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Tourism is one of the fastest growing, dynamic service activities. As a result there is a growing demand for able tourism managers with a specialist training that until now was almost non‐existent in Belgium. Moreover when appointing someone on a managerial or board level in tourism in its widest sense an economic background is normally preferred. This led to the setting up of the specialization course Tourism (a full time 1 year programme in Dutch) with the following aims:

It is well known that the laws of Leimkuhler, Mandelbrot, Lotka and the verbal formulation of Bradford's law are equivalent. In this note we prove an analogous framework of laws in which now the law of Zipf occurs instead of Mandelbrot's law. Laws in this group are Brookes' law and the graphical formulation of Bradford's law. We show that both groups of laws are very different in the sense that they are not even equal asymptotically for high rankings.

Several cross‐sectional studies reported that breakfast skipping and a poor consumption of fruits and vegetables are associated with overweight and obesity‐related morbidities. In this respect healthy eating habits such as regular breakfast and a sufficient intake of fruit and vegetables are two important items to prevent childhood and adolescent obesity. The purpose of this study is to determine the breakfast frequency and the fruit and vegetable consumption in Belgian adolescents.

A cross‐sectional study using pupils contacted by nurses in schools during an information session about female hygiene. On that occasion all pupils (boys and girls) completed a questionnaire concerning their eating habits. Subjects were boys (n = 1390) and girls (n = 3610) between 12 and 15 years of age from the main three educational programmes (general, technical and occupational programme).

Socio‐economic status significantly influenced breakfast frequency with differences between the highest educational programme (general) and the lower technical‐ and occupational programmes. The use of daily breakfast was respectively 67 versus 49 and 48 per cent for the boys and 60 versus 42 and 39 per cent for the girls). For both sexes breakfast frequency decreased when comparing age groups from 12 with 15 years of age respectively from 67 to 55 per cent for the boys and from 61 to 47 per cent for the girls. Half of the subjects who declared to have overweight (self‐image) did not take breakfast at a regular base. Twenty six per cent of the boys of the French speaking part and 19 per cent of the boys of the Flemish speaking part of Belgium declared to take only one or less than one portion of fruit and/or vegetables a day. For the girls the reported intake of one or less than one portion of fruit and/or vegetables was respectively 20 and 16 per cent. Only 13 per cent of the French speaking boys and 10 per cent of the Flemish speaking boys reported an intake of four or more fruits and/or vegetables a day. The percentage of girls reaching an intake of four or more a day was 15 per cent for the two language regions. Fruit and/or vegetable intake was influenced significantly by the educational programme and by the educational level of the mother. In conclusion, healthy eating habits among girls and boys in Belgium (as estimated by breakfast frequency and fruit and/or vegetable intake) are rather poor. These habits are influenced by age, educational programme, self‐image and educational level of the mother.

In the light of these findings action should be taken to improve the eating habits among Belgian children to prevent childhood obesity.

In this paper we start from the well‐known fact that from the law of Lotka

This paper reports some investigative results obtained through the application of differential geometry to the array manifold of a direction finding (DF) sensor array. It emphasises the crucial but so far disregarded role of the array manifold in the performance of subspace‐based direction finding (DF) algorithms and then proceeds to a compact mathematical analysis of the array manifold using the tools of differential geometry. The results thus obtained are used to quantify the effects of the array manifold properties on the performance of a DF system and to design superresolution sensor arrays.

This research paper aims to analyze the scientific and grey literature on Quality 4.0 and zero-defect manufacturing (ZDM) frameworks to develop an integrated quality 4.0 framework (IQ4.0F) for quality improvement (QI) based on Six Sigma and machine learning (ML) techniques towards ZDM. The IQ4.0F aims to contribute to the advancement of defect prediction approaches in diverse manufacturing processes. Furthermore, the work enables a comprehensive analysis of process variables influencing product quality with emphasis on the use of supervised and unsupervised ML techniques in Six Sigma’s DMAIC (Define, Measure, Analyze, Improve and Control) cycle stage of “Analyze.”

The research methodology employed a systematic literature review (SLR) based on PRISMA guidelines to develop the integrated framework, followed by a real industrial case study set in the automotive industry to fulfill the objectives of verifying and validating the proposed IQ4.0F with primary data.

This research work demonstrates the value of a “stepwise framework” to facilitate a shift from conventional quality management systems (QMSs) to QMSs 4.0. It uses the IDEF0 modeling methodology and Six Sigma’s DMAIC cycle to structure the steps to be followed to adopt the Quality 4.0 paradigm for QI. It also proves the worth of integrating Six Sigma and ML techniques into the “Analyze” stage of the DMAIC cycle for improving defect prediction in manufacturing processes and supporting problem-solving activities for quality managers.

