Engineering Economics

Event Sentiment and Cross-Country Herding Spillover Effects Using Machine Learning

Wei Chen, Muhammad Asim, Muhammad Yasir, Mehboob ul Hassan, Adnan Shoaib — Wed, 30 Apr 2025 00:00:00 +0300

This research study investigates herding behaviour and its cross-country spillover effects in the UK, US, China, and Pakistan stock markets in the presence of event sentiment. We used three machine learning models for the empirical investigation: support vector regression, single-layer neural networks, and multi-layer neural networks. The daily data set of the listed stocks has been used. The results suggest a significant predictability of the Twitter sentiment of Brexit 2016 and COVID-19. Cross-country herding spillover is also evident from the UK to Pakistan and the US in the case of Brexit 2016. Similarly, there is a herding spillover effect from China to Pakistan and UK stock markets. The overall results of machine learning models are more significant than linear regression models. Furthermore, the event sentiment improves the performance of the machine learning models. The study provides a deep insight for individual and institutional investors to take care of unpredicted events while constructing their international portfolios in these stock markets.

Deep Learning Model for Estimation Market Risk in Insurance Sector

Sasa Meza, Ljiljana Popovic, Nikola Radivojevic, Sanja Doncic — Wed, 30 Apr 2025 00:00:00 +0300

The paper developed a model for market risk assessment based on deep learning in combination with non-parametric, parametric and semi-parametric VaR and ES models. We presented the ANN-GRU model more precisely. It is intended for insurance companies operating in emerging markets because the model was developed to cover all the characteristics of emerging markets. The research was conducted on the example of 8 optimal investment portfolios for insurance companies operating in the Balkan countries. The portfolios were calibrated at the daily level and calculated for the period from 1 January 2020 to 31 December 2023. The first 500 data were used to estimate the calibration of the VaR model, the other 250 to estimate the validity of the VaR model, and the last 250 to test the validity of the VaR/ES-GRU-DL market risk estimates in accordance with Directive II. Conditional and unconditional coverage tests were used to test the validity of VaR estimates, while Berkowitz's ES test was used to test the validity of ES estimates. Due to the limitations of these tests, the validity of the backtesting VaR estimate was performed using Dufour Monte Carlo simulations, while the validity of the backtesting ES estimate used the Bootstrap procedure. The backtesting results, as well as the results of the validity of the backtesting results, show that the model generates reliable estimates of VaR and ES in accordance with the Solvency II directive as well as produces better estimates compared to the popular and widely used VaR and ES models.

Spillover Effects of Cryptocurrency Volatility on Green Finance

Iulia Cristina Iuga, Raluca Andreea Nerisanu, Larisa-Loredana Dragolea — Wed, 30 Apr 2025 00:00:00 +0300

This study investigates the risk spillover between clean and dirty cryptocurrencies and their impact on green finance indexes (solar, wind, and nuclear energy) and regional economic indexes (Baltic Dry Index and CRB Index), with data processed using the diagonal BEKK model. The results identify several dirty cryptocurrencies such as: Ethereum Cash (ETC), Litecoin (LTC), and Bitcoin (BIT) as potential diversifiers and hedges with specific green energy and economic indexes. Our findings show that news from the cryptocurrency markets predominantly have a positive, significant effect on the covariance with green finance indices. The study also presents the covolatility spillover effect, showcasing the impact of a return shock in one market, such as the cryptocurrency market or the green finance market, on the co-volatility between markets, including regional economic indices like the Baltic Dry Index and CRB Index. The analysis reveals differential spillover patterns between clean and dirty cryptocurrencies and various green finance indices, highlighting the complexity of their interactions and the varying degrees of influence on regional economic indicators.

A Systematic Literature Review of Supply Chain Management Strategies and SME Performance: A Retrospective Analysis, Current Trends and Future Opportunities

Ahmad Al Naimat, Lalita Davies — Wed, 30 Apr 2025 00:00:00 +0300

This study conducts a systematic literature review on supply chain management (SCM) strategies and their influence on Small- and Medium-sized Enterprise (SME) performance in emerging economies. Covering 241 Scopus-indexed articles from 2001 to 2024, the analysis utilizes bibliometric and content analysis with tools such as RStudio, VOSviewer, and Microsoft Excel. Three main themes emerged from the analysis: (1) SCM strategies’ impact on SME performance, (2) integration and collaboration for enhanced performance, and (3) technology adoption for competitive advantage. Findings reveal notable trends, such as the growing interest in green SCM and supply chain resilience, with the UK and India leading in contributions. This research offers SMEs actionable insights for integrating supply chain strategies, enhancing collaborative planning, and refining supply chain management capabilities. Additionally, the study provides a roadmap for future research into sustainable practices, regulatory compliance, and technology driven SCM strategies to support SMEs in addressing complex market challenges.

