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INTERNATIONAL JOURNAL OF INDUSTRIAL MANAGEMENT
ISSN: 2289-9286
e-ISSN: 2590-3594
VOLUME 17, NO. 4, 2023, 186 – 194
DOI: https://doi.org/10.15282/ijim.17.4.2023.10023
*CORRESPONDING AUTHOR | A. Azit | azizan@ump.edu.my
© 2023 The Author(s). Published by Universiti Malaysia Pahang Publishing. This is an open access article under the CC BY-NC 4.0 license 186
RESEARCH ARTICLE
THE INFLUENCE OF SELF-SERVICE EXPERIENCES ON CUSTOMER
SATISFACTION
Norashikin Jalani, Azizan Azit*, Wan Khairul Anuar Wan Abd Manan, Mazita Mokhtar
Faculty of Industrial Management, Universiti Malaysia Pahang Al Sultan Abdullah, Lebuhraya Persiaran Tun Khalil Yaakob,
Gambang 26300 Pahang, Malaysia
ABSTRACT - Successful companies consistently provide higher levels of satisfaction to their
customers. This study is to determine the impact of self-service experiences on customer
satisfaction. For the purpose of the study, 120 McDonald's customers were selected for a
survey. The results showed that being technologically ready positively and substantially
affects customer satisfaction through the medium of Customer Trust. Self-service can be more
efficient and successful, and customers can be more satisfied if the necessary technology is
in place. Self-service experience quality and client satisfaction are impacted by trust and
perceived value. This research contributes to understanding what it takes to keep repeat
customers happy and returning for more business.
ARTICLE HISTORY
Received
:
06-03-2023
Revised
:
10-04-2023
Accepted
:
15-04-2023
Published
:
21-12-2023
KEYWORDS
Customer trust
Customer satisfaction
Quality of self-service
Technology readiness
Perceived value
Self-service quality
1.0 INTRODUCTION
Successful companies consistently deliver increased levels of satisfaction to their client. Customers who are entirely
content with the company will talk positively about their interactions with the business to others, which will serve as a
form of word-of-mouth promotion for the firm. One of the most essential things in developing a competitive edge and
achieving success for Mcdonald’s is using innovative new ways to provide their services. It allowed the company to
completely revamp the design of its eateries and the way it utilised its staff. According to Liu and Hung (2022), the use
of automated self-services has become widespread in-service industries and is considered a crucial trend.
By directing clients to self-service kiosks, the company was able to substantially cut the amount of cash handled on-
site as card and contactless payments became the norm. Due to this situation, the restaurant redeployed some employees
who had been working the register. Park et al. (2021) suggested that incorporating kiosks can result in reduced operating
costs, particularly in terms of labor costs, and can help to address labor shortages. This is considered to be a significant
advantage for both companies and operators.
Important facets of service evaluation, such as the ideas of perceived risk, perceived value, and perceived satisfaction,
are modelled by this framework, which can be thought of as a model. According to the frequency, despite the fact that
self-service is deliberately designed to improve quality and contain the necessary information to fulfil customer needs,
the self-service experience has not yet achieved up to standards of Performance. This is the case despite the self-service
deliberately being designed to improve quality. This is in spite of the fact that the self-service was purposefully developed
to enhance the quality of the product. Last but not least, if more individuals were not aware of the potential problems it
could cause, it might make the customer experience more difficult.
2.0 RELATED WORK
2.1 Customer satisfaction
Satisfied customers have received adequate compensation for purchases at a predetermined price (Jeong et al., 2016).
According to Oliver (1999), customer satisfaction is an enjoyable extra activity a consumer performs while utilising a
service or product. The purchase only partially satisfies the customer's needs, wants, and expectations. She or he also
appreciates participating in this extracurricular pursuit.
According to Jamal et al. (2020), customer happiness is the connecting thread between the various phases of the
consumer purchase process. Customer satisfaction is measured before and after the transaction and in terms of the price
paid. A number of factors ensure satisfied customers when it comes to their personal data (CIS). There are many facets
to a successful business, including sales, information systems (websites), digital products and services, customer support,
post-sale service, and company culture. In contrast to other online or traditional retail organisations, e-satisfaction refers
to a customer's happiness with their online shopping experience. E-satisfaction is utilised as a proxy for the level of
contentment with an online purchase in this investigation.
