An enterprise resource planning system (ERP) is the information backbone of a company that integrates and automates all business operations. It is a critical issue to select the suitable ERP system which meets all the business strategies and the goals of the company. This study presents an approach to select a suitable ERP system for textile industry. Textile companies have some difficulties to implement ERP systems such as variant structure of products, production variety and unqualified human resources. At first, the vision and the strategies of the organization are checked by using balanced scorecard. According to the company's vision, strategies and KPIs, we can prepare a request for proposal. Then ERP packages that do not meet the requirements of the company are eliminated. After strategic management phase, the proposed methodology gives advice before ERP selection. The criteria were determined and then compared according to their importance. The rest ERP system solutions were selected to evaluate. An external evaluation team consisting of ERP consultants was assigned to select one of these solutions according to the predetermined criteria. In this study, the fuzzy analytic hierarchy process, a fuzzy extension of the multi-criteria decision-making technique AHP, was used to compare these ERP system solutions. The methodology was applied for a textile manufacturing company.

Fuzzy AHP-based decision support system for selecting ERP systems in textile industry by using balanced scorecard

A state-of-the-art survey on the influence of normalization techniques in ranking: Improving the materials selection process in engineering design

An enterprise resource planning (ERP) software selection is known to be multi attribute decision making (MADM) problem. This problem has been modeled according with analytic network process (ANP) method due to fact that it considers criteria and sub criteria relations and interrelations in selecting the software. Opinions of many experts are obtained while building ANP model for the selection ERP then opinions are reduced to one single value by methods like geometric means so as to get desired results. To use ANP model for the selection of ERP for a new organization, a new group of expert's opinions are needed. In this case the same problem will be in counter. In the proposed model, when ANP and ANN models are setup, an ERP software selection can be made easily by the opinions of one single expert. In that case calculation of geometric mean of answers that obtained from many experts will be unnecessary. Additionally the effect of subjective opinion of one single decision maker will be avoided. In terms of difficulty, ANP has some difficulties due to eigenvalue and their limit value calculation. An ANN model has been designed and trained with using ANP results in order to calculate ERP software priority. The artificial neural network (ANN) model is trained by results obtained from ANP. It seems that there is no any major difficulty in order to predict software priorities with trained ANN model. By this results ANN model has been come suitable for using in the selection of ERP for another new decision.

https://isiarticles.com/bundles/Article/pre/pdf/1173.pdf

An ERP software selection process with using artificial neural network based on analytic network process approach

ERP system selection is a complex multi-criteria decision making process.Imprecision and large-number of criteria are among the most important challenges.Use of a hybrid methodology improves the decision outcomes.ANP and PROMETHEE are collectively and synergistically used in this study.The proposed methodology produced satiating results for SMEs. Enterprise Resource Planning (ERP) system, which integrates all of the units within an organization at the information level, plays an important role for a successful enterprise. With the right ERP system, it is easier to provide coordination between the units, eliminate waste and make faster and better decisions. Adopting an ERP system is a significant investment decision for a firm, therefore a great deal of attention should be given to the selection of the right system. Since there are a large number of criteria to consider in selecting an ERP system, the process itself is regarded as a complex multi-criteria decision making problem. In this study, two prevalent multi-criteria decision making techniques, Analytic Network Process (ANP) and Preference Ranking Organization Method for Enrichment Evaluations (PROMETHEE), are used in combination to better address the ERP selection problem. First, ANP is used to determine the weights of all criteria, and then, the obtained weights are used in the PROMETHEE method for optimal ranking of the alternative system choices. To demonstrate the viability of the proposed methodology, an application case is performed on the ERP selection problem for the Small Medium Enterprises (SMEs) in Istanbul, Turkey. The proposed hybrid methodology successfully ranked the alternatives and identified the best ERP system based on the information obtained from a number of SMEs participated in this study.

Selecting The Best ERP system for SMEs using a combination of ANP and PROMETHEE methods

Content Management System (CMS) is an information system that allows publishing, editing, modifying content over internet through a central interface. By the evolution of internet and related communication technologies, CMS has become a key information technology (IT) for organizations to communicate with its internal and exterior environment. Just like any other IT projects, the selection of CMS consists of various tangible and intangible criteria which contain uncertainty and incomplete information. In this paper the selection of CMS among available alternatives is regarded as a multi criteria decision making problem. A decision model which consists of seven criteria and four alternatives is built, AHP (Analytic Hierarchy Process) integrated Grey-TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) method is proposed, and applied in a Turkish foreign trade company. In the proposed model, the weights of the criteria are determined by AHP method and the alternatives are evaluated by Grey-TOPSIS. Due to the uncertainties, grey numbers are used for evaluations of the alternatives. One at a time sensitivity analysis is also provided in order to monitor the robustness of the method. Besides, the effects of using different distance functions, such as Manhattan, Euclidian and Minkowski distance functions on the results are examined.