This research paper introduces a first-of-its-kind Quality 4.0 framework – the IQ4.0F. Each step of the IQ4.0F was verified and validated in an original industrial case study set in the automotive industry. It is the first Quality 4.0 framework, according to the SLR conducted, to utilize the principal component analysis technique as a substitute for “Screening Design” in the Design of Experiments phase and K-means clustering technique for multivariable analysis, identifying process parameters that significantly impact product quality. The proposed IQ4.0F not only empowers decision-makers with the knowledge to launch a Quality 4.0 initiative but also provides quality managers with a systematic problem-solving methodology for quality improvement.

This study examines why and when nurses' role ambiguity leads to their work alienation during the COVID-19 pandemic.

Survey data were collected from 335 hospital nurses in Ma’anshan, China. The data were analyzed using hierarchical regression and bootstrapping.

Occupational disidentification mediated the relationship between role ambiguity and work alienation. This mediating effect was not significant when nurses possessed a high level of perceived climate of prioritizing COVID-19 infection prevention (PCIP).

To reduce nurses' work alienation in a pandemic situation, the hospital management team should pay attention to and try to minimize the nurses' role ambiguity and occupational disidentification. When doing so, the management team will find it particularly helpful if they can make nurses perceive a strong climate of PCIP.

This study contributes to the existing knowledge of role ambiguity and work alienation by highlighting occupational disidentification as a mediator after controlling for organizational identification in the context of COVID-19. It further demonstrates when the mediating role of occupational disidentification is likely to be strong or weak by studying the moderating effect of perceived climate of PCIP.

In this study, the authors explore the association between employee education level and the efficiency of corporate investment using data from a sample of Chinese listed firms during the period from 2011 to 2018. By examining the impact of education on investment efficiency, the authors' study provides valuable insights that contribute to a deeper understanding of the underlying economic mechanisms related to education.

The authors conduct multivariate regression analyses to examine the relationship between investment efficiency (following Richardson, 2006) and the level of employee education, along with a series of control variables. To ensure the reliability of the authors' findings, the authors subject the their results to a comprehensive set of robustness tests, such as a staggered difference-in-difference (DiD) regression approach, an instrumental variable (IV) method and the use of alternative employee education level and investment efficiency measurements.

The findings offer compelling evidence that higher levels of education have a positive impact on firms' investment efficiency, and this effect remains robust across various model specifications and endogeneity considerations. Moreover, the influence of education is more pronounced in firms that prioritize employee training, maintain effective internal communication and offer attractive financial rewards. Furthermore, the results suggest that the relationship between education and investment efficiency is influenced by the firms' business nature and competitive environment. Factors such as business complexity, labor intensity and business location also play a role in shaping the impact of education on investment outcomes.

The study emphasizes the crucial role of education in influencing investment decisions and performance within firms. By delving into this previously unexplored area, the authors' research contributes to the existing literature, establishing that the level of employee education is a significant determinant of corporate investment efficiency. This valuable insight has substantial implications for firms aiming to enhance their investment decision-making processes and overall performance. Understanding the positive impact of education on investment efficiency can empower organizations to leverage their human capital effectively and achieve better investment outcomes, ultimately contributing to long-term success and competitiveness in the market.

This study focused on how to quantify the similarities of body shape based on the front and side images, and a shape comprehensive index (I_SC) of female upper body shape based on 2D images was proposed.

In total, 190 young women were shot for front and side images, and 18 shape parameters were automatically extracted, including seven angles and 11 ratio parameters. The coefficient of variation method was used to assign different weights for related parameters, and the I_SC was calculated to describe the body shape of each subject. Five cross-sectional curves of the upper body (e.g. shoulder, chest, waist, abdomen and hip) were selected for exploring the range of shape similarity.

According to the value of I_SC, if the difference among the subjects is within the range of ±0.02, their body shapes can be regarded as similar, and the subject with the minimum distance is considered as the most similar. Error results show that the error range of the angle parameter is from 0.2° to 3.6° and the ratio range is from 0.001 to 0.119. Moreover, the t-test value among the parameters of the similar body is above 0.05, indicating that there is no significant difference for the upper body shape of the similar groups.

This method can quantify body shapes with the upper body characteristics of young women instead of subjective judgment. The study can be extended to other parts of the body and can also provide a new thought for shape similarity retrieval based on 2D images.