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

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

How to improve the innovation level of a country? A Bayesian net approach

This study aims to provide strategic guidelines to policy makers who are developing strategies to improve their country’s innovativeness. In this paper, we claim that innovation cannot be related only to some factors inherent in the environment of a country, nor is it a single entity to be managed without any linkages to the rest of the actors comprising the competitiveness of a country. Hence, a comprehensive study on innovation should cover the interaction between competitiveness indicators and innovation. For this purpose, the innovation performance of 148 countries is analyzed using an integrated cluster analysis and a Bayesian network framework. These countries are first clustered based on the average values of their competitiveness indicators representing 12 pillars and several sub-pillars adopted from the Global Competitiveness Reports of World Economic Forum for the 2009-2012 period. As a result, five appropriate clusters emerge: Leaders, Followers, Runners Up, Developing Ones, and Laggers. A factor analysis is then conducted to reveal the main characteristics of each cluster in terms of competitiveness indicators. Subsequently, a Bayesian network is constructed and sensitivity analyses are performed to reveal important policies for each cluster

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

Understanding and managing complexity through Bayesian network approach: The case of bribery in business transactions

Managing complex business problems requires decision makers to take a systemic perspective and utilize tools that can generate knowledge from the interdependencies of the system's complex properties. As such, the current research focuses on an important yet ambiguous business problem-bribery. Using the Global Competitiveness Index data provided by the World Economic Forum, the authors constructed and analysed a Bayesian network to delineate a 'system' of bribery in business transactions. In this context, they first determined the factors related to bribery activities and then developed a structural model (the Bayesian network). Through scenario and sensitivity analyses performed over the constructed model, the authors identified the factors that have the greatest impact on bribery activities. They further analysed the resulting model based on the countries' stage of economic development in order to provide the manager and policy maker with a more informative diagnostic tool to understand and deal with bribery activities locally and globally

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

A decision support methodology for increasing the efficiency of the largest border crossing between Europe and Turkey

Kapıkule Border Crossing, the second busiest land border crossing point in the world and the busiest in Europe, has become inadequate to process the increasing number of trucks transporting goods between Europe and Turkey. To address this issue, in a previous study, a detailed process analysis was conducted, a simulation model was developed, and several action plans representing improvement strategies were analyzed and ranked in terms of the daily average number of trucks waiting in the queue to enter and leave the border crossing. However, to increase the efficiency of Kapıkule Border Crossing, the ranking of the action plans should not be solely based on the average number of trucks but should also be evaluated from a much broader perspective taking into account several objectives that are generally in conflict with each other. Therefore, in this study, we propose a multicriteria decision support methodology that evaluates these action plans by considering additional attributes; such as investment cost, operations cost, sustainability, border security, and the satisfaction of the beneficiaries, establishing a preference ranking of action plans to improve the capacity of the Border Crossing. Our results have implications for policymakers not only in Turkey but also in the EU

A decision support methodology for increasing the efficiency of the largest border crossing between Europe and Turkey

Kapıkule Border Crossing, the second busiest land border crossing point in the world and the busiest in Europe, has become inadequate to process the increasing number of trucks transporting goods between Europe and Turkey. To address this issue, in a previous study, a detailed process analysis was conducted, a simulation model was developed, and several action plans representing improvement strategies were analyzed and ranked in terms of the daily average number of trucks waiting in the queue to enter and leave the border crossing. However, to increase the efficiency of Kapıkule Border Crossing, the ranking of the action plans should not be solely based on the average number of trucks but should also be evaluated from a much broader perspective taking into account several objectives that are generally in conflict with each other. Therefore, in this study, we propose a multicriteria decision support methodology that evaluates these action plans by considering additional attributes; such as investment cost, operations cost, sustainability, border security, and the satisfaction of the beneficiaries, establishing a preference ranking of action plans to improve the capacity of the Border Crossing. Our results have implications for policymakers not only in Turkey but also in the EU

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