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

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

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

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

Kabak, Ozgur/0000-0002-5542-309X; ONSEL EKICI, SULE/0000-0003-3694-2756; Ulengin, Fusun/0000-0003-1738-9756Logistics 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 per-formance 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

Improving logistics performance by reforming the pillars of Global Competitiveness Index

Önsel Ekici, Şule (Dogus Author)The logistics performance of a country is crucial to national and international trade, and therefore has a direct effect on economic development. Owing to limited resources, policymakers need a guide for specifying the factors that need to be focused upon to bring about immediate and significant improvements in the logistics performance of their countries. This study aims to propose a methodology to develop a roadmap for policymakers in improving the logistics performance of their countries. For this purpose, we analyze the effect of the competitiveness pillars of the Global Competitiveness Index (GCI) on logistics performance (as measured by the Logistics Performance Index (LPI)), using a three-stage integrative methodology based on a tree-augmented naive Bayesian network, partial least square path model, and importance-performance map analysis. An empirical study is conducted using the GCI pillars of the World Economic Forum and the LPI of the World Bank. The results indicate that governments should focus on technological readiness, higher education and training, innovation, market size, and infrastructure to facilitate improvement in the logistics performance of their countries

Linking to compete: logistics and global competitiveness interaction

A country’s ability to trade globally depends to a great extent on the traders’ access to efficient logistics networks. The efficiency of logistics networks, in its turn, depends on government services, investments, and policies. Building infrastructure, developing a regulatory regime for transport services, and designing and implementing efficient customs clearance procedures are the areas where governments play an important role. One of the measures for logistics performance at national level is the Logistics Perfor- mance Index (LPI) published by the World Bank Group. LPI is composed of six indicators namely customs, infrastructure, service quality, timeliness, international shipments, and tracking and tracing. This study argues that there is a close relationship between global competitiveness and the logistics efficiency of a country and it analyzes the validity of these relations using an artificial neural network (ANN) and cu- mulative belief degrees (CBD) approach. For this purpose; initially, a screening process is carried out to find the World Economic Forum’s competitiveness indicators that may have an impact on each of the LPI indicators. Subsequently, the relationship between the competitiveness indicators and LPI indicators is analyzed using ANN where the LPI indicators are represented by CBDs. As a case study, this methodology is used to analyze Turkey’s logistics performance and to develop the basic strategies to be adopted by the government to achieve a targeted LPI level for the country. Among the many factors relating to logistics performance, it was found that fixed broadband Internet availability is the most important target area for improvement related to sustainable logistics policy

Determination of 355 Pesticides in Lemon and Lemon Juice by LC-MS/MS and GC-MS/MS

While pesticides have become a primary tool in modern agriculture, these compounds remain a high priority on the list of consumer concerns regarding food safety. The use of pesticides in the production and post-harvesting of lemon fruits is widely used to ensure agricultural yield and fruit quality. Therefore, monitoring studies on citrus fruits to enforce regulatory compliance and ensure food safety is in great demand. The aim of this study was to monitor multi-class pesticide residues in lemon fruits commercialized in Turkey. The transmission of residues that existed on the outer surface of the fruit into its juice was also studied. Whole fruits and lemon juice samples were prepared using the quick, easy, cheap, effective, rugged and safe (QuEChERS) methodology prior to analysis. For the screening and quantification of 355 pesticide residues, liquid chromatography-tandem mass spectrometry (LC-MS/MS) and gas chromatography-tandem mass spectrometry (GC-MS/MS) were used. The analytical method has been shown to have a sufficiently low limit of quantification with respect to current maximum residue limits (MRLs) for all target analytes. The obtained recovery and precision parameters fulfilled the requirements in DG SANTE guidelines. The in-house validated analytical method was then applied for the determination of 355 pesticide substances in 100 whole fruit samples and their juices. Sixteen different residues were detected in 43% of lemon fruits, whereas 57 lemon samples were pesticide-free. The MRLs exceedances were recorded in 29 lemon samples. The most frequently detected (17%) pesticide in lemon fruits was chlorpyrifos-methyl, with a range of 0.013–0.098 mg kg−1. A lower frequency was detected for metamitron (10%, 0.027–0.118 mg kg−1), buprofezin (9%, 0.023–0.076 mg kg−1), pyriproxyfen (9%, 0.021–0.102 mg kg−1) and malathion (7%, 0.100–0.482 mg kg−1) in whole fruits. However, none of the pesticide residues were detected in lemon juice samples. These results showed that target analytes are unable to penetrate the lemon exocarp and/or endocarp