Identifying Enablers and Challenges of Electric Vehicle Adoption: A Comprehensive Review of the Literature

Abstract

There is global pressure to increase the adoption of Electric Passenger Vehicles (EPVs), as electric cars sold in 2024 accounted for 22%, whereas in India, adoption was only 2% in 2024. Several United Nations Sustainable Development Goals (7, 9, 11, 12, and 13) highlight the importance of clean energy and climate actions, and Electric Vehicles (EVs) play a key role in meeting these targets by promoting a sustainable and environmentally friendly future. However, in recent times, the adoption of EVs in India has raised concerns despite growing interest in sustainable mobility. Any new technology in its initial stage has a low market share. To increase adoption, it is essential to study the key factors that affect consumer usage intention. A conceptual framework is proposed linking these enablers and challenges to consumer usage intention. It is necessary to understand these factors for widespread EV acceptance.

Introduction

Log inSign up for free

1. You said:

   Summarize of the text: The Jaisalmer basin a pericratonic shelf basin, well known for its well-exposed fossiliferous sedimentary successions of Mesozoic period (Pandey et al. 2022). The basin attracts considerable attention from geoscientists because of the diverse and well-preserved features of its Jurassic succession. These include abundant marine fossils, well-developed sedimentary successions, well-preserved primary and secondary sedimentary structures, dinosaur footprints etc. (Kalia & Chowdhury l983; Pandey & Fürsich 1994; Mukherjee 2009, 2010, 2017; Pandey et al. 2009a, 2009b, 2014, 2018a; Sharma & Pandey 2016; Alberti et al. 2017). The Mesozoic successions overlying the Precambrian basement rocks (Fig. 1.) of the Jaisalmer grouped into six formations (Lathi, Jaisalmer, Baisakhi, Bhadasar, Pariwar and Habur formations). Sediments of the Jaisalmer basin displays the variation in depositional environment, begin with non-marine fluvial, deltaic, and lacustrine deposits (representing the basal part of the Lathi Formation), followed by marginal marine sediments, and subsequently a sequence of alternating non-marine, marginal marine, and fully marine deposits ranging from terrestrial siliciclastic to marine carbonate deposits (Pareek 1984, Das Gupta, 1975, Mahendra & Banerji 1989, Fürsich et al. 1992, Pandey et al. 2005, 2006 a, b, c). Fig. 1 Geological map of the Jaisalmer Basin (modified after Das Gupta 1975) and study area ( ) Lithostratigraphically, Jurassic sediments of the Jaisalmer Basin have been grouped into four formations: Lathi, Jaisalmer, Baisakhi, and Bhadasar (Fig. 2). The Jaisalmer Formation is a predominantly calcareous and highly fossiliferous Jurassic unit that contains diverse ammonites, brachiopods, bivalves, gastropods, echinoids, crinoids, bryozoans, and corals. The age of the Jaisalmer Formation ranges from the Bajocian to the Oxfordian, and it has long served as a key succession for both palaeontological and sedimentological studies, as well as for interbasinal correlation with the adjacent Kachchh Basin (Swaminathan et al., 1957; Pandey and Fürsich, 1994). Because of its rich fossil content and well-preserved stratigraphic record, the formation provides an excellent framework for studying depositional history, faunal succession, and marine transgressive events in western India. Within the Jaisalmer Formation, the Bathonian–Callovian interval is represented by the Fort, Bada Bag, and Kuldhar members. Bathonian Callovian sediments exposed along the kuldhar river section has been assigned bada bagh and kuldhar members. Fig. 2 Lithostratigraphic framework of the Jurassic strata of the Jaisalmer Basin (modified after Das Gupta, 1975; Alberti et al., 2017). In the present paper, twenty-one thin sections prepared which is collected from two locations at Kuldhar river section in the western part of the Jaisalmer basin. Carbonate succession examined in this study corresponds to the bada bag nad Kuldhar Member of the Jaisalmer Formation, deposited during the Middle Jurassic in the Jaisalmer Basin (Fig. 2). II. MATERIAL AND METHODS The Bathonian Callovian sediments exposed along kuldhar river section in the western part of Jaisamer basin, measured bed by bed at centimeter scale. After collection of rock samples thin section of well-cemented rocks were prepared in laboratory for petrographic study. Thin section of 21 thin samples have been prepared and studied. For the petrographic analysis, the classification schemes for carbonate rocks proposed by Folk (1959), Dunham (1962), Embry and Klovan (1971), and James (1984) were integrated and applied. For carbonate petrography, the classification proposed by Folk (1962) is considered appropriate, as it is based on the visual estimation of the relative proportions of allochems; therefore, it has been adopted in this study. For petrography of the thin sections was carried out using Nikon petrological microscope (Nikon Eclipse E200) and Nikon E8400.

2. ChatGPT said:

   Summary

   The Jaisalmer Basin, a pericratonic shelf basin in western India, is renowned for its well-exposed and fossil-rich Mesozoic sedimentary successions, particularly the Jurassic strata. Its importance stems from the abundance of marine fossils, well-preserved sedimentary structures, diverse depositional environments, and dinosaur footprints, making it an important area for palaeontological, sedimentological, and stratigraphic research.

   The Mesozoic succession of the basin rests on Precambrian basement rocks and records a progressive change in depositional environments. Sedimentation began with non-marine fluvial, deltaic, and lacustrine deposits, followed by marginal-marine conditions and eventually alternating terrestrial, marginal-marine, and fully marine environments. The Jurassic succession is divided lithostratigraphically into four formations: Lathi, Jaisalmer, Baisakhi, and Bhadasar.

   The Jaisalmer Formation is a predominantly calcareous and highly fossiliferous unit ranging from the Bajocian to Oxfordian. It contains a diverse assemblage of ammonites, brachiopods, bivalves, gastropods, echinoids, crinoids, bryozoans, and corals. The formation is important for reconstructing depositional history, faunal succession, marine transgression, and regional correlation, particularly with the Kachchh Basin.

   The Bathonian–Callovian interval of the Jaisalmer Formation comprises the Fort, Bada Bag, and Kuldhar members. The present study focuses on the carbonate succession of the Bada Bag and Kuldhar members, exposed along the Kuldhar River section in the western Jaisalmer Basin.

