How much did the colonial state ?truly? know about India? This question underpinned Sir William Wilson Hunter?s early foundational work, The Annals of Rural Bengal, which marked his entry into colonial knowledge production. In this text, Hunter offered a searing critique of the Company?s ?unreliable? and ?incomplete? knowledge. This article argues that such anxieties about ignorance, sharpened in the post-1857 imperial order, enabled the colonial state?s investment in local knowledge, culminating in the Gazetteer project. Hunter?s reconstruction of the Santal rebellion of 1855 articulated a sense of anxiety, reframing colonial ignorance as a political problem of governance and diagnosing it as the product of an inadequate colonial knowledge framework revealed in moments of rebellion and administrative delay. In casting ignorance as a political risk, he recast violence as evidence of administrative misrecognition, thereby justifying the need for systematic forms of knowledge production such as the Gazetteer. The article shows how epistemic anxiety was translated into bureaucratic forms of knowledge production, with the Gazetteer institutionalising uncertainty rather than resolving it. ? 2026 Informa UK Limited, trading as Taylor & Francis Group.

Artificial Intelligence (AI) is reshaping organizational decision-making, with Generative AI (GenAI) enabling adaptive Decision Support Systems for complex challenges. Rather than uniform effects, organizations experience varied adjustments depending on roles, contexts, and implementation strategies. Routine tasks are increasingly automated, allowing employees to focus on higher-value activities, while GenAI also transforms how information is accessed, processed, and shared. These shifts influence communication, decision-making practices, and managerial benchmarks, alongside evolving expectations around workforce participation and ethics. This study integrates intellectual evaluation and sociotechnical frameworks to examine evidence across industries, highlighting links between GenAI deployment, psychological enablement, and societal change. Qualitative findings suggest that while GenAI enhances autonomy, creativity, and self-efficacy, it also introduces ethical risks, transparency concerns, and social disparities. Organizations that adopt human-centered integration approaches demonstrate greater adaptability, trust, and sustainable outcomes in AI-enabled work environments. ? 2026 Informa UK Limited, trading as Taylor & Francis Group.

Purpose: How do enterprising subjects experience (in)visibility in their projects of the self, at what costs and with what effects? Theorizing invisibility/imperceptibility as a constant threat to one's sense of self, existence and survival within neoliberal governmentality, this study examines self-(in)visibilization among Indian Information Technology employees.



Design/methodology/approach: This study is based on an analysis of semi-structured interviews with Indian Information Technology workers. Analytically, we follow the ?thinking with theory? methodology, which involves an abductive approach to generate novel insights.



Findings: Our analysis shows that enterprising subjects experienced fourfold threats of invisibility/imperceptibility & exclusion, obsolescence, managerial disfavours and psychic incoherence, which led them to visibilize themselves as indispensable, continuously upgraded, sycophantic and coherent subjects. However, such self-visibilization also produced its traps and challenges, including living with existential insecurity and being caught in the impermanence of visibility, the oppressive double bind of visibility, and gendered differences. Employees negotiated these contradictions through continuous revisibilization, strategic (in)visibility or enacting multiple visibilities.



Originality/value: This paper uniquely theorizes and illustrates the politics of (in)visibility within neoliberalism, which involves a constant negotiation of the simultaneous desirable consequence of recognition (security and growth), weighed against the undesirable consequence of that same recognition (exploitation and intensification). This inescapable trade-off constitutes the oppressive double bind of visibility at the core of neoliberal self-constitution.

This study aims to explore the use of equated daily instalments (EDI), as an alternative repayment schedule compared to the traditional equated monthly instalments (EMI) in consumer and commercial lending. It also discusses the feasibility, advantages, and drawbacks of EDI systems. The research compares EDI with EMI and assesses the effect on borrower behavior, financial planning and overall loan performance. It relies on case studies, borrower surveys, and financial modelling to evaluate the feasibility and efficiency of daily repayment models. EDIs has proven to be more flexible (and lower defaults, perhaps) but inherent challenges of admin complexity and self-discipline also accompany them. This study adds to the generic literature on new financial products and their effects on financial inclusion and customer satisfaction. ? 2026 selection and editorial matter, Sai Kiran Oruganti, Manoj V. Bhalerao, Vishal Gangadhar Naranje, Dalia A. Magdi and Santosh Gore; individual chapters, the contributors.

