Abstract: Global pandemic has provoked industries with unprecedented challenges. Stratagems to squash the COVID-19 bow like communal lockdown, social isolation, work at home, containment zones and all restraints sited on travel with stay home orders issued by the authorities led to sharp failure in revenues of service and manufacturing industries. The COVID-19 pandemic has shattered the transportation links with supply chain amongst suppliers, production amenities and consumers. Mostly the business executives are penetrating about passable strategies and plans for restoring production lines to encounter customer mandates. In this paper the pandemic effect of Indian business is considered which are affected by critical barriers of supply chains in the Indian scenario. These critical barriers are identified on a priority basis using the MADM approach. Furthermore, the study will help the scholars to grow conceptual models for maintaining a better supply chain to overwhelm this world-wide problem.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: This research aims to explore the significance of supply chain (SC) resilience by integrating SC-Resilience and SC-Ambidexterity concepts. SC-Ambidexterity refers to the simultaneous application of SC-Adaptability and SC-Alignment capabilities within the supply chain. In line with the dynamic capabilities view (DCV) of the firm, this research adopts a quantitative approach to investigate the relationship between variables in the context of manufacturing and production companies in Pakistan, specifically in Karachi. The results of this case study have revealed a strong positive impact of SC-Ambidexterity on SC-Resilience, confirming the significance of adopting concurrent and synchronized supply chain capabilities. Furthermore, the analysis indicated that SC-Agility plays a crucial role as a mediator in the relationship between SC-Ambidexterity and SC-Resilience. The findings suggest that organizations that proactively invest in developing both ambidextrous capabilities and agility are more likely to achieve a higher level of supply chain resilience, enabling them to effectively navigate turbulent business environments.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: Access to safe drinking water is essential for human health. In Abbottabad, tap and bore water are commonly used, but there has been a recent increase in bottled water consumption. This study aimed to compare tap and bottled water quality in Jinnahabad, Abbottabad. Physicochemical and bacteriological analysis was conducted on water samples collected from various sources. Surveys and interviews were also conducted to assess consumer perceptions and costs. The study found that, on average, bottled water had better physicochemical quality, although both alternatives met WHO limits. Tap water had higher levels of E. coli due to a weak sanitation system. Interestingly, despite perceiving bottled water as safer, most respondents still consumed tap water daily. Shopkeepers reported higher bottled water purchases for travel but lower daily consumption. Tap water was the main source, according to the Cantonment Board Abbottabad, though resources were insufficient. Doctors confirmed tap water-related diseases. The study suggests further research into consumer behavior and recommends monitoring measures, staff evaluations, and penalties to reduce costs and waste.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: This study delved into the repercussions of economic instability on household food security while aiming to construct a robust framework for enhancing the resilience of the food supply chain. It thoroughly analyzed diverse factors, including government policies, economic conditions, environmental variables, and social dynamics, to gauge their reciprocal impact on food security. The research employed a meticulously chosen probability-based sample to ensure the representativeness of findings within the population, specifically focusing on residents in the Tanjung Kupang region of Johor. The study holds paramount significance as it provides novel insights for researchers, academic practitioners, and policymakers, shedding light on the far-reaching consequences of economic uncertainty on household purchasing power and its pivotal role in upholding food security. Moreover, it aspires to devise a tailored and sustainable food supply chain framework for Malaysia's unique context. By employing a quantitative approach enriched with robust statistical analysis and insights gathered through a meticulously designed questionnaire, this study sought to illuminate the intricate dynamics at play. The findings underscore the profound impact of economic instability on diminishing the income of B40 households, thereby curtailing their purchasing power. These findings align with comprehensive literature reviews from authoritative sources, underscoring factors such as inflation, soaring prices of essential commodities, and stagnant incomes contributing to the decline in income among B40 households. The implications of this research extend to policymakers, offering invaluable insights and promoting public awareness of potential challenges, along with plausible solutions.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: Nomophobia is a term describing a growing fear in today’s world, the fear of being without a mobile device or beyond mobile phone contact. It is the biggest non-drug addiction of the 21st century and is mainly affected by teen-aged students. Those experiencing nomophobia may feel a sense of panic, anxiety, or distress when they are separated from their mobile phones. This work uses different statistical tools to identify the risk factor of nomophobia and machine learning techniques to propose a fresh way to measure and understand nomophobia. To create a predictive model for nomophobia, we gathered information from a broad sample (n = 357) of smartphone users and used a variety of machine learning methods. Using a questionnaire on 17 different factors and performing a statistically significant test (p<0.05) and ordinal logistic regression analysis on respondents age, level of education, CGPA, self-evaluation, per-day mobile phone usage, and use of media, we can recognize the most important features causative of nomophobia. The context of maximum phone usage is an important feature that highly affects nomophobia. About 201 respondents are at a moderate level. To develop a predictive model, decision tree (DT), random forest (RF), Gaussian Naïve Bayes (NB), and support vector machine (SVM) are utilized in this study for recognition of nomophobia addiction. Proposing an ensemble method to refine the predictive performance. From the analysis, we have found that the SVM feature selector with ensemble algorithm has classified the extent of smartphone addiction with a 57% accuracy rate. Our findings show that nomophobia tendencies can be accurately captured and predicted by machine learning approaches. The model distinguished between students who had symptoms of nomophobia and those who did not with remarkable accuracy. This study of machine learning-based methods presents a viable tool for diagnosing and treating nomophobia in students, eventually assisting in the creation of focused interventions and preventive measures.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)