This research investigates how transformational leadership affects the innovative behavior of knowledge-based employees in Chinese high-tech enterprises, highlighting the mediating role of organizational innovation climate. It aims to reveal how leadership shapes innovation-supportive climates to stimulate employee innovative behavior and strengthen organizational sustainable innovation. Using a questionnaire survey of 441 knowledge workers from 10 high-tech firms across four Chinese provinces, this study applies structural equation modeling (SEM) to test both the direct effect of transformational leadership on employee innovative behavior and its indirect effect via organizational innovation climate. The transmission effect of employee innovative behavior on sustainable innovation was also analyzed. Results indicate that transformational leadership significantly promotes employee innovative behavior directly and indirectly through organizational innovation climate. By fostering a supportive climate, leadership enhances employee enthusiasm for innovation, which in turn drives sustainable innovation. These findings provide contextual evidence of leadership’s role in shaping innovative behavior and long-term organizational outcomes in emerging economies. This study builds a cross-level framework of “transformational leadership—organizational innovation climate—employee innovative behavior—organizational sustainable innovation,” integrating four theories. It extends theoretical links between employee behavior and sustainable innovation, emphasizes the overlooked mediating role of organizational climate, and offers practical guidance for knowledge-intensive enterprises seeking to enhance sustainable innovation.

The exchange rate is an essential determinant of exports in any country, and export plays a vital role in driving a country’s economy. Nowadays, the variation of the exchange rate has become a highlighted topic. This paper explores the relationship between the Exchange Rate Volatility and the most exported item of Bangladesh, Knitwear Exports. This study also wants to check the connection between Bangladesh's Exchange Rate and Knitwear Exports. The study is based on secondary data for the period 1994–2022. To achieve the objectives, this study uses Knitwear exports as endogenous variables and the official exchange rate, inflation rate, and exchange rate volatility as the exogenous variables. The data are collected from the World Development Index (WDI) and the Bangladesh Garment Manufacturers and Exporters Association (BGMEA)). To effectively analyze the relationship between variables with potential mixed orders of integration, this study employs the Autoregressive Distributed Lag (ARDL) bound test. The ARDL bound test's ability to accommodate mixed-stationary data without pre-testing and its direct estimation of long-run and short-run effects make it a suitable choice for this analysis. The findings of this paper show that the exchange rate volatility negatively and significantly influences Knitwear exports in the short run with the elasticity 0.119. But in the long term, the result shows a positive but insignificant impact (elasticity: − 0.211). This study also shows that the exchange rate has a significant beneficial linkage with the exports of knitwear products in the long run. This paper recommends that although depreciation of the exchange rate has a beneficial influence on exports, it may prove harmful to other sectors of the economy. And Investment in the knitwear sector can lead to a boom in the economy of Bangladesh.

In recent years, job engagement has received considerable attention among academic community and business professionals. Still such issue needs to be prioritized in the research especially as it is an essential antecedent of organizational performance. This study aims at examining the relationship between transformational leadership style and organizational performance and to explore whether job engagement can influence on this relationship. Study data were collected from the employees working in a mobile phone company in Bangladesh and collected data were analyzed using SPSS version 20. In order to test the study hypotheses Partial Least Squares-Structural Equation Modeling (PLS-SEM) was used. The result of measurement model indicates that the relationship between transformational leadership style and organizational performance is statistically significant. In terms of mediation effects, job engagement mediates the relationship between transformational leadership style and organizational performance.

In the context of diverse financial, environmental, and social issues worldwide, green market orientation (GMO), along with environmental orientation (EO), governmental support (GS), market competition (MC) and perceived organizational support for the environment (POS-E), could be a justified solution by the SME sector, as this sector holds the majority of business fields in most countries. Therefore, this study focuses on the betterment of the financial, environmental, and social performance of SME. This study also tried to advance the SDG goals 8 and 12 through the outcomes. Although this study considers the SMEs perspective of Bangladesh in the light of the Triple Bottom Line (TBL) and Natural Resource-Based View (NRBV) theories, the scenario is almost the same in other developing countries. This study collected data from 221 SMEs through a questionnaire and used a cross-sectional design, and the data were analyzed by SEM-PLS. Findings of the study showed that EO, GS, and POS-E have a significant influence on business performance, which consists of financial, environmental, and social performance. Additionally, GMOs also showed a significant positive mediating influence between EO and BP, GS and BP, and POS-E and BP. However, this study also found the moderating impact of market competition (MC) to be negligible and weakens all hypotheses. In addition to broadening the perspective of TBL and NRBV and enhancing the existing literature, insights from this study will help the SEMs, policymakers, marketing practitioners, government, and supporting organizations to create an appropriate policy and business environment for overall higher business performance.

This paper focuses on how trade openness and foreign direct investment (FDI) affect the adoption of sustainable energy among the countries of the Regional Comprehensive Economic Partnership (RCEP) based on the panel data between 1998 and 2022. The Pesaran (IPS) and Phillips-Perron tests allow to assert the stationarity of data, and the Pedroni cointegration test indicates that there is a long-term correlation between the variables, which proves the theoretical connection between economic factors and renewable energy adoption. The research employs the Pooled Ordinary Least Squares (POLS), Fully Modified Ordinary Least Squares (FMOLS) and Dynamic Ordinary Least Squares (DOLS) to estimate long-run effects and Canonical Cointegration Regression (CCR) to assure robustness. The findings indicate that FDI has a very positive and significant impact on the usage of renewable energy, which indicates that FDI promotes the transition to cleaner energy in RCEP countries. Conversely, trade openness affects the utilization of renewable energy negatively, so that increased trade may be linked to the increased utilization of fossil fuels or the trade-offs related to the environment. The results offer useful policies that would be recommended to the RCEP countries, affirming the need to attract green FDI and use sustainable trade policies and reinforce the financial mechanisms that motivate the use of renewable energy in investments. This study is an addition to the wider debate of sustainable development and energy policy because it provides a great insight of the economic factors related to the use of renewable energy in developing nations.

This study investigates the impact of generative artificial intelligence (GenAI) on learning outcomes (LO) and lifelong skills (LLS) within higher education, emphasizing ethical considerations. Employing a quantitative approach, data was collected from 180 students via a questionnaire, examining their AI usage in education. Structural equation modeling (SEM) using SmartPLS 4.1.0.9 was used to analyze the relationship between GenAI use, LO, and LLS. Findings reveal that GenAI can enhance LO, personalize learning experiences, and contribute to developing crucial LLS. However, the study highlights the importance of ethical guidelines to prevent academic dishonesty. This research contributes to the existing literature by exploring the link between GenAI use, LO, and the development of LLS. Practically, it demonstrates that ethical GenAI use promotes both LO and LLS among higher education students, aligning with the sustainable development goals (SDGs) of inclusive and equitable quality education and lifelong learning opportunities.