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Based on farm diversification's conventional and unconventional nature, the study intends to discriminate different profiles of farm diversification businesses. Furthermore, this study analyses the links between farm diversification efforts, (open) innovation networks as well as the environmental performance (EP) and financial performance (FP) of farms.

A questionnaire was administered through personal interviews with 160 fresh fruit farmers in an inland Portuguese region. Linear regression, latent class analysis (LCA) and multinomial logistic regression were used.

There are significant differences between the levels of diversification, performance and participation in (open) innovation networks of the three classes of farmers discriminated. Different types of diversification efforts and (open) innovation networks influence EP and FP, while FP and R&D projects are associated with the likelihood of being part of a farm diversification class. Moreover, this study shows that innovation networks, promoted by specialized agricultural advisors and R&D projects, are important forms of open innovation in the agricultural sector.

The study contributes to understanding the agricultural sector's diversification efforts and (open) innovation networks and their association with EP and FP. The conventional or unconventional nature of farm diversification was self-reported.

European and local institutions are advised to develop more R&D programs directed to farmers, including environmental and financial issues, besides comprising agricultural and non-agricultural diversification.

This study provides new insights to understand the association between diversification efforts, (open) innovation networks and agricultural businesses' performance.

The agricultural sector in the USA has experienced significant structural changes. For accommodating farm business, households have diversified their operations adopting various strategies—agricultural, structural, environmental, and income strategies. The purpose of this study is to analyze the factors influencing farmer’s diversification strategies while taking into account the simultaneous decision-making process.

This study uses a nation-wide farm household data from the US. The diversification decisions are analyzed using multivariate probit regressions.

The study suggests that agricultural, structural, environmental, and income diversification strategies are interlinked. Specifically, results indicate that, on one hand, environmental and income diversification strategies are positively interlinked. On the other hand, agricultural and structural diversification strategies are positively interlinked. Additionally, the factors representing location, farm, and farmer characteristics, farm type, and financial condition of the farm are major determinants in the choice of farm diversification strategies.

In this paper, diversification activities are broadly classified under four strategies: agricultural, structural, environmental, and income. Depending on the context and country, the definition and strategy set may need revision.

Strong complementary between diversification strategies suggests that studies analyzing farm household decisions and strategies need to account for the simultaneous decision-making process. As decisions are interlinked, separately analyzing one specific strategy may lead to biased estimates. Farm business households need to develop multiple skills and flexible capacities to tackle farming-related issues, including structural changes, risk management, and income enhancing activities. Improving employment opportunities for the rural farming population can stimulate structural diversification.

This paper contributes to limited literature about diversification by analyzing factors influencing different diversification decisions and finds interlinkage between decisions.

This paper aims to analyse the main variables and causal relationships in the system structure of the diversification of non-agricultural activities on agricultural holdings using system dynamics (SD) modelling. The SD model aims to simulate depictions of the behaviour of the real system while testing the effects of alternative decisions over time.

An SD methodology was chosen to model diversification in farm tourism.

A system approach increases the authors’ understanding of the transition of agricultural holdings to farm tourism. The results indicate that the transition to farm tourism depends on the level of tourism development in a certain area. The system is influenced by subsidies allocated by authorities to expand primary agricultural activities. The model describes a situation in which the tourism and agricultural industries have been affected by the COVID-19 pandemic.

The research is limited by the small set of available data due to the limited number of farms in Slovenia. One major problem is the difference in statistical data on the same activity collected from different institutions in Slovenia.

The paper includes implications for understanding the transition process to farm tourism, allowing policymakers to experiment with subsidies and promotion to explore the efficacy and efficiency of proposed policies.

This study provides a structured, systemic view of the diversification of non-agricultural activities on agricultural holdings, where the simulation results are a reliable reflection of the behaviour of the actual system being modelled.

In low-income economies agriculture plays an important role in promoting economic growth and reducing poverty. Agricultural growth achieved through diversification toward the higher value crops enhance income and mitigate risk. The present study focuses on one of the eastern Indian states namely “Jharkhand”; where agriculture is the mainstay for the 80% of its rural population. The state per-capita income is below the national average; however, it has registered an impressive growth, especially in the agriculture sector in the last one decade. In this study, the authors attempt to identify the components in sources of agricultural growth; the authors also estimate the determinants of overall agricultural growth.

The study is based on the secondary data from 2000–2001 to 2015–2016. This paper first decomposes the agricultural growth into area, price, yields (technological improvement) and diversification effects through the method of growth accounting approach. Secondly, the study employs the new classical growth model through the ordinary least square (OLS) to examine the determinants of overall agricultural growth.