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2.2 Perceived quality of self-service
The phrase "quality of service" refers to the overall evaluation that a consumer gives regarding the performance of a
service. Since ancient times, people have considered happy customers a dependable indicator of product quality
(Boonlertvanich, 2019). According to Aker (1997), two aspects of quality should be considered when addressing
perceived quality: product quality and service quality. During the process of providing services, quality assurance
inspections are performed in industries that provide services. Every interaction you have with a customer is a chance to
create trust with them or demonstrate that you do not care about their needs (Pakurár et al., 2019). As a consequence, the
service quality improves to match, if not even exceed, the consumer's expectations. In the context of the quick-service
restaurant industry, "service quality" refers to a patron's perspective or stance with regard to the enhancement of the
quality of services provided within a dining establishment (Al-Hawari et al., 2019). This research considers aspects like
usability, convenience, enjoyment, quality control, and safety. With this system, clients may get what they want without
having to interact with employees directly, leading to improved service quality. While imperfect, this service model can
potentially improve the quality of care provided to customers. Offering self-service choices can be done for many different
reasons, such as saving money, making customers happier, and attracting new customers (Bitner et al., 2020).
2.3 Perceived value
Perceived value is a vital part of the process that must be followed to provide the right product or service to the right
client at the right time. Companies can also use the concept of perceived worth to determine comparable costs (Hussain
et al., 2015). Previous research has shown that service quality is directly related to the customer's perception of value.
Customers will regard services more highly if they require less of the money and effort.
2.4 Technology readiness
The term "technological readiness" refers to an individual's adaptability to a given piece of technology in service of
their desired end results. Numerous studies have used TRI2.0 to evaluate the rate of adoption of cutting-edge technologies
namely mobile payment, mobile social networks, internet access, and self-service technologies (SSTs) among others.
Researcher predicted they would need to adapt to technology in order to keep up with the rise of mobile commerce, social
networking, and cloud computing.
Customers' attitudes and actions towards technology can be either favourable or unfavourable, showing that
technology can yield positive and negative effects. Customers' perspectives and behaviours towards technology can be
either favourable or unfavourable. Researcher proposed four variables in assessing people's technological advancement
readiness. Each of these variables considers both positive and negative attitudes people have on technological growth. As
you will see in the next phrases, you can evaluate these traits based on how optimistic you are, how innovative you are,
how uncomfortable you are, and how insecure you are. Customers have the misconception that technology, despite being
adaptable and adjustable, can support them in delivering services more efficiently. The second component, innovation, is
beneficial since it satisfies consumers’ wishes to use contemporary technologies. In regards to this situation, the invention
is a quality that should be admired. The core cause of consumers' adverse opinions of being controlled is a lack of trust
in the technology and its capabilities practice. The root cause of customers' uneasiness is a lack of trust in the technology
and its capabilities in general. This component additionally exemplifies the unfavourable emotions that the clients hold.
3.0 HYPOTHESES DEVELOPMENT
There have been many studies on service quality and customer happiness. Rangriz et al. (2013) also looked into the
current state of providing services online. Electronic and self-service operations in service organisations rely heavily on
customers' readiness, perceived utility, and ease of use. Saleem et al. (2017) and Setiawan and Sayuti (2017), among
others, have discussed the correlation between trust and happiness.
H1. Customer trust influences customer satisfaction.
It was proven that one of the most important factors in determining customer happiness is the perceived value of the
product or service. Numerous research, such as those carried out by Konuk (2018) and Garca-Fernández et al. (2018),
have found a correlation between the ratings that customers give of a product or service and the level of contentment that
they report experiencing with that product or service. There is a substantial correlation between customers’ faith in
McDonald's and the quality of service they will receive. This idea is supported by Marakanon and Panjakajornsak (2017)
and Konuk (2017), who investigated the connection between perceived value and the happiness of consumers (2018).
