This study investigates the variables affecting the adoption of blockchain technology (BT) among small and medium-sized enterprises (SMEs) with the application of artificial intelligence (AI) via the mediating lens of risk-taking behavior. As an initial sample, 150 owners/top managers from 150 SMEs (one informant from each) in Dhaka, Bangladesh, were chosen. A stratified random sample was employed for this cross-sectional study. Applying structural equation modeling, the combined influence of internal and external variables influencing the intention to adopt BT is explored. Results show that: (1) knowledge of artificial intelligence has a positive and significant effect on the adoption of blockchain technology; (2) the relevant advantage of artificial intelligence has a positive and significant effect on the adoption of blockchain technology; (3) perceived ease of use of artificial intelligence has a positive and significant effect on the adoption of blockchain technology; (4) risk-taking behavior mediates the relationship between knowledge of artificial intelligence and adoption of blockchain technology; (5) risk-taking behavior does not mediate the relationship between relevant advantage and perceived ease of use of artificial intelligence with the adoption of blockchain technology. The current study is one of the few empirical investigations relating to SMEs using artificial intelligence and blockchain technologies for business operations. The study’s limitations are the small sample size and use of a single informant. However, the findings on the adoption of blockchain technology have applications for boosting the competitiveness of SMEs. This study’s originality stems from two factors: the novelty of blockchain technology and its potential to upend SMEs’ conventional mode of operation. It highlights the need to consider the key variables affecting SMEs’ adoption of blockchain technology with artificial intelligence.

Blockchain technology has been heralded as a game changer for addressing severe environmental and economic sustainability challenges. In response to rising environmental concerns, blockchain technology (BCT) is transforming green innovation, culminating in green economic practices and well-established business models. Recognizing this, we investigated the role of blockchain technology in green innovation practices and its impact on green economic sustainability, which has an impact on green environmental sustainability. Moreover, 184 small- and medium-sized enterprises (SMEs) were surveyed in Lima, Peru. Data for this cross-sectional study were gathered using stratified random sampling. The positivist approach was implemented using a statistical induction method. Prior studies’ research constructs were measured using validated measurement scales. For quantitative data analysis, using the partial least squares structural equation modeling (PLS-SEM) framework, this study provided two key findings. First, sustainability orientation and sustainability attitude have a positive and significant effect on the adoption of green innovation that employs green energy (solar) technology towards a sustainable green economy. Second, the intention to use blockchain technology mediates the relationship between sustainability orientation and social perception with the adoption of green innovation that employs green energy (solar) technology towards a sustainable green economy. We recommend that small- and medium-sized enterprises embrace green innovation and blockchain technology to protect the environment and boost community cohesiveness.

The purpose of the study is to examine how cybersecurity knowledge, password security, and self-perception of skill affect cybersecurity awareness issues via the mediating lens of cybersecurity attitude among university students in Bangladesh. A sample of 430 university students from two public and three private universities provided the data in Dhaka, Bangladesh. An approach known as stratified random sampling was used in this cross-sectional study. The positivist approach was used, and a hypothetical statistical induction technique was used. The research constructs, which were adopted from earlier studies, were measured using scales that had undergone validation. Smart PLS-SEM 3.3.9 was used to quantitatively analyze the data. The results indicated a positive and significant association between cybersecurity knowledge and password security with cybersecurity awareness. No conventional association was found between self-perception of skills and cybersecurity awareness. Moreover, the data analysis confirmed that cybersecurity attitudemediates the relationship between cybersecurity knowledge, password security and self-perception of skills with cybersecurity awareness. This study implies that more effort needs to be put into informing the general people likely students about cybersecurity and ethical internet use. Furthermore, the main contribution of this study is to emphasize the need of raising cybersecurity awareness among students.