Around the world, people are becoming more and more worried about how globalization will affect their standard of living. According to the literature, globalization has resulted in the marginalization of the impoverished populations in developing economies and has exacerbated inequality, while the opposite may also be true. The objective of this study is to investigate the impact of globalization on income inequality. The study used two-stage least squares (2SLS) to study the influence of globalization on income inequality in 18 developing countries from 1991–2021. Utilizing the KOF index of globalization, it is determined that globalization, together with its three aspects, has a negative effect on income inequality among developing economies. Evidence demonstrates that the combination of trade openness and foreign direct investment (FDI) plays a significant role in reducing inequality among developing economies. We recommend developing economies actively support globalization in terms of trade and FDI in accordance with the findings. By expanding trade opportunities and opening up markets, globalization can benefit developing nations. This may result in a rise in FDI, the creation of jobs, and technological developments. Governments can contribute to raising the living standards of their inhabitants, lowering rates of poverty, and closing the income gap by promoting globalization. Although the study emphasizes the well-established link between globalization and income inequality, it focuses on the effects of various globalization dimensions, emphasizing the need to comprehend how different dimensions of globalization, namely economic, political, and social globalization affects inequality in developing economies.

The potential of big data analytics (BDA) in enabling improvements in business processes has urged researchers and practitioners to understand whether and under what combination of conditions, such novel technologies can support innovation, competitive advantage, and firm performance. Although the extent of research in this area is substantial, research on the influence of the BDA components such as effective use of big data analytics tools and big data management on innovation process (IP), competitive advantage (CA), and financial performance (FP) must be conducted. This research examines the impact of effective use of BDA tools and big data management on the innovation process, competitive advantage and financial performance based on the resource-based view (RBV). Based on this conceptualisation, the current study examines the relationship between the BDA components (effective use of BDA tools and big data management) on the innovation process, competitive advantage, and financial performance. A questionnaire was designed to measure the influence of the effective use of big data analytics tools and big data management on the innovation process and its drivers on competitive advantage and financial performance. Quantitative data collected using an online survey method, and (n= 174) samples were gathered from top managers working in firms operating in the United Kingdom and the United States of America. The hypotheses and model fitness were tested in SPSS, AMOS v.26 using structural equation modelling (SEM). The findings indicate that applying the significant data analytics components (effective use of BDA tools and big data management) has a significant positive impact on the innovation process capabilities (β = .317, p = 0.000 and β = .490, p = 0.000), competitive advantage (β = .322, p = 0.000 and β = .298, p = 0.000), and financial performance (β = .188, p = 0.000 and β = .444 and p = 0.000). There is also a significant positive impact of the innovation process on competitive advantage (β = .485, p = 0.000), and the competitive advantage led to a financial performance (β = .397, p = 0.000). Statistical findings also show that the innovation process as mediator has a significant positive impact on financial performance (β = .333, p = 0.000). Surprisingly, firm mediators such as age (β = -.002 and p = 0.000), size (β = -.003 with p = 0.000), type of industry (β = -.008 with p = 0.000), and environment turbulence (β = -.001 with p = 0.000), were found not to positively impact a firm’s financial performance.This work provides an original contribution to knowledge by extending and validating a new model and the factors affecting the innovation process, competitive advantage, and financial performance.