A contextualized study of the usage of the Internet of things (IoTs) in smart farming in a typical Middle Eastern country within the context of Unified Theory of Acceptance and Use of Technology model (UTAUT)

Ronaghi, Mohammad Hossein; Forouharfar, Amir

doi:10.1016/j.techsoc.2020.101415

Cited by 104 publications

(106 citation statements)

References 48 publications

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“…While developed countries have led much of the innovation and early adoption of digital technologies [11][12][13][14], the potential impact of these technologies on agriculture in developing countries is massive given the economic, social, and environmental roles played by their agricultural sectors [6]. The available literature has tended to focus on developing countries and regions that depend most highly on agricultural production, where agricultural production is viewed as a key economic sector or where the agri-food sector is a major employer.…”

Section: Introductionmentioning

confidence: 99%

“…The Middle East and North Africa (MENA) region has received little, albeit growing, attention within the field of digital agriculture [14] and vice versa [15]. This tendency to overlook the MENA region is despite the fact that agriculture continues to be practiced and that agri-food is an important, if relatively small, sector within most countries of the region and may reflect the fact that the sector is severely constrained by both natural and human factors [16], which may limit expectations for agriculture in MENA.…”

Section: Introductionmentioning

confidence: 99%

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Digitalization for Sustainable Agri-Food Systems: Potential, Status, and Risks for the MENA Region

2021

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Digital technologies offer a potential solution to improve sustainability—economic, social, and environmental—of agri-food systems around the globe. While developed countries have led the innovation and adoption of digital agriculture, the potential impact in developing countries—including in the Middle East and North Africa (MENA) region—is massive. This article synthesizes existing evidence to review the potential and current contribution of digital technologies to the agri-food sectors in MENA. Digital agriculture shows promise in addressing the key challenges facing the agri-food sector across MENA countries. Improvements in primary production, supply chain and logistics performance, and optimized use of scarce natural resources (notably agricultural water) could be notable, if digital technologies can be implemented as envisioned. Available evidence shows that adoption of digital agriculture is at early stages, generally led by high-value agricultural production targeting domestic markets in Gulf countries and export markets in Mashreq countries. Economic sustainability appears the strongest force for current adoption, with less focus on social or environmental sustainability. Public policies should not only foster the adoption of digital technologies in MENA but also ensure equity of access, transparency of use, data protections, and labor protections. Policymakers should move beyond traditional, production-centric views to deliver also on social and environmental sustainability.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Digitalization for Sustainable Agri-Food Systems: Potential, Status, and Risks for the MENA Region

2021

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“…However, the actual implementation of IoT took place between 2008 and 2009 according to Cisco Systems [3]. Since then, IoT has been improved and applied in a different number of applications, including motion detection [4], smart home [5], farming [6,7], cities [8,9], connected cars [10], wearable health monitors [11], biometric cybersecurity scanners [12], and logistics tracking [13].…”

Section: Introductionmentioning

confidence: 99%

A Multi-Stage Classification Approach for IoT Intrusion Detection Based on Clustering with Oversampling

et al. 2021

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Intrusion detection of IoT-based data is a hot topic and has received a lot of interests from researchers and practitioners since the security of IoT networks is crucial. Both supervised and unsupervised learning methods are used for intrusion detection of IoT networks. This paper proposes an approach of three stages considering a clustering with reduction stage, an oversampling stage, and a classification by a Single Hidden Layer Feed-Forward Neural Network (SLFN) stage. The novelty of the paper resides in the technique of data reduction and data oversampling for generating useful and balanced training data and the hybrid consideration of the unsupervised and supervised methods for detecting the intrusion activities. The experiments were evaluated in terms of accuracy, precision, recall, and G-mean and divided into four steps: measuring the effect of the data reduction with clustering, the evaluation of the framework with basic classifiers, the effect of the oversampling technique, and a comparison with basic classifiers. The results show that SLFN classification technique and the choice of Support Vector Machine and Synthetic Minority Oversampling Technique (SVM-SMOTE) with a ratio of 0.9 and the k value of 3 for k-means++ clustering technique give better results than other values and other classification techniques.

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“…Although the dimensions of digital transformation are numerous, those components that have impact on businesses and different industries, and have been considered by researchers and managers of organizations, are recognized as industry 4.0, presented in 2011 (Hofmann & Rüsch, 2017 ). Ronaghi and Forouharfar ( 2020 ) believe “The concept of ‘Industry 4.0’ is directly related to the installation of smart equipment and instruments for optimal controlling of resources, as well as increasing efficiency besides improving flexibility” (Ronaghi & Forouharfar, 2020 , p.2). The presence of time stamps in the blockchain structure prevents any distortion and falsification of information without the knowledge of stakeholders.…”

Section: Introductionmentioning

confidence: 99%

The effects of blockchain technology adoption on business ethics and social sustainability: evidence from the Middle East

Ronaghi

Mosakhani

2021

Environ Dev Sustain

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Sustainable development is not just possible with regard to the environmental and economic dimensions, and social issues are also important in achieving sustainable development. Social sustainability, as one of the dimensions of sustainable development, has been considered by policy makers and managers. Social sustainability and business ethics in the organization are affected by social and behavioral interactions of individuals. Blockchain technology, as a disruptive technology, leads to a peer-to-peer and decentralized network management using distributed architecture. Blockchain technology can affect the way information is exchanged and creates transparency in the organization. Therefore, the purpose of this study is to evaluate the impact of blockchain technology on business ethics and social sustainability in the organization. In the first part of the research, a conceptual model is extracted using previous studies. In the second part, the relationship between model variables among 411 managers of small and medium enterprises (SMEs) active in the Middle East region is evaluated according to the importance of sustainability in this region. Structural equation model and SmartPLS software have been used for data analysis. The research findings show that the use of blockchain technology has a direct impact on business ethics, corporate governance and social sustainability due to the creation of a decentralized system, information transparency and traceability. Also, business ethics and corporate governance have an impact on achieving social sustainability.

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A contextualized study of the usage of the Internet of things (IoTs) in smart farming in a typical Middle Eastern country within the context of Unified Theory of Acceptance and Use of Technology model (UTAUT)

Cited by 104 publications

References 48 publications

Digitalization for Sustainable Agri-Food Systems: Potential, Status, and Risks for the MENA Region

Digitalization for Sustainable Agri-Food Systems: Potential, Status, and Risks for the MENA Region

A Multi-Stage Classification Approach for IoT Intrusion Detection Based on Clustering with Oversampling

The effects of blockchain technology adoption on business ethics and social sustainability: evidence from the Middle East

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