The paper investigates the impact of the imposition of a minimum buyback requirement on open market repurchases (OMRs) in India. We extend the signaling model of Oded (2005) by including a minimum buyback requirement and show that it increases the stock price during the repurchase period, relative to a no minimum buyback regime. Accordingly, we find that the regulatory change has led to a significant increase in the abnormal stock returns earned around buyback announcements. Also, insiders increase their purchase of firms? stock during the buyback execution period relative to the pre-reform period. These findings are consistent with a higher information value of OMR announcements in the minimum buyback regime. We further observe lower market timing through buyback execution, accompanied by a change in the execution-style, implying a weaker instinct for opportunistic buybacks. Our findings suggest that the regulatory change has lowered the ?cheap-talk? motives associated with the announcement of open market buybacks. ? 2025

National and international freight transport emissions represent about 40% of global transport emissions, with demand expected to triple by 2050, which will increase emissions further. However, to meet the 1.5?C climate goal, a rapid decrease in transport emissions is required, along with the achievement of zero emissions as soon as possible around mid-century. Given this context, long-term low-emission national development pathways provide a strategic instrument to align short-term action with long-term objectives and to reduce national freight transport emissions. However, current transport-energy modelling studies often exclude the structural and systemic mitigation options that influence the industrial production and supply chain structure, as well as modal and logistics choices, and instead focus mainly on the technological options related to road freight vehicles and fuels. In addition, such studies lack relevant policy and stakeholder-oriented explanations of the barriers and enablers associated with these options. In this paper, we introduce a new framework to design and compare long-term national and sectoral decarbonization pathways for freight transportation, facilitating the consideration of all decarbonization options and the organization of stakeholder-oriented policy dialogues. The development of this sectoral framework builds on the general Deep Decarbonization Pathways (DDP) framework and a first implementation in France. It is then applied and tested in three emerging countries: Brazil, India and South Africa and the results show that the linking of systemic and technological changes could reduce emissions per tonne-km by at least 60%, and up to 100% by 2050, while also reducing energy consumption and supporting national development. ? 2024 Informa UK Limited, trading as Taylor & Francis Group.

Federated Learning (FL) enables privacy-preserving distributed training by avoiding centralized data collection. However, most FL frameworks presume uninterrupted participation from selected clients, which is impractical in edge environments with fluctuating resources. Devices often experience low battery, high CPU or memory load, limited bandwidth, and unstable connectivity, resulting in latency, client dropout, and reduced training performance. To address this issue, we introduce a lightweight, resource-aware participation prediction model based on a HistGradientBoosting Classifier (HGBC), trained solely on device-level resource indicators. A synthetic dataset is constructed through weighted logistic scoring combined with probabilistic Bernoulli sampling to reflect realistic resource variability. Evaluation using standard classification metrics shows strong predictive capability, including a high AUC value. Overall, the results highlight that incorporating an intelligent client selection mechanism aware of real-time resource conditions can significantly improve FL efficiency. It reduces unnecessary computation, lowers the chances of client dropout, and speeds up convergence, all while maintaining scalability and compatibility with a wide range of FL architectures as a modular scheduling component. ? 2026 IEEE.

A 50-year-old woman, diagnosed with severe rheumatic mitral stenosis, was referred for transesophageal echocardiography (TEE) study to confirm suitability for percutaneous balloon valvotomy and to look for evidence of thrombus in the left atrial appendage (LAA). TEE evaluation followed by computed tomography scan and magnetic resonance imaging confirmed congenital absence of LAA ? a rare occurrence with fewer than 25 reports in the literature. Learning objective To evaluate the diagnostic process and clinical implications of absent left atrial appendage in the context of severe rheumatic mitral stenosis, emphasizing the utility of transesophageal echocardiography, contrast-enhanced computed tomography scan, and cardiac magnetic resonance imaging in identifying this rare anomaly with its impact on therapeutic decision-making. ? 2025 Elsevier Ltd.

