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Increased usage of technology is linked with poverty reduction, in existing literature but also rising income inequality due to microeconomic factors. This paper attempts to investigate how the technological penetration has impacted poverty levels and income inequality, at the global level and across different levels of income. Using data for 86 countries between 2005 and 2020, the paper employs a robust two step Systematic Generalized Moment Method (Sys-GMM) to assess the linear effect, non-linear effect, and synergy effect models. The results indicate that technological penetration has a different impact across countries, depending on the income levels. The positive association between technology and income inequality has repercussions for low-income countries, in particular. From a policy perspective, it is essential to consider macro- and micro-economic factors that affect the impact of technology penetration in low-income countries.

The purpose of this research is to investigate the associations of internal and external support mechanisms with entrepreneurial success, in the context of China's entrepreneurial sector from network theory perspective. The role of digital technology, as a moderator, has also been analyzed. Data has been obtained from 500 entrepreneurs in Jiangsu, a province in China. All hypotheses were tested using structural equation modeling. It has been found that family support, business partner support, community support and external stakeholder relationships have positive effects on entrepreneurial success. It has also been discovered that digital technology adoption strengthens the positive relationship between business partner support and entrepreneurial success. Theoretical and practical implications have been highlighted and future research suggestions have been provided.

As organizations are benefiting from investments in big data analytics capabilities building and education, our study has analyzed the impact of big data analytics capabilities building and education on business model innovation. It has also assessed technological orientation and employee creativity as mediating and moderating variables. Questionnaire data from 499 managers at enterprises in Jiangsu, China have been analyzed using Structural Equation Modeling (SEM) in SmartPLS. Big data analytics capabilities building and education strengthen technological orientation and increase business model innovation. Technology orientation increases business model innovation and plays a mediating role. Employee creativity also boosts innovation. These findings show that business managers should adopt and promote a technological orientation. They should hire and train employees with big data education and training. Organizations can try to select and support employees who show creativity.