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This article examines whether investing in ESG impacts banks’ stock returns, aiming to illustrate the value generated by ESG investment in the MSCI Emerging Markets Index. The fiscal year-end data of thirty-five financial companies within the Index, covering the period from December 31, 2015, to December 31, 2022, have been utilised. The analysis employs a pooled panel regression model utilising robust least squares estimation. Firm-specific and market-specific variables are used as independent variables. We have observed a significant positive direct relationship between the social pillar score and stock returns. Banks may initiate investments in social pillars in the Index. In addition, firm-specific variables such as market capitalisation, return on equity, capital adequacy, and price-earnings ratio influence the relationship between ESG pillar scores and stock returns. We recommend that portfolio managers closely monitor improvements in ESG pillar scores alongside firm-specific variables to predict banks’ stock returns in the index.

The Covid-19 pandemic has had a significant impact on the service sector. This paper aims to assess how firms in the service sector changed their behavior during the covid-19 pandemic regarding innovations and using flexible forms of work. We obtained responses from approximately 300 companies operating in the Moravian-Silesian region service sector through a questionnaire survey. We show that the most common innovation firms use organizational and process innovation. Moreover, we found that larger, younger, and more internalized firms enjoyed more innovation during the pandemic than others. While changes in part-time jobs and agreements held outside the employment relationship are temporary, changes in home office use and outsourcing appear to be permanent.

This article evaluates the production possibilities of the electricity sector in selected EU countries. The estimates for production functions are based on the financial data of individual companies in the selected sector. The analysis was based on a linearized version of the two-factor Cobb-Douglas production function, which was subsequently modified to compare productivity results by company size and country. The countries were selected based on the results of a cluster analysis. The cluster analysis was performed using aggregated data on the shares of energy sources in production in the electricity sector. The results show that companies from countries with a high share of renewables (such as Denmark) perform the worst in terms of total productivity. Furthermore, it was found that large companies have significantly higher productivity when compared to their smaller competitors.

In recent decades, digitalization has become increasingly important in the construction industry. Building Information Modeling (BIM), a digital planning method, is becoming increasingly important in the infrastructure sector. Infrastructure planning implementation is complex, so engineering firms still use conventional planning. This study sheds light on the influence of Building Information Modelling (BIM) on increasing productivity in the construction industry. Through a combination of qualitative interviews and quantitative data analysis, an in-depth understanding of the implementation processes, challenges and benefits of BIM was developed. Particular focus was placed on identifying components of success for the effective implementation of BIM in infrastructure engineering firms. The results show that BIM contributes significantly to increasing efficiency by improving the accuracy of project planning, facilitating communication between project participants and reducing the error rate in the execution phase. The study emphasises the need for a clear strategy and training to fully exploit the potential of BIM and provides valuable insights for companies planning to implement BIM.

This study addresses a critical gap in geopolitical finance by examining the heterogeneous capital market reactions of 370 global defense and aerospace (D&A) firms to the 2022 Russia-Ukraine war. While the impact of geopolitical shocks on financial markets is well-documented, the specific determinants of intra-sectoral returns remain underexplored. Employing an event study methodology, this research quantifies abnormal returns around the invasion date and conducts cross-sectional analyses to test whether these returns are systematically moderated by firms’ home country attributes, including geopolitical alignment (G7 vs. non-G7), economic status, and national defense budget levels. The empirical results reveal a profound and statistically significant divergence: firms domiciled in developed, G7, and high-budget nations experienced large positive abnormal returns, while those in other national contexts suffered significant losses. Critically, the analysis finds no evidence of a firm-size “leadership premium,” as the performance difference between the industry’s largest firms and their smaller counterparts was statistically insignificant. These findings suggest the market’s reaction was a sophisticated assessment of sovereign fiscal capacity, where investors priced in a “geopolitical premium” for firms in nations with a credible ability to fund a military buildup, while penalizing those in fiscally constrained countries for perceived macroeconomic risk. This research contributes to the literature by demonstrating that during a systemic geopolitical crisis, a nation’s macroeconomic and political attributes can dominate firm-specific characteristics in driving asset valuation.

