A new hybrid model for quality assessment of scientific conferences based on Rough BWM and SERVQUAL

Stević, Željko; Đalić, Irena; Pamučar, Dragan; Nunić, Zdravko; Vesković, Slavko; Vasiljević, Marko; Tanackov, Ilija

doi:10.1007/s11192-019-03032-z

Cited by 19 publications

(15 citation statements)

References 62 publications

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“…Research into the nonparametric characteristics of the distribution of expectations in responses has not established a specific type of distribution in any case. Binomial distribution, established in some previous research [23] was potentially the closest, but did not meet the verification requirements with a given significance threshold of p > 0.05 in the case of expectation and perception. Therefore, the basis for further analysis is a nonparametric Signum test.…”

Section: Resultsmentioning

confidence: 81%

“…The last part of the analysis of the research results was the implementation of a Signum test where the significance between responses for expectations and perceptions were determined. Because the collected results had non-parametric characteristics that deviated from expected binomial distributions, a Signum test was used [23].…”

Section: Analysis Of the Results Obtained Comparison Of Results In Terms Of Expectations And Quality Perceptionmentioning

confidence: 99%

“…Apart from that, many organizations have improved their quality after the application of the SERVQUAL model after obtaining poor results in the initial stage. In addition, SERVQUAL is a very useful tool for recognizing customer requirements [23]. The SERVQUAL model was known as the Gap Model, and it is used to measure quality in relation to expectations and the evaluation of performance [24].…”

Section: Literature Reviewmentioning

confidence: 99%

See 2 more Smart Citations

Development of Modified SERVQUAL–MCDM Model for Quality Determination in Reverse Logistics

Stević

Tanackov

Puška³

et al. 2021

Sustainability

Self Cite

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To run a business successfully, quality determination and customer relations are very important factors. Therefore, it is necessary to measure quality and identify critical points of business. In this paper, an original integrated model for measuring the service quality of reverse logistics (RL) was developed for the company Komunalac Teslić, which was used as an example. The Delphi and Full Consistency Method (FUCOM) was applied to determine the significance of the quality dimensions, while a modified SERVQUAL (SQ) model was used to measure the service quality of the logistics. An original SQ questionnaire was formed with a total of 21 statements that were arranged in five standard dimensions. Examining the reliability of the questionnaire for quality dimensions using the Cronbach Alpha coefficient, it was found that the measurement scales for dimensions are appropriate in terms of user expectations, while in terms of quality perception there is no measurement scale for the empathy dimension. An extensive statistical analysis was then performed to verify the results. A Signum test was applied to identify the relationship between the responses in terms of expectations and perceptions, i.e., to examine their differences. The findings obtained by this research show that the expectations were higher than the perceived quality of the services and that there was a significant statistical difference for 12 of the SQ statements. For two statements, there was a significant statistical difference in favor of perceived quality compared to expectations. Based on the results obtained, the company must improve its services in order for service quality to be at a satisfactory level.

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Section: Resultsmentioning

confidence: 81%

Section: Analysis Of the Results Obtained Comparison Of Results In Terms Of Expectations And Quality Perceptionmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

See 1 more Smart Citation

Development of Modified SERVQUAL–MCDM Model for Quality Determination in Reverse Logistics

Stević

Tanackov

Puška³

et al. 2021

Sustainability

Self Cite

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“…They used this method for site selection of roundabout construction to support decision-makers in solving Doboj traffic congestion problems. Stević et al [28] extended the method of R-BWM to the service industry and explored the service quality of international technology conferences based on the Service Quality (SERVQUAL) model. A total of 104 scholars participated in the discussion of the topic, and the results showed that R-BWM effectively integrated the opinions of many scholars and developed the best weights to illustrate the relative importance of the evaluation criteria.…”

Section: Rough Best Worst Methodsmentioning

confidence: 99%

A Novel FMEA Model Based on Rough BWM and Rough TOPSIS-AL for Risk Assessment

Chang

Chen

et al. 2019

Mathematics

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Failure mode and effects analysis (FMEA) is a risk assessment method that effectively diagnoses a product’s potential failure modes. It is based on expert experience and investigation to determine the potential failure modes of the system or product to develop improvement strategies to reduce the risk of failures. However, the traditional FMEA has many shortcomings that were proposed by many studies. This study proposes a hybrid FMEA and multi-attribute decision-making (MADM) model to establish an evaluation framework, combining the rough best worst method (R-BWM) and rough technique for order preference by similarity to an ideal solution technique (R-TOPSIS) to determine the improvement order of failure modes. In addition, this study adds the concept of aspiration level to R-TOPSIS technology (called R-TOPSIS-AL), which not only optimizes the reliability of the TOPSIS calculation program, but also obtains more potential information. This study then demonstrates the effectiveness and robustness of the proposed model through a multinational audio equipment manufacturing company. The results show that the proposed model can overcome many shortcomings of traditional FMEA, and effectively assist decision-makers and research and development (R&D) departments in improving the reliability of products.

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“…For example, the RS theory mainly focuses on the attribute reduction problem [23,28] and shows much potential in the multilabel learning [29,36], while the PCA is usually applied to the dimension reduction problem in the machine learning [9,16] and multi-objective optimization (MOO) [18,20]. What's more, the RS theory reduces attributes based on the partition of equivalence relation, which can be accomplished through the evaluation metric [30,31], like mutual information and information entropy [10,38]. In general, the RS theory achieves better performance on the categorical attribute dataset [1,11].…”

Section: Literature Review 21 Index System Reduction Algorithmsmentioning

confidence: 99%

Index System Reduction Method Based on the Index Similarity

Gao

2019

Teh. vjesn.

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Multi-attribute decision making (MADM) always suffers from the result inconsistency and computational complexity problem, due to numbers of redundant and relational attributes (indexes) of the initial evaluation index system. Therefore, this paper studies the index system (IS) reduction problem through selecting the most representative indicator from each index subsystem after the IS structure partition. First, we propose and demonstrate the Index Subsystem Judgement theorem to improve the efficiency of the classic system structure partition algorithm. Second, an algorithm of index system reduction based on the index similarity (ISRS) is put forward. The ISRS is able to reduce the index quantity while still keeping the index meaning. Third, we define the direction loss rate to measure the evaluation ability loss of the IS during reduction. The algorithm is tested for a synthetic dataset to compare the proposed ISRS with different index reduction algorithms, followed by an extensive experimentation with a real-world financial dataset. Experiment results illustrate that our proposed method is able to obtain more accessible and available reduction results in practice.

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A new hybrid model for quality assessment of scientific conferences based on Rough BWM and SERVQUAL

Cited by 19 publications

References 62 publications

Development of Modified SERVQUAL–MCDM Model for Quality Determination in Reverse Logistics

Development of Modified SERVQUAL–MCDM Model for Quality Determination in Reverse Logistics

A Novel FMEA Model Based on Rough BWM and Rough TOPSIS-AL for Risk Assessment

Index System Reduction Method Based on the Index Similarity

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