Chief technology officer roles and performance

This paper assesses the impact of Chief Technology Officers (CTO) on firm performance using upper-echelon theory, human capital theory and social capital theory. The upper-echelon theory is used to investigate how CTO roles are realised within a company regardless of the individual who carries them out, i.e. through a formal CTO position or not. Human and social capital theories are employed to assess how certain features of CTO influences his/her effect on company performance. Thus, this explorative study investigates two questions: (1) do CTO roles affect a firm's performance?, and (2) which features of the senior manager in charge of technology influence performance? To answer these questions the study first develops a conceptual model and subsequently tests the model based on a survey of 49 firms in electronics and machinery industries in Turkey. Two findings emerge: (1) the fulfilment of CTO roles increases a firm's profitability and (2) the existence of a distinct managerial technology position further improves profitability. Moreover, the study clearly shows the role of social capital theory in explaining how the company performance is likely to increase when the CTO/CTO-proxy manager is placed on a higher rung on the organisational ladder.     

Understanding the Recent Growth in Consumer Loans and Credit Cards in Emerging Markets: Evidence from Turkey

In recent years, the surge in household indebtedness to historical heights has become a significant concern for developed economies. A similar trend has been witnessed in emerging market countries including Turkey. Our objective is to help further understand the dynamics of the recent growth in consumer loans and credit cards (CLCC) in Turkey. For this purpose, we investigate the long-term equilibrating relationships and short-term deviations from the equilibrium, and explore the determinants, directions, and strengths of causality relationships between CLCC and the selected macroeconomic variables, and analyze the dynamic interactions among the variables in the post-sample period by analyzing how CLCC responds to the shocks given to other macroeconomic variables and the contribution of each variable on the forecast variability of CLCC. We use monthly data for the period of January 2004—December 2013 of seven macroeconomic variables of money supply, interest rate, income, consumer confidence, inflation, stock market, and consumer goods imports. On empirical findings, we make suggestions about which policy tools should be used to influence, and if necessary to manage, the growth in CLCC.