Service Rate Research Articles

A congested facility location problem with strategic customers

This study addresses a user-equilibrium congested facility location problem with delay-, accessibility-, and price-sensitive customers. A profit-maximizing service provider first makes location, service rate, and pricing decisions, and then strategic customers decide which facilities to patronize (if any). By incorporating the customers’ choice behavior as a set of equilibrium constraints into the service provider’s decision problem, the problem is modeled as a mixed integer non-linear program which is then reformulated as a mixed integer second-order cone program. The proposed model, tested on several standard instances, is shown to be efficiently solvable using commercial software packages.

Modeling and optimizing an AMS with DV policy, waiting servers, impatient customers, and failures: A queueing analysis

In this paper, we analyze an automated manufacturing system modeled as a queueing system with multiple servers, differentiated vacation (DV) policy, customer impatience, and server failures. We consider the waiting servers policy, where the servers wait for a random duration before leaving for a vacation once the system gets empty. Upon their return, if no customers are waiting, the servers may leave for a second type-2 vacation of shorter duration. The system may experience breakdowns and require immediate repair. During the repair period, customers are served at a lower rate, and they become impatient during busy, vacation, and repair periods, abandoning the queue if their timer expires. Further, based on the queue length, arriving customers may either join the system or balk with some probability. We use the matrix analytic method to derive the steady-state probability of the system and several performance measures. Moreover, we illustrate the effect of different system parameters on various performance measures. Additionally, we develop a cost model and optimize the system capacity, number of servers, and service rates such that cost per unit time is minimized. Finally, we analyze the impact of system parameters on the cost through numerical examples.

Developing the Social Cognitive Factor Scale (SCFS) to analyze the determinants influencing the utilization of traditional chinese medicine preventive health services among older adults

IntroductionTraditional Chinese medicine (TCM) boosts immunity, aids self-repair, and supports elderly health. Despite government efforts, older adults underutilize TCM preventive health services. This study aimed to develop a reliable and valid Social Cognitive Factor Scale (SCFS) to understand this from a behavioral psychology perspective. MethodsThe SCFS, a self-report questionnaire rooted in Bandura's social cognitive theory, was developed by an expert panel using insights from current literature, focus group qualitative research, and scale testing. Twenty experts in TCM public health research and 840 community-dwelling older adults were included in this study. Scale development involved a literature review to establish the initial item pool, two Delphi expert consultations for item screening and revision, and comprehensive testing for reliability and effectiveness. ResultsThe SCFS consisted of 22 items classified into six dimensions: perceived environment, social support, belief and knowledge, self-efficacy, outcome expectations, and self-regulation. The overall Cronbach's alpha of the scale was 0.946, and the split-half reliability of the total scale was 0.828, showing good reliability. A total of six factors were extracted, explaining 78.85 % of the total variation. Exploratory factor analysis showed that the scale had good construct validity. Scores on the SCFS were significantly and positively correlated with the utilization rate of TCM preventive health services for older adults (r = 0.537, p < 0.01). ConclusionTCM plays a significant role in actively addressing the challenges of aging. The SCFS provides a reliable and valid tool for understanding the underutilization of TCM preventive health services among older adults. A positive correlation with service utilization rates highlights its potential for guiding interventions.

Planning of electric vehicle charging stations: An integrated deep learning and queueing theory approach

