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Queuing Theory and Customer Satisfaction: A Review of Terminology, Trends, and Applications to Pharmacy Practice



Queuing theory is the formal study of waiting in line and is an entire discipline in operations management. This article will give the reader a general background into queuing theory its associated terminology and it relationship to customer satisfaction. Queuing theory has been used in the past to assess such things as staff schedules, working environment, productivity customer waiting time, and customer waiting environment. In pharmacy, queuing theory can be used to assess a multitude of factors such as prescription fill-time, patient waiting time, patient counseling-time, and staffing levels. The application of queuing theory may be of particular benefit in pharmacies with high-volume outpatient workloads and/or those that provide multiple points of service. By better understanding queuing theory service managers can make decisions that increase the satisfaction of all relevant groups - customers, employees, and management.
Hospital Pharmacy 275
Queuing Theory and
Customer Satisfaction: A Review
of Terminology, Trends, and
Applications to Pharmacy Practice
Ronald Anthony Nosek, Jr., MS* and James P. Wilson, PharmD, PhD†
Hospital Pharmacy
Volume 36, Number 3, pp 275–279
2001 Facts and Comparisons
aiting in lines or
“queues” seems to be an
American pastime.
Think about the many
times you had to wait in line in the last
month or year and the time and frustra-
tion that was associated with those
waits. Whether we are in line at the gro-
cery store checkout, the barbershop, the
stoplight, or in the pharmacy, “waiting
our turn” is part of our everyday life.
Queuing theory is the formal study
of waiting in line and is an entire disci-
pline within the field of operations
management. The purpose of this arti-
cle is to give the reader a general back-
ground into queuing theory and queu-
ing systems, its associated terminology,
and how queuing theory relates to cus-
tomer satisfaction. Also, past and pre-
sent applications of queuing technology
and what pharmacies can do to manage
patient or customer queues more effec-
tively will be discussed. Finally, auto-
mated queuing technology will be
Queuing theory utilizes mathemat-
ical models and performance measures
to assess and hopefully improve the
flow of customers through a queuing
Queuing theory has many
applications and has been used exten-
sively by the service industries. Queu-
ing theory has been used in the past to
assess such things as staff schedules,
working environment, productivity,
customer waiting time, and customer
waiting environment. In pharmacy,
queuing theory can be applied to assess
a multitude of factors such as prescrip-
tion fill-time, patient waiting time,
patient counseling time, and pharmacist
and technician staffing levels. The
application of queuing theory may be
of particular benefit in pharmacies with
high-volume outpatient workloads
and/or those that provide multiple
points of service, such as those in the
Abstract — Queuing theory is the formal study of waiting in line and is an
entire discipline in operations management. This article will give the reader a
general background into queuing theory, its associated terminology, and it
relationship to customer satisfaction. Queuing theory has been used in the past
to assess such things as staff schedules, working environment, productivity,
customer waiting time, and customer waiting environment. In pharmacy, queu-
ing theory can be used to assess a multitude of factors such as prescription fill-
time, patient waiting time, patient counseling-time, and staffing levels. The
application of queuing theory may be of particular benefit in pharmacies with
high-volume outpatient workloads and/or those that provide multiple points of
service. By better understanding queuing theory, service managers can make
decisions that increase the satisfaction of all relevant groups — customers,
employees, and management.
Key Words — customer satisfaction; queuing
Hosp Pharm — 2001;36:275–279
*Pharmacy Department, The National Naval Medical Center, Bethesda, Maryland, 20889; (Ronald A. Nosek, Jr., LCDR, MSC, USN is an active duty pharma-
cist in the United States Navy. At the time of writing this article he was attending the University of
Texas as a full time student in Navy’s Duty Under Instruction program); †Assistant Professor, Pharma-
cy Practice and Administration Division, The University of Texas College of Pharmacy, Austin, TX; Address correspondence to Dr. James P. Wilson, Pharmacy Practice and
Administration Division, PHR 2.212 – Mail Code A1930, Austin, TX 78712;
The opinions or assertions herein are the private views of the authors and are not to be construed
as official or reflecting the views of the U.S. Department of the Navy or the Department of Defense.
