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The purpose of this study is to understand the role and impact of gender on reading habits. It is an attempt to explore the probable reason why or why not gender differences take place concerning reading time, reading purpose, reading resources and digital devices among undergraduate students in the digital environment.

For this study, the researcher used a survey-based approach. To accomplish the study’s goals, a meticulously designed questionnaire has been disseminated among undergraduate students in selected colleges located in the western district of Tripura, a northeastern state in India.

The study found that female respondents have a slightly higher level of liking for reading than males. For both genders, the major purpose of reading is to enhance their knowledge unvaryingly. Furthermore, it has been observed that female respondents read electronic and print reading material more frequently compared to their male counterparts. Female respondents read fiction more frequently than males in print form. Both genders have more ease in reading print resources than digital resources. Among all digital devices, respondents are most competent at using mobile devices and prefer them for digital reading.

As part of the pilot study, investigators surveyed a limited sample population, where the participation of students was further lower because of the unavailability of students.

The gender-based level of competency with digital devices is studied as a variable among the adult population to measure its correlation with reading habits.

This study aims to integrate the theory of planned behavior (TPB) and the value-belief-norm (VBN) theory into a meta-analytic framework to synthesize green consumption literature.

By integrating the findings from 173 studies, a meta-analysis was performed adopting several analytical methods: bivariate analysis, moderation analysis and path analysis.

VBN- and TPB-based psychological factors (adverse consequences, ascribed responsibility, personal norms, subjective norms, attitude and perceived behavioral control) mediate the effects of altruistic, biospheric and egoistic values on green purchase intention. Further, inconsistencies in the proposed relationships are due to cultural factors (i.e. individualism-collectivism, power distance, uncertainty avoidance, masculinity–femininity, short- vs long-term orientation and indulgence-restraint) and countries’ human development status.

The authors selected papers published in English; hence, other relevant papers in this domain published in other languages might have been missed.

The findings are useful to marketers of green offerings in designing strategies, i.e. specific messages, targeting different customers based on countries’ cultural score and human development index, to harvest positive customer responses.

This study is the pioneering attempt to synthesize the TPB- and VBN-based quantitative literature on green consumer behavior to resolve the reported inconsistent findings.

The purpose of this study is to explore and identify the privacy concerns of smartphone app users pertinent to app usage.

Adopting a qualitative phenomenological approach, the authors conducted semi-structured interviews with app users to explore the app users' privacy concerns.

Credibility concerns, unauthorised secondary use and vulnerability concerns are the three major privacy concerns of app users, under which these concerns have sub-concerns, i.e. popularity, privacy policy, stalking, data sharing, hacking and personal harm.

The findings are useful to app marketers, app developers and app stores. App marketers, app developers and app stores can use the findings to understand and properly address app users' privacy concerns, thereby increasing the apps usage.

By exploring the privacy concerns of app users, the authors' study extends the literature and provides a theoretical development of individuals' privacy concerns in the context of a widely used technology, i.e. smartphone applications. Accordingly, this study contributes to the consumer privacy literature.

This study aims to examine the technical efficiency of the chemical-free farming system in India using a hybrid combination of data envelopment analysis (DEA) and machine learning (ML) approaches.

The study used a two-stage approach. In the first stage, the efficiency scores of decision-making units’ efficiency (DMUs) are obtained using an input-oriented DEA model under the assumption of a variable return to scale. Based on these scores, the DMUs are classified into efficient and inefficient categories. The 2nd stage of analysis involves the identification of the most important predictors of efficiency using a random forest model and a generalized logistic regression model.

The results show that by using their resources efficiently, growers can reduce their inputs by 34 percent without affecting the output. Orchard's size, the proportion of land, grower's age, orchard's age and family labor are the most important determinants of efficiency. Besides, growers' main occupation and footfall of intermediaries at the farm gate also demonstrate significant influence on efficiency.

