Prague University of Economics and Business

Perception of sustainable tourism among Czech young tourists (primary research). Young generations are more concerned with the ecology and sustainability. The chapter brings information and results of the research on how the young Czech tourists perceive sustainable tourism, what are their experiences, willingness to pay more and what are the attractors and detractors for using sustainable forms of tourism.

The chapter brings information about sustainable accommodation offers, promotion of sustainable tourism from National destination organizations, and infrastructure for sustainable transportation (cycle paths, trains, e-mobility chargers). The analysis reveals a significant competitive advantage for Austria. The Czech Republic has similar conditions, however, the potential is not fully used.

Performance and citation impact of scientific journals are measured by traditional metrics such as impact factor, article influence score, journal citation indicator, and others. While the impact factor is based on the total number of citations and does not reflect the quality of journals cited, the article influence score considers the past importance of the citing journals. This paper aims the analyze the possibility of measuring the performance of journals by data envelopment analysis (DEA) models and propose a new DEA based citation performance metrics for ranking of a set of journals. We applied traditional radial and slack-based measure DEA models with weight restrictions where the outputs of the models are the citation counts from Q1 to Q4 categories, and other journals. This basic model is extended by considering the impact factor of the journals from the previous year as one of the inputs of the model. The results of the study are illustrated in the set of 80 journals from the Web of Science category Operations Research and Management Science (ORMS). The dataset for the study was obtained from the Journal Citation Reports in the period from 2017 until 2022. The relative efficiency scores and the ranking of journals obtained by the models are compared with traditional metrics, Academic Journal Guide 2021 classification and the results of the study (Chen et al., Journal of Informetrics, 15(3), 2021) that applies DEA models for the classification of ORMS journals in the same year as our study.

This qualitative study investigates the adoption of Environmental, Social, and Governance (ESG) among German Mittelstand mechanical and plant engineering firms. Through semi‐structured interviews, the research identifies key barriers to ESG implementation, including human resource challenges, conceptual ambiguity, legal complexities, standardization gaps and rapid implementation pressures. Simultaneously, it uncovers driving forces such as customer demands, talent attraction, rating agency influence, intrinsic motivation, executive commitment, and regulatory compliance. Notably, profit and loss (P&L) impact emerge as a dual force, influencing both barriers and drivers. The study proposes a best practice model featuring clear responsibilities, centralization, and ESG integration in processes. Additional recommendations include developing a business case for ESG, engaging in industry‐specific networks, and aligning with prominent rating agencies. This research offers strategic insights for sustainable business practices within the Mittelstand context. It presents implications for governments and businesses, suggesting targeted policies to mitigate barriers and reinforce drivers of ESG adoption.

Interval linear programming provides a mathematical model for transportation problems, in which the values of supply, demand and the transportation costs are affected by uncertainty and can be independently perturbed within the given lower and upper bounds. For this model, we analyze the computational complexity of the problem of finding the worst (finite) optimal value over all possible choices of the uncertain data. First, we show that a recent result from bilevel programming implies NP-hardness of computing the worst optimal value for the equation-constrained formulation, in which the supplies have to be depleted and the demands have to be met exactly. Building on the result, we prove that computing the value exactly is NP-hard for all commonly used formulations of the interval transportation problem. Namely, we prove that a direct transformation of the equation constraints into inequalities preserves the worst finite optimal value of a weakly feasible interval transportation problem. We also highlight two promising classes not covered by the presented NP-hardness proof, for which no polynomial-time algorithm for computing the worst optimal value is known and whose complexity is still open: problems immune against the more-for-less paradox and problems with a Monge cost matrix.

Although various models of corporate-startup collaboration have been identified, it remains unclear how corporate managers should select the most suitable ones. The purpose of this study is to systematically identify, organize, and synthesize the relevant literature on corporate-startup collaborative innovation and, subsequently, to develop an integrative framework that helps differentiate individual models and provides criteria for choosing the ideal one. This study also reveals that new models emerge from established modes, and intermediaries, such as third-party organizations, play an essential role in facilitating innovation between corporates and startups. First, we contribute to the literature by identifying nine distinct models of corporate-startup collaboration and categorizing them by equity ownership and startup stage. Second, we propose a holistic framework with seven selection criteria that managers can employ to evaluate different forms of collaboration and to choose the most suitable ones.

