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The role of green and sustainable finance is crucial as the global economy, marked by increasing energy demands and environmental concerns, the need for creative solutions to meet humans need and create a better future for all, transitions towards a low-carbon, sustainable, and resilient future. This study examines the impact of green finance on the economic prosperity of the Sahel from 2001 – 2022. Descriptive statistics, boxplots, cointegration tests, and Vector Error Correction Model (VECM) analysis, were utilized to explore the interplay between the variables with the aid of EViews software. The results reveal the growth patterns of GDP, EGLC, POP, INFL, CO2 and FDI, and their significance in driving economic expansion in the Sahel. This study concludes with actionable insights and recommendations for Sahel policymakers to address energy poverty, energy transition, demographic trends, climate change, investments, financing, institutional quality, and other economic issues.

Rapid technological development has led to an information explosion in the current Web environment. Recently, tourists have become reliant on the Internet as a tool to obtain information about the places they intend to visit. However, due to the overload of information, tourists face many challenges and difficulties in making the right choice. Despite the promise of Web 3.0’s revolutionary solutions to address all of Web 2.0’s shortcomings, there is still a significant gap between currently implemented systems and the useful innovation of future technologies in the tourism industry. This study proposes a theoretical model to examine the role of personal innovativeness in tourists’ intention to use Web 3.0 based on the DeLone and McLean model. Although many attempts were made in prior work to address this issue, most of those studies focused on the evolution of Web 3.0 from the technical side and did not investigate it from the theoretical perspective in different domains in general and tourism in particular. The method of this study was based on a survey questionnaire with 643 participants. SmartPLS version 3.3.3 was used to analyze the study data. The results of this study reveal that information quality, system quality, service quality, social influence, and personal innovativeness had significant effects on tourists’ intention to use Web 3.0, while awareness did not have a significant effect. This study provides further insights, expands our understanding of the study topic, and contributes to this growing research area, and the novel research framework can act as a fundamental theoretical model for future studies in different contexts.

This paper evaluates the current state of the literature concerning the effects of exchange rate movements on trade balance. Thus, this paper is a review article and provides a survey of the alternative theories that focus on the effect of exchange rate changes on the trade balance. It systemizes the literature into four distinct reviews and approaches following the chronological order. The paper presents the (a) Standard Theory of International Trade, (b) Elasticity Approach, (c) Keynesian Absorption Approach, and (d) Monetary Approach. The study shows that higher attention should be given for the most plausible dynamic theory in this field, known as the J-Curve.

The quality of trade data is essential for any empirical study that uses them to construct a variable representing trade. However, previous studies have largely ignored the issue of trade data discrepancy. This discrepancy occurs when a country's claim on sectoral bilateral trade is different from the value reported by its trade partner. Using a size ratio and correlation coefficient computed from the values reported by both parties of bilateral trades, this study examines trade data discrepancy in 20 trade sectors from 1987 to 2016 between Malaysia and its three major Asian trade partners, i.e. China, Singapore and Japan. We detect alarming discrepancy in Malaysia's trade data. We also find that this discrepancy depends on the trade partner, time and trade sector. This study calls for attention of Malaysian policymakers regarding the possibility of customs mismanagement. We recommend that future empirical studies utilising trade in the analysis to either reconcile the data or to deploy both data sources in the econometric analysis as a robustness check.

Digital transformation is reshaping agricultural governance of local governments, yet micro-pathways through which policy instruments influence consumer behavior via market mechanisms remain unclear. This study examines the fresh corn industry in Beijing and surrounding areas to explore how local governments employ policy-driven digital marketing strategies to promote agricultural modernization and shape consumer behavior. The research constructs an analytical framework integrating policy instrument theory, multi-level governance, and consumer behavior models. Through surveying 380 consumers, Partial Least Squares Structural Equation Modeling (PLS-SEM) examined policy implementation mechanisms. Findings reveal that policy-supported digital infrastructure (β=0.328, p<0.001) and government-led platform engagement (β=0.296, p<0.001) significantly enhance public service satisfaction, which demonstrates the strongest effect on market participation behavior (β=0.512, p<0.001). Mediation tests indicate indirect effects of policy instruments through satisfaction (0.168 and 0.152) exceed direct effects (0.126 and 0.108), with public service satisfaction playing a crucial mediating role, explaining 52.3% of satisfaction variance and 58.2% of market behavior variance. Regional analysis reveals a 35% gap in policy implementation intensity between urban and rural areas, though 56.3% of consumers frequently use digital channels, indicating positive transformation progress. The study unveils governance innovation pathways of local governments transitioning from direct market intervention to platform empowerment and from technology promotion to service optimization, providing theoretical perspectives for understanding local agricultural governance in the digital era and offering transferable strategies for agricultural digital transformation in other regions. 

