Eurasian Business and Economics Perspectives

Many universities offer new business analytics and data science programs to meet the hot demand for data science and analytics (DSA) professionals. This study uses four data mining methods to investigate students’ intention toward DSA careers and their determinants. The data were collected from students majoring in two DSA programs. It is found that data mining models using the selected variables have better performance than using all variables. When selected variables are used, support vector machine models have a higher accuracy rate and ROC index among the data mining methods. The variable “fits my abilities/potential” is an important predictor of the career intention for both programs. Gender and year of study are found to affect the career intention of business analytics and data science students, respectively. Decision tree models further reveal that business analytics students with a very high perception rating on the variable “related to my program study” are most likely to take up a DSA career. On the other hand, data science students with a high or very high perception rating on the variable “fits my abilities/potential” are most likely to take up a DSA career.

This research aims to create a method for detecting mobile gaming addiction levels amongst children and adolescents by developing a mobile application that uses a neural network. The neural network trained on a dataset collected from a sample of 101 young individuals, including mobile device usage data, gaming logs, and the “Chen Internet Addiction Scale” self-reporting questionnaire. The performance of the system was evaluated in terms of accuracy, and its potential for facilitating educational interventions was explored. Preliminary findings suggest this approach to be a valuable tool for adolescents, educators, and parents and provides a non-invasive and non-threatening approach to identifying addiction levels and facilitating early intervention and prevention. The system shows promising results in accurately identifying different levels of gaming addiction and has the potential for educational interventions to prevent gaming addiction in youngsters. This study is an attempt in applying neural networks to identifying a level of mobile gaming addiction. However, future research should validate the proposed system in conjunction with psychology experts and enhance the neural network model by increasing the number of observations and adjusting architectural features.

During the past years, e-HRM has been developing. Due to the rapid growth of technology and the Internet, managers should update their traditional HRM techniques with modern technological tools to keep up with the current conditions. This research aims to examine the impact of e-HRM on a hotel’s performance. More specifically, this paper investigates the effect of e-HRM on hotel employees’ efficiency and HRM service quality. For this reason, qualitative research was conducted on five-star hotels in Cyprus. Twenty Human Resources specialists were interviewed. They worked on different five-star hotels located in Limassol and Paphos. The research outcome revealed the importance of e-HRM implementation in Cyprus hotels. More thoroughly, the results highlight the significance of e-HRM activities on enhancing HR services quality as well as personnel’s productivity. As a result, the performance of the hotel would be boosted. This paper contributes to the existing literature by expanding on the previous works on e-HRM and highlighting the importance of e-HRM implementation in the hotel sector.

The main purpose of this research is to determine whether learning agility (LA) plays a role in examining the effects of leadership style on innovative work behavior (IWB). Two leadership styles were included in the research model: transactional and transformational. IWB discussed with a two-dimensional model consists of “idea exploration and generation” and “idea championing and implementation”. 246 employees participated in the research. The analysis results showed that transactional and transformational leadership positively influence both dimensions of IWB. While Self-Awareness and Attitudinal Agility dimensions of LA fully mediate the relationship between transactional leadership and idea exploration and generation, they also partially mediate the relationship between transactional leadership and idea championing and implementation. Additionally, Attitudinal Agility dimension fully mediated the relationship between transformational leadership and idea exploration and generation and also has a partial mediation effect on the relationship between transformational leadership and idea championing and implementation. Self-Awareness, Experience Agility and Change Agility dimensions have a partial mediation effect on the relationship between transformational leadership and two dimensions of IWB. This study has a unique value in terms of revealing quantitative study and empirical data by evaluating the concepts of leadership types, learning agility and innovative work behavior combined.

Nowadays we are facing the consumption era and the environment forces us to change our practices to avoid losing natural resources. The concept of the circular economy appeared intending to lead to an increase in the durability of the use of products, the reduction of the consumption of materials and raw materials from the soil, and the greater use of secondary raw materials, resulting from the recovery of waste. Our scope is to present new economic directions and to outline an easy transition from linear business models to circular ones (CEBMs). To reach our purpose, we need to facilitate the transition to new business models, make the transition to the green economy, using digital evolution and constantly evaluating how the planet, the economy, and the social environment are affected. We will introduce current reports on the circular economy and the issue of waste, while also mentioning dedicated practices for circular business models. The results show that by integrating TBL principles with cutting-edge technologies, we could leverage sustainable development across governmental fields, business contexts, and private lifestyles from all three points of view.

Cocoa is one of the important commodities traded globally and also one of the main export products in Malaysia. This study is to determine the critical factors of sustainability for production, consumption and price and also to develop the price forecasting methodology of cocoa industry. Three cocoa bean price forecasting models were developed, i.e. multiple linear regression (MLR) model, Autoregressive Integrated Moving Average (ARIMA) model and Multivariate Autoregressive Moving Average (MARMA) model. The data from 1987 to 2019 was gathered for production and consumption model by using multiple linear regression (MLR) models. Based on the forecasting accuracy criteria, MARMA (1,1,1) model was found to be the best-fitted model. The novelty of this study is attributed to provide the price forecasting methodology to the policy maker and the industry. Based on the valuable findings, price is significant relationship in both production and consumption models. Moreover, price is also significant relationships among export, import and crude palm oil price. Therefore, Malaysian governors should support the subsidy for cocoa farmers and increase for local demand and get more attracting for cocoa grinders to get the prevailing prices on the international market.

