Outline

  • Abstract
  • Keywords
  • 1. Introduction
  • 2. Literature Review
  • 3. Methodology
  • 3.1. Analytic Hierarchy Process
  • 3.2. Topsis Technique
  • 3.3. Ahp Integrated Topsis-Grey
  • 4. Content Management Systems and Decision Criteria
  • 5. Numerical Case Study
  • 5.1. Case Study
  • 5.2. Sensitivity Analysis
  • 5.3. Effects of Distance Measures on the Results
  • 5.4. Comparison with Existing Studies
  • 6. Conclusion
  • References

رئوس مطالب

  • چکیده
  • کلیدواژه ها
  • 1. مقدمه
  • 2. بازنگری مطالب
  • 3. روش شناسی
  • 3.1 فرآیند سلسله مراتبی تحلیلی
  • 3.2 تکنیک TOPSIS
  • 3.3 AHP یکی شده TOPSIS-Grey
  • 4. سیستم های مدیریت محتوا و معیار های تصمیم
  • 5. مطالعه موردی عددی
  • 5.1 مطالعه موردی
  • 5.2 تحلیل حساسیت
  • 5.3 تاثیرات سنجش های مسافت در نتایج
  • 5.4 مقایسه با مطالعات موجود
  • 6. نتیجه گیری

Abstract

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.

Keywords: - - - -

Conclusions

In this paper, AHP integrated TOPSIS-Grey technique is proposed to be used in an IS selection problem. AHP is used to determine the weights of the decision criteria and TOPSIS is used to rank the alternatives. Grey numbers are included in TOPSIS method in order to deal with the uncertainties embedded in the selection problem. In the proposed approach, the tangible and intangible criteria evaluations are determined by Grey numbers as a representation of incomplete information. To the best of our knowledge this is the first study that uses Grey systems in an IS selection problem. The focal point of the study is the selection of content management system which is an important system for organizational communications. In order to demonstrate effectiveness of the proposed approach, it is applied in a real life company. Seven criteria are determined for the selection of CMS. According to the results of AHP application the most important criteria are determined as budget (0.28) which represents the total cost of ownership, followed by vendor reputation (0.25). Usability and capabilities criteria share the third place with the weight of 0.13. The least important criteria are found as technological infrastructure, duration and support criteria. However, the generalizability of the criteria weights is low and when similar studies are applied to other companies; different results can be detected based on the perception and the situation of the organization. According to these weights it can be concluded that the company searches for an economic solution from a well known vendor. On the other hand, the company does not concern the technology behind the interface and the duration of the project. In this method, the uncertainty associated with the alternative evaluations is handled by using grey numbers. Each alternative is evaluated using grey numbers and later the alternatives are ranked. The results show that Alternative 4 is the best alternative among the others.

The main contribution of this paper is twofold, utilizing Grey numbers with TOPSIS and AHP to deal with the selection problem and determining the criteria for CMS selection. The comparison of the proposed method with the existing ones reveal that, the proposed method can incorporate uncertainty in a practical way, the expert evaluations can be done more accurately when compared with linguistic variables, and the procedures of proposed methodology are less time consuming for experts. There are several research directions to be pursued in future. The proposed method can be compared with other crisp, fuzzy and grey decision making techniques. Fuzzy AHP can be used instead of crisp one, and the results can be compared. Finally, the model can be modified for group decision making allocating different decision makers from the company.

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