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Understanding the role of institutions and economic context on entrepreneurial value creation choice
No full textResearch background: The observable discrepancies in entrepreneurship activity across countries have motivated both researchers and policymakers to comprehend the sources of these variations. Certain scholars have suggested that the answer to this empirical puzzle lies in the macrolevel processes that influence entrepreneurial endeavours.
Purpose of the article: As the understanding of macrolevel processes that shape entrepreneurial behaviour is limited, this research aims to answer how institutions and the economic context influence entrepreneurial value creation choices (i.e., for-profit, non-profit, and mixed).
Methods: Using a cross-country sample of 7,891 entrepreneurs in 58 countries, we employ a multilevel ordered probit to evaluate a novel conceptual framework. Our analysis models the direct impact of the regulative framework, the normative pillar, and the cultural pillar, alongside the moderating influence of income inequality and economic uncertainty on value creation choices.
Findings & value added: Our findings show that the regulative framework has a positive marginal effect on for-profit and mixed-value creation, but a negative effect on non-profit value creation. Meanwhile, the normative pillar has a negative marginal effect on for-profit and mixed-value creation, but a positive effect on non-profit value creation. The cultural pillar has a negative marginal effect on for-profit and mixed-value creation, but a positive effect on non-profit value creation. Furthermore, income inequality moderates positive the relationship between normative pillar and for-profit and mixed-value creation, while economic uncertainty moderates negative the relationship between normative pillar and for-profit and mixed-value creation. Our research contributes to the literature by providing a nuanced understanding of how institutional pillars can act as drivers or barriers for different entrepreneurial forms, evidence of how uncertainty interacts with institutional forces to shape value creation decisions, and insights into the distinctive attributes of different entrepreneurial forms. Our findings have implications for public policy development
Bankruptcy prediction in the post-pandemic period: A case study of Visegrad Group countries
No full textResearch background: Effective monitoring of financial health is essential in the financial management of enterprises. Early studies to predict corporate bankruptcy were published at the beginning of the last century. The prediction models were developed with a significant delay even among the Visegrad group countries.
Purpose of the article: The primary aim of this study is to create a model for predicting bankruptcy based on the financial information of 20,693 enterprises of all sectors that operated in the Visegrad group countries during the post-pandemic period (2020?2021) and identify significant predictors of bankruptcy. To reduce potential losses to shareholders, investors, and business partners brought on by the financial distress of enterprises, it is possible to use multiple discriminant analysis to build individual prediction models for each Visegrad group country and a complex model for the entire Visegrad group.
Methods: A bankruptcy prediction model is developed using multiple discriminant analysis. Based on this model, prosperity is assessed using selected corporate financial indicators, which are assigned weights such that the difference between the average value calculated in the group of prosperous and non-prosperous enterprises is as large as possible.
Findings & value added: The created models based on 6?14 financial indicators were developed using different predictor combinations and coefficients. For all Visegrad group countries, the best variable with the best discriminating power was the total indebtedness ratio, which was included in each developed model. These findings can be used also in other Central European countries where the economic development is similar to the analyzed countries. However, sufficient discriminant ability is required for the model to be used in practice, especially in the post-pandemic period, when the financial health and stability of enterprises is threatened by macroeconomic development and the performance and prediction ability of current bankruptcy prediction models may have decreased. Based on the results, the developed models have an overall discriminant ability greater than 88%, which may be relevant for academicians to conduct further empirical studies in this field
Sociocultural valuation of ecosystem services in protected areas: A study applied to Southeast Spain
No full textResearch background: Protected areas (PAs) play a fundamental role in the maintenance of ecosystem processes and in the flow of ecosystem services (ESs) they provide. However, the management of PAs is complex due to the existence of different stakeholders with disparate and, often, opposed preferences and valuations. The sociocultural assessment of ESs contributes to optimizing the management of scarce resources based on the preferences of the different stakeholders, taking into account the economic, environmental and social dimensions of the analysed area.