A decision model for information technology selection using AHP integrated TOPSIS-Grey

Enterprise resource planning (ERP) systems have gained major prominence by enabling companies to streamline their operations, leverage and integrate business data process. In order to implement an ERP project successfully, it is necessary to select an ERP system which can be aligned with the needs of the company. Thus, a robust decision making approach for ERP software selection requires both company needs and characteristics of the ERP system and their interactions to be taken into account. This paper develops a novel decision framework for ERP software selection based on quality function deployment (QFD), fuzzy linear regression and zero-one goal programming. The proposed framework enables both company demands and ERP system characteristics to be considered, and provides the means for incorporating not only the relationships between company demands and ERP system characteristics but also the interactions between ERP system characteristics through adopting the QFD principles. The presented methodology appears as a sound investment decision making tool for ERP systems as well as other information systems. The potential use of the proposed decision framework is illustrated through an application.

https://isiarticles.com/bundles/Article/pre/pdf/1168.pdf

An integrated decision making approach for ERP system selection

A real options approach for evaluation and justification of a hospital information system

Flexibility in manufacturing processes provides an ability to change or even reverse the decisions made in earlier periods. The traditional economic evaluation methods of investments in flexible manufacturing systems ignore the value of flexibility, which should be one of the key issues in the justification process. Options approach appears as a means of overcoming the limitations of conventional discounted cash flow methods. In this work, a methodology for valuing expansion flexibility of flexible manufacturing systems is presented. Expansion flexibility in a phased manufacturing investment can be valued by viewing an initial investment as being analogous to purchasing an option to exchange one risky asset for another risky asset within a time period from the initial investment. While keeping the option to expand is of value, a thorough analysis requires that the opportunity cost of delaying expansion be taken into account. In this paper, an analytic approximation methodology for valuing sequent...

An Options Approach to Valuing Expansion Flexibility in Flexible Manufacturing System Investments

In this paper, a valuation approach that modifies traditional discounted cash flow (DCF) methodology is presented to incorporate the option premium of expansion flexibility while evaluating a flexible manufacturing system investment, Expansion flexibility allows for changing the production capacity in response to deviations in demand, while disregarding the assumption that management makes an irrevocable decision based on its future market expectations. Expansion flexibility provides a key strategic advantage by avoiding the large financial commitment at the initial investment stage and enabling investment in a phased manner according to the changes in market conditions. The aim of this paper is to present a thorough valuation methodology that accounts for both the benefits of keeping the option to expand alive and the loss of market share to competing firms if the expansion investment were delayed. In this paper, the value of expansion flexibility is computed using sequential exchange options. The proposed method employs an analytic approximation scheme for valuing American exchange options on dividend-paying assets. A numerical example demonstrates the application of the valuation framework. The options approach that incorporates the expansion flexibility option into the analysis results in a higher value than the standard DCF approach, which ignores the value of the option to expand. We also perform sensitivity analyses to see whether the expansion option increases in value in cases of high uncertainty where management can respond flexibly to new market information, and where the investment analysis ignoring flexibility yields a marginally positive net present value. The results of the proposed valuation framework are presented in comparison with a previous model that ignores the opportunity cost of delaying expansion investment.

Valuation of expansion flexibility in flexible manufacturing system investments using sequential exchange options

A stator assembly 28 for a gas turbine engine 10 is disclosed. The stator assembly includes an inner stator structure 54 and an outer stator structure 52. A plurality of tensioned members 50 extend radially between the structures to stiffen the structures against deflection and to restrain the structures against relative movement. In one embodiment, the inner stator structure is an engine casing 54, the outer stator structure 42 is a fan casing, and the radially extending members are a plurality of guide vanes 50.

C. Okan Özogul

Papers

An integrated decision making approach for ERP system selection

A real options approach for evaluation and justification of a hospital information system

An Options Approach to Valuing Expansion Flexibility in Flexible Manufacturing System Investments

Valuation of expansion flexibility in flexible manufacturing system investments using sequential exchange options

An Integrated Quality Function Deployment and Fuzzy Regression-Based Optimization Framework for Selecting an E-business Software System.