276 Volume 36, March 2001
Queuing Theory: A Review
Department of Veterans Affairs (VA),
Department of Defense (DoD), univer-
sity health systems, and managed care
organizations. Problematic queuing
systems (ie, long lines) can lead to the
customers perceptions of excessive,
unfair, or unexplained waiting time—
resulting in significant detrimental
effects on the customer’s overall satis-
faction with the service transaction.
On the surface it may seem like
queuing is just simply waiting in a line.
To most customers, the waiting experi-
ence is all that matters. However, wait-
ing in line is just a part of the overall
queuing system. A queuing system
(also known as a processing system)
can be characterized by four main ele-
ments: the arrival, the queue discipline,
the service mechanism, and the cost
The arrival is the way in which a
customer arrives and enters the system
for service. Whenever customers arrive
at a rate that exceeds the processing
system rate, a line or queue will form.
Arrivals may come in singly or in
batches; they may come in consistently
spaced or in a completely random man-
ner. A potential customer can also leave
if, on arrival, he or she finds the line too
long—this is called balking.
The queue discipline is the rule for
determining the formation of the line or
queue and the order in which jobs are
processed. There may only be one line
and jobs are processed First-In, First-
Out or FIFO. Others may have more
than one line to give certain customers
priority such as express lanes in grocery
The service mechanism describes
how the customer is served. It includes
the number of servers and the duration
of the service time—both of which may
vary greatly and in a random fashion.
The service time may be similar for
each job or it could vary greatly.
The cost structure specifies the
payment made by the customer and the
various operating costs of the system.
Other elements that impact the queue
structure and performance include the
number of service stations and the
number and speed of servers.
Pharmacy, like other service-ori-
ented industries, functions in an
increasingly competitive environment.
Speed of service has been shown to
provide businesses a competitive
advantage in the marketplace.
In addi-
tion, the literature reveals several stud-
ies documenting customer dissatisfac-
tion with long waiting times and indi-
cates that this is a pervasive problem in
pharmacy practice and a common
source of anxiety and dissatisfaction
among customers and, in many cases,
Speed of delivery is being empha-
sized increasingly and can be partly
attributed to increased competition and
the value a customer places on his or
her time. We live in a society who has
come to expect film development and
eyeglasses to be ready in an hour or
less. A brief story told from the cus-
tomers perspective will help to further
illustrate this point:
I just arrived at my local pharma-
cy to get a new prescription filled and
to pick up a few other things. There is a
line of four people at the register and
another six people sitting in the waiting
area. By the time I get to the counter to
hand the cashier/technician my pre-
scription, 5 minutes have passed. I ask
how long the wait will be and I am told
30 to 40 minutes. I go about my shop-
ping and return to the pharmacy 35
minutes later. Again, there are people in
line at the register and it takes me
another 5 minutes to find out that my
prescription is not ready. Feeling weary
and somewhat frustrated, I have a seat
in the waiting area. As I sit there, I
watch people come and go and wonder,
“Wasn’t I here before that guy?” At last
my name is called! I pay the cashier
and my pharmacy encounter is com-
plete. However, I don’t feel good about
it. Why did I have to wait so long? Did
others get special priority over me?
Maybe another pharmacy will service
my needs better? Am I a satisfied cus-
Queuing management has been
applied very successfully in many ser-
vice-oriented industries. L. L. Bean, a
large telemarketer and mail-order cata-
log house for high-quality sporting
goods and apparel, used queuing theory
to optimize staffing levels — resulting
in an estimated $500,000 per year sav-
The Department of Motor Vehi-
cles in Virginia and Arizona used queu-
ing technology to virtually eliminate
long lines and greatly improve cus-
tomer satisfaction. In addition, they
were able to significantly improve
employee morale and reduce operating
Queuing models have also been
used to plan staffing levels in an outpa-
tient hospital laboratory department
and a centralized appointment depart-
ment in Lourdes Hospital in Bingham-
ton, New York. Queuing models were
used to identify an optimal configura-
tion of capacity and staffing levels for
both departments. The lengthy delays
in answering telephone calls in the cen-
tralized appointments department were
completely eliminated by rearranging
work shifts of current employees.