   Materials and Methods

   For the study, 21 rock samples were collected from two locations along the Kuldhar River section. The succession was measured bed-by-bed at centimetre scale, and thin sections were prepared from well-cemented carbonate rocks for petrographic analysis. Carbonate rocks were classified using established schemes of Folk (1959, 1962), Dunham (1962), Embry and Klovan (1971), and James (1984). The Folk (1962) classification was primarily adopted because it is based on the relative proportions of allochems. Petrographic observations were carried out using Nikon Eclipse E200 and Nikon E8400 petrological microscopes.

   In short: The study investigates the petrography and carbonate characteristics of Bathonian–Callovian rocks of the Bada Bag and Kuldhar members of the Jaisalmer Formation, using 21 thin sections from the Kuldhar River section to better understand the nature and depositional history of these Middle Jurassic carbonate sediments.

    

3. You said:

   Summarize of the text: Software development is a core discipline of Information Technology that converts ideas and user requirements into working digital solutions. From a simple calculator application to a large banking platform, software is built to perform tasks, process information, automate work, and support decision-making. The rapid growth of the internet and smart devices has made software an essential part of personal, educational, commercial, and public activities.A software project normally begins with a problem or requirement. Developers and stakeholders discuss what users need, what the system should accomplish, and what limitations exist. The team then plans the work, designs the solution, develops the program, tests it, releases it, and maintains it. This organized approach reduces risk and improves software quality. II. DEFINATION AND OBJECT Software development is also a collaborative activity. Programmers work with analysts, designers, testers, database specialists, project managers, security professionals, and operations teams. Effective communication among these roles is important because software quality depends not only on technical code but also on correct requirements, good design, usability, security, and maintainability. Software development can be defined as a systematic process of designing, programming, testing, deploying, and maintaining software according to specified requirements. The process aims to create a product that solves a real problem and provides value to its users. The main objectives of software development are to satisfy user requirements, produce reliable results, improve efficiency, reduce repetitive manual work, protect information, and make services easier to access. A good software system should also be maintainable so that developers can correct defects and introduce improvements over time. Another important objective is scalability. A small application may initially have only a few users, but a successful system may later need to support thousands or millions of users. Developers therefore consider performance, architecture, databases, security, and infrastructure during the design stage. III. SOFTWARE DEVELOPMENT LIFE CYCLE The Software Development Life Cycle (SDLC) provides a structured framework for developing software. Although organizations may use different names or combine activities, the common stages are requirements, planning, design, coding, testing, deployment, and maintenance. IV. REQUIREMENT ANALYSIS Requirement analysis identifies what the software must do. Developers and analysts communicate with customers, users, managers, and other stakeholders to collect functional and non-functional requirements. Functional requirements describe the actions the system should perform. For example, a college management system may need to register students, record attendance, store marks, and generate reports. Non-functional requirements describe qualities such as performance, security, reliability, usability, and availability. Clear requirements are important because errors in requirements can become expensive to correct later. Teams often document requirements in a specification and review them with stakeholders before development begins. V. PLANNING AND SYSTEM DESIGN Requirement analysis identifies what the software must do. Developers and analysts communicate with customers, users, managers, and other stakeholders to collect functional and non-functional requirements. Functional requirements describe the actions the system should perform. For example, a college management system may need to register students, record attendance, store marks, and generate reports. Non-functional requirements describe qualities such as performance, security, reliability, usability, and availability. Clear requirements are important because errors in requirements can become expensive to correct later. Teams often document requirements in a specification and review them with stakeholders before development begins. VI. CODING AND PROGRMMING Coding is the implementation stage in which developers convert the system design into source code. The programming language and tools are selected according to the application's requirements. Python is widely used for automation, data science, artificial intelligence, and web applications. Java is used for many enterprise and application-development scenarios. C and C++ are important for systems and performance-oriented software, while JavaScript is central to modern interactive web development. Professional coding involves more than making a program work once. Developers use meaningful names, modular structures, comments where useful, version control, code review, and testing. Good coding practices make defects easier to locate and make future changes safer. Version control systems allow teams to record changes to source code and collaborate without losing earlier versions. Branching and merging workflows can help multiple developers work on different features while maintaining an organized project history. VII. SOFTWARE TESTING AND QUALITY A. Assurance Testing is a critical activity used to determine whether software behaves as expected. Testers and developers identify defects, verify requirements, and evaluate performance, usability, compatibility, and security. Testing can begin early in the development process instead of waiting until the entire application is completed.Unit testing checks individual modules or functions. Integration testing verifies that components work correctly together. System testing evaluates the complete application. Acceptance testing checks whether the software satisfies business or user expectations.Quality assurance is broader than testing. It includes processes and practicesintended to prevent defects and improve the overall development process. Automated tests can be executed repeatedly and are especially useful when software is changed frequently. Figure 3: Common levels of software testing. VIII. SOFTWARE DEVELOPMENT MODELS A software development model describes how development activities are organized. The Waterfall Model follows a sequential structure in which one major phase is completed before the next. It can be easy to understand and useful when requirements are stable, but late changes may be difficult. The Agile approach emphasizes short development cycles, frequent feedback, collaboration, and continuous improvement. Work is often divided into small increments so that useful features can be delivered and reviewed regularly. DevOps extends collaboration across development and operations. It encourages automation, continuous integration, continuous delivery, monitoring, and rapid feedback. DevOps can reduce the time between writing code and delivering reliable software to users. Figure 4: Three widely discussed approaches to organizing IX. DEVOPS AND CONTINUOUS DELIVERY DevOps brings development and operations practices closer together. Instead of treating software creation and software peration as completely separate activities, teams collaborate across the delivery lifecycle. Automation is commonly used for building, testing, releasing, deploying, and monitoring applications. Continuous integration encourages developers to integrate changes frequently and run automated checks. Continuous delivery keeps software in a releasable state so that validated changes can be delivered efficiently. Monitoring provides information about performance, errors, availability, and user experience after deployment. Figure 5: A simplified DevOps continuous delivery cycle. X. CYBERSECURITY IN SOFTWARE DEVELOPMENT Security must be considered throughout the software lifecycle. Applications may process personal information, financial records, passwords, business data, and other sensitive information. Weak security can lead to unauthorized access, data loss, service disruption, or financial damage. Secure software development includes threat analysis, secure coding, strong authentication, authorization, input validation, encryption where appropriate, dependency management, logging, security testing, and timely updates. Developers should also avoid storing sensitive information unnecessarily and should follow the security requirements relevant to their application. Figure 6: Security activities can be integrated across the software lifecycle. Security is most effective when it is built into the development process rather than added at the final stage. Regular testing and monitoring help teams identify new risks as technologies and threats change.

