Emergency remote learning acceptance among higher education students during COVID-19 pandemic

The current study investigates how attitudes towards digital transformation and personal innovativeness affect the acceptance of emergency remote learning in the COVID-19 pandemic environment. The pandemic has affected all aspects of societies across the globe, including higher education that was also a significant push-up factor for the digital transformation of higher education. Thus, the main aim of this paper is to investigate the factors affecting emergency remote learning acceptance among the higher education students in Bosnia and Herzegovina (BiH). The results presented in this paper gained from a study carried out among higher education students in BiH cover the period of April – July 2020 via the open-source platform. The study focused on the students’ attitude towards a digital transformation is a significant factor in accepting emergency remote learning. Also, the personal innovativeness score has proven to be a crucial factor for adopting this new learning setting, i.e., more innovative students have a greater emergency remote learning acceptance than students with a lower personal innovativeness score. Hence, this study pinpoints the necessity of changing the attitudes towards technology applications in education. It would increase the usage of remote learning services and provide students with knowledge and skills for the new labour market

Efficiency of banks in Croatia

Croatian banking sector amounts to the majority of its financial sector. Therefore, it is necessary that Croatian banks operate efficiently. In the past two decades, the Croatian banking sector went through a consolidation process that steadily decreased the number of banks and allocated the majority of assets and market share to a few large banks. A simple definition of efficiency is cost minimization and profit maximization. Therefore, a bank is efficient when it strives to minimize its costs while maximizing its profits. This paper aims to estimate efficiency of Croatian banks using the DEA methodology within the period 2014-2019. In addition, the performance indicators (return on assets, return on equity) calculated for the same period aim at comparing performance indicators to efficiency results. The results indicate that larger banks are generally more efficient in operating on the frontier. And, in comparison to performance indicators, they achieve higher levels of returns on assets and equity. Furthermore, some small banks tend to be efficient, while the benefits of being a medium bank are inconclusive since the results reveal that some medium banks have below average efficiency. Overall, average efficiency improved in the observed period, which means that the consolidation process of financial institutions creates large and efficient banks.

Long-run asymmetric association between FDI and productivity in Turkey

Incoming foreign direct investments (FDI) may enhance the productivity level of the host country by bringing new advanced technologies. On the other hand, the nexus of FDI and productivity, rather than being linear, might be nonlinear because the effect of increases and decreases in FDI on productivity may not be symmetric. In this sense, this study investigates the asymmetric relationship between FDI and productivity in Turkey by using two different productivity indicators (i.e., PROD1 and PROD2) and employing a Nonlinear ARDL approach. Our hypothesis claims there is an asymmetric association between FDI and productivity in the long run in Turkey. Nonlinear cointegration test findings indicate that selected variables are cointegrated. Hence, they move together in the long run. Our study uses aggregated data at the macro level to analyze the long-term asymmetric relationship between foreign direct investment and labor productivity in Turkey using the NARDL estimation technique. Concerning the estimation results, a long-run nonlinear relationship between incoming FDI and labor productivity was detected, and this finding remained valid across two models constructed by using two distinct labor productivity indicators. As a whole, our results are consistent with the ones found in the literature. Besides, for the first time in the literature, this study addresses the long-run asymmetric nexus between FDI and labor productivity by using macro-level data specific to Turkey and makes various policy recommendations.

Empowering leadership and human resources through stimulating innovative behaviors in higher education

In the era of the Fourth Industrial Revolution, 4IR or Industry 4.0, since highly advanced technology largely replaced human works, many production activities of both goods and services were required to be innovative. The purposes of this study were to examine the role of energizing self-efficacy as a mediator of leadership empowering and innovative behavior to analyze the mediator’s role of affective commitment between the two. A survey method was used by distributing online questionnaires to 617 lecturers in Indonesia. For researching the interrelation of empowering leadership, energizing self-efficacy, affective commitment, and innovative behavior via statistical examination of their interrelationship, we applied Stata 13 software to test the hypotheses. The results pinpointed the significant impact of empowering leadership on affective commitment, energizing self-efficacy, and innovative behavior. Energizing self-efficacy significantly influenced innovative behavior, but the impact vice versa is not significant. There was an indirect effect of empowering leadership on innovative behavior through energizing self-efficacy, but the affective commitment was not a mediator between empowering leadership and innovative behavior. These findings indicated that lecturers could stimulate their innovative behaviors by increasing their self-efficacy through empowering leadership. Our research findings highlight the importance of enhancing innovative behavior, self-efficacy, and empowering leadership

Practical application of the CCB model in Czechia

This research aimed to present a new bankruptcy prediction model and apply this original prediction method in practice. The Come Clean Bankruptcy (or CCB) model uses relevant financial indicators and ratios to detect the signs of impending financial distress in time so that the management can take appropriate measures to avoid it. The model was applied to the data reported by 199 entities operating in the textile/clothing industry in the Czech Republic. Analyzing data reported for the previous seven years enabled us to predict which companies are more likely to end in a difficult financial situation. Afterward, comparing these predictions with the actual development of those companies in 2013-2020 serves to verify the efficacy and usability of the model to corporate reality. The research has shown that companies that went bankrupt in the analyzed period represented only a fraction of the data set (roughly 4.5%). Despite the small number of financial failures occurring during the analyzed period, the CCB model could detect impending bankruptcy in one-third of the cases.