The Virginia Mason Medical Center in
Seattle, Washington used queuing theo-
ry and other classic quality manage-
ment principles to drastically reduce
patient waiting time for appointments
(42 days to 13), emergency room triage
time (45 minutes to 15), and increased
staff morale.
Queuing theory has been used
extensively in the banking industry to
increase business by careful placement
of merchandising materials while at the
Hospital Pharmacy 277
same time alleviating both the actual
and perceived amount of time a cus-
tomer spends waiting in line.
queuing theory has been applied to
computer simulation models to help
with business decisions and prob-
In general, customer satisfaction is
multifactorial and is considered a part
of overall consumer behavior model.
Consumer behavior evolves over time
and is influenced by many factors. Sev-
eral key factors that greatly influence
satisfaction include consumers expec-
tations, attitudes, and intention about
the service provided.
Expectations are the consumers
anticipated beliefs about a product or
service prior to the interaction. Atti-
tudes consist of the consumers evalua-
tions, emotional feelings, and action
tendencies toward a product or service
that has developed over time. Intentions
are the decisions the consumer makes
about future actions toward the firm
producing the product or service.
Together, these factors influence the
future behavior or the actual future
action taken by the customer.
For the most part, these factors are
intangible so it is the perceived perfor-
mance rather than the actual perfor-
mance that is more critical to customer
satisfaction. The main goal of queuing
management is to maximize the level of
customer satisfaction with the service
provided. Therefore, the primary issue
in queuing management and customer
satisfaction is not the actual amount of
time a customer waits for service, but
the customers perception about that
wait and the associated level of satis-
faction. A highly satisfied customer
will be very likely to provide repeat
business and spread the positive experi-
ence by word of mouth (advertising),
resulting in increased revenues and
profitability. Conversely, a dissatisfied
customer will most likely not provide
repeat business and will be more than
willing to share his or her bad experi-
ence with whoever will listen. This will
have an obvious negative impact on
profits and revenues.
Customer satisfaction has been
defined as the difference between the
customers perceptions of the experi-
ence and his or her expectations, which
is many times based on past experience.
Although it is possible to manage and
decrease actual waiting time and to
some extent to manage customer
expectations about customer satisfac-
tion, managing the customers percep-
tion of the queuing experience can be
the vital element in satisfaction with the
service interaction.
The measurement
of customer satisfaction as it relates to
waiting time is highly qualitative and
subjective, and the relationship is gen-
erally inverse in nature (ie, in general,
as waiting time decreases, satisfaction
increases). This relationship was fur-
ther expanded by Maister who, in 1985,
postulated that satisfaction is dependent
on customer perception and customer
Numerous scientific studies, jour-
nal articles, and text books have been
published describing the relationship
between customer satisfaction, waiting
time, and consumer behavior.
example, one study examined customer
attitudes toward waiting times in the
hotel and restaurant industry and found
that over 70% of all respondents were
clearly concerned about waiting times.
In fact, those most concerned about
waiting times were generally more
willing to pay more to avoid waiting in
line and believed that quality is worth
waiting for. The results of this survey
indicate that queues do affect the satis-
faction level of customers and their
willingness to spend. In addition, this
study also suggests that there is a point
where a lengthy wait begins to affect
the customers perception of quality.
Another study examined patient
satisfaction with outpatient pharmaceu-
tical services at a large university hos-
pital. This study reported that of the
patients who received prescriptions
from university physicians and did not
fill them at the university pharmacy,
21% went elsewhere to have their pre-
scription filled because of the long
waiting time, even though prescription
prices were less expensive through the
university system.
Similarly, another
study conducted in a large Veterans
Affairs hospital reported that pharmacy
redesign improved patient satisfaction
because of a 50% decrease in patient
waiting time.
Finally, another article
describes the relationship between
waiting time and satisfaction in the con-
text of social justice or injustice, as the
case may be.