4. ChatGPT said:

   Summary

   Software development is a core discipline of Information Technology that transforms user needs and ideas into functional digital solutions. It is used in applications ranging from simple calculators to large banking and enterprise systems. A software project generally follows a structured process involving requirements, planning, design, coding, testing, deployment, and maintenance.

   Definition and Objectives

   Software development is a systematic process of designing, programming, testing, deploying, and maintaining software according to specified requirements. It is a collaborative activity involving programmers, analysts, designers, testers, database specialists, project managers, security professionals, and operations teams.

   The main objectives are to:

   • Meet user requirements and solve real-world problems.

   • Produce reliable and efficient software.

   • Reduce repetitive manual work.

   • Protect information and improve accessibility.

   • Ensure maintainability and future improvement.

   • Support scalability as the number of users and amount of data increase.

   Software Development Life Cycle (SDLC)

   The Software Development Life Cycle (SDLC) provides a structured framework for software development. Its major stages include requirement analysis, planning, system design, coding, testing, deployment, and maintenance.

   Requirement Analysis

   Requirement analysis determines what the software should accomplish. Requirements are generally divided into:

   • Functional requirements: Describe what the system should do, such as registering students, recording attendance, and generating reports.

   • Non-functional requirements: Describe qualities such as performance, security, reliability, usability, and availability.

   Clear and well-documented requirements help prevent costly mistakes during later stages.

   Planning and System Design

   After requirements are identified, the development team plans the project and designs the software architecture, database, interfaces, and overall system structure. Good planning and design provide a foundation for developing software that is efficient, secure, maintainable, and scalable.

   Coding and Programming

   Coding converts the system design into source code. Common programming languages include Python, Java, C, C++, and JavaScript, with each being suitable for different applications. Professional programming involves modular code, meaningful naming, appropriate comments, version control, code reviews, and testing. Version control also enables multiple developers to collaborate while maintaining a history of changes.

   Software Testing and Quality Assurance

   Testing verifies that software works correctly and satisfies its requirements. Major levels of testing include:

   • Unit testing: Tests individual functions or modules.

   • Integration testing: Checks whether different components work together.

   • System testing: Evaluates the complete application.

   • Acceptance testing: Determines whether the system meets user or business expectations.

   Quality assurance (QA) is broader than testing and focuses on improving development processes and preventing defects. Automated testing is particularly useful for projects that undergo frequent changes.

   Software Development Models

   Different models organize development activities in different ways:

   • Waterfall: Uses a sequential process and is suitable when requirements are stable, but changes can be difficult later.

   • Agile: Uses short development cycles, continuous feedback, collaboration, and incremental delivery.

   • DevOps: Combines development and operations, emphasizing automation, continuous integration, continuous delivery, monitoring, and rapid feedback.

   DevOps and Continuous Delivery

   DevOps promotes close cooperation between development and operations teams. Automation is commonly used for building, testing, releasing, deploying, and monitoring software. Continuous integration allows frequent code integration and automated testing, while continuous delivery keeps software ready for reliable release. Monitoring helps teams identify performance problems, errors, availability issues, and user-experience concerns.

   Cybersecurity in

    

