Main Al-Dalahmeh

Soil temperature is a critical soil-health indicator that regulates biogeochemical processes, water balance, and carbon cycling under a changing climate. Accurate prediction of soil temperature enhances our ability to manage soil functions, sustain crop production, and mitigate climate-related risks. In this study, along with statistical exploration, we applied three predictive approaches: linear regression, random forest (RF), and a deep neural network (DNN) to predict soil temperature at depths of 5 and 50cm in Central Europe, specifically eastern Hungary. General linear models explained a very high proportion of soil-temperature variability at both depths, with R ² =0.964 for ST5 and R ² =0.913 for ST50. Minimum air temperature was the strongest climatic predictor at both depths, followed by maximum air temperature and solar radiation, whereas wind speed had a significant negative effect and relative humidity was not significant. Season also significantly affected soil temperature during 2017 – 2025, while the Group ×Season interaction was not significant at either depth. Although RF achieved the strongest training fit, DNN showed the most consistent validation and independent test performance. Under temporal testing at 5 cm, DNN achieved R ² = 0.954, RMSE= 1.777 ° C, and MAE= 1.368 ° C. When applied at 50cm, DNN retained good predictive performance, with R ² =0.870, RMSE =2.416 ° C, and MAE= 1.850 ° C. These findings highlight soil temperature as a sensitive indicator of environmental change and demonstrate the value of deep learning for soil-health monitoring. The results provide a methodological and interpretive framework for integrating predictive modelling into sustainable soil and environmental management in climate-vulnerable regions.

The rise of e-commerce necessitates sustainable practices for a greener future. While the e-commerce boom offers immense economic opportunities, minimizing its environmental impact and upholding ethical business conduct are essential. Current research on e-commerce heavily focuses on information technology (IT) for understanding and improving consumer acceptance. However, a critical gap exists in exploring IT's potential contributions to sustainability, crime prevention, and environmental safety. This study bridges this gap by exploring the role of IT integration in managerial practices to enhance environmental protection, crime prevention, and foster sustainability within Bangladesh's booming e-commerce sector. Focusing on e-commerce managers' perspectives, the research examines effective leadership strategies for IT implementation. Additionally, it utilizes the Technology Acceptance Model (TAM) to analyze the relationships between user perception and its impact on e-commerce performance. Using a structured questionnaire, we collected the data from 418 e-commerce managers. The research design incorporates a robust framework, hypothesis formulation, and methodological rigor grounded in TAM principles. The findings reveal a significant positive contribution of IT to environmental protection, crime prevention, and overall sustainability within the e-commerce sector. Managers' perceptions highlight that effective IT utilization ensures environmental safety, safeguards data against criminal activity, and promotes organizational sustainability. Furthermore, this research provides a roadmap for e-commerce businesses to accelerate their sustainability efforts. It also equips academics with valuable insights to advance knowledge on building a secure and sustainable future in the digital age.

Traditional marketing tactics have been significantly challenged by marketers, especially in the food sector. Companies have been engaging in covert and overt advertisements as an emerging marketing communication strategy to circumvent customer skepticism, build a good image, and create value for the brand. But there is a lack of literature regarding integrating traditional and new marketing tactics in building intention and ecologically conscious consumer behavior. Therefore, the purpose of the present study is to provide empirical evidence concerning the integration of different marketing tactics, i.e., Green Product Features, Green Pricing, Covert Advertisement, Overt Advertisement and Guerrilla Marketing, and their effects on Purchase Intention and Ecologically Conscious Consumer Behavior. The study also employs moderation of Brand Evangelism, Environmental Knowledge and Habitat Attitude between intention and behavior building. A visual appraisal technique was used by showing a video or picture as a sample of covert or overt marketing tactics before filling out a close-ended questionnaire to get accurate responses. The data from 568 customers of the frozen food industry were analyzed using the co-variance-based structure equation modeling technique with the help of AMOS. The findings of the study elaborate that parallel to the significant impact of conventional marketing mix tactics, covert, overt and guerrilla marketing are strong antecedents for intention building, which eventually develops Ecologically Conscious Consumer Behavior (ECCB). The results also affirm that intention can lead to ECCB significantly through brand evangelism and environmental knowledge. These findings reflect the importance of shifting marketers from conventional marketing tactics to novel hidden marketing techniques.

