This study aims to examine how female CEOs influence green innovation and whether firm size moderates this connection. Our paper focuses on CEOs, who are considered the strategic leaders of corporations, because of their crucial role in making important decisions. This research paper examines how female CEOs influence green innovation (GI) in the Asian industrial sector. The primary goal is to address these research questions: Do Asian industrial firms with female and male CEOs differ in their GI efforts? Is there a positive moderating influence of Asian industrial enterprises’ size on the nexus between women in CEO positions and eco-innovation? Based on our research questions, firm size is likely a determining factor in the GI of female CEOs. This research employs rigorous econometric modeling to analyze a substantial dataset of listed Asian industrial companies from 2013 to 2022. We have found a significant positive correlation between female CEOs and GI in Asian industrial firms. It has been proven that female CEOs in the industrial sector are more inclined to promote environmentally friendly practices. Furthermore, the size of an industrial firm amplifies the beneficial influence of a female CEO on the firm’s chances of engaging in GI initiatives. Regarding the moderating effect of size, the size of companies significantly magnifies the impact of female CEOs on GI. The effectiveness of female CEOs on environmentally friendly practices is more prominent in large corporations than in smaller ones. Our outcomes remain robust with respect to endogeneity issues using two-step GMM estimators. This study proposes that stakeholders, particularly in Asian countries, should promote the increased representation of females in CEO roles, particularly within large corporations. This is because women-led companies demonstrate superior performance in GI endeavors. Hence, regulators must establish policies that facilitate the participation of women in CEO positions within large-scale enterprises. These policies may strengthen the private sector’s capacity to foster sustainable innovation.

The study aims to examine the intricate interplay between sales growth, profitability, and tax avoidance strategies adopted by firms. Through an analysis of a diverse dataset spanning multiple industries and regions, this study investigates how sales growth influences a firm’s marketing approach to tax avoidance and its subsequent impact on profitability. The sample is Jordanian industrial firms listed on the Amman Stock Exchange for the study period between 2010 and 2020. Four critical variables used in the dataset are tax avoidance, return on assets, sales, and size. It employs a mixed-methods approach, including quantitative regression analysis and qualitative assessments of corporate tax strategies. The study results reveal a strong negative relationship between ROA and tax avoidance; for every unit increase in ROA, tax avoidance decreases by 0.198 units. Sales, however, do not exhibit a statistically significant association with tax avoidance. Firm size is an additional predictor with a marginally significant direct link with tax avoidance (β = 0.042, p = 0.049). This study highlights the central role of profitability in shaping tax avoidance strategies, with larger firms marginally more inclined toward tax planning.

Digital transformation refers to strategic activities undertaken by organizations to improve and simplify their process and even alter their business models with abreast to enhance firm performance. Thus, the aim of this study was to analyze the impact of digital transformation on organizational performance among the Jordanian commercial banks listed on the Amman Stock Exchange. The descriptive research design was used in this quantitative study. Primary data were collected to achieve the objectives of the study. The target population was employees (managers and non-managers) of Jordanian commercial banks listed on the Amman Stock Exchange. The sample size was selected using Krejcie and Morgan rule; after data cleaning procedures, the final sample of 282 respondents was used for final analysis. The study employed regression analysis to arrive at the results. The results confirm that digital transformation has a significant positive effect on customer experience and IT innovation. These results were significant at a 1% level. The results also confirm that digital transformation has a significant positive effect on firm performance, with a significance level of 1%. Moreover, the significant positive impact of customer experience and IT innovation was confirmed. Therefore, the significant positive impact of digital transformation on firm performance was found viz-a-viz direct as well as indirect route.

Liquidity is a firm’s ability to pay its current obligations as they come due and thus remain in business in the short run, which reflects the ease with which assets can be converted to cash. The objective of working capital management (WCM) is to minimize the cost of maintaining liquidity while guarding against the risk of insolvency, working capital policy applies to short-term decisions, and capital structure finance applies to long-term decisions.Several studies have been conducted on the impact of WCM on cash holding levels. The impact of WCM on liquidity and cash holding levels is analyzed in this study. The study also makes a comparison between large- and small-scale firms. Panel data for 62 Jordanian industrial firms covering an eleven-year period (2006–2016) have been analyzed. The descriptive analysis indicates that large firms hold more cash than small firms, as well as more debt, cash flow and growth.The findings of the data set indicate that WCM, as a variable (working capital net of cash), is a strong predictor of firm cash holding levels. When a firm has several cash substitutes, it will maintain low cash levels. The separate analysis shows that there are significant differences between small- and large-scale firms for determinates related to cash holding levels. Firm size and cash flow ratios were strong predictors of cash holding levels for both samples.