Alongside the values of reliability and the perceived value of consumers, research will be conducted on service quality in
customer pleasure and self-service experience for customers.
H2. Perceived value influences customer satisfaction.
According to Lin and Hsieh (2007), the level of technical expertise possessed by a customer is the single most critical
element in determining the level of success that may be achieved through self-service initiatives. To restate this idea,
improved customer service is the direct effect of beginning with tech-savvy clients. Boon-itt (2015) argued that consumer
technical readiness significantly affects judgements of the quality of the self-service experience; consequently, it stands
to reason that customers' impressions of the experience would improve with greater technological readiness. On the other
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hand, Strutt et al. (2022) demonstrated that the degree of technological preparation significantly contributed to the level
of customer happiness. Several researchers, have recently written about the relationship between trust and happiness.
H3. Technology readiness influences customer trust.
4.0 THEORETICAL FRAMEWORK
A research framework, depicted in Figure 1, was developed in accordance with the research topic and the literature
review.
Figure 1. Conceptual framework
5.0 RESEARCH METHODOLOGY
McDonald's customers were the main source of data for this study. Eliminating unnecessary factors led to the selection
of McDonald's with the most locations and consumers. The data collection spanned from July through October 2022. In
order to make reliable conclusions about the effects of the operational parameters under research, this research required
at least 120 replies from Malaysian McDonald's. In addition to that, the researchers collected the data through an online
poll.
6.0 RESULT
Regarding gender, male respondents made up 50.9% (representing 59 total respondents), while female respondents
made up 49.1% (representing 57 total respondents). This could be due, at least in part, to the fact that men typically have
more free time than women do and, as a result, choose to spend it at McDonald's. The following inquiry concerns the age
of those who filled out the survey. According to Table 1, the largest proportion of respondents is between the ages of 21
and 30 years old (60%) followed by those who are younger than 20 years old (25%). 15.00% of the respondents are
between the ages of 31 and 40, the youngest group. This is due to the fact that people in the age range 31 and below are
more difficult to communicate with than younger people. Next, for levels of education, those with at least an STPM, A-
Level, or foundational degree have the highest response rate.
The total number of respondents with a STPM/A' Level/foundation background is 45, which represents 37.5%,
followed by 26 respondents with a Bachelor Degree, which have 21.70%. The lowest percentage of respondents came
from those with master's degrees or an MBA (6.70%), followed by those with doctoral degrees (0.80%). There are just
25 individuals who have a background with a Diploma, making up 20.80% of the total. The total number of respondents
from SPM/0'Level is 15, which represents 12.5%, and there is no respondent for PMR, which represents 0. As for the
racial aspect, there are a total of 75 Malay respondents who filled out the questionnaire. Next, 31 Chinese respondents
filled out the questionnaire, followed by 12 Indian respondents. This is because there are a significantly higher number
of Malay people living in Malaysia compared to either the Chinese or the Indian population. Last but not least, when
compared, students had the greatest response rate for employment status compared to other types of respondents, 78, all
of whom are students, constitutes 65% of the sample, while the number of employed respondents, 24, accounts for 20%.
Following that comes self-employment, which accounts for 12.5% of the workforce with 15 people. There are only three
people who said that they were unable to work, with 2.5 percent.
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Table 1. Demographic profile
Information
Frequency
Percentage
1
Gender
Male
59
50.9
Female
57
49.1
Total
116
100.0
2
Age (years)
Below 20
30
25.0
21 to 30
72
60.0
31 to 40
18
15.0
Total
120
100.0
3
Ethnicity
Malay
75
62.5
Chinese
31
25.8
Indian
12
10.0
Total
118
100.0
4
Highest Education Level
PMR
0
0
SPM / 0’Level
15
12.5
STPM/ A’ Level/foundation
45
37.5
Diploma
25
20.8
Bachelor Degree
26
21.7
Masters/MBA
8
6.7
PHD
1
0.8
Total
120
100.0
5
Employment status
Employed for wages
24
20.0
Self-employed
15
12.5
A student
78
65.0
Unable to work
3
2.5
Total
120
100.0
6.1 Descriptive Analysis
The mean value of technological readiness was observed to understand which elements are the most responsible for
their impact on customer satisfaction. It is generally accepted that the factor that has the most influence on the dependent
variable is the independent variable whose mean value is the highest. The mean score for customer trust is 4.42, and the
standard deviation is 0.43. This is the category with the highest score. As a result, customer trust has the biggest impact
on the perceived quality of the self-service experience, which has the greatest influence on customer happiness in
Malaysia. The fact that the mean score for all of the impacts of perceived quality of self-service experience on customer
satisfaction is more than three or neutral indicates that the respondents have a positive attitude about the questions posed.