5. You said:

   Summarize of the text: Electronic waste (e-waste) presents an escalating global environmental and public-health challenge driven by increasing generation, inadequate collection, environmentally unsound processing, and premature loss of product and component value [1], [2], [15]. The Global E-waste Monitor reports that 62 million tonnes of e-waste were generated in 2022, with only 22.3% formally documented as collected and recycled [1]. This formal recycling indicator does not capture all flows of used electrical and electronic equipment and e-waste. Global monitoring also identifies substantial transboundary movement of used equipment and e-waste, including flows through uncontrolled channels into middle- and low-income regions [1], [28]. In developing nations such as India, historical studies indicate that a substantial proportion of e-waste has been handled through informal channels, although estimates vary according to the period, geographical boundary, and analytical method [29], [31]. Informal processing may involve manual dismantling, open burning, uncontrolled thermal treatment, acid leaching, and open dumping, creating exposure pathways for workers, communities, and the surrounding environment [2], [3]. Such practices can also favour rudimentary material-recovery routes and may reduce opportunities for controlled assessment of equipment and components for reuse or refurbishment [29]. Improving the conditions under which retired equipment is collected, stored, assessed, and routed is therefore important not only for pollution control but also for preserving equipment that may remain suitable for preparation for reuse [16]. The condition of equipment before technical assessment is therefore an important part of the reuse pathway. Messmann et al. [16] found that 86% of identifiable damage causes of WEEE in the investigated Bavarian collection-point system were associated with insufficient weatherproof roofing. This finding is specific to the investigated system and does not imply that 86% of all WEEE damage is weather-related; rather, it provides evidence that avoidable deterioration during collection and storage can affect the pool of equipment available for preparation for reuse. Electronic devices are frequently retired for administrative, economic, technological, or procurement reasons before all of their potential functional value has been exhausted [6], [7]. This creates a distinction between the end of a device's first ownership or service cycle and the end of the useful life of its components. A retired computer, for example, may remain suitable for secondary deployment after appropriate diagnostic assessment, while equipment that is unsuitable for whole-device reuse may still contain recoverable modules or individual components [7], [8], [11], [12]. International functionality studies provide further evidence that technical retirement does not necessarily correspond to complete loss of functional value. Physical inspection of used electrical and electronic equipment entering Lagos found approximately 81% of tested equipment to be functional [24]. A separate Delphi-based study reported an expert guesstimate that 63% of imported UEEE was functioning and directed toward reuse, refurbishment, or resale [5]. These values should not be transferred directly to India or treated as recovery coefficients because they were obtained from different populations and through different assessment methods. The appropriate circular strategy is therefore not to assume that all discarded equipment should be reused, but to establish a qualification process that identifies technically, economically, and operationally suitable assets before material recovery is undertaken. This distinction is particularly important for printed circuit boards (PCBs), which contain both valuable materials and complex assemblies of potentially reusable components [11], [12]. Controlled component recovery can provide an alternative pathway for selected boards that are unsuitable for whole-device deployment. However, component-level recovery requires appropriate disassembly, testing, traceability, reliability assessment, and end-use qualification rather than simple physical extraction [17], [18], [25]. The environmental rationale for retaining functional value is complementary to conventional recycling. Material recovery remains necessary for exhausted, damaged, contaminated, or otherwise non-reusable equipment [1], [11]. However, when a product, module, or component can safely perform a useful secondary function, avoiding the manufacture of an equivalent new item may preserve a greater proportion of the original manufacturing investment than immediately reducing the equipment to constituent materials [7], [8], [13]. Affordable second-life computing may also contribute to digital inclusion where the required workloads can be met by appropriately qualified equipment. Second-life systems can potentially support educational, public-administration, community-access, and other institutional applications when hardware capability, software support, security, maintenance, and reliability are adequately assessed [22]. A. Research Proposition and Analytical Approach The central research question is whether a bounded proportion of technically eligible retired computing equipment can be routed through whole-device reuse, refurbishment, and verified component recovery in a manner that simultaneously preserves functional value, reduces dependence on destructive end-of-life processing, and supports affordable institutional computing [7], [13]. The study defines an evaluation band of 15%-25% for technically eligible intake, with the upper case designated as the S25 scenario. Across this paper, S25 is established strictly as a bounded analytical evaluation scenario and modeling framework, not as an empirically established universal recovery rate. It does not represent 25% of all global e-waste, all discarded PCBs, or all retired electronics. Rather, S25 represents a scenario assumption in which 25% of a defined pool of technically eligible retired computing-equipment intake achieves a verified secondary-use outcome through a combination of whole-device reuse or refurbishment, qualified module reuse, and qualified component reuse. These pathways are combined within the same S25 numerator and expressed against the common denominator of technically eligible intake; therefore, S25 is a combined secondary-use recovery target across mutually assigned pathways rather than a 25% whole-device reuse rate. The target does not imply equivalence of functional value between whole-device, module, and component outcomes. The S25 pathway therefore begins before technical qualification: preserving the condition of eligible equipment during collection and storage may influence whether it remains suitable for subsequent testing and reuse [16]. The effect of such preservation measures is treated as an intervention to be evaluated empirically, rather than as a predetermined increase in the S25 recovery fraction. The analysis distinguishes four circular pathways: 1) Whole-device reuse or refurbishment (Path A): the complete device is qualified and redeployed where technically and operationally appropriate. 2) Module reuse (Path B): equipment unsuitable for whole-device reuse but containing potentially reusable modules is selectively disassembled, and qualified modules are redeployed where technically appropriate. 3) Component harvesting/recovery (Path C): equipment unsuitable for whole-device or module reuse may be selectively disassembled, and individual components are tested and qualified for secondary applications. 4) Material recovery (Path D): non-reusable residuals are transferred to authorized recycling processes. Whole-device reuse is prioritized where the complete asset can satisfy the required workload, software-security, electrical-safety, and reliability conditions. Component recovery is considered when whole-device reuse is not technically or economically justified. Material recycling remains necessary for non-recoverable residuals [1], [7], [8], [11]. The environmental analysis uses published life-cycle evidence to estimate avoided manufacturing impacts where secondary use displaces production of an equivalent new product [13], [27]. The S25 results are then presented separately as illustrative scenario outputs. Where a published per-unit environmental benefit is scaled to the S25 case, the calculation assumes one-for-one functional displacement and is explicitly identified as a modelling assumption rather than an empirical universal constant. The scenario is evaluated across environmental impact, material demand, technical qualification, reliability, institutional deployment, economic feasibility, behavioural participation, implementation requirements, and end-of-second-life recovery. This structure allows the proposed S25 framework to be assessed as an integrated circular-recovery pathway rather than as a simple PCB-recycling rate. B. Literature and Evidence Selection This article follows a critical evidence-synthesis approach rather than a formal systematic-review protocol. Evidence was selected to address five linked dimensions of circular electronics recovery: (i) global e-waste generation, flows, and hazards; (ii) product life extension, preparation for reuse, and component recovery; (iii) environmental consequences and life-cycle impacts; (iv) reliability, qualification, and data-security requirements; and (v) economic, behavioural, infrastructure, and policy conditions for implementation. Peer-reviewed studies were prioritized for empirical, technical, behavioural, and environmental claims, while international organizations, government agencies, and technical standards were used where they