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The purpose of this paper is to provide a framework for the optimal design of queueing systems of call centers with delay information. The main decisions in the design of such systems are the number of servers, the appropriate control to announce delay anticipated.

This paper models a multi-server queueing system as an M/M/S+M queue with customer reactions. Based on customer psychology in waiting experiences, a number of different service-level definitions are structured and the explicit computation of their performance measures is performed. This paper characterizes the level of satisfaction with delay information to modulate customer reactions. Optimality is defined as the number of agents that maximize revenues net of staffing costs.

Numerical studies show that the solutions to optimal design of staffing levels and delay information exhibit interesting differences, especially U-shaped curve for optimal staffing level. Experiments show how call center managers can determine economically optimal anticipated delay and number of servers so that they could control the trade-off between revenue loss and customer satisfaction.

Many results that pertain to announcing delay information, customer reactions, and links to satisfaction with delay information have not been established in previous studies, however, this paper analytically characterizes these performance measures for staffing call centers.

Delay is an important issue for service providers. Indeed, previous studies have widely shown the negative effect of waiting time on consumer service satisfaction. However, being satisfied with the service seems to be insufficient for customers to remain loyal. Creating customer loyalty is even more crucial than just satisfying them. The paper aims to investigate how customers weigh up their service satisfaction and waiting time satisfaction in order to determine whether they will remain loyal or not.

A survey was conducted in the Belgian health care industry. The final sample includes 946 respondents. Regression analyses were performed and the Baron and Kenny method used to test moderator and mediator impacts of variables.

The results confirm that waiting time satisfaction is not only a service satisfaction determinant, but it also moderates the satisfaction‐loyalty relationship. Moreover, determinants of customer waiting time satisfaction include the perceived waiting time, the satisfaction with information provided in case of delays, and the satisfaction with the waiting environment. In addition, it is shown that waiting time satisfaction is a complete mediating variable in the perceived waiting time and service satisfaction link.

The paper suggests several implications about the waiting time impacts on service satisfaction and customer loyalty. They show the importance of this variable in the service process and explain how to improve it.

The purpose of this paper is to examine the effect of expectancy disconfirmation on passengers’ reactions to airline delays.

The study uses a between-subject factorial design with 9 treatments involving 161 subjects to collect data to test the hypotheses.

The study showed that, when given a positive disconfirmation, subjects feel better and are more satisfied, but when given a negative disconfirmation, they feel more negative and dissatisfied. Also, the effect size of positive disconfirmation on satisfaction and feelings about the service provider were significantly less than that of negative disconfirmation of the same size. Hence, in the event of a delay, managers may have to announce the upper bound of the delay duration so that passengers might feel better and become more satisfied when the actual delay duration is shorter than what was initially expected. In addition, they must try their best not to create situations of negative disconfirmation in light of their disproportional impact on satisfaction.

According to the results, airline managers should estimate as accurately as possible the duration of a delay when there is one.

A major contribution of this study is that manipulating the way delay duration information is given to passengers can affect feelings about the delay and the level of satisfaction with the airline.

That someone can make us feel good is a quality in itself. There has been much talk within British government circles, for example, about “the feelgood” factor, which is constantly reminding us that it is just around the corner! Whether or not we can believe in this is another matter but it certainly displays an awareness that making other people feel good can also have positive benefits for ourselves. How this can be achieved will differ depending on our particular line of business. Having a good‐quality product does not in itself guarantee success as service quality must also be taken into account. This is where the feel‐good factor comes into play. It is all very well, for example, going to a restaurant to have a top‐class meal (in that the food was good), only to have it thrown at you. Quality, therefore, must not be seen as a separate entity, but more as a package deal. Service quality is important if you wish to retain your customer base as acquiring new customers can be both time‐consuming and costly. It quite often takes very little apart from good manners to keep customer loyalty as in the case of the restaurant. Other factors can, however, start creeping into the framework such as efficiency, timeliness and good communication. Is there, for example, a time limit on how long you can reasonably be expected to wait for your meal before it arrives at the table, and if there is a delay is this communicated to you? In other words, we all have expectations as to what is acceptable and what is not. The clever part is for the organization to learn by what criteria the customer judges its service quality performance.

The purpose of this research is to investigate the impact of consumer satisfaction survey respondents' demographics, satisfaction level and behavioral intentions on response rates and item completion rates.

A consumer satisfaction survey was sent to 2,000 individuals immediately after receipt of a service experience. The respondents to this initial survey were then mailed another survey one to two years following the service experience in order to identify individual consumers who could then be tracked to see who responded to the survey.

The findings indicate that age impacts survey response rates, intention to return impacts item completion rates, and satisfaction impacts both response and item completion rates.

Ensuring the accuracy of consumer satisfaction data is invaluable to an organization, as the findings are the basis from which many important decisions are made. Unfortunately, many consumers do not respond or may not completely fill out surveys, leaving the organization with imprecise results. To assess consumer perceptions properly, managers must be certain of accurate and unbiased results to be able to make key operational changes.

