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The purpose of this paper is to model the occurrences of successive failure types and times to failure of the two repairable machine systems.

Historical data on failure types and time to failures of the given machine systems (4 nos) were gainfully used. Second order time homogeneous Markov Chain models were used to characterize the occurrences of the two broad failure type, namely, mechanical and electrical, after having found that the occurrences of failure types were dependent. Second order time homogeneous Markov Chain with Bivariate Distribution function (M2BVD) was used to model the times between successive failures {T_n, n≥1} for each machine system.

It is possible to apply the theoretical framework of Markov chain models to the accumulated data on failure types and failure times of any repairable system, which provide a wealth of information on the systems and are often left unused.

The framework used in the study can be improved to accommodate multiple failure types and failure times of any repairable system to the extent that a more accurate prediction of these two variables and a better estimate of the system reliability are available.

The models for failure types and failure times of the given machine systems would be of immense use to the maintenance crew for predicting the future failure types and failure times of any given system and subsequently organizing and fine‐tuning their state of preparedness.

The purpose of this paper is to inform facility managers of the type of failure affecting certain pipe types more than others. This is useful in asset management as preventive maintenance can be undertaken for those pipe types that experience high probabilities of failure.

The probability of a specific pipe type failing given the cause of break, age at failure, pipe diameter, and type of soil at the location of the break was found using inventory and main break data from the Honolulu Board of Water Supply (HBWS). Bayes’ theorem was then applied to find the posterior probabilities of failure starting from the prior probabilities of failure.

It was observed that the greatest probabilities of failure involved corrosion, pipes aged between 20‐30 years, 8″ pipes, and pipes in fill material. The pipe types were ranked and scored based on their probability of failing due to break cause, age, diameter, and soil type. Cast iron pipes were shown to have the highest probability of failing. As such, attention should be given to replace segments of cast iron pipes as they reach the end of their service lives.

This study serves to address a major query in asset management at a public utility, that of which pipes should be selected for replacement when they reach the end of their service life. In addition, this study helps to understand the causes of failure for the various types of pipe.

The importance of having reliable water supply at low cost has immense social implications in modern communities. To deliver such service, water pipe assets have to be managed efficiently.

This paper addresses the probability of failure in a straightforward manner that the water utility can easily apply to its own data, both in its design and asset management.

Based on appraisal theory and social response theory, this study aims to explore the mechanism of AI failure types on consumer recovery expectation from the perspective of service failure assessment and validate the moderate role of anthropomorphism level.

Three scenario-based experiments were conducted to validate the research model. First, to test the effect of robot service failure types on customer recovery expectation; second, to further test the mediating role of perceived controllability, perceived stability and perceived severity; finally, to verify the moderating effect of anthropomorphic level.

Non-functional failures reduce consumer recovery expectation compared to functional failures; perceived controllability and perceived severity play a mediating role in the impact of service failure types on recovery expectation; the influence of service failure types on perceived controllability and perceived severity is moderated by the anthropomorphism level.

The findings enrich the influence mechanism and boundary conditions of service failure types, and have implications for online enterprise follow-up service recovery and improvement of anthropomorphic design.

This study aims to examine the role played by brand equity orientation and failure type in service recovery. Specifically, through the lens of forgiveness, the way brand equity orientation and failure type influence consumer response to recovery is revealed.

This research tests a novel model using data collected from 1,589 consumers in two scenario-based experimental studies. The statistical product and service solutions (SPSS) program with the PROCESS tool was used to test the mediation and moderated mediation effects.

The research findings suggest that forgiveness plays a mediation role in the relationship between recovery and satisfaction. Brand equity orientation moderates the mediation effect of forgiveness on the relationship between recovery and recovery satisfaction. In addition, failure type also plays an important role and there is a significant three-way interaction effect (service recovery × brand equity orientation × failure type) on recovery satisfaction under certain circumstances.

Building on the extant literature which focuses on the cognitive process when investigating recovery and consumer reaction, this research advocates the significant role played by the psychological process, namely, the feeling of forgiveness, in explaining the effect of distinct recovery strategies on consumer satisfaction. This research also unveils the effects of brand equity orientation and failure type on recovery outcomes.

When addressing performance failure, brand equity orientation and failure type need to be identified. Businesses could develop recovery strategies to arouse consumer forgiveness, which would lead to increased recovery satisfaction. When designing recovery strategies, managers need to be mindful of the effects of brand equity orientation and failure type.

This research is one of the few which reveals the mediating role played by forgiveness on the effect of recovery. Taking brand equity orientation and failure type into consideration, the findings of this research provide new insights into the recovery literature.

In this study the factors behind the decision‐makers’ erroneous judgements regarding failure prediction (classification of firms as bankrupt and non‐bankrupt) are analysed. The purpose is to find out the factors causing incorrect responses, i.e. the cases in which the decision‐maker is for some reason incapable of using the given information to arrive at the correct classification. The following five possible sources of disturbance in this decision‐making were hypothesized: firm‐specific factors, data, decision‐maker‐specific factors, external factors, and failure process. In further analysis these factors were empirically operationalized and their significance was tested applying logistic (logit) analysis separately for the Type I and Type II classification errors identified in an HIP study. The results indicated that the effect of all of the five hypothesized factors on misclassifications is statistically significant. The inconsistency of the cues (firm‐specific factors) may be the main factor causing errors in evaluation. Moreover, the failure process is another important factor (Type I error). Thus, human bankruptcy prediction can be improved mainly by checking the consistency of financial statements (that they give a true view of the firm’s economic status) and by paying special attention to timely identification of the possible failure process. Future HIP studies on bankruptcy prediction and also other economic events should pay attention to control the kinds of sources of disturbance identified in this study, to maintain validity.