The study used only one output and a limited set of input variables. Incorporating additional variables or dimensions like fertility of the land, climatic conditions, altitude of the land, output quality (size/taste/appearance) and per acre profitability could yield more robust results. Although pineapple is cultivated in all eight northeastern states, the data for the study has been collected from only two states. The production and marketing practices followed by the growers in the remaining six northeastern states and other parts of the country might be different. As the growers do not maintain farm records, their data might suffer from selective retrieval bias.

Given the rising demand for organic food, improving the efficiency of chemical-free growers will be a win-win situation for both growers and consumers. The results will aid policymakers in bringing necessary interventions to make chemical-free farming more remunerative for the growers. The business managers can act as a bridge to connect these remote growers with the market by sharing customer feedback and global best practices.

Although many developments have happened to the DEA technique, the present study used a traditional form of DEA. Therefore, future research should combine ML techniques with more advanced versions like bootstrap and fuzzy DEA. Upcoming research should include more input and output variables to predict the efficiency of the chemical-free farming system. For instance, environmental variables, like climatic conditions, degree of competition, government support and consumers' attitude towards chemical-free food, can be examined along with farm and grower-specific variables. Future studies should also incorporate chemical-free growers from a wider geographic area. Lastly, future studies can also undertake a longitudinal estimation of efficiency and its determinants for the chemical-free farming system.

No prior study has used a hybrid framework to examine the performance of a chemical-free farming system.

Menstruation poses psycho-physiological challenges globally due to a lack of awareness, unhygienic practices and social stigma. This paper aims to assess the existing body of research on menstrual health and hygiene (MHH) worldwide.

This study focuses on seminal works published in the Scopus Database from 1946 to 2023 for extensive bibliometric analysis, involving 756 bibliographic records analyzed through Biblioshiny and VOSviewer software. The authors use thematic analysis to identify core research themes and sub-themes, coupled with a critical review of the most highly cited articles within each thematic category.

The research into MHH has consistently grown since 2010, with a notable surge in the past five years. Among all countries, the USA emerges as the most active contributor, boasting the highest number of publications and citations. In terms of organizations, The London School of Hygiene and Tropical Medicine takes the lead with 54 articles. Further, PLOS ONE and Waterlines were the most productive and influential journals, respectively. The thematic analysis identifies key research foci, including tampons, menstrual health, sanitation, hygiene and bleeding.

Further research could be initiated in areas of menstrual education and awareness, menstrual product safety and effectiveness and menstrual disorders and treatments to address the concerns especially encountered by women from developing countries.

This research provides a comprehensive analysis of 77 years of MHH research, offering valuable insights into key areas of concern and guiding future research directions, ultimately addressing critical global health challenges.

Electric Vehicles (EVs), owing to their low carbon emissions, have gained immense importance in achieving net-zero emissions by 2070. They have also appeared as viable substitute to conventional vehicles. Aligning with global initiatives, India has created a favourable ecosystem and has implemented several policies since 2011 to achieve its target. Consequently, the market share of EVs has surged, both globally and in India, over the past decade. Taking this into account, this study aims to identify the factors that influence EVs in a developing economy using the context of India.

This study identified important determinants of EV adoption from global literature and employed a multiple linear regression model (MLRM) using the ordinary least squares (OLS) technique. Secondary data were utilised to identify determinants in the Indian context, sourced from the Ministry, NITI Aayog, AQI, the Lok Sabha Question, and the Economic Survey of India.

This study found that the number of charging stations and local pollution levels significantly influence EV adoption in India. The insignificance of the other variables may be due to the emerging state of the Indian EV market.

This study adds to the growing body of literature on EV adoption in developing economies by analysing the factors that impact its adoption using regional data. In addition, this study provides a unique perspective on a developing economy and advocates a comprehensive policy for EV adoption that reflects long-term sustainability.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-06-2023-0479.