Table 2. Descriptive analysis
Constructs
Mean
Standard
Deviation
Customer’s satisfaction (CS)
4.3917
0.41090
Perceived value (VA)
4.3833
0.43354
Customer trust (CT)
4.4250
0.42826
Technology readiness (TR)
4.3083
0.40054
6.2 Measurement model
In order to ensure convergent validity, the outer loading value must be greater than 0.70, and in order to calculate the
Average Variance Extracted or AVE, the values must be greater than 0.50. In the event that the value of outside loadings
is lower than 0.70, the entry will be removed. Due to the fact that the values are lower than 0.70, the item depicted in
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Figure 2 and Table 3 is thought to be removed. After removing the component below, all of the values have increased to
more than 0.70 at this point. These results accurately demonstrate convergent validity.
Figure 2. Initial path model
Table 3 presents the outers loading for four constructs including Customer’s satisfaction (CS), Customer trust (CT),
Perceived value (PV), and Technology readiness (TR)
Table 3. Outers loading
Constructs
Items
Loadings
Customer’s satisfaction (CS)
CS1
0.922
CS3
0.733
Customer trust (CT)
CT1
0.855
CT3
0.876
Perceived value (PV)
PV1
0.912
PV3
0.864
Technology readiness (TR)
TR1
0.900
TR3
0.832
Table 4 below summarises outer loadings, composite reliability, and Average Variance Extracted. From the table, all
composite values are higher than 0.60, which means that they are reliable. The values of AVE are more than 0.50, which
reflects good convergent validity.
Table 4. Internal consistency reliability and convergent validity results
Constructs
Items
Loadings
α
ρc
AVE
Customer
satisfaction (CS)
CS1
0.922
0.584
0.817
0.694
CS3
0.733
Customer trust (CT)
CT1
0.855
0.666
0.857
0.749
CT3
0.876
Perceived value (PV)
PV1
0.912
0.735
0.882
0.789
PV3
0.864
Technology
readiness (TR)
TR1
0.900
0.672
0.857
0.750
TR3
0.832
*Note: Item CS2, CS4, PV2, CT2, CT4, TR2 were removed to fulfil convergent validity threshold.
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According to Table 5, the value of customer trust over customer satisfaction is 0.289, the perceived value over
customer trust is 0.384, and technology readiness over perceived value is 0.315.
Table 5. Discriminant validity result (HTMT ratio)
CS
CT
PV
TR
CS
CT
.289
PV
.395
.384
TR
.145
.332
.315
6.3 Structural model
Table 6 shows the results of the hypotheses. Three hypotheses was tested. Two of the hypotheses in the research are
supported. This is because all the p-values are less than 0.05. As a result, it may be concluded that one of the hypotheses
put up in the research is not substantiated. For the p-value to be considered significant, it must be lower than the significant
value (0.05). As a result, customer trust does not have a positive association with customer satisfaction for hypothesis 1,
which examines the influence of the perceived quality of the self-service experience on customer satisfaction at
McDonald's Malaysia. The second hypothesis shows a favourable correlation between perceived value and overall
customer satisfaction. In hypothesis 3, being technologically prepared has a favourable relationship with the customer’s
trust.