Queuing theory and its application
has gotten very little attention from
pharmacy operations management;
however, pharmacy practice could ben-
efit by understanding and applying
some of the concepts of queuing theory.
A publication, Operations Man-
agement for Pharmacists, briefly dis-
cusses queuing theory and customer
wait-time management. The authors
appropriately acknowledged that the
advanced mathematical models used in
queuing theory were beyond the scope
of the book. Unfortunately, the only
suggestion offered by the authors for
managing perceived waiting time is to
distract the customer by providing
entertainment, refreshments, or com-
fortable conditions, such as television
and coffee in the waiting area.
A literature search revealed few
published articles in the area of phar-
macy practice and queuing theory.
Donehew and colleagues used queuing
theory to address prescription queues
and work measurement assessment of
prescription fill times.
Boyce and colleagues sought to deter-
Queuing Theory: A Review
278 Volume 36, March 2001
mine the impact of a computerized
waiting time program on order turn-
around time in a hospital pharmacy.
Perhaps the most common and
useful application of queuing theory in
pharmacy operations is to reduce
patient waiting time and maximize staff
effectiveness. Lin and colleagues used
workflow analysis and times study to
identify factors leading to excessive
waiting times in an ambulatory phar-
macy at the University Hospital Inc.
(TUH), Cincinnati, Ohio.
In another
study, also by Lin, work measurement
and computer simulation were used to
assess the re-engineering of community
pharmacies to facilitate patient counsel-
Although queuing theory was
never mentioned in these articles, the
authors used many concepts similar to
queuing theory’s and their results could
be instrumental in designing queuing
applications for reducing patient wait-
ing time and improving staff utilization.
In a study by Moss, queuing theo-
ry was used to assess the relationships
among the number of pharmacy staff
members, prescription dispensing
process, and outpatient waiting times.
He used a mathematical queuing model
to estimate the probability of waiting
time exceeding a given value, when
prescription arrival and service rates
and number of servers are known. The
study revealed that the major factors
determining outpatient waiting time
were the arrival pattern of prescriptions
at the pharmacy, sequencing of work,
and percentage of staff at work.
Finally, Vemuri used computer
simulation with a queuing model to
assess patient waiting time in the outpa-
tient pharmacy at the Medical College
of Virginia. This study concluded that
the most significant factor contributing
to patient waiting times was the interac-
tion between pharmacy service
providers, specifically the typist and the
Many different mathematical
equations can be used to describe queue
formation and behavior; however, the
decision to choose one over the other is
beyond the scope of this article.
Although Moss
provided the mathe-
matical formula used in his research,
most queuing research applications are
now completed through some form of
computerization due to the complexity
of the models and the accessibility of
off-the-shelf software and personal
It is true that many pharmacies do
not experience problems with queues.
However, there are many pharmacies
that do experience difficulties with
queue formation. For example, pharma-
cies that experience high-volume pre-
scription workload frequently have dif-
ficulty in managing workflow and wait-
ing times. This could also be true in
pharmacies that offer their customers
multiple points of service (ie, bank
teller design). Pharmacies such as those
in large managed care organizations,
university health systems, and those in
the VA and DoD typically fit this
It is safe to say that the traditional
methods employed by pharmacies to
distract customers (eg, comfortable
waiting area, coffee, and television)
would be of limited benefit in pharma-
cies that fill in excess of 1,000 prescrip-
tions per day and have patient waiting
times that commonly exceed 1 to 2
Recently, however, automated
queuing technology has been success-
fully developed and applied in areas of
pharmacy practice that specifically
address customer waiting times. Prior
to this innovation, the most advanced
queuing applications to manage cus-
tomer waiting times in pharmacies was
a consecutive number ticketing system
commonly found in barber shops and
grocery stores.
Automated queuing technology
(AQT) is primarily utilized in the feder-
al sector and includes numerous phar-
macies in the DoD and the VA. Howev-
er, several prominent nonfederal phar-
macy organizations utilize AQT,
including the University of North Car-
olina, Medical College of Virginia,
Jewish Hospital in Cincinnati, and
Parkland Hospital in Dallas, just to
name a few.
