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The purpose of this paper is to compare a firm’s net cost and post-apprenticeship benefits of providing apprenticeship training in Austria and Switzerland: two countries with many similarities but some critical institutional differences.

The authors draw on detailed workplace data with information on the costs and benefits of apprenticeship training, as well as on hiring costs for skilled workers from the external labour market. The authors use nearest-neighbour matching models to compare Austrian firms with similar Swiss firms based on observable characteristics.

On average, a Swiss firm generates an annual net benefit of €3,400 from training an apprentice, whereas a firm in Austria incurs net costs of €4,200. The impetus for this difference is largely a higher relative apprentice pay in Austria. However, compared with Swiss firms, Austrian firms generate a higher post-training return by retaining a higher share of apprentices and savings on future hiring costs.

The authors demonstrate that apprenticeship systems can exist under different institutional environments. For countries currently in the process of establishing or expanding apprenticeship systems, the comparative analysis clearly shows that policymakers should consider more than just one country’s particular apprenticeship model.

The authors provide a first comparative analysis between two apprenticeship countries that empirically assesses a firm’s costs and benefits of training during an apprenticeship programme and also provides a monetary value of a particular type of post-training benefits that firms can generate by retaining former apprentices as skilled workers (i.e. savings in future hiring costs for skilled workers).

The purpose of this study is to investigate whether business growth intention (BGI) and entrepreneurial motivations enhance the explanatory power of the theory of planned behavior (TPB) to predict environmental intention (EI) among nascent entrepreneurs.

In the context of nascent entrepreneurship, the authors collected data from 193 nascent entrepreneurs in France. To test the hypotheses, stepwise multiple regression was performed.

The results show that BGI has a positive influence on EI. This indicates that it is possible for French nascent entrepreneurs to plan the simultaneous pursuit of business growth and environmental goals. However, entrepreneurial motivations have a mixed effect on EI. If necessity motivations negatively influence EI, opportunity motivations have no significant effect on the latter.

To the best of the authors’ knowledge, this research is among the first to extend the TBP model with additional factors, namely, BGI and necessity/opportunity motivations, to study EI. Moreover, the extended TBP model is validated in the under-research context of nascent entrepreneurship.

The purpose of this study is to investigate the complexity of how demands and stress are mitigated to enhance employee performance in remote working arrangements.

A time-lagged snowball sample of 223 full-time remote working adults in the United States participated in an online survey. Data were analyzed using R 4.0.2 and structural equation modeling.

Results suggest remote job resources involving organizational trust and work flexibility increase performance via serial mediation when considering information communication technology (ICT) demands and work–life interference (WLI). The findings provide insights into counterbalancing the negative aspects of specific demands and stress in remote work arrangements.

This study provides insights for managers to understand how basic job resources may shape perspectives on demands and WLI to impact performance. Specific to remote working arrangements, establishing trust with the employees and promoting accountability with their work flexibility can play an important part in people and their performance.

This study contributes theoretically to the literature by evidencing how components of the E-Work Life (EWL) scale can be used with greater versatility beyond the original composite measurement because of the job-demand resource (JD-R) framework and conservation of resources theory (COR). This study answers several calls by research to investigate how ICT demands and WLI play a complex role in work performance.

Genre classification of songs based on lyrics is a challenging task even for humans, however, state-of-the-art natural language processing has recently offered advanced solutions to this task. The purpose of this study is to advance the understanding and application of natural language processing and deep learning in the domain of music genre classification, while also contributing to the broader themes of global knowledge and communication, and sustainable preservation of cultural heritage.

The main contribution of this study is the development and evaluation of various machine and deep learning models for song genre classification. Additionally, we investigated the effect of different word embeddings, including Global Vectors for Word Representation (GloVe) and Word2Vec, on the classification performance. The tested models range from benchmarks such as logistic regression, support vector machine and random forest, to more complex neural network architectures and transformer-based models, such as recurrent neural network, long short-term memory, bidirectional long short-term memory and bidirectional encoder representations from transformers (BERT).

The authors conducted experiments on both English and multilingual data sets for genre classification. The results show that the BERT model achieved the best accuracy on the English data set, whereas cross-lingual language model pretraining based on RoBERTa (XLM-RoBERTa) performed the best on the multilingual data set. This study found that songs in the metal genre were the most accurately labeled, as their text style and topics were the most distinct from other genres. On the contrary, songs from the pop and rock genres were more challenging to differentiate. This study also compared the impact of different word embeddings on the classification task and found that models with GloVe word embeddings outperformed Word2Vec and the learning embedding layer.

This study presents the implementation, testing and comparison of various machine and deep learning models for genre classification. The results demonstrate that transformer models, including BERT, robustly optimized BERT pretraining approach, distilled bidirectional encoder representations from transformers, bidirectional and auto-regressive transformers and XLM-RoBERTa, outperformed other models.

The study investigates the moderating effect of personal resources, including optimism and resilience, on the link between fear of Covid-19 and perceptions of academic safety among university students in Ghana.