Smart IoT devices, such as lights, locks, washing machines, security cameras, etc., are becoming omnipresent in households and companies across all industries. However, most of these devices communicate over non-secure local protocols or via cloud services where security policies are not transparent. Vulnerabilities may lead to unauthorized access to such IoT devices. Blockchain is a technology that brings security by design and can be exploited also in the area of controlling access to IoT devices. The goal of the paper is to test the use of blockchain with IoT devices to increase the security of device usage while ensuring that the user experience remains efficient and user-friendly. Three approaches to use blockchain are proposed and tested: a) application without the blockchain using standard HTTPS protocol; b) an application using blockchain, where users sign the transactions themselves; c) an application using blockchain where the server signs the transactions. The paper successfully shows that blockchain can be used to enhance IoT device security, with an focus on user-friendliness testing to ensure the solutions are practical for everyday use.

This paper uses the Malmquist Productivity Index to evaluate the impact of the COVID-19 pandemic on hotel productivity. It decomposes total factor productivity change (TFPC) into technical efficiency, pure and scale efficiency, and technical change to conclude on productivity growth before and after the outbreak of the pandemic. 112 hotels in four cities of the United States between 2011–2021 were subject to the analysis, using a multi-input (room, labor, and F&B costs) multi-output (accommodation, F&B, and total revenue) DEA-Malmquist model. The pandemic did not have an adverse effect on hotel productivity change, mainly due to the developments attributed to technological advancements. The paper offers crucial managerial implications. The results of the analysis emphasize the prominence of investment in technology to sustain productivity levels. It supports managers with strategy development and offers decision makers a wider overview of the sector.

This study aims to understand the factors influencing consumers' intention to adopt the metaverse as a marketplace for physical products and the role of trust specifically focusing on the generation aged 18–28. It also explores the moderating role of trust towards the company Meta in these relationships. An exploratory sequential mixed-method research design was employed to develop an encompassing conceptual model, enhance hypothesis formulation, and validate findings through triangulation. In the first phase of the study, in-depth interviews were conducted with professionals and students (n=11), and in the second phase, Likert-type questionnaire was administered (n=386) to university students. The data collected in the second phase was analyzed using Covariance-Based Structural Equation Modeling (CB-SEM) to validate the conceptual model. This included Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA) for reliability and validity, followed by the assessment of path coefficients. Double-mean centering was applied to test moderating effects, with all analyses conducted using the R software's lavaan package. The results confirmed the positive effects of novelty, relative advantage, realism, and compatibility on consumers' intention to adopt the metaverse as a marketplace for physical products, while complexity and financial costs were identified as barriers. Trust towards Meta did not have a moderating effect. The findings provide insights for managers to develop the metaverse in a customer-centric manner and promote its unique features while addressing complexity and financial concerns. The study extends the literature on the metaverse in the consumer goods sector and contributes to Innovation Adoption Theory.

The article discusses the existing structure of agricultural production in Ukraine and defines the key role of farmers in providing the population with food products at the beginning of a full-scale war. The high adaptability of the small goods sector of the agrarian economy and insufficient attention to its development in the pre-war period have been proven. An assessment of the main challenges, general losses and measures taken regarding the development of agriculture in Ukraine during the war period is given, and the importance of international financial support is emphasized. The need for a balanced model of the corporate and small commodity sectors development in the postwar period with a change in priorities to support small farmers is emphasized. It is proposed to develop a National Action Plan for the Development of Farming, which should be an integral part of the post-war reconstruction plan for Ukraine.

This study examines the effects of consumer price index (CPI) and regional minimum wage policy on firms’ sustainable growth from both economic and social perspectives. Using a balanced panel of 146 agricultural and manufacturing firms in Vietnam over 2011–2022 (1,752 firm-year observations), the analysis employs panel data regression models to estimate both linear and nonlinear effects. The results reveal clear evidence of inverted U-shaped relationships between CPI and the economic aspect of firm sustainable growth, indicating that moderate inflation promotes growth while excessive inflation constrains it. For the social aspect—measured by employees’ income growth, minimum wage policy show positive effects within certain thresholds, but the effects weaken beyond those levels. To ensure robustness, the system GMM approach is applied, and the results remain consistent. Overall, the findings provide firm-level evidence on how inflation and wage policies influence sustainable growth and offer implications for balanced policy design in emerging markets.

