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The development of mathematics allows scientists from related fields to build certain scientific models and conduct research. This is especially true for econometric research involving the processing of large amounts of data. One of the main roles in this case is played by a set of regression analysis methods. Its essence is to determine the influence of some variables on others. Up to this point, the studied topic of the relationship between economic growth and financial development was largely characterized by the construction of regression models, comparing them with each other, and determining the most fair and justified ones. The methods of these studies were different, as well as the results. This is due to the rapid development of this scientific field.

The purpose of this paper is to investigate the effect of inclusive leadership on team climate. Drawing on the social exchange theory (SET), this study proposes a theoretical model in which (1) inclusive leadership enhances team climate, (2) the moderating effect of team power distance and trust in leadership in the relationship between inclusive leadership and team climate.

A quantitative research method was applied, with a survey of 247 Nigerian employees nested in 59 teams in multiple small manufacturing firms across diverse industries widely distributed into textile, furniture, bakery and palm oil production firms. The partial least square structural equation modelling was used to test the study's proposed hypotheses.

The results revealed that inclusive leadership has a positive and direct effect on team climate. Also, this study found that (1) team power distance positively influences the relationship between inclusive leadership and team climate; and (2) trust in leadership positively influences the relationship between inclusive leadership and team climate.

This study affirms the explanatory power of SET to investigate inclusive leadership and team climate at the team level. Also, the study utilised the SET to confirm the significance and value of team power distance and trust in leadership in the relationship between inclusive leadership and team climate at the team level in the Nigerian context.

The paper examined the relationship between inclusive leadership and team climate with team power distance and trust in leadership as moderators. The findings suggest that inclusive leadership play a paramount role in understanding team climate among small manufacturing firms. Moreover, the findings can be applied in organisations by creating different assessment mechanisms, e.g. webinars and training sessions, to encourage effective inclusive leadership behaviours in fostering a team climate for creativity and innovation.

The main contribution of this current research to knowledge is on the examination of the distinctive leadership style that influences team climate. The study indicates that when team members are allowed to fully contribute to the team, inclusion is promoted among group members, and trust in leadership is strengthened, which increases their perception of team climate within organisations.

This paper aims to create and evaluate a model for cryptocurrency adoption by investigating how age, education, and gender impact Behavioural Intention. A hybrid approach that combined partial least squares structural equation modeling (PLS-SEM) and artificial neural network (ANN) was used for the purpose.

This study uses a multi-analytical hybrid approach, combining PLS-SEM and ANN to illustrate the impact of various identified variables on behavioral intention toward using cryptocurrency. Multi-group analysis (MGA) is applied to determine whether different data groups of age, gender and education have significant differences in the parameter estimates that are specific to each group.

The findings indicate that Social Influence (SI) has the greatest impact on Behavioral Intention (BI), which suggests that the viewpoints and recommendations of influential and well-known individuals can serve as a motivating factor to invest in cryptocurrencies. Furthermore, education was found to be a moderating factor in the relationship found between behavioral intention and design.

Prior studies on technology adoption have utilized superficial SEM and ANN methods, whereas a more effective outcome has been suggested by implementing a dual-stage PLS-SEM and ANN approach utilizing a deep neural network architecture. This methodology can enhance the accuracy of nonlinear connections in the model and augment the deep learning capacity.

The research is based on the Unified Theory of Acceptance and Use of Technology (UTAUT2) and expands upon this model by integrating elements of design and trust. This is an important addition, as design can influence individuals' willingness to try new technologies, while trust is a critical factor in determining whether individuals will adopt and use new technology.

Cryptocurrencies are a relatively new phenomenon in India, and their use and adoption have grown significantly in recent years. However, this development has not been without controversy, as the implications of cryptocurrencies for society, the economy and governance remain uncertain. The results reveal that social influence is an important predictor for the adoption of cryptocurrency in India, and this can help financial institutions and regulators in making policy decisions accordingly.

Given the emerging nature of cryptocurrency adoption in India, there is certainly a need for further empirical research in this area. The current study aims to address this research gap and achieve the following objectives: (a) to determine if a dual-stage PLS-SEM and ANN analysis utilizing deep learning techniques can yield more comprehensive research findings than a PLS-SEM approach and (b) to identify variables that can forecast the intention to adopt cryptocurrency.