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The purpose of this paper is to estimate the market demand and compare the average market margins for six broad categories of fresh produce in different retail formats across five select cities of the country. It also tries to qualitatively understand the supply chain management practices of these retailers across cities.

Registered retail outlets were selected randomly from online sources. Market potential was estimated as the average sales of each category of fresh produce. Personal interviews were conducted with the market players in order to collect qualitative data about their supply chain management practices.

Potatoes, onions and tomatoes are the largest consumed category of fresh produce across cities. Consumers in Tier 1 and Tier 2 cities exhibit different buying behavior and preferences. Large retailers and small retailers coexist in the cities. Marketing margins of retail formats are not uniform across cities.

The study did not capture the reasons for the differences observed in consumer preferences and buying behavior across cities. The study has taken into consideration only registered neighborhood stores in the study locations.

To the best of the authors’ knowledge, the paper is first of its kind which has attempted to estimate the categorywise market potential of fresh produce across study cities.

The study aimsto analyze the main elements associated with the evolution of Brazilian agtechs from the initial conception of the business model to becoming companies in the scale-up stage.

The exploratory research was conducted based on data collected through in-depth interviews. The answers were analyzed quantitatively using descending hierarchical classification (DHC) and correspondence factor analysis (CFA) and qualitatively using content analysis.

Five main elements were identified as responsible for the evolution of the companies up to their entering the scale-up phase: (1) governance, (2) decisions inherent to resource allocation, (3) monitoring of strategic, tactical and operational activities, (4) fostering human capital development and (5) business model validation. Each element presents a set of performance indicators that show the scalability of these companies.

The model developed can help companies that have not yet advanced from the conception of the business model to the scalability of different sectors, in addition to agribusiness.

Proposal of a model that presents the main elements that impact on scalability and respective indicators that contributed to the scalability process of Brazilian agtechs.

This study contributed to advancing the knowledge on the organizational life cycle (OLC) of agricultural startups, particularly regarding the factors responsible for their scalability.

This paper aims to explore the development of digital platforms in agtech space as a mechanism to mitigate the disconnects among the various actors in the innovation, business and entrepreneurship and extension ecosystems that impede the journey of technology from labs to farms. It does so by tracing the birth and evolution of KisanMitr, an agriculture digital platform created in India.

The research follows a participatory action research approach.

Digital platforms can be useful for integrating varied actor groups, in particular by facilitating the open flow of information among actors, and thus bringing to light the ways in which they can collaborate.

The paper demonstrates that digital platforms can become the backbone of integrated agricultural innovation systems, just as in the high-tech industries. Greater information flow enabled by such platforms allows the actors to collaborate more effectively. However, it is necessary to maintain farmer-focus, undertake off-platform activities to facilitate mutual engagement among actors and watch for potential governance issues if these platforms were to make a true impact for farmers.

KisanMitr was initiated with the motive of helping the Indian farmers, especially the reverse migrants during the COViD-19 pandemic, specifically for increasing the range of technology options available to them to make agriculture a viable livelihood option.

KisanMitr platform is one the first of its kind in India and in the agricultural sector. Unlike the digital platforms developed by private corporations, it was created by a government agency.

It becomes a strategic option for enterprises to upgrade and improve supply chain efficiency (SCE) by promoting the digital transformation (DT). This study formulated a parallel mediation model to analyze the relationships among DT, supply chain transparency (SCT), supply chain agility (SCA) and SCE to reveal how DT affects SCE through the mediation of SCT and SCA.

Three paradigms, i.e. resource-based view (RBV), dynamic capability view (DCV) and structure-conduct-performance (SCP) were employed to address the parallel mediation effects. A total of 392 questionnaires (samples) from the port-hinterland supply chain in the DT pilot project of New Land-Sea Corridor in western China were collected, which was then applied to formulate a structural equation model (SEM) to verify the proposed hypotheses.

The results confirmed the existences of parallel mediating effects of SCT and SCA between DT and SCE. On one hand, the direct effect of DT on SCE is not significant when SCT and SCE plays jointly impacts on DT and SCE. On the other hand, SCT and SCA play a positive parallel full mediating effect of DT on SCE.

This study contributed to the literature on changing activities of SCE in DT processes. Specifically, it highlighted how DT leads to SCE via SCT and SCA activities. In addition, this study specified the conditions that the insignificant direct effect of DT has reflects on SCE, it is the time when SCT and SCE are jointly acting on DT and SCE.

By integrating insights from the RBV, DCV and SCP paradigms, this study clarified the mechanisms of DT on SCE, and provided insight on the role of SCT and SCA in the relationship between DT and SCE. The novelty of this study and the results extend the existing literature and provide implications for future research.

