International competitiveness power and human development of countries

Human development should be the ultimate objective of human activity and its aim should be healthier, longer, and fuller lives. It is expected that if the competitiveness of a country is suitably managed, human welfare will be enhanced as a consequence. The research described here seeks to explore the relationship between the competitiveness of a country and its use for human development. For this purpose, 45 countries were evaluated using data envelopment analysis, where the global competitiveness indicators are taken as input variables and the human development index indicators as output variables. A detailed analysis is also conducted for the emerging economies

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

This is the post-print (final draft post-refereeing) version of the article. Copyright @ 2013 Elsevier B.V. All rights reserved.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

Analyzing two-way interaction between the competitiveness and logistics performance of countries

Logistics has crucial importance in national and international trade and, hence, in the development and competitiveness of a country. On the other hand, making investments in different pillars of competitiveness, such as infrastructure, higher education, etc., is expected to enhance logistics performance. In this study, this two-way interaction between the competitiveness and logistics performance of countries is investigated using a hybrid methodology. Initially, the causal directions between the competitiveness of countries and their logistics performance are established by using a Bayesian Net (BN). Subsequently, the cause-effect information gathered from the BN is taken as the input in a Partial Least Square (PLS) path model to highlight the competitiveness pillars that are more critical in contributing to countries’ logistics performance. As the last step, an importance performance map analysis (IPMA) is applied to specify the importance of the pillars that have a significant effect on logistics performance. As a result, a roadmap is provided to policymakers that specify which pillars to focus on, thus delivering a significant and immediate improvement in the logistics performance and highlighting which logistics performance indicators will lead to improvements in the competitiveness of the countries. An empirical study is conducted based on two basic indexes, as follows: (1) the Global Competitiveness Index (GCI) and its pillars are used to track the competitiveness performance, and (2) the Logistics performance Index (LPI) is used to analyze the logistics performance. According to the results, the most important GCI pillars that affect the logistics performance of a country are determined to be “Business Sophistication”, “Financial Market Development”, “Infrastructure” and “Good Market Efficiency” and “Higher Education and Training”. On the other hand, the improvement in the logistics performance index, in its turn, will especially influence the Market Size pillar of a country