This study presents a hybrid solution for the charging station location-capacity problem. The proposed approach simultaneously determines the location and capacity of charging stations (i.e., number of charging piles), and assigns piles to electric vehicles based on their level of charge. The problem is formulated as a bi-objective mixed-integer nonlinear programming model to minimize the total cost of establishing charging stations together with the average customers’ waiting time. The proposed solution combines queueing theory with mathematical modelling to estimate the average waiting time. A deep learning algorithm is then developed to enhance the precision of waiting time estimation. Another contribution is involving a deep neural network model in improving NSGA-II algorithm. Numerical experiments are conducted in Halifax, Canada to assess the performance of the proposed framework. The results demonstrate the strong predictive performance of the deep learning algorithm and highlight the limitations of traditional queueing models in estimating waiting times in charging stations (i.e., 99.8% improvement in computation time, as well as accuracy improvement of time estimations from 13% to 1.6% deviation). Several valuable insights are obtained to improve the operational performance of charging stations such as achieving a significant (i.e., 61.5%) drop in the average waiting time across the network by a modest (i.e., 29.2%) increase in the initial investments. Also, it reveals that the variability of service rate significantly impacts the average waiting time (i.e., a 50% increase in the variability of service rate causes a substantial 950.56% surge in the average waiting time). The findings underscore the need to control service rate fluctuations to reduce wait times and boost driver satisfaction. The improved NSGA-II algorithm shows 12.77% improvement in the Pareto front solutions. Finally, the proposed prioritization strategy based on the charging level of vehicles could reduce the average waiting time and cost compared to the first-come-first-served strategy.

Age of Information in NOMA-IoT Networks: A Temporal Queuing Model Perspective

The Internet of Things (IoT) with non-orthogonal multiple access (NOMA) has been anticipated to offer diverse real-time applications, wherein the crux is to guarantee the age of information (AoI) for dynamic traffic. However, the traffic temporal variation provokes the interdependence between queue status and interference, in which context the AoI performance remains to be further explored. In this paper, an analytical framework is established to characterize the AoI performance in NOMA-IoT networks with random Bernoulli and deterministic periodic arrivals. Particularly, a numerical algorithm is devised to obtain the queue service rate, and tractable expressions for AoI violation probability and average AoI under both the first-come first-served (FCFS) and the preemptive last-come first-served (LCFS-PR) service disciplines are derived. Simulations are conducted to validate the proposed analysis. The results unveil that LCFS-PR conduces to better AoI performance than FCFS, and yet the gain diverges for each device with different traffic arrival configurations. In addition, the result shows that with sporadic traffic arrival, the periodic pattern outperforms the Bernoulli pattern, whereas this advantage gradually diminishes with more frequent packet arrival.

Chinese university students’ help-seeking behaviors when faced with mental health challenges

Background Mental illnesses and mental health challenges have become increasingly pervasive among Chinese university students. However, the utilization rate of mental health services is low among students. Aims We aimed to explore Chinese university students’ help-seeking behaviors to understand how they deal with mental health challenges and use the results to inform the development of effective mental health promotion initiatives. Methods In this study, we conducted 13 focus group interviews with students in six universities in Jinan, China, including 91 (62%) female students and 56 (38%) male students. We drew on the Theory of Planned Behaviors to guide our thematic analysis to gain a contextual understanding of participants’ accounts on help-seeking. Results Our results have depicted the help-seeking patterns of Chinese university students and show that there are four major behaviors which are self-reliance, seeking support from peers and families, seeking professional support, and accessing virtual mental health care. Conclusion Results from this study can be used to inform the development of mental health literacy programming for students in universities that share similar contexts, and the study has also opened up a new space for using qualitative approaches to study mental health needs and access to care in diverse populations.

QUEUING EFFICACY OF AUTOMATED TELLER MACHINES OPERATIONS ON MARKET PERFORMANCE OF SELECTED DEPOSIT MONEY BANKS IN RIVER STATE, NIGERIA

Generally, this study examines the queuing efficacy of ATMs operations on market performance of selected deposit money banks in Rivers State. Specifically, the study investigates how queuing efficiency affects customers’ patronage of money deposit banks in River State. Data were collected from selected ATM users at urban centres in River State. Descriptive and inferential statistics was used to discuss the findings which explain that Queuing Efficacy will increase customers’ patronage of banks in River State. The result presented shows that Queuing Efficacy had a positive relationship with customers’ patronage which its relationship was statistically significant at p = .000 [R = .267, p &lt;.05]. This indicates that service rate and customers’ patronage move in the same direction, that as service rate increases, customers’ patronage also increases. The model R2 (coefficient of determination) was 0.071 indicates that service rate explained 7.1% of the variance observed in customers’ patronage. Keywords: Customer Loyalty, Self Efficacy and Market Value Ratio.