Table 6. Hypothesized relationships (direct)
Relationships
VIF
β
SD
t -
value
p -
value
Confidence
Interval
Effect
Size
(f2)
Explanatory
Power (R2)
Decision
LL
UL
H1: CT → CS
1.051
0.007
0.105
1.027
0.305
0.097
0.317
0.012
0.111
Unsupported
H2: PV → CS
1.051
0.017
0.88
3.314
0.001
0.128
0.473
0.092
Supported
H3: TR → CT
1.000
0.013
0.093
2.503
0.012
0.075
0.418
0.057
0.054
Supported
*Note. SD = Standard Deviation, LL = Lower Limit, UL = Upper Limit, VIF = Variance Inflation Factor
7.0 DISCUSSION
Hypothesis 1 shows an insignificant effect of customer trust on customer satisfaction. This might be due to the context
of the study which might shows a lack of trust on self-service in McDonald’s. The technical readiness of the self-service
also has an effect how customers build trust on self-service. In Hypothesis 2, customers are more likely to have faith in
the business that provides a service when that service's quality is improved. After concluding that trust does not play a
role in the level of e-satisfaction customers experience, the logical next step is to investigate the hypothesis that technology
readiness plays a role in the level of e-satisfaction customers experience via the quality of self-service options. Customers
who have faith that a company will be able to fulfil their requirements are more inclined to approach that company to
form a collaborative collaboration. It is crucial for customers that the service provider they choose consider their
requirements and adjust to the shifting conditions both within and outside the organisation (Liu et al., 2008). Earning the
trust of your consumers is vital if you want to leave a lasting impact on them and raise the happiness they feel with your
business. There is widespread consensus among industry professionals that the degree to which a customer is at ease
utilising self-service options is one of the most important determinants of the overall quality of their experience (Boon-
itt, 2015).
It is better to improve the characteristics that generate consumer confidence since trust can have a good and large
effect on customer satisfaction. This is because trust can be earned in a variety of ways. In order to guarantee the highest
possible level of satisfaction for McDonald's customers, the company's self-service machines and other gadgets, including
their safety aspects, demand special attention. Multiple studies have pointed to a variety of elements that have a role in
determining the level of satisfaction experienced by McDonald's customers. Potential factors include the users'
perceptions of the service's usefulness and accessibility, as well as the users' own capabilities, the functionality of their
devices, the value and informative content of the service, and the service's efficiency in terms of both the users' own time
and the user's time. Many studies corroborated this idea, yet it was still rejectedFurthermore, additional questions might
have produced different outcomes as there were just three questions utilised to assess trust in this study.
In Hypothesis 3, the idea that one gets more for their money despite making fewer payments gives the impression of
value. The difference between the amount paid for an item or service and the degree to which the purchaser is pleased
with that item or service is what economists refer to as value. The combination of a low price and a high-quality result in
a favourable opinion of value. On the other hand, the functional value is an all-encompassing picture of the value
developed using empirical methods. According to the research findings, providing outstanding customer service has a
significant and favourable impact on customers' opinions of the product or service's value (Ho & Ko, 2008; Boon-itt,
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2015). The excellent experiences that customers have with financial services are a significant contributor to their overall
value. Customers who are pleased with the technology they are utilising can better get past the first learning curve and
recognise the advantages of using self-service processes. Customers value the absence of human involvement, the
convenience of self-service alternatives, the ability to save time and money, and the speed which technical solutions can
be implemented. If consumers are aware and appreciate these benefits, they will have a more favourable attitude on SSTs,
which will result in them judging the value of SSTs to be higher. The findings of Boon-itt (2015) and Hsu et al. (2013)
research lend credence to this argument.
Previous studies have shown that boosting a customer's perception of the value they receive for the money they spend
is one of the most effective ways to boost overall customer satisfaction with a product or service. As a result of the fact
that perceived value is a second-order factor, it follows that perceived quality must already exist before it can be taken
into consideration. In addition to this, the support of related theories and the approval of the work from academics such
as Boon-itt (2015), Lin (2007), and Hsu et al. (2013) provides additional evidence in favour of the second hypothesis
(H2). Thus, customers' perceptions of product quality significantly impact the value they place on the products they buy
and services they experience online.
