Search results

The Internet of Things (IoT) is perceived as an evolving trend in the tourism industry, with the potential to change its dynamics. IoT will help destinations, airlines, hotels and cruises personalise their services for tourists and guests. Moreover, it has several advantages for them, such as cost savings, increased productivity, greater efficiency and customised and differentiated services. The readers of this chapter will learn about the trends of IoT in the tourism industry, discover its benefits and learn about the most critical applications.

Scholarly interest in the business effects of organised crime (OC) has recently increased. This study aims to conduct a systematic literature review (SLR) on the conditions under which OC could pose a threat to or take control of firms within a particular context.

We use narrative synthesis and thematic analysis, with a sample of 46 theoretical and empirical studies published over the past 30 years on the relationship between OC and firms within the disciplines of Business, Management and Accounting (BMA).

SLR and thematic analysis show that scholarly interest has focused on four key domains: OC as a firm, the impact of OC on firms, firms’ efforts to counter OC’s influence and governmental interventions. Using medical metaphors, we also develop a diagram depicting the interplay between OC and firms within the BMA literature.

This study contributes to the literature shaping an agenda to steer future research towards these four key themes. The effectiveness of anti-OC tools and measures depends on a thorough understanding of local norms, behaviours and business practices. In addition to measurement and methodological challenges, several grey areas remain, including the distinction between criminal enterprises and legitimate businesses. Ambiguities also surround the circumstances under which the OC preys upon firms or employs them to establish dominance over a territory.

This study aimed to examine the antecedents, correlates, and consequences of burnout among higher education faculty in Saudi Arabia using the theoretical framework of the job demands-resources model.

Using a quantitative research design, a cross-sectional survey was employed to collect data from faculty members across multiple Saudi universities. The constructs were measured using validated scales, and data analysis included exploratory factor analysis, Pearson correlation analysis, factorial ANOVA, and multiple regression.

The study identified moderate levels of burnout, confirming a significant positive relationship with role conflict and a negative relationship with internal locus of control. Burnout significantly contributed to depression, insomnia, and turnover intentions. However, no significant relationship was found between burnout and workplace conflict when controlling for other variables.

The study's findings can inform policymakers and academic administrators about measures to alleviate faculty burnout, thus contributing to healthier academic work environments aligned with Saudi Arabia's Vision 2030 goals.

This research extends the job demands-resources model within the context of higher education institutions in Saudi Arabia, offering nuanced insights into burnout dynamics among university faculty in this region. Despite the model's robustness, the absence of a significant relationship between burnout and workplace conflict signals the need for a more intricate understanding of burnout's antecedents and consequences.

This study aims to evaluate the nutrient profile, carbon footprint and water footprint of one-month menus presented in five hospitals in Turkey and compare their environmental impacts with that of the Mediterranean diet.

The energy and nutrient content of menus were compared with recommendations of the Turkey Dietary Guidelines (TUBER) 2022. Nutrient profiles of hospital menus were evaluated using Nutrient Rich Food 9.3 (NRF 9.3) and SAIN-LIM models. The carbon and water footprints of the menus were calculated and compared with those of the Mediterranean diet.

Menus’ energy and nutrient content did not conform with TUBER 2022. The SAIN-LIM score of Hospital A (5.7 ± 1.1) was significantly higher than that of Hospitals C (4.8 ± 0.7, p = 0.001) and E (5.1 ± 0.7, p = 0.025). The carbon footprint of Hospital A was significantly lower (2.6 ± 0.3 kg CO₂ eq/person/day) and that of Hospital D (4 ± 0.9 kg CO₂ eq/person/day) was significantly higher than those of others (p < 0.001). While other menus were similar (p > 0.05), the water footprint of Hospital A was significantly lower (3.5 ± 0.7 L/kg, p < 0.001). In addition, if the menus were suitable for the Mediterranean diet, a reduction of 2.2–23.4% in the carbon footprint and 37.5–58.6% in the water footprint could be achieved. Moreover, menus’ carbon and water footprints were negatively correlated with NRF 9.3 and SAIN-LIM scores.

