Araştırma Makalesi
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Tarım & Gıda Pazarlamasında KOBİ'lerin Yeni Teknolojiler (Yapay Zeka, Blokzincir, Makine Öğrenmesi ve Nesnelerin İnterneti) ile Dijital Dönüşümü ve Başarı Faktörleri

Yıl 2024, Cilt: 13 Sayı: 3, 1192 - 1218, 30.09.2024
https://doi.org/10.15869/itobiad.1400182

Öz

Ülke ekonomilerinde önemli bir yer tutan küçük ve orta ölçekli işletmeler (KOBİ) tedarik zinciri yapısında daha fazla yaygınlaşması karmaşık ve rekabetçi bir iş ortamında ülke ekonomilerinin gelişiminde oldukça önemlidir. Bununla birlikte KOBİ’ler Sürdürülebilir Kalkınma Hedeflerinin (SDG) sağlanması için önemli katkıları olabileceği gibi gıda KOBİ'leri tarım sektöründe tarımsal verimlilik üzerinde de dolaylı etkileri olabilir. Birleşmiş Milletler Gıda ve Tarım Örgütü (FAO) ve buna benzer uluslararası organizasyonlar buna yol açabilecek uygulamaları desteklemektedir. KOBİ'ler, çalışan sayısı, yıllık cirosu veya yıllık bilanço toplamı belirli bir eşiğin altında olan işletmelerdir. KOBİ’ler ekonomik yaşama olumlu katkılar sağlamasının yanı sıra insanların en temel ihtiyaçları olan gıda ürünleri için gıda arzını da sağlayarak önemli bir fonksiyonu yerine getirmektedirler. Rekabetçi ve karmaşık bir iş ortamında, uygun stratejilerin uygulanması KOBİ'lerin gelişimini ilerletmek için özellikle önemli bir çabadır. Bu makale, tarım & gıda pazarlamasında KOBİ'lerin yeni teknolojiler ile dijital dönüşümünü ve başarı faktörlerini analiz etmiştir. Çalışmada, Web of Science, Scopus ve Google Scholar gibi önemli veri tabanları aday gösterilerek sistematik analiz yöntemi önerilmiştir. Araştırma amacına uygun olarak doğrulanmış anahtar kelimeler kullanılarak farklı literatür platformlarından elde edilen makaleler gözden geçirilmiştir. Araştırma sonuçları, KOBİ’lerin başarı faktörlerini ve yeni teknolojileri benimsemelerinin tarım & gıda pazarlamasını da tüm yönleriyle etkileyeceğini doğrulamaktadır. Bu nedenle KOBİ’ler için stratejiler belirlenirken tüm bu faktörler de dikkate alınarak yeni teknolojilerin tüm süreçlere entegre edilmesine daha çok önem verilmelidir.

Etik Beyan

Bu çalışmanın hazırlanma sürecinde bilimsel ve etik ilkelere uyulduğu ve yararlanılan tüm çalışmaların kaynakçada belirtildiği beyan olunur.

Destekleyen Kurum

Bu araştırmayı desteklemek için dış fon kullanılmamıştır.

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Digital Transformation and Success Factors of SMEs with New Technologies (Artificial Intelligence, Blockchain, Machine Learning and Internet of Things) in Agriculture & Food Marketing

Yıl 2024, Cilt: 13 Sayı: 3, 1192 - 1218, 30.09.2024
https://doi.org/10.15869/itobiad.1400182

Öz

The greater prevalence of small and medium-sized enterprises (SMEs), which have an important place in country economies, in the supply chain structure is very important in the development of country economies in a complex and competitive business environment. However, while SMEs can make significant contributions to achieving the Sustainable Development Goals (SDGs), food SMEs can also have indirect effects on agricultural productivity in the agricultural sector. Food and Agriculture Organization of the United Nations (FAO) and similar international organizations support practices that may lead to this. SMEs are businesses whose number of employees, annual turnover or annual balance sheet total is below a certain threshold. In addition to making positive contributions to economic life, SMEs also fulfill an important function by providing food supply for food products, which are people's most basic needs. In a competitive and complex business environment, implementing appropriate strategies is a particularly important effort to advance the development of SMEs. This article analyzed the digital transformation and success factors of SMEs with new technologies in agriculture & food marketing. In the study, a systematic analysis method was proposed by nominating important databases such as Web of Science, Scopus and Google Scholar. Articles obtained from different literature platforms were reviewed using validated keywords in accordance with the research purpose. Research results confirm that SMEs' success factors and adoption of new technologies will affect all aspects of agriculture & food marketing. Therefore, when determining strategies for SMEs, more importance should be given to integrating new technologies into all processes, taking into account all these factors.

