| Abstrakt: |
The agricultural economy strives to increase productivity to feed the world's growing population. In this regard, agricultural digitalization has been enormously concerned and proffered. Digitalizing agriculture must be incorporated into most developing countries to gain benefits. For this purpose, every developing country needs to define a digitalization strategy. Many governments face a challenge while assessing digitalization options. Without an appropriate assessment technique, selecting the best solution is hardly possible among the many available technologies. This paper aims to conceptualize a new framework for assessing strategies. Antifragility analysis algorithm (AAA), introduced in the present study, is a state-of-the-art future-based scenario method that can maximize decision outcomes. According to the literature, an antifragile system increases its capability to thrive due to shocks, volatility, attacks, etc. In this research, the heuristic involves altering model inputs for future scenarios by considering the most significant environmental factors shaping future uncertainty. An antifragile strategy produces better average results than the current scenario after adjustments. Finally, antifragile strategies are ranked based on their antifragility scores. To explain the technique, we examined seven strategies for digitalizing the small farming sector in northern Iran. Then, we showed the alternatives' priority based on six key indicators that formed the future scenarios. According to the results, among the digitalization strategies implementable in the small farming sector in Iran, IoT will be the most antifragile strategy considering future scenarios, and following, the sensor strategy will be the next option. While considering the most important elements of decision-making, i.e., complexity and uncertainty, the proposed approach can benefit managers, organizations, policymakers, in making strategic decisions. [ABSTRACT FROM AUTHOR] |
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