This study introduces enhancements to three established swarm intelligence-based optimization algorithms: the Improved Crow Search, Dynamic BAT, and Levy Whale Optimization. Mutation operators, traditionally used in evolutionary-based optimization like genetic algorithms, help escape local optima to converge towards a global solution. This work integrates two novel mutation operators into these algorithms, enhancing their ability to effectively explore and exploit the search space. We employed 12 benchmark functions to analyze performance, observing improvements in global optimal values ranging from 29% to 152%. Furthermore, we applied these algorithms as training optimizers for neural networks, aiming to predict pelvic joint location from fingertips and these data have been used to train a multi-layered feedforward neural network. The algorithms without mutation and with mutation operators have been used as optimizers to train neural networks. A significant decrease in the absolute average percentage from experimental data has been observed. These findings highlight the potential of mutation operators to refine the exploration and exploitation capabilities of swarm intelligence algorithms. ? The Author(s), under exclusive license to Springer Nature Switzerland AG 2026.

Customer expectations for quick delivery have shifted significantly. Today, speed is the new currency, with customers wanting faster delivery while prioritising cheaper delivery. Hence, some changes have been made to address this faster delivery process in the retail industry. This research will address what factors need to be considered in adopting the quick-commerce service in retail and address the interdependence among factors and subfactors using supply chain agility. To address these problem the information was gathered from experts in the retailing area from academics and industry and proposed a hybrid multiple criteria decision-making model incorporating the Decision-Making Trial and Evaluation Laboratory (DEMATEL)-based Analytic Network Process (DANP). The findings result in 19 subfactors categorised into five factors from the literature review, which might be important in adopting a q-commerce service. The cause-and-effect relationship has been drawn among the factors and subfactors. The top subfactor, based on the influencing weights, is classified into three tiers, in which the first tier factors are core critical factors, the second tier is for enhancing the efficiency of the organisation, and the third tier is for enhancing customer satisfaction, engagement and trust for q-commerce (quick commerce) service. To successfully adopt q-commerce in retail, artificial intelligence and machine learning facilitate advanced demand forecasting, route optimization, and inventory management, thereby enhancing operational responsiveness in highly dynamic urban environments. Additionally, real-time order tracking, intelligent warehousing, and temperature-controlled transportation are made possible by Internet of Things technology, guaranteeing product quality and supply chain transparency. This knowledge helps to clarify how managers and merchants can use these elements to improve the q-commerce service. This study is novel in that it highlights the factors that contribute to the retail adoption of q-commerce and explores the interdependencies between these aspects. ? 2026 Elsevier B.V.

In this work, we conduct a narrative review of pressing equity and justice issues within global modelled scenarios and propose a new research agenda to strengthen their consideration in future model developments and applications. We begin by introducing a typology of equity and justice limitations in climate mitigation scenarios, distinguishing among structural, methodological, and epistemological issues that shape what integrated assessment models (IAMs) can reveal at policy-relevant scales. Reflecting on these concerns, we develop a research agenda that describes new avenues of work and draws together distinct emerging initiatives, ranging from incremental improvements to structural reforms and alternative participatory approaches. Drawing on reflexive insights from integrated assessment practitioners, this agenda prioritizes embedding equity principles directly into scenario design through differentiated effort sharing and finance flows, developing new frameworks that incorporate sufficiency and demand transformations while protecting decent living, and establishing genuine co-production with underrepresented communities beyond mere consultation. Underlying this research agenda is a recognition that modeling communities must engage more critically with the implicit assumptions in scenario and model design and use that have equity and justice implications. Achieving equitable climate futures will require transformative actions that integrate diverse justice concerns, advance sustainable development, and confront systemic inequities across both human and ecological dimensions. Although models will never capture all these aspects, these can be significantly enhanced to support more informed discussion and practical application. Our contribution proposes a way forward to achieving this goal. ? 2026 Pachauri et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Purpose ? This study aims to examine how job autonomy promotes employee agility in young entrepreneurial ventures through work engagement and founder trust, drawing on the job demands?resources (JD-R) framework. Design/methodology/approach ? We conducted two studies across distinct contexts: a two-wave field survey of employees in young Indian ventures (n?=?205) and a survey study through Prolific in the United States of America (n?=?184). Confirmatory factor analyses (AMOS) were employed to validate the constructs, and mediation and moderated mediation analyses were conducted using the PROCESS macro in SPSS. Findings ? Results indicate that work engagement mediates the relationship between autonomy and agility. Trust in the founder strengthens the effect of engagement on agility, thereby amplifying the indirect effect of autonomy on agility through engagement. This moderating effect was significant in India but not in the United States of America, suggesting that institutional and cultural contexts condition the influence of trust as a resource. Practical implications ? The findings suggest that the impact of autonomy on agility is buffered by trust and engagement mechanisms. The results highlight the need for context-sensitive practices, with trust playing a greater role in developing economies and collectivist cultures. Originality/value ? This study extends the JD-R theory to entrepreneurial contexts, demonstrating that employee agility emerges from the dynamic interplay of autonomy, engagement and trust, with contextual variations across national settings. ? 2025 Emerald Publishing Limited

