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The purpose of this paper is to investigate the adoption of two categories of agricultural technologies among beginning farmers (10 years or less of experience) operating in the specialty crops industry. A secondary goal is to characterize the beginning farmers' population in the specialty crops industry and compare them to more experienced farmers (more than 10 years of farming experience).

Using a series of regressions, this paper tests the hypothesis that beginning farmers are more likely to adopt agricultural technologies such as growing technologies (i.e. hydroponics and hoop houses) and value-added (VA) technologies (drying and cutting produce into customer-ready portions) relative to counterparts. Using a unique primary collected dataset of specialty crops farmers, the dependent variable for each model is the binary decision to adopt each agricultural technology, while the main variables of interest are the dummy variables beginning farmers and the interaction terms created between beginning farmers and land farmed, percent of land rented, crop diversification, local sales, and part-time farming.

Farmers' characterization suggests that, on average, beginning farmers are more likely to adopt growing technologies than more experienced farmers. However, after controlling for other determinants of adoption, there is no significantly difference between the two groups. Lastly, results suggest that beginning farmers are more likely to adopt VA technologies relative to experienced farmers.

While the adoption of agricultural innovations can lead to increases in economic and environmental resilience, little is known about beginning farmers adopting agricultural technologies, and studies are even less common for specialty crops operations. As the world population continues to grow rapidly, the demand for agricultural food products is expected to increase up to 100% between 2010 and 2050. This growth places additional stress on the limited access to land and water for agricultural production. Farm profitability can be boosted by increasing economies of scope through the use of growing technologies that increase yield or by adding value to specialty crops. The increasing global demand for food makes it imperative to understand what influences the adoption of agricultural technologies among beginning farmers growing food crops.

The purpose of this study is to identify and analyze the barriers associated with the adoption of Industry 4.0 technologies in agricultural supply chains.

The study initially identified thirteen barriers by conducting a literature review and semi-structured interviews with key stakeholders. Subsequently, these barriers were validated and modeled using an integrated Fuzzy Delphi-ISM approach. Finally, MICMAC analysis was employed to categorize the barriers into distinct clusters.

The results provide considerable insights into the hierarchical structure and complex interrelationships between the barriers as well the driving and dependence power of barriers. Lack of information about technologies and lack of compatibility with traditional methods emerged as the two main barriers which directly and indirectly influence the other ones.

The robust hybrid Fuzzy Delphi and ISM techniques used in this study can serve as a useful model and benchmark for similar studies probing the barriers to Industry 4.0 adoption. From a theoretical standpoint, this study expands the scope of institutional theory in explaining Industry 4.0 adoption barriers.

The study is timely for the post-COVID-19 recovery and growth of the agricultural sector. The findings are helpful for policymakers and agriculture supply chain stakeholders in devising new strategies and policy interventions to prioritize and address Industry 4.0 adoption barriers.

It is the first comprehensive, multi-country and multi-method empirical study to comprehensively identify and model barriers to Industry 4.0 adoption in agricultural supply chains in emerging economies.

This paper to examine the relationship between performance expectancy and behavioural intention to use mobile-based communication technologies for agricultural market information dissemination in Uganda.

A descriptive field survey method was adopted. A total of 302 commercial farmers and agribusiness traders in Eastern Uganda participated in the study from whom data were collected using self-administered questionnaires. Descriptive statistics, factor analysis, correlation and regression analyses were used in the study.

The findings reveal a significant positive relationship between performance expectancy and behavioural intentions to use mobile-based communication technologies for agricultural information access and dissemination. This implies that, commercial farmers’ behavioural intentions to use mobile-based communication technologies for agricultural market information dissemination and access will be influenced if they anticipate mobile-based communication technologies to offer greater performance in their daily transactions.

This study was conducted in the context of resource constrained countries particularly in sub-Saharan Africa, however reflecting knowledge from other contexts. The study was conducted with a structured questionnaire being the main data collection tool, and this limited the study from collecting views outside the questions asked in the questionnaire. The variables studied could not be analysed for a long time, given that the study was cross-sectional in nature.

The study provides recommendations on how to further boost farmers’ behavioural intentions to use mobile-based communication technologies for agricultural information dissemination. Policy makers need to ensure that policies are put in place that encourage third party software developers and telecommunication companies to provide software products and solutions that are beneficial to the commercial farmers and can enable them complete their agricultural transactions in time.

