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The domains of Industry 4.0 and Smart Farming encompass the application of digitization, automation, and data-driven decision-making principles to revolutionize conventional sectors. The intersection of these two fields has numerous opportunities for industry, society, science, technology and research. Relatively, this intersection is new, and still, many grey areas need to be identified. This research is a step toward identifying research areas and current trends.

The present study examines prevailing research patterns and prospective research prospects within Industry 4.0 and Smart Farming. This is accomplished by utilizing the Latent Dirichlet Allocation (LDA) methodology applied to the data procured from the Scopus database.

By examining the available literature extensively, the researchers have successfully discovered and developed three separate research questions. The questions mentioned above were afterward examined with great attention to detail after using LDA on the dataset. The paper highlights a notable finding on the lack of existing scholarly research in the examined combined field. The existing database consists of a restricted collection of 51 scholarly papers. Nevertheless, the forthcoming terrain harbors immense possibilities for exploration and offers a plethora of prospects for additional investigation and cerebral evaluation.

This study examines the Industrial Revolution's and Smart Farming's practical effects, focusing on Industry 4.0 research. The proposed method could help agricultural practitioners implement Industry 4.0 technology. It could additionally counsel technology developers on innovation and ease technology transfer. Research on regulatory frameworks, incentive programs and resource conservation may help policymakers and government agencies.

The paper proposes that the incorporation of Industry 4.0 technology into agricultural operations can enhance efficiency, production and sustainability. Furthermore, it highlights the significance of creating user-friendly solutions specifically tailored for farmers and companies. The study indicates that the implementation of supportive legislative frameworks, incentive programmes and resource conservation methods might encourage the adoption of smart agricultural technologies, resulting in the adoption of more sustainable practices.

This study examines the Industrial Revolution's and Smart Farming's practical effects, focusing on Industry 4.0 research. The proposed method could help agricultural practitioners implement Industry 4.0 technology. It could additionally counsel technology developers on innovation and ease technology transfer. Research on regulatory frameworks, incentive programs and resource conservation may help policymakers and government agencies.

Based on a thorough examination of existing literature, it has been established that there is a lack of research specifically focusing on the convergence of Industry 4.0 and Smart Farming. However, notable progress has been achieved in the field of seclusion. To date, the provided dataset has not been subjected to analysis using the LDA technique by any researcher.

This chapter investigates diverse policy experiences of smart village strategy in Korea. The Korean approach has been highly influenced by the European Union (EU) experience emphasizing the importance of a bottom-up territorial development. The Korean government acknowledges agriculture is not the only driver of rural jobs and wealth creation. Rather it understands that diversified non-farm activities in rural areas are essential to revitalize the rural economy. The major policies relevant to the development of rural smart village are first, establishing regional innovation system fitted for depressed regions, second, inducing agriculture to become value-added industries, third, diversifying rural economic activities and integrating industrial support, fourth, improving the welfare of rural residents by improving settlement conditions, and finally, encouraging rural–urban interaction. Since the campaign of smart rural village as a rural development strategy is closely related with the discussion of rural tourism in Korea, this study investigates past and recent streams of rural tourism strategies pursued by the central government in Korea. Along with introducing the historical development strategy in Korea, this study presents the current and possible future characteristics of rural development strategies in Korea. This study investigates the perceived role of tourism as well as recent streams of rural development policies such as 6th industrialization and smart farming in the rural development strategies. Presenting success and failure stories, this study also considers why development of rural tourism has been slow in rural areas in Korea, reviewing restraints, reservations, and problems identified during the last few decades in Korea.

Stakeholders all over the European Union (EU), including academics, local and national authorities, business representatives, civil society, and the EU institutions are interested in creating a better life for citizens inhabiting rural areas. Building up on previous successful policies, including for instance the Common Agricultural Policy (CAP) and political actions, such as those outlined in the Cork 2.0 Declaration, these stakeholders assessed the current and future challenges of EU rural areas. The EU agri-food sector is not only the backbone of the EU rural areas but it is also a driver of the EU economy, that is, delivering 44 million jobs in the EU and representing 3.7% of EU GDP. The EU is thus the world’s number one exporter of agricultural and food products amounting to 138 billion, in 2017.

