis, is an important factor so that application
users are willing to recommend services and provide positive reviews of the
services provided which encourages service satisfaction and loyalty in using
the platform.
Conclusion
In conclusion, The role of brand image
and continuity intention as mediating variables is an important aspect in
increasing the significance of the influence of perceived value on platform
brand loyalty. This shows that value is not enough to explain how the loyalty
construct is formed in the context of mobile platform services. and also the insignificance of the functional platform value
variable to perceived value indicates the possibility of differences from the
point of view of the digital service context, where in this research the object
being studied is the user of the electricity service application, where this is
a primary utility need in the modern era.
One limitation of this research is that it only focuses on one
type mobile platform of Indonesian stated owned company digital services. Some
exploration on the impact of values and quality toward platform brand loyalty
in other types of industry or company would be considerably beneficial for the
digital services and marketing literature. In addition, the research was
conducted in a context where the PLS is the ideal concept of the measurement.
Future studies should examine the role of overall platform values in
influencing other factors that can enhance the services improvement on digital
marketing and services sector.
BIBLIOGRAPHY
Aaker,
D. . (1991). Managing Brand Equaty: Capitalizing on the Value of a Brand. New
York: The Free Press, 1991.
Al Amin, M., Muzareba, A. M., Chowdhury, I. U., & Khondkar, M. (2023).
Understanding e-satisfaction, continuance intention, and e-loyalty toward
mobile payment application during COVID-19: an investigation using the
electronic technology continuance model. Journal of Financial Services
Marketing, 0123456789. https://doi.org/10.1057/s41264-022-00197-2
APJII. (2023). Survei APJII Pengguna Internet di Indonesia Tembus 215 Juta
Orang. Apjii.Do.Id, March, 10–12.
https://apjii.or.id/berita/d/survei-apjii-pengguna-internet-di-indonesia-tembus-215-juta-orang
Ayutthaya, S. S. N. (2013). Impact of Perceived Service on Brand Image and
Repurchase Intentions of Thai Passengers towards Low Cost Carriers. In AU
Journal of Management (Vol. 11, pp. 46–56).
https://aujm.au.edu/index.php/aujm/article/view/41%0Ahttps://aujm.au.edu/index.php/aujm/article/download/41/27
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
Chen, C.-M., & Liu, H.-M. (2017). Exploring the Impact of Airlines
Service Quality on Customer Loyalty: Evidence from Taiwan. International
Journal of Business and Management, 12(5), 36.
https://doi.org/10.5539/ijbm.v12n5p36
Chin, W. W. (1998). The partial least squares approach to structural
equation modelling. In Marcoulides G. A. (Ed.). Modern Methods for Business
Research, 295(2), 295–336.
Chou, S. F., Horng, J. S., Sam Liu, C. H., & Lin, J. Y. (2020).
Identifying the critical factors of customer behavior: An integration
perspective of marketing strategy and components of attitudes. Journal of
Retailing and Consumer Services, 55(September 2019), 102113.
https://doi.org/10.1016/j.jretconser.2020.102113
Dam, S. M., & Dam, T. C. (2021). Relationships between Service
Quality, Brand Image, Customer Satisfaction, and Customer Loyalty. Journal
of Asian Finance, Economics and Business, 8(3), 585–593.
https://doi.org/10.13106/jafeb.2021.vol8.no3.0585
Dobre, C., Milovan, A. M., Preda, G., & Naghi, R. (2023).
Post-purchase behaviour triggers in branded mobile shopping apps. Marketing
Intelligence and Planning, 41(3), 344–359.
https://doi.org/10.1108/MIP-08-2022-0357
Fajariah, N., Thoyib, A., & Rahman, F. (2016). Pengaruh Brand
Awareness, Perceived Quality, dan Brand Image terhadap Brand Loyalty pada
Generasi Y di Indonesia. Jurnal Aplikasi Manajemen, 14(3),
471–480. https://doi.org/10.18202/jam23026332.14.3.08
Fitriani, N., & Paramita, T. (2022). Improving the Loyalty of Online
Transport User Trough Brand Image, Brand Awareness, and Brand Trust. MEC-J
(Management and Economics Journal), 6(2), 173–184.
https://doi.org/10.18860/mec-j.v6i2.16215
Garcia, J. M., Freire, O. B. D. L., Santos, E. B. A., & Andrade, J.
(2020). Factors affecting satisfaction and loyalty to online group buying. Revista
de Gestao, 27(3), 211–228. https://doi.org/10.1108/REGE-02-2018-0037
Hair, J. F., Black, Jr, W. C., Babin, B. J., & Anderson, R. E. (2019).
Multivariate Data Analysis. In Pearson New International Edition.