After the fall of Burma on 10 March 1942 the British government extensively implemented scorched-earth policies in Bengal like denial of rice and boats. The British government had inadequate defense equipment to resist Japanese attack in Bengal. After the Japanese invasion supply of Burmese rice suddenly stopped. Faridpur district used to import rice from Burma. The Burmese conquest created an immediate and serious crisis for several rice imported districts and coastal districts of Bengal. Hence, none of the districts of East Bengal could escape its brutal clutches and severity recorded in Chittagong, Dhaka, Faridpur, Tripura, Noakhali, Bakargonj and so on.

Among the affected districts of Bengal, Faridpur has been chosen as study area due to severity of famine. This study addresses the famine scenario of Faridpur. Data has been collected from primary and secondary sources. Content Analysis Research method is used to test reliability and validity of the data. Historical Analysis Research method has been followed in this study.

Finding of the study shows that the government relief issues, ignorance of warnings, political nepotism and denial policy of British government intensified the famine of Faridpur district. The wartime tactics adopted by the colonial government aggravated the famine situation. This article has shed light on the government war time policy, activity and some impacts of British decline in Burma that fueled the famine in Faridpur district.

This study is my original research work and has not been published else where.

This paper examines the role of institution in the combating crime in India. This study also assesses institutions for controlling property crime in India in the post-reform era.

Crime and socio-economic data are taken from National Crime Record Bureau and the Reserve Bank of India, respectively. Twenty major Indian states are selected for the study purpose for the period of 1994–2019. Fixed effect panel data technique is used for analysis purpose.

Property crime rate declines with economic growth, while it increases with financial development. Findings of fiscal policy instruments are different. Own tax is positively associated with property crime in India, while non-tax fiscal instruments such as fine, penalty, and so on, are inversely related to it. Property crime rate is inversely related to institutional factors like charge sheet and conviction rate.

Further research is needed for other crimes in India. State-level data are used here for analysis purpose; however, spatial or cluster analysis techniques might provide more insights for combating crimes in India.

This study suggests that economic growth and fiscal instrument along with institutional development are essential to control property crime in India.

Government should take steps to improve the law-and-order system to control property crime across states.

Impact of non-tax fiscal instrument reduces property crime while that of own tax is increases it in India. These findings are unique and added certain insight in the study. Institutional roles are captured its performances like charge sheet and convict rate, which are significantly reduce property crime in Indian states. Least square dummy variable model is applied to capture individual state effects.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-01-2023-0063

This study aims to explore the impact of systematic liquidity risk on the averaged cross-sectional equity return of the Indian equity market. It also examines the effects of illiquidity and decomposed illiquidity on the conditional volatility of the equity market.

The present study employs the Liquidity Adjusted Capital Asset Pricing Model (LCAPM) for pricing systematic liquidity risk using the Fama & MacBeth cross-sectional regression model in the Indian stock market from January 1, 2012, to March 31, 2021. Further, the study employed an exponential generalized autoregressive conditional heteroscedastic (1,1) model to observe the impact of decomposed illiquidity on the equity market’s conditional volatility. The study also uses the Ordinary Least Square (OLS) model to illuminate the return-volatility-liquidity relationship.

The study’s findings indicate that the commonality between individual security liquidity and aggregate liquidity is positive, and the covariance of individual security liquidity and the market return negatively affects the expected return. The study’s outcome specifies that illiquidity time series analysis exhibits the asymmetric effect of directional change in return on illiquidity. Further, the study indicates a significant impact of illiquidity and decomposed illiquidity on conditional volatility. This suggests an asymmetric effect of illiquidity shocks on conditional volatility in the Indian stock market.

This study is one of the few studies that used the World Uncertainty Index (WUI) to measure liquidity and market risks as specified in the LCAPM. Further, the findings of the reverse impact of illiquidity and decomposed higher and lower illiquidity on conditional volatility confirm the presence of price informativeness and its immediate effects on illiquidity in the Indian stock market. The study strengthens earlier studies and offers new insights into stock market liquidity to clarify the association between liquidity and stock return for effective policy and strategy formulation that can benefit investors.