9782 research outputs found
Sort by
Automating Corporate Strategy: How Cloud AI Transforms Managerial Intelligence
No full textThe contemporary corporate landscape, characterized by volatility and data saturation, renders traditional intuition- based strategic models inadequate. This chapter argues that Cloud Artificial Intelligence (AI) is catalyzing a paradigm shift, fundamentally transforming managerial intelligence. We demonstrate how Cloud AI automates and augments the entire strategic lifecycle—from environmental scanning and forecasting to planning and execution. By deconstructing core strategic functions and presenting detailed use cases, the chapter illustrates the practical application of machine learning, natural language processing, and optimization algorithms. Crucially, it provides a critical examination of the profound implications of this transition, analyzing the managerial, practical, ethical, and social consequences. The future of competitive advantage lies in a symbiotic human- AI collaboration, necessitating new competencies, ethical frameworks, and organizational structures for responsible and effective strategy formulation
Supply Chain Management of Sugar Industry in India: A Case of Uttar Pradesh and Uttarakhand
No full textThis study is a blend of theoretical applications that provides an insight into the complete supply chain system of the sugar industry. This study conducted in India, covered the states of Uttar Pradesh and Uttarakhand. Some unique characteristics were identified with respect to the sugar industry in India. The main aim of this study was to understand the role of different supply chain partners like sugarcane farmers, millers, distributors (includes brokers, wholesalers, and retailers) and other stakeholders of the sugar industry. This will bring radical improvement to the system at different stages/levels i.e. farmers’ level, procurement level, sugar production level, and distribution level. The researchers, academia, industrialists, and policy makers will definitely understand the real-time working structure and business environment of the sugar supply chain system in Uttar Pradesh and Uttarakhand, probably similar for other states too
Navigating environmental challenges in rice cultivation for food purpose
No full textRice, the crucial staple crop, is threatened by widespread climate change impacts on its cultivation. The rice agronomic traits including plant height, tiller number, leaf number, panicle count, and overall yield are strongly dependent on environmental factors such as day length, temperature, rainfall and soil parameters. Rice growth is affected by temperature fluctuations leading to heat stress or cold damage, which diminish yields, and decreases grain quality. High and low rainfall conditions have negative effects on growth conditions, as plant height, tiller number and grain yield are reduced. Genes interact with soil parameters such as texture, pH and nutrients, organic matter content to influence rice growth. Good soil conditions will further benefit nutrient absorption and root development, and will in turn benefit agronomic performance. However, the plant height, tiller production, and yield are all limited by suboptimal soils with nutrient imbalances or poor structure. This is important for developing rice varieties that are resilient to changing climatic conditions by understanding the complex interactions of genetic and environmental factors. Rice breeders and farmers can help produce more resilient varieties to thrive under adverse conditions with genetic tools and good environmental management to achieve food security and economic profitability
Loya Jirga: An Indigenous Approach to Female Rights in Afghanistan
No full textThis chapter examines the Loya Jirga as a traditional, Afghan-centric approach for addressing concerns related to females' rights in present-day Afghanistan after the ruling regime takeover in 2021. The issue of female rights gained significant attention both in national and international affairs. The restrictions imposed by them have severely limited women's access to education and employment, thereby infringing upon their fundamental rights and freedoms. The Taliban justifies these measures by claiming adherence to Islamic Shari'a law. This chapter explores how the Loya Jirga, a historically significant decision-making body, can serve as a platform for addressing current issues related to women's rights. By analysing its potential role, this chapter contributes to discussions on indigenous solutions to female rights. Through a qualitative and comparative analytical methodology, the study provides a robust framework for academic research, highlighting women's issues under the ruling authorities and suggesting culturally sustainable and religiously aligned solutions. Furthermore, the chapter examines historical instances where the Loya Jirga has played a pivotal role in significant political and legal changes in Afghanistan, offering insights into its potential effectiveness in addressing the current crisis. This study explores how the Loya Jirga can effectively shape policy responses, contributing to the discussion on sustainable, community-driven solutions to the pressing women's rights issues. The findings provide valuable perspectives for the Taliban regime, international actors, and policymakers on how indigenous culturally relevant strategies can promote gender equality in a restrictive environment
Electricity Theft Detection Using Data-Driven Approach
No full textElectricity theft poses a significant challenge to power utilities, resulting in substantial financial losses and compromising the reliability of the power system. Effective Electricity Theft Detection (ETD) is crucial for minimizing financial losses and ensuring the economic operation of the power system. This paper proposes a predictive ETD framework based on consumer load profiles. Statistical features, such as the mean and standard deviation of monthly energy consumption, are used to distinguish between normal and abnormal usage patterns. Several machine learning algorithms are applied to classify consumption behavior, and the model's performance is evaluated using metrics such as accuracy, precision, recall, and the Receiver Operating Characteristics (ROC). The results demonstrate that the proposed feature-based approach enhances detection accuracy, validating the framework's effectiveness in identifying electricity theft
Integrating Marketing Strategies With TQM Strategies for Enhancing Client Experience in Ethiopia
