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1 – 10 of 52Elisabetta Benevento, Davide Aloini, Nunzia Squicciarini, Riccardo Dulmin and Valeria Mininno
The purpose of this study is twofold: exploring new queue-based variables enabled by process mining and evaluating their impact on the accuracy of waiting time prediction. Such…
Abstract
Purpose
The purpose of this study is twofold: exploring new queue-based variables enabled by process mining and evaluating their impact on the accuracy of waiting time prediction. Such queue-based predictors that capture the current state of the emergency department (ED) may lead to a significant improvement in the accuracy of the prediction models.
Design/methodology/approach
Alongside the traditional variables influencing ED waiting time, the authors developed new queue-based predictors exploiting process mining. Process mining techniques allowed the authors to discover the actual patient-flow and derive information about the crowding level of the activities. The proposed predictors were evaluated using linear and nonlinear learning techniques. The authors used real data from an ED.
Findings
As expected, the main results show that integrating the set of predictors with queue-based variables significantly improves the accuracy of waiting time prediction. Specifically, mean square error values were reduced by about 22 and 23 per cent by applying linear and nonlinear learning techniques, respectively.
Practical implications
Accurate estimates of waiting time can enable the ED systems to prevent overcrowding e.g. improving the routing of patients in EDs and managing more efficiently the resources. Providing accurate waiting time information also can lead to decreased patients’ dissatisfaction and elopement.
Originality/value
The novelty of the study relies on the attempt to derive queue-based variables reporting the crowding level of the activities within the ED through process mining techniques. Such information is often unavailable or particularly difficult to extract automatically, due to the characteristics of ED processes.
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Ali Asghar Jomah Adham and Razman Mat Tahar
Nowadays, e‐queues are built up everywhere where customer online service is necessary such as in banks' e‐service, enterprises' e‐business, etc. In order to enhance quality of…
Abstract
Purpose
Nowadays, e‐queues are built up everywhere where customer online service is necessary such as in banks' e‐service, enterprises' e‐business, etc. In order to enhance quality of service (QoS), active queue management (AQM) algorithms are frequently employed due to their efficiency in congestion avoidance as well as the differentiated forwarding of packets. This paper aims at developing a novel AQM algorithm to better QoS in terms of congestion prediction, queuing delay, packet loss and link utility, etc.
Design/methodology/approach
Upon the traditional designs of AQM, this paper establishes a new integrated AQM scheme (RQ‐AQM) by employing input rate and current queue length to calculate the packet dropping/marking probability. In this way, the rate feedback control enables to rapid response to congestion, decreasing the packet loss from buffer overflow. Meanwhile, the queue length feedback control stabilizes the queue length around a given target, achieving predictable queuing delay and lower delay jitter. Thus, the main feature of the design is to use coefficients of both proportional rate control and proportional‐integral queue length control, and to simplify parameter setting, the control parameters were scaled by the link capacity C to normalize the rate and by the bandwidth‐delay product BDP to normalize the queue length, respectively.
Findings
The stability performance of RQ‐AQM was tested via simulation under several conditions. The results proved that it is able to maintain the queue length around the given target. Also, the comparison results with other AQM schemes, including RED, ARED, PI controller, AVQ and REM, demonstrated the superiority of RQ‐AQM in low packet loss, faster convergence to target queue length and closest to the target queue length.
Research limitations/implications
The main limitation of this study is that all the simulations were merely under a single bottleneck network topology. Furthermore, the system stability was examined under just a few cases. Other cases like TCP connections mixed with HTTP connections, or UDP flows, etc. can also be tested. Furthermore, the multiple bottleneck scenarios should be covered in the future work with more parameters set to enhance the proved results.
Practical implications
The paper sets clear but ideal conditions for the performance of proposed algorithm; so the simulation results can only be used as a rough reference instead of an exact practical one. But the concepts the paper attempted to advocate could be considered seriously.
Social implications
The scope of the paper is within the general theory of AQM. So it can be referred to any specific field that employs AQM technology, no matter locally or globally.
Originality/value
There are not much new brand contents in the paper. The main contribution is on some extension of the known related work.
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Rungting Tu, Wenting Feng, Cheryl Lin and Pikuei Tu
Companies work hard to reduce queue lengths due to the common belief that queues in general are undesirable. Extant literature mainly has focused on the negative consequences of…
Abstract
Purpose
Companies work hard to reduce queue lengths due to the common belief that queues in general are undesirable. Extant literature mainly has focused on the negative consequences of queues and overlooked the potential positive effects. The purpose of this paper is to address the benefits of queues by examining how consumers of different segments may read into the lines (queues) as well as why and when positive effects occur.
Design/methodology/approach
Applying and integrating psychology and marketing theories, the study develops a model with several propositions to identify and explain the mechanism and conditions under which queues have positive effects.