To test the diversification benefits of REIT sub-groups formed based on dividend payout ratios, we forecast ex-ante variance-covariance matrices using a rolling window correlation and a DCC model. Regression-based mean-variance spanning tests, mean-variance efficient frontiers, and a minimum variance portfolio allocation approach using ex-ante optimization frameworks are considered. A major finding of the current study is the dividend payout ratios of REITs affect REIT market diversification benefits. Apart from extending stock market index investors’ investment universe and providing more efficient (higher profitability and/or lower risk) portfolios, REITs offer diversification benefits directly related to dividend policies. A unique level of diversification is attained by classifying REITs based on their dividend payout ratios. As well, these REIT sub-groups are capable of left-shifting the efficient frontier of a market portfolio with either of the REIT sub-groups.

According to the service-dominant logic, the customer always contributes their resources to service delivery. This study adopts the service-dominant logic approach to social marketing in the context of preventative healthcare services for children immunization and investigates the influence of organizational (administrative quality, technical quality, and interpersonal quality) and customer operant resources (cultural resources, physical resources, and social resources) on word-of-mouth. Hierarchical multiple regression was used to test our hypotheses and the evidence indicated that all three quality dimensions of organizational operant resources significantly predict word-of-mouth behavior. Conversely, among three types of customer operant resources, social resources significantly predict word-of-mouth. The study contributes empirical insights to services marketing theory, social marketing theory, and practice.

This study explores the influence of the Covid-19 period on earnings management behaviour (EM) for 150 Algerian companies. The period of study (2018 to 2021) was divided into the pre-pandemic period (2018 and 2019) and the pandemic period (2020 and 2021). The study used two measures for earnings management: discretionary accruals (accounting EM) and abnormal cash flows (real EM). The results indicate that accounting EM decreased during Covid-19 compared to pre-Covid-19. But for real EM, it was the opposite; it has seen an increase during Covid-19. These results have many implications regarding the commitments of various contributors to preparing financial information and other related parties to ensure the accuracy of financial reporting during periods of crisis. More specifically, accounting standards setters should issue additional explanations regarding the accounting for some items, and auditors should extend the range of verification when certifying financial statements.

We study the trade-off between real earnings management activities (REM) and accrual-based earnings management (AEM) among newly listed Vietnamese firms from 2009 to 2019. First, we found that firms exhibit REM as well as AEM around listing events to beat earnings targets. We further explore whether managers use REM and AEM as substitutes, considering both internal factors- firms’ characteristics and external factors like audit quality and institutional environments. Our results indicate that companies employ a greater amount of AEM and less REM when they have a higher firm size, measured by total assets, experience higher levels of liquidity. Nevertheless, firms experiencing higher levels of cash flow from operating activities, net operating assets are more likely to engage in REM and but less likely to use AEM. However, when considering external factors including audit quality and institutional environments, there is limited evidence of a trade-off between the two methods. While audit quality appears to constrain only AEM, the corruption index has a negative impact on REM. Interestingly, consistent with previous studies, we also provide evidence that managers make adjustments to the level of accruals after the fiscal year-end based on the actual level of real earnings realized during the year.

Commercial real estate loans (CREL) are a modern essential business segment and of major relevance to the financial stability of an economy as they interconnect the financial markets and the real economy. Consequently, CREL are of specific interest to regulatory authorities. As far as the author knows, there exists no universal definition of CREL in the global financial industry and the regulatory environment. This has been subject to criticism due to resulting gaps and bias in data generated by regulatory filing. This study contributes to academia and applied sciences by providing the missing link. It develops a comprehensive categorization of CREL on a foundation of 34 sources predominately provided by regulatory authorities in the US and the EU. The categorization is based on a qualitative synthesis of main CREL characteristics of this particular heterogeneous asset class outlined in the detected sources. The objective of this work is to support the development of a common understanding of this investment segment among banks, institutional investors and regulatory authorities in order to allow an accurate and prompt filing.