Possibilistic linear programming approach for fuzzy Supply Chain Planning

Son yıllarda, küreselleşmeyle artan rekabet ile birlikte, Tedarik Zinciri Planlamanın (TZP) önemi artmaktadır. Bu nedenle; TZP’de stratejik kararlarının verilmesi çok büyük önem taşımaktadır. Gerçek problemlerin hepsinde görüldüğü gibi, tedarik zincirinin ilgili süreçlerinde de belirsizlikler ile karşılaşılmaktadır. Bundan ötürü; TZP modellerinde belirsizliklerin göz ardı edilmemesi gerekmektedir. Literatürde TZP’deki belirsizlikleri modelleyen çalışmalarda uzun dönemli stratejik kararların kesin olarak verildiği ve bunların orta ve kısa vadede revize edilmeleri gerektiği tespit edilmiştir. Bu çalışmada, uzun dönemli kaynak atama, ürün tedariki ve üretim kararlarının verilebilmesi için bir Olabilirsel Doğrusal Programlama (ODP) modeli geliştirilmiştir. ODP modelini kullanmanın temel amacı, tedarikçi ilişkilerinde ve üretim planlamada esneklik sağlamak üzere bulanık kararların verilmesini olanaklı kılmaktır. Bu yüzden önerilen ODP’de, sadece talep ve verim oranları gibi kritik TZP girdileri değil aynı zamanda satış miktarı, üretim miktarı ve tedarik miktarı gibi karar değişkenleri de bulanık kabul edilmiştir. Önerilen ODP’nin amacı firmanın tedarik zinciri faaliyetleri sonucunda oluşan kârı en büyüklemektedir. Çalışmada ODP’yi çözmek için DP modeline çevrilmesi önerilmiştir. Bu amaçla girdi parametreleri ve karar değişkenleri üçgen bulanık sayılar ile ifade edilmiştir. ODP’de önerilen amaç fonksiyonu ve kısıtlar, üçgen bulanık sayılar için geliştirilen toplama ve çarpma işlemleri ile büyüktür/küçüktür ilişkileri ile DP’ye çevrilmiştir. Çalışmada ayrıca önerilen modelin etkinliği hipotetik bir örnek üzerinde gösterilmiştir. Anahtar Kelimeler: Tedarik Zinciri Planlama, olabilirsel doğrusal programlama, bulanık modelleme.The interest in Supply Chain Planning (SCP) has recently raised due to the fact that the opportunity of an integrated planning of the supply chain (SC) can increase the profitability, reduce production and outsourcing costs and enhance customer service levels, so that the enterprises can cope with increasing competitiveness introduced by the market globalization. A SC is an integrated system which synchronizes a series of inter-related business processes in order to convert raw materials into the specified finished products and distribute and promote these products to retailers or customers. Supply chain planning problems are due to uncertainties like the other real life problems. Uncertainties that affect the SCs can be categorized in two groups: (i) environmental uncertainties, and (ii) system uncertainties. Environmental uncertainties include supply quantity, raw material costs, lead times, and demand product price while system uncertainties contain operation efficiency, resource usage efficiency, labor cost, production capacity, and stock level. Among these uncertainty types, demand has been the most important and extensively studied source of uncertainty. The emphasis on incorporating demand uncertainty into the planning decisions is appropriate given the fact that effectively meeting customer demand is what mainly drives most SCP initiatives. Furthermore, demand is the main source of uncertainties as the fluctuations of it affects the production system and suppliers gradually. The main idea of the proposed model is to make uncertain and therefore flexible decisions to cope with the uncertainties revealed in strategic SCP. Demand affects system uncertainty in which some other types of uncertainty also exist. System uncertainty and supply uncertainty mutually affects each other. In this circumstances to make crisp decisions may cause irrelevant or irreversible long term decisions that will need huge revisions in medium or short term. In this paper a Possibilistic Linear Programming (PLP) model is proposed to support strategic decisions of the enterprises concerning the production resources utilization and outsourcing. In order to deal with the external and internal uncertainties fuzzy inputs and fuzzy outputs are considered. The problem examined in the paper is  described as; Given: (1) A supply chain that is the integration of the focal enterprise, its current suppliers and customers, as well as the potential suppliers and customers, and related products, semi-products and raw materials (in the rest of the paper "product" will be used for these three concepts),(2) Resources used to produce the products as well as their costs and capacity levels,(3) Outsourced products and other outsourcing opportunities, as well as their costs,(4)Production and outsourcing yield rates of product. Using the inputs defined above, the model proposed helps the enterprise make decisions about the following strategic questions: (1) Which product should be produced internally? (2) Which resources should be utilized to the production of which product? (3) Which products should be outsourced, and how much? (4) Demands of which market should be satisfied? The proposed PLP contains fuzziness in some of the constraint parameters and in all decision variables. The objective of the PLP model is to maximize the profit of enterprise's SC facilities. To solve the proposed PLP model it is suggested to be transformed into a linear programming model, which can be solved easily with the least mathematical effort. Therefore the inputs and the decision variables of the model are represented by triangular fuzzy numbers. Then  the summation, multiplication operations as well as the greater than and less than relations that are defined for triangular fuzzy numbers are employed to transform the PLP to a linear program. The proposed PLP model is then applied in a hypothetical example to evaluate the applicability and validity of the model and the solution methodology. As a result of the application it is realized that the uncertainty in the outputs depends on the uncertainty in the inputs. The uncertainty in the inputs affects both the uncertainty and the amount of profit. Under these circumstances the model aims to decrease the uncertainty on the decisions and increase the profit. Consequently model is proved to give satisfactory results. Keywords: Supply Chain Planning, possibilistic linear programming, fuzzy sets

Are road transportation investments in line with demand projections? A gravity-based analysis for Turkey

This is the post-print version of the article which has been published and is available at the link below.In this research, an integrated gravity-based model was built, and a scenario analysis was conducted to project the demand levels for routes related to the highway projects suggested in TINA-Turkey. The gravity-based model was used to perform a disaggregated analysis to estimate the demand levels that will occur on the routes which are planned to be improved in specific regions of Turkey from now until 2020. During the scenario development phase for these gravity-based models, the growth rate of Turkey's GDP, as estimated by the World Bank from now until 2017, was used as the baseline scenario. Besides, it is assumed that the gross value added (GVA) of the origin and destination regions of the selected routes will show a pattern similar to GDP growth rates. Based on the estimated GDP values, and the projected GVA growth rates, the demand for each selected route was projected and found that the demand level for some of these road projects is expected to be very low, and hence additional measures would be needed to make these investments worthwhile

Analyzing competitiveness of automotive industry through cumulative belief degrees

Ülengin, Füsun (Dogus Author) -- Önsel, Şule (Dogus Author) -- Kabak, Özgür (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 2012This study aims to analyze the automotive industry from competitiveness perspective using a novel cumulative belief degrees (CBD) approach. For this purpose, a mathematical model based on CBD is proposed to quantify the relations among the variables in a system. This model is used to analyze the Turkish Automotive Industry through scenario analysis.SEDEFED (Federation of Industrial Associations), REF (TÜSİAD Sabanci University Competitiveness Forum), and OSD (Automotive Manufacturers Association