8.0 CONCLUSIONS
The study's constraints require further explanation and could lead to potential areas for future investigation. The study
was designed to assess a theory that could appear impartial. However, construct validity was ensured in this study. This
study contributed to the practitioners, where managers can use this information to better understand the relationship
between consumers' technological sophistication and their perceptions of service quality and satisfaction. This prompts
management to deliberate thoroughly before acting. Identifying customers’ needs through observation is becoming
increasingly important as consumers become more enlightened and thus have higher expectations of the services they
use. More care should be taken to meet their client’s requirements. First, determining the clients' technological
competence helps service providers better meet their needs. Customers' feelings of gratitude will increase, leading to
stronger brand loyalty.
Both self-service quality and consumer perception of its worth, as well as self-service quality and technology
readiness, have the strongest correlation coefficients in the route analysis. This means that McDonald's and banks must
design self-service environments inclusive of customers of varying socioeconomic statuses and cultural backgrounds.
Authorities in developing countries should offer free training programmes to better prepare clients for the technological
advances that are taking place. McDonald's is recommended to lower the price of such services and build better
infrastructures to get an edge in the market, attract new customers, and retain existing ones. Many factors must be
considered in the design of such systems, including constant availability, straightforward installation and use, fool proof
functionality, and precise data capture and presentation. In this way, businesses can guarantee superior service to their
patrons.
The last recommendations come from a study of the correlation coefficients between customer trust and self-service
quality. This demonstrates that McDonald's may increase consumer trust by enhancing self-service quality. Due to this
situation, it is crucial to take into account variables like continual access, efficient launch and implementation, faultless
performance throughout the operation, no internet outage, and precise order-taking while designing such a system. It is
advised that consumers have constant, simple access to this platform because of the variables that contribute to the overall
perception of the self-service experience. It is important that McDonald's have a system in place that can dependably take
orders, get those orders to the kitchen, deal with any problems that may develop, speed things up with associated
procedures, and improve itself over time. Websites give users reliable information that is useful for making decisions.
The system must be monitored so that it does not take any action, and ways of misusing information on the internet must
be eliminated. McDonald's also has to improve the safety of its online infrastructure. Information pertaining to a
transaction should be kept secure.
Future research can investigate from the perspective of elaborating the theory by analysing more in-depth and with
rigorous data. Other national settings and industries can be further explored by future research.
9.0 ACKNOWLEDGEMENT
The authors thank Universiti Malaysia Pahang for funding this work under an RDU grant, RDU210301.
10.0 REFERENCES
Al-Hawari, M., Ward, T. and Newby, L., (2009), The relationship between service quality and retention within the
automated and traditional contexts of retail banking. Journal of Service Management, 2, 455-472.
Butkevičienė, V., Stravinskienė, J., & Rūtelionienė, A. (2008). Impact of consumer package communication on consumer
decision-making process. Engineering Economics, 56(1).
Barua, Z., Aimin, W. and Hongyi, X. (2018), A perceived reliability-based customer satisfaction model in self-service
technology. The Service Industries Journal, 38(7), 446-466.
Jalani et al. │ International Journal of Industrial Management │ Vol. 17, No. 4 (2023)
journal.ump.edu.my/ijim 193
Bitner, M.J., Ostrom, A.L. and Meuter, M.L. (2002), Implementing successful self-service technologies. Academy of
Management Perspectives, 16, 96-108.
Boon-Itt, S. (2015), Managing self-service technology service quality to enhance e-satisfaction. International Journal of
Quality and Service Sciences, 7 (4), 373-391.
Brian J. Taillon, Bruce A. Huhmann. (2019). Strategic consequences of self-service technology evaluations. Journal of
Strategic Marketing, 27(3)
Bai, C., Satir, A., & Sarkis, J. (2018). Investing in lean manufacturing practices: an environmental and operational
perspective. International Journal of Production Research, 1-15.
Belekoukias, I., Garza-Reyes, J. A., & Kumar, V. (2014). The impact of lean methods and tools on the operational
performance of manufacturing organisations. International Journal of Production Research, 52(18), 1-21.
