Serbian Journal of Management

Co-movement of bitcoin and gold, USD, oil, VIX: evidence of wavelet coherence and DCC-GARCH from the pandemic period

Bilgehan Tekin, Fatma Temelli, Sadik Aden Dirir — Mon, 26 Aug 2024 00:00:00 +0200

This study examines the relations of Bitcoin (BTC) prices and fluctuations with gold, USD, oil, VIX index, hedging, and diversification features in Turkiye. For this purpose, wavelet coherence and dynamic conditional correlations (DCCs) were used in the study. Our research explores whether the bubble behavior patterns in BTC prices during the COVID-19 pandemic can be used in the short term to protect against the bubble behavior in the markets that are the subject of this research and vice versa. However, whether other assets can be used to manage and hedge BTC's downside risk is also being explored. The aim is to understand how and at what level critical financial instruments and indicators are affected by each other in times of crisis and economic recession, such as pandemics, and to present valuable results to decision-makers. The sample for this study includes Turkiye for the period between 12/31/2019 and 13/07/2022. Wavelet Coherence and DCC-GARCH results indicate significant positive and negative movements of BTC prices with gold, oil, USD prices, and the VIX fear index during the pandemic. We find evidence of volatility persistence, causality, and phase differences between BTC and other financial instruments and indicators.

Designing streets for people: a multicriteria decision-making study

Wed, 06 Nov 2024 00:00:00 +0100

Designing Streets for People involves selecting appropriate materials, determining the optimal configuration, and finding the best solution based on technical criteria for urban structures. This paper aims to identify the best solution by comparing two multicriteria decision-making methods: the WISP (Weighted Sum-Product) and AHP-Gaussian, which represents a recent algorithm for the Analytical Hierarchy Process (AHP) decision- making. We created a matrix with eight factors (cost, braking distance, lifetime, sidewalk width, carbon footprint, electricity consumption, and pavement temperature) to choose between four pavement options (concrete and asphalt with different sidewalk widths). The WISP recommended a concrete pavement and 2.0-meter sidewalk. The least viable option was asphalt pavement with a 1.2-meter sidewalk, due to its higher carbon footprint (12%), increased air temperatures (10%), and greater public lighting expenses (11%). WISP allows for assigning weights to criteria with robustness, computational effectiveness, and transparency. Conversely, AHP-Gaussian incorporates a sensitivity feature that lets decision-makers assign weights based on statistical analysis. Despite each method's limitations, both are suitable for urban projects, estimating decisions based on multiple technical aspects, thereby promoting more integrated and efficient choices.

Banking fintech adoption: systematic review with bibliometric and content analysis

Muhammad Asif, Farhan Sarwar, Rab Nawaz Lodhi, Rida Akbar — Tue, 20 Aug 2024 00:00:00 +0200

This study presents a comprehensive overview of the impact of Financial Technology (FinTech) on the banking sector, scrutinizing key trends and proposing future research directions to address the evolving challenges and opportunities in the field. Utilizing the PRISMA Flowchart, the study analyzes 93 papers on FinTech in banking published between 2016 and 2022 from the Web of Science database. Employing bibliometric and content analysis methodologies, RStudio, VOSviewer, and NVivo are used for descriptive, keyword co-occurrence, and content analyses, respectively. China leads in FinTech and banking research publications, while the United States surpasses all other nations in total citations. Word cloud charts and frequency analyses reveal that "Banks" and "FinTech" are frequently mentioned. The study identifies "Adoption," "Innovation," "Artificial Intelligence," and "Crowdfunding" as primary research topics. Emphasizing the global integration of blockchain, cloud computing, and big data into FinTech research, the study provides valuable insights into the possibilities and risks associated with technological advancements in the financial sector.

Educators' learning experiences and intention to use online learning management systems’ platforms: a perceptual study

Shruti Singh, Anindita Chakraborty — Thu, 15 Aug 2024 00:00:00 +0200

This study examines the adoption and use of Online Learning Management Systems (OLMS) in central government universities in India, emphasizing the impact of instructors' previous online learning experiences. To accomplish this, we employed the Technology Acceptance Model as the theoretical foundation, expanding its scope to encompass external factors and perceived variables related to O-LMS adoption. We investigate OLMS adoption patterns, platform preferences, and the impact of ownership status on technological integration using survey data obtained from faculty members at the top ten central government universities. Through a rigorous survey conducted among 326 faculty respondents from esteemed institutions and universities, we delved into their experiences, challenges, and perceived benefits associated with O-LMS utilization. Our data show that Moodle is the most widely used OLMS platform, with 85% of surveyed universities using this open-source system. Furthermore, we identify the important impact that educators' prior online learning experiences have in molding their opinions of OLMS, emphasizing the need for extensive training and continuous support programs. Furthermore, our findings highlight the need for further research to investigate the efficacy of various OLMS platforms, longitudinal studies to track the long-term effects of adoption, and qualitative investigations into educators' perspectives and experiences. By focusing on these research directions, stakeholders can improve technology integration in educational settings, resulting in more effective and inclusive learning environments.