A total of 618 students took part in the research by completing an online self-reported questionnaire. The respondents were chosen using a simple random sample method. The data was processed and analysed using IBM SPSS version 24 and SEM-PLS, respectively.

Results reveal fear of Covid-19 positively influence students' perception of academic safety. Furthermore, both resilience and optimism mitigate the impact of fear of Covid-19 on students' perceptions of academic safety.

This is the first study to examine personal resources as a moderator between fear of Covid-19 and students' perceptions of academic safety. Practical and theoretical implications are added to the text.

The potential underlying causal factors of environmental behaviours have been examined from various theoretical angles by mostly focusing on individual motivations in the literature. The purpose of this paper is to develop a conceptual model based on an integrative approach to better understand eco-sensitive consumer behaviours and their predictors.

The paper reviews distinct theoretical approaches and, based on the integrative perspective, develops a model using the framework of the goal framing theory (GFT).

On the basis of the GFT, the authors propose that 12 variables influence the pro-environmental behaviours of consumers: biospheric values, egoistic values, altruistic values, environmental concern, awareness of consequences, ascription of responsibility, subjective norms, attitudes towards behaviour, perceived behavioural control, personal norms, affect, and behavioural intention. Furthermore, the authors categorize environmental behaviours based on three different stages of the consumption process of consumers: purchase, usage, and post-use.

The proposed model will offer future studies a holistic understanding of the factors that predict environmentally sensitive behaviours of consumers and the extent to which such behaviours depend on moral considerations, feelings, or self-interest motives.

This study aims to analyze the impact of digital transformation on firm performance within the banking sector, specifically focusing on the Amman Stock Exchange (ASE)-listed banks from 2015 to 2022. Additionally, it explores the influence of gender dynamics on the implementation and outcomes of these digital transformation initiatives.

The study adopts a robust empirical approach, using manual content analysis of annual reports from ASE-listed banks. The Digital Transformation Disclosure Index (DTDI) is used to assess the extent and nature of digital transformation initiatives within these banks. The methodology is designed to provide a comprehensive evaluation of the correlation between digital transformation efforts, firm performance and gender dynamics.

The research reveals that digital transformation initiatives have a significant positive impact on the performance of ASE-listed banks. It also uncovers nuanced insights into the role of gender dynamics, indicating that gender diversity within firms influences the adoption and success of digital transformation strategies in complex ways.

The findings of this study contribute to the understanding of digital transformation in the banking sector, offering empirical evidence on its benefits for firm performance. Additionally, the study illuminates the intricate role of gender dynamics in digital transformation, providing a new perspective on organizational diversity within the context of technological change.

This research pioneers in academically linking digital transformation and gender dynamics within the banking sector, addressing a notable gap and introducing a fresh academic perspective. Practically, it equips banking executives and policymakers with actionable insights for gender-inclusive digital strategies, crucial for enhanced firm performance. Methodologically, the study sets a benchmark in research innovation, using the DTDI to offer a replicable model for future investigations in this evolving field.

The aim of this study is to investigate whether activity-based workspaces (ABWs) are able to solve the privacy-communication trade-off known from fixed-desk offices. In fixed-desk offices, employees work in private or open-plan offices (or in combi-offices) with fixed workstations, which support either privacy or communication, respectively. However, both dimensions are essential to effective employee performance, which creates the dilemma known as the privacy-communication trade-off. In activity-based workspaces, flexible workstations and the availability of different spaces may solve this dilemma, but clear empirical evidence on the matter is unavailable.

To address this knowledge gap, the authors surveyed knowledge workers (N = 363) at a medium-sized German company at three time points (T1–T3) over a one-year period during the company’s move from a fixed-desk combi-office (a combination of private and open-plan offices with fixed workplaces) to an ABW. Using a quantitative survey, the authors evaluated the employees’ perceived privacy and perceived communication in the old (T1) and the new work environments (T2 and T3).

The longitudinal study revealed a significant increase in employees’ perceived privacy and perceived communication in the ABW. These increases remained stable in the long term, which implies that ABWs have a lasting positive impact on employees.

As the privacy and communication dimensions were previously considered mutually exclusive in a single workplace, the results confirm that ABWs can balance privacy and communication, providing optimal conditions for enhanced employee performance.

Suicidal attempts and thoughts are particularly relevant to the health of the elderly and can impact not only the individual, but family, friends and spouses as well. This topic is important for the gerontological research community, particularly as it relates to social isolation and the feeling of loneliness, common in this population group. The purpose of this paper is to investigate new knowledge about the relationship between an increased risk of suicide in the elderly and social isolation or loneliness.

An extensive search was conducted to find relevant studies to answer the research question. Database research was done in PubMed and PsycINFO for relevant studies within the last 10 years. The title and abstract of relevant articles were screened before the full-text was acquired.

In PubMed 163 studies were identified, and in PsycINFO 66 studies were identified. After a thorough screening, nine studies were found to be appropriate for this study.

It is not clear which risk factor leads to an increase in suicidal thoughts and attempts, however most studies contemplated loneliness and isolation as a covariant. A causal link between the concepts is not simple. Nevertheless, loneliness and isolation seem to be relevant factors for suicidal ideations.