provide authoritative monitoring data, regulatory requirements, or technical frameworks [1], [17], [19], [20]. The evidence base is interpreted according to the strength and function of the underlying source. Accordingly, the international functionality estimates used in this study are interpreted according to their underlying methodology. The approximately 81% figure reported by Odeyingbo et al. [24] is based on physical inspection of tested UEEE, whereas the 63% estimate reported by Thapa et al. [5] is an expert guesstimate derived through a Delphi process. The 86% value reported by Messmann et al. [16] refers specifically to identifiable WEEE damage causes associated with insufficient weatherproof roofing. These measures describe different stages or dimensions of the recovery pathway and are not combined into a single recovery rate. Published experimental, field, and life-cycle results are treated as empirical evidence; standards and institutional reports are treated as technical or policy evidence; and values introduced specifically for S25, including the recovery fraction, displacement factor, incentive assumptions, and selected economic parameters, are treated as scenario assumptions. Derived S25 environmental and economic values are therefore presented separately from published measurements and are not interpreted as universal empirical recovery rates. Life-cycle interpretation follows the principles and framework of ISO 14040 [19]. Where published per-unit environmental evidence is applied to the S25 scenario, the mathematical scaling is shown explicitly, allowing the reader to distinguish the source evidence from the assumptions and calculations introduced by the present study. II. ENVIRONMENTAL HAZARDS AND QUANTITATIVE POLLUTION MITIGATION A. Informal Processing, Transboundary Risk, and Exposure Pathways Informal e-waste processing can create hazardous exposures across multiple stages of material recovery. Open burning of wires and plastics can release hazardous combustion products; uncontrolled thermal treatment can expose workers to metal-containing emissions; acid leaching can generate corrosive and metal-containing effluents and hazardous fumes; mechanical processing can generate contaminated dust; and uncontrolled dumping can contribute to soil and water contamination [2], [3]. Printed circuit board (PCB) assemblies are an important intervention point because they combine valuable metals with complex electronic assemblies and hazardous substances [3], [11]. Electronic devices are frequently retired before the end of their technically useful life, leaving residual potential for reuse, repair, or component recovery [6]-[8]. A verified reuse-first gate can therefore divert technically eligible equipment from immediate destructive processing. Where whole-device reuse is technically and functionally feasible, the original product can retain a greater proportion of its embodied manufacturing value and may avoid some impacts associated with production of an equivalent new device [7], [8], [21]. Where whole-device reuse is not feasible, selected modules and components may be recovered subject to diagnostic, reliability, and compatibility requirements [17], [18], [25]. Non-reusable residuals remain subject to appropriate end-of-life recycling or disposal pathways [1], [11]. B. Environmental Mitigation Pathways and the S25 Scenario Life-cycle evidence indicates that extending the useful life of electronic equipment can reduce environmental burdens because production of electronic products contains substantial material and manufacturing impacts [7], [8], [27], [21]. However, the magnitude of the benefit depends on product type, remaining useful life, refurbishment requirements, functional equivalence, displacement of new-device demand, transport, and the subsequent end-of-life pathway [19], [21]. The preservation of equipment before qualification is also an environmental intervention because deterioration during collection can shift potentially reusable equipment toward repair, component recovery, or material treatment. The Bavaria evidence indicates that collection and storage conditions can influence this pathway, although the magnitude of the effect must be determined for each operating context [16]. Table I therefore distinguishes between published evidence, qualitative mitigation pathways, and S25 scenario outputs. Numerical S25 reductions are reported only where a directly relevant per-unit environmental factor is available. The absence of a numerical value for an impact category does not imply an absence of environmental benefit; it indicates that a defensible percentage cannot be calculated from the evidence and assumptions used in the present scenario. TABLE I ENVIRONMENTAL MITIGATION PATHWAYS AND TREATMENT OF THE S25 SCENARIO Impact vector Principal pressure addressed Evidence for reuse/recovery Treatment in S25 Primary material extraction and resource depletion Demand for virgin metals and other primary materials associated with production of new electronic equipment Product life extension can reduce the need for production of replacement equipment, while reuse and controlled recycling can retain material value [7], [8], [21] Qualitative in the present S25 model. No independent percentage reduction is assigned without a product-specific material inventory and displacement model. Soil toxicity and heavy-metal contamination Uncontrolled dumping, dismantling, and other environmentally unsound treatment pathways Informal e-waste handling can expose soils and surrounding environments to hazardous substances [2], [3]. Reuse-first routing can divert eligible equipment from immediate destructive processing [1], [2], [11] Qualitative in the present S25 model. No numerical percentage is assigned because the fraction of avoided uncontrolled processing is not independently quantified. Water and effluent contamination Acid leaching, contaminated runoff, and uncontrolled treatment residues Informal processing can generate contaminated effluents and contribute to environmental releases [2], [3], [11] Qualitative in the present S25 model. No numerical percentage is assigned without a defined avoided-processing inventory and fate model. Air pollution and greenhouse-gas emissions Emissions from uncontrolled processing and environmental burdens associated with manufacture of replacement equipment ICT manufacturing has substantial embodied GHG impacts [27]. A commercial second-hand laptop LCA reported approximately 39-50% lower environmental impacts across assessed categories, with approximately 40% reduction for climate change in the baseline comparison [21] Applies only to qualified whole-device reuse/refurbishment (Path A); the climate benefit depends on qualified whole-device displacement and the product-specific displacement factor. The combined S25 target also includes module and component recovery and therefore is not equivalent to 25% whole-device displacement. The separate laptop illustration in Section II-D is hypothetical and does not represent the combined S25 environmental outcome. The S25 scenario therefore does not assume that 25% reuse automatically produces a 25% reduction in every environmental impact category. The environmental effect depends on the impact avoided per reused unit and on whether the reused equipment actually displaces production of an equivalent new product [19], [21]. C. Establishing the 15-25% Evaluation Band and the S25 Scenario Published preparation-for-reuse evidence provides a basis for evaluating the feasibility of a bounded reuse scenario, but it does not establish a universal recovery rate for all electronic equipment. This emphasis on preparation for reuse is also consistent with European waste-prevention policy, where reuse and preparation-for-reuse are recognized as important elements of waste-prevention and circular-economy strategies [9]. Messmann et al. [16], based on assessments at 61 collection points in Bavaria, reported approximately 13-16% immediate preparation-for-reuse potential across the assessed waste streams, with an additional 13-29% potential depending on waste type and improvements in collection, storage, and treatment conditions. These findings demonstrate that a measurable fraction of collected WEEE can be suitable for preparation for reuse, while also showing that the attainable rate is sensitive to handling and system conditions. The same study provides a further rationale for treating collection and storage as part of the recovery system. Messmann et al. [16] found that 86% of identifiable damage causes of WEEE at the investigated collection points were attributed to insufficient weatherproof roofing. This result supports the proposition that preservation of equipment condition can be an upstream determinant of preparation-for-reuse potential. However, the 86% value is not used as a recovery multiplier in the present study and is not interpreted as a universal proportion of WEEE damage. On this basis, the present study uses 15-25% as an analytical evaluation band for technically eligible intake, with the upper value defining the principal S25 scenario. The 15-25% range is therefore a scenario assumption informed by published preparation-for-reuse evidence, rather than a universal empirical recovery rate. The scenario concerns only the defined pool that has passed the initial eligibility boundary. For clarity, the S25 recovery fraction represents the combined proportion of technically eligible intake that achieves a verified secondary-use outcome through whole-device reuse/refurbishment, qualified module reuse, or qualified component reuse. These recovery pathways are evaluated against the same denominator of technically eligible retired computing-equipment intake. Accordingly, S25 is defined as:

