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Despite the susceptibility of cotton crops to pest attacks in the Malwa Region of Indian Punjab, no crop insurance policy has been implemented there– not even the Pradhan Mantri Fasal Bima Yojana (PMFBY), which is a central scheme. Therefore, this paper attempts to gauge the likely impact of the PMFBY on Punjab cotton farmers and assess the changes needed for greater uptake and effectiveness of PMFBY.

The authors have conducted a primary survey to conduct this study. Initially, the authors compared the costs of cotton production with the returns in two scenarios (with and without insurance). Additionally, the authors have applied a logistic regression framework to examine the determinants of the willingness of farmers to participate in the crop insurance market.

The study finds that net returns of cotton crops are conventionally small and insufficient to cope with damages from crop failure. Yet, PMFBY will require some modifications in the premium rate and the level of indemnity for its greater uptake among Punjab cotton farmers. Additionally, using the logistic regression framework, the authors find that an increase in awareness about crop insurance and farmers' perceptions about their crop failure in the near future reduces the willingness of the farmers to participate in the crop insurance markets.

The present study looks for the viability of PMFBY in Indian Punjab for the cotton crop, which can also be extended to other crops.

Punjab could also use crop insurance to encourage diversification in agriculture. There is a need for special packages for diversified crops under any crop insurance policy. Crops susceptible to volatility due to climate-related factors should be identified and provided with a special insurance package.

There exist very scant studies that have discussed the viability of a central crop insurance scheme in the agricultural-rich state of India, i.e. Punjab. Moreover, they do not also focus on crop losses accruing due to pest and insect attacks.

Food labels are increasingly used to provide information to consumers. As a common design strategy used for food package labels globally, label frame is often used to expand the perceived breadth of a brand and create a broader brand image. We evaluated the effect of the presence or absence of a non-genetically modified organism (non-GMO) label frame on consumers' preferences for non-GMO foods.

This study collected data from 120 MBA students at a university in Sichuan, China, and 126 foreign volunteers in a shopping mall in Chengdu, Sichuan Province. The study investigates the effect of the presence or absence of non-GMO label frame (i.e. label with or without an outline) on non-GMO food preferences through a field survey and two controlled experiments. To empirically analyse the psychological mechanisms by which non-GMO label frames affect consumers' preferences for non-GMO food, we set up the mediating variable of food association of safety.

For ordinary consumers, a framed non-GMO label is more likely to evoke food association of safety and further enhance consumer preference for non-GMO foods. It facilitates consumers' choice of healthier foods. This finding did not otherwise vary across demographic characteristics.

This study is the first to examine the influence of non-GMO label frames on consumers' non-GMO food preferences, which is an innovative research question. The findings of this study are instructive for food manufacturers and policymakers to better design and use non-GMO label frames to attract more consumers to choose non-GMO foods.

The goal of this study is to predict the farmers’ concerns about agricultural index-insurance (AII) for weather risk mitigation of horticultural crops in hilly regions. The key impetus of analysis is to prioritize the AII requirements based on the farmers’ perspectives using the requirements prioritization approach.

The integrated approach has been applied in this paper. Initially, the MoSCoW prioritization technique has been employed to prioritize the AII attributes utilizing a four-dimensional agriculture insurance scale. Later, the rank sum weighting method was deployed to assign the ultimate rank to AII attributes based on the farmers’ responses.

Findings specified that out of 15 AII attributes, majority of 11 attributes were placed in “must have” and “should have” categories that related to claim, design, premium and grievance management dimensions. However, three AII attributes are placed in the “could have” category. Additionally, findings of rank-sum weighting method-based ranking can help insurers in redesigning farmers-oriented AII services for risk mitigation of horticulture crops by incorporating these ranks as per their priority level.

The prioritized AII attributes are helpful for insurers and managers in order to solve the problems associated with design, premium, claim and grievance management of AII.

Findings deliver significant insights to insurers to incorporate the prioritized AII attributes ranked by farmers.

This is the initial known analysis that integrated the MoSCoW and rank sum weighting method to prioritize the AII requirements prioritization among Indian farmers.

This study’s purpose is to analyze the effects of trade interventions and non-tariff impediments between the exporters (the United States and Brazil) and China for soybean trade.

A spatial model is developed and solved using an optimized Monte Carlo simulation (OMCS) and is used to minimize the costs of supplying soybeans to China. The costs included the origin basis; transportation to ports, including trucks, railways and barges; demurrage; and ocean freight. The sum of these charges determines the delivered costs to China from each origin. Most variables are random and correlated. Time-series distributions are based on historical data. Production and exports are highly seasonal and important.

