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This study examines the role of technology as a driver of sustainable tourism perceptions among Generation Z.

The work considers the perspective of locals in Pakistan and uses a multi-method, multiphase embedded research design approach.

The research findings demonstrated that technology has a positive correlation with the environmental, socio-cultural and economic dimensions of sustainable tourism perception among Generation Z. Therefore, technology could be considered a dimension of sustainable tourism perception for locals, but perceptions differ significantly depending on the size of the city of the participant. The results of the experimental design phase that utilized picture stimuli demonstrated a linear relationship between technology and sustainability and enhanced their definition and implementation for developing countries.

This research diverges from most past research on these topics by focusing on Generation Z, for whom digital media and technology play a crucial role and for whom these technologies are positively correlated with sustainability and its overall perception. Implications for policies and practices for emerging country governments are provided.

A systematic investigation of postgraduate leadership programs for health and/or human services offered by Australian higher education institutions was undertaken.

Quantitative analysis identified the core characteristics of the programs. A thematic analysis of the course learning outcomes was conducted and six major themes of disciplinary leadership and management knowledge; research and analytical skills; professional practice; communication and collaboration; creativity and innovation; and system knowledge are shared in this study.

The authors conclude that Australian universities have taken an evidence-based approach to leadership education.

More work might need to be undertaken to ensure leadership theories are incorporated into learning outcomes.

The purpose of this work is to optimize the monitoring of vibrations on dynamometric test rigs for railway brakes. This is a quite demanding application considering the continuous increase of performances of high-speed trains that involve higher testing specifications for brake pads and disks.

In this work, authors propose a mixed approach in which relatively simple finite element models are used to support the optimization of a diagnostic system that is used to monitor vibration levels and rotor-dynamical behavior of the machine. The model is calibrated with experimental data recorded on the same rig that must be identified and monitored. The whole process is optimized to not interfere with normal operations of the rig, using common inertial sensor and tools and are available as standard instrumentation for this kind of applications. So at the end all the calibration activities can be performed normally without interrupting the activities of the rig introducing additional costs due to system unavailability.

Proposed approach was able to identify in a very simple and fast way the vibrational behavior of the investigated rig, also giving precious information concerning the anisotropic behavior of supports and their damping. All these data are quite difficult to be found in technical literature because they are quite sensitive to assembly tolerances and to many other factors. Dynamometric test rigs are an important application widely diffused for both road and rail vehicles. Also proposed procedure can be easily extended and generalized to a wide value of machine with horizontal rotors.

Most of the studies in literature are referred to electrical motors or turbomachines operating with relatively slow transients and constant inertial properties. For investigated machines both these conditions are not verified, making the proposed application quite unusual and original with respect to current application. At the same time, there is a wide variety of special machines that are usually marginally covered by standard testing methodologies to which the proposed approach can be successfully extended.

The primary purpose of this paper is to identify the so-called core authors and their publications according to pre-defined criteria and thereby direct the users to the fastest and easiest way to get a picture of the otherwise pervasive field of bankruptcy prediction models. The authors aim to present state-of-the-art bankruptcy prediction models assembled by the field's core authors and critically examine the approaches and methods adopted.

The authors conducted a literature search in November 2022 through scientific databases Scopus, ScienceDirect and the Web of Science, focussing on a publication period from 2010 to 2022. The database search query was formulated as “Bankruptcy Prediction” and “Model or Tool”. However, the authors intentionally did not specify any model or tool to make the search non-discriminatory. The authors reviewed over 7,300 articles.

This paper has addressed the research questions: (1) What are the most important publications of the core authors in terms of the target country, size of the sample, sector of the economy and specialization in SME? (2) What are the most used methods for deriving or adjusting models appearing in the articles of the core authors? (3) To what extent do the core authors include accounting-based variables, non-financial or macroeconomic indicators, in their prediction models? Despite the advantages of new-age methods, based on the information in the articles analyzed, it can be deduced that conventional methods will continue to be beneficial, mainly due to the higher degree of ease of use and the transferability of the derived model.

The authors identify several gaps in the literature which this research does not address but could be the focus of future research.

The authors provide practitioners and academics with an extract from a wide range of studies, available in scientific databases, on bankruptcy prediction models or tools, resulting in a large number of records being reviewed. This research will interest shareholders, corporations, and financial institutions interested in models of financial distress prediction or bankruptcy prediction to help identify troubled firms in the early stages of distress.

Bankruptcy is a major concern for society in general, especially in today's economic environment. Therefore, being able to predict possible business failure at an early stage will give an organization time to address the issue and maybe avoid bankruptcy.

To the authors' knowledge, this is the first paper to identify the core authors in the bankruptcy prediction model and methods field. The primary value of the study is the current overview and analysis of the theoretical and practical development of knowledge in this field in the form of the construction of new models using classical or new-age methods. Also, the paper adds value by critically examining existing models and their modifications, including a discussion of the benefits of non-accounting variables usage.

People who identify as transgender face stigma, isolation and harassment while often struggling to come to terms with their gender identity. They also disproportionately experience mental health difficulties. The purpose of this paper is to present the voices of transgender people in the Republic of Ireland (RoI) in regard to the issues they are facing, improvements they would like to see made to schools, workplaces, services and society in general and whether mental health supports fulfil their needs.