The primary aim should be to ensure that the planned menus follow the dietary guidelines. In addition, it is an undeniable fact that sustainable nutrition is a complex process with many dimensions. However, it seems possible to improve the nutrient profiles of the menus and reduce their environmental footprint with minor changes to be made in food services.

It seems possible to improve the nutrient profiles of the menus and reduce their environmental footprint with minor changes. For both health and environmental impacts, food services should switch to menus suitable for the Mediterranean diet.

The findings provide new insights into hospital menus’ quality and environmental impact.

The research paper aims to study dissatisfaction of teleworking employees in Spain during the Covid-19 health pandemic in order to propose three models: sociodemographic profile of the teleworking dissatisfied employee; advantages and disadvantages for the teleworking dissatisfied employee and advantages for the teleworking dissatisfied employee.

This study uses official open data obtained from the Spanish National Statistical Institute (INE, 2022) through Decision Trees statistical multivariable models implementing Classification and Regression Trees and Recursive Partitioning and Regression Trees techniques to determine the variables that can influence the satisfaction or dissatisfaction of the subjects.

This investigation offers three models with two sociodemographic profiles of dissatisfied teleworking employee, who is a high/middle-level manager/employee around 45 years old, and she/he lives with the partner. Regarding the most important advantage of teleworking, employees consider “use/saving of time” and as disadvantage “worse organization and coordination of work”.

This research provides empirical evidence with inductive reasoning on understanding the challenges of teleworking dissatisfied employees in Spain not only in turbulent times but also in “normalcy” to improve overall teleworker well-being and accomplish company’s and organization’s long-term objectives for better productivity and effectivity. The study has high practical value due to the integral approach incorporating dissatisfaction as a driver that can trigger negative behaviours towards the organizations and that is seldom addressed in the literature. Additionally, this paper could provide some new ideas for accomplishing “Spain Digital 2025” and “Europe’s Digital Decade: 2030” plans on institutional level.

The present study is about generating metadata to enhance thematic transparency and facilitate research on interview collections at the Research Documentation Centre, Centre for Social Sciences (TK KDK) in Budapest. It explores the use of artificial intelligence (AI) in producing, managing and processing social science data and its potential to generate useful metadata to describe the contents of such archives on a large scale.

The authors combined manual and automated/semi-automated methods of metadata development and curation. The authors developed a suitable domain-oriented taxonomy to classify a large text corpus of semi-structured interviews. To this end, the authors adapted the European Language Social Science Thesaurus (ELSST) to produce a concise, hierarchical structure of topics relevant in social sciences. The authors identified and tested the most promising natural language processing (NLP) tools supporting the Hungarian language. The results of manual and machine coding will be presented in a user interface.

The study describes how an international social scientific taxonomy can be adapted to a specific local setting and tailored to be used by automated NLP tools. The authors show the potential and limitations of existing and new NLP methods for thematic assignment. The current possibilities of multi-label classification in social scientific metadata assignment are discussed, i.e. the problem of automated selection of relevant labels from a large pool.

Interview materials have not yet been used for building manually annotated training datasets for automated indexing of scientifically relevant topics in a data repository. Comparing various automated-indexing methods, this study shows a possible implementation of a researcher tool supporting custom visualizations and the faceted search of interview collections.

The goal of this study was to understand which employee-focused workplace practices and priorities – more formally known as human resource (HR) practices and priorities – employees with mental health and/or addiction challenges (MHAC) valued and how they perceived the day-to-day implementation of those practices and priorities in the workplace integration social enterprises (WISEs) that employed them.

Twenty-two WISE workers who self-identified as having serious MHAC participated in semi-structured interviews. Interviews were transcribed and coded to identify ways that employees did or did not feel supported in their WISEs.

Participants identified three HR practices and two HR priorities as important to establishing an inclusive workplace that accommodated their MHAC. The extent to which individual participants felt included and accommodated, however, was shaped by interactions with their supervisors and coworkers.

By evaluating the salience of WISEs’ employee-focused workplace practices and priorities through the lens of the employees themselves, our study articulates the critical role that interactions with coworkers and supervisors have in determining whether HR practices and priorities have the intended effect on worker experience.