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The objective of this study is to ascertain the financial literacy (FL) of the farmers in three South Asian economies (India, Bangladesh and Pakistan). Further, an effort was made to explore various demographic and socioeconomic antecedents of FL of the farmers.

The study used secondary data of 11,025, 782 and 657 farmers from India, Bangladesh and Pakistan respectively from Financial Inclusion Insights (2017) database. “Big five” FL questions were used to measure the FL of the farmers. Appropriate statistical techniques and censored Tobit regression were used to identify the determinants of such FL.

Bangladeshi farmers (48.75%: Moderate) were found to exhibit greater FL as compared to Pakistani (38.96%: Poor) and Indian (32.61%: Poor) farmers. The outcome of the study revealed that the farm ownership and educational attainment of the farmers significantly determined FL of the farmers in all three Asian countries. Financial confidence and gender were observed to exacerbate a positive influence on the level of FL of farmers belonging to India and Pakistan. Age, marital status, financial inclusion and economic status were found to be the major determinants of FL of Indian farmers.

There is a dearth of studies in the scholarship examining the FL of farmers in both developed and developing economies. The present study makes an original contribution to the literature by unearthing FL amongst farmers and its determinants in three South Asian economies using a large sample of 12,464 farmers for the first time.

The peer-review history for this article is available at: https://publons.com/publon/10.1108/IJSE-12-2022-0776

This paper aims to make a modest attempt to classify the Asia-Pacific countries in terms of the access to information and communication technology (ICT) to unearth the prevalence of digital divide (if any) in the Asia-Pacific region. In addition to that, this paper also examines the role played by the digital skill in bridging the digital divide in the context of Asia–Pacific countries.

Secondary data on 43 Asia-Pacific countries for the period from 2012 to 2017 was collected from International Telecommunication Union (ITU) database and World Development Indicators, World Bank. K-means clustering technique was applied to explore the natural grouping of the Asia-Pacific countries based on ICT access. The role of digital/ICT skill in narrowing the access-based digital divide was investigated using panel data regression technique.

Clustering of countries suggested a significant difference amongst the Asia-Pacific countries in terms of ICT access, signifying the prevalence of access based digital divide. Digital skill played pivotal role in promoting ICT access and thereby reducing the digital divide during the period of the study. Per capita income level, level of education, openness of the economy and urbanisation were observed to be the determining factors in reducing the digital divide during the period of study in the Asia-Pacific region.

The study makes an unique attempt to explore the role of digital/ICT skill in tapering the access-based digital divide in the context of Asia-Pacific region.

Energy-related financial literacy (ERFL) which consists of energy literacy, financial literacy and lifecycle cost literacy, can play an instrumental role in addressing climate change by ensuring efficient energy consumption (macro level benefit) and promoting financial well-being (micro level benefit) of households. This study aims to highlight the ERFL level and its effect on the energy consumption of the sample households in the state of West Bengal, India.

The study used primary data on 155 sample households from the two districts, i.e. Hooghly and North 24 Parganas in West Bengal, India, surveyed from September 2022 to November 2022 using a structured questionnaire. The study used the conceptual framework suggested by Blasch et al. (2018) to measure the ERFL. Pertinent statistical techniques and the ordinary least square regression method were used to attain the objectives of the study.

The outcome of the study showed that the average ERFL score was found to be moderate (63%). The findings of the study also indicated that the ERFL exerts a positive influence on reducing energy consumption among the sample households in India.

There is a dearth of research studies on the topic of ERFL around the globe. The very few studies so far conducted are mostly in the context of European economies and Nepal. Perhaps, to the best of the our knowledge, this is the first study on the issue of ERFL in the Indian context. Therefore, the present study will make an original contribution to the small but growing scholarship on ERFL.

The purpose of this paper is to narrow the research gap by examining the relationship between new ecological paradigm (NEP), consideration of future consequences (CFC), the intention to buy and the intention to pay a premium in the context of electric car (EC) purchase in India.

This study used a structured questionnaire to measure the variables of the research. The study successfully obtained useable data from a sample of 491 consumers residing in India. The analysis of the variables and their relationships was done using structural equation modelling using SMARTPLS4 software.

The relationship between the values of NEP and CFC was observed in the context of electric cars that has a significant impact on the intention to buy and pay a premium. It also highlights the role of CFC future and CFC immediate on the intention to buy and between NEP and the intention to pay a premium.

The study only covers electric cars, and therefore further testing of these relationships is required in the context of other forms of environmentally friendly transportation. The results are generalizable across the potential consumers of EC but are even more pertinent to higher-income millennial consumers.

Potential buyers of electric cars, having a positive orientation towards the environment and also consideration for future consequence, were observed to have a stronger intention to buy EC. The study finds a way in increasing the intention to buy an EC by catalyzing environmental concern of consumers through CFC future.