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  • Tripathy, S., Aich, S., Chakraborty, A., & Lee, G. M. (2016). Information technology is an enabling factor affecting supply chain performance in Indian SMEs: a structural equation modelling approach. Journal of Modelling in Management, 11(1), 269-287.
  • Ünal, E., Urbinati, A., & Chiaroni, D. (2019). Managerial practices for designing circular economy business models: The case of an Italian SME in the office supply industry. Journal of manufacturing technology management, 30(3), 561-589.
  • Ünal, S., Deveci, F. G., & Yildiz, T. (2019). Do we know organic food consumers? The personal and social determinants of organic food consumption. Istanbul Business Research (IBR), 48(1), 1-35.
  • Vanderroost, M., Ragaert, P., Devlieghere, F., & De Meulenaer, B. (2014). Intelligent food packaging: The next generation. Trends in food science & technology, 39(1), 47-62.
  • Van Hoof, B., & Thiell, M. (2014). Collaboration capacity for sustainable supply chain management: small and medium-sized enterprises in Mexico. Journal of Cleaner Production, 67, 239-248.
  • Walker, T. R., McGuinty, E., Charlebois, S., & Music, J. (2021). Single-use plastic packaging in the Canadian food industry: Consumer behavior and perceptions. Humanities and Social Sciences Communications, 8(1), 1-11.
  • Willenbacher, M., Scholten, J., & Wohlgemuth, V. (2021). Machine learning for optimization of energy and plastic consumption in the production of thermoplastic parts in SME. Sustainability, 13(12), 6800.
  • Wisner, J. D. (2003). A structural equation model of supply chain management strategies and firm performance. Journal of Business logistics, 24(1), 1-26.
  • Wognum, P. N., Bremmers, H., Trienekens, J. H., Van Der Vorst, J. G., & Bloemhof, J. M. (2011). Systems for sustainability and transparency of food supply chains–Current status and challenges. Advanced engineering informatics, 25(1), 65-76.
  • Wong, L. W., Leong, L. Y., Hew, J. J., Tan, G. W. H., & Ooi, K. B. (2020). Time to seize the digital evolution: Adoption of blockchain in operations and supply chain management among Malaysian SMEs. International Journal of Information Management, 52, 101997.
  • Wooi, G. C., & Zailani, S. (2010). Green supply chain initiatives: investigation on the barriers in the context of SMEs in Malaysia. International Business Management, 4(1), 20-27.
  • Xia, Y., Xu, T., Wei, M. X., Wei, Z. K., & Tang, L. J. (2023). Predicting chain’s manufacturing SME credit risk in supply chain finance based on machine learning methods. Sustainability, 15(2), 1087.
  • Yıldırım, S., & Kantarcı, T. (2022). A review on sustainability policies of businesses: Recycling and waste reduction. Journal of Recycling Economy & Sustainability Policy, 1(1), 1-9.
  • Zaridis, A., Vlachos, I., & Bourlakis, M. (2021). SMEs strategy and scale constraints impact on agri-food supply chain collaboration and firm performance. Production Planning & Control, 32(14), 1165-1178.
  • Zhang, L., Hu, H., & Zhang, D. (2015). A credit risk assessment model based on SVM for small and medium enterprises in supply chain finance. Financial Innovation, 1(1), 1-21.
  • Zhao, G., Liu, S., Lopez, C., Lu, H., Elgueta, S., Chen, H., & Boshkoska, B. M. (2019). Blockchain technology in agri- food value chain management: A synthesis of applications, challenges and future research directions. Computers in industry, 109, 83-99.
  • Zhu, Y., Xie, C., Wang, G. J., & Yan, X. G. (2017). Comparison of individual, ensemble and integrated ensemble machine learning methods to predict China’s SME credit risk in supply chain finance. Neural Computing and Applications, 28, 41-50.
  • Zhu, Y., Zhou, L., Xie, C., Wang, G. J., & Nguyen, T. V. (2019). Forecasting SMEs' credit risk in supply chain finance with an enhanced hybrid ensemble machine learning approach. International Journal of Production Economics, 211, 22-33.
Toplam 209 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Konular Tarım Ekonomisi
Bölüm Makaleler
Yazarlar

Hüseyin Fatih Atlı 0000-0002-1397-1514

Yayımlanma Tarihi 30 Eylül 2024
Gönderilme Tarihi 5 Aralık 2023
Kabul Tarihi 22 Temmuz 2024
Yayımlandığı Sayı Yıl 2024 Cilt: 13 Sayı: 3

Kaynak Göster

APA Atlı, H. F. (2024). Tarım & Gıda Pazarlamasında KOBİ’lerin Yeni Teknolojiler (Yapay Zeka, Blokzincir, Makine Öğrenmesi ve Nesnelerin İnterneti) ile Dijital Dönüşümü ve Başarı Faktörleri. İnsan Ve Toplum Bilimleri Araştırmaları Dergisi, 13(3), 1192-1218. https://doi.org/10.15869/itobiad.1400182
İnsan ve Toplum Bilimleri Araştırmaları Dergisi  Creative Commons Atıf-GayriTicari 4.0 Uluslararası Lisansı (CC BY NC) ile lisanslanmıştır.