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This paper aims to analyse the governance structures of the Indonesian chilli value chain, price volatility issues across the chain and to critically explore the value chain actors' perceptions and responses to price volatility.

The authors used semi-structured interviews with 148 primary actors of the Indonesian chilli value chain. In-depth interviews with 22 key stakeholders – from local, provincial and national levels – were conducted in order to obtain additional information about their roles and the current policies and challenges in the chilli industry. The authors also conducted focus group discussions (FGDs) with farmers and support providers and held a national workshop to gather governance and price volatility risk-related information.

The Indonesian chilli value chains are long, complex and involve multiple actors. Most relationships within the value chains are based on market governance in which price regulates transactions. Most value chain actors shared a similar perception of price volatility and its causes. Under different governance structures, the value chain actors identified production, product characteristics and marketing as a major cause of price volatility. Although strategies applied by the value chain actors varied, in the main they are all aimed at minimising the impact of price volatility. Contractual arrangements are viable alternatives to minimising price risk.

This research relies primarily on qualitative data derived from purposive data collection methods, which may reduce the ability to generalise the findings. A quantitative analysis is required to validate the level of price volatility perceived by the stakeholders and to assess the cause and impact of price volatility across the chain. Future research should focus on proposing and assessing potential policy interventions that address price volatility, in order to facilitate the development of the Indonesian chilli industry.

To the best of the author’s knowledge, this study is the first to investigate the governance structures of the Indonesia chilli value chain, the value chain actors' perceptions of price volatility and their responses under the different types of governance in a developing country context.

This study analyzes the impact of COVID-19 on agricultural production in South India by evaluating the influence of market channels and socioeconomic conditions on the production decisions of farmers during two key cropping seasons. We base our analysis on primary data from 200 marginal, small and medium farmers, primarily focusing on the key seasonal crops, namely paddy and black gram.

We studied the downstream supply chains of paddy and black gram crops in the district of Villupuram, situated in the South Indian state of Tamil Nadu. Using a Bi-Probit model, we analyzed the production decisions of marginal, small and medium farmers engaged in paddy and black gram cultivation. Various factors are considered, including farmers’ socioeconomic characteristics, gender, market channels accessed and the coping strategies employed.

After the easing of lockdown measures in June 2020, our research revealed substantial disruptions in agricultural production during the critical Kharif and Rabi seasons. Most farmers refrained from returning to their fields during the Kharif season; those who did produced millet as the main crop. Factors such as choice of market channels in previous seasons, economic status, access to all-weather roads, labor availability, gender and coping strategies played an important role in the return to production in the subsequent Kharif and Rabi seasons.

Our data revealed several interesting threads related to price volatility, irrigation and access to markets and their impact on food security. The role of intermediaries and market channels in providing liquidity emerges as an important aspect of farmers' choice of markets. The pandemic impacted all these factors, but a detailed analysis was beyond the scope of this study.

We also find that resilience to economic shocks varies not only by economic status but also by gender and social groups. Farmers with female members are more likely to be resilient, and marginal and small farmers primarily belong to social groups that are economically less developed.

This study contributes to the literature on factors influencing farmer choice and decision-making and provides nuances to discussions by analyzing crop-specific supply chains, highlighting the critical role of socioeconomic factors. It also highlights the role of demographics and infrastructural factors like access to all-weather roads and access to markets that influence farmers’ production decisions.

This paper gives a model of collusion formation and a method of measuring the degree of it among the traders/bidders in the agricultural commodity markets in India. The important assumption is that the bidding is repetitive with a set of common bidders. The theory has been derived based on the behavior of the wholesale market of agricultural commodities in India. The paper is based on full information in the collusion formation. The paper first derives the theoretical structure of the bidders' behavior and thereafter derives a measure of collusion formation with the help of real-life data.

The paper used the standard theory of optimization and the theory of auction and probability statistics.

This is a complete information model of cartel formation. The bidding is repetitive and continues forever in discrete time. Hence bidders behavior is observable. Using the proposed method, if the APMC measures for each market and publishes on a periodic basis, say weekly basis, then it will be easier to break the collusion in the market where relative collision is present. For example, if a farmer has three options to sell in three different markets, then the published data would help them to select the market where the degree of collusion is relatively lower. Moreover, the undesirable loss can be avoided based on the right choice of market. As a result, transaction costs will be optima.

