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The study explores the evolution of Indian domestic electronics manufacturing post-economic reforms and also investigates the lack of natural growth stages among Indian start-up/SME electronics manufactures.

The theoretical framework is inspired by Dawar and Frost's survival strategy theory that local companies may follow to overcome competitive threats from MNCs. The study adopts a qualitative methodology, more precisely, a phenomenological approach to walking through policy/regulatory reforms amid market distortions, technological gaps and colonial mindset from the perspective of Indian domestic electronics manufacturers. The study has adopted Gioia method of data analysis to inductively suggest a few research propositions.

The phenomenological approach revealed eight essential structure (essence) narratives to explore the complex issue that plague the industry: make in India, made in India, preferential market access strategy, equitable market access strategy, blue ocean strategy, competitive positioning strategy, technical capability and importance of policy/regulatory arbitrage.

The situation of Indian electronics manufacturing units is comparable to the bonsai tree situation, where natural evolution in business stages does not exist; they are born and die as start-ups/MSMEs. The study advocates for equitable market access by removing market distortions. The long-term solution may lie in making available locally manufactured products as a dependable alternative to the imported products or produced locally by MNC OEMs in terms of cost, quality, technology, volume, after-sale service and integrated supply chain.

While the favorable FDI policies, digital India and make-in India initiatives have strengthened domestic electronics production, it is yet to significantly impact India's position in global trade, including manufacturing and exports.

This study aims to identify the determinants of adopting financial technology (FinTech) in Haryana (India). Further, the authors also compare the behavioural intention among male and female respondents to deliver a comprehensive understanding of the adoption of FinTech.

The current study contains two cross-sectional surveys about males and females. Study M is completed with (333) males, and Study F is conducted on (317) female users towards FinTech adoption. This study used “Partial least squares-structural equation modelling (PLS-SEM)” for data analysis.

The outcomes indicate that in both (Studies M and F), perceived usefulness and perceived ease of use substantially impact attitude and behavioural intention. Moreover, the results show that perceived value significantly influences, while perceived risks insignificantly influence behavioural intention. Surprisingly, relative advantage (in Study M) and trialability (in Study F) has insignificant impact on behavioural intention. Further, the outcomes also confirm that in both studies (M and F), attitude and behavioural intention substantially influence the actual use of FinTech.

To the best of the authors’ knowledge, this is the preliminary research on FinTech to inspect the role of gender in the technology adoption process. The adoption difference between males and females and the insightful result that the authors found help shed light on the uniqueness of the context. This study is also one of the initial to test three credible technology determinant theories and then offer a robust model for the actual use of FinTech that is to be used by both practitioners and researchers.

The public distribution system (PDS) is an Indian food security system established to manage the distribution of food grains at affordable prices. As a result of the population explosion, the long-established PDS system finds it challenging to maintain operational efficiency, quality, trust and transparency. This paper explores the possibility of leveraging blockchain technology to overcome these operational hurdles.

Through a literature review and expert interactions, the present research identifies critical success factors in terms of enablers and barriers that influence the adoption of blockchain technology in PDS. Furthermore, we propose two independent interpretive structural models (ISM) and MICMAC to characterize these attributes.

The research identifies 15 distinct enablers and ten barriers that influence the diffusion of the latest technology in the sector at focus. The analyses disclose the interrelationships/dependencies among these enablers and between barriers, along with their individual driving power and dependence power.

The research showcases the importance of automating the system and illustrates how the features of blockchain technology can assist in augmenting stakeholder satisfaction levels. However, poor or nonexistent government regulations and patronage are found to be the major impediments to adoption. The research also delineates the cost implications of this barrier through its interrelationships with other barriers.

Interesting inferences are drawn from the models that offer actionable insights for the industry, government and technologists for improving PDS performance. Such interventions will ensure national food security through enhanced trust and transparency, which can further improve efficiency and effectiveness.

This study aims to explore differences in the usability of the Google Drive application based on demographic characteristics, computer skills and use frequency of Google Drive among public library users of Lahore.

The study adopted a quantitative approach and survey-based research method to achieve the study's objectives. The cloud usability model (user perspective) has been used as a theoretical lens to guide the study objectives. It comprises five dimensions of usability – capable, personal, reliable, valuable and secure.

The findings of the study revealed that the usability of Google Drive varied statistically significantly on the basis of depending on the respondents gender, age, academic qualification, computer skills and Google Drive use frequency.

It is a valuable study since it and adds knowledge to existing literature and has implications for practice.

The findings might be helpful for cloud support teams including Google Drive as they can notice the demographic and other differences among users' perceived usability of Google Drive and can enhance certain features of usability which leads attributes to increase its usage among users.

Globally, the governance has shifted from positivist to the regulatory-centric approach, necessitating accurate contouring of regulatory governance framework. The study proposes a novel approach to unravel the regulatory governance framework in the context of the Indian electronics industry – extendable to other sectors in India and other emerging economies.

The research objective has been operationalized through document analysis and thematic analysis of semi-structured interview transcripts in three steps: (1) arrive at parameters of the regulatory governance framework, (2) identify instruments against each parameter and (3) characterize parameters in terms of dominant instruments and their underlying modalities. The authors have adopted a set of 6 Cs modalities (control, communications, competition, consensus, code and collaboration) and regulatory space theory to analyze existing modalities mix in the dominant instruments.

In summary, the study has (1) identified eight macro and twenty micro regulatory governance parameters, (2) mapped regulatory governance parameters with instruments and institutions (3) revealed the top two dominant modalities for each regulatory governance parameter.

The existing modality characteristics of regulatory governance parameters can be used by manufacturers, investors and other stakeholders to make a realistic assessment of regulatory governance and reduce regulatory risk and regulatory burden.