Ten open questions were embedded within a quantitative online survey (LGBTIreland study) on factors impacting social inclusion, mental health and care. These open questions were re-analysed with exclusive focus on the transgender participants (n = 279) using content/thematic analysis.

The participants in this study reported significant signs of mental distress. The following themes emerged: impact of stigma, deficiencies in mental health services, need for education on transgender identity, importance of peer support, achieving self-acceptance and societal inclusion questioned.

Efforts to recruit young participants have led to a possible over-representation in this study.

The findings suggest the need for improvement in mental health support services, including further education in how to meet the needs of transgender individuals.

Transgender people in Ireland experience social exclusion. The need for more inclusivity was emphasised most in secondary schools. Education on transgender identities in all contexts of society is recommended by the participants.

This study reports on the largest group of transgender participants to date in RoI. Their voices will affect perceptions on social inclusion and mental health care.

This study aims to examine the effects of climate change and agricultural technologies on crop production in Vietnam for the period 1990–2018.

Several econometric techniques – such as the augmented Dickey–Fuller, Phillips–Perron, the autoregressive distributed lag (ARDL) bounds test, variance decomposition method (VDM) and impulse response function (IRF) are used for the empirical analysis.

The results of the ARDL bounds test confirm the significant dynamic relationship among the variables under consideration, with a significance level of 1%. The primary findings indicate that the average annual temperature exerts a negative influence on crop yield, both in the short term and in the long term. The utilization of fertilizer has been found to augment crop productivity, whereas the application of pesticides has demonstrated the potential to raise crop production in the short term. Moreover, both the expansion of cultivated land and the utilization of energy resources have played significant roles in enhancing agricultural output across both in the short term and in the long term. Furthermore, the robustness outcomes also validate the statistical importance of the factors examined in the context of Vietnam.

This study provides persuasive evidence for policymakers to emphasize advancements in intensive agriculture as a means to mitigate the impacts of climate change. In the research, the authors use average annual temperature as a surrogate measure for climate change, while using fertilizer and pesticide usage as surrogate indicators for agricultural technologies. Future research can concentrate on the impact of ICT, climate change (specifically pertaining to maximum temperature, minimum temperature and precipitation), and agricultural technological improvements that have an impact on cereal production.

To the best of the authors’ knowledge, this study is the first to examine how climate change and technology effect crop output in Vietnam from 1990 to 2018. Various econometrics tools, such as ARDL modeling, VDM and IRF, are used for estimation.

Many individuals start a new firm each year, mainly intending to become independent or improve their financial situation. For most of them, the first years of operations mean a substantial investment of time, effort and money with highly insecure outcomes. This study aims to explore how entrepreneurs running new firms perform financially compared with the established ones and how this situation influences their well-being.

A questionnaire survey was completed in 2021 and 2022 by a representative sample of N = 1136 solo self-employed and microentrepreneurs in the Czech Republic, with dependent self-employed excluded. This study used multiple regressions for data analysis.

Early-stage entrepreneurs are less satisfied with their financial situation, have lower disposable income and report more significant financial problems than their established counterparts. The situation is even worse for the subsample of startups. However, this study also finds they do not have lower well-being than established entrepreneurs. While a worse financial situation is generally negatively related to well-being, being a startup founder moderates this link. Startup founders can maintain a good level of well-being even in financial struggles.

The results suggest that policies should focus on reducing the costs related to start-up activities. Further, policy support should not be restricted to new technological firms. Startups from all fields should be eligible to receive support, provided that they meet the milestones of their development. For entrepreneurship education, this study‘s results support action-oriented approaches that help build entrepreneurs’ self-efficacy while making them aware of cognitive biases common in entrepreneurship. This study also underscores that effectuation or lean startup approaches help entrepreneurs develop their startups efficiently and not deprive themselves of resources because of their unjustified overconfidence.

This study contributes to a better understanding of the financial situation and well-being of founders of new firms and, specifically, startups. The personal financial situation of startup founders has been a largely underexplored issue. Compared with other entrepreneurs, this study finds that startup founders are, as individuals, in the worst financial situation. Their well-being remains, however, on a comparable level with that of other entrepreneurs.

The purpose of this paper was identification and empirical assessment of the differentiation of consumers' attitudes in Ukraine and Poland to Russian brands and other brands offered on the Russian market after Russia’s aggression against Ukraine on February 24, 2022.

The main research methods include a systematic literature review and the authors' own surveys conducted in November 2022. The research sample comprised 950 consumers – 67% of them were Poles, 30% – Ukrainians and 3% from other countries.

A respondents' country (Poland and Ukraine) does not impact attitudes to brands offered on the Russian market after Russia's invasion of Ukraine on February 24, 2022. Moreover, it does not affect and differentiate emotional engagement in the conflict and assistance to war victims. Cluster analysis resulted in identifying two groups on the basis of consumers' declared emotional reactions to the war. The first group was smaller (N = 353, 37.2%), referred to as “indifferent consumers”, and was characterized by a greater inclination to purchase brands offered in Russia. The other cluster, referred to as “sensitive consumers” (N = 597, 62.8%), comprises those engaged in offering assistance to war victims, showing strong emotions in connection with the aggression and military activities and characterized by a clearly negative attitude to Russian and other offered brands and an inclination to boycott these brands.