Both the DoD and the VA
operate very busy outpatient pharmacy
departments, some filling in excess of
2,500 outpatient prescriptions and ser-
vicing over 1,000 patients daily.
Automated queuing systems are
typically PC based systems that can
track a multitude of useful information
that was previously very difficult to
quantify for pharmacy managers. Phar-
macies utilizing AQT can easily track
variables such as customer arrival and
departure time, patterns of arrival, pre-
scription fill time, waiting time, and
individual staff member productivity.
In addition, AQT can track numerous
points of service and different service
categories (ie, certain patients may get
priority service or can be used to track
patient counseling) if desired.
Finally, AQT can also provide
pharmacy customers with information
that can directly improve their queuing
experience, such as with a ticket with a
unique number and the estimated wait
time. This makes for a less confusing,
more relaxed, and much more positive
waiting environment for the patient. At
the time this article was submitted for
publication, only one company, the Q-
Matic Corporation, that distributes
automated queuing technology systems
could be identified. Their website
address is
Queuing theory is a powerful man-
agement tool that often gets over-
looked, especially in pharmacy opera-
tions management. Proper application
Queuing Theory: A Review
Hospital Pharmacy 279
Queuing Theory: A Review
of this effective management tool can
yield impressive results. There are vol-
umes of additional material on queuing
theory and in fact this paper has only
touched the surface. The goal of this
paper was to give the reader a general
understanding of concepts, current
technology, and applications of queuing
theory as it relates to customer satisfac-
tion and waiting time.
Undoubtedly, there are numerous
factors—physical, psychological, and
emotional, to name a few—that affect a
customers perception of the waiting
experience. By better understanding
queuing theory and the various mea-
sures associated with customer waiting
time, service managers can make deci-
sions that have a beneficial impact on
the satisfaction of all relevant partici-
pants: customers, employees and man-
agement. There are several tools such
as computer simulation, modeling , and
automated queuing technology that can
assist in this process improvement
Waiting in line will always be
prevalent in our society and in our phar-
macies. As the health care industry con-
tinues to evolve, pharmacists are under
continued and growing pressure to do
more and more. Wouldn’t it be nice to
practice pharmacy in a setting where
the worry and burden of wait time man-
agement was eased, even eliminated —
keeping customers happy and decreas-
ing the anxiety of those behind the
counter trying to provide the best phar-
macy service?
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... Effective scheduling and sequencing have become more crucial recently, according to Nosek and Wilson (2001). This rise is partly attributable to the acceptance of just-in-time and lean manufacturing. ...
... Vohra (2017), in his empirical study titled "Application of Operations Research Technique in Effective Management," unraveled the fact that the scheduling and sequencing technique is the least embraced method in many African counties. This brings about issues of ignoring the methods despite the benefits, as Nosek and Wilson (2001) highlighted. Fashion design outlets are a core sector where customer waiting is peculiar. ...
... According to an expert, service scheduling becomes more challenging when more than one resource must be coordinated and scheduled. Cancellations are frequent and can further disrupt and confuse the scheduling process, making matters more difficult (Nosek & Wilson, 2001). Jonah (2017) emphasised the scheduling and sequencing presumptions, which might only be true occasionally. ...
... McClain (1976) investigated the research on applying the queueing system in bed assignment policies and its effect on utilization, waiting time, and the probability of turning away patients [25]. The application of this theory in pharmacy is reviewed by [26]. ...
... Constraint (26) calculates the expected total number of patients in part . ...
Full-text available
One of the patients' basic needs when referring to the hospital is to access doctors as soon as possible at a low cost. In this regard, many hospital managers aim to improve healthcare quality. They strive to plan and perform better patient flow in different parts of hospitals. With the widespread of Covid-19, the importance of this matter has become more apparent. Queueing systems are one of the methods that help recognize delays and help to identify bottlenecks. This paper has extended a queue theory model to measure the number of servers in each part of the hospital. The model aims to reduce the hospital's expected total cost, including the waiting time cost of the patients in queues, idle server cost, operating, and the marginal cost of the servers, in a covid-19 pandemic. The proposed model has been solved with Grasshopper Optimization Algorithm (GOA) for large-scale data. Then sensitivity analysis is presented to understand the model better and identify effective parameters.