A mall has a holistic solution for a variety of consumer needs. Malls have aggressively spread in small cities too. The presence of malls in tier II & III cities of India may have provided diversified experiences of mall culture to its residents. Malls offer an abundance of retail offerings with entertainment and leisure. Previous studies focused upon metro city malls and provided results towards mall attributes, consumer experiences, evoked emotional responses, and patronage intentions. Hence, it is indeed necessary to examine the behavioral aspects associated with visitors of small (non-metro/tier II & III) city malls to assess the change in consumption patterns of small city consumers. The present study attempts to investigate linkages among mall attractive dimensions, visitors’ experiences, and visitors’ emotions. A sample size of 613 (from malls of tier II & III cities, India) was analyzed using SEM through SmartPLS 3. Finding suggests significant relationships with few exceptions. Responders’ emotions (pleasure and arousal) are predicted when they are interacted with mall attractive dimensions due to experiences. The results may benefit mall management, mall tenants, consumers, and society at large.

This study focuses on intergenerational differences in attitudes towards sustainable consumer behaviour. The research is based on the framework of the UN Sustainable Development Goals (Agenda 2030) and analyses the attitudes of Generation Z, Millennials and Generation X. Opinions on this issue were obtained through a questionnaire survey of 703 respondents. The results show that younger generations are more positively disposed towards sustainability and more open to ecological innovations, but their decisions are often influenced by price and a lack of reliable information. Older generations take a more pragmatic approach to sustainable choices and prefer quality, price and brand trust when making purchases. The study confirms the presence of a value-action gap between intention and reality of consumption across all age groups and highlights the importance of transparency and credibility of environmental information. The findings underscore the need for differentiated marketing communication tailored to generational specifics. Institutions should respond with stricter regulation of environmental labelling and the creation of a uniform standard for the certification of sustainable products to improve transparency for consumers.

The use of Virtual Reality (VR) to visualize data is increasingly common in various fields, from medical science to education. However, visualization of geospatial data in VR is still not handled well. GIS data comes in various formats and converting them to 3D can be challenging. The choice of a format capable of streaming large amounts of spatial data in the VR scene is crucial. However, the challenge lies in ensuring the reusability of the presented scenes with different GIS data. Most applications (including the 3D scene models) are created for a single use case and do not allow for simple interchangeability of presented data. This article proposes a reusable architecture of a general-purpose web service for processing and visualizing spatial data in VR using 3D Tiles as the chosen format. The goal of the architecture is to allow fast VR scene generation from GIS data. The critical aspect is the conversion of standard GIS format to 3D Tiles. Several conversion tools were tested and compared using publicly available point and polygon feature layers in order to choose which can be used in the proposed architecture.

The paper focuses on valuation multipliers for privately held companies, with the aim of developing and applying a methodological procedure to improve the accuracy of estimating the market value. This improvement is achieved through the differentiation of an industry multiplier using financial decomposition. We applied the proposed methodology enhancements to a dataset comprising 50 Czech breweries, estimating their market value using the discounted cash flow method. Importantly, our proposed modification to the methodology is not limited to this sample of breweries; its nature makes it a generally applicable procedure. Our results demonstrate that the application of our proposed procedure significantly enhances the accuracy of market value estimation for privately held companies, yielding an increase of 40–50% compared to the use of the median value.

90 per cent of enterprises in the European Union (EU), including Lithuania, are small enterprises that prepare the abridged financial statements. Verifying the fairness of these reports for stakeholders is challenged due to the lack of data. The aim of this research is to develop a novel model based on fuzzy logic for detecting fraudulent financial statements in micro and small enterprises by using financial ratios suitable for abridged financial statements. The results have shown that the developed fuzzy model enables estimation of the level of fraud in each individual element of accounting. Identifying each fraudulent accounting element allows us to gain insights into the areas where the enterprise has committed fraud. The proposed model has been designed to help small businesses reduce the risk, but it may also be used by public authorities as a tool for achieving greater business transparency.

This paper analyses the attitudes and opinions of statutory auditors regarding the issue of Environmental, Social and Governance reporting and its verification in the Czech Republic. The research examines auditors’ willingness to perform ESG assurance, their attitudes towards ESG issues, and their views on key skills and training needs. A questionnaire survey was conducted among Czech statutory auditors, and the results were analysed using statistical methods. The findings reveal differing attitudes between auditors employed in audit firms and self-employed auditors. Auditors from larger companies are more likely to perceive ESG reporting as a meaningful tool for responsible business and demonstrate greater interest in its verification, whereas self-employed auditors tend to be more sceptical and regard ESG as more of a formal obligation. Although the study focuses on the Czech Republic, it is based on European legislation, and the results can be generalised across the EU.