Estrategia sostenible para mejorar la eficiencia de los servicios de inseminación artificial en ganado bovino en el trópico

The aim of this study was to evaluate the efficiency of artificial insemination (AI) services in Holstein x Brahman cows under a heat induction programme. Three experiments were carried out. In Exp. 1, a retrospective analysis of the efficiency of AI insemination of 41 000 cows treated with the combination of progesterone and oestradiol benzoate or equine chorionic gonadotropin (eCG) was carried out. In Exp. 2 it was evaluated 863 cows inseminated after heat induced with progesterone and oestradiol benzoate to know the physiological events that occur before and after service in herds with a high incidence of anoestrus. Gynaecological examinations and determination of progesterone in milk were performed. The purpose of Exp. 3 was to improve the effectiveness of AI services for cows in postpartum anoestrus treated with progesterone and oestradiol benzoate combined with a technique to identify and induce the return to service of females that did not conceive. Only 30% of the cows exceeded 40% conception. The best results were obtained when using eCG (47% vs 29%). The problems associated with the low conception rate were unfertilized oestrus, embryonic mortality and anoestrus after breeding (Exp. 2). The return to service induction technique increased (p&lt;0.001) the conception rate of the second induced service and the percentage of accumulated pregnancy in the treated group compared to the control (69.0 and 32.0%, respectively) (Exp. 3).

THE EFFECT OF TRUST IN BANKING INSTITUTIONS ON BEHAVIOURAL INTENTIONS FOR E-SERVICES

The adoption rate of electronic banking services (e-services) by consumers has increased significantly in recent years. For example, in the European Union, according to EUROSTAT data, the rate of individuals using the internet for internet banking increased by more than 25% between 2012 and 2023 (Eurostat, 2024). This may be due to several factors: the evolution of technology, the COVID-19 pandemic period, the time needed to complete a transaction, the availability of services, etc. The main objective of this paper was to assess whether trust in banking institutions can influence consumers' behavioural intentions when discussing the use of e-services. The following dimensions were considered to measure trust in the banking unit: Ability, Integrity, Benevolence (Bhattacherjee, 2002). A scale with the following dimensions was also used to measure behavioural intentions: loyalty, switch, pay more, external response (Zeithaml et al., 1996). The relationships were tested both between the "trust" and "behavioural intentions" dimensions taken as a whole and between the "trust" dimension taken separately and the "behavioural intentions" dimension taken as a whole. To achieve the objective of this study, the author collected data from 500 respondents in Romania via an online questionnaire. The surveys were conducted between April and August 2022. Partial least squares (PLS-SEM) was used for data analysis. The PLS-SEM results confirmed the significance of three out of four direct relationships. For one of the hypotheses, the dimension "integrity" was removed from the proposed conceptual model due to preliminary tests. These findings can help credit institutions to take various measures to increase public trust in such institutions and encourage the use of e-banking services. The areas targeted by these measures include: financial education programmes; corporate social responsibility (CSR) campaigns; transaction security; quality of banking staff; and transparency of credit institutions. For future research, it would be valuable to know what results can be obtained in other geographical areas. It is recommended to adapt and create new scales that can measure trust in companies and consumer behavioural intentions. These tools can help companies develop in their industries.