... The important element that needs to be defined in queuing theory is arrival rate, service rate and utilization (Allen, 1980;Gross, 2008). When implementing the queuing system in an intelligent manner waiting times and customer satisfaction will be improved (Nosek Jr & Wilson, 2001). In order to improve queuing systems, it must be understood in-depth and queuing theory is used to do this, which leads to a Queuing Management System. ...
Purpose: This paper aimed to improve and optimize the overall performance of the banking service system using queue theory in various activities whilst maximizing profits. Research Methodology: Based on previous literature and interview with related experts, the initial status of the banking system is analyzed as well as the methodologies of queue theory. The data was analyzed to modeling queuing systems for understanding queuing behavior using Wittness Software for simulation. Different queuing strategies will be implemented using the waiting time to find the most efficient solution and the optimized result is concluded. Result: In this paper, the performance of the banking system is investigated and improved by the queuing theory. The sensitive analysis approach will provide new solutions for the optimization of the bank queuing, which could later be implemented for better banking performance. Based on the results obtained, the recommended method produces the best customer satisfaction and maximizes profits. The results of the paper enable decision-makers to obtain useful results with enough knowledge of the behavior of the system. Limitation: This research only described the Iranian bank system. There is different limitation regarded as external factors that varies from one banking system to another and many works are needed to further combat the problems faced by the banking sectors. Contribution: The results are a guideline for managers or decision makers and help them shorten cycle time and to save costs, and resolve problems. It also serves as a useful base for researchers to expand further research concerning the problems of the banking system in other organizations. Keywords: 1. operation system 2. queue theory 3. optimization of the banking system
... Negative experiences within socially distanced queues may cause customers to leave, or shop elsewhere next time. Studies prior to the COVID-19 pandemic have shown that negative queueing experiences have caused individuals to leave queues early, or avoid them altogether [76,77], causing their future shopping choices to change due to the negative emotions they felt [78]. During the COVID-19 pandemic, customers may generally have been experiencing more anxiety in their everyday lives [1][2][3][4], and associating more threat with queueing and waiting environments [33]. ...
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The COVID-19 pandemic increased global anxiety, and many people shopped less frequently. This study quantifies customer preferences in where to shop while following social distancing regulations, specifically focusing on customers’ anxiety. Collecting data online from 450 UK participants, we measured trait anxiety, COVID-19 anxiety, queue awareness, and queue safety preferences. Confirmatory factor analyses were used to develop novel queue awareness and queue safety preference variables from new items. Path analyses tested the hypothesised relationships between them. Queue awareness and COVID-19 anxiety were positive predictors of queue safety preference, with queue awareness partially mediating the effect of COVID-19 anxiety. These results suggest that customers’ preferences for shopping at one business and not another may depend on safe queueing and waiting conditions, especially in those more anxious about COVID-19 transmission. Interventions that target highly aware customers are suggested. Limitations are acknowledged and areas for future development are outlined.
... The real life application of queuing mathematical theory enhances faster services, improving traffic flow in the clinics and reduce patients' waiting time. It has the ability to accommodate random variation in patients' arrival time and helps the system focused on the well-being and life of the clients/ patients (Nosek, and Wilson, 2001). ...
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This study examine the application of mathematical theory in the effective Management of outpatient services in a Federal University Teaching Hospital in South-South Geo-Political zone, Nigeria. The researchers prepared the ground for the study by identifying the research problem, the study objectives and research questions. Three hypothesis were framed for the study and a well-designed questionnaire was prepared and three hundred and twenty eight copies (328) were distributed to patients during outpatient clinic session for completion. The completed questionnaire were returned and data extracted for analysis. Percentage was used to compare the responses, using structured questionnaire. The result of the study revealed that: queuing of patients enhanced efficient service provision at the outpatient clinic of the Teaching Hospital; application of queuing mathematical theory improve patients' waiting time and queuing mathematical theory can serve as a suitable model for managing congestion at the outpatient clinic of the Teaching Hospital. Recommendations were proffered for implementation.
