Multicriteria Personnel Selection by the Modified Fuzzy VIKOR Method

A methodology for personnel selection in business development: An interval type 2-based fuzzy DEMATEL-ANP approach

The employee selection procedure holds significant importance for every company or organization involved in current economic activities. It is vital to underscore staff selection since it plays a crucial role in determining a firm's success. When a corporation selects a suitable applicant for a position and initiates the recruiting process, it might mark a critical point for the firm and substantially impact its functioning. In the present study, I utilized the trapezoidal interval type-2 (IT2) fuzzy Decision-Making Trial and Evaluation Laboratory (DEMATEL) - Analytic Network Process (ANP) methodology to conduct person selection. Additionally, statistically significant values for both the primary and secondary criteria related to staff recruitment were determined. The employment of square comparison matrices is essential for implementing the DEMATEL-ANP approach. The number of subcriteria for this application is equal to that of the alternative. The approach was successfully executed without facing any obstacles. The aim of this research was to investigate the viability of employing IT2 Fuzzy Systems to handle and control uncertainty efficiently. In addition, the implementation of sensitivity analysis plays a vital role in the context of multicriteria decision-making (MCDM) techniques.

Identification of critical quality factors and critical satisfaction gaps in emergency training courses for new nurses by the multi-criteria network structure model

OBJECTIVE

To identify critical quality factors and critical satisfaction gaps in emergency training courses for new nurses through a systematic decision-making model.

METHODS

Firstly, the service quality (SERVQUAL) was used in the evaluation index system of this study. Then, the decision-making trial and evaluation laboratory (DEMATEL) method was used to analyze the relationship structure and the corresponding weights between the indicators. Finally, the importance-performance analysis (IPA) method was used to identify the categories of all indicators and the corresponding strategic directions. Fifteen new nurses in Taizhou Hospital of Zhejiang Province were selected as participants in this study.

RESULTS

The IPA results showed that "(C₁₃)," "(C₂₂)," "(C₅₂)," "(C₅₃)," "(C₅₄)," "(C₅₅)," "(C₅₆),"and "(C₅₇)" are critical satisfaction gaps. From the results of influence network and weight, empathy (C₅) was the critical quality factor of the entire training course. The influence network relationship structure and weight had a 98.1% significant confidence level, indicating good stability.

CONCLUSION

Teachers' empathy is key to the learning outcomes of new nurses in emergency nursing training courses. Hence, teachers should be attentive to the empathetic quality of their teaching methods to help new nurses gain knowledge and experience in emergency care, especially when they come from different professions and departments.

Human error identification and risk prioritization in LPG unloading operations

Objectives. Errors due to human activities in any operation are analyzed using human reliability analysis in which the principal step is to identify potential human errors followed by quantification and analysis of the error. This work intends to apply a methodology for identifying human errors and to prioritize the risk associated with them in a liquefied petroleum gas (LPG) unloading operation. Methods. The methodology uses hierarchical task analysis which provides the basic framework, along with a systematic human error reduction and prediction approach which aids in identification and categorization of the errors associated with each task with the help of predefined error taxonomy. Also, in order to quantify the risk associated with each identified error, fuzzy failure mode and effect analysis has been adopted. To rank and prioritize the risk associated with each identified error where the individual constituent components are non-commensurable in nature, the VIseKriterijumska Optimizacija I Kompromisno Resenje method has been incorporated. Results and conclusions. Applicability of the methodology presented will help comprehend the severity of risk corresponding to each error at different levels, and the ranking mechanism thus developed in this work aids to prioritize the action to minimize the likelihood of errors.

A Hybrid Fuzzy Decision Model for Evaluating MEMS and IC Integration Technologies

Integrated devices incorporating MEMS (microelectromechanical systems) with IC (integrated circuit) components have been becoming increasingly important in the era of IoT (Internet of Things). In this study, a hybrid fuzzy MCDM (multi-criteria decision making) model was proposed to effectively evaluate alternative technologies that incorporate MEMS with IC components. This model, composed of the fuzzy AHP (analytic hierarchy process) and fuzzy VIKOR (VIseKriterijumska Optimizacija I Kompromisno Resenje) methods, solves the decision problem of how best to rank MEMS and IC integration technologies in a fuzzy environment. The six important criteria and the major five alternative technologies associated with our research themes were explored through literature review and expert investigations. The priority weights of criteria were derived using fuzzy AHP. After that, fuzzy VIKOR was deployed to rank alternatives. The empirical results show that development schedule and manufacturing capability are the two most important criteria and 3D (three-dimensional) SiP (system-in-package) and monolithic SoC (system-on-chip) are the top two favored technologies. The proposed fuzzy decision model could serve as a reference for the future strategic evaluation and selection of MEMS and IC integration technologies.

A DATA-DRIVEN MADM MODEL FOR PERSONNEL SELECTION AND IMPROVEMENT

Personnel selection and human resource improvement are characteristically multiple-attribute decision-making (MADM) problems. Previously developed MADM models have principally depended on experts’ judgements as input for the derivation of solutions. However, the subjectivity of the experts’ experience can have a negative influence on this type of decision-making process. With the arrival of today’s data-based decision-making environment, we develop a data-driven MADM model, which integrates machine learning and MADM methods, to help managers select personnel more objectively and to support their competency improvement. First, RST, a machining learning tool, is applied to obtain the initial influential significance-relation matrix from real assessment data. Subsequently, the DANP method is used to derive an influential significance-network relation map and influential weights from the initial matrix. Finally, the PROMETHEE-AS method is applied to assess the gap between the aspiration and current levels for every candidate. An example was carried out using performance data with evaluation attributes obtained from the human resource department of a Chinese food company. The results revealed that the data-driven MADM model could enable human resource managers to resolve the issues of personnel selection and improvement simultaneously, and can actually be applied in the era of big data analytics in the future.

Analysis of Priority Scale for Watershed Reforestation Using Trapezoidal Fuzzy VIKOR Method: A Case Study in Semarang, Central Java Indonesia

Recently, resolving a problem based on multi-criteria decision-making systems has become an attractive method. One of recent techniques is trapezoidal fuzzy VIKOR method which was used for selecting the best option among criteria. This research is aimed to utilize the VIKOR method in prioritization of watershed reforestation in Semarang City, Indonesia. Several criteria have been set for the prioritization of reforestation areas to select watersheds as reforestation targets. In this case, the six criteria and six alternatives were used in order to determine the best priority of reforestation. The result showed that VIKOR method was successfully applied to determine the best option and Kali Garang watershed was the top priority as it has the highest rank and it meets reforestation criteria compared with other watersheds criteria.