Implementation Of Activity Based Costing On The Rate Of Inspired Services For Covid-19 Patients At Pusri Hospital, Palembang City

This study aims to determine: (1) The cost calculation used by the hospital. Pu sri Palembang to determine the tariff for inpatient services for covid-19 patients in 2021, (2) Calculation of the Activity Based Costing System to determine the rate for inpatient services for COVID-19 patients at the hospital. Pusri Palembang in 2021, (3) Comparison of the calculation of the cost of inpatient services for Covid-19 patients based on hospital calculations with calculations using the Acitvity Based Costing System in 2021. The research method used is descriptive analysis method. The data collection method used in this research is to use the interview method and the documentation method. The interview method was used to obtain supporting data for writing, as for the list of questions as follows: How is the calculation of the cost method used by the hospital. Pusri Palembang to determine the tariff for inpatient services for Covid-19 patients in 2021?. The documentation method is used to obtain data on the list of rates for inpatient services for COVID-19 patients, hospitalization costs, and length of days of hospitalized patients. Based on the results of the study showed that: (1) The method applied by RS. Pusri Palembang to determine the tariff for inpatient services for COVID-19 patients at a rate of Rp. 2,473,606.50 (2) The tariff for inpatient services for Covid-19 patients using the Activity Based Costing method provides cheaper results. The difference that occurs is due to the imposition of overhead costs on each product. In the unit cost method, the overhead costs for each product are charged to only one cost driver, namely the number of days of hospitalization. Activity Based Costing is able to allocate activity costs to each product appropriately based on the consumption of each activity

Buick at a Crossroads: Building Brand Momentum

Few cases allow the student to understand the relationship between brand strategy, marketing strategy, implementation, and analysis. While some conceive of the process as being sequential, this case demonstrates that in fact, this process is more fluid, and that implementation and analysis impact subsequent strategy.This field-based case provides a rare glimpse into the turnaround of a brand that was all but dead. After Buick suffered more than five decades of declining business results and an inferior brand image versus all rivals, few thought that the brand could be resuscitated. This case provides a valuable under-the-hood look at how the Buick team, over time, progresses through a series of marketing improvements all anchored on an evolved strategy. Specifically, Buick introduced a shift in brand strategy behind an evolved brand essence statement (i.e., brand positioning), improved product lineup, new-to-the-world innovation, enhanced dealership service, and more compelling advertising. The results led to a record number of product awards, significantly improved advertising measures, improved service ratings, and better business results.Despite significant improvement across multiple dimensions of the business, Buick still trailed key competitors on one of the most important measures Buick tracked—the brand momentum rating—suggesting that there was still more work needed to complete the brand turnaround. The case introduces Molly Peck, the new marketing director on Buick, who is wondering what more, if anything, Buick should do. The material allows for instruction around marketing strategy and the process of converting it into implementation through the use of a creative brief.

A Study of Electronic Banking in India

Digital cash and online transactions in the current market scenario have a great effect on e-banking and digital banking. E-banking comprises mainly of electronic funds transfer and usage of online banking services. Electronic banking was offered by the international banks initially since flow of digital cash was not predominant in the Indian market until the advent of demonetization. E-banking plays a major role in the present banking functionality. Electronic banking is inferred to be safe and secured, compared to physical banking. e-banking ensures qualitative banking operations compared to traditional banking. However, it has its own limitations and challenges when we talk about security, on the contrary. After visually perceiving the growth rate of e-banking services it can be verbalized that e-banking is accepted in the banking sector and an abundance of work can be done in this sector to make it more advance, safe and more accommodation provider in finance sector.

Discounted cost exponential semi-Markov decision processes with unbounded transition rates: a service rate control problem with impatient customers

Discounted cost exponential semi-Markov decision processes with unbounded transition rates: a service rate control problem with impatient customers

Breeding practices and evaluation of hormonal estrus synchronization and mass artificial insemination of dairy cattle in southwest Ethiopia