Since the post-liberalization era, a noticeable structural change and transition in employment have unfolded within the Indian economy. Hence, the purpose of this paper is to understand employment transition and elucidate the evolving dynamics of rural economies and employment patterns from agriculture to more productive non-agricultural sectors. Additionally, the study investigates the underlying causes of socioeconomic disparities and their repercussions on employment trends.

To address the aforementioned issues, this study utilised secondary data from labour surveys conducted by the National Sample Survey Organisation spanning from 2004–05 to 2023. Initially, the study computed the magnitude of employment in both agriculture and non-agriculture sectors. Subsequently, the distribution of non-agricultural labour across various socioeconomic characteristics was estimated. Furthermore, a logistic regression model was employed to evaluate the impact of socioeconomic factors on employment choices. Finally, Fairlie’s decomposition model was applied to elucidate workers’ decisions to engage in non-agricultural sectors.

The study reveals a significant rise in rural non-agricultural employment, from 98.4 m in 2004–05 to 193.3 m in 2023, indicating changing job preferences. Notably, the construction and trade sectors emerge as significant drivers of this trend. However, self-employment and casual labour persist, highlighting job vulnerability. Additionally, women and marginalised individuals with low levels of education and socioeconomic status lag behind in non-agricultural employment.

This study makes a significant contribution by offering a thorough analysis of the employment transition from agriculture to non-agriculture over a span of two decades. It provides valuable insights into the evolving dynamics of employment trends.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-11-2023-0904.

The choice of a sales channel for fresh vegetables is an important decision a farmer can make. Typically, the farmers rely on their personal experience in directing the produce to a sales channel. This study examines how sales forecasting of fresh vegetables along multiple channels enables marginal and small-scale farmers to maximize their revenue by proportionately allocating the produce considering their short shelf life.

Machine learning models, namely long short-term memory (LSTM), convolution neural network (CNN) and traditional methods such as autoregressive integrated moving average (ARIMA) and weighted moving average (WMA) are developed and tested for demand forecasting of vegetables through three different channels, namely direct (Jaivasree), regulated (World market) and cooperative (Horticorp).

The results show that machine learning methods (LSTM/CNN) provide better forecasts for regulated (World market) and cooperative (Horticorp) channels, while traditional moving average yields a better result for direct (Jaivasree) channel where the sales volume is less as compared to the remaining two channels.

The price of vegetables is not considered as the government sets the base price for the vegetables.

The existing literature lacks models and approaches to predict the sales of fresh vegetables for marginal and small-scale farmers of developing economies like India. In this research, the authors forecast the sales of commonly used fresh vegetables for small-scale farmers of Kerala in India based on a set of 130 weekly time series data obtained from the Kerala Horticorp.

The goal of the present study is to examine the degree of knowledge amongst Indian women about millet grain and its nutritional advantages. Millet is regarded to be five times more nutritious than rice and wheat. Despite the fact that millet contributes to 10% of India's food grain basket and has an annual production of 18 million tonnes, it is not consumed in the same proportion as mainstream cereals (that is rice and wheat). As a result, the study's primary objective is to determine the level of awareness and consumption pattern of millet amongst Indian women regarding millet grains.

The research was carried out in the city of Bengaluru in the state of Karnataka, India. For the purpose of study, a sample of 855 female respondents was approached using a non-probability sampling technique known as convenience sampling. The data were gathered through the use of a self-administered structured questionnaire.

According to the findings of the study, the vast majority of respondents consume millet for preserving overall health. Building self and family immunity is the most important factor with 4.11 mean scores and low standard deviation of 0.985. The results reveal that 80.6% of women in the study are aware of millet but only 62.7% of women are consuming millet. The motivating factors and demotivating factors leading to consumption and non-consumption behaviour, respectively have also been identified. The study also reveals that demographic factors such as age, qualification and income have a direct influence on millet consumption.

The scope of research can be extended to explore the impact of millet consumption on long term health benefits of millet amongst the target respondents. Further, the study can be extended to explore the consumption pattern of millet among different target audience in various parts of India. The media interventions in creating awareness of millet consumption benefits need to be studied for increasing the consumption of millet.

Companies involved in producing Fast Moving Consumer Goods (FMCG) products can be encouraged to produce millet based foods like cereals, biscuits, ready to eat foods etc. Workshops can be organized to raise awareness on how the millet can replace traditional grains in the cooking process.