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Rumah Sakit Lotim Medical Center merupakan Rumah Sakit Swasta yang teletak di Kabupaten Lombok Timur. Aspek kepuasan pelanggan dapat menjadi indikator kualitas produk barang atau jasa yang ditawarkan sehingga produsen dapat terus meningkatkan mutu produk dan layanannya agar kepuasan dapat tercapai. Salah satu aspek layanan di Rumah Sakit yang dapat meningkatkan kepuasan pelanggan adalah waktu tunggu pelayanan atau sistem antrian. Ketidakpastian dalam proses antrian atau waktu tunggu seringkali menjadi masalah di dalam pelayanan kesehatan. Sistem antrian yang digunakan oleh Poliklinik Interna Rumah Sakit Lotim Medical Center adalah Single Channel Single Phase, sedangkan disiplin antrian yang digunakan adalah First Come First Serve. Waktu tunggu layanan adalah 55.2 menit masih memenuhi standar waktu tunggu layanan yang ditentukan yaitu 60 menit. Kinerja sistem antrian kurang optimal karena utilitas atau kegunaan server melebihi kapasitas pada jam-jam serta hari-hari tertentu dan probabilitas tidak ada pasien dalam antrian cukup tinggi pada jam-jam dan hari-hari tertentu, sehingga implikasi manejerial yang ditawarkan adalah perbaikan sistem dengan cara mengatur distribusi kedatangan dan melakukan pembatasan jumlah pasien perhari.
The main objective of the study is to find out how queue management affects the level of customer satisfaction in the case of Commercial Bank of Ethiopia. The study tried to discover the impact of queue management in the Bank on the behavior of consumers the article is carried out in the following logical sequence: the nature and impact of queue management on customer satisfaction, evaluation of queue management mechanisms used, the key problems that face commercial Bank of Ethiopia in the implementation and administering of queue management. The methodological tools of the work include: the method of questioning (to collect primary information from both the client base and operational managers), descriptive statistics and STATA (for data analysis based on analytical statistical tools – frequency distribution tables, cross-tabulation), regression model (to determine the influence of independent variables on the dependent value). Independent factors are presented by the author in the form of waiting environment, perception of waiting time, the information provided to the client from the commercial Bank and queue discipline, dependent indicator – the level of customer satisfaction. As a result of the study, the author concludes that the majority of clients of the commercial Bank of Ethiopia are not satisfied with the current mechanisms of the queue management. The paper states that the key factor influencing customer satisfaction is the waiting time. The study empirically confirms that the Bank’s customers are not satisfied with the information that comes into the waiting room, and the conditions of waiting in banks. The author states the following reasons for dissatisfaction with the mechanisms of queue management on the part of customers: the use of a physical bank, manual queue measurement systems, poor-quality Internet banking, and mobile banking. The paper substantiates recommendations for Ethiopian commercial banks to increase their additional investment in queue management mechanisms, which will contribute to increasing customer satisfaction through the introduction of warning and alarm systems, the use of interactive communication, and advertising on television screens. Keywords: Commercial Bank, Customer satisfaction, Queue management mechanisms.
This work seeks to augment policy directions on single-digit inflation rates convergence. The paper resorted to both univariate and multivariate forecasting procedures to predict the inflation rates of the member countries in the West African Monetary Zone (WAMZ) area, on the proposed date for the introduction of the Eco. Essentially, we did not find enough evidence that the introduction of the Eco will materialize on the set date. The paper cautions against a hasty introduction of the Eco. WAMI should therefore continue to create avenues for assisting member countries to improve their macroeconomic dynamics.