Chavez, R., Yu, W., Jacobs, M., Fynes, B., Wiengarten, F., & Lecuna, A. (2015). Internal lean practices and performance:
The role of technological turbulence. International Journal of Production Economics, 160, 157-171.
Cherrafi, A., Elfezazi, S., Chiarini, A., Mokhlis, A., & Benhida, K. (2016). The integration of lean manufacturing, Six
Sigma and sustainability: A literature review and future research directions for developing a specific model.
Journal of Cleaner Production, 139, 828-846.
Dos Santos Bento, G., & Tontini, G. (2018). Developing an instrument to measure lean manufacturing maturity and its
relationship with operational performance. Total Quality Management & Business Excellence, 1-19.
Djelassi, S., Diallo, M. F., & Zielke, S. (2018). How self-service technology experience evaluation affects waiting time
and customer satisfaction? A moderated mediation model. Decision Support Systems, 111, 38–47.
Dabholkar, P. A. (1996). Consumer evaluations of new technology-based self-service options: an investigation of
alternative models of service quality. International Journal of Research in Marketing, 13(1), 29-51.
Dabholkar, P. A., & Bagozzi, R. P. (2002). An attitudinal model of technology-based self-service: moderating effects of
consumer traits and situational factors. Journal of the Academy of Marketing Science, 30(3), 184-201.
De Leon, M. V., Atienza, R. P., & Susilo, D. (2020). Influence of self-service technology (SST) service quality dimensions
as a second-order factor on perceived value and customer satisfaction in a mobile banking application. Cogent
Business & Management, 7(1).
Ekinci, Y., Dawes, P. L., & Massey, G. R. (2008). An extended model of the antecedents and consequences of consumer
satisfaction for hospitality services. European Journal of Marketing, 42(1/2), 35-68.
Gelderman, C. J., Paul, W. T., & Van Diemen, R. (2011). Choosing self-service technologies or interpersonal services—
The impact of situational factors antechnology-related attitudes. Journal of Retailing and Consumer
Services, 18(5), 414-421.
Gunawardana, H. M. R. S. S., & Perera, W. L. M. V. (2015). Impact of self service technology quality on customer
satisfaction: A case of retail banks in Western Province in Sri Lanka. Gadjah Mada International Journal of
Business, 17(1), 1-24.
Galdolage, B. S. (2020). Do it yourself: Customer self-directed learning in self-service technologies.
Galdolage, B. S. (2022). Customers' Technology Know-How and Error-Correction Capability in using Self-Service
Technologies. Vidyodaya Journal of Management, 8(1).
Hsiao, W. H., & Chang, T. S. (2014). Understanding consumers’ continuance intention towards mobile advertising: a
theoretical framework and empirical study. Behaviour & Information Technology, 33(7), 730-742.
Ing, P.G., Zheng Lin, N., Xu, M. and Thurasamy, R. (2020), Customer loyalty in Sabah full service restaurant. Asia
Pacific Journal of Marketing and Logistics, 32(7), 1407-1429.
Johns, R. and Perrott, B. (2008), The impact of internet banking on business‐customer relationships (are you being self‐
served?). International Journal of Bank Marketing, 26(7), 465-482.
Kuvykaite, R., Dovaliene, A., & Navickiene, L. (2009). Impact of package elements on consumer’s purchase
decision. Economics and management, (14), 441-447.
Kheng, L. L., Mahamad, O., & Ramayah, T. (2010). The impact of service quality on customer loyalty: A study of banks
in Penang, Malaysia. International Journal of Marketing Studies, 2(2), 57.
Liu, C., & Hung, K. (2022). Improved or decreased? Customer experience with self-service technology versus human
service in hotels in China. Journal of Hospitality Marketing & Management, 31(2), 176–204.
Minglong Li, Dexiang Yin, Hailian Qiu, Billy Bai. (2022) Examining the effects of AI contactless services on customer
psychological safety, perceived value, and hospitality service quality during the COVID‐19 pandemic. Journal of
Hospitality Marketing & Management, 31(1).