PhD studies in transition conditions – the basis for the educational system and economic development: a case study Serbia

Živan Živković, Marija Panić — Tue, 22 Oct 2024 00:00:00 +0200

The quality of PhD studies is a key factor in an educational system that depends on human resources development as the basis for society's development in the 21st century. This paper used the Multiple Criteria Decision Support (MCDS) and voting methods in the SWOT environment, along with the hybrid SWOT-AHP method, to assess the quality of PhD studies in Serbia. Through expert analysis within the SWOT-AHP hybrid model, the determinants of SWOT subfactors and possible strategic options were defined, and the prioritization of defined strategies was determined, with the application of which all the current weaknesses of PhD studies in Serbia can be eliminated, and the path to reaching the level of quality defined by EU standards can be defined. This study aims to direct the scientific public's attention to the declining trend in the quality of PhD studies in Serbia and its consequences.

Attitudes of SMEs towards HRM in the most important business sectors in the V4 countries

Jaroslav Belas, Juraj Cug, Veronika Svatosova, Justas Streimikis — Thu, 29 Aug 2024 00:00:00 +0200

The main objective of the research study was to formulate the attitudes of SMEs that appropriately characterize the field of HRM. In a second step, these attitudes were compared in the three most important business sectors in the V4 countries. Data collection was carried out by the external agency MNFORCE using the "Computer Assisted Web Interviewing" in June 2022. The sample of 995 respondents consisted of SMEs belonging to the three most important sectors according to the number of respondents in each V4 country. The statistical hypotheses were tested using descriptive statistics and Z-scores at a significance level of α = 5%. According to our findings, SMEs in the V4 countries consider people in the firm as the most important asset, and statistically significant differences were found within the sample set. SMEs confirmed that they consider HRM as the most important area of corporate management. The empirical research showed the existence of statistically significant differences between the assessed sectors. In view of the previous results, the approach to staff performance appraisal and motivation can be considered appropriate. No statistically significant differences within the sample were found. The manufacturing sector demonstrated the best approach to each HRM claim in the V4 countries, followed by the trade and service sectors.

The impact of knowledge vacuum to innovation process during public research organizations merger

Tue, 19 Nov 2024 00:00:00 +0100

Maintaining innovation process during merger in a merged public research organization is quite a challenge. Knowledge vacuum is a potential rising issue due to merger. This study aims to examine knowledge vacuum as intervening role between organizational factors and individual factor, also how it impacts the innovation process. PLS-SEM is applied by using software SmartPLS 4.0, and 198 innovation actors are involving in questionnaires survey. Surprisingly, the results show that knowledge vacuum positively and significantly influences absorptive and adaptive capability to form distinctive competencies. It shows that missing knowledge flows among high-performer actors, such as innovators, will enhance competencies during chaotic event due to merger. In addition, distinctive competencies have a significant positive influence to innovation process. On the other hand, knowledge vacuum is not having a direct relationship to distinctive competencies. Resource and infrastructure management has a contribution to positively forming knowledge vacuum during merger to create strong absorptive and adaptive capability and curve prominent distinctive competencies, which eventually will positively impact the innovation process.

Linking leaders’ toxic leadership behaviors to employee attitudes and behaviors

Ozan Büyükyılmaz, Cihan Kara — Mon, 20 May 2024 00:00:00 +0200

The aim of this research is to examine the detrimental impacts of toxic leadership behaviors displayed by managers on their subordinates. Specifically, the study investigates the effects of toxic leadership behaviors such as lack of appreciation, self-interest, selfishness, and negative spiritual state, as perceived by employees, on various organizational outcomes including affective commitment, job satisfaction, organizational identification, perceived job performance, and turnover intention. A total of 419 employees working in public or private institutions completed a questionnaire to collect the data. The study first assessed the reliability and validity of the measurement scales and then tested the proposed hypotheses utilizing path analysis within the framework of structural equation modeling. The results of the study indicate that lack of appreciation, self-interest, and selfishness have significant predictive effects on different employee attitudes and behaviors, whereas negative spiritual state does not significantly affect employee attitudes and behaviors. Consequently, the study demonstrates that toxic leadership negatively affects affective commitment, job satisfaction, organizational identification, perceived job performance, and increases the intention to leave. The findings provide important insights for scholars and practitioners alike, and can be used to develop strategies to mitigate the negative effects of toxic leadership on employees and organizations.

