Coşkun Özkan

The Fuzzy ART algorithm: A categorization method for supplier evaluation and selection

For most of managers purchasing is a strategic issue. Thus, to select the suitable suppliers has strategic importance for every company. The objective of supplier selection is to reduce purchasing risk, maximize overall value to the purchaser and build a long term, reliable relationship between buyers and suppliers. Many methods have been proposed and used for supplier evaluation and selection; most of them try to rank the suppliers from the best to the worst and to choose the appropriate supplier(s). Supplier evaluation and selection is a complex and typical multi criteria decision-making problem. Because of human judgment needs in many area of supplier selection such as preferences on alternatives or on the attributes of suppliers or the class number and borders supplier selection becomes more difficult and risky. In this study, a new tool for supplier selection is proposed. In this paper, we applied Fuzzy Adaptive Resonance Theory (ART)s classification ability to the supplier evaluation and selection area. The proposed selection method, using Fuzzy ART not only selects the most appropriate supplier(s) and also clusters all of the vendors according to chosen criteria. To explain the Fuzzy ART method a real-life supplier selection problem is solved and suppliers are categorized according to their similarities. The obtained results show that the proposed method is well suited as a decision-making tool for supplier evaluation and selection problem.

Development of a customer satisfaction index model: An application to the Turkish mobile phone sector

Purpose – The purpose of this study is to develop and test a new customer satisfaction index model for Turkish mobile phone sector (TMPS).Design/methodology/approach – Based on relevant literature and theoretical considerations on customer satisfaction, a new measurement model was developed. A survey based on the proposed model was conducted to 700 mobile phone users in Istanbul. Partial least squares method was employed to estimate the proposed structural equation model (SEM).Findings – The general applicability of a SEM depends on the reliability and validity of the modeling results. The proposed satisfaction model exhibits strong explanatory power with its satisfactory reliability and validity results.Research limitations/implications – The proposed model was tested for the TMPS. It should ideally be tested periodically for different sectors with more data, and the index results should be compared.Practical implications – The results of this study provide very important information for the managers in ...

Multiple Criteria ABC Analysis with FCM Clustering

The number of stock keeping units (SKUs) possessed by organizations can easily reach quite a few. An inventory management policy for each individual SKU is not economical to design. ABC analysis is one of the conventionally used approaches to classify SKUs. In the classical method, the SKUs are ranked with respect to the descending order of the annual dollar usage, which is the product of unit price and annual demand. The few of the SKUs that have the highest annual dollar usage are in group A and should be taken into account mostly; the SKUs with the least annual dollar usage are in group C and should be taken into account least; the remaining SKUs are in group B. In this study, we proposed fuzzy c-means (FCM) clustering to a multicriteria ABC analysis problem to help managers to make better decision under fuzzy circumstancse. The obtained results show that the FCM is a quite simple and an easily adaptable method to inventory management.

Use of Partial Least Squares (PLS) in TQM Research: TQM Practices and Business Performance in SMEs

Advances in structural equation modeling (SEM) techniques have made it possible for management researchers to simultaneously examine theory and measures. When using sophisticated SEM techniques such as covariance-based structural equation modeling (CBSEM) and partial least squares (PLS), researchers must be aware of their underlying assumptions and limitations. SEM models such as PLS can help total quality management (TQM) researchers achieve new insights. Researchers in the area of TQM need to apply this technique properly in order to better understand the complex relationships proposed in their models. This paper attempts to apply PLS in the area of TQM research. Consequently, special emphasis is placed on identifying the relationships between the most prominent TQM constructs and business performance based on a sample of SMEs operat- ing in the Turkish textile industry. The analysis of PLS results indicate that a good deal of support is found for the proposed model where a satisfactory per- centage of the variance in the dependent constructs is explained by the independent constructs.

Determination of Effective Parameters for Coal Moisture Content Determination Using a ‘Design of Experiment’ Method

ABSTRACT Drying of low rank coal is a very significant topic due to its high economic value. One of the most important parameter in the designing of a dryer is the exiting moisture content of the material at the specified conditions and time. Aim of this study was to utilize the design of experiment methodology to determine the most effective parameters on the moisture content of the dried coal. The investigated parameters were dryer bed height, coal particle size, inlet drying air velocity, inlet drying air temperature, inlet drying air relative humidity, exit drying air relative humidity, and time. The results showed that bed height and time were the most effective parameters, and inlet air relative humidity and inlet drying air velocity were less effective parameters. Additionally, particle size and inlet drying air temperature parameters were also significant. To attain more accurate results in the prediction of the exiting coal moisture content, only more influential parameters may be used. Therefore, the design of experiment methodology was a significant way of determining the effective parameters in the coal drying process.

Fuzzy adaptive resonance theory approach to supplier involvement in product development: a case study in Turkish automobile industry

This study proposes a mechanism to evaluate suppliers for involvement during product development process. The proposed methodology is discussed within a multinational automobile firm and preliminary analysis indicates that the approach provides an effective mechanism for selecting suppliers involved in the product development process. To remedy to supplier integration problems, a clustering approach – fuzzy adaptive resonance theory (Fuzzy ART) – is used. The proposed methodology is explained using a case study that is realised in an automobile firm. Eventually, the results are presented comparatively, which obtained by current supplier evaluation system of the firm and provided from Fuzzy ART methodology. [Submitted 14 July 2009; Revised 16 November 2009; Accepted 17 November 2009]