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India’s rapid economic growth has triggered a significant transformation in its logistics sector, fueled by comprehensive reforms and digital initiatives outlined in the National Logistics Policy. Smart warehouses, equipped with cutting-edge technologies such as IoT, AI and automation, have taken center stage in this evolution. They play a pivotal role in India’s digital journey, revolutionizing supply chains, reducing costs and boosting productivity. This AI-driven transformation, in alignment with the “Digital India” campaign, positions India as a global logistics leader poised for success in the industry 4.0 era. In this context, this study highlights the significance of smart warehouses and their enablers in the broader context of supply chain and logistics.

This paper utilized the ISM technique to suggest a multi-tiered model for smart warehouse ecosystem enablers in India. Enablers are also graphically categorized by their influence and dependence via MICMAC analysis.

The study not only identifies the 17 key enablers fostering a viable ecosystem for smart warehouses in India but also categorizes them as linkage, autonomous, dependent and independent enablers.

This research provides valuable insights for practitioners aiming to enhance technological infrastructure, reduce costs, minimize wastage and enhance productivity. Moreover, it addresses critical academic and research gaps contributing to the advancement of knowledge in this domain, thus paving the way forward for more research and learning in the field of smart warehouses.

The qualitative modeling is done by collecting experts' opinions using the ISM technique solicits substantial value to this research.

In this chapter, I illustrate the use of visual ethnography to uncover the nuanced role of informal processes and structures, henceforth referred to as informality, in navigating the complex challenges of water governance in India through enabling repair. By repair, I refer to the ability of informality to act as a transformative approach, adept at navigating and addressing the multifaceted governance challenges faced by Indian cities. The mapping of informality in repair within urban water governance uncovered three dilemmas: 1) the difficulty of documenting transient oral narratives, 2) the discrepancies between verbal accounts and observed practices and 3) ethical concerns associated with documenting illicit activities. To address these dilemmas, I coupled ethnographic approaches with photographic methods. Ethnography provided reflection, clarity and a documented record, although it introduced a delay in capturing observations. Photographic methods compensated for this by offering an immediate visual record and facilitating live analysis alongside textual notes. I outline five routines of conducting visual ethnography, applied in the cities of Bhopal and Bhuj, to shed light on how various actors enact informality in addressing the gaps within urban water governance. These routines served as a photographic praxis to critically engage with both human and non-human actors in these locales. Through these routines, I illustrate how informality results in two types of repairs: reactive and reparative. Reactive repair serves as a temporary measure to restore the status quo. In contrast, reparative repair aims at fostering long-term change, illustrating the dynamic ways in which informality contributes to repairing the intricacies of water governance in India.

The purpose of this paper is to covenant with the cost assessment of a complex repairable system, consisting of two subsystems (Subsystem 1 and Subsystem 2) connected in series configuration and being operated by a human operator. Each subsystem has two identical units in parallel configuration and has different types of failure and two types of repairs (general repair and copula repair). Through the transition diagram, the system of first-order partial differential equations is derived and solved using a supplementary variable technique, Laplace transforms. All failures are assumed to follow exponential distribution, whereas repairs follow two types of distributions that are general and Gumbel–Hougaard family copula. In this paper, explicit expressions for reliability, availability, mean time to failure (MTTF) and cost analysis functions have been obtained. In this paper, two types of repairs (copula repair and general repair) have been studied, and it has been concluded that copula repair is more reliable as compared to general repair. Some computations are taken as particular case by evaluating: reliability, availability, MTTF and cost analysis, so as to capture the effect of both failure and repair rates to reliability measures. The results have been shown in tables and graphs. The convincing part has been discussed in last section of this study.

This paper is focused on the cost assessment of a system consisting two subsystem series configuration. Each subsystem has two identical units in parallel configuration. The performance of the system has been analyzed by supplementary variable techniques and Laplace transforms. Various measures of the reliability have been discussed by evaluations. Software called Maple 13 is used for computations.

In this research paper, the authors have evaluated the operational cost and incurred profit of the system together with other reliability measures for various situations and different types of failures and two types of repairs using Gumbel–Hougaard family copula distribution.

The present research focuses on the series and parallel configured complex systems that is used everywhere in industry and other sectors. The authors main aim is to claim that repair through the joint probability distribution copula is far better than general repair. Copula repair for a completely failed system is more beneficial for industrial system operations that will increase profit to the industrial sector.

The authors have observed that when repair follows general distribution the values of reliability obtained of the system are less compared to the those obtained when the authors apply copula repair, a joint probability distribution. It is a clear implication for industrial sector and organization to use the policy for a better generate revenue.

According to the best of authors’ knowledge, there is no social implication as this study is meant for reliability section. The study in management and case study matters is considered to have social implication.

This research is the original work of authors. Nothing has been copied from any paper or book. The references are cited according to the relevance of study.

This study aims to determine the factors that influence payment Fintech application adoption intention among low-income groups in India.