Creating shared value as a framework for responsible application of artificial intelligence in Serbia

Gordana Bulatović — Fri, 08 Nov 2024 00:00:00 +0100

This paper proposes a model of creating shared value as a framework for responsible application of artificial intelligence in Serbia, taking into account key social and economic challenges brought by this technology. The work relies on analysis of existing literature in the fields of artificial intelligence, creating shared value and Serbia's strategies for AI development. Key challenges and opportunities related to AI application in Serbia have been identified. The proposed model of creating shared value can provide a responsible and beneficial development of the AI sector in Serbia, considering the social and economic impacts of this technology.

Waste management in Slovakia and Poland as European Union member states

Bartosz Nieścior, Eleonóra Marišová — Wed, 20 Nov 2024 00:00:00 +0100

The basic European Union (EU) waste legislation is regulated by European Waste Framework Directive (1975). Since then, this directive has been significantly revised and updated and all EU members are obliged to implement the EU waste legislation into their legislation. The article presents the most important issues related to waste management in Slovakia and Poland. The paper reviews national legislation along with EU legislation. The study includes relevant conclusions with a brief comparison of the analyses carried out. The obtained results shows that the main goal relating to municipal waste - significant deviation from waste landfilling, set in both states, was not achieved.

Understanding the attitudes towards climate change in the context of trust in selected countries of Central and Eastern Europe

Zsuzsanna Deák, Gintarė Vaznonienė, Agnieszka Wojewódzka-Wiewiórska — Sat, 23 Nov 2024 00:00:00 +0100

Although there is a growing trend in scientific and political discussions about how people feel about climate change in the context of trust, adequate research in this area is lacking in Central Eastern Europe (CEE). This article aims to determine whether trust is an important factor for the perception of climate change by the inhabitants of selected CEE countries. European Social Survey (ESS) Round 10 data were used, and a multivariable binary logistic regression method was applied. This paper considers three different dimensions of climate change, concern, personal norms, and attribution, as well as a composite indicator reflecting climate attitudes (skeptic or proponent). Four different models are presented that differ only in terms of their dependent variables, while the independent variable (trust) and the control variables (socio-demographic variables) are the same in all the cases. The results show that both personal and institutional trust are very low in the selected countries. Institutional trust was significant in all four models, while personal trust was significant in the environmental norm and skepticism models. Greater trust in institutions decreases the odds of being worried about climate change and increases the odds of having feelings of personal responsibility for climate change reduction. An increased level of personal or institutional trust increases one’s chances of being in the climate proponent group. Of the socio-demographic variables examined only political left-right scale did not affect attitudes significantly.

Entropy techniques for robust management decision making in high-dimensional data

Jan Kalina — Mon, 25 Nov 2024 00:00:00 +0100

Entropy, a key measure of chaos or diversity, has recently found intriguing applications in the realm of management science. Traditional entropy-based approaches for data analysis, however, prove inadequate when dealing with high-dimensional datasets. In this paper, a novel uncertainty coefficient based on entropy is proposed for categorical data, together with a pattern discovery method suitable for management applications. Furthermore, we present a robust fractal-inspired technique for estimating covariance matrices in multivariate data. The efficacy of this method is thoroughly examined using three real datasets with economic relevance. The results demonstrate the superior performance of our approach, even in scenarios involving a limited number of variables. This suggests that managerial decision-making processes should reflect the inherent fractal structure present in the given multivariate data. The work emphasizes the importance of considering fractal characteristics in managerial decision-making, thereby advancing the applicability and effectiveness of entropy-based methods in management science.

Public debt management in Serbia during transition, great recession and Covid-19 pandemic

Vladimir Andric — Tue, 15 Oct 2024 00:00:00 +0200

This paper examines the nonlinear asymmetric behavior of the public debt/GDP ratio in Serbia in the first two decades of economic transition following the political and market reforms initiated at the beginning of the twenty-first century. Using quarterly data for the public debt/GDP ratio, a two-regime self-exciting threshold autoregressive threshold (SETAR) model of order one identifies a public debt/GDP ratio threshold of 66.2% above which fiscal policymakers in Serbia take corrective action in the form of increased fiscal prudence. The estimated public debt/GDP ratio threshold roughly corresponds to a 60% threshold from the Maastricht fiscal criteria and shows how fiscal policymakers in Serbia systematically ignore the 45% public debt/GDP limit set in the national fiscal rules. Such fiscal policy behavior could jeopardize the credibility of fiscal institutions in Serbia and have a negative impact on fiscal discipline and the likelihood of sovereign default