Estrus synchronization is the process of controlling or guiding a cow/heifer estrous cycle so that they can mate at roughly the same time. It may be used to increase the probability of detecting estrus, increase the rate of calving in response to feed availability and market demand for dairy products, and increase the possibility of pregnancy in dairy cattle. The aim of this study was to assess breeding practices, evaluating of hormonal estrus synchronization and mass artificial insemination of dairy cow/heifers in Andracha and Masha districts of Southwestern Ethiopia. Three hundred eighty-nine (389) synchronized cows were selected from record of artificial insemination center (logbook). For experimental (action) study a total of 210 (103 from Andracha and 107 from Masha) dairy cows/heifers were selected and injected single dose of prostaglandin. Cow/heifers which do not respond by single injection were re-injected another single dose of prostaglandin. The data were analyzed using SPSS version 21 software. The study revealed that cows or heifers treated with single dose of prostaglandin 157(74.8 %), and 53(25.2 %) responded to heat and none response respectively in the study location. The study also revealed that overall conception rate (CR) and number of services per conception (NSPC) for single dose of prostaglandin injection in the researched areas were 68 (43.3 %), and 2.3 respectively. It was concluded that the effectiveness of PGF2α used to synchronize estrus in dairy cows/heifers was good and the overall conception rate 43.1 higher than national level conception rates (7.14–40.23) to first inseminations.

Future Industrial Applications: Exploring LPWAN-Driven IoT Protocols.

The Internet of Things (IoT) will bring about the next industrial revolution in Industry 4.0. The communication aspect of IoT devices is one of the most critical factors in choosing the device that is suitable for use. Thus far, the IoT physical layer communication challenges have been met with various communications protocols that provide varying strengths and weaknesses. This paper summarizes the network architectures of some of the most popular IoT wireless communications protocols. It also presents a comparative analysis of some of the critical features, including power consumption, coverage, data rate, security, cost, and quality of service (QoS). This comparative study shows that low-power wide area network (LPWAN)-based IoT protocols (LoRa, Sigfox, NB-IoT, LTE-M) are more suitable for future industrial applications because of their energy efficiency, high coverage, and cost efficiency. In addition, the study also presents an Industrial Internet of Things (IIoT) application perspective on the suitability of LPWAN protocols in a particular scenario and addresses some open issues that need to be researched. Thus, this study can assist in deciding the most suitable IoT communication protocol for an industrial and production field.

Queues with resetting: a perspective

Abstract Performance modeling is a key issue in queuing theory and operation research. It is well-known that the length of a queue that awaits service or the time spent by a job in a queue depends not only on the service rate, but also crucially on the fluctuations in service time. The larger the fluctuations, the longer the delay becomes and hence, this is a major hindrance for the queue to operate efficiently. Various strategies have been adapted to prevent this drawback. In this perspective, we investigate the effects of one such novel strategy namely resetting or restart, an emerging concept in statistical physics and stochastic complex process, that was recently introduced to mitigate fluctuations-induced delays in queues. In particular, we show that a service resetting mechanism accompanied with an overhead time can remarkably shorten the average queue lengths and waiting times. We examine various resetting strategies and further shed light on the intricate role of the overhead times to the queuing performance. Our analysis opens up future avenues in operation research where resetting-based strategies can be universally promising.

Enhanced Feature-driven Multi-objective Learning for Optimal Cloud Resource Allocation

In cloud networks, especially those with distributed computing setups and data centers, one of the biggest obstacles is allocating resources. This is the key area, and this must be balanced between optimizing system performance on one side and affordability, stability (reliance) of operation, and energy efficiency. The importance of improving resource allocation methodologies in these complex cloud computing systems is recognized, and therefore this paper comes with an appropriate title--“Enhanced Feature-Driven Multi-Objective Learning for Optimal Cloud Resource Allocation” (OCRA), which integrates together both the latest machine learning techniques as well as traditional concepts from research into cloud computing. OCRA capably analyzes historical files on CPU, memory, disk and network usage. In addition to neatly assimilating large data sets such as that was the compliance rate with past SLAs or workload frequencies over certain time periods and resource allocations; even their patterns of service requests are an important piece of information for many busy people’s lives today the adaptive mechanism is one of the defining traits of the model. It can accurately anticipate changes in resource demand and immediately adjust supply, fully able to respond rapidly when fluctuations arise suddenly or unexpectedly. Multi-Objective Random Forests are at the very core of OCRA. Each tree for decision making is specially designed to meet a particular performance objective in mind. Combining these trees into a Random Forest ensemble increases not only the model's predictive accuracy but also its stability. Pareto optimization is wisely used to maintain a balance among performance indicators, without an excessive focus on one effect alone. OCRA is proven empirically through experimental studies where key performance indicators such as Resource Utilization Rate and Quality of Service (QoS) Adherence Rate are taken into account. OCRA is both energy-efficient, an important attribute in today's environmentally conscious world, and does not sacrifice performance. As far as speed, flexibility and overall efficiency are concerned, OCRA has always been superior to the other cloud resources allocation programs of its own day. While it's still not quite ready for users who don't have a firm background in computer science or programming skills (ocra is plotted on 0-x), with sufficient memory and dominant minutes turn into mechanical equipment without configuration services.