No full textThe integration of marketing strategies and Total Quality Management (TQM) strategies holds immense potential for enhancing client experience in Ethiopia. A sample of 400 participants, including marketing professionals, quality management experts, and business leaders, was surveyed to understand the key factors influencing the alignment of marketing and TQM strategies, the embracing of organizational agility, and their collective impact on client experience in Ethiopia. Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA) were conducted to identify the underlying dimensions of marketing strategies, TQM strategies, organizational agility, and client experience. The Kaiser-Meyer-Olkin (KMO) measure of sampling adequacy. Structural Equation Modeling (SEM) was then employed to examine the mediating role. The findings of this study provide valuable insights into how the strategic integration of marketing and TQM strategies can enhance client experience through the cultivation of organizational agility
Fast, Faster, Blinkit: Sustaining Quick-Commerce Leadership
No full textAs fiscal year 2025 drew to a close, Albinder Dhindsa, co-founder and chief executive officer of Blinkit Commerce Private Limited (Blinkit), was faced with some serious questions due to the growing competitive pressure. Without consumer loyalty to the company, Dhindsa had to find creative ways of maintaining Blinkit’s leadership position. His core challenge was determining what competitive strategy would allow Blinkit to sustain its lead in an increasingly crowded and cost-intensive market. Should Blinkit double down on rapid geographic expansion, diversify into higher margin assortments, or deepen integration with Zomato’s broader ecosystem to lock in customers
Automating Exclusion: Facial Recognition and the Erosion of the Right to Food in India
Full text linkThe Supreme Court of India in People’s Union for Civil Liberties v. Union of India (2001) has established that the right to food is an integral component of the right to life under Article 21 of the Indian Constitution. The National Food Security Act, 2013, also grants pregnant women, lactating mothers and children a statutory entitlement to free nutritious meals for their healthy life. However, in July 2025, the Ministry of Women and Child Development (MWCD), Government of India, mandated facial recognition-based verification for pregnant women, lactating mothers and children to access nutrition benefits such as take-home ration under the POSHAN 2.0 mission, an integrated nutritional support program. This requirement works through a mandatory facial recognition-based electronic Know-Your-Customer (e-KYC) verification. As of August 2025, about 76.9% of the beneficiaries have completed their e-KYC, exposing the remaining quarter of the beneficiaries to the risk of delayed access to the nutrition benefits. Furthermore, Anganwadi workers– frontline nutrition and childcare workers–have also argued that the mandatory facial recognition requirement is impractical in the rural field conditions where compliance is constrained by the lack of mobile phones, outdated Aadhar (India’s national biometric identification system) numbers and photographs, facial scan failures and server disruptions. This shift towards technology-dependent access to nutrition entitlements has converted welfare responsibilities into technological demands at a time when 12 per cent of India’s population continues to be undernourished, as indicated by the Global Hunger Index 2025 report. The facial recognition requirement goes beyond administrative convenience and calls into question the legitimacy of the State placing technological barriers between marginalised groups and the food that is crucial for their survival
Social and psychological impact of deepfakes: a comprehensive bibliometric review
No full textPurpose: Deepfakes, which first appeared in 2017, use artificial intelligence (AI) to generate modified but incredibly realistic digital content, including political satire, posing serious moral, legal, and societal concerns. The purpose of the study is to identify the evolving landscape of deepfake technology, with a focus on its psychological and societal impacts.
Design/methodology/approach: The researchers carried out a comprehensive bibliometric analysis of research from 2019 to 2024, using data obtained from the Web of Science and Scopus bibliographic databases. After combining 688 bibliographic entries from both databases using Bibliometrix R. After eliminating nonEnglish publications and studies irrelevant to the bibliometric scope of deepfake research, a total of 463 articles were included for further study.
Findings: Based on our results, the researchers found that academic scholarships on detection techniques, misinformation, and social impact has grown rapidly, particularly in China, the United States, and India. Six main study areas have emerged, such as deepfake detection methods, information integrity, machine learning, social media influences, forensic analysis, and facial manipulation. The findings reveal that the increasing complexity of deepfake generation and its consequences for ethical concerns significantly affects digital trust, privacy infringement, and the spread of misinformation.
Originality/value: More interdisciplinary techniques combining AI, social sciences and ethics are required despite notable gains in detection. To reduce the risks associated with deepfakes, the study highlights the significance of strong detection technologies, regulatory frameworks and public awareness. The psychological effects of deepfake exposure and the creation of moral standards for appropriate AI use should be the focus of future studies
Heterogeneous interests and monetary payments for afforestation: findings from a framed field experiment (FFE) in Uttara Kannada, India
No full textAfforestation and forest restoration have been central to emerging global strategies for climate change mitigation. Based on a framed field experiment (FFE) conducted in the Uttara Kannada region in Karnataka, India, this study investigates whether monetary incentives could effectively promote afforestation and what the likely distributional consequences are. The FFE set-up was designed to provide respondents with choices on planting native or commercial trees in their village common forest. The native trees were associated with higher risk of survival compared to commercial trees. They also provided a mix of monetary and non-monetary benefits which differed across three variations in the experimental design. We find that monetary payments for planting native species worked better when combined with non-monetary benefits. Also, private tenurial rights mediated responses to monetary incentives. The results highlight how heterogeneous interests within the community could play an important role in determining effectiveness and distributional outcomes of afforestation policy