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Environmental tourism impacts are considered to be unbalanced. The implementation of environmental sustainability focuses on restoring a balance through environmentally responsible behavior. As Generation Z was found in recent studies to exhibit divergent levels of environmentally responsible behavior compared to other generations, but also to have intra-generational differences, this study aims to explore the underlying reasons and explanations behind their attitudes and behavioral attempts.

Four focus group discussions with young people belonging to Generation Z allow to probe deep into their environmental sustainability orientation.

The results of this study demonstrate that Generation Z’s environmental attitude is triggered by social pressure, social media, as well as by the COVID-19 pandemic. For their touristic behavioral intention, they concentrate predominantly on climate-friendly travel and on-site mobility, waste avoidance as well as emphasizing economic and social sustainability. By furthermore highlighting Generation Z’s responsibility ascription to the supply and the demand side, in addition to illustrating the demand for framework conditions to be created from governments and destinations, the knowledge scope on environmental sustainability is expanded.

In particular, this study enriches environmentally responsible behavior research by incorporating the perspective of Generation Z, while it deepens Generation Z’s behavioral understanding. Furthermore, the results of this study allow to derive implications for tourism policymakers.

环境旅游影响被认为是不平衡的。环境可持续性的实施侧重于通过对环境负责的行为来恢复平衡。由于最近的研究发现Z一代与其他几代人相比表现出不同的环境责任行为水平, 且存在代际差异, 本研究探讨了他们的态度和行为尝试背后的潜在原因和解释。

采用四个焦点小组与Z世代年轻人讨论, 深入探究他们的环境可持续性导向。

这项研究的结果表明, Z世代的环境态度是由社会压力、社交媒体以及COVID-19大流行引发的。对于他们的旅游行为意向, 他们主要关注气候友好型旅行和现场移动性, 避免浪费以及强调经济和社会的可持续性。通过进一步强调Z世代对供给侧和需求侧的责任归因, 并阐释政府和目的地对框架条件的需求, 扩大了环境可持续性的知识范围。

特别地, 本研究通过纳入Z世代的视角, 丰富了环境责任行为研究, 加深了Z世代的行为理解。此外, 本研究的结果可以为旅游政策制定者提供启示。

Los impactos medioambientales del turismo se consideran desequilibrados. La implementación de la sostenibilidad medioambiental se centra en restablecer el equilibrio mediante un comportamiento responsable con el medio ambiente. Estudios recientes señalan que la Generación Z muestra niveles divergentes de comportamiento responsable con el medio ambiente en comparación con otras generaciones, pero también presenta diferencias intra-generacionales. Este estudio explora las razones y explicaciones subyacentes a sus actitudes e intenciones de comportamiento.

Cuatro grupos de discusión con jóvenes de la Generación Z permiten profundizar en su orientación hacia la sostenibilidad medioambiental.

Los resultados de este estudio evidencian que la actitud medioambiental de la Generación Z está provocada por la presión social, medios sociales, así como por la pandemia del COVID-19. En cuanto a su intención de comportamiento turístico, se concentran predominantemente en los viajes respetuosos con el clima y la movilidad in situ, evitar residuos, así como en hacer hincapié en la sostenibilidad económica y social. Al destacar la responsabilidad que la Generación Z atribuye a la oferta y la demanda, además de inculcar la demanda para la creación de condiciones marco por parte de gobiernos y destinos, se amplía el alcance del conocimiento sobre la sostenibilidad medioambiental.

En particular, este estudio enriquece la investigación sobre el comportamiento responsable con el medio ambiente al incorporar la perspectiva de la Generación Z y profundizar en la comprensión del comportamiento de esta generación. Asimismo, los resultados de este estudio permiten desarrollar implicaciones para los responsables de las políticas turísticas.

In cities with high density, heat is often trapped between buildings which increases the frequency and intensity of heat events. Researchers have focused on developing strategies to mitigate the negative impacts of heat in cities. Adopting green infrastructure and cooling pavements are some of the many ways to promote thermal comfort against heat. The purpose of this study is to improve microclimate conditions and thermal comfort levels in high-density living conditions in Seoul, South Korea.

This study compares six design alternatives of an apartment complex with different paving and planting systems. It also examines the thermal outcome of the alternatives under normal and extreme heat conditions to suggest strategies to secure acceptable thermal comfort levels for the inhabitants. Each alternative is analyzed using ENVI-met, a software program that simulates microclimate conditions and thermal comfort features based on relationships among buildings, vegetation and pavements.

The results indicate that grass paving was more effective than stone paving in lowering air temperature and improving thermal comfort at the near-surface level. Coniferous trees were found to be more effective than broadleaf trees in reducing temperature. Thermal comfort levels were most improved when coniferous trees were planted in paired settings.

