PurposeThe purpose of this paper is to propose a model for analysing the influence of costs of quality.Design/methodology/approachA model is designed by using a causal loop diagram and is analysed through a system dynamics approach. The model simulation is prepared by Vensim software.FindingsPrevention and appraisal costs are the two effective cost factors. The model represented in this paper reveals that prevention costs have the most effect on total cost of quality and especially external failure costs. Hence, in order to achieve the customer expected quality level, prevention and appraisal costs should be considered.Research limitations/implicationsCalculating and measuring non‐conformance costs is very difficult in organizations and some errors and mistakes may happen.Practical implicationsA system dynamics approach can analyse and measure the amount of prevention cost effects on cost of quality in different organizations.Originality/valueThe proposed methodology demonstrates the use of an innovative approach in developing a cost of quality concept and constructing a practical framework for system dynamics in a real case.

No abstract

Purpose The purpose of this study is to propose a model to evaluate the performance of organizational units considering intellectual capital (IC) and employee loyalty approach applying principal component analysis and data envelopment analysis (PCA-DEA) method. Design/methodology/approach Organization units are considered as decision-making units, IC components including human capital (HC), structural capital (SC) and customer capital are inputs and employee loyalty is output. The principal component analysis was used to converts inputs and outputs into the independent variables. As a return to scale is variable, a modified envelopment input-oriented BCC model applied to obtain the efficiency of organization units. Also, all units of organization are ranked. Eventually, sensitivity analysis performed to show how input variables influence on output variable. Findings Operation, design and construction, production planning, internal affairs, quality control and security were recognized as efficient units. Also, units of operation, internal affairs and quality control ranked first to third, and the human resource unit earned the last rank. In addition, results of sensitivity analysis on input variables showed that the order of impact intensity is: customer capital, HC and SC, respectively. Originality/value Existence a framework for the development of human resource strategies and prioritization in the allocation of organizational resources to improve the performance of the organization considering human resources is vital. Most of the previous studies, just have examined the impact of IC on different dimensions of organizational performance. Meanwhile, evaluating the performance of IC with employee loyalty approach, using PCA-DEA simultaneously can evaluate and measure the impact of IC on the performance of the organization and its units regarding employee loyalty, which has a significant impact on improving the organization’s level of IC and human resource management.

Purpose – The purpose of this paper is to prioritize service quality dimensions (SQDs) using importance-performance analysis (IPA) and to compare the results for the customer groups segmented by data envelopment analysis (DEA). Design/methodology/approach – Customers of three four-star hotels located in Isfahan have been asked to report on their expectation of service prior to receiving it as well as their perception of the service after receiving it. Afterwards, DEA has been used to assign the customers into two groups of fastidious (with relatively high expectations but low perceptions) and ordinary (with relatively low expectations but high perceptions). Next, IPA has been exploited for prioritizing SQDs in each group. Eventually, the prioritized SQDs in each group have been compared and insightful information has been extracted for further research and practical purposes. Findings – Findings imply that despite occasional similarities, there is a significant difference in the way the two groups value SQDs. Also, the segmented groups have different priorities of SQDs. Research limitations/implications – Findings revealed that in order to decrease the ambiguity of customer voice in prioritizing SQDs, it might be helpful to first segregate the participants based on their attitudes towards the quality of service to have a more congruent sample and then, to analyze the data. Practical implications – In this study, a smarter approach for prioritizing SQDs based on the data of two major groups of customers has been proposed, which can help hoteliers in devoting their resources more efficiently. Originality/value – The combination of DEA and IPA in homogenizing the sample and prioritizing SQDs for each homogenized group within the sample seems relatively novel.

No abstract

Enterprise resource planning implementation has been one of challenges of organizations during the last decade; and there have been many barriers in implementing ERP successfully. Organizations can reduce the effect of failure through identifying their strengths and weaknesses. One of the most applicable methods which may prevent occurring defects in organizations is failure mode and effect analysis (FMEA). FMEA has been used for many applications as a quality management instrument. In FMEA, risks of failure modes are identified through the estimation of severity and occurrence values. In this paper, the proposed FMEA identifies major failure causes and effect of potential defects in ERP implementation. Furthermore, critical failure factors are characterized by the severity, occurrence and detection values by using the adopted FMEA table. A case study is also presented to prove the applicability of the proposed method.

Several methods have been proposed for solving multi-criteria decision making problems (MCDM). A major criticism of MCDM is that different techniques may yield different results when applied to the same problem. A decision maker looks for a solution that is closest to the ideal, in which alternatives are evaluated according to all established criteria. The multiple criteria decision making (MCDM) methods including TOPSIS, ELECTRE and VIKOR are based on an aggregating function representing ''closeness to the ideal'', which are originated in the compromise programming method. This study provides a comparison analysis of the above-three methods: eight parallel production lines from a factory will be analyzed using these three methods and also aggregate methods will be exploited in order to compare these methods.

No abstract