In this paper, a taxonomy of supply chain and logistics innovations was developed and presented. The taxonomy was based on an extensive literature survey of both theoretical research and case studies. The primary goals are to provide guidelines for choosing the most appropriate innovations for a company and helping companies in positioning themselves in the supply chain innovations landscape. To this end, the three dimensions of supply chain innovations, namely the goals, supply chain attributes, and innovation attributes were identified and classified. The taxonomy allows for the efficient representation of critical supply chain innovations information, and serves the mentioned goals, which are fundamental to companies in a multitude of industries.

Başar, A., Özsamlı, N., A. E. Akçay, G. Kahvecioğlu, Ertek., G. (2011). “A taxonomy of supply chain innovations”. African Journal of Business Management. 5(30), pp. 11968-11977, 30 November, 2011.

Note: This is the final draft version of this paper. Please cite this paper (or this final draft) as above.

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A taxonomy of supply chain innovations

Dr. Gürdal Ertek recommends the following related books:

• Supply Chain Management (5th Edition)
• World-Class Warehousing and Material Handling 1st Edition

 

 

 

Re-mining is a general framework which suggests the execution of additional data mining steps based on the results of an original data mining process. This study investigates the multi-faceted re-mining of association mining results, develops and presents a practical methodology, and shows the applicability of the developed methodology through real world data. The methodology suggests re-mining using data visualization, data envelopment analysis, and decision trees. Six hypotheses, regarding how re-mining can be carried out on association mining results, are answered in the case study through empirical analysis.

Ertek, G., Tunç, M.M., (2012) “Re-Mining Association Mining Results through Visualization, Data Envelopment Analysis, and Decision Trees”, in Computational Intelligence Applications in Industrial Engineering, Ed: C. Kahraman, Springer.

Note: This is the final draft version of this paper. Please cite this paper (or this final draft) as above.

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Re-mining Association Mining Results Through Visualization, Data Envelopment Analysis, And Decision Trees

Dr. Gürdal Ertek recommends the following related books:

• Information Visualization: Design for Interaction (2nd Edition)
• Introduction to Data Envelopment Analysis and Its Uses: With DEA-Solver Software and References 2006th Edition
• Data Mining: Concepts and Techniques, Third Edition (The Morgan Kaufmann Series in Data Management Systems) 3rd Edition
• Post-mining of Association Rules: Techniques for Effective Knowledge Extraction 1st Edition
  

 

 

 

Association mining is the conventional data mining technique for analyzing market basket data and it reveals the positive and negative associations between items. While being an integral part of transaction data, pricing and time information have not been integrated into market basket analysis in earlier studies. This paper proposes a new approach to mine price, time and domain related attributes through re-mining of association mining results. The underlying factors behind positive and negative  relationships can be characterized and described through this second data mining stage. The applicability of the methodology is demonstrated through the analysis of data coming from a large apparel retail chain, and its algorithmic complexity is analyzed in comparison to the existing techniques.

Demiriz, A., Ertek, G., Kula, U., Atan, T. (2011). “Re-Mining Item Associations: Methodology and a Case Study in Apparel Retailing”. Decision Support Systems, 52,pp. 284–293.

Note: This is the final draft version of this paper. Please cite this paper (or this final draft) as above.

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Re-mining item associations: Methodology and a case study in apparel retailing

Dr. Gürdal Ertek recommends the following related books:

• Analyzing Social Media Networks with NodeXL: Insights from a Connected World 1st Edition
• Data Mining: Concepts and Techniques, Third Edition (The Morgan Kaufmann Series in Data Management Systems) 3rd Edition

 

 

 

Association mining is the methodology within data mining that researches associations among the elements of a given set, based on how they appear together in multiple subsets of that set. Extensive literature exists on the development of efficient algorithms for association mining computations, and the fundamental motivation for this literature is that association mining reveals actionable insights and enables better policies. This motivation is proven valid for domains such as retailing, healthcare and software engineering, where elements of the analyzed set are physical or virtual items that appear in transactions. However, the literature does not prove this motivation for databases where items are “derived items”, rather than actual items. This study investigates the association patterns in changes of exchange rates of US Dollar, Euro and Gold in the Turkish economy, by representing the percentage changes as “derived items” that appear in “derived market baskets”, the day on which the observations are made. The study is one of the few in literature that applies such a mapping and applies association mining in exchange rate analysis, and the first one that considers the Turkish case. Actionable insights, along with their policy implications, demonstrate the usability of the developed analysis approach.