Findings
Contrary to conventional belief, queues may serve as positive signs. In certain segments, consumers can perceive a queue as a reflection of superior service/product quality, an opportunity to fulfill the need(s) for self-uniqueness or social inclusion or an avenue to avoid social exclusion. In addition, the benefits of long queues may come from consumers’ joining a line to seek desirable outcomes/gains based on their attribution of the queue, and consumers’ prefactual thinking that regards “not joining” the queue as potential losses. Furthermore, the magnitude of such effects depends on queue distinctiveness, choice heterogeneity, consumption hedonism and performance uncertainty.
Originality/value
This paper explains how, why and when a long queue can be read as positive cues and benefits both the firms and target/potential consumers. The authors demonstrate the psychological mechanisms of joining a queue based on attribution and prefactual thinking, and identify conditions under which positive queue effects are most likely to occur.
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Markov chains and queuing theory are widely used analysis, optimization and decision‐making tools in many areas of science and engineering. Real life systems could be modelled and…
Abstract
Purpose
Markov chains and queuing theory are widely used analysis, optimization and decision‐making tools in many areas of science and engineering. Real life systems could be modelled and analysed for their steady‐state and time‐dependent behaviour. Performance measures such as blocking probability of a system can be calculated by computing the probability distributions. A major hurdle in the applicability of these tools to complex large problems is the curse of dimensionality problem because models for even trivial real life systems comprise millions of states and hence require large computational resources. This paper describes the various computational dimensions in Markov chains modelling and briefly reports on the author's experiences and developed techniques to combat the curse of dimensionality problem.
Design/methodology/approach
The paper formulates the Markovian modelling problem mathematically and shows, using case studies, that it poses both storage and computational time challenges when applied to the analysis of large complex systems.
Findings
The paper demonstrates using intelligent storage techniques, and concurrent and parallel computing methods that it is possible to solve very large systems on a single or multiple computers.
Originality/value
The paper has developed an interesting case study to motivate the reader and have computed and visualised data for steady‐state analysis of the system performance for a set of seven scenarios. The developed methods reviewed in this paper allow efficient solution of very large Markov chains. Contemporary methods for the solution of Markov chains cannot solve Markov models of the sizes considered in this paper using similar computing machines.
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Nasser Abdali, Saeideh Heidari, Mohammad Alipour-Vaezi, Fariborz Jolai and Amir Aghsami
Nowadays, in many organizations, products are not delivered instantly. So, the customers should wait to receive their needed products, which will form a queueing-inventory model…
Abstract
Purpose
Nowadays, in many organizations, products are not delivered instantly. So, the customers should wait to receive their needed products, which will form a queueing-inventory model. Waiting a long time in the queue to receive products may cause dissatisfaction and churn of loyal customers, which can be a significant loss for organizations. Although many studies have been done on queueing-inventory models, more practical models in this area are needed, such as considering customer prioritization. Moreover, in many models, minimizing the total cost for the organization has been overlooked.
Design/methodology/approach
This paper will compare several machine learning (ML) algorithms to prioritize customers. Moreover, benefiting from the best ML algorithm, customers will be categorized into different classes based on their value and importance. Finally, a mathematical model will be developed to determine the allocation policy of on-hand products to each group of customers through multi-channel service retailing to minimize the organization’s total costs and increase the loyal customers' satisfaction level.
Findings
To investigate the application of the proposed method, a real-life case study on vaccine distribution at Imam Khomeini Hospital in Tehran has been addressed to ensure model validation. The proposed model’s accuracy was assessed as excellent based on the results generated by the ML algorithms, problem modeling and case study.
Originality/value
Prioritizing customers based on their value with the help of ML algorithms and optimizing the waiting queues to reduce customers' waiting time based on a mathematical model could lead to an increase in satisfaction levels among loyal customers and prevent their churn. This study’s uniqueness lies in its focus on determining the policy in which customers receive products based on their value in the queue, which is a relatively rare topic of research in queueing management systems. Additionally, the results obtained from the study provide strong validation for the model’s functionality.
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Pasquale Legato and Rina Mary Mazza
An integrated queueing network focused on container storage/retrieval operations occurring on the yard of a transshipment hub is proposed. The purpose of the network is to support…
Abstract
Purpose
An integrated queueing network focused on container storage/retrieval operations occurring on the yard of a transshipment hub is proposed. The purpose of the network is to support decisions related to the organization of the yard area, while also accounting for operations policies and times on the quay.
Design/methodology/approach
A discrete-event simulation model is used to reproduce container handling on both the quay and yard areas, along with the transfer operations between the two. The resulting times, properly estimated by the simulation output, are fed to a simpler queueing network amenable to solution via algorithms based on mean value analysis (MVA) for product-form networks.
Findings
Numerical results justify the proposed approach for getting a fast, yet accurate analytical solution that allows carrying out performance evaluation with respect to both organizational policies and operations management on the yard area.
Practical implications
Practically, the expected performance measures on the yard subsystem can be obtained avoiding additional time-expensive simulation experiments on the entire detailed model.
