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Very little research addresses whether the values that consumers bring to a situation can affect their reactions to a brand failure. This paper suggests the interesting possibility that consumers may react very differently to the same brand failure depending upon their values. Here, the authors introduce a new construct to the marketing literature – honor values – and demonstrate its effect on responses to brand failures.

Three experiments and one secondary data study were utilized.

Across four studies, honor values are shown to aggravate consumers’ desire for vengeance following a brand failure. That is, as honor values increase, so too does desire for vengeance in the face of a brand failure. Additionally, this desire can be attenuated by allowing the consumer to play a role in resolving the failure or by giving a heartfelt apology.

High-honor consumers are a major obstacle for firms facing a brand failure. To overcome this challenge, the authors offer strategies, including (1) allowing high-honor consumers to suggest ways to punish the offending employee, and (2) offering simple, heartfelt apologies to high-honor consumers, which are as effective as monetary compensations.

The healthcare system is regarded as one of the most critical service industries. The surgical unit is the heart of hospitals in that any failures directly affect the safety of patients, so they should be managed thoroughly. It is an intricate multi-attributes decision-making problem with uncertainty. Uncertain information in the form of fuzzy sets theory has been applied widely to describe the different aspects of system uncertainty. This study aims to present a new methodology to manage the healthcare system failures due to the multi-attributes decision-making process.

This study introduces a new risk evaluation methodology by failure mode and effect analysis (FMEA) and MULTIMOORA method. Group decision-making process in this methodology is presented under uncertain information in the form of interval-valued hesitant fuzzy linguistic sets (IVHFLSs). IVHFLSs encompass both qualitative and quantitative interpretation of experts to reflect their preferences, as well the ability and flexibility of derivation of linguistic information by several linguistic terms increase. To avoid the different ranking order of MULTIMOORA approaches, a new interval multi-approaches multi-attribute methodology, namely, technique of precise order preference (TPOP), is extended to provide precise ranking order.

The application and precision of proposed integrated IVHFL-MULTIMOORA methodology with TPOP is examined in a case study of healthcare systems. The results indicate the superiority of proposed methodology to prioritize and assess the failures as well as handling system uncertainty.

This study addresses the challenges of an organization to prioritize potential failures by implementing FMEA method. Moreover, this paper contributes to making the manager's ability in decision-making. The value of this study can be discussed in two aspects. First and foremost, this study provides a new FMEA-based methodology to rank failures precisely. The results prove that the proposed methodology is more robust to changes of different ranking order methods, applied by FMEA. On the other hand, using the capability of IVHFLSs allows collecting accurate information in an ambiguous and uncertain environment.

This paper seeks to present a prognostics approach using the Mahalanobis distance (MD) method to predict the reliability of multilayer ceramic capacitors (MLCCs) in temperature‐humidity‐bias (THB) conditions.

Data collected during THB testing of 96 MLCCs were analyzed using the MD method. In the THB tests, three parameters (capacitance (C), dissipation factor (DF), and insulation resistance (IR)) were monitored in situ. A Mahalanobis space (MS) was formed from the MD values of a set of non‐failed MLCCs. MD values for the remaining MLCCs were compared with an MD threshold. Data for MLCCs which exceeded the threshold were examined using the failure criteria for the individual electrical parameters to identify failures and precursors to failure.

It was found that the MD method provided an ability to detect failures of the capacitors and identify precursors to failure, although the detection rate was not perfect.

It was observed that the quality and construction of the MS, together with the choice of the MD threshold, were the critical factors determining the sensitivity of the MD method. Recommendations are offered for improved sensitivity to enable assessment of intermittent failures.

MD analysis of the multivariate MLCC data set illustrates how detection of failures can be simplified in a system for which several parameters were monitored simultaneously. This makes the MD method of great potential value in a health‐monitoring system.

This study aims to improve the reliability of emergency safety barriers by using the subjective safety analysis based on evidential reasoning theory in order to develop on a framework for optimizing the reliability of emergency safety barriers.

