What Turkey expects from logistics outsourcing ?

Copyright @ 2011 Yasar UniversityThe economies of the world have become increasingly interdependent, and organizations have come under tremendous pressure to maximize productivity and profitability. Creating value through outsourcing has emerged as a popular competitive strategy for firms of all sizes in all types of industries. The aim of this research is to investigate the use of third party logistics in Turkish companies from the users’ perspective to identify the types of logistics services outsourced, problems encountered in outsourcing these services, logistics costs, decision makers in outsourcing logistics activities, and information sources used in the decision-making process. A structured survey was selected as the tool for data collection. The field study involved face-to-face interviews with 204 companies out of top 500 companies ranked in terms of turnover that are registered with industrial associations and chambers of commerce in Turkey. Moreover, a decision support system based on Bayesian Causal Map is proposed for 3PLs in order to assist them in their service proposals for different sectors. This study is a first attempt to reveal and compare the outsourcing perception of the companies in different sectors, to expose the firms’ underlying motives as well as the respective importance of these motives for outsourcing logistics activities in Turkey. The use of Bayesian Causal Map based on the survey results provides an important guide to the 3PL providers to pick a suitable strategy and to prioritize their operational activities in different sectors in such a way to achieve a competitive advantage

Analyzing competitiveness of automotive industry through cumulative belief degrees

Copyright @ 2012 The European Mathematical SocietyThis 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.This research is supported by SEDEFED (Federation of Industrial Associations), REF (TÜSİAD Sabanci University Competitiveness Forum), and OSD (Automotive Manufacturers Association

How Ethical Behavior of Firms is Influenced by the Legal and Political Environments: A Bayesian Causal Map Analysis Based on Stages of Development

Cataloged from PDF version of article.Even though potential impacts of political and legal environments of business on ethical behavior of firms (EBOF) have been conceptually recognized, not much evidence (i.e., empirical work) has been produced to clarify their role. In this paper, using Bayesian causal maps (BCMs) methodology, relationships between legal and political environments of business and EBOF are investigated. The unique design of our study allows us to analyze these relationships based on the stages of development in 92 countries around the world. The EBOF models structured through BCMs are used to explain how EBOF in a given country group are shaped by how managers perceive political, legislative, and protective environments of business in these countries. The results suggest that irregular payments and bribes are the most influential factors affecting managers’ perceptions of business ethics in relatively more advanced economies, whereas intellectual property protection is the most influential factor affecting managers’ perceptions of business ethics in less-advanced economies. The results also suggest that regardless of where the business is conducted in the world, judicial independence is the driving force behind managers’ perceptions of business ethics. In addition, the results of this study provide further support for scholars who argue that business ethics is likely to vary among countries based on their socio-economic factors. In addition to its managerial implications, the study provides directions for policy makers to improve the ethical conduct of businesses in their respective countries

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

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

Remote Sensing and Geovisualization of Rock Slopes and Landslides

Over the past two decades, advances in remote sensing methods and technology have enabled larger and more sophisticated datasets to be collected. Due to these advances, the need to effectively and efficiently communicate and visualize data is becoming increasingly important. We demonstrate that the use of mixed- (MR) and virtual reality (VR) systems has provided very promising results, allowing the visualization of complex datasets with unprecedented levels of detail and user experience. However, as of today, such visualization techniques have been largely used for communication purposes, and limited applications have been developed to allow for data processing and collection, particularly within the engineering–geology field. In this paper, we demonstrate the potential use of MR and VR not only for the visualization of multi-sensor remote sensing data but also for the collection and analysis of geological data. In this paper, we present a conceptual workflow showing the approach used for the processing of remote sensing datasets and the subsequent visualization using MR and VR headsets. We demonstrate the use of computer applications built in-house to visualize datasets and numerical modelling results, and to perform rock core logging (XRCoreShack) and rock mass characterization (EasyMineXR). While important limitations still exist in terms of hardware capabilities, portability, and accessibility, the expected technological advances and cost reduction will ensure this technology forms a standard mapping and data analysis tool for future engineers and geoscientists

E-commerce and the Market Structure of Retail Industries

While a fast-growing body of research has looked at how the advent and diffusion of e-commerce has affected prices, much less work has investigated e-commerce's impact on the number and type of producers operating in an industry. This paper theoretically and empirically takes up the question of which businesses most benefit and most suffer as consumers switch to purchasing products online. We specify a general industry model involving consumers with differing search costs buying products from heterogeneous-type producers. We interpret e-commerce as having reduced consumers' search costs. We show how such reductions reallocate market shares from an industry's low-type producers to its high-type businesses. We test the model using U.S. data for three industries in which e-commerce has arguably decreased consumers' search costs considerably: travel agencies, bookstores, and new auto dealers. Each industry exhibits the market share shifts predicted by the model. Interestingly, while the industries experienced similar changes, the specific mechanisms through which e-commerce induced them differed. For bookstores and auto dealers, industry-wide declines in small outlets reflected market-specific impacts, evidenced by the fact that more small-store exit occurred in local markets where consumers' use of e-commerce channels grew fastest. For travel agencies, on the other hand, the shifts reflected aggregate changes driven by airlines cutting agent commissions as consumers started buying tickets online.

Ling browser: a NLP based browser for linguistic information

Linguistic students and researchers need practical tools providing information about elements of a language to understand its properties and conduct research on that language. Many computer assisted language learning tools have been developed since the emerging of computers. However, none of these tools aim to satisfy the needs of advanced learners. In this thesis, we introduce a tool, LingBrowser, which is an intelligent hyper-text browser that employs natural language processing technology to provide an interactive environment for advanced language learners to access all kinds of linguistic information about the words in a Turkish text. LingBrowser provides immediate information about morphological, segmental, pronunciation and semantic properties about the words in any text. Also, with a search interface, LingBrowser can locate examples of many linguistic phonemena in the source text

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 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