A large number of people of the fringe areas of Sundarban enter into the forests every year and encounter with the tigers simply for their livelihood. This study attempts to examine the extent and impact of human-animal conflicts in the Sundarban Reserve Forest (SRF) area in West Bengal, India. An intensive study of the data of the victims (both death and injury) between 1999 and 2014 reveals that, fishermen crab collector, honey collectors and woodcutters are generally victimized by the tiger attack. Pre monsoon period (April to June) and early winter period (Jan to March) are noted for the two-peak periods for casualties. Maximum casualty occurs between 8-10 am, and 2-4 pm. Jhilla (21.1%), Pirkhali (19.72 %), Chandkhali (11.72%), and Arbesi (9.35%) are the four most vulnerable forest blocks accounting more than 60 per cent occurrence of incidences. 67.24 per cent of the tiger attack victims were residents of Gosaba followed by Hingalganja (15%) and Basanti, (9.76%). The vulnerability rating puts the risk of tiger attack to 0.88 for every 10,000 residents of Gosaba block followed by 0.33 at Hingalganj Block and 0.11 at Bansanti Block. The majority of the victims (68%) were found to be males, aged between 30 and 50 years.

The rise of online gambling in Indonesia has emerged as a significant public health concern, driven by various psychological, social, and regulatory factors. Despite stringent laws prohibiting gambling, the accessibility and appeal of online platforms have led to increased participation, particularly among young adults. This phenomenon is characterized by a paradoxical sense of control that users feel while gambling online, which can lead to compulsive behaviors and addiction. The structural characteristics of online gambling platforms, including fast-paced games and easy accessibility, further exacerbate this issue. Social influences, particularly through social media and peer interactions, normalize gambling behaviors, making them more appealing to adolescents. Mental health issues, such as anxiety and depression, are closely linked to online gambling addiction, as individuals may use gambling as a coping mechanism. The COVID-19 pandemic has intensified these challenges, with many individuals turning to online gambling for entertainment during lockdowns. To address the growing prevalence of online gambling addiction, comprehensive regulatory frameworks are needed, alongside responsible gambling initiatives and public awareness campaigns. Collaboration among stakeholders, including government agencies, healthcare providers, and gambling operators, is crucial for effective intervention. Continuous monitoring and evaluation of online gambling trends will inform future policies and help identify emerging risks. By adopting a multifaceted approach, Indonesian policymakers and stakeholders can work towards minimizing the risks associated with online gambling and fostering a healthier environment for its citizens.

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.

Food safety in supply chains remains a critical concern due to the complexity of global distribution networks. This study develops a conceptual framework to evaluate how food safety risks influence supply chain performance through predictive analytics. The framework identifies and minimizes food safety risks before they cause serious problems. The study examines the impact of food safety practices, supply chain transparency, and technological integration on adopting predictive analytics. To illustrate the complex dynamics of food safety and supply chain performance, the study presents supply chain transparency, technological integration, and food safety practices and procedures as independent variables and predictive analytics as a mediator. The results show that supply chain managers’ capacity to anticipate and control risks related to food safety can be improved by predictive analytics, leading to safer food production and distribution methods. The research recommends that businesses create scalable cloud-based predictive model solutions, combine data sources, and employ cutting-edge AI and machine learning tools. Companies should also note that strong, data-driven approaches to food safety require cooperative data sharing, regulatory compliance, training initiatives and ongoing improvement.