Purpose: This study investigates the mediating effect of Environmental Attachment (EA) among consumers in an emerging market, concentrating on the impact of two key factors: Green Environmental Awareness (GEA) and Sense of Responsibility (SOR) on Sustainable Product Consumption (SPC). Design/methodology/approach: A thorough online survey was carried out with Google Docs and distributed to 304 Pakistani consumers who now use or are considering purchasing sustainable or green products. Structural Equation Modeling (SEM) was used to rigorously test the suggested model utilizing a non-probability sampling technique, specifically the stratified purposive sampling approach. Findings: Green environmental awareness (GEA) and a sense of responsibility (SOR) have been shown to have a substantial impact on creating environmental attachment (EA) in both existing and potential customers of sustainable products. The findings of this study also revealed that environmental attachment (EA) plays an important role as a mediator in the links between green environmental awareness (GEA) and the consumption of sustainable goods (SPC), as well as between a sense of responsibility (SOR) and SPC. Despite this, it is crucial to note that the projected direct effect of GEA on SPC was shown to be statistically insignificant. This conclusion implies that additional factors outside the scope of this study may influence the relationship between GEA and SPC. Research limitations/implications: It is vital to highlight that the focus of this study is on an online sample of consumers near Punjab, Pakistan. Future studies should look at other parts of Pakistan to acquire a more complete picture of sustainable consumption trends. Furthermore, our findings suggest that characteristics impacting sustainable consumption, such as Green Environmental Awareness (GEA) and Sense of Responsibility (SOR), may differ among countries. As a result, performing a comparison analysis involving two or more countries could provide valuable insights into projecting sustainable product consumption among current and potential sustainable product customers. Originality/Value: This study contributes to the literature by investigating the factors of sustainable consumption using the lens of the Norm Activation Model theory (NAM), notably Green Environmental Awareness (GEA) and Sense of Responsibility (SOR), to predict sustainable product consumption. The findings are important for promoting long-term goals in Pakistan and provide a framework that can be applied in other emerging markets.

The paper considers an important problem of the successful development of social qualities in an individual using machine learning methods. Social qualities play an important role in forming personal and professional lives, and their development is becoming relevant in modern society. The paper presents an overview of modern research in social psychology and machine learning; besides, it describes the data analysis method to identify factors influencing success in the development of social qualities. By analyzing large amounts of data collected from various sources, the authors of the paper use machine learning algorithms, such as Kohonen maps, decision tree and neural networks, to identify relationships between different variables, including education, environment, personal characteristics, and the development of social skills. Experiments were conducted to analyze the considered datasets, which included the introduction of methods to find dependencies between the input and output parameters. Machine learning introduction to find factors influencing the development of individual social qualities has varying dependence accuracy. The study results could be useful for both practical purposes and further scientific research in social psychology and machine learning. The paper represents an important contribution to understanding the factors that contribute to the successful development of individual social skills and could be useful in the development of programs and interventions in this area. The main objective of the research was to study the functionalities of the machine learning algorithms and various models to predict the students’s success in learning.

The study, focusing on Malaysian managers, employs a two-round Delphi research methodology to identify and rank variables influencing their emotional intelligence at work. The research is structured into five key areas, with factors ranked in ascending order of significance. Empathy and emotional resilience are deemed the most important, followed by emotional and self-awareness, work-life balance and stress management, social awareness and relationship management, learning and development, adaptability and continuous improvement, cultural and organizational dynamics, experience, and age. This study sheds light on the variables impacting Malaysian managers’ emotional intelligence skills and provides a ranking of key factors essential for successful development. It not only offers crucial guidance for personal and professional balance but also provides insightful recommendations for understanding and enhancing emotional intelligence skills in the workplace for Malaysian managers and organizations.

This study examines factors associated with an increasingly poor perception of the novel coronavirus in Africa using a designed electronic questionnaire to collect perception-based information from participants across Africa from twenty-one African countries (and from all five regions of Africa) between 1 and 25 February 2022. The study received 66.7% of responses from West Africa, 12.7% from Central Africa, 4.6% from Southern Africa, 15% from East Africa, and 1% from North Africa. The majority of the participants are Nigerians (56%), 14.1% are Cameroonians, 8.7% are Ghanaians, 9.3% are Kenyans, 2% are South Africans, 2.1% are DR-Congolese, 1.6% are Tanzanians, 1.2% are Rwandans, 0.4% are Burundians, and others are Botswana’s, Chadians, Comoros, Congolese, Gambians, Malawians, South Sudanese, Sierra Leoneans, Ugandans, Zambians, and Zimbabweans. All responses were coded on a five-point Likert scale. The study adopts descriptive statistics, principal component analysis, and binary logistic regression analysis for the data analysis. The descriptive analysis of the study shows that the level of ignorance or poor “perception” of COVID-19 in Africa is very high (87% of individuals sampled). It leads to skepticism towards complying with preventive measures as advised by the WHO and directed by the national government across Africa. We adopted logistic regression analysis to identify the factors associated with a poor perception of the virus in Africa. The study finds that religion (belief or faith) and media misinformation are the two leading significant causes of ignorance or poor “perception” of COVID-19 in Africa, with log odd of 0.4775 (resulting in 1.6120 odd ratios) and 1.3155 (resulting in 3.7265 odd ratios), respectively. The study concludes that if the poor attitude or perception towards complying with the preventive measures continues, COVID-19 cases in Africa may increase beyond the current spread.