Base-case flows are highly seasonal, are risky and reflect actual trade. Sensitivities illustrate the effects of mitigating the quality differentials and interpreting a term of the Phase One agreement that purchases would be made so long as the prices are competitive. The results are also used to illustrate the influence of diversifying from the United States as a supplier. Finally, the policy implications are discussed.

Removing the quality discounts for US soybeans raises the US market share by 9%. These results also illustrate that diversification of supply sources is important for the importing country. Indeed, if China were to pursue less diversification import costs and/or risks would escalate. Hence, these results suggest that diversification is an appealing element of an import strategy. The results suggest a large distribution of prices and costs, particularly in Brazil. On average, the United States is most likely to be competitive for only a few months of the year, and the results are highly seasonal.

Competition in supplying soybean to China is extremely competitive and the underlying factors impacting spatial competition are risk, correlated and spatially dependent. In addition to these, there are quality differences, and there are trade policies and strategies that affect competition. The empirical model and results illustrate the intensity of competition in this market as well the impacts of these non-tariff barriers and trade strategies in this market.

Important policies have been taken and continue to be under review regarding competition and trade among these countries. These results illustrate the impacts of these policies on market shares and competition.

This problem is important to the world soybean trading sector, and the methodology captures important seasonal and random variables that affect trade flows. The OMCS model is appropriate for this problem and has only been used minimally in the recent literature about commodity trade.

This study examines a controversial issue (biotechnology) and how news disputes about misinformation related to the issue impacts individuals' attitudes toward a biotechnology company and their trust in the media source.

This study conducts a 2 (risk: low vs. high) x 2 (pre-existing attitude: anti gene-editing technology vs. pro gene-editing technology) x 2 (dispute message: absent vs. present) x 2 (media source: Buzzfeed vs NYT) factorial online experiment using a Qualtrics panel (N = 1,080) to examine the impact on individuals' attitudes toward a biotechnology company and trust in the media source.

Results indicate that dispute messages enhance attitudes toward the company but decrease trust in media sources. Interaction effects between pre-existing attitude and the dispute message, along with perceived risk and the dispute message, illustrate stark differences in how individuals with favorable vs. unfavorable pre-existing attitudes assessed the company after viewing the dispute message.

This study applies arguments from extant literature about prebunking and debunking misinformation. Specifically, this study investigates how dispute messages, a form of debunking through source derogation, actually impact individuals' perceptions of media credibility and/or their attitudes about the content they are reading. The study findings also reveal new insights regarding the interaction between pre-existing attitudes and perceived risk, as well as how dispute messages interact with each of the aforementioned factors.

With increasing wine consumption in Armenia, both residents and inbound tourists have become attractive target groups for wine sales, which are stimulated by wine tourism activities. The objective of this explorative study is to shed light on the potential of wine tourism for rural development in Armenia.

The paper starts with a structured and interdisciplinary literature review. Based on qualitative surveys among local tour operators and wine producers, and complemented by three expert interviews, the offer of wine tourism activities in Armenia will then be analyzed.

Each of the surveyed wine producers offers wine tourism activities. Foreign tourists know little about the Armenian wine industry, however, and are interested in cultural experiences and Armenia’s breathtaking nature. Armenian wine producers need to understand the expectations of their target groups to develop or adapt their offers successfully.

Due to the explorative nature of this study, the sample size of the surveyed wineries and tour operators is small and hence not representative. In addition, only local tour operators were surveyed. The sample should be extended to include foreign tour operators and more wineries in future research projects.

Whereas first studies on the structure and competitiveness of the Armenian wine sector exist, there is no survey on the general wine tourism in Armenia and its potential to foster rural development.

As families engage in entrepreneurship, particularly in developing economies, women's engagement in such activities is subject to the traditional cultures, norms and values of the communities to which they belong. This paper aims to investigate how the socio-cultural context influences women's entrepreneurship as women engage in “family entrepreneuring”.

The study draws on an inductive qualitative approach to explore how multiple cultural, social and economic contexts encourage women's entrepreneurship and, thus, position them at the centre of family entrepreneuring within this community. Using snowballing techniques, we analyse narratives from 51 women entrepreneurs, generated through semi-structured interviews, to reveal key insights into the practice of family entrepreneuring.