6. ChatGPT said:

   Summary

   Electronic waste (e-waste) is a growing global environmental and public-health concern because of increasing generation, inadequate formal collection, unsafe informal processing, and the premature loss of valuable equipment and components. In 2022, approximately 62 million tonnes of e-waste were generated globally, while only 22.3% was formally documented as collected and recycled. Significant quantities also move through uncontrolled transboundary and informal channels, particularly in low- and middle-income regions.

   In countries such as India, informal e-waste processing has historically included manual dismantling, open burning, uncontrolled heating, acid leaching, and open dumping. These practices can expose workers and communities to hazardous substances and contaminate air, soil, and water. Poor collection and storage conditions can also damage equipment that might otherwise have been suitable for reuse or refurbishment. Therefore, proper collection, weather protection, storage, testing, and routing are important for both pollution prevention and preservation of residual product value.

   A key argument of the study is that technical retirement does not necessarily mean the end of a product's useful life. Electronic equipment may be discarded because of administrative, economic, technological, or procurement decisions while still being functional. A computer, for example, may be suitable for secondary use after testing, while unsuitable whole devices may still contain reusable modules or individual components. However, published functionality estimates from different countries and methodologies cannot be directly treated as universal recovery rates.

   The study therefore proposes a reuse-first approach in which retired computing equipment is assessed before destructive recycling. Four circular pathways are identified:

   1. Whole-device reuse/refurbishment (Path A): Complete devices are tested and redeployed when they meet functional, security, safety, reliability, and workload requirements.

   2. Module reuse (Path B): Devices unsuitable for complete reuse are selectively dismantled to recover usable modules.

   3. Component recovery (Path C): Individual components are tested, qualified, and recovered from equipment unsuitable for whole-device or module reuse.

   4. Material recovery (Path D): Non-reusable materials and residuals are sent to authorized recycling processes.

   The proposed S25 scenario represents a 25% secondary-use recovery target among a defined pool of technically eligible retired computing equipment. Importantly, S25 is an analytical modelling scenario, not an established universal recovery rate. The 25% includes the combined outcomes of whole-device, module, and component recovery and therefore does not mean that 25% of all e-waste—or even 25% of the eligible equipment—will necessarily be reused as complete devices.

   The study evaluates a broader 15–25% scenario band, with 25% designated as S25. This range is informed by published preparation-for-reuse evidence but is treated as an assumption that must be tested rather than as an empirical fact. The study also emphasizes that collection and storage conditions can influence whether equipment remains suitable for reuse; evidence from Bavaria, for example, showed substantial damage associated with inadequate weather protection at collection points, although this finding is specific to that investigated system.

   Environmental significance

   The reuse-first strategy is intended to complement, rather than replace, conventional recycling. Extending the life of functioning electronics can potentially:

   • reduce demand for manufacturing replacement equipment;

   • reduce the need for virgin material extraction;

   • retain more of the original manufacturing and functional value;

   • divert eligible equipment from destructive or unsafe processing;

   • reduce some greenhouse-gas and other environmental impacts associated with manufacturing new devices; and

   • support affordable second-life computing for educational, governmental, community, and institutional applications.

   However, the study does not assume that a 25% reuse rate automatically produces a 25% reduction in environmental impacts. Environmental benefits depend on factors such as the type and condition of the equipment, remaining useful life, refurbishment requirements, transportation, functional equivalence, whether a new product is actually displaced, and the subsequent end-of-life pathway.

   Evidence and analytical approach

   The paper uses a critical evidence-synthesis approach rather than a formal systematic review. Evidence is drawn from research on:

   • global e-waste generation and hazardous flows;

   • preparation for reuse and product life extension;

   • component and PCB recovery;

   • environmental and life-cycle impacts;

   • reliability, testing, and data security;

   • economic and behavioural factors; and

   • infrastructure and policy requirements.

   Published measurements are kept separate from assumptions introduced specifically for the S25 model. Thus, values such as the 15–25% recovery range, S25 target, displacement assumptions, and selected economic parameters are treated as modelling assumptions rather than universal empirical values.

   Overall conclusion

   The text proposes a circular-economy framework for retired computing equipment that prioritizes reuse and recovery before material recycling. Its central proposition is that a defined proportion of technically eligible equipment can potentially retain useful value through whole-device reuse, refurbishment, module recovery, and component recovery, while non-reusable materials continue to conventional recycling. The S25 model provides a bounded scenario for evaluating this proposition, rather than claiming that 25% is a universally achievable recovery rate.

   In simple terms, the study's approach can be summarized as:

   Collect carefully → preserve condition → test and qualify → reuse whole devices → recover modules/components → recycle remaining materials.

    

