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The purpose of this study was to investigate the likely causes of failure of some sections of road pavements in Ajaokuta, Northcentral Nigeria. This was achieved through a geotechnical assessment of subgrade soils in affected areas.

The methods entailed field and laboratory methods and statistical analysis. Subgrade soil samples were retrieved from a depth of 1,000 mm beneath the failed portions using a hang auger. The soils were analyzed for natural moisture content (NMC), Atterberg limit (liquid limit, plastic limit and linear shrinkage), grain size distribution, compaction and California bearing ratio (CBR), respectively.

The results of the geotechnical tests ranged from NMC (12.5%–19.4%), sand (84%–98%), fines (2%–16%), LL (16.0%–32.2%), PL (17%–27.5%), LS (2.7%–6.4%), PI (2.5%–18.4%), maximum dry density (1756 kg/m2–1961 kg/m2), optimum moisture content (13.2%–20.2%), unsoaked CBR (15.5%–30.5%) and soaked CBR (8%–22%), respectively. Pearson’s correlation coefficient performed on the variables showed that some parameters exhibited a strong positive correlation with r2 > 0.5.

Funding was the main limitation.

Comparing the results with Nigerian standards for road construction, and the AASHTO classification scheme, the subgrade soils are competent and possess excellent to good properties. The soils also exhibited very low plasticity, a high percentage of sand, high CBR and low NMC, which implies that it has the strength required for road pavement subgrades. The likely causes of the failures are, therefore, due to the use of poor construction materials, technical incompetence and poor compaction of sub-base materials, respectively.

The purpose of this study is to identify and validate the key consumer-related factors influencing consumer attitude toward electric vehicles (EVs) and intention to purchase EVs. The role of consumer attitude in mediating consumer-related factors and intention to buy is also explored in this study. Consumer-related factors considered in this study include environmental orientation (EO), new technology orientation (NTO), social orientation (SO) and perceived monetary benefits (PMB).

Data for the study were collected from individuals who do not own an EV in Chennai, Tamil Nadu, India. Data were collected from 388 respondents using Google Forms. Convenience sampling technique was used to identify the respondents. Both descriptive and inferential statistics techniques were used to analyze data collected.

The study identified EO, SO and PMB as antecedents of attitude (ATT) toward EV and NTO, SO and PMB as potential drivers of EV purchase intention (PI). In addition, the authors also observe that EO is fully mediated by ATT toward consumer PI, whereas ATT partially mediates the relationship between the independent variables SO and PMB and the dependent variable PI.

EVs are at the forefront of automotive innovation. Automobile industries producing EVs showcase a commitment to embracing cutting-edge technology, positioning their companies as forward-thinking and technologically advanced. Creating awareness about EV technology, dispelling myths about range anxiety and charging times should be done methodologically. The lower operating costs of EVs and the government policies that reduce the total cost of ownership can lead to faster market penetration. The widespread adoption of EVs can contribute to a nation’s economic growth by adding new businesses in the industry, infrastructure development and job creation.

The reduced environmental impact of EVs, such as improved air quality and reduced greenhouse gas emissions, can lead to significant societal benefits in terms of better human health and mitigating the effects of climate change. Governments can leverage these benefits to achieve climate targets and improve public health.

Studies about EV diffusion and adoption in India are yet to gain momentum considering the slow penetration of EVs in the Indian automobile market. The Indian Government is enforcing policies and incentives to accelerate the adoption of EVs. However, without understanding the drivers of consumer EV adoption, it is difficult for policymakers to accelerate the growth of the EV market. The present study is one step toward understanding the same in its original sense.

Research on battery electric vehicles (BEVs) has typically considered environmental concern a key determinant of behavioral intention that leads individuals to prefer electric vehicles. This paper challenges this assumption and argues that technology frameworks may require new variables to capture consumers' preferences. A UTAUT2-based study has been developed to assess the role of environmental concern in the BEVs context and put forward the technology show-off (TS) concept to explain the technology's acceptance.

A quantitative and cross-sectional look at behavioral intention is adopted. The study uses structural equation modeling to analyze a sample of 236 Macau residents to determine the relevance of the factors behind the choice to adopt BEVs.

The findings indicate that environmental concern and price may be relevant to explain behavioral intention to adopt the BEVs technology. Furthermore, the UTAUT2 framework seems to benefit from adding new variables, with TS playing a pertinent role in explaining technology acceptance.

The findings show that environmental concern fails to build an argument for the shift to full electric mobility and promote the desired behavioral change toward adopting BEVs. Herein lies the necessity to consider new variables that can better describe the characteristics of modern society.

This paper proposes the TS construct, combining visibility and trialability as significant determinants of behavioral intention to use technology. The study also stresses the need to reconsider the role of environmental concerns' impact on consumer decision-making.

In today’s environment, electric vehicles (EVs) industries and services provided to consumers are facing many challenges. The public in large numbers is not adopting Electric Vehicles because of the unavailability of suitable EVs and not getting proper charging infrastructure to the consumers. The purpose of this study and research work is to analyze the condition of this industry, its charging infrastructure and E-government policies. Based on the above analysis, frameworks/models are to be designed to assist organizations in formulating strategies for the EV industry and providing proper infrastructure to the consumer.