Today, the technological progress and the digital economy are transforming the EU economy in a way and speed never seen before; agriculture and food production are no exception. Obviously, the agriculture and the food production activities may have less obvious significance to the smart city but are key in the smart village concept. The ongoing technological transformation of agriculture will certainly enable and influence the design and implementation of any concept of smart villages. The question is therefore complex: How can agriculture and food production contribute and influence the smart villages concept and related policy strategies? This chapter dwells on this issue.

Smart farming technologies (SFTs) can increase yields and reduce the environmental impacts of farming by improving the efficient use of inputs. This paper is to estimate farmers' preference and willingness to pay (WTP) for a well-defined SFT, smart drip irrigation (SDI) technology.

This study conducted a discrete choice experiment (DCE) among 1,300 maize farmers in North China to understand their WTP for various functions of SDI using mixed logit (MIXL) models.

The results show that farmers have a strong preference for SDI in general and its specific functions of smart sensing and smart control. However, farmers do not have a preference for the function of region-level agronomic planning. Farmers' preferences for different functions of SDI are heterogeneous. Their preference was significantly associated with their education, experience of being village cadres and using computers, household income and holding of land and machines. Further analysis show that farmers' WTP for functions facilitated by hardware is close to the estimated prices, whereas their WTP for functions wholly or partially facilitated by software is substantially lower than the estimated prices.

Findings from the empirical study lead to policy implications for enhancing the design of SFTs by integrating software and hardware and optimizing agricultural extension strategies for SFTs with digital techniques such as videos.

This study provides initial insights into understanding farmers' preferences and WTP for specific functions of SFTs with a DCE.

Agriculture is under pressure to produce more food under increasingly variable climate conditions. Consequently, producers need management innovations that lead to improved physical and financial productivity. Currently, farm accounting technologies lack the sophistication to allow producers to analyse productivity of water. Furthermore water-related agricultural technology (“agtech”) systems do not readily link to accounting innovations. This study aims to establish a conceptual and practical framework for linking temporal, biophysical and management decision-making to accounting by develop a soil moisture and climate monitoring tool.

The paper adopts an exploratory mixed-methods approach to understand supply of and demand for water accounting and water-related agtech; and bundling these innovations with farm accounting to generate a stable tool with the ability to improve agricultural practices over time. Three phases of data collection are the focus here: first, a desk-based review of water accounting and water technology – including benchmarking of key design characteristics of these methods and key actor interviews to verify and identify trends, allowing for conceptual model development; second, a producer survey to test demand for the “bundled” conceptual model; third and finally, a participant-based case study in potato-farming that links the data from direct monitoring and remote sensing to farm accounts.

Design characteristics of water accounting and agtech innovations are bundled into an overall irrigation decision-making conceptual model based on in-depth review of available innovations and verification by key actors. Producer surveys suggest enough demand to pursue practical bundling of these innovations undertaken by developing an integrated accounting, soil moisture and climate monitoring tool on-farm. Productivity trends over two seasons of case study data demonstrate the pivotal role of accounting in leading to better technical irrigation decisions and improving water productivity.

The model can assist practitioners to gauge strengths and weaknesses of contemporary water accounting fads and fashions and potential for innovation bundling for improved water productivity. The practical tool demonstrates how on-farm irrigation decision-making can be supported by linking farm accounting systems and smart technology

From the perspective of any nation, rural areas generally present a comparable set of problems, such as a lack of proper healthcare, education, living conditions, wages and market opportunities. Some nations have created and developed the concept of smart villages during the previous few decades, which effectively addresses these issues. The landscape of traditional agriculture has been radically altered by digital agriculture, which has also had a positive economic impact on farmers and those who live in rural regions by ensuring an increase in agricultural production. We explored current issues in rural areas, and the consequences of smart village applications, and then illustrate our concept of smart village from recent examples of how emerging digital agriculture trends contribute to improving agricultural production in this chapter.

The paper aims to evaluate how progressive stakeholders view the adoption of contemporary techniques such as virtual technology in driving sustainable quality in an emerging economy context.

