Yazar "Ersoz S." seçeneğine göre listele

Listeleniyor 1 - 2 / 2
  • [ X ]
    Öğe
    A non-linear programming model with fuzzy evaluations for customer satisfaction index estimation
    (Computers and Industrial Engineering, 2014) Aktepe A.; Ersoz S.; Toklu B.
    Customer satisfaction index (CSI) is a cause-and-effect model of advanced customer satisfaction analysis. CSI models are used by several private and public institutions for developing key customer strategies throughout the world. Index values are based on predictions of customer evaluations. In the literature CSI is mostly modeled with linear statistical estimation methods. In a few of the studies, non-linear approach is used for estimation. Estimation of CSI with minimum error results in a more reliable and robust prediction. Therefore, in this study we propose a non-linear programming model for estimating CSI with fuzzy customer evaluations minimizing estimation errors. The estimation model brings significant contributions in this field of study. With the help of the model, we can find weights of measurement variables of a latent variable with minimized squared errors which is a key success factor in producing reliable indexes. In addition the model enables us to find coefficients of prediction equations that contribute to extend evaluation of index results. The model is also tested with data of a comprehensive survey application and application results are included.
  • [ X ]
    Öğe
    Personnel evaluation under intuitionistic fuzzy environment
    (Ismail Saritas, 2020) Kokoc M.; Ersoz S.
    In this paper, a new approach is proposed to solve multi-person and multi-attribute evaluation problems under an intuitionistic fuzzy environment. The proposed evaluation approach is mainly grounded on the integration of the score function and aggregation operator for intuitionistic fuzzy sets. To illustrate the application of the novel approach, a numerical example for evaluating engineers according to attributes of T-shaped engineers is given. The novelty of this study is that it defines T-shaped engineer selection as a multi-attribute evaluation problem in the literature for the first time. In addition, it proposes an integrated intuitionistic fuzzy evaluation approach in which the candidates are evaluated at both technical (hard) skills and non-technical (soft) skills. This study contributes to the literature as it provides a novel insight into the theoretical ground of the personnel selection problem. © 2020, Ismail Saritas. All rights reserved.