The use of artificial intelligence (AI) in the detection and diagnosis of plant diseases has gained significant interest in modern agriculture. The appeal of AI arises from its ability to rapidly and precisely analyze extensive and complex information, allowing farmers and agricultural experts to quickly identify plant diseases. The use of artificial intelligence (AI) in the detection and diagnosis of plant diseases has gained significant attention in the world of agriculture and agronomy. By harnessing the power of AI to identify and diagnose plant diseases, it is expected that farmers and agricultural experts will have improved capabilities to tackle the challenges posed by these diseases. This will lead to increased effectiveness and efficiency, ultimately resulting in higher agricultural productivity and reduced losses caused by plant diseases. The use of artificial intelligence (AI) in the detection and diagnosis of plant diseases has resulted in significant benefits in the field of agriculture. By using AI technology, farmers and agricultural professionals can quickly and accurately identify illnesses affecting their crops. This allows for the prompt adoption of appropriate preventative and corrective actions, therefore reducing losses caused by plant diseases.

This study examines the interaction between foreign direct investment (FDI), idiosyncratic risk, sectoral GDP, economic activity, and economic growth in ASEAN countries using structural equation modeling (SEM) performed using AMOS software. The analysis uses data from the ASEAN Statistics Database 2023 to distinguish the significant direct and indirect impacts of FDI on idiosyncratic risks, sectoral GDP, economic activity and aggregate economic growth can. ASEAN, which includes ten Southeast Asian countries, has experienced rapid economic growth and increasing integration in recent decades, making it an interesting area to study these relationships. The study covers a comprehensive period to capture trends and differences among ASEAN member states. Applying SEM with AMOS allows a detailed examination of complex relationships between important economic variables. The results show a clear link between FDI inflows, idiosyncratic risks, industry GDP performance, economic activity, and overall economic growth. More specifically, FDI inflows have a notable direct influence on idiosyncratic risks, which then impact GDP growth by sector, and the level of economic activity and ultimately contribute to economic growth trends. economy more broadly in ASEAN countries. These findings highlight the importance of understanding and effectively managing the dynamics between FDI and various economic indicators to promote sustainable economic development across ASEAN. This information can inform policymakers, investors, and stakeholders in developing targeted strategies and policies that maximize the benefits of FDI while minimizing related risks to promote strong and inclusive economic growth in the region. This study highlights the multifaceted relationships in the ASEAN economic context, emphasizing the need for strategic interventions and policy frameworks to exploit the potential of foreign investment directed at ASEAN, to the Sustainable Development Goals and long-term economic prosperity in the region.

Purpose: This study investigates the mediating effect of Environmental Attachment (EA) among consumers in an emerging market, concentrating on the impact of two key factors: Green Environmental Awareness (GEA) and Sense of Responsibility (SOR) on Sustainable Product Consumption (SPC). Design/methodology/approach: A thorough online survey was carried out with Google Docs and distributed to 304 Pakistani consumers who now use or are considering purchasing sustainable or green products. Structural Equation Modeling (SEM) was used to rigorously test the suggested model utilizing a non-probability sampling technique, specifically the stratified purposive sampling approach. Findings: Green environmental awareness (GEA) and a sense of responsibility (SOR) have been shown to have a substantial impact on creating environmental attachment (EA) in both existing and potential customers of sustainable products. The findings of this study also revealed that environmental attachment (EA) plays an important role as a mediator in the links between green environmental awareness (GEA) and the consumption of sustainable goods (SPC), as well as between a sense of responsibility (SOR) and SPC. Despite this, it is crucial to note that the projected direct effect of GEA on SPC was shown to be statistically insignificant. This conclusion implies that additional factors outside the scope of this study may influence the relationship between GEA and SPC. Research limitations/implications: It is vital to highlight that the focus of this study is on an online sample of consumers near Punjab, Pakistan. Future studies should look at other parts of Pakistan to acquire a more complete picture of sustainable consumption trends. Furthermore, our findings suggest that characteristics impacting sustainable consumption, such as Green Environmental Awareness (GEA) and Sense of Responsibility (SOR), may differ among countries. As a result, performing a comparison analysis involving two or more countries could provide valuable insights into projecting sustainable product consumption among current and potential sustainable product customers. Originality/Value: This study contributes to the literature by investigating the factors of sustainable consumption using the lens of the Norm Activation Model theory (NAM), notably Green Environmental Awareness (GEA) and Sense of Responsibility (SOR), to predict sustainable product consumption. The findings are important for promoting long-term goals in Pakistan and provide a framework that can be applied in other emerging markets.