The authors adopted a systematic literature review to develop the theoretical framework for virtual reality (VR) technology adoption in sustaining quality in agriculture production. The framework was refined after discussion with a panel of academic experts. The refined theoretical framework was further empirically validated using Partial Least Square Structure Equation Modelling.

The study focuses on the future perspective of the perception for progressive farming with the adoption of VR technology in an emerging economy. The data were collected from the stakeholders (farmers, collectives, cooperative, etc.), for their future perspectives for the adoption of VR technology and sustainable quality agriculture production. The study may help build up VR technology in emerging economies which may take years to be established.

The perception of the future perspective of VR technology study conducted has limitations. The findings are well established on technology adoption; however, the technology used will take many extra years to find its application in the agriculture sector. The study offers insightful theoretical, managerial and policy implications for sustainable quality in agriculture production through the adoption of virtual reality (VR) technology. The authors found very few works that focused on VR technology adoption.

The study discusses VR, which has an impact on sustaining the quality of agriculture production. The study has notable managerial and policy implications that suggest the future perspective for VR technology in agriculture production. The study is an unexplored area that needs research to capture future perspectives.

The main intention of this paper is to analyze various factors hindering the growth of the agricultural supply chain and several industry 4.0 technologies to eliminate the same. In addition to a detailed assessment on the implementation of these technologies in agriculture, this manuscript also presents a priority list providing a rank to them based on the relative efficiency of these advancements in addressing these obstacles.

This research proceeds with a two-step process. The particular barriers in the agriculture supply chain and industry 4.0 technologies are determined in the first step. Next, the proposed framework, a combination of data envelopment analysis (DEA) and analytic hierarchy process (AHP), i.e. DEA-AHP, is used to determine a hierarchical structure for the factors and the relative productive efficiencies of the alternatives. The DEA methodology gives a performance analysis of various decision-making units. At the same time, AHP helps in evaluating alternatives weights based on numerous criteria, allowing us to categorize their importance further.

This study reveals how the involvement of technological advancements in agriculture can help manage the supply chain more efficiently. It also justifies how the large quantities of data generated can handle these increasing challenges in the agricultural supply chain.

The results of this study provide a priority list of alternatives based on their final weights. This ranking system can help farmers and the government select the best-suited technology for bringing automation into the agricultural supply chain.

This research is unique as it analyes the general factors hindering the development of the agriculture supply chain while simultaneously providing a list of alternatives based on their relative efficiencies. The study enriches existing literature by providing an analytic approach to determine the weightage of various critical success factors that can help improvise and entrust the real and undeniable requirements of consumers, suppliers and producers.

This study aims to investigate the use of Artificial Intelligence (AI) applied to vertical farms to evaluate whether disrupting technology supports sustainability and increases strategic business model choices in the agricultural sector. The study responds through empirical analysis to the gap on the subject of AI-driven business models present in the growing sector literature.

The paper analyzes the case of “ZERO”, a company linked to the strategy innovation ecosystem of the Ca’ Foscari University of Venice, Italy. The empirical data were collected through a semi-structured questionnaire, interviews and the analysis of public news on the business model available in the analyzed case study. The research is empirical and uses exploratory, descriptive analysis to interpret the findings. The article focuses on the evaluation of AI impact on the agricultural sector and its potential to create new business models.

The study identified how AI can support the decision-making process leading to an increase in productivity, efficiency, product quality and cost reduction. AI helps increase these parameters through a continuous learning process and local production, and the possible decrease in prices directed toward the goal of zero km food with fresh products. AI is a winning technology to support the key elements of the vertical farm business model. However, it must be coupled with other devices, such as robots, sensors and drones, to collect enough data to enable continuous learning and improvement.

The research supports new research trends in AI applied to agriculture. The major implication is the construction of ecosystems between farms, technology providers, policymakers, universities, research centers and local consumer communities.

The ZERO case study underlines the potential of AI as a destructive technology that, especially in vertical farms, eliminates external conditions by increasing productivity, reducing costs and responding to production needs with adequate consumption of raw materials, boosting both environmental and social sustainability.

The study is original, as the current literature presents few empirical case studies on AI-supporting business models in agriculture. The study also favors valuable strategic implications for the policies to be adopted in favor of new business models in agriculture.