The hard impact low probabilities’ impacts on power distribution system economy

Electricity distribution systems benefit customers, investors, and operational managers economically. However, natural hazards pose significant risks to these networks, contributing to economic instability. This study assesses the impact of low-probability, high-impact events, particularly storms, on asset management and lifespan within the electricity distribution industry. By introducing three key indicators—rate of return, service rate, and cost per asset—the research investigates how different assets respond to various risks. Each asset has a distinct threshold for risk tolerance, which diminishes as its lifespan increases. Utilizing a cost model and analyzing breakpoint curves, the study evaluates the effects of high impact and low probability (HILP) incidents on the indicators mentioned earlier, factoring in asset composition changes. The study assesses the impact of storms with varying intensities on a sample network by formulating economic relations and allocating budgets for HILP events across different network conditions. Results highlight the allocation of budgetary resources for securing assets of different ages within the network. Furthermore, sensitivity analysis explores how changes in network expansion coefficients and failure rates influence these factors. Notably, findings reveal that systems with slower development rates exhibit greater asset resilience; as demonstrated in scenario 3, the assets are strengthened from a 70-year life to a 6-year life for a 145 km storm.

Optimal Control of Service Rates of Discrete-Time (s, Q) Queueing-Inventory Systems with Finite Buffer

Optimal Control of Service Rates of Discrete-Time (s, Q) Queueing-Inventory Systems with Finite Buffer

Decomposition analysis on the equity of health examination utilization for the middle-aged and elderly people in China: based on longitudinal CHARLS data from 2011 to 2018

BackgroundThis study aimed to investigate the utilization rate and equity of health examination service among the middle-aged and elderly population in China from 2011 to 2018. The contribution of various determinants to the inequity in health examination service utilization was also examined.MethodsData from the China Health and Retirement Longitudinal Survey (CHARLS) were analyzed to assess the health examination service utilization rate among the middle-aged and elderly population. A concentration curve and concentration index were employed to measure the equity of health examination service utilization and decomposed into its determining factors. Horizontal inequity index was applied to evaluate the trends in equity of health examination service.ResultsThe health examination service utilization rates among the middle-aged and elderly population were 29.45%, 20.69%, 25.40%, and 32.05% in 2011, 2013, 2015, and 2018, respectively. The concentration indexes for health examination service utilization were 0.0080 (95% CI: − 0.0084, 0.0244), 0.0155 (95% CI: − 0.0054, 0.0363), 0.0095 (95% CI: − 0.0088, 0.0277), and − 0.0100 (95% CI: − 0.0254, 0.0054) from 2011 to 2018, respectively. The horizontal inequity index was positive from 2011 to 2018, evidencing a pro-rich inequity trend. Age, residence, education, region, and economic status were the major identified contributors influencing the equity of health examination service utilization.ConclusionsA pro-rich inequity existed in health examination service utilization among the middle-aged and elderly population in China. Reducing the wealth and regional gap, providing equal educational opportunities, and strengthening the capacity for chronic disease prevention and control are crucial for reducing the inequity in health examination service utilization.