Policy-makers are often hesitant to invest in unproven solutions because of a lack of the decisio... more Policy-makers are often hesitant to invest in unproven solutions because of a lack of the decision-making framework for managing innovations as a portfolio of investments that balances risk and return, especially in the field of developing new technologies. This study provides a new portfolio matrix for decision making of policy-makers to identify IoT applications in the agriculture sector for future investment based on two dimensions of sustainable development as a return and IoT challenge as a risk using a novel MADM approach. To this end, the identified applications of IoT in the agriculture sector fall into eight areas using the meta-synthesis method. The authors extracted a set of criteria from the literature. Later, the fuzzy Delphi method helped finalise it. The authors extended the SWARA method with interval-valued triangular fuzzy numbers (IVTFN SWARA) and used it to the weighting of the characteristics. Then, the alternatives were rated using the Additive Ratio Assessment (ARAS) method based on interval-valued triangular fuzzy numbers (IVTFN ARAS). Finally, decision-makers evaluated the results of ratings based on two dimensions of sustainability and IoT challenge by developing a framework for decision-making. Results of this paper show that policy-makers can manage IOT innovations in a disciplined way that balances risk and return by a portfolio approach, simultaneously the proposed framework can be used to determine and prioritise the areas of IoT application in the agriculture sector.
The agricultural sector needs to produce more food, both in terms of quantity and quality, on a p... more The agricultural sector needs to produce more food, both in terms of quantity and quality, on a planet that face enormous challenges like scarce resources and changing climate. The advancement of digital technologies, Internet of Things and analytics offers new solutions to these complex challenges. Hence, the purpose of this research is to identify the applications of IoT in smart agriculture. With the help of meta-synthesis approach, we have examined 480 academic documents written in English and published over a period of 8 years (2010-2017), among which only 168 have been selected for the final analysis. Selected documents were categorized into eight areas of agriculture (including “farming,” “greenhouse,” “urban agriculture,” “horticulture,” “livestock” and “supply and distribution network of agriculture”) and then clustered into six analytics domains corresponding to: “monitoring,” “control,” “tracing,” “diagnosis” and “descriptive planning”. Finally, by using the Shannon entropy method, the effect coefficient of the elements was determined in selected documents and technical uses of internet of things in each agriculture sector have been addressed.
Policy-makers are often hesitant to invest in unproven solutions because of a lack of the decisio... more Policy-makers are often hesitant to invest in unproven solutions because of a lack of the decision-making framework for managing innovations as a portfolio of investments that balances risk and return, especially in the field of developing new technologies. This study provides a new portfolio matrix for decision making of policy-makers to identify IoT applications in the agriculture sector for future investment based on two dimensions of sustainable development as a return and IoT challenge as a risk using a novel MADM approach. To this end, the identified applications of IoT in the agriculture sector fall into eight areas using the meta-synthesis method. The authors extracted a set of criteria from the literature. Later, the fuzzy Delphi method helped finalise it. The authors extended the SWARA method with interval-valued triangular fuzzy numbers (IVTFN SWARA) and used it to the weighting of the characteristics. Then, the alternatives were rated using the Additive Ratio Assessment (ARAS) method based on interval-valued triangular fuzzy numbers (IVTFN ARAS). Finally, decision-makers evaluated the results of ratings based on two dimensions of sustainability and IoT challenge by developing a framework for decision-making. Results of this paper show that policy-makers can manage IOT innovations in a disciplined way that balances risk and return by a portfolio approach, simultaneously the proposed framework can be used to determine and prioritise the areas of IoT application in the agriculture sector.
The agricultural sector needs to produce more food, both in terms of quantity and quality, on a p... more The agricultural sector needs to produce more food, both in terms of quantity and quality, on a planet that face enormous challenges like scarce resources and changing climate. The advancement of digital technologies, Internet of Things and analytics offers new solutions to these complex challenges. Hence, the purpose of this research is to identify the applications of IoT in smart agriculture. With the help of meta-synthesis approach, we have examined 480 academic documents written in English and published over a period of 8 years (2010-2017), among which only 168 have been selected for the final analysis. Selected documents were categorized into eight areas of agriculture (including “farming,” “greenhouse,” “urban agriculture,” “horticulture,” “livestock” and “supply and distribution network of agriculture”) and then clustered into six analytics domains corresponding to: “monitoring,” “control,” “tracing,” “diagnosis” and “descriptive planning”. Finally, by using the Shannon entropy method, the effect coefficient of the elements was determined in selected documents and technical uses of internet of things in each agriculture sector have been addressed.
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Papers by Ali Reza Qorbani