Policy measures may include millet being promoted through technology dissemination, creating awareness about advantages of millet and including millet in the Public Distribution System (PDS). It is also important to promote the cultivation, maintenance and processing of the local variety of millet with competent marketing strategies so as to increase their cultivation comparable to the cash crops. Farmers should be educated on the importance of cultivation of minor millet.

The fast-paced lifestyle of urban Indians has a direct impact on their dietary preferences. The World Health Organization (WHO) recommends that people have a nutritionally balanced diet and engage in regular physical activity to reduce health risks. In India, as a result of women's increased participation in the workforce, women are forced to manage many tasks and obligations, which has detrimental effects on their health. The poor nutritional status of modern-day workers is attributed to a lack of education, lack of awareness and a general disregard for health-related concerns. There is a need to investigate if Indian women are aware of the nutritional benefits of millet grains that are higher in protein.

The nexus between sustainable agri-food production and food security outcomes of farm households in sub-Saharan Africa is attracting policy attention. This study analyzes the effects of crop diversity on the incidence of food scarcity, dietary diversity, and the sale and consumption of own crops.

The study uses panel data collected in 2015 and 2018 on a randomly selected sample of 2553 households from 49 villages in northern Ghana. The study employed a fixed effects modeling approach in the empirical analysis.

The study finds that crop diversity is positively associated with better dietary diversity, reduced hunger, lower food expenditure, and higher consumption of own produce. The results show positive effects of crop diversity on the total harvested output and sale of agricultural production. Whilst sales improved sustainable food and nutrition security by providing purchasing power to buy nutritional inputs in the market, consumption of own produce rather improved food availability by reducing food scarcity and malnutrition.

Crop diversity is one of the pathways for promoting sustainable agri-food production systems to ensure the food and nutritional security of vulnerable populations and promote biodiversity to achieve environmental goals in sub-Saharan Africa. Crop diversity reduces food expenditure and raises rural incomes through improved outputs and sales, which empowers farm households to diversify their dietary options to be able to overcome incidences of hunger and malnutrition in periods of food scarcity.

The present study improves the understanding of sustainable agri-food production through crop diversity and its implications on food and nutrition security outcomes. The panel data and fixed effects modelling approach address the endogeneity problem between crop diversity and household tastes and preferences.

This study aims to examine peoples’ perception of climate change. It assessed their attitude, behavioural motivation for mitigating and adapting to climate change in the two capital cities of South Asia: Islamabad in Pakistan and Dhaka in Bangladesh.

This study used the quantitative research technique based on responses of 800 close-ended questions embedded in a close-ended questionnaire, which were filled-out from randomly selected sample of respondents. The primary data was analysed and presented through tabulation. For binary dependent variables, the standardised logistic coefficients were projected for more reliable estimates.

The findings reveal that the population of both capital cities have a low personal perception of climate change. Also, the dwellers of both cities have a low level of motivation to take mitigative and adaptive measures against climatic hazards. The results of the logistic regression model further indicate that the people who believe that climate change is a threat to their lives are more likely to adopt mitigative and adaptive strategies. This mostly applies to the people with a relatively higher income and education level.

This study implies to create awareness and sensitise the local community in both the capitals and beyond through information dissemination. Further, the availability of toolkits to handle emergencies remains imperative in registering attitudinal and behavioural changes to reduce the impacts of climate variability in poor localities.

This research study analysed the link between climate change mitigation and energy conservation from the societal attributes of perception, motivation, attitude and behaviour, which remains essential for community-based mitigation against climatic hazards.

The study analyzed the profitability of tomato farmers and determinants of farmers' choice of marketing outlets (wholesaler or retailer) in Ghana.

A two-stage sampling technique was used to collect data from 100 tomato farmers in Ghana. Analytical tools which include descriptive statistics, gross margin analysis (GM), profitability ratios and binary logit model were employed.

Profitability analysis indicates that farmers who supply to wholesalers have gross margin of Gh¢7.86 (US$1.67) per 25 kg crate, while farmers who supply to retailers recorded a major loss of Gh¢5.36 (US$1.14) per 25 kg crate. The result suggests that farmers selling to wholesalers are better off than farmers supplying to retailers. The binary logit regression analysis reveals a positive relationship between farmers' choice of marketing outlet (wholesaling) and age of respondents, quantity of tomato sold and cost of labor for production. A negative relationship also existed between farmers' choice of marketing outlet and weighted average selling price and household size.

The results call for policy efforts to provide an enabling environment for more extension education and establishment of farmer associations to make marketing information for price development among farmers available.

The choice of marketing outlet greatly influences profitability of tomato production. This study examines the performance of the various tomato marketing outlets in Ghana.