This is the first study that has examined the NEP-CFC relationship, and provides evidence that the intention to buy an electric car is not only NEP (environmental concern)-dependent but also considers CFC's future orientation. This study adds the CFC aspect as another important variable regarding the purchase of EC, and proves that environmental concern is not the only moderating factor to buy an EC.

The study aims to explore the savings behaviour of Indian farmers. An attempt is also made to inspect the effect of financial literacy (FL) and financial confidence (FC) on the savings behaviour of the farmers in India.

This study used secondary data on 10,263 Indian farmers from Financial Inclusion Insights, 2017 database. Relevant statistical techniques and ordered probit regression were used to unfold the effect of FL and FC on the savings behaviour of farmers.

The outcome of the study revealed that the majority of the Indian farmers exhibited poor levels of FL and FC. Of the total, 42.99% were found to save regularly. FL and FC were observed to play instrumental roles in steering the savings behaviour of the Indian farmers. Household size, financial shocks, gender, farm ownership, income, household financial decision-making process, religion and educational attainment have emerged to be significant predictors of the savings behaviour of Indian farmers.

The present study makes an original contribution to the extant literature by unfolding the savings behaviour of Indian farmers and the effect of FL and FC on such behaviour using a rich sample of 10,263 farmers for the first time.

The article makes a modest attempt to explore the level of financial literacy (FL) amongst the farmers in India. An effort was also made to unearth the factors affecting such FL.

The study used secondary data on 11,030 farmers across various regions of India from the Financial Inclusion Insight Survey, 2017. Standard and Poor Global FL questions were used to measure the level of FL amongst the respondents. In addition to the appropriate statistical tools and techniques, the censored tobit regression model and generalized structural equation model were applied to explore the determinants of FL of the Indian farmers.

The outcome of the study indicated that the majority of Indian farmers are financially illiterate. The average FL score obtained by the sample farmers was found to be only 33%. The results of the study signaled significant regional variation in FL amongst the farmers across India. Apart from the regional variation in FL, farmer type, state-specific agricultural productivity, gender, marital status, age, educational attainment and financial inclusion were found to be the major determinants of the FL amongst the farmers.

Evaluation of FL amongst farmers is scanty in the literature in developed nations and especially in the context of emerging economies, like India. The authors tried to fill this gap by exploring FL and its determinants amongst Indian farmers. In addition to this, the study for the first time used a comprehensive and rich dataset of 11,030 Indian farmers while exploring the level of FL and its determinants.

In the present knowledge economy, intellectual capital (IC) is regarded as one of the significant determinants of efficiency, profitability, and ultimately value of a firm. This chapter empirically investigates the ramifications of the IC on the level of efficiency of the firm. In addition, exploration of the changing dynamics in the relationship between IC and firm level efficiency in the face of global economic crisis is of special interest of this chapter. In attaining the objectives of the study, a comprehensive database of 299 manufacturing firms (chosen randomly from a stratification of six BSE manufacturing industry subsectors) were utilized during the period from 1999–2000 to 2013–2014. Firm level efficiency scores and implications of IC (as measured by employing Pulic's Value Added Intellectual Capital Model) on the level of efficiency of the firms were examined simultaneously using Stochastic Frontier Analysis. Empirical results revealed that IC significantly determines the efficiency of the manufacturing firms during the period of study. However, the impact of financial crisis was not robust in changing the synergy between efficiency and IC. Size, age, and leverage were also found to be significant determinants of efficiency during the period of study.

The purpose of this study is to compare the prediction models for half-cell potential (HCP) of RCC slabs cathodically protected using pure magnesium anodes and subjected to chloride ingress.The models for HCP using 1,134 data set values based on experimentation are developed and compared using ANFIS, artificial neural network (ANN) and integrated ANN-GA algorithms.

In this study, RCC slabs, 1000 mm × 1000 mm × 100 mm were cast. Five slabs were cast with 3.5% NaCl by weight of cement, and five more were cast without NaCl. The distance of the point under consideration from the anode in the x- and y-axes, temperature, relative humidity and age of the slab in days were the input parameters, while the HCP values with reference to the Standard Calomel Electrode were the output. Experimental values consisting of 80 HCP values per slab per day were collected for 270 days and were averaged for both cases to generate the prediction model.

In this study, the premise and consequent parameters are trained, validated and tested using ANFIS, ANN and by using ANN as fitness function of GA. The MAPE, RMSE and MAE of the ANFIS model were 24.57, 1702.601 and 871.762, respectively. Amongst the ANN algorithms, Levenberg−Marquardt (LM) algorithm outperforms the other methods, with an overall R-value of 0.983. GA with ANN as the objective function proves to be the best means for the development of prediction model.

Based on the original experimental values, the performance of ANFIS, ANN and GA with ANN as objective function provides excellent results.