The multidimensional use of parameters, instruments and modalities broadens the understanding of the existing regulatory governance framework and may assist the regulators in optimizing it to meet market requirements.

The purpose of this study is to increase awareness of current supply chain (SC) security-related issues by providing an extensive analysis of existing SC security solutions and their limitations. The security of SCs has received increasing attention from researchers, due to the emerging risks associated with their distributed nature. The increase in risk in SCs comes from threats that are inherently similar regardless of the type of SC, thus, requiring similar defence mechanisms. Being able to identify the types of threats will help developers to build effective defences.

In this work, we provide an analysis of the threats, possible attacks and traceability solutions for SCs, and highlight outstanding problems. Through a comprehensive literature review (2015–2021), we analysed various SC security solutions, focussing on tracking solutions. In particular, we focus on three types of SCs: digital, food and pharmaceutical that are considered prime targets for cyberattacks. We introduce a systematic categorization of threats and discuss emerging solutions for prevention and mitigation.

Our study shows that the current traceability solutions for SC systems do not offer a broadened security analysis and fail to provide extensive protection against cyberattacks. Furthermore, global SCs face common challenges, as there are still unresolved issues, especially those related to the increasing SC complexity and interconnectivity, where cyberattacks are spread across suppliers.

This is the first time that a systematic categorization of general threats for SC is made based on an existing threat model for hardware SC.

The main aim of this study is to understand the role of smart technologies and show the rankings of various smart technologies in collection and classification of electronic waste (e-waste).

This study presents a framework integrating the concepts of collection and classification mechanisms and smart technologies. The criteria set includes three main, which are economic, social and environmental criteria, including a total of 15 subcriteria. Smart technologies identified in this study were robotics, multiagent systems, autonomous tools, smart vehicles, data-driven technologies, Internet of things (IOT), cloud computing and big data analytics. The weights of all criteria were found using fuzzy analytic network process (ANP), and the scores of smart technologies which were useful for collection and classification of e-waste were calculated using fuzzy VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR).

The most important criterion was found as collection cost, followed by pollution prevention and control, storage/holding cost and greenhouse gas emissions in collection and classification of e-waste. Autonomous tools were found as the best smart technology for collection and classification of e-waste, followed by robotics and smart vehicles.

The originality of the study is to propose a framework, which integrates the collection and classification of e-waste and smart technologies.

Waste generated from electrical and electronic equipment, collectively known as E-waste, remains a persistent environmental, economic and social problem. Sustainable E-waste management (EWM) has numerous benefits, such as preventing electronic waste from entering landfills, reducing the need for virgin materials by recovering valuable materials from recycling and lowering greenhouse gas emissions. Circular economy (CE) practices are considered the initial steps toward sustainable EWM, but some hurdles have been reported in the adoption of these practices. Therefore, the current study aims to identify the common CE practices, sustainability of the EWM process and the challenges in EWM, and to develop a conceptual framework for effective EWM.

Very few studies have proposed frameworks that acknowledge the challenges and CE practices of EWM. To fill this gap, a systematic literature review (SLR) was performed, and 169 research articles were explored.

A total of seven challenges in the adoption of effective EWM were identified: rules and policy, infrastructure, consumer behaviour, informal sectors, community culture, technology and economy. Eight common CE practices were also found for effective EWM: reuse, recycle, remanufacturing, refurbishment, repair, reduce, recover and repurpose.

A conceptual framework guiding sustainable EWM was proposed, which includes solutions for the identified challenges, and CE practices with sustainable benefits.

The main aim of this study is to review different aspects of Industry 5.0 (I5.0) along with Kaizen measures to foster this novel aspect of industrial sustainability. The study makes a comprehensive study to explore the implementation status of I5.0 in industries, key technologies, adoption level in different nations and barriers to I5.0 adoption together with mitigation actions.

To do a systematic study of the literature, the authors have used preferred reporting items for systematic reviews and meta-analysis (PRISMA) methodology to extract articles related to the field of the study.

It has been found that academic literature on the I5.0 is continuously growing as the wheel of time is running. Most of the studies on I5.0 are conceptual-based, and manufacturing and medical industries are the flag bearer in the adoption of this novel aspect. Further, due to I5.0's infancy, many organizations face difficulty to adopt the same due to financial burden, resistive nature, a well-designed standard for cyber-physical systems (CPS) and an effective mechanism for human–robot collaboration. Further studies also provide avenues for future research in terms of the identification of collaborative mechanisms between machines and wells, the establishment of different standards for comparison and the development of I5.0-enabled models for different industrial domains.

The study is the first of its kind that reviews different facets of I5.0in conjunction with Kaizen's measures and application areas and provides avenues for future research to improve an organization's environmental and social sustainability.

The focus is on determining the long-term relationship in explaining how technological capabilities interact with trade and global value chain (GVC) participation to aid in the upgradation process using a panel auto-regressive distributed lag (ARDL) model. The results suggest that export of both low-skill and medium-skill technology-intensive manufactures and patents by residents positively and significantly impact GVC participation.

This paper examines the dynamic linkages between GVC participation and technological capability of major Asian countries in a comparative (1995–2018) perspective.

This implies that certain sectors enable greater integration into GVCs in the long-run, supported by critical learning variables. Further, with the help of the panel causality test, a bi-directional flow between GVC participation and export of high-technology manufactures and import of labour-intensive technology manufactures is witnessed. Even a one-way flow from research and development (R&D) intensity to GVC participation is seen.

The technological capabilities are found to be characterising the initial structure of local enterprises in trade and GVCs, as well as the extent to which emerging-market firms may harness knowledge flows and migrate into high-tech industries.