The study provides critical literature on the influence of performance expectancy on commercial farmers’ behavioural intentions to use mobile-based communication technologies for agricultural market information access and dissemination in resource constrained settings.

It is noted that farmers in Uganda are slowly progressing to newer mobile information and communication technology tools for market information access and dissemination; however, little is known as to why there is slow adoption of these mobile technologies for agricultural purposes; yet policy makers need to come up with proper strategies to encourage wide scale use of mobile technologies for agricultural market purposes.

This study aimed to identify the determinants of farmers' participation in agricultural information-sharing digital groups and their impacts on farm performance.

Primary data of the 2015/2016 crop year collected from 175 cattle farmers were analyzed using descriptive statistics and econometric models. Farmers who had smartphones and participated in social groups/applications, especially those created to exchange agricultural information, were considered adopters of the technology.

A Poisson hurdle model showed that farmers' decision to participate in agricultural information-sharing digital groups is determined by schooling, age (negative effect) and use of tools for planning production. The intensity of participation is affected by risk propensity, interaction with specialist advisors, use of tools for planning production and participation in cooperatives. The authors also found empirical evidence that farmers' participation in agricultural information-sharing digital groups positively affects farm income per hectare.

The results of this study are important for accelerating the diffusion of low-cost digital technologies, which are powerful tools for improving farmers' sharing and access to valuable information in real time and in locations far from urban areas.

To the best of the authors’ knowledge, this is the first empirical analysis of the adoption and impacts of agricultural information-sharing digital groups/applications by Brazilian cattle farmers. The diffusion of simple digital technologies is important for reducing heterogeneity and increasing the efficiency of cattle production.

A research and development project disseminated ecological technologies to approximately 3,250 vegetable farmers through farmer field schools (FFS) in four districts of Bali and East Java provinces of Indonesia. This article aims to assess the economic sustainability of vegetable production after FFS participation.

A survey randomly sampled 500 farmers, comprised of FFS participants (50%) and non-FFS participants (50%). Based on 1,000 farm operations, this analysis employed input-saving technology as the fundamental model examined using the double-difference method. Simultaneous reduction of agrochemicals and improvement of productivity represent indicators of economic sustainability.

Results indicate that pesticide use decreased without jeopardising farm productivity; moreover, vegetable production increased. These findings indicate that the ecological technologies transferred through FFS significantly improved economic sustainability performance.

This study purposively selected farmers who grew tomato and chilli. Thus, the outcomes are not generalisable to other crops.

FFS continues to be an effective method for transferring agricultural technologies to farmer communities. Policymakers are recommended to use FFS for disseminating beneficial and sustainable technologies to broader agricultural communities.

The adoption of ecological technologies provides positive economic and ecological milieus.

This study employs a double-differences approach to verify input-saving technological progress. Therefore, the performance of economic sustainability attributable to the project intervention is theoretically justified.

Constructing a low-carbon agriculture (LCA) park is considered an effective means to reduce greenhouse gas (GHG) emissions in developing countries. This study aims to explore the effectiveness of integrated low-carbon agricultural technologies based on evidence from a pilot LCA experiment in Shanghai, China, from 2008 to 2011.

Integrated low-carbon technologies in an agricultural park were adopted to reduce GHG emissions. Reduced emissions and net economic benefits were calculated by comparing emissions before and after the implementation of the experiment.

Results show that the low-carbon agricultural park experiment markedly reduced GHG emissions. This outcome can be attributed to the integrated technologies adopted in the experiment, including the reuse and recycle of resources, control of environmental pollution and GHG emissions and improvement of economic efficiency and social benefit. All the technologies adopted are already available and mature, thus indicating the great potential of LCA to reduce GHG emissions despite the lack of advanced technologies. However, supporting policies may be necessary to motivate private interests in LCA because of the considerable starting investments.

Previous macro-level and policy studies on LCA are based on knowledge from experimental studies, which typically specify environmental conditions to explore solely the effects of one low-carbon technology. Practically, integrating several low-carbon technologies in one experiment may be more effective, particularly for extensive agriculture, in developing countries. The effectiveness of integrated technologies is insufficiently discussed in the literature. Therefore, this study explores how effective integrated feasible LCA technologies can be in terms of both emission reduction and economic benefits based on the data obtained from an experiment in Shanghai, China.

The purpose of this study is to examine the effects of mobile Internet adoption on technology adoption extensity.

