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Role of investments in profit formation in the era of Industry 4.0: Case study of the Czech manufacturing industry
(Technická Univerzita v Liberci, ) Kral, Martin; Hedvicakova, Martina; Ekonomická fakulta
This study investigates the role of investments in shaping profitability within the Czech manufacturing industry between 2008 and 2022. Drawing on comprehensive industry-level data, we analyze the relationship between investment volume, efficiency, and profitability, particularly within the evolving framework of Industry 4.0. Our findings show that larger sectors with higher investment volumes generally achieve greater profitability. However, this relationship is non-linear: excessive investments can reduce efficiency, as reflected in declining added value per unit of investment. Regression analyses reveal that added value is the primary driver of profitability across manufacturing industrial sectors. Other factors, such as workforce size and the lagged effects of investments, exhibit only limited explanatory power. Furthermore, the study identifies inefficiencies arising from overinvestment, which may be attributed to market saturation, failure to fully realize economies of scale, and the unintended effects of government subsidy schemes. These results emphasize the importance of strategic investment planning that prioritizes long-term efficiency rather than short-term quantitative expansion. In the rapidly evolving context of Industry 4.0, firms must align their investment strategies with sector-specific conditions and technological demands to maintain sustainable competitiveness. This study illuminates the complex dynamics between investment behavior and profitability, offering valuable insights for managerial decision-making and economic policy formulation. It contributes to a broader understanding of how targeted investment strategies can enhance the performance of manufacturing sectors undergoing technological transformation.
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How can co-institutional investors enhance the core competitiveness of enterprises? Evidence from China
(Technická Univerzita v Liberci, ) Lu, Xinyong; Xi, Meinong; Ekonomická fakulta
As of 2023, institutional investors hold approximately 44.1% of the total market capitalization of China’s outstanding stocks. By simultaneously investing in multiple firms within the same industry, common institutional investors gain access to broader information channels and proprietary market insights at lower search costs. As shareholder linkages become increasingly common in the capital market, understanding their impact on firm behavior is of considerable practical relevance. This study empirically examines the relationship between common institutional investors and corporate innovation efficiency, using a panel of A-share listed companies in Shanghai and Shenzhen from 2010 to 2019. The results show that such investors enhance innovation efficiency through both monitoring and resource effects. Moreover, the effectiveness of these mechanisms is amplified by stronger internal control systems and better information environments. The study also finds that the impact of co-institutional investors is more pronounced in firms with higher agency costs and in non-state-owned enterprises. This research contributes to the literature on institutional ownership and innovation by providing micro-level evidence of the governance role played by co-institutional investors. It also offers practical insights for promoting sustainable and high-quality development in China and other developing economies.
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Financial innovation and financial inclusion in European countries: How do they interact?
(Technická Univerzita v Liberci, ) Nuta, Alina Cristina; Cutcu, Ibrahim; Puime-Guillen, Felix; Ekonomická fakulta
The most challenging moments in economic history necessitated adaptability to new realities and foreshadowed innovative reactions from economic agents. The recent global health crisis compelled all the stakeholders to find viable solutions to prevent the economic recovery from stalling. As finance serves as the fuel that keeps the economic engine running, exploring the factors affecting financial innovation is pivotal. Europe’s digital transition strategy provides a vibrant approach to bolstering the digital economy and financial landscape. This study evaluates the link between financial inclusion and financial innovation in selected European countries moderated by digital technology. Moreover, subsequent factors related to socio-economic development, like the standard of living, education, urbanization, and globalization, are studied to assess their impact on financial innovation. The study used new-generation panel data techniques to analyze the selected European countries from 2000 to 2020. Durbin Hausman’s cointegration test shows a long-run relationship. Our findings from fully modified ordinary least square (FMOLS) and dynamic ordinary least squares (DOLS) tests highlighted an inverse relationship between financial inclusion and financial innovation. Thus, expanding the inclusion of people in the financial ecosystem will not increase the usage of innovative financial tools. However, it will only encourage access to essential financial services and products, considering the high levels of financial inclusion in Europe and the newcomers’ financial and digital literacy levels. Additionally, the preference for using cash in European countries, which is still at high levels, also explains our results regarding the indirect connection between financial inclusion and financial innovation diffusion. Moreover, a strong direct correlation is observed between education, standard of living, and urbanization. Konya causality analysis results displayed a causal relationship between independent variables and financial innovation in different countries.
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Promoting reverse logistics decisions using a new hybrid model based on deep learning and failure mode and effects analysis approaches
(Technická Univerzita v Liberci, ) Ahmadkhan, Kamelia; Yazdani-Chamzini, Abdolreza; Bakhshizadeh, Alireza; Šaparauskas, Jonas; Turskis, Zenonas; Zeidyahyaee, Niousha; Ekonomická fakulta
The problem of reusing and recycling the returned products plays a crucial role in mitigating waste. Therefore, authorities must make the best decision in such situations. However, this problem is a paradoxical decision because different components often conflict with each other, which can impact the decision-making process. The proposed framework uses sentiment analysis algorithms to help decision-makers adopt the best reverse logistics decision strategy based on customer feedback. The framework provides a procedure for extracting, categorizing, and analyzing customer opinions. It strategically decides in reverse logistics to increase profit, efficiency, and customer satisfaction while reducing the returned products, costs, and waste. The framework has a high potential for utilization in a wide range of industries, so the probability of a biased opinion resulting from the limitation of taking into account a specific location or time is significantly diminished. This paper employs a big data mining approach to optimize the decision procedure in reverse logistics by using social media data based on customer satisfaction. To demonstrate the capability and effectiveness of the proposed framework, a real case study based on the Apple Notebook, a branch of the electronics industry, is illustrated. Consequently, a separate sentiment analysis based on a recurrent neural network (RNN), a deep learning approach, is fulfilled for notebook features and models. The framework can determine the most appropriate disposition decision in reverse logistics. Furthermore, a failure mode and effects analysis (FMEA) procedure was employed to make some suggestions about Apple.
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Mahalanobis distance and Stutzer ratio modelling in emerging markets portfolios
(Technická Univerzita v Liberci, ) Zivkov, Dejan; Kuzman, Boris; Subic, Jonel; Ekonomická fakulta
This study examines the performance of multi-asset portfolios in global emerging markets, emphasizing their exposure to systemic risk and risk-adjusted returns. The analysis encompasses portfolios from regions such as Southeast Asia, the Middle East and Central Asia, Central and Eastern Europe, Africa, and Latin America. The research uses daily data, covering a 10 years period. Two advanced methodologies are applied in the portfolio construction – the Mahalanobis distance and the Stutzer ratio. The financial turbulence index constructed for the systemic risk measurement reveals a pronounced allocation bias toward a single asset, driven by its distinctive attributes. Interestingly, the asset with the highest weight in the portfolio originates from frontier markets, which are less integrated into the global financial system and thus more insulated from global economic shocks. The Stutzer ratio, through its calculation of the decay parameter theta, provides insights into whether an emerging market portfolio is characterized by high volatility and frequent market fluctuations or is more aligned with long-term investment strategies that emphasize stability and consistent performance. The results indicate that all emerging markets portfolios have higher Stutzer ratio than the developed portfolio, which indicates better risk-adjusted results. However, the theta parameter is mostly lower in the emerging markets portfolios, suggesting higher risk in these markets. The highest Sharpe ratio is found in the African countries portfolio, while the best portfolio, when using the more advanced Stutzer ratio, is with Latin American countries. This study provides insightful guidance for international investors exploring opportunities in emerging markets, focusing on systemic risk and evaluating returns through a risk-adjusted lens.