The research presented aims to close a gap in the measurement of digital maturity for the domain of service which was identified through a systematic literature review. The study provides a holistic Digital Service Transformation Maturity Self-Assessment Model for service provider companies in a B2B-context based on analysis of different digital maturity models and by means of a qualitative approach through expert feedback in a Delphi-process and additional complementary literature review to define maturity assessment items. The presented Digital Service Transformation Maturity Model comprises 8 factors, 27 subfactors and 403 related specific assessment items describing digital maturity from a holistic point of view. The model has been further converted into a simple and practical tool to self-assess and visualize current state of digital maturity. The assessment model finally was pilot tested and the outcomes are also outlined in this article. The designed model provides practical implications for the ease of evaluating and improving digital maturity levels in every aspect of its factors and contributes to the successful management of digital transformation in service provider organizations by offering effective guidance how to move to the desired future maturity level based on a solid understanding of current digital maturity accomplishments.

This research delves into effective messaging strategies employed by companies to shape their reputation in anticipation of an initial public offering (IPO). Drawing insights from the analysis of 1162 media headlines encompassing 30 brands during their IPOs on NASDAQ or NYSE, the study offers valuable recommendations for entrepreneurs and startups engaging in rhetorical preparations for an IPO. By synthesizing the examination of successful companies' media framing with pertinent well-known communication frameworks (strategic communication and the PESO model), the article introduces the new 6I's model. This model serves as a comprehensive marketing guide, empowering entrepreneurs, and businesses to adeptly manage their company's reputation and highlight diverse accomplishments for the cultivation of a positive media image towards the IPO. The 6I's model encompasses messages centered on Increasing and rapid growth, Innovative technology, Immediate relevance, Individuals and personnel, In-charge management, and In-chronicle history and company tradition. Based on the suggested model, this study further develops the theoretical understanding of corporate narrative and strategic communication to mold the reputations of organizations.

This study explores the correlation between emotional intelligence (EI) and alcohol consumption patterns among Generation Z, with a focus on university students and graduates with backgrounds in economics and management. The present study explores emotional intelligence as a personal trait that potentially influences risky alcohol behaviors. These behaviors are assessed using the AUDIT (Alcohol Use Disorders Identification Test) and the TEIQue-SF (Trait Emotional Intelligence Questionnaire – Short Form). A sample of 128 respondents, recruited through online platforms, completed these standardized questionnaires. A comprehensive statistical analysis was conducted, encompassing the utilization of Spearman’s correlation coefficient and t-tests. This analysis yielded a negative correlation between emotional intelligence (EI) and the consumption of alcohol in a risky manner. The findings indicated that individuals with lower EI levels exhibited an elevated propensity for alcohol-related risks. Furthermore, gender disparities have been identified as a contributing factor to heightened alcohol consumption risk among males compared to females. While the findings of the present study confirm the association between emotional intelligence (EI) and alcohol risk, they also suggest the presence of complex underlying factors in alcohol consumption behaviors that extend beyond EI. This research contributes to the understanding of the role of emotional intelligence in managing alcohol use, with implications for  developing intervention strategies aimed at promoting emotional awareness and healthier coping mechanisms within Generation Z. Our results not only confirm older models (e.g. Kun et al., 2019; Kun and Demetrovics, 2010; Bar-On, 2006), but also reveal generation-specific nuances—e.g., a lower overall rate of risky drinking, but a persistent gender difference and the fundamental importance of self-control.

This study examines the links between conspicuous consumption and user activity on social media platforms, focusing on Generations Z, Y, and X. A set of statements focusing on conspicuous consumption, consumer behaviour on social media, and their food consumption habits was developed and tested on a sample of 679 respondents from the Czech Republic comprising these generations. Factor analysis was used to group tested statements into factors, and regression analysis was used to examine their association with salient consumption patterns. While the link between social media activity and conspicuous consumption was only confirmed for Generation X, the online behaviour of Generation Z, the confirmed influence of influencers on the purchasing behaviour of this generation, suggests a potential link that requires further  investigation.

