Çalışmanın amacı büyük şehirler için çevre yolunda dinamik trafik akışına uygun düzenlemelerle akışı iyileştirerek emisyonu azaltmak, seyahat süresini uzatan beklemeleri azaltarak yakıt tasarrufu sağlamaktır. Bir çevre yolundaki trafik akışı için farklı kuralları içeren senaryolar Goldratt Research Labs tarafından AnyLogic üzerinde hazırlanan Traffic Flow paket simülatörü kullanılarak operasyonel bazda kıyaslanmıştır. Yaygın kullanılan statik ve sensörlerle desteklenen hibrit uygulamalar yerine trafik yoğunluğuna dayalı katılım sınırı içeren dinamik sistem kullanıldığında yoldan geçen araç sayısı artmakta ve seyahat süresi kısalmaktadır. Büyüyen şehirler ve artan lojistik hacim çevre yol düzenlemesini gerektirmektedir. Özellikle transit geçişlerdeki yerleşim yerlerinde ve trafik yoğunluğu yaşanan büyük şehirlerde mevcut trafik sensörleriyle bağlantılı olarak kullanılabilecektir. Çevre yolu trafik düzenlemeleri arasında İstanbul’da uygulanmayan akıllı sinyalizasyon, yan yolun akıllı geçiş tercihine bağlanması, yola katılım sınırlaması, otoyolda trafik sinyalizasyonu gibi alternatifler simülasyon ortamında değerlendirilmiştir. Metot içindeki acil geçiş – araba – kamyon kurgusu, iş dünyasındaki acil işler – normal kapsamlı işler – geniş kapsamlı işler olarak yorumlandığında proje yönetimi için de geçerli görünmektedir.

Background: Consumer preferences are one of the most dominant factors shaping the implementation of last-mile delivery innovations. This study investigates how innovative delivery methods affect consumers’ last-mile delivery preferences and focuses on understanding consumer expectations for integrating these methods. Methods: A discrete choice experiment was implemented. Data from 480 participants in Istanbul were analyzed by multinomial logistic regression using the Apollo package in R Studio. Results: For the selection of delivery to the address, the delivery price, delivery term, and the delivery time window are significant attributes. However, the delivery method and information and tracking attributes do not emerge as decisive attributes in this choice. For the selection of delivery points, the delivery price, delivery term, distance, pick-up accessibility, information and tracking, and the delivery method have been identified as key influencing attributes. Conclusions: The study suggests actionable recommendations aimed at improving negative perceptions of delivery points, advocating for harmonized regulatory frameworks, strategically integrating technology, and developing delivery schedules to enhance overall service quality. This study fills a gap in the literature by examining different last-mile delivery attributes and locations. It also provides valuable insights in understanding consumer expectations and innovative delivery methods.

Purpose: Agricultural sector not only meets the nutritional requirements of all living creatures but also generates the primary source of the raw material provided by various branches of industry to fulfill their functions. It is of great importance to increase studies on oilseeds which have an important role in Turkey's agricultural products. They are grown in almost all of the country, which are vital for the nutrition and many sectors. The main purpose of the study is to offer an integrated approach to determine potential warehouse locations for oilseeds.Design/methodology/approach: This is the first study that integrates Delphi, analytical hierarchical process (AHP), technique for order preference by similarity to ideal solution (TOPSIS), P-Median and Panel data analysis in a real case. This integrated approach consists of the following steps, respectively: (1) The criteria were determined by the Delphi method. (2) The weights of the criteria were calculated by AHP and the provinces with the highest oilseed warehouse potential in seven regions of Turkey were specified by TOPSIS. (3) Oilseed warehouse numbers and locations were obtained by P-Median. (4) In order to answer whether the distribution network is profitable in the future with the determined center locations, a forecast model based on panel data analysis was created. (5) Regional representatives were determined for 2030, and the distribution network was analyzed again. (6) The costs that arose in 2018 and 2030 were computed and compared by cost analysis. (7) The effect of the change in criteria weights on the alternative results was tested by scenario analysis.Findings: The findings indicated that oilseed crop production potential and oilseed crop production area turned out to be the most important criteria. Furthermore, the results showed that this model is robust and suitable for warehouse location selection studies.Practical implications: The study can serve as a guide for local and central policy makers with both the criteria it uses and the model it develops.Originality/value: The main contribution of this study is that the integrated approach has been used for the first time in location selection in a real case.

Tüm sektörlerin dijital dönüşümüyle birlikte ortaya çıkan “akıllı” kavramı teknolojiye dayalı çözümlerin önem kazanmasını sağlamıştır. Akıllı fabrikalarla birlikte kullanılan nesnelerin interneti, siber fiziksel sistemler, 3D yazıcılar vb. teknolojilerin hayatın farklı alanlarına dâhil edilmesiyle “akıllı şehirler”, “akıllı binalar”, “akıllı ulaşım”, “akıllı enerji” gibi teknoloji odaklı yönetim süreçleri ortaya çıkmıştır. Akıllılık kavramı, tedarik zinciri ve lojistik alanında da kendini göstererek dijital dönüşümün bu alanlarda da ortaya çıkmasını sağlamıştır. Son yıllarda bu alana yönelik çalışmaların artmasına rağmen literatürün mevcut durumu ve yönelimler hakkında yeterli düzeyde bilgi bulunmamaktadır. Bu çalışmanın amacı akıllı lojistikle ilgili yapılan çalışmaların sistematik bir derlemesini sunmak ve literatürdeki boşlukları ortaya koyarak bu alanda çalışacak araştırmacılara katkı sağlamaktır. Çalışmada yöntem olarak sistematik haritalama kullanılmıştır. “Web of Science”, “Scopus” ve “Dergipark” veri tabanları kullanılarak yapılan araştırmada 67 makale değerlendirilmiştir. İnceleme sonucunda akıllı lojistikle ilgili yapılan çalışmalara yönelik tanımlayıcı bulgular, akıllı lojistiğin getirdiği avantajlar, uygulamada karşılaşılan engeller ortaya konulmuştur.

This research aims to investigate university students' perceptions of crowdsourced delivery and identify factors that influence crowdsourced delivery platform acceptance as a consumer and as a driver. Research design is a qualitative exploratory case study that was performed on university students' perceptions of crowdsourced delivery in Turkey. Online focus group discussions were used to collect data with 35 university students. Data included six online focus groups and were analyzed using thematic analysis. To increase credibility and trustworthiness, the researcher triangulation was applied. The findings show that as a consumer; performance expectancy, price sensitivity, social influence, and perceived risk and as a driver; compensation, working environment, and perceived risk affect acceptance of crowdsourced delivery. The findings are helpful for crowdsourced delivery platforms to increase the acceptance rate in the beginning stage of crowdsourced delivery and provide suggestive knowledge for other emerging countries. This paper highlights what factors influence students' acceptance of crowdsourced delivery in the introduction phase from the perspective of a group of university students in an emerging country.