A decision support system to evaluate the competitiveness of nations

The measurement of competitiveness and strategy development is an important issue for policy makers. The aim of this paper is to explore methodological transparency as a viable solution to problems created by existing aggregated indices as well as to conduct a detailed analysis on the ongoing performance of nations’ competitiveness. For this purpose, a methodology composed of three steps is used. To start, a combined clustering analysis methodology is used to assign countries to appropriate clusters. In current methods, country clustering is generally based on GDP. However, we suggest that GDP alone is insufficient to define the stage of competitiveness a country belongs. In the proposed methodology, 135 criteria are used for a proper classification of the countries. Relationships between the criteria and classification of the countries are determined using Artificial Neural Networks (ANNs). ANN provides an objective method for determining the attribute/criteria weights, which are, for the most part, subjectively specified in existing methods. Finally, in the third step, the countries of interest are ranked based on weights generated in the previous step. Beyond the ranking of countries, the proposed methodology can also be used to identify those attributes that a given country should focus on in order to improve its position relative to other countries, i.e., to transition from its current cluster to the next higher one. As a final analysis, the dynamic change of the rank of the countries over years has also been investigated

Effects of quotas on Turkish foreign trade: a gravity model

As stated by a European Union Commission Report (2009), Turkey's role as a world trade participant has grown in recent years, particularly as the country has been capitalizing more on its unique geopolitical position. Given the substantial trade volume and deep-rooted relations between Turkey and the EU, due attention should be paid to their trade and economic relations, and steps should be taken to improve these relations. Turkey is the biggest economy that is in a Customs Union (CU) with the EU, but not a member of the EU, along with Andorra, Monaco, and San Marino. When it joined the CU in 1996, Turkey removed all customs duties and equivalent charges as well as quantitative restrictions. However, some EU countries impose quota limits on Turkish road transporters that may indirectly restrict trade between Turkey and the country in question. This study has investigated the effect of road-transport quotas on Turkish foreign trade with EU countries. A gravity model estimated using panel data from 18 selected EU countries between 2005 and 2012 was used for this purpose. Furthermore, as one of the leading sectors using road transportation for Turkish exports to EU countries, the textile sector was analyzed as a case study. The results indicated that quotas have significant effects on total Turkish exports by road transport as well as Turkish textile exports to EU countries. The estimated loss of Turkish exports to the selected countries in the time period analyzed was 10.6 billion dollars of Turkey's total exports by road transport and 5.65 billion dollars of Turkey's total textile exports. Therefore, it can be concluded that the quota limitations are against CU regulations because they limit not only road transportation, but also trade between parties

A new perspective on the competitiveness of nations

The capability of firms to survive and to have a competitive advantage in global markets depends on, amongst other things, the efficiency of public institutions, the excellence of educational, health and communications infrastructures, as well as on the political and economic stability of their home country. The measurement of competitiveness and strategy development is thus an important issue for policy-makers. Despite many attempts to provide objectivity in the development of measures of national competitiveness, there are inherently subjective judgments that involve, for example, how data sets are aggregated and importance weights are applied. Generally, either equal weighting is assumed in calculating a final index, or subjective weights are specified. The same problem also occurs in the subjective assignment of countries to different clusters. Developed as such, the value of these type indices may be questioned by users. The aim of this paper is to explore methodological transparency as a viable solution to problems created by existing aggregated indices. For this purpose, a methodology composed of three steps is proposed. To start, a hierarchical clustering analysis is used to assign countries to appropriate clusters. In current methods, country clustering is generally based on GDP. However, we suggest that GDP alone is insufficient for purposes of country clustering. In the proposed methodology, 178 criteria are used for this purpose. Next, relationships between the criteria and classification of the countries are determined using artificial neural networks (ANNs). ANN provides an objective method for determining the attribute/criteria weights, which are, for the most part, subjectively specified in existing methods. Finally, in our third step, the countries of interest are ranked based on weights generated in the previous step. Beyond the ranking of countries, the proposed methodology can also be used to identify those attributes that a given country should focus on in order to improve its position relative to other countries, i.e., to transition from its current cluster to the next higher one

A problem-structuring model for analyzing transportation–environment relationships

This is the post-print version of the final paper published in European Journal of Operational Research. The published article is available from the link below. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. Copyright @ 2009 Elsevier B.V.This study discusses a decision support framework that guides policy makers in their strategic transportation related decisions by using multi-methodology. For this purpose, a methodology for analyzing the effects of transportation policies on environment, society, economy, and energy is proposed. In the proposed methodology, a three-stage problem structuring model is developed. Initially, experts’ opinions are structured by using a cognitive map to determine the relationships between transportation and environmental concepts. Then a structural equation model (SEM) is constructed, based on the cognitive map, to quantify the relations among external transportation and environmental factors. Finally the results of the SEM model are used to evaluate the consequences of possible policies via scenario analysis. In this paper a pilot study that covers only one module of the whole framework, namely transportation–environment interaction module, is conducted to present the applicability and usefulness of the methodology. This pilot study also reveals the impacts of transportation policies on the environment. To achieve a sustainable transportation system, the extent of the relationships between transportation and the environment must be considered. The World Development Indicators developed by the World Bank are used for this purpose