The Variables for the EV and EVsCI case study are identified from an exhaustive literature review, stakeholders’ perspectives, experts’ opinions, existing EV policies, future policy blueprints and data available for this industry, applying the Situation Actor Process-Learning Action Performance (SAP-LAP) methodology. After that, the Interpretive Ranking Process (IRP) is integrated with the SAP-LAP approach to develop models.

The rankings of Actors Versus Processes and Actions Versus Performances have been obtained and then models have been developed. These models can serve policymakers in framing and implementing effective policies.

Although the SAP-LAP approach is an innovative approach for identifying variables, however, this approach lacks perfect interactive relationships among the variables. It may lead to imperfect decision-making. To avoid this, the IRP approach is integrated with the SAP-LAP approach which provides more accurate models for analysis and providing recommendations to government and organizations.

The COVID-19 pandemic resulted in a dramatic downturn in the global stock markets. Investors look for safe stocks that can provide better risk-adjusted returns. Stocks with higher Environmental, Social, and Governance (ESG) scores can be good choices for investors. This study focuses on this argument by examining the relationship between ESG indicators and stock returns while considering financial and macroeconomic variables.

In this study, 39 non-financial firms listed in Nifty-50, for which data is available, have been included. Panel data from 2018 to 2021 is collected to examine this relationship in the presence of COVID-19. Additionally, the panel regression method is used.

The empirical findings indicate a positive relationship between ESG scores and stock returns. This relationship holds even when the control variables like Return on Assets (ROA), Gross Domestic Product (GDP), Return on Equity (ROE), age, size, leverage of the firm, inflation, and crisis period are used in the model.

This study contributes by examining the linkage between ESG indicators and stock return while controlling the impact of the financial and macroeconomic variables in Indian markets, which has not been undertaken so far. Moreover, this is the first study to use the ESG score data of S&P Global, which gives more weight to the material factors of a firm.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-10-2023-0819.

This study aims to investigate into the dynamic connection between ESG scores and the volatility term structure for Indian companies listed BSE. The study divides the BSE-100 listed companies into two panels based on their median ESG scores in 2022, creating high and low ESG scoring groups to capture volatility structure.

The study employs time-varying symmetric and asymmetric GARCH models and followed by continuous Wavelet to capture volatility structure and explore comparative resilience behavior.

The study found similar volatility patterns regardless of ESG scores, nudging doubt on the direct impact of ESG on volatility. Additionally, both high- and low-ESG-scored companies displayed high vulnerabilities during the pandemic, raising questions about the effectiveness of ESG frameworks in capturing risks. Finally, by examining the resilience behavior of ESG-scored companies during the pandemic, our study contributes to the evolving understanding of the intersection between ESG performance and crisis response.

The study carries vital implications for investors and policymakers. It highlights the urgent need to strengthen the ESG framework and scores to shield investors from short- and long-term volatilities and economic vulnerabilities.

To the best of the authors’ knowledge, this is the first study investigating the Indian market by examining the volatility structure and resilience behavior of high- and low-ESG-scored companies during the pandemic.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-02-2024-0113

In vitro millifluidic cultures with perfusion are essential tools to analyse and understand the interactions between cells, their matrix and multi-cell populations. The purpose of this paper is to focus on the design and development of a 3D-printed template that can be used for fabrication of a clear view poly (dimethyl siloxane) (PDMS) device. The major objective is to obtain a transparent device prototype that allows perfusion culture of two cell types for multiple days that can be imaged using laser scanning confocal microscopy.

The authors used a two-step approach for achieving the final geometric structure at a faster timeline and lower cost. The first part focuses on comparing the fidelity of the printing templates using fused deposition modelling (FDM) and stereolithography (SLA) printers for a range of dimensions. They then show that the complex geometry chip with connection chambers can be printed using low resolution low cost FormLab SLA printer. The final optimized design was then printed using high-resolution Projet 6000 SLA printer to obtain smoother structures.

In this work, the authors have shown that the FormLab SLA printer yields significantly lower error for printing complex design geometries as compared to FDM printer. Result shows that FormLab printer can be used to achieve a minimum dimension of 0.5 mm. They then use the printer to optimize the device dimension for the culture chip which requires several iterations of printing and experimenting. They showed the two-step protocol of printing the optimized template in a high-resolution SLA printer and further fabricating a clear view millifluidic PDMS device that is compatible confocal microscopy imaging. They used this culture chip for perfusion culture of two cell type, and the controlled fluidic exchange between the two chambers led to the formation of neuroglia junction.

One of the major bottlenecks for obtaining complex geometry in mili/microfluidic device by 3D printing is the need of multiple iterations on printing. This makes the tuning of dimension significantly expensive. Another challenge is to obtain a smooth surface of PDMS that leads to a leak proof clear view device compatible for laser based confocal imaging. The combination of two printers plays a crucial role for the rapid prototyping of the imaging device with flow control. The proposed approach lowers the cost for prototyping of in vitro culture chip with complex geometries to improve on biological research demanding multi-chamber fluidic device.