The emergency event tree analysis is combined with an interval type-2 fuzzy-set and analytic hierarchy process (AHP) method. In order to the quantitative data is not available, this study based on interval type2 fuzzy set theory, trapezoidal fuzzy numbers describe the expert's imprecise uncertainty about the fuzzy failure probability of emergency safety barriers related to the liquefied petroleum gas storage prevent. Fuzzy fault tree analysis and fuzzy ordered weighted average aggregation are used to address uncertainties in emergency safety barrier reliability assessment. In addition, a critical analysis and some corrective actions are suggested to identify weak points in emergency safety barriers. Therefore, a framework decisions are proposed to optimize and improve safety barrier reliability. Decision-making in this framework uses evidential reasoning theory to identify corrective actions that can optimize reliability based on subjective safety analysis.

A real case study of a liquefied petroleum gas storage in Algeria is presented to demonstrate the effectiveness of the proposed methodology. The results show that the proposed methodology provides the possibility to evaluate the values of the fuzzy failure probability of emergency safety barriers. In addition, the fuzzy failure probabilities using the fuzzy type-2 AHP method are the most reliable and accurate. As a result, the improved fault tree analysis can estimate uncertain expert opinion weights, identify and evaluate failure probability values for critical basic event. Therefore, suggestions for corrective measures to reduce the failure probability of the fire-fighting system are provided. The obtained results show that of the ten proposed corrective actions, the corrective action “use of periodic maintenance tests” prioritizes reliability, optimization and improvement of safety procedures.

This study helps to determine the safest and most reliable corrective measures to improve the reliability of safety barriers. In addition, it also helps to protect people inside and outside the company from all kinds of major industrial accidents. Among the limitations of this study is that the cost of corrective actions is not taken into account.

Our contribution is to propose an integrated approach that uses interval type-2 fuzzy sets and AHP method and emergency event tree analysis to handle uncertainty in the failure probability assessment of emergency safety barriers. In addition, the integration of fault tree analysis and fuzzy ordered averaging aggregation helps to improve the reliability of the fire-fighting system and optimize the corrective actions that can improve the safety practices in liquefied petroleum gas storage tanks.

The paper aims to construct a method to simulate the relationship between the parameters of soil properties and the area of sliding mass of the true slip surface of a landslide.

The smoothed particle hydrodynamics (SPH) algorithm is used to calibrate a response surface function which is adopted to quantify the area of sliding mass of the true slip surface for each failure sample in Monte Carlo simulation. The proposed method is illustrated through a homogeneous and a heterogeneous cohesive soil slope.

The comparison of the results between the proposed method and the traditional method using the slip surface with minimum factor of safety (FS_min) to quantify the failure consequence has shown that the landslide risk tends to be attributed to a variety of risk sources, and that the use of a slip surface with FS_min to quantify the consequence of a landslide underestimates the landslide risk value. The difference of the risk value between the proposed method and the traditional method increases dramatically as the uncertainty of soil properties becomes significant.

A geotechnical engineer could use the proposed method to perform slope failure analysis.

The failure consequence of a landslide can be rationally predicted using the proposed method.

Describes research into the problem of estimating the distribution parameters of failure data of industrial equipment subject to two failure modes. It is assumed that time to failure data are available, but it is unknown for each failure which of the two main failure modes caused the event. A loglikelihood method was developed and tested on generated mixed failure mode data. Shortcomings of this method triggered the development of two additional methods, MINESS and MINESS+, which minimize the error sum of squares of the reliability function, after separating the failure data into two sets.

Previous works in constructing interaction diagrams have only focused on incorporating transient creep strain implicitly in the ultimate limit strain. The present paper aims to use different approaches to define concrete ultimate limit strain (failure strain) envelops at high temperatures for preloaded and unloaded, confined and unconfined, columns during heating are proposed. These approaches are chosen to understand the effect of using different techniques to determine transient creep strain on the resulted N_u–M_u diagrams.

Transient creep strain is included within the concrete ultimate limit strain relationships, implicitly and explicitly, by four different ways, and accordingly, four different failure criteria are suggested. To define the concrete ultimate limit strain, studies are conducted to evaluate the compression strain corresponding to the maximal flexural capacity at elevated temperatures. In the analysis, the thermal and structural analyses are decoupled and, based on the resulted ultimate limit strain, the N_u – M_u diagrams are constructed at different fire exposures.