Please cite this paper as follows:

Arabacı, M., Aktuğ, A., Ertek, G. (2011) “Actionable Insights Through Association Mining of Exchange Rates: A Case Study.” Proceedings of International Symposium on Innovations in Intelligent Systems and Applications 2011. (IEEE). June 15-17, 2011, Istanbul, Turkey.

Dr. Gürdal Ertek recommends the following related books:

Essentials of Business Analytics 2nd Edition

Information Visualization: An Introduction, 3rd Ed. 2014 Edition

Literature on association mining, the data mining methodology that investigates associations between items, has primarily focused on efficiently mining larger databases. The motivation for association mining is to use the rules obtained from historical data to influence future transactions. However, associations in transactional processes change significantly over time, implying that rules extracted for a given time interval may not be applicable for a later time interval. Hence, an analysis framework is necessary to identify how associations change over time. This paper presents such a framework, reports the implementation of the framework as a tool, and demonstrates the applicability of and the necessity for the framework through a case study in the domain of finance.

Çinicioğlu, E. N., Ertek, G., Demirer, D., Yörük, E., (2011) “A Framework for Automated Association Mining Over Multiple Databases”. Proceedings of International Symposium on Innovations in Intelligent Systems and Applications 2011. (IEEE). June 15-17, 2011, Istanbul, Turkey.

Note: This is the final draft version of this paper. Please cite this paper (or this final draft) as above.
Download
A Framework for Automated Association Mining Over Multiple Databases

Dr. Gürdal Ertek recommends the following related books:

• Data Mining: Concepts and Techniques, Third Edition (The Morgan Kaufmann Series in Data Management Systems) 3rd Edition
• Analyzing Social Media Networks with NodeXL: Insights from a Connected World 1st Edition
• Post-mining of Association Rules: Techniques for Effective Knowledge Extraction 1st Edition

 

 

 

This chapter investigates the relationship between interbank funds and efficiencies for the commercial banks operating in Turkey between 2001 and 2006. Data Envelopment Analysis (DEA) is executed to find the efficiency scores of the banks for each year, and fixed effects panel data regression is carried out, with the efficiency scores being the response variable. It is observed that interbank funds (ratio) has negative effects on bank efficiency, while bank capitalization and loan ratio have positive, and profitability has insignificant effects. This chapter serves as novel evidence that interbank funds can have adverse effects in an emerging market.

Aysan, A. F., Ertek, G., Öztürk, S. (2011) “Assessing the Adverse Effects of Interbank Funds on Bank Efficiency Through Using Semiparametric and Nonparametric Methods” in , Financial Services: Efficiency and Risk Management (Studies in Financial Optimization and Risk Management). Eds: Meryem Duygun Fethi, Chrysovalantis Gaganis, Fotios Pasiouras, Constantin Zopounidis. Nova Science Pub Inc.

Note: This is the final draft version of this paper. Please cite this paper (or this final draft) as above.

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ASSESSING THE ADVERSE EFFECTS OF INTERBANK FUNDS ON BANK EFFICIENCY THROUGH USING SEMIPARAMETRIC AND NONPARAMETRIC METHODS

Dr. Gürdal Ertek recommends the following related books:

• Financial Services:: Efficiency and Risk Management (Studies in Financial Optimization and Risk Management)
• Introduction to Data Envelopment Analysis and Its Uses: With DEA-Solver Software and References 2006th Edition