Examining mobile banking performance among college students in Indonesia

VUСA is a chaotic and rapidly changing business environment that, based on the variability, uncertainty, complexity and ambiguity of the modern world, transforms the approach of banks to the analysis of financial stability. The aim of the paper is to improve tools for monitoring the impact of VUCA-world conditions on the financial stability of banks, namely a model for studying and analyzing the impact of the modern business space “VUCA” on the financial stability of the country's banks. To test the model, the method of constructing regression equations in multifactor regression analysis is used. For this study, data from some Eastern European countries (Ukraine, Belarus, Latvia, Lithuania, Moldova) were used, and time series data were used for 10 years from 2010 to 2019.
Having considered the definition of “VUCA-world conditions”, the model of modern business space “VUCA” was developed when analyzing the activity of banks in the studied countries. Drivers, consequences, requirements and macroeconomic indicators of the countries’ activities in the VUСA-world conditions are determined. The VUCA-world conditions also consider the study of key macroeconomic indicators that allow building long-term relationships throughout the value chain. The analysis of the studied Eastern European countries showed that with the increase of factors of GDP growth, GNI per capita growth, research and development costs, foreign direct investment, and net inflow of 1%, the effective ratio of bank capital and assets also increases. The assessment, in contrast to the existing ones, makes it possible to consider the impact of the macroeconomic environment of banks on their financial stability.

The stock market represents complex systems where multiple agents interact. The complexity of the environment in the financial markets in general has encouraged the use of modeling by multi-agent platforms and particularly in the case of the stock market.
In this paper, an agent-based simulation model is proposed to study the behavior of the volume of market transactions. The model is based on the case of a single asset and three types of investor agents. Each investor can be a zero intelligent trader, fundamentalist trader or traders using historical information in the decision making process. The goal of the study is to simulate the behavior of a stock market according to the different considered endogenous and exogenous variables.

The present article originates from the effort to answer the following question: is it possible for an organizational structure to steer between organizational routines and Black Swans? (Taleb, 2007). Unexpected, unique and low-frequency events are “unknown variable” that, despite the planning and precautions deployed, catch an organization off-guard, and might have catastrophic consequences. Unexpected events impact organizations, undermining the knowledge and redefining the list of competences that an organization needs in order to be competitive. The main goal of the present article is to shed light on the role and the challenges that firms undertake in their defining moments of adaptation of their organizational assets – the structure –. The rational pattern of adaptation is exemplified by the use of ambidextrous organizational structures, which focus on activities that can be defined as exploration and exploitation. Within the analysis of “the science of complexity”, parallels, paradoxes and metaphors representing a synthesis of a largely shared doctrine will be investigated: firms need to utilize known variables, or sometimes unknown ones, that are inevitably complex, in order to find the right fit, react swiftly to change, successfully compete, and obtain results.