Landscape elements show promise for the improvement of thermal conditions because it is much easier to redesign landscape elements, such as paving or planting, than to change fixed urban elements like buildings and roads. The results identified the potential of landscape design for improving microclimate and thermal comfort in urban residential complexes.

The results contribute to the literature by examining the effect of tree species and layout on thermal comfort levels, which has been rarely investigated in previous studies.

Automatically extracting stance information from natural language texts is a significant research problem with various applications, particularly after the recent explosion of data on the internet via platforms like social media sites. Stance detection system helps determine whether the author agree, against or has a neutral opinion with the given target. Most of the research in stance detection focuses on the English language, while few research was conducted on the Arabic language.

This paper aimed to address stance detection on Arabic tweets by building and comparing different stance detection models using four transformers, namely: Araelectra, MARBERT, AraBERT and Qarib. Using different weights for these transformers, the authors performed extensive experiments fine-tuning the task of stance detection Arabic tweets with the four different transformers.

The results showed that the AraBERT model learned better than the other three models with a 70% F1 score followed by the Qarib model with a 68% F1 score.

A limitation of this study is the imbalanced dataset and the limited availability of annotated datasets of SD in Arabic.

Provide comprehensive overview of the current resources for stance detection in the literature, including datasets and machine learning methods used. Therefore, the authors examined the models to analyze and comprehend the obtained findings in order to make recommendations for the best performance models for the stance detection task.

Present for more than 20 years, 3D food printing (3DFP) technology has not experienced the same widespread adoption as its non-food counterparts. It is believed that relevant business models are crucial for its expansion. The purpose of this study is to identify the dominant prototypical business models and patterns in the 3DFP industry. The knowledge gained could be used to provide directions for business model innovation in this industry.

The authors established a business model framework and used it to analyse the identified 3DFP manufacturers. The authors qualitatively identified the market’s prototypical business models and used agglomerative hierarchical clustering to extract further patterns.

All identified 3DFP businesses use the prototypical business model of selling ownership of physical assets, with some variations. Low-cost 3D food printers for private usage and dedicated 3D food printers for small-scale food producers are the two primary patterns identified. Furthermore, several benefits of 3DFP technology are not being used, and the identified manufacturers are barely present in high-revenue markets, which prevents them from driving technological innovation forward.

The extracted patterns can be used by the companies within the 3DFP industry and even in other additive manufacturing segments to reflect upon, refine or renew their business model. Some directions for business model innovation in this industry are provided.

To the best of the authors’ knowledge, this is the first quantitative study to give an account of the current 3DFP business models and their possible evolution. This study also contributes to the business model patterns methodological development.

This paper aims to classify journal papers in the context of hybrid quality function deployment QFD and multi-criteria decision-making (MCDM) methods published during 2004–2021.

A conceptual classification scheme is presented to analyze the hybrid QFD-MCDM methods. Then some recommendations are given to introduce directions for future research.

The results show that among all related areas, the manufacturing application has the most frequency of published papers regarding hybrid QFD-MCDM methods. Moreover, using uncertainty to establish a hybrid QFD-MCDM the relevant papers have been considered during the time interval 2004–2021.

There are various shortcomings in conventional QFD which limit its efficiency and potential applications. Since 2004, when MCDM methods were frequently adopted in the quality management context, increasing attention has been drawn from both practical and academic perspectives. Recently, the integration of MCDM techniques into the QFD model has played an important role in designing new products and services, supplier selection, green manufacturing systems and sustainability topics. Hence, this survey reviewed hybrid QFD-MCDM methods during 2004–2021.

The purpose of this paper is to explore the relationship between general self-efficacy (GSE), job search self-efficacy (JSSE), extraversion and job search success within a sample of new entrants in the labour market. It is hypothesised that JSSE acts as a mediator between GSE and job search success. Evaluation of the hireability – made by expert interviewers – of new entrants involved in a job interview simulation is proposed as a job search success criterion. Moreover, the moderating role of extraversion on the relationship between JSSE and job search success is explored.

Data were collected on 177 graduates from an Italian university. Participants were involved in a simulation of an interview conducted by experts of the personnel selection process, who gave an evaluation. Macro PROCESS for SPSS was used to test the hypotheses.

GSE has an indirect effect on job search success via JSSE. Moreover, extraversion has a moderating effect on the JSSE–job search success relationship for more extraverted job seekers.

Job search and counselling practitioners should consider extraversion and personal differences to improve the effectiveness of interventions aimed at fostering new entrants' self-regulatory resources and behaviours during the job search.

This study contributes to the existing research about the job search process by testing a new and important job search success criterion, showing that GSE could help new graduates in establishing a specific self-efficacy, such as JSSE, and demonstrating that extraversion interacts with JSSE.

The purpose of this paper is to identify sensing, seizing and reconfiguring routines of dynamic capabilities that enable digital transformation in firms.

