Manufacturing companies in today's industrial world are seeking to use the new manufacturing process methods. The primary goal of corporations is to achieve optimum production while deploying minimal capital. The fundamental purpose of this study is to examine the influence of various lean manufacturing practices on the sustainability performance of companies and the mediating role of green supply chain management (GSCM). The data was gathered using questionnaires from 250 Pakistani manufacturing firms and analyzed using AMOS 25. Results demonstrate that process and equipment, product design, supplier relationships, and customer relationships significantly affect sustainable performance. It is also recognized that Green Supply Chain Management mediates the interaction between HR processes, product design, supplier relationship, customer relationship, and environmental performance. The findings of this study will enable managers and decision-makers of manufacturing companies to increase sustainable efficiency and reduce waste through the use of lean manufacturing and GSCM implementation.

Every emerging technology has its pros and cons; health-conscious users pay more importance to healthy and environment-friendly technologies. Based on the UTAUT2 model, we proposed a comprehensive novel model to study the factors influencing consumers’ decision-making to adopt the technology. Compared to prior studies that focused on linear models to investigate consumers’ technology adoption intentions and use behavior. This study used a Structural Equation Modeling-fuzzy set qualitative comparative analysis (SEM-fsQCA) approach to account for the complexity of customers’ decision-making processes in adopting new technology. We collected valid responses from 830 consumers, analyzed them, and evaluated them using a deep learning SEM-fsQCA technique to capture symmetric and asymmetric relations between variables. We have extensively incorporated a health-consciousness attitude as a predictor and mediator to understand better the decision-making toward technology adoption, specifically 5G technology. All the factors tested in our model are statistically significant except the economic factors. Health-consciousness attitude (HCA) and behavioral intention (BI) found significant predictors and valid mediators in the process of 5G technology adoption.FsQCA provided six configurations to achieve high 5G adoption. The findings have significant practical ramifications for telecom corporations, advertisers, government officials, and key policymakers. Additionally, the study added substantial theoretical literature to technology adoption, particularly the adoption of 5G technology.

It has been a decade since the first extensive study on the internet's adoption and use was conducted. Circumstances have changed in the last decade internet has become an essential need for every human being. Socio-psychological, economic, and personal factors play a significant role in shaping human behaviour. But their role in shaping consumer behaviour toward 5G is still unexplored. In order to determine the impact of socio-psychological elements on 5G technology adoption intention, the study integrated curiosity, perceived value, functional value, and environmental awareness into UTAUT2 and analyzed how they interact. Instead of relying on linear models, this study employed a dual-stage SEM-ANN approach because customers' decision-making process to adopt new technology is complex. Valid responses from 840 respondents were collected, investigated, and ranked using the deep learning ANN approach. All predictors were found statistically significant except social influence. ANN sensitivity analysis revealed that newly integrated predictors (environmental awareness, curiosity) are surprisingly the most important predictors, followed by facilitating conditions and perceived satisfaction. SEM-ANN hybrid two-step deep learning approach explained 83.6% variance higher than the baseline model (UTAUT2). The study improved UTAUT2 by adding new variables and expanding its canvas to predict user technology adoption. This will show how consumers react to 5G services and help telecoms grow into new markets.

During the COVID-19 pandemic, online teaching modes were found vital to continue students’ learning process, but sustainable implementation of online teaching models is an area of concern for policymakers. Psychiatrists are also eager to know students’ behavior toward learning and modes of teaching during COVID-19. We have drawn a model based on the big five personality traits to study students’ satisfaction with online teaching modes and their adoption intentions toward online teaching modes. We have collected data from 718 bachelor’s and master’s level students from four different universities. We have applied the SEM-ANN dual-stage approach to test personality traits’ influence and ranked them based on their normalized importance. The results revealed that agreeableness, conscientiousness, neuroticism, and openness positively influence students’ satisfaction with online teaching models, but that extraversion negatively influences their satisfaction. Agreeableness, extraversion, and neuroticism positively impact, but openness negatively influences. Conscientiousness does not affect adoption intention. Furthermore, agreeableness is the most significant, and conscientiousness is the least important factor for students to adopt online teaching modes. The findings of the study have useful perceptiveness for educational policymakers, academics, and psychiatrists.

Sustainable green economy is the need of time, and eco-friendly products can play a decisive role in this goal. Low consumption of eco-friendly products is a serious concern of researchers and policymakers. To address this issue, we have studied the phenomenon in a developing country and provided insights to researchers and policymakers about the factors that influence the consumers’ behaviour in developing behaviour. We have designed an integrated model based on UTAUT to study the developing countries’ behavioural intentions towards eco-friendly products. 805 useable sample is obtained to analyze by implying SEM-ANN dual-stage hybrid model. Results revealed that environmental knowledge is a significant predictor and a moderator, but consumers are less educated about ecological issues in developing countries. Results also revealed that male and female consumers’ preferences are differently influenced by factors studied to measure adoption intentions of eco-friendly products. Sensitivity analysis results revealed that social influence followed by effort expectance and perceived expectancy of eco-friendly products are more important for developing countries’ customers. The study also provides empirical evidence of methodological advancement using SEM-ANN and suggests a dual-stage hybrid model in studies involving human behaviour.