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The purpose of this paper is to identify, present and compare agricultural production financing alternatives available to grain producers in South Africa. From the South African perspective, agricultural land cannot always be utilised as collateral and therefore alternative financing has developed.

The study makes use of an exploratory study by applying qualitative techniques. The research population was agricultural finance providers in South Africa and semi‐structured interviews were conducted with representatives of the sample.

The production financing alternatives identified and presented include: grain contract financing; grain contract financing with additional collateral; and corporate farming. A comparison of these alternatives indicates that although the traditional balance sheet financing is a cheaper form of financing, using agricultural land as collateral has a number of limitations, especially within the South African context.

Using agricultural land as collateral to obtain production financing is not always viable considering the present South African agricultural environment. Commercial grain producers should therefore consider the identified alternative production financing.

Limited research on agricultural production finance from the South African perspective has been performed. Furthermore, no previous research on identifying production financing alternatives without utilising agricultural land as collateral has been performed. This paper therefore provides new knowledge by combining South African practice with theory.

Information and communication technologies (ICT)-presented technological developments, such as soil sensors, remote sensing, artificial intelligence (AI) and big data, have shown the potential to increase crop output and quality while consuming fewer resources and having a smaller environmental impact. The first step in ushering in a new era of technological advancement in the agricultural sector in the Kingdom of Bahrain is evaluating how prepared farmers and farm owners are to adopt these technologies. Therefore, the current study examines how ICT are prepared, accepted and adopted in agriculture in the Kingdom of Bahrain.

The study's goals were attained by using both quantitative and qualitative methodologies. A survey was created to learn more about the present state of ICT usage in agriculture, including its awareness, readiness, acceptance and adoption. To strengthen the conclusions and investigate the current situation related agricultural behavior, production and the use of information technology (IT) to support agriculture in the chosen farms, four exploratory field visits were made. Additionally, a strength-weakness-opportunities-threat (SWOT)-threat, opportunities, weakness, strength (TOWS) analysis was performed to evaluate the Kingdom of Bahrain's readiness and long-term plans for implementing ICT in agriculture. On the basis of secondary data, survey data and interview findings, SWOT-TOWS were created.

The findings revealed insufficient knowledge and awareness about ICT in agriculture. Despite the high level of digital infrastructure readiness in Bahrain, farmers are not ready to adopt sophisticated devices and complex applications such as crop sensing tools, the internet of things (IoT) and AI; however, there is a strong acceptance among farmers to implement new ideas and agriculture approaches.

The Arabian Gulf Countries, which are characterized by an arid environment, sporadic vegetation, weak soil and a lack of water supplies and arable land, have few studies that explore the crucial role of ICT in growing the agricultural sector. Considering the influence of ICT on the provision of more productive agriculture in a challenging and complicated environment, the study contributes to the body of knowledge by conducting an empirical investigation that addresses an urgent issue. The study is considered one of the few in the countries of the Arabian Gulf to address this subject.

The purpose of this paper is to provide insights about the approaches and techniques of professionals that nowadays are designing Digital Products and Services (DPS) in the European agriculture. The emphasis is paid on the integration of end-users and participatory approaches such as agile, considering its current influence.

A survey was conducted to professionals of businesses and entities from 14 European countries. A balanced sample of replies was achieved between private–public background, size of the business or experience of experts. Afterwards, the collection of answers and the opinions of professionals were compared with the state of the art referred in the literature. It allowed checking its soundness and critically discusses the results.

From the raw analysis of responses, professionals show awareness about the importance of end-user involvement and they are eager to incorporate innovative farmers and early adopters to collect the best requirements for products and services. They also declare knowledge and uptake in their companies of new approaches, such as agile. Confronting results with literature, the discussion highlights some inconsistencies and possibilities for leveraging. Types of end-users considered should be enlarged. Their superficial participation must also be avoided.

There is a lack of research on procedures for projects in agro-food sector. Due to the momentum in the digital transformation of agriculture, there are many project teams working in developing DPS and are relevant to discuss about proper methodologies for improving success.

This paper is a literature review on use of artificial intelligence (AI) among agricultural value chain (AVC) actors, and it brings out gaps in research in this area and provides directions for future research.

The authors systematically collected literature from several databases covering 25 years (1994–2020). They classified literature based on AVC actors present in different stages of AVC. The literature was analysed using Nvivo 12 (qualitative software) for descriptive and content analysis.

