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The purpose of this study is that service sectors sectors create queues intentionally as a promotional strategy. Potential buyers might become actual customers after witnessing and joining queues. However, the effectiveness of company promotional activities involving queues remains unclear. Despite the innovativeness of this marketing strategy, few companies have adopted this approach, owing to the lack of research on how waiting influences customer behaviors toward waiting in queues.

Therefore, this study identifies four factors of customer willingness to stand in a queue using questionnaire survey: company promotional activities, improvement of waiting environment, company’ reactions to the queue and customers’ perceptions regarding waiting time.

This study identifies causal relationships among the aforementioned factors. The results of this investigation reveal that a company’s promotional activities significantly and indirectly reduce customers’ perceived waiting time by improving the waiting environment. Analytical results also show that a company’s queuing management can indirectly reduce customers’ perceived waiting time by improving the waiting environment.

Based on the analytical results concerning causal relationships, improving the waiting environment is critical to affecting positively customers’ perceptions regarding waiting time. Queuing management can indirectly reduce customers’ perceived waiting time by improving the waiting environment. A company’s promotional activities can indirectly reduce customers’ perceived waiting time by improving the waiting environment. Customers who enjoy both the waiting environment and the promotional activities experience much shorter perceived waiting time.

To study the optimization of a randomized control problem in an M/G/1 queue in which a removable and unreliable server may provide two phases of heterogeneous service to arriving customers.

Arriving customers follow a Poisson process and require the first essential service (FES). As soon as FES of a customer is completed, the customer may leave the system or opt for the second optional service (SOS). The service times of FES channel and SOS channel are assumed to be general distribution functions. The server requires a startup time with random length before starting service. When the server is working, he may meet unpredictable breakdowns but is immediately repaired. The inter‐breakdown time and repair time of the removable server are exponentially random variable and generally random variable, respectively. By the convex combination property and the renewal reward theorem, several system performances are obtained. A cost model is developed to search the optimal two‐threshold policy at a minimum cost. Sensitivity analysis is performed.

Expressions for various system performances are derived. Sensitivity analysis of optimal randomized control policy (based on the developed expected cost function) with respect to system parameters is investigated.

It is the first time that analytic results of sensitivity analysis of optimal randomized control policy for the complex system have been obtained which is quite useful and significant for engineers.

While the goal of almost any service provider is to eliminate wait from the consumption experience, there are a number of service environments where this ideal may be impractical, if not impossible, to deliver, among them live sport. Live sporting events often have queues at entry and exit gates, facility concessions and toilets. This study tests a model featuring antecedents not used in prior research on waiting. Findings suggest that facility layout features and waiting fill time both have a positive influence on spectators' feelings about a wait. Most interestingly perhaps, these same antecedents may also serve as a cue that long waits are likely.

Since waiting in a queue may induce both negative and positive effects on customers’ quality perceptions of which the queue is formed, an optimal queuing wait which is long enough but not too long to have positive effects on the pursued service is critical for successful queuing management. This study examined the existence of an optimal queuing wait at theme parks by merging the interpretative approach of institutional norms with the measuring application of the adapted Return Potential Model from crowding studies. Using quota and systematic sampling techniques, survey data were collected from 1,440 visitors to five leading theme parks in Taiwan. An optimal queuing wait represented by an institutional norm among visitors with moderate consensus for the longest acceptable waiting time (LAWT) was revealed in this study. As a critical reversal point of visitors’ quality perception, significant ascent of visitors’ crowding perception did occur when their actual waiting times exceeded their LAWT.

The authors consider parallel four-state tandem open queueing network. The queue capacity is infinite. Passenger arrival rate is Poisson distribution and service rate is exponential distribution. The queue is constructed in the form of tandem queue, and each and every queue of tandem queue is single server (M/M/1) queue. In tandem queue, passengers will leave the system once they receive service from both the states. The purpose of this paper is to provide performance analysis for four-state tandem open queue network, and a governing equation is formulated with the help of transition diagram. Using Burke theorem, the authors formulated equation for average number of passenger in the system, average waiting time of passenger in the system, average number of passenger in the queue and average waiting time of passenger in the queue.

This paper used Burke’s theorem.

In this paper, performance analysis is done for parallel four-state tandem open queueing network and performance measure solved using Burkes theorem formula. K. Sreekanth et al. has done performance analysis for single tandem queue with three states. In this paper, the authors have done performance analysis for two tandem queues parallel with four states. This four-state tandem open queueing network is suitable for real world applications. This paper can extend for more number of service states and multi-server states according to the application, and in such case, the authors have to prove and explain with numerical examples. This analysis is more useful for the applications such as airports, railway stations, bus-stands and banks.

In this paper, parallel four-state tandem open queueing network and performance measure has been solved using Burke’s theorem formula.