The author's findings indicate that there has been a shift in cropping patterns from the cultivation of cereals to non-cereals in the state during the study period. Among the major crops, the area under pulses cultivation has increased by 19% from 2000–t2002 to 2014–2016. The increase in area under cultivation and the diversification in favor of higher-value crops have been the major reasons for the accelerating overall agricultural growth in the state along with improvements in technology. The study reveals that increased use of fertilizer per hectare, capital formation and road density are the main determinants of high agricultural growth in the state.

The study is based on secondary data and based on one state. A primary study to complement this could have been better. The limited data available for some of important variables related to mechanizations are also a limitation of the present study.

Several studies have analyzed the diversification and agricultural growth in India. With our best knowledge this kind of study has not been done so far for the state of Jharkhand in eastern India.

This study aims to evaluate the effectiveness of crop diversification in increasing the income of farm households. In addition, this study introduces the impact of natural disasters in the analysis to determine how diversification helps mitigate the negative effect of disasters on farm income. More importantly, the study also analyses the effect of diversification on farm income by farm class to see where the benefits of diversification are concentrated.

This study uses a linear model, in which agricultural income is expressed as a function of diversification, natural disasters and several control variables. Diversification is measured using the Simpson index of diversification. The linear model is enhanced with the inclusion of an interaction term of natural disasters with the diversification index to shed light on the role of diversification in negating their harmful effect on agricultural income. Finally, to analyze the impact of institutional variables on farm income, the interactions of diversification with irrigation, insurance, usage of technical information and formal training are incorporated in the linear model.

The study highlights the importance of demographic, farm and institutional variables in raising farm income. The study suggests that an increase in education level, irrigation, usage of technical information and possession of Kisan Credit Card (KCC) have a positive impact on agricultural income. The study reveals that crop diversification has a positive impact on farm income and the benefits of diversification are conditioned by institutional factors. Thus, there is a need for policy intervention to ensure increased irrigation facilities along with extension services to provide information to the farm households. It has been found that small farmers gain more from crop diversification than larger farmers. Furthermore, the results show that natural disasters negatively impact farm income, but their impact can be mitigated by higher levels of diversification.

The results of the study are based on the recent unit-level data from the 77th Round of the National Sample Survey Office survey. The survey covers a large number of farm households and reports information for the year 2018–2019.

Studies on the performance of agribusiness cooperatives in Brazil focus on economic and financial aspects. The purpose of this paper is to further delve into such studies by investigating which commonly measurable structural production factors (horizontal, vertical and lateral diversification; operating area; number of associates; and time in operation) have greater impacts on the financial performance of such cooperatives.

To achieve such a goal, a survey was conducted with a sampling pool divided by size (annual net revenues of US$ 50 million or higher), and the questionnaire was employed as a method of data collection. The sample was concentrated in the southern, south-eastern and mid-western regions of Brazil; classified by size; and deemed adequate after several adequacy tests.

The results were analysed using Spearman’s correlation, which showed that there were no significant correlations between the structural production factors considered in this study and the economic-financial performance of agricultural cooperatives, which leads to questions about the effectiveness of employing diversification strategies with a conjoint approach. Nonetheless, it was possible to identify several relationships not mentioned in the original hypotheses that might be addressed further in future studies.

The data obtained should be interpreted with caution because heteroscedasticity was detected. Although the cause could not be clearly identified, the presence of heteroscedasticity could mean that smaller and similar cooperatives present similar variation in their diversification and production base strategies.

This work sought to generate knowledge regarding operations management, which was achieved by demonstrating that production diversification in a dynamic and relevant economic sector, that is, agricultural cooperatives, is limited in terms of financial return when performed in an isolated mode. Hence, cooperatives’ production managers should take into account the totality of structural production factors during their planning activities.

Agriculture diversification acts as income enhancing as well as distress mitigating strategy. India has witnessed rise in per-capita income which in turn has increased the demand for food particularly high-valued food items but agricultural production has failed to keep pace with the growing demand. The purpose of this paper is to examine spatio-temporal variations in agricultural diversification (AD) in India. Second, the authors try to identify the determinants of AD. Third, the authors examine the convergence hypothesis with reference to agriculture diversification across Indian states.

The study is based on the panel data constituting 20 major states of India during 1990–1991 to 2013–2014. It uses Simpson Diversification Index to measure AD. The heteroskedasticity-corrected panel regression model is applied to find out the determinants of AD. The fixed-effects model is used to examine β-convergence in AD across the sample states. Alternative time series models are applied to examine σ-convergence in AD.

The rising per-capita income and urbanization are driving dietary diversity towards high-valued crops and providing ample opportunity for AD. But poor and inadequate cold storage facility and rising cost of cultivation are posing major hindrance to it. Small land holding and road length have negatively influenced AD which is contrary to the traditional wisdom. The study found divergence in diversification and rising inequality in diversification.

The study is based on secondary data. A primary study to complement this could have been better. It is only based on one country.