Research related to digitalization in the event industry is scarce and even less to digital maturity models for the event industry. This paper aims to fill the gap and propose a digital maturity model suitable for evaluating event industry digital maturity. The model proposes five maturity levels and consists of 35 digital maturity indicators that were grouped into five dimensions such as technology, dynamic capabilities, processes, customer experience and ecosystem which have been obtained by engaging an external group of experts in the subject matter and clustering dimensions from the existing digital maturity models that have been analyzed. Then, a digital maturity model developed had been validated in the Russian context to identify the digital maturity level of event industry. A questionnaire was developed and sent to 127 leading event companies of the country. The Russian event industry comprises mainly micro and small-sized enterprises, mostly needing support to understand their path towards digital transformation and effective ecosystem based on cooperation with stakeholders through digital channels. This study is the attempt to provide a deeper understanding of a digital maturity phenomenon in the event industry by proposing a new digital maturity model and also provides insights for events practitioners.

Artificial Intelligence has changed the hotel industry, which is adjusting quickly. Al is modernizing hotels to increase service and quality. To effectively compete in the era of globalization, managers must prioritize the use of technology and the internet above traditional methods. The scope of this research is twofold: (1) to investigate the perspectives of hotel managers about the deployment of AI in Cypriot hotels and (2) to examine the potential for enhancing service quality in Cypriot hotels via the use of AI, robotics, and automation. Interviews with a sample frame consisting of 40 Human Resources managers of four-star hotels in Cyprus have been applied to collect the data. The research demonstrates that hotel managers not only endorse the integration of AI in the hotel industry, but also see it as an essential need. Their goal is to incorporate AI, robotics, and automation into their operations with the belief that it would result in time savings, enhanced service quality, and a competitive advantage. Furthermore, certain challenges related to the use of technology are observed. This paper enhances the theory by expanding the AI literature and demonstrating the significance of AI in the context of hotels.

This paper reports on a research study that considers businesses transitioning through the Initial Public Offering (IPO) stage when share ownership changes from private to public. There are many important considerations that need to be managed at this stage in the development of a business, including ensuring the best leadership team is in place to reassure potential investors that it represents a good investment. Whereas it might be expected that a professional CEO would oversee decision making at this stage, it is often the case that the original entrepreneurial founder of the business retains control. Based upon a review of previous research undertaken, it is clear that the personal characteristics of the founder-CEO have the potential to influence strategic decision-making related to the development of an appropriate business growth strategy. The research also indicates that if the founder-CEO has an output functional background, and/or a high education level, then a research and development growth strategy is more likely, whereas a founder-CEO with a throughput functional background, a lower level of education, and/or well-developed external relationships, is more likely to support a lower-risk growth strategy based upon mergers and acquisitions.

This study aims to assess the digitization of E-commerce in the Visegrad Group (Czech Republic, Poland, Hungary, and Slovak Republic) by comparing their development from 2011 to the present against the best-performing EU countries and the EU average. This comparison is crucial to determine if the Visegrad Group is aligning with their strategic goal of converging with the EU in terms of economic and digital growth. Utilizing a comprehensive analysis of E-commerce indicators from the Digital Economy and Society Index (DESI), this research focuses specifically on the adoption and evolution of E-commerce in these countries. Our methodology involves a comparative data analysis to trace E-commerce trends and growth patterns. Key findings reveal that only the Czech Republic has surpassed the target in E-commerce adoption, with the other Visegrad nations lagging in their convergence to the EU average. Notably, the Slovak Republic shows significant volatility and instability in its E-commerce growth. The study also observes the impact of the COVID-19 pandemic on E-commerce trends, highlighting a clear growth trajectory before the pandemic and a subsequent period of stagnation.

In managerial work, the issue of competencies plays an important and inseparable role. It is crucial to determine the abilities, skills, and competencies that a business manager should have to properly perform their work. The main objective of the contribution is therefore to identify the factors of creating a business competency model for business managers and detect the possible existence of statistically significant links between the factors of managerial competency assessment and the factors of creating a business competence model. Based on the theoretical starting points, the research aims to verify the established hypothesis on a sample of 256 business managers from Slovakia using the original AMC23 questionnaire designed to assess managerial competencies, namely Motivational, Performance, Social and Target competencies. According to the research findings, statistically significant correlations between the factors of managerial competencies assessment and the factors of creating a business competency model were recorded. Using BCMCQ methodology, the degrees of importance of the individual competencies were also determined, and the final managerial competency model was refined. The research study also contains the previously proposed and research-verified business competency model.