This study used an expanded technology acceptance model (TAM; covering perceived usefulness, perceived ease of use, social influence, perceived risk and financial literacy), which was tested using 310 low-income respondents in Northern India. The PLS-SEM approach was used to analyse the data.

The results indicate that perceived usefulness, perceived ease of use, social influence and financial literacy all has a direct positive relationship with the intention to use Fintech. Furthermore, financial literacy was found to be the moderator in moderating the relationship between social influence and intention to use the Fintech app.

This study ameliorates existing research and deepens the authors’ understanding of users’ intentions to use Fintech among low-income groups. The findings of the study help both policymakers and academicians in designing effective strategies for promoting Fintech usage.

This study examines the factors that determine Fintech application adoption, particularly among low-income individuals. The TAM framework was expanded to include perceived risk and financial literacy as two of the factors influencing Fintech adoption. Furthermore, the moderating role of financial literacy on intention to use Fintech app was considered in this study in the context of a developing country such as India.

This paper aims to explore the key drivers of a resilient supply chain for the Indian pharmaceutical industry for enhanced and sustainable export pursuits in a disruptive business time.

This study literarily identifies the key drivers of supply chain resilience in the Indian pharmaceutical industry and methodologically appraises, analyzes and assesses them to derive a structural model that catalytically acts as facilitators and drivers for enhanced export performance. By reviewing relevant literature, it identifies research and development (R&D), procurement and sourcing, manufacturing, distribution and reverse logistics factors. It collects Likert scale feedback from stakeholders and probes interrelationships among them in achieving the enhanced export performance of India’s pharmaceutical sector.

The results lucidly identify the key enablers affecting the export performance of India’s pharmaceutical sector. These primarily include developing excellence in manufacturing, reverse logistics and distribution. Furthermore, sourcing and R&D are the antecedents of manufacturing expertise, catalytically contributing to improved export outcomes. Based on the derived structural model, the interrelationships are evaluated to explore causal links in achieving supply chain resilience and simultaneously elucidating the managerial and socio-economic interventions.

Narrating the results, this paper scholarly identifies the key drivers that need to be factored in for enhanced export outcomes of India’s pharmaceutical sector. The paper explains how to achieve supply chain resilience for export performance in India’s pharmaceutical sector.

Unlike many existing methods that are primarily focused on two-dimensional localization, this research paper extended the scope to three-dimensional localization. This enhancement is particularly significant for unmanned aerial vehicle (UAV) applications that demand precise altitude information, such as infrastructure inspection and aerial surveillance, thereby broadening the applicability of UAV-assisted wireless networks.

The paper introduced a novel method that employs recurrent neural networks (RNNs) for node localization in three-dimensional space within UAV-assisted wireless networks. It presented an optimization perspective to the node localization problem, aiming to balance localization accuracy with computational efficiency. By formulating the localization task as an optimization challenge, the study proposed strategies to minimize errors while ensuring manageable computational overhead, which are crucial for real-time deployment in dynamic UAV environments.

Simulation results demonstrated significant improvements, including a channel capacity of 99.95%, energy savings of 89.42%, reduced latency by 99.88% and notable data rates for UAV-based communication with an average localization error of 0.8462. Hence, the proposed model can be used to enhance the capacity of UAVs to work effectively in diverse environmental conditions, offering a reliable solution for maintaining connectivity during critical scenarios such as terrestrial environmental crises when traditional infrastructure is unavailable.

Conventional localization methods in wireless sensor networks (WSNs), such as received signal strength (RSS), often entail manual configuration and are beset by limitations in terms of capacity, scalability and efficiency. It is not considered for 3-D localization. In this paper, machine learning such as multi-layer perceptrons (MLP) and RNN are employed to facilitate the capture of intricate spatial relationships and patterns (3-D), resulting in enhanced localization precision and also improved in channel capacity, energy savings and reduced latency of UAVs for wireless communication.

The purpose of this paper is to evaluate performance of mobile communication system with reliability measures.

The mobile communication system consists of a mobile station (MS), base transceiver station (BTS), base station controller (BSC) and the mobile switching center. The MS is connected to BTS, BTS is connected to BSC and BSC is connected with the mobile switching system. With the help of these stations working, the authors have developed a mathematical model using Markovian approach.

Using the supplementary variable technique, the Laplace transformations and Markov process theory, the reliability indices of the mobile communication system are determined.

In the present work, the authors have developed a mathematical model based on a mobile communication system.

This paper attempts to elucidate the fundamental determinants—both enablers and impediments—that shape a resilient business ecosystem for the medical devices sector in India, with a particular emphasis on sustainable export endeavours under the ambit of the Medical Devices Policy 2023.