That someone can make you feel good is a quality in itself. There has been much talk within British government circles, for example, about “the feel‐good factor”, which is constantly reminding us that it is just around the corner! Whether or not we can believe in this is another matter, but it certainly displays an awareness that making other people feel good can have positive benefits for you also. How this can be achieved will differ depending on your particular line of business. Having a good quality product does not in itself guarantee success as service quality must also be taken into account. This is where the feel‐good factor comes into play. It is all very well, for example, going to a restaurant to have a top‐class meal (in that the food was good), only to have it thrown at you. Quality, therefore, must not be seen as a separate entity, but more as a package deal.

The present study compares two types of compensation – i.e. on‐the‐spot and delayed – and tries to reveal how and when firms can utilize delayed compensation effectively. For this, failure severity is considered how these two types of compensation affect satisfaction and repurchase intentions.

A scenario‐based experiment in the hotel and restaurant industries was used with a sample of 292 students.

The results show that failure severity acts as a moderating variable in a recovery process of compensation‐satisfaction‐repurchase intention. The more severe consumers perceive the failure is, the more they depend on satisfaction to decide repurchase intentions. The two types of compensation are also moderated by failure severity on their effects on satisfaction and repurchase intentions. On‐the‐spot compensation leads to more satisfaction and repatronage intentions when failures are severe, but the results are not as straightforward when failures are insignificant. Under such a condition, while delayed compensation does not engender customer satisfaction with recovery as much as on‐the‐spot compensation, repatronage intentions for both types of compensation were similar in the hotel industry and even higher in restaurant services.

Industry differences such as ease of visit, frequency of visit, competition factors, and primary value (e.g. hedonic versus utilitarian) are expected to influence the effects of on‐the‐spot versus delayed compensation.

The study provides practitioners with the implication that the timing of compensation should be approached strategically according to the severity of failure and recovery outcomes they expect to achieve.

The present study tries to focus on compensation, one of the most commonly used recovery strategies, and tries to find the effects of different timings of it.

A combined model involving the intensity of negative emotions and the strategic combinations (timing and means) of service recovery is developed. The purpose of this paper is to evaluate the performances of these different combinations through customer satisfaction, repurchase intention and fitting curves between the two under hotel service scenarios.

A 2 (recovery timing: immediate/delayed) × 2 (recovery means: psychological/economic) × 3 (type of service failure: failure in a delivery system/failure in responding to customer needs/improper employee behavior) between-subject experimental design was used with 456 participants.

The results suggest that immediate and economic recovery effectively raises the service recovery evaluations from customers with low-intensity negative emotions, whereas delayed and psychological recovery helps customers with high-intensity negative emotions to give higher evaluations.

When service failures happen, the strategies for and timing of recovery directly influence customers’ service recovery evaluations. This study sheds light on the role that negative emotions play in the process of service recovery and provides implications for service industry managers.

Variations in customer expectations pose a challenge to service quality improvement in the airline industry. Understanding airline customers' expectations and satisfaction help service providers improve their offerings. The extant literature examines airline passengers' expectations in isolation, neglecting the overall impact of online reviews on service quality improvement. This paper systematically evaluates the airline industry's passengers' expectations and satisfaction using expectation confirmation theory (ECT) and the SERVQUAL framework. The paper analyzes online reviews to examine the relationship between airline service quality attributes and passengers' satisfaction.

The SERVQUAL framework was employed to examine the effects of customer culture, the reason for traveling, and seat type on customer's expectations and satisfaction across a large sample of airline customers.

A total of 17,726 observations were gathered from the Skytrax review website. The lowest satisfaction ratings were from passengers from the USA, Canada and India. Factors that affect perceived service performance include customer service, delays and baggage management. Empathy and reliability have the biggest impact on the perceived satisfaction of passengers.

This research increases understanding of the consumer expectations through analysis of passengers' online reviews. Results are limited to a small sample of airline industries.

This study provides airlines with valuable information to improve customer service by analyzing online reviews.

This study provides the opportunity for airline customers to gain better services when airline companies utilize the findings.

This paper offers insights into passengers' expectations and their perceived value for money in relation to seat types. Previous studies have not investigated value for money as a construct for passengers' expectations and satisfaction relative to service quality dimensions. This paper addresses this need.

The purpose of this paper is to provide delay announcements for call centers with hyperexponential patience modeling. The paper aims to employ a state-dependent Markovian approximation for informing arriving customers about anticipated delay in a real call center.

Motivated by real call center data, the patience distribution is modeled by the hyperexponential distribution and is analyzed by its realistic significance, with and without delay information. Appropriate M/M/s/r+H₂ queueing model is structured, including a voice response system that is employed in practice, and a state-dependent Markovian approximation is applied for computing abandonment. Based on this approximation, a method is proposed for estimating virtual delays, and it is investigated about the problem of announcing virtual delays to customers upon their arrival.

There are two parts of findings from the results obtained from the case study and a numerical study of simulation comparisons. First, using an H₂ distribution for the abandonment distribution is driven by an empirical study which shows its good fit to real-life call center data. Second, simulation experiments indicate that the model and approximation are reasonable, and the state-dependent Markovian approximation works very well for call centers with larger pooling. It is concluded that our approach can be applied in a voice response system of real call centers.

Many results pertain to announcing delay information, customer reactions and links to estimating hyperexponential distribution based on real data that have not been established in previous studies; however, this paper analytically characterizes these performance measures for delay announcements.