Generational Disparities and Their Impact on Sectoral Labour Demand

Wed, 30 Apr 2025 00:00:00 +0300

This study estimates the economic impacts of demographic changes driven by generational changes on the labour market and business environment in the Slovak Republic and selected European countries (Hungary, Poland, Czech Republic, Germany, France, Italy). It examines how demographic changes influence sectoral labour demand and the number of business entities. The main research questions are: RQ1: How do generational disparities affect sectoral demand? RQ2: How do generational disparities affect the number of entrepreneurs in the labour market? A comparative analysis of statistical data from 2013 to 2023 shows that sectors such as wholesale, retail, industry, and information and communication technology (ICT) face a shortage of skilled labour. To address RQ2, a regression analysis covering the long-term period from 1995 to 2020 is applied. The evaluation of RQ2 is supported by two hypotheses (H). H1: Changes in population development affect the number of enterprises at a statistically significant level. H2: Changes in population development affect the size of companies in a statistically significant variable. The results indicate that demographic trends associated with generational changes are reshaping the labour market structure, with the most significant impact observed in industries with high skill requirements and the segment of small and medium-sized enterprises. These businesses are flexible yet particularly vulnerable to shortages of skilled labour.

Beyond Reality: The Role of Innovation in Virtual Sport Events

Wed, 30 Apr 2025 00:00:00 +0300

With the arrival of Pandemic COVID, most sporting events were suspended, including popular foot races, known for their massification and occupation of public space. This global situation forced sporting events to innovate to become safer and to continue offering their activities despite the restrictions. From this evolution, virtual editions of many events emerged and promoted a new format that is still in force. The present study addresses the role of innovation from three perspectives: service newness in the market, incremental service innovation and technology-focused innovation, to subsequently explain the perceived quality, perceived value and satisfaction with the event. The sample was 560 participants of the Medellin Virtual Marathon. Results show that incremental service innovation and technology-focused innovativeness are important to explain perceived quality, while newness in the market is not. Subsequently, quality influences value and value influences satisfaction. Therefore, innovation must be considered in the management of virtual sporting events.

An Integrating Framework through the Extension of the UTAUT2 Model for Online Banking: A Context from a Two-Staged Approach with PLS-SEM and Fuzzy Z-AHP

Wed, 30 Apr 2025 00:00:00 +0300

This study aims to develop a conceptual model for online banking by identifying key factors influencing its acceptance and use. In light of the complexities of online banking and the challenges posed by the COVID-19 pandemic, the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) model was extended with three additional constructs: customer service, perceived security, and fear of COVID-19. The proposed framework combines the UTAUT2 model with a hybrid methodology that integrates PLS-SEM and Fuzzy Z-AHP. The study first tested the model’s hypotheses using PLS-SEM, and the results were used to construct a decision matrix for Fuzzy Z-AHP analysis. Data were collected from 346 online banking customers in Albania, revealing that habit is the most influential factor in online banking adoption. This research makes significant contributions across theoretical, managerial, and methodological domains. Theoretically, it enriches the UTAUT2 model by incorporating new constructs, enhancing its applicability. From a managerial perspective, the findings highlight critical factors shaping customer decisions, offering actionable insights for practitioners. Methodologically, the study introduces a sequential multi-method research approach by integrating PLS-SEM and Fuzzy Z-AHP.

Endogenous Growth Factors and Economic Development: An In-depth Analysis of the Impact of Investments in R&D and Human Capital on Total Factor Productivity and Export Dynamics

Sonja Šlander-Wostner, France Križanič, Borut Vojinovic — Wed, 30 Apr 2025 00:00:00 +0300

Investments in research and development (R&D) and human capital affect economic growth by influencing total factor productivity (TFP) and competitiveness (exports). The determinants of this influence were analysed on a cointegrated panel of seven large countries and separately on five medium-sized or small countries. The results show that TFP and exports per unit of R&D or per unit of human capital mainly depend on the interconnection of these two factors, but also on capital per employee, the control of inflation, the foreign trade share in GDP, oil prices, digitalisation, electrification, the concentration of development activity related to the share of military expenditures in GDP, energy efficiency and ecological protection in the national economy. In medium-sized or small countries, the influence of regulation is greater, while the effect of development activities related to military expenditures is much smaller than in the large countries.