Meuter, M. L., Bitner, M. J., Ostrom, A. L., & Brown, S. W. (2005). Choosing among alternative service delivery modes:
An investigation of customer trial of self-service technologies. Journal of Marketing, 69(2), 61-83.
Jalani et al. │ International Journal of Industrial Management │ Vol. 17, No. 4 (2023)
journal.ump.edu.my/ijim 194
Meuter, M. L., Ostrom, A. L., Roundtree, R. I., & Bitner, M. J. (2000). Self-service technologies: understanding customer
satisfaction with technology-based service encounters. Journal of marketing, 64(3), 50-64.
Mitra, A., & Sahoo, D. (2015). The impact of customer’s perceived service innovativeness on image congruence,
satisfaction and behavioral outcomes. Journal of Hospitality and Tourism Technology, 6(3), 288-310.
Murphy, P. T., Clogher, L., Van Laar, A., O’Regan, R., McManus, S., McIntyre, A., … Hallahan, B. (2022). The impact
of service user’s suicide on mental health professionals. Irish Journal of Psychological Medicine, 39(1), 74–84.
Park, S., Lehto, X., & Lehto, M. (2021). Self-service technology kiosk design for restaurants: An QFD application.
International Journal of Hospitality Management, 92,
Paulssen, M., Brunneder, J., & Sommerfeld, A. (2019). Customer in-role and extra-role behaviours in a retail setting: The
differential roles of customer-company identification and overall satisfaction. European Journal of Marketing,
53(12), 2501-2529.
Pooya, A., Abed Khorasani, M., & Gholamian Ghouzhdi, S. (2020). Investigating the effect of perceived quality of self-
service banking on customer satisfaction. International Journal of Islamic and Middle Eastern Finance and
Management, 13(2), 263-280.
Raheman, K. U. (2017). Perceptions of service quality and the impact on adoption of self-service technologies. South
Asian Journal of Marketing & Management Research, 7(1), 4-16.
Shahid Iqbal, M., Ul Hassan, M., & Habibah, U. (2018). Impact of self-service technology (SST) service quality on
customer loyalty and behavioral intention: The mediating role of customer satisfaction. Cogent Business &
Management, 5(1).
Strutt, P. A., Johnco, C. J., Chen, J., Muir, C., Maurice, O., Dawes, P., … Wuthrich, V. M. (2022). Stress and Coping in
Older Australians During COVID-19: Health, Service Utilization, Grandparenting, and Technology Use. Clinical
Gerontologist, 45(1), 106–119.
Tzavlopoulos, Ι., Gotzamani, K., Andronikidis, A., & Vassiliadis, C. (2019). Determining the impact of e-commerce
quality on customers’ perceived risk, satisfaction, value and loyalty. International Journal of Quality and Service
Sciences, 11(4), 576-587.
Taylor, S. A., & Hunter, G. L. (2002). The impact of loyalty with e‐CRM software and e‐services. International journal
of service industry management, 13(5), 452-474.
Ugwuanyi, C. C., Uduji, J. I., & Oraedu, C. (2021). Customer experience with self-service technologies in the banking
sector: Evidence from Nigeria. International Journal of Business and Systems Research, 15(4), 405–425.
Wang, C., Harris, J., & Patterson, P. G. (2012). Customer choice of self‐service technology: the roles of situational
influences and past experience. Journal of Service Management, 23(1), 54-78.
Wu, X., Gursoy, D., & Zhang, M. (2021). Effects of social interaction flow on experiential quality, service quality and
satisfaction: moderating effects of self-service technologies to reduce employee interruptions. Journal of
Hospitality Marketing & Management, 30(5), 571-591.
Wang, X., Wong, Y. D., Sun, S., & Yuen, K. F. (2022). An investigation of self-service technology usage during the
COVID-19 pandemic: The changing perceptions of ‘self’and technologies. Technology in society, 70.
Winner, J. G., Carhart, J. M., Altar, A., Allen, J. D., & Dechairo, B. M. (2013). A prospective, randomized, double-blind
study assessing the clinical impact of integrated pharmacogenomic testing for major depressive
disorder. Discovery medicine, 16(89), 219-227.