This study uses cross-sectional data collected in 2018 from 932 smallholder litchi farmers in Guangdong Province and Guangxi Province in southern China. A Poisson regression with endogenous treatment effects (ETPR) model is applied to estimate the effects of mobile Internet adoption on technology adoption extensity.

The ETPR model results indicate that mobile Internet adoption can significantly enhance technology adoption extensity. In addition, the extensity of technology adoption is also determined by education level, training, share of litchi farming income, guidebook use and cooperative membership. Disaggregated analyses further confirm the positive impact of mobile Internet adoption on the number of capital- and labor-intensive technologies adopted.

This study contributes to the literature on agricultural technology adoption. The findings highlight the need to facilitate modern agricultural technology penetration by promoting the use of mobile Internet technologies.

The purpose of this paper is to investigate factors affecting the adoption of agricultural technologies in Sub-Saharan Africa, specifically the role of credit market inefficiency in adoption of agricultural technologies in the region.

Most importantly, the paper applies a 2SLS model on a unique data set on nine agrarian countries from Sub-Saharan Africa’s intensification of food crops agriculture (Afrint) to provide evidence on how credit market inefficiency affects adoption of technologies in the sub region.

The study finds that the relationship between credit and technology adoption is one-way causal relation (i.e. credit access leads to technology adoption) as opposed to a two-way relation (i.e. mutual dependent relation). Further, the results indicate that credit market inefficiency can be a major barrier to the adoption of yield enhancing technologies in Sub-Saharan Africa. Further, the study showed mixed results for household variables. The results give credence to studies that highlight the importance of infrastructure and risk control in the adoption of new technologies.

The study is limited to only nine countries in Sub-Saharan Africa. Thus, the findings and interpretations should be considered as such. Further, there is the need for further research that considers all the region so as to establish whether or not there is a relationship between credit market inefficiencies and technology adoption in the region.

The policy implication is that microfinance institutions should consider scaling up their credit services to ensure that more households benefit from it, and in so doing technology adoption will be enhanced.

The main contribution of the study lies in its use of a unique data set from Sub-Saharan Africa’s intensification of food crops agriculture (Afrint) to investigation relationship between credit market inefficiency and technology adoption.

The purpose of this paper is to explore the effect of agricultural extension services provided by public sector on the individual technology adoption behaviour of rice farmers in Sri Lanka.

The study used data from a cross sectional survey conducted in seven rice procuring regions in Sri Lanka. Eight rice technologies were selected to explore the effect of extension service on adoption behaviour of rice farmers using probit models. The extension service variable was identified as potentially endogeneous and instrumented using average extension for each region.

The results revealed that the extension service variable was positive and indicative of a high level of significance in all the rice technologies promoting the adoption. Hence the public agricultural extension service programmes were considered as significant explanators of technology adoption. The farmers who received agricultural extension service were more likely to adopt a technology.

At present, the position of agricultural extension service is questioned and the future is unknown. Therefore, this study advises policy makers to prioritise agricultural policies to strengthen public spending on agricultural extension for effective adoption of technological innovations.

The paper adds solid empirical evidence to the literature on technology adoption behaviour from a peasant agricultural context in a developing country scenario that uses farm level data. Moreover, the study contributes to the literature by reiterating the significance of public provision of extension and training programmes as a direct motive in the technology adoption behaviour of farmers.

The purpose of this study is to evaluate food supply chain stakeholders’ intention to use Industry 5.0 (I5.0) drones for cleaner production in food supply chains.

The authors used a quantitative research design and collected data using an online survey administered to a sample of 264 food supply chain stakeholders in Nigeria. The partial least square structural equation model was conducted to assess the research’s hypothesised relationships.

The authors provide empirical evidence to support the contributions of I5.0 drones for cleaner production. The findings showed that food supply chain stakeholders are more concerned with the use of I5.0 drones in specific operations, such as reducing plant diseases, which invariably enhances cleaner production. However, there is less inclination to drone adoption if the aim was pollution reduction, predicting seasonal output and addressing workers’ health and safety challenges. The findings outline the need for awareness to promote the use of drones for addressing workers’ hazard challenges and knowledge transfer on the potentials of I5.0 in emerging economies.

To the best of the authors’ knowledge, this study is the first to address I5.0 drones’ adoption using a sustainability model. The authors contribute to existing literature by extending the sustainability model to identify the contributions of drone use in promoting cleaner production through addressing specific system operations. This study addresses the gap by augmenting a sustainability model, suggesting that technology adoption for sustainability is motivated by curbing challenges categorised as drivers and mediators.