For the past ten years or so, librarians have been discussing the way reference service is provided, the most conspicuous recent installments being the “Re‐thinking Reference in Academic Libraries” conference and the widely publicized changes at Brandeis University. No one has heard every statement in this debate because it has been so extensive in time, space, and medium. Nevertheless, it seems safe to say that mathematical queuing theory has not played a significant role in it. At first, this lacuna is puzzling, since queuing problems are one of the fundamental types treated in operations research, which in “those thrilling days of yesteryear,” the fifties, sixties, and early seventies, was taught in some library and information science programs. By 1978 articles that applied the theory specifically to reference work appeared. Yet, the second edition of a text on operations research for librarians that appeared in 1991 says not a word about reference queues. Perhaps this theory has been neglected in recent discussions because it is usually applied to telephone calls or local area networks and other configurations of computers, while its use in analyzing queues of people in banks, supermarkets, and the like was passed over as too mundane. Perhaps, too, the failure of banks to take the theory to its logical limits in arranging the queues for bank tellers has led to caution.

This paper aims to consider a single server queue with system disasters and impatience behavior are evident in our daily life. For this purpose, authors require to know the general behavior of these systems. Transient analysis shows for us how the system will operate up to some time instant t.

In this paper, authors consider a single server queue with system disaster and impatient behavior of customers in a multi-phase random environment, in which the system transits to a repair state after each system disaster. When the system is in a failure phase or going through a repair phase, the new arrivals would be impatient. In case the system is not repaired before the customer’s time expires, the customer would leave the queue and never return. Moreover, after repair, the system becomes ready for service in an operative phase with probability $q_{i} \ge 0.$. Using generating functions along with continued fractions and some properties of the confluent hypergeometric function, authors obtained on their own results.

Explicit expressions have been obtained for the time-dependent probabilities of the underlying queuing model. Also, time-dependent mean and variance of customers in the system are deduced.

The system authors are dealing with is somewhat complicated, there are some performance measures that cannot be achieved, but some of them have been obtained, such as the expectation and variance of the number of customers in the system.

Based on the obtained results, some numerical examples are some numerical examples are presented to illustrate the effect of various parameters on the behavior of the proposed system.

Authors’ studied transient analysis of a single server queue with system disaster and impatient customer system is suitable for behavior interpretation of many systems in our lives, such as telecommunication networks, inventory systems and impatient telephone switchboard customers, manufacturing system and service system.

To the best of the author’s/authors’ knowledge and according to the literature survey, in a multi-phase random environment, no previous published article is presented for transient analysis of a single server queue with system disaster and impatient customer behavior in a random environment.

State‐based management (SBM) is a specific form of the game‐play methodology (GPM) – an approach to the application of constraints in humanity activity systems. The theory that supports GPM was developed using a team sports model and promotes a coordination of workers’ efforts, without limiting their individual abilities to be creative in support of corporate goals. This paper reports on research undertaken to prove the applicability of GPM to a business environment. The case studies focused on over‐the‐counter (OTC) banking services. The use of game‐play tactics (SBM) in the banking chamber was highly successful. It provided a mechanism for designing constraints that addressed issues of the incomplete and inaccurate system state knowledge usually held by the tellers. Further, the process promoted the development of a team ethos, and this change in attitudes had positive repercussions on the overall working environment

Investigates the extent to which there is a gap between customers’ perception of waiting time compared with the actual waiting time and, whether this gap could be reduced. Maister originally identified eight propositions based around the idea that the perception of waiting lines are modified by a range of factors. Although other studies have discussed Maister’s propositions by identifying the level of management control and customers’ perceptions of waiting lines, rarely has the basic idea ‐ that perceived and actual wait times may be different ‐ been empirically tested. Reviews those studies which have compared actual waiting time with perceived waiting time, before going on to report on the first known UK study. The research involved an experimental study into two of Maister’s propositions involving 300 members of the general public. Tests a control group of 100 people queueing in a small retail food outlet to identify whether there is a significant difference between perceived and actual waiting times. Repeats the measurement on two further random samples of 100 people. Then discusses the implications of this study, and the earlier studies, with respect to a revision of Maister’s original eight propositions. Concludes with a review of how queue management may be carried out more effectively in relation to matching more closely actual and perceived waiting times.

This paper aims to investigate the optimal price and service rate decisions in a customer-intensive service, where customers’ perceived service quality decreases in the service speed. Customers are assumed to be forward-looking in purchase decision-making and heterogeneous in their reservation utilities. The purpose of this paper is to study the impact of customers’ forward-looking behavior and the heterogeneity on the operational decisions in a customer-intensive context.

The service is delivered through an M/M/1 queue system with unobservable queues. Customers are forward-looking in queue joining decisions, where the purchase decisions are made when the expected utility is greater than the reservation utility. The optimal price and service rate decisions are analyzed with both homogeneous and heterogeneous customers, where homogenous customers have the same reservation utility in purchase decision-making, while heterogeneous customers have different reservation utilities, which are captured by a random variable.

The optimal price and service rate decisions with forward-looking customers depend on the customer intensity, potential market size and customers’ reservation utility distribution. The results suggest that customers’ heterogeneity in terms of their reservation utilities affects the optimal decisions, market coverage and the expected revenue. Service providers need to take customers’ heterogeneity and the forward-looking behavior into operational decision-making.

This paper extends previous studies in customer-intensive service and contribute to the service operations management area by explicitly incorporating customers’ forward-looking behavior and heterogeneity in purchase decision-making. Assuming customers are forward-looking and heterogeneous is more realistic and practical. The results highlight that knowing customers’ behavioral characteristics can better improve decision-making in service operations, which is critical for enhancing customers’ satisfaction and loyalty, thus critical to a firm’s success in the market with intensive competition.