The study aimed to determine the impact of m-banking apps’ ease of use on brand trust, including the moderating effect of users’ demographic factors on that relationship. The research was quantitative, where 400 samples were selected based on simple random sampling. The participants were m-banking app users based on their availability and popularity and concentrated on the Dhaka division. The collected data were processed through the SPSS V23 and SmartPLS. Structural equation modeling (SEM) was run to test the hypothesis. The study revealed a positive significant impact of m-banking apps’ ease of use on brand trust. In addition, gender and age had a moderating effect on the relationship between ease of use and brand trust, especially the male and older class groups who had strong brand trust at the high level of m-banking apps’ ease of use.

Traditionally, market comparison requires identifying a peer group, which still poses unresolved practical difficulties today. This research seeks to provide valuable insights into the practicality, efficiency, and accuracy of machine learning in valuing a company. It employs a state-of-the-art machine learning technique, Gradient Boosting Decision Trees (GBDT), to predict the valuation multiple directly. A yearly dataset of U.S. public companies from 1980–2021 was used. The most common multiples (EV/EBITDA, EV/EBIT, P/E, and EV/Sales) were tested. The performance of GBDT was assessed against an industry-based method. GBDT consistently outperformed the alternative method with an average 24 percentage point decrease in the median average percentage error. The results support GBDT’s potential as a supplementary tool in valuation practice.

Global mergers and faster business cycles create weakly harmonized supply chain (SC) systems. Industry 4.0’s smart digitalization opportunities significantly alter business model innovation rates. Consequently, the complexity of aligning value exploration and exploitation has increased, often missing the needed integration level. A holistic systems engineering (SE)-driven methodology for innovation, transformation, and optimizing smart SC systems is not available so far. Case studies at SAP SE's development organization for Industry 4.0 SCM solutions and three automotive companies explored objectives, obstacles, and methods for digital transformation. The results were synthesized into a holistic SC business model transformation and optimization methodology. Complementary to traditional SCM, the study proposes SE-driven meta-modelling to improve the performance, resilience, and synchronization of end-to-end supply chains. Moreover, holistic simulations and evaluation methods for the ambidexterity of SC business models have been developed, enhancing the effectiveness of value exploration and exploitation, and innovation productivity by holistically viewing emergence and convergence throughout SC capabilities' life cycles. Ambidexterity management and dynamic capabilities are addressed by SE methods like capability engineering and complex dynamic systems theory, integrated into a concise SE model.

The research focuses on the calibration and measurement of the relationship between the selected behavioural biases and the risk perceptions of Indian retail investors, as well as its ultimate implications on equity investment decisions. Further, it examines the association of the factors to non-financial determinants such as ESG investing consciousness. The research leveraged a structured questionnaire for data collection across 438 samples. EFA for factor-extraction and assessing dimensional validity; CFA for understanding the factor structure, the validity & reliability of the latent variables; and AMOS-based SEM for the establishment of path analysis and structural causal relationships amongst the variables are used for the study. The study confirms the significant impact of risk perception on equity investment decisions and establishes a significant link between the selected biases for the study and the perceived risk. The findings also indicate a statistically significant relationship between ESG consciousness and the risk perception of investors. Further, there is confirmation of a statistically significant negative moderation effect of ESG consciousness on the relationship between the selected biases and investors’ perceived risk, indicating that higher ESG consciousness weakens the positive relationship between investors’ perceived biases and risk perception.

Meteorological conditions exert a considerable influence on traffic patterns. This paper examines the influence of meteorological variables on the daily number of traffic accidents requiring fire brigade intervention. The influence of meteorological variables, including maximum temperature, wind speed, air pressure, precipitation, snow cover and sunshine, was examined. A Generalized Additive Model for variables with a Poisson distribution was employed for modelling purposes, as this allows for the representation of non-linear dependencies. The analysis demonstrates that the lowest incidence of accidents occurs at temperatures approximating 10 °C. The average daily number of accidents increases with windy weather, the minimum number of accidents occurs at zero precipitation, and the accident rate rises with higher levels of sunshine. In the Czech Republic, the period of greatest risk in terms of road traffic accidents is the summer and winter months. The findings may have several practical applications, for example, in the improvement of meteorological warnings in traffic.