Food inflation has serious adverse effect on the society at large. It is necessary to promote AD for controlling food price inflation. Minimum support price provided by the government should be extended to all crops; otherwise, it will fuel inflation. Given the fact fragmentation of land holding is adversely affecting AD, community based farming and consolidation of farm land should be the way forward to improve farmers’ income as well as reduce risk.

To best of the authors’ study, this is the first study that examines determinants of AD and convergence in AD during the high growth period of India.

This study investigates implications of crop and income diversifications on consumption expenditure (welfare) of rice-producing households in Ghana. It further compares diversification by three rice production systems: two-season rain-fed, two-season irrigated and one-season rain-fed rice production.

Primary data were sourced from 225 rice farmers. Margalef index and three-stage least-squares were employed.

Majority of rice-farming households in Ghana diversify livelihoods. The extent of livelihood diversification differs among two-season rain-fed, two-season irrigated and one-season rain-fed rice-producing households. Credit, distance to district capitals, production purpose and number of farming seasons influence crop and income diversifications, and consumption expenditure of rice-producing households. While crop diversification reduces consumption expenditure, income diversification increases it. Crop and income diversifications positively influence each other. Consumption expenditure reduces crop diversification but increases income diversification.

Policy should be directed towards the promotion of more livelihood activities to boost rice farmers' welfare. There should be awareness creation and training programmes to enable rice farmers realize different economic activities within and outside the agricultural value chain.

Crop and income diversifications were measured as continuous response variables, unlike previous studies that used a binary response variable. The authors established a synergy among crop and income diversifications, and consumption expenditure (welfare). The authors further compared crop and income diversifications by three rice production systems: two-season rain-fed, two-season irrigated and one-season rain-fed rice production systems.

The aim of this study was to evaluate determinants of four diversification practises by cocoa smallholders in West Sulawesi, Indonesia: (1) growing other crops, (2) keeping livestock, (3) off-farm work for wages (4) off-farm self-employment, and the impact of diversification on welfare of community members.

Household interviews (n = 116) conducted in two subdistricts (Anreapi and Mapilli) of Polewali-Mandar District, West Sulawesi, provided quantitative data on household characteristics, crop and livestock production, income sources, expenditure and credit access. Two villages per subdistrict were included in the study, each producing cocoa as the main crop but differing in their proximity to a market town. Logistic regression was applied to identify determinants of diversification by households. Multiple linear regression (MLR) models evaluated the impact of diversification practices and other explanatory variables on two proxies of welfare (or household wealth): per capita value of durable assets (household assets other than land or livestock) and per capita expenditure for each household.

Mean per capita cocoa production in the sample was low (51 kg dry beans/annum). The mean dependency ratio (proportion of household occupants age <18 and >64) was 35%, with an average of five occupants per household. Household heads were predominantly male (95%), averaging 46 yo and 7 years of formal education. Most households (72%) depended on loans, but only 24% accessed formal loans. Significant determinants of diversification practices were access to formal credit for self-employment and subdistrict for livestock, with Mapilli subdistrict households more likely to keep livestock. Household predictors in the MLR accounted for 28% variation of the dependent, per capita value of durable goods. Off-farm self-employment and raising livestock significantly improved welfare, but growing other crops or off-farm work for wages had little effect. Other household variables demonstrated to have significant positive effects on welfare were education of the household head, proximity to a market town and land area per household.

The study was restricted to a relatively small sample size (n = 116). Studies including panel data or larger numbers of households could enable the identification of further determinants of diversification.

The study demonstrates that diversification has the potential to improve rural livelihoods, but that obstacles, especially formal credit access, may deter poorer households from diversifying their income sources.

Programs and policies that facilitate access to formal finance by smallholders could encourage diversification into small business and improve livelihoods in cocoa-dependent communities.

In the light of the decline in cocoa farm productivity in West Sulawesi, the study demonstrates the potential benefits, as well as limitations, of income diversification by smallholders.

The purpose of this paper is to identify the trends in crop diversification (CD) while examining its impact on the technical efficiency of peasant farmers in Nigeria.

The paper employs the Herfindahl and Ogive indices to compute the diversification indices and the stochastic frontier production model (SFPM) to estimate the technical efficiency (TE) level of the farms using unbalanced panel data covering three farming seasons (2006/2007 to 2008/2009).

The results of both the Herfindahl and Ogive indices showed that cropping pattern increased significantly with the intensification of crop diversification in the study across the three seasons. The result of the SFPM shows evidence of decreasing returns‐to‐scale and technical progress in the food crop production in the region. Education, extension, and CD are identified as efficiency increasing policy variables while an average TE level of about 81 percent was obtained from the analysis.

To the best of the author's knowledge, this the very first study that employs panel data to analyze technical efficiency of farms in Nigeria.