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The purpose of this study was to determine how well Federal Medical Centre (FMC) Gusau manage queue during COVID-19 pandemic in relation to patient satisfaction. The study used primary data through questionnaire where a sample of 270 registered patients in this hospital were randomly selected and provided with the questionnaires to answer questions but only 268copies of questionnaires were retrieved. The research was conducted between September, 2020 and October, 2020. Queue management was studied using waiting time for service, the waiting environment conditions and service quality in relation to customer satisfaction. Regression analysis was employed in analysing data for the study. The findings indicated that a significant percentage of the patients were dissatisfied with the way queues were managed at Federal Medical Centre Gusau. The results from the regression analysis shows that all the three dimensions of service quality have significant effect with the patient's satisfaction. While service quality, and waiting environment were positively correlated overall satisfaction patients towards service provided at the hospital, but the waiting time had negative effect on the patients' satisfaction.
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This study analyzes the contributions and applications of queuing theory (QT) in the field of health service management problems. This review presents a classification system of healthcare examined with the aid of queuing models. The purpose of this is to analyze the contributions and applications of QT in the field of problem management in health services and to give indications of when and how to use QT in order to enhance daily management decisions. A literature review was carried out to investigate the health areas supported by queuing models, searching articles that described problem models and their topics or keywords related to QT and population health or health problems. The present study analyzed 314 articles that address the applications of QT in healthcare management between 2014 and 2020. This review demonstrates that QT can contribute to the improvement of health services and provide resource managers to achieve this improvement. A discussion of why, when, and requirements to apply QT is presented.
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Lourdes Hospital uses a centralized system to schedule appointments by phone for outpatients, inpatients, and other ambulatory services requested by physicians, their staff, hospital personnel, and patients. Customer surveys and an increase in customer complaints revealed lengthy delays in answering telephone calls. We used a queuing model to find the optimal staffing levels to handle the variation in call arrivals within a day. The problem was solved by just rearranging the work shifts, without adding any staff. We also provide an easy-to-reference generalized queuing table to aid others in deciding staffing levels where M/M/c approximation is appropriate.
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Queueing environment and feedback regarding the likely magnitude of the delay can also influence customer attitudes and ultimately, in many instances, a firm's market share. Even if we focus on the wait itself, the 'outcome' of the queueing experience may vary nonlinearly with the delay, thus reducing the importance of average time in queue, the traditional measure of queueing performance. This speculative paper uses personal experiences, published and unpublished cases, and occasionally 'the literature' to begin to organize our thoughts on the important attributes of queueing.
A quality improvement approach incorporating the techniques of workflow analysis and time study was used in a study of excessive patient waiting time in a hospital's outpatient pharmacy. Investigators identified factors contributing to long waits by observing and timing pharmacy dispensing procedures. The results of the time study indicated that two-thirds of an average 2-hour wait occurred before filling prescriptions (49.2 minutes) and before data entry (35.8 minutes). Improvement strategies should therefore focus on improving the methods of and the capacity for, order filling and data entry. The use of an automated dispensing system and additional data- entry terminals or a faster computer system were recommended. The approach used is a practical and accurate method for diagnosing system problems and lays a solid foundation for improvement strategies.
1. Introduction. 2. Markovian Queueing Systems. 3. The Busy Period, Output and Queues in Series. 4. Erlangian Queueing Systems. 5. Priority Systems. 6. Queueing Networks. 7. The System M/G/1 Priority Systems. 8. The System GI/G/1 Imbedded Markov Chains. A. Appendix. B. Bibliography. Index.
We developed and implemented an economic-optimization model for telephone-agent staffing at L. L. Bean, a large telemarketer and mail-order catalog house for quality outdoor sporting goods and apparel. The staffing levels we obtained with economic optimization were very different from those used by the company in the past, when staff size was determined by service-level criteria. For L. L. Bean, the resultant savings were estimated to amount to more than $500,000 per year. In the model, we used queuing theory, devised an expected total-cost objective function, and accounted for retrials and potential caller abandonments through a regression model that related the abandonment rates to the telephone-service factor (percentage of calls answered within a predetermined time interval).
Considers computer simulation as a method for studying the behaviour of business systems under a variety of assumed conditions for analysing the simultaneous interaction of many variables to produce valuable insights into problems. Looks at how simulations can help to provide answers to complex decisions and problems which cannot be solved by conventional methods.