The aim of this study is to analyze the effect of credit utilization on inflation volatility in the context of commercial and consumer loans in Turkey, which is an example for developing countries. In the study, the relations between these two variables are tested for the 2005–2020 period in Turkey, which has been struggling with the inflation problem for many years. In this context, the effects of consumer and commercial loans used in Turkey, as well as consumer price index (CPI) and producer price index (PPI) inflation rates on the volatility were examined by ARCH, GARCH, E-GARCH models. Consumer loan utilization rates it has been determined that inflation rates increase the volatility. In other words, it was concluded that the increase in the usage rate of consumer loans in Turkey in the mentioned period caused an inflationary effect on the consumer basis. Also, the utilization rate of commercial loans reduces the volatility of inflation rates. That means that the increase in the use of commercial loans increases the real money supply by decreasing the money demand in the economy.

The main objective of the study is to reveal whether the decision-making process of consumers and businesses is affected by the occurrence of climate risk. To benefit from both a spatial and a temporal perspective, a panel regression framework is used to account for 26 EU member countries over a two-decade time span (between 2000 and 2021). The key variables used as proxies for the climate change risk are represented by the level of CO2 emissions and four climate indices (the Climate Change Performance Index, the Climate Risk Index, the Climate Risk Vulnerability Index, and the Climate Risk Readiness Index). The empirical model is enhanced with a series of control variables that exhibit the main macroeconomic features of each country in the sample, while the dependent variable is represented by the Economic Sentiment Index. The findings highlight that the perception of households and companies related to their current and future economic/financial performance and their own expectations are affected by developments in various metrics of climate change. There is awareness on the climate challenges and impact not only from a macroeconomic standpoint but also at the microeconomic level of individuals and businesses.

This study examines the causal links between financial development and international trade for Indian economy, during the time period from 1980 to 2020. Our study utilizes the new measure of financial development constructed by the International Monetary Fund, namely, the broad-based financial development index and its two sub-indices, the financial market development index and the financial institutional development index; encompassing dimensions of financial access, depth and efficiency. Johansen Cointegration, Vector Error Correction model, and Vector Auto-Regressive model are estimated to examine the nature of long run relationship and short run dynamics among these variables. Econometric results indicate the existence of cointegration between the broad-based index of financial development and trade openness. Cointegration is also found to exist between trade openness and financial market development index. However, there is no evidence of cointegration between financial institutional development index and trade openness. Granger causality test results point towards the presence of uni-directional causality running from the composite index of financial development to trade openness. Financial market development is also found to Granger cause trade openness. Empirical evidence thus underlines the importance of formulating policies that recognize the role of well-developed financial markets in accelerating trade openness of Indian economy.

This paper investigates whether the calendar effect exists or not, especially the Monday effect and the January effect in the American stock market by using daily returns and monthly returns of the S&P500 index, the Russell 2000 index, and the NASDAQ index in the period 2012 to 2021. The models used in the paper are the OLS model, the GARCH model and the ARMA-GARCH model. Meanwhile, the dummy variables are inserted into models to identify different date of daily stock returns or monthly stock returns. As a result, it is obviously witnessed that there is no Monday effect and no January effect in the American stock market from 2012 to 2021. Nonetheless, the calendar effect of the large-cap stock index is different from that of the small-cap stock index. For the large cap stock index, there is a existence of the day of the week calendar effect that the average daily return on Friday in the S&P500 index is apparently different from average daily return on Monday. For the small cap stock index, there is a presence of the monthly calendar effect that average monthly return in November in the Russell 200 index is significantly different from average monthly returns in January.

This study aims to investigate the impact of dark triad personality traits (narcissism, Machiavellianism, and psychopathy) on financial crime. The author runs a multiple regression analysis to examine the impact of the dark triad on financial crime. The results indicate a significant positive relationship between narcissism and financial crime, a significant negative relationship between Machiavellianism, and an insignificant relationship between psychopathy and financial crime. This paper highlights the importance of offenders’ profiles and personality traits in detecting and deterring financial crime. Also, this study emphasizes that personality traits are essential variables that should be considered during risk assessment and that psychometric data collection can be an important stage while recruiting individuals. To our knowledge, this is the first study empirically exploring the relationship between narcissism, Machiavellianism and psychopathy, and financial crime.

The European Single Electronic Format (ESEF) introduced mandatory reporting in eXtensible Business Reporting Language (XBRL) in 2020. XBRL is more advantageous compared to data from commercial databases that only use standard financial statements. The data is more granular and non-standardized which avoids errors in data collection. While financial reports are available in XBRL format, it is rather unclear how to process them. Academic research is extracting XBRL elements with self-created software code, which requires significant programming knowledge. Additionally, the methods of XBRL data extraction are rarely specified in detail. In this paper, an open-source software called Arelle is introduced as a tool to process and analyse ESEF filings in XBRL format. Arelle is a certified XBRL software that enables the processing of XBRL filings without any prior knowledge of programming and allows the transfer into common formats such as CSV. Opportunities via Arelle, such as XBRL elements extraction or the checking of validation errors for XBRL assurance are presented by analysing German DAX 40 filings. Issues include reporting errors such as the use of incorrectly implemented prefixes. Therefore, this work is an introduction to an XBRL processing software that lacks user guides as well as its opportunities and limitations for users.