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The objectives of this paper are firstly to investigate the relationship between smart farming and sustainable development goal (SDG) 2 i.e. zero hunger. Secondly, the paper applies SWOT analysis to better understand the strengths, weaknesses, opportunities and threats of implementing smart farming in Southeast Asia (SEA). Finally, the paper provides research and practical implications for smart farming in SEA.

This study applies SWOT analysis to evaluate the strengths, weaknesses, opportunities and threats of smart farming in SEA in its goal to achieve zero hunger. The SWOT analysis is performed by conducting a comprehensive review of past and relevant literature on smart farming and its relationship with SDG 2. The use of SWOT analysis provides a foundation to identify the desired future position, identifies existing issues and better informs leaders and policymakers on how to resolve the weaknesses and take advantage of the opportunities available.

Smart farming has shown great promise in increasing food production sustainably whilst maintaining a high standard of food safety and quality. Smart farming offers a path towards achieving SDG 2 by providing innovative ways into a more profitable, resilient and green agri-food system. It is also found that a regional approach towards ensuring food security should be taken in SEA due to the dependency of the states on one another for the supply of food and agricultural products. For smart farming to take off in the region, a stronger government initiative is needed to encourage Science Technology Engineering and Mathematics (STEM) learning to equip the local workforce.

This study contributes to the literature by highlighting the role of smart farming in achieving zero hunger. This may assist policymakers to understand the implications of adopting smart farming in the region when compared to other competing trade locations. In addition, this study uses SWOT analysis to evaluate internal and external factors which may assist in formulating strategies by allowing researchers to gain insights and to think of possible solutions for existing or potential problems.

Artificial Intelligence-based smart farming technologies have brought impressive changes in farming. This paper aims at exploring the farmers’ intention to adopt smart farming technologies (SFT). Also, the authors intend to know how far the belief of farmers on land as God influences their decision to adopt SFT.

The data were gathered from 500 farmers chosen purposively. A well-crafted survey instrument was employed to amass data from farmers for measuring their adoption of SFT. As the authors sought to measure the farmers’ behavioural intention (BI) towards the adoption of SFT, the technology acceptance model developed by Davis (1989) came in handy, including perceived usefulness (PU), perceived ease of use (PEU) and BI. The authors have adopted this model as it was considered a superior model. The items on the attitude of confidence (AC) were adapted from Adrian et al. (2005). Survey instruments of Thompson and Higgins (1991) and Compeau and Higgins (1995) were also referred to finalize the statements relating to attitude towards use. Moreover, the authors developed items relating to the perceived belief of land as God based on frequent interaction with the farmers.

The study results divulged that attitude to use (AU) is directly influenced by the rural farmers’ PU, PEU and AC. Similarly, this investigation has observed behaviour intention directly influenced by the AU of farmers. It is observed that AU was the most influential variable, which ultimately influenced the BI to use SFT.

This study has an important limitation in the form of representing only the culture, belief and value system of farmers in India.

The outcome of this study will facilitate the policymakers to draw suitable policy measures keeping the sensitivities of the farmers in mind in their technology adoption drive. The agricultural officers can encourage farmers to take logical decisions by supplying adequate information in a time-bound manner. Marketers can make suitable adjustments in their sales and promotion activities that focus on farmers.

The belief of farmers on land as God has a small yet unmissable influence on farmers’ AU and BI in their technology adoption decision. Based on the above evidence, the authors recommend that marketers fine-tune their product design, product packaging and promotional activities keeping the belief and sensitivities of farmers at the core of their marketing campaign.

This article provides original insights by demonstrating the positive influence of PU, PEU and AC on technology adoption by farmers. This research is the first of a kind linking the belief of farmers on land as God with smart farming technology adoption in farming.

This paper aims to investigate how actors in the farmer’s network influence the adoption of smart farming technology (SFT) and to understand how social media affects this adoption process, in particular focusing on the influence of social media on trust in knowledge dissemination within the network.

The methodology used a two-stage process, with semi-structured interviews of farmers, augmented by a netnographic approach appropriate to the social media context.

The analysis illustrates the key role of the farmer network in the dissemination of SFT knowledge, bringing insight into an important B2B context. While social media emerges as a valuable way to connect farmers and promote discussion, it remains underused in knowledge dissemination on SFT. Also, farmers exhibit more trust in the content from peers online rather than from SFT vendors.

Novel insights are gained into the influence of the farming network on the accelerated adoption of SFT, including the potential role of social media in mitigating the homophilous nature of peer-to-peer interactions among farmers through exposure to more diverse actors and information. The use of a social network theory lens has provided new insights into the role of trust in shaping social media influence on the farmer, with variances in farmer trust of information from technology vendors and from peers.

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.

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.

This paper reviews the academic contributions that have emerged to date on the broad definition of farm-level management information systems (MISs). The purpose is twofold: (1) to identify the theories used in the literature to study the adoption of digital technologies and (2) to identify the drivers of and barriers to the adoption of such technologies.

The literature review was based on a comprehensive review of contributions published in the 1998–2019 period. The search was both automated and manual, browsing through references of works previously found via high-quality digital libraries.

Diffusion of innovations (DOIs) is the most frequently used theoretical framework in the literature reviewed, though it is often combined with other innovation adoption theories. In addition, farms’ and farmers’ traits, together with technological features, play a key role in explaining the adoption of these technologies.

So far, research has positioned the determinants of digital technology adoption mainly within the boundaries of the farm.

On the practical level, the extensive determinants’ review has potential to serve the aim of policymakers and technology industries, to clearly and thoroughly understand adoption dynamics and elaborate specific strategies to deal with them.

This study’s contribution to the existing body of knowledge on the farm-level adoption of digital technologies is twofold: (1) it combines smart farming and existing technologies within the same category of farm-level MIS and (2) it extends the analysis to studies which not only focus directly on adoption but also on software architecture design and development.

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.

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

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.

Traceability of food is of paramount importance to the increasingly sustainability-conscious consumers. Several tracking and tracing systems have been developed in the AgriFood sector in order to prove to the consumers the origins and processing of food products. Critical challenges in realizing food's traceability include cooperating with multiple actors on common data sharing standards and data models.

This research applies a design science approach to showcase traceability that includes preharvest activities and conditions in a case study. The authors demonstrate how existing data sharing standards can be applied in combination with new data models suitable for capturing transparency information about plant production.

Together with existing studies on farm-to-fork transparency, our results demonstrate how to realize transparency from field to fork and enable producers to show a complete bill of sustainability.

The existing standards and data models address transparency challenges in AgriFood chains from the moment of harvest up to retail (farm-to-fork) relatively well, but not what happens before harvest. In order to address sustainability concerns, there is a need to collect data about production activities related to product quality and sustainability before harvesting and share it downstream the supply chain. The ability to gather data on sustainability practices such as reducing pesticide, herbicide, fertilizer and water use are crucial requirements for producers to market their produce as quality and sustainable products.