Trust-based performance measurement using fuzzy operators

Abstract

Performance assessment is a critical aspect for any organization, as it provides them with the means to measure their performance. Decision makers and top management need to gain a comprehensive view of the capabilities and performance of decision making units (DMU's) in order to make efficient decisions and beneficial improvements. In this study a novel model has been proposed to place performance assessment outputs in linguistic form, which utilize proper trust labels. Trust labels provide explicit qualitative scales, instead of representing pure numerical data, which are more meaningful for top manager. Fifteen scenarios are formed based on two main factors: the number of decision making units and the number of timeslots, which together form the basis of the proposed method for performance assessment. The efficiency rates of the current, previous and following years, along with the average efficiency and standard deviation, are the five inputs to this model. The approach uses time series forecasting to predict the future efficiency rate and is armed with an Auto Correlation Function (ACF) for input selection. The model utilizes fuzzy t-norm and snorm as the final modeling tools. To show the applicability and superiority of the proposed model, it is applied to a data set provided by running a simulation structured by a unique logic.

A Performance Measurement Model Minimizing Housekeeping Personnel Costs

“…Tyagi et al [20] analyze the enablers in order to implement a flexible supply chain performance measurement system using fuzzy decision-making trial-and-evaluation laboratory approach. Azadeh et al [1] propose a novel model to place performance assessment outputs in linguistic form, which utilize proper trust labels. De Sousa et al [6] identify and International Journal of Fuzzy Systems classify uncertainty components of performance measurement systems, and propose a qualitative method for performance measurement systems' quality assessment using fuzzy logic.…”

A trust-based performance measurement modeling using t-norm and t-conorm operators

“…In Wang et al [28] a trust evaluation model for mobile e-commerce trading platform was proposed which was formed based on an improved Grey-prediction model. Azadeh et al [29] proposed the only work which utilized the concept of trust in order to put the performance measurement outputs in a linguistic form. A trust-based credit scoring approach which made use of an artificial neural network-based model to classify potential customers according to various categories was proposed by Mirtalaei et al [30].…”