Browsing by Author "Mohammed, Shoaib"

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    Beyond Official Channels: Informal Economic Structures and Cross-Border Exchange Patterns in India-China Border Regions
    (Economic Sciences, 2025) Vaishnav, Jaimine; Mohammed, Shoaib; Bathia, Amit; Balasubramanian, Jayashree; Dosani, Rahil; Grover, Pooja
    This study critically examines the informal economy in India–China cross-border trade through the Nathula Pass in Sikkim, using ethnographic and econometric methods. Grounded theory and mixed-method research—including 73 interviews, participant observation, and archival analysis—reveal how ancestral trader dominance, bureaucratic bottlenecks, and weak infrastructure obstruct the economic potential of the Nathula Trade Agreement (2006). Despite revisions in trade caps and commodity lists, restrictive policies, geo-climatic challenges, and militarization continue to limit trade. The research deconstructs security-centric narratives by foregrounding Sikkimese micro-entrepreneurs whose informal trade constitutes over 40% of daily revenue. Drawing from dependency theory, James C. Scott’s “moral economy,” and Foucault’s “biopolitics,” the study situates informal trade as both survivalist and entrepreneurial. Brokers from West Bengal and Bihar create additional rent-seeking layers, reflecting a complex broker-state structure. Recent Commerce Ministry data shows a steep post-2017 decline in formal trade, with informal markets expanding into electronics, garments, and traditional medicines. Yet poor infrastructure reduces throughput by 35%. The study urges policy shifts toward fiscal decentralization, participatory customs governance, and localized Trade Facilitation Councils. By treating informal trade as a vernacular economy, not deviance, India can turn its peripheries into geo-economic assets, balancing security with developmental peace and people-centered diplomacy.
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    Contemporary Trends and Challenges and Advances, in the Manufacturing Industry, with a special focus on applications of Artificial Intelligence and Deep Learning
    (European Economic Letters, 2024) Grover, Pooja; Kumari, Sweta; Vaishnav, Jaimine; Mohammed, Shoaib
    In the last few years’ artificial intelligence (AI), has begun to make its appearance in our everyday life. Even though it is still in its early stage of development, AI has proved beyond human intelligence. DeepMind’s AlphaGo is an illustration of how the AI could provide amazing benefits, particularly in industries such as manufacturing. At the moment there are attempts to connect AI technology with precision engineering and manufacturing in order to change classical production methods. This research paper focuses on some notable milestones that have already been attained in the realization of AI for manufacturing and how it will change the face of any manufacturing facility. There are several challenges in the AI manufacturing application; these include data acquisition and management, human resources, infrastructure, security risks associated with trust issues as well implantation of hurdles. For instance, the collection of data required to train AI models can be challenging for rare events or expensive in large datasets that require labeling. The introduction of AI models into industrial control systems can also pose risks to the security, and some players in industry may be reluctant to use AI because they don’t trust it or understand what is going on. However, these hindrances do not deter AI from becoming an effective solution for predictive maintenance and quality assurance in the sector of manufacturing. Therefore, one should ponder over each manufacturing case and its needs before deciding if or how to adopt AI. The aim of this research paper is to analyze the current progress, problems and prospects in AI-ML across manufacturing entities. Its aim is to enhance knowledge of accessible technologies, support decision-making in choosing appropriate AI/ML technologies and determine where further research needs are possible centered on latest developments. Initial findings indicate that the combination of AI/ML technologies with advanced data collection capabilities from manufacturing networks can produce massive cost and efficiency gains. Though the accurate representation of complex phenomenon in manufacturing is problematic, AI can revolutionize this industry. Other areas where AI is intensively studied include medical image analysis, bioinformatics, recommendation systems and finance. Many notable AI products such as Amazon’s Alexa, IBM Watson and DeepMind AlphaGo have already integrated into our daily use. To address limitations such as interpretability and degraded performance with insufficient data, several sub-branches of deep learning are currently researched namely; Physics - Informed Deep Learning (PIDL), Explainable AI(XAI), Domain Adaptation, (DA) Active Leaning (AL), Multi Task Learning MTL, Graph Neural Network GNN. Convergence of AI with other engineering industries have a potential issue that should not be ignored. The aim is to enable an effective use of AI by the precision engineering and manufacturing community for future-oriented manufacture.
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    Evaluating Effectiveness of IPO Pricing in the Indian Markets
    (Accountancy Business and the Public Interest, 2025) Bhatia, Amit; Mohammed, Shoaib; Homavazir, Malcolm
    The Indian IPO market has also been growing at a rapid rate in the recent past with companies from various sectors of business listing on the market to mobilize funds. Indian IPO valuations are influenced by various factors such as economic environments, regulatory announcements, sentiment of investors, and firm-specific events. This study aims to analyze the trend in IPO pricing in India from 2016 to 2025 in terms of average IPO prices, IPO issuance, most active IPO sectors, and performance of IPOs post-listing. The study uses data from various sources such as company prospectuses, stock exchange websites, and financial newspapers. The findings show that the average IPO valuations have increased significantly over the years, with the highest valuation achieved by the technology, financial service, and consumer goods sectors. The study further picks on the impact of retail participation on IPO valuations, and investor sentiment as determinants for the success of IPOs. Overall, the study illuminates the dynamics of the IPO market in India and provides valuable information to investors, policymakers, and market participants.
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    Profit Pathways
    (Shine Book Publishing, 2024) Vaishnav, Jaimine; Mohammed, Shoaib