Fifty percent of the reviewed studies were empirical, and 35% were conceptual. The review showed that AI adoption in AVC could increase agriculture income, enhance competitiveness and reduce cost. Among the AVC stages, AI research related to agricultural processing and consumer sector was very low compared to input, production and quality testing. Most AVC actors widely used deep learning algorithm of artificial neural networks in various aspects such as water resource management, yield prediction, price/demand forecasting, energy efficiency, optimalization of fertilizer/pesticide usage, crop planning, personalized advisement and predicting consumer behaviour.

The authors have considered only AI in the AVC, AI use in any other sector and not related to value chain actors were not included in the study.

Earlier studies focussed on AI use in specific areas and actors in the AVC such as inputs, farming, processing, distribution and so on. There were no studies focussed on the entire AVC and the use of AI. This review has filled that literature gap.

The purpose of this paper is to shed light on the role of and relationships between human, structural and relational capital assets for strategic management in a farm business. In particular, it analyzes the interaction between human capital’s creativity skills and the introduction of climate-smart technologies for the competitiveness of the firm.

An explorative case study was conducted on one of the largest Italian farm businesses to gain an understanding of the drivers of intellectual capital (IC) and of their implications for strategic management. Full-time employees’ perception of the skills required to achieve strategic goals and their perception of whether they possessed these abilities were investigated to determine if an alignment was present. The skills were subsequently classified using the framework of Amabile (1988) into domain-relevant and creativity-relevant skills. Then, two linear regression models were used to investigate the effects of training on the acquisition of these two sets of skills.

The analysis confirmed the strategic role of interactions among human capital assets to effectively exploit the structural capital of the company. When investigating employees’ perceptions, a gap emerged about informatics capabilities and knowledge of soils. As the company’s investments in innovation are oriented to ICT technologies, the company could strengthen informatics training to enable its employees to implement effective innovation.

The paper contributes to the literature on IC by highlighting the role of interconnections of assets to align organizations with their strategic goals. Therefore, the provision of IC accounting contributes to the strategic management of human capital.

The use of management accounting in the agricultural industry has received very little attention by accounting researchers. Agriculture is currently in an era of significant change and adjustment, where change in accounting practice needs to occur in response to external pressures. The traditional use of the gross margin system of accounting has tended to underline a notion that has had a powerful influence on farm business planning that most costs are fixed and that the best way of reducing them to achieve profit maximisation is to spread them by increasing the scale of operation. This logic has been supported by an economic environment heavily influenced by agricultural policy measures that focused on artificial support for market prices and/or direct payments linked to production activities. We argue that the decoupling of support from production has combined with a number of other changes related to payments and cost structures (including those linked to the recent dramatic rise in the price of oil) to provide a very different economic context for farm business planning. The response we advocate to this changed situation is to make greater use of two alternative methods of cost analysis; namely relevant costing and target costing. These have been developed and applied outside agriculture. They have not so far been used in a formal sense within agriculture but have links to existing methodologies used in farm business planning, such as partial budgeting, and in intuitive approaches already adopted by farmers as revealed in recent fieldwork.

The increased availability and adoption of precision agriculture technologies has left researchers to grapple with how to best utilize the associated high-frequency large-volume of data. Since the wealth of information from precision equipment can easily be aggregated in real-time, this poses an interesting question of how aggregates of high-frequency data may complement, or substitute for, publicly released periodic reports from government agencies.

This study utilized advances in event study and yield projection methodologies to test whether simulated weekly harvest-time yields potentially drive futures price that are significantly different from the status quo. The study employs a two-step methodology to ascertain how corn futures price reactions and price levels would have evolved if market participants had access to weekly forecasted yields. The marginal effects of new information on futures price returns are first established by exploiting the variation between news in publicly available information and price returns. Given this relationship, the study then estimates the counterfactual evolution of corn futures price attributable to new information associated with simulated weekly forecasted yields.

The results show that the market for corn exhibits only semi-strong form efficiency, as the “news” provided by the monthly Crop Production and World Agricultural Supply and Demand Estimates reports is incorporated into prices in at most two days after the release. As expected, an increase in corn yields relative to what was publicly known elicits a futures price decrease. The counterfactual analysis suggests that if weekly harvest-time yields were available to market participants, the daily corn futures price will potentially be relatively volatile during the harvest period, but the final price at the end of the harvest season will be lower.