The paper first derives the theoretical structure of the bidders' behavior and thereafter derives a measure of collusion formation with the help of real-life data.

The paper aims to examine agrochemical traders’ tax morale in three Ghanaian regions.

Primary data were collected from 92 respondents using structured questionnaires. A multistage sampling technique was employed and used in selecting respondents.. Descriptive statistics, factor analysis and quantile regression analysis were used to analyse data obtained via the questionnaires.

The study found tax reporting knowledge, tax calculating knowledge and tax payment knowledge to be the keen factors influencing agrochemical traders’ tax knowledge. It was also revealed that age, religion and marriage positively influence the tax morale of traders. Inversely, gender, high level of education and monthly sales were found to affect tax morale negatively. Moreover, trust (respect, trustworthiness and expertise knowledge) negatively influenced tax morale. Authorities’ tax knowledge and power (sanction and lockdown) were revealed to impact tax morale positively. However, tax morale decreases amongst agrochemical traders with higher tax morale when sanction increases.

Unlike previous studies which focussed on tax morale amongst individuals and firms outside the agribusiness sector, this study examined the tax morale within the informal agrochemical trading sector, which has recently attracted colossal patronage due to the high usage of agrochemicals amongst farmers in Africa and Ghana. This study also assumed tax morale to be at different levels; hence the factors that affect the morale at different levels differ. Therefore, the study examined the factors influencing tax morale amongst agrochemical traders by segregating tax morale into quartiles. Relating to theory, the economic deterrence theory was used to ground the study, which is not usually used in most tax morale studies.

The provision of fair and remunerative prices to farmers through government intervention is one of the key debates to address the farmers' distress in India. This article identifies how different marketing channels are responsible for higher price realization over the officially announced minimum support price (MSP).

The study uses the NSSO-SAS, 2012–13 and NSSO-SAS, 2018–19 for Aggregate level data and Unit Level Data on the Situation Assessment Survey of Farmers' households. It uses logit regression to determine the factors responsible for better price realization.

Our major findings indicate that two factors importantly determine better price realization than MSP. Firstly, government agencies provide better prices for crops covered by MSP, such as paddy, wheat and cotton. However, the probability of receiving higher prices increases for some crops if the farmers belong to the upper land size classes and upper social category. Secondly, jowar, bajra, maize and ragi, other important crops that don't benefit from government agencies, may require higher levels of procurement at the state level.

The present study only analyzes selected major crops. Distance is an important factor in choosing a marketing channel that is not incorporated due to unavailability in NSS Data.

The study is based on the latest original empirical evidence and sheds light on the variation in price realization in different agricultural marketing channels in India.

This paper examines whether farmers' knowledge of the minimum support prices (MSPs) affects farm-gate prices. MSP is the minimum guaranteed price for agricultural commodities announced by the Government of India for 24 commodities. Most farmers in India prefer to sell their produce at the farm-gate due to a small marketable surplus and hence do not directly benefit from MSP. The authors test the common argument in the political discourse that if farmers have knowledge of MSP, then they can bargain with traders during the farm-gate transaction and demand a better price close to MSP.

The authors use matching methods to examine the impact of knowledge of MSP on farm-gate prices.

Using nationally representative data, the authors show that there is no empirical evidence that the knowledge of MSP of the crops leads to higher bargaining power and better farm-gate prices.

Price information (MSP in this case) alone cannot improve the bargaining power of farmers and result in a better price realization. As a safety net, MSP fails in the absence of procurement of products by the government. This also raises the question of the equitability of the price support system in India and calls for a rethink of the MSP policy.

This study is the first of its kind to examine the anchoring effect of knowledge of MSP on farm-gate prices using a nationally representative dataset.

Maize and rice constitute the two major staple crops in Ghana. The demand for maize and rice outstrips production levels in Ghana, creating deficits for farmers to capitalize on to increase yield. Farmers procure certified seeds from different supply outlets to improve crop yield. This study assessed the effectiveness of supply outlets of certified maize and rice seeds. This study also examined factors that influence smallholder farmers' decisions in sourcing seed from the identified supply outlets.