The validity of the proposed model is established by comparing its predictions with experimental results found in the literature. Finally, comparative calculations regarding interaction diagrams obtained by the proposed model and by other methods found in the literature are performed. It was found that the proposed model predictions agree well with experimental results. It was also found that the suggested approaches, which include simplifications, reasonably predicted the exact column capacity.

The model.

This paper aims to develop a system dynamics (SD) model to identify causal relationships among the elements of failure modes and effects analysis (FMEA), i.e. failure modes, effects and causes.

A causal loop diagram (CLD) has been developed based on the results obtained from interdependencies and correlations analysis among the FMEA elements through applying the integrated approach of FMEA-quality function deployment (QFD) developed by Shaker et al. (2019). The proposed model was examined in a steel manufacturing company to identify and model the causes and effects relationships among failure modes, effects and causes of a roller-transmission system.

Findings indicated interactions among the most significant failure modes, effects and causes. Moreover, corrective actions defined to eliminate or relieve critical failure causes. Consequently, production costs decreased, and the production rate increased due to eliminated/decreased failure modes.

The application of CLD illustrates causal relationships among FMEA elements in a more effective way and results in a more precise recognition of the root causes of the potential failure modes and their easy elimination/decrease. Therefore, applying the proposed approach leads to a better analysis of the interactions among FMEA elements, decreased system's failure rate and increased system availability.

The literature review indicated a few studies on the application of SD methodology in the maintenance area, and no study was performed on the causal interactions among FMEA elements through an FMEA-QFD based SD approach. Although the interactions of these elements are significant and helpful in risks ranking, researchers fail to investigate them sufficiently.

This paper tested a model to collect the voice of the customer to improve service delivery in call centers using the concept of failure demand. Customer responses are quantified for improvement in service delivery. There are many academic studies reporting effective and validated research methodologies to measure service quality. However, these methods are complex and unwieldy. The purpose of this paper is to adapt the lean service concept of working from the customer's viewpoint – to measure, then improve customer satisfaction, and thereby reduce costs.

A checklist of best practices for call centers was developed from the literature and multiple iterations used to develop a three part call evaluation system to include value demand, failure demand, not able to determine, and value demand as stated by the customer.

The findings indicated that the value/failure demand measurement system was useful and many failure demand occurrences occurred.

This paper is limited to service providers in call centers and their managers. Call center operators logged customer perceptions so it has the potential to lack objectivity.

Service providers need simple tools to assess operations, improve quality, and efficiency. This paper will assist in the development of an easy‐to‐use and generic tool for the continuous improvement of services.

The paper is one of very few studies that use the actual customer voice to measure failure demand and call centers can apply this process.

The purpose of this study is to introduce a relatively simple method of probabilistic analysis on the dimensions of gravity retaining walls which might lead to a more accurate understanding of failure. Considering the wall geometries in the case of allowable stress design, the probability of wall failure is not clearly defined. The available factor of safety may or may not be sufficient for the designed structure because of the inherent uncertainties in the geotechnical parameters. Moreover, two cases of correlated and uncorrelated geotechnical variables are considered to show how they affect the results.

This study is based on the failure and stability of gravity retaining walls which can be stated in three different modes of sliding, overturning and the foundation-bearing capacity failure. Each of these modes of failure might occur separately or simultaneously with a corresponding probability. Monte Carlo simulation and Taylor series method as two conventional methods of probability analysis are implemented, and the results of an assumed example are calculated and compared together.

The probability analysis of the failure in each mode is calculated separately and a global failure mode is introduced as the occurrence of three modes of sliding, overturning and foundation-bearing capacity failure. Results revealed that the global mode of failure can be used along with the allowable stress design to show the probability of the worst failure condition. Considering the performance and serviceability level of the retaining structure, the global failure mode can be used. Furthermore, the correlation of geotechnical variables seems to be relatively more dominant on the probability of global failure comparing to each mode of failure.

The introduced terminology of global mode of failure can be used to provide more information and confidence about the design of retaining structures. The resulted graphs maintain a thorough insight to choose the right dimensions based on the required level of safety.