The term "ecosystem" is mostly noticed in the science of biology; nonetheless it frequently appears in economy related literature, as well. The following terms can be found throughout particular writings: business ecosystem, entrepreneurship ecosystem, an innovation ecosystem, digital business ecosystem and industrial ecosystem. The aim of this research is to compare these analogies. Every analogy has different actors, its environment and various interactions between them; furthermore every ecosystem is a community of subjects that interact as a complete system. Biological ecosystem analogies have a distinctive effect on their entities and the environment, moreover they have different key determinant affecting the performance of the whole system.
The paper deals with the issues relevant to behavioural economics studies, demonstrating psychological and behavioural aspects of Muslim banking customers across the world. The aim of the research is to investigate the factors that are significant to customers using the Islamic hire purchase (auto financing) in Pakistan. The novelty of this study is to develop a modified model based on the Theory of Planned Behaviour (TPB) and apply it to bridge this gap as well as to identify the determinants. The TPB model was applied to examine the intention of customers buying automobiles through Islamic hire purchase financing. This study involves 730 respondents who are customers of Islamic hire purchase (IHP) from major Islamic banks of Pakistan. The results of the study demonstrated that the basic items of the TPB instrument, for instance, subjective norms, attitude, and perceived behavioural control, significantly influenced customers' intention to use Islamic hire purchase financing. At the same time, researchers assimilated three factors such as religious belief, pricing of Islamic banking products, and knowledge of Islamic banking products as moderating variables. The results verified their moderation and exhibited a significant link between items of the Theory of Planned Behaviour model and intention to use the Islamic hire purchase.
This article examines the effects of trade openness on the economic growth and competitiveness of Central and Eastern European countries (CEEs). Although CEEs are characterised by high indicators of trade openness, they show rather different trends of economic development and competitiveness. In most CEEs, trade policies are oriented towards regional trade cooperation with an explicit aim of integration in global economics. The empirical research was conducted on the basis of the panel data for 11 CEEs over the period 2000 to 2014 by applying correlation analysis. Granger-causality test and vector autoregression (VAR) model. This methodological framework allows to test the direct causality relations among trade openness, economic growth and competitiveness, and enables to distinguish between short-run and long-term effect. The research results have confirmed the empirical interdependence among the triad components-trade openness, economic growth and competitiveness, i.e. it has been established that economic growth leads to the improvement of trade openness, while competitiveness of the CEE region leads to the improvement of economic growth, which has obviously disclosed the validity of the theoretical insights. Granger-causality test as well as the developed VAR model have revealed that economic growth has a long-lasting effect on trade openness, while the indicators of competitiveness have a longlasting effect on GDP per capita in CEEs.
As the COVID-19 pandemic came unexpectedly, many real estate experts claimed that the property values would fall like the 2007 crash. However, this study raises the question of what attributes of an apartment are most likely to influence a price revision during the pandemic. The findings in prior studies have lacked consensus, especially regarding the time-on-the-market variable, which exhibits an omnidirectional effect. However, with the rise of Big Data, this study used a web-scraping algorithm and collected a total of 18,992 property listings in the city of Vilnius during the first wave of the COVID-19 pandemic. Afterwards, 15 different machine learning models were applied to forecast apartment revisions, and the SHAP values for interpretability were used. The findings in this study coincide with the previous literature results, affirming that real estate is quite resilient to pandemics, as the price drops were not as dramatic as first believed. Out of the 15 different models tested, extreme gradient boosting was the most accurate, although the difference was negligible. The retrieved SHAP values conclude that the time-on-the-market variable was by far the most dominant and consistent variable for price revision forecasting. Additionally, the time-on-the-market variable exhibited an inverse U-shaped behaviour.
The article presents the analysis of the relationship between e-business benefits and competitive advantage. Different approaches of authors towards e-business and competitive advantages have been analyzed and summed up, the analysis of the e-business impact on usual business processes has been outlined, resource-based as well as M. Porter's approaches to competitive advantage were compared. The model relating positive impact of e-business on nine different business processes and competitive advantage was developed. The model may be integrated into broader research framework constructed for the analysis of e-business development and its role in gaining competitive advantage in any industry. Although many studies confirmed that e-business solutions have a positive impact on various business processes e-business benefits do not necessarily lead to the increased profits and/or sales, thus the association of e-business value with the competitive advantage should be made with caution. The type of the article: Theoretical article.
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