Multi-stage sampling was used to collect data from smallholder farmers. A total of 360 farmers were interviewed for the analysis. The multivariate probit model was used to estimate the main drivers of the supply outlets of certified seeds.

The findings revealed that farmers' decisions to use certified seeds from a particular supply outlet are contingent on household size, years of farming, extension contacts, distance to the nearest market, distance to the district capital, access to credit and farm size.

Sourcing certified seeds from National Seed Traders Association of Ghana, Research Institutions and Ministry of Food and Agriculture is more effective than input dealers, open market and family and friends.

This study is one of its kind that looked at how effective are the supply outlets of certified seed purchasing outlets.

The Million Farmers School (MFS) program—also known as Kisan Pathshala was launched to impart training to the farmers by the government of the state of Uttar Pradesh (India) in December 2017. This study estimates the impact of training on agricultural knowledge of the farmers.

The study is based on household survey conducted in Uttar Pradesh (UP), India, during March–May 2019. The authors employed matching methods, the two-stage least square (2SLS)-residual and endogenous switching regression approaches to control for selection bias and endogeneity.

The results suggest that knowledge outcomes are significantly better among participants vis-à-vis non-participants. The results are robust to different model specifications. Further, the benefits are observed across different regions and social groups.

The MFS program can go a long way in enhancing agricultural know-how and the farmers' economic well-being, bringing a transformative change in the agricultural landscape of UP.

This study is based on a field survey data and analyzes various aspects of the program's impact, design and implementation, and offers implementation advice for greater efficacy in future.

In developing countries, local buyers often rely on relational contracting based on reciprocity and trust. This paper analyzes relational contracting and global value chain (GVC) governance by focusing on how domestic and foreign coffee exporters in Rwanda confront challenges.

Semi-structured interviews were conducted with 25 representatives of Rwandan private, Rwandan cooperative-owned and foreign exporters, and four coffee sector stakeholders.

Foreign firms export most Rwandan coffee, and local exporters express concerns about their ability to compete. Rwandan exporters face challenges accessing capital, competing with foreign firms and managing high transaction costs. They use relational contracts to reduce transaction costs, and they benefit from a monopsony zoning regulation that reduces competition. Foreign exporters face regulatory challenges: a government-set coffee price and the zoning regulation. They vertically integrate to reduce costs and lock in suppliers through prefinancing.

Future research should analyze differences between local and foreign exporters in other contexts to advance understanding of the different challenges faced and contracting approaches used.

Few GVC governance studies address the role of relational contracts in contexts where enforcement is costly. Considering relational contracts within GVCs can improve value chain analysis, specifically in the developing countries where many GVCs start.

This study aims to explore how sustainable business models (SBM) can be developed within agri-innovation systems (AIS) and emphasize an integration of the two with a systemic understanding for reducing food loss and value loss in postharvest agri-food supply chain.

This study conducted longitudinal qualitative research in a developing country with food loss challenges in the postharvest supply chain. This study collected data through multiple rounds of fieldwork, interviews and focus groups over four years. Thematic analysis and “sensemaking” were used for inductive data analysis to generate rich contextual knowledge by drawing upon the lived realities of the agri-food supply chain actors.

First, this study finds that the value losses are varied in the supply chain, encompassing production value, intrinsic value, extrinsic value, market value, institutional value and future food value. This happens through two cumulative effects including multiplier losses, where losses in one model cascade into others, amplifying their impact and stacking losses, where the absence of data stacks or infrastructure pools hampers the realisation of food value. Thereafter, this study proposes four strategies for moving from the loss-incurring current business model to a networked SBM for mitigating losses. This emphasises the need to redefine ownership as stewardship, enable formal and informal beneficiary identification, strengthen value addition and build capacities for empowering communities to benefit from networked SBM with AIS initiatives. Finally, this study puts forth ten propositions for future research in aligning AIS with networked SBM.

This study contributes to understanding the interplay between AIS and SBM; emphasising the integration of the two to effectively address food loss challenges in the early stages of agri-food supply chains. The identified strategies and research propositions provide implications for researchers and practitioners seeking to accelerate sustainable practices for reducing food loss and waste in agri-food supply chains.