Examining the factors of influence on avoiding personalized ads on Facebook

Ad personalization is becoming the dominant promotional tactic, further enhanced by new technologies applications. Greater efficiency is the main goal of such an advertising approach, but it can cause the appearance of the so-called “privacy paradox” that can induce negative consumer reactions in terms of avoiding such ads. This paper investigates the factors influencing the avoidance of personalized ads communicated through the social network Facebook. Part of the research model deals with the impact of perceived personalization, perceived irritation, and perceived privacy concerns on skepticism towards advertising and advertising avoidance. Furthermore, the empirical research was conducted on data collected through the Facebook and WhatsApp mobile applications. Following the obtained results, there is no negative effect of perceived personalization to skepticism towards advertising while it exists toward advertising avoidance. Furthermore, a positive effect of perceived irritation to skepticism towards advertising does not exist, but positive effects to ad avoidance do. The direct positive effect of perceived privacy concerns to skepticism and ad avoidance was not found. Also, skepticism about personalized ads was found not to be positively associated with avoiding personalized ads. In addition to new insights, the results can help design and implement promotional campaigns through social media technologies.

Urban employment in post-transition economies: skill mismatch in the local labor market

The paper explores the mismatch between the skills and qualifications required by the labour market and those acquired through education and on-the-job learning. The skill mismatch in transition economies tends to be even more pronounced as the labour markets in these countries are characterized by structural unemployment, affecting both older workers with obsolete skills and the young ones. Employers face poor incentives for investing in workforce skill development, due to the inadequate investment climate and volatile business environment. Transition countries face increasing outward mobility of an educated workforce, loss of human capital, and shortage of workforce in the fields such as ICT, medicine, science and research. The research is based on empirical data generated in a survey on ICT and manufacturing enterprises in the City of Niš, Serbia. The research methodology combines workers' self-assessment method for the skill gap measurement and the competence approach combined with the statistical methods. The findings indicate the presence of a qualification mismatch, in the form of the over-qualification as a dominant irregularity in the analysed labour market. The results of the study are expected to contribute to creating a network of policy instrumentaria that tend to be effective on a sub-national level in addressing the mismatch.

A qualitative approach to evaluate the reconciliation of GOLDX and OneGram in Islamic Finance

The purpose of this study is two-folded. The first purpose is to examine the perception of Islamic finance experts and Shariah scholars on the Islamic cryptocurrency (i.e., GOLDX and OneGram). The question is whether it has a role in reconciling cryptocurrency in Islamic finance. The second is to introduce the new Islamic cryptocurrency to serve these rich Islamic populaces. The study used a qualitative research approach by conducting interviews to explore the Islamic scholars’ views on the framework of the new Islamic cryptocurrency. The scholars have been deemed to meet particular requirements of having comprehensive knowledge and have extensive experience in both the Islamic Shariah and cryptocurrency. Accordingly, the number of such scholars was limited, and eventually, with the access offered only to five scholars from different Islamic countries. We thoroughly analyzed the collected data from the interviews. The findings reveal that Islamic law is absent on the essential models for the conventional cryptocurrency utilization(such as bitcoin) as either a legitimate or illicit apparatus exchange device. Consequently, introducing new Islamic cryptocurrencies is to reconcile cryptocurrencies such as GOLDX and OneGram. They will play a vital role in attracting more than 1.5 billion Muslims around the globe to enter the world of cryptocurrency.

An implementation of ensemble methods, logistic regression, and neural network for default prediction in Peer-to-Peer lending

Credit scoring has become an important issue because competition among financial institutions is intense and even a small improvement in predictive accuracy can result in significant savings. Financial institutions are looking for optimal strategies using credit scoring models. Therefore, credit scoring tools are extensively studied. As a result, various parametric statistical methods, non-parametric statistical tools and soft computing approaches have been developed to improve the accuracy of credit scoring models. In this paper, different approaches are used to classify customers into those who repay the loan and those who default on a loan. The purpose of this study is to investigate the performance of two credit scoring techniques, the logistic regression model estimated on categorized variables modified with the use of WOE (Weight of Evidence) transformation, and neural networks. We also combine multiple classifiers and test whether ensemble learning has better performance. To evaluate the feasibility and effectiveness of these methods, the analysis is performed on Lending Club data. In addition, we investigate Peer-to-peer lending, also called social lending. From the results, it can be concluded that the logistic regression model can provide better performance than neural networks. The proposed ensemble model (a combination of logistic regression and neural network by averaging the probabilities obtained from both models) has higher AUC, Gini coefficient and Kolmogorov-Smirnov statistics compared to other models. Therefore, we can conclude that the ensemble model allows to successfully reduce the potential risks of losses due to misclassification costs.

Governance and civil and political rights as FDI determinants in transition countries

This paper aimed to investigate the FDI determinants in 27 transition countries within the 2002 – 2018 period by employing system GMM analysis. One of the results of our research is that an uncertain political situation and civil liberties violations have a significant negative impact on foreign investors’ confidence. Generally, the erosion of democratic institutions acts as a deterrent to FDI inflows. Transition countries which experienced prolonged periods of central planning also recorded lower levels of FDI inflows. The results show that creating conditions for stimulating foreign investors through the improvement of institutional quality embodied in the control of corruption and voice and accountability impacted positively on FDI inflows. The interplays between overall institutional quality, voice and accountability, regulatory quality, government effectiveness and GDP growth are positive and significant. Hence, macroeconomic development has an important impact on the marginal effect of institutional quality. Therefore, we concluded that the influence of governance on FDI inflows is conditional on the transition countries’ macroeconomic performance. Our findings also reveal that of the governance dimensions, control of corruption and voice and accountability have a significant influence on the decision of multinationals to undertake investment.