Özay Özaydın

Optimizing Fire Station Locations for the Istanbul Metropolitan Municipality

The Istanbul Metropolitan Municipality IMM seeks to determine locations for additional fire stations to build in Istanbul; its objective is to make residences and historic sites reachable by emergency vehicles within five minutes of a fire station’s receipt of a service request. In this paper, we discuss our development of a mathematical model to aid IMM in determining these locations by using data retrieved from its fire incident records. We use a geographic information system to implement the model on Istanbul’s road network, and solve two location models—set-covering and maximal-covering—as what-if scenarios. We discuss 10 scenarios, including the situation that existed when we initiated the project and the scenario that IMM implemented. The scenario implemented increases the city’s fire station coverage from 58.6 percent to 85.9 percent, based on a five-minute response time, with an implementation plan that spans three years.

A decision support methodology to enhance the competitiveness of the Turkish automotive industry

Three levels of competitiveness affect the success of business enterprises in a globally competitive environment: the competitiveness of the company, the competitiveness of the industry in which the company operates and the competitiveness of the country where the business is located. This study analyses the competitiveness of the automotive industry in association with the national competitiveness perspective using a methodology based on Bayesian Causal Networks. First, we structure the competitiveness problem of the automotive industry through a synthesis of expert knowledge in the light of the World Economic Forum’s competitiveness indicators. Second, we model the relationships among the variables identified in the problem structuring stage and analyse these relationships using a Bayesian Causal Network. Third, we develop policy suggestions under various scenarios to enhance the national competitive advantages of the automotive industry. We present an analysis of the Turkish automotive industry as a case study. It is possible to generalise the policy suggestions developed for the case of Turkish automotive industry to the automotive industries in other developing countries where country and industry competitiveness levels are similar to those of Turkey.

Critical Success Factors for the Iron and Steel Industry in Turkey: A Fuzzy DEMATEL Approach

The attempt to improve the efficiency and competitiveness of an industrial sector is aided by the determination of critical success factors (CSFs) which focus efforts in those areas that really affect the whole industry, thereby conserving limited resources. In this paper, a three-stage methodology is proposed to find CSFs for an industrial sector. The methodology specifies the interrelations between factors that shape the global competitiveness of a country as a whole and those that shape the competitiveness of the particular industry in question. It integrates a Web-based survey, a Delphi-type workshop, and a fuzzy decision making trial and evaluation laboratory model to highlight those CSFs upon which policymakers should especially concentrate in order to increase the competitiveness of a given industry. This methodology is then applied to a case study, identifying the CSFs of the iron and steel industry in Turkey. The results show that the burden of custom procedures, total tax rate, scope and impact of taxation, and solidity of banks are the CSFs for the competitiveness of the Turkish iron and steel industry.

Cumulative belief degrees approach for analyzing the competitiveness of the automotive industry

As traditional competition becomes global, businesses fail to take, on their own, the measures that are required to become more competitive. Hence, in a globally competitive environment, national improvement and competitiveness have also become vital. Businesses must utilize and be supported by the international competitiveness of their nations. This study aims to analyze the competitiveness of the automotive industry from a national competitiveness perspective, using a three-stage methodology. For this purpose, a novel cumulative belief degrees (CBD) approach is introduced, to quantify the causal relations among the variables in the system. This methodology is illustrated by the analysis of the Turkish automotive industry for developing suggestions to assist policymakers in their decisions to improve the competitiveness of the industry. Although the findings are country specific, the methodology is applicable to a wider range of industries in developed and developing countries.

Analyzing competitiveness of automotive industry through cumulative belief degrees

Ulengin, Fusun (Dogus Author) -- Onsel, Şule (Dogus Author) -- Kabak, Ozgur (Dogus Author) -- Conference full title: 10th International Fuzzy Logic and Intelligent Technologies inNuclear Science Conference, FLINS 2012; Istanbul; Turkey; 26 August 2012 through 29 August 2012