This paper investigates the impact of different forms of consumption on subjective well-being. The study focuses on five key constructs: status as a fundamental motive, status consumption, bandwagon and snob luxury consumption, and materialism. Large-scale online survey findings suggest that individuals motivated by a strong drive for status attainment are more likely to engage in the consumption of goods that confer status, while they can also hold materialistic values. Model findings highlight that status consumption is a bandwagon and snob luxury consumption antecedent. Furthermore, the data highlight that subjective well-being is positively affected by status and bandwagon consumption. Surprisingly, the results showed that snob consumption and materialism negatively affect subjective well-being. To the best of our knowledge, this is the first empirical study that deals with the impact of these different forms of status-driven consumption on a consumer’s subjective well-being, offering new insights into this complex relationship.

Access to finance is a primary concern for enterprises, serving as a critical component of tangible resources within the Resource-based View (RBV) framework and driving entrepreneurial activities globally. Bank credit stands as the preferred source of debt financing for enterprises, yet information asymmetry between lenders and borrowers poses significant credit obstacles. To address these challenges, we leverage the Theory of Planned Behavior (TPB), contending that entrepreneurs’ personal attitudes, perceived behavioral control, and subjective norms influence bank credit access. Additionally, we argue that innovation performance, an intangible resource within RBV, facilitates credit access by enhancing firms’ quality and creditworthiness from lenders’ perspectives. This paper aims to examine the relationships between TPB constructs, bank credit access, and innovation performance, as well as the mediating role of innovation performance, through an analysis of 1367 enterprises across diverse European countries. Our findings reveal that innovation performance fully and inconsistently mediates the relationships between personal attitude-credit access and subjective norm-credit access, as the direct impacts of personal attitude and subjective norm on bank finance are found to be insignificant and negative, respectively. These results underscore the pivotal role of innovation performance in linking entrepreneurial behaviors to credit access, contributing to the uniqueness of this research within the entrepreneurship literature. Moreover, our study emphasizes the need for training initiatives that foster innovative and entrepreneurial attitudes among firm executives, thereby facilitating easier credit access. As highlighted by our cross-cultural analyses, these implications extend beyond national borders, offering valuable insights for enhancing credit accessibility across diverse contexts.

The most of Sub‐Saharan African (SSA) countries have been affected by climate change and food insecurity problems due to the reduction of production and productivity of cereal crops in the continent. The purpose of this research was to examine the short‐run and long‐run effects of climate change on agricultural productivity in 24 selected SSA countries. In the study, a systematic Generalized Method of Moments (GMM) Model was used with recent data from 24 SSA countries from 2001 to 2020. The panel regression result revealed that temperature and precipitation showed positive significant effects whereas carbon dioxide emission had negatively influenced the cereal crop productivity in the region. Specifically, the empirical result indicates that a one percent increase in precipitation increases cereal crop productivity by 0.27%. The empirical result of the GMM model revealed that political stability, temperature, GDP per capita, trade openness, carbon dioxide emission, fertilizer consumption, and precipitation have both short‐run and long‐run effects, while precipitation has only a short‐run effect on agricultural productivity in the study area. A key implication of this work is the realization of the lagging effects of climate change in determining cereal crop production and productivity. This study was unable to include all SSA countries because the excluded countries did not have sufficient data on the selected variables in the study. Hence, adopting high‐temperature and drought‐resistant types of enhanced cereal crops is advised to combat the negative effects of climate change in the study area.

We show that rational but inattentive agents can become polarized ex ante. We present how optimal information acquisition and subsequent belief formation depend crucially on the agent-specific status quo valuation. Beliefs can systematically—in expectations over all possible signal realizations conditional on the state of the world—update away from the realized truth, and even agents with the same initial beliefs might become polarized. We design a laboratory experiment to test the model’s predictions. The results confirm our predictions about the mechanism (rational information acquisition) and its effect on beliefs (systematic polarization), and they provide general insights into demand for information. (JEL C92, D72, D83, D91)

The primary aim of this research is to examine what makes millennial Muslim females more materialistic and less satisfied with their lives in Pakistan during the COVID-19 pandemic. In today’s world, investigating the underlying mechanism of the exponential increase in Muslim female materialism tendency is considered a worthwhile problem. Therefore, the current research develops a theoretical model based on the stress–strain model. It uses the framework to test the impact of morning TV show consumption on Muslim females’ life satisfaction, social consumption, and compulsiveness through the mediation of materialism in COVID-19. Structural equation modeling (SEM) was used. The data was collected through the mall intercept survey method from 720 millennial Muslim females. During COVID-19, the study findings revealed that high viewing of morning TV shows appears to be a significant determinant that leads to high materialism, which results in highly negative outcomes (i.e., compulsive buying, social consumption, and less satisfaction). Moreover, the results found that materialism mediated the relationship between morning TV show consumption and three studied outcomes.

