Partners Universal International Research Journal https://puirj.com/index.php/research en-US editor@puirj.com (Editor) editor@puirj.com (support) Thu, 25 Jun 2026 00:00:00 +0000 OJS 3.3.0.8 http://blogs.law.harvard.edu/tech/rss 60 When Technology Works but Adoption Fails: Leadership Capability Gaps in Enterprise Artificial Intelligence Transformation https://puirj.com/index.php/research/article/view/244 <p>In all sectors, organisations have spent a lot on artificial intelligence, but a significant percentage of these projects fail to yield tangible results. This article proposes that this is not due to the technology per se, which has developed quickly, but to the skill deficits of the leaders of such technology adoption. All too frequently, senior technology leaders view AI as a product that can be bought and turned on, rather than a transformation programme for the entire enterprise that requires disciplined governance, data readiness, workforce engagement, and financial accountability. Based on the experience of 30 years of seeing what works and what doesn't work in manufacturing, global capability centres and large enterprises alike, the discussion highlights common problems pilots without success criteria, disjointed data, legacy systems that do not integrate, front-line workers who are not engaged with new tools, and a lack of ability to prove return on investment. Next, it outlines the disciplines of successful adoption defined problem, executive sponsorship, governed data, realistic integration, human oversight, and continuous measurement. The article also looks at the development of specific transformation leadership positions. The key message is positive businesses thrive when AI is viewed as a business change initiative with smart, self-directed business leaders and not as a procurement decision handed over to vendors. This article is aimed at executives, practitioners and the interested public.</p> Dr. A. Shaji George Copyright (c) 2026 https://puirj.com/index.php/research/article/view/244 Thu, 25 Jun 2026 00:00:00 +0000 Employee Retention in the Modern Workplace: The Role of Organizational Culture, Leadership, and Career Growth Beyond Compensation https://puirj.com/index.php/research/article/view/245 <p>The belief that monetary factors are the major influences on employee retention has been widely challenged by the empirical evidence that shows that the most important factors are non-monetary. This article looks at the idea that although a job may be a good one with a high pay, it's the culture, relationships and the development that will keep them at the job. Building on theory from organizational behavior, human resource management and industrial-organizational psychology, the manuscript draws on cross-national studies, and the manuscript theorizes about the psychological and structural mechanisms that underlie voluntary turnover. The analysis reveals a phenomenon here called graduated disengagement, where workers slowly disengage emotionally, cognitively and physically prior to their official exit and their bosses likely never realize it. Eight dimensions of innovation are explored cultural architecture, psychological safety, leadership quality, growth ecosystems, recognition systems, well-being infrastructure, communication transparency and meaning-making. The article discusses a need for paradigm change from transaction to relationship human capital management for the contemporary retention strategies. Practical applications and relevance to the public-sector, policy implications, and directions for future research are discussed. The results have implications for the sustainability of organisations, productivity of employees as well as the welfare of societies in a globalised labour market with increased labour mobility and changing employee expectations.</p> Dr. A. Shaji George Copyright (c) 2026 https://puirj.com/index.php/research/article/view/245 Thu, 25 Jun 2026 00:00:00 +0000 Degrees, Skills, and the Architecture of Human Capital: Reconceptualising India's Path to Inclusive Economic Development https://puirj.com/index.php/research/article/view/246 <p>This article proposes a common analytical approach to the understanding of the role of human capital formation in economic development of a large economy with a young population like India, with global implications. The manuscript takes a different approach from the binary framework where formal degrees and vocational skills are often pitted against one another that is often analytically misleading, and suggests that a tightly coupled degrees-plus-skills model, where credentialed education, applied skills, and lifelong learning are all complementary inputs, is developmentally optimal. Based on the concepts of human capital theory, signalling theory, the capability approach and endogenous growth models, the article builds a conceptual framework which differentiates the basic, signal, productive and adaptive roles of education and places skills within. It then critically reviews empirical evidence on the returns to education, employability gaps and skill mismatches in each country before moving to eight chapters of in-depth analysis on the practical applications, societal impact, social benefit, governmental use, public-sector development, policy relevance, implementation considerations and future opportunities. The analysis shows that the demographic dividend can only materialise as a sustained one if the educational system is coherent, with a connection between curricula, certification, labour market signals, and continuous reskilling, rather than on a particular expansion of any one educational modality. This article concludes that the real policy issue is not choice of degrees vs. skills but engineering the alignment, portability, and equity of an integrated human capital system.</p> Dr. A. Shaji George, Dr. T. Baskar Copyright (c) 2026 https://puirj.com/index.php/research/article/view/246 Thu, 25 Jun 2026 00:00:00 +0000 Digital Inclusion vs. Fiscal Revenue Assessing India's Per-Gigabyte Data Tax https://puirj.com/index.php/research/article/view/247 <p>India has reportedly submitted a study proposal to its DoT which has the potential to change the digital landscape of the country. The proposal is to impose a one rupee charge on each gigabyte of mobile Internet data used, and the aim is to discourage the youth from consuming data that is not productive and to reduce their addiction to social media. The proposal seems modest and could generate just under three billion dollars in new annual revenues, but it would increase the average user's mobile bill by 10 to 15 per cent. However, beneath this seemingly simple proposal lie a range of technical, economic, philosophical, and constitutional issues. This article aims to critically analyse the proposal and place it in the context of the ongoing digital transformation in India and the international discourse on the taxation of the Internet economy. It assesses the rationale of nudging users to behave in a certain way, the inability to distinguish between productive and unproductive data flows, the regressive consequences for lower-income users, and macroeconomic risks for sectors relying on low-cost connectivity. The article also refers to the experiences of other countries, such as Uganda and Hungary, to illustrate that the internet usage tax has consistently failed. Finally, it suggests alternative policy frameworks that will mitigate the concerns while maintaining digital inclusion, innovation and fundamental rights.</p> Dr. A. Shaji George Copyright (c) 2026 https://puirj.com/index.php/research/article/view/247 Thu, 25 Jun 2026 00:00:00 +0000 Combined Set of Several Sets of Observations: Cubic Mean https://puirj.com/index.php/research/article/view/248 <p>An algebraic expression of the cubic mean of a set of observations, which is the combined set of several sets of observations in terms of the cubic means of the sets and the respective numbers of observations in the sets, has been derived for the purpose of computing the cubic mean of the combined set when the observations of the sets are unknown but the individual cubic means of the sets along with the respective numbers of observations are known. Derivation of the formula, along with a numerical example, has been presented in this article.</p> Dhritikesh Chakrabarty Copyright (c) 2026 https://puirj.com/index.php/research/article/view/248 Thu, 25 Jun 2026 00:00:00 +0000