Purpose of the article: In this work, a sociocultural assessment of the ESs provided by a PA in southeast Spain is carried out. The objective is to identify which the various ESs provided by this PA are and to establish their degree of importance for all the stakeholders involved.
Methods: For this, different complementary methodologies have been used in successive phases, both qualitative and quantitative. Specifically, a literature review, in-depth interviews and an assessment questionnaire were used.
Findings & value added: Based on the results obtained, a series of measures are proposed to improve the sustainable management of the PA and the socioeconomic development of its environment. The results of this study may be useful for PAs whose management tries to find a balance between conservation measures and the design of models that contribute to the socioeconomic development of their area of influence
Is green finance capable of promoting renewable energy technology? Empirical investigation for 64 economies worldwide
No full textResearch background: As an outcome of a global consensus on combating climate change, green finance is expected to play an important role in promoting green growth and innovation progress. Some studies note that green credit policy yields a negative influence on green innovation, while how green finance affects renewable energy innovation has received scant attention in academia. This study focuses on the impact of green finance on renewable energy innovation.
Purpose of the article: This research investigates the influence of green finance on an economy\u27s renewable energy innovation by using green bond data from the Climate Bonds Initiative. This research further tests whether it varies for different kinds of energy types and economic development levels. Given that policies are key to renewable energy technology development, this research checks whether government stability changes the relationship between green finance and renewable energy innovation.
Methods: Using the panel fixed effects model and big-scale data from 64 economies worldwide during the period 2014-2019, we investigate green finance\u27s impact on renewable energy innovation. In the robustness test, the dynamic panel model and the panel Tobit model are employed.
Findings & value added: This research finds that green finance has a positive effect on renewable energy innovation. This effect is prominent in non-OECD economies as well as middle-income and low-income economies. Government stability enhances the influence of green finance on renewable energy innovation. Moreover, the results indicate that green finance mainly promotes innovation progress for wind energy and produces little effect for other renewable energies. The subsample analysis also sheds light on the heterogeneity of the role of green finance in promoting renewable energy innovation
Economic sentiment indicators and their prediction capabilities in business cycles of EU countries
No full textResearch background: The post-World Financial Crisis period has showed us that an application of the qualitative data focused on the expectations of the enterprises and consumers in a combination with the quantitative data in the individual economy sectors is a good prerequisite for reliable prediction of the economic cycles.
Purpose of the paper: The main goal of the presented study was to test the ESI prediction capabilities and its components in a relation to the economic cycles of the EU countries in the individual time periods.
Methods: The time series for the period Q1 2000 to Q4 2022 and the three selected time periods were a subject to undergo the selection of the cyclical component applying the Hodrick-Prescott filter and then, the relationship between the variables was determined employing the Pearson correlation coefficient with the time shifts. The relation of ESI and its components to GDP and the Index of Industrial Production (IIP), which represent the economic cycle, was analysed. The prediction volume and the cross-correlation values determined the nature of the observed cyclical variables.