The union budget is an annual exercise, but it gives a sense of direction for policy in terms of emphasising or moving away from certain schemes and programmes, especially in a sector like agriculture, as it is highly heterogeneous across India and faces many challenges from multiple sustainability challenges. More recently, the agricultural sector has performed better than in the past in terms of the growth rate. This article examines the allocations of the Union Budget 2026?27 for the agricultural and rural sectors in terms of both changing focus (from subsidies to investments, and from production to market support) as well as reasons for higher or lower allocations, as seen through the utilisation pattern of such allocations over the years and in the previous year. ? 2026, Economic and Political Weekly. All rights reserved.

Agro-industrialisation is the natural next step after agricultural growth and development as a part of the structural transformation process towards an industrial economy, which leads to value addition and new employment opportunities. The Indian Punjab, known for the Green Revolution in its agricultural sector, has lagged in this transformative sectoral movement of the economy. This chapter discusses the rationale for agro-industrialisation with the help of the theory of agro-industrial development and examines the factors which hindered the agro-industrial process, followed by enabling factors and policies which can facilitate such a transformation. ? 2026 selection and editorial matter, Pritam Singh and Meena Dhanda; individual chapters, the contributors.

A developer's popularity plays a crucial role in their success within open source software (OSS) communities and their access to sponsorship opportunities. This study seeks to answer the question: which signals have the most predictive power for popularity and sponsorship volume on social coding platforms? Using algorithm-supported abductive theory generation supplemented by qualitative insights from observations and interviews, we arrive at a theory of peer evaluation in OSS communities. We examine a large number of signals and categorize them. The two categories are signaling via self-disclosure through profile signals and signaling via contribution quantity and quality through behavioral signals. The large amount of data available to us allows us to use machine learning techniques to arrive at top-ranking predictors within each category. We generate our theory by finding robust patterns and test our theory using a hold-out sample. Our findings indicate that easily observable credibility-enhancing and approachability-related developer profile signals hold greater predictive importance in shaping popularity. However, harder to observe and more complex behavioral signals show greater predictive importance for sponsorship volume. These results signify that OSS social coding platforms are not meritocratic, as developer self-disclosure significantly influences popularity. In contrast, sponsorship decisions, due to their high cost and irreversibility, depend on within-platform contribution-related signals. This research contributes to a deeper understanding of popularity and sponsorship within peer-to-peer followership networks in OSS communities. Through our research, platforms are better informed about the predictors of popularity and sponsorship and can introduce measures to enhance the meritocratic nature of these communities. Developers who seek influence and sponsorship on the platform can be more strategic about information disclosure and their contributions. ? The Author(s) 2026

In the early stages of the Covid-19 pandemic, individual compliance with preventive behaviours was the central public health tool available to control the spread of the disease. While the extant literature studied a range of psychological, social, economic, and political factors driving these behaviours, we argue that communication framing was such that personal values could be an important antecedent to explain compliance. Drawing on theoretical frameworks linking personal values to behaviour, we develop hypotheses that we test using survey data comprising 500 participants from four large cities in India. We measured key variables such as self-transcendent and self-enhancement values, perceived risk of infection, and sociodemographic factors using validated measures in the extant literature. We use ordinary least squares regression models to test our hypotheses. Consistent with our hypotheses, we find strong evidence that self-transcendent or altruistic values have a strong positive association with mask-wearing. In contrast, self-enhancement or egoistic values are associated positively with the frequency of hand hygiene. These relationships persist irrespective of the respondents' perception of Covid-19 risk for themselves or others. Additionally, we find that women and older individuals are more likely to wash their hands frequently. Although social desirability bias was present in some models, it did not affect the study's broad findings. Our study highlights the importance of personal values in shaping compliance with Covid-19 protective behaviours. Studies exploring the effectiveness of altruistic versus egoistic message framing in public health communications would benefit from controlling for personal value orientations. ? 2026 The Authors.

