Auteur: Necmi K. Avkiran

Necmi Kemal Avkiran is currently an Associate Professor in banking and financial studies. The main focus of his research has been bank performance measurement. Necmi is currently studying the efficiency of bank networks and transmission of systemic risk. He specializes in the applications of the productivity measurement technique data envelopment analysis and structural equation modelling in the service sector. He holds an award for excellence from the MCB University Press for a research paper on bank customer service quality, and his publication on bank networks has been identified by Thomson Reuters Essential Science Indicators as a featured Fast-Breaking Paper in the field of Economics & Business, August 2010. In May 2006 he published the third edition of the research book entitled Productivity Analysis in the Service Sector with Data Envelopment Analysis. The journals in which he has published include the  Journal of Banking and Finance, OMEGA, Pacific-Basin Finance Journal, Accounting & Finance, Journal of Business Research, Annals of Operations Research, Scientometrics, Personnel Review, and International Journal of Human Resource Management,  as well as on-campus publications. He is a member of the Australian Society for Operations Research (ASOR), and FINSIA. Christian M. Ringle is a Chaired Professor of Management at the Hamburg University of Technology (TUHH) and a Conjoint Professor at the Faculty of Business Law at the University of Newcastle. His research addresses the management of organizations, strategic and human resource management, marketing, and quantitative methods for business and market research. His research in these fields has been published in well-known journals such as Annals of Tourism Research, International Journal of Research in Marketing, Information Systems Research, Journal of Business Research, Journal of Service Research, Journal of the Academy of Marketing Science, Long Range Planning, MIS Quarterly, and Tourism Management. He is a cofounder of Smart PLS, a statistical software tool with a graphical user interface for partial least squares structural equation modeling (PLS-SEM).