This study dives into India’s medical device export firms, analysing factors influencing their performance. By reviewing relevant literature, it identifies regulatory, manufacturing, marketing, distribution and import-related factors. A Likert scale questionnaire was designed and shared with industry stakeholders to gather primary data, and it was analysed via SPSS/AMOS. This quantitative approach unveiled the direct impacts of enablers and barriers, shaping a structural model to elucidate interrelationships, thus informing strategies for enhancing India’s medical device export sector.

The results lucidly identify the barriers that affect the export performance of India’s medical devices, such as complicated product registration formalities, complexity in the registration and approval process for sale, export restrictions and price control measures, local competition and policies, finance and investment challenges and low knowledge and expertise in the trade of medical devices. Considering the relevance of these barriers in affecting India’s export achievement, a model is derived for understanding their interrelationship, exploring causal links and comprehending managerial and policy-level implications for suitable corrective actions.

The study’s limitations must be recognized, notably the focus on India and the Medical Devices Policy 2023 context. Accordingly, the results hinge on India’s “Make-in-India” policy and incentives for the medical devices sector, possibly not translating directly to countries with distinct policies or industrial priorities. With a sample size of 224 firms, sector diversity representation may be inadequate, potentially restricting the findings’ generalizability. While offering insights into Indian challenges and opportunities, broader validation across diverse contexts and larger samples is essential to ensure the results’ robustness and broader applicability beyond outlined circumstances.

The model’s insights hold crucial implications for policymakers in India’s medical devices sector. Firstly, urgent attention is required to tackle identified challenges for sustainable export growth. Prioritizing initiatives to enhance sector knowledge and expertise through training programs and collaborations with experts is paramount. Moreover, streamlining regulatory barriers, including product registration and approval processes, are imperative for simplifying market entry. Additionally, addressing financial challenges by facilitating access to finance through tax incentives or funding schemes is essentially vital. Furthermore, learning from successful models in other countries like Costa Rica, South Korea, Germany and China can guide effective policy implementation in an Indian context. Correspondingly, the business firms should nurture a competitive domestic market through innovation support and stakeholder engagement for long-term growth.

For managers in India’s medical devices sector, these implications are equally significant. Investing in knowledge and regulatory expertise is paramount to navigate complex landscapes effectively. Accordingly, there is a need to develop robust financial planning strategies, exploring diverse funding sources and tailoring products to meet local demands while aligning with global standards. Moreover, active engagement with policymakers is required for supportive policy reforms and similarly, collaboration with industry stakeholders can create a favourable operating environment. By addressing these implications collaboratively, policymakers and managers can overcome barriers, drive innovation and foster sustainable growth, positioning India as a global leader in medical device exports.

Narrating the results, this paper identifies the barriers that need to be factored into the Medical Devices Policy 2023. The paper sequentially explains how to nurture an enabling business ecosystem for export excellence in India’s medical devices industry.

This study aims to explore the association of board quality and firm innovation on climate risk disclosure in the context of large listed companies in India. It builds upon the framework developed by the stakeholder theory and the legitimacy theory to examine the association between the key variables of the study.

The climate risk disclosure is measured through content analysis of the annual reports of the respective companies. A panel data framework analyzes the relationship between board quality, firm innovation and climate risk disclosure.

The findings indicate a gradual increase in climate risk disclosure throughout the sample period. This study also finds that certain board characteristics and investment in innovation are significant determinants of a firm’s approach toward identifying and mitigating risks arising from rapid climate change. This study has implications for practitioners, policymakers and academicians who strive toward creating resilient and sustainable organizations.

This study is relevant for practitioners as it identifies an increasing trend in the identification and reporting of climate risk disclosure in the sample firms. This would be beneficial for managers and other stakeholders of the organizations who would be interested in the mitigation of climate risk. The organizational leadership may identify key parameters of their firms, which helps them prepare against the adverse impact of climate change on business.

To the best of the authors’ knowledge, this is the first study to evaluate climate risk disclosure practices of large listed companies in India. This study highlights how large Indian companies are developing an overall approach for identifying and mitigating risks associated with rapid climate change, which has not been conducted for any economy.

The current study employs a modified framework of the unified theory of acceptance and use of technology (UTAUT) to predict students' intention to adopt online learning in India. The moderating role of openness to change in influencing the proposed relationships is also assessed.

A structured questionnaire was emailed to 650 students enrolled in various courses in public and private universities in India. In total 424 responses were considered for analysis using structural equation modeling (SEM). Moderation analysis was carried out with multi-group SEM and chi-square difference tests.

The results reveal that there is a significant impact of performance expectancy (PE), effort expectancy (EE), social influence (SI), facilitating conditions (FS) and perceived security (PS) on students' intention to adopt online learning. Further, openness to change moderates the impact of PE, FS and PS on intention of students to opt for online learning.

This study is one of the initial efforts to examine the factors affecting students' intention to adopt online learning at the onset of third wave of coronavirus disease 2019 (COVID-19) pandemic in India. Besides the factors of the UTAUT model, this study highlights the importance of PS and openness to change in influencing students' intention to opt for online learning.