Purpose: This paper discusses whether the gender dimension of immigrants influences their entrepreneurial activities in host societies. Human capital theory, social capital theory, and disadvantage theory are used to explore immigrant entrepreneurship and its understanding as a migration research field worthy of more attention.Design/methodology/approach: Based on the systematic analysis of literature and peer-reviewed papers, a comprehensive analytical framework was developed. This framework is provided with an overview to discover the 20 articles written between 2000 and 2021 from different countries are discussed.Findings: It has been found that female immigrant entrepreneurs face many different challenges to sustain their businesses in the host countries, based on their human capital, social-capital, and disadvantage perspectives. Consequently, this research adds to the literature on female immigrants and has practical implications for policymakers and the immigrant community.Social Implications: The implication of this study is that destination countries should do something to improve the human and social capital of female immigrants to decrease the disadvantages they face.Originality/value: In this study, we specifically consider female immigrant enterprises to be as important as male enterprises in the destination countries to support the social and economic integration of migrants. On the other hand, this study also shows the disadvantages female immigrant entrepreneurs face before establishing a business and after starting their entrepreneurial activities.

This study aims to demonstrate how senior leadership applies to high-reliability organizations' functions when managing the Coronavirus pandemic in healthcare organizations and extend the current research by focusing on identifying which functions are more important for the leadership when managing crises in healthcare organizations. To achieve the aim of the study, a qualitative research approach was applied with well-known statistical analyses. Descriptive statistics were applied to determine the characteristics of variables. A correlation matrix shows the relationship between variables, while explanatory factor analyses were employed to determine the reliability of the variables. Ordinary least square regression analysis was used to emphasize the relationship between the role of leadership and different functions in high reliability healthcare organizations in Turkey. It has been found that the role of leadership has a positive and significant relationship with organizational safety, organizational trust, collective mindfulness, flexibility, and communication functions. In addition, the importance of leadership in healthcare organizations will improve many functions in an effective and professional manner, which is reflected in the reduction of the spread of Coronavirus which has been found among workers and in different environments.

The Covid-19 pandemic has caused changes in the social and economic environments for healthcare. Particularly, to avoid spreading the Coronavirus pandemic, release the stress among healthcare workers, and make them work effectively during the epidemic, high-reliability healthcare organizations give great importance to the improvement of their functions. This study aims to show the importance of high-reliability healthcare organizations comparing their effectiveness during a pandemic by applied qualitative research method with many statistical analyses. In order to achieve the aim of the study, a Likert scale survey technique is used to collect the data by using an online survey. 280 healthcare workers filled the survey from January 17, 2021, to February 22, 2021. Based on the outcomes of the analyses, it has been found that such functions as shared knowledge pattern, provision of self-care, awareness of the coronavirus consequences at the workplace of high-reliability healthcare organizations have a positive and significant relationship at p < 0.01 level with taken appropriate measures against coronavirus variable. Self-awareness of organizational role, organizational resources to provide safety, flexibility of work, environmental safety, and collective mindfulness do not have any relationship with the appropriate measures against Covid-19 variable. This outcome indicates that shared knowledge pattern, provision of self-care, and awareness of the coronavirus consequences at the workplace have a more important role in combating Covid-19 in high-reliability healthcare organizations. AcknowledgmentsWe would like to thank all the healthcare workers, who filled the survey of the study. This paper is supported by EFOP-3.6.3-VEKOP-16-2017-00007—“Young researchers for talent”— supporting careers in research activities in higher education program.

The purpose of the study is to show two essential elements of the occupational status of international migrants in OECD countries. The study extends the current research by focusing on how the educational attainment of international migrants and the gender dimension affect migrants’ occupational status. To achieve the aim of the study, a quantitative research approach was followed. Ordinary least square regression analysis was used to emphasize the relationship between educational attainment and gender differences, and occupational status. The databases were taken from the OECD DIOC 2015/2016. It has been found that high-level educational attainment matches with representative vacancies, and female migrants tend to have those occupations more than male migrants in OECD countries. On the other hand, the study’s limitations included a lack of data on testing the exact occupational status of migrants in OECD countries, as well as educational attainment levels that were not specifically divided into each level of education in the databases.