The study uses simulation to show the potential evolution of corn futures price if market participants had access to weekly harvest-time yields. In doing so, the study provides insights centered around the ongoing debate regarding the economic value of USDA reports in the presence of growing information availability within the private sector.

Considering the relevance of innovative business models in the digitally transformed market and the lack of clarity on the internet of services (IoS) contribution for a business model deployment in current literature, this study aims to fill this gap by evaluating a business model that converges to an IoS adoption in a direct sale of free-range eggs from farmers to consumers.

From the bibliographical research regarding the IoS and business model, the authors developed an IoS-based model framework. The framework has been evaluated in a real business scenario by using a single case study through an interview with the entrepreneur and documental analysis.

As the main result, a framework with the attributes can be considered a tool for an IoS-based business model deployment. The case study concluded that the business is aligned with the IoS adoption, and the framework presents adherence to it.

The case study was limited to only one company owing to the IoS’s novelty and the lack of correlated business models. Although the case study limits to the agriculture field, the proposed framework may be broadly applied.

Considering that the lack of a comprehensive business model causes new businesses to face challenges, it is relevant bringing up the present case study of the IoS-based business model, which correlates these two subjects, still poorly explored in the scientific literature: IoS and business models.

This paper aims to identify and analyze the agtech classification and categorization systems in the Brazilian context.

The systematic literature review (SLR) was carried out according to the protocol of Kitchenham and Charters (2007). The classification systems found in literature were evaluated using the thinking aloud protocol, as proposed by Ericsson and Simon (1993). The responses obtained were evaluated through lexicographic analysis, described by Bécue-Bertaut (2019) and content analysis, described by Bardin (2011).

SLR identified four agtech classification systems. The model proposed by Dias, Jardim, and Sakuda (2019) was the one with the highest adherence to classify Brazilian agtechs. From the analysis of the systems found in literature, the authors proposed a new categorization model of agricultural startups (agtechs).

The study has limitations in relation to the theoretical and empirical validation of the model proposed by the authors. This limitation can be the subject of subsequent research.

The SLR study considers the evolution of the classification systems of a new agribusiness reality, the agtechs. In addition, there is a practical contribution in proposing a new classification system that attempts to address some of the limitations found in previous studies.

Agtechs are startups focused on developing solutions for agriculture and have shown a significant increase in recent years. However, there are few studies focused on this type of company. Even rarer are the studies that seek to classify and categorize them. The present work opens the horizon for future studies focused on this new reality.

Food waste is one of the most challenging issues humanity is currently facing. Therefore, there has been a growing interest in the prevention of food waste because of world hunger, environmental impacts, resource scarcity and economic costs. The purpose of the study is to investigate the factors that influence food waste and the role of technology in tackling food waste in India and the Netherlands.

In order to explore differences in food loss and waste further this study will examine a number of practices on both the production and the consumer side, in a developing country and a developed country with different culture/economic backgrounds: India and the Netherlands. The factors that influence food waste were examined with a preliminary qualitative study, which consists of semi-structured interviews, and quantitative research that comprises a survey. Semi-structured interviews were conducted in both India and the Netherlands, which consists of five interviews. The survey data was collected from 78 individuals from India and 115 individuals from the Netherlands.

One of the main findings of the research is food waste is divided into waste within agricultural production (i.e. food loss) and final household consumption (i.e. food waste). Different factors influence food loss in different stages in the supply chain. Some of these factors include wastage during processing, storage, transportation and at the market-place. New technologies can utilize food loss for new purposes, so food loss is reduced to the minimum. Food waste is mainly influenced by food passing expiry date, food that is left too long in the fridge and consumers buying too much food. In final household consumption, technologies such as digital platforms enable individuals or organizations to share and donate their food, thereby creating awareness on food waste prevention and the environmental and ethical benefits.

The authors examine to what extent and in which ways supporting consumers to minimize food waste can be achieved via three stages: (1) understanding and evaluating food loss and waste, (2) identifying the factors that influence food loss and waste, (3) understanding consumer behaviors to encourage food waste reduction and (4) identifying the technological impact that would reduce food waste. As such, this paper contributes to ongoing debates about food waste by looking at the role of context and culture and by exploring differences between developed and developing countries. Also, the authors advance the debate by exploring both the role of advanced technology such as blockchain and drones in both preventing loss and waste as well as non-technological mechanisms.