The findings reveal the complex socio-cultural context within the “Adja” community, where polygamy, a traditional and cultural practice, enables the transfer of culturally and socially embedded informal knowledge. The study explains how women's entrepreneuring activities are supported by informal in-family apprenticeships, resulting in family members learning specific skills while also experiencing the feeling of belonging to the family. Showcasing the heterogeneity of contexts, particularly those found in Africa, this study challenges the normative view within the Global North and the dominance of the “heroic male” in entrepreneurship by showcasing how women (especially matriarchs) are significant actors in training other women, co-wives, daughters and relatives in family entrepreneuring.

Thus, this study contributes to the extant literature on family entrepreneuring by revealing an unusual case of women from polygamous families becoming the focal actors in family entrepreneuring activity and challenging the culturally ascribed gender roles to evolve into the breadwinners in their households, as well as focusing on how this process is driven by endogenous knowledge exchange.

This review paper delves into the comprehensive understanding of Ashwagandha, spanning its botanic occurrence, conventional applications, extraction techniques and pivotal role in addressing various disorders.

Introduction Ashwagandha, also known as Withania somnifera, is a remarkable botanical resource with a rich history of use in traditional medicine.

In botany, Withania somnifera thrives in diverse ecosystems, particularly in tropical and subtropical regions. Its extensive distribution across regions, the Canary Islands, South Africa, the Middle East, Sri Lanka, India and China underscores its adaptability and resilience. The traditional uses of Ashwagandha in Ayurvedic and indigenous medicine systems have persisted for over 3,000 years. With over 6,000 plant species utilized historically, India, often regarded as the “botanical garden of the world,” has firmly established Ashwagandha as a cornerstone in traditional healing practices.

Extraction methods play a pivotal role in harnessing the therapeutic potential of Ashwagandha. Ultrasonic-assisted extraction and high-performance liquid chromatography are among the techniques employed to obtain the key bioactive compounds. Ashwagandha’s significance in modern medicine is underscored by its potential to address a spectrum of health issues. The multifaceted bioactivity of Ashwagandha is attributed to its antioxidant, anti-inflammatory, heart conditions, metabolic disorders, renal ailments, hepatic diseases and adaptogenic properties, making it a subject of increasing interest in contemporary medical research. This review synthesizes the assorted perspectives of Ashwagandha, from its botanical roots and conventional employments to its advanced extraction strategies and its intention to basic well-being challenges, advertising important bits of knowledge for analysts, specialists and healthcare experts alike.

The present study examines the relational, structural and cognitive dimensions of social capital developed within members of self-help groups (SHGs) in India.

The study has used multistage random sampling to collect 1,285 samples covering 4 districts such as Sundargarh, Mayurbhanj, Koraput and Rayagada in Odisha. Structure equation modeling (SEM) is used in hypothesis formulation and data analysis.

The result highlighted that relational, structural and cognitive social capital are significant to social capital formation among the participants of SHGs. However, structural social capital has the highest impact compared with others in building social capital.

Policy professionals, development agencies and government departments must use social capital as a catalyzing agent for the successful implementation of welfare schemes in rural areas.

The paper adds valuable contributions in advancing the theory of social capital. Additionally, marginalized households fail to uplift their socioeconomic conditions in developing nations due to a lack of social capital; hence, its measurement is critical.

The peer-review history for this article is available at: https://publons.com/publon/10.1108/IJSE-10-2023-0804.

This study aimed to understand the agri-entrepreneurial traits of undergraduate university students using machine learning (ML) algorithms.

This study used a conceptual framework of individual-level determinants of entrepreneurship and ML. The Google Survey instrument was prepared on a 5-point scale and administered to 656 students in different sections of the same class during regular virtual classrooms in 2021. The datasets were analyzed and compared using ML.

Entrepreneurial traits existed among students before attending undergraduate entrepreneurship courses. Establishing strong partnerships (0.359), learning (0.347) and people-organizing ability (0.341) were promising correlated entrepreneurial traits. Female students exhibited fewer entrepreneurial traits than male students. The random forest model exhibited 60% accuracy in trait prediction against gradient boosting (58.4%), linear regression (56.8%), ridge (56.7%) and lasso regression (56.0%). Thus, the ML model appeared to be unsuitable to predict entrepreneurial traits. Quality data are important for accurate trait predictions.

Further studies can validate K-nearest neighbors (KNN) and support vector machine (SVM) models against random forest to support the statement that the ML model cannot be used for entrepreneurial trait prediction.

This research is unique because ML models, such as random forest, gradient boosting and lasso regression, are used for entrepreneurial trait prediction by agricultural domain students.