7. You said:

   Summarize of the text: There is one-fourth of global emission through transportation sector. Road transport accounts for 74% (Pamidimukkala et al., 2024). It is also a major contributor to 23% of greenhouse gas emissions (Suman and Rajak, 2024). This makes it necessary for the introduction of some sustainable solutions to reduce these emissions. This highlights the need for the adoption of alternative technologies that can replace internal combustion engine vehicles (ICEVs). Electric vehicles are introduced as the solution to address these environmental issues (Patyal et al., 2021). Electric vehicles not only help reduce pollution but also help achieve several United Nations Sustainable Development Goals (UNSDGs). Despite these advantages, some challenges hinder the widespread adoption of EVs. It is important to identify these enablers and challenges and their impact on consumers' intention. Globally, EV sales crossed 14 million in 2023 (KEK et al., 2024), bringing the total number of EVs on the road to around 40 million (IEA, 2024). This growth is driven by financial incentives, longer battery range, and heightened environmental awareness, which motivate consumers to adopt EVs (Clinton & Steinberg, 2019; Tran et al., 2021; Wang & Witlox, 2025). The EV market in India is growing, having already achieved a milestone of 100,000 EV sales (IBEF, 2025). According to reports, EV manufacturers are launching new models early in 2026 across segments to dominate the market. This indicates industry preferences regarding emphasis on cleaner transportation technology (IBEF, 2026). EV sales in India are improving, and policy support is available, but progress is slow as many consumers remain uncertain about adopting EVs. To achieve sustainable transportation, it is important to increase adoption, which requires proper planning (Krishna, 2021). Prior research shows that digitalisation and sustainability orientation strengthen the innovation capability of emerging ventures (Tikkha et al., 2024), which is relevant to EV adoption, where new entrants are driving progress in charging infrastructure, battery technologies, and mobility services. As part of planning, understanding consumer perception of EVs is important for achieving the targets and goals set by the government. Understanding challenges and enablers can provide in-depth insights into the adoption process and consumer behavior. Due to the presence of both enablers and challenges in EV adoption, it becomes necessary to study them together and understand how they influence consumer intention, which affects EV adoption. To identify these factors, this study conducts a comprehensive review of the literature. II. RESEARCH GAPS AND OBJECTIVES Previous studies used theories such as the Theory of Planned Behavior (Ajzen, 1985) (TPB), the Technology Acceptance Model (David, 1989) (TAM), Unified Theory of Acceptance and Use of Technology (Venkatesh, 2003) (UTAUT), etc., to understand consumer behavior. Although these models are widely used for technology adoption, they only provide general insights. They use broad general constructs like performance expectancy, social influence, perceived ease of use, perceived usefulness, etc. Few studies have examined EVs' specific factors and their influence on consumers (Sovacool 2017). Since this technology is new, overlooking enablers and challenges limits the understanding of consumer intention. Structural modelling approaches such as ISM have been used to identify the key drivers of emerging sectors (Tikkha et al., 2025), but such approaches remain underused for EV-specific factors. It is important to identify the EV-specific factors that are impacting consumers' intention and address this gap. Hence, this study applies the SLR to identify these enablers and challenges impacting consumer behaviour and proposes the conceptual framework based on them. The objectives of the study are 1) Objective 1: To identify the enablers and challenges that impact consumer intention through a comprehensive review of the literature 2) Objective 2: To propose a conceptual framework that links enablers and challenges to intention. III. METHODOLOGY A comprehensive review of the literature approach has been used. Search Process: Sources used to search for the papers are ABDC, SCOPUS, Web of Science, etc. Keywords like electric vehicle adoption, enablers of electric vehicles, challenges of electric vehicles, technology adoption, sustainable mobility, sustainable transportation, etc are used for searching. 1) Inclusion criteria: Peer-reviewed, published in English, and focused on electric vehicle adoption, electric vehicle enablers, and electric vehicle challenges are included. Apart from this, both international and national papers are also included. Papers on consumer intention and factors impacting consumers' intention are also included. 2) Exclusion Criteria: Papers that are not related to electric vehicles, published in a local region, non-peer-reviewed such as blogs, etc., and not published in English are excluded. Apart from this, papers not available in full text are also excluded. 3) Screening and Selection: To check whether the paper is relevant or not, the title and abstract were first screened to remove irrelevant papers. The remaining papers are then fully read to check their relevance. After this, around 40 papers are reviewed in detail. 4) Analysis: Based on the enablers and challenges of electric vehicles, selected papers are read and grouped. The primary focus is given to those papers that have discussed more than one enabler and challenges. Figure 1 Methodology A. Discussion The literature proposed four enablers that boost electric vehicle adoption and five challenges that hinder consumer acceptance IV. ENABLERS A. Financial Incentives Financial Incentives are the most important enabler of electric vehicle adoption that impact consumers' incentives. Consumers are hesitant to buy electric vehicles due its purchase cost. These incentives are introduced by the government to reduce the cost. These incentives include subsidies, tax rebates, reduced registration fees, etc that make electric vehicles affordable to consumers. These incentives not only address the issue of cost but also help in changing the perception of electric vehicles among consumers. Previous literature highlights that consumers' intention to purchase electric vehicles increases with financial benefits (Dua et. al., 2021; Chhikara et. al., 2021). B. Maintenance Cost Maintenance costs of Electric vehicles are another important enabler to boost adoption. Internal combustion engine vehicles have engines that constantly require oil changes and other maintenance. But electric vehicles do not have engines instead, they have batteries, for which maintenance is relatively less for example no oil change is required. This lowers service routine and maintenance costs for electric vehicles. Consumers' intention to adopt EVs increases if they find EVs more cost-effective. This can boost the overall adoption of electric vehicles (Dua et. al., 2021; Mesquita et. al., 2025). C. Environmental Impacts Environmental impacts are the most significant enabler for electric vehicles. Electric vehicles are introduced to reduce emissions and lower the harmful impact of ICEVs on the environment. Due to this, it is widely perceived by consumers as the cleaner alternative to ICEVs. It has many environmental benefits, such as reduced greenhouse gas emissions, reduced dependence on fossil fuels, and improved air quality. Consumers are aware of environmental issues and EVs' benefits. These benefits are making consumer attitudes towards EVs positive, especially among consumers who are environmentally conscious. This helps boost the overall adoption of electric vehicles (Rezvani et. al., 2015; Khurana et. al., 2020). D. Government investments Governments are actively investing in increasing electric vehicle adoption. Investments like increasing the charging infrastructure and battery technology are helping to reduce the challenges. These investments have addressed some consumers' issues like range anxiety, battery efficiency, and convenience. Apart from the government is also providing incentives to manufacturers to increase the manufacturing of electric vehicles, which will address the issue of limited model availability. Government support is changing consumers' perceptions through awareness. This has increased consumers' intention to adopt (Chhikara et

8. ChatGPT said:

   Summary

   The text examines the factors influencing consumer adoption of electric vehicles (EVs), focusing on both the factors that encourage adoption (enablers) and those that discourage it (challenges).

   Transportation is a major source of global greenhouse-gas emissions, with road transport contributing a substantial share. The growing environmental impact of internal combustion engine vehicles (ICEVs) has increased interest in EVs as a cleaner transportation alternative. EVs can reduce emissions and contribute to several United Nations Sustainable Development Goals (UNSDGs). Although global EV adoption is increasing rapidly, significant barriers remain, particularly in countries such as India where consumers may still be uncertain about switching to EVs.

   Global EV sales exceeded 14 million in 2023, bringing the number of EVs on the road to approximately 40 million. Factors such as financial incentives, improved battery range, environmental awareness, and technological development have supported this growth. In India, EV sales are also increasing, supported by government policies and the introduction of new models. However, adoption remains slower than desired, making it important to understand consumer perceptions and the factors affecting purchase intention.

   Research Gap and Objectives

   Previous research has commonly used models such as the Theory of Planned Behavior (TPB), Technology Acceptance Model (TAM), and Unified Theory of Acceptance and Use of Technology (UTAUT) to explain technology adoption. However, these models often use broad constructs such as perceived usefulness, performance expectancy, ease of use, and social influence.

   The study argues that these general models do not sufficiently capture EV-specific factors. Structural modelling approaches such as Interpretive Structural Modelling (ISM) have been used in emerging technology sectors but remain relatively underused for identifying relationships among EV-specific adoption factors.

   The study therefore has two main objectives:

   1. Identify the enablers and challenges affecting consumer intention to adopt EVs through a comprehensive literature review.

   2. Develop a conceptual framework linking these enablers and challenges with consumer intention.

   Methodology

   The study uses a comprehensive literature review. Research papers were collected from databases such as ABDC, Scopus, and Web of Science, using keywords related to EV adoption, EV enablers and challenges, technology adoption, sustainable mobility, and sustainable transportation.

   The selection process included:

   • Inclusion: Peer-reviewed English-language studies focusing on EV adoption, consumer intention, EV enablers, and EV challenges, including both national and international studies.

   • Exclusion: Non-EV studies, non-peer-reviewed sources such as blogs, non-English publications, studies unavailable in full text, and studies limited to unsuitable local contexts.

   • Screening: Titles and abstracts were initially examined, followed by full-text assessment.

