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Small and Medium-sized Enterprises (SMEs) are regarded as the backbone of the growth of the world economy. They had recently experienced rapid growth and improved their business activities in terms of customer numbers and revenue expansion when they began using e-commerce in their business. Although there is a growing interest in e-commerce, its use is still insufficient in Algeria. SMEs show a little acceptance of e-commerce in their business processes. Consequently, e-commerce has not yet found its place in Algeria, since it has not achieved the desired start as an approved means of trade. The main objective of this study is to identify the direct, indirect and mediating factors that have prevented SMEs from adopting e-commerce in Algeria and develop a model to be adopted. To obtain a clear vision on the subject of adopting e-commerce in Algeria, a preliminary study was established with semi-structured interviews that were conducted with 7 SME managers. Then, the conceptual model was developed through the models and theories which are among the most frequently applied theoretical models on the adoption of e-commerce in developing countries. These models are Unified Theory of Acceptance and Use of Technology (UTAUT), Technology Organisation Environment (TOE), and Perceived eReadiness Model (PERM) as well as from the results of the preliminary study. This research uses the quantitative research method, where a survey responded by 315 SMEs in Algeria. The research hypotheses were examined, and the proposed research model was validated through Structural Equation Modelling (SEM) using AMOS software. The main findings of the present study comprise some key factors that have a significant effect on e-commerce adoption which are competitive pressure, delivery systems, necessary guidance and assistance, buying habits, enterprise financial resource, human resources, and trust in the state system and IT skills. The significant effects were mediated by three variables which are awareness, fear of risk in e-commerce, and the intention to adopt e-commerce. At the same time, there are three non-significant factors which are government e-readiness, bank e-readiness and technology resources. Besides, the measures of goodness-of-fit indices GOFI indicate that the conceptual model revised is a fit model for e-commerce adoption by SMEs in Algeria. This model would be provided useful information for SMEs, policymakers, and academics.

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The fourth pillar of the United Nations Sustainable Development Goals is 'Quality education' to provide peace and prosperity to the world population; in addition, Special Education Reforms under the Malaysian government scope are influenced by the 'Shared Prosperity Vision 2030'. Special needs education underlines the importance of technological integration in the learning environment to support communication, teaching, and learning needs. Technological advancements assist educators in transforming the educational needs of neurodiverse learners at all academic levels. The early intervention-based teaching and learning process is advocated worldwide, as it has shown positive cues toward neurodiverse learners, especially those with Autism Spectrum Disorder (ASD). However, very little is known about the perception and behavior of teachers toward acceptance of technology-based intervention. Therefore, to bridge the identified gap in academic literature, this study explores the teachers' behavioral intentions concerning the use of technology for teaching children with ASD. A conceptual framework has been developed based on the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) model and other recent studies to address the problem. In this study, constructs such as Performance Expectancy (PE), Personal Innovation (PI), Effort Expectancy (EE), Habit (H), Social Influence (SI), Time (T), Access to Technology (ATT), Voluntariness (V), Self-Efficacy (SE), Facilitating Conditions (FC), Job Relevance (JR), Hedonic Motivation (HM), Risk (RK), and Trust (TR) are measured. The researcher later tested the hypotheses through a survey-based self-administered questionnaire among special education teachers in different parts of Malaysia. This study's theoretical model was evaluated using two different techniques. The first used the PLS-SEM and the Smart-Partial Least Squares software tool. Structural equation modeling was used to evaluate hypothetical relationships. In the second technique, validating hypotheses, assessing their methodology, and gauging their prediction capacity are all tasks that benefit greatly from the application of Machine Learning. In order to look into the correlational routes between constructs, a quantitative research approach of cross-sectional survey method was adopted. A total of 386 replies were compiled using a cluster sampling strategy. 12 out of 17 hypotheses were determined to be statistically significant, and five were found to be insignificant, according to research findings. The findings showed that the following variables had a significant impact on teachers' behavioral intention (BI) to adopt technology for teaching children with ASD and their use behavior (UB): PE, EE, H, ATT, SE, FC, JR, HM, RK, and TR. Whereas BI, H, and FC explain use behavior. The study's findings demonstrated that the suggested model matched the data correctly. Additionally, this study predicts and validates the UTAUT2 model in the context of technology adoption among the teachers of children with ASD, expanding the applicability of the UTAUT2 in IS research. The ML generic algorithms predicted the conceptual model with the best results for the Random Forest algorithm, R2 value for the training (0.993) and testing (0.971) with a minimum error of RMSE = 0.1729 and MAE = 0.1239, in comparison to the predictive power of TAM (R² = 0.67) and UTAUT (R² = 0.73). Finally, this research added to the understanding of technology acceptance among teachers responsible for teaching children with ASD. The study's identification of crucial elements would influence stakeholders, school administrators, and policy and lawmakers to design and implement an inclusive special needs education system and use technology effectively to teach children with ASD, particularly in Malaysia.

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