Additive manufacturing (AM), particularly Laser Powder Bed Fusion (L-PBF), has transformed mold and core fabrication in foundry applications by enabling complex geometries, rapid prototyping, and patternless production. Despite these advancements, the consistent achievement of high-dimensional accuracy, mechanical strength, and surface integrity in sand-based AM remains challenging due to intricate thermal?process parameter interactions. To address these issues, the present study aims to optimize the process parameters of an indigenously developed Sand-based Additive Manufacturing (SAAM) apparatus based on a flying-optics CO2 laser for fabricating sand molds without conventional tooling. Four key parameters: laser power, layer thickness, scan speed, and overlap were analyzed for their influence on dimensional accuracy (diameter and height), compressive strength, surface porosity, and areal surface roughness. A Central Composite Design (CCD) under Response Surface Methodology (RSM) was used for modelling, followed by single- and multi-objective optimization using the Teaching Learning-Based Optimization (TLBO) algorithm. The regression models showed high predictive accuracy (R? >96% for all responses), while the optimized process parameters yielded less than 4.24% deviation between predicted and experimental outcomes. The multi-objective optimization produced an optimal parameter set (t = 0.3946?mm, P = 14.94?W, v = 64.84?mm/s, W = 19.52%) that enhanced mold quality and structural integrity, enabling the successful patternless casting of A356 aluminium alloy. Overall, this work provides an experimentally validated framework for parameter optimization in SAAM, highlighting its industrial potential for cost-effective, high-precision, and sustainable mold fabrication. ? The Author(s), under exclusive licence to Springer-Verlag France SAS, part of Springer Nature 2025.

Efficient operation on the factory floor has been hindered by data latency and communication delays, leading to production downtime and associated costs. This research investigates the use of an IoT-enabled Andon system integrated with a vendor-neutral Business Intelligence (BI) visualisation layer, within a genset manufacturing business. Through a sociotechnical intervention, this work examines how integration of real-time monitoring, data visualisation, and visual management influences operational performance. The single-case study method confirms the effect of implementing an IoT-enabled Andon: a 55.55% reduction in unscheduled downtime and a 4% increase in Overall Equipment Effectiveness. The effectiveness of the Andon and Power BI system was due to ?technology? and, importantly, its empowerment of operators to make responsive and aligned production decisions. The research provides empirical validation of an integrated Industry 4.0 intervention through a sociotechnical lens. It highlights the synergy between digital tools and human decision-making, offering strategic directions for digital transformation. ? 2026 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.

It has been scientifically established that the transportation and logistics sectors are critical in the determination of sustainable global initiatives because of their immense effects on the environment. This chapter uses a holistic round scheme to examine how sustainability principles are incorporated into transport and logistics. This model identifies these components, Catalysts, Conversions, Outputs, and Impacts. Necessarily, these include alternative fuel vehicles (AFVs), routing software for optimal decisions together, and collaboration. Improving the routes taken when making deliveries, optimizing vehicle loads, and changing modes of transport are examples of catalysts that have been implemented in real-world systems through operationalization. These steps then give rise to things like less pollution, less fuel usage, or more successful supply chain operations. The successful yield, in turn, has cumulative significant impacts that result in better environmental performance, cost savings, and happy customers. ? 2026 selection and editorial matter, Dr. Ashu Sharma, Dr Veena Vohra and Dr. Rose Antony; individual chapters, the contributors.

?Mindful consumption? in tourism services helps to create a positive experience for the consumer by enabling the latter to effectively utilise the resources available at the tourist destination. While numerous studies have explored the idea of mindful consumption, most of them have largely examined the overarching concepts. In contrast, this study focuses on evaluating the effect of mindful consumption in the tourism sector on the residents? well-being of the tourist destination using Stimulus-Organism-Response (SOR) Theory. A mixed method was used to evaluate the impact of the antecedents of mindful consumption on residents? well-being of the tourist destination. A qualitative and quantitative study was also conducted to test the proposed conceptual model. The study extends the SOR Theory with new and novel constructs in the context of tourism. It also lists managerial implications for travel agents and providers of tourism services to attract consumers endowed with a high environmentally sustainable attitude and self-consciousness. ? 2025 Informa UK Limited, trading as Taylor & Francis Group.