Considers a system (machine) that is subject to failure (breakdown). Two characterizations are presented. In the first characterization, the state of the system is described by the real age of the machine and the number of failures incurred to date. In the second characterization, the state of the system is described by the real age of the machine and the virtual age of the machine. In either characterization, upon failure, the unit may undergo a repair which can partially reset the failure intensity of the unit. The degree of reset assumed by the repair is a function of the characterization utilized. The other alternative, at a failure, is to conduct a major overhaul that serves to refresh the failure intensity of the unit. General cost structures, depending upon (real age, number of failures) in characterization one or (real age, virtual age) in characterization two are permitted. The decision, on failure to repair or renew is formulated as a discrete semi‐Markov Decision process. Optimal decisions are of the threshold type. The threshold rules depend upon the characterization.

This paper aims to explore whether demographic differences between diverse customers and service providers impact service failure and recovery perceptions.

The critical incidents technique was used to gather data on service failures and recovery. Chi‐square test of independence and analysis of variance was used to test the hypotheses.

Results from the main study provide little support to the notion that different service failure types or service recovery efforts are being applied when demographic differences exist. However, a post‐hoc analysis focusing on respondents who felt that their demographic differences had impacted their encounter revealed that ethnic differences impacted service failure and recovery perceptions the most.

One limitation is the use of quota sampling that may limit the generalizability of the results. However, due to the exploratory nature of the study and the need for representative cases, this technique was viewed as an effective sampling technique for the purposes of the study.

The post‐hoc results suggest that future diversity training should include employee‐customer diversity, especially in the case of age and ethnicity. Further, that managing perceptions is important so that customers do not feel that they are treated any differently based on a visible demographic variable.

In general, the exploration of customer‐employee demographic differences in the services marketing literature is still somewhat nascent. This paper is unique in that it specifically examines several demographic differences between customers and employees in terms of service failure and recovery perceptions.

Demonstrates a method for examining service failures and recovery strategies in service industries and provides a typology of service failures and recoveries in the restaurant industry. Based on 373 critical incidents collected from restaurant customers, uses the critical incident technique (CIT) to identify 11 unique failure types and eight different recovery strategies. Additional data regarding the magnitude of the service failure, the service recovery rating, the lapsed time since the failure/recovery incident, and customer retention rates were also collected. Presents this information along with managerial and research implications.

The purpose of this paper is to examine how service failure affects customers’ negative response and how service recovery affects perceived justice in the context of different relationship norms.

It includes four studies that examine how relationships influence customer reactions to service failures. In study 1, the paper examines how service failures affect customers’ negative reaction. In study 2, the paper examines how service recoveries influence perceived justice. Study 3 and study 4 test the robustness of the results of study 1 and study 2. All studies have a 2×2 between-subjects design.

The results show that individuals in exchange relationships experience a stronger feeling of betrayal than those in communal relationships during service failures. Further, individuals feel more betrayed and show greater negative responses during process failures. They perceive greater justice when offered physical recoveries, which, in turn, contributes to higher service-recovery satisfaction.

This study was conducted in Taiwan. Customer reactions to service failures may vary according to cultural and environmental contexts.

Service providers are encouraged to cultivate relationships with customers and identify different types of customers to compensate them more effectively, according to their preferences.

This study introduces relationship norms to investigate consumer responses to service failures. The main contributions are twofold; it investigates the effect of relationship norms on customer responses to service-failure types and service-recovery types.

Unmanned aircraft applications are quickly expanded in different fields. These systems are complex that include several subsystems with different types of technologies. Maintenance and inspection planning is necessary to obtain optimal performance and effectiveness. The failure rate in these systems is more than commercial and manned aircraft since they are usually cheaper. But maintenance and operation planning are difficult because we deal with a system that has multi-components, multi-failure models, and different dependencies between subsystems without any advanced health monitoring system. In this paper, this matter is considered and a framework to determine optimal maintenance and inspection plan for this type of system is proposed to improve system reliability and availability. The new criteria according to this field are proposed.

Maintenance of unmanned systems influences their readiness; also, according to the complexity of the system and different types of components, maintenance programming is a vital requirement. The plan should consider several criteria and disciplines; thus, multicriteria decision approaches may be useful. On another side, the reliability and safety of unmanned aircraft are the most important requirements in the design and operation phases. The authors consider these parameters and develop a framework based on risk-based maintenance to overcome the problems for unmanned systems. This framework consists of two stages: at the first stage, the critical components and failure modes are determined by FMEA, and in the second stage, the priority of maintenance tasks is determined by a fuzzy multicriteria weighted decision system. In this study, fourteen criteria with different levels of importance are developed and proposed to find the best plan for maintenance and inspection intervals. These criteria have been extracted from the literature review, the author's experience, and expert opinions.

A novel framework for risk-based maintenance has been proposed. Risk determination and risk criteria are the most important factors in this framework. Risks are determined by FMEA, and new criteria are proposed that are used for decision-making. These criteria are proposed based on practical experience and experts' opinions for the maintenance process in the aeronautic industry. These are evaluated by industrial cases, and this framework capability has been demonstrated.

The proposed framework and criteria for small unmanned aircraft have been developed based on a practical point of view and expert opinion. Thus for implementation in other aeronautic industries, the framework may need a minor modification.

Two important subsystems of an unmanned aircraft have been studied, and the capabilities of this method have been presented.

This research is original work to determine a maintenance program for unmanned aircraft that their application has rapidly grown up. Practical and design parameters have been considered in this work.