Digital transformation is reshaping agricultural governance of local governments, yet micro-pathways through which policy instruments influence consumer behavior via market mechanisms remain unclear. This study examines the fresh corn industry in Beijing and surrounding areas to explore how local governments employ policy-driven digital marketing strategies to promote agricultural modernization and shape consumer behavior. The research constructs an analytical framework integrating policy instrument theory, multi-level governance, and consumer behavior models. Through surveying 380 consumers, Partial Least Squares Structural Equation Modeling (PLS-SEM) examined policy implementation mechanisms. Findings reveal that policy-supported digital infrastructure (β=0.328, p<0.001) and government-led platform engagement (β=0.296, p<0.001) significantly enhance public service satisfaction, which demonstrates the strongest effect on market participation behavior (β=0.512, p<0.001). Mediation tests indicate indirect effects of policy instruments through satisfaction (0.168 and 0.152) exceed direct effects (0.126 and 0.108), with public service satisfaction playing a crucial mediating role, explaining 52.3% of satisfaction variance and 58.2% of market behavior variance. Regional analysis reveals a 35% gap in policy implementation intensity between urban and rural areas, though 56.3% of consumers frequently use digital channels, indicating positive transformation progress. The study unveils governance innovation pathways of local governments transitioning from direct market intervention to platform empowerment and from technology promotion to service optimization, providing theoretical perspectives for understanding local agricultural governance in the digital era and offering transferable strategies for agricultural digital transformation in other regions. 

In the context of agricultural digital transformation, how local government digitalization policies influence enterprise technological innovation has become a critical theoretical and practical issue. This study constructs a multi-level moderated mediation model based on the Technology-Organization-Environment (TOE) framework and Innovation Diffusion Theory to explore how local government digitalization policies affect enterprise AI marketing strategy adoption and market performance in China's fresh corn industry. Using survey data from 128 fresh corn enterprises across 15 provinces and 3,842 consumer questionnaires, we employ Partial Least Squares Structural Equation Modeling (PLS-SEM) for empirical analysis. The findings reveal that: (1) local government digitalization policies significantly promote enterprise AI marketing adoption (β=0.21, p<0.01), which positively impacts market performance (β=0.34, p<0.001), with the model explaining 58.7% of variance (R²=0.587); (2) policy environment characteristics significantly moderate the policy-enterprise relationship, with effects in high-support environments (0.43) being 2.5 times those in low-support environments (0.17); (3) industry competition intensity strengthens the AI adoption-performance relationship (β=0.21, p<0.01); (4) organizational learning capability (indirect effect=0.126) and customer satisfaction (indirect effect=0.187) play partial mediating roles; (5) regional heterogeneity analysis shows policy effects in eastern regions (β=0.38) significantly exceed western regions (β=0.19).This study extends digital governance theory applications in agriculture and provides empirical evidence for local governments to formulate differentiated digital agriculture support policies and for enterprise technological innovation decision-making.

In the context of agricultural digital transformation, how local government digitalization policies influence enterprise technological innovation has become a critical theoretical and practical issue. This study constructs a multi-level moderated mediation model based on the Technology-Organization-Environment (TOE) framework and Innovation Diffusion Theory to explore how local government digitalization policies affect enterprise AI marketing strategy adoption and market performance in China's fresh corn industry. Using survey data from 128 fresh corn enterprises across 15 provinces and 3,842 consumer questionnaires, we employ Partial Least Squares Structural Equation Modeling (PLS-SEM) for empirical analysis.The findings reveal that: (1) local government digitalization policies significantly promote enterprise AI marketing adoption (β=0.21, p<0.01), which positively impacts market performance (β=0.34, p<0.001), with the model explaining 58.7% of variance (R²=0.587); (2) policy environment characteristics significantly moderate the policy-enterprise relationship, with effects in high-support environments (0.43) being 2.5 times those in low-support environments (0.17); (3) industry competition intensity strengthens the AI adoption-performance relationship (β=0.21, p<0.01); (4) organizational learning capability (indirect effect=0.126) and customer satisfaction (indirect effect=0.187) play partial mediating roles; (5) regional heterogeneity analysis shows policy effects in eastern regions (β=0.38) significantly exceed western regions (β=0.19).This study extends digital governance theory applications in agriculture and provides empirical evidence for local governments to formulate differentiated digital agriculture support policies and for enterprise technological innovation decision-making.

Purpose: This study delves into the intricacies of performance   management   system design and implementation within chinese organizations, drawing   parallels with the challenges faced   by the various other countries commerce and sectoral Associations (AACCSA).   Theoretical reference: As china emerges as a global economic powerhouse, its diverse business landscape, influenced   by cultural, economic, and regulatory factors, presents unique challenges and opportunities in optimizing organizational efficiency through effective performance management.   Method: The research employs a mixed- method approach, combining qualitative and quantitative data from chinese   organizations   to explore practices, challenges, and attitudes towards performance management.   Result and conclusion:    The discussion   interprets   finding, highlighting   strengths and areas for improvement   within   AACCSA’s   performance   management.   Implication: The study reveals a balances gender distribution and a mature workforce within AACCSA, coupled with a highly educated and experienced   employee base.