   • Final analysis: Approximately 40 papers were reviewed in detail and grouped according to the enablers and challenges they discussed.

   The review identifies four major enablers and indicates that five challenges hinder EV adoption.

   Major Enablers of EV Adoption

   1. Financial incentives

   Financial incentives are identified as an important factor encouraging EV adoption. EVs can have relatively high initial purchase prices, so government measures such as subsidies, tax rebates, and reduced registration fees can make them more affordable. Financial support can also improve consumers' perceptions and increase their intention to purchase EVs.

   2. Lower maintenance costs

   EVs generally require less routine mechanical maintenance than conventional ICEVs because they do not use conventional internal-combustion engines and do not require services such as engine oil changes. Lower maintenance and servicing costs can therefore make EVs economically attractive and increase consumers' willingness to adopt them.

   3. Environmental benefits

   Environmental considerations are another major driver of EV adoption. EVs are perceived as a cleaner alternative to conventional vehicles because they can reduce dependence on fossil fuels and, depending on the electricity source and lifecycle conditions, reduce greenhouse-gas emissions and local air pollution. Consumers with stronger environmental awareness may therefore show greater interest in EVs.

   4. Government investment

   Government investment supports EV adoption by improving the surrounding ecosystem. Investments in charging infrastructure, battery technology, EV manufacturing, and consumer awareness can reduce concerns related to charging availability, driving range, battery performance, and limited

Conclusion

The study used a comprehensive review of literature approach to identify the enablers and challenges that impact the consumer intention to adopt EVs. The study reviewed relevant papers and identified four enablers and five challenges of electric vehicle adoption. Enablers help in boosting the adoption and change consumers\' perceptions about EVs. But due to challenges, there is hesitance among consumers to adopt EVs. A conceptual framework is proposed connecting these enablers and challenges to the intention. Enablers and challenges are the antecedents, and intention is the consequence. This can be used in future research on electric vehicle adoption.

References

[1] Ajzen, I. (1985). From intentions to actions: A theory of planned behavior. In Action control: From cognition to behavior (pp. 11-39). Berlin, Heidelberg: Springer Berlin Heidelberg. [2] Chhikara, R., Garg, R., Chhabra, S., Karnatak, U., & Agrawal, G. (2021). Factors affecting adoption of electric vehicles in India: An exploratory study. Transportation Research Part D: Transport and Environment, 100, 103084. [3] Clinton, B. C., & Steinberg, D. C. (2019). Providing the Spark: Impact of financial incentives on battery electric vehicle adoption. Journal of Environmental Economics and Management, 98, 102255. [4] Dua, R., Hardman, S., Bhatt, Y., & Suneja, D. (2021). Enablers and disablers to plug-in electric vehicle adoption in India: Insights from a survey of experts. Energy Reports, 7, 3171-3188. [5] Goel, S., Sharma, R., & Rathore, A. K. (2021). A review on barrier and challenges of electric vehicle in India and vehicle to grid optimisation. Transportation engineering, 4, 100057. [6] KEK, V., Kandasamy, J., R, V., Bose, B., Menon, A. K., & K, S. (2024). Digital technology adoption model for electric vehicle battery recycling supply chain-an influential relationship mapping: VKEK et al. Operations Management Research, 1-40. [7] Khurana, A., Kumar, V. R., & Sidhpuria, M. (2020). A study on the adoption of electric vehicles in India: The mediating role of attitude. Vision, 24(1), 23-34. [8] Krishna, G. (2021). Understanding and identifying barriers to electric vehicle adoption through thematic analysis. Transportation Research Interdisciplinary Perspectives, 10, 100364. [9] Kumar, R., Jha, A., Damodaran, A., Bangwal, D., & Dwivedi, A. (2020). Addressing the challenges to electric vehicle adoption via sharing economy: An Indian perspective. Management of Environmental Quality: An International Journal, 32(1), 82-99. [10] Mesquita, A. R., de Abreu, V. H. S., Poyares, C. N., & Santos, A. S. (2025). Barriers to electric vehicle adoption: a framework to accelerate the transition to sustainable mobility. Sustainability, 17(18), 8318. [11] Pamidimukkala, A., Kermanshachi, S., Rosenberger, J. M., & Hladik, G. (2024). Barriers and motivators to the adoption of electric vehicles: A global review. Green Energy and Intelligent Transportation, 3(2), 100153. [12] Patyal, V. S., Kumar, R., & Kushwah, S. (2021). Modeling barriers to the adoption of electric vehicles: An Indian perspective. Energy, 237, 121554. [13] Rezvani, Z., Jansson, J., & Bodin, J. (2015). Advances in consumer electric vehicle adoption research: A review and research agenda. Transportation research part D: transport and environment, 34, 122-136. [14] Sovacool, B. K. (2017). Reviewing, reforming, and rethinking global energy subsidies: towards a political economy research agenda. Ecological Economics, 135, 150-163. [15] Suman, D., & Rajak, S. (2026). Analysis of barriers to the implementation of circular economy in an Indian electric vehicle batteries manufacturer. Environment, development and sustainability, 28(1), 1949-1998. [16] Tran, M. K., Bhatti, A., Vrolyk, R., Wong, D., Panchal, S., Fowler, M., & Fraser, R. (2021). A review of range extenders in battery electric vehicles: Current progress and future perspectives. World Electric Vehicle Journal, 12(2), 54. [17] Tikkha, V., Agarwal, P., Rajwanshi, R., & Swami, S. (2024). Innovation capability of agro startups: from digitalisation to sustainability. International Journal of Agriculture Innovation, Technology and Globalisation, 4(4), 359–383. [18] Tikkha, V., Rajwanshi, R., Agarwal, P., & Swami, S. (2025). Modelling the key drivers of agro-based startups: an ISM-based study. Journal of Global Entrepreneurship Research, 15(1), 1–17. [19] Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view1. MIS quarterly, 27(3), 425-478. [20] Wang, Y., & Witlox, F. (2025). Global trends in electric vehicle adoption and the impact of environmental awareness, user attributes, and barriers. Energy Reports, 13, 1125-1137. Websites • IBEF 2025 India\'s Automobile Industry: Growth & Trends | IBEF • IBEF 2026 EVs, SUVs to headline automakers’ early-2026 launches | IBEF

Copyright

Copyright © 2026 Ms. Rajnandini Sharma, Dr. Rohit Rajwanshi, Prof. Sanjeev Swami, Dr. Vrinda Tikkha. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.