The main goal of this article is to provide an overview of the use and characteristics of intelligent systems and neuroscience tools applicable in the field of contemporary advertising. The newly emerging field of computational advertising is undergoing dynamic development, and this concept is now placed in the context of advanced intelligent systems, artificial intelligence, and virtual reality. According to the specified parameters, a systematic literature search of scientific publications was carried out and subsequently evaluated. The research questions are focused on the identification of intelligent systems and current consumer neuroscience tools finding application in the current trend of computational advertising. It follows from the processed systematic literature review that there are currently a number of intelligent systems and also a number of tools in the field of consumer neuroscience that can find application within the broader concept of computational advertising. These more or less intelligent systems and neuroscientific tools are already affecting all phases of the advertising life cycle. At the same time, a number of ethical issues associated with the use of both these technologies and tools have been found, which still need to be explored. The article attempts to fill the gap in the lack of literature dealing with this issue. Last but not least, the article contains a critical view of these new technological possibilities and also describes a number of new ethical challenges arising in this area.

Dishonest behaviours such as tax evasion impose significant societal costs. Ex ante honesty oaths—commitments to honesty before action—have been proposed as interventions to counteract dishonest behaviour, but the heterogeneity in findings across operationalizations calls their effectiveness into question. We tested 21 honesty oaths (including a baseline oath)—proposed, evaluated and selected by 44 expert researchers—and a no-oath condition in a megastudy involving 21,506 UK and US participants from Prolific.com who played an incentivized tax evasion game online. Of the 21 interventions, 10 significantly improved tax compliance by 4.5 to 8.5 percentage points, with the most successful nearly halving tax evasion. Limited evidence for moderators was found. Experts and laypeople failed to predict the most effective interventions, though experts’ predictions were more accurate. In conclusion, honesty oaths were effective in curbing dishonesty, but their effectiveness varied depending on content. These findings can help design impactful interventions to curb dishonesty.

This study explores the effects of mental load and emotional load on counterproductive work behavior (CWB). Building on the conservation of resources theory and the challenge-hindrance stressor framework, we hypothesize that mental load enhances the effort and engagement of employees to accomplish goals and subsequently reduces organizational deviance (e. g., working time fraud), while emotional load, through resource depletion, weakens this relationship. We also suggest that by depleting emotional resources, emotional load could increase interpersonal deviance, with mental load exacerbating this effect due to synergistic effects. The results of a two-wave survey among 303 UK employees show that mental load reduces organizational deviance only when emotional load is low to moderate; when emotional load is high, mental load may even increase organizational deviance. The results also show that emotional load increases interpersonal deviance, irrespective of the level of mental load. The findings underscore the distinct nature of interpersonal and organizational deviance, challenges previous interpretations of the relationship between workplace stressors and CWB, and highlights the importance of considering the complex interplay between different types of stressors in predicting workplace outcomes.

We develop a novel observation-driven model for high-frequency prices. We account for irregularly spaced observations, simultaneous transactions, discreteness of prices, and market microstructure noise. The relation between trade durations and price volatility, as well as intraday patterns of trade durations and price volatility, is captured using smoothing splines. The dynamic model is based on the zero-inflated Skellam distribution with time-varying volatility in a score-driven framework. Market microstructure noise is filtered by including a moving average component. The model is estimated by the maximum likelihood method. In an empirical study of the IBM stock, we demonstrate that the model provides a good fit to the data. Besides modeling intraday volatility, it can also be used to measure daily realized volatility.

Global problems with a shortage of nurses and an increasing demand for nursing care raise questions about whether the education system as the primary source of new nurses is in line with future demands. Despite the shortage, the situation in the Czech Republic is not yet critical, but the analysis of the age structure and the small number of graduates indicates a problem on the horizon of 15 to 20 years. The objective of the article is to present the methodology developed to estimate the demand for the profession of a nurse to maintain a functional health care system according to demographic changes and to propose the optimal number of students enrolled in the nursing study program. Authors created the methodology as part of the project “Competent Nurse for the 21st Century: Analysis and proposal for optimisation of nursing education and professional practice”, supported by the Czech Republic Technological Agency. The methodology was certified by the Czech Republic Ministry of Health at the end of 2022.