He, J., & Zhang, S. (2022). How digitalized interactive platforms
create new value for customers by integrating B2B and B2C models? An empirical
study in China. Journal of Business Research, 142(March 2021),
694–706. https://doi.org/10.1016/j.jbusres.2022.01.004
Hew, J. J., Lee, V. H., Ooi, K. B., & Lin, B. (2016). Mobile social
commerce: The booster for brand loyalty? Computers in Human Behavior, 59,
142–154. https://doi.org/10.1016/j.chb.2016.01.027
Homer, P. M. (2008). Perceived quality and image: When all is not “rosy.” Journal
of Business Research, 61(7), 715–723.
https://doi.org/10.1016/j.jbusres.2007.05.009
Huang, Y. C. (2022). How marketing strategy, perceived value and brand
image influence WOM outcomes—The sharing economy perspective. Journal of
Retailing and Consumer Services, 68(June), 103071.
https://doi.org/10.1016/j.jretconser.2022.103071
Jaya, I. P. G. I. T., & Prianthara, I. B. T. (2020). Role of Social
Media Influencers in Tourism Destination Image: How Does Digital Marketing
Affect Purchase Intention? Advances in Social Science, Education and
Humanities Research, 426(Icvhe 2018), 9–20.
https://doi.org/10.2991/assehr.k.200331.114
Kapoor, K., Ziaee Bigdeli, A., Dwivedi, Y. K., Schroeder, A., Beltagui,
A., & Baines, T. (2021). A socio-technical view of platform ecosystems:
Systematic review and research agenda. Journal of Business Research, 128(February),
94–108. https://doi.org/10.1016/j.jbusres.2021.01.060
Kock, N. (2015). Common Method Bias in PLS-SEM. International Journal
of E-Collaboration, 11(4), 1–10.
https://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/ijec.2015100101
Le, C. X., & Wang, H. (2021). Integrative perceived values influencing
consumers’ attitude and behavioral responses toward mobile location-based
advertising: an empirical study in Vietnam. Asia Pacific Journal of
Marketing and Logistics, 33(1), 275–295.
https://doi.org/10.1108/APJML-08-2019-0475
Mariano, A. M., Silva, M. C., Mello, T. M., & Santos, M. R. (2022).
The importance of mobile applications for companies’ brand image: A study using
structural equations. Procedia Computer Science, 214(C),
1128–1135. https://doi.org/10.1016/j.procs.2022.11.287
Maroufkhani, P., Asadi, S., Ghobakhloo, M., Jannesari, M. T., &
Ismail, W. K. W. (2022). How do interactive voice assistants build brands’
loyalty? Technological Forecasting and Social Change, 183(December
2021), 121870. https://doi.org/10.1016/j.techfore.2022.121870
Murillo-Zegarra, M., Ruiz-Mafe, C., & Sanz-Blas, S. (2020). The
effects of mobile advertising alerts and perceived value on continuance
intention for branded mobile apps. Sustainability (Switzerland), 12(17).
https://doi.org/10.3390/SU12176753
Nikhashemi, S. R., Knight, H. H., Nusair, K., & Liat, C. B. (2021).
Augmented reality in smart retailing: A (n) (A) Symmetric Approach to
continuous intention to use retail brands’ mobile AR apps. Journal of
Retailing and Consumer Services, 60(December 2020), 102464.
https://doi.org/10.1016/j.jretconser.2021.102464
Omoregie, O. K., Addae, J. A., Coffie, S., Ampong, G. O. A., & Ofori,
K. S. (2019). Factors influencing consumer loyalty: evidence from the Ghanaian
retail banking industry. International Journal of Bank Marketing, 37(3),
798–820. https://doi.org/10.1108/IJBM-04-2018-0099
Ortiz, S. E., Zimmerman, F. J., & Adler, G. J. (2016). Increasing
public support for food-industry related, obesity prevention policies: The role
of a taste-engineering frame and contextualized values. Social Science and
Medicine, 156, 142–153.
https://doi.org/10.1016/j.socscimed.2016.02.042
Pandey, N., & Rupnawar, A. (2022). Idea Generation for New Service
Development (NSD): Harnessing the Power of Social Media Platforms. Multidisciplinary
Business Review, 15(1), 2–10.
https://doi.org/10.35692/07183992.15.1.2
Parasuraman, A., Zeithaml, V. A., & Berry, L. L. (1985). A Conceptual
Model of Service Quality and Its Implications for Future Research. Journal
of Marketing, 49(4), 41. https://doi.org/10.2307/1251430
Park, S. Y., & Kim, Y. (2013). An Analysis of the Interaction Effect
of Benefit and Cost on Cloud Computing Service. KIPS Transactions on
Computer and Communication Systems, 2(1), 27–34.