Findings & value added: The results of the analysis point to the fact that ESI and its components are able to ensure a high-quality prediction of the economic cycle only in the selected EU countries. Regarding the components of the ESI, the Consumer confidence indicator, Construction and Industrial confidence indicators show the best predictive capabilities. The analytical outcomes show that the ESI size and lead period vary over time and after the 2008 crisis, the ESI showed better predictive capabilities in a relation to GDP and IIP than before the crisis. The Covid 19 pandemic had a significant negative impact on the ESI predictive capabilities
Analysis of the pointwise completeness and the pointwise degeneracy of the standard and fractional descriptor linear systems and electrical circuits
No full textThe Drazin inverse of matrices is applied to analysis of the pointwise completeness and the pointwise degeneracy of the descriptor standard and fractional linear continuous-time and discrete-time systems. It is shown that: 1) The descriptor linear continuous-time system is pointwise complete if and only if the initial and final states belong to the same subspace. 2) The descriptor linear discrete-time system is not pointwise complete if its system matrix is singular. 3) System obtained by discretization of continuous-time system is always not pointwise complete. 4) The descriptor linear continuous-time system is not pointwise degenerated in any nonzero direction for all nonzero initial conditions. 5) The descriptor fractional system is pointwise complete if the matrix defined by (36) is invertible. 6) The descriptor fractional system is pointwise degenerated if and only if the condition (41) is satisfied. Considerations are illustrated by examples of descriptor linear electrical circuits
Zasady międzynarodowej polityki handlowej kształtowane przez WTO
No full textW artykule omówiono politykę handlową prowadzoną przez Międzynarodową Organizację Handlu oraz jej rolę w liberalizacji handlu usługami i własnością intelektualną. Przeanalizowano ostatnią rundę negocjacji w Dausze i odpowiedziano na pytanie dlaczego nie było możliwe osiągnięcie porozumienia. Zbadana została rola Międzynarodowego Funduszu Walutowego oraz Banku Światowego w międzynarodowym systemie walutowym, a także ich aktualna działalność pod kątem spełniania przez nich założonych funkcji
Estimation of route speed parameters designed for electric buses
No full textThe paper presents a method for the estimation of speed parameters on urban bus routes designed for the use of electric buses. The considered bus route is divided into stopping and running sections. The bus stops are the stopping sections. The running sections connect two neighbouring bus stops. A bus equipped with the GPS receiver moves along the urban bus route at a variable speed. The GPS receiver records at a constant frequency location data that include current bus position and the measurement time. The location data enable the estimation of the time of varying speeds for the running sections and the stop time for the stopping sections. The speed parameters for the sections involve the specification of time periods assigned to the defined speed ranges. Measurement data were recorded on the selected bus route in off-pick and pick hours. The results obtained allow estimation of speed parameters for individual sections and by aggregation for the entire bus route considered. The speed parameters of the bus route correspond to the energy consumption of electric buses and can be applied to determine the properties of the urban bus routes on which electric buses are introduced
High-speed turnout as part of the track
No full textThis paper presents the classification and construction of high-speed railway turnouts operated on European railway lines. The existing computer programs supporting the diagnostics of high-speed railway turnouts with the most common causes of failures originating from infrastructure elements were analyzed. The authors point to the need for integration of high-speed turnouts as a single system containing modern point machine control of switch area and swing nose crossing area with induction heating of moving turnout elements. Attention was also paid to the need to use appropriate means of transport dedicated for railway turnouts in order to improve the initial quality of the product
Perception technology for conversion of off-road vehicles for the purposes of unmanned missions
No full textAutonomous ground vehicles (AGV) have great potential for a wide range of applications, both in the civilian and military fields. Nowadays there is an interest in converting existing off-road vehicles into remotely controlled platforms with autonomous mode due to several benefits, including reducing the risk to human life, increasing efficiency and accuracy, and allowing the vehicles to operate in hazardous zones. Environmental perception technology plays a critical role in enabling the safe and effective operation during unmanned missions. This technology involves sensors, cameras, and other devices to gather information about the environment and provide the unmanned ground platform (UGV) with a perception of its surroundings. In recent years, there has been significant progress in the development of environmental perception systems, including the use of advanced sensors, machine learning algorithms, and other innovations have become a focus of research and development for many countries. This paper describes a combination of commercially available vision sensors, laser scanners and navigation modules for comprehensive understanding of operational environment, orientation, objects recognition during autonomous mode. Typical methods for vision and lidar-based obstacle detection and object classification for unmanned vehicles are described. The aim of the work was to examine in real environment the performance of a perception system that was configured using a daylight-thermal observation and stereo cameras, lidar sensor, GNSS module, radio links along with computing units. This system was evaluated in terms of performance of different sensors considering implementation for all terrain vehicle as subsystem for unmanned mode