Boom‐Baby CEOs,Career Experience,and Risk Taking: A Natural Experiment Using Chinese CEOs’ Growth Paths

China's economy represents a unique experimental environment, in that it has undergone a successful transformation from a planned to a more open system. Leveraging this natural experimental setting, this study examines the impacts of CEOs’ formative experiences on their risk‐taking behavior. Two events likely constitute formative experiences for CEOs: economic reforms that commenced in 1978 and their prior career experiences. In turn, CEOs’ risk tolerance attitudes likely reflect the influences of these significant events. The results show that CEOs who experienced economic reforms in their early adult life exhibit higher risk‐taking likelihood and greater risk tolerance than those who grew up during the planned economy era. Furthermore, firm performance achieved by CEOs’ risk taking is significantly better when CEOs originally started working in and then remained within business sectors.     

Signaling for more money: The roles of founders' human capital and investor prominence in resource acquisition across different stages of firm development

We use signaling theory to explain how new ventures effectively signal future prospects to acquire external resources. Based on a sample of 235 new ventures drawn from a unique dataset combining multiple sources, we examine the signals of founders' human capital (i.e., education, industry experience, and founding experience) and investor prominence and their influence on the amount of external funding received across two stages of venture funding. We find that founders' founding experience and education have the greatest effects for acquiring first-round financing, but in later stages, only the signaling effect from education remains. Furthermore, we find important interactions between founders' human capital and investor prominence in the second round of funding. By utilizing lagged funding information, we show that different types of signals have a dynamic and temporal impact on new ventures' resource acquisition, including the persistence of some signals and the temporariness of others.     

Specifics of Real Estate Taxation in the Czech and Slovak Republics

International Advances in Economic Research - This article is focused on the real estate tax in the Czech and Slovak Republics. Different approaches to the tax are applied (determination of...     

Modelling driver propensity for traffic accidents: a comparison of multiple regression analysis and fuzzy approach

Abstract

This research proposes an assessment and decision support model to use when a driver should be examined about their propensity for traffic accidents, based on an estimation of the driver’s psychological traits. The proposed model was tested on a sample of 305 drivers. Each participant completed four psychological tests: the Barratt Impulsiveness Scale (BIS-11), the Aggressive Driving Behaviour Questionnaire (ADBQ), the Manchester Driver Attitude Questionnaire (DAQ) and the Questionnaire for Self-assessment of Driving Ability. In addition, participants completed an extensive demographic and driving survey. Various fuzzy inference systems were tested and each was defined using the well-known Wang-Mendel method for rule-base definition based on empirical data. For this purpose, a programming code was designed and utilized. Based on the obtained results, it was determined which combination of the considered psychological tests provides the best prediction of a driver’s propensity for traffic accidents. The best of the considered fuzzy inference systems might be used as a decision support tool in various situations, such as in recruitment procedures for professional drivers. The validity of the proposed fuzzy approach was confirmed as its implementation provided better results than from statistics, in this case multiple regression analysis.     

Will AI ever sit at the C-suite table? The future of senior leadership

As the sophistication of artificial intelligence (AI) systems develop and AI becomes a key element of organizational strategy across a wide spectrum of industries, new demands are being placed on senior leaders. To understand the growing challenges leaders will face in the age of AI, we conducted interviews with 33 senior leaders in several countries across a wide range of industries. Our research highlights key capabilities and skills that leaders will require. Underlying these capabilities is a mindset oriented toward continuous learning and self-development, which will enable ongoing and rapid adaptation to change. Our findings identified the following key capabilities: digital know-how, data-driven focus, networking, ethics, and agility. To successfully navigate the coming era, senior leaders will need to focus on reskilling the workforce, recruiting and retaining highly skilled talent, building an intrapreneurial culture, and managing unprecedented changes in technologies and the nature of work.     

New development: Between politics and strategic planning—the management of government priorities in Lithuania

ABSTRACT

How do political agendas impact on strategic planning practices? This article shows that recent changes to the framework for managing government priorities have made Lithuania’s strategic planning system more politically responsive by mobilizing political attention, leadership and state funding to major government commitments. However, these changes have not yet translated into any longer term outcomes because policy implementation practices did not change very much.     

Empirical Analysis of the Market Value Added in the Czech Automotive Industry

International Advances in Economic Research -     

Returns of Education in the Czech Republic

Prepared for presentation at the Congress of the International Institute of Public Finance (IIPF) in Seville, Spain, 28–31 August 2000, for the session on the opportunity-equalising effects of fiscal systems.University education is nowadays provided as public goods in the Czech Republic. Due to economic pressure on public finance the trend of the 90s became the internalisation of costs associated with university education.The generally accepted hypothesis is that nowadays the returns from the costs of university education are achieved in a shorter time than before economic transition. Additionally, it is thought that the return on university education is differentiated by professions. We aim to test these hypotheses. That is why the cornerstone of our study is the deeper analysis of the differentiation of selected professions in the current state in comparison to the period before transition.After 1989, due to the economic transition and development of the market economy, wage differentiation accelerated in the Czech Republic. An important factor in differentiation seems to be the level of human capital, represented above all by university education. Education significantly increased the chance of finding a job, as another analysis has proven. However, these positive effects of education have been paid for by considerable monetary and non-monetary costs.The paper provides an economic analysis at the level of an individual and his point of return between costs and revenues from university education. To achieve an exact but still simple analysis we take into account only quantifiable monetary costs and revenues. The calculation of the point of return is done with the use of the construction of a cumulated whole-life income and its interpolation. The analysis uses data for the Czech Republic in 1988 and 1997.     

How High is the Private Gain from Wage Indexation?

The effects of firm‐specific shocks on the gain from writing state‐contingent wage contracts are examine in an extension of the model in Gottfries (1992) . It is shown that the introduction of firm‐specific uncertainty increases the gain from indexation to prices only moderately. Moreover, nominal wage contracts should be more prevalent when unemployment benefits are high or unemployment spells are short.