https://doi.org/10.3745/ktccs.2013.2.1.027
Pitt, C., Plangger, K., & Eriksson, T. (2020). Accommodation eWOM in
the sharing economy: automated text comparisons from a large sample. Journal
of Hospitality Marketing and Management, 30(2), 1–18. https://doi.org/10.1080/19368623.2020.1781733
PLN. (2022). Punya Banyak Fitur Canggih, Aplikasi PLN Mobile Diunduh Lebih
35 Juta Pengguna. PLN, 1. https://web.pln.co.id
Prabowo, H., Astuti, W., & Respati, H. (2020). Effect of Service
Quality and Brand Image on Repurchase Intention through Word of Mouth at Budget
Hotels Airy Rooms. Open Journal of Business and Management, 08(01),
194–207. https://doi.org/10.4236/ojbm.2020.81012
Pratiwi, R. S., Salim, U., & Sunaryo, S. (2021). the Effect of Brand
Experience and Perceived Value on Brand Loyalty Mediated By Brand Trust. Jurnal
Aplikasi Manajemen, 19(2), 310–318.
https://doi.org/10.21776/ub.jam.2021.019.02.07
Rahmatulloh, R., Yasri, Y., & Abror, A. (2019). The Influence of
Brand Image and Perceived Quality on Brand Loyalty with Brand Trust as Mediator
in PT Bank Syariah Mandiri. 64, 569–578.
https://doi.org/10.2991/piceeba2-18.2019.38
Ratasuk, A. (2021). The Impact of the No-Plastic-Bag Campaign on Customer
Repurchase Intentions and its mechanism in the Modern Trade Business in
Bangkok. Asia Social Issues, 15(2), 251631.
https://doi.org/10.48048/asi.2022.251631
Roig, J. C. F., Garcia, J. S., Tena, M. A. M., & Monzonis, J. L.
(2006). Customer perceived value in banking services. International Journal
of Bank Marketing, 24(5), 266–283.
https://doi.org/10.1108/02652320610681729
Ryu., K., Lee, H.-R., & Kim, W. G. (2011). The influence of the
quality of the physical environment, food, and service on restaurant image,
customer perceived value, customer satisfaction, and behavioral intentions. International
Journal of Contemporary Hospitality Management, 24(2), 175–199.
https://doi.org/10.1108/09596111211206141
Sadli, T., Hartono, V. C., & Proboyo, A. (2022). Mediation Role of
Purchase Intention on The Relationship Between Social Media Marketing, Brand
Image, and Brand Loyalty: A Case Study of J&T Express Indonesia. Petra
International Journal of Business Studies, 5(2), 206–216.
https://doi.org/10.9744/ijbs.5.2.206-216
Sekaran, U., & Bougie, R. (2016). Research methods for business: A
skill building approach. In Wiley (Vol. 7, Issue 2). Wiley.
https://doi.org/10.1016/0024-6301(93)90168-f
Shankar, A., & Jebarajakirthy, C. (2019). The influence of e-banking
service quality on customer loyalty: A moderated mediation approach. International
Journal of Bank Marketing, 37(5), 1119–1142.
https://doi.org/10.1108/IJBM-03-2018-0063
Tam, C., Barroso, M., & Cruz-Jesus, F. (2022). Understanding the
determinants of users’ continuance intention to buy low-cost airline flights
online. Journal of Hospitality and Tourism Technology, 13(2),
264–280. https://doi.org/10.1108/JHTT-12-2020-0316
van Dat, T. (2020). Assessing the effects of service quality, experience
value, relationship quality on behavioral intentions. Journal of Asian
Finance, Economics and Business, 7(3), 167–175.
https://doi.org/10.13106/jafeb.2020.vol7.no3.167
Wade, M., Loucks, J., Noronha, A., & Macaulay, J. (2016). Digital
vortex: How today’s market leaders can beat disruptive competitors at their own
game. Global Center for Digital Business Transformation, 266.
Widiani, E., Agung, I. G., Teja, E., & Widnyana, I. W. (2022). Building
BPJS Image , Public Trust and Intention to Use JKN Mobile Services During the
Covid Pandemic. 15(3), 187–209.
Wijaya, A. F. B., Surachman, S., & Mugiono, M. (2020). the Effect of
Service Quality, Perceived Value and Mediating Effect of Brand Image on Brand
Trust. Jurnal Manajemen Dan Kewirausahaan, 22(1), 45–56.
https://doi.org/10.9744/jmk.22.1.45-56
Yang, D., & Wang, X. (2010). The effects of 2-tier store brands’
perceived quality, perceived value, brand knowledge, and attitude on store
loyalty. Frontiers of Business Research in China, 4(1), 1–28.
https://doi.org/10.1007/s11782-010-0001-7
Zeithmal, V. (2001). Service Quality , Profitability , and the Economic
Worth of Customers : What We Know and What We Need to Learn Service Quality ,
Profitability , and the Economic Worth of Customers : What We Know and What We
Need to Learn. Journal of the Academy of Marketing Science, 28(1),
67–85.
|
Copyright
holder: Fristyan Pradipta, Daniel Tumpal H Aruan (2024) |
|
First
publication right: Syntax Literate: Jurnal Ilmiah Indonesia |
|
This
article is licensed under:
|