A short time horizon, the study confined to two countries, difficulties in reaching Ukrainian respondents due to power failures in Ukraine in the period of conducting the survey (November 2022), a non-representative research sample – overrepresentation of people aged 18–25 years.

The research study contributes to the knowledge about consumer brand attitudes and preferences under unique social, economic and market conditions. These conditions were created by Russia's invasion of Ukraine in 2022, as well as the international and global character of the war in Ukraine. The significant implications of the study refer to brand communication policies and companies' CSR-related declarations. A number of consumers' errors were recorded, resulting from wrong brand retrieval, which were rectified at a later stage as a result of international restrictions imposed on Russia, harsh media criticism and social international embargoes imposed on brands offered in Russia. The marketing communication of contemporary global brands should give consideration to the informative function of CSR activities, and the communication process should be continuous. Critical attitudes and an inclination to boycott brands point to the possible consequences faced by inconsistent and ethically doubtful brand policies. This implication is clearly confirmed by the results of the study.

The authors also wish to highlight the implications for practice and society. As mentioned earlier, Polish consumers involved in providing aid to victims of the war also expressed their opposition to the war by boycotting Russian products and international brands remaining in Russia. Popularization of the research results obtained by the authors can be a form of sensitizing the public to the need for long-term relief, awakening global awareness of the essence and importance of sanctions imposed on Russia, as well as the possibility of expressing opposition through individual purchasing decisions and boycotting brands still present in Russia.

The study allowed for identifying consumers' differentiated brand attitudes in two countries: a country inflicted by war (Ukraine) and a front-line country, strongly supporting Ukraine (Poland). The research contributes to consumer behavior theories and studies of consumer attitudes and preferences from the perspective of international corporations' CSR activities under the unique conditions of war. Also, it contributes to the knowledge of the mechanism of forming attitudes to Russian and international brands offered in Russia among CEE consumers.

Due to the uniqueness of individual construction projects, identifying the dominant risk factors is needed for risk mitigation in ongoing and future projects. This study aims to identify the dominant construction supply chain risk (CSCR) factors, based on studies conducted between 2002 and 2022.

The study adopts the preferred reporting items for systematic reviews and meta-analysis (PRISMA) procedure to identify, screen and select relevant articles in order to provide a bibliography and annotation of the prevalent risks in the supply chains. A descriptive analysis of the findings then follows.

The study’s findings have highlighted the three most prevalent risks in the construction supply chain (poor communication across project teams, changes in foreign currency rate, unfavorable climate conditions) as reported in literature, that project teams need to pay closer attention to and take proactive steps to mitigate.

Due to limitations imposed by the chosen research methodology, tools, time frame and article availability, the study was unable to examine all CSCR-related papers.

The results will serve as a useful roadmap for risk/supply chain managers in the construction industry to take strategically proactive steps towards allocating resources for CSCR mitigation efforts.

Context-specific research on the impact of social and cultural risks on the construction supply chain would be beneficial, due to emerging social network risk factors and the complex socio-cultural settings.

There is presently no study that has reviewed extant studies to identify and compile the dominant risk factors (DRFs) associated with the supply chain of construction projects for ranking in the supply chain risk management process.

The purpose of this paper is to develop a software-library in the R programming language that implements the concepts of the interpretive coordinate, interpretive axis and interpretive plane. This allows for the automatic and reliable interpretation of results from the multiple correspondence analysis (MCA) as previously proposed and published. Consequently, the users can seamlessly apply these concepts to their data, both via R commands and a corresponding graphical interface.

Within the context of this study, and through extensive literature review, the advantages of developing software using the Shiny library were examined. This library allows for the development of full-stack applications for R users without the need for knowledge of the corresponding technologies required for the development of complex applications. Additionally, the structural components of a Shiny application were presented, leading ultimately to the proposed software application.

Software utilizing the Shiny library enables nonexpert developers to rapidly develop specialized applications, either to present or to assist in the understanding of objects or concepts that are scientifically intriguing and complex. Specifically, with this proposed application, the users can promptly and effectively apply the scientific concepts addressed in this study to their data. Additionally, they can dynamically generate charts and reports that are readily available for download and sharing.

The proposed package is an implementation of the fundamental concepts of the exploratory MCA method. In the next step, discoveries from the geometric data analysis will be added as features to provide more comprehensive information to the users.

The practical implications of this work include the dissemination of the method’s use to a broader audience. Additionally, the decision to implement it with open-source code will result in the integration of the package’s functions by other third-party user packages.

The proposed software introduces the initial implementation of concepts such as interpretive coordination, the interpretive axis and the interpretive plane. This package aims to broaden and simplify the application of these concepts to benefit stakeholders in scientific research. The software can be accessed for free in a code repository, the link to which is provided in the full text of the study.