A qualitative approach is used. Representatives from a firm going through digital transformations are interviewed, and focus groups have been carried out with a consultancy firm experienced in giving advice to firms going through digital transformation.

Six routines identified as relevant specifically for digital transformation are identified. These are cross-industrial digital sensing, inside-out digital infrastructure sensing, digital strategy development, determination of enterprise boundaries, decomposition of digital transformation into specified projects and creation of a unified digital infrastructure.

The authors provide direction for managers on how to approach digital transformation. In relation to previous research, the authors provide more specific guidance regarding how to reconfigure the organization in digital transformation.

The paper uses a novel context for digital transformation and complements the very few studies available using dynamic capabilities to understand digital transformation.

This scientific article aims to evaluate the efficacy of the drug Doxorubicin for treating hepatocellular carcinoma (HCC) in Egypt. The study analyzes data from patients referred to a multi-disciplinary consultation at the National Cancer Institute, Cairo University. The study includes 40 intermediate-stage HCC patients who underwent treatment with either Doxorubicin-Lipiodol or Doxorubicin-loaded drug-eluting beads-trans-arterial chemoembolization (DEB-TACE).

Patients referred to a multi-disciplinary consultation at the National Cancer Institute, Cairo University with a possible diagnosis of HCC in the intermediate stage were eligible for the study.

The study finds that the plasma peak concentration of Doxorubicin is significantly higher in patients treated with Lipiodol compared to those treated with DEB-TACE. The median plasma peak concentration of patients treated with Lipiodol was significantly higher 424 (202.5–731) than the peak level of patients treated with beads 84.95 (26.6–156.5) with p-value = 0.036. However, there is no significant difference in other pharmacokinetic parameters between the two treatment groups. The research article also investigates the genetic polymorphisms in HCC patients treated with Doxorubicin-Lipiodol and Doxorubicin-loaded DEB-TACE. It identifies a significant association between the ABCB1 gene (C3435T) and the concentration of Doxorubicin in plasma. Patients with the CCand computed tomography (CT) genotypes of ABCB1 have higher concentrations of Doxorubicin compared to those with the TT genotype. Furthermore, the study examines the progression-free survival rates and tumour response in the two treatment groups. It demonstrates that DEB-TACE patients have a higher progression-free survival rate compared to cTACE patients. DEB-TACE also leads to better tumour regression.

The current study helps to increase the understanding of the genetic factors that may contribute to HCC susceptibility in the Egyptian population. However, it is essential to consider that genetic polymorphism is just one aspect of HCC risk, and other factors such as environment, lifestyle and viral infections also play crucial roles. Further research is needed to elucidate the complex interactions between genetic and environmental factors in HCC development among Egyptians.

The development of e-grocery allows people to purchase food online and benefit from home delivery service. Nevertheless, a high rate of failed deliveries due to the customer’s absence causes significant loss of logistics efficiency, especially for perishable food. The purpose of this paper is to propose an innovative approach to use customer-related data to optimize e-grocery home delivery. The approach estimates the absence probability of a customer by mining electricity consumption data, in order to improve the success rate of delivery and optimize transportation.

The methodological approach consists of two stages: a data mining stage that estimates absence probabilities, and an optimization stage to optimize transportation.

Computational experiments reveal that the proposed approach could reduce the total travel distance by 3-20 percent, and theoretically increase the success rate of first-round delivery approximately by18-26 percent.

The proposed approach combines two attractive research streams on data mining and transportation planning to provide a solution for e-commerce logistics.

This study gives an insight to e-grocery retailers and carriers on how to use customer-related data to improve home delivery effectiveness and efficiency.

The proposed approach can be used to reduce environmental footprint generated by freight distribution in a city, and to improve customers’ experience on online shopping.

Being an experimental study, this work demonstrates the effectiveness of data-driven innovative solutions to e-grocery home delivery problem. The paper also provides a methodological approach to this line of research.

The purpose of this paper is to measure Chinese industries’ eco-efficiency during 2006-2013. The Chinese industry attained rapid achievement in recent decades, but meanwhile, overconsumption of energy and environmental pollution have become serious problems. To solve these problems, many research studies used the data envelopment analysis (DEA) to measure the Chinese industry’s eco-efficiency. However, because the target set by these works is usually the furthest one for a province to be efficient, it may hardly be accepted by any province.

This paper builds a new “closest target method” based on an additive DEA model considering the undesirable outputs. This method is a mixed-integer programming problem which can measure the ecological efficiency of provinces and more importantly guide the province to perform efficiently with minimum effort.

The results show that the eco-efficiency of Chinese provinces increased at the average level, but the deviations remained at a larger value. Compared to the “furthest” target methods, the targets by the approach proposed by this study are more acceptable for a province to improve its performance on both economy and environment counts.

This study is the first attempt to introduce the closest targets concept to measure the eco-efficiency and set the target for each provincial industry in China.