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Article

Strategic Analysis for Advancing Smart Agriculture with the Analytic SWOT/PESTLE Framework: A Case for Turkey

by
Deniz Uztürk
1 and
Gülçin Büyüközkan
2,*
1
Department of Business Administration, Business Research Center, Galatasaray University, Istanbul 34349, Turkey
2
Department of Industrial Engineering, Galatasaray University, Istanbul 34349, Turkey
*
Author to whom correspondence should be addressed.
Agriculture 2023, 13(12), 2275; https://doi.org/10.3390/agriculture13122275
Submission received: 7 November 2023 / Revised: 8 December 2023 / Accepted: 13 December 2023 / Published: 15 December 2023
(This article belongs to the Section Artificial Intelligence and Digital Agriculture)

Abstract

In the contemporary discourse, smart agriculture (SA) stands out as a potent driver for sustainable economic growth. The challenges of navigating SA transition are notably intricate in developing nations. To effectively embark on this transformative journey, strategic approaches are imperative, necessitating a thorough examination of the prevailing agricultural ecosystem. This study seeks to formulate strategies that advance Turkey’s agricultural sector. The primary research questions focus on optimizing the benefits of SA by aligning strengths and opportunities with diverse socio-economic and environmental factors, while also exploring effective strategies to mitigate the impact of weaknesses and threats within the agricultural landscape. To achieve this objective, the utilization of the 2-Tuple linguistic (2TL) model integrated DEMATEL (Decision-Making Trial and Evaluation Laboratory) methodology in conjunction with SWOT (Strengths, Weaknesses, Opportunities, and Threats) and PESTLE (Political, Economic, Social, Technological, Legal, Environmental) analyses is proposed. The integration of linguistic variables enhances the capacity to delve deeper into system analysis, aligning more closely with human cognitive processes. The research commences with SWOT and PESTLE analyses applied to Turkey’s agricultural sector. Subsequently, the 2TL-DEMATEL approach is employed to investigate interrelationships among analysis components. This inquiry aims to establish causal relations, facilitating the derivation of relevant strategies. The case study centers on Turkey, a developing country, with outcomes indicating that the highest-priority strategies revolve around addressing ‘environmental threats’ and ‘economic weaknesses’. The subsequent evaluation encompasses eight dimensions, resulting in the generation of fifteen distinct strategies, a process facilitated by collaboration with field experts. Importantly, both the results and strategies undergo rigorous validation, drawing upon insights from the recent literature and field experts. Significantly, these findings align seamlessly with the Sustainable Development Goals (SDGs), substantiating the study’s broader significance in fostering a sustainable future for Turkey.
Keywords: smart agriculture; strategy generation; Turkey; SWOT/PESTLE analysis; DEMATEL; 2-Tuple linguistic model smart agriculture; strategy generation; Turkey; SWOT/PESTLE analysis; DEMATEL; 2-Tuple linguistic model

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MDPI and ACS Style

Uztürk, D.; Büyüközkan, G. Strategic Analysis for Advancing Smart Agriculture with the Analytic SWOT/PESTLE Framework: A Case for Turkey. Agriculture 2023, 13, 2275. https://doi.org/10.3390/agriculture13122275

AMA Style

Uztürk D, Büyüközkan G. Strategic Analysis for Advancing Smart Agriculture with the Analytic SWOT/PESTLE Framework: A Case for Turkey. Agriculture. 2023; 13(12):2275. https://doi.org/10.3390/agriculture13122275

Chicago/Turabian Style

Uztürk, Deniz, and Gülçin Büyüközkan. 2023. "Strategic Analysis for Advancing Smart Agriculture with the Analytic SWOT/PESTLE Framework: A Case for Turkey" Agriculture 13, no. 12: 2275. https://doi.org/10.3390/agriculture13122275

APA Style

Uztürk, D., & Büyüközkan, G. (2023). Strategic Analysis for Advancing Smart Agriculture with the Analytic SWOT/PESTLE Framework: A Case for Turkey. Agriculture, 13(12), 2275. https://doi.org/10.3390/agriculture13122275

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