Originality/value
As a major takeaway, deepening the MVA for generally distributed service times has proven to produce reliable estimations on expected values for both user- and system-oriented performance metrics.
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The purpose of this paper is to describe and evaluate three different models of how to organise services to tenants in municipal housing companies.
Abstract
Purpose
The purpose of this paper is to describe and evaluate three different models of how to organise services to tenants in municipal housing companies.
Design/methodology/approach
The empirical data used in this study are gathered from a detailed two‐year case study.
Findings
Three different functions are identified: customer service (e.g. reporting of faults); the letting process; and caretaking (day‐to‐day activities and control over in‐ and outdoor areas). The three models for local administration differ as to which functions are decentralised to a local group and which are centralised, and are evaluated from several different perspectives. The models where more decisions are decentralised leads to better information about the local conditions, makes it easier to coordinate work in an area, creates more motivation for the staff and makes it easier to involve the tenants. The main problem with the decentralised models is moral hazard problems, e.g. that the local team create their own agenda, are pressured by certain tenants to give them advantages and that the result is lack of control and an inconsistent policy in the company.
Research limitation/implications
The primary issue of the study is how housing companies can organise their resources in order to create an efficient local administration in large housing estates. Further research is needed to decide if the economic profitability differs between different organizational models in relation to tenants' perceived service quality.
Originality/value
The research identifies and analyses different organisation models for local administration in large housing estates more thoroughly than earlier research.
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Navid Hooshangi, Navid Mahdizadeh Gharakhanlou and Seyyed Reza Ghaffari-Razin
The duration of an urban search and rescue (USAR) operation directly depends on the number of rescue teams involved. The purpose of this paper is to simplify the earthquake…
Abstract
Purpose
The duration of an urban search and rescue (USAR) operation directly depends on the number of rescue teams involved. The purpose of this paper is to simplify the earthquake environment and determine the initial number of rescuers in earthquake emergencies in USAR operation.
Design/methodology/approach
In the proposed methodology, four primary steps were considered: evaluation of buildings damage and the number of injured people by exerting geospatial information system (GIS) analyses; determining service time by means of task allocation; designing the simulation model (queuing theory); and calculation of survival rate and comparison with the time of rescue operations.
Findings
The calculation of buildings damage for an earthquake with 6.6 Richter in Tehran’s District One indicated that 18% of buildings are subjected to the high damage risk. The number of injured people calculated was 28,856. According to the calculated survival rate, rescue operations in the region must be completed within 22.33 h to save 75% of the casualties. Finally, the design of the queue model indicated that at least 2,300 rescue teams were required to provide the calculated survival rate.
Originality/value
The originality of this paper is an innovative approach for determining an appropriate number of rescue teams by considering the queuing theory. The results showed that the integration of GIS and the simulation of queuing theory could be a helpful tool in natural disaster management, especially in terms of rapid vulnerability assessment in urban districts, the adequacy and appropriateness of the emergency services.
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Vikramaditya Pant and William P. Wagner
This paper explains the concept of how XML can be used to tie together the many different communication channels into a single contact point system. The purpose is to propose a…
Abstract
Purpose
This paper explains the concept of how XML can be used to tie together the many different communication channels into a single contact point system. The purpose is to propose a contact point framework that utilizes XML technologies to integrate multiple communication channels.
Design/methodology/approach
This is a conceptual paper where two general approaches to channel integration are described and critiqued and a third one proposed.
Findings
This paper has suggested that contact point channel integration products based on XML technology can be used to lower the design, development, management and maintenance costs. The proposed framework can be an initiative in the open source community where software developers can contribute towards the modular development of such software. The use of XML as the primary data interchange language promises to add value to the contact points of a business at a relatively low cost.
Research limitations/implications
Further research is necessary to evaluate and perfect the use of XML in this context.
Practical implications
This research suggests a roadmap for how systems integrators can use XML technology to integrate multiple communication channels in a Customer relationship management (CRM) environment.
Originality/value
This is the first research to examine the different approaches to CRM channel integration and propose an XML‐based framework for accomplishing this.
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This paper examines the benefit of incorporating a group of employees that exhibit dynamic service rates into scheduling tours in a service operation. The service operation that…
Abstract
This paper examines the benefit of incorporating a group of employees that exhibit dynamic service rates into scheduling tours in a service operation. The service operation that is examined includes a fully productive core (full‐time) workforce along with a contingent (full‐ and part‐time) workforce that experiences the learning effect. Two methods that account for the learning effect are analyzed along with two methods that do not consider learning effects. The schedules generated by each method are tested in a simulation of the service environment. The results of a full‐factorial experiment indicate that methods that account for learning effects will yield superior solutions over a variety of operating conditions when compared to alternative methods that do not consider learning effects. The performance improvement of schedules generated with the most precise learning curve method was substantially and significantly better than the other methods. The conditions in which the learning curve methods provide the most benefit are explored.
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